Dr. M.K. Jha

Integration of asset preselection with appropriate portfolio optimization techniques can improve the performance of the portfolio optimization models. This paper morphed the potential asset selection and the optimal portfolio construction rather than focusing on one. A large volume of sample data from 25 stocks is used for the experiment from the National Stock Exchange, India, between January 2005 and December 2021. Initially, a 3-step screening approach, an asset selection method is applied to select potential assets. The 3-steps comprise data choice, fundamental screening, and the Long Short Term Memory model anticipating real-time stock prices to shortlist stocks with higher expected returns. The suggested approach is effective in determining the quality of assets. Further, the optimal asset allocation is done by introducing a novel exponentially weighted-mean-variance model. This exponential weighting …

An optimization problem is formulated in this study to optimize the total investment in education, apprenticeship, and financial incentive to address the skilled labor shortages in the construction industry. Three separate mathematical models, namely linear programming (LP) models, fuzzy mathematical models, and structural equation models are compared for their accuracy, robustness, and ease of application in solving the optimization problem. LP models are found to be the best fit for solving the optimization problem. Relevant data on construction budget and investment preferences in education, apprenticeship, and financial incentive are obtained through a survey questionnaire from construction firms engaged in commercial and residential construction. The survey response suggests that more apprentices lean toward electrical and plumbing over carpentry due to the higher pay scale in both trade fields, thus …

Conventional toxic organic solvents used for the fabrication of polymeric membranes are harmful to the environment and human health. Herein, we have investigated Himalayan essential oils (EOs) as green solvents for some polymers. Hit and trial method is used to introduce suitable EOs solvent for the desired polymer to develop thin films and nano/microfibrous membranes. Solvent casting and electrospinning methods are employed to develop polycaprolactone (PCL) thin films and electrospun fibrous membranes, respectively. The physicochemical properties of as-fabricated membranes were investigated using FESEM, TGA, and FTIR spectroscopy. Nano/microfibrous electrospun membranes are successfully developed from PCL using cinnamon oil as a solvent. The antibacterial activity and biocompatibility evaluation revealed that as-fabricated PCL membranes would have high potential in tissue engineering …

Determining the canal route alignment and placing Rectangular Inclined (RI) drops in terms of the number and the height of each RI is a complex activity due to various technical, economic, and hydraulic issues. Although extensive research has been conducted to design the optimal flow section parameters in a cost-effective manner, an intelligent optimization model that simultaneously evaluates different aspects of the design of an irrigation canal needs further investigation. This paper presents a three-dimensional irrigation canal optimization model for optimally aligning the canal route, place the RI drops, and simultaneously design the flow section parameters. The model has been developed by integrating relevant geospatial information with a particle swarm algorithm to select a real-world option with the least cost without violating executive and hydraulic constraints in the steep-sloping area. The model has been employed with two examples to examine its capability in real-world applications. The results show that the model can optimize canal alignment and RI drop placement in areas with different terrain complexities and slopes. It is also found that while the placement of RI drops is nearly identical to the experimentally stated standards in conventional methods, the solution is obtained in a reasonably shorter computational duration. Pre-cost-estimation tables for different variants of canal routes and RI drop sets along the path of the canal are obtained. The results are very useful for efficient planning and design of irrigation canals.

The COVID-19 pandemic caused business shutdown worldwide because of which there was a significant reduction in roadway traffic movement and vehicle miles travelled. This, in turn resulted in lower gasoline sales. This paper assesses the economic impact of reduced vehicle miles of travel due to COVID-19 and determines the impact on the revenue generated in the highway trust fund due to reduced gasoline taxes collected in Maryland, USA. An economic loss assessment is performed using gasoline sales and vehicle miles of travel. The effect of declining Annual Average Daily Traffic (AADT) between 2018-2020 is analyzed for the 23 Maryland Counties and Baltimore city, to identity Counties that were significantly impacted due to the declining AADT. Finally, a machine learning model using artificial neural network is performed to predict the significance of various Counties subjected to declining AADT during COVID-19. The results are useful for assessing the economic impact of COVID-19 on roadway improvement projects owing to reduced gasoline sales.© 2023The Authors. Published by El sevie rB. V.

Portfolio theory underpins portfolio management, a much-researched yet uncharted field. This research suggests a collective framework combined with the essence of deep learning for stock selection through prediction and optimal portfolio formation through the mean-variance (MV) model. The CNN-LSTM model, proposed in Stage I blends the benefits of the convolutional neural network (CNN) and the long-short-term memory network (LSTM). The model combines feature extraction and sequential learning about temporal data fluctuations. The experiment considers thirteen input features, combining fundamental market data and technical indicators to capture the nuances of the wildly fluctuating stock market data. The input data sample of 21 stocks was collected from the National Stock Exchange (NSE) of India from January 2005 to December 2021, spanning two significant market crashes. Thus, the sample …

In Fig. 3, the y axis titles were mistakenly written showing a single-differential cross section in either dimuon pT or rapidity, when in fact the cross section is normalized by both the pT and rapidity ranges used for a given measurement point. The corrected version is shown in the new Fig. 3 provided below.

Background: Facial dog bite injuries result in significant emotional, psychological, and physical trauma to the victims involved and should be considered a significant health issue. The purpose of this study is to share our experience in the management and to add to the existing medical literature regarding the epidemiological patterns of facial dog bite injuries. Materials and Methods: This is a single-center retrospective observational study conducted at Dr. RML Hospital, New Delhi, from January 2021 to January 2022. A total of 105 patients were included. The wounds were managed according to the recommendations made by the national rabies control program and surgical intervention was performed in the form of primary suturing or flap cover. Results: Children of age group 0 to 10 years are most commonly affected. Pet dogs are the cause in 61% of cases and 57.1% of bites were provoked. Midface is most …

Urban flooding is caused due to poor drainage design, extreme weather, and excessive rain. Such flooding severely affects the road infrastructure. While there are a number of hydrologic software (e.g., TR-55, HydroCAD, TR-20, HEC-RAS, StreamStats, L-THIA, SWMM, WMOST, MAST, HY-8) available to examine extent of urban flooding, the softwares primarily require walking through a series of manual steps and address each study area individually preventing a collective view of an urban area in an efficient manner for hydrologic analysis. Furthermore, the softwares have no ability to recommend optimal culver pipe sizes to minimize flooding. In this paper, we develop a non-linear optimization formulation to minimize urban flooding using underdrain pipe size as a decision variable. We propose a solution algorithm in an integrated GIS and Python environment. Monte Carlo Simulation is used to simulate rainfall intensity by using empirical data on extreme weather from the National Oceanic and Atmospheric Administration. An example using the storm-drain system for the Baltimore County is performed. The results show that the model is effective in identifying storm-drain deficiencies and correcting them by choosing appropriate storm-drain inlet types to minimize flooding. The proposed method eliminates the need to examine each study area manually using existing hydrologic tools. Future works may include expanding the methodology for large datasets. They may also include a more sophisticated modeling approach for estimating rainfall intensity based on extreme weather patterns.

Parking choice models have been developed in previous works with certain limitations, such as fixed demand, lack of real-time knowledge of parking availability at the parking facilities, and fixed parking duration, to name a few. Furthermore, such models when developed using mathematical optimization approaches, suffer from computational complexity that limits their practical applicability. This paper proposes a machine learning and simulation-based dynamic parking choice model for airport parking. It considers real-time variable parking demand, which influences access time and parking cost to various parking lots. Drivers ultimately decide to seek a parking lot depending on: (1) their value of time; (2) parking duration, and (3) availability of a parking lot. The model uses a Random Forest classifier to predict a driver's choice of a parking lot. The results, based on some empirical data, show that parking demand is …

In Fig. 3, the y axis titles were mistakenly written showing a single-differential cross section in either dimuon pT or rapidity, when in fact the cross section is normalized by both the pT and rapidity ranges used for a given measurement point. The corrected version is shown in the new Fig. 3 provided below.

Here, we report high surface area nanoporous activated carbon (AC) derived from bhang (Cannabis) stems by H3PO4 activation method. X-ray diffraction (XRD) and Raman scattering confirmed the formation of graphitic structure of the resulting AC, which also incorporate oxygen/nitrogen/sulfur-containing functional groups as confirmed by the XPS. The AC was studied as a supercapacitor electrode, and it exhibited a maximum specific capacitance of 160 F g−1 at a current density of 0.5 A g−1 with a cyclic stability of 101 % after 3000 cycles. The obtained results suggest that the bhang stems, an abundantly found bio-waste, could be the potential precursor of nanoporous carbon for supercapacitors.

Solid-pseudopapillary tumor of pancreas is a rare pancreatic tumor that occurs predominantly in a young female with only a small minority concerning children. These tumors have low malignant potential, found incidentally which are usually single lobed. Surgical resection remains the mainstay of treatment. Our case is 26 years female with vomiting and abdominal pain localized to the right upper quadrant. Computerized tomography scans showed two well-defined hypodense lesions at neck and body of the pancreas with greatest diameter of six centimeter. The patient underwent central pancreatectomy and histopathology confirmed solid-pseudopapillary tumor with complete resection with all resected margin free of tumor. Symptoms may be present such as abdominal pain or vomiting due to compression, mainly in large tumors. In benign cases parenchyma sparing surgery such as central pancreatectomy can preserve the exocrine and endocrine function of pancreas which helps patient to have better postoperative quality of life.

[en] The Multichannel Charge Sensitive Amplifier (MCSA-16) module using VECC001 ASIC has already been developed successfully for the front-end signal processing of silicon strip detectors used in Charge Particle Detector Array (CPDA) at VECC. A single channel of Shaping and Timing ASIC has been designed successfully and will be sent for fabrication after chip-finishing to Semiconductor Laboratory, Chandigarh. This ASIC will be packaged in CQFP-120 package and functional testing will be carried out. A generalized NIM module similar to the commercial module mentioned above will be developed using this ASIC for self-reliance and as an import substitute

Background:Postburn flexion contractures of the knee may arise even with adequate treatment of the burn injury. Pedicled medial sural artery perforator (MSAP) flap has been described for the reconstruction of defects of the knee and proximal third of the leg. Its use in the management of postburn contracture release is sparse. We are presenting the use of a medial sural artery pedicled flap for the reconstruction following postburn knee contracture release.Materials and Methods:This study included six patients with postburn unstable scars and a mild degree of knee contractures who underwent release of the contracture and coverage using MSAP pedicled flap. The results in terms of flap size, recurrence, complications, functional outcome, and cosmesis were assessed.Results:The flap size ranged from 7 cm× 6 cm to 13 cm× 7 cm with a mean pedicle length of 9.41 cm. All six flaps survived without any complications …

Land-use transition is one of the most profound human-induced alterations of the Earth’s system. It can support better land management and decision-making for increasing the yield of food production to fulfill the food needs in a specific area. However, modeling land-use change involves the complexity of human drivers and natural or environmental constraints. This study develops an agent-based model (ABM) for land use transitions using critical indicators that contribute to food deserts. The model’s performance was evaluated using Guilford County, North Carolina, as a case study. The modeling inputs include land covers, climate variability (rainfall and temperature), soil quality, land-use-related policies, and population growth. Studying the interrelationships between these factors can improve the development of effective land-use policies and help responsible agencies and policymakers plan accordingly to improve food security. The agent-based model illustrates how and when individuals or communities could make specific land-cover transitions to fulfill the community’s food needs. The results indicate that the agent-based model could effectively monitor land use and environmental changes to visualize potential risks over time and help the affected communities plan accordingly.

It is widely known that land use/land cover (LULC) changes significantly alter watershed hydrology and sediment yields. The impact, especially on erosion and sedimentation, is likely to be exacerbated in regions dominated by high rainfall patterns such as monsoons. This study analyzed the hydrological responses of LULC changes in terms of streamflow (SF) and sediment yield (SY) in a monsoon-dominated tropical watershed, the Periyar River Watershed (PRW) in Kerala, India. This watershed drains an area of 4793 km2 characterized by an average monsoon rainfall of 2900 mm from June to November. The watershed hydrology and sediment dynamics were simulated using the Soil and Water Assessment Tool (SWAT) model for the impact assessment at the watershed outlet and the sub-watershed level. Historical LULC data were analyzed for 1988, 1992, 2002, and 2016 using the maximum likelihood method, and future LULC changes were projected for 2030, 2050, 2075, and 2100 using the Markov chain–cellular automata technique. Between 1988 and 2016, the urban area increased by 4.13 percent, while plantation and forest coverage decreased by 1.5 percent. At this rate, by 2100, the urban area is expected to grow by 16.45% while plantations and forest area will shrink by 13.7% compared to 1988. The effects of these changes on SF and SY were found to be minimal at the watershed outlet; however, at the spatial scale of sub-watersheds, the changes varied up to 70% for surface runoff and 200% for SY. These findings highlight the potential impacts of LULC changes in a monsoon-dominated watershed and may contribute to the …

Rainfall is one of the dominating climatic parameters that affect water availability. Trend analysis is of paramount significance to understand the behavior of hydrological and climatic variables over a long timescale. The main aim of the present study was to identify trends and analyze existing linkages between rainfall and streamflow in the Nilwala River Basin (NRB) of Southern Sri Lanka. An investigation of the trends, detection of change points and streamflow alteration, and linkage between rainfall and streamflow were carried out using the Mann–Kendall test, Sen’s slope test, Pettitt’s test, indicators of hydrological alteration (IHA), and Pearson’s correlation test. Selected rainfall-related extreme climatic indices, namely, CDD, CWD, PRCPTOT, R25, and Rx5, were calculated using the RClimdex software. Trend analysis of rainfall data and extreme rainfall indices demonstrated few statistically significant trends at the monthly, seasonal, and annual scales, while streamflow data showed non-significant trends, except for December. Pettitt’s test showed that Dampahala had a higher number of statistically significant change points among the six rainfall stations. The Pearson coefficient correlation showed a strong-to–very-strong positive relationship between rainfall and streamflow. Generally, both rainfall and streamflow showed non-significant trend patterns in the NRB, suggesting that rainfall had a higher impact on streamflow patterns in the basin. The historical trends of extreme climatic indices suggested that the NRB did not experience extreme climates. The results of the present study will provide valuable information for water resource planning …

Background:Burn injuries involving the dorsum of the hand are very common. Most burn injuries heal with dressings or skin grafting. Deep burns can lead to soft tissue defects and require durable cover to protect the underlying extensor tendons and the bone. Dorsal metacarpal artery-based flaps are reliable locoregional flaps that provide good soft tissue cover.Materials and Methods:This study included nine patients with postburn dorsal finger defects who underwent debridement and coverage using dorsal metacarpal artery perforator (DMAP)-based flaps from January 2019 to January 2022. Parameters in terms of flap dimensions, reliability, complications, and donor-site morbidity were assessed.Results:The flap size ranged from 5 cm× 2.5 cm to 7 cm× 2.5 cm. Two flaps had marginal necrosis, and one had venous congestion, which settled over time and healed with dressings. All the flaps settled well with a …

In the present study, the streamflow simulation capacities between the Soil and Water Assessment Tool (SWAT) and the Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) were compared for the Huai Bang Sai (HBS) watershed in northeastern Thailand. During calibration (2007–2010) and validation (2011–2014), the SWAT model demonstrated a Coefficient of Determination (R2) and a Nash Sutcliffe Efficiency (NSE) of 0.83 and 0.82, and 0.78 and 0.77, respectively. During the same periods, the HEC-HMS model demonstrated values of 0.80 and 0.79, and 0.84 and 0.82. The exceedance probabilities at 10%, 40%, and 90% were 144.5, 14.5, and 0.9 mm in the flow duration curves (FDCs) obtained for observed flow. From the HEC-HMS and SWAT models, these indices yielded 109.0, 15.0, and 0.02 mm, and 123.5, 16.95, and 0.02 mm. These results inferred those high flows were captured well by the SWAT model, while medium flows were captured well by the HEC-HMS model. It is noteworthy that the low flows were accurately simulated by both models. Furthermore, dry and wet seasonal flows were simulated reasonably well by the SWAT model with slight under-predictions of 2.12% and 13.52% compared to the observed values. The HEC-HMS model under-predicted the dry and wet seasonal flows by 10.76% and 18.54% compared to observed flows. The results of the present study will provide valuable recommendations for the stakeholders of the HBS watershed to improve water usage policies. In addition, the present study will be helpful to select the most appropriate hydrologic model for humid tropical watersheds …

Urban flooding is caused due to poor drainage design and excessive rain. It severely affects the road infrastructure. Existing hydrologic software tools to examine the extent of urban flooding primarily require walking through a series of manual steps and address each study area individually, preventing a collective review of poor storm-drains in an efficient manner. Previous methods for optimal drainage design were inefficient and lacked the ability of solving the underlying optimization problem due to the inherent nonlinearity of the decision variables. In this paper, we develop a nonlinear optimization formulation to minimize urban flooding using underground pipe size as a decision variable. We propose a solution algorithm using sequential least squares quadratic programming and spatial datasets. The proposed method eliminates the need to examine each study area manually using existing hydrologic tools. An example using the storm-drain system for the Baltimore County is performed. The results show that the model is effective in identifying storm-drain deficiencies and correcting them by choosing appropriate storm-drain inlet types to minimize flooding. Future works may include using large datasets and a more sophisticated modeling approach for estimating rainfall intensity based on extreme weather patterns. The method can be applied to other jurisdictions if relevant hydrological and underdrain piping network data were available.

Streambed aggradation and degradation are ways in which a stream will respond to changes in the incoming flow and sediment loads. Several environmental and societal problems are attributed to these channel bed adjustments. Prior studies have extensively used stream power to discern dominant channel processes and establish threshold limits required to trigger channel modifications. However, these studies were constrained by limited datasets and the scope of the applications. The current study used a large dataset of streambed median grain size (D50) across the contiguous U.S. in conjunction with a screening tool to assess the streambed stability for channel erosion and deposition potential. Analysis at the Physiographic Province level indicated major geomorphic changes are highly likely to occur in the Blue Ridge and Pacific Border provinces. Deposition-dominated streams are prominent in the Central Lowland, Great Plains, and Coastal Plain, whereas the Colorado Plateaus and Wyoming Basin have the highest percentage of stable channels. Smoothed spatial maps of stream power indicated the prevalence of high stream power in the Northeast and Pacific Northwest regions of the U.S. Comparison of channel erosion and deposition predictions using the stream power map with actual field calculated aggradation and degradation results yielded a 55% prediction accuracy. Further analysis based on the stream order revealed the association of higher stream power with lower stream orders.

Food accessibility and food security have increasingly become critical components for individuals and communities all over the world. Millions of people across the world struggle to access fresh fruits and vegetables and live in food deserts, including in the United States (US). According to the United States Department of Agriculture (USDA), food desert is a low-income area with limited access to affordable and nutritious foods like fresh fruits, vegetables, and other healthful whole foods; generally, they refer to the locations where the public do not have access to supermarkets that provide a good variety of quality, reasonably priced healthy foods. Studying factors that contribute to food deserts are essential for policymakers and other responsible agencies to understand the nature of the problem and hence formulate suitable plans and policies. Different factors of the natural (eg, temperature, precipitation, soil qualities …

The noise optimization of CMOS-based front-end electronics for semiconductor based detector readout consists of current and voltage noise minimization in the design of Charge Sensitive pre-Amplifier (CSA). However, the leakage current which is in the order of tens of nA contributes significant amount of noise which is detrimental in case of low noise application eg detector with PIN diode type configuration. The CSA with a capacitor and a resistor in feedback type of architecture would not block detector leakage current, produced by thermally generated electron-hole pairs within the depletion region. The fluctuations of the leakage current are the source of noise and higher leakage current can even cause saturation of CSA output. The front-end signal processing for multichannel setup viz. CPDA, GMDA at VECC relies on the self-developed customized ASIC and has the advantage of introducing a leakage current compensation circuit (LCC)[1] with the CSA which is otherwise not available in the commercial preamplifiers. With this motivation, LCC has been designed using CMOS and integrated in the second version of GMDA ASIC. The detail design of the LCC has been described in this paper. The result obtained after simulation has been shown and explained.

Connected and autonomous vehicles (CAVs) are largely at the experimental stage. Their successful deployment and field implementation require a careful consideration of their vulnerabilities to cyberattacks. The primary security vulnerability is in the controller area network (CAN) protocol, which permits communication among electronic control units in CAVs. To address this vulnerability and mitigate cyberattacks, machine learning (ML) algorithms can be developed for intrusion detection in CAV’s CAN protocol. In this research, the data structure of certain experimental datasets on message injection attack from the Hacking and Countermeasure Research Lab is examined. A random forest classifier-based ML model is developed owing to its efficiency in predicting cyberattacks on CAVs consisting of over 3 million datasets. A number of procedures within the Python programming environment are employed to clean the dataset before performing the prediction. The prediction for intrusion detection is performed with a 70: 30 split of the training: testing data with a random state of 11 and number of estimators as 200. The accuracy is found to be over 92% for all three scenarios in performing the prediction. The model can be deployed in real-time investigation of cyberattacks in CAVs if real-time data were available. The data cleaning method developed in this study can be applied in other ML applications consisting of large datasets, such as credit card fraud and drug discovery, to name a few.

Background Mechanical skin stretching (SS) is now becoming one of the commonly sought after procedures for wound healing. This study was aimed to assess the efficacy of preoperative SS for the closure of large wounds and to evaluate various postoperative outcome parameters. Methodology An observational study was conducted from December 2017 to May 2019 where a sample size of 30 patients was included with inclusion criteria being wounds of ≥5 cm width that require surgical management, presence of sufficient healthy skin edge of the wound/scar (at least one) for the stretching procedure, and age between 18 and 70 years. SS devices used were the top closure tension relief system. Postoperatively, various parameters were recorded to evaluate outcomes and complications. Results Majority of wounds that is 16 (53.3%) were <50 cm2, 9 (30%) were between 50 and 75 cm2, and 5 (16.7 …

Climate change (CC) affects millions of people directly or indirectly. Especially, the effect of CC on the hydrological regime is extensive. Hence, understanding its impact is highly essential. In this study, the Bharathapuzha river basin (BRB) lying in the Western Ghats region of southern India is considered for CC impact assessment, as it is a highly complex and challenging watershed, due to its varying topographical features, such as soil texture, land use/land cover types, slope, and climatology, including rainfall and temperature patterns. To understand the CC impact on the hydrological variables at BRB in the future, five downscaled global circulation models (GCMs) were used, namely BNU-ESM, Can-ESM, CNRM, MPI-ESM MR, and MPI-ESM LR. These GCMs were obtained for two representative concentration pathway (RCP) scenarios: 4.5 representing normal condition and 8.5 representing the worst condition of projected carbon and greenhouse gases concentration on the lower atmosphere. To obtain the continuous simulation of hydrological variables, the SWAT hydrological model was adopted in this study. Results showed that rainfall pattern, evapotranspiration, and soil moisture will increase at moderate to significant levels in the future. This is especially seen during the far future period (i.e., 2071 to 2100). Similar results were obtained for surface runoff. For instance, surface runoff will increase up to 19.2% (RCP 4.5) and 36% (RCP 8.5) during 2100, as compared to the average historical condition (1981–2010). The results from this study will be useful for various water resources management and adaptation measures in the future, and …

Streamflow analysis is one of the significant challenges in the field of hydrology as there are substantial complex natural and human-induced factors that cause rivers to change in water levels continuously. Among these factors, several studies have reported that climate and land use changes play an essential role in streamflow variations. Therefore, timely and accurate streamflow prediction is vital to managing hydrological extremes: floods and drought. Moreover, it is crucial to understand the feature of the watershed runoff process and is valuable input for water resources systems planning towards utilization of the available water efficiently. Based on that context, the study aims to apply the SWAT (Soil and Water Assessment Tool) model and GIS to analyze streamflow response in the Upper Neuse River Watershed of North Carolina. SWAT is a physically based hydrologic model appropriate to simulate the quantity …

In the recent years, VECC has developed and tested successfully a Multichannel CSA and Shaper ASIC (VECC002) for the energy measurement of alpha (1-40 MeV) and proton in Granular charged-particle Multiplicity-filter Detector Array (GMDA). As this detection of particle will be carried out in coincident with gamma rays, particle identification capabilities have to be incorporated in the signal processing chain of GMDA. The inherent capability of CsI (Tl) detector in identification of particles is being utilized in GMDA for identification of alpha, gamma, proton etc. However, the conventional method of pulse shape discrimination [2] using the method of obtaining the ratio of the late-time charge deposition to the total deposition suffers from low Figure of Merit (FOM) especially in the lower energy region. The ZCT (Zero-Cross-Over-Timing) technique is considered as the best method for particle identification (PID) as it is independent of detector time resolution. However, higher FOM of ZCT method depends on the time resolving power of the timing discriminator circuit. For CsI (Tl) detectors, the difference in decay time constants of output for different particles corresponds to different rise times in preamplifier output. It has been identified from the experimental data that this property can be exploited for efficient pulse shape discrimination at lower energies using a timing discriminator circuit with time resolution around tens of picosecond.The development of a high resolution timing discriminator circuit in sub-micron CMOS technology has been undertaken for this purpose. The design details of this circuit has been described in the subsequent section followed …

The uncertainty associated with the financial domain in modern portfolio selection problems can be overcome by using fuzzy set theory. The portfolio is modified in this paper using the possibility theory instead of the probability theory by formulating the risk return as fuzzy numbers, and we also take into account the V-shaped transaction costs. The possibilistic semi-absolute deviation portfolio selection technique is used to develop a portfolio selection framework by considering the investor demands and stock characteristics. The higher computational complexity associated with the possibilistic mean semi-absolute deviation portfolio model is reduced using the hybris salp swarm-based Coot algorithm (SCOOT). The main aim of the hybrid SCOOT algorithm is to reduce the risk and increase the expected return. The salp swarm algorithm is integrated with the coot algorithm to enhance the global search capability. The …

Roadway and highway agencies across the globe spend a sizable fraction of their annual budget for the upkeep and maintenance of roadways. Different road segments deteriorate at different rates owing to variable traffic flow along the segments. In previous works, various forms of mathematical formulations were provided for roadway maintenance and pavement deterioration modeling. Numerical solutions algorithms using linear programming, dynamic programming, and genetic algorithms were proposed. The solution algorithms, however, did not benefit from the prescriptive and predictive capabilities of machine learning (ML) algorithms (eg, random forest classifier, support vector machine, and artificial neural networks). Furthermore, previous methods treated transition probabilities of condition states of a pavement in future years to be static. In this paper, a variable transition probability is introduced based on the deterioration rate of a pavement over time. A modified capacitated arc routing formulation is developed for a highway infrastructure management information system. Prescriptive and predictive analytics are performed using ML to analyze the road network in simulation studies and from Montgomery County, Maryland, USA. The pavement condition index (PCI) for the road network is predicted using ML algorithms. The results show a good promise for PCI prediction based on variable deterioration rate and for obtaining condition states in future years subject to varying transition probabilities.

In the execution of transportation and construction projects, the regulatory approval requirements and changes in original scope of work arising due to weather, design changes, and other unforeseen issues often result in significant cost overruns, thereby delaying the project completion schedule. In this paper, we develop a machine learning-based active learning framework to capture the risk and uncertainty in transportation and construction scheduling. In a typical critical path method, the duration times of individual tasks are assumed to be given and deterministic. In order to account for risk and uncertainty, we assume that the estimated activity duration is available from a large random sample between specified bounds. We conduct a case study for a 20-activity transportation and construction project. The result shows that the true extent of delay and cost overrun due to risk and uncertainty can be captured in the …

Land use/land cover (LULC) changes significantly affect catchment hydrology and sediment yields. The current study intends to analyze the hydrological responses of LULC changes in a monsoon dominated watershed of the Periyar River basin (PRB), Kerala, India. The Soil and Water Assessment Tool (SWAT) model is used to assess impacts on surface runoff and sediment yield. The model runs are performed by varying LULC inputs between 1988 to 2100 to evaluate the effects of LULC change. The historical LULC maps were prepared from maximum likelihood classification technique and the future LULC maps using Markov chain-cellular automata algorithm. The major LULC changes were identified as an increase of urban area by 4.13% of the catchment area and a decrease of plantation coverage by 3% between 1988 and 2016. The increase in urban area is anticipated to expand by up to 15.65%, while the …

The streambed median grain size (D50) has been an integral part of many sediment transport and stream power equations seeking to characterize stream channel stability conditions. However, its previous usage is constrained by regional applicability, localization of datasets, and a limited number of data points. This study uses a large and geographically diverse data set (n> 2400), from five published sources, to present quantitative information and assess the distribution of D50 data across the contiguous US Spatial distribution was analyzed based on the three regional frameworks: Physiographic Provinces, Level III Ecoregions, and Hydrologic Landscape Regions (HLRs). Gravel was found to be the dominant streambed material in most Physiographic Provinces. Regions with a humid climate, permeable soil, and plateaus exhibit a higher average D50 than regions with other climate, geologic texture, and landscape forms. Further analysis of all data across the US using smoothed spatial maps showed the dominance of sand and fine gravel in streams located in the central and southern US, and the dominance of coarse gravel and cobbles in the northeastern US

Introduction Bromelain based debridement (BBD) of deep burns with a concentrate of proteolytic enzymes enriched in Bromelain is approved for use in adults in several regions worldwide. Children are a large part of the patient population in many burn centers around the world. Clinical trial experience and off label reports point to BBD safety and efficacy in children as well. The aim of this study was to further assess the safety and efficacy of BBD in children, in efforts to support regulatory approval for the use of BBD in children. Methods One hundred and forty five children aged 0-18 years old suffering from deep thermal burns between 1-30% TBSA were enrolled in a multicenter, multinational, open label, randomized, controlled phase III study. Seventy two children were randomized to eschar removal with BBD and 73 children to standard of care (SOC) surgical and/or non …

The charged particle detector Array for kinematic reconstruction and analysis (ChAKRA)[1], developed for intermediate energy (∼ 10–60MeV/A) nuclear physics experiments is using an imported 16-channel commercial module for first-stage signal processing of the current signal from detector. An indigenous multichannel ASIC has been designed and developed at VECC to replace this imported module and the characterization of the ASIC has been carried out successfully for low power and low noise application.Although this ASIC has the ability to couple itself directly with the detector inside the vacuum chamber for its low power dissipation (~ 10mW/ch) as compared to the commercial module (~ 100mW/ch), however, presently, the development of a similar module, MCSA-16 (in respect of mechanical dimension, connectors etc. of the imported module) using the CSA ASIC has been undertaken for import substitution and easy transition of the existing front-end signal processing of ChAKRA. The design, development of MCSA-16 module has been described in this article followed by the characterization in respect of using it with ChAKRA. The comparison of the specification with the imported module is also carried out and shown in this paper.

journals and funding agencies. She served as associate editor for the Journal of Environmental Quality and the Soil Science Society of America Journal. She is an expert on method development for analysis of

Adequate healthy and affordable food access is the main challenge worldwide because there is a global demand for food. The World Food Summit declares as food security exists when all people at any time have enough access to healthy and affordable food which meets their needs and preferences for a healthy and active life. A food desert (FD) is a geographical area where residents have limited access to fresh fruits, vegetables, and other healthful foods. The problems of sustainable consumption of healthy foods come both from the consumers and producers. Therefore, studying the action and interaction between production and consumption-related factors contributing to FD is essential to minimizing food insecurity. Based on that context, this research aims to study the interaction between main factors in production and consumption systems using geospatial tools and agent-based modeling (ABM). The …

A Maintenance Management System (MMS) was first developed in the 1982 for implementation in the Arizona Department of Transportation in the United States. It allows for a forecast of future maintenance activities for a road network which deteriorates over time. Successive enhancements to the original MMS have been made over the years by different researchers, including some by the first author. The primary enhancements have been in the formulation and solution algorithms. The initial solution algorithms were Linear Programming (LP) and Dynamic Programming (DP), which, in some previous works, were replaced by genetic algorithms due to their efficiency over LP and DP. In this paper, we propose a Machine Learning (ML) framework for the development of a MMS, which can be a better approach than previously developed approaches. The ML framework uses a Python-based solution methodology in conjunction with geo-spatial modeling, which appears more attractive and efficient in working directly with GIS maps and databases. With respect to application, the attention is focused on African countries using Kenya as a case study example. A recent report on state of Kenyan roads found over 35 percent of Kenyan roads to be still in poor condition even though a comparison of the condition of the roads between 2003 and 2018 showed a successive improvement in road condition over the years. Poor road condition affects mobility and, in turn affects the country’s economy. We adopt a Markov Decision Process to predict the maintenance actions to be undertaken for the Kenyan road network in order to keep an acceptable level of …

Ecosystem-based adaptation (EbA) can potentially mitigate watershed degradation problems. In this study, various EbA measures were evaluated using a bio-physical model called the Soil and Water Assessment Tool (SWAT), in a small, forested watershed named Hui Ta Poe, in the northeastern region of Thailand. The developed watershed model was first used to investigate the effect of various degraded watersheds due to land-use changes on the sediment yield in the study area. The most degraded watershed produced an annual average sediment yield of 13.5 tons/ha. This degraded watershed was then used to evaluate the effectiveness of various EbA measures such as reforestation, contouring, filter strips, and grassed waterways in reducing the sediment yield. Under all individual and combined EbA scenarios analyzed, there was a significant reduction in sediment yield; however, the maximum reduction of 88% was achieved with a combined scenario of reforestation, grassed waterways, and filter strips. Reforestation alone was found to be the second-best option, which could reduce the sediment yield by 84%. Contouring alone was the least effective, with a reduction in sediment yield of only 23%. This study demonstrates the usefulness of implementing EbA measures for sediment management strategies to address watershed degradation, which is a severe problem across the globe.

The United Arab Emirates (UAE) has witnessed fast growth in urban development in the past four decades. A plan to build 7270 houses by 2021 has been initiated by the local authorities. Different local sustainability guidelines are being implemented, including the Public Realm Manual in Abu Dhabi. These local guidelines are tailored to consider the hot and arid climate of the UAE as well as the applied materials, the inclusion of greenery, shading devices, etc. Dubai, Abu Dhabi, and Al Ain are cities that have imposed the application of such guidelines. Additionally, the newly developed housing programs match the governmental plan. To understand the effect of these design programs on the outdoor thermal comfort (OTC), further investigations are necessary for each city. The most widely built prototype is detached villas, which result in untreated waste areas without shading or greenery. In the old local neighborhoods, Arabic houses were built next to each other to maximize the shading and to ease pedestrians’ walkability. This study aims to examine the districts where the housing programs are applied and to determine the most effective strategy to minimize the outdoor air temperatures and enhance walkability. The methodology implements the following processes in order: district analyses of the buildings as well as the externally applied materials, microclimate site measurements, ENVI-met (main software used) models of the current and future scenarios, results and recommendations. The strategies have different impacts in both cites due to the microclimate and other conditions.

T associated with unobserved particles and spurious values of pmiss T arising from jet energy mismeasurements. No excess of event yields above the expected standard model backgrounds is observed. The results are interpreted in terms of constraints on the parameter space of several simplified models of supersymmetry that assume the pair production of top squarks. The search provides sensitivity to a broad range of top squark (t) decay modes, including the two-body decay t→ c χ01, where c is a charm quark and χ0 1 is the lightest neutralino, as well as the four-body decay t→ b f f χ0 1, where b is a bottom quark and f and f are fermions produced in the decay of an intermediate off-shell W boson. These modes dominate in scenarios in which the top squark and lightest neutralino are nearly degenerate in mass. For these modes, top squarks with masses as large as 260 and 225 GeV are excluded, respectively, for the two-and four-body decays.© 2017 The Author. Published by Elsevier BV This is an open access article under the CC BY license

The fuzzy set theory is widely used to describe the uncertainty of financial markets in modern portfolio selection problems. In this study, the credibility theory (a popular branch of the fuzzy set theory) is applied to extend Markowitz’s mean–variance portfolio selection model into mean–variance–skewness portfolio selection model. For this, the returns on risky stocks are regarded as trapezoidal fuzzy variables. The credibilistic skewness is obtained originally for trapezoidal fuzzy variable, and the incorporation of the credibilistic variance of trapezoidal fuzzy variable enables the estimation of risk on portfolio return. To solve the proposed multi-objective optimization problem, a polynomial goal programming approach is suggested in this study. In addition, a dominant numerical analysis of the proposed work and its comparison with existing works are presented.

Food access and food security became critical components of individuals or communities, and it continues to be a serious issue all over the world, despite of the significant increase in food production. In the United States (US), millions of people struggle to access fresh fruits and vegetables and live-in food deserts (FDs). According to USDA, FD is a low-income area with limited access to affordable and nutritious foods like fresh fruits, vegetables, and other healthful whole foods. Only ten percent of adult Americans meet the standards recommended for fruits and vegetables according to a study by (Lee-Kwan et al., 2017) and most of the US census tracts are FD areas while having a high capacity to produce a large variety of fresh fruits and vegetables. Although, several researchers have analyzed food desert and security issues from an economic perspective, the factors related to natural and human systems have not …

24 The Dynamic Sight Distance (DSD) problem involves the dynamically allocated sight distance as a left-25 turning vehicle makes a move to clear a signalized intersection during the permissive phase, whose line-26 of-sight is obstructed from the presence of stationary vehicles in opposing left-turning lanes. In this paper 27 we study the DSD problem with a Machine Learning (ML) algorithm called Random Forest (RF) 28 classifier. In our previous works we used limited field data to measure gap sizes and a driver’s willingness 29 to accept or reject critical gaps to formulate the DSD problem; and calculated the probability of line-of-30 sight in the analysis. This paper extends the previous methodology by introducing additional variables 31 attributed to gap acceptance, such as obstruction angle, driver’s age, number of queued vehicles, and 32 presence or absence of a peak hour. The results show that presence or absence of peak hour and number 33 of queued vehicles are highly correlated to the driver’s decision-making in accepting or rejecting a gap. 34 Several simulation runs were conducted to improve the accuracy of the model. We conclude that the RF 35 classifier is highly effective and better than traditional Raff’s method in predicting a driver’s behavior to 36 accept or reject a gap associated with the DSD problem. Future works may include extending the 37 methodology for arterial network with many signalized intersections with DSD issues, traffic signal 38 optimization, simulation related studies, Vehicle to Vehicle communication, and Vehicle Infrastructure 39 Integration. 40

Activated carbons (ACs) were prepared from Bayer (Ziziphus Mauritiana) seed stone, an agricultural waste found in Nepal, by chemical activation with potassium hydroxide (KOH) in 1: 1 ratio by weight at two different temperature (500 C-700 C). Char and activated char were also prepared from this carbon precursor. The physiochemical properties of as-prepared ACs were examined using Iodine number, Methylene Blue number, Field Emission scanning electron microscopy (FE-SEM) and BET surface area analysis. Results showed that the activated carbon prepared at 700 C has the highest porosity and surface area. Therefore, this highly porous AC was employed as an electrode material to evaluate its possible applicability in energy storage devices. Results showed that the electrochemical performance of this AC in an acidic electrolyte is better than that in neutral electrolyte. Therefore, as-synthesized activated carbon at 700 C is suitable for adsorbent material and can also be applied for energy storage applications.

In the study of local-level food security, terms such as food variety, availability, accessibility and utilization represent quantitative metrics to describe one's relationship to the tangible and intangible food environment. Food availability entails how close one is located to the nearest food location. These locations could be healthy and fresh food as applied explicitly to the study food deserts, generally considered to be low-income areas that are far from healthy and fresh food. In the Geographic Information Systems (GIS) network model where travel times and distances are either calculated along a line network such as a series of roads or via more traditional techniques such as Manhattan or Euclidean distance, healthy and fresh food locations are defined as destinations. The places people are traveling from are referred to as sources. However, modeling source locations can be increasingly complex. In just measuring …

s= 13 TeV with the CMS detector at the LHC. Events with two leptons (e or μ) and at least four reconstructed jets, including at least two identified as b quark jets, in the final state are selected. In the full phase space, the measured ratio is 0. 022±0. 003 (stat)±0. 006 (syst), the cross section σt tbb is 4. 0±0. 6 (stat)±1. 3 (syst) pb and σt tjj is 184±6 (stat)±33 (syst) pb. The measurements are compared with the standard model expectations obtained from a powheg simulation at next-to-leading-order interfaced with pythia.© 2017 The Author. Published by Elsevier BV This is an open access article under the CC BY license

As technology advances, data-driven work is becoming increasingly important across all disciplines. Data science is an emerging field that encompasses a large array of topics including data collection, data preprocessing, data visualization, and data analysis using statistical and machine learning methods. As undergraduates enter the workforce in the future, they will need to “benefit from a fundamental awareness of and competence in data science”[9]. This project has formed a research-practice partnership that brings together STEM+C instructors and researchers from three universities and an education research and consulting group. We aim to use high-frequency monitoring data collected from real-world systems to develop and implement an interdisciplinary approach to enable undergraduate students to develop an understanding of data science concepts through individual STEM disciplines that include engineering, computer science, environmental science, and biology. In this paper, we perform an initial exploratory analysis on how data science topics are introduced into the different courses, with the ultimate goal of understanding how instructional modules and accompanying assessments can be developed for multidisciplinary use. We analyze information collected from instructor interviews and surveys, student surveys, and assessments from five undergraduate courses (243 students) at the three universities to understand aspects of data science curricula that are common across disciplines. Using a qualitative approach, we find commonalities in data science instruction and assessment components across the disciplines. This …

Access to healthy foods such as fresh fruits and vegetables has recently become the focus of policy initiatives and other responsible agencies to reduce several food-related diseases and increase food security. Various studies have shown that eating fresh fruit and vegetables protects against cardiovascular, cancer, diabetes, etc. However, according to the US Department of Agriculture (USDA), about 23.5 million people in the US live in food deserts (FD). FD are geographical areas where residents have limited access to fresh fruits and vegetables and other healthful whole foods. This research investigates and develops geospatial agent-based modeling (ABM) to understand and assess FD in our study area in NC one of the states dealing with the FD issue. Several natural and human factors contribute to food deserts, such as agricultural limitation due to increased population density, climate change, shortage of …

Bed materials of stream channels exhibit spatial size variation that is commonly attributed to abrasion and selective sorting. This spatial variation results in a process known as downstream fining, which becomes evident as one traverses from upstream to the downstream section of a river channel. This study attempted to capture the fining phenomenon using a comprehensive dataset that spanned the contiguous U.S. The dataset analyzed includes major hydrological and morphological parameters including discharge, channel slope, stream order, and median grain size for over 2200 data points. The approach adopted a regional framework of five large regions for data analyses and model development. Consistently for all five regions, the channel slope showed a continuous decremental trend with an increase in stream order. The downstream fining process was captured in most regions through a decremental …

Improvement in quality of life and optimum functional recovery after burn injury is the final goal of burn care. After major burn injuries, look (body image) and functionality changed a lot. How a person perceive himself or herself, how confident about his/her looks, and how much confident about his/her body appearance are collectively known as body image. Severe distress is present in 30% of burn survivors and perceives their distorted body image after their first hospitalization. Pre-and postoperative physiotherapy and occupational therapy provide alternative ways for these problems of burn patients. Almost everyone has certain degree of changes in their recovery phase, but most of them get used to the change in their appearance over the time.

Uncertainty surrounding the sources of nonpoint pollution and producer response to prospective policy incentives complicates the nonpoint policy problem. To explain, neither policy-makers nor producers know the exact effect of current and alternative farming practices on the contributions of specific cropped fields to nutrient pollution. Spatial heterogeneity of the production technology and environmental damage of runoff also precludes the formulation of an analytic solution, so that producer response to prospective policies is unknown a priori to the policy maker. To address the complexity arising from point source uncertainty and spatial heterogeneity, we draw on recent computational advances to reformulate the classic nonpoint source pollution problem as a multi-objective bilevel optimization problem, employing genetic algorithm (GA) solution methods. This computational framework explicitly accounts for the …

© 2016 CERN. Measurements are presented of the cross section for the production of at least four jets, of which at least two originate from b quarks, in proton-proton collisions. Data collected with the CMS detector at the LHC at a center-of-mass energy of 7 TeV are used, corresponding to an integrated luminosity of 3 pb-1. The cross section is measured as a function of the jet transverse momentum for pT > 20 GeV, and of the jet pseudorapidity for |η| < 2.4 (b jets), 4.7 (untagged jets). The correlations in azimuthal angle and pT between the jets are also studied. The inclusive cross section is measured to be σ(pp→2b+2j+X)=69±3(stat)±24(syst) nb. The η and pT distributions of the four jets and the correlations between them are well reproduced by event generators that combine perturbative QCD calculations at next-to-leading-order accuracy with contributions from parton showers and multiparton interactions.

Global warming and water/air contamination caused by human activities are major challenges in environmental pollution and climate change. The improper discharge of a large amount of agro-forest byproduct is accelerating these issues mainly in developing countries. The burning of agricultural byproducts causes global warming, whereas their improper waste management causes water/air pollution. The conversion of these waste materials into effective smart materials can be considered as a promising strategy in waste management and environmental remediation. Over the past decades, activated carbons (ACs) have been prepared from various agricultural wastes and extensively used as adsorbents. The adsorption capacity of ACs is linked to a well-developed porous structure, large specific surface area, and rich surface functional moieties. Activated carbon needs to increase their adsorption capacity, especially for specific adsorbates, making them suitable for specific applications, and this is possible by surface modifications of their surface chemistry. The modifications of surface chemistry involve the introduction of surface functional groups which can be carried out by various methods such as acid treatment, alkaline treatment, impregnation, ozone treatment, plasma treatment, and so on. Depending on the treatment methods, surface modification mainly affects surface chemistry. In this review, we summarized several modification methods for agricultural-waste-based ACs. In addition, the applications of AC for the adsorption of various pollutants are highlighted.

Ground vibration induced by blasting is a serious environmental issue in Mining industry. When explosives are detonated in a blast hole much of the energy is used to break up and move the rock or Mineral. However, there is always some energy left over and this is converted into to vibration that travels away from the blast area through both the ground and air. The vibration through the air is generally known as air overpressure & the vibration through ground is known as blast induced Ground vibration. In current mining practice, the selection of appropriate delay time is more important for rock mass movement. An initiation system is a means of detonating high explosive charges reliably at the specified time and in the correct sequence. Commonly available initiation systems for selecting suitable timing combinations are often not conveniently packaged for direct application by site engineers during the design process. On the basis of a case study, this paper evaluates the amount of vibration generated due to three initiation systems namely Electronic Detonator (ED), Non-electric with Shock Tube Delay Detonator (NONEL) and Cord Relay (CR) with Detonating Fuse (DF).

Materials and Methods:This prospective, observational study included thirty patients and was conducted from November 2016 to May 2018. Patients with thermal burns sustained< 72 h with facial burns, age group 18–60 years, were included in the study.Results:FOB was done in thirty patients. About 26.67% of patients had closed space injuries. Singeing of scalp hair/eyebrows was present in 46.67% of patients. Singeing of nasal vibrissae/mustache was present in 56.67% of patients. Eversion of eyelids and lips was present in 33.33% and 50% of patients, respectively. Hoarseness of voice, edema of tongue, and tachycardia were present in 16.67%, 50%, and 66.67% of cases, respectively. On auscultation, 26.67% patients had basal crepts. In the chest X-ray, 16.67% of patients had pulmonary edema. Forty percent of patients had arterial hypoxemia and acidosis at the time of arrival. About 56.67% of patients were …

Background Reconstruction of the auricular margin defects is challenging due to the ear’s intricate architecture. Tubed flap raised from the postauricular area is a simple and reliable option for reconstructing marginal defects. Methods Eight patients with various auricular margin defects were reconstructed, using a postauricular tubed flap in a staged manner. Parameters like flap survival, reliability, complications, and cosmesis were assessed. Results Out of eight patients, one patient had marginal necrosis, which was managed with debridement and lengthening of the flap. All the flaps settled well with a good aesthetic outcome. Conclusion Postauricular tubed flap is a reliable and efficient method for reconstructing auricular margin defects.

Accurate rainfall estimates are important in many hydrologic activities. Rainfall data are retrieved from rain gauges (RGs), satellites, radars, and re-analysis products. The accuracy of gauge-based gridded precipitation products (GbGPPs) relies on the distribution of RGs and the quality of rainfall data records obtained from these. The accuracy of satellite-based precipitation products (SbPPs) depends on many factors, including basin climatology, basin topography, precipitation mechanism, etc. The hydrologic utility of different precipitation products was examined in many developed regions; however, less focused on the developing world. The Huai Bang Sai (HBS) watershed in north-eastern Thailand is a less focused but an important catchment that significantly contributes to the water resources in Thailand. Therefore, this research presents the investigation results of the hydrologic utility of SbPPs and GbGPPs in the HBS watershed. The efficiency of nine SbPPs (including 3B42, 3B42-RT, PERSIANN, PERSIANN-CCS, PERSIANN-CDR, CHIRPS, CMORPH, IMERG, and MSWEP) and three GbGPPs (including APHRODITE_V1801, APHRODITE_V1901, and GPCC) was examined by simulating streamflow of the HBS watershed through the Soil & Water Assessment Tool (SWAT), hydrologic model. Subsequently, the streamflow simulation capacity of the hydrological model for different precipitation products was compared against observed streamflow records by using the same set of calibrated parameters used for an RG simulated scenario. The 3B42 product outperformed other SbPPS with a higher Nash–Sutcliffe Efficiency (NSEmonthly>0.55 …

The large cross section for b quark production at the CERN LHC and the high luminosity of the accelerator provide the possibility to study rare B meson decays. Recently, several experiments have reported the likely presence of structures in the J/ψφ (1020) mass spectrum from B±→ J/ψφ (1020) K±decays [1–7]. A natural extension of these results is to study the ψ (2S) φ (1020) K±and the ψ (2S) φ (1020) mass spectra. As part of that investigation, we report the first observation of the decay B±→ ψ (2S) φ (1020) K±, with ψ (2S)→ μ+ μ− and φ (1020)→ K+K−. We measure the corresponding branching fraction using data collected at the LHC with the CMS detector in proton–proton (pp) collisions at

Ground vibrations, air blasts, fly rocks, back breaks, and noises are the unkind effects of blasting, which are unavoidable but can be minimised up to permissible level to avoid damages to the surrounding environment and structures. Among all the ill effects, ground vibration is a significant concern to the engineers, designers, and environmentalists. Various laws have been communicated by scientists and are being adopted to check the ground vibration levels. This study was conducted to predict the blast-induced ground vibration (peak particle velocity) using ANN to remove the structures existing near-surface coal mines safely. The data obtained from the different mines were analysed and found that the correlation coefficient R2 between predicted and observed peak particle velocity for the ANN model was (R2= 0.865).

Variable Energy Cyclotron Centre uses plenty of Neutron Flux Monitors (NFM) for the purpose of radiation safety at different places around cyclotron installations. The NFM monitor is mainly composed of a Charge Sensitive Pulse Converter (CSPC) at the first stage after detector and a controller module connecting other units for the purpose of monitors, indicators, safety relays and remote communication. The CSPC of the existing commercial monitor, using BF3 neutron detector, faltered due to drift in the discrete components for aging effect. These components are presently obsolete and as an alternative, Cremat Inc. based CSA and shaper modules with large dynamic range/output voltage (2.1 pC/~ 3V) were used which worked successfully [1].Nevertheless, the charge produced by the neutron detector is in the range of hundreds of femtocoulomb depending upon the sensitivity and volume of the detectors. In order to keep the dynamic range of the CSPC within that limit and to have a maximum detectable voltage of one volt for high SNR, the feedback capacitor of the CSA would be in the range of hundreds of femtofarad. Such small value of capacitance is not implementable using discrete components due to parasitic effects. Moreover, as the sensitivity of BF3 detector for thermal neutron lies between 0.4-0.5 cps/nV, an optimization of equivalent noise charge is important to detect neutron flux correctly from other backgrounds [2]. The optimization techniques require alteration of the parameters of the input MOS of the CSA, bandwidth of CSA and shaper etc. which is difficult to design with discrete components and therefore a monolithic circuit is the …

Food desert communities face persistent barriers in accessing affordable fresh and healthy foods, particularly for the underserved and limited-resourced minority population. This research brief proposes an integrated design concept examining human-environment dynamics of food deserts to identify strategies that would provide effective planning to prevent, prepare for, or respond to disruptive events such as natural disasters or pandemics in the future. The North Carolina example we describe identifies the potential overlapping areas between food deserts and number of COVID-19 cases to demonstrate how an unpredictable event could exacerbate public health in food desert communities to a greater extent than in communities with better food access, availability, and accessibility. The improved understanding of food systems could help in addressing unprecedented challenges such as those due to the COVID-19 crisis.

Measuring the production of hadrons that contain b quarks plays an important role in testing quantum chromodynamics (QCD). Such studies have been carried out by several experiments, including UA1 [1, 2] at CERN, as well as CDF [3–6] and D0 [7, 8] at Fermilab. The most recent measurements are from the ATLAS [9, 10], CMS [11–17], and LHCb [18–20] Collaborations at the CERN LHC in pp collisions at centre-of-mass energies at 7 and 8 TeV. Similar studies at the higher LHC energy of 13 TeV provide a new test of theoretical calculations [21, 22]. This Letter describes a measurement of the inclusive B+ differential production cross sections as a function of the transverse momentum (pB

Background It has been a matter of discussion in years even after using an FST. Because of being a single valued membership, a fuzzy set can't express desired information. Further extended as HFSs which allows all possible membership degree lying between [0,1] is used widely where hesitancy occurs in taking preference over matters in Decision Making. Objective The aim in this paper is to create a diversified portfolio where the return is maximum and the risk is minimal. Methods Decision making methods like Fuzzy Soft Set, Mean Potentially Approach, and Soft Hesitant Fuzzy Rough Set which are based on Fuzzy Soft Set theory for construct the optimal portfolio. And non-fuzzy set method is applied for the optimal portfolio. It is found that a Soft hesitant fuzzy rough set is best as compare to other methods. Then, the ratio of optimal portfolio is obtained with the help of firefly optimization. Results Soft Hesitant …

Dealing with problems on portfolio selection models fuzzy set theory is effectively interpolating investor’s attitude. The credibility theory (Branch of fuzzy set theory) is broadly utilized to describe uncertainty of the financial markets. We regard the return rate of each risky stock as a trapezoidal fuzzy number. Variance and semi-variance of fuzzy return on stocks are widely accepted as risk measures in portfolio selection models. This paper obtains credibilistic semi-variance of trapezoidal fuzzy variable and applied this concept to quantify the risk in stock fuzzy portfolio selection. A multi-criteria credibilistic mean-semivariance-skewness model is proposed with numerical illustration taking historical data set from the premier market for financial assets. Three objectives are taken into account namely, expected portfolio return, risk on expected portfolio return and portfolio skewness to construct multi-objective programming problem, along with cardinality constraint, complete capital utilization, floor and ceiling constraint, no short selling constraints. To solve the proposed multi-objective optimization problem, optimal goal programming approach is suggested. Finally, a case study is conducted to highlight the effectiveness of the proposed models through the real-world data from the Bombay Stock Exchange (BSE), an Indian premier market for financial stocks. Furthermore, results comparison of semi-variance as risk measure with other existing risk measures is performed.

A field experiment consists of conservation agriculture (CA) and conventional tillage (CT) practices were set up in two areas, Robit and Dangishta, in sub-humid Ethiopian highlands. Irrigation water use, soil moisture, and agronomic data were monitored, and laboratory testing was conducted for soil samples, which were collected from 0 to 40 cm depth before planting and after harvest during the study period of 2015–2017. Calculation of crop coefficient (Kc) revealed a significant decrease in Kc values under CA as compared to CT. The result depicted that CA with a drip irrigation system significantly (α = 0.05) reduced Kc values of crops as compared to CT. Specifically, 20% reductions were observed for onion, cabbage, and garlic under CA whereas 10% reductions were observed for pepper throughout the crop base period. Consequently, irrigation water measurement showed that about 18% to 28% of a significant irrigation water savings were observed for the range of vegetables under CA as compared to CT. On the other hand, the results of soil measurement showed the CA practice significantly (α = 0.05) increased soil moisture (4%, 7%, 8%, and 10% increment for onion, cabbage, garlic, pepper) than CT practice even if irrigation input was small in CA practice. In addition, CA was found to improve the soil physico-chemical properties with significant improvement on organic matter (10%), field capacity (4%), and total nitrogen (10%) in the Dangishta experimental site. CA with drip irrigation is evidenced to be an efficient water-saving technology while improving soil properties to support sustainable intensification in the region.

A review of the literature published in 2019 on topics associated with the fate of environmental pollutants is presented. Environmental pollutants covered include pharmaceuticals, antibiotic‐resistant bacteria and genes, pesticides and veterinary medicines, personal care products and emerging pollutants, PFAS, microplastics, nanomaterials, heavy metals and radionuclides, nutrients, pathogens and indicator organisms, and oil and hydrocarbons. For each pollutant, the occurrence in the environment and/or their fate in engineered as well as natural systems in matrices including water, soil, wastewater, stormwater, runoff, and/or manure is presented based on the published literature. The review includes current developments in understanding pollutants in natural and engineered systems, and relevant physico‐chemical processes, as well as biological processes.

The aim of the study was to understand the dynamics of cognitive dissonance in the context of financial product purchase. A mixed methodology research approach was undertaken to explore the attitudinal and behavioural dimensions (qualitative) and subsequent empirical validation (quantitative) with a sample of customers of financial products. Qualitative research was conducted through focus group discussions to arrive at a pool of 99 items which were then pruned and validated with the help of academic and industry experts. The items were empirically tested and validated with the help of appropriate statistical tools to arrive at a “5 factor and 25 items” measurement scale for cognitive dissonance. The study found two factors “Emotional Gain” & “Financial Concern” as distinguishing factors emerging out as key findings. The arousal of cognitive dissonance after the purchase decision taken by consumer can be a major concern for marketers as it might result in order cancellations, loss of trust for the brand as well as loss of loyal customers. Measuring dissonance in financial product context post purchase can help marketers devise appropriate strategies to reduce dissonance, thereby retaining and attracting customers.

Changes in land use and land cover can have many drivers, including population growth, urbanization, agriculture, demand for food, evolution of socio-economic structure, policy regulations, and climate variability. The impacts of these changes on water resources range from changes in water availability (due to changes in losses of water to evapotranspiration and recharge) to degradation of water quality (increased erosion, salinity, chemical loadings, and pathogens). The impacts are manifested through complex hydro-bio-geo-climate characteristics, which underscore the need for integrated scientific approaches to understand the impacts of landscape change on water resources. Several techniques, such as field studies, long-term monitoring, remote sensing technologies, and advanced modeling studies have been contributing to better understanding the modes and mechanisms by which landscape changes impact water resources. Such research studies can help unlock the complex interconnected influences of landscape on water resources for quantity and quality at multiple spatial and temporal scales. In this Special Issue, we published a set of eight peer-reviewed articles elaborating on some of the specific topics of landscape changes and associated impacts on water resources.

Zinc oxide (ZnO) nanorods incorporated activated carbon (AC) composite photocatalyst was synthesized using a hydrothermal process. The AC was prepared from lapsi (Choerospondias axillaris) seed stone, an agricultural waste product, found in Nepal by the chemical activation method. An aqueous suspension of AC with ZnO precursor was subjected to the hydrothermal treatment at 140 °C for 2 h to decorate ZnO rods into the surface of AC. As-obtained ZnO nanorods decorated activated carbon (ZnO/AC) photocatalyst was characterized by various techniques, such as scanning electron microscopy (SEM), X-ray diffraction (XRD), and photoluminescence (PL) spectroscopy. Results showed that highly crystalline hexagonal ZnO nanorods were effectively grown on the surface of porous AC. The photocatalytic property of the as-prepared ZnO/AC composite was studied by degrading methylene blue (MB) dye under UV-light irradiation. The ZnO/AC composite showed better photocatalytic property than that of the pristine ZnO nanorods. The enhanced photocatalytic performance in the case of the ZnO/AC composite is attributed to the combined effects of ZnO nanorods and AC.

The traditional agriculture production system in sub-Saharan Africa (SSA) caused significant soil erosion and degradation of soil quality. In addition, dependability of rainfall for irrigation needs limits the crop production. Advanced agricultural practices are thus needed at the local level to sustain the livelihood of smallholder farmers in the region. In this study, conservation agriculture (CA) practice with drip irrigation technology was compared (using field experiments and watershed modeling) with the traditional conventional tillage (CT) practice for its potential in improving soil quality and crop productivity in the region. Biophysical data were collected (2015 to 2017) from a total of 43 paired plots (CA and CT) at four study sites in SSA: Dangishita and Robit in Ethiopia, Yemu in Ghana, and Mkindo in Tanzania. The Agricultural Policy/Environmental eXtender (APEX) model was calibrated and validated with reasonable …

The combination of measurements of the W boson polarization in top quark decays performed by the ATLAS and CMS collaborations is presented. The measurements are based on proton-proton collision data produced at the LHC at a centre-of-mass energy of 8 TeV, and corresponding to an integrated luminosity of about 20 fb− 1 for each experiment. The measurements used events containing one lepton and having different jet multiplicities in the final state. The results are quoted as fractions of W bosons with longitudinal (F 0), left-handed (F L), or right-handed (F R) polarizations. The resulting combined measurements of the polarization fractions are F 0= 0. 693±0. 014 and F L= 0. 315±0. 011. The fraction F R is calculated from the unitarity constraint to be F R=− 0. 008±0. 007. These results are in agreement with the standard model predictions at next-to-next-to-leading order in perturbative quantum …

Food desert (FD) is the area that has limited access to affordable and nutritious foods such as fresh fruits, vegetables, and other healthful whole foods. FDs are important socio-economic problems in North Carolina (NC), potentially contributing to obesity in low-income areas. If farmland is available, local vegetable production could potentially help alleviate FDs. However, little is known about land use and land-use transitions (LUTs) in the vicinity of FDs. To fill this knowledge gap, we study the farmland use in three NC counties, Bladen, Guilford and, Rutherford, located in Coastal, Piedmont, and, Mountain regions of the state, respectively. The analysis combines the United States Department of Agriculture (USDA) 2015 FD/NFD delineation of census tracts, and geospatial soil productivity and 2008–2019 land cover data. The understanding of farmland use is expected to contribute to the development of LUT components of FD Agent-Based Models (ABM).

Today the market is highly competitive and saturated with multiple products, to survive and sustain in such an environment customer experience (CE) plays a vital role. Globally, marketers and academicians are focusing on understanding and creating pleasant CE. For marketing managers understanding the elements essential to create experience will help in better management and creation of CE. The present research identifies and assess the critical success factors affecting CE for shopping malls and prioritises to determine which is more significant and causative to achieve promising CE. The study is based on the existing literature on 'customer experience' and results obtained from brainstorming sessions with academicians and retail industry experts. It scrutinises the critical success factors affecting CE which are finally confirmed in the context of shopping malls. With the analytical hierarchy process, 11 main …

The frequency and severity of floods have been found to increase in recent decades, which have adverse effects on the environment, economics, and human lives. The catastrophe of such floods can be confronted with the advance prediction of floods and reliable analyses methods. This study developed a combined flood modeling system for the prediction of floods, and analysis of associated vulnerabilities on urban infrastructures. The application of the method was tested on the Blue River urban watershed in Missouri, USA, a watershed of historical significance for flood impacts and abundance of data availability for such analyses. The combined modeling system included two models: hydrodynamic model HEC-RAS (Hydrologic Engineering Center—River Analysis System) and hydrologic model SWAT (Soil and Water Assessment Tool). The SWAT model was developed for the watershed to predict time-series hydrograph data at desired locations, followed by the setup of HEC-RAS model for the analysis and prediction of flood extent. Both models were calibrated and validated independently using the observed data. The well-calibrated modeling setup was used to assess the extent of impacts of the hazard by identifying the flood risk zones and threatened critical infrastructures in flood zones through inundation mapping. Results demonstrate the usefulness of such combined modeling systems to predict the extent of flood inundation and thus support analyses of management strategies to deal with the risks associated with critical infrastructures in an urban setting. This approach will ultimately help with the integration of flood risk assessment …

This paper investigates the spatial differences in fresh vegetable spending in Guilford County, North Carolina. We create a geo-coded spatial-temporal database for both human factors and natural factors to understand why food deserts have become a serious issue in a county with many farming activities. We find that residents living in food deserts do not buy enough fresh vegetables compared with their counterparts, even when they are shopping at full-service grocery stores. Social-economic factors are most sensitive and are important determinants of fresh food demand. Using an agent-based toy model, we find that fresh vegetable demand in each census tract in Guilford County varies to a large extent. The results suggest that the formation of food deserts may root from the demand side.

As one of the top agricultural-producing States, North Carolina can supply enough fresh produce to meet consumer demand. However, food deserts, areas with limited access to available and affordable fresh produce, are common in North Carolina. For example, Guilford County has about900 farms, and nearly 20% of its census tracts are defined as food deserts. Literature has documented that some chronic diseases, such as diabetes and obesity (eg, Flórez et al., 2015), and nutritional inequality are associated with food deserts (eg, Allot et al., 2019). This paper investigates the impact of the food environment in North Carolina, represented by three types of measurement, on fresh vegetable purchasing behavior using Nielsen Homescan data. About 3,000 households in North Carolina reported their purchased grocery items, including packaged and unpackaged vegetables, to the Nielsen database after they made about one million grocery trips between 2012 and 2017. They also reported their geographic locations (zip codes) and their socioeconomic characteristics. We use HUD-USPS ZIP crosswalk files data to identify whether one zip code has any overlap with any food desert area and the portion of residents within a zip code living in a food desert census tract. We also use average driving distance/time from households to the nearest full-service grocery stores, calculated in ArcGIS, in a zip code to approximate the food environment in that zip code. i hmiao@ ncat. edu

Events with no charged particles produced between the two leading jets are studied in proton-proton collisions at

The following is a review of published literature on textile wastewater in 2019. Presented are the sections described for the review: concise introduction on the textiles wastewater, followed by a review of present textile treatment technologies organized by physicochemical, biological, and combined processes. Lastly, a discussion of the future topics is presented. Practitioner points The discharge of textile dye wastewater represents a serious environmental problem and public health concern. Effluents from textile manufacturing, dyeing, and finishing processes contain high‐concentration recalcitrant chemicals that are resistant to biodegradation. The textile wastewater needs environmental‐friendly and cost‐effective combined treatment process.