Miracle-dz/UniFAR-FTUs huggingface dataset:
Wintertime Boundary Layer Evolution and Air Pollution Potential Over the Kathmandu Valley, Nepal

Meteorological effects on wintertime air pollution in the Kathmandu Valley were investigated using SOnic Detection and Ranging soundings, Automatic Weather Station measurements, numerical simulation using Weather Research and Forecasting data, and Chemical Transport Modeling during February 2013. A surrogate for black carbon was used for transport simulation in order to better understand the effects of local meteorological factors on air pollution. In the simulation, the emission strength of the black carbon surrogate was assumed temporally constant and spatially uniform over the Kathmandu Valley floor. The Weather Research and Forecasting simulation results were well correlated with observed meteorological measurements and demonstrated diurnal periodicity such as intrusion of westerly‐northwesterly wind into the Kathmandu Valley and modification of the boundary layer activity due to afternoon wind. The transport simulation suggested long‐lasting weak wind, thermally stable stratification, and associated small turbulence during the night and morning caused potentially severe air pollution. We propose a method using wind velocity and turbulent kinetic energy in the surface layer to characterize pollution level in the Kathmandu Valley.
Advances in Intelligent Systems and Computing

Requirements engineering and business analysis are activities considered to be important to software project success but also difficult and challenging. This paper reports on a survey conducted in Polish IT industry, aimed at identifying most widespread problems/challenges related to requirements. The survey was targeted at people performing role of analyst in commercial IT projects. The questionnaire included 64 pre-defined problems gathered from a literature review and a workshop involving a small group of analysts. It was completed by 55 respondents, each of whom assessed the frequency of occurrence for pre-defined problems and optionally could report additional problems based on their work experience. A ranking of most frequent problems is presented in this paper. Additional analyses for more specific contexts: agile projects and smaller/larger development teams are also provided. Final sections of the paper include comparison of our results and results of reported surveys conducted in other countries, followed by a discussion.
MDS-Net: A Model-Driven Stack-Based Fully Convolutional Network for Pancreas Segmentation

The irregular geometry and high inter-slice variability in computerized tomography (CT) scans of the human pancreas make an accurate segmentation of this crucial organ a challenging task for existing data-driven deep learning methods. To address this problem, we present a novel model-driven stack-based fully convolutional network with a bi-directional convolutional long short-term memory network for pancreas segmentation, termed MDS-Net. The MDS-Net's cost function includes data approximation term and prior knowledge regularization term combined with a stack scheme for capturing and fusing the two-dimensional (2D) and local three-dimensional (3D) context information. Specifically, 3D CT scans are divided into multiple stacks, and each multi-slice stack is used as a basic unit for network training and modeling of the local spatial context. To highlight the importance of single slices in segmentation, the inter-slice relationships in the stack data are also incorporated in the MDS-Net framework. For implementing this proposed model-driven method, we create a stack-based U-Net architecture and successfully derive its back-propagation procedure for end-to-end training. Furthermore, a bi-directional convolutional long short-term memory (BiCLSTM) network is utilized to integrate upper and lower slice information, thereby ensuring the consistency of adjacent CT slices and intra-stack. Finally, extensive quantitative assessments on the NIH Pancreas-CT dataset demonstrated higher pancreatic segmentation accuracy and reliability of MDS-Net compared to other state-of-the-art methods.
WORKING PAPER SERIES

Since the work of Cobb and Douglas [18], two main innovations have been introduced in applied factor demand analysis, i.e. the use of exible functional forms and the modelling of dynamics, expectations, and the interrelatedness of the adjustment process. Recently, cointegration theory has provided an additional important contribution, yielding empirical content to the notion of equilibrium employed in economic analysis, encompassing both the idea of centre of gravity relationship, suggested by Classical economists, and the notion of market-clearing position, employed by Neoclassical economist. Also in the light of the most recent generalizations of the concept of cointegration, allowing for economic attractors changing over time, as the evolution of the structural features of the economy proceeds, this paper critically assess the key theoretical and empirical issues in factor demand analysis. Key words : factor demand, exible functional forms, error correction model, cointegration. JEL classi cation
The Emotional Experience of Guilt in Ethically Questionable Consumer Situations

The current research scrutinizes the discrete emotion of guilt in situations in which the consumer benefits at the expense of the seller. A first objective was to endorse previous made assumptions of guilt being an important emotion in ethically questionable consumer situations. Therefore, in a first study the experience of guilt (versus shame) is explored across four different questionable consumer behaviors relying on two key ingredients of the guilt emotion, i.e. perceived control and omission/commission. A second objective was to examine what causes guilt to occur in these questionable situations (study 2a/b). Two distinct conceptualizations of the guilt emotion are investigated, i.e. the intrapsychic and interpersonal perspective. Results support both notions of the guilt emotion separately in the context of consumer ethics. When investigating the consequent ethical intentions, it was found to be sufficient for consumers’ behavioral decisions to alter if one of the two perspectives is made salient, that is, when guilt is aroused. Implications are discussed for both consumer ethics literature and consumer behavior research in general.
Content-based image retrieval: Concept and current practices

Research in content-based image retrieval (CBIR) today is a lively discipline and expanding in breadth. Content-based image retrieval is a computer vision technique to the image retrieval problem of searching for digital images in huge databases. Weather forecasting, data mining, remote sensing, medical imaging, education, crime prevention and management of earth resources are a few domains where content-based image retrieval technique is in huge demand. To improve visual similarity search and image retrieval process in content-based image retrieval many studies have been conducted and methods developed in recent years, but there are a few issues that need to be addressed. This paper explores the current practices in content-based image retrieval and their effectiveness.
Interannual and Seasonal Patterns of Carbon Dioxide, Water, and Energy Fluxes From Ecotonal and Thermokarst‐Impacted Ecosystems on Carbon‐Rich Permafrost Soils in Northeastern Siberia

Eastern Siberia Russia is currently experiencing a distinct and unprecedented rate of warming. This change is particularly important given the large amounts of carbon stored in the yedoma permafrost soils that become vulnerable to thaw and release under warming. Data from this region pertaining to year‐round carbon, water, and energy fluxes are scarce, particularly in sensitive ecotonal ecosystems near latitudinal treeline, as well as those already impacted by permafrost thaw. Here we investigated the interannual and seasonal carbon dioxide, water, and energy dynamics at an ecotonal forested site and a disturbed thermokarst‐impacted site. The ecotonal site was approximately neutral in terms of CO2 uptake/release, while the disturbed site was either a source or neutral. Our data suggest that high rates of plant productivity during the growing season at the disturbed site may, in part, counterbalance higher rates of respiration during the cold season compared to the ecotonal site. We also found that the ecotonal site was sensitive to the timing of the freezeup of the soil active layer in fall, releasing more CO2 when freezeup occurred later. Both sites showed a negative water balance, although the ecotonal site appeared more sensitive to dry conditions. Water use efficiency at the ecotonal site was lower during warmer summers. Overall, these Siberian measurements indicate ecosystem sensitivity to warmer conditions during the fall and to drier conditions during the growing season and provide a better understanding of ecosystem response to climate in a part of the circumpolar Arctic where current knowledge is weakest.
Thermodynamic and dynamic influences in the Far East‐Okhotsk region on stagnant Meiyu‐Baiu

Westerly perturbation is enlarged over the Far East‐Okhotsk region in late June and early July and is associated with the largest land‐sea heating contrast surrounding the Sea of Okhotsk. The corresponding characteristics in the lower troposphere are southward deepening of the cold low over northeastern China, and intensification of the Okhotsk high. Coincidentally, the Meiyu‐Baiu coupled with the western North Pacific (WNP) subtropical high is nearly stagnant during this period. By simulations using a global climate model with an intensified Okhotsk surface high in response to cooling Sea of Okhotsk, it is suggested that the enhanced thermal contrast over the Far East‐Okhotsk region can generate an obstacle to Meiyu‐Baiu poleward migration. Corresponding to the intensified Okhotsk high, the WNP subtropical high is strengthened by the high ridge over Taiwan. The East Asian midlatitude westerly jet stream in the northern flank of the WNP subtropical high also strengthens; the consequently enhanced midtropospheric warm temperature advection can regulate the latitude position of the Meiyu‐Baiu. The wave source generated in the upper troposphere is located over the midlatitude WNP (anomalous cyclone) bordering the Sea of Okhotsk, whereas that in the lower troposphere is related to the strengthened westerly in the northern WNP subtropical high. The wave activity propagation consistently indicates the strengthening and equatorward confinement of the westerly jet. Therefore, the intensified Okhotsk high and enlarged westerly perturbation beginning in late June are suggested as an inherently geographic limit of the Far East‐Okhotsk region in regard to Meiyu‐Baiu migration.
Metabolic health , weight management and obesity prevention in childhood and adolescence Effectiveness of lifestyle intervention in overweight children

Therapy of choice in obese children and adolescents is lifestyle intervention based on nutrition education, behavioural treatment and exercise treatment. Its efficacy even after the end of intervention has been proven by several randomised-controlled trials and meta-analyses including a recent Cochrane review. However, randomised-controlled trials are likely to overestimate the effectiveness. Studies under normal day-to-day circumstances demonstrated only a very moderate effect on weight loss (<10% success rate 2 years after the onset of intervention). A reduction of >0.5 SDS-BMI (which means a stable weight over 1 year in growing children) is associated with an improvement of cardiovascular risk factors, while improvements of quality of life seem independent of the degree of weight loss. Younger children and less overweight children particularly profit from lifestyle interventions in contrast to extremely obese adolescents. Recent studies demonstrated that involving parents is crucial for success, suggesting that parents and children and not children alone should be the primary target of interventions. Failures in weight reduction are attributed not only to a lack of motivation but also to other aspects particular to the genetic background. The techniques, more than the contents, of an intervention influence the treatment outcome. Besides behavioural therapy, systemic and solution-focused treatments are important. Future longitudinal research should focus on the identification of which children and adolescents profit from which kind of intervention, in order to be able to tailor specific treatment approaches. Studies under normal dayto-day circumstances are necessary to prove the benefit of this kind of intervention.
NeuroImage: Clinical

With the advent of Big Data Imaging Analytics applied to neuroimaging, datasets from multiple sites need to be pooled into larger samples. However, heterogeneity across di ﬀ erent scanners, protocols and populations, renders the task of ﬁ nding underlying disease signatures challenging. The current work investigates the value of multi-task learning in ﬁ nding disease signatures that generalize across studies and populations. Herein, we present a multi-task learning type of formulation, in which di ﬀ erent tasks are from di ﬀ erent studies and populations being pooled together. We test this approach in an MRI study of the neuroanatomy of schizophrenia (SCZ) by pooling data from 3 di ﬀ erent sites and populations: Philadelphia, Sao Paulo and Tianjin (50 controls and 50 patients from each site), which posed integration challenges due to variability in disease chronicity, treatment exposure, and data collection. Some existing methods are also tested for comparison purposes. Experiments show that classi ﬁ cation accuracy of multi-site data outperformed that of single-site data and pooled data using multi-task feature learning, and also outperformed other comparison methods. Several anatomical regions were identi ﬁ ed to be common discriminant features across sites. These included prefrontal, superior temporal, insular, anterior cingulate cortex, temporo-limbic and striatal regions consistently implicated in the pathophysiology of schizophrenia, as well as the cerebellum, precuneus, and fusiform, middle temporal, inferior parietal, postcentral, angular, lingual and middle occipital gyri. These results indicate that the proposed multi-task learning method is robust in ﬁ nding consistent and reliable structural brain abnormalities associated with SCZ across di ﬀ erent sites, in the presence of multiple sources of heterogeneity.
Computer Vision and Image Understanding

Human motion recognition is one of the most important branches of human-centered research activities. In recent years, motion recognition based on RGB-D data has attracted much attention. Along with the development in arti ﬁ cial intelligence, deep learning techniques have gained remarkable success in computer vision. In particular, convolutional neural networks (CNN) have achieved great success for image-based tasks, and recurrent neural networks (RNN) are renowned for sequence-based problems. Speci ﬁ cally, deep learning methods based on the CNN and RNN architectures have been adopted for motion recognition using RGB-D data. In this paper, a detailed overview of recent advances in RGB-D-based motion recognition is presented. The reviewed methods are broadly categorized into four groups, depending on the modality adopted for recognition: RGB-based, depth-based, skeleton-based and RGB+D-based. As a survey focused on the application of deep learning to RGB-D-based motion recognition, we explicitly discuss the advantages and limitations of existing techniques. Particularly, we highlighted the methods of encoding spatial-temporal-structural information inherent in video sequence, and discuss potential directions for future research.
Mechanisms for wintertime fjord-shelf heat exchange in Greenland and Svalbard

No region has felt the effects of global climate change more acutely than the cryosphere, which has changed at an unprecedented rate in the past two decades. The scientific consensus is that these changes are driven largely by increasing ocean heat content at high latitudes. In southeast Greenland, acceleration and retreat of the marine-terminating glaciers contributes significantly towards global sea level rise. Circulation in the fjords which accommodate these glaciers is thought to be driven both by freshwater input and by barrier wind-driven shelf exchange. Due to a scarcity of data, particularly from winter, the balance between these two mechanisms is not fully understood. In Svalbard, increasing water temperature has decimated sea ice cover in many of the fjords, and had substantial implications for the local ecosystem. While there is a relatively comprehensive literature on shelf exchange mechanisms in Svalbard fjords, questions remain over how the internal circulation interacts with exchange mechanisms. The region shares a similar underwater topography and oceanographic setting with southeast Greenland, with marine-terminating glaciers in close proximity to warm Atlantic waters, and results from Svalbard can hence be used to inform studies of high-latitude fjord-shelf exchange in a broader context. A realistic numerical model was constructed with the aim of better understanding the interaction between Kangerdlugssuaq Fjord and the adjacent continental shelf, and quantifying heat exchange during winter. The model was initially run in an idealised configuration with winter climatological forcing fields, incorporating a parameterisation for melting at the terminus, and used to test the impact of barrier wind events. The Earth’s rotation played a crucial role in the nature of the circulation and exchange in the fjord, with inflow on the right (looking up-fjord) and outflow on the left. While the heat delivered into the fjord-mouth was smaller than that observed in summer, the background internal circulation was found to efficiently distribute waters through the fjord without external forcing, and the heat delivered to the glacier terminus was comparable to summer values. Barrier winds were found to excite coastally-trapped internal waves which propagated into the fjord along the right-hand side. The process was capable of doubling the heat delivery. The process also enhanced the background circulation, likely via Stokes’ Drift. The model was then adapted to simulate winter 2007-08 under historical forcing conditions. Time series
Studies on morphometry and hydrology of Gandhisagar reservoir with special reference to its fisheries

Gandhisagar, the second largest reservoir of India is located in Mandsaur district of Madhya Pradesh at latitude 24°44'N and longitude 75°33'E at an altitude of 403.56m MSL in orientation from NE to SE. It has an extensive water spread area of 66000 ha at full reservoir level with a maximum and mean depth of 49.52 and 11.73 m respectively. The maximum length and width of the reservoir are 112 and 16km having a total shore line of 442km. Details of catchment area, bathymetry, standard hydrological data giving water level relation of the basin to water spread area, volume and fish production and the bottom topographical details of 11 experimental fishing stations and 6 fish landing centres are discussed.
Monetary Policy and the House Price Boom Across U.S. States

The authors use a dynamic factor model estimated via Bayesian methods to disentangle the relative importance of the common component in the Office of Federal Housing Enterprise Oversight’s house price movements from state- or region-specific shocks, estimated on quarterly state-level data from 1986 to 2004. The authors find that movements in house prices historically have mainly been driven by the local (state- or region-specific) component. The recent period (2001–04) has been different, however: “Local bubbles” have been important in some states, but overall the increase in house prices is a national phenomenon. The authors then use a VAR to investigate the extent to which expansionary monetary policy is responsible for the common component in house price movements. The authors find the impact of policy shocks on house prices to be very small.
Phytosocytological and Floristic Analysis of Caatinga Biome in Aparecida, PB, Brazil

This study aimed to evaluate the floristic composition and the phytosociological structure in two apiaries areas on Caatinga biome: a non-preserved and a preserved area both in the municipality of Aparecida, PB, Brazil. The non-preserved area (area I) had 25 apiaries, and the preserved area had 28 apiaries (area II). A total of 110 individuals, five families, and ten species were found at area I, and 330 individuals, eight families and 12 species at area II. However, area I showed higher Shannon-Wiener diversity index (1.93) than area II (1.52). The deforestation is responsible by the low number of individuals at the area I. Our results show a diversity of shrubs and trees species with great apicultural potential to be used by family farmers from the planning of the beekeeping activity.
Technical Efficiency and Its Determinants in Production of Cropping Systems in Kolar District, Karnataka

Technical efficiency was examined by collecting data from Kolar district of Karnataka under four distinct groups viz., vegetable-based small (VS), vegetable-based large (VL), cereal-based small (CS) and cereal-based large (CL) cropping systems by adopting multistage purposive cum random sampling technique. Data Envelopment analysis (DEA) was used for estimating the technical efficiency and the results indicated that nearly 38.33 per cent of farms under assumption of constant returns to scale performed with the efficiency level equal to 0.9 or greater, i.e., 46 out of 120 farmers in the entire cropping system. Distribution of farms in three regions of production frontier revealed that majority of farms i.e., 70 per cent of the farms in VS, 60 per cent in VL, 77 per cent in CS and 67 per cent in CL systems were found to be operating in the region of increasing returns or the suboptimal region. The production scale of these farms can increased while decreasing costs, since they were performing below the optimum production scale. Original Research Article Raghavendra and Sreenivasa; JEMT, 22(4): 1-9, 2019; Article no.JEMT. 47480 2
International Journal of Evaluation and Research in Education (IJERE)

Received Dec 14, 2021 Revised Jun 13, 2022 Accepted Jul 4, 2022 Literature suggested that the enforcement of lockdowns such as the Movement Control Order (MCO) had limited physical social interaction and therefore increased the inclination on social media and other means of digital communication. This shift of social pattern was reported to alter the way young adults develop their mattering, the sense of how much they matter to others. While mattering has been reported as the protective factors against social anxiety, this study aims to investigate the contribution of interpersonal mattering and societal mattering on social anxiety among university students who had to study online from home during the enforcement of the MCO in Malaysia amidst the COVID-19 pandemic in early 2021. Purposive sampling was conducted to recruit 158 participants (89 females, 69 males) with their ages ranging from 18 to 25 years of age (M=21.77, SD=1.54) to respond to Mattering to Others Questionnaire, University Mattering Scale, and Social Phobia Inventory. The results of multiple linear regression supported the hypotheses that both types of mattering negatively predict social anxiety, and that interpersonal mattering was no longer a significant predictor when controlling for societal mattering.