Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling Recovery Rate for Incomplete Defaults Using Time Varying Predictors

The Internal Rating Based (IRB) approach requires that financial institutions estimate the Loss Given Default (LGD) parameter not only based on closed defaults but also considering partial recoveries from incomplete workouts. This is one of the key issues in preparing bias-free samples, as there is a need to estimate the remaining part of the recovery for incomplete defaults before including them in the modeling process. In this paper, a new approach is proposed, where parametric and non-parametric methods are presented to estimate the remaining part of the recovery for incomplete defaults, in predefined intervals concerning sample selection bias. Additionally it is shown that recoveries are driven by different set of characteristics when default is aging. As an example, a study of major Polish bank is presented, where regression tree outperforms other methods in the secured products segment, and fractional regression provides the best results for non-secured ones.
Adsorption of Pharmaceutically Active Compounds (PhACs) by Powdered Activated Carbon from Natural Water --Influence of Natural Organic Matter (NOM)

iv List of Tables vii List of Figures viii 1. Background and Introduction 1 1.1 Presence of PhACs in the Environment 1 1.2 Concentrations in the Environment 2 1.3 Treatment Techniques 4 1.4 Activated Carbon Adsorption 6 1.5 Objectives of Study 10 2. Experiment 12 2.1 Adsorbates 12 2.2 Adsorbent 14 2.3 HPLC Measurement 17 2.4 Kinetics Experiment 17 2.5 Isotherm Experiment 18 2.6 Mathematical Modeling of Isotherm Data 19 2.6. 1 Langmuir Isotherm 19 2.6. 2 Freundlich Isotherm 19 2.6. 3 Koble–Corrigan Isotherm 19 3. Results and Discussion 22 3.1 Adsorption Isotherms 22 3.2 Possible Intermolecular Forces 28 3.3 Adsorption Kinetics 30 3.4 Modeling Results of Isotherms and Kinetics Data 32 3.4. 1 Isotherm Modeling 32 3.4. 2 Kinetics Modeling 35 4. Conclusion 41
Feeding behaviour and pugmark analysis of elephants in Sarguja, Chhattisgarh

The pugmark analysis of the elephants offers basic information to track the wild elephant migratory route, identification and census. For its study, four blocks viz, Sitapur, Lundra, Batouli (Sarguja district) and Farsabahar (Jashpur district) of northern Chhattisgarh were selected because these blocks are commonly visited by elephants and a major path route of movement of heard in inter/intra state. The most commonly consumed species belongs to family poaceae (22.58%) followed by fabaceae (19.35%) but their diet was mainly dependent on availability of seasonal food round the year and on their migration. Elephants extensively fed on Artocarpus heterophyllus, Syzygium cumini, Acacia nilotica, A. catechu, Dalbergia sissoo, Zizyphus mauritiana, Aegle marmelos and Ficus species, besides these elephants also utilized various grasses and shrubs as their food, which mainly included Dendrocalamus strictus, Cynodon dactylon etc. Elephants sometimes spent long time to feed on some particular plant species like D. strictus and Ficus species. Crop raiding, which was sporadic during the rainy season, gradually increased with more area being cultivated with the onset of monsoon. Analysis of pugmark revealed that the circumference varied from 63.80 cm to 172.70 cm whereas length x width varied from 22x20 cm to 60x55 cm, which reflects a substantial variation/differentiation of individual in heard in respect of their age, sex, size etcTherefore, management implications are needed to conserve the corridors for their long term survival and reduction of HEC. The study will be helpful to provide key information and facilitate better understating of the scenario to the forest department, policy maker and conservationist to plan, manage and improve the habitat towards the restoration and afforestation of suitable palatable species preferred by elephants of northern corridors of Chhattisgarh.
Marketed Surplus of Coffee by Smallholder Farmers in Seka Chokorsa District, Jimma Zone, Ethiopia: Determinants Analysis

Coffee is mainly produced for market and is an important export cash crop in the study area. This study analyzed the determinants of sundried coffee marketed surplus by smallholder farmers in Seka chokorsa district of Jimma Zone. Both data sources and types, primary and secondary, qualitative and quantitative, were used to achieve the objective of the study under consideration. These data were collected from 124 smallholders coffee producers who were randomly selected in the study area using questionnaires and other stakeholders who directly or indirectly deal with coffee production and supply were interviewed. Multiple linear regression model was used to analyze the determinants of sundried coffee marketed surplus as all coffee producers were supplied coffee to the market and the assumptions of OLS were tested which indicated the absence of violations due to fitness of the model with data collected. The result of multiple regression model revealed that coffee farming experience, family size, land size, coffee market information and membership to the cooperatives affected marketed surplus of sundried coffee positively and significantly whereas sex of the household head and distance from the nearest market affected negatively and significantly. Therefore, policy needs to emphasize at encouraging women to increase their coffee supply and expanding the accessibility of market infrastructure to close the gap, and further, strengthening farmers cooperatives, increasing the production and productivity of coffee land, developing farmers experience through skills and knowledge, and facilitation of market and information access are highly recommended in order to increase coffee marketed surplus by smallholder coffee farmers in the area. Keywords: Determinants, Sundried Coffee, Marketed surplus, Multiple Linear Regression Model DOI: 10.7176/DCS/10-8-02 Publication date: August 31 st 2020
Soil Carbon Fractions in Rubber Trees, Pasture, and Secondary Forest Areas

This study quantify the total organic carbon content, light fraction organic matter (LFOM), and soil organic matter fractions (from chemical and physical fractionations) in four different cultivation areas: 1 and 2) rubber tree clonal plantations (FX 3864 and IAN 873); 3) a pasture; and 4) a secondary forest. The research was carried out using soil samples from clonal plantations of eight-year-old rubber trees, located in the coastal plain (Tabuleiros Costeiros) of the state of Rio de Janeiro. The difference in the management of the rubber tree clone area promoted improvements in the soil quality, as it increased the carbon contents of the granulometric fractions, LFOM, and humic substances from the IAN 873 clone area. Both rubber tree areas evaluated presented higher mineral-associated organic carbon levels and humic substances than did the pasture area, reinforcing the reforestation potential of areas with degraded pastures through hevea culture.
Empirical Research on the Application of a Structure-Based Software Reliability Model

Reliability engineering implemented early in the development process has a significant impact on improving software quality. It can assist in the design of architecture and guide later testing, which is beyond the scope of traditional reliability analysis methods. Structural reliability models work for this, but most of them remain tested in only simulation case studies due to lack of actual data. Here we use software metrics for reliability modeling which are collected from source codes of post versions. Through the proposed strategy, redundant metric elements are filtered out and the rest are aggregated to represent the module reliability. We further propose a framework to automatically apply the module value and calculate overall reliability by introducing formal methods. The experimental results from an actual project show that reliability analysis at the design and development stage can be close to the validity of analysis at the test stage through reasonable application of metric data. The study also demonstrates that the proposed methods have good applicability.
1 Crop Breeding and Applied Biotechnology - 20(2): e282920217, 2020 Adaptability and yield stability of soybean genotypes by REML/BLUP and GGE Biplot

: The aim of this study was to ascertain the association between the REML/BLUP and GGE Biplot methodologies for selection of superior genotypes in regard to adaptability and yield stability for various regions of the Middle North region of Brazil. Sixteen soybean genotypes were evaluated in eight environments during the 2015/2016 and 2016/2017 crop seasons, analyzing the following traits: number of days to maturity, plant height, one hundred seed weight, and grain yield. In this study, the REML/BLUP and the GGE Biplot methods are highly correlated in terms of genotype ranking for selection and recommendation purposes. The genotypes BRASBT13-0528, M8372 IPRO, and BRASBT13-0621 most approximate a hypothetical ideal genotype.
Polyp-Net: A Multimodel Fusion Network for Polyp Segmentation

Computer-aided diagnosis of disease primarily depends on proper vision-based measurement (VBM). The traditional approach followed for diagnosis of colorectal cancer includes a manual screening of colorectum via a colonoscope and resection of polyps for histopathological analysis to decide the grade of malignancy. This procedure is time-consuming and expensive, and removal of benign polyp for analysis signifies the inefficiency of the diagnosis system. These drawbacks inspired us to develop an automatic vision-based analysis method for preliminary in vivo malignancy analysis of the polyp region. In this work, we have proposed a fusion-based polyp segmentation network, namely, Polyp-Net. Recently, convolutional neural networks (CNNs) have shown immense success in the domain of medical image analysis as it can exploit in-depth significant features with high discrimination capabilities. Therefore, motivated by these insights, we have proposed an enriched version of CNN with a nascent pooling mechanism, namely dual-tree wavelet pooled CNN (DT-WpCNN). The resultant segmented mask contains some surplus high-intensity regions apart from the polyp region. These shortcomings are avoided using a new variation of the region-based level-set method, namely, the local gradient weighting-embedded level-set method (LGWe-LSM), which shows a significant reduction of false-positive rate. The pixel-level fusion of the two enhanced methods shows more potentiality in the segmentation of the polyp regions. Our proposed network is trained on CVC-colon DB and tested on CVC-clinic DB. It achieves a dice score of 0.839, volume-similarity of 0.863, precision of 0.836, recall of 0.811, F1-score of 0.823, F2-score of 0.815, and Hausdorff distance of 21.796 which outperforms the existing baseline CNN’s and recent state-of-the-art methods.
Metabolic Mechanisms of Host Species Against Citrus Huanglongbing (Greening Disease)

Abstract Huanglongbing (HLB), previously known as citrus greening disease, is a devastating disease caused by gram negative, phloem-limited, fastidious bacteria Candidatus Liberibacter spp. HLB exists in nearly all commercially cultivated citrus, causing losses to growers by affecting tree vigor, production, fruit development, and quality. Recently, some promising HLB-tolerant germplasm has been identified, and showed particularly high concentration of metabolites, such as flavone, flavanone, aldehyde, and monoterpene. This review focuses on the citrus metabolic response against the HLB and we have summarized a comprehensive metabolic pathway that is activated in response to HLB. The antibacterial role of these metabolites, which were high in the HLB tolerant varieties are discussed. Generally, most of the amino acids, flavonoids, terpenes, and volatile compounds were significantly higher, even hundreds times of increase, in HLB-tolerant varieties. We also summarized the secondary metabolites, which were differentially altered in leaves, fruits, phloem sap (stem), and roots of infected citrus plants. Different metabolic studies have suggested that particular metabolites may play vital role in restricting the movement and multiplication of pathogens. Moreover, these metabolic signatures can be developed into tolerance markers against HLB. Genome-editing technologies should be used to confirm the functions of candidate genes responsible for increased production of compounds related to HLB tolerance. Engineering the metabolic pathways to create an ideal combination of gene alleles to propel metabolite flow for the antimicrobial activities, is an alternative tool to breed tolerant cultivars against HLB.
Cooperative Relaying for URLLC in V2X Networks

We characterize a two-phase transmission scheme for a vehicle-to-everything (V2X) network, designed for ultra-reliable low-latency communications (URLLC). In the proposed scheme, the user-plane latency period for the URLLC application is divided into two phases by a partitioning factor. First, we derive the signal to noise ratio (SNR) coverage probability of a test vehicular node in the network as a function of the partitioning factor. We also study the impact of interference on the system performance. We show that the proposed scheme performs better in terms of the service outage as compared to a broadcast-only protocol for small file sizes. On the contrary, resource partitioning proves detrimental for large file sizes. Then, for the noise-limited case, we study the trend of the optimal resource-partitioning factor with respect to the transmitted data-size and the density of the vehicular nodes in the network. This letter shows that the data-size has a larger impact on the information outage, as compared to the density of the vehicular nodes.
Will Public External Debt And Private Investment Sustain Agricultural Growth In Nigeria? A Monte Carlo Simulation Approach

The recent debate of research is the conflicting view with respect to public debt and empowerment of private sector as a driving force for the sustainability of the economy. Therefore this study was undertaken to evaluate the extent to which changes in public external debt and changes in private investment affect the agricultural growth. The result of the study showed that by increasing public external debt and decreasing domestic private investment the simulated data was higher compared to the baseline result implying that it supports the Keynesian view. By decreasing public external debt and increasing domestic private investment, the scenario simulated data, for agricultural growth were lower compared to the baseline implying that private investment alone cannot sustain agricultural growth in Nigeria. It was therefore recommended that specialized development agencies should be set up with the aim of implementing and evaluating government policies on foreign external debt and domestic private investment.
Variability, heritability and genetic advance for yield and its component traits in NPT core set of rice (Oryza sativa L.)

Presence of adequate genetic variability and its critical analysis are needed for initiating any crop improvement programme and for adopting appropriate selection techniques. An investigation was carried out to know the extent of genetic variability present in forty six genotypes of rice during kharif 2017. Analysis of variance revealed highly significant differences for all the 12 characters, indicating the presence of genetic variability among the genotypes. The magnitude of PCV was slightly higher than GCV for the traits viz., plant height, number of tillers per plant, number of panicles, panicle weight, grain number, test weight, single plant yield, plot yield and biomass, indicating less influence of environmental factors on the expression of traits and the possibility for genetic improvement through direct selection for these traits. The estimates of PCV and GCV were moderate for the traits viz., days to 50% flowering, panicle length and harvest index, indicating the influence of environment rather than the genotype alone. The heritability and genetic advance estimates were moderate for panicle length and high for all the other traits viz., days to 50% flowering, plant height, number of tillers per plant, number of panicles, panicle length, panicle weight, grain number, test weight, single plant yield, plot yield, biomass and harvest index, indicating the influence of additive gene action, as such selection would likely be effective for improvement of these traits.
Traditional yogurt dilemma; rich flavor vs. microbial safety: An investigation on Volatile Aroma Profiles, Chemical, and Microbiological Qualities of Traditional Yogurts

This study aimed to bring out chemical, physical, and microbiological quality together with volatile aroma profiles of traditional yogurts collected from the highlands of Ordu and Giresun cities in the Black Sea Region (Turkey). For this purpose, 24 traditional yogurts, 20 of which were produced from cow milk and the remaining were produced from buffalo milk, were collected and analyzes were performed. The average dry matter, protein, fat, pH, total acidity (lactic acid%), viscosity (10 °C), and syneresis values for cow milk and buffalo milk yogurts were 12.68 vs. 14.44%, 3.51 vs. 4.13%, 4.51 vs. 6.55%, 3.80 vs. 3.78, 1.32 vs. 1.60%, 241.09 vs. 1009.21 cP, and 17.43 vs. 9.02%, respectively. The buffalo milk yogurts had higher dry matter, protein, fat, viscosity but lower syneresis values compared to those of cow milk yogurts. The lactic acid bacteria counts were under the required number of 107 for cow yogurts while yeast & mould counts were over 105 for both cow and buffalo yogurts. Moreover, five of the cow yogurts were found to have coliforms and one being contaminated with Escherichia coli indicating unhygienic production conditions. All yogurts contained acetaldehyde, acetoin, ethanol, hexanoic acid, octanoic acid, hexanal, 2-Heptanaone, and 2-Nonanone while diacetyl could not be detected in any yogurt samples. Regarding their compositional values, homemade yogurts were acceptable however they were not appropriate for consumption microbiologically and require improved hygienic conditions for healthier products.
Study of depression, anxiety, and social media addiction among undergraduate students

This paper studies the connection between social media addiction and mental disorder from the existing investigation among undergraduate students. A comprehensive document search was conducted by using six electronic databases, including PubMed, Scopus, ScienceDirect, Web of Science, JSTOR, ProQuest Education to identify articles published before November 21st, 2019. All collected papers focused on studying social media addiction and psychosis. Two reviewers individualistically evaluated the quality of the study by using the Joanna Briggs Institute’s approach. Five articles were filtered out through the screening process and included in the review. The high prevalence of social addiction among college students (9.7% ~ 41%) has been clarified. The association between social media addiction and mental disorders is positive for student health. This article contributes to raising awareness and finding solutions to these risk problems. The study also confirms the connection between online shopping addiction and eating disorders among social addicts. We also discuss the causes and harms of social media addiction.
Horse Gait Identification Using Distributed Acoustic Sensing

In this paper field measurements are carried out using a distributed acoustic sensing system (DAS) for the identification of horse gait. The DAS system has a spatial resolution of 1 m, frequency range of 1–5 kHz and the fiber length is of about 70 m. The optical fiber cable lays down into trench of 15 cm of depth. Several measurements are also carried out in order to fully understand the measuring capacity of the system, including a 2 kg calibrated impact hammer and a small controlled blast of 12.6 Pa of air pressure. Results demonstrate the capacity to measure soil mechanical waves speed of 171 m/s for the impact hammer tests and sound speeds in air of about 366 m/s for the controlled blast tests. The experiments involving horses allowed the identification of three distinct horse gait patterns: step, trot and gallop, as well the horse speed in each gait with SNR about 30 dB.
Novel ‘Bacteriospray’ Method Facilitates the Functional Screening of Metagenomic Libraries for Antimicrobial Activity

Metagenomic techniques, notably the cloning of environmental DNA (eDNA) into surrogate hosts, have given access to the genome of uncultured bacteria. However, the determination of gene functions based on DNA sequences alone remains a significant challenge. The functional screening of metagenomic libraries represents an interesting approach in the discovery of microbial metabolites. We describe here an optimized screening approach that facilitates the identification of new antimicrobials among large metagenomic libraries. Notably, we report a detailed genomic library construction protocol using Escherichia coli DH10B as a surrogate host, and demonstrate how vector/genomic DNA dephosphorylation, ligase inactivation, dialysis of the ligation product and vector/genomic DNA ratio greatly influence clone recovery. Furthermore, we describe the use of an airbrush device to screen E. coli metagenomic libraries for their antibacterial activity against Staphylococcus aureus, a method we called bacteriospray. This bacterial spraying tool greatly facilitates and improves the functional screening of large genomic libraries, as it conveniently allows the production of a thinner and more uniform layer of target bacteria compared to the commonly used overlay method, resulting in the screening of 5–10 times more clones per agar plate. Using the Burkholderia thailandensis E264 genomic DNA as a proof of concept, four clones out of 70,000 inhibited the growth of S. aureus and were found to each contain a DNA insert. Analysis of these chromosomic fragments revealed genomic regions never previously reported to be responsible for the production of antimicrobials, nor predicted by bioinformatics tools.
The design and operation of oil-gas production separator desanding systems : Oil and natural gas production

Details are given of extensive tests done to study the design and operation of desanding systems for oil-gas production separators. Sand and water are used in vessels of diameter between 0.9 m and 2.7 m. The use of non-dimensional groups, representing solids volume, wash time and wash jet momentum, permits generic scaling of the data. The fluidization factor, F, is defined which is found, for a given solid, to have a critical optimum value, higher values implying unnecessarily excessive washing and lower values less than optimum solids removal. The increase in critical F found between sand and Proppant appeared to be mainly due to increased particle size. Specific recommendations are made regarding wash jet design and deployment, the spacing and design of drain points and the use of discrete baffled wash zones. For large tanks multiple tiers of wash pipes are recommended. The optimum time to stop washing is identified and an overall design procedure is outlined. Although the procedure has been proven for washing relatively fine uncontaminated sand from production separators in the Forties field, further design information may be needed for washing alternative types of solids.
Structures of Neural Network Effective Theories

We develop a diagrammatic approach to effective field theories (EFTs) corresponding to deep neural networks at initialization, which dramatically simplifies computations of finite-width corrections to neuron statistics. The structures of EFT calculations make it transparent that a single condition governs criticality of all connected correlators of neuron preactivations. Understanding of such EFTs may facilitate progress in both deep learning and field theory simulations.