Miracle-dz/UniFAR-FTUs huggingface dataset:
An Assessment of Training and Its Effectiveness on Employees’ Job Performance”: A Critical Review on The Banking Sector of Ethiopia

With the current expansion of the global economy and the fast-changing of technology and innovation, Effectiveness Training is necessary for any organization especially in connection with new technology. The objective of the study is to investigate the effect of training on employees’ job performance in Hawassa City, in order to examine the study data was collected through a self-administered structured questionnaire from a population of 195 employees from various branches of the Banking sector in Hawassa city. The data collected was analyzed using frequency, mean, standard deviation, correlation, and regression analysis. Regression results indicate that effectiveness training it positively and significantly contributes towards employees’ job performance. Based on the finding of the study the researcher forwarded some recommendations the management of the CBE.
The Interconnection and Damping Assignment Passivity-Based Control Synthesis via the Optimal Control Method for Electric Vehicle Subsystems

The interconnection between optimal control theory and the theory of energy-shaping control is described in our paper. For linear and nonlinear systems, the application of the theory of optimal control for the synthesis of parameters of energy-shaping control matrices is demonstrated in detail. The use of a Riccati equation allows us to form an optimality criterion and to synthesize the energy-shaping control system that provides the desired transient processes. The proposed approach was applied to the synthesis of control influences for electric vehicle subsystems, such as a two-mass system and a permanent magnets synchronous motor. The results of computer simulation studies, as well as those conducted on real experimental installations, are given in this paper.
Assessment of Drought Effects on Forests using Non- Parametric Methods and Satellite Imagery

Temperate forests are a vital part of the natural environment and important for human existence. Yet, they are increasingly threatened by changing disturbance regimes, especially more severe droughts. Here, we combine Landsat and Sentinel-2 time series and use a kernel density estimation (KDE) to assess the baseline phenology of a mixed forest area in Germany. We compared this baseline to the forest’s development during the drought year of 2018 and the following growing season of 2019. Our results show that parts of the examined forest were negatively impacted to an unprecedented degree. With the use of satellite remote sensing analyses and the KDE, we can assess the impact of drought on vegetation development without relying on parametric methods.
Prediction of Life Expectancy at Birth, Total (years) By Analyzing Capture fisheries production (metric tons) And Industry (including construction), value added (current US$) In Italy 1990 ??? 2016

We consider the role played by an industry’s factor intensities and assess whether industries that have high physical and human capital intensities generate more pollution per unit of output. Fish from wild capture fisheries and aquaculture make a crucial contribution to both global food production and overall nutrition (SDG2, zero hunger; SDG3, good health and well-being), providing 3 billion people with almost 20% of their mean per capita intake of animal protein4 and providing essential micronutrients in otherwise deficient diets. The human health effects of omega-3 oils are the subject of much scientific and policy interest. The specific roles of a-linolenic acid (ALA, 18:3n-3), eicosapentaenoic acid (EPA, 20:5n-3) and docosahexaenoic acid (DHA, 22:6n-3) in preventing cardiovascular disease. This study uses multiple linear regression analysis to predict and predict changes in the value of certain variables when other variables change. Correlation is one of the statistical analysis techniques used to find the relationship of how strong the relationship between two or more variables that are quantitative. By using the Linearity Test (Lillie force test) where fcount> ftable is, 68.978411> 3.354 Then, Ho is rejected. This means that multiple linear regression analysis can be used to predict Life expectancy at birth, total (years in Italy by analyzing Variable Capture fisheries production (metric tons) and Industry (including construction), value added (current US$) data. Obtained the multiple linear regression equation is Y = 84.98627772 - 2.1921E-05X1 + 4.51839E-12X2, the correlation value of the variables above is 0.922937 the value is superior correlation scale ranging from 0.76 to 0.99. Is where t1 count< t table is -10.1945< 2.052, then Ho is accepted, meaning there is no significant effect partially between the Variable Life expectancy at birth and Capture fisheries production (metric tons). Then the value of the t2 count > t table is 2,638824 >2.052, Ho is rejected, it means that there is a large significant influence partially between the Life expectancy at birth and against the Industry (including construction), value added (current US$) variable in the Italy 1990 - 2016.
Clinical Note Generation to Address Physician Burnout

Physician burnout is one of the main contributors to the decreasing quality and personalized touch of clinical visits. Burnout in large part can be attributed to tedious and inefficient documentation processes of current EHR systems, as each visit can cost several hours of documentation afterwards. In this paper, we aim to build a language model to help generate clinical note contents, which could be deployed as part of an auto-complete system to increase efficiency of the documentation process. We believe that we are one of the first to deploy GPT-2 architecture for this objective. Results show that a small GPT-2 model finetuned on the MIMIC-III clinical note corpus can replicate note structure quite dependably and often fills in contents of reasonable length and semantic appropriateness. The same model struggles to handle medical abbreviations, special characters, and nuanced formatting, illustrating the importance of data quality pre-processing. Appending additional diagnosis history did not improve model performance. Our findings provide evidence of feasibility for using such models in text-prediction software under real-life clinical settings.
Character Embedding and Self Attention Mechanism with SQuAD

The Stanford SQuAD challenge is a reading comprehension contest, which requires us to train a model which can understand the provided contexts and predict the answer correctly. The Stanford SQUAD dataset provides a thorough testing for our model. In this paper, we have explored various ways to achieve better performance to answer the questions from the SQuAD dataset, including BiDAF with character embedding, similarity score based attention layer and self attention mechanism. Our best model achieved the F1 scores = 64.186 and EM = 60.524 on the test set
The age of tomato plants affects the development of Macrosiphum euphorbiae (Thomas, 1878) (Hemiptera) colonies

We tested the hypothesis that the intensity and duration of Macrosiphum euphorbiae infestations in tomato depend on both the age (phenological stage) of the host plant and the initial number of aphids present in the colony. We compared the effects of three initial levels of infestation and two phenological stages of the plant (pre-flowering and flowering stages) on infestation curves. The position of the infestation peak over time was significantly affected by the plant phenological phase. Populations of M. euphorbiae reached the highest peak of abundance on plants infested at the pre-flowering stage compared to those subsequently infested. Within a phenological phase, the maximum abundance also varied according to the initial aphid density on the plant. The implications concerning the management of the pest in the field are briefly discussed
Fuzzy enhancement and deep hash layer based neural network to detect Covid-19

This paper proposes a deep learning framework for Covid-19 detection by using chest X-ray images. The proposed method first enhances the image by using fuzzy logic which improvises the pixel intensity and suppresses background noise. This improvement enhances the X-ray image quality which is generally not performed in conventional methods. The pre-processing image enhancement is achieved by modeling the fuzzy membership function in terms of intensity and noise threshold. After this enhancement we use a block based method which divides the image into smooth and detailed regions which forms a feature set for feature extraction. After feature extraction we insert a hashing layer after fully connected layer in the neural network. This hash layer is advantageous in terms of improving the overall accuracy by computing the feature distances effectively. We have used a regularization parameter which minimizes the feature distance between similar samples and maximizes the feature distance between dissimilar samples. Finally, classification is done for detection of Covid-19 infection. The simulation results present a comparison of proposed model with existing methods in terms of some well-known performance indices. Various performance metrics have been analysed such as Overall Accuracy, F-measure, specificity, sensitivity and kappa statistics with values 93.53%, 93.23%, 92.74%, 92.02% and 88.70% respectively for 20:80 training to testing sample ratios; 93.84%, 93.53%, 93.04%, 92.33%, and 91.01% respectively for 50:50 training to testing sample ratios; 95.68%, 95.37%, 94.87%, 94.14%, and 90.74% respectively for 80:20 training to testing sample ratios have been obtained using proposed method and it is observed that the results using proposed method are promising as compared to the conventional methods.
Inpatients with severe-enduring anorexia nervosa: Understanding the “enduringness” specifier

Abstract Background Despite the need for a common definition of severe and enduring anorexia nervosa (SE-AN) with the overarching goal to optimize treatments, this definition still is being debated. Therefore, in this study we conducted an in-depth investigation of the history of AN and its clinical outcomes on inpatients with AN to ascertain the eventual “profiles” for individuals with varying durations of the illness (DOI). Methods We recruited 169 inpatients with AN, grouping them according to DOI: <3 years (short duration, SD-AN); 3–6.99 years (medium duration, MD-AN); and ≥7 years (long duration, LD-AN). We then performed a self-report and interview-based investigation of AN history, clinical data, eating, and general psychopathology, including personality, premorbid traits, stage of change, and quality of life. We measured the clinical outcomes for hospitalization as well. Results The majority of the measures did not differ across groups. Those with LD-AN were older and diagnosed mostly with the binge-purging AN subtype, failed more previous AN-related treatments, reported a lower lifetime body mass index, and trended toward a younger age at onset when compared to the other groups. All patients responded equally well to hospitalization, but patients with SD-AN improved less in drive for thinness and body-related concerns. Conclusions We did not find the “enduringness” of AN to be a specifier of severity. Hospitalization was effective for those with LD-AN and MD-AN, while interventions for the core cognitive aspects of over-evaluation of body shape should be offered to patients with SD-AN.
EECS 598 Project Final Report Due

ive QA is a relatively new yet promising and rapidly developing area of research. In this project, we implemented an abstractive QA system for answering user queries for privacy policy documents for mobile applications. The biggest obstacle in developing the generation module was the lack of annotated data, both for training of the parameters and the testing and validation of our models. A promising line of further work is to investigate how transfer learning from other Question Answering datasets can be leveraged to combat this problem. Moreover, we believe that systemic grid search of scoring parameters (importance weights) and in-domain training of component models will lead to better performance of the final generator model.
Cultural Tezozómoc , Azcapotzalco , Ciudad de México Phytophagous mites and insects in the Recreational and Cultural Tezozómoc park trees , Azcapotzalco , Mexico City

Urban and suburban trees are essential elements in the character of populated areas as they have the capacity to transform cities, providing environmental, aesthetic, cultural and economic benefits. In Mexico City, Tezozomoc Park is very important for the neighbors in the northern area because it has an artificial central lake surrounded by abundant vegetation. However, its trees have been damaged by different, which led to in this study, in which phytophagous insects and mites were detected and determined. For the diagnosis, 10 % of the total frequency of the dominant tree and shrub species was sampled, while the total of the individuals was considered for the low frequency host species. The damages caused by the organisms were: chlorosis, gills or cecidia, defoliation, damage to phloem and bark. Samples were obtained by direct collection in vials with 70 % alcohol. Most of the specimens collected were insects and sap sucking mites; the secondary damage associated with them was the formation of fumagins. The tree species most susceptible to pests was Salix bonplandiana, with 10 species of phytophagous that represented 19 % of the total found on the trees in the park. Derived from this study, the Eulophidae wasp and gill-forming aphelinidae in S. bonplandiana, the Specularius impressithorax bruch and the seed borer in Erythrina coralloides are recorded for the first time.
Impact of Covid-19 Pandemic On Local Rice Supply Chain FlowPatterns In Kapuas Regency, Central Kalimantan, Indonesia

The fact that the pandemic condition due to Covid-19 that broke out in early 2020 has caught the attention of various elements of society. The visible impact is not only on public health, but also influences the distribution and availability of various food supplies, especially local rice in the study area. The purpose of this study was to examine the flow patterns of the local rice supply chain during the Covid-19 pandemic. Data analysis using supply chain analysis of Supply Chain management (SCM). The results of the analysis show that at the farmer / producer level it does not significantly affect farming activities, only 29.77 percent of farmers stated that there was an influence on farming activities. The impact of Covid-19 mainly affects the level of intermediary institutions in the rice distribution process. Long product (material) flow patterns by business actors need to be shortened by a short distribution route. Another effect is the inaccuracy of product arrival time due to delays in the inspection process for products brought to the research location. The impact of Covid-19 is mainly felt by distributors / wholesalers who flow products to other areas, mainly due to the increase in additional costs related to Covid-19 requirements. The solution to integrate all SCM elements through an information system can facilitate the flow pattern of local rice in Kapuas District, by intensifying the management of information related to production at the producer level, as well as controlling rice supplies at the level of intermediary institutions. © 2021, World Scientific and Engineering Academy and Society. All rights reserved.
Convolutional neural network with near infrared for plastic waste

: Plastic waste is a relevant challenge for waste management sector and further 31 technological means has to be urgently researched. Near infrared spectroscopy (NIR), as 32 a non-destructive, cost-effective and mature technology, is currently operational in some 33 waste-sorting facilities. However, NIR remains challenging to discriminate different 34 black plastics because black targets have low reflectance in the its spectral region. 35 Therefore, this study aimed to address the problem in black plastic classification. Seven 36 kinds of plastics: High Impact Polystyrene (
Phenotypic and molecular characterization of fluoroquinolone resistant Pseudomonas aeruginosa isolates in Palestine Caracterização fenotípica e molecular de isolados de Pseudomonas aeruginosa resistentes a fluoroquinolonas na

This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Fluoroquinolones are important antimicrobial agents for the treatment of Pseudomonas infections. A total of 11 isolates of P. aeruginosa were collected from different clinical samples from different medical centers in the North West Bank-Palestine during 2017. In this study, resistance to fluoroquinolones and secretions of β-lactamases were detected by phenotypic methods, while presence of β-lactamase gene sequences and other virulence factors were detected by PCR technique. PCR product for gyrA, parC and parE genes were sequenced for further analyses. The phylogenetic analyses, population diversity indices and haplotypes determination were conducted using computer programs MEGA version 6, DnaSP 5.1001 and median-joining algorithm in the program Network 5, respectively. Results of this study showed that the MIC for ciprofloxacin and norfloxacin had a range of 32-256 μg/ml. In addition, all isolates carried either exoT or exoT and exoY genes, different β-lactamase genes and 82% of these isolates harbored class 1 integrons. Analyses of the gyrA, parC and parE sequences were found to be polymorphic, had high haplotype diversity (0.945-0.982), low nucleotide diversity (0.01225-0.02001) and number of haplotypes were 9 for each gyrA and parE genes and 10 haplotypes for parC gene. The founder haplotypes being Hap-1 (18%), Hap-2 (27.3%) and Hap-6 (9.1%) for gyrA, parC and parE genes, respectively. Two of ParE haplotypes were detected as indel haplotypes. The Median-joining(MJ) networks constructed from haplotypes of these genes showed a star-like expansion. The neutrality tests (Tajima’s D test and Fu’s Fs test) for these genes showed negative values. Palestinian fluoroquinolone resistant P. aeruginosa strains showed high MIC level for fluoroquinolones, β-lactamase producers, carried type III secretion exotoxin-encoding genes, most of them had integrase I gene and had high level of mutations in QRDR regions in gyrA, parC and parE genes. All these factors may play an important role in the invasiveness of these strains and make them difficult to treat. Isolation of these strains from different medical centers, indicate the need for a strict application of infection control measures in Medical centers in the North West Bank-Palestine that aim to reduce expense and damage caused by P. aeruginosa infections. Molecular analyses showed that Palestinian fluoroquinolone resistant P. aeruginosa haplotypes are not genetically differentiated; however, more mutations may exist in these strains.
Bioinspired Hierarchical Tin Oxide Scaffolds for Enhanced Gas Sensing Properties

Nature is greatly capable of providing inspiration for the novel design of functional materials. Herein, the efficient bioreactors’ construction of pollen grains inspires us to mimic them for superior gas sensing application. By developing a facile two-step soakage process and subsequent calcinations, the bioreactors are mimicked fully: (I) biosensitive pollen coats on pollen grains are replaced by gas sensitive tin oxide (SnO2) coats, and (II) the fine hierarchical scaffolds are maintained by the self-support of newly formed SnO2 coats. For gas sensing application, as-fabricated SnO2 microreactors exhibit high and fast responses to nitrogen dioxide (219.5 to NO2 of 50 ppm) and other gases. The good sensing properties should be indeed ascribed to the specific construction of microreactors, which shows elaborate hierarchical porous structures and large accessible space/surface area favorable for both gas molecule transports and sensing reactions. This present strategy provides us with new insight on the ex.
Copolymerization of Cyclic Esters Controlled by Chiral NNO-Scorpionate Zinc Initiators

Reaction of the chiral alcohol-scorpionate compound bpzteH [bpzteH = 2,2-bis(3,5-dimethylpyrazol-1-yl)-1-para-tolylethanol] with [ZnR2] (R = Me, CH2SiMe3) in a 1:2 molar ratio afforded the dinuclear chiral alkyl zinc complexes [Zn(R)(κ2-NNμ-O)Zn(R)2] (1 and 2) [κ2-NNμ-O = bpzte, R = Me 1, CH2SiMe3 2]. Subsequent alcoholysis reaction with ArOH (1 equiv; Ar = 2,6-C6H3Me2) yielded the chiral dinuclear zinc complexes [(ZnR)2(κN:κN-μ-O)(μ-OAr)] (3 and 4) [κN:κN-μ-O = bpzte, R = Me 3, CH2SiMe3 4]. The X-ray crystal structures of 1 and 3 confirmed a dinuclear structure in all complexes, with the alkoxide of the heteroscorpionate ligands in a μ-bridging mode between the two Zn(II) centers. The zinc complexes 1–4, bearing trisalkyl and alkyl-aryloxide ligands, are shown to function as highly efficient single-component initiators for the ring-opening homopolymerization of e-caprolactone and l-/rac-lactide. These initiators enable rapid polymerization at ambient temperatures, affording materials with low molecular w.
Trade Policy as an Exogenous Shock: Focusing on the Specifics

This paper proposes a novel strategy for identifying the effects of import competition on economic outcomes that avoids standard concerns related to the endogeneity of trade policy and provides a consistent measure of exposure to trade over time. Conditioning on the level of import tariffs, our approach exploits cross-industry differences in the relative importance of specific rather than ad valorem tariffs. As they are expressed in per unit terms rather than as a share of value, the effective protection provided by a given specific tariff varies with price levels. Using digitized tariff line data between 1900 and 1940, we relate inflation-driven changes in trade protection to changes in imports and labor market outcomes in the full count U.S. census. We show that our measure predicts import growth at both the industry and county level. Using our measure as an instrument, we show that import competition reduces labor force participation in traded sectors during this period. Labor market effects are widespread but fall most heavily on those with little experience or fewer outside labor market options: the young, seniors, and those in rural areas.
COVID-19 Epidemics in Brazil: Political Influences on Its Incidence and the Economic Impacts of Its Mortality

We performed an economic valuation of the excess mortality resulting from non-compliance with social isolation measures in Brazil, mainly establishing the impact of political alignment to the conduct of the epidemic by the federal government. The political alignment was concluded to be associated with a decrease of 2% in compliance. The excess mortality was accessed using an SEIR model, concluding that 25,538 (10,528 – 40,554) of the 58,314 deaths that occurred in the country from February 26th to June 29th could be associated to political alignment, with an economic impact of USD 35 (11·8 – 68·1) billion. Results show that the impacts of variations in isolation and the economic consequences are very high, even in the face of minimal changes in compliance. In a political scenario that was characterized by political polarization and conflicts, they corroborate with the need for efficient and integrated public health measures to control de pandemics in the country. <br>