Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Short Text Through Lexical Semantic Analysis

Information of quick texts is crucial for many packages however there are many demanding situations. First, the fast texts do not constantly look at a written language’s syntax. As a end result, traditional natural language processing gear cannot be without problems applied, ranging from element-of-talk tagging to dependency parsing. second, brief texts usually do now not incorporate sufficient statistical signals to help a few of the state of play Thirdly, short texts are greater ambiguous land noisier, land are generated in a big quantity, which further will increase the problem of coping with them. We argue that semantic knowledge is important for better understanding of brief texts. on this paintings, we build a prototype gadget for short text expertise that takes advantage of semantic expertise furnished by using a famous know-how base and harvests it automatically Our methods for responsibilities which includes text segmentation, component-of-speech tagging, and idea labeling, inside the feel that during these kind of duties we awareness on semantic. We perform a complete evaluation of the overall performance on actual-existence facts. The outcomes display that semantic information is critical for the understanding of quick texts and our information-intensive technique.
Working Hard to Take the Easy Way Out: How the Need for Cognitive Closure Shapes Strategic Effort Investment to Ease Future Decision Making

Consumers make countless decisions each day that force them to determine the amount of effort they are willing to invest into the decision process. Due to their desire for immediate resolution and propensity to seize upon available options, individuals high in the need for cognitive closure make decisions that are traditionally associated with reduced effort investment. Counter to this traditional perspective, this research demonstrates that those seeking closure strategically invest effort into the decision process, so long as the initial effort investment is expected to simplify similar decisions in the future. Three experiments demonstrate that those motivated by closure put forth greater effort when they expect to repeat the decision (Experiment 1) and in contexts where a justifiable choice option is not readily available (Experiment 2). Furthermore, this effort investment is shown to payoff in terms of streamlining subsequent decision making (Experiment 3). These findings detail the strategic use of effort by those seeking closure to ease future decision making and thus provide a conceptual framework for when and why those seeking closure allocate effort in decision making.
Predicting tuberculosis drug resistance using machine learning based on DNA sequencing data

Tuberculosis is a serious infectious disease caused by Mycobacterium tuberculosis (MTB) that primarily affects the lungs. It is known that several strains of MTB are resistant to drugs used in the treatment. This situation calls for the importance to detect and prevent further drug resistance and thus reducing the mortality rate. The conventional molecular diagnostic test is costly, requires a long time to conduct, and has low prediction ability. This research aims to explore the Machine Learning approach to accurately predict drug resistance which offers a much faster and cheaper solution than the conventional one. Experiments were carried out on 3393 isolates of MTB using several Machine Learning algorithms including C4.5, Random Forest, and Logitboost. Multiple drugs evaluated in this study include rifampicin (RIF), isoniazid (INH), pyrazinamide (PZA), and ethambutol (EMB). By using 10-fold cross-validation, the result had demonstrated that the model can accurately predict drug resistance with an accuracy of 99% and with Area Under Curve (AUC) reaching (near) 1. This result suggests that Machine Learning approach has a promising result in predicting Tuberculosis drug resistance.
The addition of ethylhydrazine to α,β- and β,γ-unsaturated ketones: a quantum-chemical modeling

The reactivity of α,β- and β,γ-unsaturated ketones with respect to the nucleophilic attack by ethylhydrazine in one of the key stages of the formation of 4,5-dihydropyrazole has been studied. It is shown that the addition of the terminal nitrogen atom of ethylhydrazine to the carbonyl group of β,γ- and α,γ-unsaturated ketones with the formation of β,γ- and α,β-unsaturated hydrazones is energetically preferable with the participation of two water molecules. At the same time, the addition of the internal nitrogen of ethylhydrazine to the double C=C bond of the α,β-unsaturated ketone (which is preferable in the presence of one water molecule) to give β-ethylhydrazinyl ketone occurs with a lower activation barrier and is thermodynamically more favorable than the addition to the C=O bond.
Rainfed cultivation with supplemental irrigation modelling on seed yield and oil of Coriandrum sativum L. using precision agriculture and GIS moisture mapping

The aim of the present study was to determine the effects of rainfed and supplemental irrigation, and sowing period (SP) treatments on coriander (Coriandrum sativum L.) yield, essential oil content and umbel heights by applying new agro-technologies (TDR-sensors for soil moisture (SM), geographical information system (GIS), precision agriculture, soil-hydraulic analyses and geostatistical models) for yield and SM root zone geospatial modelling and two-dimensional GIS mapping. Results of laboratory analysis indicated a suitable soil for coriander's growth and revealed that field's soil was characterized sandy clay loam (SCL) with mean values: soil organic matter (SOM) = 1.70%, bulk specific gravity = 1.42 g·cm−3, plant available water = 0.129 cm·cm−1, pH = 7.10 and cation-exchange capacity (CEC) = 19.3 cmol·kg−1. The two-way ANOVA statistical analysis (P = 0.05) results revealed that the irrigation treatments (IR1: rainfed, IR2: rainfed plus supplemental irrigation [best]), and the SP treatments (SP1: October's last week, SP2: November's first week [best]) significantly affects coriander's seed yield and essential oil content, but the SP have no significant effect on plant's umbel height (P = 0.873). Supplemental irrigation, using a limited amount of water, if applied during the critical crop growth stages, can result in substantial improvement on seed yield (+284.934%), essential oil content (+125.396%) and plant's umbel height (+117.929%).
Analysis Of Steel-Rcc Composite Deck Bridge

Article History: Received:11 January 2021; Accepted: 27 February 2021; Published online: 5 April 2021 Abstract. : In the literature, provisions for analysis and design of steel-RCC composite deck type truss and cablestayed bridges do not exist. A composite deck type truss bridge model is analyzed using STAAD Pro V8i software and a model with the same dimensions is tested in the laboratory. The experimental test results are used to validate the STAAD analysis results. Bottom chord strain and mid-span deflection of the composite bridge model as found from the STAAD analysis and the laboratory experiment closely tally with each other. This validates the standard STAAD analysis results. However, in the top chord member, due to shrinkage cracks in the deck slab concrete, the experimentally recorded strain is higher by about 100% than the STAAD analysis result. Shear force in studs is considerably large near supports and joints as compared to the midsection. Therefore, the design of shear studs may be carried out based on the shear forces in the studs found from the STAAD analysis. Thus it is recommended that STAAD or any other standard finite element analysis software can be used for analysis and design of the composite bridges.
Performance of SMOTE in a random forest and naive Bayes classifier for imbalanced Hepatitis-B vaccination status

The alternative approach to predict the classification of HB vaccination status is using a machine learning approach such as random forest and naive Bayes classifier. However, for imbalanced classification, the algorithms are biased towards the majority class. To increase the accurate prediction of the classifier, we consider the Synthetic Minority Oversampling Technique (SMOTE) to have more balanced data. The purpose of this study was to compare the performance of SMOTE in the random forest and naive Bayes classifier for imbalanced Hepatitis-B vaccination data. The study used the National Socio-Economic Survey data in 2017 for Aceh province with 2264 cases and 14 variables. The results show that the application of SMOTE in the random forest and naive Bayes classifier improves the accuracy of identification of Hepatitis-B non-vaccination status by 30.08% and 26.09%, respectively, compared to non-SMOTE. Random forest with SMOTE is the best model for classification HB vaccination status. The most important factors that influence the Hepatitis-B vaccination status of Aceh province are the mother’s last education, mother’s occupation, father’s occupation, father’s previous education, and the number of health facilities.
Compression of Person Re-identification Model Based on Depthwise Separable Convolutional Network

In practical application, the network depth and the number of parameters of person re-identification(re-ID) model bring great challenges to its deployment on devices with weak computing capabilities such as cloud desktop, mobile terminal and embedded terminal. To solve the above problem, this paper proposed a model compression method based on a depthwise separable convolutional network. Knowledge distillation is used to the core idea of model compression. Knowledge distillation is to transfer knowledge from a complex model to a simple model. The complex model is called the teacher model. The simple model is called the student model. This paper proposed ResNet18 based on depthwise separable convolution (ResNet18-DSC). ResNet50 is used as a teacher network and ResNet18-DSC is used as a student network. To narrow the performance gap between student and teacher networks. KL divergence loss function is used to approximate the soft label distribution of student network to that of teacher network. With a slight decrease in recognition rate, this method reduces the number of parameters by about 20 times and improves the calculation speed by about 20 times.
Factors Facilitating the Implementation of the Sustainable Development Goals in Regional and Local Planning—Experiences from Norway

Successful implementation of the Sustainable Development Goals (SDGs) depends on regional and local authorities’ ability to implement the goals in their respective contexts. Through a survey and interviews with informants in Norwegian municipalities and county councils, this paper explores and offers new empirical insight into (1) which factors can be identified as facilitating the implementation of the SDGs in Norwegian local and regional planning; (2) how the facilitating factors are conditioned by the different local and regional institutional contexts; and (3) how these factors from the Norwegian context correspond or differ from those in the international literature. We find that the existing Planning and Building Act is considered a suitable framework for the implementation of the SDGs in the Norwegian context, and that the SDGs are high on the national and regional governmental agendas. However, work remains in integrating the SDGs into underlying governmental activities. They must be incorporated into action plans and planning tools, which will require involvement, collaboration and development work across sectors and authority levels, and the development of guidelines for how this can be done. Allocating enough resources for this work will be crucial, and smaller municipalities may need other types and degrees of support than larger ones.
The redox chemistry of neptunium in γ-irradiated aqueous nitric acid

Abstract The redox chemistry of neptunium in irradiated 4 M nitric acid was investigated using γ-ray irradiation and UV/Vis spectroscopic measurements. Irradiation caused changes in the abundances of Np(V) and Np(VI) regardless of the initial fractional components of these oxidation states. At low absorbed doses Np(V) was oxidized to Np(VI) in irradiated solution, due to its reaction with oxidizing, radiolytically-produced, free radicals. However, when sufficient radiolytically-produced nitrous acid accumulated, the reduction of Np(VI) to Np(V) occurred, even at this high nitric acid concentration. Neptunium(IV) was not produced. A kinetic model which incorporates the standard water radiolysis reactions, estimated radical yields for 4 M HNO3, and rate constants for neptunium reactions available from the literature was used to successfully reproduce the experimental results.
Influence of extract derived cell cultures of broccoli against osteoporosis in ovariectomized rats

This study was conducted to enhance broccoli secondary metabolites; using plant biotechnology techniques and tissue culture as well as to evaluate the therapeutic effect of broccoli extract against osteoporosis in ovariectomized (OVX) rats. Cell culture technique was implemented in order to achieve and produce polyphenols from leaf explants of broccoli. The highperformance liquid chromatography (HPLC) technique was used to evaluate the polyphenolic profiles of ethanolic extracts for cell cultures compared to the dried inflorescences of broccoli (cultivated plant). However, total phenol and flavonoid contents were determined by spectrophotometric technique. Induction of osteoporosis was performed via ovarectomy operation where rats were divided into 5 groups (10 rats each). Group 1: Sham operated control group and the remaining rats were ovariectomized for 12 weeks to produce osteoporosis model. Group 2: Ovariectomized osteoporotic positive control group. Groups 3-5: Ovariectomized rat daily received 17-β-estradiol (10 μg/kg), broccoli cell suspension culture ethanol extracts (300 & 600 mg/kg) orally. The obtained results showed that Murashige and Skoog basal nutrient medium (MS) fortified with 2.25 μM of 2,4Dichlorophenoxyacetic acid (2,4-D) and 0.55 μM of kinetin (kin.) showed the best medium for calli production. Addition of methionine enhanced polyphenolic production in cell suspension culture which was identified by HPLC. Administration of broccoli cell suspension extract elevated the uterine weight, high density lipoprotein-cholesterol and estradiol 2 (E2) serum levels and reduced serum levels of lipid profile, liver and kidney functions, osteocalcin and total procollagen type 1 N-terminal propeptide (TPINP). In conclusion, broccoli may be a promising source of secondary metabolites; polyphenol contents and flavonoids for treatment of bone loss and cell damage in osteoporosis.
Examining the accuracy of residents’ self-assessments and faculty assessment behaviours in anesthesiology

Background Residents’ accurate self-assessment and clinical judgment are essential for optimizing their clinical skills development. Evidence from the medical literature suggests that residents generally do poorly at self-assessing their performance, often due to factors relating to learners’ personal backgrounds, cultures, the specific contexts of the learning environment and rater bias or inaccuracies. We evaluated the accuracy of anesthesiology residents’ self-assessed Global Entrustment scores and determined whether differences between faculty and resident scores varied by resident seniority, faculty leniency, and/or year of assessment. Methods We employed variance components modeling techniques and analyzed 329 pairs of faculty and self-assessed entrustment scores among 43 faculty assessors and 15 residents. Using faculty scores as the gold standard, we compared faculty scores with residents’ scores (xi(faculty)–xi(resident)), and determined residents’ accuracy, including over- and under-confidence. Results The results indicate that residents were respectively over- and under-confident in 10.9% and 54.4% of the assessments but more consistent in their individual self-assessments (rho = 0.70) than faculty assessors. Faculty scores were significantly higher (α = 0.396; z = 4.39; p < 0.001) than residents’ self-assessed scores. Being a lenient/dovish (β = 0.121, z = 3.16, p < 0.01) and a neutral (β = 0.137, z = 3.57, p < 0.001) faculty assessor predicted a higher likelihood of resident under-confidence. Senior residents were significantly less likely to be under-confident compared to junior residents (β = -0.182, z =-2.45, p < 0.05). The accuracy of self-assessments did not significantly vary during the two years of the study period. Conclusions The majority of residents’ self-assessments were inaccurate. Our findings may help identify the sources of such inaccuracies.
Phenolic compounds and biological activities of phenolic extract of olive oil mill wastewater issue from the cold extraction of olive oil from Khenchela (Algeria)

This study aimed to the determination of antioxidant, anti-inflammatory, and anticoagulant activities of phenolic compounds present in olive oil mill wastewater (OMW) issue from the cold extraction of olive oil from Khenchela eastern of Algeria.After polyphenols extraction, a quantity and quality analysis by LC-MS was made. The LC-MS (liquid chromatography–mass spectrometry)results were revealed the presence of 20 phenolic compounds in theextract of OMW which were: (quinic acid, gallic acid, protocatechuic acid, caffeic acid, p-coumaric acid, rutin, transfrolic acid, hyperoside (quercetin-3-o-galactoside), luteolin-7-o-glucoside, naringin, 4.5-di-caffeoyquinic acid, quercetrin(quercetin-3-o-rhamonosid), apegenin-7-o-glucoside, salviolinic acid, kampherol, quercetin, naringenin, apegenin,cirsiliol, and cirsilineol). The results of antioxidant activity with DPPH(2,2-diphenyl-1-picrylhydrazyl), ABTS+ (2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid), and FRAP (ferric reducing ability of plasma)showed that the IC50(half-maximal inhibitory concentration) were(9.62 ± 0.28µg/mL, 7.10 ± 0.11µg/mL and 3.59 ± 0.24µg/mL)respectively. The extract of OMW was found to exhibit the highestinhibitory effectanti-inflammatory activity usinginhibition of protein denaturation(IPD) and membrane stabilizing potential (MSP) tests (80.46 ± 3.81; 87.43 ± 0.66 µg/mL) more than the standard used. In addition, the extract had the best anticoagulation activity in the endogenous and exogenous pathways (44.77 ± 0.25s; 15.84 ± 0.12s). Based on these results, it is right to conclude that OMW is an important source of natural phenolic compounds that have important antioxidant, anti-inflammatory, and anticoagulant activities.
The numerical implementation of land models: Problem formulation and laugh tests

The intent of this paper is to encourage improved numerical implementation of land models. Our contributions in this paper are two-fold. First, we present a unified framework to formulate and implement land model equations. We separate the representation of physical processes from their numerical solution, enabling the use of established robust numerical methods to solve the model equations. Second, we introduce a set of synthetic test cases (the laugh tests) to evaluate the numerical implementation of land models. The test cases include storage and transmission of water in soils, lateral sub-surface flow, coupled hydrological and thermodynamic processes in snow, and cryosuction processes in soil. We consider synthetic test cases as “laugh tests” for land models because they provide the most rudimentary test of model capabilities. The laugh tests presented in this paper are all solved with the Structure for Unifying Multiple Modeling Alternatives model (SUMMA) implemented using the SUite of Nonlinear and DIfferential/Algebraic equation Solvers (SUNDIALS). The numerical simulations from SUMMA/SUNDIALS are compared against (1) solutions to the synthetic test cases from other models documented in the peer-reviewed literature; (2) analytical solutions; and (3) observations made in laboratory experiments. In all cases, the numerical simulations are similar to the benchmarks, building confidence in the numerical model implementation. We posit that some land models may have difficulty in solving these benchmark problems. Dedicating more effort to solving synthetic test cases is critical in order to build confidence in the numerical implementation of land models.
Achieving Environmental Policy Objectives through the Implementation of Sustainable Development Goals. The Case for European Union Countries

One of the key challenges for climate policies is the identification of strategies that will effectively support the implementation of environmental goals. Environmental policies are connected with other development policies carried out by governments. In order to comprehensively shape environmental policy, it is important to understand the interactions between sustainable development goals (SDGs) as well as their impact on environmental goals. Employing econometric modeling based on the least absolute shrinkage and selection operator (Lasso) method and full-factorial analysis, the authors identify a number of statistically significant relationships between the implementation of sustainable development goals and the environmental variable represented by greenhouse gas emissions. Analysis reveals that implementation of particular sustainable development goals, namely SDG4 (Ensure inclusive and equitable quality education and promote lifelong learning opportunities) and SDG17 (Strengthen the means of implementation and revitalize the global partnership for sustainable development), explicitly facilitate the achievement of environmental policies. In addition, other SDGs exert an indirect influence on environmental goals through their reinforcing interactions with SDG4 and SDG17 variables. These are: SDG1 (End poverty), SDG3 (Ensure healthy lives and promote well-being), SDG8 (Promote sustained, inclusive and sustainable economic growth, and productive employment) and SDG15 (Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests and halt biodiversity loss). These findings have important implications for proper identification of effective government policy instruments which indirectly support the achievement of environmental goals.
An investigation of histopathologic and morphometric effect of black carrot juice on acrylamid induced neurotoxicity

Acrylamide is an organic compound that is known to have neurotoxic influences. People have high exposure to its impacts because of its extensive uses in the industrial fields and its occurrence in foods. This situation has induced the scientific word to identify naturel components that may eliminate these neurotoxic effects. In this experimental study the influence of black carrot juice containing bioavailable flavonoids was researched on acrylamide neurotoxicity. In the study, laboratory rats were divided in to four groups. Group 1 rats were the control group. While the rats in Group 2 were administered acrylamide substance, the rats in Group 3 were supplemented with black carrot juice + acrylamide, and the rats in Group 4 were given black carrots juice only. At the experiment’s end, biochemical, histopathological, and histomorphometry analysis were performed on exanguned rats. Significant histopathological degenerations were observed in the acrylamide treated group. Despite a volumetric degrease in all brain regions examined histomorphometrically, this decrease was not statistically significant. The malondialdehyde and Glutathione S-transferase levels of the acrylamide group showed a significant increase compared to the control group. The glutathione, carboxylesterase and acetylcholinesterase levels were observed to increase in the acrylamide and black carrot applied group, compared to the acrylamide group. This study’s findings have revealed the black carrot’s healing effects on acrylamide neurotoxicity.