jimnoneill/paper-to-field-training huggingface dataset:
Effect of Ciklavit® - (A Poly-Herbal Formulation) on the Pharmacokinetics of Proguanil in Healthy Nigerian Volunteers

Field: Pharmacology, Toxicology and Pharmaceutics (Life Sciences)

The therapeutic efficacy of herbal medicines in the treatment of human diseases or disorders has gained more attention over the years. A survey established that approximately 15 % of patients receiving orthodox medicine also take herbal products, and among these, potential adverse herbto-drug interactions were observed in 40 % of patients. Recently, there have been reports of herbdrug interactions which have impacted on wellness of users resulting in toxicity or loss of therapeutic efficacy of either the herb or the orthodox drug when co-administered. These reports make herb-drug interactions a research area of public interest. This study was embarked upon to evaluate the effect of Ciklavit® used for the management of sickle cell anaemia on the pharmacokinetic profile of proguanil tablets in healthy Nigerian volunteers. Twelve healthy participants were recruited and completed the study after signing a consent form. The study was performed using a single dose, two-way randomized crossover design. The participants were randomly grouped into control and treatment. The treatment group were administered proguanil tablets with Ciklavit® while the control group took proguanil with water only. The blood and urine samples collected at different time interval for 24 hours were analyzed using HighPerformance Liquid Chromatography. The results obtained, demonstrated that co-administration of Ciklavit® with proguanil altered pharmacokinetic parameters of proguanil but the difference in values were found to be statistically insignificant (p>0.05). The study demonstrated that there are no significant pharmacokinetic interactions between proguanil and Ciklavit® hence the two medicinal agents can be co-administered.
Protein classi .cation into domains of life using markov chain models

Field: Biochemistry, Genetics and Molecular Biology (Life Sciences)

It has recently been shown that oligopeptide composition allows clustering proteomes of different organisms into the main domains of life. In this paper, we go a step further by showing that, given a single protein, it is possible to predict whether it has a bacterial or eukaryotic origin with 85% accuracy, and we obtain this result after ensuring that no important homologies exist between the sequences in the test set and the sequences in the training set. To do this, we model the sequence as a Markov chain. A bacterial and an eukaryote model are produced using the training sets. Each input sequence is then classified by calculating the log-odds ratio of the sequence probability for each model. By analyzing the models obtained we extract a set of most discriminant oligopeptides, many of which are part of known functional motifs.
EQUILIBRIUM COUNTERFACTUALS

Field: Economics, Econometrics and Finance (Social Sciences)

Abstract We incorporate structural modelers into the economy they model. Using traditional moment matching, they treat policy changes as zero probability (or exogenous) “counterfactuals.” Bias occurs since real‐world agents understand policy changes are positive probability events guided by modelers. Downward, upward, or sign bias occurs. Bias is illustrated by calibrating the Leland model to the 2017 tax cut. The traditional identifying assumption, constant moment partial derivative sign, is incorrect with policy optimization. The correct assumption is constant moment total derivative sign accounting for estimation‐policy feedback. Model agent expectations can be updated iteratively until policy advice converges to agent expectations, with bias vanishing.
Emotional Analysis of Online Evaluation of Tourism Based on Improved Bayesian Algorithm

Field: Computer Science (Physical Sciences)

Aiming at tourists' emotional analysis can better activity tourists' real feedback, most of the tourists' comment data are generated by tourists' initiative after the tour, and its authenticity is higher. Analyzing the differences in tourists' perceptions and influencing factors in tourism can help scenic spots develop differentiated service strategies and improve tourist satisfaction. Taking four 5A-level scenic spots as research objects, machine learning algorithms and content analysis are utilized to classify the emotional of tourism reviews. Firstly, Python crawler is used to obtain the data of tourism reviews, and the acquired data are cleaned and processed; secondly, a plain Bayesian classifier is improved and constructed according to the feature attributes of the samples, and then the data of the test set are classified based on the Dalian University of Technology emotional Dictionary. Conclusion It is proved that the algorithm can effectively improve the accuracy of text emotional classification, reveal the perception differences of tourists from the level of perceived content and emotional features, and effectively avoid the effect that the attribute whose conditional probability is equal to 0 has its a posteriori probability of the whole class equal to 0.
A Primer on Equal Employment Opportunity Law and Contemporary Enforcement

Field: Social Sciences (Social Sciences)

The purpose of this chapter is to provide a brief overview of the legal issues that are most relevant to industrial/organizational psychologists in the United States. The chapter first reviews the legal process, describing laws and acts relevant to the workplace, such as Title VII of the Civil Rights Act, Executive Order (EO) 11246, Age Discrimination in Employment Act, American with Disabilities Act, and the Equal Pay Act of 1963. Next, it outlines the equal employment opportunity (EEO) enforcement agencies. It then describes the two broad theories of discrimination, disparate treatment and adverse impact, and the regulatory frameworks. The chapter provides basic primers for a set of contemporary EEO topics, including disability discrimination, pay equity, employer retaliation, and age discrimination. The chapter concludes with the notion that EEO law is constantly evolving, particularly as the scope of who is protected expands and the legal system clarifies ambiguities in the law.
POST-OPERATIVE PERCENTAGE REDUCTION OF GLOMERULAR FILTRATION RATE AS A MARKER FOR ACUTE KIDNEY INJURY AND WARNING OF LONG-TERM FUNCTIONAL OUTCOME OF ITS RESECTION

Field: Medicine (Health Sciences)

The existing criteria of acute kidney injury assessment fail to identify kidney parenchyma damage of small severity and predict long-term outcomes of its resection. The aim of the research was to assess percentage reduction of glomerular filtration rate as a marker for acute kidney injury and functional outcome one year after surgery
A Feasibility Study of Small Hydroelectric Power Plant at Madhabkunda Waterfall, Moulvibazar, Bangladesh

Field: Energy (Physical Sciences)

Electricity generation from hydropower is generally regarded as a cost-effective energy option. In this article, the potential for the construction of a small hydropower station at the Madhabkunda waterfall, situated in the Barlekha Upazila of the Moulvibazar district of Bangladesh, is examined. The primary objective of this study was to determine the potential electricity generation capacity that could be attained by the establishment of a small hydroelectric power station at the Madhabkunda waterfall. The flow rate, resulting in the output power, is determined by employing a pitot tube. Furthermore, a reservoir design is proposed as a means of mitigating flow fluctuations. It is indicated by our research that the Madhabkunda waterfall possesses a sufficient head and an available flow rate conducive to the support of a small hydroelectric power facility. The results demonstrate that small hydropower at Madhabkunda has the capacity to provide a monthly average power output ranging from 1.74 MW to 2.56 MW during the rainy season months.
Understanding the relationships between information technology and lean and agile supply chain strategies: a systematic literature review

Field: Business, Management and Accounting (Social Sciences)

Abstract This study analyzes the relationships studied in the literature between Information Technologies (IT) and two supply chain strategies that have similar mechanisms of action: Lean Supply Chain (LSC) and Agile Supply Chain (ASC). The purpose is to identify and understand the role that IT plays in the two strategies depending on the way that it is conceptualized, and whether this is transferred to performance. The Systematic Literature Review is the methodology used to locate articles, select and analyze their content. In general terms, research to date shows a positive association between IT and these two supply chain strategies and that this association improves business results. However, the study shows that research into LSC and ASC has used different conceptualizations of IT and, in some cases, these conceptualizations can have different effects on the study’s outcomes. This paper proposes directions for future research and theoretical development are suggested.
Curbing populism: remove barriers and make actual benefits visible

Field: Social Sciences (Social Sciences)

Trump’s election victory and Brexit reflected a growing scepticism towards globalisation. The populist waves have swept across the globe because not everyone has benefited from the overall economic gains as a result of trade liberalisation. Over the years, the wealth gap has widened alongside the expansion of the global economic pie says Chloe Lok Yi Lam. For instance, the United Kingdom’s gini coefficient has shown more than 35% growth from the mid-70s to the late 2000s. This shows that parts of the population might not have been rewarded proportionally for their hard work. In fact, the less privileged groups who feel left behind have been rising in number, which is well evidenced by a surging number of “nationalism supporters”.
Peer Review #2 of "Synthetic neuronal datasets for benchmarking directed functional connectivity metrics (v0.2)"

Field: Neuroscience (Life Sciences)

Background: Datasets consisting of synthetic neural data generated with quantifiable and controlled parameters are a valuable asset in the process of testing and validating directed functional connectivity metrics.Considering the recent debate in the neuroimaging community concerning the use of these metrics for fMRI data, synthetic datasets that emulate the BOLD signal dynamics have played a central role by supporting claims that argue in favor or against certain choices.Generative models often used in studies that simulate neuronal activity, with the aim of gaining insight into specific brain regions and functions, have different requirements from the generative models for benchmarking datasets.Even though the latter must be realistic, there is a tradeoff between realism and computational demand that needs to be contemplated and simulations that efficiently mimic the real behavior of single neurons or neuronal populations are preferred, instead of more cumbersome and marginally precise ones.Methods: this work explores how simple generative models are able to produce neuronal datasets, for benchmarking purposes, that reflect the simulated effective connectivity and, how these can be used to obtain synthetic recordings of EEG and fMRI BOLD signals.The generative models covered here are AR processes, neural mass models consisting of linear and nonlinear stochastic differential equations and populations with thousands of spiking units.Forward models for EEG consist in the simple three-shell head model while the fMRI BOLD signal is modeled with the Balloon-Windkessel model or by convolution with a hemodynamic response function.Results: the simulated datasets are tested for causality with the original spectral formulation for Granger causality.Modeled effective connectivity can be detected in the generated data for varying connection strengths and interaction delays.Discussion: all generative models produce synthetic neuronal data with detectable causal effects although the relation between modeled and detected causality varies and less biophysically realistic models offer more control in causal relations such as modeled strength and frequency location.
Collapse Behavior and Energy Absorption Characteristics of Design Multi-Cell Thin Wall Structure 3D-Printed Under Quasi Statistic Loads

Field: Engineering (Physical Sciences)

Crashworthiness is a passive device that has an important function as an absorbing component of the impact energy resulting from an accidental event. The main problem in the crashworthy design is the dimensional limitation on the front end of the vehicle with the driver so that most of the energy absorption is limited. Besides, the complexity of crashworthiness design is difficult to make conventionally. This research aims to find out the effectiveness of crashworthiness design in energy absorption and the resulting deformation patterns. Crashwortines are made in a multi-cell shape using PLA material and printed using a 3D printing raise machine. Crashworthiness is produced with four variation shapes of a Multi-cell circle (MCC), Multi-Cell square (MCS), Multicell pentagonal (MCP), and Multi-Cell pentagonal circles (MCPC) with a side thickness of 2 mm and a length of 150 mm. Experimental quasi-static testing is carried out in the frontal direction using a UTM machine at an operating speed of 2mm/s. The results of the study show that the design of the crash box of the pentagon circle has a significant increase in the energy absorption value of 62.49%, which can be recommended in future impact resistance tube designs. The characteristics of the deformation pattern and the failure resulting from the crashworthiness tend to form the pattern of the bending lamina failure. Failures can occur due to plastic fold, elastic bend, and pressure deformation mechanisms followed by new folding formations (lobes).
Plastic Surgery and COVID-19 in the GCC: Fears, Lessons Learned, and the Plan for the Future

Field: Medicine (Health Sciences)

Background: With the labeling of Coronavirus Disease 2019 (COVID-19) as a pandemic by the World Health Organization, national directives were issued instructing to close all cosmetic clinics, suspend all cosmetic procedures, and only operate on an emergency basis. As a result, many plastic surgeons faced challenges sustaining their practice. We aimed to investigate the effect of these national directive instructions on the surgeons and to review their strategies for adapting their practices during this new pandemic. Methods: A cross-sectional descriptive study was conducted using an online questionnaire. It was constructed to assess the attitudes and practices of plastic surgeons in the Gulf Cooperation Council countries during the COVID-19 lockdown. It also explored their strategies on reopening their practice, as well as their plans on modifications of practice during and after the lockdown. Results: In total, 197 surgeons responded to the survey. The majority were from Saudi Arabia (42.1%), followed by the United Arab Emirates (37.6%), with relatively smaller participation from the remaining countries. Over two-thirds (69.5%) indicated that the pandemic had affected their practice. Surgeons in private practices were significantly affected ( P < 0.001) compared with those in the public sector. Only 39% of respondents mentioned COVID-19 testing as part of their post-pandemic surgical protocol. Conclusions: Surgeons’ responses to the pandemic varied. Fear and future uncertainty significantly led to a surge in the utilization of different technical means to maintain the patient pool. Surgeons’ education about post-pandemic precautions is essential to maintain high standards of care in the region.
SAR Target Configuration Recognition via Discriminative Statistical Dictionary Learning

Field: Computer Science (Physical Sciences)

The establishment of the dictionary is of crucial importance to sparse representation (SR) based algorithms. It has been proved that learned dictionaries are more compact and have better performance than predefined ones. A dictionary learning (DL) algorithm is proposed for synthetic aperture radar (SAR) target configuration recognition in a statistical way with discriminative power embedded in under the SR framework, which is named as discriminative statistical DL (DSDL) in this paper. A better description of the SAR image is obtained from the statistical standpoint and, thus, improving the robustness of the proposed algorithm. To make the learned dictionary more discriminative, the dictionary is finally determined while minimizing differences within the same target configuration and, meanwhile, maximizing differences among different configurations. The proposed DSDL algorithm can provide dictionaries for SR-based recognition algorithms. Experimental results on the moving and stationary target acquisition and recognition database validate the effectiveness and robustness of the proposed DSDL-SR recognition algorithm. A comparison with other recognition techniques further demonstrates its superiority.
WhysoSeriousGame: A conceptual framework for learning motivation through serious game

Field: Computer Science (Physical Sciences)

The aim of this paper is to construct a framework for serious games' motivation in learning. Additionally, it attempts to emphasizes the importance of motivational factors as an integral component of serious games for university students. Existing research on serious games for university students' learning is insufficient, and students are reported to be discouraged from exploring serious games in their learning. Thus, the objective of this paper is to develop the WhysoSeriousGame framework in order to provide a comprehensive, serious game-based framework that emphasizes motivation as a critical aspect of learning. Additionally, this paper provides a description on how the framework can be implemented in teaching and learning for university students. The framework also serves as a source of reference for future Serious Game development.
An Examination of the Oxidation of Aldehydes by Horse Liver Alcohol Dehydrogenase

Field: Biochemistry, Genetics and Molecular Biology (Life Sciences)

Horse liver alcohol dehydrogenase (EC 1.1.1.1) has been shown to oxidize aldehydes with the net reduction of NAD+. The enzyme shows a low maximal velocity with acetaldehyde but increasing maximal velocities with butanal, hexanal, and octanal. At high NAD+ concentrations horse liver alcohol dehydrogenase exhibits a maximal velocity with octanal which is approximately one-tenth that of ethanol. Starch gel electrophoresis of the enzyme coupled with activity staining shows that every component that is capable of oxidizing ethanol is also capable of oxidizing octanal. The stoichiometry of the reaction of horse liver alcohol dehydrogenase with octanal shows that 1 mole of NAD+ is reduced per mole of octanoic acid formed.
Analysis of host range phenotypes of primate hepadnaviruses by in vitro infections of hepatitis D virus pseudotypes. J Virol 78:5233–43

Field: Biochemistry, Genetics and Molecular Biology (Life Sciences)

Hepatitis B virus (HBV) and woolly monkey hepatitis B virus (WMHBV) have natural host ranges that are limited to closely related species. The barrier for infection of primates seems to be at the adsorption and/or entry steps of the viral replication cycle, since a human hepatoma cell line is permissive for HBV and WMHBV replication following transfection of cloned DNA. We hypothesized that the HBV and WMHBV envelope proteins contain the principal viral determinants of host range. As previously shown by using the hepatitis D virus (HDV) system, recombinant HBV-HDV particles were infectious in chimpanzee as well as human hepatocytes. We extended the HDV system to include HDV particles pseudotyped with the WMHBV envelope. In agreement with the natural host ranges of HBV and WMHBV, in vitro infections demonstrated that HBV-HDV and WM-HDV particles preferentially infected human and spider monkey cells, respectively. Previous studies have implicated the pre-S1 region of the large (L) envelope protein in receptor binding and host range; therefore, recombinant HDV particles were pseudotyped with the hepadnaviral envelopes contain-ing chimeric L proteins with the first 40 amino acids from the pre-S1 domain exchanged between HBV and WMHBV. Surprisingly, addition of the human amino terminus to the WMHBV L protein increased infectivity on spider monkey hepatocytes but did not increase infectivity for human hepatocytes. Based upon these data, we discuss the possibility that the L protein may be comprised of two domains that affect infectivity and that
How Bilateral Trade Deals Get in the Way of Multilateral Agreements

Field: Economics, Econometrics and Finance (Social Sciences)

Aghion et al. (2007) developed a dynamic bargaining model that considers bilateral versus multilateral trade agreements. Employing a ‘Nash in Nash’ applied general equilibrium framework, we provide empirical evidence for their approach. Considering the Trans-Pacific Partnership (TPP), our model determines the welfare maximizing set of bilateral trade agreements by sectors (there are ten) and compares that to an agreement involving all countries/sectors. We find that a multilateral agreement generates more collective welfare than most bilateral agreements and that this welfare gain is unlikely to be achieved by countries’ individual pursuit of bilateral agreements. We find that superadditivity (i.e., additional welfare associated with the expansion of free trade to additional sectors and countries) holds across all regions and all sectors, but not for every pair of regions and sectors. Thus, it is possible for a set of regions to increase their collective welfare by excluding some sectors from their trade agreement.
Root canal working length determination using Cone-Beam Computed Tomography

Field: Dentistry (Health Sciences)

Introduction Cone-Beam Computed Tomography (CBCT) represents unique supporting diagnostic tool in all areas of dentistry as well as endodontics. One of the uses in endodontics is determining working length of the root canals-odontometry. The aim of this paper was to test the efficacy of CBCT application in determining working length of root canals. Methods Forty-three extracted human teeth were placed in three wax models shaped as a horseshoe. Preoperatively, CBCT model scanning (voxel size: 0.2 mm) was performed. Access cavities were prepared and working length determined by introducing expanders #08 into the root canal until the apical foramen. The length was measured using a micrometer odontometer. The CBCT working length was simply measured by following the line between the apical foramen and the selected reference point. Two experienced operators performed all measurements, independently. The t-test was used to compare the obtained values. Results CBCT measurements showed small deviation from manual measurements. The mean value of the absolute difference between CBCT measurements and manual measurements was 0.39 mm (0.25-0.74 mm). The results of the t test (t = 0.311; p = 0.757) showed that there was no statistically significant difference between the odontometry performed by the endodontic instrument and odontometry performed using CBCT. Conclusion the CBCT measurement is reliable method for determining working length of root canals. In 94.29% of examined teeth, discrepancies less than 1 mm were found, which was not of clinical significance.