Miracle-dz/UniFAR-FTUs huggingface dataset:
The integrated use of physicochemical and in vitro data for predicting chemical toxicity

The general aim of this PhD project was to investigate the integrated use of physicochemical and in vitro data for predicting the toxicological hazard of chemicals in animals. This was achieved in two stages: firstly, by developing two types of model for acute dermal and ocular toxicity - structure-activity relationships (SARs) based on easily calculated physicochemical properties, and prediction models (PMs) based on experimentally derived physicochemical or in vitro data; and secondly, by evaluating the tiered testing approach to hazard classification, in which different classification models (CMs) are applied sequentially before animal testing is conducted. The thesis therefore reports the development and assessment of CMs for skin irritation, skin corrosion and eye irritation, as well as the outcome of simulations in which these models were incorporated into tiered testing strategies for these toxicological endpoints. The results show that the tiered testing approach to hazard classification provides a reliable means of reducing and refining the use of animals, without compromising the ability to classify chemicals. In addition to developing the above-mentioned CMs, regression models for corneal permeability were developed, and the relationship between corneal permeability and eye irritation was investigated. The thesis also describes the development and assessment of a novel statistical method called embedded cluster modelling (ECM), which generates elliptic models of biological activity from embedded data sets. The combined use of this method with the existing method of cluster significance analysis (CSA) is illustrated through the development of SARs for eye irritation potential. Finally, novel applications of the bootstrap resampling method were investigated. In particular, algorithms based on this method are shown to provide a means of assessing: a) the minimal variability associated with the Draize rabbit tests for skin and eye irritation; and b) the variability in Cooper statistics (commonly used to summarise the performance of two-group CMs) that arises from chemical variation.
Stabilizing a blasius boundary layer with dielectric barrier discharge plasma actuation: experimental characterization

This paper presents an experimental characterization of Dielectric Barrier Discharge (DBD) plasma actuation on a two-dimensional (2D) boundary layer around a §at plate using both Laser Doppler Anemometry (LDA) and hot wire probings. The experiments are conducted in a subsonic wind tunnel at a free-stream velocity U ∞ = 35 m/s for a single DBD actuator and several electrical parameters. Hot wire probings are used to quantify the transition delay and mean velocity pro¦les far enough from the plasma region, while mean velocity pro¦le inside the plasma extent are measured using LDA after the method has been validated from a comparison with hot wire measurements. Measurements inside the plasma extent allow to quantify the ionic wind contribution to the actuated mean velocity pro¦les in a case where the transition is delayed by the actuator. A maximal ionic wind of 7 m/s is found to be added 2 mm downstream the actuator for a consumed electrical power of 80 W/m.
Using Natural Language Processing to Classify Serious Illness Communication with Oncology Patients

One core measure of healthcare quality set forth by the Institute of Medicine is whether care decisions match patient goals. High-quality "serious illness communication" about patient goals and prognosis is required to support patient-centered decision-making, however current methods are not sensitive enough to measure the quality of this communication or determine whether care delivered matches patient priorities. Natural language processing offers an efficient method for identification and evaluation of documented serious illness communication, which could serve as the basis for future quality metrics in oncology and other forms of serious illness. In this study, we trained NLP algorithms to identify and characterize serious illness communication with oncology patients.
Quinoxaline-based conjugated polymers for polymer solar cells

Bulk heterojunction (BHJ) polymer solar cells (PSCs), as a promising alternative to conventional silicon-based solar cells, have achieved rapid development in recent years. In the BHJ concept, the active layer of the PSC normally consists of a blended film of a conjugated polymer donor and an electron acceptor. To be a conjugated polymer with OPV function, the polymer should have sufficient solubility, a broad absorption spectrum, a high absorption coefficient, and well-matched energy levels with the electron acceptor. With this aim, numerous conjugated polymers have been developed to date. Among them, quinoxaline-based polymers have been shown to have a promising future, reaching a very outstanding power conversion efficiency (PCE) of more than 11%, which shows that they have significant potential in reaching the efficiency limit of commercial applications of polymer solar cells. In this review, we summarize the quinoxaline-based conjugated polymers for efficient polymer solar cells by classifying them in terms of different donors, alkyl and/or aromatic chains, and functional groups, and we also give an overview of their photovoltaic device performances to provide a better understanding of and guidelines for the structure–performance relationship in such quinoxaline-based polymers. We believe that further developments of quinoxaline-based conjugated polymers achieved through the synergy of molecular engineering strategies will increase the photovoltaic performance to levels closer to those required for commercial applications in the near future.
Nutritional value of tifton 85 bermudagrass at two cutting heights and different times of storage

The goal of this study was to assess the dehydration curve and nutritional value of Tifton 85 bermudagrass at two cutting heights from ground level (4 and 8 cm) during 120 days of storage in a closed shed. The dehydration curve was determined using samples from the entire plant at eight different times. The experimental design consisted of randomized blocks with plots subdivided per times and five replicates. The second step consisted of assessing the nutritional value of the stored Tifton 85 bermudagrass in randomized blocks with plots subdivided per times and two treatments per plot: cutting height of four and eight centimeters from the ground, and five different times for the subplots, with five replicates. Dehydration of Tifton 85 bermudagrass at the two heights occurred in 48 hours, considered an ideal time for hay drying. The dry matter content responded quadratically to the time of storage of the two heights, only differing during baling and after 120 days of storage. Crude protein content had a quadratic behavior in the two cutting heights, with the smallest value after 30 days of storage (107.0 g kg-1) and the largest after 90 days (147.8 g kg-1) in the cutting height of eight centimeters. The ether extract exhibited a quadratic behavior in the two cutting heights, only differing after 90 days of storage. The neutral detergent fiber content had linear positive response according to the time of storage, with no difference between the cutting heights. For the neutral detergent fiber content in the two cutting heights, the quadratic regression model was the best fit to the data, differing between the heights after 30 and 60 days of storage. In vitro dry matter digestibility and in vitro cell wall digestibility values of the stored hay were lower than the values obtained at the time of cutting. Cutting performed at four centimeters from the ground was the most suitable for hay production due to higher dry matter production and nutritional value without difference between bailing treatments. Hay storage caused undesirable changes in the nutritional value, especially in fiber content and in vitro digestibility.
A computational characterization of CO@C60

ABSTRACT The carbon monoxide encapsulation into C60 is evaluated using the DFT and MP2 calculations. The CO encapsulation is attractive, yielding an energy gain of more than 12 kcal/mol. This substantial encapsulation energy should produce at the conditions used in the high-temperature and high-pressure synthesis (originally used for encapsulation of rare gases in fullerenes) an equilibrium CO@C60 fraction of about 3.5% compared to the empty C60. The computed IR and NMR spectra agree with the available observations for CO encapsulated into open-cage C60 derivatives.
GPU-Accelerated Constraint-Based Causal Structure Learning for Discrete Data

Learning the causal structures from high-dimensional observational data is an omnipresent challenge in data science. State-of-the-art methods for constraint-based Causal Structure Learning (CSL) apply conditional independence (CI) tests to determine the underlying causal structures. In the context of discrete data, each CI test requires calculating the marginals over contingency tables based on the respective observations. This calculation leads to long overall execution times. In our work, we propose a parallel execution strategy tailored for constraint-based CSL on a Graphics Processing Unit (GPU) to accelerate the execution for discrete data. Hence, we introduce the gpuPC algorithm that performs all CI tests on a GPU and extends the existing parallel execution strategy for constraint-based CSL by calculating the marginals over contingency tables within units of threads. Further, gpuPC implements explicit memory management to handle the corresponding auxiliary data structures in GPU memory. An experimental evaluation shows that gpuPC scales well even for higher-dimensional settings, with auxiliary data structures exceeding on-chip memory. In particular, running on NVIDIA Tesla V100 hardware gpuPC outperforms a GPU baseline by factors of up to 45 . 6 and further outperforms existing parallel CPU-based implementations running on 40 cores by a factor of 62 . 1.
AStudy toDecipher thePotential Effects ofButylphthalide against CentralNervousSystemDiseasesBasedonNetworkPharmacology and Molecular Docking Integration Strategy

Background. Butylphthalide (NBP), approved by the China National Medical Products Administration (NMPA) for the treatment of ischemic stroke (IS), showed pleiotropic potentials against central nervous system (CNS) diseases, including neuroprotection and cognitive deficits improvement. However, the effects and corresponding modes of action were not fully explored. /is study was designed to investigate the potential of NBP against IS-associated CNS diseases based on network pharmacology (NP) and molecular docking (MD). Methods. IS was inputted as the index disease to retrieve the “associated diseases” in DisGeNET. /reedatabase-based IS genes were obtained and integrated (DisGeNET, Malacards, and OMIM). /en, IS-associated genes were identified by combining these genes. Meanwhile, PubMed references and online databases were applied to identify NBP target genes. /e IS-related disease-disease association (DDA) network and NBP-disease regulation network were constructed and analyzed in Cytoscape. In silicoMD and references were used to validate the binding affinity of NBP with critical targets and the potential of NBP against certain IS-related CNS disease regulation. Results. 175 NBP target genes were obtained, while 312 ISrelated disease genes were identified. 36 NBP target genes were predicted to be associated with IS-related CNS diseases, including Alzheimer’s disease (AD), epilepsy, major depressive disorder (MDD), amyotrophic lateral sclerosis (ALS), and dementia. Six target genes (i.e., GRIN1, PTGIS, PTGES, ADRA1A, CDK5, and SULT1E1) indicating disease specificity index (DSI) >0.5 showed certain to good degree binding affinity with NBP, ranging from −9.2 to −6.7 kcal/mol. And the binding modes may be mainly related to hydrogen bonds and hydrophobic “bonds. ” Further literature validations inferred that these critical NBP targets had a tight association with AD, epilepsy, ALS, and depression. Conclusions. Our study proposed a drug-target-disease integrated method to predict the drug repurposing potentials to associated diseases by application of NP and MD, which could be an attractive alternative to facilitate the development of CNS disease therapies. NBP may be promising and showed potentials to be repurposed for treatments for AD, epilepsy, ALS, and depression, and further investigations are warranted to be carefully designed and conducted.
Review Article Protocols Used by Occupational Therapists on Shoulder Pain after Stroke: Systematic Review and Meta-Analysis

Introduction. Shoulder pain as a consequence after a stroke has multifactorial causes and can prevent the functional return of the upper limb. In addition, the effectiveness of clinical protocols applied by occupational therapists remains uncertain. Objective. To identify the main treatments currently used by occupational therapists for pain in the shoulder after a stroke. Method. Articles in English published between 2015 and 2019, of the randomized clinical trial type, with populations that stroke survivors a stroke and sequelae of shoulder pain were selected. The terms and combinations used were “shoulder pain and stroke and occupational therapy,” in the electronic databases, Directory of Open Access Journals (DOAJ), Occupational Therapy Systematic Evaluation of Evidence (OTseeker), and PubMed. Statistical Review Manager (version 5.3) established the significance level P ≤ 0:05. Results. Thirty-nine articles were found, but only four met the inclusion criteria. Electrical stimulation, therapeutic bandaging, and dry needling were eventually employed. For the meta-analysis, pain was the primary outcome, and range of motion (ROM) and upper limb function were secondary. Pain, ROM (external rotation, abduction, and flexion), and manual function were compared, and the meta-analysis showed improvement in the treatment group in clinical trials: pain (MD -2.08; 95% CI -3.23, -0.93; P = 0:0004), ROM (MD 4.67; 95% CI 1.54, 7.79; P = 0:0003), and manual function (MD 1.84; 95% CI 0.52, 3.16; P = 0:006). Conclusion. Dry needling, California tripull taping (CTPT), and functional electrical stimulation controlled by brain-machine interface (BCI-FES) are proved effective in shoulder pain and functionality.
Cost-effectiveness of hydroxychloroquine versus placebo for hand osteoarthritis: economic evaluation of the HERO trial

Background: An economic evaluation alongside the Hydroxychloroquine Effectiveness in Reducing symptoms of hand Osteoarthritis (HERO) trial was undertaken to assess the cost-effectiveness of hydroxychloroquine compared with placebo for symptomatic treatment of hand osteoarthritis for patients with at least moderate hand pain and inadequate response to current therapies. Methods: A trial-based cost–utility analysis was undertaken from the perspective of the UK National Health Service and Personal Social Services over a 12-month time horizon, using evidence from 248 participants included in the HERO trial, conducted in England. Patient-level data were collected prospectively over a 12-month period, using participant-completed questionnaires and investigator forms, to collect healthcare utilisation, costs and quality-adjusted life years (QALYs) using the EQ-5D-5L. The base-case analysis was conducted on an intention-to-treat basis and used multiple imputation methods to deal with missing data. Results were presented in terms of incremental cost-effectiveness ratios (incremental cost per QALY) and net health benefit, with uncertainty surrounding the findings explored using cost-effectiveness acceptability curves. Results: The base-case analysis estimated slightly lower costs on average (−£11.80; 95% confidence interval (CI) −£15.60 to −£8.00) and marginally fewer QALYs (−0.0052; 95% CI −0.0057 to −0.0047) for participants in the hydroxychloroquine group versus placebo group at 12 months. The resulting incremental cost-effectiveness ratio of £2,267 per QALY lost indicated that although costs were saved, health-related quality of life was lost. Even assuming symmetrical preferences regarding losses and gains for health benefits, the findings do not fall within the cost-effective region. Similar findings arose for analyses conducted from the societal perspective and using complete cases only. Conclusions: This economic evaluation indicates that hydroxychloroquine is unlikely to provide a cost-effective pain relief option for improving health-related quality of life in adult patients with moderate-to-severe hand osteoarthritis.
RealGraph-Web: A Graph Analysis Platform on the Web

In this demo, we present RealGraph Web , a web-based platform that provides various kinds of graph analysis services. RealGraph Web is based on RealGraph, a graph engine that addresses the problem of performance degradation in processing real-world big graphs, achieving great performance improvement up to 44 times over existing state-of-the-art graph engines. RealGraph Web runs on a single machine with a web-based interface, thereby allowing users to easily and conveniently enjoy graph analysis services and perform various graph algorithms anywhere on the web . In this demo, we present how a user can analyze a graph on RealGraph Web in three steps and get the analysis result quickly via a graphical user interface.
Deep Learning techniques for cell stage classiﬁcation

The various phases and mechanisms that happen sequentially during a life of a cell form the cell cycle and the correct progression along this cycle is essential for the maintenance of life. For a typical eukaryotes cell this cycle can be separated into 2 main phases: interphase, during which the cell is growing, and mitosis, where the cell separates into two daughter cells. The interphase can be further divided into 3 main phases, G1, where the cell is growing, the S phase, where the DNA is replicated and the G2 phase during which the cell continues growing in preparation for mitosis. Due to the importance of the cellular cycle, the correct staging of a cell (i.e. correct classiﬁcation of its current phase) is of the utmost importance for biological and pharmacological research. However, current methods for cell staging have traditionally relied on ﬂuorescent microscopy and the analysis of cell population and present some drawbacks such as the need for speciﬁc biological markers or the destruction of the cell culture to determine its stage. As such, in this project, a new method that relies on the use of DAPI stained cell cultures (one of the most common cell imaging techniques) and deep learning techniques is proposed. By using deep learning algorithms, this method is capable of staging single data points without relying on cell population analysis and will not require speciﬁc biological markers, resulting in fairly simpler process to achieve cell staging.
Developing Synergistic Drug Combinations To Restore Antibiotic Sensitivity in Drug-Resistant <named-content content-type='genus-species'>Mycobacterium tuberculosis</named-content>

Tuberculosis (TB) is a leading global cause of mortality owing to an infectious agent, accounting for almost one-third of antimicrobial resistance (AMR) deaths annually. We aimed to identify synergistic anti-TB drug combinations with the capacity to restore therapeutic efficacy against drug-resistant mutants of the causative agent, Mycobacterium tuberculosis. We investigated combinations containing the known translational inhibitors, spectinomycin (SPT) and fusidic acid (FA), or the phenothiazine, chlorpromazine (CPZ), which disrupts mycobacterial energy metabolism. Potentiation of whole-cell drug efficacy was observed in SPT-CPZ combinations. This effect was lost against an M. tuberculosis mutant lacking the major facilitator superfamily (MFS) efflux pump, Rv1258c. Notably, the SPT-CPZ combination partially restored SPT efficacy against an SPT-resistant mutant carrying a g1379t point mutation in rrs, encoding the mycobacterial 16S rRNA. Combinations of SPT with FA, which targets the mycobacterial elongation factor G, exhibited potentiating activity against wild-type M. tuberculosis. Moreover, this combination produced a modest potentiating effect against both FA-monoresistant and SPTmonoresistant mutants. Finally, combining SPT with the frontline anti-TB agents, rifampicin (RIF) and isoniazid, resulted in enhanced activity in vitro and ex vivo against both drug-susceptible M. tuberculosis and a RIF-monoresistant rpoB S531L mutant. These results support the utility of novel potentiating drug combinations in restoring antibiotic susceptibility of M. tuberculosis strains carrying genetic resistance to any one of the partner compounds.
Reinforcement Learning in 20Q Game with Generic Knowledge Bases

20Q, invented by Robin Burgener in 1988, is a computerized game of twenty questions that began as a test in artiﬁcial intelligence. The game asks the player to think of something and the system will then try to guess what they are thinking of with twenty yes-or-no questions. Due to the highly ﬂexible and volatile game setting, designing a best questioning strategy for the system is not trivial. In the proposal, we hope to provide possible research directions, particularly under the formulation of the problem as reinforcement learning. We would also investigate on methods and potential challenges of incorporating the use of a knowledge base for the game. The presentation can be found at https://drive.google. com/ file/d/1lZ7tTvTFfspJ1P_TEpJvG5TPu0lFSVW6/view? us=sharing
Market Premium andMacroeconomic Factors as Determinants of Industry Premium: Evidence from Emerging Economies

id�1568267. [36] P. Chou, W. -S. Li, S. Rhee, and J.-S. Wang, “Do macroeconomic factors subsume anomalies in long investment horizons? ,” 2007, http://www.emeraldinsight. com/journals.htm? articleid�1621158&show�html. [37] W. Mengyun, M. Zakaria, Z. Linrong, M. U. Farooq, and S. K. Muhammad, “Terrorism and political instability on equity premium: evidence from Pakistan,” Physica A: Statistical Mechanics and Its Applications, vol. 492, pp. 1753–
The First Record of Leocratides kimuraorum (Annelida, Hesionidae) from Korea, with DNA Barcode Data

A hesionid species, Leocratides kimuraorum Jimi, Tanaka and Kajihara, 2017 is newly reported from the sublittoral zones (100 m depth) of the Korean coasts. This species is characterized by lateral antennae as long as the palps, peristomial membrane without papillose, peristomial dorsolateral tubercles with two round marginal lobes, and pharyngeal with terminal papillae. The intra-specific genetic distance among the cytochrome c oxidase subunit I (COI) sequences of L. kimuraorum specimens from Japan (type locality) and Korea (this study) was in the range of 0.0020. 005. The inter-specific genetic distance between L. kimuraorum and other hesionid species were 0.166-0.307. The present study is the first record of Leocratides species in Korean fauna. This paper also provides a morphological description and photographs of L. kimuraorum, with partial sequences of the mitochondrial COI based on Korean specimens.