Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Cannabidiol-Based Sublingual Tablets on Diabetic Neuropathic Pain

Background: This is a prospective, open-label, drug and dose-controlled study. The primary objective of this study is to evaluate the safety and efficacy of cannabidiol (CBD) sublingual tablets for the treatment of patients with chronic diabetic neuropathic pain. The secondary objects are to evaluate the impact of CBD tablets on sleep quality and anxiety. We describe the effectiveness data at the completion of a 21-day study.
Potential Role of a Three-Gene Signature for Predicting Diagnosis in Patients With Myocardial Infarction

ObjectiveIncreasing evidence underscored that the expression of genes was associated with the development and progression of myocardial infarction (MI). In this study, We evaluated the diagnostic value of the feature genes in MI based on data from the Gene Expression Omnibus (GEO) database.MethodsWe used the data from the GEO database (GSE66360) to identify a set of significant differentially expressed genes (DEGs) between MI and healthy control. Univariable logistic regression, the least absolute shrinkage and selection operator (LASSO), SignalP 3.0 server and multivariable logistic regression were used to find the potential role of genes for predicting diagnosis in patients with MI. Receiver operating characteristic (ROC) curve analyses, area under the curve (AUC) and C-index were used to estimate the diagnostic value of genes in patients with MI. The validation for the association was conduct in another six independent data sets (GSE141512, GSE24519, GSE34198, GSE48060, GSE60993, and GSE109048). Then, a meta-analysis was performed to evaluate the diagnostic value of genes in MI.ResultsA total of 44 DEGs were selected from GSE66360. Functional enrichment and KEGG analysis were performed to reveal the DEGs in some inflammation-related biological processes and pathways. A three-gene signature consisted of CCL20, IL1R2 and ITLN1, which could effectively distinguish patients in MI (AUC and C-index were the same value of 0.975). The three-gene signature was effectively validated in 7 independent cohorts, and diagnostic meta-analysis results of the three-gene signature showed that the pooled sensitivity, specificity and ROC curve AUC for MI were0.82 (95% CI: 0.68-0.90), 0.91 (95% CI: 0.81-0.96) and 0.94(95%CI, 0.91-0.96), respectively. ConclusionIt was magnificently suggest that the three-gene signature might potentially serve as novel candidate biomarkers for distinguishing MI from healthy control. Besides, more well-designed cohort studies need to be implemented to warrant the diagnostic value of three-gene signature in clinical purpose.
STUDIES ON CHOICE OF TRAITS FOR SEED YIELD IMPROVEMENT THROUGH BREEDING IN BREAD WHEAT (TRITICUM AESTIVUM L.) GENOTYPES

A study was conducted to estimate the genetic variability of economic traits in 68 genotypes of wheat in randomized block design with three replications during rabi season 2018-19 at Agriculture Research Farm, Department of Genetics and Plant Breeding, Lovely Professional University, Phagwara (Punjab), India. Analysis of variance revealed that genotypes exhibited significant variation for all the characters studied. The estimate of PCV in all the traits studied were greater than those of the GCV, the close the proximity between PCV and GCV values for most of the characters indicated less influence of environment on the expression of the characters under study. Heritability for broad sense was estimated for all the characters under study and observed range from 22.58 to 96.39%. Harvest index and grain yield per plant exhibits High PCV and GCV whereas, plant height and protein content revealed high heritability coupled with high genetic advance as per cent of mean andthe charactersto be under additive genetic control and also scope of improvement through direct selection.
Employing Quantile Regression for Influences of Human Resource Management on Employee Performance

The current study has employed the regression of quantile to explore the impacts of human resource management practices on employee performance at enterprises in business. The research data was collected in Vietnam as a developing economy. The empirical results offer a quite comprehensive picture of the causal linkages from the practices of human resource management to employee performance in emerging economies. These complex linkages have been explored at different quantiles of the conditional distribution of employee performance. The findings reveal that at different points of the conditional mean of employee performance, the effects of human resource management practices are different. The current work is helpful to researchers and business directors, especially in emerging countries like Vienam, by providing them with a more comprehensive picture of the multifaceted links from the practices of human resource management to employee performance. Accordingly, they are able to make better business decisions on the implementation of suitable human resource management. Finally, their enterprises can achieve better employee performance, which in turn leads to superior firm performance.
New Insight into the Americium/Curium Separation by Solvent Extraction using Diglycolamides

The liquid–liquid extraction process called EXAm was developed by the CEA to allow the recovery of Americium alone from a PUREX raffinate. Americium is extracted from a highly acidic feed solution (HNO3 4–6 M) by a mixture of two extractants: DMDOHEMA and HDEHP. The Am/Cm selectivity is improved using a specific diglycolamide (TEDGA) as a selective aqueous complexing agent which retains preferentially Cm and heavier lanthanides in the aqueous phase. In this study, the impact of the lipophilicity and steric hindrance of several diglycolamides on the Am/Cm selectivity was investigated in order to understand the enhancement brought by TEDGA. For this purpose, liquid–liquid extraction and partitioning experiments were performed under various conditions.
On the Power of Oblivious Poisoning Attacks

Poisoning attacks have emerged as a signiﬁcant security threat to machine learning algorithms. It has been demonstrated that adversaries who make small changes to the training set, such as adding specially crafted data points, can hurt the performance of the output model. Most of these attacks require the full knowledge of training data or the underlying data distribution. In this paper we study the power of oblivious adversaries who do not have any information about the training set. We ﬁrst formalize the deﬁnitions related to various aspects of such attacks. We then demonstrate that such attacks, in general, are provably weaker by showing a separation between full-information and oblivious poisoning attacks in various settings. Speciﬁcally, we show the existence of natu-ral learning problems that are rather robust against oblivious adversaries whose goal is to add a non-relevant features to the model with certain poisoning budget. On the other hand, we prove that for same problem setting, non-oblivious (full information) adversaries with the same budget can craft poisoning examples based on the rest of the training data and successfully hurt the performance. Finally, we design and run experiments and observe that they validate our theoretical ﬁndings.
HAWatcher: Semantics-Aware Anomaly Detection for Appified Smart Homes

As IoT devices are integrated via automation and coupled with the physical environment, anomalies in an appified smart home, whether due to attacks or device malfunctions, may lead to severe consequences. Priorworks that utilize data mining techniques to detect anomalies suffer from high false alarm rates and missing many real anomalies. Our observation is that data mining-based approaches miss a large chunk of information about automation programs (also called smart apps ) and devices. We propose Home Automation Watcher (HAWatcher), a semantics-aware anomaly detection system for appified smart homes. HAWatcher models a smart home’s normal behaviors based on both event logs and semantics. Given a home, HAWatcher generates hypothetical correlations according to semantic information, such as apps, device types, relations and installation locations, and verifies them with event logs. The mined correlations are refined using correlations extracted from the installed smart apps. The refined correlations are used by a Shadow Execution engine to simulate the smart home’s normal behaviors. During run-time, inconsistencies between devices’ real-world states and simulated states are reported as anomalies. We evaluate our prototype on the SmartThings platform in four real-world testbeds and test it against totally 62 different anomaly cases. The results show that HAWatcher achieves high accuracy, significantly outperforming prior approaches.
Morphological Characteristics of Ectomycorrhizas on Merbau

Merbau [Intsia bijuga (Colebr.) O. Kuntze] is one of valuable timber tree in south-east Asia which has been known having ectomycorrhizae (EcM) though being ignored. Identification of the ectomycorrizae is prime important for being basis of further studies. This study investigated the EcM fungi associated with Merbau by using both sporocarp morphology and EcM morphotypes. Morphological characters of sporocarps and basidiocarps of the fungi and EcM morphotypes obtained from seedlings and trees from natural and plantation stands of merbau, as well as from nurseries were compared to the description of those resulted from baiting method. Only one species of ectomycorrhizal fungus was found associated with merbau [Intsia bijuga (Colebr.) Kuntze] which has not been described yet. The fungus formed mycorrhizae with monopodial pinnate branching. The fungus was identified belonging to the genus of Scleroderma. The fungus was more common to occur beneath merbau seedlings than trees. The sporocarps may be yielded under greenhouse condition and could be cultured in MMN agar media, thus it facilitates to the production of inoculums used for further studies.
Bothrops moojeni venom: a new tool to investigate osteoclasts differentiation

Bothrops moojeni, a Brazilian lanced-head viper, presents a rich, but not well explored, venom composition. This venom is a powerful tool for the discovery of new molecular targets in many different biological processes. Osteoclasts (OC) are extremely important for bone maintenance, calcium physiology, and balance of tissue regeneration being involved in such diseases as osteoporosis and rheumatoid arthritis. The goal of our study was to evaluate the effect of Bothrops moojeni's venom and its fractions of human peripheral blood mononuclear cells derived OCs in vitro differentiation.After the induction of OCs differentiation, on day 4 the venom was added at different concentrations (5, 0.5, and 0.05 μg/mL), and the reduction of tartrate-resistant acid phosphatase positive (TRAP+) osteoclasts, which was more prominent at the concentration of 5 μg/mL were observed. Phalloidin staining was used for morphological analyzes of F-actin rings integrity. Venom provoked F-actin ring disruption in treated versus control OCs. We obtain high molecular weight (HW) and low molecular weight (LW) venom fractions. Both fractions induced the reduction of TRAP+ OCs (HW fraction at a concentration of 5 μg/mL and LW fraction at 1 μg/mL, respectively). We performed a secretome analysis of OCs treated with venom and its fractions using mass spectrometry (LC-MS/IT-Tof). The data obtained demonstrate possible pathways and mechanisms involved in OCs reduction after the treatment. Example giving is catabolic mechanisms for HW and proteins correlated with genetic modifications for LW. New experiments are in progress, aiming to discover the molecules that possibly interfering in the osteoclasts differentiation.
The Challenges Faced by the Parents of Autistic Children in Jordan

The present study aimed to explore the challenges faced by the parents of autistic children in Jordan. The researcher adopted a descriptive analytical approach. He selected a purposive sample that consists from 8 mothers and 6 fathers who have autistic children. Those parents were selected from a private centre for autism in Amman, Jordan. They were contacted and interviewed via the phone. Their answers were analysed. It was found that the parents of autistic children in Jordan face financial, social, marital and psychological challenges. For instance, some respondents suggested that providing special education is costly. Some respondents suggested that it’s difficult for them to engage in social events and make visits to their friends and relatives. Some respondents suffer from stress. Some respondents reported that their children were misdiagnosed. The researcher recommends conducting studies about the impact of having an autistic child on siblings in Jordan.
Understanding the Heterogeneity of Tourists’ Choices under Climate Change Risks: A Segmentation Analysis

This paper undertakes a data-driven segmentation analysis on tourists’ choice of island destinations in the context of a changing climate. To this end, 2528 tourists visiting ten European islands in the Mediterranean, Baltic, and Atlantic regions were posed hypothetical situations in which diverse impacts caused by CC (i.e., beach loss, heatwaves, storm intensification, etc.) were affecting the islands being visited. In each scenario, tourists’ responses ranged from stay on the island to change to an alternative destination. Cluster analysis allowed the identification of four segments: (1) LO-loyal oriented—tourists willing to stay on the island despite any climatic event (in this group, tourists would often change the travel date); (2) RA-risk-averse—tourists who would always avoid islands affected by CC; (3) WIL-risk-specific—a segment of tourists with a special aversion to the risks associated with wildlife disappearance and damage to infrastructure, and (4) 3S-sun, sea and sand seekers—tourists who would always avoid visiting islands where CC induced effects are related to beach loss or extreme events. Further analysis is dedicated to comparing segments in regard to their sociodemographic characteristics, the image of the island, and the importance given to the protection of environmental attributes when choosing an island destination. The results alert us about the climate-specific risks and tourist profiles that are relevant to explaining changes in the tourism geography and seasonality of islands. The findings are useful for providing operational marketing recommendations for destination managers, especially for taking competitive advantage of climate services, and for prevention and responsiveness management strategies.
Cognitive ability and academic performance among left-behind children: evidence from rural China

ABSTRACT Little attention has been paid to the role that low levels of cognitive development (or IQ) play among both left-behind children (LBCs) and children living with parents (CLPs) in the context of poor educational attainment in rural China. In this paper, we examine how general cognitive abilities contribute to the academic achievement gains of both LBCs and CLPs in poor areas of rural China. We measure the general cognitive ability of the 4,780 sample students using the Raven’s Standard Progressive Matrices (Raven IQ) and assess academic achievement using a curriculum-based mathematics exam. We find that IQ and left-behind status predict achievement gains for the average student. Among low-IQ students, however, left-behind status does not correlate with a change in achievement, suggesting that the migration of parents does not immediately/automatically translate into a loss of academic achievement for students with delays in their general cognitive ability.
IS MARKET RATIOS REFLECTED IN STOCK PRICES?

The most fascinating thing in the stock market world is forecasting stock prices. Almost all players in the stock market race to find the best method for forecast stock prices. After years of researching and practicing, we can divide all methods into two main methods, fundamental and technical analysis. Fundamental analysis based its forecasting method on macroeconomic factors, industry analysis, and company internal factors, while technical analysis is based on studying financial accounting numbers and stock price trends in the past and present. This study will be focusing on the uses of technical analysis in forecasting stock prices. There are many ways in technical analysis to forecast stock prices. Investors and analysts usually use stock price trends or financial ratios to do that. The latest is the most simple and powerful tool that almost everyone can use, regardless of its limitations. When it comes to using financial ratios, there is a lot of contradicting results that make its users need to make a comparison between ratios and make a decision. This paper tries to use another solution to overcome those problems by using composite indicators. The composite indicator will be compared with another market ratio to find out which method is the best for forecasting stock prices. The result is composite indicator is the best method for forecasting stock prices compared with the price to sales ratio, price to book value ratio, price to earnings per share ratio, and price to operating cash flow ratio.
Data‐Driven Inference of the Mechanics of Slip Along Glacier Beds Using Physics‐Informed Neural Networks: Case Study on Rutford Ice Stream, Antarctica

Reliable projections of sea‐level rise depend on accurate representations of how fast‐flowing glaciers slip along their beds. The mechanics of slip are often parameterized as a constitutive relation (or “sliding law”) whose proper form remains uncertain. Here, we present a novel deep learning‐based framework for learning the time evolution of drag at glacier beds from time‐dependent ice velocity and elevation observations. We use a feedforward neural network, informed by the governing equations of ice flow, to infer spatially and temporally varying basal drag and associated uncertainties from data. We test the framework on 1D and 2D ice flow simulation outputs and demonstrate the recovery of the underlying basal mechanics under various levels of observational and modeling uncertainties. We apply this framework to time‐dependent velocity data for Rutford Ice Stream, Antarctica, and present evidence that ocean‐tide‐driven changes in subglacial water pressure drive changes in ice flow over the tidal cycle.
Assessment of severity, quality of life and suicidal ideation in patients with depressive disorders

Depression is estimated to be the third leading cause of disability and about 350 million people suffer from depression worldwide. Various biological, social, economic, cultural factors and environmental factors contribute for depression. A total of 102 patients were enrolled in the study. Majority of the patients (64, 62.74%) included in the study were female. The mean age of the study subjects was found to be 20.4±11.88 years. The severity of symptoms in depressed patients evaluated using Hamilton Depression Rating Scale (HDRS) shows that 33.33% of the subjects were very severely depressed, followed by 29.41% of the subjects with moderate depression, 23.52 % with severe depression and 11.76% with mild depression. Quality of life was evaluated using WHOQOL BREF Scale in the study population. 51.96 % of subjects were having low quality of life (QoL) followed by 48% of subjects with medium QoL and 0.98% subjects with high QoL. Modified Scale for Suicidal Ideation (MSSI) was used to evaluate severity of suicidal ideation in study population. Interpretation of results shows that 74.50% were having low suicidal ideation and few subjects (8.82%) were found to have severe suicidal ideation. Depression negatively impacts individual’s functioning, work satisfaction, relationships, leisure, physical and mental health, sexual functioning, sleep patterns and overall sense of fulfilment and contentment with life. Severe form of depression can lead to suicidal risk, increased risk of morbidity, mortality, substantial imbalance on individual’s occupational potential, significant physical and psychosocial impairment.
A HISTOLOGICAL STUDY OF BREAST CANCER PATIENTS IN DIYALA SOCIETY, IRAQ

This study was conducted on a group of women patients diagnosed with breast cancer attending the Tumors Cancer Center at Baquba Teaching Hospital in Diyala Governorate. This study included 100 samples that were divided into 50 women diagnosed with breast cancer and 50 normal women without the disease as a control group. The obtained results of this study showed that the women diagnosed with breast cancer in the age group (40-49) is the highest class of disease infected, as it reached (42%) among the other age classes of affected women, with a significant difference at the probability level of P0.05. The results also showed that there is a significant difference at the probability level of P0.01 among the women infected by disease and smoking. The percentage of women who did not smoke and suffering from disease was 74%, while 26% of the affected women had shown a relationship between smoking and disease. Meanwhile, the invasive ductal carcinoma was the most common and prevalence type than the other types with a ratio of 80%, while the less common type was the tubular type, at a ratio of 2%. The results of the histological aspect of the study showed that invasive ductal carcinoma cells are characterized by a dark nucleus with shapes and sizes that differ from one another and are multinucleated. On the other hand, the cancer cells appear clustered together as groups in multiple places where they form nests separated from other groups by connective tissue. The results indicated the presence of the second type of invasive lobular breast cancer, where the cancer cells were characterized by being small in size, regular and inconsistent and similar to the Indian file in shape. The carcinoma tubular type of cancer was 2% of the total samples examined in the current study, and the distinguishing feature of this type is that the majority of the tubules is open and made up of a single layer of epithelial cells containing a clear cavity.
OP-MOLB200089 2322..2331

Gene duplication serves a critical role in evolutionary adaptation by providing genetic raw material to the genome. The evolution of duplicated genes may be influenced by epigenetic processes such as DNA methylation, which affects gene function in some taxa. However, the manner in which DNA methylation affects duplicated genes is not well understood. We studied duplicated genes in the honeybee Apis mellifera, an insect with a highly sophisticated social structure, to investigate whether DNA methylation was associated with gene duplication and genic evolution. We found that levels of gene body methylation were significantly lower in duplicate genes than in single-copy genes, implicating a possible role of DNA methylation in postduplication gene maintenance. Additionally, we discovered associations of gene body methylation with the location, length, and time since divergence of paralogous genes. We also found that divergence in DNA methylation was associated with divergence in gene expression in paralogs, although the relationship was not completely consistent with a direct link between DNA methylation and gene expression. Overall, our results provide further insight into genic methylation and how its association with duplicate genes might facilitate evolutionary processes and adaptation.