Miracle-dz/UniFAR-FTUs huggingface dataset:
Firm Fundamentals in the COVID-19 Stock Market

The effects of the COVID-19 crisis allow for an opportunity to examine what types of firms are most durable to sudden and prolonged stock market shocks. Using data on the constituents of the Russell 3000, I find that firms with more capital-intensive operations, higher leverage, and larger cash balances were most prone to drops in daily return related to increases in the growth of COVID-19 infections. Larger, more profitable, and more liquid firms saw positive interactions between daily returns and COVID-19 infection growth. However, I also find a potential reversal of these trends as riskier and more leveraged firms exhibit higher cumulative abnormal returns off vaccine hopes, which may signal a renewed interest in riskier investment profiles as the world begins and continues to move past the COVID-19 pandemic. This study presents insight on daily stock return reactions to COVID-19 infection growth throughout the course of the virus.
Impact of Characteristics of Firm on Quality of Financial Reporting of Quoted Industrial Goods Companies in Nigeria

The increasing pervasive failure of companies made it imperative to advocate for increased financial reporting quality and to make stronger management control through creation of reliable firm characteristics. Therefore, the paper examines the effect of characteristics of firm from viewpoint of structure of firm, structure of board, structure of performance and structure of ownership variables on quality of financial reporting in quoted Industrial goods companies in Nigeria proxied by Roychowdhury (2006) model. Correlational design was employed by the study using a panel balanced data of 11 companies which is the sample of the study for the period of 2011-2018.Multiple regression technique was used as analysis tool. Firm size, leverage, firm age and women directors were established to have significant and negative effect on real earnings manipulation of quoted Industrial goods companies in Nigeria. These does imply that the variables improve the financial reporting worth of companies. Furthermore, board meetings and profitability significantly but positively influence the worth of financial reporting of companies, however, liquidity, growth and ownership structure proxies have weak influence on the financial reporting worth. The paper recommends that the management of quoted industrial goods companies must place more emphasis on other structures rather than only ownership structure in order to guarantee continuous improvement in their financial reporting quality as manipulative accounting activities of management is reduced.
Histomorphometric analysis of the effects of Quercetin on testicular apoptosis and oxidative damage

Lead is one of the common heavy metal pollutants, which causes apoptosis and oxidative damage on various organs in humans. The current morphometric study was conducted to evaluate the effect of quercetin in improving that damage. Forty adult male albino rats were divided into four groups (10 rats/each): control group; quercetin group; lead group; Pb + quercetin group; All treatments were performed daily for 30 days. Serum testosterone, FSH, LH levels, oxidative stress parameters and testicular analysis were conducted. The results revealed that lead exposure caused significant elevations in cytokines and inflammatory mediators, concentration of lead in testis, oxidative stress with significant reduction in sexual hormones and antioxidants. Lead intoxicated rats showed marked increase in the percentage of dead sperms and abnormal sperm rate, while significant decrease in sperm concentration and sperm motility. Co-administration with quercetin caused a significant increase in testosterone levels, testicular SOD and CAT activities, and a decrease in MDA levels, with improvement in morphometric alterations. Quercetin averts cell death and antioxidant injury through numerous mechanisms, as scavenging oxygen radicals, defending against lipid peroxidation and chelating Pb ions [1, 2]. Quercetin is accounted as a surpass free-radical scavenging antioxidant due to a capacity to provide electrons or hydrogens, and scavenges hydroxyl groups, hydrogen peroxide, and superoxide anions [3]. In conclusion, co-treatment with quercetin prevent degenerative changes induced by lead, reduced oxidative stress, cytokines and inflammatory mediators, and restored the biochemical changes.
Caroli Syndrome Associated with Polycystic Kidney and Congenital Heart Disease in Children in Africa

Caroli syndrome (CS) is defined as the association of Caroli disease with congenital liver fibrosis. It is a rare congenital pathology with a global prevalence of less than 1 / 1,000,000 inhabitants. We report a case of CS associated with polycystic kidney disease (PKD). He is a 7 years old boy followed from the age of 2 years for epigastric pain. Abdominal ultrasounds were performed at the ages of 2 years, 4 years and 6 years. They showed hepatomegaly associated with dilation of the intrahepatic bile ducts, hepatic fibrosis and bilateral renal cysts and micro-stones. The child received several hospitalizations, the last of which was at the age of 6 years for abdominal pain, ascites, digestive haemorrhage secondary to portal hypertension and hematuria. On admission, the weight was 19 kg (-2 DS), the size was 119cm (-1 DS) and the BMI was 13.41 (-3DS). The child had no icterus. The abdomen was distended and a painless hepatomegaly was palpated with a hepatic arrow at 12.5cm and stage II splenomegaly. The urine test showed hematuria. The liver test showed an isolated elevation of alkaline phosphatase. The abdominal computed tomography scan showed hepatomegaly, dilation of the intrahepatic bile ducts and the presence of bilateral renal hypodense cystic lesions. The patient received Aldactone, Propanolol, Captopril, a blood transfusion and ursodesoxycholic acid as treatment. The evolution is stationary awaiting surgical management.
CONMEBOL Libertadores Cup: Altitude impact on goals and results in 16 years of soccer matches

Background: The CONMEBOL Libertadores Cup, is the continent’s most important international club tournament. Teams are exposed to different altitudes with short acclimatization periods. The present study describe the effect of altitude on the results and goals of soccer club teams matches between 2000 and 2015 in the CONMEBOL Libertadores Cup. Materials & Methods: All home and away matches from the group phase onwards and which have been played at the traditional team venue were taken into account, thus, 2039 games were analysed. The teams were classified into altitude categories according to the physiological impact and registered hometown altitude. A Poisson´s generalized linear model was used to study the relationship between the altitude of both home and away teams and the number of goals scored for each team according to the altitude category. The probabilities that the home team winning, drawing, or losing the match were estimated using a regression model for ordinal variables and assuming a multinomial probability distribution with the logistic linkage. Factors as heat, temperature and general performance of the teams were not considered. Results: Home team scores more (2.62 goals) when the away team descends three altitude categories, followed by a descent of two altitude categories (2.01 goals) and an ascent of three altitude categories (1.89 goals). This is associated with an increase probability of winning for the home team, being 5.5 times more likely when the away team descends three altitude categories, 2.3 times more when it descends two categories, and 2.5 times more when it ascends three altitude categories. Conclusions: These findings suggest that the away team is more likely to lose a match when it has to descend two or three altitude categories and when it ascends three altitude categories.
Effect of Crop Management on Soil Bacterial Communities in Organic and Conventional Farming Systems

Elabed, N. , Bouri, M. , Rhouma, A. , Ben Kheder, M. , and M'Hamdi, M. 2016. Effect of crop management on soil bacterial communities in organic and conventional farming systems. Tunisian Journal of Plant Protection 11: 37-49. The aim of the present study was to assess the population of bacteria isolated from organic and conventional soils and to identify antagonistic ones with a potential antifungal activity against some pathogenic fungi (Rhizoctonia solani and Fusarium oxysporum). All cultivable bacterial isolates were evaluated for their antifungal activity and the most effective ones were identified based on 16S rDNA sequence analysis. The results showed that among a total number of 100 bacteria isolated from soil, eight isolates displayed antifungal activity against F. oxysporum and twenty four isolates had suppressed R. solani growth. The results indicated that tested bacterial species exhibited varying degree of antagonistic potential against pathogenic fungi which ranged from 22.7% using AB95 isolate to 77.2% with AB40 and AB8 tested against F. oxysporum and from 22.7% using AB51 and AB5 to 68.1% with AB75 and AB64 tested against R. solani. DNA sequencing reaction of purified PCR amplicon was carried out using 16sF and 16sR primers. Sequence alignment with the reference sequences of the databases using BLAST was performed. The most dominant genuswas Bacillus. Phylogenetic tree was built.
RUNNING HEARD: OVERSPECIFICATION AND INCREMENTAL PROCESSING Overspecification and incremental referential processing: An eye-tracking study

Using eye-tracking, we examined if over-specification hinders or facilitates referent selection, and the extent to which this depends on the properties of the attribute mentioned in the referring expressions and the underpinning processing mode. Following spoken instructions, participants selected the referent in a visual display while their eye movements were monitored. The referring expressions were presented either simultaneously with the displays, so the attributes could be incrementally processed in sequence, or before the display presentation, so the attributes could be processed in parallel from the outset of search. Experiment 1 showed that when the attributes were processed incrementally, how quickly an earlier-mentioned attribute discriminated determined whether a late-mentioned, over-specified attribute contributed to discrimination: When color was mentioned first and is fully discriminating, the referent was selected fast regardless of the secondmentioned pattern, whereas when pattern was mentioned first and is fully discriminating, the second-mentioned color facilitated discrimination. Experiment 2 found that under incremental processing, color mention after a fully discriminating pattern increased fixations but delayed referent selection relative to a pattern-only description; under parallel processing, however, color mention immediately eliminated alternatives and sped up referent selection. Experiment 3 showed that pattern mention after a fully discriminating color delayed referent selection and tended to reduce fixations relative to a color-only description in both processing modes. Hence, additional attributes can speed up referent selection but only when they can discriminate much faster than alternative attributes mentioned in a more concise description, and critically, when they can be used early for
Relative Merits of Data Mining Algorithms of Chronic Kidney Diseases

Early prediction of Chronic Kidney Disease in human subjects is considered to be a critical factor for diagnosis and treatment. The use of data mining algorithms to reveal the hidden information from clinical and laboratory samples helps physician in early diagnosis, thus contributing towards increase in accuracy, prediction and detection of Chronic Kidney Disease. The experimental results obtained from this work, with subjected to optimal data mining algorithms for better classification and prediction, of Chronic Kidney Disease. The result of applying relevant algorithms, like K-Nearest Neighbors, Support Vector Machine, Multi Layer Perceptron, Random Forest, are studied for both clinical and laboratory samples. Our findings show that K Nearest Neighbour algorithm provides the best classification for clinical data and, similarly, Random Forest for laboratory samples, when compared with the performance parameters like, precision, accuracy, recall and F1 Score of other data mining analysis techniques. Keywords—Ultrasound images; support vector machine (SVM) k-nearest algorithm (K-NN); multilayer perceptron algorithm (MLP); random forest (RF); clinical data
Indoor Localization and Navigation based on Deep Learning using a Monocular Visual System

Now-a-days, computer systems are important for artificial vision systems to analyze the acquired data to realize crucial tasks, such as localization and navigation. For successful navigation, the robot must interpret the acquired data and determine its position to decide how to move through the environment. This paper proposes an indoor mobile robot visuallocalization and navigation approach for autonomous navigation. A convolutional neural network and background modeling are used to locate the system in the environment. Object detection is based on copy-move detection, an image forensic technique, extracting features from the image to identify similar regions. An adaptive threshold is proposed due to the illumination changes. The detected object is classified to evade it using a control deep neural network. A U-Net model is implemented to track the path trajectory. The experiment results were obtained from real data, proving the efficiency of the proposed algorithm. The adaptive threshold solves illumination variation issues for object detection. Keywords—Visual localization; visual navigation; autonomous navigation; feature extractor; object detection
The Effects of Glucagon-Like Peptide-1 Receptor Agonists and Dipeptydilpeptidase-4 Inhibitors on Blood Pressure and Cardiovascular Complications in Diabetes

Glucagon-like peptide-1 receptor (GLP-1R) agonists are a class of newly introduced antidiabetic medications that potentially lower blood glucose by several molecular pathways. DPP-4 inhibitors are the other type of novel antidiabetic medications which act by preventing GLP-1 inactivation and thereby increasing the activity levels of GLP-1, leading to more glucose-induced insulin release from islet β-cells and suppression of glucagon release. Most patients with diabetes have concurrent hypertension and cardiovascular disorder. If antihyperglycemic agents can attenuate the risk of hypertension and cardiovascular disease, they will amplify their overall beneficial effects. There is conflicting evidence on the cardiovascular benefits of GLP-1R induction in laboratory studies and clinical trials. In this study, we have reviewed the main molecular mechanisms by which GLP-1R induction may modulate the cardiovascular function and the results of cardiovascular outcome clinical trials.
Automated Dictionary Creation for Analyzing Text: An Illustration from Stereotype Content

Recent advances in natural language processing provide new approaches to analyze psychological open-ended data. However, many of these methods require translating to the needs of psychologists working with text. Here, we introduce automated methods to create and validate extensive dictionaries of psychological constructs using Wordnet and word embeddings. Specifically, we first expand an initial list of seed words by using Wordnet to obtain synonyms, antonyms, and other semantically related terms. Next, we evaluate dictionary reliability by using word embeddings trained on independent sources. Finally, we evaluate the dictionaries’ convergent validity against traditional scale ratings and human judgments. We illustrate these innovations by creating stereotype content dictionaries, a construct in social psychology that lacks specialized and validated dictionaries for coding open-ended data. These dictionaries achieved over 80% coverage of new responses, compared to 20% coverage by the seed-word-only approach. Cosine similarity with word embeddings confirmed that the dictionaries are more similar within the same concept than across concepts. Moreover, open-ended responses predicted both traditional scale ratings and human judgments about the dictionary topic. The R package Automated Dictionary Creation for Analyzing Text (ADCAT; https://github.com/gandalfnicolas/ADCAT) allows anyone to create novel dictionaries for constructs of interest and to access the stereotype content dictionaries.
IMPROVEMENT OF THE METHODOLOGY FOR ASSESSING THE LEVEL OF INNOVATIVE ACTIVITY IN THE REGIONS OF THE REPUBLIC OF KAZAKHSTAN

In the Republic of Kazakhstan, the economic environment in general not yet favorable for innovation. The main tasks of the scientific sector of industrial enterprises should be the creation of new goods and services of science-intensive content that is, obtaining new knowledge in the field development of nature and society. To develop an innovation, it is necessary to conduct market research, research and experimental work, organizational and technological preparation of production, to carry out production and formalize the results. The article analyzes the state of innovation activity in the regions of the Republic of Kazakhstan. Identified factors, which influenced the stimulation of innovative activity and sustainable development of enterprises in the regions of the Republic of Kazakhstan. Despite the measures taken by state, level of innovation activity and regional actors of sustainable development remains low. In order to build a regional innovation strategy, taking into consideration the strengths and weaknesses in the innovation sphere of the region, an effective methodology for assessing the innovation activity of the region’s subjects is needed. In the article methods and indicators related to the measurement of innovation activity are studied and direction for sustainable development are presented. However, the existing methods of measurement and analysis of this indicator depend on the purpose of the research and therefore not all aspects of innovation activity can be uncapped and sustainable development depends on politics and its state support. Accordingly, the authors suggest to use integrated assessment methods, where the coordinated system of index and indicators acts as a basis, and apply the recommendations of international experts for sustainable development.
CHANGE OF SOME OSMOLYTES ACCUMULATION IN WATER-STRESSED COLZA (BRASSICA NAPUS L.) AS AFFECTED BY 24-EPIBRASSINOLIDE*

Brassinosteroids are phytohormones possessing a wide spectrum of antistress activity. To seewhether this hormone is able to ameliorate the effects of water stress, the effects of 24-epibrassinolise onplant growth, accumulation of osmolytes (proline, sugars and ions), lipid peroxidation and electrolyte leakagewere investigated in Colza (Brassica napus L. cv. Fusia) plants which were under water stress. The seedswere sown in plastic pots containing sand, clay and peat (in a proportion of 1:1:1). Solution of 24-epibrassinolidat 10-7 M concentration containing 0.01% Tween-20 (polyoxyethylene sorbitan) was sprayed onleaves at intervals of 1, 2 and 3 weeks after sowing. Control plants were sprayed with 0.01% Tween-20, andwater treatment was applied 26 days after germination, withholding water for 3 or 4 days. One month aftersowing, plants were harvested. Lipid peroxidation and electrolyte leakage significantly increased under waterstress, but when plants were pretreated with 24-epibrassinolid and put under water stress these parametersdecreased, revealing that less oxidative damage occurred in this group. Proline and reduced sugars contentwas increased when 24-epibrassinolide were applied. FW and DW were significantly decreased under waterstress. Water stress also increased the uptake of K and Ca, but the uptake of Na significantly decreased. 24- epibrassinolide considerably increased ions uptake by plants. Taken together, these results showed that 24- epibrassinolide alleviated the effects of water stress and increased the tolerance of plants to stress byincreasing osmolytes accumulation and therefore could be used to improve crops in harsh conditions.
HISTOMORPHOLOGICAL SPECTRUM OF SOFT TISSUE TUMORS IN A TERTIARY CARE CENTER: A 5yr STUDY

Due to their rarity, STSs are always outnumbered by carcinomas in many primary sites, therefore not reported in most researches categorizing cancers with the International Classification of Diseases. [6,12] This hinders the accurate diagnosis and appropriate treatment and at the same time makes it difficult to accumulate a sufficient number of cases of STS at a single institution for statistical analysis. [13] Thereby making the soft tissue tumor literature dominated by retrospective series. This is a single tertiary care center five year study of these soft tissue tumors correlating the demographics, anatomical site, histological features and immunohistochemistry at the same time.
Hybrid Edge-Cloud based Ensemble Learning for Forecasting Occupancy of Open-plan Offices

Estimating and forecasting occupancy of open-plan and agile offices is of great value to many businesses, since it allows them to better allocate the necessary space, and save on energy and insurance costs. In this work we use a massive amount of data collected in an open-plan office having a large number of IoT sensors over an extended time period to explore how to best forecast occupancy in an open-plan office. We implement, evaluate, and compare statistical, machine learning, and deep learning forecasting methods, while using as inputs a variety of features including seasonal factors and weather data that affects occupancy patterns. It is shown that the best forecasts can be achieved using a deep learning model (LSTM), trained on a large amount of prior data. However, an ensemble model (composed of seasonal ARIMA and Decision Trees) is likely to be a more practical and reliable solution in hybrid Edge-Cloud scenarios, where less data may be available and privacy is important. In the ensemble approach, data can be split between Edge and Cloud platforms – keeping recent data and light models locally, and sending less recent data to the Cloud only when needed for model retraining.
Expression and significance of RNA-binding protein 38 and p53 gene in lung adenocarcinoma

[摘 要] 目的: 分析肺腺癌组织中RNA结合基序蛋白38基因(RNA-binding motif protein 38, RBM38)及抑癌基因p53 mRNA和 蛋白的表达情况,探讨其在肺腺癌发生发展中的意义。 方法: 取2012年10月至2015年6月新疆医科大学附属肿瘤医院收治的 50例肺腺癌患者的肿瘤组织标本作为实验组,相对应的癌旁组织标本作为对照组。 用RT-PCR法检测两组中RBM38及 p53 mRNA相对表达量,用Western blotting法检测两组中RBM38及p53蛋白的相对表达量。 结果: 实验组RBM38 mRNA及蛋白相 对表达量(0.357±0.170、0.294±0.149)均高于对照组(0.271±0.128、0.206±0.099),实验组 p53 mRNA及蛋白(0.457±0.208、 0.671±0.200)相对表达量均高于对照组(0.308±0.167、0.332±0.071),差异均有统计学意义(均 P<0.01)。 RBM38 表达与肺 腺癌患者 TNM 分期、浸润深度有关 (P<0.05),p53 表达与患者TNM分期有关(P<0.05)。 实验组 RBM38与p53蛋白表达呈负 相关(r=-0.626,P<0.01)。 结论: 肺腺癌组织RBM38、p53 mRNA及蛋白表达均高于癌旁组织,两者均与患者TNM分期等病理参 数关系密切。 随着RBM38蛋白表达的增加 p53蛋白随之减少,RBM38可能通过抑制 p53的翻译从而促进肺癌的发生发展, RBM38可能成为肺腺癌分子靶向治疗的靶点。 [关键词] 肺腺癌; RNA结合基序蛋白38基因; p53基因 [中图分类号] R730.2;R734.2 [文献标识码] A [文章编号] 1007-385X(2017)08-0900-04