Miracle-dz/UniFAR-FTUs huggingface dataset:
Endothelium condition and role of immunocompetent cells in atherosclerosis development as a cause of ischemic stroke

The aim. To determine the state of the cerebral vascular endothelium and the role of immunocompetent cells in the ischemic stroke development on the background of atherosclerosis. Materials and methods. We studied cerebral vessels of 50 deaths with ischemic cerebral infarctions, 50 – with severe cerebral atherosclerosis without CVD (cerebrovascular disease) manifestation and 50 deaths, whose cause of death was not related to CVD and atherosclerosis (control group). Histological preparations of vessels were stained with hematoxylin-eosin and Masson Trichrome, and also immunohistochemical study was conducted using CD31/PECAM-1 (Endothelial Cell Marker) Ab-1, CD4 (CD4 Ab-8), CD8 (SP 16), CD20 (CD20 Ab-1) CD68 and (CD68/Macrophage Marker Ab-4) markers. Results. Under ischemic strokes and severe atherosclerosis the cerebral vessels endothelium acquires structural changes in form of rupture, desquamation and exfoliation, formation of desquamated endothelial cells clusters. Speaking of endothelial damage, it should not be supposed that changes should occur at the macroscopic level only, endothelial damage at the cellular level shall be sufficient enough. Immunocompetent cells are of key importance in atherosclerosis development; adhesion on the luminal surface of arteries, presence of a large number of these cells under the endothelium and of more mature macrophages in the intima depth indicates the influx of these cells, which actively potentiate atherosclerosis formation, from the blood into the artery wall. Conclusions . Disorders of the endothelial lining with changes in endothelial cells morphology contribute to the atherosclerotic plaque development. Lymphocytes and macrophages form the molecular basis of many important processes, including the inflammatory response and the immune response
Before the damage is done: Early childhood hyperactivity difficulties in adolescents with deliberate self-harm – findings from the DALSC cohort

Abstract Background: Deliberate self-harm (DSH) is a growing issue among Danish adolescents, and a dramatic increase in the incidence of DSH has been observed since the turn of the millennium. The importance of early childhood factors on later development has been established, but research on the trajectories of DSH is still scarce, and longitudinal studies are much needed. Method: Participants were 3,291 children and their mothers from The Danish Longitudinal Survey of Children (DALSC), a Danish population-based birth cohort from 1995. Logistic regression and mediation analyses were used to examine significant early childhood determinants of self-harming behavior in adolescence. Results: The study found that 17.9% of the children had a history with DSH at the age of 18 years. A significant relationship was found between the likelihood of DSH at the age of 18 years and hyperactivity difficulties assessed through the Strengths and Difficulties Questionnaire (SDQ) at 3 and 7 years of age. Using a mediation model, it is documented that difficulties in peer relationships at the age of 11 years is a partial mediator explaining 19% of the variation. Limitations: i) a vague definition of self-harm in the questionnaires; ii) lack of sample representation as children of lower socio-economic groups have lower participation rates, and only Danish-ethnicity children have been sampled; iii) possibility of omitted variable bias. Conclusion: The adolescents engaging in DSH are experiencing a more complex range of psychosocial problems than those who do not have experience with DSH. The main finding of the study is that hyperactivity as a risk factor for the development of DSH in adolescence can be identified as early as 3–7 years of age. This relationship between the very early occurring hyperactivity and later DSH, to the best of our knowledge, has not previously been described.
On the vibrational structure in photoelectron spectra by the method of Green's functions

The density of states functions, which describe the vibrational structure in PE spectra, are calculated with the help of Green's functions. In addition to the exact solution of the one‐body problem, two different approaches to calculate reorganization and many‐body effects are presented. In all cases no data of the ion are required, and all transitions except those between linear and bent configurations are included. It is shown that the density of states is well approximated by using only the first‐order coupling constants in the one‐particle approximation. This means that already a simple calculation becomes a powerful tool in interpreting PE spectra.
Examining the effects of materialism on compulsive buying from 2013 to 2015 using meta-analysis approach

This study is conducted for meta-analysis of studies done on the effect of materialism on compulsive buying from 2013 to 2015. The study population is the studies on compulsive buying. From among 70 studies in this area, some of which are related to psychology, economics, and marketing, we diagnosed 5 cases in marketing proper for meta-analysis. Research method in inferential statistics is meta-analysis. We have used Comprehensive Meta-Analysis (CMA) software to analyze the collected data. The results have shown a small effect of materialism on compulsive buying.
An Overview on Network Representation Learning

Representation learning has proven its usefulness in many activities such as photography and text mining. The goal of network representation learning is to learn distributed vector representation for each vertex in the networks, an essential feature of network analysis is now increasingly recognised. Some techniques of network representation research network systems for learning. In effect, vertices of the network contain rich data (such as text), that cannot be used with the traditional algorithmic frameworks. We suggest DeepWalk in text-associated form, by showing that DeepWalk, a high-tech network representation solution, is equal to matrix factorisation (TADW). In the context of matrix factorisation, TADW introduce text features of vertices in network representation research. Through applying them to the multi classifying of vertices, we compare our system and different baseline methods.The experimental results show that, our method outperforms other baselines on all three datasets, especially when networks are noisy and training ratio is small. INDEX TERMS Network representation learning, recommendation algorithm
Object Detection using Deep Learning with OpenCV and Python

---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Computer Vision is a field of study that helps to develop techniques to recognize images and displays. It has different features like image recognition, object detection and image creation, etc. Object detection is used in face detection, vehicle detection, web images, and safety systems. The Objective is to distinguish of objects utilizing You Only Look Once (YOLO) approach. This technique has a few focal points when contrasted with other object detection algorithms. In different algorithms like Convolutional Neural Network, Fast-Convolutional Neural Network the algorithm won't take a gander at the image totally yet in YOLO the algorithm looks the image totally by anticipating the bounding boxes utilizing convolutional network and the class probabilities for these boxes and identifies the image quicker when contrasted with different algorithms. Using
PREDICTING MUNICIPAL SEWAGE EFFLUENT QUALITY INDEX USING MATHEMATICAL MODELS IN THE AL-RUSTAMIYA SEWAGE TREATMENT PLANT

Efficient management of treated sewage effluents protects the environment and reuse of municipal, industrial, agricultural and recreational as compensation for water shortages as a second source of water. This study was conducted to investigate the overall performance and evaluate the effluent quality from AlRustamiya sewage treatment plant (STP), Baghdad, Iraq by determining the effluent quality index (EQI). This assessment included daily records of major influent and effluent sewage parameters that were obtained from the municipal sewage plant laboratory recorded from January 2011 to December 2018. The result showed that the treated sewage effluent quality from STP was within the Iraqi quality standards (IQS) for disposal and the overall efficiency indicated a positive efficiency of the STP within the order BOD > COD > TSS > chloride. The results revealed that the effluent quality index (EQI) lied under a good water category for both effluent disposal and irrigation use. The multiple linear regression model (MLR) was used for the prediction of EQI and the results provided good estimates for the EQI data sets with a high coefficient of determination (R2=98%). From this analysis, EQI is highly significantly interrelated with TSS, BOD5, and COD within the values 88.9%, 78.6%, and 76.3% respectively. The artificial neural network (ANN) model was developed to predict the effluent quality index based on the selected sewage characteristics. Results provided good estimates for the EQI data sets with a high coefficient of determination (R2=99.8%) and lower relative error and TSS was more effective on the EQI model other than parameters with the relative importance 47.3%. So, the MLR and ANN models were found to provide an effective tool in efficient predicting EQI that can be used effectively to monitor effluent parameters and describe the suitability of treated sewage to quality achieved according to Iraqi quality standards (IQS) for effluent disposal and Food Agriculture Organization (FAO) standards for irrigation purposes.
The Trajectory Generation via Deep Neural Network for Hypersonic Vehicle

In this paper, we propose a method based on deep neural networks to generate the reentry trajectory of hypersonic vehicle. There are some complex constraints in the reentry trajectory optimization problem, such as dynamic pressure constraint and no-fly zones for threat avoidance. It’s hard to present the real-time controls by traditional optimal control methods, due to the limitation of onboard computer. In order to obtain the training data, we adopt gauss pseudo-spectral method (GPM) to compute the optimal trajectories, which contain the optimal states and controls. Deep neural network (DNN) are trained with the optimal states and controls. The reentry trajectory driven by the trained DNN is efficient, and the trained neural networks can present the real-time optimal controls, according to the reentry states of hypersonic vehicle.
The Influence of CFO and CEO Narcissism on Financilal Reporting

We utilize the size of CFO and CEO signatures as a proxy for narcissism to determine the influence of the executive’s personality on financial reporting characteristics and outcomes. Our experimental validation study first demonstrates that narcissism predicts misreporting behavior among students, and that student signature size predicts misreporting through its positive association with narcissism. Our archival tests subsequently examine notarized CFO and CEO signatures drawn from the same document and reveal that CFO narcissism predicts accruals and real earnings management as well as lower conditional accounting conservatism, weaker internal controls, and a higher probability of accounting restatements and shareholder lawsuits. CEO narcissism is not associated with any of these financial reporting characteristics or outcomes. Taken together, the results suggest that signature size is valid proxy for narcissism, and that CFO narcissism can lead to poor reporting quality.
BIOSURFACTANTS AND ITS PROSPECTIVE APPLICATION IN THE PETROLEUM INDUSTRY

Increasing number of reports on the oil degrading performances from microbes shows a good prospective for successful microbial remediation in treating environmental pollution caused during the production and accidental spillage of petroleum hydrocarbon. Biosurfactantproducing and hydrocarbon-utilizing microbes increase the bioavailability of complex hydrocarbons by synthesizing biosurfactant thus enhancing the bioremediation process. Bioremediation has been proven as a method that is effective in treating oil contaminated sites as well as cost effective and gives complete degradation of organic contaminants. Biosurfactant is well-known for its unique properties such as not exhibiting toxicity effect, biodegradable, efficient at low concentration and having high stability towards extreme environment. Their advantages over synthetic surfactants make them a better alternative for application in many fields. Most emphasis to date has been on the optimization and application of biosurfactant in petroleum-related activities. Optimization involving physical and nutrient factors has been attempted as a primary step to improve biosurfactant production. This mini-review article aims to emphasize recent findings on microbial biosurfactant and its potential applications and limitations particularly in the petroleum industry.
Use of thermally sprayed aluminium (TSA) to protect offshore structures in submerged and splash zones

The most commonly used corrosion mitigation methods for structures operating in seawater include a combination of protective coatings and cathodic protection (CP) provided by sacrificial anodes, but the use of such systems is not without limitations. In the absence of an effective CP system, organic coatings can provide protection to steel only when they remain intact. In subsea where the CP is effective, sacrificial anodes can considerably increase the overall mass of the structure and have to be replaced periodically (which is very costly). An alternative method, increasingly used in the offshore sector, is application of thermally sprayed aluminium (TSA) coatings. TSA offers long-term, maintenance-free protection to steel substrate, working as a barrier to the corrosive environment when intact, and acting as an evenly distributed anode which sacrificially protects steel when damaged. Furthermore, high resistance to mechanical damage, large operating temperature range, and low corrosion rate makes it an excellent corrosion mitigation coating for offshore applications. Offshore constructions operate not only in constant seawater immersion but also in alternating wetting and drying conditions in the so called “splash zone”. This zone is particularly corrosive due to constant splashing of highly aerated seawater. Confined volume of electrolyte, easy access to oxygen and atmospheric pollutant deposited on the metals’ surface lead to more severe corrosion in this region than in the submerged zone. In this work, the behaviour of several arc-sprayed aluminium coatings is investigated under full artificial seawater immersion, and compared with simulated splash zone conditions under droplets of artificial seawater exposed to controlled conditions. Effectiveness of TSA coatings is evaluated using electrochemical techniques and corrosion products are examined by SEM/EDX and XRD. The effect of sealers is also assessed.
Effectiveness of a modified toothbrush with continuous water supply on plaque control

Einführung: Den Erkrankungen des Zahnhalteapparates und der Zahnhartsubstanzen aufgrund von mikrobiellen Belägen kann bis dato nicht ausreichend vorgebeugt werden. Neben zahnärztlichen Maßnahmen zur Verbesserung der häuslichen Mundhygiene wie Motivation und Instruktion wird deshalb versucht, effizientere Mundhygienehilfsmittel zu entwickeln. In der vorliegenden Pilotstudie sollte der Einfluss einer kontinuierlichen Wasserzufuhr bei manuellen und elektrischen Zahnbürsten auf die orale Plaquekontrolle geprüft werden. Methode: Es wurden insgesamt 26 Probanden einbezogen und auf 2 Gruppen verteilt (Gruppe 1: 14 Probanden, Alter 22,9 ± 5,8 Jahre; Gruppe 2: 12 Probanden, Alter 72,1 ± 3,9 Ja-hre). Nach einer 48-stündigen Plaqueakkumulationsphase wurden je eine manuelle und elektrische Zahnbürste mit (Waschzahnbürste) und ohne kontinuierliche Wasserzufuhr in einer einmaligen Anwendung getestet. Zur Beurteilung der Plaquereduktion wurden der Quigley-Hein-Index nach Turesky sowie der Approximale-Plaque-Index nach Lange jeweils vor und nach dem Zähneputzen erhoben. Ergebnisse: Die durchschnittliche Reinigungseffektivität auf den Glattflächen erwies sich bei der manuellen und elektrischen Waschzahnbürste verglichen mit den konventionellen Prof. Dr. Hüsamettin Günay (Foto: privat)
Investment , Security Design and Information 1

We consider the decisions of a venture capitalist who starts a new project. The prospects for the resale values of the newly created rm(s) are important features of the choice of the project. We assume that they crucially depend on the state of information when the rms are o ered on the stock market. Such an information is likely to be asymmetric, which typically discourages the general public to invest in the new rms. This market imperfection in uences the initial choices of the capitalist: it favors the projects where the asymmetry of information is the least pronounced (or, equivalently in our model, the risks born by the investor are smaller), and projects whose risk characteristics may be useful as a hedge to the market at large. The paper illustrates this argument in a two stage CARA gaussian model with the following structure. In a rst stage, the venture capitalist chooses her/his investment, as well as the asset structure of her/his rm(s). In the second stage, after some information has been revealed on the investment pro tability, the rms are oated on the market. The stock market is competitive, with some noise that prevents prices to reveal all the available information. The rst stage decisions are analyzed under rational expectations of the outcome of the stock market: we study security design (should the venture capitalist put all her/his projects into a single or several rms? ), and the investment choice. Journal of Economic Literature Classi cation Codes : D82, G14. October 5, 1998 { 09 : 48 1
Exploration of interethnic variation in the ibuprofen metabolizing enzyme CYP2C9: a cautionary guide for treatment of COVID-19 symptoms

Coronavirus disease 2019 (COVID-19), is a rapidly spreading infectious illness that causes a debilitating respiratory syndrome. Supportive therapy remains the standard for mild-to-moderate cases, including treatment with non-steroidal anti-inflammatory drugs (NSAIDs) e.g. ibuprofen, however such medications may increase COVID-19 complications when used in patients with acute viral respiratory infections. P450 enzyme CYP2C9 are known to be involved in the metabolism of NSAIDs, however, their pharmacogenetic data are limited. This study aims to better understand the genetic landscape of CYP2C9 sequence variation across different ethnic and geographic groups, in correlation with ibuprofen dosing guidelines. A cohort of 101 Jordanian Arab samples were retrospectively recruited and genotyped using Affymetrix DMET Plus Premier Package. This study identified 18 single nucleotide polymorphisms (SNPs) within CYP2C9 in these Jordanian Arabs, within the context of over 100,000 global subjects in 417 published reports. Genetic structure analysis across populations revealed that Jordanian Arabs share the closest CYP2C9 sequence homology to Near East and European populations. However, European populations are 7.2x more likely to show impaired ibuprofen metabolism than Sub-Saharan populations, and 4.5x more likely than East Asian ancestry populations. This is the most comprehensive and up-to-date analysis for CYP2C9 allele frequencies across multi-ethnic populations world-wide. The use of modern genomic tools coupled with a proactive assessment of the most likely gene-drug candidates will lead to a better understanding of the role of pharmacogenetics for COVID-19 and more effective treatments.
Path integral centroid molecular-dynamics evaluation of vibrational energy relaxation in condensed phase

We present a method based on centroid molecular dynamics (CMD) to calculate nonlinear quantum force correlation functions important in the golden rule approach for studying vibrational energy relaxation (VER) in condensed phases. We consider a model of a diatomic molecule in a two-dimensional neon liquid and also a diatomic coupled to a small Helium cluster. The predictions of the theory for the neon bath are compared and found in close agreement with available theories for VER based on the Egelstaff correction factor and Feynman–Kleinert variational theory. For the Helium cluster, the force spectrum obtained from CMD is found to be in slightly better agreement with the exact result than a method based on a cumulant approach. The results support the use of CMD in condensed phase studies of VER when quantum effects are important.
The complex interplay between tidal inertial waves and zonal flows in differentially rotating stellar and planetary convective regions

Context. Quantifying tidal interactions in close-in two-body systems is of prime interest since they have a crucial impact on the architecture and the rotational history of the bodies. Various studies have shown that the dissipation of tides in either body is very sensitive to its structure and to its dynamics. Furthermore, solar-like stars and giant gaseous planets in our Solar System experience differential rotation in their outer convective envelopes. In this respect, numerical simulations of tidal interactions in these objects have shown that the propagation and dissipation properties of tidally excited inertial waves can be strongly modified in the presence of differential rotation. Aims. In particular, tidal inertial waves may strongly interact with zonal flows at the so-called co-rotation resonances, where the wave’s Doppler-shifted frequency is cancelled out. The energy dissipation at such resonances could deeply modify the orbital and spin evolutions of tidally interacting systems. In this context, we aim to provide a deep physical understanding of the dynamics of tidal waves at co-rotation resonances in the presence of differential rotation profiles that are typical of low-mass stars and giant planets. Methods. In this work, we have developed an analytical local model of an inclined shearing box that describes a small patch of the differentially rotating convective zone of a star or a planet. We investigate the propagation and the transmission of free inertial waves at co-rotation, and more generally at critical levels, which are singularities in the governing wave differential equation. Through the construction of an invariant called the wave action flux, we identify different regimes of wave transmission at critical levels, which are confirmed with a one-dimensional three-layer numerical model. Results. We find that inertial waves can be fully transmitted, strongly damped, or even amplified after crossing a critical level. The occurrence of these regimes depends on the assumed profile of differential rotation, on the nature as well as the latitude of the critical level, and on wave parameters such as the inertial frequency and the longitudinal and vertical wavenumbers. Waves can thus either deposit their action flux in the fluid when damped at critical levels, or they can extract action flux from the fluid when amplified at critical levels. Both situations can lead to significant angular momentum exchange between the tidally interacting bodies.