Miracle-dz/UniFAR-FTUs huggingface dataset:
Employer Neighborhoods and Racial Discrimination

Using a large field experiment, we show that racial composition of employer neighborhoods predicts employment discrimination patterns in a direction suggesting in-group bias. Our data also show racial disparities in the geographic distribution of job postings. Simulations illustrate how these patterns combine to shape disparities. When jobs are located far from Black neighborhoods, Black applicants are doubly disadvantaged: discrimination patterns disfavor them, and they have fewer nearby opportunities. Finally, building on prior work on Ban-the-Box laws, we show that employers in less Black neighborhoods appear much likelier to stereotype Black applicants as potentially criminal when they lack criminal record information.
An electrodeposited cobalt–selenide-based film as an efficient bifunctional electrocatalyst for full water splitting

Design and development of noble metal-free, active and bifunctional electrocatalysts is crucial for both the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) in the full water splitting process. Herein, an amorphous cobalt–cobalt oxide/cobalt selenide composite film (CoOx–CoSe) has been fabricated directly on a three-dimensional macro-porous Ni foam (NF) substrate by a facile electrodeposition method, which shows remarkable activity and good long-term stability as an efficient bifunctional electrocatalyst for the OER and HER under alkaline conditions. In 1.0 M KOH, this catalyst as a robust 3D O2-evolving anode can achieve 100 mA cm−2 and 500 mA cm−2 only at overpotentials of 300 mV and 380 mV, respectively. When used as a HER catalyst, similarly, this electrode shows excellent catalytic performance, which needs an overpotential of 90 mV to deliver 10 mA cm−2. This bifunctional electrode can allow an alkaline electrolyzer to obtain a water-splitting current density of 20 mA cm−2 at a cell voltage of around 1.66 V, which offers potential applications in the field of water splitting.
Numerical modelling of Phosphorus Advection and Diffusion in Water Bodies (Case study: Sefidrood River)

Phosphorus is one of the vital nutrients for plants and algae growth. Low solubility of phosphorus compared of other nutrients, has caused phosphorus plays key role in algae growth and its often limiting nutrient in most freshwater. So that excessive phosphorus level in water can produce more algae that cannot be consumed by water body creatures and can cause eutrophication, water quality reduction and harmful condition for aquatic ecosystem. Therefore, it is important to identify the main sources of entering into rivers, recognizing the mechanism of transport and its distribution as well as the conditions created in rivers due to the advection and diffusion of phosphorus. For this purpose, in this research, after identifying the main sources of phosphorus entry into the river, it investigates and simulates the advection and dispersion of phosphorus in the Qezel-Ozan, Shahrood and Sefidrood Rivers based on field measuring data and using HEC-RAS software. Five scenarios were designed based on statistics and engineering studies to predict the phosphorus concentration of rivers due to rising temperatures, changes in river discharge due to drought and wet season, human population growth and development of irrigation networks in the region for the future. Then, by numerical simulating using HECRAS software, the impacts of phosphorus dispersion have been investigated in the region research area. The result presented that controlling human activities that entering phosphorus to Qezel-Ozan and Shahrood rivers can reduced total phosphorus concentration of Sefidrood river but mass of algae has been increased only by increasing air temperature and discharge of rivers and decreasing by reduced river discharge. Besides, the results showed that maximum total phosphorus concentration of Sefidrood River (downstream river) predicted by the numerical simulation related to the developed scenarios was higher than the maximum desired total phosphorus concentration for warm and cold water fish. For this reason, pay more attention to limit entering phosphorus sources have to be considered for development programme in the upstream rivers (Shahroood and Qezel-Ozan) in the region.
Importance of antiepileptic drugs interactions in routine clinical practice

Riziko lékových interakcí je u antiepileptik vysoké. Výsledek může být buď prospěšný, kdy dojde ke zvýšení terapeutického účinku, nebo škodlivý, jestliže se zvýší riziko nežádoucího účinku nebo se sníží terapeutický efekt léčiva. Skutečný vliv lékové interakce je velice obížné predikovat vzhledem k významné interindividuální variabilitě mezi pacienty. Terapeutické monitorování léčiv je metoda používaná jako nástroj k dosažení optimálního dávkovacího režimu u konkrétního pacienta s epilepsií. Klíčová slova: antiepileptika, interakce, terapeutické monitorování léčiv.
Study on the seasonal variation of Aeolus detection performance over China using ERA5 and radiosonde data

Abstract. Aeolus wind products have been available to ordinary users on May 12, 2020. In this paper, the Aeolus wind observations, L-band radiosonde (L-band RS) data and the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth generation atmospheric reanalyses (ERA5) are used to analyse the seasonality of Aeolus detection performance over China. Based on the Rayleigh-clear data and Mie-cloudy data, the data quality of the Aeolus effective detection data is verified, and the results show that the Aeolus data is in good agreement with the L-band RS data and the ERA5 data. The relative errors of Aeolus data in the four regions (Chifeng, Baoshan, Shapingba and Qingyuan) in China were calculated according to different months (July to December 2019, May to October 2020). The relative error of the Rayleigh-clear data in summer is significantly higher than that in winter, as the mean relative error parameter in July is 174 % higher than that in December. Besides, the distribution about the wind direction and the high-altitude clouds in different months (July and December) are analysed. The results show that the distribution of angle, between the horizontal wind direction of the atmosphere and the horizontal line of sight (HLOS), has a greater proportion in the high error interval (70°–110°) in summer, and this proportion is 8.14 % higher in July than in December. In addition, the cloud top height in summer is about 3–5 km higher than in winter, which may reduce the signal-to-noise ratio (SNR) of Aeolus. The results show that the detection performance of Aeolus is affected by seasonal factors, which may be caused by seasonal changes in wind direction and cloud distribution.
Constructing Linguistic Verb Source for Relation Extraction

In bio-literature mining, relation extraction is one of the important subjects. In RE, verbs are a key to determine a relation type between entities. However, it was not paid much attention to the study related with construction of the biomedical verb list and the study of defining biomedical verbs. Therefore, we attempted to define the biomedical verb, and based on the definition, we established the actual list of verb and constructed the list using PKDE4J. We attempt to construct the verb list with relation type classified by their characteristics and a nominalization form of extracted verbs for usability. Finally, we established the actual list of biomedical verb and constructed the linguistic
Computational Intelligence Prediction Model Integrating Empirical Mode Decomposition, Principal Component Analysis, and Weighted k -Nearest Neighbor

On the basis of machine leaning, suitable algorithms can make advanced time series analysis. This paper proposes a complex k-nearest neighbor (KNN) model for predicting financial time series. This model uses a complex feature extraction process integrating a forward rolling empirical mode decomposition (EMD) for financial time series signal analysis and principal component analysis (PCA) for the dimension reduction. The information-rich features are extracted then input to a weighted KNN classifier where the features are weighted with PCA loading. Finally, prediction is generated via regression on the selected nearest neighbors. The structure of the model as a whole is original. The test results on real historical data sets confirm the effectiveness of the models for predicting the Chinese stock index, an individual stock, and the EUR/USD exchange rate.
The Addictive Potential of Sexual Behavior (Impulse) review2 (1)

This paper examines the addictive potential of sexual behavior through behavioral and neurophysiological mechanisms analogous to other formalized addictions. Sexual behavior refers to any action or thought preformed with the intention of sexual gratification, such as the consumption of explicit material, masturbation, fantasizing of sexual scenarios, and sexual intercourse. Addiction is defined by the presence of tolerance, preoccupation, withdrawal, dependence, and the continuation of behavior despite risk and/or harm. Sexual addiction demonstrates high relapse potential due to the frequency of reward-associated cues encountered in daily life, and the low effort and risk required for sexual pleasure. Currently, sexual addiction lacks a formal diagnosis despite behavioral, psychological, and physiological evidence. An official diagnosis recognized by a governing authority, such as the American Psychological Association, would offer greater access to treatment, funding for research, and exposure and education for the general public about this disorder.
AN OVERVIEW OF CUBOSOMES-SMART DRUG DELIVERY SYSTEM

Cubosomes are square and rounded particles with internal cubic lattices visible. The invention of cubosomes is a distinctive story and spans the fields of food science, differential geometry, biological membranes and digestive processes. Self-assembled cubosomes act as active drug delivery systems; highly accepted, has got importance after innovation and nomination. Cubosomes are thermodynamically stable; they enclose a structure similar to “Honeycomb” through bicontinuous domains of water and lipid. Inside the surfactant, it is assembled into bilayers and wrapped into a three dimension, periodic and minimal surface, forming a strongly packed structure. Bicontinuous cubic liquid crystalline phase with optically lucid, extremely viscous material and have exclusive structure at the nanometer range. On the whole, cubosome render high importance in nano drug preparations for melanoma treatment outstanding to their aDepartment of Pharmaceutics, Faculty of Pharmacy, Sri Ramachandra University, Porur, Chennai 116. potential advantages, including heavy payloads of drug because of increased surface area and cuboidal structures. They have very simple method of preparation; whereas biodegradability of lipids have the capability of encapsulating hydrophobic, hydrophilic and amphiphilic substances meanwhile targeted and controlled release of bioactive agents. Cubosome dispersions are bioadhesive and biocompatible. Because of their properties, cubosome are versatile systems, administrable by different ways such as oral, percutaneous and parenteral. Cubosomes have broad vast applications in many areas and are characterized by various parameters. Consequently, Cubosomes are in move forward of awareness by pharmaceutical development division.
Data-Driven Technology Management Supported by Artificial Intelligence Solutions

Technology Management is an important part of a company’s business strategy. Procuring, evaluating, and processing information is crucial for this process' success. This paper describes the way of dealing with today’s challenge of information overload. It introduces a concept of technology databases based on opportunity evaluation and the systematical development process of technical systems. The idea is to capture two perspectives – generic technology information outside the company and internal technology knowledge – in one comprehensive database to be used as a basis for decision-making in technology management. Complementing this, the paper presents concepts of Artificial Intelligence-based information retrieval and processing that are suitable to efficiently support and semi-automate the filling and updating of such a database. Furthermore, existing software solutions are considered as exemplary. The finding of this paper is a combined approach of such a technology database with artificial intelligence methods for information retrieval that can support the process of technology management more comprehensively than is currently possible.
New tools in minimal invasive aortic valve surgery: case report

Minimal invasive aortic valve replacement (MI-AVR) is turning a routine surgical procedure, but still, many surgeons are reluctant because of perception of some technical difficulties like the annular suture placement and the legature. We present the surgical case of a MI-AVR by using novel suturing and knotting device that could facilitate surgery and diminish technical difficulties. This is the case of a 65 years old female patient with a pathologic bicuspid aortic valve, with stenosis and prevalent regurgitation. The patient was symptomatic for dyspnea (NYHA Class II) and referred to surgery for AVR, and after obtaining informed consent, we performed MI-AVR through upper hemisternotomy (UHS) by using two new surgical devices, particularly designed for minimal invasive surgery. The first device is composed by two handpieces: one is known as RAM, and it allows the passage of the suture, with the pledget in the ventricular side, through the native aortic valve anulus after the cusps have been removed and decalcification performed. Double “U” stitches are homogeneously and symmetrically placed. The second element, called SEW-EASY is used to pass equally the double needle suture through the sewing ring of the valvular prosthesis. To conclude, in this case we have also utilized a second device, a knotting one, known as COR-KNOT, giving rise to a quick and efficient suture ligature. Postoperative course was uneventful and the patient was on good conditions after 1 year of follow-up. The present case highlights the need and evolution of technology aimed to improve, simplify and increase safety in minimal invasive surgery.
Performance Assessment of using OpenCL on FPGA Systems for ODE Solvers

Parameter optimization is a common task in various fields such as computational biology. In these scientific fields, optimization can be, e.g. based on ordinary differential equations with the computational task getting increasingly computation-intensive for increasing complexity of ODE and the parameters to determine. Hence, this raises requirements for an efficient treatment on high-performance computing architectures. In HPC, it is essential, besides an efficient implementation, to choose the best fitting architecture for each problem. Latest research has shown that FPGAs are a better accelerating device than GPUs or multi-core CPUs for specific issues. Therefore, this thesis deals with the implementation and assessment of ODE solvers optimized for FPGAs. Since FPGAs are relatively new in HPC, the thesis first explains the essential components of FPGAs and how to program them. Subsequently, the thesis expounds on the FPGA implementation of an efficient ODE solver and how it integrates into an automatic code generation to support different ODE systems. Furthermore, it illustrates the effect of the different optimizations on hardware utilization and execution time. The results are finally compared to those of CPUs and GPUs. The comparison reveals that for small problem sizes, the FPGA performs better than the CPU and almost as good as the GPU. For larger problems, both other architectures outperform the FPGA. The results give a first tendency when which architecture fits best. Consequently, this thesis builds a good foundation for further research about the usability of FPGAs for ODE solvers. This thesis did not take energy efficiency into account.
Physicochemical properties of bactericidal plasma-treated water

Plasma-treated water (PTW), i.e. distilled water (DW) exposed to low-temperature atmospheric pressure helium plasma, exhibited strong bactericidal activity against Escherichia coli in suspension even within a few minutes of preparation. This effect was enhanced under acidic conditions. The bactericidal activity of PTW was attenuated according to first-order kinetics and the half-life was highly temperature dependent. The electron spin resonance (ESR) signal of an adduct of the superoxide anion radical (O2−•) was detected in an aqueous solution using a spin-trapping reagent mixed with PTW, and adding superoxide dismutase to the PTW resulted in a loss of the bactericidal activity and weakening of the ESR adduct signal of O2−• in the spin-trapping. These results suggest that O2−• plays an important role in imparting bactericidal activity to PTW. Moreover, molecular nitrogen was required both in the ambient gas and in the DW used to prepare the PTW. We, therefore, suggest that the reactive molecule in PTW with bactericidal effects is not a free reactive oxygen species but nitrogen atom(s)-containing molecules that release O2−•, such as peroxynitrous acid (ONOOH) or peroxynitric acid (O2NOOH). Considering the activation energy for degradation of these species, we conclude that peroxynitric acid stored in PTW induces the bactericidal effect.
Quantitative Determination of Rice Moisture Based on Hyperspectral Imaging Technology and BCC‐LS‐SVR Algorithm

In this study, a method for quantitative determination of rice moisture based on hyperspectral imaging technology was proposed. First, the hyperspectral imaging system in the spectral range of 871–1766 nm was used to collect the hyperspectral images of 120 rice samples of 10 moisture grades. Support vector regression (SVR), least-squares support vector regression (LS-SVR), and bacterial colony chemotaxis least-squares support vector regression (BCC-LS-SVR) models were established to determine the moisture content by using full wavelengths spectra data. Among all the models, the BCC-LS-SVR model showed the best results. To simplify the calibration model, successive projections algorithm (SPA) was used for feature selection and the number of characteristic wavelengths was determined as 25. Principal component analysis (PCA) was used for feature extraction and the cumulative contribution rate of the first six principal components reached 99%, which could reflect most of the information of the full spectra data. Three new regression models based on the selected wavelengths were built and the results were improved obviously. The BCC-LS-SVR-SPA model got the best accuracy in prediction and calibration with of 0.980, RMSEP of 0.967%, of 0.985 and RMSEC of 0.591%. The overall results from this study demonstrated that hyperspectral image technology is feasible to detect rice moisture. Practical Applications The quality of rice has a direct relationship with the moisture content of rice. Because of the moisture content over standard, rice storage time becomes shorter and rice is easy to go bad. It's harmful to eat this rice for a long time. Traditional methods for identification of rice moisture mainly focus on the appearance of rice and depend on the feelings of professionals, which are tedious, time-consuming, expensive and greatly influenced by subjective factors. Hyperspectral imaging technology has the advantages of nondestructive, rapid, non-pollution, and so on. The results showed that hyperspectral imaging technology for the detection of the rice moisture is feasible and it can measure the moisture of rice.
Penyisihan Total Suspended Solid Dan Material Organik (Polisakarida) Dalam Air Laut Dengan Menggunakan Teknologi Membran Ultrafiltrasi

Air laut dapat digunakan sebagai salah satu sumber untuk mengatasi peningkatan kebutuhan air bersih. Salah satu pengolahannya adalah dengan desalinasi yaitu teknologi membran reverse osmosis. Tantangan terberat dalam teknologi membran ini adalah terjadinya fouling. Salah satu cara untuk mengatasinya adalah dengan pre treatment RO menggunakan membran MF dan UF. Penelitian ini difokuskan terhadap filtrasi larutan garam NaCl dengan konsentrasi bervariasi yang mengandung sodium alginat sebagai model material organik (polisakarida) dan kaolin sebagai model TSS dalam foulin membran MF dan UF. Membran yang digunakan adalah membran MF PES dan UF. Penelitian dilakukan dengan mengamati kinerja membran lewat hasil uji fluks dan rejeksi. Hasil yang diperoleh dari uji fluks menunjukkan adanya penurunan profil fluks seiring dengan meningkatnya konsentrasi garam monovalen dalam larutan. Hal ini menunjukkan bahwa seiring bertambahnya konsentrasi garam, potensi fouling dari kaolin dan sodium alginat semakin meningkat. Hasil rejeksi tidak selalu meningkat dengan penambahan konsentrasi garam dan penurunan profil fluks. Terdapat pengaruh lainnya yang mempengaruhi rejeksi seperti ukuran molekul foulant dan pori membran. Pada hasil SEM dan FTIR terlihat fouling kaolin dan sodium alginat di permukaan membran.
Can fundamental value predict stock returns? An empirical assessment of the Feltham -Ohlson model

In valuation research, two modeling approaches that have become prominent are those based on the Residua! Income Model (RIM) and those based on the FelthamOhlson framework. OMson (1995) develops a valuation model which links a firm’s fundamental value to the book value of equity, earnings and other relevant information. Feltham and OMson (1995) extend the OMson (1995) model to incorporate growth and conservative accounting. This study provides an evaluation of the Feltham-OMson (1995) model assuming market inefficiency. Analyst forecast data are obtained from the international I/B/E/S files. Financial information and share prices are obtained from the Compustat Database. Canadian T-bill rates and exchange rates are obtained from the Internationa! Financial Statistics database. All variables are scaled by the market value o f equity at fiscal year end to mitigate for heteroscedasticity. Financial firms are excluded. Following Myers (1999), the discount rate is measured as the sum of the Canadian T-bill rate and the firm’s industry risk premium. Panel data methodology with lagged values is used to determine the parameters of the linear dynamics equations. Net operating assets are found to have a negative relationship with abnormal earnings. For the firms in the sample, net operating assets are diminisMng over the time period 1990-1998. Managers are selling off assets or they are not making investments sufficient to offset the effects of depreciation.
Sustainable biobased blends from the reactive extrusion of polylactide and acrylonitrile butadiene styrene

Polymer blends containing poly(lactic acid) (PLA) and acrylonitrile butadiene styrene (ABS) with high biobased content (50%) were made by extrusion and injection molding. Two additives, one acrylic copolymer and one chain extender were used separately and in combination to increase mechanical properties. Interestingly, the combination of both the acrylic copolymer and chain extender worked to synergistically increase the impact strength by almost 600%. This was attributed to the complementary additive toughening effects which allowed increased energy dissipation of the blend at high speed testing, such as in the impact test. Morphology and rheology investigation showed that the two additives worked together to vastly change the dispersion and phase sizes, suggesting a decreased tension between the PLA and ABS. Finally, Fourier transform infrared spectroscopy supported the evidence that the epoxy groups of the chain extender undergo ring opening to react with the functional groups of the PLA. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 43771.