Miracle-dz/UniFAR-FTUs huggingface dataset:
The protective effect of Nigella Sativa oil on Penconazole induced -renal toxicity in adult albino rats: Histological, Immunohistochemical and Biochemical study

High doses of penconazole causing nephrotoxicity and renal damage. Nigella sativa (black seed) is one of the native plants. It has anti-inflammatory, antidiabetic and anti-cancerous properties.Aim: This work aimed to evaluate the effect of Nigella sativa oil on Penconazole induced renal toxicity in a rat model.Material and Methods: Sixty male adult albino rats were used . They were divided into equal four groups. Group I (control): rats were received distilled water Group II (N. sativa): rats were given orally 0.2ml N. sativa oil /100 g b. wt. three days/week for four weeks.Group III(PEN –treated): the animals were received intraperitoneally 67 mg penconazole /kg b. wt. three days/week for four weeks. Group IV(PEN+ N.sativa): rats were given penconazole (67 mg/kg b.w) and N. sativa oil (0.2ml/100 g) simultaneously three days weekly for four weeks. At the end of the experiment, kidney tissues were prepared for biochemical, immunohistochemical, light and electron microscopic studies.Results: Histological examination of penconazole treated group revealed glomerular atrophy, widening of the subcapsular space and hypercellularity of the glomerular cells. Detachment of podocytes and disruption of their processes resulted in impairment of the blood renal barrier. Tubular degeneration and necrosis were confirmed by significant decrease in Bcl2 immune marker. An increase in activity of intercalated cells of cortical collecting tubules was an indication of metabolic acidosis. Renal fibrosis was confirmed by an significant increase in α SMA and collagen fibers. Biochemical study revealed an increase in MDA level, decrease in both superoxide dismutase (SOD) and catalase (CAT). These changes were reserved by concomitant administration of Nigella sativa oil.Conclusion: The antioxidant properties of Nigella sativa could be attributed in ameliorating penconazole-induced nephrotoxicity in rats.
Signal processing in evoked potential research: applications of filtering and pattern recognition.

: The separate but closely related topics of waveform estimation by filtering and information extraction by pattern recognition are covered in this review. Because of the low signal-to-noise ratio generally encountered in evoked potential research, a variety of filtering methods have been employed for improving waveform estimation. Initially the filtering was done with analog devices but with the availability of high performance minicomputers virtually all filtering is now done digitally. Filters of various types are considered. Among them are single and multiple channel Wiener filtering, Kalman filtering, minimum mean square error filtering, maximum signal-to-noise filtering, and several types of nonlinear filters. The application of adaptive filtering techniques is also considered. In recent years there has been a continual increase in the application of pattern recognition techniques to the processing of evoked potentials. The techniques are based on statistical decision theory and the underlying basis of these procedures is reviewed. The technique of linear stepwise discriminant analysis is considered as well as the use of general discriminant functions of linear and quadratic types. Applications of these procedures to psychophysiological testing are discussed with particular emphasis on auditory and visual event-related potentials.
A New Semantics for JML Signals Clauses

JML, which stands for ”Java Modeling Language”, is a behavioral interface specification language designed to specify Java classes and interfaces. JML uses syntactic sugar to make specifications easier to read and write. In this paper, we reveal that the current JML desugaring of signals clauses has a somewhat counterintuitive meaning. A new semantics is proposed that is more intuitive. Special attention is given to the desugaring of signals clauses that are spread over different behavior blocks connected by the keywords also or and. The described desugaring ensures behavioral subtyping. The consequences of the new semantics are worked out.
Distribution of selected cardiovascular disease risk factors among hemodialysis patients: a cross-sectional study, Cameroon

Objective: To determine the distribution of conventional cardiovascular disease risk factors in hemodialyzed patients in a novel Cameroonian regional hemodialysis center. Methods: This was cross-sectional study carried out at the hemodialysis center of the Garoua Regional Hospital during the period April to August 2014. Sociodemographic, clinical, anthropometric and biochemical data were assessed. Results: Our sample population constituted 35 patients with stage V chronic kidney disease (CKD) undergoing hemodialysis. Among them, 74.3% were physically inactive while 22.9% and 2.9% presented with alcohol and tobacco consumption, respectively. The prevalence of hypertension, diabetes, dyslipidemias, overweight and obesity were estimated at 91.4%, 22.9%, 85.7%, 25.7% and 14.8%, respectively. There was a significant difference between men and women concerning the mean values of diastolic blood pressure (p = 0.036) and HDL cholesterol (p = 0.024). Moreover, the mean systolic (P = 0.028) and diastolic (P = 0.005) blood pressures were significantly highest in patients with less than a year of hemodialysis. Conclusion: Our findings suggest that dyslipidemias and other cardiovascular disease risk factors frequently occur in hemodialyzed patients in our setting. Keywords: Cardiovascular Diseases, Chronic Kidney Disease, Renal Dialysis, Risk Factors
Acute Phase Proteins in Staphylococcus aureus Positive Milks

In this study, acute phase proteins including haptoglobin, serum amyloid A, fibrinogen, albumin and total protein levels were investigated in cows with Staphylococcus aureus (S. aureus) positive subclinical mastitis. Healthy Jersey cows in lactation constituted the animal materials of the study. CMT test were applied to detect subclinical mastitis. In 21 milk samples collected from cows with subclinical mastitis, S. aureus was identified by PCR after bacteriologic isolation. These milk samples formed the study group. Healthy milks in which no bacteriological growth was observed were used as the control group. Elevations in haptoglobin (Hp) and serum amyloid A (SAA) levels in infected milk group compared to control milk group were statistically determined as p<0,05. Although an increase was observed in fibrinogen (Fb), total protein (TP) and albumin (Alb) levels, the variations were not statistically significant. In conclusion, in infected milks, total protein elevation is an expected result due to the presence of somatic cell and bacteria. In the present study, an increase was determined in total protein level, but it had no statistical significance. However, a significant increase was determined regarding haptoglobin and serum amyloid A in infected milk samples. This suggests that haptoglobin and serum amyloid A are more sensitive indicators in subclinical mastitis and may be beneficial in clinical practice.
An Efficient Channel Estimation Technique in NB-IoT Systems

In this paper, a novel low-complexity channel estimation algorithm with estimation error suppression based on the conventional least squares (LS) method is proposed for downlink narrowband internet of things (NB-IoT) systems. This algorithm suppresses channel estimation error by employing additional operations on conventional LS method without exploiting extra frequency-band resources. The potentiality of the proposed algorithm is substantiated through extensive simulations in terms of channel mean square error (MSE) and block error rate (BLER) against signal-to-noise ratio (SNR). Simulation results vindicate that our proposed algorithm outperforms the conventional LS algorithm.
Traffic Flow Simulation Based on Adaptive Agent

This paper describes the driver's vehicle behavior as the response of an intelligent body according to the environment and situation, and describes the characteristics of macro-traffic flow through the response of each independent intelligent body, providing a basis for intelligent driving and intelligent control. First, the adaptability description is carried out with the behavior of single-lane vehicles. Three driving states are defined and their driving behaviors and decision-making rules are analyzed based on the driver's expectation objectives. The simulation is realized by using the mathematical description the Boid model method of Couzin et al. [6][7][8]. The simulation results show that the behavior change of the individual adaptive driving vehicle is completely consistent with the characteristics of the macro-traffic flow, and the cooperative characteristics of the group intelligence are presented. Individual driving vehicles show good adaptability and self-drive to the change of environment and current traffic condition. The change of individual driving behavior of the vehicle will have an impact on the adjacent local vehicle individuals. The change of traffic density affects the speed of traffic flow. Bad driving behavior will affect the speed of local or even the whole traffic flow on the road, which will lead to the closing and splitting of the vehicle queue. In serious cases, the vehicle queue will stop and stop, leading to the decrease of the road capacity.
The Research on Identity Recognition Based on Multi-Biological Feature Awareness

With the rapid development of information technology in modern society, the role of user identity authentication technology in people's lives has become increasingly important. Biometric technology has become the most promising and most widely used information security technology because of its uniqueness, non-replicability, and lack of memory. With more and more research on biometrics technology, identity authentication technology of single biometrics has been widely used in life. However, due to the single biometric technology used, the collection of data is vulnerable to environmental impacts and other reasons, it is difficult for the technology to play its advantages in practical applications. Therefore, this paper proposes a method of using multiple biometrics to authenticate users, so as to solve the problem of user identity authentication conveniently, quickly, and safely. Finally, experiments show that the proposed multi-biometric user identification method is feasible.
An ERP Study to Evaluate the Quality of Speech Processed by Wiener Filtering

Speech enhancement algorithms (SEAs) play a crucial role in speech signal processing. Wiener filtering (WF) as one of the most popular SEAs introduces undesired speech distortion to the enhanced signals. It is important to objectively examine the perception of the enhanced speech in different conditions (i.e., signal-to-noise ratio (SNR) level). The purpose of this work was to investigate whether the mismatch negativity (MMN) response based on the event-related potential (ERP) could objectively evaluate the quality of speech processed by WF. There were two deviant stimulus types: the noisy stimuli corrupted by a steady-state noise at SNR of -5 and +5 dB and their corresponding enhanced stimuli processed by WF. Experimental results showed that the MMN amplitude elicited by the noisy stimuli at -5 dB SNR was larger than that at +5 dB SNR, accounting for the effect of SNR level on the quality of speech. The results also demonstrated that the enhanced stimuli at -5 dB SNR evoked a shorter MMN latency and a larger MMN amplitude than that at +5 dB SNR, reflecting the effect of SNR level on the quality of WF-processed speech. The MMN may be potentially used as an objective measure for evaluating the quality of speech processed by WF.
Identifying the Ozone Weekend Effect in the air quality of the northern Andean region of Ecuador

The Weekend Effect (WE) is a phenomenon that occurs in some urban areas, characterized by increased concentrations of O3 and decreased emissions of its precursors (NOx and VOC) during weekend days, in comparison to weekdays. The study of the WE is relevant for understanding the behavior of pollutants; and hence, for air quality control. We analyzed the hourly records of the period 2005– 2012, from 8 stations of the air quality network from the Distrito Metropolitano de Quito (northern Andean region of Ecuador). Both for each station and year, 3 mean-daily profiles were obtained for CO, NO2, PM2.5 and O3, corresponding to weekdays, Saturdays and Sundays. The CO, NO2 and PM2.5 profiles from Centro (historic center of Quito) and Belisario (center-north) stations, declined on Sundays. However the O3 profiles were higher on Saturdays and Sundays. The O3 8-h mean concentrations of Sundays were higher in Belisario (19.7–31.1%) and Centro (11.7–18.4%), in comparison to weekdays. These results indicate the presence of the WE around these 2 stations, which probably are located in a VOClimited region for photochemical O3 production.
Simulação computacional de dispositivos de mistura em câmara de combustão para gases de carbonização

O carvão vegetal proveniente de ﬂorestas plantadas é uma fonte de energia renovável utilizada na siderurgia do Brasil, todavia, em sua produção há liberação do gás de pirólise, que pode ser considerado um gás com baixo poder calorífico inferior. A sustentabilidade da produção de carvão vegetal tem demandado a queima destes gases, podendo ser, inclusive, uma condicionante ambiental. Neste artigo foi avaliado o desempenho de diferentes dispositivos de mistura para câmara de queima, sistema que permite mitigar os impactos ambientais decorrentes da carbonização, assim como o possível aproveitamento da energia térmica na secagem da madeira e geração de energia elétrica. Um sistema de queima de gases existente foi utilizado como referência, sendo determinados a composição, vazão dos gases e temperaturas de trabalho para calibração de modelo em dinâmica dos ﬂuidos computacional. O modelo utilizado consiste nas equações diferenciais de conservação de massa, quantidade de movimento, energia e de espécies químicas, sendo empregado nos estudos de otimização de diferentes dispositivos de mistura. Dentre os dispositivos estudados (AC), o AC5 apresentou-se mais eficiente quanto ao aproveitamento do volume físico da câmara, tendo menor porcentagem de zona morta, representando ganho de 5% no tempo de residência, quando comparado ao AC1, dispositivo usado sistema de referência. Verificou-se por meio das distribuições espaciais da fração de volume de CO e O2, e das linhas de corrente, que os dispositivos de mistura internos são fundamentais para uma melhor mistura entre o combustível e o comburente e, consequentemente, produzir queima de gases com melhor qualidade.
Asymptomatic Phytoplasma Reveal a Novel and Troublesome Infection

Asymptomatic infections are by their nature challenging to study and even more difficult to monitor across broad geographical ranges, particularly as methods are reliant on expensive molecular techniques. The plant pathogen that causes Witches’ Broom disease of lime (Candidatus Phytoplasma aurantifolia) is a major limiting factor in lime production across the Middle East and was recently detected in Brazil, but without the typical symptoms from the Middle East. Here, we discuss the difficulty of monitoring asymptomatic infections and highlight the threat posed by highlight future outbreaks. Asymptomatic infections have important implications for understanding the evolution of pathogens within perennial hosts. We use three model systems of asymptomatic infections: (i) a Phytoplasma and (ii) a bacterial infection of lime (Citrus aurantifolia) and (iii) an “out-group” Phytoplasma of Cassava (Manihot esculenta) to demonstrate consistency across divergent hosts. We found that although all plants in the study were intentionally infected, assays typically did not confirm this diagnosis. Emergent technologies monitoring gene expression could be used to both study novel biology associated with asymptomatic infections and develop monitoring technologies. We highlight the difficulty of monitoring asymptomatic infections in possible future outbreaks and have important implications for understanding the evolution of pathogens within perennial hosts.
Atomistic and holistic approaches to human reliability analysis in the US nuclear power industry

Abstract A variety of methods have been developed to generate human error probabilities in the US nuclear power industry. When actual operations data are not available, it is necessary for an analyst to estimate these probabilities. Most approaches, including THERP, ASEP, SLIM-MAUD, and SPAR-H, feature an atomistic approach to characterizing and estimating error. The atomistic approach is based on the notion that events and their causes can be decomposed and individually quantified. In contrast, in the holistic approach, such as found in ATHEANA, the analysis centers on the entire event, which is quantified as an indivisible whole. The distinction between atomistic and holistic approaches is important in understanding the nature of human reliability analysis quantification and the utility and shortcomings associated with each approach.
Darkstar: the java game server

So, you have a great idea for the next big multiplayer game. Maybe it's a virtual world based on your favorite sci-fi television show. Or maybe it's an online bowling league for you and your friends. Regardless, the challenge of building a networked multiplayer computer game goes far beyond having a great idea. It can be so significant that it prevents great games from becoming reality. Darkstar breaks down this barrier of complexity. It provides an easy-to-use library of functions that handles the challenging aspects of networked game development for you. Further, it provides a robust, industrial-strength server that can scale with your game as it grows in popularity. With Darkstar, you can quickly turn your idea for a multiplayer game into a (virtual) reality.
Practical analysis of encrypted network traffic

Andrew M. White: PRACTICAL ANALYSIS OF ENCRYPTED NETWORK TRAFFIC (Under the direction of Fabian Monrose) The growing use of encryption in network communications is an undoubted boon for user privacy. However, the limitations of real-world encryption schemes are still not well understood, and new side-channel attacks against encrypted communications are disclosed every year. Furthermore, encrypted network communications, by preventing inspection of packet contents, represent a significant challenge from a network security perspective: our existing infrastructure relies on such inspection for threat detection. Both problems are exacerbated by the increasing prevalence of encrypted traffic: recent estimates suggest that 65% or more of downstream Internet traffic will be encrypted by the end of 2016. This work addresses these problems by expanding our understanding of the properties and characteristics of encrypted network traffic and exploring new, specialized techniques for the handling of encrypted traffic by network monitoring systems. We first demonstrate that opaque traffic, of which encrypted traffic is a subset, can be identified in real-time and how this ability can be leveraged to improve the capabilities of existing IDS systems. To do so, we evaluate and compare multiple methods for rapid identification of opaque packets, ultimately pinpointing a simple hypothesis test (which can be implemented on an FPGA) as an efficient and effective detector of such traffic. In our experiments, using this technique to “winnow”, or filter, opaque packets from the traffic load presented to an IDS system significantly increased the throughput of the system, allowing the identification of many more potential threats than the same system without winnowing. Second, we show that side channels in encrypted VoIP traffic enable the reconstruction of approximate transcripts of conversations. Our approach leverages techniques from linguistics, machine learning, natural language processing, and machine translation to accomplish this task despite the limited information leaked by such side channels. Our ability to do so underscores
Accident and disease prevention in working life: Common grounds and areas for mutual learning

Globally, there are more than six times more fatalities caused by a poor working environment than due to occupational accidents. In this paper we compare the basic strategies involved in accident and disease prevention. We find that the basic thinking is the same. The preventive strategies involve control of hazards in a hierarchy from elimination to application of personal protective equipment. Also, the Norwegian regulation on internal control of HSE is applicable for both accident and disease prevention, involving the idea of continuous improvement. Still, the nature of the hazards differ, as well as the possible consequences. In the area of occupational safety, the hazards are usually visible and the consequences of accidents are immediate. In the area of occupational health, the hazards are often invisible and the consequences of exposure delayed. There is a potential for better integration of the two areas in practical management, and a potential for mutual learning from concepts and models in the two fields. that the workers in this sector have increased risk for lung diseases (Bergdahl et al., 2004; Robinson, Petersen, Sieber, Palu, & Halperin, 1996; Vermeulen, Heederik, Kromhout, & Smit, 2002). Also in Norway the statistics from NOA shows that workers in the construction industry have more respiratory complaints, and more declared work related respiratory complaints than the national mean (Aagestad, 2015). Recent studies have also detected an association between exposure and an increased risk of COPD in the construction industry (Fell, Aasen, & Kongerud, 2014). In addition 59% of construction workers state that that they inhale smoke, dust or exhaust in their work situation (NOA, 2017). The purpose of this paper is to compare the main strategies for the prevention of occupational diseases and occupational accidents. 2 PREVENTION OF OCCUPATIONAL DISEASES 2.1 Exposure assessment The traditional approach for chemical risk assessment is to compare the exposure level of the chemical agent to their Occupational Exposure Limits (OELs). These OELs were established from late 19 century (Jayjock MA, 2000). Still this approach is regarded to be the best practice for risk assessment for chemical agents and noise. These limit values are given for occupational exposures during 8 hours shift, and there is guidelines on how
Question Features Exaction Method Based on Syntactic and Semantic Information

This paper analyzes the current question parsing techniques in Question Answering(QA),and proposes a question feature exaction method based on syntactic structure and semantic information. The method parses question trunks based on syntax structure,then extracts characteristics of question from the semantic information point of view and uses modified Bayesian algorithm in question classification. Experiments show that this method can raise the accuracy of the question classification.