Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic decision making system with environmental and traffic data

By using computer vision and machine learning methods, driving lane detection and tracking, the position of the vehicles in the vicinity, their speed and direction will be determined through real-time processing of images taken from the traffic camera. Processing of the collected data using artificial intelligence and fuzzy logic and to calculate the data within the scope of “game theory” and to implement the dynamic control of the vehicle in the light of calculated data is planned. In addition to that, the designed system can also function as a driver assistant for non-autonomous vehicles with an appropriate user interface. First, the positions of the vehicles and driving lanes will be detected and monitored using computer vision and machine learning methods. Then, the vehicle speeds will be calculated by taking advantage of the historical data of the vehicle positions in the surrounding area from the previous observations, and the location estimation will be made by creating probability distributions of where each vehicle will be in the future. With the position estimation and the obtained speed information, it will be ensured that the vehicle is in the safest position in the transportation process to the destination and that it travels again at the safest speed.
Potentiometric Sensor Based on an Ion-Imprinted Polymer for Determination of Copper

A novel potentiometric sensor based on an ion-imprinted polymer (IIP) has been developed for selective recognition and determination of Cu(II) ions. The IIP is synthesized by precipitation polymerization using Cu(II) ions as template, methacrylic acid as functional monomer and trimethylolpropane trimethacrylate as cross-linking agent. The IIP based plasticized poly(vinyl chloride) membrane electrode exhibits a Nernstian response (27.5 mV/decade) to Cu(II) ions over a wide concentration range of 1.0 x 10(-7)-1.0 x 10(-2) mol/L with a detection limit of 4.3 x 10(-8) mol/L. The selectivity of the electrode has been characterized and the logarithmic Nikolskii coefficients for Cu(2+) over Ca(2+), Zn(2+), Cd(2+), Pb(2+) and Al(3+) have been determined as -3.40, -3.75, -2.90, -2.45 and -3.87, respectively. The sensor shows rapid response, good reproducibility and satisfactory long-term stability.
QTL analysis associated to single nucleotide polymorphisms (SNP) involved in the dairy phenotype of Holstein cattle

The aim was to identify QTLs associated with single nucleotide polymorphisms (SNPs) whose action contributes to the productive, reproductive and health phenotypic development of Holstein dairy cattle. 341 QTLs located in 120 genes of the Bos taurus UMD_3. 1.1 genome and associated with 189 SNPs with effects on productive (FY, NM, MY, MTCAS, MBLF and PL), reproductive (CONCRATE, DPR, EMBSUR, DAYOPEN and CONCEPT) and health traits (SCC, BTBS and RESRATE) were identified. SNPs were verified in the dbSNP-NCBI database, according to which 42 % were located in introns. The Jvenn platform revealed that the SNPs rs135744058, rs110828053 and rs109503725 were common in all three traits. The network of correlations between traits and genes generated by MetScape (Cytoscape 3.4), showed a positive correlation between PL, DPR, DAYOPEN, CONCRATE and CONCEPT, and a negative correlation of FY with PL, NM, DPR and CONCRATE. The functionality of each gene was validated in the Gene-NCBI and UniProt databases, and ClueGo (Cytoscape 3.4) was used to select functional pathways with a significance value less than 0.05, which rendered an intertwining between the development of the mammary gland, the activation of the immune system and the response to steroid hormones evident, the GH Rev Mex Cienc Pecu 2020;11(4): 1192-1207 1193 gene being the one that directs this functionality. Although the genetic panorama shows that there is an antagonism between productive and reproductive traits, the functional genetic activity due to the 189 SNPs analyzed exhibits an interwoven action in ontological pathways that influence the production processes, as well as in reproductive and health pathways.
Assessing the Predictive Power of Online Social Media to Analyze COVID-19 Outbreaks in the 50 U.S. States

As the coronavirus disease 2019 (COVID-19) continues to rage worldwide, the United States has become the most affected country, with more than 34.1 million total confirmed cases up to 1 June 2021. In this work, we investigate correlations between online social media and Internet search for the COVID-19 pandemic among 50 U.S. states. By collecting the state-level daily trends through both Twitter and Google Trends, we observe a high but state-different lag correlation with the number of daily confirmed cases. We further find that the accuracy measured by the correlation coefficient is positively correlated to a state’s demographic, air traffic volume and GDP development. Most importantly, we show that a state’s early infection rate is negatively correlated with the lag to the previous peak in Internet searches and tweeting about COVID-19, indicating that earlier collective awareness on Twitter/Google correlates with a lower infection rate. Lastly, we demonstrate that correlations between online social media and search trends are sensitive to time, mainly due to the attention shifting of the public.
Acidity and Hydrophobicity of Several New Potential Antitubercular Drugs: Isoniazid and Benzimidazole Derivatives

Hydrophobicity values (log Po/w )d etermined both by potentiometry and by the conventional shake-flask method and aqueous pKa values obtained by potentiometry for seven isoniazid and nine benzimidazole derivatives are presented. Several of these compounds have strong hydrophilic or hydrophobic character, and some of them show two or more ionizable sites, sometimes very acidic or very basic. These facts have compelled us to work near the limits of the potentiometric technique, and therefore, a critical evaluation of the results obtained in these extreme working conditions is presented. Particularly, details about the potentiometric determination of log Po/w values of the most hydrophilic and most hydrophobic compounds are clearly described.
Influencing Factors and Countermeasures to Promote the Large-scale Development of Rural Solar Houses in China

The development and utilization of renewable energy, especially solar energy, is an important way to solve the problem that China’s rural conventional power grids cannot cover remote rural areas. It is also an inevitable requirement of China’s rural development strategy. This article explores the influencing factors of Chinese farmers’ vigorous promotion of the use of solar houses, studies relationships among perceived value, farmer’s attitude and willingness to convert traditional houses into solar houses. Using data collected by a questionnaire from 413 rural households in Chongqing, China, the results show that perceived value has a significant and positive effect on farmer’s attitude and willingness to convert traditional houses into solar houses. Most importantly, the results of this research show that farmers’ attitude partially mediates the effects of perceived value on willingness to convert. Finally, the study also proposes relevant suggestions for policy makers, marketing managers and further research.
Digitalization in hydropower generation: development and numerical validation of a model-based Smart Power Plant Supervisor

The paper presents the development of a model-based Smart Power Plant Supervisor, a digital tool targeting the optimization of the operation and maintenance of hydroelectric units to improve ancillary services provision to the power system. The paper focuses on a control-oriented modelling methodology which allows integrating the operational parameters of the hydroelectric unit in an optimization algorithm steering the advanced control of the units. The technique to develop analytical functions representing the behaviour of the hydropower plant is presented and validated by comparing numerical simulations with measurements of the real time operation of the run-of-river hydropower plant Vogelgrun. The results show a good performance of the modelling technique able to correctly predict the power generation of the power plant over one month of operation.
Influence of flow patterns on the performance of straight-through labyrinth seals. Numerical study and validation against experimental data

When numerically simulating the performance of a complete Francis turbine, it is common practice to omit the seals to save computing power. Volumetric and friction losses are usually taken into account using empirical values. There is abundant literature on the topic, but all analytic formulations rely on widely variable empirical coefficients. To overcome the uncertainty in determining volumetric losses, a detailed analysis of the sealing is necessary. Focusing on straight seals and configurations with cavities, in-house experimental data and numerical simulations have been used to show that few geometric parameters play a fundamental role in defining the flow patterns inside the clearance and even more so inside and between cavities. As is to be expected, the seals effectiveness is heavily influenced by these flow structures. It is also shown that certain methods of dealing with near-wall flow structures are better suited than others for the estimation of the discharge behaviour when compared to experimental results. Even though in the framework of the RANS equations CFD has proven to be a reliable tool for a wide range of geometries, further investigations are necessary on deep cavities. For aspect ratios above 0.75, the flow patterns inside the cavity change drastically, leading to bad convergence rates of the solver and, more important, to a considerable misalignment between numerical and experimental results. Lid-driven cavity flow is known to be a complex problem in 2D domain, and in this case, the flow becomes three-dimensional due to the tangential velocity induced by rotation. However, the reasons behind the problems in CFD analysis are not entirely clear. Given the observed variations of the flow structures inside sealings with different geometric parameters, it becomes clear why a simplified, generic formulation is very difficult to obtain, if not by adopting empirically defined coefficients which are needed to tune the analytical model.
Tracking System Using Artificial Neural Network for FPGA Cart Follower

Wheelchair users may have difficulty carrying their luggage while travelling. A proposed solution is introduced based on the problem stated. A tracking system for cart followers introduced to improve wheelchair mobility while transporting their luggage. The cart will track and follow the wheelchair at an appropriate distance. A Camera acts as input to enable the cart to track and follow the wheelchair. Pixy CMUcam5 is used to detect the predefined colour code (CC) in this project. The visual-based sensor gathered the information of the CC, which situated behind the wheelchair and translated the collected data into relative position information, such as distance and skew angle, which helps the cart in following the wheelchair. This translation is done in the Artificial Neural Network (ANN). The type of ANN used is a Multilayer perceptron (MLP) with the Levenberg-Marquardt training algorithm. Log sigmoid (Logsig) and Pure linear (Purelin) activation functions used in the hidden and output layer, respectively. The errors for distances and angles after computed with ANN are presented accordingly in Simulink. The MSE value obtained is 0.14007. The ANN implemented in the Field Programmable Gate Array (FPGA). The implementation of the ANN on the FPGA done through software and hardware configuration. The time taken for hardware implementation is faster than software due to parallel computations. The error value for output distance is less than 0.8000, and 0.3000 for the output angle during the simulation.
An Auto-Contouring Method for Kidney based on SVM

In adaptive radiotherapy planning, the contour map of the treatment target area is still the most difficult problem. Usually this work is done by a professional radiologist oncologist, which is very time-consuming and labor-intensive. In order to solve this problem, this paper proposes an automatic contour method based on support vector machine. Experiments were conducted on the lower abdomen MR data set of eight patients. In the experiment, the simulated data was only used to train the classifier, and the treatment day images were used to evaluate the performance of the classifier. DSI was used to compare the manual contour and automatic contour of the kidney. The experiment showed that, The automatic contour method based on support vector machine has better classification performance than most classification algorithms. Among the eight sets of results, the DSI value of the six sets of results is 1, and the smallest DSI value is also greater than 9.423.
Assistive devices for the people with disabilities enabled by triboelectric nanogenerators

According to data released by the World Health Organization, more than one billion people in the world experience some form of disability, in which they face all kinds of inconveniences. As a practical tool to help people with disabilities participate in social life, assistive devices for the people with disabilities play an important role in their daily lives. As an effective electromechanical signal conversion technology, triboelectric nanogenerator (TENG) has been successfully applied to various types of biosensors. This review aims to provide an overview of the development of assistive devices for the people with disabilities based on TENG with five categories: hearing, vision, pronunciation, gustation and limb/joint, according to the classification method of the impaired part. Meanwhile, a human–computer interaction system for the people with disabilities is also investigated. Finally, the prospect and potential challenges of this new field are discussed.
Investigation of sediment erosion phenomenon for different blade angle distribution in Francis runner

Wear and tear of hydraulic turbine due to sediment erosion is one of the major problems in hydropower plants located in the Himalayan and Andes regions. High sediment concentration in water of such areas wears down the mechanical components rapidly which causes significant operational challenges. In the present work, a prototype high head Francis runner with speed number 0.32 has been considered as reference case and other designs have been obtained modifying the blade angle distribution with same hydraulic parameters. Full turbine steady state numerical calculations were carried out at the best efficiency point and corresponding performance and erosion pattern are observed. Hydraulic efficiency and sediment erosion rate density are compared for the different cases taken into consideration. Sediment erosion analysis gives an indication of relative erosion intensity and critical zones of erosion damage in runner. Erosion was observed at the inlet near hub and shroud region and was mostly concentrated at the outlet of runner blades for all cases, where relative velocity is higher. Numerical results from CFD are also compared with the actual eroded turbine from the powerplant.
Serological and Molecular characterization of Bacterial isolates using 16S Ribosomal DNA Restriction Analysis from soil sediments of Kotumsar Cave Ecosystem, Chhattisgarh, India

Bacterial communities exist everywhere in the universe so in the caves. The ever increasing human activities inside any cave, in the form of ecotourism exert a major impact on its native microbial communities, which often stops its growth and pollutes the whole ecosystem. The situation is often found to be responsible for producing some human pathogenic bacteria inside it, which might pose a threat of infection to the other tourist. Kotumsar cave is a well known tourist pulling limestone cave of central India. In the present study the soil bacterial communities earlier isolated and characterized from different microhabitats of Kotumsar cave have been further confirmed by molecular identifications by applying 16S rDNA analysis and serotyping. All bacterial strains were also assayed for antibiotic resistance. Among the tested strains, support the PIB-win results and also shows the maximum resistance (about 69.23%) to Vancomycin and Polymyxin B. © 2014 Elixir All rights reserved ARTIC LE INF O Article h istory: Received: 29 July 2013; Received in revised form: 24 January 2014; Accepted: 12 February 2014;
Students metaphoric perceptions regarding the concept of distance education during the pandemic

The aim of this study is to examine the views of students at different education levels on the concept of distance education through metaphors. In this study, the phenomenological design was used in accordance with the nature of qualitative research. The participants of the study, for whom the ethical rules were taken into account, consisted of 63 gifted students in total studying at primary and secondary school levels. In the collection of data, each participant was asked to fill in the form containing an open-ended item for the concept of distance education. The data obtained from the students were later analysed using the content analysis technique. When the relevant metaphors were examined, a total of 63 different categories were revealed. Depending on these categories, it has been observed that the concept of distance education is represented through different metaphors. According to the findings, it was determined that primary and secondary school students simulated the concept of distance education to different metaphors such as speaking class, longing for friends and intelligence cube. Key words: Metaphor, perception, phenomenology design, distance education, students.
LEXICAL DEVELOPMENT ACROSS SECOND LANGUAGE PROFICIENCY LEVELS IN INDIAN CONTEXT: AN EXPLORATORY STUDY

The present study was investigated how second language (L2) productive vocabulary develops over time by targeting multiple dimensions of word knowledge. The research question addressed were a) Is there a difference in the rate of lexical variety between learners of different proficiency level? b) Is there a difference in the rate of lexical density between learners of different proficiency level? c) Which kind of lexis features more in both the proficiency level? The study drew on a 2071word written corpus produced by 10 intermediate and secondary level learners from Hyderabad regional school, their L2 is English. They were 13 year old (8 th grade) and 15 years old (10 th grade) English learners. Data analyses were based on type token ratio formulated by Guiraud, 1957 was applied for finding the lexical variation between two groups, and Ure’s method was used to find out lexical density between two groups. Findings indicate that learners’ written vocabulary did not have significant difference in their rate of lexical variety and density according to their difference in proficiency level. Contradictory to the researcher’s hypotheses 8 grade pupils were more proficient than 10 th grade pupils. 10 th grade pupils outperformed 8 th grade in using nouns, adjectives and adverbs except in verb which shows a less difference regarding their proficiency level.
A Test for State-Dependent Predictive Ability based on a Markov-Switching Framework

This paper proposes a new test for comparing the out-of-sample forecasting performance of two competing models for situations in which the predictive content may be state-dependent (for example, expansion and recession states or low and high volatility states). To apply this test the econometrician is not required to observe when the underlying states shift. The test is simple to implement and accommodates several different cases of interest. An out-of-sample forecasting exercise for US output growth using real-time data illustrates the improvement of this test over previous approaches to perform forecast comparison.
Power Quality Improvement in PV Flyback Microinverter using Adaptive Fuzzy-PR Controller

this project presents an power quality improvement in PV Flyback microinverter using adaptive fuzzy-PR controller. The proposed control strategy consists of the proportional-resonant (PR) controller with fuzzy logic controller. Compared to the conventional control strategy using the proportional-integral controller, the PR controller with HC and fuzzy logic controller provides a higher system gain at the fundamental and harmonic frequencies of the grid without using a high gain in both operation modes. Then, it enhances the tracking speed and disturbance rejection performances satisfied, By applying fuzzy logic controller yielded from the proposed operation mode selection, the disturbance rejection is achieved more effectively, and the control burden is reduced. Finally, the simulation and experimental results were shown to verify the tracking speed and disturbance rejection performances of the proposed control strategy.
Adaptive Observation of Emerging Cyber Attacks targeting Various IoT Devices

For years, honeypots have been a valuable tool for observing cyber attacks. But in the age of Internet-of-Things (IoT), where various kinds of devices are being connected to the Internet, honeypots need to achieve diversity and interactivity. In this paper, we propose X-POT, an adaptive honeypot framework that emulates various IoT devices while maintaining a certain level of interactivity. We use components to observe attacks on all TCP ports and by conducting an Internet-wide scan of relevant hosts, we collect responses from real devices. We then selectively choose them as honeypot responses and observe attacks targeting vulnerable IoT devices. We implemented an HTTP honeypot with X-POT framework and exposed it on the Internet for 2 months. We observed 4,729,097 HTTP requests on 64,912 ports and captured 1,276 malware samples. Moreover, we were successful in observing attacks targeting different services such as Docker API and CouchDB. We compared our system with well-known monitoring systems and obtained 669 types of attack defined by an open source Intrusion Detection System, which is up to 2.2 times higher than other systems, and collected 284 malware samples, which is up to 3.5 times higher than other systems. To this end, we reveal our malware datasets for interested researchers.