Miracle-dz/UniFAR-FTUs huggingface dataset:
Can taxonomic distinctness assess anthropogenic impacts in inland waters? A case study from a Mediterranean river basin

SUMMARY 1. It is increasingly recognised that adequate measures of biodiversity should include information on the ‘relatedness’ of species within ecological assemblages, or the phylogenetic levels at which diversity is expressed. Taxonomic distinctness measures provide a series of indices to achieve this, which are independent of sample size. Taxonomic distinctness has been employed widely in marine systems, where it has been suggested that this index can provide a reliable measure of anthropogenic impact. 2. We tested the behaviour of three related taxonomic distinctiveness indices (Average Taxonomic Distinctness, D + ; Variation in Taxonomic Distinctness, K + ; and Total Taxonomic Distinctness, sD + ) in relation to putative levels of anthropogenic impact in inland waters and their potential utility in environmental monitoring, using an extensive data set for aquatic beetles from the south-east of the Iberian Peninsula. 3. Taxonomic distinctness measures were not able to identify human disturbance effects and there were no clear relationships between these new biodiversity measures and the disturbance level recorded at individual localities. Furthermore, the taxonomic distinctness measures used were apparently less sensitive to the effects of anthropogenic impact than other diversity metrics, such as species richness and rarity. 4. We conclude that taxonomic distinctness indices may not always perform as well as other metrics in the assessment of environmental quality. In addition, taxonomic distinctness measure should be interpreted with caution, as their performance and ability to detect anthropogenic disturbance may depend on the phylogenetic structure of sampled taxa within a region, and their evolutionary and ecological history.
LOW SIDELOBE COSECANT-SQUARED PATTERN SYNTHESIS FOR LARGE PLANAR ARRAY USING GENETIC ALGORITHM

A cosecant-squared radiation pattern synthesis for a planar antenna array by using the genetic algorithm (GA) is presented. GA makes array synthesis flexible to achieve two desired features, namely, low peak side lobe level (PSLL) and small deviation (ripples) in the shaped beam region. In order to obtain a desired csc2 pattern with the PSLL constrained, GA optimizes both the excitation amplitude and phase weights of the array elements. Dynamic range ratio (DRR) of the excitation amplitudes is improved by eliminating the weakly excited array elements from the optimized array without distorting the obtained pattern. To illustrate the effectiveness and advantages of GA, the beam pattern with specified characteristics is obtained for the same array by using particle swarm optimization (PSO). Results show that the performances of GA and PSO are comparable when dealing with small-tomoderate planar antenna arrays. However, GA significantly outperforms PSO on large arrays. Moreover, numerical results reveal that GA is superior to PSO in terms of cost function evaluation and statistical tests.
Impact of broken cells of lactococci or propionibacteria on the ripening of Saint-Paulin UF-cheeses: extent of proteolysis and GC-MS profiles

UF-cheeses have been successfully developed in many countries. However, proteolysis and the general extent of ripening were shown to be far slower compared to traditional varieties. The absence of starter lysis has been cited as a plausible explanation. In this work, propionibacteria and lactococci cells were disrupted using a new pilot homogenizer. Crude broken suspension (CBS), or cell-free extract (CFE), obtained after centrifugation, were added to UF-St Paulin retentate (concen- tration factor 6) made with a usual lactic starter. RO water was added to the control. Proteolysis was estimated by NCN, NPN and free amino acids. Neutral volatile compounds were determined by GC- MS. A low extent of ripening was noted in the control and the absence of starter lysis was effectively proved using immunodetection of lactococci cytoplasmic proteins. The addition of lactococci CBS or CFE increased free amino acid content (1.5 to 3 times) whereas propionibacteria CBS or CFE exhibited no significant increase, even when cheeses were ripened at 20 o C instead of 12 o C. By con- trast, addition of propionibacteria CBS generated a significant increase in several volatile compounds like alcohols and ketones, whereas CFE did not, showing that the presence of live cells was required to form these compounds. CBS or CFE of lactococci did not significantly change the volatile com- pound profile. In conclusion, it was possible to influence the ripening of UF-cheese by the addition of crude broken bacterial cell suspensions. Other strains and species should now be investigated. ultrafiltration / UF-cheese / GC-MS profile / broken cells / ripening / proteolysis / Lactococcus / propionibacteria
COMPACT DUAL-BAND MIMO ANTENNA SYSTEM FOR LTE SMARTPHONE APPLICATIONS

—The design of an eight-port MIMO antenna at the sub-6-GHz (LTE 42/43 and 46) bands for ﬁfth-generation (5G) smartphone is presented. First, based on the Babinet’s principle, a microstrip slot antenna (MSA) is designed from its counterpart complementary structure, microstrip patch antenna (MPA) to operate over the LTE 46 band. In order to make the MSA to operate at the speciﬁed three LTE bands, a proposed single antenna, namely RMSA, is achieved by adding a strip-ring resonator within the grounded slot of MSA which shows a good measured impedance bandwidth ( S 11 ≤ − 6 dB) of 3 . 28 ∼ 3 . 84 GHz and 5 . 14 ∼ > 6 . 0 GHz. Then, eight similar antenna elements of RMSA are printed on a smartphone printed circuit board (PCB). An FR4 substrate is used as the system PCB with an overall dimension of 80 × 150 × 0 . 8 mm 3 . Two techniques, namely polarization and pattern diversity, are exhibited by designing the MIMO system due to the orthogonal arrangement of microstrip lines feeding the RMSAs. Simulated and experimental results are conducted to examine the performance of the designed MIMO antenna. Good isolation, acceptable gain, and eﬃciency are obtained over the bands of interest which verify the suitability of the proposed system for MIMO smartphone applications.
Varietal resistance of rice to blast fungus Magnaporthe oryzae at two sites in southwestern Nigeria

This study was conducted to elucidate the performance of varieties with known resistance genes of rice at two sites and assess the efficiency of the two sites for screening rice genotypes for blast resistance. Thirty-four (34) varieties plus one local check were screened for resistance to rice blast disease caused by a fungus (Magnaporthe oryzae) at Ibadan and Ikenne under natural infection for two years. The experiment was laid out using randomized complete block design with four replicates. Data were collected on disease development and severity using standard evaluation scale. Data were subjected to analysis of variance and the effect of genotype, environment, and their interaction were further analyzed using genotype main effect plus genotype-by-environment (GGE) biplot. Results revealed that the thirty-five varieties responded differently to blast infection and the two sites were significantly different from each other. Genotype-by-environment interaction was significant and had the highest contribution to the total sum of squares for disease development and severity scores. GGE biplot revealed that only Moroberekan was resistant to blast fungus across years and sites. In conclusion, although, the two sites are found in the same agroecology, Ibadan was identified as a better site for screening rice genotypes for blast resistance than Ikenne.
SERIES COMPENSATED TRANSMISSION LINE FAULT LOCATION USING GPS SYNCHRONIZED VOLTAGE MEASUREMENT

The transmission line faults are very often occurred and destroy the quality of power being transmitted through the transmission line. The detection of faults in a transmission line using measurement of voltage or current using current transformers is very common but its efficiency is limited by the efficiency of the current transformers which seems very poor. In this paper a new algorithm is presented for fault location in series compensated transmission lines with Fixed Series Capacitor (FSC). The time domain modeling of a transmission line and FSC system are used in this proposed algorithm. The series compensated lines have limitations with metal oxide varistor (MOV) operation, prefault system condition, and high resistance fault and shunt capacitance. The measurement of voltages may be done using GPS technology for accurate synchronization. This paper gives a fault-location method for transmission lines using only synchronized voltage measurements at both ends of the line which eliminates the inherent errors due to current transformers. This method is applicable for both transposed and un-transposed lines. This method is tested using results from a steady state faultanalysis program and EMTP, and generated voltage signals are preprocessed, and phasor are estimated through DFT algorithm in the MATLAB.
Challenges in health technology assessments of genetic tests

In the past decade, the use of genetic tests has grown rapidly worldwide. These technologies are often used in prenatal screening, carrier testing, prognostic testing, and diagnostic testing. Standard methods for meta-analysis of diagnostic test accuracy and cost-effectiveness analysis may need adaptation for health technology assessments (HTAs) of genetic tests. We provide some considerations relevant to these evaluations. We briefly address the following challenges for HTAs of genetic tests: (I) performing Bayesian meta-analysis of diagnostic test accuracy for rare genetic conditions; (II) performing Bayesian meta-analysis of diagnostic test accuracy in the absence of a perfect reference standard; (III) constructing economic models that account for conditional dependence between tests in the absence of a perfect reference standard; (IV) ascertaining the true prevalence of genetic conditions for economic analyses; (V) defining the time horizon and specifying health outcomes for economic modelling; and (VI) cost item measurement and valuation.
Data, Power and Bias in Artificial Intelligence

Artificial Intelligence has the potential to exacerbate societal bias and set back decades of advances in equal rights and civil liberty. Data used to train machine learning algorithms may capture social injustices, inequality or discriminatory attitudes that may be learned and perpetuated in society. Attempts to address this issue are rapidly emerging from different perspectives involving technical solutions, social justice and data governance measures. While each of these approaches are essential to the development of a comprehensive solution, often discourse associated with each seems disparate. This paper reviews ongoing work to ensure data justice, fairness and bias mitigation in AI systems from different domains exploring the interrelated dynamics of each and examining whether the inevitability of bias in AI training data may in fact be used for social good. We highlight the complexity associated with defining policies for dealing with bias. We also consider technical challenges in addressing issues of societal bias.
Integrative Analysis of lncRNAs in Kidney Cancer to Discover A New lncRNA (LINC00847) as A Therapeutic Target for Staphylococcal Enterotoxin tst Gene

Objective Bacterial toxin can cause cell death through induction of apoptosis in cancer cell lines as well as changes in the expression patterns of long non-coding RNAs (lncRNAs) and genes. In the present study, the effect of tst gene on ACHN cell lines was reported along with proposing a novel pathway of apoptosis in kidney cancer. Materials and Methods In this experimental study, effective lncRNAs and genes were predicted from different criteria for renal cell carcinoma (RCC) by bioinformatics methods and lncRNA-miRNA-mRNA interaction was constructed; then the effect of Staphylococcus aureus tst gene on induction of apoptosis pathways on ACHN and HDF cell lines was investigated. Results After creation of lncRNA-miRNA-mRNA interaction, changes in expression levels of lncRNA LINC00847 (P=0.0024) and PTEN gene (P=0.0027) were identified, as potential apoptosis biomarkers for kidney cancer, after treating ACHN cell line by pCDNA3.1 (+)-tst compared to the empty vector. In contrast, there was no statistically significant difference in DICER1 expression levels in ACHN-tst cell (P≥0.05). In addition, transfection by pcDNA3.1 (+)-tst could increase ACHN cell apoptosis level (P<0.0001) compared to the pcDNA3.1 (+) group; but no significant effect was observed on normal cells. Conclusion It is suggested that lncRNA LINC00847, discovered in this study, could provide a new landscape for researches aimed to determine relationship between functional lncRNA and RCC pathways. pcDNA3.1 (+)-tst was found to increase apoptosis in the transfected cells.
Use of Combined Railway Inspection Data Sources for Characterization of Rolling Contact Fatigue

Rolling contact fatigue is caused by interaction of train wheels with railheads. To minimize operational risks railways infrastructure owners can ask for regular inspections to determine critical sections of assets in a predictive maintenance scheme. Some defect types, for instance (sub-)surface anomalies like squats, were herein assessed with the EURAILSCOUT train UST02 by specific ultrasonic (UT) and eddy current (ET) testing probes, but each with inherent limitations. Additionally surface imaging video (VT) was recorded. Machine learning techniques were applied to combine data from these three inspection systems from a recorded track, which had a squat defect population. The target was to provide optimized classification as basis for prediction of rolling contact fatigue growth. Results are described of a ‘combined systems method’, CSM, with classification features derived from densely spaced clusters with input from UT B-scans, and parameters from ET and VT raw data after signal and image processing, respectively. In comparison to classification per single system, CSM gave significantly improved hit rate without degradation of specificity.
The effect of prompted self-revision on student performance in the context of open-ended problems using Randomized Control Trials

Assessments improve student learning. More than 50 years ago, Benjamin Bloom showed how to conduct this process in practical and highly effective ways when he described the practice of mastery learning (Bloom, 1968, 1971). Open-ended problems in assignments, as opposed to more closed-ended problems where there are a small set of known correct responses, offer an opportunity for students to demonstrate their understanding by articulating their underlying thought processes. In such problems, students are required to explain in a sentence or two, how to solve a particular problem or how they arrived at a solution. Open-ended responses stimulate a thought process in a student and allow teachers to better evaluate the student’s deeper understanding of a topic beyond what can be observed in other problem types. Due to the open-ended nature of student responses to these problems, however, it is sometimes difficult for teachers to devote time to assessing student work, which causes students to apply lower effort or disengage from such problems if it is believed that a teacher is unlikely to attend to it. In order to promote better student engagement with these open-ended questions and to motivate them to apply more effort in answering these questions, I have built an infrastructure to conduct RCTs(Randomized Control Trials) with open-ended problems within ASSISTments, an online assessment tool; I have built an infrastructure that caters to machine learning models for the automated assessment of the student work. I am using this infrastructure to design an RCT that will evaluate the effect of prompted self-revision on the quality of the student responses.
A Matlab Approach For Design Of Virtual Footwear

: Image processing in the future will dramatically change the experience of the human brain. A vast number of applications, software, and techniques for image processing help extract complex image features. While image processing works beyond multidimensional today and see what the image actually contains. Many techniques that draw on images in real time, but the real core is image processing. This paper addresses an overview of technologies, tools and techniques for measurement of various foot images of human being and obtain the foot dimensions using image processing and EMD algorithm in MATLAB software. Measuring and valuing a distance between two points is important in the processing of objects. The idea is to make the Euclidean distance between two points a measure of how near (or distant) two points are to each other based on two ranges. Using this we can obtain the foot measurements with less efforts and in affordable price. The need to extract information from foot images and interpret their content was the driving factor in major footwear manufacturing industries and also in health care for proving artificial legs.
GloVeNoR-Global Vectors for Node Representations

A graph is a very powerful abstract data type that can be used to model entities (nodes) and relationships (edges). Many real world networks like biological, computer and friendship networks can be represented as graphs. Graphs can be mined to extract interesting patterns and interactions between the participating entities. Recently, various Artificial Intelligence (AI) and Machine Learning (ML) techniques are used for this purpose. In order to do that, the nodes of a graph have to be represented as low dimensional feature vectors. Node embedding is the process of generating a n-dimensional feature vector corresponding to each node of a graph, such that the structurally similar nodes remain close in the n-dimensional space. There are many state-of-the-art methods, like node2vec and DeepWalk to compute node embeddings. These techniques borrow methods like the Skip-Gram model, used in the domain of Natural Language Processing (NLP) to compute word embeddings. This project explores the idea of porting the GloVe (Global Vectors for Word Representation) model, a popular technique for word embeddings, to a new method called GloVeNoR to compute node embeddings in a graph. We evaluate the model’s quality by comparing it with node2vec and DeepWalk on the problem of community detection on five different data sets. We observe that GloVeNoR discovers similar or better communities than the other existing models on all the datasets.
Optimum Antenna Design for DGPS Ground Reference Stations

The Global Positioning System (GPS) user community is growing exponentially. Although many of these users are content with the accuracy provided by the GPS Standard Positioning Service (SPS), an increasing number of applications require the precision provided tither by code-differential or carrier-differential techniques. An example is precision approach and landing. All candidate precision approach architectures involve the use of differential processing schemes. Multipath has been well-established as the primary error source in DGPS, yet most current antenna designs do not address this fact. This paper discusses the state of the art in GPS antenna design and analyzes antenna performance for the case of DGPS ground reference stations. This serves as the background for the design of an optimum ground reference station antenna system. The optimizing criteria is multipath rejection and this is achieved through the use of multiple antenna types and phased-array design.
Ultrasonography of normal reticulum in 30 healthy buffalo (Bubalus bubalis)

Reticulum is incriminated in most cases of gastrointestinal disturbances in bovines and should be firstly examined. The aim of the present study was to assess ultrasonographic appearance and relation of reticulum to its surrounding in a normal buffalo (N = 30). Sonographic examination was performed in a standing nonsedated buffalo using 3.5-MHz convex transducer. B and M modes of display were used for examination. Reticulum appeared as a half-moon-shaped structure with a smooth contour; it could be easily accessed from the left and right ventral thoracic region than from midline. Biphasic contraction was recorded in all examined buffalo while only four animals had a triphasic contraction. Four to five contractions were recorded during a 4-minute examination period. The mean distance between reticulum and left abdominal wall was 1.603±0.566 cm. The duration of the first and second reticular contractions were 3.080±0.43 and 4.407±0.796 sec, respectively. However, the duration of relaxation interval was 42.63±3.187 sec. The amplitude of first contraction was 6.341±1.600 cm. In conclusion, reticular appearance and characters of reticular motility in buffalo is similar to that reported in cows, but reticulum was best accessed from left and right ventral thorax than from midline. M mode of display is an alternative tool for evaluation of reticular motility. The result of the present study could be used as a reference for reticular examination in a healthy buffalo.
Highly responsive heading control of underactuated modified BlueROV using sliding-mode controller

The control of Autonomous Underwater Vehicle (AUV) presents some challenging tasks such as dealing with the nonlinearity of AUV dynamics, coupling effects, and taking into consideration the hydrodynamics uncertainties and disturbances such as current. One of the more robust control method for controlling a nonlinear system is Sliding-Mode Control (SMC). In literature, SMC had been used to control the depth and yaw of an underactuated AUV. However, the switching term of the SMC had to be tuned to get a proper balance between performance and robustness and it has low responsiveness to track desired reference signal. This paper introduces the usage of smoothing filter to make the SMC more responsive to track desired heading motion. The methodology starts with deriving heading model of an AUV, then estimating the parameters in the AUV model, followed by designing the heading controller based on SMC, and finally optimizing the controller parameters. The design model is based on underactuated modified BlueROV. Results shown that when the reference heading signal is smoothed, the SMC is able to achieve 95.55% responsiveness compared to only just 78.05% responsiveness without smoothing. The thrusts produced by the AUV is also less strained when the smoothing filter is applied. Therefore, to get a highly responsive SMC and to preserve the longevity of the thrusters of an AUV, a smoothing filter had to be considered in controller design of an underactuated AUV.
Continuation Task: A Critical Review and Directions for Future Research

Continuation task has witnessed a tremendous growth of research since it was firstly advanced by Wang, as an effective approach to L2 learning. The basic idea of continuation task is that learners should first read a given text with the end removed, then they should finish the continual writing in a logical and coherent way with imagination on the basis of the given text. In the process of continuation, learners need to not only fully understand the given text, but create new content, imitate and use the words and structures that appeared in the given text, thus producing interactive alignment effects, and improving the efficiency of learning foreign language. Researches on continuation tasks cover key issues regarding to the effectiveness on L2 learning and task-related or learner-related factors in continuation task that influence L2 learning. Since the number of researchers investigating the application of continuation task to L2 teaching and learning continues to grow, it is necessary to assess the current state of the researches in this area and establish future directions of investigation. This review aims to provide an overview of recent researches on continuation task and offer some suggestions for future researches.