Miracle-dz/UniFAR-FTUs huggingface dataset:
Transfer Learning for Brain-Computer Interfaces: A Complete Pipeline

Transfer learning (TL) has been widely used in electroencephalogram (EEG) based brain-computer interfaces (BCIs) to reduce the calibration effort for a new subject, and demonstrated promising performance. After EEG signal acquisition, a closed-loop EEG-based BCI system also includes signal processing, feature engineering, and classification/regression blocks before sending out the control signal, whereas previous approaches only considered TL in one or two such components. This paper proposes that TL could be considered in all three components (signal processing, feature engineering, and classification/regression). Furthermore, it is also very important to specifically add a data alignment component before signal processing to make the data from different subjects more consistent, and hence to facilitate subsequential TL. Offline calibration experiments on two MI datasets verified our proposal. Especially, integrating data alignment and sophisticated TL approaches can significantly improve the classification performance, and hence greatly reduce the calibration effort.
Network effects and the appointment of female board members in Japan

We investigate the dynamics in the networks of Japanese corporates and its interplay with the appointment of female board members. We find that firms with female board members show homophily with respect to gender and often have above average profitability. We also find that new appointments of women are more likely at boards which observe female board members at other firms to which they are tied by either ownership relations or corporate board interlocks.
COMBINATION OF FUNGAL AND BACTERIAL ANTAGONISTS FOR MANAGEMENT OF ROOT AND STEM ROT DISEASE OF SOYBEAN

Trichoderma harzianum and plant growth promotory rhizobacteria Pseudomonas fluorescens were tested alone and in combinations for their relative biocontrol potential against many soil-borne plant pathogens viz., Rhizoctonia solani, Sclerotium rolfsii and Macrophomina phaseolina responsible for root and stem rot disease of soybean. Investigations under glass-house and field conditions revealed a general trend towards greater suppression and enhanced consistency against the pathogens by mixture of antagonists. Application of more than one antagonists of diverse origin is suggested as a reliable means of reducing the variability and increasing the reliability of biological control.
Cooking Is All About People: Comment Classification On Cookery Channels Using BERT and Classification Models (Malayalam-English Mix-Code)

The scope of a lucrative career promoted by Google through its video distribution platform YouTube 1 has attracted a large number of users to become content creators. An important aspect of this line of work is the feedback received in the form of comments which show how well the content is being received by the audience. However, volume of comments coupled with spam and limited tools for comment classification makes it virtually impossible for a creator to go through each and every comment and gather constructive feedback. Automatic classification of comments is a challenge even for established classification models, since comments are often of variable lengths riddled with slang, symbols and abbreviations. This is a greater challenge where comments are multilingual as the messages are often rife with the respective vernacular. In this work, we have evaluated top-performing classification models and four different vectorizers, for classifying comments which are a mix of different combinations of English and Malayalam (only English, only Malayalam and Mix of English and Malayalam). The statistical analysis of results indicates that Multinomial Naïve Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Random Forest and Decision Trees offer similar level of accuracy in comment classification. Further, we have also evaluated 3 multilingual sub-types of the novel NLP language model, BERT and compared its’ performance to the conventional machine learning classification techniques. XLM was the top-performing BERT model with an accuracy of 67.31%. Random Forest with Term Frequency Vectorizer was the best the top-performing model out of all the traditional classification models with an accuracy of 63.59%.
Computer-aided diagnosis system of thyroid nodules ultrasonography

Abstract To evaluate the diagnostic efficiency of computer-aided diagnosis (CAD) system and 111 radiologists with different experience in identifying benign and malignant thyroid nodules, and to summarize the ultrasound features that may affect the diagnostic of CAD and radiologists. Fifty thyroid nodules and 111 radiologists were enrolled in this study. All the 50 nodules were diagnosed by the 111 radiologists and the CAD system simultaneously. The diagnostic performance of the CAD system, senior and junior radiologists with the maximum accuracy were calculated and compared. Interobserver agreement for different ultrasound characteristics between the CAD and senior radiologist were analyzed. CAD system showed a higher specificity than junior radiologist (87.5% vs 70.4%, P = .03), and a lower sensitivity than the senior radiologist and junior radiologist but the statistics were not significant (76.9% vs 86.9%, P > .5; 76.9% vs 82.6%, P > .5). The CAD system and senior radiologist got larger AUC than junior radiologist but the differences were not statistically significant (0.82 vs 0.76, respectively; P = .5). The interobserver agreement for the US characteristics between the CAD system and senior radiologist were: substantial agreement for hypoechoic and taller than wide (kappa value = 0.66, 0.78), and moderate agreement for irregular margin and micro-calcifications (kappa value = 0.52, 0.42). The CAD system achieved equal diagnostic accuracy to the senior radiologists and higher accuracy than the junior radiologists. The interobserver agreements in the US features between the CAD system and senior radiologist were substantial agreement for hypoechoic and taller than wide; moderate agreement for irregular margin and micro-calcifications. The location of a thyroid nodule and the feature of macrocalcification with wide acoustic shadow may influence the analysis of the CAD system.
Serum profile of low molecular weight fucosylated glycoproteins for early diagnosis of hepatocellular carcinoma

Our previous study reported a method of using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to analyze the association between abnormal fucosylation of serum glycoproteins and the progression of hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). In the present study, the aforementioned method was improved by focusing on fucosylated glycoproteins <10 kD, classification models were established and blind tests were performed on an enlarged sample size (n=299). According to the present results, the classification models had a sensitivity and specificity of 74.31 and 76.32%, respectively, to identify HCC among all serum samples, 81.65 and 83.08%, respectively, to distinguish HCC from HBV-associated cirrhosis and chronic hepatitis Band 88.99 and 84.62%, respectively, to distinguish HCC from HBV-associated cirrhosis. When combined with α-fetoprotein (AFP) measurements (AFP >20 ng/ml), the sensitivity and specificity of the models were significantly elevated to 80.73 and 87.37%, 87.16 and 90.00%, and 92.66 and 93.84%, respectively. In addition, the HBV-HCC vs. HBV-cirrhosis classification model was used to analyze serum samples collected from 9 patients with cirrhosis 1 year before they were diagnosed with HCC, and from 6 patients who had cirrhosis but developed no signs of HCC for the following 3 years. The model identified 7 patients (77.78%) with no significant clinical symptoms of HCC, and gave no false positive results, demonstrating that the classification models established in the present study may be useful for the early diagnosis of HCC. After isolation and purification, two proteins with differential expression were identified as isoform 1 of inter-α-trypsin inhibitor heavy chain 4 precursor, and thymosin β-4-like protein 3. These may be used as candidate markers for HCC diagnosis. Additionally, the present study indicates that defucosylation of serum glycoproteins may occur during the development and progression of HCC.
DESIGN AND DEVELOPMENT OF FLOATING PULSATILE DRUG DELIVERY OF LOSARTAN POTASSIUM

Objective: The objective of the present investigation was to the development of floating pulsatile drug delivery system of Losartan potassium (LP) tablets for obtaining no drug release during floating followed by pulsed, rapid drug release to achieve chronotherapeutic release. In hypertension, the risk of getting heart attacks early in the morning is high and therefore, there was need to develop drug delivery, which will release drugs at morning hours and provide efficacious therapy. LP is a short biological half-life (1.5-2.5h) and readily absorbed from the stomach and upper gastrointestinal tract. Methods: Tablet formulation was prepared by press coating of rapid release core tablets and core tablets were further top coated with a buoyant layer of HPMC K4M and sodium bicarbonate. Various grades of HPMC polymer (E5/E15/E50) were used for the pulsatile coating layer. The developed formulations were characterized for physical characteristics, floating lag time, floating time, release lag time, drug content, swelling index, in vitro dissolution studies, DSC and XRD. Results: The FTIR and DSC studies predicted that there was no chemical interaction between drug and excipients. The core tablet coated with HPMC E50 showed a high swelling index and release the drug 97.60±1.2% at 6h. Buoyant layer with 80 mg HPMC K4M and 25 mg sodium bicarbonate gave satisfactory floating lag time. Conclusion: The system showed an excellent lag phase followed by burst release in the distal small intestine, which gives site and time-specific delivery of LP acting as per chronotherapy for treatment of hypertension.
Effect of age and weight on physical activity

Background: Individuals tend to develop metabolic disorders and other chronic diseases, due to the poor conduction of physical activities. Meanwhile, a high level of physical activity positively affects the quality of life. However, irrespective of the numerous studies reported on the correlation between age, weight, and physical activity, there is limited study on the differences of physical activities in the geriatric and adult groups of obese and non-obese people. This study, therefore, aims to investigate the effect of age and weight on physical activity in geriatric and adult groups. Design and methods: The purposive sampling technique was used to obtain data from 154 respondents from community-integrated health care in Surabaya, East Java, Indonesia. These respondents were equally divided into two groups of adult (21-60 years) and geriatric (>60 years) groups. Results: The Chi-Square test showed that there were no significant differences between physical activity in the obese and nonobese people of the geriatric groups (P>0.05). Conversely, in the adult group, there were significant differences between physical activities and the age of obese and non-obese groups (P<0.05). Conclusions: In conclusion, age affects physical activity in adult and geriatric groups. Significance for public health Age and weight are factors that influence physical activity levels. Low levels of physical activity have major impacts on the physical, social, emotional, and qualities of life. This study shows the different levels of physical activity between obese and non-obese in the geriatric and adult group.
The cytological instability of neoallopolyploids suggesting a potent way for DNA introgression: The case of synthetic hexaploid wheat × Aegilops peregrina

SHW-L1 is a newly synthetic hexaploid wheat, which has a genomic combination analogous to that of natural common wheat. In the present study, intergeneric F(1) hybrids of SHW-L1 - Aegilops peregrina AS24 were produced without embryo rescue. Among the 31 F(1) hybrid plants observed, 20 had the expected chromosome number 2n = 35 and were euploids (genome ABDUS(I)). The remainder 11 plants were aneuploids with 33, 34, 36 and 37 chromosomes, indicating that the neoallohexaploid SHW-L1 was cytologically instable and produced aneuhaploid gametes with 19, 20, 22 and 23 chromosomes, respectively. The hybrid plant lacking chromosome 5B carrying Ph1 showed a very high level of homoeologous chromosome pairing. The absence of Ph gene provides a potent cytological mechanism for DNA introgression among homoeologous chromosomes between newly synthetic wheat and wild species.
Framework to select an improved radiographic image using Speed-constrained modified particle swarm optimization

Radiographic images suffer from contrast problems. Contrast Limited Adaptive Histogram Equalization (CLAHE) is a widely used local contrast enhancement algorithm that can solve this problem. There are no fixed values of CLAHE input parameters that always produce the best output images in terms of contrast enhancement for radiographic images, so to find the parameters that satisfy the optimal condition in a radiography image we use the Speed-constrained Modified Multi-objective Particle Swarm Optimization (SMPSO). Since the output is a set of solutions (called Pareto Set), in this paper we propose to use and compare a posteriori decision methods with a multi-objective approach, in order to select the solutions of the Pareto front that are aligned with the visual criteria of an expert. Three decision making methods were used (utility function-based, distance-based and a fuzzy method). In order to validate which decision methods gave better results, they were evaluated by a medical expert, concluding that methods based on utility functions and distance obtain better quality information. The Fuzzy method was discarded because it selects solutions with a lot of distortion.
Feeding Ecology of the Snake Community of the Red Hills Region Relative to Management for Northern Bobwhite: Assessing the Diet of Snakes Using Stable Isotopes

Snakes can respond to variation in resource availability through changes in diet and species interactions. For many species, however, patterns of variation in diet are poorly known. Making use of novel 13C, through the provision of supplemental food in the form of milo (Sorghum spp.) for Northern Bobwhite (Colinus virginianus), we used carbon (&dgr;13C) and nitrogen (&dgr;15N) stable isotope analyses to evaluate the specificity of mammalian and herpetofaunal diet, trophic niche width, and trophic niche overlap between five snake species in the Red Hills of the southeastern United States. Most mammalian prey and Northern Bobwhite were characterized by different &dgr;13C values in the milo- and non-milo-treated areas. Using milo to reflect dietary patterns we determined that Coachwhip (Masticophis flagellum), Cottonmouth (Agkistrodon piscivorus), and Eastern Rat Snake (Pantherophis alleghaniensis) were dietary generalists, revealed by larger isotopic range and lack of correspondence between isotopic values and those of distinct prey groups. In contrast, Black Racer (Coluber constrictor) and Corn Snake (Pantherophis guttatus) were dietary specialists. Black Racers fed largely on herpetofauna, and &dgr;13C values of Corn Snake revealed a gradual ontogenetic/size-related diet shift from herpetofauna to a mammalian-based diet. There was considerable overlap of isotopic trophic niche between snake species, except for the Cottonmouth with &dgr;15N values higher than other sampled species. These findings provide novel insight into snake trophic ecology.
A preliminary approach to evolutionary multitasking for dynamic flexible job shop scheduling via genetic programming

Genetic programming, as a hyper-heuristic approach, has been successfully used to evolve scheduling heuristics for job shop scheduling. However, the environments of job shops vary in configurations, and the scheduling heuristic for each job shop is normally trained independently, which leads to low efficiency for solving multiple job shop scheduling problems. This paper introduces the idea of multitasking to genetic programming to improve the efficiency of solving multiple dynamic flexible job shop scheduling problems with scheduling heuristics. It is realised by the proposed evolutionary framework and knowledge transfer mechanism for genetic programming to train scheduling heuristics for different tasks simultaneously. The results show that the proposed algorithm can dramatically reduce the training time for solving multiple dynamic flexible job shop tasks.
Multiobjective direction driven local search for constrained supply chain configuration problem

Supply chain configuration (SCC) is to make optimal choices for the members in supply chain management. The configurations of members with different choices can influence the total cost (totalCost) and the total time (totalTime) for the productions of the supply chain. This paper focuses on a constrained SCC (CSCC) problem to minimize the totalCost and to meet the totalTime constraint (i.e., the deadline limitation). To handle the constrained problem, existing methods may use constraints handing techniques like penalty or repair to help obtain feasible solutions. Differently, this paper considers the constraint of totalTime as another objective, and proposes a multiobjective direction driven local search (MDDLS) algorithm to solve the CSCC problem. The MDDLS explores the search path from a solution with smaller totalCost (or totalTime) to another solution with smaller totalTime (or totalCost). This way, MDDLS can obtain a set of solutions with different totalCost and totalTime values. The solution with best (smallest) totalCost value among all the feasible solutions (whose totalTime values satisfy the time constraint) is regarded as the final solution. The experiments show that MDDLS outperforms some compared algorithms for the CSCC problem.
Delivering diverse web server configuration in a moving target defense using evolutionary algorithms

Creating diverse service configurations that can be swiftly swapped is the essence of the so called Moving Target Defense: presenting a different attack surface for attackers profiling a system for further advances can be applied to many different services and systems. In this paper we focus on using evolutionary algorithms to generate a host of web server configurations. Even if this is an easy target for evolutionary algorithms, we will prove how evolutionary algorithms provide a supply of secure and diverse configurations, with minimum intervention of experts, even with the added challenge of the time the evaluation of a single system takes.
Effects of hydropower peaking on epilithon and invertebrate community trophic structure

Hydropower generation induces rapid and frequent fluctuations of hydrodynamic parameters in rivers downstream of hydroelectric impoundments. On the FontaulieGre river (ArdeGche basin, France), water releases come from the Loire basin and the flow varies from 1.3 to 20 m3/s for one reach and from 0.1 to 20 m3/s for another reach. A reference site upstream was chosen to compare the communities with two downstream impacted sites. These two sites enabled two different base flow situations to be studied simultaneously and also the effect of base flow enhancement at one site. Benthic and epilithic samples were collected at the three sites on three dates. Epilithon development was linked to hydraulic regimes, with a major increase in algal biomass, dominated by filamentous algae, linked to the minimum base flow level and to the duration of periods without peaks. The macroinvertebrate communities of impacted reaches were less diversified and more specialized, with predominance of one or two taxa, whereas communities in upstream reaches were more diverse. The different morphological units specificity was attenuated in hydropeaking situations. In the case of a very low base flow, the lentic units with very low velocities (less than 4 cm s−1) had different fauna. The downstream algal development explained part of the change in benthic community structure in trophic groups (i.e. dominance of scrapers) in the site with the higher base flow. When the base flow was too low, a trophic discordance was observed and excess algal biomass represented a limiting factor. Thus, this study indicated that base flow level and duration had important effects on epilithic development and on invertebrate trophic structure in terms of mean velocities and of number of days without peaks.
A Method for Isolation of High Quality RNA from Various Juglans regia Tissues

Isolation of high-quality RNA is a prerequisite for gene expression studies. However, RNA extraction from walnut tissues is difficult due to the presence of rich polysaccharides, flavonoids and polyphenolic compounds. In this study, we tried an improved protocol to isolate total RNA in high yield and integrity from walnut leaves, green nuts, shoots, seeds and roots, which contained high levels of flavonoids, polysaccharides and polyphenolic secondary metabolites. Polyvinylpolypyrrolidone (PVPP) at 2% and β-mercaptoethanol at 4% were added to the standard CTAB extraction buffer, and after chloroform and phenol extraction followed by ethanol/sodium acetate precipitation, a second phenol/chloroform extraction was introduced to remove coprecipitated polysaccharides. The modified CTAB method resulted in isolation of high yield (174µg/g) and high quality (A260)/A280)≈2.0) RNA, and at least two distinct rRNA hands were detected after electrophoresis in agarose gels. Sharp hybridization signals were obtained from Northern blots and 185 gene fragments were successfully amplified by RT-PCR, suggesting the high integrity of isolated RNA. The total RNA isolated by this protocol was of sufficient quality for subsequent molecular applications.
Multi-objective evolutionary GAN

Generative Adversarial Network (GAN) is a generative model proposed to imitate real data distributions. The original GAN algorithm has been found to be able to achieve excellent results for the image generation task, but it suffers from problems such as instability and mode collapse. To tackle these problems, many variants of the original model have been proposed; one of them is the Evolutionary GAN (EGAN), where a population of generators is evolved. Inspired by EGAN, we propose here a new algorithm, called Multi-Objective Evolutionary Generative Adversarial Network (MOEGAN), which reformulates the problem of training GANs as a multi-objective optimization problem. Thus, Pareto dominance is used to select the best solutions, evaluated using diversity and quality fitness functions. Preliminary experimental results on synthetic datasets show how the proposed approach can achieve better results than EGAN.