Miracle-dz/UniFAR-FTUs huggingface dataset:
Selenium bioavailability in chicken fed selenium-fertilized wheat

Abstract The study compares the effects of adding selenium in cereal production by fertilization or later in the food production chain on selenium concentration in broiler. Wheat was produced using either selenate or selenium-enriched yeast as selenium fertilizer. Selenium-enriched yeast was also blended directly into one fodder. Individually fed broilers were fed by one of four different diets with different levels of selenium; from 37 µg to 185 µg selenium kg–1, for 21 days. The selenium concentration in thigh muscle, liver and excreta, and the activity of glutathione peroxidase increased with increasing selenium intake. Broiler weight and feed efficiency ratio was not affected by selenium intake. Diets based on selenium-fertilized wheat or wheat combined with selenium-enriched yeast lead to increased selenium concentration in liver and muscle of broilers. The selenium concentration was three times higher in liver than in muscle; chicken liver may therefore be a good source for selenium.
Adaptive Positioning Repair Method for Aero-Engine Blades by Using Speckle Vision Measurement

The repair of damaged aero-engine blades has an extremely high economic value. Due to the complexity of the blade surface and various kinds of deformation during the lifetime, blade positioning in the repair process has always been one of the key problems in the aviation industry. In this study, a method of blade self-adaptive positioning repair method based on speckle vision measurement is proposed. Firstly, a speckle vision measurement system is established to measure the speckles coated on the damaged blade surface to obtain its surface point cloud. Meanwhile, the coordinates of the reference points on the fixture are obtained to build the relative pose model between the blade and the fixture. Secondly, through the solution of posture relations among the mark point coordinate system, measuring camera coordinate system, probe coordinate system, and machine coordinate system, the self-adaptive positioning of the under-positioning clamping blade in the machine coordinate system is achieved. Then based on the positioning model, the machining repair parameters are selected reasonably to complete the CNC (Computer numerical control) path planning of tool repair. Finally, the DMU five-axis numerical control center was used to carry out adaptive positioning repair experiments on the damaged blades. The experimental results showed that this method could achieve satisfying repair effect in under positioning clamping, and provide a new method for repairing damaged aero-engine blades.
Sentiment Analysis Of Product Reviews – A Survey

: With expanding development of the web network, informal communities, online gateways, audits, reviews, suggestions, evaluations, and input are produced by clients and it can be about anything like books, individuals, items, explore, occasions, and so on. These opinions become advantageous for organizations, political body, and people. While this is intended to be valuable, a greater part of this client produced content require utilizing the opinion mining methods or sentiment analysis. Sentiment Analysis is a field in which we study about feelings, conclusions and subjectivity of opinions. This review paper is a similar investigation of numerous as of late proposed calculations' upgrades and different slant examination applications. Mainly for product reviews that how sentiment analysis can be used to recommend a product based on reviews by the client. The related fields to estimation investigation that pulled in specialists as of late are examined. The fundamental objective of this review is to give nearly full picture of sentiment analysis, its sorts and characterization. The primary commitments of this paper include the complex orders of late articles and the outline of the ongoing pattern of research in the sentiment analysis and its related territories.
Feasibility Analysis for the Penetration of Electric Vehicles in India in Future

Globally, there has been a paradigm shift in the automotive industry. This paper deals with the very basic issue of measuring and estimating the future energy consumption by electric vehicle (EV) in India. So, first the future analysis is made to know the electric vehicle fleet and then the future energy consumption per year is estimated for 2030 considering different scenarios of 20%, 30% and 100% electrification of vehicles, as these targets are to be achieved by the government of India. Data of automobile production has been collected from the Society of Indian Automobiles Manufacturer (SIAM) and with that trend of production the future vehicles in 2030 has been estimated. For the different categories of automobiles the battery specifications of EV by different manufacturers has been collected and the average of those is taken for the analysis. Further, the average distance driven by each vehicle is assumed and for that the energy consumption annually has been estimated. This paper also depicts the cost saving analysis which elaborates the difference in cost when the conventional vehicles are used and when EV are used. As we know that the prices of fuel are exorbitantly rising which is a huge concern for the economy of the country. This analysis will estimate that the total cost saved if100% electrification of vehicles takes place which will undeniably a colossal boost to the economy of the country.
Genetic Architecture of Early Vigor Traits in Wild Soybean

A worldwide food shortage has been projected as a result of the current increase in global population and climate change. In order to provide sufficient food to feed more people, we must develop crops that can produce higher yields. Plant early vigor traits, early growth rate (EGR), early plant height (EPH), inter-node length, and node count are important traits that are related to crop yield. Glycine soja, the wild counterpart to cultivated soybean, Glycine max, harbors much higher genetic diversity and can grow in diverse environments. It can also cross easily with cultivated soybean. Thus, it holds a great potential in developing soybean cultivars with beneficial agronomic traits. In this study, we used 225 wild soybean accessions originally from diverse environments across its geographic distribution in East Asia. We quantified the natural variation of several early vigor traits, investigated the relationships among them, and dissected the genetic basis of these traits by applying a Genome-Wide Association Study (GWAS) with genome-wide single nucleotide polymorphism (SNP) data. Our results showed positive correlation between all early vigor traits studied. A total of 12 SNPs significantly associated with EPH were identified with 4 shared with EGR. We also identified two candidate genes, Glyma.07G055800. 1 and Glyma.07G055900. 1, playing important roles in influencing trait variation in both EGR and EPH in G. soja.
INRISCO: INcident monitoRing in Smart COmmunities

Major advances in information and communication technologies (ICTs) make citizens to be considered as sensors in motion. Carrying their mobile devices, moving in their connected vehicles or actively participating in social networks, citizens provide a wealth of information that, after properly processing, can support numerous applications for the benefit of the community. In the context of smart communities, the INRISCO [1] proposal intends for (i) the early detection of abnormal situations in cities (i.e., incidents), (ii) the analysis of whether, according to their impact, those incidents are really adverse for the community; and (iii) the automatic actuation by dissemination of appropriate information to citizens and authorities. Thus, INRISCO will identify and report on incidents in traffic (jam, accident) or public infrastructure (e.g., works, street cut), the occurrence of specific events that affect other citizens’ life (e.g., demonstrations, concerts), or environmental problems (e.g., pollution, bad weather). It is of particular interest to this proposal the identification of incidents with a social and economic impact, which affects the quality of life of citizens.
Total Influence and Hybrid Simulation of Independent Cascade Model using Rough Knowledge Granules

The paper defines a new theoretical measure Total Influence, of a node as well as a set of nodes in the social network. Total influence uses probabilistic theory to obtain the expected size of the information spreading in the social network under the independent cascade model of diffusion. In order to quantify the size of the spreading practically, the paper proposes a new hybrid simulation methodology for the independent cascade model. The hybrid method uses rough set theory and defines rough knowledge agents around all the seed nodes from which the information is propagating. The lower approximation is calculated using the probabilistic approach, while the size of influence in the boundary region is quantified by Monte-Carlo simulation on a reduced network. The reduce network is formed by compacting all the nodes in the lower approximate region as a super-node. Experimental results on two synthetically generated directed network show that the hybrid method runs magnitude faster than its counterpart with a similar accuracy of the spreading size.
Contour Detection by Simulating the Curvature Cell in the Visual Cortex and its Application to Object Classification

This paper addresses contour detection by simulating the human visual system and its application to visual object classification. Unlike previously designed bioinspired contour detection algorithms, we consider contour to be the salience of an edge image, and we extract the salience by simulating the endstopped cell and curvature cell in the visual cortex. Generally, we follow a local-to-global feed-forward architecture, in which the size of the receptive field (RF) increases from the primary visual cortex to the higher visual cortex. Edges are first detected by simple cells in small RFs, where textural details are suppressed by non-classical receptive fields (NCRFs) and sparse coding. Second, edges are integrated into local segments by complex cells. Afterwards, they are combined into the salience of edge images by endstopped cells and curvature cells and are ultimately the core of the final contour. In addition, we also apply the bioinspired contour detection algorithm to visual object classification tasks. Experiments on contour extraction show that, compared with state-of-the-art bioinspired algorithms, our algorithm makes a considerable improvement on contour detection. Experiments on visual object classification show that the contours produced by our proposal are powerful representations of the original images, which implies that our proposal is both biologically plausible and technologically useful.
Emotional feedback ameliorates older adults’ feedback-induced learning

In older age, learning and feedback processing are usually impaired. This is thought to be due to impairments in the dopaminergic system and the anterior cingulate cortex. By contrast, processing of affective information seems to remain relatively intact. Recent research has also demonstrated that cognitive functioning can be influenced by affective materials or contexts and lead to an enhancement in diverse cognitive tasks. Hence, the aim of the present study was to explore, whether emotional feedback would counteract age-related learning deficits and strengthen early and later phases of feedback processing as reflected in the feedback-related negativity (FRN) and P3b of the event-related potential (ERP). Younger and older participants conducted a probabilistic reinforcement learning task in which the accurate responses had to be learned via feedback. In emotional trials, feedback stimuli consisted of faces with smiling and disgusted expressions, and in a non-emotional condition, positive and negative feedback was indicated by the background color of faces with neutral expressions. Our main results were that older adults showed better learning performance in the emotional feedback condition and a larger P3b after emotional than non-emotional feedback indexing heightened working memory updating after task relevant events.
CoV2ID: Detection and Therapeutics Oligo Database for SARS-CoV-2

The ability to detect the SARS-CoV-2 in a widespread epidemic is crucial for screening of carriers and for the success of quarantine efforts. Methods based on real-time reverse transcription polymerase chain reaction (RT-qPCR) and sequencing are being used for virus detection and characterization. However, RNA viruses are known for their high genetic diversity which poses a challenge for the design of efficient nucleic acid-based assays. The first SARS-CoV-2 genomic sequences already showed novel mutations, which may affect the efficiency of available screening tests leading to false-negative diagnosis or inefficient therapeutics. Here we describe the CoV2ID (http://covid.portugene.com/), a free database built to facilitate the evaluation of molecular methods for detection of SARS-CoV-2 and treatment of COVID-19. The database evaluates the available oligonucleotide sequences (PCR primers, RT-qPCR probes, etc.) considering the genetic diversity of the virus. Updated sequences alignments are used to constantly verify the theoretical efficiency of available testing methods. Detailed information on available detection protocols are also available to help laboratories implementing SARS-CoV-2 testing.
SW-SDF based privacy preserving for k-means clustering

— Privacy preserving data mining is a new direction in data mining which ensures the privacy of individual and company related information even after mining. Personalized privacy preservation uses flag for differentiating actual records which require privacy and records which does not require privacy such that overall information loss can be reduced. SW-SDF based privacy preservation uses sensitive weight (SW) and sensitive disclosure flag (SDF). Sensitive weight is used for differentiating between records which actually require privacy and which does not require privacy. Among records which require privacy, SDF value is accepted. SDF=0 indicate record owner is not ready to disclose his information and SDF=1 indicate record owner is ready to reveal his identity. The major drawback of this approach is that methods were not defined for specific mining algorithms. In this paper we have defined the representation of SW-SDF based privacy method on k-means clustering. Experiment results indicate that the mean of the original cluster is almost similar to the original mean and privacy is retained. Index Terms — privacy preserving data mining(PPDM), privacy preserving data publishing(PPDP), SW-SDF privacy, security, clustering , K-means, unsupervised learning.
Nanoemulgel for Improved Topical Delivery of Retinyl Palmitate: Formulation Design and Stability Evaluation

Retinyl palmitate is a vitamin A ester belonging to the family of endogenous natural retinoid and used to treat various skin disorders like acne, skin aging, wrinkles, and dark spots, as well as to protect against psoriasis. Despite the known therapeutic benefits of retinyl palmitate, the conventional topical delivery of retinyl palmitate commonly associated with adverse reactions such as skin irritation, redness, excessive peeling, and dryness. Therefore, the current study aims to encapsulate the retinyl palmitate in nanoemulsion then incorporate it into a hydrogel system to improve the topical delivery and stability. Low-energy emulsification method was used for the nano-encapsulation of retinyl palmitate. The phase behavior study was used for the investigation and the optimization of the formulation. The droplet size of the optimized nanoemulsion was in nano dimension (16.71 nm) with low polydispersity index (PdI) (0.015), negative zeta potential (−20.6 mV). It demonstrated the influence of vortexing on droplet size and PdI during nanoemulsion preparation. The retinyl palmitate loaded nanoemulgel delivery system exhibited significant improvement (p < 0.05) in skin permeability after topical application. Employment of the nano-encapsulation approach afterward dispersion into hydrogel system for the development of a topical delivery system of retinyl palmitate resulted in improvement in its UV and storage stability as well.
To what extent does severity of loneliness vary among different mental health diagnostic groups: A cross-sectional study.

Loneliness is a common and debilitating problem in individuals with mental health disorders. However, our knowledge on severity of loneliness in different mental health diagnostic groups and factors associated with loneliness is poor, thus limiting the ability to target and improve loneliness interventions. The current study investigated the association between diagnoses and loneliness and explored whether psychological and social factors were related to loneliness. This study employed a cross-sectional design using data from a completed study which developed a measure of social inclusion. It included 192 participants from secondary, specialist mental health services with a primary diagnosis of psychotic disorders (n = 106), common mental disorders (n = 49), or personality disorders (n = 37). The study explored differences in loneliness between these broad diagnostic groups, and the relationship to loneliness of: affective symptoms, social isolation, perceived discrimination, and internalized stigma. The study adhered to the STROBE checklist for observational research. People with common mental disorders (MD = 3.94, CI = 2.15 to 5.72, P < 0.001) and people with personality disorders (MD = 4.96, CI = 2.88 to 7.05, P < 0.001) reported higher levels of loneliness compared to people with psychosis. These differences remained significant after adjustment for all psychological and social variables. Perceived discrimination and internalized stigma were also independently associated with loneliness and substantially contributed to a final explanatory model. The severity of loneliness varies between different mental health diagnostic groups. Both people with common mental disorders and personality disorders reported higher levels of loneliness than people with psychosis. Addressing perceived mental health discrimination and stigma may help to reduce loneliness.
Cloning and functional expression of a food-grade circular bacteriocin, plantacyclin B21AG, in probiotic Lactobacillus plantarum WCFS1

There is an increasing consumer demand for minimally processed, preservative free and microbiologically safe food. These factors, combined with risks of antibiotic resistance, have led to interest in bacteriocins produced by lactic acid bacteria (LAB) as natural food preservatives and as protein therapeutics. We previously reported the discovery of plantacyclin B21AG, a novel circular bacteriocin produced by Lactobacillus plantarum B21. Here, we describe the cloning and functional expression of the bacteriocin gene cluster in the probiotic Lactobacillus plantarum WCFS1. Genome sequencing demonstrated that the bacteriocin is encoded on a 20 kb native plasmid, designated as pB21AG01. Seven open reading frames (ORFs) putatively involved in bacteriocin production, secretion and immunity were cloned into an E. coli/Lactobacillus shuttle vector, pTRKH2. The resulting plasmid, pCycB21, was transformed into L. plantarum WCFS1. The cell free supernatants (CFS) of both B21 and WCFS1 (pCycB21) showed an antimicrobial activity of 800 AU/mL when tested against the WCFS1 (pTRKH2) indicator strain, indicating functional expression of plantacyclin B21AG. Real-time PCR analysis revealed that the relative copy number of pB21AG01 was 7.60 ± 0.79 in L. plantarum B21 whilst pCycB21 and pTRKH2 was 0.51 ± 0.05 and 25.19 ± 2.68 copies, respectively in WCFS1. This indicates that the bacteriocin gene cluster is located on a highly stable, low copy number plasmid pB21AG01 in L. plantarum B21. Inclusion of the native promoter for the bacteriocin operon from pB21AG01 may result in similar inhibitory zones observed in both wild type and recombinant hosts despite the low copy number of pCycB21.
Development of Xanthomonas fragariae populations and disease progression in strawberry plants after spray‐inoculation of leaves

Xanthomonas fragariae is the causative agent of angular leaf spot disease of strawberry. Greenhouse experiments were conducted using a X. fragariae isolate tagged with a green fluorescent protein (GFP) for detailed population dynamic studies in and on leaves after spray-inoculation. The GFP-tagged bacteria were monitored with dilution plating of leaf washings and leaf extracts, and analysis of intact leaves using a non-invasive monitoring system called PathoScreen, based on laser radiation of fluorescent cells in plant tissues and signal recording with a sensitive camera. PathoScreen was also used to monitor bacteria grown on an agar medium after leaf printing. During the first 3 days after inoculation, bacterial populations washed off leaves rapidly decreased by at least a factor of 1000, after which populations remained stable until 14 days post-inoculation (dpi), when symptoms first started to appear. Thereafter, populations increased to a level of 1012 colony-forming units (CFU) g−1 of leaf material or higher. Similarly, densities in leaf extracts were low during the first 3 days after inoculation, at a level of 100–1000 CFU g−1 of leaf tissue. Gradually populations increased to a level of 109–1012 CFU g−1 at 28 dpi. Higher densities of epiphytic populations were found on the abaxial side than on the adaxial leaf side during the first 2 weeks after inoculation. After spray-inoculation of leaves, bacterial populations released from infected plants remained low until symptoms appeared, after which plants became highly infectious, in particular under high humidity.
Effects of Low-Dose Gamma-Ray Radiation on Apoptosis and Development of Zebrafish Embryo Brain

To investigate the effects of low-dose γ irradiation on apoptosis and development of the brain in zebrafish embryos, cumulative 15 mGy doses of γ rays from a 137Cs source were used to irradiate zebrafish embryos at 2 h post-fertilization (hpf) for 120 h. Apoptosis of the brain, brain morphological development, cell submicroscopic structure and mRNA expression were analyzed, respectively. Results indicate that after 15 mGy exposure, the apoptosis of zebrafish brain increased, vacuoles appeared in brain tissue, some organelles were damaged and vacuoles appeared locally in brain cells. The mRNA expression level of axin2 was significantly upregulated, and those of frizzled, β-catenin, camk2, TCF/ LEF and bcl9 were significantly downregulated in brain tissue. These genes are involved in the Wnt signaling pathway. The findings of this work suggest that low-dose radiation may influence the apoptosis and development of the brain in the zebrafish embryo by inhibiting the Wnt signaling pathway.