Miracle-dz/UniFAR-FTUs huggingface dataset:
Altering undigested neutral detergent fiber through additives applied in corn, whole barley crop, and alfalfa silages, and its effect on performance of lactating Holstein dairy cows

Objective We hypothesized that silage additives may alter the undigested neutral detergent fiber (uNDF) content through ensiling. Therefore, urea and formic acid were applied to corn, whole barley crop (WBC) and alfalfa to change uNDF content of the ensiled forages. Methods Six experimental diets at two groups of high uNDF (untreated corn and alfalfa silages [CSAS] and untreated whole barley and alfalfa silages [BSAS]) and low uNDF (urea-treated corn silage+untreated alfalfa silage [CSUAS], urea-treated whole barley silage+untreated alfalfa silage [BSUAS], untreated corn silage+formic acid-treated alfalfa silage [CSASF], and untreated whole barley silage+formic acid-treated alfalfa silage [BSASF]), were allocated to thirty-six multiparous lactating Holstein dairy cows. Results The untreated silages were higher in uNDF than additive treated silages, but the uNDF concentrations among silages were variable (corn silage0.05). Milk yield tended to increase in the cows fed high uNDF diets than those fed low uNDF (p = 0.10). The cows fed diet based on urea-treated corn silage had higher milk yield than those fed other silages (p = 0.05). The substitution of corn silage with the WBC silage tended to decrease milk production (p = 0.07). Changing the physical source of NDF supply and the uNDF content from the corn silage to the WBC silage caused a significant increase in ruminal NH3-N concentration, milk urea-N and fat yield (p< 0.05). The cows fed diets based on WBC silage experienced greater rumination time than the cows fed corn silage (p<0.05). Conclusion Administering additives to silages to reduce uNDF may improve the performance of Holstein dairy cows.
Immunoinformatics Prediction of Epitope Based Peptide Vaccine Against Madurella mycetomatis Translationally Controlled Tumor Protein

Background Madurella. mycetomatis is most common causative agent of mycetoma in Sudan and worldwide. No vaccines are available till now so design of effective vaccine is essential as protection tool. Peptide vaccine can overcome the common side effects of the conventional vaccines. The aim of this study was to design peptide based vaccine for M.Mycetomatis Translationally Controlled Tumor Protein (TCTP) using immunoinformatics tools. Materials and methods TCTP sequences were retrieved from NCBI and then processed using BioEdit program to determine conserved regions and different immunoinformatics tools from IEDB. Population coverage analysis was performed for the most promising epitopes. Homology modelling was performed to show their structural positions in TCTP. Protein analysis was done using Expasy (ProtParamsotware). Results and conclusion Four epitopes passed the Bepipred, Emini, Kolaskar and Tongaonkar tools. 111 epitopes were predicted to interact with MHCI alleles with IC50 < 500 nM, three of them were most promising. 274 predicted epitopes were interacted with MHCII alleles with IC50 < 100 nM, four of them were most promising. The epitope (YMKSVKKAL) was the most promising one concerning its binding with MHCI alleles, while (FRLQSTSFD) was the most promising for MHC II. The epitope (YLKAYMKSV) is shared betweenMHC I and II. For the population coverage of M. Mycetomatis TCTP vaccine Sudan (90.39%) had the highest percentage for MHC I. This is the first computational vaccinology study conducted in mycetoma caused by M. Mycetomatis using TCTP.
Attention explores space periodically at the theta frequency

Voluntary attention is at the core of cognitive functions. Attention can be sustained at a location, or reoriented in space to allow processing at other locations, critical in an ever-changing environment. Numerous studies have investigated attentional orienting in time and space but little is known about the spatio-temporal dynamics of attentional reorienting. Here, we explicitly manipulated attentional reorienting using a cueing procedure in a 2-AFC orientation discrimination task. At various delays during the task, we interrogated attentional deployment by flashing two probe stimuli. Then, solving a second-degree equation to estimate the report probability at each probe location, we demonstrated that attention reorients periodically at ~4 Hz (theta) between the two stimulus locations. We further observed that each stimulus location is sampled at ~11 Hz (alpha). Finally, we support our mathematical approach using simulations and show that this method is sufficiently powered making it a valuable tool for studying the spatio-temporal dynamics of attention.
Chemical constituents of Calotropis procera latex and ultrastructural effects on Haemonchus contortus

Abstract This study aimed to evaluate the anthelmintic and ultrastructural effects of Calotropis procera latex on Haemonchus contortus. C. procera latex was twice centrifuged at 10,000×g and dialyzed to obtain a fraction rich in proteins, named LP (latex protein), and at 3,000 rpm to obtain a fraction rich in secondary metabolites, named LNP (latex non-protein). Specimens of H. contortus exposed to LNP, LP and PBS in the Adult Worm Motility Test (AWMT) were submitted to scanning (SEM) and transmission (TEM) electron microscopy to verify changes in their ultrastructure. Phytochemical tests in the LNP indicated the presence of phenols, steroids, alkaloids and cardenolides. High-Performance Liquid Chromatography (HPLC) characterized the presence of the compounds gallic acid and quercetin in the LNP. The protein content in the LP was 43.1 ± 1.1 mg/mL and 7.7 ± 0.3 mg/mL in LNP. In AWMT, LNP and LP inhibited the motility of 100% of the nematodes, with LNP being more effective than LP and ivermectin more effective than both (p <0.05). Cuticle changes were observed by SEM and TEM in nematodes treated with LP and LNP. Calotropis procera latex has anthelmintic effects against H. contortus, causing damage to its cuticle and other alterations in its ultrastructure.
Joint toxicity effects of cyanotoxins and chemical compounds

Aquatic organisms may be exposed to cyanotoxins and anthropogenic contaminants originated from harmful cyanobacterial blooms and human activities, respectively. Microcystin-LR (MC-LR) and cylindrospermopsin (CYN) are the most frequently detected cyanotoxins in harmful cyanobacterial blooms and have been simultaneously reported in the water. Metals and pesticides are anthropogenic contaminants commonly found in the aquatic environment as a result of the intensification of agricultural and industrial activities. Cadmium (Cd) and terbuthylazine (TBA) were chosen as an example of the possible metals and pesticides that can co-occurr with cyanotoxins in the environment. However, the ecotoxicological risk of combinations of cyanotoxins and/or anthropogenic contaminants in the aquatic environment needs more studies. The present work aimed to elucidate some biological behaviours and patterns regarding these combinations. The effects of binary mixtures of MC-LR, CYN, Cd and TBA on the growth rate of the freshwater algae Chlorella vulgaris were assessed after 4 and 7 days of exposure using the reference model of independent action (IA). The MIXTOX tool was used to detect possible deviations (due to the interaction between compounds) from the reference model such as synergism/antagonism, dose ratio and dose level dependency. The results demonstrated that several patterns of response were obtained depending on the binary mixture. Synergism was detected in the mixture of MC-LR and CYN for the two exposure periods. In the MC-LR and TBA mixture, a dose-level deviation was observed for the two exposure periods indicating antagonism at low dose levels and synergism at high dose levels. In the MC-LR and Cd mixture, deviations for antagonism were found for a 4-day exposure period while a dose-level deviation was observed for a 7-day exposure period showing synergism at low dose levels and antagonism at high dose levels. A dose-ratio deviation was observed in the CYN and TBA mixture, with a pattern for antagonism when CYN was the compound dominant, while deviations for antagonism were observed in the CYN and Cd mixture for a 4-day exposure period. Similar patterns of response were obtained for both mixtures involving CYN after 7 days of exposure, namely dose-level deviation indicating synergism at low dose levels and antagonism at high dose levels. For TBA and Cd mixture, antagonism was found for a 4-day exposure period and a doselevel deviation (antagonism at low dose levels and synergism at high dose levels) was observed for a 7-day exposure period. Due to the diversity of effects and behaviours that can result from the combination of very common toxicants, this study shows the importance of evaluating the combined effects of cyanotoxins and/or anthropogenic contaminants.
Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks

The increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated the intrusion detection system based on the in-vehicle system. We combined two algorithms to realize the efficient learning of the vehicle’s boundary behavior and the detection of intrusive behavior. In order to verify the accuracy and efficiency of the proposed model, it was evaluated using real vehicle data. The experimental results show that the combination of the two technologies can effectively and accurately identify abnormal boundary behavior. The parameters of the model are self-iteratively updated using the time-based back propagation algorithm. We verified that the model proposed in this study can reach a nearly 96% accurate detection rate.
A Self-Calibration Method for 5G Full-Digital TDD Beamforming Systems Using an Embedded Transmission Line

In this article, a self-calibration method for 5G full-digital time-division duplexing (TDD) beamforming systems is proposed and demonstrated, including the self-calibration for both the transmit (Tx) and receive (Rx) channels. By incorporating an embedded transmission line (ETL) in the antenna array that weakly couples with all the radiating elements, the relative magnitude and phase of each Tx/Rx channel can be obtained with the proposed calibration procedure. Comparing with conventional self-calibration methods, the proposed approach requires simpler hardware and reduced calibration time. As a proof-of-concept example, a $1\times 8$ full-digital TDD beamforming array operating at 3.5 GHz with an ETL is fabricated for validation. To further evaluate the accuracy of the calibration data, the “stepped null” calibration was conducted by the over-the-air (OTA) measurement. It is shown that the root mean square (rms) phase and magnitude errors of the calibration results for the Tx and Rx channels are 5.8°/0.84 and 6.3°/0.91 dB, respectively, which are sufficiently accurate for beamforming in 5G communication systems.
Distributed Optimization for Computation Offloading in Edge Computing

Edge computing is a promising technology that offers data analysis and computing for Internet of Things (IoT) services at the network edge. It has the potential to significantly reduce the latency and improve the reliability of IoT services by allowing computation workloads and local data generated by IoT devices to be offloaded to edge nodes. This paper aims to develop algorithms for efficient provision of both job assignment and resource allocation for edge computing networks. The main objective is to minimize the long-term average of the response time delay subject to constraints on computation resources and power consumption. We apply a drift-plus-penalty based Lyapunov optimization approach to convert the original problem into an upper bound optimization problem. We then relax the latter to a convex optimization problem. Finally, a distributed algorithm based on branch-and-bound approach is provided and the gap between the distributed algorithm solution and the optimal solution of the original problem is theoretically analyzed. Numerical results based on extensive experiments have demonstrated that our distributed algorithm can achieve the required performance of edge computing that supports IoT systems, under static traffic conditions as well as under dynamic environments with time-varying traffic.
Understanding the Diverse Field of “Educational Technology” as Revealed in Twitter Job Postings: Encoding / Decoding Approach

In this study, we attempt to understand discursive interrelationships among five professional job advertisements which are often used interchangeably, including educational technology, educational design, instructional design, learning design, and instructional systems design The purpose is to better understand the distinctions, interactions, and overlaps of these disciplines using Encoding/Decoding Model over the discourses of the jobs announcements We collected data using a social network analysis tool, NCapture, and imported to qualitative analysis software (i e , NVivo) to conduct thematic analyses For this study, 171 job postings in Twitter were captured by using NCapture as a Web-browser extension Findings indicated that the relations between the targeted disciplines can be explained by Stuart Halls Communication Model (1980) Results can serve as a guide for scholars and students studying at the intersection of technology and education fields
Perchloroetylene and Dibutyltin Dichloride Removal from Packed Column by Surfactant Solution

Surfactant enhanced remediation is viewed as a potential method for removing organometallic compounds from contaminated aquifers. Dibutyltin dichloride (DBT), as a representative organometallic compound, was applied in sand packed columns to observe its solubilization behavior compared to that of perchloroetylene (PCE), a normal organic solvent. Ottawa sand was used as the porous media. A mixture of DBT and PCE was applied as the contaminant. The tracer study exhibited the plug flow condition with a retention time of 79.9 min. The surfactant solution was a mixture of 3.6 wt. % SDHS and 0.4 wt. % C16DPDS with various concentrations of CaCl 2 . The column experiments were carried out by single and gradient surfactant systems. The effluent exhibited a general solubilization pattern for PCE, governed by a rate limiting mechanism. However, the concentration of DBT in the effluent observed in every experiment was just a slice of its solubilization capacity. The adsorption of DBT on the sand was suspected to be the cause of the problem. The solubilization of DBT by a surfactant was ineffective at removing DBT from the contaminated media. It may be concluded that DBT exhibits the properties of both an organic and inorganic compound; it could be solubilized by a surfactant and absorbed strongly on sand. Nevertheless, the results indicate that trapped DBT could be removed by mobilization in the form of a PCE-DBT mixture and that adsorption could be prevented by a very low pH condition. DOI: http://dx.doi. org/10.14456/aer.2014. 21
Improved Gait Speed Calculation via Modulation Spectral Analysis of Noisy Accelerometer Data

Chronic diseases among older adults carry a heavy burden on a country’s healthcare system and economy. As such, there is a critical need for the development of cost-effective, technology-based tools that can be scaled to meet the needs of older adults. Gait speed, for example, is an important predictor of change in functional status and health outcomes in older adults. There is no universally accepted method for measuring gait speed in clinical practice and research, and differences in methods may influence the observed associations between gait speed and health. Moreover, existing methods are sensitive to artifacts, which are present in burgeoning low-cost wearable devices. To overcome this limitation, this paper proposes an artifact-robust gait speed calculation method using spectro-temporal signal processing of accelerometer data. To this end, a new so-called modulation domain gait speed (MD-GS) metric is proposed and tested on data collected from forty older adults performing a 400-meter walk test with a sensor placed on a waist-worn belt. Average gait speed calculation is performed for each participant. Experimental results showed the proposed method achieved very high correlation ( $\rho =0.98$ ) with ground truth gait speeds, as well as low errors and error variability (0.05±0.14) m/s, thus substantially outperforming gait speed calculation using a well-known kinematic model. The increased robustness against artifacts, make it a promising solution for aging-in-home applications based on low-cost wearable devices.
ASSOCIATION OF CYP3A5 (6986G>A) GENE POLYMORPHSIM WITH ESSENTIAL HYPERTENSION AND BLOOD PRESSURE

Hypertension is the premier cause of the disease burden in developed as well as developing countries of the world. Hypertension affects approximately 37-55% population of the developed countries and the genetic susceptibility to it could be an outcome of the inherited differences in the capacity of sodium retention.CYP3A5 enzyme has been implicated in the regulation of blood pressure (BP) and thus, may serve as a potential risk factor for the development of hypertension. Carriers of the CYP3A5*1 allele had high, whereas homozygous carriers of the CYP3A5*3 allele exhibit low CYP3A5 expression in the kidney, where it represents the major isoform of the CYP3A family. The aim of the present hospital based case control study was to investigate the association of the CYP3A5*1 rs776746 (6986 A→) allele with BP in hypertension cases and healthy controls in a sample of Kashmiri population, a north India state. The study included 150 hypertension patients (78 males and 72 females; age (mean ± S.D) 60.55 ± 11.19 years) and normotensive controls (79males and 71 females; age (mean ± S.D) 60.11±9.92 years). The distribution of CYP3A5 genotype in hypertension cases and controls was assessed by PCRRFLP method. Logistic regression was used to assess the relationship between CYP3A5 genotype and the risk of essential hypertension. Although CYP3A5*1 genotype was higher in cases (10%) than in controls (3.66%), however, it did not reach a statistically significance It was found that CYP3A5*1 carriers showed decrease in systolic blood pressure (SBP ) by World Journal of Pharmaceutical Research SJIF Impact Factor 5.990 Volume 4, Issue 10, 912-921. Research Article ISSN 2277– 7105 Article Received on 04 Aug 2015, Revised on 26 Aug 2015, Accepted on 19 Sep 2015
Aerial Base Station Deployment in 6G Cellular Networks Using Tethered Drones: The Mobility and Endurance Tradeoff

Airborne base stations (BSs) (carried by drones) have a great potential to enhance the coverage and capacity of 6G cellular networks. However, one of the main challenges facing the deployment of airborne BSs is the limited available energy at the drone, which curtails the flight time. In fact, most current unmanned aerial vehicles (UAVs) can only operate for a maximum of 1 h. The need to frequently visit the ground station (GS) to recharge limits the performance of the UAV-enabled cellular network and leaves the UAV? s coverage area temporarily out of service. In this article, we propose a UAV-enabled cellular network setup based on tethered UAVs (tUAVs). In the proposed setup, the tUAV is connected to a GS through a tether, which provides the tUAV with both energy and data. This enables a flight that can last for days. We describe in detail the components of the proposed system. Furthermore, we list the main advantages of a tUAV-enabled cellular network compared to typical untethered UAVs (uUAVs). Next, we discuss the potential applications and use cases for tUAVs. We also provide Monte Carlo simulations to compare the performance of tUAVs and uUAVs in terms of coverage probability. For instance, for a uUAV that is available 70% of the time (while unavailable because of charging or changing the battery 30% of the time), the simulation results show that tUAVs with a 120-m tether length can provide up to a 30% increase in coverage probability compared to uUAVs. Finally, we discuss the challenges, design considerations, and future research directions to realize the proposed setup.
Stability of nut-based beverage made of Brazil nut (Bertholletia excelsa) and baru (Dipteryx alata Vogel)

People are looking for foods that promote health benefits and sometimes free of some compounds that are present because some individuals have restrictions to them, e.g. in protein foods. This trend has driven the food processing market to offer new products with a high nutritional content, low calorie, lower fat content, with specific characteristics such as lactose-free, gluten-free and convenience products, with the objective to meet the demands of consumers. In this context, watersoluble extracts appear as a plant-based beverage that have commercial and nutritional appeal and that also have been used as alternative to lactose-free assdiets. Thus, the aim of this study was to process and determine the stability during storage under refrigeration of a nut-based beverage made with 9,2% (w/w) brazil nut (Bertholletia excelsa), 21,7% of (w/w) baru (Dipteryx alata Vogel), 69,1% (w/w) of water, added of 10% (w/v) of sugar, expressed in sucrose. Analysis of color, pH, tritratable acidity, proximate composition, microorganisms and sensory evaluation were performed to determine the shelf life of the nut-based beverage. The beverage presented color ranging from red to yellow and complied with the microbiological standards established by current legislation, remaining microbiologically stable for at least 28 days. The water-soluble extract based on Castanha-do-Brasil and Baru obtained a high acceptance rate above 70% and achieved high scores for sensory attributes, with averages ranging between 7.09 and 7.26, on the hedonic scale, implying a shelf life greater than 28 days of storage under refrigeration.
Identification of Potent Inhibitors of COVID-19 Main Protease Enzyme by Molecular Docking Study

Within the span of a few months, the severe acute respiratory syndrome coronavirus, COVID-19 (SARS-CoV-2), has proven to be a pandemic, affecting the world at an exponential rate. It is extremely pathogenic and causes communicable infection in humans. Viral infection causes difficulties in breathing, sore throat, cough, high fever, muscle pain, diarrhea, dyspnea, and may lead to death. Finding a proper drug and vaccines against this virus is the need of the hour. The RNA genome of COVID19 codes for the main protease Mpro, which is required for viral multiplication. To identify possible antiviral drug(s), we performed molecular docking studies. Our screen identified ten biomolecules naturally present in Aspergillus flavus and Aspergillus oryzae fungi. These molecules include Aspirochlorine, Aflatoxin B1, Alpha-Cyclopiazonic acid, Sporogen, Asperfuran, Aspergillomarasmine A, Maltoryzine, Kojic acid, Aflatrem and Ethyl 3-nitropropionic acid, arranged in the descending order of their docking score. Aspirochlorine exhibited the docking score of – 7.18 Kcal/mole, higher than presently used drug Chloroquine (-6.2930522 Kcal/mol) and out of ten ligands studied four has docking score higher than chloroquine. These natural bioactive compounds could be tested for their ability to inhibit viral growth in- vitro and in-vivo.