Miracle-dz/UniFAR-FTUs huggingface dataset:
Looking before Crossing: An Optimal Algorithm to Minimize UAV Energy by Speed Scheduling with a Practical Flight Energy Model

Unmanned aerial vehicles (UAVs) are being widely used in wireless communication, e.g., collecting data from ground nodes (GNs), where energy is critical. Existing works combine speed scheduling, i.e., the controlling of speed, with trajectory design for UAVs, making it complicated to solve while loses focus on the fundamental nature of speed scheduling. We focus on speed scheduling by considering straight line flights, with applications in monitoring power transmission lines, roads, water/oil/gas pipes and rivers/coasts. By real-world flight tests, we disclose a speed-related flight energy consumption model, distinct from typical distance-related or duration-related models. Based on such a practical energy model, we develop the looking before crossing (virtual rooms) algorithm, where virtual rooms on the time-distance diagram represent the spatio-temporal constraint of GNs in wireless transmission. This algorithm is proved to be optimal in solving the offline problem, where all information is known before scheduling. For the online problem, i.e., GN information is not unavailable unless flies close, we propose an offline-inspired online heuristic. Simulation shows its performance is near the offline optimal. Our study on the practical flight energy model and speed scheduling sheds light on a new research direction on UAV-aided wireless communication.
Washing lignin precipitated from kraft black liquor

The washing properties of lignin precipitated from kraft black liquor were studied at varying precipitation pH, wash water pH, wash pressures and wash water temperatures. Significant experimental difficulties were encountered in several cases where the filter cake and/or the filter media were plugged, probably by re-dissolved/precipitated lignin. A peak in lignin concentration in the wash water between wash ratios 1-2 was detected, which may be attributed to a lowered ionic strength and a rather high pH in this area. The problems were minimised by applying a low wash water pH (approximately 1) and a low wash water temperature (20°C). After a wash ratio of approximately 1.75-2 is reached, no major effects on the remaining sodium levels can be achieved by additional washing. The final purity of the lignin varied considerably. These variations can be explained in some cases by a partial plugging of the filter cake, leading to an uneven distribution of wash water. In the successful experiments, the amount of impurities was reduced to very low levels, with sodium concentrations down to 0.065%. The sulphur content after washing was approximately 1.2% while the nitrogen content was below 0.86 mg/g. The lignin washing process could be modelled in a rather satisfactory way, with the advection-dispersion equation accounting for an average of 84% of the washing process, and with effective dispersion coefficients varying between 3.6·10-7 to 4.7·10-6. The equilibrium constant was very small in most cases. The modelling could be improved somewhat by adding an inlet mixing step to the model.
Covid-19: Mental Health Issues and Impact on Different Professions

The World Health Organization (WHO) defines health as "a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity" (Constitution WHO, 2005). Along with physical health, mental health is also very important to consider an individual as completely healthy and both are closely associated through various mechanisms (Funk et al., 2005). Mental health is often a misunderstood and neglected domain. Mental health is described by WHO as ―a state of well-being in which the individual realizes his or her own abilities, can cope with the normal stresses of life, can work productively and fruitfully, and can contribute to his or her community‖. Since 1950 many studies have reinforced the fact that medically sick patients International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 7 (2020) Journal homepage: http://www.ijcmas. com
Effect of brand communities on consumer engagement and trust

The use of Facebook as a social media platform has been cited to revolutionize the performance of different brands and firms globally. The performance of the products and brands has been attributed to the creation of Facebook media brand communities, whose level of engagement influences consumer product outcomes. This study attempted to establish to what extend Facebook social media brand communities and brand engagement on brand trust. The study established that the three attributes of Facebook brand communities positively influenced consumer brand engagement (shared consciousness (β=1.52, p=0.001), shared rituals (β=1.44, p=0.001), obligations to society (β=2.11, p=0.001). The study further established that social media brand engagement positively influenced brand trust. The study recommends that firms should effectively increase their product and brand promotion and engagement through Facebook. © 2020 by the authors. Licensee SSBFNET, Istanbul, Turkey. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Quali-Quantitative Analysis of Flavonoids for Mulberry Leaf and Fruit of ‘Suhyang’

BACKGROUND: Globally, mulberry (Morus sp.) is exploited for feeding leaf to silkworms in order to obtain silk fiber or for animal feedstock production. Also, mulberry fruit is known to a by-product that was produced from mulberry tree after harvesting leaves for silkworm rearing, as a yield and consumption of mulberry fruit was increased, it has been fixing to a new income crop.Mulberry leaves and fruits are used for the health benefits of human beings. Mulberry contains various bioactive components, such as alkaloids and flavonoids. Mulberry flavonoids are an important part of the diet because of their effects on human nutrition. The flavonoids in mulberry leaf and fruit of ‘Suhyang’(Morus alba L.) were determined. METHODSANDRESULTS:Flavonoids formulberry leaf and fruit of ‘Suhyang’ were analysed using ultrahigh performance liquid chromatography coupled with diode array detection and quadrupole time-of-flight mass spectrometry (UPLC-DAD-QTOF/MS) technique.AnUPLCDAD-QTOF/MS system was used, and identification of mulberry leaves constituentswas carried out on the basis of the complementary information obtained fromLC spectra, MS ions, and MS/MS fragments. The mulberry leaf (16 flavonoids) and fruit (9 flavonoids) were isolated and analyzed from Suhyang using UPLC-DAD-QTOF/MS chromatogram. To the best of our knowledge, Quercetin 3-O-(6''-O-malonyl) glucoside and quercetin 3-O-rutinoside (rutin) was detected on the highest content in leaf and fruit, respectively and further researchwill be devoted to evaluate their biological activity. CONCLUSION:Obtaininginformationabout theconcentration of functional materials inmulberry leaves could contribute to the development and promotion of processed, functional products and offer possible industrial use of ‘Suhyang’, holding promises to enhance the overall profitability of sericulture.
Long-term analysis of the Antarctic total ozone zonal asymmetry by MERRA-2 and CMIP6 data

Objectives. To analyze ozone monthly mean data from the MERRA-2 reanalysis and CMIP6 model. To determine Antarctic ozone asymmetry climatology for austral spring months (September, October, November) over the 1980–2014 period. Methods. Processing and visualization of the MERRA-2, CMIP6 data on total ozone and ozone partial pressure, following analysis, interpretation, and comparison. Getting 2D (total ozone column) and 3D (ozone partial pressure) monthly mean ozone values for the zonal band (0 ° –90 ° S) at pressure levels (1000–0.1 hPa) for each month of the chosen period. Calculating climatology of the total ozone and ozone partial pressure. Comparison of model and reanalysis of results. Results. The amplitude of ozone zonal asymmetry was calculated to provide the monthly, latitudinal, longitudinal and altitudinal analysis. It is shown that the largest ozone zonal asymmetry is observed in spring, especially in October, with dominant wave-1 structure with zonal minimum over 0 ° –90 ° W, and maximum over 120 ° –180 ° E longitudinal sectors. The area with high ozone content is located at the 40 ° –80 ° S zonal band and gradually shifts to the south from September to November. The model underestimates amplitude of ozone zonal asymmetry, especially in October. Conclusions. Latitudinal mean maximums in zonal mean ozone distribution are observed over 62 ° S, in October over 66 ° S, and in November over 68 ° S for MERRA-2 and over 64 ° S, 65 ° S and 66 ° S respectively for CMIP6. The poleward shift of ozone latitude maximum continues until March with decreasing of ozone level, but in April, the shift reverses its direction to equatorward and ozone level starts to increase, however in the model this process is slower. In September the shift again becomes poleward. In the longitudinal distribution wave-1 pattern dominates with a shift of longitude ozone minimum. From September to October the shift is eastward, and from October to November westward by MERRA-2 data and only eastward by CMIP6 data. The highest difference in altitude ozone distribution is observed during October in the stratosphere between ozone zonal minimum and maximum points and reaches approximately 68% (44%) of the zonal average value at 65 ° S (65.4 ° S) by MERRA-2 (CMIP6) data. MERRA-2 profiles unlike CMIP6 one show higher location of altitudinal maximum over the zonal minimum and lower over the zonal maximum with the zonal mean in the middle. All three CMIP6 profiles have the same height of altitude maximum.
Phylogenetics: A Catalyst for a Biophilic Revolution?

A biology framework in Environmental Education can inspire biophilia, the love for the complex array of lifeforms on this planet, in students. In this paper, a simple, multi-scaled phylogenetic tree is presented to express such a framework. When viewing life from a framework such as a phylogenetic tree, the human species is seen as just one part of something vastly complex. This view is contrasted to another framework, more anthropocentric in nature, that seems to be more typical in the developed world. Challenging students to view the role of humanity from a biocentric, rather than anthropocentric, framework can lead to a greater appreciation of the diversity of life. This, in turn, could be a catalyst for a biophilic revolution, reducing environmental problems and lead to a more ecologically-minded status quo.
Effect of resistance elicitors on the biology and feeding preference of Spodoptera frugiperda (J.E.Smith) (Lepidoptera: Noctuidae) in corn

This study searches for efficient and low environmental impact alternatives to control Spodoptera frugiperda. Application of elicitors capable of inducing resistance in plants has already been highlighted. The elicitors trigger the plant's defense capacity against attack of herbivores and phytopathogenic organisms. Thus, the present study aimed to evaluate the effect of resistance elicitors on some biological aspects and food preference of Spodoptera frugiperda (J. E. Smith) in corn in laboratory conditions. The treatments consisted of: Control (distilled water); Biofertilizer (25 mL L -1 ); Acibenzolar-S-methyl-ASM (2 mg mL -1 ); Potassium silicate (10 mL L -1 ) and T5: Potassium silicate (10 mL L -1 ) + ASM (2 mg mL -1 ). The treatments were foliar application of elicitors with adjustable jet pressure sprayer to the whole plant with an amount of 20 mL of the solution per plant. The larval phase (weight at 7 and 14 days, duration and viability); pupal phase (weight after 24 h, duration and viability) and adult phase (number of eggs / female, number of eggs/posture/female and longevity of adults) were evaluated. Free-choice and no-choice food preference test experiments were also carried out on 1st and 3rd instar caterpillars, after which the leaves collected at 5 and 10 days after spraying. The results showed that Acibenzolar-S-methyl induces resistance in corn plants when applied either alone or together with potassium silicate. Therefore, it adversely affects development of S. frugiperda. The leaves treated with Potassium Silicate + ASM were less preferred and consumed by 1st and 3rd instar caterpillars in free-choice food preference test.
Self-diagnosed Depression of Chinese High School Students: Do Gender and Urban-Rural Location Make a Difference?

Depression is a worldwide common mental illness, and its burden is on the rise globally, particularly for adolescents. Surprisingly, a review of the literature indicates that there are much fewer studies conducted using Chinese adolescents as study subjects, which is not commensurable to China being the fastest developing country with 1/5 of the global population. The purpose of this study is to understand the self-diagnosed depression level of Chinese adolescents and examine if gender and rural-urban location make a difference. Using the Beck Depression Inventory (BDI), 72 high school students in two high schools of different locations in Southern China were surveyed. The survey data were analyzed using descriptive statistics and univariate statistical t-tests. Results indicate that the students have on average a mild mood disturbance, while 18% of them had moderate or severe depression. The mean level of male students' mood disturbance is much higher than that of female students, although it is not statistically significant. Urban students' mood disturbance level is significantly higher than rural students. This study supports the efficient implementation of depression research in China by providing a snapshot of high school students' mental health from the perspective of the surveyed results through self-assessment. Implications for high school mental health counseling and further research are discussed.
A hybrid feature selection algorithm combining information gain and genetic search for intrusion detection

Network attacks are one of the main threats to the stable operation of smart grid equipment. As a real-time monitoring system to prevent network attacks, intrusion detection is widely used in smart grid protection. However, the massive data in the network transmission process contains a large number of redundant and irrelevant features, which makes it difficult for the intrusion detection system to process in time and reduce the efficiency. Feature selection is a method to solve this kind of problem. It can improve the speed of intrusion detection by filtering the characteristics of massive data. Therefore, a hybrid feature selection algorithm which combines information gain and genetic search to improve the work efficiency of intrusion detection systems is proposed. The algorithm is mainly divided into three parts. Firstly, the information gain value of all features is calculated by using information gain, according to which all features are ordered, and the ordered features is ranked according to an exponential increase strategy; secondly, the ranked features is used to guide the genetic algorithm search process, and a new fitness function can be used to control the search direction of genetic algorithm; finally, a classification algorithm is used to test the dataset after feature selection. In experiments, by comparing with other feature selection algorithms on 5 sets of high-dimensional UCI datasets, it is concluded that the IGExpGA proposed in this paper significantly improves the detection rate and detection speed. More importantly, in the KDD1998 network data, the algorithm proposed improves the detection rate to 98.8%, which is significantly better than other algorithms.
The Impact of remittances on household food security: Evidence from a survey in Bangladesh

ABSTRACT This paper examines the impact of international remittances on household food security, using robust food security measurement indices constructed from a cross-section sample of rural households in Bangladesh. A Two Stage Least Square Instrumental Variable Method (2SLS-IV) and Generalised Method of Moments (GMM) were used to regress food security measurement indicators with remittances and households socioeconomic and demographic variables. Results indicate that remittances influence food security conditions significantly and therefore represent a critical component of household food security. In general, remittances are positively correlated with household food-related consumption expenditures. The results also indicate that the presence of remittances reduces food-related uncertainties and provides a coping strategy for the household to counterbalance food-related shocks and improves the quality of diet in remittance-receiving households. Overall, it seems that emigration of a household member and consequent remittance flows increase the probability of a household being food secure.
Use of RNA and DNA to Identify Mechanisms of Microbial Community Homogenization

Biotic homogenization is a commonly observed response following conversion of native ecosystems to agriculture, but our mechanistic understanding of this process is limited for microbial communities. In the case of rapid environmental changes, inference of homogenization mechanisms may be confounded by the fact that only a minority of taxa is active at any given point. RNA- and DNA-based community inference may help to distinguish the active fraction of a community from inactive taxa. Using these two community inference methods, we asked how soil prokaryotic communities respond to land use change following transition from rainforest to agriculture in the Congo Basin. Our results indicate that the magnitude of community homogenization is larger in the RNA-inferred community than the DNA-inferred perspective. We show that as the soil environment changes, the RNA-inferred community structure tracks environmental variation and loses spatial structure. The DNA-inferred community loses its association with environmental variability. Homogenization of the DNA-inferred community appears to instead be driven by the range expansion of a minority of taxa shared between the forest and conversion sites, which is also seen in the RNA-inferred community. Our results suggest that complementing DNA-based surveys with RNA can provide unique perspectives on community responses to environmental change. IMPORTANCE Two primary mechanisms by which community homogenization occurs are: 1) the loss of environmental heterogeneity driving community convergence, and 2) increased rates of biotic mixing, driven by exotic invasions or range expansions. Better identifying these mechanisms could help inform future mitigation strategies. Only a minority of soil taxa tends to be active at any time, which makes identifying these mechanisms difficult. To circumvent this problem, we measured prokaryotic community structure in two ways: RNA-based inference (which should enrich for active taxa), and DNA-based inference (which includes active and inactive taxa) along a gradient of land use change. Our results suggest that changes to soil heterogeneity impact the RNA-inferred community, while range expansions contribute to the homogenization of both DNA- and RNA-inferred communities. Thus, RNA-based community inference may be a more sensitive indicator of environmentally driven homogenization, and researchers interested in microbial responses to rapid environmental change should consider this method.
Ultrafast electron transport in metallic antiferromagnetic 
Mn2Au
 thin films probed by terahertz spectroscopy

The ultrafast electron transport is central to the requirement of all-electrically controlled spintronics in metallic collinear antiferromagnetic (AFM) ${\mathrm{Mn}}_{2}\mathrm{Au}$ thin films within the terahertz (THz) range. Here we use the THz time-domain spectroscopy to measure the conductivity spectra of ${\mathrm{Mn}}_{2}\mathrm{Au}$ thin films with different thicknesses and temperatures. We demonstrate an onset of carrier localization in ${\mathrm{Mn}}_{2}\mathrm{Au}$ with decreasing the film thickness from 15 to 5 nm. By using optical pump-THz probe spectroscopy, we found the surface trapping states in the thinnest ${\mathrm{Mn}}_{2}\mathrm{Au}$ film limit its photoconductivity significantly. The DC conductivity and scattering time become larger and longer with decreasing temperature for all samples, which suggests that ${\mathrm{Mn}}_{2}\mathrm{Au}$ behaves in a typical metallic fashion. The THz optical and conductivity properties of ${\mathrm{Mn}}_{2}\mathrm{Au}$ films will advance our understanding of ultrafast electronic transport processes in AFM ${\mathrm{Mn}}_{2}\mathrm{Au}$ thin films.
Reaction-Diffusion Mechanisms Underlying Hirschprung’s Disease and their Practical Impications

The erratic extent of aganglionic and hypoganglionic segments in Hirschsprung’s disease (HD) makes it difficult to predict the amount of the intestine to remove in order to restore the proper functional motility. Our aim was to assess whether the embryonic rostro-caudal intestinal colonization by neuroblasts from the neural crest follows a predictable pattern in HD. In touch with Turing’s reaction diffusion model (RD), which describes biological patterns (such as leopard spots and lung branching morphogenesis) in terms of interactions/competitions between activating and inhibiting factors, we hypothesized that intestinal neural density could be triggered by local gut factors that counteract the proximal-distal embryonic progression of neural progenitors. While the neuronal number is approximately the same throughout the whole intestine in healthy subjects, in HD neural density decreases rostro-caudally towards the rectal region, due to an augmented activity and concentration of distal local inhibitors. In order to prove our hypothesis of HD’s nervous rostro-caudal adjustments driven by Turing-like processes, we compared the neuronal density patterns achieved through RD models’ simulations with the neuronal numbers detected in different colonic regions from affected children. We showed that the virtual and the real plots display fully overlapping and matching features. The fact that neuronal decreases in impaired colons match Turing equations’s previsions points towards the human intestine (both healthy and sick) as colonized through a diffusive proximal-distal neural pattern that is predictable, allowing us to straightforwardly calculate the length of the gut to resect during surgical procedures for HD.
SOYBEAN LEAF DISEASES DETECTION AND CLASSIFICATION USING RECENT IMAGE PROCESSING TECHNIQUES

Purpose: India is an agricultural country and soybean production is one of the major sources of earning. Due to the major factors like diseases, pest attacks, and sudden changes in the weather condition, the productivity of the soybean crop decreases. Automatic detection of soybean plant diseases is essential to detect the symptoms of soybean diseases as early as they appear on the growing stage. This paper proposed a methodology for the analysis and detection of soybean plant leaf diseases using recent digital image processing techniques. In this paper, experimental results demonstrate that the proposed method can successfully detect and classify the major soybean diseases. Methodology: MatLab 18a is used for the simulation for the result and machine learning-based recent image processing techniques for the detection of the soybean leaf disease. Main Findings: The main finding of this work is to create the soybean leaf database which includes healthy and unhealthy leaves and achieved 96 percent accuracy in this work using the proposed methodology. Applications of this study: To detect soybean plant leaf diseases in the early stage in Agricultural. The novelty of this study: Self-prepared database of healthy and unhealthy images of soybean leaf with the proposed algorithm.