Miracle-dz/UniFAR-FTUs huggingface dataset:
Salicylic acid alleviates salt stress on guava plant physiology during rootstock formation

ABSTRACT Guava is a fruit widely produced in Northeast Brazil, a region that has sources of water with high levels of salts, making it difficult for irrigated fruit production to expand. Thus, it is extremely important to search for techniques that allow the management of these waters in irrigated agriculture. Thus, the objective of present study was to evaluate the photosynthetic pigments, the quantum yield of photosystem II, and the intercellular leakage of electrolytes in the leaf blade of ‘Paluma’ guava seedlings as a function of irrigation with water of different salinities and foliar application of salicylic acid during rootstock formation phase. The experiment was conducted in a greenhouse, using the randomized block design in a 5 × 5 factorial arrangement, which consisted of five values of electrical conductivity of water - ECw (0.6, 1.5, 2.4, 3.3, and 4.2 dS m-1) and five concentrations of salicylic acid (0, 0.8, 1.6, 2.4, and 3.2 mM L-1), with four replicates, and two plants per plot. Salicylic acid up to 1.3 mM L-1 increased the relative water content and decreased electrolyte leakage in the leaf blade of ‘Paluma’ guava seedlings. Foliar application of salicylic acid at a concentration of 1.7 mM L-1 attenuated the effects of salt stress on chlorophyll a of guava seedlings irrigated with water of up to 1.6 dS m-1. The deleterious effects of salt stress on carotenoid concentration and quantum efficiency of photosystem II were not attenuated by the application of salicylic acid.
Attack and Defense: Adversarial Security of Data-Driven FDC Systems

In modern industries, data-driven fault detection and classification (FDC) systems can efficiently maintain industrial security and stability, while the security of the data-driven FDC system itself is rarely or even never considered. The security problem named adversarial vulnerability is the intrinsic of data-driven machine learning models, which will give incorrect predictions under the maliciously perturbed input data. This paper presents a work on this new security topic of the data-driven FDC systems, by 1) summarizing and comparing various recent and typical adversarial attack and defense methods for fault classifiers; 2) proposing novel attack and defense techniques for unsupervised fault detectors; 3) constructing a novel industrial adversarial security benchmark on FDC systems in the Tennessee-Eastman process (TEP) dataset; 4) exploring and discussing which attack is most potentially threatening for FDC systems and which defense technique is most applicable to mitigate attacks. The results reveal unique security properties of FDC systems, mainly including 1) for fault classifiers, black-box attack is close to the attack strength of white-box FGSM and the universal transferable attack is not significantly stronger than random noise; 2) weak adversarial training is excellent with high adversarial accuracy improvement and negligible clean accuracy decrease; 3) fault detectors are intrinsically more robust, and can be well protected by strong adversarial training. More intriguing properties and profound insights are demonstrated in the paper. This pioneering work could guide researchers and practitioners in discovering and navigating the field of FDC system adversarial robustness, outlining the research directions and open problems.
Exploring the Health and Social Needs of Community Residents Using an Online Community Care Platform: Linkage to the International Classification of Functioning, Disability, and Health

Objectives This study aimed to analyze the outcomes of the Comprehensive Health and Social Need Assessment (CHSNA) system, which identifies community residents’ health and social needs, and to link these needs with the International Classification of Functioning, Disability, and Health (ICF). Methods Adult community residents in a metropolitan city in Korea were recruited. They were asked to assess their health and social needs via the CHSNA system, which was integrated into an online community-care platform. Three assessment steps (basic health assessment, needs for activities of daily living, and in-depth health assessment) associated with five ICF components were used to evaluate physical health impairment, difficulties in activities and participation, and environmental problems. The final list of health and social needs was systematically linked to the domains and categories of the ICF. Only data from participants who completed all three assessment steps were included. Results Wide ranges of impairments and difficulties regarding the daily living activities, physical health, and environmental status of the community were recorded from 190 people who completed assessments of their health and social needs by the CHSNA system. These participants reported various health and social needs for their community life; common needs corresponded to the ICF components of body functions and activities/participation. Conclusions The ICF may be suitable for determining the health-related problems and needs of the general population. Possible improvements to the present system include providing support for completing all assessment steps and developing an ICF core set for an enhanced understanding of health and social needs.
Using multivariate adaptive regression splines and classification and regression tree data mining algorithms to predict body weight of Nguni cows

ABSTRACT The study was performed to determine the association between body weight and biometric traits and to examine the effect of biometric traits on the live body weight of Nguni cows using Multivariate Adaptive Regression Splines (MARS) and Classification and Regression Tree (CART) data mining algorithms. In total, 105 Nguni cows aged three to four years were used for body weight (BW) and biometric traits viz; head width (HW), head length (HL), ear length (EL), body length (BL), rump height (RH), withers height (WH), sternum height (SH), body depth (BD), bicoastal diameter (BCD), rump width (RW), rump length (RL) and heart girth (HG). Coefficient of determination (R2), adjusted coefficient of determination (Adj.R2), root-mean square error (RMSE), standard deviation ratio (SD ratio) and Pearson correlation between actual and predicted values were predicted to find out the best fit models. MARS models in prediction of BW presented as the best fit as compare with CART model with higher R2 = 0.993 and Adj.R2 = 0.991 with the lowest RMSE = 5.97 and SD ratio = 0.081. In this study, MARS models established are the significant statistical tools that might be used for describing studied breed standards for breeding purposes.
Prevalence of Anemia and Associated Factors Among Under Five Children Attending Public Health Facilities in Hargeisa City, Somaliland 2020

: Background: Anemia is a widespread public health problem associated with an increased risk of morbidity and mortality. It is considered to be an important contributing factor to the global burden of disease. Affecting both developed and developing countries, it has an impact not only on human health and productivity but in the process it affects the socio-economic development of a nation. Objective: this study is to assess the prevalence of Anemia and associated factors among under-five children attending public health facility in Hargeisa, Somaliland 2020. Method: facility based cross sectional study design was conducted in Hargeisa, Somaliland from April to July , 2020. Total of 417 of children were participating and selected consecutively in the study. Data were collected by face to face interview with the mothers/caregivers of the child, by using semi structural questionnaire. Blood sample were collected from each child by using portable Hemocue Hb201 analyzer. Data were entered on to Epi data and exported to SPSS software version 20 for analysis, Descriptive statistics, Bivariate and Multivariate analysis were conducted. Crude odds ratio and adjusted odds ratio with 95% confidence interval was calculated. Statistical significance was set at p-value less than 0.05. Result: the overall prevalence of Anemia was 49.4% (95% CI (44.8-54.2)), 139 (33.3%) had mild anemia, 56 (13.4%) had moderate anemia, and 11 (2.6%) had severe anemia. Age of the child 6–11, 12–23 and 24-35 months (AOR=10.478 (95% CI: 4.113-26.694), (AOR =4.909 (95% CI: 1.826-13.198), (AOR= 4.433 (95% CI: 1.754-11.208, illiterate mothers and able Read and write (AOR = 2.998 (95% CI: 1.439-6.249), (OR=3.803 (95% CI: 1.720-8.411)), early (<6months) and late introduction of complementary foods (AOR = 2.626; 95% CI: (1.422-4.851), (AOR = 2.680 (95% CI: 1.401-5.126), diarrhea (AOR= 2.422 (95% CI: 1.371-4.278), underweight (AOR= 2.533 (95% CI: 1.439-4.460), wealth (AOR = 1.79 (95% CI: 1.066-3.020), deworming (AOR 3.032 (95% CI: 1.839-5.000)) were factors significantly associated with Anemia. Conclusion : The prevalence of anemia in this study is higher and it was severe public health problems according to WHO classification. Age of the child, mother’s education, complementary feeding, and diarrhea, underweight and deworming were factors significantly associated with anemia among under-five children This study well recommended interventions to improve the health status and infant and young child feeding practices need to be prioritized to prevent deficiency of anemia.
Herbal oils in healthcare: a review

The herbal medicine market has grown considerably as an alternative currently used for the application of plants in the treatment of various diseases. In this environment, studies on the bioactivity of essential oils and the search for those that have antimicrobial, analgesic, anti-inflammatory, anti-tumor, antioxidant properties and also oils that can inhibit key enzymes are highlighted. However, research on the use of plants in the pharmaceutical industry, chemical composition of native species and possible biological activities are still scarce. Therefore, studies for the knowledge of native species with therapeutic potential gain great relevance. This study carried out a review of the research already done on essential oils from species with potentially promising biological activities for the contribution of the sustainable use of biodiversity and the relevance of their medicinal potential.
Improved Numerical Method for Aw-Rascle Type Continuum Traffic Flow Models

Continuum traffic flow models are essentially nonlinear hyperbolic systems of partial differential equations. Except for limited specific cases, these systems must be solved numerically. Mathematical structure of continuum models can be different for each class of models. As a result, suitable numerical schemes for some classes may not be efficient for others. In this study, an improved numerical method is proposed for a class of second-order traffic flow models. The method is based on McCormack scheme, which is a widely-used method for non-homogeneous second-order traffic flow models, but fails to produce reasonable results for homogeneous models including Aw-Rascle type models which are the focus of this paper. It is shown that this is mainly due to spurious numerical oscillations. Smoothing methods to overcome these issues are studied and applied. Central dispersion and artificial viscosity (AV) methods are incorporated into the standard McCormack scheme and tested. To reduce numerical diffusion, a total variation diminishing Runge-Kutta time stepping scheme is applied. Results show the capability of the proposed methods, and especially the AV method, to eliminate the oscillations of the standard McCormack scheme as well as controlling numerical diffusion.
Pandemic Priors

The onset of the COVID-19 pandemic and the great lockdown caused macroeconomic variables to display complex patterns that hardly follow any historical behavior. In the context of Bayesian VARs, an off-the-shelf exercise demonstrates how a very low number of extreme pandemic observations bias the estimated persistence of the variables, affecting forecasts and giving a myopic view of the economic effects after a structural shock. I propose an easy and straightforward solution to deal with these extreme episodes, as an extension of the Minnesota Prior with dummy observations by allowing for time dummies. The Pandemic Priors succeed in recovering these historical relationships and the proper identification and propagation of structural shocks.
Timetable Optimization for Regenerative Energy Utilization in Subway Systems

In subway systems, kinetic energy can be converted into electrical one by using regenerative braking systems. If regenerative energy (RE) is fully used, the energy demands from power grid can be dramatically reduced. Since energy storage systems usually have a high cost, they are not considered in this work. Thus, RE has to be immediately utilized by accelerating trains; otherwise, it is wasted into heat via resistors. Timetable optimization methods are often used to coordinate accelerating and braking trains at a station, such that RE can be optimally used by the former. To improve RE utilization (REU) in a subway line, we propose a timetable optimization problem and establish its mathematical model. Many realistic constraints with the decision variables, i.e., headway time and dwell time, are considered. Then we design an improved artificial bee colony (IABC) algorithm to solve the problem. Several numerical experiments are conducted based on the actual data from a subway line in Beijing, China. The correctness of the mathematical model and effectiveness of IABC are shown by comparing it with commercial software CPLEX and a genetic algorithm, respectively. The impact of the decision variables on REU is analyzed, which helps to improve the timetable currently used in this subway line. We also test the robustness of the optimized timetable when certain disturbance takes place.
Approach to the Weight Estimation in the Conceptual Design of Hybrid-Electric-Powered Unconventional Regional Aircraft

The present work deals with the development of an innovative approach to the weight estimation in the conceptual design of a Hybrid-Electric-Powered (HEP) Blended Wing Body (BWB) commercial aircraft. In the last few decades, the improvement of the environmental impact of civil aviation has been the major concern of the aeronautical engineering community, in order to guarantee the sustainable development of the system in presence of a constantly growing market demand. The sustained effort in the improvement of the overall efficiency of conventional aircraft has produced a new generation of vehicles with an extremely low level of emissions and noise, capable of covering the community requirements in the short term. Unfortunately, the remarkable improvements achieved represent the asymptotic limit reachable through the incremental enhancement of existing concepts. Any further improvement to conform to the strict future environmental target will be possible only through the introduction of breakthrough concepts. The aeronautical engineering community is thus concentrating the research on unconventional airframes, innovative low-noise technologies, and alternative propulsion systems. The BWB is one of the most promising layouts in terms of noise emissions and chemical pollution. The further reduction of fuel consumption that can be achieved with gas/electric hybridisation of the power-plant is herein addressed in the context of multidisciplinary analyses. In particular, the payload and range limits are assessed in relation to the technological development of the electric components of the propulsion system. The present work explores the potentialities of an energy-based approach for the initial sizing of a HEP unconventional aircraft in the early conceptual phase of the design. A detailed parametric analysis has been carried out to emphasise how payload, range, and degree of hybridisation are strictly connected in terms of feasible mission requirements and related to the reasonable expectations of development of electric components suitable for aeronautical applications.
The Influence of Staffs’ Knowledge on Preparedness of Catholic Mission Hospitals for Health Service Delivery during Emergency Inflow of Patients in Nairobi County, Kenya

Purpose: To determine the influence of staffs’ knowledge on preparedness of catholic mission hospitals for health service delivery during emergency inflow of patients in Nairobi County, Kenya. Methodology: A cross sectional descriptive study design was used with quantitative approach for data collection and analysis. Four tier-3 Catholic Mission Hospitals were purposively selected and a stratified random sample of 647 members of staff from different cadres was taken. A structured questionnaire was used to collect data. Data was analyzed using STATA software v.16, where descriptive statistics were presented using frequencies and percentages whereas inferential statistics were presented using correlation and regression analysis. Findings: The study found out that staff training and exercises for knowledge and skills influenced preparedness of Catholic Mission Hospitals for health service delivery during emergency influx of patients. A positive and significant relationship was found at (r=0.211; p<0.01). This means that the hospitals are perceived as prepared for health service delivery during emergency influx of patients. However, staff drills (staff exercises) at (r = -0.147; p<0.05) were found insignificantly influencing services delivery. This means that the hospitals would be unprepared even if staff drills were in place. Recommendations: The study recommends that the managers of catholic hospitals should have scheduled staff trainings and drills for efficient and timely response in times of need for emergency service deliver. Policy guidelines on skills acquisition for the staff in the health institutions need to be developed to guide the trainings and frequent drills to sharpen the theory and practice of the healthcare team.
Changes in Chemical Composition of Betung Bamboo (Dendrocalamus asper) after Alkali Immersion Treatment under Various Immersion Times

This research aimed to analyze the change in chemical composition of the betung bamboo (Dendrocalamus asper) strands after alkali immersion treatment under various immersion times. The bamboo culms were converted into strands with the target length, width, and thickness of 70, 25, and 0.5 mm, respectively. Strands were alkali immersion-treated with 1% NaOH solution for 1, 2, and 3 h. Preparation of powder for chemical component analysis refers to the Technical Association of the Pulp and Paper Industry (TAPPI) standard T 264 cm-07 regarding the preparation of wood test samples for chemical analysis. Structural and non-structural bamboo strand chemical components such as holocellulose, alpha-cellulose, hemicellulose, klason lignin, and extractives were analyzed. The results showed that alkali immersion treatment decreased the hemicellulose content from 21.55% before treatment to 20.30% after 3 h immersion. Thus, it changed the holocellulose and alpha-cellulose composition. Alkali immersion treatment also changed the extractive substances dissolved in cold water, hot water, 1% NaOH, and ethanol-benzene solution. The decrease in hemicellulose, molecular weight lignin, and extractive substances would be beneficial for bamboo-oriented strand board manufacture to improve strand adhesion, dimensional stability, mechanical properties, and durability against biological agents attack. Keywords: alkali immersion times, alkali immersion treatment, bamboo, chemical components, pre-treatment
Electroweak radiative B-decays as a test of the Standard Model and beyond

Recently the radiative B-decay to strange axial-vector mesons, B--> K1(1270) gamma, was observed with a rather large branching ratio. This process is particularly interesting as the subsequent K1-decay into its three-body final state allows us to determine the polarization of the photon, which is mostly left(right)-handed for Bbar(B) in the Standard Model while various new physics models predict additional right(left)-handed components. In this thesis, a new method is proposed to determine the polarization, exploiting the full Dalitz plot distribution, which seems to reduce significantly the statistical errors on the polarization parameter lambda_gamma measurement.This polarization measurement requires, however a detailed knowledge of the K1--> K pi pi strong interaction decays, namely, the complex pattern of the various partial wave amplitudes into several possible quasi-two-body channels as well as their relative phases. A number of experiments have been done to extract all these information while there remain various problems in the previous studies. In this thesis, we investigate the details of these problems. As a theoretical tool, we use the 3P0 quark-pair-creation model in order to improve our understanding of strong K1 decays.Finally we try to estimate some theoretical uncertainties: in particular, the one coming from the uncertainty on the K1 mixing angle, and the effect of a possible ``off-set'' phase in strong decay S-waves. According to our estimations, the systematic errors are found to be of the order of sigma(lambda_gamma)^th K* e^+ e^-, Bd--> K* gamma and Bs--> phi gamma, for the determination of the ratio of the Wilson coefficients C7gamma^‘eff/C7gamma^eff. We show an example of the potential constraints on C7gamma^‘eff/C7gamma^eff. in several scenarios of supersymmetric models.
A Sulfated Polysaccharide from Red Algae (Gelidium crinale) to Suppress Cells Metastasis and MMP-9 Expression of HT1080 Cells

Sulfated polysaccharides from red algae have a variety of biological activities, especially antitumor activities. Matrix metalloproteinase-9 (MMP-9) is a proteolytic metalloenzyme that degrades the central part of the extracellular matrix (ECM) and promotes tumor metastasis. In this research, we have investigated the influence and mechanism of GNP (sulfated polysaccharide from Gelidium crinale) on tumor metastasis and MMP-9 expression of human fibrosarcoma (HT1080) cells. The results inflected that the concentration of GNP below 100 μg/mL has no toxicity to HT1080 cells, but showed excellent activity in inhibiting cells migration and invasion. In addition, GNP effectively inhibits the mRNA of MMP-9 and reduces its expression and activity by regulating nuclear factor-kappa B (NF-κB), mitogen-activated protein kinases (MAPK) and mTOR/PI3K/Akt signaling pathways. GNP has great potential as MMP-9 inhibitor and could be developed as a functional food or drug to prevent tumor metastasis.
Level Of Anxiety Among College Students During COVID-19 Pandemic

Background: The Coronavirus outbreak which has become a pandemic for more than a year could potentially cause health problems, including mental health. Mental health problems can occur to any group of people including the students because of the policy of learning from home using online learning technology. Mental health disorders or problems that may occur during the COVID-19 pandemic are high levels of anxiety. Methods: It was quantitative with a cross-sectional design study. The sample was 344 respondents that were collected through purposive sampling. It was available from 1 to 12 August 2021 using Depression Anxiety Stress Scales (DASS-42) Questionnaire via a google form. The data was analyze through frequency for univariate analysis and chi-square for bivariate analysis using statistical software Results: Based on the level of anxiety, the normal level was 13.1%; mild level was 8.7%; moderate level was 21.8%; severe level was 23.8%; extremely severe was 32.6%. The majority of respondents showed an extremely severe level of anxiety with a percentage. According to bivariate analysis, gender variable has a significant correlation to anxiety level while others have not. Conclusion: It is recommended for the college to provide and develop student counseling centers in order to support the psychological condition of students.