Miracle-dz/UniFAR-FTUs huggingface dataset:
Markers of atherosclerotic risk in patients with non-alcoholic fatty liver disease: A preliminary study

Introduction: The prevalence of Non-Alcoholic Fatty Liver Disease (NAFLD) is rising continuously. Cardiovascular disease is one among the leading causes of morbidity and premature mortality in patients with NAFLD. Aims and Objectives: To determine the risk of atherosclerosis in NAFLD subjects diagnosed by USG at K.S. Hegde Charitable hospital. Materials and Methods: A cross-sectional study involving 203 persons diagnosed with NAFLD were included in the study. Subjects with alcoholic liver disease, renal failure, tuberculosis, hepatitis B and/or C and those on lipid lowering drug were excluded from the study. Lipid profile was measured and Atherogenic Index of Plasma (AIP) was calculated as log (TG/HDL-c). Categorization of the subjects with respect to risk of atherosclerosis was done based on serum LDL-c, non HDL-c and AIP. Statistical analysis was done using Chi Square test and p value < 0.05 was considered significant. Results: More than normal values were observed for serum total cholesterol, LDL-c, triglyceride and non HDL-c in high percentage of NAFLD subjects (76.8%, 84.7%, 70.4% and 72.4% respectively). Serum HDL-c level was low in 53.2% subjects. 51.2% of subjects had high AIP and 23.6% had moderately high AIP. Conclusion: Results of categorization of the subjects with respect to risk of atherosclerosis based on serum LDL-c, non HDL-c and AIP showed that high percentages of subjects were in moderate and high risk categories. AIP is probably a better marker to determine the risk of atherosclerosis.
Organizational Commitment and Labor Satisfaction. Case: A University Organization in the State of Morelos. México

This article measures two organizational factors of importance for every organization: labor satisfaction and organizational commitment. The analysis is made under the perspective of the sociology of organizations: Frederick Herzberg's theory of the two factors of motivation (hygienic and motivational) and Meyer and Allen's model of the three components of organizational commitment (1990). The methodology is empirical, descriptive and quantitative. The study was carried out with a sample of 59 employees, classified as reliable personnel of the Academic Secretary of an Institution of Higher Education (IES) in the city of Cuernavaca, Morelos. The instruments used were two questionnaires emanated from the theory itself with the purpose of knowing aspects related to the two study variables. This instrument allowed to identify the types of organizational commitment and the levels of work satisfaction and satisfaction that exist in the university organization.
Going green in logistics: The case of small and medium-sized enterprises in Poland

Abstract Aim/purpose – The aim of the paper is to identify the features of ‘green’ small and medium-sized enterprises operating in Poland. Design/methodology/approach – The paper is based on a quantitative approach and a group of 200 small and medium-sized enterprises operating in Poland were examined. The classification tree method was used to analyze the data gathered. Findings – The ‘green’ small and medium-sized enterprises operating in Poland were characterized and their important features were identified, e.g., belonging to the TFL (Transport Forwarding Logistics) sector and a direct relationship with the supply chain leader. In the case of enterprises from the TFL sector, their area of activity is a natural environment for the development of ‘green logistics’ practices. In turn, the supply chain leader usually pushes for specific solutions aimed at achieving the assumed goals, including environmental goals. Research implications/limitations – The research results enable the identification process of small and medium-sized enterprises interested in implementing the ‘green logistics’ concept and, consequently, their support. Nevertheless, small and medium-sized enterprises operating in Poland were the only examined, thus the research findings cannot be generalized for other countries. However, the paper could be a starting point for comparative analyses on an international scale. Originality/value/contribution – The development of ‘green logistics’ among small and medium-sized enterprises in Poland is still not recognized by researchers. The paper is a valuable addition to this research gap.
Bird composition of different valley habitats after land-use changes in Northern Honduras

The northern coast of Honduras is potentially covered with tropical rainforests, reaching from the Caribbean Sea up to the cloud forests of the Pico Bonito summits. Therefore, it was blessed with the mega-diverse avifauna of the Central American humid neotropics. Although local bird species have been generally well documented, there are hardly any updates on the biodiversity of northern Honduras. Thus, this study contributes to our knowledge of the natural shift of bird life, following up the Cangrejal River with its different slight land use intensification in the region. Standardized bird records along the valley are analyzed, reaching from the beaches of La Ceiba up to the managed rainforests of El Toncontins in the lower montane rainforests. Nine points were checked over the course of at least 6 days, taking point counts between 16 March and 20 June 2005. A NMDS of the joined nine point-lists elucidates four main groups, namely the beach/city ecosystems, open habitats along the river banks, slightly cleared forests (park landscape), and a mature rainforest. In total, 115 bird species, from 102 genera and 44 families, were found in 2005. As methods are limited, results can represent merely a prodromus of bird composition of neotropical valleys of the Central American isthmus. However, avi-diversity is affected by forest degradation and increasing land-use changes. Since deforestation is still soaring in the region, bird species composition should be monitored, as it will be as dynamic as land use changes in the region.
M&SH Questionnaire – a simple method of measuring mental and social health from the perspective of public health prevention

Background & Study Aim: The necessity to estimate mental health and social health, even in the simplest way, is not questioned. Both phenomena belong to the key elements of the widely and narrowly understood public health. The aim of this paper is recommendation the M&SH Questionnaire as a simple tool (method) used to measure mental and social health in order to verify the Profile of Sense of Positive Health and Survival Abilities that was in advance determined based on declaration of a single respondent. Material & Methods: The prototypes of the M&SH Questionnaires are based on verbal simulations tools for assessment of the phenomena involving particular human actions performed under difficult and extreme conditions. Verification of validity of the accepted concept involving mental health and social health measurements using simulation methods, as well as verification of each indicator, was based on the assessment of five independent experts in pedagogy, psychology and health science (2 professors and 3 PhDs). All these competent judges have many years’ experience in scientific exploration based on simulation methods and pedagogical practice involving preparation of a person for actions under difficult and extreme situations. Results: The M&SH Questionnaire consists of 12 statements (or questions) informing about hypothetical situations with the respondent participation. The result of each respondent’s declaration is based on five-point scale (conventional points, which simplifies statistical analysis): 5 (declared answer indicates a very high level of mental and/or social development); 1 (the opposite of such a conclusion); 4, 3, 2 remain in the middle. Conclusions: The authors recommend using M&SH Questionnaire as a simple tool of estimating mental health and social health based on the described simulated situations, which meet the required validity standards of empirical study methodology. The validity of using this questionnaire will be finally determined based on the results of independent (of the authors) verification of this research tool reliability and the results of research using M&SH tests associated with different diagnostic. prophylactic and therapeutic effects.
Fractional order adaptive MRAC controller for an active suspension system

This paper investigates the use of fractional order operators in conventional model reference adaptive control (MRAC). A fractional adaptive controller is designed based on the use of a fractional-order parameter adjustment rule. Applied in numerical simulations for an active suspension system and compared with the conventional MRAC, it is shown that the performances of FOMRAC are superior to classical control schemes.
Pemodelan Cuaca Menggunakan Model Hidden Markov Untuk

Renewable energy is an alternative energy to address problems that arise in conventional energy, which is limited and cause pollution that can damage the environment. On the other hand, Indonesia as a tropical country located in the the Equator area, has the potential of solar energy abundant and shining all year round. LAPAN records the average daily radiation of solar energy is 4.8 KWh/m2. Thus, solar power systems (PLTS) have enormous potential as a key source of energy for use in Indonesia in the future. One of the main problems when planning a PLTS is the weather uncertainty, it causes difficulty in planning the needed capacity of PLTS. This problem can be solved if this weather uncertainty can be solved. A reliable method to address this uncertainty is the stochastic modeling, this is because stochastic modeling is a model built using opportunity rules. The Model Hidden Markov (MHM) is one of the most reliable stochastic modeling without having to know the factors causing the problem to be modelled, including the problem in this weather where the factors are difficult to observe. In the middle of the limitation, this modeling uses BMKG daily weather data on the area of Samarinda, East Kalimantan on July 1 to October 31, 2019 (as many as 123 days). The weather Data obtained is grouped into four categories, namely sunny, bright-cloudy, cloudy, rainy. Models are created using weather data of 105 days, of which the remaining 18 days is used to check the accuracy of the model predictions. The results showed that the model had the accuracy as much as 87 from 105 days (82.86%). The accuracy of the model to predict as much as 13 of 18 days (72.67%).
On the Determinants of Inflation in Nigeria: 1980-2003

35 Central Bank of Nigeria Economic and Financial Review Volume 45/1 March 2007 This paper sets out to examine the main economic determinants of inflation in Nigeria over the period 1980-2003 using quarterly data. Using, among other measures, the Hodrick and Prescott filter, inflation is decomposed into its trend, cyclical, seasonal, and, random components. Based on the time series characteristics of the variables used in the analysis, the paper adopted the generalto-specific modelling approach to investigate the main determinants of each component. The results confirm that, in the long run, inflation is largely and positively related to the level of (narrow) money supply and, marginally, to fiscal deficit. In the medium term inflation is observed to be positively related to exchange rate depreciation and the growth of money supply. In the short run, it is observed that inflation is positively related to growth in money supply and exchange rate depreciation while it is negatively related to growth in real GDP. Some marginal significance is observed for the influence of pump price adjustment of petroleum products. The paper further observes that inflation is positively related to growth in money supply, exchange rate and growth in non-oil GDP. It is further observed that money supply affects inflation in the short to long run while exchange rate is influential in the short to medium run. Since fiscal deficit and government borrowing in Nigeria are largely financed by the (central) banking system, the findings lend support to the conventional elements of a typical stabilisation programme that reducing both the budget deficit and credit to the government are crucial in fighting inflation. Finally, since the results indicate the negative impact of economic growth on inflation, structural reforms and infrastructural improvements to increase the country’s productive capacity should be considered important elements of an overall economic reform program.
MODELING AND OPTIMIZATION OF BACs EXTRACTION FROM ALGERIAN Rosmarinus Officinalis L.VIA GREEN EXTRACTION

The aim of this study is to improve extraction of biologically active compounds (BACs) found in Rosmarinus officinalis L. from Algeria country using green extraction process. The effect of the main process variables (time, ethanol concentration, solid-to-liquid ratio) on maceration efficiency has been studied using Factorial Design (FD) to verify the single factors effects. Total Polyphenol Content (TPC) and Total Flavonoids Content (TFC) were measured to control the maceration efficiency in different experimental conditions. The iso-response curves and the response contours have been exploited. The best experimental results were 0.15 g/mL, 50 %, 1hour and 0.15 g/mL, 50 %, 72hours for TPC and TFC respectively. The values of TPC and TFC were 2.5 mg GAE/g DW and 1 mg QE/g DW respectively. These results were in perfect agreement with the expected theoretical model. The relationship between the TPC and TFC provides a high correlation coefficient (0.82).
Accelerate Inference of CNNs for Video Analysis While Preserving Exactness Exploiting Activation Sparsity

This paper proposes a range-bound-aware convolution layer that accelerates the inference of rectiﬁed linear unit (ReLU)-based convolutional neural networks (CNNs) for analyzing video streams. Since video analysis systems require to process each video frame in real-time, the computational cost of inference of CNNs must be reduced. Several techniques heuristically skip the computation for the current frame and reuse the results of the previous frame when the current and previous frames are sufﬁciently similar. However, for critical applications such as surveillance systems, their accuracy can be unsatisfactory because they sacriﬁce accuracy for efﬁciency. In contrast, our method reduces the computational cost of convolution layers accompanied by ReLU while producing exactly the same inference results as an original model. We utilize both temporal similarity of video frames and activation sparsity in ReLU-based CNNs to guarantee to skip truly redundant computations. We experimentally conﬁrm that our method can accelerate widely used pre-trained CNNs with both CPU and GPU implementations.
Employees Involvement as Agent of Change Management and Performance of Local Governments in Eastern Uganda: An Empirical Study

Performance of Local Governments is key in delivering essential services to the citizens of the Country. Citizen get health, education for children thus developing the human resource, roads to enable movement of people and goods to markets, and technical assistance for farmers. However, the citizens are not getting the appropriate levels of services: evidenced by poor health facilities, low grades in schools, impassable or no roads despite Government and donor funding. The question, therefore, is; how can Local Governments improve performance in service delivery? The study investigated the relationship between employee involvement and performance of Local Governments in Eastern Uganda. A cross-sectional study design was used involving both quantitative and qualitative approaches with a sample of 48. Stratified, simple random and purposive sampling techniques were used to select the respondents. Data analysis involved descriptive and inferential statistics of Spearman Product Moment Correlation and regression. The findings indicated a strong positive relationship (r=0.724**) between employees involvement and performance of Local Governments. Employees involvement accounted for 55% (Adjusted R2 = 0.550) of variance in performance of Local Governments in Eastern Uganda. The study concludes that there is a strong positive relationship between employees involvement and performance of Local Governments. It is recommended that the managers and practitioners of Local Governments in Eastern Uganda should involve employees as change agents so as to improve performance.
Development of phenotyping system using low altitude UAV imagery and deep learning

In this study, a lightweight phenotyping system that combined the advantages of both deep learning-based panicle detection and the photogrammetry based on light consumer-level UAVs was proposed. A two-year experiment was conducted to perform data collection and accuracy validation. A deep learning model, named Mask Region-based Convolutional Neural Network (Mask R-CNN), was trained to detect panicles in complex scenes of paddy fields. A total of 13 857 images were fed into Mask R-CNN, with 80% used for training and 20% used for validation. Scores, precision, recall, Average Precision (AP), and F1-score of the Mask R-CNN, were 82.46%, 80.60%, 79.46%, and 79.66%, respectively. A complete workflow was proposed to preprocess flight trajectories and remove repeated detection and noises. Eventually, the evident changed in rice growth during the heading stage was visualized with geographic distributions, and the total number of panicles was predicted before harvest. The average error of the predicted amounts of panicles was 33.98%. Experimental results showed the feasibility of using the developed system as the high-throughput phenotyping approach. Keywords: panicle detection, vision-based phenotyping, deep learning, unmanned aerial vehicle (UAV) DOI: 10.25165/j.ijabe. 20211401.6025 Citation: Lyu S X, Noguchi N, Ospina R, Kishima Y. Development of phenotyping system using low altitude UAV imagery and deep learning. Int J Agric & Biol Eng, 2021; 14(1): 207–215.
Pregnant Women and Infants Infected with SARS-COV-2: A Brief Overview

http Coronaviruses are a large family of viruses that can infect both humans and animals, some of which cause respiratory infections. Human respiratory infections range from a mild disease like the common cold to severe illnesses such as Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS) (1). A novel coronavirus has been identified as the cause of an outbreak of respiratory illness that began in December 2019 in Wuhan, China, and then spread throughout the world. The most common and initial symptoms of COVID-19 include fever (83%-98%), cough (56%-85%), myalgia or fatigue (44%-51%), and dyspnea (31%). Special groups of people are more prone to the disease such as the elderly, people with lung disease, cancer, heart failure, brain disease, kidney disease, liver disease, and also pregnant women. The morbidity and mortality rates were higher in these group than in healthy controls (2). To date, no credible scientific evidence on the susceptibility of pregnant women to COVID-19 has been published. However, because of the immune system and physiological changes in pregnant women, they might be more susceptible to viral respiratory infections, such as COVID-19. Earlier studies showed that the immune system is weakened by pregnancy, which makes mothers more susceptible to various infections and diseases. About 90% of pregnant women have a weak immune system during the 9 months of pregnancy, the main reason for which is a hormonal imbalance in the body. For this reason, pregnant women may be at higher risk for acute illnesses (such as severe acute respiratory coronavirus syndrome (SARS-CoV) and Middle East coronavirus respiratory syndrome (MERS-CoV) and other viral respiratory infections, such as influenza) than other people (3). No complications have been reported in pregnant women infected with COVID-19 during Pregnant Women and Infants Infected with SARSCOV-2: A Brief Overview
Open Speech Command Translator System for Executing Positive, Negative, and Neutral Decisions

 This research proposes a system that uses an open speech command and translates it into a Positive, Negative, or Neutral decision. An ordinary voice command targeted to an object is generally composed of two parts: the object identification, and the desired instruction to execute from it. Using this structure, several voice features could be analyzed such as pitch, intensity, formants, among other statistical characteristics to recognize if a pattern exists. For this research, the “object” segment was ideally converted to text using existing speech-to-text tools; on the other hand, the “instruction” segment was ideally processed by applying a Naïve Bayes Classifier to classify instructions as Positive, Negative, or Neutral with up to 72% accuracy. This idea could be used in external systems for people with special-needs, among other yet unimagined applications. The system will enable improved natural interaction between humans and computers by using a basic but effective open communication.
SPIRITUALITY AND JOB SATISFACTION AMONG THE CONGREGATIO MATER MISERICORDIAE BROTHERS IN INDONESIA PROVINCE: BASIS FOR PSYCHOSPIRITUAL ENHANCEMENT Perang, Blasius blasisprang81@gmail.com

This research is designed to examine the relationships between spirituality and job satisfaction of the Congregatio Mater Misericordiae (CMM) Brothers in Indonesia Province. In order to determine the profile of spirituality and job satisfaction and their relationship, eighty (80) CMM Brothers was chosen to be respondents. The respondents were living in various convents in Indonesia (Sumatra, Java, Sulawesi, and Kalimantan). The age range of the respondents was 2150 and above years old. Assessment of Spirituality and Religious Sentiment (ASPIRES) and Job Satisfaction Survey (JSS) were used as instruments to collect data. The data were analyzed by utilizing descriptive statistics like frequency and percentage distribution, means, standard deviation, Kruskal Wallis Test, and Spearman’s to determine the relationship between the variables. Results revealed that there was no significant relationship between spirituality and job satisfaction. Religiosity and Total Job Satisfaction (r= .151, p= .181), Religious Crisis and Total Job Satisfaction (r= -.173, p .124), Prayer Fulfillment and Total JS with r=. 330, p= . 003) Universality and Total JS (r .025, p .826), Connectedness and Total JS (r= -.111, p= .327), Spiritual Transcendence and Total JS with r= . 109, p = . 337. The result of this study will be significant to the CMM Brothers for improving spirituality and job satisfaction.
Investigation on the direct shoot regeneration in date palm CV.Pyarum and possible genetics changes in induced shoots

The palm (Phoenix Dactylifera) is one of important trees, and is economically important in south of Iran. Date palm is propagated by the offshoots, number of which is limited. Therefore, adult Date palms produce shoot tips and axillary shoot meristems through the use of a tissue culture. This study was conducted to perform in -vitro tissue culture direct shoot regeneration and determine the best combination of plant regulators and other conditions. To achieve organogenesis and multiplication directly from shoot tips and axillary shoot meristems of Date palm (Phoenix Dactylifera L. Var Pyarum) was used without callus formation. Direct regeneration of vegetative buds minimizes the risk of somaclonal variation among plant regenerates. Results revealed that MS medium supplemented with 4mg/l of kinetin and 3 mg/l of IAA or 2mg/l of BA and 4 mg/l of NAA was the best formation from shoot tip after 16-20 weeks. Subculture per month was evaluated at following conditions: temperature for growth of 27±1°C during the lighted period and 22±1°C during the dark period.