Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic characterization of Mexican Pelibuey sheep using microsatellite markers

This study aimed to genetically characterize 23 subpopulations of the Mexican Pelibuey sheep and a Cuban flock using nine microsatellite markers. A total of 99 alleles and a polymorphic information content (PIC) of 0.84 were observed. The observed FIS, FST, and FIT were 0.007, 0.151, and 0.158, respectively. Three primers (OarFCB304, Rev Mex Cienc Pecu 2021;12(1):36-57 37 OarJMP29, and ILSTS5) showed deviations in the Hardy-Weinberg equilibrium (HWE; P<0.05). In a subpopulation analysis, the number of alleles per subpopulation ranged from 28 to 49, the mean number of alleles (MNA) was 4.08, and the effective number of alleles (NE) was 3.25. The observed and expected heterozygosity values were 0.726 and 0.731, respectively. Six of the 24 evaluated subpopulations showed deviations of the HWE (P<0.05). The FIS values by subpopulation varied between -0.71 and 0.138. Nine private alleles were detected, and no shared alleles were observed. Using a principal component analysis (PCA), subpopulations were grouped into two clusters. Mantel's test determined that the genetic distance (measured by Nei's unbiased minimum distances) was not related to the geographic distance (r= -0.062; P>0.05). The population structure analysis determined two founder populations (K), similar to the PCA. This study concludes that the Pelibuey sheep in Mexico have high genetic diversity and that its subpopulations are grouped into two clusters, one of which shows the most preserved genetic material.
Structure from Motion (SfM) method to characterize fluvial sedimentology in Way Semaka river in Lampung province, Indonesia

Structure from motion (SfM) has been applied recently in fluvial sedimentology. This application is due to the availability of many low-cost unmanned aerial vehicles/drones, which can help overcome challenging terrain, provide efficient and reproducible and high-accuracy topographic images and data. The current study describes the application of SfM to build a geomorphological model and estimate the surface water velocity of the Way Semaka River in the Bandar Negeri Suoh (BNS) region in the West Lampung area. Way Semaka is a river type with an extensive meandering system and stable extension tectonic regime relatively. River morphology approximately 96.62 m width and 4 m depth in straight (relatively) area, whereas in channel area approximately 171.22 m width and 5 m depth. The velocity range between 0.39 – 1.56 m/s based on image analysis proven by current meter measurements onsite with an RMS error of 0.25. Manual geomorphic unit level 2 analysis revealed that 9% of the coverage consisted of basins for the channel’s zone, 35% of the coverage consisted of convexity, 9% consisted of planar features, and 37% of the coverage consisted of the transition zone.
REGISTRATION OPTIMIZATION OF MOBILE HANDHELD SCANNER POINT CLOUDS WITH STATIC SCANS

In recent years, 3D acquisition methods involving different types of scanners have undergone a phenomenal technological growth. Nowadays, mobile acquisition devices are popular because of their ease of use and their fairly competitive cost. Static scanners provide higher accuracy and more detail, but the acquisition time required with these systems is higher than with mobile systems. Mobile scanners are known for their high acquisition speed but lower point density and accuracy. Until now, the choice of the type of system to use was dependent on the geometry of the study area and the required accuracy. This research aims to find a way to optimize the survey by finding a compromise between the two types of devices, in order to take advantage of both systems for the same acquisition campaign. The first objective is to study the minimum number of static positions required for respecting the required accuracy. A solution is also proposed for compensating the drift of the mobile device. Secondly, the pertinence to use static stations for the principal loop and mobile system for adjoining rooms is investigated. The datasets chosen allow, on the one side, to quantify the limits of the mobile system for the acquisition of indoor buildings and, on the other side, to give recommendations regarding the configuration of static stations as a reference for mobile point clouds. Based on these experiments, a methodology is proposed for indoor environments to combine the use of the two acquisition systems and thus to save time in the field while still providing a good registration quality.
LARGE SCALE SEMANTIC SEGMENTATION OF VIRTUAL ENVIRONMENTS TO FACILITATE CORROSION MANAGEMENT

This paper reports the results of a study that aims to develop semi-automatic methods for assessing the degree of corrosion in industrial plant. We evaluated two fully convolutional networks (U-Net and DeepLab v3 +) to segment corroded areas in panoramic images of offshore platforms. The experimental analysis was based on two datasets built for this study. The datasets comprise 9,112 2D images and 3,732 panoramic images. Both FCNs trained on 2D images were tested on 2D images and cubic projections of panoramic images. In addition to pointing out encouraging results, the experiments indicated that most prediction errors concentrated in corrosion defects with a small pixel area.
INFORMATION ACQUISITION ON PEDESTRIAN MOVEMENTS IN URBAN TRAFFIC WITH A MOBILE MULTI-SENSOR SYSTEM

Abstract. This paper presents an approach which combines LiDAR sensors and cameras of a mobile multi-sensor system to obtain information about pedestrians in the vicinity of the sensor platform. Such information can be used, for example, in the context of driver assistance systems. In the first step, our approach starts by using LiDAR sensor data to detect and track pedestrians, benefiting from LiDAR’s capability to directly provide accurate 3D data. After LiDAR-based detection, the approach leverages the typically higher data density provided by 2D cameras to determine the body pose of the detected pedestrians. The approach combines several state-of-the-art machine learning techniques: it uses a neural network and a subsequent voting process to detect pedestrians in LiDAR sensor data. Based on the known geometric constellation of the different sensors and the knowledge of the intrinsic parameters of the cameras, image sections are generated with the respective regions of interest showing only the detected pedestrians. These image sections are then processed with a method for image-based human pose estimation to determine keypoints for different body parts. These keypoints are finally projected from 2D image coordinates to 3D world coordinates using the assignment of the original LiDAR points to a particular pedestrian.
Effects of freezing periods and polythene packaging with or without turmeric powder paste on proximate composition of Labeo bata fish

Article history: Received: April 13, 2020 Accepted: September 29, 2020 The study was designed to investigate the effects of freezing periods and the combination of packaging with or without turmeric on the proximate composition of whole and sliced Labeo bata. The samples were subjected to 28 days of frozen (-20 °C) storage periods and analyzed for proximate composition such as moisture, protein, lipid and ash at intervals of 0, 14 and 28 days. Data obtained was subjected to analysis of variance (ANOVA) at 95% significant level. Different preservation periods and methods significantly affected the nutritional composition of fresh fish. Moisture, protein, lipid and ash content decreased with increasing storage periods when compared to the fresh fish as control. The highest percentage of protein was found in turmerictreated whole fish preserved in polythene, C4, after the 14 (15.70±0.14) and 28 (15.27±0.21) day. On the other hand, the lowest percentage (14.01±0.10 and 13.22±0.18 for the 14 and 28 day, respectively) was found in sliced fish preserved without polythene, C5. In conclusion, the turmeric-treated whole fish preserved in polythene retained fish nutrients and ensured its good quality and composition longer than other treatments, thereby extending the shelf life during frozen storage.
Manipulating Interactions between T4 Phage Long Tail Fibers and <named-content content-type='genus-species'>Escherichia coli</named-content> Receptors

Bacteriophages are the most abundant and diverse biological entities on Earth. Phages exhibit strict host specificity that is largely conferred by adsorption. However, the mechanism underlying this phage host specificity remains poorly understood. In this study, we examined the interaction between outer membrane protein C (OmpC), one of the Escherichia coli receptors, and the long tail fibers of bacteriophage T4. T4 phage uses OmpC of the K-12 strain, but not of the O157 strain, for adsorption, even though OmpCs from the two E. coli strains share 94% homology. We identified amino acids P177 and F182 in loop 4 of the K-12 OmpC as essential for T4 phage adsorption in the copresence of loops 1 and 5. Analyses of phage mutants capable of adsorbing to OmpC mutants demonstrated that amino acids at positions 937 and 942 of the gp37 protein, which is present in the distal tip (DT) region of the T4 long tail fibers, play an important role in adsorption. Furthermore, we created a T4 phage mutant library with artificial modifications in the DT region and isolated and characterized multiple phage mutants capable of adsorbing to OmpC of the O157 strain or lipopolysaccharide of the K-12 strain. These results shed light on the mechanism underlying the phage host specificity mediated by gp37 and OmpC and may be useful in the development of phage therapy via artificial modifications of the DT region of T4 phage. IMPORTANCE Understanding the host specificity of phages will lead to the development of phage therapy. The interaction between outer membrane protein C (OmpC), one of the Escherichia coli receptors, and the gp37 protein present in the distal tip (DT) region of the long tail fibers of T4 bacteriophages largely determines their host specificity. Here, we elucidated the amino acid residues important for the interaction between gp37 and OmpC. This result suggests that the shapes of both proteins at the binding interface play important roles in their interactions, which are likely mediated by multiple residues of both binding partners. Additionally, we successfully isolated multiple phage mutants capable of adsorbing to a variety of E. coli receptors using a mutant T4 phage library with artificial modifications in the DT region, providing a foundation for the alteration of the host specificity.
A Test of the validity of Crowding-out (or- in) hypothesis: A new examination of link between public borrowing and private investment in Emerging Europe

This study seeks to test the existence of the crowding-out (orin) hypothesis in a sample of 17 Emerging Europe countries divided in two panels. The study employs a panel autoregressive distributed lag (ARDL) model based on three estimators, Mean Group Estimator (MG), Pooled Mean Group (PMG) and Dynamic Fixed Effect (DFE), in order to evaluate the of stability of short run and long run coefficients using consistently compiled public borrowing and private investment data between 2000 and 2019. The empirical findings of the paper generally confirm the existence of a crowding out effect in both long run and short run in European post-transition countries, and in the long run for European transition countries. More specifically, elasticity of private investment with respect to public debt is greater in the European transition countries than in the European post-transition countries. However, the findings on the crowding out (in) effect of government spending and economic growth on private investment are mixed and conflicting in both the long run and the short run. Accordingly, the study recommends that selected countries should reassess their austerity agendas employed for lowering debt levels, and follow new strategies for managing public debt burden.
Adjusting for Nonresponse in the Healthcare Survey of DoD Beneficiaries

This paper presents the findings of an investigation of alternative forms of weighting adjustments to compensate for nonresponse in the Health Care Survey of DoD Beneficiaries. Currently, we compensate for potential nonresponse bias by adjusting for nonresponse within weighting cells defined by the stratification variables: enrollment status, beneficiary group, and geographic area. However, a great deal more is known about both respondents and nonrespondents from the sample frame. The first stage of the research identified variables from the frame that were most related to response to the survey. Second, we incorporated the chosen auxiliary variables into a weighting adjustment procedure. Three alternative weighting adjustment procedures were used: (1) a response propensity model, (2) forming weighting cells by dividing the predicted response propensity scores distribution into equal, ordered subgroups, and (3) forming weighting cells according to predicted response propensity scores and multiple outcome variables. Lastly, we compared and evaluated the results of using the alternative weighting procedures and the current procedure.
Leak Detection in Pipelines Using Wavelet Transform and Cepstrum Analysis Methods

Nowadays, a piping system is one of the important features in either home or industrial user. Leak in piping systems is a major operational problem around the world. Leaks result to loss in the fluid through the flow and automatically affect to the economy of the user. Objective of this research is utilizing the signal processing using Wavelet Transform and Cepstrum Analysis methods to leak detect in pipeline. After experiment has been completed, the data analysis process by using Matlab Software takes place. The result shows that the accuracy of the leak location detection is accurate with small error results below 10%. Keywords—leak detection, MDPE, wavelet transform, cepstrum analysis
The Elasticity of Health Expenditure on Agricultural Productivity Growth in Southeast Asia

BACKGROUND: Recently, agricultural productivity growth has experienced a sharp downward turn across the countries of Southeast Asia partly due to population ageing, increasing pace of urbanization, and industrialization. OBJECTIVE: To provide empirical evidence to the elasticity of prevailing health spending as a proxy of human capital stock on agricultural productivity growth in Southeast Asia. METHODS: This study analysed the data obtained from the World Development Indicators for 2000-2016 using panel data regression models. RESULTS: The empirical evidence suggests that prevailing health expenditure, though statistically significant, exerts a strong positive effect on agricultural productivity growth. Therefore, a unit rise in prevailing health spending relative to GDP would increase agricultural productivity growth by 28% across countries of Southeast Asia, all else constant. CONCLUSION: The trend of rapid agricultural productivity declines in Southeast Asia could be altered by augmenting investment to the prevailing health spending as an indicator of human capital stock. POLICY IMPLICATIONS: The governments of Southeast Asia should increase investment in prevailing health spending relative to GDP, to stimulate more growth in agricultural productivity, greatly improved human capital stock, and eventually increase economic growth
Analysis Method of Lactoferrin Based on Uncoated Capillary Electrophoresis

1School of Food Science and Technology, National Engineering Research Center of Seafood, Dalian Polytechnic University, Dalian, Liaoning 116034, China 2College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing, Jiangsu 210046, China 3Department of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150090, China 4Center of Experimental Instrument, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, People’s Republic of China
Water sources of riparian plants during a rainy season in Taihu Lake Basin, China: a stable isotope study

Abstract In this study, we investigated water sources of three typical plant species, i.e., Ginkgo biloba (Ginkgo biloba L.), Green soybean (Glycine max (L) Merr. ), and Mulberry tree (Morus alba L.) in a rainy season by using a dual stable isotope approach (δ18O and δ2H). Potential water sources were divided into direct or internal (i.e. soil water at different depths) and indirect or external water sources (i.e. precipitation, river water and groundwater). The results indicated that the surface soil water δ18O and δ2H is enriched probably due to evaporation. Ginkgo biloba and Green soybean prefer using soil water from the upper soil layer (0–60 cm) and precipitation, and the Mulberry tree mainly used deep soil water (120-150 cm) and groundwater. The different water use strategies of the three plant species are likely to be determined by their different root distribution at the above correspondent soil depths.
EXTRACTING ESSENTIAL OIL FROM FRAGRANT LEMONGRASS PLANTS BY STEAM-HYDRO DISTILLATION METHOD USING MICROWAVE AS A HEATER

This research studies the process of extracting citronella oil by the steam-hydro distillation method with microwaves (microwave). In addition, study the effect of temperature (105 C, 110 C, 115 C) and the size of the material enumeration (0.5 cm; 1 cm; 1.5 cm) on the yield of oil produced. This research was conducted by the steam-hydro distillation method. In this method a solvent is added in the form of water to dissolve the oil in the fragrant lemongrass stems and leaves. The resulting steam is condensed and then distillate in the form of a mixture of oil and water is taken after 120 minutes and separated using a separating funnel. From the results of the study, it was found that the% yield of high citronella oil in the variable size of the enumeration material was 0.5 cm at a temperature of 115 with a yield of 1.92%. The content of Citronella obtained in the oil of this research is 59.28%. The density of lemongrass oil is 0.875. The refractive index value is obtained in the range of 1.467351. 46925.
FUSING MULTI-MODAL DATA FOR SUPERVISED CHANGE DETECTION

With the rapid development of remote sensing technology in the last decade, different modalities of remote sensing data recorded via a variety of sensors are now easily accessible. Different sensors often provide complementary information and thus a more detailed and accurate Earth observation is possible by integrating their joint information. While change detection methods have been traditionally proposed for homogeneous data, combining multi-sensor multi-temporal data with different characteristics and resolution may provide a more robust interpretation of spatio-temporal evolution. However, integration of multi-temporal information from disparate sensory sources is challenging. Moreover, research in this direction is often hindered by a lack of available multi-modal data sets. To resolve these current shortcomings we curate a novel data set for multi-modal change detection. We further propose a novel Siamese architecture for fusion of SAR and optical observations for multi-modal change detection, which underlines the value of our newly gathered data. An experimental validation on the aforementioned data set demonstrates the potentials of the proposed model, which outperforms common mono-modal methods compared against.
A Modular approach for Big Data Management in IoT using SDN

— The Collaboration of wireless sensor network, embedded systems, advanced Cloud computing and implementation of 5G technology and data analytics crafts a new shape of intelligence that predicts futuristic IoT based smart Technology. The massive integration of numerous technologies causes the considerable aspects of issues, challenges and security within the IoT infrastructure. Software Defined Networking is enabling network technology capable of supporting the dynamic nature of IoT applications while supporting the big data analysis and statistics procedures. This paper proposes an innovative scheme for secure and successful dissemination of big data between nodes and applications and for the dynamic injection of policies at real time; using modular app based edge SDN controller. The proposed algorithm deals with big data activities as per application needs; while highlighting the future research directions along with some open unresolved issues of SDN integration and deployment
Burkholderia Pseudomallei Short-Chain Dehydrogenase/ Oxidoreductase: Potential Urine Biomarker Candidate for Acute Melioidosis

INTRODUCTION: In the current climate of urgency in identifying biomarkers for the development of rapid diagnostic kits, the use of urine samples to diagnose acute melioidosis was evaluated, comparing urine samples from Burkholderia pseudomallei culture-positive and culture-negative patients, and comparing pneumonic and septicemic melioidosis. MATERIAL AND METHODS: Eleven urine samples from clinically suspected melioidosis patients from a tertiary referral center, Hospital Tengku Ampuan Afzan, Pahang was used. An in-solution method for the detection of bacterial proteins using liquid chromatography-mass spectrometry quadrupole time-of-flight (LCMS QTOF) was used. RESULTS: Three bacterial proteins were consistently detected among all the culturepositive and PCR-positive cases tested, namely SDR family NAD(P)-dependent oxidoreductase protein (32kDa), 3-hydroxyacyl-CoA dehydrogenase Burkholderia sp. (32kDa), and NAD(P)-dependent dehydrogenase (short-subunit alcohol dehydrogenase family) Burkholderia sp. (33kDa). CONCLUSIONS: Short-chain dehydrogenase (SDO) proteins could potentially be a urine biomarker candidate as these have shown to aid in the ability of Burkholderia spp. to invade host cells as this action is important for the initial intracellular survival of the organism.
SOIL ORGANIC MATTER IN AREAS UNDER YERBA MATE CULTIVATION AND SWINE WASTE APPLICATION

Carbon and nitrogen contents, as well as their chemical fractions (humic acid HAF, fulvic acid FAF, humin HUM) and particle-size fractions (particulate organic carbon POC, mineral-associated organic carbon MAOC) of organic matter were evaluated in areas cultivated with yerba mate (Ilex paraguariensis) with 35 (E35) and 45 (E45) consecutive years of cultivation, in addition to a native forest area (NF), taken as reference. The soils of the study area were classified as Cambissolo Háplico (Inceptisol). Soil samples were collected at depths of 0.0-0.05, 0.05-0.10, 0.10-0.20 and 0.20-0.40 cm. A completely randomized design in split plots (3 areas and 4 depths) with 4 replicates was used. The E45 area, due to the longer cultivation time and the addition of organic fertilizer, had higher TOC, N and POC contents in comparison to the E35 area, with similar values of these attributes being observed in the forest area at some depths. The most stable carbon fractions (MAOC and HUM) did not vary between cultivated areas (E35 and E45); however, there were reductions of 25 and 14% (HUM 0-5 cm) and 12 and 21% (MAOC 5-10 cm) in these fractions, respectively, in comparison to the native forest. There was no difference between the evaluated areas for FAF, but HAF values were higher in the native forest area than in the cultivated areas.