Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance evaluation of a novel improved slime mould algorithm for direct current motor and automatic voltage regulator systems

This study deals with the controlling the speed of a direct current (DC) motor via a fractional order proportional–integral–derivative (FOPID) controller and maintaining the terminal voltage level of an automatic voltage regulator (AVR) via a proportional–integral–derivative plus second order derivative (PIDD2) controller. To adjust the parameters of those controllers, a novel improved slime mould algorithm (ISMA) is proposed. The latter is a novel metaheuristic algorithm developed in this work. The proposed algorithm aims to improve the original SMA in terms of exploration with the aid of a modified opposition-based learning scheme and in terms of exploitation with the aid of the Nelder–Mead simplex search method. A time domain objective function, which includes time response specifications of steady state error and maximum overshoot along with rise and settling times, is used as a performance index to design the FOPID controller-based DC motor system and PIDD2 controller-based AVR system. The performance of the proposed novel approaches for both systems are assessed through time and frequency domain simulations along with statistical tests which show the greater performance of the improved algorithm. Further to this, the efficacy of the proposed approaches for both systems is compared with other available and effective approaches in the literature. The extensive comparative results demonstrate the proposed method to be superior to those state-of-the-art approaches for both DC motor speed and AVR control systems.
Puzzle based Learning in Undergraduate Studies

All undergraduate Radiography students require training in image interpretation and evaluation of x-ray images in their second year of studies as part of work integrated learning.The method of teaching pedagogy influences the student's learning process and recall ability during examinations. if the teaching process moves to a student-centred approach, students become responsible for their own learning allowing active engagement and construction of their knowledge systems.Aim/ ObjectivesThe aim of the study is to implement and evaluate the use of puzzle-based learning in the teaching and learning process of undergraduate studiesObjectivesTo determine the efficacy of crossword and jigsaw puzzles as a novel teaching tool for medical imaging educationTo increase student's interest and involvement with image interpretation topicsTo improve and assess recognition and recall of medical terminologyTo improve the understanding of innovative learningMethodsThe study is a cross sectional qualitative research design.Approval will be obtained from the Research and Ethics Committee of health Sciences.Online consent will be obtained from students involved, by means of Google Form submission, followed by an information session on Blackboard collaborate on the topic "Image evaluation and interpretation of radiographic imaging". ConclusionThe research will prove the important collaboration of active teaching methodologies with simple, easy to use didactic material to improve student's understanding of basic concepts in their core module subject
Mesh Completion with Virtual Scans

Meshes generated by range scanners are often incomplete and contain complex holes due to limited input coverage and occlusion. In this paper, we present an effective method to fill the gap regions on meshes by leveraging the templates inferred from the learning-based method. We first segment both source and template models into corresponding parts. Each part will be aligned with non-rigid deformation. We then modify the gap regions by “virtual” depth maps rendered using the aligned parts from newly selected viewpoints. Comparing with the template-based mesh completion approaches, our algorithm can generate natural appearances without any user interaction. Comparing with the state-of-the-art volumetric fusion methods, our approach supports selective blending, which only modifies the regions of interest and prevents bad template inference from impacting the source.
CFD model of NOx reduction by SNCR method

Clanek se zabýva numerickým modelovanim SNCR metody. K simulacim byl využit CFD program Ansys/CFX. SNCR metoda byla definovana zakladnimi dominantnimi reakcemi, ktere byly vyhledany v mezinarodni chemicke databazi NIST. Samotne reakce zahrnovaly nejen redukci NOx, ale take změnu koncentrace polutantů N2O a CO ve spalinach. Navržený chemický mechanizmus zahrnutý v CFD simulaci byl aplikovan na dva kotle. Prvni simulace sloužila k upřesněni fyzikalnich konstant a validaci chemických reakci. Druha simulace již sloužila k verifikaci sestaveneho reakcniho schematu.
Binding free energy of protein/ligand complexes calculated using dissociation Parallel Cascade Selection Molecular Dynamics and Markov state model

We recently proposed a computational procedure to simulate the dissociation of protein/ligand complexes using the dissociation Parallel Cascade Selection Molecular Dynamics simulation (dPaCS-MD) method and to analyze the generated trajectories using the Markov state model (MSM). This procedure, called dPaCS-MD/MSM, enables calculation of the dissociation free energy profile and the standard binding free energy. To examine whether this method can reproduce experimentally determined binding free energies for a variety of systems, we used it to investigate the dissociation of three protein/ligand complexes: trypsin/benzamine, FKBP/FK506, and adenosine A2A receptor/T4E. First, dPaCS-MD generated multiple dissociation pathways within a reasonable computational time for all the complexes, although the complexes differed significantly in the size of the molecules and in intermolecular interactions. Subsequent MSM analyses produced free energy profiles for the dissociations, which provided insights into how each ligand dissociates from the protein. The standard binding free energies obtained by dPaCS-MD/MSM are in good agreement with experimental values for all the complexes. We conclude that dPaCS-MD/MSM can accurately calculate the binding free energies of these complexes.
Synergistic antimicrobial activity of honey combined with silver nanoparticles topically applied in experimentally infected wounds in Wistar albino rats

Background: Silver nanoparticles (AgNPs) show ample antibacterial activities when combining with honey. Aim and Objective: The study was designed to determine the antibacterial activity of different kinds of honey against the common wound pathogen Staphylococcus aureus. Materials and Methods: Bacterial strain was used to inoculate the wound. S. aureus ATCC-25923 was used in the study. Results: Wound infection examination was done by total count of bacterial load. In all three groups, better percentage of the wound closer, histological, blood, and tissue parameters identified in honey combine with AgNPs, showed a synergistic effect. Conclusion: Honey and AgNPs showed synergistic effect. It is recommended to apply both the products together.
Role of Microphysics and Convective Autoconversion for the Better Simulation of Tropical Intraseasonal Oscillations (MISO and MJO)

The seasonal prediction of the Indian summer monsoon (ISM) and Monsoon Intraseasonal Oscillations (MISO), as well as the Madden Julian Oscillations (MJO) that strongly modulate MISO, is of much importance to the agriculture sectors of the Indian Sub‐continent. This study highlights the importance of selecting proper “autoconversion” coefficients for precipitation formation in Coupled Global Climate Model's convective and microphysical schemes in simulating MISO and MJO. With a series of sensitivity experiments, we systematically examined the convective autoconversion and microphysical autoconversion coefficients in the National Centers for Environmental Prediction Coupled Forecast System version 2 (CFSv2). The mean and intraseasonal features of MISO and MJO are improved with a proper combination of autoconversion coefficients, which not only provide a better partition of cloud water and ice but also better feedback between the large‐scale condensation and convective parameterization. The results demonstrate a road map for the improvement of MISO as well as MJO simulation using a coupled climate model.
Synthesis of Polypyrrole-based Nitrogen-containing Porous Carbon Nanotubes for CO2 Adsorption

1Department of Polymer Materials and Engineering, Department of Chemistry, MOE Key Laboratory of Natural Resources of the Changbai Mountain and Functional Molecules, Yanbian University, Park Road 977, Yanji 133002, Jilin Province, PR China 2Instrumental Analysis Center, Yanbian University, Park Road 977, Yanji 133002, Jilin Province, PR China 3Research Institute of Standars and Analysis, Inha University, 100 Inharo, Incheon 402-751, South Korea
Effect of regular exercise with different intensities on oxidized LDL levels in obese men

Introduction: Macrophages and oxidized low-density lipoprotein (ox-LDL) have been verified playing vital roles in the pathogenesis of atherosclerosis. The role of exercise intensity in circulating ox-LDL is not clearly understood in obesity and it is not well known which exercise intensity is needed to ox-LDL reductions in response to endurance training. Thus the purpose of this study was to comparison the effect of regular high-intensity vs. moderate-intensity exercise on ox-LDL in obese men. Material & Methods: Twenty four sedentary obese men (aged: 41.0 ± 5.9 years and BMI: 31.1 ± 3.4 kg/m2; ± SD) volunteered to participate in this study. The subjects were randomly assigned to moderate-intensity exercise (MIE) group (n=8), high-intensity exercise (HIE) group (n=8) or control group (n=8). The subjects in MIE group walked 2 miles in 30 minutes on a treadmill on 4 days per week for 12 weeks according to the guidelines of the Centers for Disease Control and Prevention and American College of Sports Medicine; however, the subjects in the HIE group performed endurance training 4 days a week for 12 weeks at an intensity corresponding to 75-80% individual heart rate reserve (HRR) for 45 min. Results: The results showed that total cholesterol (TC), triglycerides (TG) and LDL were decreased and HDL increased after MIE and HIE (P<0.05). ox-LDL concentration was decreased only after HIE. For TC and HDL significant differences were observed between MIE group and HIE group (P<0.05). Conclusions: The results suggest that although lipid profile of obese men improves after regular moderate and high-intensity exercise, ox-LDL levels decreases only after regular high-intensity exercise.
Comparative Chloroplast Genomics in Phyllanthaceae Species

Family Phyllanthaceae belongs to the eudicot order Malpighiales, and its species are herbs, shrubs, and trees that are mostly distributed in tropical regions. Here, we elucidate the molecular evolution of the chloroplast genome in Phyllanthaceae and identify the polymorphic loci for phylogenetic inference. We de novo assembled the chloroplast genomes of three Phyllanthaceae species, i.e., Phyllanthus emblica, Flueggea virosa, and Leptopus cordifolius, and compared them with six other previously reported genomes. All species comprised two inverted repeat regions (size range 23,921–27,128 bp) that separated large single-copy (83,627–89,932 bp) and small single-copy (17,424–19,441 bp) regions. Chloroplast genomes contained 111–112 unique genes, including 77–78 protein-coding, 30 tRNAs, and 4 rRNAs. The deletion/pseudogenization of rps16 genes was found in only two species. High variability was seen in the number of oligonucleotide repeats, while guanine-cytosine contents, codon usage, amino acid frequency, simple sequence repeats, synonymous and non-synonymous substitutions, and transition and transversion substitutions were similar. The transition substitutions were higher in coding sequences than in non-coding sequences. Phylogenetic analysis revealed the polyphyletic nature of the genus Phyllanthus. The polymorphic protein-coding genes, including rpl22, ycf1, matK, ndhF, and rps15, were also determined, which may be helpful for reconstructing the high-resolution phylogenetic tree of the family Phyllanthaceae. Overall, the study provides insight into the chloroplast genome evolution in Phyllanthaceae.
Daily soil temperature modeling improved by integrating observed snow cover and estimated soil moisture in the USA Great Plains

Abstract. Soil temperature (Ts) plays a critical role in land–surface hydrological processes and agricultural ecosystems. However, soil temperature data are limited in both temporal and spatial scales due to the configuration of early weather station networks in the USA Great Plains. Here, we examined an empirical model (EM02) for predicting daily soil temperature (Ts) at the 10 cm depth across Nebraska, Kansas, Oklahoma, and parts of Texas that comprise the USA winter wheat belt. An improved empirical model (iEM02) was developed and calibrated using available historical climate data prior to 2015 from 87 weather stations. The calibrated models were then evaluated independently, using the latest 5-year observations from 2015 to 2019. Our results suggested that the iEM02 had, on average, an improved root mean square error (RMSE) of 0.6 ∘C for 87 stations when compared to the original EM02 model. Specifically, after incorporating the changes in soil moisture and daily snow depth, the improved model was 50 % more accurate, as demonstrated by the decrease in RMSE. We conclude that, in the USA Great Plains, the iEM02 model can better estimate soil temperature at the surface soil layer where most hydrological and biological processes occur. Both seasonal and spatial improvements made in the improved model suggest that it can provide a daily soil temperature modeling tool that overcomes the deficiencies of soil temperature data used in assessments of climatic changes, hydrological modeling, and winter wheat production in the USA Great Plains.
Geo-spatially integrated soil quality evaluation: a case of Toba Tek Singh, Pakistan

Agricultural development and rapid human population growth are among the key prevalent factors that have caused soil degradation in several terrestrial ecosystems. Soil quality is being increasingly affected by water and wind-related erosion, aridity, salinity due to misuse, and erroneous agrarian practices. Evaluating soil quality is an essential tool for crop management and soil sustainability; this is exclusively unique in semi-arid and dry regions where the observation of soil quality offers a prospect to gauge land management systems. Here, we evaluated the soil quality in the agricultural district Toba Tek Singh, Punjab, Pakistan. For this purpose, the Integrated Quality Index (IQI) model was executed through Total Dataset (TDS) and Minimum Dataset (MDS) methods of data selection. TDS shows the soil quality results of all the selected indicators (i.e., EC, pH, CaCO3, OM, P, K, SP). To select the MDS, the Principal Component Analysis was used and three indicators were selected including pH, EC, and OM. Among the two indices (IQITDS and IQIMDS), moderate and low soil quality were recognized as a leading grade for soil quality of the study area. The reason for low-quality soil was a considerably low percentage of OM, a lower amount of CaCO3 in soil, a high rate of pH and EC, and a lesser amount of Phosphorous and K in the soil of the study area. The results for TDS and MDS were found to be appropriate to each other as confirmed by the Geographically Weighted Regression (GWR) model (Adjusted R 0.81). Thus, this approach might be used as a helpful tool for the development of quantitative techniques to estimate soil quality. This is helpful to identify areas where soil quality is low and can be improved with better management practices and maintain a suitable amount of fertilizers in the soil.
An Efficient Algorithm for End-to-End Latency Optimization Over IEEE 802.15.4 Wireless Network for IoT Applications

: The continuous evolution of new wireless technologies has given birth to new application areas for the Internet of Things (IoT) such as Smart Cities, Smart Home, Intelligent Transport Systems, Wireless Sensor Networks, etc. IoT is a network of networks that enables, via small wireless electronic devices called "sensor", to identify and communicate with physical objects. The main IoT objective is to measure and exchange data between physical and virtual worlds. However, the use of these sensors in applications characterized by the coexistence of different traffic loads in the same network could lead to power consumption and latency problems. In this article, we present a new efficient algorithm called (BMPriority-based CSMA/CA) based on message priority and battery energy level of sensor to manage access to the transmission channel. More precisely, our algorithm uses a weighting function to calculate the contention window during which a sensor node must wait before starting its data transmission. Simulation results show that our proposed protocol outperforms S-MAC, IEEE 802.15. 4, and ECA-MAC protocols in terms of optimizing Packet Delivery Ratio (PDR), end-to-end latency, and throughput.
The Determinant Factors of Food and Beverage Small and Medium Industries Competitive Advantage that Mediated by E-Commerce Adoption Level in Bogor

The research aims to examine the determinant factors of culinary Small-and-Medium Industries (SMIs) competitive advantage that mediated by e-commerce adoption level in Bogor. This research uses a quantitative approach using Structural Equation Modelling. The primary data is collected using online questionnaires. The population size is 360 culinary SMIs that already used e-commerce. The sampling technique is using purposive sampling. The sample size determination method is using Slovin’s formula with 85% confidence level and the sample size in this study is 42 culinary founders. The data analyse using Smart PLS 3.0. Based on the data analysis, the top management is the only determine the SMIs to adopt e-commerce for each ecommerce adoption level. For adoption level 1, the ecommerce adoption affects growth and quality. For adoption level 2, the e-commerce adoption affects quality, growth, and differentiation. For adoption level 3, the e-commerce adoption affect growth. For adoption level 4, the e-commerce adoption affects growth, differentiation, quality, and cost reduction. the e-commerce adoption level, the cost reduction, company differentiation, sales growth, and quality. Keywords— Small-and-Medium Industry; culinary industry; e-commerce adoption level; TechnologyOrganization-Environment; competitive advantage
Biodegradable Capability of the Indigenous Micrococcus sp. Oil Degrading Bacteria Isolated from Oil Contaminated Soil, Motor Workshop Area of Bahror, Alwar, Rajasthan, India.

: Crude oil contamination is one of the important issue in the current environment pollution. Physical, chemical and biological methods are applied for bioremediation. Use of microorganisms is one of the most popular methods among them. In this experiment, soil samples were collected from the different motor workshop areas to isolate potential microbes capable of crude oil degradation. Isolation of the crude oil degrading bacteria was followed by enriching the microorganisms by providing suitable growth conditions. The microorganisms those were capable of degrading the crude oil were identified as Bacillus spp. , Pseudoxanthomonas spp. , Phenylobacterium spp. and Micrococcus spp. by morphological and biological methods. Among them, biodegradation capability of Micrococcus sp. was studied at different oil concentrations.
CYCLEA BARBATA LEAF EXTRACT: LIPOXYGENASE INHIBITORY ACTIVITY AND PHYTOCHEMICAL SCREENING

Objective: The aim of this study was to test the anti-inflammatory activity of methanol, ethyl acetate, and n-hexane Cyclea barbata Mier. leaf extractsusing a lipoxygenase inhibition method.Methods: Enzyme activity assay was performed using colorimetric method with lipoxygenase from soybean and linoleic acid as a substrate.Absorbance was measured at 234 nm. The total flavonoid content of the most active extract was determined using a colorimetric method with AlCl3and phytochemical screening.Results: The ethyl acetate extract had the highest lipoxygenase inhibiting activity, with an IC50 value of 0.267 mg/mL. In addition, this extract had atotal flavonoid content of 21.62 mgQE/g and contained flavonoids, glycosides, and terpenoids.Conclusion: This finding indicated that C. barbata provides a possible anti-inflammatory effect through the inhibition of lipoxygenase. However,further research is still needed to strengthen this result.
Sorption behavior of Co-radionuclides from radioactive waste solution on graphene enhanced by immobilized sugarcane and carboxy methyl cellulose

Abstract Novel graphene-sugarcane bagasse-carboxy methyl cellulose (GSCCMC) nanocomposite have been synthesized via freeze-drying technique after preparation of graphene from natural graphite by modified Hummer method and evaluated as adsorbent for sorption of 60Co(II)-radionuclides from radioactive waste solution and real wastewater samples using a series of batch adsorption experiments and compared with graphene. The synthesized (GSCCMC) nanocomposite was characterized using Fourier transformer infrared (FT-IR), Transmission electron microscope (TEM), Thermal analysis, Elemental analysis, Specific Surface area (SBET) and X-ray diffraction (XRD), which confirmed the successful formation of graphene-sugarcane bagasse-carboxy methyl cellulose (GSCCMC) nanocomposite. Different parameters affecting the removal process including pH, contact time and metal ion concentration were investigated. Isotherm and kinetic models were studied. Adsorption kinetics described well by pseudo-second-order. The Langmuir model provides a better fitting than the Freundlich and Temkin models and the maximum adsorption capacity from Langmuir model were found to be 0.4186 and 0.2424 mol/g for (GSCCMC) nanocomposite and graphene (G), respectively. From Dubinin–Radushkevich (D–R) isotherm model, the sorption energy (E)-values of graphene (G) and (GSCCMC) are 10.16 and 10.564 kJ/mol, respectively and this mean the adsorption of 60Co(II)-radionuclides can be explained by chemisorption process, which is characteristic of ion exchange. Desorption of 60Co(II)-radionuclides from loaded (GSCCMC) nanocomposite was studied using different eluents (0.1 M HCl, 0.1 M NaOH and H2O). The data illustrated that 0.1 M HCl solution showed maximum desorption percent (D%) than other eluents. The economic viability of the adsorption process for the removal of 60Co(II) from wastewater samples was studied. The result indicated that the cost for preparation of (GSCCMC) nanocomposite is lower than for (GSCCMC) nanocomposite that prepared from purchase the graphene powder. Therefore, the synthesized (GSCCMC) nanocomposite was used as regenerated material for sorption of 60Co(II)-radionuclides from aqueous solutions and can be used for many times as a cost-effective and environmental friendly material in wastewater treatment.
The Origin of Systematic Forecast Errors of Extreme 2020 East Asian Summer Monsoon Rainfall in GloSea5

This study examined the origin of the systematic underestimation of rainfall anomalies over East Asia during July–August 2020 in operational forecasts. Through partial nudging experiments, we found that the East Asian rainfall anomalies were successfully predicted in GloSea5 with corrected tropical sea surface temperature (SST) forcing. Once the observed SST is applied over the Indian Ocean and tropical central‐eastern Pacific, a low‐level anticyclonic anomaly over the subtropical western Pacific, which transports warm‐moist air from the tropics to increase the East Asian precipitation, is well reproduced as observed. By further separating the SST into climatological and anomalous components, we revealed that the cold and dry mean state bias over the Indian Ocean and central‐eastern Pacific is responsible for the weak anomalous atmospheric teleconnection patterns from the tropics to East Asia. This implies that correcting the model mean climatological fields can directly impact the operational seasonal forecast skill.