Miracle-dz/UniFAR-FTUs huggingface dataset:
An efficient grasshopper optimization with recurrent neural network controller-based induction motor to replace flywheel of the process machine

This paper proposes a convenient power electronic circuitry with a control approach for the flywheel replacement of an induction motor. The proposed control approach is the joined execution of grasshopper optimization algorithm and recurrent neural network based on duty ratio controller and hence the proposed work is named grasshopper optimization with recurrent neural network. The main contribution of this work is, the power electronic circuitry gets the input voltage samples and limits the deviation to appraise the instantaneous torque demand. The required voltage for the instantaneous torque demand is produced by the proposed control technique. In the proposed grasshopper optimization with recurrent neural network technique, the grasshopper optimization algorithm is a meta-heuristic population-based algorithm, which works from the perspective of the swarming behavior of grasshoppers in nature. In the proposed system, the recurrent neural network learning procedure is improved by the grasshopper optimization algorithm in the perspective of the minimum error objective function. the proposed grasshopper optimization with recurrent neural network technique optimizes the inverter switching states by limiting the error between the setpoint torque and the demand torque regarding objective function. With this proposed technique, the unbalance between demand torque and generated torque is found with high precision and the quicker execution to pull back out the torsional pulsation insensitive load linked transmission systems. By utilizing the proposed methodology, the extreme fluctuation of load torque due to peaky loads in an induction motor will be detected accurately. Also, the proposed technique reduces the torsional vibrations, weakness in components and minimizes the outages of uninterrupted production leading to higher profits. The proposed strategy is actualized in the MATLAB/Simulink platform and evaluated their performance. The performances are appeared differently compared with the existing methods.
Performance and exergy analysis of a diesel engine run on petrodiesel and biodiesel blends containing mixed CeO2 and MoO3 nanocatalyst

Abstract In this research, the second law of thermodynamics was employed to analyze the exergy of a diesel engine fueled with diesel–biodiesel blends (B5 and B10) and hybrid nanocatalyst additives at three concentrations (30, 60 and 90 ppm), containing cerium oxide and molybdenum oxide on amide-functionalized multiwall carbon nano tubes (MWCNTs). The research engine was a single-cylinder, four-stroke, direct-injection, air-cooled diesel engine. The exergy analysis was performed under full load conditions, at four engine speeds (1700, 2100, 2500 and 2900 rpm). The results revealed that by increasing the amount of nanocatalysts (CeO2-MWCNTs and MoO3-MWCNTs) in the fuel blends, the net exergy work rate of the diesel engine increased for both fuel blends (B5 and B10). The maximum net exergy work rate of the diesel engine was 7.71 (25.33% of total fuel exergy rate) for the B10 + 90ppm fuel blends at 2500 rpm. The exergy efficiency of the diesel engine ranged from 17.97% to 31% for B5 and 18.3% to 31.7% for B10 fuel blends, respectively. B10 containing 90 ppm nanocatalyst showed the highest exergy efficiency, at an engine speed of 1700 rpm. All fuel blends containing nanocatalyst emitted less carbon monoxide, hydrocarbon and NOx compared with nanocatalyst-free fuel blends.
The Impact of Global Trends on Organization and Customer Satisfaction

The study aims to examine the impact of global trends on "MakeMyTrip" company as well as its customer satisfaction. The study has been done with the help of information provided on the company's websites, people's personal experiences, various hypotheses, and some statistical data. Surveys are also done to collect data from customers about their hospitality experiences and satisfaction. The findings and results which are based on the facts provided by customers and organization website suggested that the global trend does give a significant impact on organization and customer satisfaction. The study is aimed to provide ideas and solutions for organizations based on the impacts shown.
Comparison of SWAT-K and HSPF for Hydrological Components Modeling in the Chungju Dam Watershed

SWAT-K model is a modified version of the original SWAT, and is known to more accurately estimate the streamflows and pollutant loadings in Korean watersheds. In this study, its hydrological components were compared with those of HSPF in order to analyse the differences in total runoff including evapotranspiration(ET), surface flow, lateral flow and groundwater flow from the Chungju Dam watershed during . Averaged annual runoff with SWAT-K overestimated by 1%, and HSPF underestimated it by 3% than observed runoff. Determination coefficients() for observed and simulated daily streamflows by both the models were relatively good(0.80 by SWAT-K and 0.82 by HSPF). Potential ET and actual ET by HSPF were lower in winter, but similar or higher than those by SWAT-K. And though there were some differences in lateral and groundwater flows by two models because of the differences in hydrological algorithms, the results were to be reasonable. From the results, it was suggested that we should utilize a proper model considering the characteristic of study area and purposes of the model application because the simulated results from same input data could be different with models used. Also we should develop a novel model appropriate to Korean watersheds by enhancing limitations of the existing models in the future.
A Novel Grid and Place Neuron’s Computational Modeling to Learn Spatial Semantics of an Environment

Health-related limitations prohibit a human from working in hazardous environments, due to which cognitive robots are needed to work there. A robot cannot learn the spatial semantics of the environment or object, which hinders the robot from interacting with the working environment. To overcome this problem, in this work, an agent is computationally devised that mimics the grid and place neuron functionality to learn cognitive maps from the input spatial data of an environment or an object. A novel quadrant-based approach is proposed to model the behavior of the grid neuron, which, like the real grid neuron, is capable of generating periodic hexagonal grid-like output patterns from the input body movement. Furthermore, a cognitive map formation and their learning mechanism are proposed using the place–grid neuron interaction system, which is meant for making predictions of environmental sensations from the body movement. A place sequence learning system is also introduced, which is like an episodic memory of a trip that is forgettable based on their usage frequency and helps in reducing the accumulation of error during a visit to distant places. The model has been deployed and validated in two different spatial data learning applications, one being the 2D object detection by touch, and another is the navigation in an environment. The result analysis shows that the proposed model is significantly associated with the expected outcomes.
Fibrinogen-Conjugated Gold-coated Magnetite Nanoparticles for Antiplatelet Therapy

Selective targeting of activated platelets is desirable for anti-platelet therapy as it allows for disruption of platelets involved in blood clots to be treated but prevents targeting of quiescent circulating platelets. We propose using human fibrinogen to target platelets through the integrin IIB3 which is only competent to bind fibrinogen upon platelet activation. The function and selectivity of fibrinogen-conjugated nanoparticles was evaluated with an emphasis on potential in vivo application. While human systems are convenient for in vitro studies, future in vivo studies would require use of a murine animal model. The utility of human fibrinogen in a murine platelet system was examined through platelet aggregation studies, and with nanoparticle labeling was tested using either murine or human fibrinogen. The ability of fibrinogen-conjugated nanoparticles to bind to preformed platelet aggregates in the presence of unconjugated fibrinogen, which resemble in vivo conditions, was examined. To better understand the selectivity of fibrinogen-conjugated nanoparticles, a system in which tagged, unactivated platelets and activated platelets were mixed and labeled with fibrinogen-conjugates was developed. No significant differences between human and murine fibrinogen in aggregation or labeling of murine platelets were observed. Fibrinogen-conjugated nanoparticles were found localized to the area around the granulomere in surface-activated platelets and at platelet-platelet junctions and the open canalicular system in aggregated platelets. Preformed aggregates exhibited a similar labeling pattern but with fewer labels present. Fibrinogen-conjugated nanoparticles were found to be selective for activated platelets.
A High Manganese-Tolerant Pseudomonas sp. Strain Isolated from Metallurgical Waste Heap Can Be a Tool for Enhancing Manganese Removal from Contaminated Soil

Manganese (Mn) is widely used in industry. However, its extensive applications have generated a great amount of manganese waste, which has become an ecological problem and has led to a decrease in natural resources. The use of microorganisms capable of accumulating Mn ions from contaminated ecosystems offers a potential alternative for the removal and recovery of this metal. The main aim of this work was an investigation of removal potential of Mn from soil by isolated bacterial. For this purpose, eleven bacterial strains were isolated from the soil from metallurgical waste heap in Upper Silesia, Poland. Strain named 2De with the highest Mn removal potential was selected and characterized taking into account its ability for Mn sorption and bioaccumulation from soil and medium containing manganese dioxide. Moreover, the protein profile of 2De strain before and after exposition to Mn was analyzed using SDS/PAGE technique. The 2De strain was identified as a Pseudomonas sp. The results revealed that this strain has an ability to grow at high Mn concentration and possesses an enhanced ability to remove it from the solution enriched with the soil or manganese dioxide via a biosorption mechanism. Moreover, changes in cellular protein expression of the isolated strain were observed. This study demonstrated that autochthonous 2De strain can be an effective tool to remove and recover Mn from contaminated soil.
Asymptotically consensus tracking control of connected Lagrangian systems with input quantization

This paper studies the leader-following consensus problem for a class of connected Lagrangian systems, which include input quantization, time-varying control gain and unknown bounded external disturbance under undirected communication topology. Because it is usually not easy to correctly measure the upper bounds of time-varying control gain, nor to measure bounded external disturbance, the upper bounds are considered unknown in this paper. In the undirected communication graph case, the bound of the leader’s trajectory can be estimated by a group of observers for each agent. Then, based on the new technique of two-step adaptive distributed control, the tracking errors can asymptotically converge to zero. Moreover, the nonlinearities of the input quantization and the time-varying control gain can be compensated by a carefully selected smooth control protocol. It is shown that all the closed-loop signals are uniformly bounded, and a practical example simulation is given to demonstrate the effectiveness of the proposed scheme.
Multifaceted Exercise Prescription in the Management of an Overhead Athlete with Suspected Distal Biceps Tendinopathy: A Case Report

Background and Purpose: Distal biceps brachii tendinopathy is an uncommon diagnosis. Various exercise prescriptions have demonstrated efficacy in the management of tendinopathy, although studies frequently focus on the effects of a specific type of muscular contraction (i.e., concentric, isometric, or eccentric). Currently, there is limited research guiding the conservative management of distal biceps tendinopathy, particularly with overhead athletes, and even less evidence reporting a multifaceted exercise prescription for individuals with tendinopathy. The purpose of this case report is to describe the integration of various modes of therapeutic exercise into a rehabilitation program for an overhead athlete with suspected distal biceps brachii tendinopathy. Case Description: A 19-year-old male collegiate baseball pitcher presented to an outpatient physical therapy clinic via direct access for left antecubital pain, which began 6 weeks prior to the evaluation while pitching during try-outs. Following physical examination, distal biceps tendinopathy was the likely clinical diagnosis. Interventions focused on early eccentric exercise eventually progressing to concentric and plyometric activity for return to sport. Outcomes: The patient was seen five times over the course of 4 weeks. He had significant improvements of pain, patient-reported functional outcomes, global rating of change, strength, tenderness, and provocation testing. The patient was able to return to an off-season pitching program. Discussion: An impairment-based and task-specific exercise prescription was effective for this patient with distal biceps tendinopathy. Understanding the biomechanical demands of an individual’s functional limitation, in this case baseball pitching, may assist the decision-making process and optimize outcomes. Additional research into the most effective exercise prescriptions for individuals with uncommon tendinopathies is warranted.
Gender Difference in STEM Career Aspiration and Social-Cognitive Factors in Collectivist and Individualist Cultures

Gender equity in STEM demands that girls and women are provided with learning experiences, opportunities, and resources that meet their educational and vocational goals. This study examined gender difference in STEM learning experience, parental involvement, and self-efficacy to predict STEM career aspiration of different sociocultural groups. Two independent samples of high school students, one recruited from a collectivist culture (Taiwanese sample, N = 590) and the other recruited randomly from an individualist culture (American sample, N = 590), were used to examine the differences. Findings suggested a greater gender difference in STEM learning experience, parental involvement, and STEM self-efficacy of students from the collectivist culture than students from the individualist culture. Results of logistic analyses showed differential prediction of STEM career aspiration in two different cultural contexts. Findings were discussed in light of socio-cultural contexts.
Steric aspects of the interaction of metal species with nucleic acid constituents

The delineation of steric effects in the interaction of metal species with biomolecules has been addressed. More specifically, a focus has been placed on the interaction of platinum complexes with nucleoconstituents. Steric effects thus characterised have been related to the biological properties of such complexes. Steric aspects of metal complex speciation have been investigated both from experimental and theoretical viewpoints. Manipulation of steric effects within model systems has been carried out by way of judicious ligand design.
High-Temperature Mechanical Properties of IN718 Alloy: Comparison of Additive Manufactured and Wrought Samples

Wire Arc Additive Manufacturing (WAAM) is one of the most appropriate additive manufacturing techniques for producing large-scale metal components with a high deposition rate and low cost. Recently, the manufacture of nickel-based alloy (IN718) using WAAM technology has received increased attention due to its wide application in industry. However, insufficient information is available on the mechanical properties of WAAM IN718 alloy, for example in high-temperature testing. In this paper, the mechanical properties of IN718 specimens manufactured by the WAAM technique have been investigated by tensile tests and hardness measurements. The specific comparison is also made with the wrought IN718 alloy, while the microstructure was assessed by scanning electron microscopy and X-ray diffraction analysis. Fractographic studies were carried out on the specimens to understand the fracture behavior. It was shown that the yield strength and hardness of WAAM IN718 alloy is higher than that of the wrought alloy IN718, while the ultimate tensile strength of the WAAM alloys is difficult to assess at lower temperatures. The microstructure analysis shows the presence of precipitates (laves phase) in WAAM IN718 alloy. Finally, the effect of precipitation on the mechanical properties of the WAAM IN718 alloy was discussed in detail.
Addressing the Social Determinants of Health in the Nordic Countries: Wicked or Tame Problem?

Dette prosjektet studerte hvilken nasjonal politikk de nordiske land utvikler for a pavirke helsens determinanter. Fokus pa helsens determinanter krever bevissthet om strukturelle betingelser for god helse. Prosjektet hadde en kvalitativ tilnaerming, data besto av dokumenter og intervjuer. Vi undersokte om landene hadde en helhetlig tilnaerming, om politikken var et ansvar for alle sektorer og om den var forpliktende. Sosiale ulikheter kan kalles et innflokt (wicked) problem, der det finnes politiske konflikter som bidrar til problemer med a gjennomfore politikk som ivaretar determinant perspektivet. Alle landene har formulert politiske malsetninger om a utjevne sosiale helseforskjeller, men tiltak finnes mest pa lokalt niva og fokuserer mest pa levevaner. De bredere helsedeterminantene blir ofte ikke anerkjent og innflokte problemer blir omdefinert til tamme problemer, som er mer ukontroversielle og lettere a implementere.
Analytical Non-Stationary Satellite to Aircraft Channel Modeling over Open Area Based on Regular Shaped Geometry-Based Stochastic Model

Channel modeling is crucial to the development and evaluation of modern wireless communication systems including satellite communication system, since there might be critical safty-of-life applications. Also, the channel model is of great importance to the performance evaluation of mobile communication systems. In recent years, encouraged by the widely application of unmanned aerial vehicles, the research on channel modeling for aerial and aeronautical communications attract lots of interests. In the published articles, stationary and non-stationary channel models have been developed for air-to-ground communications based on regular shaped geometry-based stochastic model (RS-GBSM). The modeling of air-to-air or satellite-to-aircraft (S2A) communication is still quite simple or completely lacking. For obtaining more precise model of S2A channel, this paper presents an analytical non-stationary S2A channel mode based on RS-GBSM with considerations on line-of-sight path, specular reflection path, and ground scattering path. Analytical expressions of the channel impulse responses, the transfer functions, the auto-correlation functions, and the Doppler power spectrum density based on 3-path model are derived and simulated. Also, the distributions of the path antennation, the path delay, and the normalized Doppler shift based on uniform distribution of the scatterers are derived, simulated and fitted.
Modeling Measurement Errors of the Exogenous Composites From Congeneric Measures in Interaction Models

ABSTRACT We investigated the performance of two single indicator methods: latent moderated structural equation (LMS) and reliability-adjusted product indicator (RAPI) methods, on testing interaction effects with congeneric measures, which vary in factor loadings and error variances under a common factor. Additionally, in the simulation study, we compared the performance of four reliability estimates (Cronbach’s alpha, omega composite, Coefficient H, and greatest lower bound [GLB]) to adjust for the exogenous composites’ measurement errors. Results from the study showed that: while estimating interaction effects with exogenous composites from congeneric measures, the four reliability estimates performed comparably well. Recommendations on the choice of reliability estimates between the LMS and the RAPI methods under different sample sizes and population reliability conditions are further discussed.
Task Based Semantic Segmentation of Soft X-ray CT Images Using 3D Convolutional Neural Networks

Semantic segmentation refers to the process of linking each pixel in an image to a class label, for example, cell phenotype, membrane, nucleus, or mitochondria. In practice, semantic segmentation simplifies a tomographic reconstruction and enables quantifiable analysis of the organelles in the cell, such as density differences, spatial distance metrics such as distances between organelles, and morphometrics. In Soft X-ray Tomography (SXT), segmentation is based on the measured Linear Absorption Coefficient (LAC) and guided and confirmed by structural cues, sub-cellular location, together with data from other imaging modalities. Currently, segmentation is a time-consuming, mostly manual process that often depends on specialist knowledge of the specimen to identify features in the reconstruction. To address this bottleneck, and make segmentation less dependent on user effort and expertise, we aim to incorporate automated, machine learning segmentation algorithms into our existing data processing and analysis pipeline. To date, NCXT staff and users have segmented thousands of individual cells. Since each segmentation represents many hours or even days of effort, the accumulated information and data is an enormously valuable resource for training machine learning algorithms. We have begun taking advantage of this resource by developing a data-driven machine learning segmentation pipeline Fig. 1. Our aim is to refine our segmentation pipeline to improve accuracy and set up a task-based framework, where users can define the required semantic information for their problem, and get a tailor-made algorithm that draws on all the available reference data for that specific task.
EVIDENCE-BASED NUTRITIONAL GUIDELINES What is meant by trustworthy recommendations

The article aims to describe the characteristics of trustworthy recommendations as well as standards for trustworthy guidelines published by the Institute of Medicine and tools that can be used for quality assessment. The next section summarizes published assessments of guidelines quality using AGREE (Appraisal of Guidelines, Research and Evaluation) Instrument and the problems raised by the National Academy of Sciences regarding the development process of nutritional guidelines. Similar problems are also reflected in the assessment of quality of dietary guides, since less than 50 % of the documents were rated as high quality. The article is concluded with the description of the NutriRECS protocol, as an example of a strict, transparent and comprehensive approach to draw up nutritional guidance.