Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Simplifications of the Dynamic Model on the Motion of a Six-Jointed Industrial Articulated Robotic Arm Movement

This research investigates the impact of model simplification on the dynamic performance of an ABB IRB-140 six-jointed industrial robotic arm, concentrating on torque prediction and energy consumption. The entire mathematical model of forward, reverse, differential kinematics, and dynamic model proposed based on the technical specifications of the arm, and to obtain the center of the mass and inertia matrices, which are essential components of the dynamic model, Utilizing Solidworks, we developed three CAD/CAM models representing the manipulator with varying detail levels, such as simplified, semi-detailed, and detailed. Our findings indicate minor differences in the model's torque and energy consumption graphs. The semi-detailed model consumed the most energy, except for joint 1, with the detailed model showing a 0.53% reduction and the simplified model a 6.8% reduction in energy consumption. Despite these variations, all models proved effective in predicting the robot's performance during a standard 30-second task, demonstrating their adequacy for various industrial applications. This research highlights the balance between computational efficiency and accuracy in model selection. While the detailed model offers the highest precision, it demands more computational resources, which is suitable for high-precision tasks. In discrepancy, simplified, less precise models offer computational efficiency, making them adequate for specific scenarios. Our study provides critical insights into selecting dynamic models in industrial robotics. It guides the optimization of performance and energy efficiency based on the required task precision and available computational resources. This comprehensive comparison of dynamic models underscores their applicability and effectiveness in diverse industrial settings.
THE EFFECTS OF ALLOYING ELEMENTS AND EXPOSURE ATMOSPHERES ON SIGMA FORMATION IN FERRITIC ALLOYS

Tests were performed on a variety of model and commercial ferritic steels in simulated cathode and anode environments of an intermediate temperature solid oxide fuel cell (SOFC). The alloys were picked for their similarity to currently used interconnect materials. Results from the test provide inside into the effect of exposure atmospheres and alloying elements on the nucleation and growth of sigma phase in the ferritic alloys. Two possible mechanisms for sigma phase transformation were discussed, but the exact method was not able to be determined based on the results shown. The cathode environment was simulated by either using dry laboratory air, or in the case of a pipe-sealant leak in the SOFC, dry air with 10% water vapor at 700 °C. Three model alloys were tested in these environments to determine the effect of water vapor and alloying elements on the nucleation and growth of sigma phase. It was confirmed that molybdenum is a sigma phase promoter and allows for the nucleation and growth to occur. The presence of water vapor in the exposure environment caused an increased amount of sigma phase formation, although the exact reason why remains unknown. The anode environment was simulated by using an Ar-4%H2-10%H2O gas-water vapor mixture at 700 °C. A variety of model alloys and commercial alloys were tested in this environment. To simulate the effect of a nickel mesh touching the interconnect in the SOFC cell, nickel was electroplated onto some specimens prior to exposure. The pre-coat of nickel caused the formation of an austenitic interdiffusion zone in all alloys, and in all but the low-Cr alloy, this also lead to the formation of sigma phase. Two possible mechanisms for sigma phase formation were suggested. The first is that the ferrite phase decomposed directly into austenite and sigma phase. The second is that the ferrite phase first transformed into austenite, which then transformed into sigma phase. Neither method could be confirmed based on the results obtained.
Positive and Negative Effects of Administering a Magnetic Field to Patients with Rheumatoid Arthritis (RA)

Background: Magnetotherapy applied to patients with rheumatoid arthritis (RA) produces anti-inflammatory, analgesic and antioedema effects. Observations suggest that the beneficial and adverse effects of magnetotherapy are related to the parameters of the magnetic field applied. This study aimed to assess the positive and negative effects of magnetotherapy, taking into account the type of the field. Methods: This study involved 39 patients with RA, who were randomly assigned to two groups: SMF—static magnetic field (n = 18) and PEMF—low-frequency pulsed electromagnetic field (n = 21). The examinations carried out before and after the therapy included a general assessment of the functional status, assessment of pain severity, measurement of the duration and severity of morning stiffness, computer-aided measurement of the range of motion of the hand joints and measurement of the hand volume using water displacement method. The patients received kinesiotherapy and magnetotherapy, as determined by the randomisation. Results: The findings show improved functional status by 0.26 points on average (p = 0.0166) measured with the Health Assessment Questionnaire (HAQ-20), reduced pain by 2.2 points on average (p = 0.0000) on the Visual Analogue Scale (VAS), decreased duration of morning stiffness by 23.2 min on average (p = 0.0010) and reduced severity of morning stiffness by 15.2 points on average (p = 0.0010). The assessment of the dominant hand showed improved range of motion by 1.9 mm on average (p = 0.0036) and reduced volume by 0.9 mm3 on average (p = 0.0230). A significantly reduced duration and severity of morning stiffness was observed in the SMF group. Statistically significant changes in the HAQ-20 scores, range of motion and the volume of the dominant hand were identified in the PEMF group. Conclusions: Magnetic fields improved the functional status and reduced pain, morning stiffness and swelling in the hand. A static magnetic field may be more effective in reducing morning stiffness, whereas a pulsed magnetic field may, to a greater extent, improve function and reduce swelling in the rheumatoid hand. The effects of magnetotherapy reported so far require further observation.
ICT-Based or -Assisted Mathematics Learning and Numerical Literacy: A Systematic Review and Meta-Analysis

Numerous empirical studies related to the use of Information and Communication Technology (ICT) in mathematics learning for enhancing numerical literacy have been increasingly carried out in three last decades. Of those studies, however, it can be stated that ICT-based or -assisted mathematics learning has an inconsistent effect on numerical literacy. Consequently, this recent study aims to examine the effectiveness of ICT-based or -assisted mathematics learning on numerical literacy skills, and several substantial factors in differentiating students’ numerical literacy. A systematic review combined to meta-analysis was performed to carry out this study whereby 53 documents published in the period of 2001–2023 were involved as the data. Overall, those documents generated 64 units of effect size and 6,599 students. Some tests, such as Z, Q Cochrane, fill & trim, and funnel plot were used to analyze the data. The results of this current study reported that ICT-based or -assisted mathematics learning had positive moderate effect (g = 0.527; p < 0.05) on students’ numerical literacy, and significantly enhanced students’ numerical literacy. Additionally, educational level, learning environment, intervention duration, and instrument type were significant factors in differentiating students’ numerical literacy. Meanwhile, there was no sufficient evidence to state that other substantial factors, such class capacity, participant, technology used, mathematical content, and technology role significantly affected students’ heterogeneous numerical literacy. This study suggests mathematics educator, such as teacher and lecturer to integrate ICT in mathematics learning, especially in enhancing numerical literacy. Moreover, they have to consider some factors, such as educational level, learning environment, intervention duration, and instrument type in performing ICT-based or -assisted mathematics lesson, mainly in cultivating students’ numerical literacy.
Investigation of functional and sensory properties of plantain flour in citric acid

Purpose: This study investigated the effects of process variables on the proximate, functional, and sensory properties of plantain flour. Research Methodology: The plantain fruit was sorted and hand-peeled using kitchen knives. It was then cut into various slices of 2 – 6 mm and steeped in citric acid solutions with concentrations ranging between 1 – 5 %. The steeping time varied between 30 – 120 min. The pretreated plantain slices were processed into flours. Process parameters were analyzed using the response surface methodology of Design Expert software. Results: The proximate parameters of the flour samples showed no significant difference (p > 0.05), but there were significant effects (p< 0.05) on the functional and sensory properties of the flour samples. The functional properties were found to differ significantly. Limitation: This study did not consider the application of other optimization methods such as genetic algorithm and particle swarm optimization in estimating the optimum points. Future studies could focus on these areas. Contribution: The validation of the optimization processes showed success in the application of citric acid in the production of novel plantain flour.
Impact of the coronavirus disease 2019 pandemic on the diversity of notifiable infectious diseases: a case study in Shanghai, China

The outbreak of coronavirus disease 2019 (COVID-19) has not only posed significant challenges to public health but has also impacted every aspect of society and the environment. In this study, we propose an index of notifiable disease outbreaks (NDOI) to assess the impact of COVID-19 on other notifiable diseases in Shanghai, China. Additionally, we identify the critical factors influencing these diseases using multivariate statistical analysis. We collected monthly data on 34 notifiable infectious diseases (NIDs) and corresponding environmental and socioeconomic factors (17 indicators) from January 2017 to December 2020. The results revealed that the total number of cases and NDOI of all notifiable diseases decreased by 47.1% and 52.6%, respectively, compared to the period before the COVID-19 pandemic. Moreover, the COVID-19 pandemic has led to improved air quality as well as impacted the social economy and human life. Redundancy analysis (RDA) showed that population mobility, particulate matter (PM2.5), atmospheric pressure, and temperature were the primary factors influencing the spread of notifiable diseases. The NDOI is beneficial in establishing an early warning system for infectious disease epidemics at different scales. Furthermore, our findings also provide insight into the response mechanisms of notifiable diseases influenced by social and environmental factors.
Effect of Radiation on Casson Hybrid Nano-fluid Flow over an Inclined Surface Using Blasius Rayleigh-Stokes Variable: Application in Solar Aircraft

Solar energy is the most important heat source from the sun, with photovoltaic cells, solar power plates, photovoltaic lights, and solar pumping water being widely used. This study looks at solar energy analysis and a method for increasing the efficacy of solar aircraft by combining solar and nano-technological energy. To enrich the research on solar aircraft wings, the study is built on the investigation of heat transfer by employing a hybrid nano-fluid past inside the parabolic trough solar collector (PTSC). The thermal source is referred to as the solar radiative flow. The heat transfer efficiency of the wings was validated for different qualities such as porous medium, viscous dissipation, play heating, and thermal energy flow. The modelled energy and momentum equations were controlled by utilizing the Galerkin-weighted residual method (GWRM). This study used two types of nano-solid particles, copper (Cu) and zirconium dioxide (ZrO2), in ethylene glycol (EG) as the standard fluid. Various control parameters for velocity, temperature outlines, frictional factor, and Nusselt number were explained and shown in figures and tables. Also, analyses reveal that the thermal profile reduces with an increase in variable thermal conductivity parameters. This study will be of considerable economic value to marine engineers, mechanical engineers, physicists, chemical engineers, and others since its application will help them improve their operations. The findings revealed that the magnetic term is positively impacted by the Cu-ZrO2/EG hybrid nanofluid's thermal distribution.
Height Estimation and Error Assessment of Inland Water Level Time Series calculated by a Kalman Filter Approach using Multi-Mission Satellite Altimetry

Abstract Inthisposter,wepresentourmethodologyforestimatingwaterleveltimeseriesoverlakes,reservoirs,andrivers.Furthermore,anerrorassessmentoftheresultingwaterleveltimeseriesisdemonstrated. Forcomputingthewaterleveltimeseriesmulti-mission satellite altimetry data is used. The estimation is based on altimeter data from Topex, Jason-1, Jason-2, GFO, ERS-2,Envisat,andSaral/Altika–dependingonthelocationofthewaterbody.Accordingtotheextentoftheinvestigatedwaterbody1Hz,high-frequentorretrackedaltimetermeasurementscanbeused.DifferentoutlierrejectionssuchasthresholdsorSupportVectorRegression(SVR)canbeusedforrejectingoutliers.ForestimatingwaterlevelheightsaKalmanfilterapproachappliedtothegridnodesofahexagonalgridcoveringthewaterbodyofinterestisimplemented. Aftersettinganerrorlimitontheresultingwaterlevelheightsofeachgridnode,aweightedaveragewaterlevelperpointoftimeisderivedreferringtoonereferencelocation.Fortheestimationofwaterlevelheightaccuracies,atfirst,theformalerrorsarecomputedapplyingafullerrorpropagationwithinKalmanfiltering.Hereby,theprecisionoftheinputmeasurementsareintroducedbyusingthestandarddeviationofthewaterlevelheightalongthealtimetertrack.Forvalidationofthetimeseries,wecompareourresultswithinsitudataandexternalinlandaltimeterdatabasesfromHydroweb(LEGOS),RiverandLakes(ESA-DMU),andGlobalRiverandLakesMonitor(GRLM)byUSDA.WeyieldlowRMSdifferencesandveryhighcorrelationsbetweenabsolutewaterlevelheighttimeseriesfromaltimetryandgauges. Moreover,thecomparisonsofwaterlevelheightsarealsousedforthevalidationoftheerrorassessment.Morethan250waterleveltimeserieswerealreadycomputedandmadepublicavailableviathe"DatabaseforHydrologicalTimeSeriesofInlandWaters"(DAHITI)whichisavailableviahttp://dahiti.dgfi. tum.deoperatedbyDGFI-TUM.
Supply chain of the Molluscan Shellfish: Overview of Key Food Safety Issues

Molluscan shellfish (hereafter, shellfish), together with finfish, crustaceans and other mollusks, are among the most internationally traded food commodities. Shellfish are low in fat, with a high concentration of monounsaturated and polyunsaturated fat, and provide high quality protein for the human diet, but their consumption, particularly raw or undercooked, is not risk-free. In fact these animals consume organic material through the flow of water from their aquatic environment by specialized filtration systems, and in this way they can hold and even concentrate contaminants, including harmful bacteria and viruses, chemicals and marine biotoxins. From an epidemiological point of view, the foodborne diseases of major concern linked to the consumption of shellfish are caused by enteroviruses, as Noroviruses (NoVs) and Hepatitis A virus (HAV), and pathogenic marine bacteria, as V. parahaemolyticus and V. vulnificus . Considering that it is impossible to determine whether shellfish are contaminated with pathogenic microorganisms without microbiological testing, it is very important to control them at the origin (monitoring of the growing areas) or eliminate them by post-harvest treatments. This review will focus on the key safety issues of the supply chain of shellfish, having regard with the regulatory and supervision rules established in Europe and U.S, with the specific aim to point out criticisms.
Autophagy, Pyroptosis and Ferroptosis are Rising Stars in the Pathogenesis of Diabetic Nephropathy

Abstract Diabetic nephropathy (DN) is one of the most common microvascular complications in diabetes and can potentially develop into end-stage renal disease. Its pathogenesis is complex and not fully understood. Podocytes, glomerular endothelial cells (GECs), glomerular mesangial cells (GMCs) and renal tubular epithelial cells (TECs) play important roles in the normal function of glomerulus and renal tubules, and their injury is involved in the progression of DN. Although our understanding of the mechanisms leading to DN has substantially improved, we still need to find more effective therapeutic targets. Autophagy, pyroptosis and ferroptosis are programmed cell death processes that are associated with inflammation and are closely related to a variety of diseases. Recently, a growing number of studies have reported that autophagy, pyroptosis and ferroptosis regulate the function of podocytes, GECs, GMCs and TECs. This review highlights the contributions of autophagy, pyroptosis, and ferroptosis to DN injury in these cells, offering potential therapeutic targets for DN treatment.
Description of the COVID-19 epidemiology in Malaysia

Introduction Since the COVID-19 pandemic began, it has spread rapidly across the world and has resulted in recurrent outbreaks. This study aims to describe the COVID-19 epidemiology in terms of COVID-19 cases, deaths, ICU admissions, ventilator requirements, testing, incidence rate, death rate, case fatality rate (CFR) and test positivity rate for each outbreak from the beginning of the pandemic in 2020 till endemicity of COVID-19 in 2022 in Malaysia. Methods Data was sourced from the GitHub repository and the Ministry of Health’s official COVID-19 website. The study period was from the beginning of the outbreak in Malaysia, which began during Epidemiological Week (Ep Wk) 4 in 2020, to the last Ep Wk 18 in 2022. Data were aggregated by Ep Wk and analyzed in terms of COVID-19 cases, deaths, ICU admissions, ventilator requirements, testing, incidence rate, death rate, case fatality rate (CFR) and test positivity rate by years (2020 and 2022) and for each outbreak of COVID-19. Results A total of 4,456,736 cases, 35,579 deaths and 58,906,954 COVID-19 tests were reported for the period from 2020 to 2022. The COVID-19 incidence rate, death rate, CFR and test positivity rate were reported at 1.085 and 0.009 per 1,000 populations, 0.80 and 7.57%, respectively, for the period from 2020 to 2022. Higher cases, deaths, testing, incidence/death rate, CFR and test positivity rates were reported in 2021 and during the Delta outbreak. This is evident by the highest number of COVID-19 cases, ICU admissions, ventilatory requirements and deaths observed during the Delta outbreak. Conclusion The Delta outbreak was the most severe compared to other outbreaks in Malaysia’s study period. In addition, this study provides evidence that outbreaks of COVID-19, which are caused by highly virulent and transmissible variants, tend to be more severe and devastating if these outbreaks are not controlled early on. Therefore, close monitoring of key epidemiological indicators, as reported in this study, is essential in the control and management of future COVID-19 outbreaks in Malaysia.
Analysis and testing of a winter orographic precipitation model

ANALYSIS AND TESTING OF A WINTER OROGRAPHIC PRECIPITATION MODEL In the mid-1970's, an orographic precipitation model was developed by J. Owen Rhea in an effort to determine the ability to diagnose the effect of topography on winter precipitation for western Colorado. The model was tested for various time periods for differing wind regimes using upper air data and a fine-mesh topographic grid. The model is two-dimensional, steady state and multi-layer. Computations follow parcels at layer mid-points through topographically-induced moist adiabatic ascents and descents. The Lagrangian coordinate system allows for consideration of precipitation shadowing effects by upstream barriers. The model was originally tested for 13 winter seasons and the results were well correlated to observed values of snowpack water equivalent and spring and summer runoff. Although large discrepancies often existed between model and observations on a daily basis, the model frequency distribution of daily precipitation totals was realistic. This study attempted to update and improve the historical comparisons of model calculations to observations and also investigate the application of the model to current-season snowpack diagnosis and prediction. Model calculations were performed for the most recent 15
Magnetic anisotropies of (Ga,Mn)As films and nanostructures

In this work the magnetic anisotropies of the diluted magnetic semiconductor (Ga,Mn)As were investigated experimentally. (Ga,Mn)As films show a superposition of various magnetic anisotropies which depend sensitively on various parameters such as temperature, carrier concentration or lattice strain. However, the anisotropies of lithographically prepared (Ga,Mn)As elements differ significantly from an unpatterned (Ga,Mn)As film. In stripe-shaped structures this behaviour is caused by anisotropic relaxation of the compressive lattice strain. In order to determine the magnetic anisotropies of individual (Ga,Mn)As nanostructures a combination of ferromagnetic resonance and time-resolved scanning Kerr microscopy was employed in this thesis. In addition, local changes of the magnetic anisotropy in circular and rectangular structures were visualized by making use of spatially resolved measurements. Finally, also the influence of the laterally inhomogeneous magnetic anisotropies on the static magnetic properties, such as coercive fields, was investigated employing spatially resolved static MOKE measurements on individual (Ga,Mn)As elements.