Miracle-dz/UniFAR-FTUs huggingface dataset:
Validating a Computational Framework for Ionic Electrodiffusion with Cortical Spreading Depression as a Case Study

Abstract Cortical spreading depression (CSD) is a wave of pronounced depolarization of brain tissue accompanied by substantial shifts in ionic concentrations and cellular swelling. Here, we validate a computational framework for modeling electrical potentials, ionic movement, and cellular swelling in brain tissue during CSD. We consider different model variations representing wild-type (WT) or knock-out/knock-down mice and systematically compare the numerical results with reports from a selection of experimental studies. We find that the data for several CSD hallmarks obtained computationally, including wave propagation speed, direct current shift duration, peak in extracellular K+ concentration as well as a pronounced shrinkage of extracellular space (ECS) are well in line with what has previously been observed experimentally. Further, we assess how key model parameters including cellular diffusivity, structural ratios, membrane water and/or K+ permeabilities affect the set of CSD characteristics.
Increased Brain Volumetric Measurement Precision from Multi-Site 3D T1-weighted 3T Magnetic Resonance Imaging by Correcting Geometric Distortions

Magnetic resonance imaging (MRI) scanner-specific geometric distortions may contribute to scanner induced variability and decrease volumetric measurement precision for multi-site studies. The purpose of this study was to determine whether geometric distortion correction increases the precision of brain volumetric measurements in a multi-site multi-scanner study. Geometric distortion variation was quantified over a one-year period at 10 sites using the distortion fields estimated from monthly 3D T1-weighted MRI geometrical phantom scans. The variability of volume and distance measurements were quantified using synthetic volumes and a standard quantitative MRI (qMRI) phantom. The effects of geometric distortion corrections on MRI derived volumetric measurements of the human brain were assessed in two subjects scanned on each of the 10 MRI scanners and in 150 subjects with cerebrovascaular disease (CVD) acquired across imaging sites. Geometric distortions were found to vary substantially between different MRI scanners but were relatively stable on each scanner over a one-year interval. Geometric distortions varied spatially, increasing in severity with distance from the magnet isocenter. In measurements made with the qMRI phantom, the geometric distortion correction decreased the standard deviation of volumetric assessments by 35% and distance measurements by 42%. The average coefficient of variance decreased by 16% in gray matter and white matter volume estimates in the two subjects scanned on the 10 MRI scanners. Geometric distortion correction using an up-to-date correction field is recommended to increase precision in volumetric measurements made from MRI images.
Pulsewidth Modulated Three-Level Buck Converter Based on Stacking Switch-Cells for High Power Envelope Tracking Applications

Envelope tracking is a well-known RF technique that alleviates the efficiency problem of linear power amplifiers used in wireless communication transmitters. It consists in varying the supply voltage of the amplifier, which is commonly constant, according to the envelope of the communication signal. Therefore, a switching-mode power converter with a bandwidth of several megahertz is required to perform the fast voltage changes needed for tracking the envelope properly. Another important requirement is that the converter needs to be able to achieve high efficiency not only at peak output power, but also at low output power because it operates in that power range most of the time due to the characteristics of modern communication signals. Taking into account these requirements, the design of the converter is very challenging, especially in the case of base stations, where higher power levels are reached by means of higher voltage levels. As a result, transistors with low breakdown voltages (20–30 V), which offer the highest speed, cannot be used in the converter. In this article, a novel multilevel converter able to use transistors with low breakdown voltages is proposed to alleviate that problem. Moreover, it shows a better switching behavior than the previously proposed multilevel converters, thus reducing the switching losses and, consequently, increasing the efficiency. In order to experimentally validate the proposed topology, a 73-W prototype with a switching frequency of 8 MHz was built. The efficiency is 94% and 81.7% at peak output power and at one-tenth of peak output power, respectively.
A Short-Term Solar Photovoltaic Power Optimized Prediction Interval Model Based on FOS-ELM Algorithm

Solar energy conversion efficiency has improved by the advancement technology of photovoltaic (PV) and the involvement of administrations worldwide. However, environmental conditions influence PV power output, resulting in randomness and intermittency. These characteristics may be harmful to the power scheme. As a conclusion, precise and timely power forecast information is essential for the power networks to engage solar energy. To lessen the negative impact of PV electricity usage, the offered short-term solar photovoltaic (PV) power estimate design is based on an online sequential extreme learning machine with a forgetting mechanism (FOS-ELM) under this study. This approach can replace existing knowledge with new information on a continuous basis. The variance of model uncertainty is computed in the first stage by using a learning algorithm to provide predictable PV power estimations. Stage two entails creating a one-of-a-kind PI based on cost function to enhance the ELM limitations and quantify noise uncertainty in respect of variance. As per findings, this approach does have the benefits of short training duration and better reliability. This technique can assist the energy dispatching unit list producing strategies while also providing temporal and spatial compensation and integrated power regulation, which are crucial for the stability and security of energy systems and also their continuous optimization.
Relationship between heat storage and parameters of thermotolerance and fatigue in exertional-heat stress

Background/Aim. The risk assessment of heat illness and fatigue development is very important in military services. the aim of our study was to investigate the relationship between heat storage and various psychophysiological parameters of heat stress, as well as potential peripheral markers of fatigue in soldiers performing exertional heat stress test. Methods. 15 young, healthy and unacclimatized men underwent exertional heat stress test (EHST) with submaximal work load in warm conditions (WBGT 29 ? C) in climatic chamber. Every 5 minutes following parameters of thermotolerance were measured or calculated: core temperature (Tc), mean skin (Tsk) and body temperature (Tb), heart rate (HR), heat storage (HS), physiological strain index (PSI), as well as peripheral markers of fatigue (blood concentrations of ammonia, urea nitrogen (BUN), lactate dehydrogenase (LDH), cortisol and prolactin) and subjective parameters: thermal sensation (TS) and rate of perceived exertion (RPE). Results. Tolerance time varied from 45-75 minutes (63? 7,7 min). Average values of Tc, Tb, and HR constantly increased during EHST, while Tsk after 10 minutes reached the plateau. Concentrations of all investigated peripheral markers of fatigue were significantly higher after EHST compared to baseline levels (31,47? 7,29 vs. 11,8? 1,11 ? mol/l for ammonia; 5,92? 0,73 vs. 4,69? 0,74 mmol/l for BUN, 187,27? 28,49 vs.152,73? 23,39 U/l for LDH, 743,43? 206,19 vs. 558,79? 113,34 mmol/l for cortisol and 418,08? 157,14 vs. 138,79? 92,83 ? IU/mL for prolactin). Conclusions. This study demonstrates the relationship between heat storage and Tc, HR, TS and RPE, but also with PSI. Concentrations of cortisol and especially prolactin showed significant correlation with parameters of thermotolerance.
Vital exhaustion and psychosocial health among offshore personnel working in the Philippines

The offshore environment is a high-risk and demanding workplace exposing crew members to various physical and psychological stressors. Health and safety programs are implemented to prevent accidents and promote well-being among personnel. This study aims to determine the association between vital exhaustion and psychosocial health among offshore workers in the Philippines. Quantitative non-experimental descriptive correlational design was used and standardized questionnaires namely: Maastricht Vital Exhaustion (MVEQ) and Copenhagen Psychosocial Questionnaires (COPSOQ III) were utilized to gather data from fifty-five respondents (54 male; Mage = 42.69). Majority of them are assigned in the maintenance and marine departments with an average offshore experience of 11.69 years. Offshore workers have low vital exhaustion (VE) levels and good psychosocial health (PH) scores. Highest recorded scores for PH fall under Influence and Development, Outcome Scales and Interpersonal relations and leadership. Lower mean scores in Further Parameters and Demands at work also translate to favourable PH. There was a significant relationship among four PH scales and VE levels of respondents. There was also a significant relationship between VE and the demographic profile of offshore workers in terms of job assignment and work type however there was no significant association between PH and all demographic variables considered in the study. Majority of the participants claimed that environmental conditions are well-designed and safety concerns are managed appropriately in the workplace. The responses from offshore personnel provide a clear picture of their overall health. The resilience and camaraderie among the all-Filipino crew played a major role in keeping their VE levels low and promoting good PH scores.
A Local Thermal Nonequilibrium Analysis of Silicon Carbide Ceramic Foam as a Solar Volumetric Receiver

A volumetric solar receiver receives the concentrated radiation generated by a large number of heliostats. Heat transfer takes place from the receiver solid phase to the air as it passes through the porous receiver. Such combined heat transfer within the receiver, associated radiation, convection and conduction, are investigated using a local thermal nonequilibrium model. The Rosseland approximation is applied to account for the radiative heat transfer through the solar receiver, while the low Mach approximation is exploited to investigate the compressible flow through the receiver. Analytic solutions are obtained for the developments of air and ceramic temperatures as well as the pressure along the flow direction. The results show that the pore diameter must be larger than its critical value to achieve high receiver efficiency. Subsequently, there exists an optimal pore diameter for achieving the maximum receiver efficiency under the equal pumping power. The solutions serve as a useful tool for designing a novel volumetric solar receiver of silicon carbide ceramic foam. [DOI: 10.1115/1.4005758]
Performance evaluation of a high power density PMASynRM with ferrite magnets

Although motors that use rare-earth permanent magnets typically exhibit high performance, high costs and concerns about the stability of raw material supplies are leading to their decreased production. However, the performance of such motors is not easily matched without the use of rare-earth permanent magnets. This paper proposes and examines a permanent magnet assisted synchronous reluctance motor with ferrite magnets that has the same power density as rare-earth permanent magnet synchronous motors. A suitable rotor structure for high torque and high power is also discussed with respect to demagnetization and mechanical strength.
Improving the classification of phishing websites using a hybrid algorithm

In this article, a hybrid algorithm has been proposed for the identification of phishing and legitimate websites. The dataset may have an imbalanced class distribution and may consist of irrelevant features. Therefore, in the data preprocessing, the adaptive synthetic sampling approach has been used to handle the imbalanced data. Irrelevant or redundant features are removed from the balanced data using the proposed binary version of Rao algorithms. The S‐shaped and V‐shaped transfer functions are applied for mapping continuous search space to discrete search space. Also, the results of these S‐shaped and V‐shaped transfer functions are analyzed for proposed algorithms. The performance is improved by optimizing the value of the k parameter in the kNN classifier. The dataset used in this article has been taken from the UCI machine‐learning repository. The performance of the proposed approach has been evaluated using the polygon area metric. The obtained classification accuracy is 97.044%. A comparison of the proposed hybrid algorithm with the other state‐of‐the‐art techniques is also made for validation. Moreover, the proposed approach has been compared with seven metaheuristic feature selection algorithms and six filter methods for performance analysis. Additionally, we have applied the proposed approach to URLs that are registered on the PhishTank website.
Entrepreneurship and Marketing in Audience Development within New Zealand Performing Arts Companies

The paper aims to develop a framework for future research on the interface between relationship marketing and entrepreneurship in the performing arts in New Zealand and the role this interface might play in the successful development of audiences. The common link between relationship marketing and entrepreneurship is network analysis, focusing on both a strategic and operational level. It is proposed that relationship marketing enhances the audience development function, and those arts managers and marketers who use relationship marketing are likely to be successful in attracting and maintaining their audience base. Not only do they maintain regular subscribers but constantly look at ways of increasing attendance by attracting new audiences. An important factor could be that such managers espouse an entrepreneurial approach - they are willing to take risks and stretch the boundaries of their artistic product by supporting innovative programming. Biography Tara Werner is Director, Arts Management Programmes in the School of Creative and Performing Arts at the University of Auckland. She was previously Director of the MBA and Master of Management within Executive Programmes at the School of Business and Economics. She has been a music and arts journalist, most recently with the New Zealand Herald, where she was classical music critic for 13 years.
Job Characteristics, Well-Being and Physical Activity: A Field Study Using a Consumer Fitness Tracker

The relation between job characteristics and health is one of the most important fields of research within work and organizational psychology. Another prominent variable influencing health is physical activity. The physical activity mediated Demand-Control (pamDC) model (Häusser & Mojzisch, 2017, https://doi.org/10.1080/02678373.2017.1303759) combines these health indicators in a new theoretical framework. Based on the pamDC model the current study aims to clarify the role of leisure time physical activity (LTPA) in the interplay of job demands, job control and well-being. We expect physical activity to partially mediate the impact of job characteristics on health. To avoid self-report bias considering physical activity we used a consumer fitness tracker to collect additional data. In total, 104 white-collar workers participated in the study. The results show that job control and job demands could predict well-being in cross-sectional analyses. In longitudinal analyses, this was only the case for job demands. Regarding the proposed mediating effect of LTPA between job characteristics and health, we could not detect a significant mediation in our sample. This was true for both self-reported and objective data on physical activity. This study provides a first step in validating the pamDC model and has implications for future research.
Noncatalytic Oxidative Coupling of Methane (OCM): Gas-Phase Reactions in a Jet Stirred Reactor (JSR)

Oxidative coupling of methane (OCM) is a promising technique for converting methane to higher hydrocarbons in a single reactor. Catalytic OCM is known to proceed via both gas-phase and surface chemical reactions. It is essential to first implement an accurate gas-phase model and then to further develop comprehensive homogeneous–heterogeneous OCM reaction networks. In this work, OCM gas-phase kinetics using a jet-stirred reactor are studied in the absence of a catalyst and simulated using a 0-D reactor model. Experiments were conducted in OCM-relevant operating conditions under various temperatures, residence times, and inlet CH4/O2 ratios. Simulations of different gas-phase models related to methane oxidation were implemented and compared against the experimental data. Quantities of interest (QoI) and rate of production analyses on hydrocarbon products were also performed to evaluate the models. The gas-phase models taken from catalytic reaction networks could not adequately describe the experimental gas-phase performances. NUIGMech1.1 was selected as the most comprehensive model to describe the OCM gas-phase kinetics; it is recommended for further use as the gas-phase model for constructing homogeneous–heterogeneous reaction networks.
Foodomic-Based Approach for the Control and Quality Improvement of Dairy Products

The food quality assurance before selling is a needed requirement intended for protecting consumer interests. In the same way, it is also indispensable to promote continuous improvement of sensory and nutritional properties. In this regard, food research has recently contributed with studies focused on the use of ‘foodomics’. This review focuses on the use of this technology, represented by transcriptomics, proteomics, and metabolomics, for the control and quality improvement of dairy products. The complex matrix of these foods requires sophisticated technology able to extract large amounts of information with which to influence their aptitude for consumption. Thus, throughout the article, different applications of the aforementioned technologies are described and discussed in essential matters related to food quality, such as the detection of fraud and/or adulterations, microbiological safety, and the assessment and improvement of transformation industrial processes (e.g., fermentation and ripening). The magnitude of the reported results may open the door to an in-depth transformation of the most conventional analytical processes, with the introduction of new techniques that allow a greater understanding of the biochemical phenomena occurred in this type of food.
Design and Modeling of Bioreactor Utilizing Electrophoresis and Di-Electrophoresis Techniques for Regenerating Reabsorption Function of Human Kidney PCT in Microfluidics Environment

The need for innovation in medical device technology is immense; especially to replace dialysis techniques the necessity is extremely high. Available techniques that promised to replace dialysis have not yet geared up to the marketization level. The utilization of live kidney cells makes these devices costly, delicate, and unreliable. This paper aims to design a bioreactor to mimic the reabsorption function of the kidney that is fully artificial and highly controllable, which can be one step forward to the emerging Kidney-on-Chip (KOC) technology. The additional benefit of the proposed design is that it utilizes size-dependent reabsorption along with charge-dependent reabsorption phenomena to make it more compatible with human kidney function. The electrophoresis (EP), and di-electrophoresis (DEP) techniques are utilized to mimic the reabsorption function in this report. The structure utilized in the present design exactly replicates the proximal convoluted tubule (PCT) dimensions and functions as well. The whole setup is implemented in the COMSOL Multiphysics FEM benchmark tool for simulation, and analysis with appropriate boundary conditions. The device when excited by an electric field, Electrophoresis has produced a maximum velocity of 1.07 m/s for DC excitation and di-electrophoresis has produced a maximum flow velocity of 1.23 m/s, where both the offset voltages are the same (0.7 V). The flow velocity obtained utilizing both EP and DEP produced a reabsorption rate of 50-58% depending on the voltage applied and dimensions considered which is close to 60% reabsorption rate of the normal human kidney PCT. In accordance with the outcomes produced, the di-electrophoresis technique proved to be more efficient in realizing bioreactor as compared to electrophoresis. The novelty of the present work lies in the creation of a simulation environment, rigorous analysis, and optimization of the bioreactor supported by compact mathematical model.
Double beamforming processing in a seismic prospecting context

ABSTRACTThe use of larger numbers of sensors is becoming more common at the large, continental scale for deep-structure imaging in seismology, and at a smaller scale with exploration geophysics objectives. Seismic arrays require array processing from which new types of observables contribute to a better understanding of the wave propagation complexity. From among these array processing techniques, this study focuses on a way to select and identify different phases between two source-receiver arrays based on the double beamforming (DBF) method. At the exploration geophysics scale, the goal is to identify and separate low-amplitude body waves from high-amplitude dispersive surface waves. A synthetic data set from a finite-difference time-domain simulation is first used to validate the array processing method. From directional information obtained with DBF, and due to the double-plane wave projection, it is demonstrated that surface and body waves can be extracted with a higher efficacy compared to classical.
Active energy control in civil structures

This study explores the use of a linear PMDC machine as a regenerative force actuator for the mitigation of earthquake disturbances in civil structures. Unlike previous studies of this kind, the control system developed is purely active, meaning no 'hybrid' control techniques are used, such as the combination of active force actuation and passive tuned mass dampers. Modeling methods for the machine as well as its associate drive electronics are briefly described. It is shown that for this purely active system, it is possible and feasible to develop regenerative excitation schemes which drive the machine primarily by absorbing power from the excited building. Such regenerative excitation makes it possible to isolate the actuator from the external power grid, which is necessary during earthquakes, where the quality, or even the mere availability of external power is questionable. Furthermore, results are presented which find the minimum reservoir of energy necessary to excite the machine during the beginning of the earthquake, and it is shown that the actuator local power supply will see a gain in energy across the duration of the disturbance. The control system design methods presented employ position feedback. Then, force limiting techniques are employed to regulate power flow in the machine. The effectiveness of this control design is evaluated on a 3-story building, and performance is briefly compared to that of semi-active control designs proposed elsewhere.