Current State Research Articles

Authority as (qualified) indubitability

ABSTRACT Self-ascriptions of one's current mental states often seem authoritative. It is sometimes thought that the authority of such self-ascriptions is, in part, a matter of their indubitability. However, they do not seem to be universally indubitable. How, then, should claims about self-ascriptive indubitability be qualified? Here I consider several such qualifications from the literature. Finding many of them wanting, I nevertheless settle on multiple specifications of the thesis that self-ascriptions are authoritatively indubitable. Some of these specifications concern how other agents ought to treat one's self-ascriptions, while a final specification concerns how one is entitled to respond to others’ doubts about one's self-ascriptions. The result is a pluralistic view of self-ascriptive indubitability: different types of mental state self-ascriptions are indubitable in different ways, and for different people.

Integrated on-board electric vehicle battery charger with multifunctional features

ABSTRACT Because of the continuous demand for reliable, efficient, small-size, light weighted, and low-cost Electric Vehicle (EV) battery charging systems, an integrated on-board charger is proposed with a high-power propulsion motor drive. It utilises stator windings of motor, the 6-leg Voltage Source Converter (VSC), DC-DC converter, and feedback sensors to facilitate vehicular battery charging. With this system, soft switching technique based bidirectional isolated DC-DC converter is proposed that offers the advantage of simple circuitry design due to no usage of extra passive or active components. This paper presents mathematical modelling, analysis, and controller design of this proposed configuration under various operating modes. The complete system is developed in Sim Power system toolbox of MATLAB software and tested in real-time environment. The performance investigations of proposed system are carried out for three operating modes like Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G), Vehicle-to-Vehicle (V2V) under Constant Current (CC) and Constant Voltage (CV) battery charging modes. Furthermore, the investigations ensure the system’s excellent efficiency, less THD, and nearly unity power factor operation under all operating conditions.

Research on SOP Estimation Based on SOC Constraints under Static Operating Conditions

In a battery management system (BMS), accurate estimation of system operating power (SOP) is essential to ensure battery performance and extend service life. In this paper, an SOP estimation method based on open circuit voltage (OCV), state of charge (SOC) and battery current is studied. By analyzing the battery data under dynamic stress test (DST) conditions, the estimated value of continuous peak charge and discharge current is calculated, and the corresponding continuous peak charge and discharge power is estimated accordingly. Comparing the estimated charging and discharging power with the experimental value, the results show that the new algorithm can significantly improve the estimation accuracy of SOP. It not only improves the accuracy of SOP estimates, but also helps to optimize BMS, thereby improving the overall performance and service life of the power battery.

Applying dynamic systems theory and complexity theory methods in psychotherapy research: A systematic literature review

Objective Dynamic systems theory and complexity theory (DST/CT) is a framework explaining how complex systems change and adapt over time. In psychotherapy, DST/CT can be used to understand how a person's mental and emotional state changes during therapy incorporating higher levels of complexity. This study aimed to systematically review the variability of DST/CT methods applied in psychotherapy research. Methods A primary studies search was conducted in the EBSCO and Web of Knowledge databases, extracting information about the analyzed DST/CT phenomena, employed mathematical methods to investigate these phenomena, descriptions of specified dynamic models, psychotherapy phenomena, and other information regarding studies with empirical data (e.g., measurement granularity). Results After screening 38,216 abstracts and 4,194 full texts, N = 41 studies published from 1990 to 2021 were identified. The employed methods typically included measures of dynamic complexity or chaoticity. Computational and simulation studies most often employed first-order ordinary differential equations and typically focused on describing the time evolution of client-therapist dyadic influences. Eligible studies with empirical data were usually based on case studies and focused on data with high time intensity of within-session dynamics. Conclusion This review provides a descriptive synthesis of the current state of the proliferation of DST/CT methods in the psychotherapy research field.

Numerical simulation of local scour around an inclined monopile in steady current

Local scour around the underwater supports of constructions would reduce the embedment depth and bearing capacity of support structures, seriously threatening the safety of the structures. Most existing investigations focused on the local scour of a vertical pile. However, in practical engineering, inclined piles are widely applied in underwater foundation structures to withstand lateral loads. The pile inclination can result in flow field alteration around the pile, thereby affecting the development of local scour. Consequently, a threedimensional numerical model of local scour around an inclined pile under steady current is established using the open-source CFD package OpenFOAM, in which the hydrodynamics are solved based on the Reynolds-averaged Navier-Stokes (RANS) equations together with k – ω SST turbulence closure in this model. It is then coupled with both bed load and suspended load transport descriptions, which drive the resultant morphology of the bed. The numerical model is verified by comparing it with the existing laboratory experiment. Discussions are carried out on the effects of inclination angles on the flow field alteration and the local scour depth variation.

Current State and Future Perspective of Diabetic Wound Healing Treatment: Present Evidence from Clinical Trials.

Diabetes is a chronic metabolic condition that is becoming more common and is characterised by sustained hyperglycaemia and long-term health effects. Diabetes-related wounds often heal slowly and are more susceptible to infection because of hyperglycaemia in the wound beds. The diabetic lesion becomes harder to heal after planktonic bacterial cells form biofilms. A potential approach is the creation of hydrogels with many functions. High priority is given to a variety of processes, such as antimicrobial, pro-angiogenesis, and general pro-healing. Diabetes problems include diabetic amputations or chronic wounds (DM). Chronic diabetes wounds that do not heal are often caused by low oxygen levels, increased reactive oxygen species, and impaired vascularization. Several types of hydrogels have been developed to get rid of contamination by pathogens; these hydrogels help to clean up the infection, reduce wound inflammation, and avoid necrosis. This review paper will focus on the most recent improvements and breakthroughs in antibacterial hydrogels for treating chronic wounds in people with diabetes. Prominent and significant side effects of diabetes mellitus include foot ulcers. Antioxidants, along with oxidative stress, are essential to promote the healing of diabetic wounds. Some of the problems that can come from a foot ulcer are neuropathic diabetes, ischemia, infection, inadequate glucose control, poor nutrition, also very high morbidity. Given the worrying rise in diabetes and, by extension, diabetic wounds, future treatments must focus on the rapid healing of diabetic wounds.

Transcriptomics of intracranial aneurysms: current state and opportunities in flow diversion.

Over the last 2 decades, the field of transcriptomics has emerged as a major subdiscipline in biology. Transcriptomic techniques have been used by many groups over this time to better understand intracranial aneurysm development, rupture, and treatment. However, only a few studies have applied transcriptomics to understand the mechanisms behind flow diversion (FD) specifically, despite its increasing importance in the neurointerventional armamentarium. FD is an increasingly safe and effective treatment option for intracranial aneurysms. However, the clinical understanding and use of FD has far outpaced the understanding of the underlying mechanisms. To make FD more predictable, clinically efficacious, and safe, it is important to understand the biological mechanisms at play that lead to successful and unsuccessful FD. In this review, the authors focus on the current understanding of FD biology, the recent advances in transcriptomics, and what future studies could be performed to deepen the understanding of FD. They propose the new concept of the FD microenvironment to be studied, which may unlock a deeper biological understanding. This review provides the background for prospective studies into the development of targeted aneurysm therapy, whether by modified devices or by medical adjuncts.

Hybrid Residual Multiexpert Reinforcement Learning for Spatial Scheduling of High-Density Parking Lots.

Industries, such as manufacturing, are accelerating their embrace of the metaverse to achieve higher productivity, especially in complex industrial scheduling. In view of the growing parking challenges in large cities, high-density vehicle spatial scheduling is one of the potential solutions. Stack-based parking lots utilize parking robots to densely park vehicles in the vertical stacks like container stacking, which greatly reduces the aisle area in the parking lot, but requires complex scheduling algorithms to park and take out the vehicles. The existing high-density parking (HDP) scheduling algorithms are mainly heuristic methods, which only contain simple logic and are difficult to utilize information effectively. We propose a hybrid residual multiexpert (HIRE) reinforcement learning (RL) approach, a method for interactive learning in the digital industrial metaverse, which efficiently solves the HDP batch space scheduling problem. In our proposed framework, each heuristic scheduling method is considered as an expert. The neural network trained by RL assigns the expert strategy according to the current parking lot state. Furthermore, to avoid being limited by heuristic expert performance, the proposed hierarchical network framework also sets up a residual output channel. Experiments show that our proposed algorithm outperforms various advanced heuristic methods and the end-to-end RL method in the number of vehicle maneuvers, and has good robustness to the parking lot size and the estimation accuracy of vehicle exit time. We believe that the proposed HIRE RL method can be effectively and conveniently applied to practical application scenarios, which can be regarded as a key step for RL to enter the practical application stage of the industrial metaverse.

Demonstration of a violet-distributed feedback laser with fairly small temperature dependence in current-light characteristics

We have developed a GaN-based distributed feedback laser diode (DFB-LD) with the detuning of +5 nm to obtain a smaller temperature dependence of the threshold current. We found that the current-light characteristics almost overlapped up to 300 mW between 25 °C and 80 °C. The estimated characteristic temperature is about 2550 K. These indicate that our DFB-LD is promising for applications that require small temperature dependence in the output power and oscillation wavelength at constant operation current without precise temperature control.

Recent advances in the study of epitopes, allergens and immunologic cross-reactivity of edible mango

Mango (Mangifera indica L.) is a tropical fruit that is widely consumed as both fresh fruits and processed products around the world. The high incidence of mango allergy, on the other hand, has sparked widespread concern. Therefore, a summary and analysis of the current status and issues in mango allergen research can guide in-depth study on the mechanism of mango allergy and reveal effective desensitization methods. We described the incidence of fruit allergy, as well as the mechanism and clinical symptoms of mango allergy, in this review. We also looked into the structural properties of mango allergens, the effect of processing methods on mango allergens, prediction methods for mango allergen epitopes, and the current state of research on mango cross-reactive allergens and preventive measures. Finally, the research directions and ideas for the future are proposed and discussed.

The Impact of Adversarial Attacks on Federated Learning: A Survey.

Federated learning (FL) has emerged as a powerful machine learning technique that enables the development of models from decentralized data sources. However, the decentralized nature of FL makes it vulnerable to adversarial attacks. In this survey, we provide a comprehensive overview of the impact of malicious attacks on FL by covering various aspects such as attack budget, visibility, and generalizability, among others. Previous surveys have primarily focused on the multiple types of attacks and defenses but failed to consider the impact of these attacks in terms of their budget, visibility, and generalizability. This survey aims to fill this gap by providing a comprehensive understanding of the attacks' effect by identifying FL attacks with low budgets, low visibility, and high impact. Additionally, we address the recent advancements in the field of adversarial defenses in FL and highlight the challenges in securing FL. The contribution of this survey is threefold: first, it provides a comprehensive and up-to-date overview of the current state of FL attacks and defenses. Second, it highlights the critical importance of considering the impact, budget, and visibility of FL attacks. Finally, we provide ten case studies and potential future directions towards improving the security and privacy of FL systems.

Technology integration and teachers’ competency in the development of 21st-century learning in EFL classroom

This study examined the role of technology integration and teachers' professional competence in developing 21st-century learning. Present studies show a significant gap between technology integration and teachers’ competency in developing 21st-century learning. This study highlights the pivotal roles of technology integration and teacher competence in modern education. In an era where technology has transformed teaching and learning, understanding the synergy between these two factors is crucial for educational advancements. The study employs a descriptive quantitative approach. It seeks to understand the current state of technology integration and teacher competence by collecting data from in-service teachers within the English teacher's forum. The data collection methods encompass questionnaires and interviews to gain comprehensive insights into the subject matter. The research design of this study primarily relies on a descriptive approach, which involves the systematic collection and analysis of data to describe and understand the existing situation. The data-gathering process, through questionnaires and interviews, ensures a comprehensive exploration of the research questions. The results show that technology integration and teacher competency significantly influence the development of 21st-century learning.

Current State of Application of Formal Thought Disorder Screening Methods in First-Degree Relatives of Patients With Schizophrenia: A Narrative Review

Abstract: Historically, formal thought disorder (FTD) has been considered one of the distinctive key symptoms of schizophrenia and is still regarded as an important early warning sign and a marker of illness severity with solid predictive value. Recent studies are able to found that the presence of FTD is predictive of the subsequent diagnosis of schizophrenia and often precedes the frank clinical picture by several months. Much effort has been put into developing scales that can reliably detect FTD and can be readily applied in routine clinical practice. This narrative review investigated the use of FTD as a screening tool to assess risk in first-degree relatives of patients with schizophrenia. The results show that the use of these scales in firstdegree relatives of schizophrenic individuals during clinical contact and counseling is still an exception, despite their uniquely heightened vulnerability profile. To our knowledge, this is the first time that the application of FTD screening methods in first-degree relatives of schizophrenic individuals has been reviewed in a structured way.

Epigenetics of Fear, Anxiety and Stress - Focus on Histone Modifications.

Fear-, anxiety- and stress-related disorders are among the most frequent mental disorders. Given substantial rates of insufficient treatment response and often a chronic course, a better understanding of the pathomechanisms of fear-, anxiety- and stress-related disorders is urgently warranted. Epigenetic mechanisms such as histone modifications - positioned at the interface between the biological and the environmental level in the complex pathogenesis of mental disorders - might be highly informative in this context. The current state of knowledge on histone modifications, chromatin-related pharmacology and animal models modified for genes involved in the histone-related epigenetic machinery will be reviewed with respect to fear-, anxiety- and stress-related states. Relevant studies, published until 30th June 2022, were identified using a multi-step systematic literature search of the Pub- Med and Web of Science databases. Animal studies point towards histone modifications (e.g., H3K4me3, H3K9me1/2/3, H3K27me2/3, H3K9ac, H3K14ac and H4K5ac) to be dynamically and mostly brain region-, task- and time-dependently altered on a genome-wide level or gene-specifically (e.g., Bdnf) in models of fear conditioning, retrieval and extinction, acute and (sub-)chronic stress. Singular and underpowered studies on histone modifications in human fear-, anxiety- or stress-related phenotypes are currently restricted to the phenotype of PTSD. Provided consistent validation in human phenotypes, epigenetic biomarkers might ultimately inform indicated preventive interventions as well as personalized treatment approaches, and could inspire future innovative pharmacological treatment options targeting the epigenetic machinery improving treatment response in fear-, anxiety- and stressrelated disorders.

Agricultural and industrial wastes applied on the high performance energy storage devices

Driven by population growth, the destruction of the environment and the energy demand continue to increase dramatically. This study uses garlic skin and carbon fiber from agricultural and industrial wastes to prepare energy storage devices. Carbon quantum dots (CQDs) were obtained from garlic skin using high-temperature pyrolysis. The specific capacitance of the gel electrolyte could be effectively increased with a small number of CQDs doping. A methylcellulose-based carbon fiber-electrode was prepared by grinding and depositing the industrial recycled carbon fiber onto a biodegradable methylcellulose substrate. The methylcellulose-based recycled carbon fiber-electrode has the highest specific capacitance, energy density, and power density, which are 155 F/g, 10 Wh/kg, and 4047 W/kg, respectively, at a scan rate of 0.02 V/s, and demonstrates excellent performance, such like high specific capacitance, low internal resistance as well as rapid charge and discharge characteristics, which may have potential to replace the expensive carbon nanotubes and graphenes. The electrodes were made from recycled carbon fiber, the gel electrolyte with garlic CQDs, and a separator assembled into a sandwich structure to form supercapacitors. The capacity retention rate of the supercapacitor still retained 96 % of its initial value after 2000 cycles of charge and discharge testing at a constant current of 0.20 mA. This demonstrates the supercapacitor prepared in this study with competitive power density, energy density, high rate capability, and excellent life cycle stability by combining the garlic skin and carbon fiber from agricultural and industrial wastes, highlighting the enormous potential of agricultural and industrial wastes for energy storage applications.

Single-Phase Robust Charger with High Power Quality for Electric Vehicle Application

The widespread use of electric vehicles (EVs) necessitates the development of a robust charging infrastructure. The goal of this research paper is to create a high-quality, single-phase charger for electric cars. The purpose of this design is to provide a charger that is both fast and efficient but also protects against power quality problems including harmonics, power factor correction, and voltage variations. A single-phase–single-stage improved power quality EV charger for small and medium power applications has been designed and simulated. A single DC-DC converter is utilized for constant charging and improved power quality operation. The charger presented exhibits improved power quality as sinusoidal current is drawn from the utility grid supply with the total harmonic distortion (THD) in compliance with the IEEE 519 and IEC 61000-3-2 standards. In order to charge the battery of an electric vehicle, most two-stage converters first use a boost converter for power factor correction (PFC), and then they use a DC-DC converter that can accept any input voltage. These two-stage conversions are inefficient and use more parts than necessary. This work proposes a PFC converter based on a single-stage switching inductor Cuk converter, which has the advantages of high step-down gain, low current stress, high efficiency, and a small number of components. The suggested converter’s operational analysis and design equations are performed in continuous current mode. The proposed converter is the subject of extensive mathematical modelling, analysis, simulation, and experimentation presented in this study. With both constant voltage (CV) and constant current (CC) loads, the proposed converter’s performance is analysed with regard to power quality indices like voltage total harmonic distortion (THD), current THD, and total power factor. Additionally, in CV mode and CC mode, the suggested converter’s dynamic performance with battery charging is evaluated in relation to the extensive supply changes. The developed charger presents a reliable and efficient solution for EV charging, fostering the transition to a cleaner and more sustainable transportation system.

Current state of knowledge and theories on second language reading

There is a thorny controversy regarding defining second language (L2) reading based on the required levels of interacting with the decoded texts and including theories that could prevent or facilitate the L2 process. This research attempts to fill the gap through providing a comprehensive analysis to the current state of knowledge and theories on second language reading; schema theory, orthographic depth hypothesis, socio-cultural theory, as well as influence from prior educational experiences, the concept of common underlying proficiency, and cross-language interference. Understanding such second language reading-related theories and hypotheses could enhance redirecting the attention to more practicality and reliability in the field as well as justifying insufficient learning outcomes of second language reading; dedicated particularly to Saudi EFL learners.

Mechanical and micro-structural studies of pulsed and constant current TIG weldments of super duplex stainless steels and Austenitic stainless steels

Abstract In the present research work, the influence of heat input rates on microstructures, hot tensile properties, and weld surface hardness number of Super Duplex Stainless Steel 2507 super duplex steels and austenitic steels 316L plates were investigated. Pulsed current and constant current modes were used in Tungsten Inert Gas (TIG) welding to join the dissimilar metals using ER2205 as filler. Microstructural studies were revealed at different zones of pulsed and constant current TIG weldments using optical microscopy. The tensile test was conducted at two different temperature conditions (i.e., 27 and 350°C) to investigate the strength of dissimilar weldments. Hardness measurements were made on the weld surface along the transverse direction using Vicker’s hardness tester. The microstructures revealed the formation of inter-granular austenite at the fusion zone with grain boundaries with austenite structures. Due to the constant heat input, a significant microstructural development with high austenite fractions was observed in constant current (CC)-TIG weldment. In comparison to CC-TIG weldments (UTS at 27°C = 600 MPa UTS at 350°C = 456 MPa), higher tensile characteristics were noted in Pulsed Current (PC)-TIG weldments (UTS at 27°C = 695 MPa UTS at 350°C = 475 MPa). The UTS of PC-TIG weldment is improved by 15.8% when compared to CC-TIG weldment due to the controlled heat input rates. PC-TIG weldments exhibited improved hardness numbers in various zones with smaller HAZ widths than CC-TIG weldments.

An improved model predictive control for linear induction machine drive-based split-source inverters

The Split Source Inverter (SSI) is a single-stage DC-AC converter topology widely recognized for its beneficial features compared to the Z-source inverter. These advantages include a reduced number of components, a constant input current, and minimized losses. This study aims to extensively investigate and analyze the operation of a 3 kW Linear Induction Motor (LIM) using SSI through comprehensive simulations. The suggested control approach, employing finite control-model predictive thrust control (FC-MPTC), exhibits remarkable dynamic behavior and achieves a fast transient response without necessitating modifications to the control loop. Moreover, the proposed method allows for the manipulation of multiple variables by utilizing a single cost function, eliminating the need for lookup tables. The efficacy of the proposed control method is validated through comprehensive simulations and experimental tests, which exhibit accurate reference tracking speed and superior dynamic performance in regulating the thrust and primary flux. The results also showed that the proposed method had lower undulations of 5.8% than the traditional method. The proposed approach outperforms the DTC-SVM method under varying load and speed conditions by delivering remarkable accuracy and improved control characteristics.

Performance enhancement for direct borohydride fuel cells through ternary Ru–Co–B oxide catalyst

Dielectric barrier discharge (DBD) plasma is used to prepare ternary heterostructured Ru–Co–B oxide catalyst with considerable RuO2/CoO/B20H26O interface and oxygen vacancy (Ov) for enhanced borohydride oxidation reaction. the Ru–Co–B catalyst displayed remarkable electrocatalytic activity and long-term stability Due to the difference in energy band structure at the interface where the charge distribution is not homogeneous, the heterogeneous structure will spontaneously generate a built-in electric field which prompts the interfacial charge transfer. The production of Ov increases its active site and promotes its catalytic activity. While it is used in membrane-less direct borohydride fuel cells (DBFCs), it showed a peak power density of 206 mW cm−2 at room temperature and a remarkable stability of 270 h at a constant current of 20 mA that is superior to commercial Pt/C.