Current Generation Research Articles

Design of a novel multizone cooling system for performance improvement in proton exchange membrane fuel cell

Thermal management is critical to developing proton exchange membrane fuel cell systems, impacting their output performance, safety, and lifetime. Currently, studies on thermal management use single zone cooling technique to control the cell temperature, which leads to the non-uniform distribution of water inside the cell and reduces the cell’s output performance and life span. In this paper, a novel multizone cooling system is developed to optimise the thermal management of the cell, and the effect of multizone cooling technology on the cell is investigated under different operating parameters. The experimental results demonstrate that cell voltage and current density uniformity improved when the cell bottom temperature was high and the inlet temperature was low. The performance enhancement was significant as the back pressure and outlet temperature increased. Notably, the cell with multizone temperature control showed significantly reduced reverse current generation and improved current density uniformity. Compared to cells using single zone cooling technique at 60 °C, the voltage increased by 9.98 %, 12.07 %, and 15.98 % at current densities of 400, 800, and 1200 mA cm−2, respectively. Multizone cooling technology notably enhances current density uniformity, achieving a 40.93 % improvement at 400 mA cm−2.

Enhanced Electrochemical Performance of Tin Oxide Quantum Dots on Reduced Graphene Oxide under Light.

The study utilized a simple and cost-effective approach to improve the photoelectrochemical (PEC) water-splitting performance of various materials, including reduced graphene oxide (rGO), tin oxide nanostructures (SnO2), and rGO/SnO2 composites. The composites examined were rS15, containing 15 mg of rGO and 45 mg of SnO2, and rS5, with 5 mg of rGO and 50 mg of SnO2, tested in a sodium hydroxide (NaOH) electrolyte. Notably, the rS5 electrode showed a significant increase in PEC efficiency in 0.1 M NaOH, achieving a peak photocurrent density of 13.24 mA cm-2 under illumination, which was seven times higher than that of pristine rGO nanostructures. This enhancement was attributed to the synergistic effects of the heterostructure, which reduced resistance and minimized charge recombination, thereby maximizing the catalytic activity across the various electrochemical applications. Furthermore, the rS5 anode demonstrated improved Tafel parameters, indicating faster reaction kinetics and lower overpotential for efficient current generation. These results highlight the potential for optimizing nanostructures to significantly enhance PEC performance, paving the way for advancements in sustainable water-splitting technologies.

PoweREST: Statistical Power Estimation for Spatial Transcriptomics Experiments to Detect Differentially Expressed Genes Between Two Conditions.

Recent advancements in Spatial Transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost of current ST data generation techniques restricts its application in large-scale population studies. Consequently, there is a pressing need to maximize the use of available resources to achieve robust statistical power. One fundamental question in ST analysis is to detect differentially expressed genes (DEGs) among different conditions using ST data. Such DEG analysis is often performed but the associated power calculation is rarely discussed in the literature. To address this gap, we introduce, PoweREST (https://github.com/lanshui98/PoweREST), a power estimation tool designed to support power calculation of DEG detection with 10X Genomics Visium data. PoweREST enables power estimation both before any ST experiments or after preliminary data are collected, making it suitable for a wide variety of power analyses in ST studies. We also provide a user-friendly, program-free web application (https://lanshui.shinyapps.io/PoweREST/), allowing users to interactively calculate and visualize the study power along with relevant the parameters.

The relationship between pro-environmental behavior, subjective well-being, and environmental impact: a meta-analysis

Abstract A substantial change towards more pro-environmental behavior (PEB) is essential to reach the required reduction in greenhouse gas emissions and mitigate climate change. These behavior changes will have consequences on people’s daily lives and thus might affect their well-being. Previous research generally finds positive correlations between PEB and well-being. This meta-analysis explores whether the relationship between PEB and well-being depends on the environmental impact of the performed PEB. Overall, the paper finds a small but significant positive relation between PEB and well-being. When accounting for the environmental impact of the PEB, however, the positive relationship only remains for low-impact PEB. The meta-analysis does not provide any evidence that engaging in high-impact PEB relates to well-being. Consequently, these findings demonstrate that there is more ambiguity in the relationship between PEB and well-being than previously described in the literature and that the environmental impact of PEB matters when evaluating its relationship with well-being. These findings have important implications for policy-making trying to facilitate mitigation efforts that ultimately aim to balance the well-being of the current and future generations.

JuMonC: A RESTful tool for enabling monitoring and control of simulations at scale

As systems and simulations grow in size and complexity, it is challenging to maintain efficient use of resources and avoid failures. In this scenario, monitoring becomes even more important and mandatory. This paper describes and discusses the benefits of the advanced monitoring and control tool JuMonC, which runs under user control alongside HPC simulations and provides valuable metrics via REST-API. In addition, plugin extensibility allows JuMonC to go a step further and provide computational steering of the simulation itself. To demonstrate the benefits and usability of JuMonC for large-scale simulations, two use cases are described employing nekRS and ICON on JURECA-DC, a supercomputer located at the Jülich Supercomputing Centre (JSC). Furthermore, a large-scale use case with nekRS on JSC’s flagship system JUWELS Booster is described. Finally, the interplay between JuMonC and LLview (a standard monitoring tool for HPC systems) is presented using a simple and secure JuMonC-LLview plugin, which collects performance metrics and enables their analysis in LLview. Overall, the portability and usefulness of JuMonC, together with its low performance impact, make it an important application for both current and future generations of exascale HPC systems.

Jewish women dermatologists who escaped the perils of National Socialism: Triumph over adversity

The period of National Socialism (1933-1945), including the Holocaust and World War II, has had a profound impact on dermatology. We have identified Jewish women dermatologists who escaped the perils of National Socialism, document their struggles, and describe their contribution to medicine and dermatology. Medical, history, and media databases were searched. Relevant contributions in languages other than English were translated into English. Fourteen dermatologists were identified, and for seven, there was sufficient information to describe their lives in more detail: Helen Ollendorff-Curth (née Ollendorff) (1899-1982), Bertha Ottenstein (1891-1956), Sidonie Fürst (1891-1973), Marianne Bauer (née Jokl) (1885-1980), Hedwig Fischer (née Hoffmann) (1888-1983), Vera Shukhman (1900-1987) and Lili Farkas (1899–1992). The challenges that confronted the dermatologists were sizeable. Status as a woman, antisemitism, persecution in various forms during National Socialism, murder of family and dermatology colleagues, untimely death of family members in other ways, loss of jobs and status, the stress of relocation, and myriad obstacles in a newly adopted country were among hurdles that they faced; nevertheless, collectively, the seven dermatologists could make a range of contributions in clinical, academic, and administrative areas. The dermatologists displayed courage, tenacity, and determination and served as role models of resilience for current and future generations of women in the dermatology field.

A mobile-optimized convolutional neural network approach for real-time batik pattern recognition

This research focuses on preserving and sharing knowledge about Indonesian batik, a blend of art and technology symbolizing the nation's creativity. To address declining awareness of batik types, a mobile application is introduced for real-time recognition and classification of batik motifs. The goal is to maintain appreciation and understanding of this cultural heritage. Using the EfficientNet convolutional neural network (CNN) architecture, the study enhances model accuracy with effective scaling. A dataset of 1350 images representing 15 batik types supports robust model training and evaluation. Results demonstrate successful implementation, yielding an Android app capable of deep learning-based real-time recognition with an 83% accuracy rate. This innovation aims to empower users to identify and appreciate distinct batik types, ensuring cultural preservation for current and future generations.

LLMs: Their Past, Promise, and Problems

Transformer-based large language models are currently at the forefront of modern artificial intelligence. Their prominence followed from the seminal paper Attention is All You Need [1]. Vaswani and his colleagues suggested placing attention mechanisms within the encoder and decoder modules of autoencoders rather than using them to focus between these two modules. In this paper we present first the seminal insights of early AI that lead to deep learning. We then describe the mathematical tools necessary for understanding the current generation of LLMs and follow this with a brief description of the transformer architecture. We then provide examples of LLMs in action and conclude with some observations of their promise and problems.

Employee Happiness and Green Practices: A Case Study of Internal Corporate Social Responsibility

The concept of Corporate Social Responsibility (CSR) has arisen as a result of due to the increase in pollution and excessive exploitation of the Earth's resources, as well as the human resources caused by the activities of companies that seek to make profits at any cost. As resources have become increasingly limited and human performance has decreased due to burnout, and also because current generations move from one job to another if they consider that the organizational environment does not provide them a certain degree of comfort, companies have had to adapt certain policies to support both the environment and employees. Thus, the role of the current research is to identify those components of internal CSR that impact employee happiness, as well ase components of internal CSR that impact employee happiness and green practices. In this sense, by applying a questionnaire addressed to a number of 123 respondents whose answers were imported into Smart PLS, it was wanted to validate the hypotheses according to which the variables work-life balance and equal opportunities, adaptability to change, and occupational health and safety have a role in defining employee happiness, as well as green practices within companies.

Abatement of ionizing radiation for superconducting quantum devices

Ionizing radiation has been shown to reduce the performance of superconducting quantum circuits. In this report, we evaluate the expected contributions of different sources of ambient radioactivity for typical superconducting qubit experiment platforms. Our assessment of radioactivity inside a typical cryostat highlights the importance of selecting appropriate materials for the experiment components nearest to qubit devices, such as packaging and electrical interconnects. We present a shallow underground facility (30-meter water equivalent) to reduce the flux of cosmic rays and a lead shielded cryostat to abate the naturally occurring radiogenic gamma-ray flux in the laboratory environment. We predict that superconducting qubit devices operated in this facility could experience a reduced rate of correlated multi-qubit errors by a factor of approximately 20 relative to the rate in a typical above-ground, unshielded facility. Finally, we outline overall design improvements that would be required to further reduce the residual ionizing radiation rate, down to the limit of current generation direct detection dark matter experiments.

Long-term effect of biodegradable vs durable polymer everolimus-eluting stents on neoatherosclerosis in ST-segment elevation myocardial infarction: the CONNECT trial.

Neoatherosclerosis is a leading cause of late (>1 year) stent failure following drug-eluting stent implantation. The role of biodegradable (BP) versus durable polymer (DP) drug-eluting stents on long-term occurrence of neoatherosclerosis remains unclear. Superiority of biodegradable against durable polymer current generation thin-strut everolimus-eluting stent (EES) was tested by assessing the frequency of neoatherosclerosis 3 years after primary percutaneous coronary intervention (pPCI) among patients with ST-segment elevation myocardial infarction (STEMI). The randomized controlled, multicentre (Japan and Switzerland) CONNECT trial (NCT03440801) randomly (1:1) assigned 239 STEMI patients to pPCI with BP-EES or DP-EES. The primary endpoint was the frequency of neoatherosclerosis assessed by optical coherence tomography (OCT) at 3 years. Neoatherosclerosis was defined as fibroatheroma or fibrocalcific plaque or macrophage accumulation within the neointima. Among 239 STEMI patients randomized, 236 received pPCI with stent implantation (119 BP-EES; 117 DP-EES). A total of 178 patients (75%; 88 in the BP-EES group and 90 in the DP-EES group) underwent OCT assessment at 3 years. Neoatherosclerosis did not differ between the BP-EES (11.4%) and DP-EES (13.3%; odds ratio 0.83, 95% confidence interval 0.33-2.04, p=0.69). There were no differences in the frequency of fibroatheroma (BP-EES 9.1% vs DP-EES 11.1%, p=0.66) or macrophage accumulation (BP-EES 4.5% vs DP-EES 3.3%, p=0.68), and no fibrocalcific neoatherosclerosis was observed. Rates of target lesion failure did not differ between groups (BP-EES 5.9% vs DP-EES 6.0%, p=0.97). Use of BP-EES for primary PCI in patients presenting with STEMI was not superior to DP-EES regarding frequency of neoatherosclerosis at 3 years.

Analysis Of Microbial and Chemistry Contamination Thai Tea Drink in Junior High School

Thai Tea drink is the current favorite drink of the current millennial generation. Thai Tea beverage products are usually sold in places that are easily accessible to consumers, such as on the side of the highway. This thing makes Thai Tea beverage products have potential to become a medium for foreign object to enter the body if they are not processed properly. This study aims to determine the safety of Thai Tea beverage products that are sold around junior high schools in Central Bogor District. This study used seven samples taken from 7 junior high schools in seven different sub-districts and used a purposive sampling method. Product analysis was carried out twice, including testing the microbial contamination levels of Total Plate Number, Coliforms, Escherichia coli, heavy metal lead chemical contamination and sucrose content in Thai Tea drinks. Research is also supported by field observations and interviews. The research showed that all samples of Thai Tea drinks contained TPC microbial contamination that exceeded the standard, twelve repetition were contaminated with coliform bacteria and Escherichia coli, all repetition were not detected by heavy metal lead contamination and the sucrose content of all repetition did not exceed the maximum daily sugar intake limit.

MODERNIDADE LÍQUIDA E AS DIFERENTES GERAÇÕES

The text discusses the challenges faced by education in the current era, highlighting the individualized search for knowledge through technological resources. Under the influence of individualism and social regression, technology gains prominence in educational discussions. Access to information via the internet is considered a form of democratization, but the mere availability of information does not constitute education. The school is asked to position itself as a technology guide, recognizing the need for innovation to meet the demands of students. The search for autonomy, a crucial path to liberation, is intrinsically linked to the concept of humanizing education. This approach highlights the importance of dialogue as an essential foundation for acquiring knowledge. Bibliographic research covers secondary sources, seeking new approaches. The objective is to analyze Bauman’s “Liquid Modernity” and the perspectives of different generations, exploring how education should adapt to modernity and the characteristics of the current generation, and how institutions and teachers should respond to this reality.

Improved Harmonic Mitigation and Power Injection Technique for Solar-fed DG System Using GA and PSO

This paper deals with Distributed Generation (DG) system requiring power quality features such as current harmonics, reactive power compensation, and power factor improvement in grid tied operation. The motivation is to combine DG system with the capabilities of shunt active filter to perform real power injection, current harmonics mitigation and power factor improvement. The control algorithm employed in this setup utilizes a reference current generator based on p-q theory together with a pulse width modulation controller for switching pulse generation. The control strategy utilizes PI controller with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for finding optimal PI controller parameters. The effectiveness of the proposed method is verified using MATLAB/Simulink and experimental model developed for 3kWp inverter. The PI-PSO controller injects 0.588kW active power into the grid results in sharing 54% of load power demand and the current harmonics is reduced from 23.70% to 1.63%. The obtained results demonstrate that the grid tied inverter maintains harmonic standards in accordance with the IEEE-519 standard while injecting maximum possible active power to the line.

Research on External Manifestation of Character Existentialism in Chinese Animation in the New Media Era - Taking The Outcast, Killer Seven and Incarnation as Examples

Existentialism, after over a century of development, has evolved from a philosophical idea into a way of life. In recent years, a group known as "refined egoists" has emerged in both reality and animated works. The appearance of these extreme existentialists who ignore social responsibility reveals that in this era of transition between old and new ideologies, existentialist thought has awakened in people's value systems. This article intends to analyze the external manifestations of character’s existentialism in animation works to summarize the reflections of objective phenomena in reality and to discuss the contradictions and problems that the current young generation are facing between themselves and society. This article uses qualitative research methods to analyze representative characters from three animated series, The Outcast, Killer Seven, and Incarnation, and uses a thematic analysis method that combines existentialism theory to summarize the external manifestations of characters in terms of their internal conflicts, conflicts between individuals, and conflicts between individuals and society. These manifestations include the denial of determinism, affirmation of subjectivity under relative justice, identification with minority groups, denial of authority, and autonomous choice of values. Young generation people are confronted with unprecedentedly great uncertainty and insecurity brought about by the freedom of choice, as well as the social reality of the gradual awakening of existentialist consciousness in contemporary society.

Narrativizing the Nexus between Climate Crisis and Immigration in Amitav Ghosh's Gun Island: An Ecocritical Exploration

Eco-criticism is a branch of literary scholarship that finds tangible connections between the environment and literature. The environmental problem is one of the most prominent issues of current generation. Climate crisis stands as a sole factor in the environment in view of ecological imbalance. This is an ever increasingly presence in our daily lives. prominent causes of climate change are an increase of green house gasses, deforestation to develop human settlements, excessive use of fossil fuels and so on. Decline in agricultural productivity is another impact of climate change. Thus, this is widely recognized as a contributing and exacerbating factor in immigration. The climate crisis, migration and refugees' acute situation have allegedly lost security and stability of humans and non-humans. The paper attempts to look how Amitav Ghosh has put his best endeavors to discover the inordinate use of nature by human beings. The materialistic and anthropocentric attitudes of human beings undergo extreme climate crisis and the displacement of livings. Now, the major environmental issues become the ethical concerns in the eco pages of literary writers to highlight the problems of ecosystem. The novel "Gun Island" deals with the issue of climate crisis and immigration. Planetary environmentalism identifies the planetary crisis caused by climate change. It seeks environmental justice both for humans and nonhumans across the planet. The whole planet goes beyond geographical boundary because of threatening of climate change. Ghosh in this novel wants to procure awareness among the readers regarding the impending calamities of the global environment and thus a warning to mend exploitative attitudes towards our Mother Nature.

Design and Implementation of Bridgeless Power Factor Corrector with Low Static Losses

Research and development of power factor corrector (PFC) for AC/DC converters of single-phase AC power supply network are discussed within this article. Two-channel bridgeless PFC is proposed in this paper. The proposed converter allows us to lower current DC component generation in the power network and to reduce static and dynamic losses of semiconductor devices. The suggested solution characteristic features are the absence of a diode bridge while using two identical converters operating in different power network voltage half periods. Due to cumulative chokes in each converter, the function setting the consumption current sinusoidal form is realized with the ability of wide-range output voltage regulation. A number of Simulink-models have been developed in order to study operating modes and to test control algorithms of the proposed bridgeless PFC. The input current harmonic content, efficiency coefficient, passive elements’ electrical parameters, and output voltage pulsation coefficient of the proposed bridgeless PFC were researched by Simulink-models. The results obtained show the efficiency of the proposed solutions regarding PFC. The THD value does not exceed 1.3% in steady state mode and is not over 4% during the voltage stabilization process; the minimal value of the output voltage pulsation coefficient is 3.1%. The suggested solutions can be applied in accumulator batteries’ charging sets and DC motors’ reduced-current start.

Interactive dual-stream contrastive learning for radiology report generation

Radiology report generation automates diagnostic narrative synthesis from medical imaging data. Current report generation methods primarily employ knowledge graphs for image enhancement, neglecting the interpretability and guiding function of the knowledge graphs themselves. Additionally, few approaches leverage the stable modal alignment information from multimodal pre-trained models to facilitate the generation of radiology reports. We propose the Terms-Guided Radiology Report Generation (TGR), a simple and practical model for generating reports guided primarily by anatomical terms. Specifically, we utilize a dual-stream visual feature extraction module comprised of detail extraction module and a frozen multimodal pre-trained model to separately extract visual detail features and semantic features. Furthermore, a Visual Enhancement Module (VEM) is proposed to further enrich the visual features, thereby facilitating the generation of a list of anatomical terms. We integrate anatomical terms with image features and proceed to engage contrastive learning with frozen text embeddings, utilizing the stable feature space from these embeddings to boost modal alignment capabilities further. Our model incorporates the capability for manual input, enabling it to generate a list of organs for specifically focused abnormal areas or to produce more accurate single-sentence descriptions based on selected anatomical terms. Comprehensive experiments demonstrate the effectiveness of our method in report generation tasks, our TGR-S model reduces training parameters by 38.9% while performing comparably to current state-of-the-art models, and our TGR-B model exceeds the best baseline models across multiple metrics.

Explicit-implicit priori knowledge-based diffusion model for generative medical image segmentation

The diffusion probabilistic model (DPM) has achieved unparalleled results in current image generation tasks, and some recent research works employed it in several computer vision tasks, such as image super-resolution, object detection, etc. Thanks to DPM's superior ability to generate fine-grained details, these research efforts have yielded significant successes. In this paper, we propose a new DPM-based generative medical image segmentation method, named EIDiffuSeg. Specifically, we first construct an explicit-implicit aggregation priori knowledge with directional supervision ability by mining the semantic distribution pattern in the frequency and spatial domains. Then, the explicit-implicit aggregation priori knowledge is integrated into the different encoding stages of the denoising backbone network using a novel unsupervised priori knowledge induction strategy, which can guide the model to generate a segmentation mask of the region of interest directionally from a random inference process. We evaluate our method on three medical image segmentation benchmark datasets with different modalities and achieve the best segmentation results compared to state-of-the-art methods. Especially, compared to several current diffusion-based image segmentation methods, we achieved a 9% Dice improvement in the polyp segmentation benchmark. Our code will be available at https://github.com/Notmezhan/EIDiffuSeg.

Giant spin seebeck effect with highly polarized spin current generation and piezoelectricity in flexible V2SeTeO altermagnet at room temperature

Studies on altermagnetic materials are attracting extensive research efforts owing to their directional dependent spin split band structure. However, it is rare to find reports on the possibility of multifunctionality in altermagnetic systems. Here, we explore the spin dependent transport properties and piezoelectricity of two-dimensional V2SeTeO altermagnet. The V2SeTeO system has a direct band gap of 0.32 eV with a Neel temperature of 510 K. We find a giant effective Seebeck coefficient of 0.64 mV/K at 300 K. This is several times larger than that found in bulk and other two-dimensional materials. Moreover, the effective Seebeck effect is entirely determined by either only spin-up or spin-down component. This feature implies that we can generate highly spin polarized current by temperature gradient at room temperature. We attribute this pure spin current generation to the directional dependent spin split band structure. Along with the spin dependent transport properties, we also find that the Janus V2SeTeO altermagnet shows outstanding flexibility and piezoelectric response with out-of-plane piezoelectric coefficient of d31=0.245pm/V. Overall, we propose that the V2SeTeO altermagnet system exhibits multifunctional physical properties at room temperature, and this can be utilized for potential spintronics and flexible piezoelectric applications simultaneously.