bluuebunny/crossref_metadata_2025 huggingface dataset:
Residents and Fellows of US Medical Residencies and Fellowships Strongly Prefer In-Person to Virtual Conference Format
Authors: Glattke Kaycee , Tummala Sailesh V. , Weldon Edward , Bingham Joshua
Published: April 2024

Introduction:

Medical conferences are an integral aspect of medical education as they allow attendees to stay up to date with recent advancements in medicine, to develop presentation and communication skills, and to network and establish connections with professionals in their field of interest. But, when the coronavirus disease 2019 (COVID-19) pandemic was declared in March 2020, face-to-face medical conferences were suspended, and conference organizers began shifting their meetings to virtual platforms. These new virtual conferences afforded medical residents and fellows the unique opportunity to attend conferences from the comfort of their own home or workplace; however, the virtual meeting platforms did not provide attendees with the same networking experiences as in-person conferences. Since the end of the COVID-19 public health emergency, medical conferences are now faced with the question of whether they should remain virtual, shift back to in-person meetings, or develop a hybrid model of both options. Thus, the purpose of this study was to analyze medical resident and fellow sentiments and preferences by comparing virtual and in-person conference formats.

Methods:

A voluntary electronic survey was distributed to medical residents and fellows across the United States through their program coordinators and directors.

Results:

The main findings of this study suggest that medical residents and fellows largely prefer in-person conferences (85%) as compared to a virtual format because of the networking opportunities afforded to them along with the development of camaraderie with their peers. The findings in this study suggest that the largest benefit in attending a virtual conference is the flexibility to attend from any location (79% important or very important), which offered convenience, flexibility, and comfort to participants (n = 100).

Conclusion:

These results support our hypothesis that despite the convenience and portability afforded by attending conferences virtually, medical residents and fellows still ultimately prefer to attend conferences in person. Overall, the findings in this study are of relevance to conference organizers in understanding the driving forces behind attendance and should be considered in determining meeting format.
Biogeography and Paleogeography of Taxonomic Diversity of Coniacian–Santonian Dinocysts of the Northern Hemisphere
Authors: Lebedeva N.K.
Published: April 2024

—Dinocyst assemblages are subjected to taxonomic typification based on a qualitative and quantitative assessment of their generic composition for the Northern Hemisphere during the Coniacian–Santonian time in order to identify correlation taxa. The typification is carried out using a cluster analysis according to the Jacquard calculation model (BioDiversity Professional, 1997). Three types of dinocyst assemblages have been identified in the Coniacian. As compared to the Turonian, the relatively cold-water West Siberian basin is characterized by a decrease in the number of cosmopolitan taxa and an increase in species endemism. The only taxa identified at present are those allowing for intrabasin correlations. Three types of dinocyst assemblages have also been established for the Santonian. Free interbasin connections in the Northern Hemisphere contribute to the equalization of the generic composition between the three identified types and to the identification of characteristic taxa that allow for interregional correlation.
The Green Energy Conundrums
Authors: Earhart James W , Neblett Stuart
Published: April 2024

There is a big push in the western world to "de-carbonize." Such erudite publications as The Economist and academics as Bent Flvbjerg (Oxford, author of How Big things Get Done.) and Richard Muller (UC, Berkeley, physicist and Author of Physics for Future Presidents) are convinced that such is necessary. Solar, wind, and possibly nuclear electricity appear to be the most feasible green/renewable solutions to the problem. The serious problems with the proposed solutions are the conundrums.

Renewable power is inherently sporadic: the wind does not blow consistently, solar power is unavailable at night, and hydropower electricity is seasonal. Also, renewable power is not always connected to the market requiring it at the time of generation. Therefore, there must be some means of storing electricity for when these sources are not available or are fully committed.

Pump storage, or variations thereon, are a hot topic among renewable energy advocates-as demonstrated by a report in the April 25, 2022 edition of the New Yorker magazine (Matthew Hutson, 2022).
Qing-Re-Yi-Liu decoction suppresses the malignant behaviors of breast cancer cells by attenuating the MnSOD/CaMKII/AMPK signaling and Warburg effect
Authors: 张 哲 , zhao xin , sun lian , wang jun , du jing , zhang ying , Yuan ying
Published: April 2024

Background
The Qing-Re-Yi-Liu decoction (QRYLD) is a clinical effective prescription for the treatment of breast cancer due to its activity of heat clearing and detoxification. Our preliminary studies have found that QRYLD can interfere with the Warburg effect of breast cancer cells, inhibiting the proliferation of breast cancer MCF-7 cells.The chemical components and molecular mechanisms underlying the actions of QRYLD in regulating the Warburg effect in breast cancer cells are still unclear.
Methods
The bioactive components of QRYLD aqueous extracts were detected by HPLC. The biological processes and signaling pathways in MCF-7 cells of QRYLD targets were measured with transcriptome analysis. The effect of QRYLD on the malignant behaviors of MCF-7 cells were analyzed by CCK-8 assay,transwell invasion assay, wound healing assay, apoptosis detection. The effect of QRYLD on glucose uptake, lactic acid production and Warburg effect in MCF-7 cells assessed by colorimetry and western blotting. The volumes of xenograft breast tumors and body weights of mice were measured, and the effect of QRYLD on the tumor tissues was assessed with immunohistochemistry.
Results
Here, we show that the QRYLD aqueous extracts contain several bioactive components. Analysis of transcriptomes indicated that QRYLD treatment altered the expression of many genes, such as manganese superoxide dismutase (MnSOD), that were involved in biological processes and signaling pathways, particularly for glucose metabolism in MCF-7 cells. Functionally, QRYLD treatment, like MnSOD silencing, inhibited the malignant behaviors of MCF-7 and enhanced their apoptosis while MnSOD over-expression had opposite effects. Furthermore, QRYLD treatment, like MnSOD silencing, limited glucose uptake and lactic acid production in MCF-7 cells, which were associated with a decrease in the relative levels of Glut-1, HIF-1α, c-Myc, HK-2, PFK-1, LDH-A, PKM-2, MnSOD, calmodulin dependent kinase II (CaMKII) and AMPK expression. Finally, treatment with QRYLD, like MnSOD silencing, significantly mitigated the growth of xenograft MCF-7 tumors in mice and reduced the expression of MnSOD, CaMkII and AMPK expression in the tumors.
Conclusion
These data suggest that QRYLD may target MnSOD to attenuate the MnSOD/CaMKII/AMPK signaling, leading to inhibition of the Warburg effect and malignant behaviors in MCF-7 cells. These findings may provide new insights into the pharmacological mechanisms underlying the actions of QRYLD in inhibiting the Warburg effect and malignant behaviors of breast cancer cells.
Effective oxidation decomplexation of Cu-EDTA and Cu2+ electrodeposition from PCB manufacturing wastewater by persulfate-based electrochemical oxidation: Performance and mechanisms
Authors: Sun Ming , Liu Xuemei , Liu Zhanmeng
Published: April 2024

Complex wastewater matrices such as printed circuit board (PCB) manufacturing wastewater present a major environmental concern. In this work, simultaneous decomplexation of metal complex Cu-EDTA and reduction/electrodeposition of Cu2+ was conducted in a persulfate-based electrochemical oxidation system. Oxidizing/reductive species were simultaneously produced in this system, which realized 99.8% of Cu-EDTA decomplexation, 94.5% of Cu2+ reduction/electrodeposition and within 3 h treatment under the original solution pH 3.2. Almost complete mineralization (74.1% total organic carbon removal) of the solution was obtained after 3 h of treatment. •OH and SO4•– drove the Cu-EDTA decomplexation, destroying the chelating sites and finally it was effectively mineralized to CO2, H2O and Cu2+. The mechanisms of copper electrodeposition on the stainless steel cathode and persulfate activation by the BDD anode were proposed based on the electrochemical measurements. The electrodes exhibited excellent reusability and low metal (total iron and Ni2+) leaching during 20 cycles of application. This study provide an effective and sustainable method for the application of the electro-persulfate process in treating complex wastewater matrices.
Isotopic evidence of acetate turnover in the Precambrian continental crust
Authors: Mueller Elliott , Panehal Juliann , Song Min , Hansen Christian , Warr Oliver , Boettger Jason , Heuer Verena , Bach Wolfgang , Hinrichs Kai-Uwe , Eiler John , Orphan Victoria , Lollar Barbara Sherwood , Sessions Alex
Published: April 2024

The deep continental crust represents a vast potential habitat for microbial life where its activity remains poorly constrained. A common characteristic of these ecosystems is the presence of organic acids like acetate, but the role of these molecules in the subsurface carbon cycle - including the mechanism and rate of their turnover - is still unclear. Here, we developed an isotope-exchange ‘clock’ based on the temperature-dependent abiotic equilibration of H-isotopes between acetate’s methyl-group and water, which can be used to define the maximum in situ residence time for acetate. We applied this technique to the fracture fluids in Birchtree and Kidd Creek mines within the Canadian Precambrian crust. At both sites, we found isotopic disequilibrium between acetate and water, indicating acetate residence times <1 million years and a rate of turnover that could theoretically support microbial life. However, radiolytic water-rock reactions could also contribute to acetate production and degradation, a process that would have global relevance for the deep biosphere. More broadly, our study demonstrates that isotope-exchange clocks can constrain in situ residence times of biomolecules with possible applications to other environments.
PDE4B regulating NOX3/JNK/ALKBH5-mediated GCK methylation in accelerating the development of type 2 diabetes combined with fatty liver
Authors: Guan Yaqing , Luo Jie , Su Man , Yue Lin
Published: April 2024

Objective: This study aims to explore the regulatory mechanism of PDE4B on NOX3/JNK/ALKBH5-mediated GCK methylation and its impact on the acceleration of type 2 diabetes in conjunction with fatty liver development.
Methods: A model of type 2 diabetes combined with fatty liver was established, and a HepG2 cell model stimulated with high glucose was utilized. Western blotting was employed to monitor changes in oxidative stress-related proteins (P22PHOX, P47PHOX, P67PHOX) and signaling pathway proteins (ERK1/2, JNK, ALKBH5). Phosphosite mapping was conducted to assess GCK methylation, while RT-PCR was used to analyze changes in gluconeogenesis-related gene expression. Colorimetric assays were performed to measure glucose, total cholesterol, triglycerides, and glycogen levels, and Oil Red O staining was utilized to detect lipid droplet formation.
Conclusion: Oil Red O staining demonstrated increased lipid droplet content in the liver of type 2 diabetes combined with fatty liver model. High glucose stimulation led to increased lipid droplet content in HepG2 cells. Colorimetric assay results revealed elevated levels of triglycerides, total cholesterol, and glucose in the type 2 diabetes combined with fatty liver model. Western blot results showed that PDE4B knockout reduced the expression of P22PHOX, P47PHOX, P67PHOX, ERK1/2, JNK, and ALKBH5. MSP analysis indicated decreased GCK methylation levels. RT-PCR analysis demonstrated decreased levels of gluconeogenic genes (G6pase, PGC1a, PEPCK). Colorimetric assays indicated a decrease in glycogen synthesis levels, while Oil Red O staining showed a reduction in lipid droplet content.
Survey on the perceptions of Asian endoscopists to artificial intelligence
Authors: Lee Jonathan , QUEK Sabrina Xin Zi , KOO Chieh Sian , LIU Lin , LEUNG Wai Keung , TANG Raymond Shing Yan , Chung Hyunsoo , ZHANG Xuesong , ICHIMASA Katsuro , NGO Denis , MARALIT Ruter , DAO Viet Hang , KHIEN Vu Van , DUSEJA Ajay , PRATAP Nitesh , LEE Yeong Yeh , RENALDI Kaka , SIM Shi Min , WU Clement Chun Ho , LI James Weiquan , TAN Jarrod Kah Hwee , KOH Calvin Jianyi , SO Jimmy Bok Yan
Published: April 2024

OBJECTIVES: Recent studies have demonstrated the potential of artificial intelligence (AI) in diagnostic and therapeutic endoscopy for managing gastrointestinal diseases. However, there is limited knowledge of the perspective of endoscopists towards AI technology, particularly in the Asian community. This study aims to bridge this knowledge gap to guide policymakers, healthcare providers, and technology developers through an Asian AI Task Force.

MATERIALS AND METHODS: An online survey of 45 questions exploring (a) the perceived benefits of AI in endoscopy, (b) the barriers to adopting AI in endoscopy, (c) the priority areas and barriers to research in AI endoscopy, as well as (d) priorities for an Asian AI Task Force were distributed between November 2022 and May 2023 to endoscopists from sixteen medical institutes across ten Asian regions.

RESULTS: 293 participants completed the survey. Two-fifths (41.98%, n=123) reported no prior exposure to AI endoscopy. The majority (73.2%, n=90/123) of those without prior AI exposure expressed concerns about the accountability of AI and its impact on working practices. Almost all participants agreed that AI would enhance quality improvement (90.8%, n=266) and better diagnosis (90.4%, n=265). 69% (n=202) identified “staying up to date with AI advances'' as the top challenge towards clinical adoption of AI. Notably, those without prior exposure expressed high concern regarding accountability for the wrong diagnoses (73.2% vs. 60.6%, p =0.03) and lack of clinical trials (76.4% vs. 57.1%, p <0.01). Most respondents prioritised developing a reference paper guide for clinicians interested in AI (81.2%) and supporting funding applications for AI research (81.5%) as key areas that an Asian AI Endoscopy task force should address.

CONCLUSION: The survey results from Asian endoscopists emphasise the pressing need for collaborative frameworks and educational initiatives, including establishing an Asian AI Task Force, to facilitate the successful integration of AI in endoscopy practice and research across the region.
Eigen-Entropy based Time Series Signatures to Support Multivariate Time Series Classification
Authors: Patharkar Abhidnya , Huang Jiajing , Wu Teresa , Forzani Erica , Thomas Leslie , Lind Marylaura , Gades Naomi
Published: April 2024

Most current algorithms for multivariate time series classification tend to overlook the correlations between time series of different variables. In this research, we propose a framework that leverages Eigen-entropy along with a cumulative moving window to derive time series signatures to support the classification task. These signatures are enumerations of correlations among different time series considering the temporal nature of the dataset. To manage dataset's dynamic nature, we employ preprocessing with dense multi scale entropy. Consequently, the proposed framework, Eigen-entropy-based Time Series Signatures, captures correlations among multivariate time series without losing its temporal and dynamic aspects. The efficacy of our algorithm is assessed using six binary datasets sourced from the University of East Anglia (UEA), in addition to a publicly available sepsis dataset and an institutional sepsis dataset from the Mayo Clinic. We employ recall as a metric for evaluation against the baseline algorithm, Dependent Dynamic Time Warping with 1 Nearest Neighbor. Our algorithm outperforms the baseline algorithm for UEA datasets in terms of recall with an average value of 10% across all datasets, and by 38% for an institutional sepsis dataset. For the public sepsis dataset, the performance of our algorithm is comparable to the baseline algorithm.
Female Legislators Decrease Epidemic Deaths
Authors: Saito Takaharu
Published: April 2024

Recent discourse has lauded the eﬀicacy of female leadership in national governments, particularly during the COVID-19 pandemic. This study employs two-way fixed effect (TWFE) and instrumental variable (IV) regression methodologies to reveal a more pronounced association between the proportion of female legislators and reduced epidemic-related mortality, rather than a direct correlation with female executive leadership. Further analysis elucidates that the effectiveness of female legislative representation is amplified through its interaction with the deliberative processes in governance. This suggests that policy diversity and inclusive decision-making mechanisms are instrumental in enhancing epidemic response eﬀicacy.
Multi-Energy Storage SOC Equalization Strategy Based on Virtual DC Motor Control
Authors: Wang Junrui , Bai Bingchao , Wang Rui , Dou Shuai , Tan Lu , Zhu Xuqiang
Published: April 2024

Droop control is commonly used in DC microgrid to maintain the reasonable distribution of power between DC micro-sources to ensure the stable and safe operation of DC microgrid. However, the traditional state of charge balance control strategy based on droop control will cause problems such as bus voltage drop and unreasonable system power distribution due to its own characteristics. Therefore, a multi-energy storage state of charge balance control strategy based on virtual DC motor control is proposed. Firstly, according to the instantaneous power balance characteristics of DC microgrid, the fluctuation of load or photovoltaic output is controlled by first-order high-pass filtering as an additional amount of rated power controlled by conventional virtual DC motor, which provides additional inertia and damping support for the system to improve the transient stability of the system. Secondly, the state of charge balance strategy based on improved adaptive droop control is used to realize the state of charge balance between multiple sets of batteries and the reasonable distribution of system power. Finally, the virtual DC motor control is combined with adaptive droop control, and the control strategy is verified by building a simulation model of photovoltaic multi-energy storage DC microgrid and an experimental platform. The results show that the proposed control method can reduce the influence of power fluctuation on DC bus voltage and realize the state of charge balance between multiple sets of batteries.
Microscopic detection and molecular characterization of Sarcocystis miescheriana in wild boars (Sus scrofa): first report from Greece
Authors: Dimzas Dimitris , Rubiola Selene , Pacifico Laura , Veneziano Vincenzo , Chiesa Francesco , Chassalevris Taxiarchis , Diakou Anastasia
Published: April 2024

The genus Sarcocystis includes protozoan parasites with an indirect life cycle. Sarcocystis spp. can infect various animal species and humans, causing sarcocystosis, a parasitosis of economic importance and zoonotic concern. Wild boars can act as intermediate hosts for Sarcocystis mieshieriana and the zoonotic Sarcocystis suihominis that infects humans by consumption of raw or undercooked infected swine meat. In the present study, diaphragmatic muscle tissue of 123 wild boars hunted in northern Greece were examined to determine the frequency of Sarcocystis spp. The samples were examined by tissue compression and molecular techniques. Under light microscopy, 34 out of 123 (27.6%) wild boars tested positive for Sarcocystis spp., while a higher infection prevalence (75%) was revealed by multiplex PCR performed in 100 of the samples. The partial mtDNA cox1 gene (~1100 bp) of 20 samples tested positive for S. miescheriana by multiplex PCR was amplified and sequenced. Sarcocystis miescheriana was identified as the only species involved in these infections. This is the first study on the prevalence of Sarcocystis spp. in wild animals in Greece. Further large-scale surveys are needed to assess the prevalence and species of this parasite in Greece and to design efficient control and preventive measures in a One Health perspective.
A data-centric machine learning approach to improve prediction of glioma grades using low-imbalance TCGA data
Authors: Sánchez-Marqués Raquel , García Vicente , Sánchez José Salvador
Published: April 2024

Accurate prediction and grading of gliomas play a crucial role in evaluating brain tumor progression, assessing overall prognosis, and treatment planning. In addition to neuroimaging techniques, identifying molecular biomarkers that can guide the diagnosis, prognosis and prediction of the response to therapy has aroused the interest of researchers in their use together with machine learning and deep learning models. Most of the research in this field has been model-centric, meaning it has been based on finding better performing algorithms. However, in practice, improving data quality can result in a better model. This study investigates a data-centric machine learning approach to determine their potential benefits in predicting glioma grades. We report six performance metrics to provide a complete picture of model performance. Experimental results indicate that standardization and oversizing the minority class increase the prediction performance of four popular machine learning models and two classifier ensembles applied on a low-imbalanced data set consisting of clinical factors and molecular biomarkers. The experiments also show that the two classifier ensembles significantly outperform three of the four standard prediction models. Furthermore, we conduct a comprehensive descriptive analysis of the glioma data set to identify relevant statistical characteristics and discover the most informative attributes using four feature ranking algorithms.
HDRP: Integrated Strategies for Robust Heart Disease Detection using Random Crop LSTM Processing and Regression Models
Authors: Kumar Shrawan , Thakur Bharti , Mishra Vinaytosh
Published: April 2024

Detecting heart disease is significant for timely intervention and improved patient outcomes. With the rising global burden of cardiovascular disorders, there is an urgent need for accurate and efficient diagnostic tools. Advanced technologies, such as Machine Learning (ML) and Artificial Intelligence (AI), have shown promise in enhancing early detection and risk assessment. Integrating these innovative approaches into clinical practice can significantly contribute to the early identification of heart disease, facilitating timely interventions and personalized patient care. Addressing this need is vital for reducing the impact of heart disease on public health. This research presents a comprehensive examination of heart disease detection models, encompassing neural networks, backpropagation, random crop techniques, Long Short-Term Memory (LSTM), and regression methods. The investigation included a comparative analysis of various models, including Heart Disease Evaluation (HBE), AdaBoost, Support Vector Machine (SVM), Random Forest, and proposed method (HDRP), with a focus on accuracy, error rates, and precision over 5 and 10 epochs. Notably, the HDRP model emerged as a standout performer, consistently demonstrating superior accuracy and the lowest error values, showcasing its efficacy in heart disease prediction. The discussion highlights the unique features of HDRP, attributed to advanced methodologies or distinctive design elements. The study emphasizes the importance of future research to delve into the specific attributes contributing to HDRP's performance, exploring model architecture, optimization strategies, and scalability across diverse datasets.
Cross-border data sharing for research in Africa: An analysis of the data protection and research ethics requirements in 12 jurisdictions
Authors: Staunton Ciara , Edgcumbe Aliki , Abdulrauf Lukman , Gooden Amy , Ogendi Paul , Thaldar Donrich
Published: April 2024

Background In recent years, there has been a notable uptake in genomic and health-related research activities across the African continent. Similarly, there has been increased introduction of data protection legislation that affects the sharing of personal data such as health data and genomic data, including for research. Many of these statutes have stricter requirements when sharing personal data across borders. Consequently, the cross-border sharing of health data that includes genetic data requires careful navigation of the pertinent data protection legislation, in particular concerning the sharing of such data for research purposes. To help researchers navigate these legal frameworks, 12 African countries were analysed to develop country guides on cross-border data sharing.Results Of the 12 countries that were analysed, ten have data protection laws in place (Botswana, Ghana, Kenya, Malawi, Nigeria, Rwanda, South Africa, Tanzania, Uganda, and Zimbabwe), while two countries (Cameroon and The Gambia) do not. With the exception of Ghana, all countries with data protection statutes or bills had additional requirements to be met when sharing personal data across borders. Consent and adequacy are the most common grounds for justifying the sharing of personal data across borders.Conclusion Given the limitations of the current models of consent, consent is not a suitable basis to transfer large quantities of data for research. Adequacy is a common ground, but there are national differences in the implementation of this ground. Researchers must therefore analyse each national legal framework and make decisions on a case-by-case and country-by-country basis.
Molecular characterization and functional analysis of Peptidoglycan recognition protein-L2 in Hexagrammos otakii
Authors: Bai Yifan , Liu Yingying
Published: April 2024

Peptidoglycan recognition proteins (PGRPs) belong to the pattern recognition receptors (PRRs), which are essential for sensing and defending against pathogenic microorganisms during innate immunity pathways. Although an increasing body of research indicates that the PGRP protein in fish has various biological functions such as antimicrobial activity, amidase activity, and the ability to regulate multiple signaling pathways, the molecular mechanisms by which PGRP contributes to the innate immune processes in fish remain relatively limited. In the present study, we have recombinantly expressed a long-type PGRP from fat greenling (Hexagrammos otakii) (HoPGRP-L2) and analyzed its molecular mechanism in the pathogen identification process. The open reading frame (ORF) of HoPGRP-L2 is 1449 bp in length that encodes for a peptide with 482 amino acids. As a PRR, HoPGRP-L2 has a typical PGRP domain that enables HoPGRP-L2 to recognize and conjugate to bacterial peptidoglycan (PGN) on the cell wall. We demonstrated that HoPGRP-L2 could bind to pathogenic microorganisms and promote the agglutination of them. Furthermore, HoPGRP-L2 was confirmed to possess zinc ion-dependent amidase activity and exhibited an effect on the growth inhibition of chosen bacteria. HoPGRP-L2 also prolongs the survival time in carp injected with Aeromonas hydrophila. Taken together, our results indicate that PGRP acts as a PRR involved in recognizing and eliminating pathogens during the innate immune response in Hexagrammos otakii.
Bitter gourd improvement through the selection of attributes contributing to yield by character association and path analysis
Authors: Sriniva B. , Padma S. S. Vijaya , Naidu L. Naram , Rao M. Paratpara , Kumar Ch. Kiran , Sekhar V.
Published: April 2024

The current study was carried out at the Vegetable Experimental Farm of the College of Horticulture in Venkataramannagudem, Andhra Pradesh. The objective was to analyse associations between characters and direct and indirect effects for 12 traits associated with bitter gourd improvement and yield using a half diallel design. The experiment involved seven parents, twenty-one hybrid combinations, and two standard checks which were evaluated in a randomized complete block design with three replications. For every trait, genotypic correlations were found to be higher than phenotypic correlations, demonstrating that various traits have an inherent connection. Notably, at both the phenotypic and genotypic levels, yield per plant was significantly associated with plant height, number of fruits per plant, average fruit weight, fruit length and diameter, internodal length, and seeds per fruit. This shows that all six attributes should be studied together in order to increase bitter gourd yield. The average fruit weight, number of fruits per plant, plant height, days to female flower appearance, fruit length and diameter, internodal length, and sex ratio all had a substantial and positive direct influence on fruit yield per plant, according to path coefficient analysis. This means that direct selection based on these attributes would result in increased bitter gourd fruit yield per plant.
Hyperbolic metamaterials assisted ultrathin Pd films for high-sensitivity hydrogen sensors
Authors: Chen Zhiying , Wu Xiaohu , Liu Haotuo , Baqir Muhammad Abuzar , Yu Kun , Zhang Kaihua
Published: April 2024

Optical hydrogen sensors can use optical fiber as the medium for light transmission or sensing, and realize hydrogen detection based on the relevant physicochemical properties of hydrogen-sensitive materials, which have excellent characteristics such as intrinsic safety, good stability, small size, high specificity, and easy to network. However, traditional hydrogen-sensitive materials such as Pd metal usually require a large thickness to obtain good performance, but this will shorten the service life of the sensor. In response to this issue, a hydrogen sensor based on hyperbolic metamaterials and ultrathin Pd films is proposed. The control of the Pd film thickness to be less than 0.02 μm ensures that mechanical deformation does not occur during the formation of hydrides in the Pd film. The calculations indicate that the sensor sensitivity can be maintained at approximately 2300 even when the thickness of the palladium film is reduced to 0.011 μm. This work provides a promising solution for high-performance optical hydrogen detection, characterized by high sensitivity, low latency, and low cost.
A Compact Parallel Dispensing Machine of High-viscous Adhesive Based on Electrostatic-induced Mechanism
Authors: Xu Zheng , Liu Yuanchun , Sun Zhongping , Zhang Jiaqi , Wang Xiaodong , Xu Xiaoyu
Published: April 2024

Adhesive bonding process has been widely applied in the assembly of micro-electro-mechanical system products, in which the efficient micro-dispensing technique of high-viscous liquid is important for the bonding performance. In this paper, we propose a compact and portable machine for the parallel dispensing task of high-viscous adhesive based on electrostatic-induced mechanism. The designed flexible probe array can reduce the impact of height difference Δh on transferring stage to thereby improve the dispensing consistency. With the developed machine, both parallel and serial dispensing modes are built up with replaceable dispensing head to satisfy various requirements. The dispensing efficiency is increased by 91.44% via parallel dispensing mode, comparing with previous single-probe mode. In addition, smart patterning with Mean square deviation σd less than 0.026 mm is achieved with both the configurable probe-status and the replaceable dispensing head. We believe this machine can be used efficiently and smartly in the adhesive bonding process.
Comparison of Transient Spray Characteristics of N-dodecane and OME 3 Using Large Eddy Simulation
Authors: Al-lehaibi Moaz , Menacer Brahim
Published: April 2024

There have been continuing efforts in the Engine Combustion Network (ECN) community to understand the detailed spray characteristics by investigating several standard diesel injectors. With the increasing interest in the use of alternative and renewable fuels, the present study conducted large eddy simulations with dynamic structure subgrid closure in the Eulerian volume-of-fluid (VOF) framework to identify the characteristics of oxymethylene ethers (OME), which has distinct physical and chemical properties leading to low soot emissions. In particular, the spray features of n-dodecane and OME3 were compared and analyzed in terms of their transient dynamics following the nozzle opening. ECN Spray A, C, and D were considered to assess the effects of nozzle convergence factor and nozzle diameter. The measured nozzle geometries by the Argonne National Laboratory were adopted to mimic the internal flow development. Due to the higher density of OME3, it generates a higher projected density, but a lower injection velocity is obtained. This behavior is attributed to its higher mass inertia. The diverging Spray C injector induces a significantly lower projected density and mass flow rate than the converging Spray D injector owing to cavitation just after the sharp nozzle inlet corner. By comparison, the Spray A injector generates the lowest projected density and mass flow rate for its smallest nozzle diameter. Various fuels demonstrate similar flow fields, evidenced by the significantly similar pressure distribution. The OME3 cases lead to a slightly higher temperature distribution within the nozzle channel, which is attributed to the lower turbulent kinetic energy and thus the slower heat transfer process.
Numerical Modeling of Downstream Scour in Circular Culverts: Impact of Inlet Blockages and Variable Flow Conditions
Authors: Ahmed Kaywan Othman , Kavianpour Mohammad Reza , Amini Ata , Aminpour Younes
Published: April 2024

Accurate estimation of scour depth downstream of culvert outlets is essential for culvert design integrity. Inadequate designs can result in structural failures, leading to increased costs for maintenance and rehabilitation. This research evaluates the efficacy of numerical models in predicting scour depth and its location downstream of circular culverts under variable flow conditions. Two hydrographs were created for unsteady flow, featuring nine different flow discharges, while steady flow conditions were analysed at flow rates of 14 l/s and 22 l/s. The study investigated circular culverts with inlet blockages of 0%, 15%, and 30%, comparing outcomes with predictions from the Flow-3D software by using renormalization group (RNG) turbulence model. Extensive experimental data on circular culverts were utilized, with simulations performed using commercial software. This involved analysing the scour’s downstream profile, its maximum depth, and location, and comparing these metrics with actual observed data. Results showed that numerical model predictions closely matched the experimental data, although the simulated scour was generally less than what was observed for both steady and unsteady flows. While blockage rates notably impacted the scour patterns in unsteady flow scenarios, escalating blockage percentages did not uniformly translate into proportional increases in scour depth within steady flow environments.
Generative Deep Belief Differential Lotka Volterra-Based Data Transmission in Wsn for Real-Time Health Care Monitoring
Authors: Sachin B M , Sarvagya Mrinal
Published: April 2024

Wireless Sensor Networks (WSNs) have considerable awareness owing to their extensive scope of applications, to name a few being, natural disaster prohibition, health care monitoring video surveillance and so on. Moreover, the energy consumed during communication is a substantial quantity of energy loss and the routing protocol is the most suitable means to address this issue by fine-tuning weights to conserve the energy. Therefore the main issue experienced by WSN is the routing and data transmission and hence distinct points of reference need to be addressed when designing the routing protocol for real time healthcare monitoring. Motivated by these issues, in this work a method called, Probabilistic Generative Deep Belief and Differential Game Lotka Volterra (PGDB-DGLV) based data transmission in WSN for real-time health care monitoring is proposed. The PGDB-DGLV method is split into two sections, namely, optimal route discovery and robust data transmission. To measure route stability Balanced Centrality and Probabilistic Generative Deep Belief Network algorithm is designed. In the proposed model, a fine-tuned adjacency matrix employing the Stable Balanced Centrality function is defined to determine the next hop based on certain parameters like, hop count, residual energy and link quality. These parameters are salient assessments in adjacent node selections with which routing can be performed. Also, the initialization of the adjacency matrix and its corresponding fine-tuning is performed via the Probabilistic Generative Deep Belief Network. Second, to minimize the transmission speed and therefore reduce packet loss significantly, two kinds of game models, i.e., cooperative and cooperative models are constructed. Finally, the Lotka Volterra function is applied to ensure robust data transmission. At last, the performance of the proposed PGDB-DGLV method is evaluated using different evaluation metrics they are energy consumption, throughput transmission speed and packet loss rate. Finally, the evaluated results are compared with the prevailing data transmission methods. Among these methods, the proposed PGDB-DGLV method has achieved a better transmission speed with minimum energy consumption and maximum throughput considerably.
A Bayesian Network Approach to Hybrid Threat
Modelling
Authors: Vonk Maarten , Sweijs Tim , Minicozzi Raffaele
Published: April 2024

Western governments have adopted an assortment of counter-hybrid threat measures to defend against hostile actions below the conventional military threshold. The impact of these measures is unclear because of the ambiguity of hybrid threats, their cross-domain nature, and uncertainty about how countermeasures shape adversarial behaviour. This paper presents a model to simulate the impact of countermeasures on hybrid threat behaviour through a Bayesian Network approach - a probabilistic modelling technique. The model balances the costs of countermeasures, their ability to dissuade the adversary from executing hybrid threats, and their potential to mitigate the impact of hybrid threats. We run 1000 variants of a semi-synthetic scenario simulating the strategic interaction between attacking agent A and defending agent B over a cyber attack on critical infrastructure to explore the effectiveness of a set of five different counter-hybrid threat measures. Counter-hybrid measures range from strengthening resilience and denial of the adversary's ability to execute a hybrid threat to dissuasion through the threat of punishment. Our analysis primarily evaluates the overarching characteristics of counter-hybrid threat measures This approach allows us to generalize the effectiveness of these measures, rather than attributing results to measures individually. In addition, we discuss policy relevance and outline future research avenues.
The impact of climate risks on the cost of capital of oil and gas companies
Authors: Bettega Leonardo de Carvalho Bastos , Goncalves Edson Daniel Lopes , de Souza Rafael Martins
Published: April 2024

In a context of energy transition and decarbonization, companies operating in the oil and gas sector may be more exposed to climate risks, both physical and transition related. This greater exposure may reflect in a higher cost of capital, given the risk of stranded assets, stigmatization of the sector and reduced funding. This paper seeks to study this hypothesis, applying econometric models to analyze whether climate risk, represented here by a Carbon Intensity metric (scope 1 and scope 2 greenhouse gas emissions per US$ of revenue), has a significant effect on the systematic risk coefficient (beta) of these companies. The results show that Carbon Intensity has a statistically significant positive effect on beta, contributing to the argument that greater climate risk can increase companies' systematic risk. According to the most robust model (Model 1), a 100% increase in Carbon Intensity generates a corresponding rise of 0.0608 in beta, everything else kept constant - an increase of 7.25% in relation to the average beta of the sample.
Исследование школьной тревожности у детей-мигрантов младшего школьного возраста
Authors: Сорокоумова Е.А. , Кобзев Е.А. , Скрябина Т.Н.
Published: April 2024

В статье даны понятия и определение миграции. Описаны различные виды иноязычных обучающихся. Обозначаются личностные особенности и проблемы детей-мигрантов. В результате проведенного исследования выявлено отсутствие значимых различий в проявлении тревожности среди русскоязычных и иноязычных обучающихся первого класса общеобразовательной школы.
Взаимосвязь жизнестойкости и психологического здоровья педагогов-психологов
Authors: Свередюк Е.В.
Published: April 2024

В статье представлены результаты эмпирического исследования выявления взаимосвязи жизнестойкости с показателями психологического здоровья педагогов-психологов, представляющих разные типы учреждений образования из разных регионов Республики Беларусь. Результаты исследования выявили наличие взаимосвязи между жизнестойкостью и показателями психологического здоровья педагогов-психологов. Сильная положительная связь установлена между показателями «Вовлеченность», «Контроль», «Принятие риска», интегральным показателем «Жизнестойкость» и показателями «Управление средой», «Самопринятие» и интегральным показателем «Психологическое благополучие». Умеренная положительная связь установлена между показателем «Жизнестойкость» и интегральным показателем «Психологическое здоровье», его составляющими: «Эмоциональное состояние», «Социальное функционирование», «Жизнеспособность», «Эмоциональное благополучие». Установлена сильная и умеренная положительная связь показателя «Жизнестойкость» со следующими индикаторами психологического благополучия: «Позитивные отношения», «Автономия», «Личностный рост», «Цели в жизни».
THE DOUBLE-EDGED SWORD: HOW LEARNING CAN INFLUENCE AGGRESSION
Authors: Alahakoon Sonath K. , Filippovich Yulia S.
Published: April 2024

Students strivefor knowledge, but learning sometimes fuels aggression. Stress, rivalry, fatigue, and loneliness can trigger anger. Research shows these factors affect minds and bodies, leading to hostile actions. Eyers et al, Sinha et al, and others explain the complex causes. However, coping strategies exist: reduce pressure, encourage teamwork over contests, and build supportive academic settings. With care, education need not breed violence. Studies by Hofmann and others, Johnson & Johnson, Ellis & Knauff back, as well as Walker’s work confirm these techniques work well. In summary, recognizing academic stress may lead to aggression is key. Using the suggested approaches can foster a more upbeat, productive learning setting for pupils
MNEMOSINE E APRENDIZAGEM
Authors: De Souza Paula Oliveira , Alves Tarso Ferreira
Published: April 2024

A memória é a capacidade humana de apreender os acontecimentos do passado, de modo que os mesmos possam ser difundidos pelos homens nos séculos posteriores. Nas sociedades tradicionais, onde ainda não existia a escrita, a oralidade garantia a conservação das tradições. Ao realizar um recorte nas sociedades tradicionais e referindo-se à Grécia Antiga, a maior parte da cultura grega foi disseminada pela oralidade até o final do século V a.C, antes da disseminação da escrita. No Fedro de Platão, o filósofo, através de um mito, traz a questão do perigo proeminente que é o fato dos homens confiarem a sua memória à depositários externos. No mundo contemporâneo é comum os sujeitos confiarem a sua mnemosine à internet e a outros dispositivos - o que leva ao enfraquecimento da memória-interior e a sua identidade. O propósito é demonstrar, a partir do Fedro de Platão, a importância do resgate da memória enquanto instrumento de aquisição e transmissão do conhecimento, para então refletir sobre a sua relação com a contemporaneidade.
A Study on Development Plans for Small Libraries in Incheon Metropolitan City : Focusing on interviews with a group of experts
Authors:   The Korean Publishing Science Society, Lee Mun Hag
Published: April 2024

This study examined the operation status of private small libraries in Incheon Metropolitan City and suggested development plans, and a total of 22 expert group interviews were conducted from January 28 to February 8, 2024. As a result of the study, first, the respondents often established small libraries to expand the leisure space of local residents. Second, although the satisfaction level of the library operation was moderate, there were deep concerns about the lack of support budget, operating manpower, and the low usage rate of local residents. Third, most of the respondents said that the biggest function of the small library is to contribute to the promotion of the reading culture of local residents, and the most important function of the current small library is to promote the reading culture of local residents, and various reading-related programs are operated. Fourth, the type of support received from government agencies and local governments was the largest amount of support for collections, and what was needed for the continued operation of small libraries was the expansion of the support budget of local governments, and fifth, there were many opinions that they hoped that the operation of small libraries would be operated as a place to provide a gathering place for local residents.
Research Trend in Publishing Science by Text-Mining : focused on Studies of Korean Publishing Science
Authors:   The Korean Publishing Science Society, Kim Mun Ki , Lee Jang Suk
Published: April 2024

The evolving IT technologies such as digital publishing content and AI publishing have a significant impact on the publishing industry. Therefore, it is important to consolidate research achievements in the field of publishing studies and provide direction to cope with these changes. In this study, we conducted topic modeling analysis on 459 academic papers published in Korean publishing studies, collecting titles, abstracts, and keywords. The analysis revealed four topics: technological advancement and environmental changes, reflections on publishing acceptance, utilization of internal capabilities and assessments in the publishing industry, and education in the publishing field. Prior to 2010, three topics emerged: initial digital transformation, changes in the industry environment, and responses to publishing acceptance changes. After 2010, four topics emerged: digital transformation, changes in publishing acceptance and response, education in the publishing field, and the current status of the publishing industry. The research results shed light on the significant topics addressed in Korean publishing studies and suggest the need for research topics that provide more practical insights for the publishing industry.