bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantum Applications of an Atomic Ensemble Inside a Laser Cavity
Authors: Ben Amar Baranga Andrei , Koganov Gennady A. , Levron David , Bialolenker Gabriel , Shuker Reuben
Published: January 2024

Many quantum device signals are proportional to the number of the participating atoms that take part in the detection devices. Among these are optical magnetometers, atomic clocks, quantum communications and atom interferometers. One way to enhance the signal-to-noise ratio is to introduce atom entanglement that increases the signal in a super-radiant-like effect. A coherent em field inside a laser cavity is suggested to achieve atoms’ correlation/entanglement. This may also play an important role in the basic quantum arena of many-body physics. An initial novel experiment to test the realization of atoms’ correlation is described here. A Cs optical magnetometer is used as a tool to test the operation of a cell-in-cavity laser and its characteristics. A vapor cell is inserted into an elongated external cavity of the pump laser in Littrow configuration. Higher atom polarization and reduced laser linewidth are obtained leading to better magnetometer sensitivity and signal-to-noise ratio. The Larmor frequency changes of the Free Induction Decay of optically pumped Cs atomic polarization in the ambient earth magnetic field at room temperature is measured. Temporal changes in the magnetic field of less than 10 pT/√Hz are measured. The first-order dependence of the magnetic field on temperature and temperature gradients is eliminated, important in many practical applications. Single and gradiometric magnetometer configurations are presented.
Machine Learning Based Automatic Mode-Locking of a Dual-Wavelength Soliton Fiber Laser
Authors: Yan Qi , Tian Yiwei , Zhang Tianqi , Lv Changjian , Meng Fanchao , Jia Zhixu , Qin Weiping , Qin Guanshi
Published: January 2024

Recent years have witnessed growing research interest in dual-wavelength mode-locked fiber lasers for their pivotal role in diverse applications and the exploration of nonlinear dynamics. Despite notable progress in their development, achieving reliable mode-locked dual-wavelength operation typically necessitates intricate manual adjustments of the cavity’s polarization components. In this article, we present the realization of automatic mode-locking in a dual-wavelength soliton fiber laser. To provide guidance for the algorithm design, we systematically investigated the impact of polarization configurations and initial states on the laser’s operation through numerical simulations and linear scan experiments. The results indicate that operational regimes can be finely adjusted around the wave plate position supporting the mode-locked dual-wavelength solution. Furthermore, the laser exhibits multiple stable states at the mode-locked dual-wavelength point, with critical dependence on the initial conditions. Accordingly, we developed a two-stage genetic algorithm that was demonstrated to be effective for realizing automatic dual-wavelength mode-locking. To further improve the performance of the algorithm, a feedforward neural network was trained and integrated into the algorithm, enabling accurate identification of the dual-wavelength states. This study provides valuable insights into understanding how polarization configurations and initial conditions impact the operational regimes of dual-wavelength mode-locked fiber lasers. The algorithm developed can be extended to optimize other systems with multiple stable states supported at the same parameter point.
Tea Polyphenols Inhibit the Occurrence of Enzymatic Browning in Fresh-Cut Potatoes by Regulating Phenylpropanoid and ROS Metabolism
Authors: Guan Yuge , Lu Sainan , Sun Yan , Zheng Xinrui , Wang Run , Lu Xinghua , Pang Linjiang , Cheng Jiyu , Wang Lei
Published: January 2024

During fresh-cut processing, potatoes lose their inherent protective cellular structure, leading to enzymatic browning that compromises sensory and edible quality. Tea polyphenols (TPs), natural preservatives with potent reducing properties, are hypothesized to impact this browning process. However, their influence and regulatory mechanism on the enzymatic browning of fresh-cut potatoes remain poorly understood. This study used the “Holland Seven” potato as the research material to explore the effects of a treatment with different TP concentrations (0.1 g L−1, 0.2 g L−1, and 0.3 g L−1) on the browning phenomenon and quality of fresh-cut potatoes during storage. The results showed that appropriate concentrations of TP treatment had a good preservation effect on the appearance and edible quality of fresh-cut potatoes. Furthermore, exogenous TP treatment reduced the content of enzymatic browning substrates (caffeic acid, p-coumaric acid, and ferulic acid) by regulating phenylpropanoid metabolism. Meanwhile, TP treatment augmented the activities of antioxidative enzymes (superoxide dismutase, catalase, ascorbate peroxidase, and glutathione reductase), maintained higher levels of ascorbic acid (Vc), and reduced glutathione (GSH). Consequently, the TP treatment could inhibit enzymatic browning by regulating reactive oxygen species (ROS) metabolism and the Vc-GSH cycle in fresh-cut potatoes.
Moderate Water Stress Impact on Yield Components of Greenhouse Tomatoes in Relation to Plant Water Status
Authors: Alomari-Mheidat Munia , Corell Mireia , Martín-Palomo María José , Castro-Valdecantos Pedro , Medina-Zurita Noemí , de Sosa Laura L. , Moriana Alfonso
Published: January 2024

The scarcity of water resources affects tomato production. Deficit irrigation may optimize water management with only a low reduction in yield. Deficit irrigation scheduling based on applied water presented no clear conclusions. Water stress management based on plant water status, such as water potential, could improve the scheduling. The aim of this work was to evaluate the physiological and yield responses of different tomato cultivars to deficit irrigation. Three experiments were carried out in 2020 and 2022 at the University of Seville (Spain). “Cherry” and “chocolate Marmande” cultivars with an indeterminate growth pattern were grown in a greenhouse. Treatments were: Control (full irrigated) and Deficit. Deficit plants were irrigated based on water potential measurements. Moderate water stress did not significantly reduce the yield, although it affected other processes. Fruit size and total soluble solids were the most sensitive parameters to water stress. The latter increased only when persistent water stress was applied. However, truss development and fruit number were not affected by the level of water stress imposed. Such results suggest that moderate water stress, even in sensitive phenological stages such as flowering, would not reduce yield. Deficit irrigation scheduling based on plant water status will allow accurate management of water stress.
A Combination of Three Genomic Regions Conditions High Level of Adult Plant Stripe Rust Resistance in Australian Wheat Cultivar Sentinel
Authors: Chemayek Bosco , Wagoire William , Bansal Urmil , Bariana Harbans
Published: January 2024

A seedling susceptible Australian common wheat cultivar Sentinel showed resistance to stripe rust under field conditions. A Sentinel/Nyabing3 (Nyb3)-derived recombinant inbred line (RIL) population was phenotyped. A DArTseq marker-based linkage map of the Sentinel/Nyb3 RIL population was used to determine the chromosomal location of the adult plant stripe rust resistance possessed by Sentinel. Three consistent quantitative trait loci (QTL); QYr.sun-1BL, QYr.sun-2AS and QYr.sun-3BS were detected, and they on an average explained 18%, 15.6% and 10.6% of the variation in stripe rust response, respectively. All three QTL were contributed by Sentinel. QYr.sun-1B corresponded to the previously characterized gene Yr29. Sentinel expressed resistance at the four-leaf stage at 21 ± 2 °C in the greenhouse. Monogenic segregation among the RIL population was observed when screened at the four-leaf stage at 21 ± 2 °C in the greenhouse, and the underlying resistance locus was temporarily named YrSen. QYr.sun-3BS peaked on YrSen. QYr.sun-2AS was mendelized by generating and phenotyping a mongenically sgregating F6 RIL population, and it was temporarily designated YrSen2. RILs carrying Yr29, YrSen and YrSen2 in combination exhibited responses like the parent Sentinel. Based on a comparison of the genomic locations and resistance expression with stripe rust resistance genes previously located in their respective chromosomes, QYr.sun-2AS (YrSen2) and QYr.sun-3BS (YrSen) were concluded to represent new loci.
Oil Production Optimization Using Q-Learning Approach
Authors: Zahedi-Seresht Mazyar , Sadeghi Bigham Bahram , Khosravi Shahrzad , Nikpour Hoda
Published: January 2024

This paper presents an approach for optimizing the oil recovery factor by determining initial oil production rates. The proposed method utilizes the Q-learning method and the reservoir simulator (Eclipse 100) to achieve the desired objective. The system identifies the most efficient initial oil production rates by conducting a sufficient number of iterations for various initial oil production rates. To validate the effectiveness of the proposed approach, a case study is conducted using a numerical reservoir model (SPE9) with simplified configurations of two producer wells and one injection well. The simulation results highlight the capabilities of the Q-learning method in assisting reservoir engineers by enhancing the recommended initial rates.
Combined Application of Juniperus communis Essential Oil and Amikacin, Clarithromycin and Rifampicin against Mycobacterium avium and Mycobacterium intracellulare
Authors: Peruč Dolores , Štifter-Vretenar Sanja , Planinić Ana , Gobin Ivana
Published: January 2024

The group of nontuberculous mycobacteria (NTM) includes about 200 mycobacteria that are widespread in the natural environment as free-living saprophytic bacteria, commensals or symbionts. NTM, also referred to as atypical mycobacteria, are mostly apathogenic; nowadays, they are increasingly important environmental opportunistic pathogens. This study continues the work of previous studies which investigated the individual and synergistic effect of different essential oils (EOs) on NTM. The aim was to investigate the effect of the interaction of the common juniper (Juniperus communis) EO and the antimicrobials, amikacin, clarithromycin and rifampicin, against Mycobacterium avium and M. intracellulare using the checkerboard synergy method in an enriched Middlebrook 7H9 broth. Morphological changes of treated NTM cells were observed with a transmission electron microscope. The most synergistic combinations were found at subinhibitory concentrations of the common juniper EO and rifampicin against both tested NTM and this EO and clarithromycin against M. avium. A slightly smaller number of synergistic effects on both NTM were found using a combination of this EO and amikacin. Combinations of clarithromycin and the common juniper EO showed no synergism against M. intracellulare. The exposure of both NTM to synergistic combinations of this EO and antimicrobials caused significant morphological changes in mycobacterial cells. Synergism with the combined use of EOs and antimicrobials allows the use of low effective concentrations via the sustained antimicrobial effect of the tested substances, but with potentially reduced toxicity.
Fluid-Loss Control Technology: From Laboratory to Well Field
Authors: Islamov Shamil , Islamov Ravil , Shelukhov Grigory , Sharifov Anar , Sultanbekov Radel , Ismakov Rustem , Agliullin Akhtyam , Ganiev Radmir
Published: January 2024

Effective fluid-loss control in oil wells is a critical concern for the oil industry, particularly given the substantial reserves situated in carbonate reservoirs globally. The prevalence of such reservoirs is expected to rise with the slow depletion of hydrocarbons, intensifying the need to address challenges related to deteriorating reservoir properties post well-killing operations. This deterioration results in significant annual losses in hydrocarbon production at major oil enterprises, impacting key performance indicators. To tackle this issue, this study focuses on enhancing well-killing technology efficiency in carbonate reservoirs with abnormally low formation pressures. To address this issue, the authors propose the development of new blocking compositions that prevent the fluid loss of treatment fluids by the productive reservoir. The research tasks include a comprehensive analysis of global experience in well-killing technology; the development of blocking compositions; an investigation of their physico-chemical, rheological, and filtration properties; and an evaluation of their effectiveness in complicated conditions. The technology’s application in the oil and gas condensate fields of the Volga-Ural province showcases its practical implementation. This study provides valuable insights and solutions for improved fluid-loss control in carbonate reservoirs, ultimately enhancing well performance and hydrocarbon recovery.
A Dynamic Permeability Model in Shale Matrix after Hydraulic Fracturing: Considering Mineral and Pore Size Distribution, Dynamic Gas Entrapment and Variation in Poromechanics
Authors: Zhang Qihui , Li Haitao , Li Ying , Wang Haiguang , Lu Kuan
Published: January 2024

Traditional research on apparent permeability in shale reservoirs has mainly focussed on effects such as poromechanics and porosity-assisted adsorption layers. However, for a more realistic representation of field conditions, a comprehensive multi-scale and multi-flowing mechanism model, considering the fracturing process, has not been thoroughly explored. To address this research gap, this study introduces an innovative workflow for dynamic permeability assessment. Initially, an accurate description of the pore size distribution (PSD) within three major mineral types in shale is developed using focussed ion beam-scanning electron microscopy (FIB-SEM) and nuclear magnetic resonance (NMR) data. Subsequently, an apparent permeability model is established by combining the PSD data, leading to the derivation of dynamic permeability. Finally, the PSD-related dynamic permeability model is refined by incorporating the effects of imbibition resulting from the fracturing process preceding shale gas production. The developed dynamic permeability model varies with pore and fracture pressures in the shale reservoir. The fracturing process induces water blockage, water-film formation, and water-bridging phenomena in shale, requiring additional pressure inputs to counteract capillary effects in hydrophilic minerals in shale, But also increases the overall permeability from increasing permeability at larger scale pores. Unlike traditional reservoirs, the production process commences when the fracture is depleted to 1–2 MPa exceeds the pore pressure, facilitated by the high concentration of hydrophobic organic matter pores in shale, this phenomenon explains the gas production at the intial production stage. The reduction in adsorption-layer thickness resulting from fracturing impacts permeability on a nano-scale by diminishing surface diffusion and the corresponding slip flow of gas. this phenomenon increases viscous-flow permeability from enlarged flow spacing, but the increased viscous flow does not fully offset the reduction caused by adsorbed-gas diffusion and slip flow. In addition to the phenomena arising from various field conditions, PSD in shale emerges as a crucial factor in determining dynamic permeability. Furthermore, considering the same PSD in shale, under identical pore spacing, the shape factor of slit-like clay minerals significantly influences overall permeability characteristics, much more slit-shaped pores(higher shape factor) reduce the overall permeability. The dynamic permeability-assisted embedded discrete fracture model (EDFM) showed higher accuracy in predicting shale gas production compared to the original model.
Improvement of Thermal Protection in Recycled Polyolefins through Hybrid Mesoporous Silica–Antioxidant Particles
Authors: Blázquez-Blázquez Enrique , Barranco-García Rosa , Díez-Rodríguez Tamara M. , Posadas Pilar , Pérez Ernesto , Cerrada María L.
Published: January 2024

The deficient management of plastic waste has caused a serious worldwide environmental problem. Thus, one of the main challenges for the industry in the plastics sector in contributing to sustainability and a circular economy consists of providing a subsequent service life to this waste. For that purpose, the appropriate incorporation of antioxidants will play a key role in preventing or postponing the degradation of plastic waste, where the formation of radicals is initiated during its previous lifetime by the action of degrading agents. Functionalized particles, based on mesoporous MCM-41 silica with Irganox 1076, were prepared with two different protocols and were further incorporated into a material containing virgin PP and 30 wt.% of recycled PP, with the purpose of guaranteeing thermal stability during its next service life. A very significant increase in the thermal stability of the resulting composites was found, attributable to the synergistic action between the Irganox 1076 antioxidant and the MCM-41 particles. In addition, the presence of hybrid particles leads to an important nucleating effect for the crystallization of PP. Moreover, a reinforcing role was also played by these modified mesoporous silicas in the resultant systems. The presented methodology constitutes, therefore, a promising strategy for contributing to the circular economy—since the synergy between the Irganox 1076 antioxidant and MCM-41 particles was found to play an important role in the ultimate performance of recycled polyolefins.
Centrality-Based Equal Risk Contribution Portfolio
Authors: Patki Shreya , Kwon Roy H. , Lawryshyn Yuri
Published: January 2024

This article combines the traditional definition of portfolio risk with minimum-spanning-tree-based “interconnectedness risk” to improve equal risk contribution portfolio performance. We use betweenness centrality to measure an asset’s importance in a market graph (network). After filtering the complete correlation network to a minimum spanning tree, we calculate the centrality score and convert it to a centrality heuristic. We develop an adjusted variance–covariance matrix using the centrality heuristic to bias the model to assign peripheral assets in the minimum spanning tree higher weights. We test this methodology using the constituents of the S&P 100 index. The results show that the centrality equal risk portfolio can improve upon the base equal risk portfolio returns, with a similar level of risk. We observe that during bear markets, the centrality-based portfolio can surpass the base equal risk portfolio risk.
Industrial Product Surface Anomaly Detection with Realistic Synthetic Anomalies Based on Defect Map Prediction
Authors: Peng Tao , Zheng Yu , Zhao Lin , Zheng Enrang
Published: January 2024

The occurrence of anomalies on the surface of industrial products can lead to issues such as decreased product quality, reduced production efficiency, and safety hazards. Early detection and resolution of these problems are crucial for ensuring the quality and efficiency of production. The key challenge in applying deep learning to surface defect detection of industrial products is the scarcity of defect samples, which will make supervised learning methods unsuitable for surface defect detection problems. Therefore, it is a reasonable solution to use anomaly detection methods to deal with surface defect detection. Among image-based anomaly detection, reconstruction-based methods are the most commonly used. However, reconstruction-based approaches lack the involvement of defect samples in the training process, posing the risk of a perfect reconstruction of defects by the reconstruction network. In this paper, we propose a reconstruction-based defect detection algorithm that addresses these challenges by utilizing more realistic synthetic anomalies for training. Our model focuses on creating authentic synthetic defects and introduces an auto-encoder image reconstruction network with deep feature consistency constraints, as well as a defect separation network with a large receptive field. We conducted experiments on the challenging MVTec anomaly detection dataset and our trained model achieved an AUROC score of 99.70% and an average precision (AP) score of 99.87%. Our method surpasses recently proposed defect detection algorithms, thereby enhancing the accuracy of surface defect detection in industrial products.
Perceived Factors Affecting the Implementation of Occupational Health and Safety Management Systems in the South African Construction Industry
Authors: Kunodzia Rejoice , Bikitsha Luviwe Steve , Haldenwang Rainer
Published: January 2024

Although notable efforts have been made in the past to improve Occupational Health and Safety (OHS), the overall performance has not significantly improved as high-level injuries, risks, and fatalities continue to occur. Earlier studies have shown that implementing an Occupational Health and Safety Management System (OHSMS) ensures a reduction in accidents on site, which is, however, not easy due to the many challenges arising during its implementation. The research objectives were to identify, in order of importance, factors that affect the implementation of an OHSMS on construction sites and to analyse how an OHSMS can be implemented in the construction industry of the Western Cape, South Africa, using the Plan Do Check Act (PDCA) method. The research questionnaire obtained online opinions from construction professionals. The data were analysed using the Statistical Package for Social Sciences (SPSS) software version 27.0. The data were interpreted through Cronbach’s alpha coefficient, frequencies, descriptive statistics, and a multi-regression analysis. A multi-regression test was conducted to determine the relationship between internal and external factors and the implementation of an OHSMS, including the use of the PDCA method. The findings reveal that both internal and external factors affected the implementation of the OHSMS. The most important internal factors were risk control strategies, senior management commitment, and support and communication channels. The most common external factors were pressure from clients on project delivery, company reputation, OHS enforcement, and government legislation. A framework was developed to outline how an OHSMS can be implemented using the PDCA approach based on the findings from this study. The framework can be adopted by the construction industry to improve effectiveness when implementing their OHSMS.
Hate-Speech Countering by Immigrant and Pro-Immigrant Associations in Almeria (Spain)
Authors: Rodriguez Martinez Pilar , Martinez Joya Lucía , Villegas Lirola Francisco
Published: January 2024

In recent years, there has been an exponential increase in anti-immigrant hate speech on social media. Drawing on interviews with 15 immigrant associations and 11 pro-immigrant associations in the southern Spanish province of Almería, as well as digital ethnography, this article explores strategies used by immigrant and pro-immigrant associations to counter hate speech. The rise of this hate speech, disseminated mainly by far-right parties, has occurred at a time when many immigrant associations have little or no access to social media platforms. However, members of all these associations (immigrant and pro-immigrant) are aware of the perverse effects of these discourses, as they have either received them on their personal social media platforms or experienced abhorrent hate-speech attacks against their members and/or users. Despite their difficulties in navigating the “glocaline political arena”, they have participated in a number of projects and developed tools that allow them to generate a counter-discourse. We identify and explore the richness and diversity of these online campaigns and activities, highlighting the difficulties that immigrant associations—compared to pro-immigrant ones—face in navigating the glocaline political arena.
A Survey on Factors Preventing the Adoption of Automated Software Testing: A Principal Component Analysis Approach
Authors: Murazvu George , Parkinson Simon , Khan Saad , Liu Na , Allen Gary
Published: January 2024

Automated software testing is a crucial yet resource-intensive aspect of software development. This burden on resources affects widespread adoption, with expertise and cost being the primary challenges preventing adoption. This paper focuses on automated testing driven by manually created test cases, acknowledging its advantages while critically analysing its implications across various development stages that are affecting its adoption. Additionally, it analyses the differences in perception between those in nontechnical and technical roles, where nontechnical roles (e.g., management) predominantly strive to reduce costs and delivery time, whereas technical roles are often driven by quality and completeness. This study investigates the difference in attitudes toward automated testing (AtAT), specifically focusing on why it is not adopted. This article presents a survey conducted among software industry professionals that spans various roles to determine common trends and draw conclusions. A two-stage approach is presented, comprising a comprehensive descriptive analysis and the use of Principal Component Analysis. In total, 81 participants received a series of 22 questions, and their responses were compared against job role types and experience levels. In summary, six key findings are presented that cover expertise, time, cost, tools and techniques, utilisation, organisation, and capacity.
A Novel Machine Learning-Based Prediction Method for Early Detection and Diagnosis of Congenital Heart Disease Using ECG Signal Processing
Authors: Pachiyannan Prabu , Alsulami Musleh , Alsadie Deafallah , Saudagar Abdul Khader Jilani , AlKhathami Mohammed , Poonia Ramesh Chandra
Published: January 2024

Congenital heart disease (CHD) represents a multifaceted medical condition that requires early detection and diagnosis for effective management, given its diverse presentations and subtle symptoms that manifest from birth. This research article introduces a groundbreaking healthcare application, the Machine Learning-based Congenital Heart Disease Prediction Method (ML-CHDPM), tailored to address these challenges and expedite the timely identification and classification of CHD in pregnant women. The ML-CHDPM model leverages state-of-the-art machine learning techniques to categorize CHD cases, taking into account pertinent clinical and demographic factors. Trained on a comprehensive dataset, the model captures intricate patterns and relationships, resulting in precise predictions and classifications. The evaluation of the model’s performance encompasses sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve. Remarkably, the findings underscore the ML-CHDPM’s superiority across six pivotal metrics: accuracy, precision, recall, specificity, false positive rate (FPR), and false negative rate (FNR). The method achieves an average accuracy rate of 94.28%, precision of 87.54%, recall rate of 96.25%, specificity rate of 91.74%, FPR of 8.26%, and FNR of 3.75%. These outcomes distinctly demonstrate the ML-CHDPM’s effectiveness in reliably predicting and classifying CHD cases. This research marks a significant stride toward early detection and diagnosis, harnessing advanced machine learning techniques within the realm of ECG signal processing, specifically tailored to pregnant women.
2,4-D Herbicide-Induced Hepatotoxicity: Unveiling Disrupted Liver Functions and Associated Biomarkers
Authors: Martins Rafael Xavier , Carvalho Matheus , Maia Maria Eduarda , Flor Bruno , Souza Terezinha , Rocha Thiago Lopes , Félix Luís M. , Farias Davi
Published: January 2024

2,4-dichlorophenoxyacetic acid (2,4-D) is a widely used herbicide worldwide and is frequently found in water samples. This knowledge has prompted studies on its effects on non-target organisms, revealing significant alterations to liver structure and function. In this review, we evaluated the literature on the hepatotoxicity of 2,4-D, focusing on morphological damages, toxicity biomarkers and affected liver functions. Searches were conducted on PubMed, Web of Science and Scopus and 83 articles were selected after curation. Among these studies, 72% used in vivo models and 30% used in vitro models. Additionally, 48% used the active ingredient, and 35% used commercial formulations in exposure experiments. The most affected biomarkers were related to a decrease in antioxidant capacity through alterations in the activities of catalase, superoxide dismutase and the levels of malondialdehyde. Changes in energy metabolism, lipids, liver function, and xenobiotic metabolism were also identified. Furthermore, studies about the effects of 2,4-D in mixtures with other pesticides were found, as well as hepatoprotection trials. The reviewed data indicate the essential role of reduction in antioxidant capacity and oxidative stress in 2,4-D-induced hepatotoxicity. However, the mechanism of action of the herbicide is still not fully understood and further research in this area is necessary.
Jelleine, a Family of Peptides Isolated from the Royal Jelly of the Honey Bees (Apis mellifera), as a Promising Prototype for New Medicines: A Narrative Review
Authors: Lima William Gustavo , Brito Julio Cesar Moreira , Verly Rodrigo Moreira , Lima Maria Elena de
Published: January 2024

The jelleine family is a group of four peptides (jelleines I–IV) originally isolated from the royal jelly of honey bee (Apis mellifera), but later detected in some honey samples. These oligopeptides are composed of 8–9 amino acid residues, positively charged (+2 to +3 at pH 7.2), including 38–50% of hydrophobic residues and a carboxamide C-terminus. Jelleines, generated by processing of the C-terminal region of major royal jelly proteins 1 (MRJP-1), play an important biological role in royal jelly conservation as well as in protecting bee larvae from potential pathogens. Therefore, these molecules present numerous benefits for human health, including therapeutic purposes as shown in preclinical studies. In this review, we aimed to evaluate the biological effects of jelleines in addition to characterising their toxicities and stabilities. Jelleines I–III have promising antimicrobial activity and low toxicity (LD50 > 1000 mg/Kg). However, jelleine-IV has not shown relevant biological potential. Jelleine-I, but not the other analogues, also has antiparasitic, healing, and pro-coagulant activities in addition to indirectly modulating tumor cell growth and controlling the inflammatory process. Although it is sensitive to hydrolysis by proteases, the addition of halogens increases the chemical stability of these molecules. Thus, these results suggest that jelleines, especially jelleine-I, are a potential target for the development of new, effective and safe therapeutic molecules for clinical use.
Prediction of the Subgrade Soil California Bearing Ratio Using Machine Learning and Neuro-Fuzzy Inference System Techniques: A Sustainable Approach in Urban Infrastructure Development
Authors: Gowda Sachin , Kunjar Vaishakh , Gupta Aakash , Kavitha Govindaswamy , Shukla Bishnu Kant , Sihag Parveen
Published: January 2024

In the realm of urban geotechnical infrastructure development, accurate estimation of the California Bearing Ratio (CBR), a key indicator of the strength of unbound granular material and subgrade soil, is paramount for pavement design. Traditional laboratory methods for obtaining CBR values are time-consuming and labor-intensive, prompting the exploration of novel computational strategies. This paper illustrates the development and application of machine learning techniques—multivariate linear regression (MLR), artificial neural networks (ANN), and the adaptive neuro-fuzzy inference system (ANFIS)—to indirectly predict the CBR based on the soil type, plasticity index (PI), and maximum dry density (MDD). Our study analyzed 2191 soil samples for parameters including PI, MDD, particle size distribution, and CBR, leveraging theoretical calculations and big data analysis. The ANFIS demonstrated superior performance in CBR prediction with an R2 value of 0.81, surpassing both MLR and ANN. Sensitivity analysis revealed the PI as the most significant parameter affecting the CBR, carrying a relative importance of 46%. The findings underscore the potent potential of machine learning and neuro-fuzzy inference systems in the sustainable management of non-renewable urban resources and provide crucial insights for urban planning, construction materials selection, and infrastructure development. This study bridges the gap between computational techniques and geotechnical engineering, heralding a new era of intelligent urban resource management.
Mycobacterium tuberculosis Deficient in PdtaS Cytosolic Histidine Kinase Displays Attenuated Growth and Affords Protective Efficacy against Aerosol M. tuberculosis Infection in Mice
Authors: Prendergast Kelly A. , Nagalingam Gayathri , West Nicholas P. , Triccas James A.
Published: January 2024

New control measures are urgently required to control tuberculosis (TB), as the current vaccine, Bacille Calmette–Guérin (BCG), has had a limited impact on disease spread. The identification of virulence mechanisms of Mycobacterium tuberculosis is an important strategy in vaccine design, as it permits the development of strains attenuated for growth that may have vaccine potential. In this report, we determined the role of the PdtaS response regulator in M. tuberculosis virulence and defined the vaccine potential of a pdtaS-deficient strain. Deletion of pdtaS (MtbΔpdtaS) resulted in reduced persistence of M. tuberculosis within mouse organs, which was equivalent to the persistence of the BCG vaccine in the lung and liver of infected mice. However, the generation of effector CD4+ and CD8+ T cells (CD44+CD62LloKLRG1+) was similar between wild-type M. tuberculosis and MtbΔpdtaS and greater than that elicited by BCG. Heightened immunity induced by MtbΔpdtaS compared to BCG was also observed by analysis of antigen-specific IFN-γ-secreting T cell responses induced by vaccination. MtbΔpdtaS displayed improved protection against aerosol M. tuberculosis compared to BCG, which was most apparent in the lung at 20 weeks post-infection. These results suggest that the deletion of the PdtaS response regulator warrants further appraisal as a tool to combat TB in humans.
Electric Vehicle and Photovoltaic Power Scenario Generation under Extreme High-Temperature Weather
Authors: Li Xiaofei , Li Chi , Jia Chen
Published: January 2024

In recent years, with the intensification of global warming, extreme weather has become more frequent, intensifying the uncertainty of new energy output and load power, and seriously affecting the safe operation of power systems. Scene generation is an effective method to solve the uncertainty problem of stochastic planning of integrated systems of new energy generation. Therefore, this paper proposes a scenario generation and scenario reduction model of photovoltaic (PV) output and electric vehicle (EV) load power under extreme weather based on the copula function. Firstly, the non-parametric kernel density estimation method is used to fit a large number of sample data. The kernel density estimation expressions of PV and EV powers under extreme weather conditions are obtained and the corresponding goodness of fit tests are carried out. Then, a variety of joint distribution models based on the copula function are established to judge the goodness of fit of each model, and the optimal copula function is selected as the joint probability distribution function by combining the Kendall and Spearman correlation coefficients of each model. Finally, the optimal copula joint probability distribution is used to generate PV and EV power scenarios. The data of extremely hot weather in a certain province were selected for an example analysis. The results show that the output scenario obtained conforms to the correlation under this extreme weather, and has higher accuracy in reflecting the actual PV output and load power in this province under this extreme weather, which can provide a reference for reliability analyses of power systems and power grid planning.
Prospects of Passenger Vehicles in China to Meet Dual Carbon Goals and Bottleneck of Critical Materials from a Fleet Evolution Perspective
Authors: Yu Rujie , Cong Longze , Li Yaoming , Ran Chunjia , Zhao Dongchang , Li Ping
Published: January 2024

China has pledged to peak its CO2 emissions by 2030 and achieve carbon neutrality by 2060. To meet these goals, China needs to accelerate the electrification of passenger vehicles. However, the rapid development of electric vehicles may impact the supply of critical raw materials, which may hinder the low-carbon transition. Therefore, the impact of vehicle electrification on CO2 emissions and the corresponding bottlenecks in the supply of critical raw materials should be systematically considered. In this study, we developed the China Automotive Fleet CO2 Model (CAFCM) to simulate a mixed-technology passenger vehicle fleet evolution. We further assessed the impact of energy and CO2 emissions and evaluated the demand for critical battery materials. We designed three scenarios with different powertrain type penetration rates to depict the potential uncertainty. The results showed that (1) the CO2 emissions of passenger vehicles in both the operation stage and the fuel cycle can peak before 2030; (2) achieving the dual carbon goals will lead to a rapid increase in the demand for critical raw materials for batteries and lead to potential supply risks, especially for cobalt, with the cumulative demand for cobalt for new energy passenger vehicles in China being 5.7 to 7.3 times larger than China’s total cobalt reserves; and (3) the potential amount of critical material recycled from retired power batteries will rapidly increase but will not be able to substantially alleviate the demand for critical materials before 2035. China’s new energy vehicle promotion policies and key resource supply risks must be systematically coordinated under the dual carbon goals.
Evaluation of Urban Green Open Space Asset Utilisation
Authors: Andrianto Tomy , Tiafahmi Angestiwi  , Aceng Gima Sugiama
Published: January 2024

Urban Green Open Space/Ruang Terbuka Hijau Kawasan Perkotaan (RTHKP) is an essential part of the urban population ecosystem, one of which is the City of Bandung. One of the uses of RTHKP is as a city park, an alternative for tourist activities. This study aims to evaluate the use of City Parks as one of the RTHKP assets by understanding the perceptions and activity preferences of residents of Greater Bandung (Bandung City, Bandung Regency, West Bandung Regency, Cimahi) related to city parks in Bandung City. This research uses quantitative methods with descriptive analysis to understand perceptions and preferences as well as regression and correlation analysis to understand the relationship between the two variables. Two hundred sixty-five resident respondents who have visited one of the eleven city parks in Bandung City have completed the questionnaire. The result is that the City Park aspect in Bandung City can be a place for recreation and a children's playground that gets the highest score for perceptions and willingness to use public transportation, and the safety aspect still needs to be considered. Meanwhile, for activity preferences in city parks in Bandung City, the highest position is a place for refreshing, recreation and sports, and the lowest is for socialising and inviting children to play. There is a significant relationship between the perceptions and preferences of residents of Greater Bandung, especially for recreational and refreshing activities.
Nursing Students' Perceptions and Expectations of Digital Health Education
Authors:   Korean Society of Nursing Research, Yang Hwa-Mi , Jang Young-Eun
Published: January 2024

Purpose : This study aimed to explore the perceptions and expectations of nursing students regarding digital health education. Methods : We conducted focus group interviews among 10 nursing students in Seoul and Gyeonggi-do. Data were collected from July 31 to August 4, 2023. Results : The participants perceived various benefits and possibilities of digital health and expected it to help improve personalized nursing care and medical record management. Digital health may aid medical aspects, such as diagnosis, treatment selection, and predicting clinical outcomes. Participants also understood that digital health can aid patient location, emergency response, and health status monitoring. However, they recognized that patient safety and privacy are important when adopting digital health and that they need to be prepared and educated on digital security issues. Participants also recognized a need to understand the latest technologies and to develop digital competencies through digital health education, as well as the need for education in a practical environment and in using advanced technologies. Conclusion : Digital nursing competencies are considered part of the core competencies among nursing students to grow as future nursing professionals. Continual updating of their curriculum and improvement in field experience are considered the most important.
Nurse's Perceptions of Patient Safety Culture and Patient Participation Culture in Comprehensive Nursing Care Service Wards and General Wards: A Study in Small and Medium-Sized General Hospitals
Authors:   Korean Society of Nursing Research, Kim Hee Jung , Park Myong Hwa
Published: January 2024

Purpose : This study aimed to improve patient safety and nursing quality by comparing nurse's perceptions of patient safety culture and patient participation culture in comprehensive service and general ward. Methods : The research included 171 nurses from four general hospitals, with 87 working in comprehensive service wards and 84 in general wards. Data was collected through self-reporting questionnaires between September 21 and October 6, 2020. The collected data was then analyzed using SPSS/WIN 25.0 for descriptive analysis, t-test, ANOVA, Scheffé test, and Cronbach's alpha. Results : There was no significant difference in nurse's perceptions of patient safety culture between comprehensive service and general wards. However there was a statistically significant difference in their perceptions of patient participation culture. Conclusion : This findings show nurses in comprehensive service ward have more cooperative relationships with patients indicating that their attitude toward patient participation is more positive.
Experience of College Life of Adult Male Students Majoring in Nursing
Authors:   Korean Society of Nursing Research, Yeom Gye Jeong , Kim Jihyun , Park Chan Hyuk
Published: January 2024

Purpose : The purpose of this study was to explore the meaning of male students’ life experience who started studying late for nursing. Methods : The data were collected through in-depth interviews of 8 male nursing students from 3rd to 4th grade who experienced clinical practice. Giorgi's phenomenological method was used for data analysis. Results : Findings included 7 main themes and 15 themes. The main themes concerning mature male students were ‘Entering school to start a second life.’, ‘Need to adapt to unfamiliar learning methods.’, ‘Maintaining interpersonal relationships while emphasizing courtesy.’, ‘Practice in the field with a attitude.’, ‘The reactions of those around me are varied, but they support me.’, ‘Dealing with economic difficulties.’, ‘Hope for successful employment.’ Conclusion : The results of this study provide a deeper understanding of male students’ experience who started studying late for nursing. These results can be used in the development of strategies to support mature male students in nursing.
Glossite migratória benigna estudo da prevalência e da sua associação com fatores de riscos
Authors: Neuber Julia Dora Niem , Carvalho Wagner José Sousa , Arioso Letícia Sant’ana , Cardoso Camila Lopes
Published: January 2024

A glossite migratória benigna (GMB) popularmente conhecida como língua geográfica é uma condição que afeta a língua como um achado relativamente comum, apesar de sua etiologia ainda permanecer não esclarecida.  Avaliar a prevalência da glossite migratória benigna através de prontuários de pacientes que foram atendidos na Clínica de Estomatologia do Curso de Odontologia, do Centro Universitário Sagrado Coração – Unisagrado, nos últimos dez anos. Os objetivos específicos foram: investigar a prevalência da glossite migratória benigna e a associação com gênero, idade, doenças auto imunes ou outras doenças sistêmicas, uso de medicamentos e também com língua fissurada. O estudo apresentou carácter retrospectivo, documental, descritivo. Foi realizado um estudo retrospectivo através de prontuários de pacientes que foram atendidos na Clínica de Estomatologia, no período de 2012 a 2022. Após a seleção dos prontuários incluídos no estudo, foram coletadas as informações: gênero, idade, doenças autoimunes ou outras doenças sistêmicas, uso de medicamentos e também com língua fissurada. De 1024 prontuários avaliados, foram incluídos apenas 16 (1,56%). Quando levado em consideração o gênero, os resultados mostraram 9 (56,25%) mulheres e 7 homens (43.75%). Considerando o uso de medicação, 12 (75,5%) pacientes faziam o uso de pelo menos algum tipo de medicamento. Todos os pacientes pertencentes a apresentavam uma doença sistêmica. Os medicamentos para controle de problemas cardiovasculares, como a hipertensão e antidepressivos foram os mais frequentes. Neste estudo, a GMB foi muito pouco frequente, entretanto, os achados sistêmicos presentes nessa pequena amostra motivam a realização de novos estudos prospectivos.
Tendência temporal da mortalidade por alcoolismo e uso de substâncias psicoativas no Brasil no período de 2010 a 2019
Authors: Willemann Julia Hoepers , Simiano Rubens Volpato Galvani , Leverone Camila Abaurre , Araujo Luana Marcelino Mattos , De Souza Julia Correa , De Souza Ana Júlia Rocha , Correa Idalina Cardoso , Marcon Chaiana Esmeraldino Mendes
Published: January 2024

Introdução: A dependência em drogas lícitas ou ilícitas é considerada pela Organização Mundial da Saúde (OMS) uma doença e um grave problema de saúde pública no mundo todo. As drogas psicoativas são substâncias capazes de atuar a nível de Sistema Nervoso Central (SNC) e modificar seu funcionamento, gerando alterações de consciência, humor, percepção e comportamento. Objetivo: Avaliar a tendência das taxas de mortalidade em decorrência de distúrbios mentais ocasionados pelo uso de álcool e substâncias psicoativas, no Brasil no período de 2010 a 2019. Metodologia: Foi realizado estudo observacional do tipo ecológico, retrospectivo, descritivo de tendência temporal. A população estudada foi composta por indivíduos residentes no Brasil cuja morte ocorreu em decorrência de transtornos mentais e comportamentais devidos ao uso de álcool e transtornos mentais e comportamentais devidos ao uso de drogas e substâncias psicoativas. A extração doa dados foi através do DataSUS, pelo SIM. Resultados: Dos óbitos notificados, 95,71% estavam relacionados a transtornos mentais devidos ao uso do álcool, sendo os 4,28% restantes relacionados ao uso de drogas e substâncias psicoativas. Destaca-se que a região Nordeste que apresentou as maiores taxas de mortalidade em decorrência do uso de álcool com média de 3,5 mortes para cada 100 mil habitantes, no entanto, mesmo com as maiores taxas, apresentou queda gradual a cada ano nas taxas dessa região. Ressalta-se, ainda, a região Sul do Brasil apresentou as maiores taxas de mortalidade relacionadas ao uso de drogas com média nas taxas de 0,19 mortes para cada 100 mil habitantes da região. Conclusão: Diante dos dados coletados, ficou evidenciado que o alcoolismo, por sua maior prevalência, obteve a maior taxa de morte entre os anos estudados quando comparada com as mortes relacionadas ao uso de drogas, cuja taxa de mortalidade chegou a ser 18 vezes menor em comparações ano a ano. Houve, porém, uma diminuição na taxa de mortes relacionadas ao álcool, enquanto as mortes em decorrência do uso de drogas obtiveram aumento.