bluuebunny/crossref_metadata_2025 huggingface dataset:
Clustering Hyperspectral Imagery via Sparse Representation Features of the Generalized Orthogonal Matching Pursuit
Authors: Guo Wenqi , Xu Xu , Xu Xiaoqiang , Gao Shichen , Wu Zibu
Published: September 2024

This study focused on improving the clustering performance of hyperspectral imaging (HSI) by employing the Generalized Orthogonal Matching Pursuit (GOMP) algorithm for feature extraction. Hyperspectral remote sensing imaging technology, which is crucial in various fields like environmental monitoring and agriculture, faces challenges due to its high dimensionality and complexity. Supervised learning methods require extensive data and computational resources, while clustering, an unsupervised method, offers a more efficient alternative. This research presents a novel approach using GOMP to enhance clustering performance in HSI. The GOMP algorithm iteratively selects multiple dictionary elements for sparse representation, which makes it well-suited for handling complex HSI data. The proposed method was tested on two publicly available HSI datasets and evaluated in comparison with other methods to demonstrate its effectiveness in enhancing clustering performance.
The Right Triangle Model: Overcoming the Sparse Data Problem in Thermal/Optical Remote Sensing of Soil Moisture
Authors: Carlson Toby N.
Published: September 2024

The simplicity of the so-called triangle method allows estimates of evapotranspiration and soil water content to be made without ancillary data external to the image and with just a few simple algebraic calculations. Drawing on many examples in the literature showing that the pixel distribution in temperature/fractional vegetation cover (NDVI) space closely resembles a right triangle, this paper shows that adoption of a right triangle shape further simplifies the triangle model. Moreover, it allows one to mostly avoid the problem of sparse or low-resolution data. A time dimension can be included showing that trajectories inside the triangle can provide additional information on root zone soil water content. After discussing some of the ambiguities in the triangle method, and the advantageous properties of the right triangle, a proposal is made to illuminate the relationship between thermal/optical measurements and root zone water content within the right triangle framework.
Understanding University Students’ Foreign Language Learning Attitudes: An Analysis Based on Stereotypes
Authors: Güntaş Işık Selime , Aslantürk Altıntuğ Fatma , Süzek Birkollu Sibel , Güneyli Ahmet
Published: September 2024

The study aims to understand university students’ perceptions of stereotypes in foreign language learning in Cyprus, a multilingual and multicultural island. The goal is to comprehend how stereotypes impact foreign language education, enabling educators to tailor teaching environments and methodologies accordingly. The research question probes the extent and the influencing variables of stereotypes held by students in Cyprus during their language learning journey. This quantitative descriptive study involved 832 students from various faculties of a private North Cyprus university during the 2021–2022 academic year. A sample of 550 students, comprising 269 males and 281 females, was randomly selected. The stereotyped thought scale for a foreign language, a tool developed by Ünal in 2015 with 42 items across 8 sub-dimensions, was employed to gauge students’ stereotypical thoughts. The study’s results revealed an average score of 2.99 out of 5 on the scale, indicating that students’ stereotyped thinking falls within the average range. Notably, several variables, including gender, age, education, family, and language proficiency, significantly influence the stereotypes students hold during their language learning process.
Women and Leadership: A Case of the Kenyan and South African Banking Sector
Authors: Genga Cheryl Akinyi , Babalola Sunday Samson
Published: September 2024

Throughout the history of management theories, masculine ideals have dominated the development of organisational leadership structures, often leading to a belief in the inherent superiority of men in leadership roles. Despite progress, many organisations still operate under the assumption that women are somehow deficient compared to men in leadership capabilities. The research objective was to investigate the difficulties Black African women encounter in leadership positions in Kenyan and South African banks, specifically concerning how society views women in leadership roles. The study conducted semi-structured interviews and focus groups involving 41 Black African women managers from the banking sectors of both countries, employing an inter-categorical intersectionality approach. The research revealed a perceived lack of fit for top executive leadership positions among African-Black women. A comparison between masculine and feminine leadership styles underscored the gendered sex-role stereotypes that hindered the advancement of Black African women into top executive roles within the banking sector. In summary, the findings emphasise that, as long as ‘think manager, think male’ persists in leadership, Black African women will continue to encounter obstacles in attaining top executive positions within the banking sectors of Kenya and South Africa. The study’s practical implications are that it emphasises the understanding of women and leadership and its role as an obstacle for Black women managers in the Kenyan and South African banking sectors. The originality of this study is that it contributes to the understanding of women and leadership literature in the banking sectors of Kenya and South Africa, as well as sub-Saharan African countries.
Structural Disadvantage in Housing Opportunities
Authors: de Noronha Nigel
Published: September 2024

This paper discusses the ways that race and migration have shaped the housing opportunities people experience in England. It explores the historical development of policy and practice that has shaped racial inequalities in housing. It argues that the violence created by national and local state-supported housing policies has disproportionately affected racialised minorities, as has the slow violence generated by the neglect and stigmatisation of working-class housing. In turn, this has provided the justification for clearances and the remaking of space for those with the money to invest in the financialisation of land and housing through dispossession and denial of the right to safe, secure, and affordable housing. This analysis will be used as a basis to propose ways in which housing research can develop a coherent, critical perspective to race and migration and develop an alternative discourse to challenge the dominant market-driven, individualistic narratives. Adopting a critical approach allows researchers to move beyond the logic of housing policies at national and local levels to analyse and propose action to address persistent racial inequalities in housing.
Prevalence and Factors Associated with Mental Health Complaints in Japanese Collegiate Athletes
Authors: Kimura Takeshi , Mącznik Aleksandra , Kinoda Akira , Yamada Yuichi , Muramoto Yuki , Katsumata Yoshinori , Sato Kazuki
Published: September 2024

Investigations into mental health epidemiology in various cultural contexts were one of the main recommendations by the recent consensus statement on mental health in athletes, but the evidence in different sporting populations is rising slowly. This study aimed to investigate the prevalence of mental health complaints in Japanese collegiate athletes. The online survey was sent to the Japanese collegiate athletes associated with UNIVAS asking about the mental health complaints experienced during their sporting careers. Out of 10,999 athletes, 269 (2.4%) reported at least one complaint. Mental health complaints were more prevalent in female (3.6%) than male (1.5%) athletes. Skill sports had the highest prevalence (4.1%) of mental health complaints, and power sports had the lowest prevalence (1.5%) of mental health complaints. This study found a very low prevalence of self-reported mental health complaints in Japanese collegiate athletes. Preventive efforts should focus on monitoring early symptoms (rather than diagnoses), especially in skill sports and female athletes. Anxiety (38%) and depression (35%) were the most reported complaints and should be targeted first.
Development of an Active Transportation Framework Model for Sustainable Urban Development
Authors: Papageorgiou George N. , Tsappi Elena
Published: September 2024

Active transportation, with simple mobility modes such as walking and cycling, could be pivotal in addressing multiple sustainability challenges related to socio-economic, environmental, and public health issues. This paper investigates the facilitators for active transportation and assesses its impact on health, well-being, and urban sustainability. As a result, a multidimensional conceptual framework is developed to analyze the determinants influencing individuals’ propensity to engage in active transportation and thereby lead to a sustainable, high-quality way of life. Through an extensive review of the relevant literature, key elements for active transportation, accessibility, and social inclusion are identified, and their potential impact on urban health and sustainability is investigated. Findings suggest that interrelationships between factors such as enhanced infrastructure, safety measures, and improved urban accessibility would significantly encourage active transportation usage. The proposed framework argues for a positive association between active transportation and improved health outcomes, contributing to sustainable urban environments. Furthermore, it is advocated that changing attitudes and mindsets could be achieved by urban planning and policy reforms supporting active transportation, as well as by effectively communicating the multiple benefits for individuals, the economy, and society at large. Comprehensive policy strategies, which include improvements in urban design and increased public awareness of the benefits of active transportation, could establish a paradigm shift for promoting a higher quality of life through a healthy, active, and sustainable urban lifestyle.
Investigating the Potential of Microbially Induced Carbonate Precipitation Combined with Modified Biochar for Remediation of Lead-Contaminated Loess
Authors: He Pengli , Guo Jinjun , Zhang Shixu
Published: September 2024

Lead (Pb) contamination in loess poses a significant environmental challenge that impedes sustainable development. Microbially induced carbonate precipitation (MICP) is an innovative biomimetic mineralization technology that shows considerable promise in remediating soil contaminated with heavy metals. However, the toxicity of lead ions to Bacillus pasteurii reduces the efficiency of mineralization, subsequently diminishing the effectiveness of remediation. Although biochar can immobilize heavy metal ions, its adsorption instability presents a potential risk. In this study, we first compared the pH, electrical conductivity (EC), unconfined compressive strength (UCS), permeability coefficient, and toxicity leaching performance of lead-contaminated loess specimens remediated using biochar (BC), red mud (RM), red-mud-modified biochar (MBC), and MICP technology. Additionally, we evaluated the mechanism of MICP combined with varying amounts of MBC in remediating lead-contaminated loess combing Zeta potential, X-ray diffraction (XRD) analyses, and scanning electron microscopy (SEM) tests. The results showed that MICP technology outperforms traditional methods such as RM, BC, and MBC in the remediation of lead-contaminated loess. When MICP is combined with MBC, an increase in MBC content results in a higher pH (8.71) and a lower EC (232 us/cm). Toxic leaching tests reveal that increasing MBC content reduces the lead leaching concentration in loess, with optimal remediation being achieved at 5% MBC. Microscopic analysis indicates that the remediation mechanisms of MICP combined with MBC involve complexation, electrostatic adsorption, ion exchange, and precipitation reactions. The synergistic application of MICP and MBC effectively adsorbs and immobilizes lead ions in loess, enhancing its properties and demonstrating potential for pollution remediation and engineering applications.
Developing a Culture of Safety for Sustainable Development and Public Health in Manufacturing Companies—A Case Study
Authors: Kabiesz Patrycja , Tutak Magdalena
Published: September 2024

One of the most important values in human life is health and safety. This is reflected in the Sustainable Development Goals (SDG3, SDG8), which were presented by the United Nations in 2015. These goals emphasize the importance of ensuring healthy lives, promoting well-being for all, and fostering inclusive and sustainable economic growth through decent work and safe working conditions. Taking into account the importance of issues related to safety, including occupational safety and human health, research was carried out to examine the impact of the development of a safety culture during employees’ work on improving public health. In order to conduct the research, a survey questionnaire was developed, consisting of 20 questions relating to 10 attributes of safety culture. The research surveys were carried out among 363 employees in a production enterprise, and an interview questionnaire was administered to 3 employees of the Occupational Health and Safety Service of this enterprise. The results revealed that the enterprise’s employees rate the level of safety culture very highly. Along with the improvement of working conditions in the enterprise, the level of safety increases, the number of accidents at work decreases, and thus the protection of employee health is higher. Therefore, a high level of safety culture is correlated with a high value attached to the health and life of employees, and this, in turn, affects public health. Moreover, fostering a strong safety culture aligns with the principles of sustainable development, contributing to long-term societal well-being and aligning with global goals for responsible and ethical growth.
Multilevel Middle Point Clamped (MMPC) Converter for DC Wind Power Applications
Authors: Karni Awais , Beik Omid , Gholamian Mahzad , Homaeinezhad Mahdi , Manzoor Muhammad Owais
Published: September 2024

This manuscript introduces a novel multilevel middle point clamped (MMPC) DC-DC converter and its associated switching scheme aimed at maintaining the desired medium-voltage DC (MVDC) collector grid within offshore all-DC wind farms. Building upon previous work by the authors, which proposed an all-DC structure serving as a benchmark system, this study explores the application of the MMPC DC-DC converter within this framework. Within the all-DC wind generation system, a 9-phase hybrid generator (HG) integrated into the wind turbine is linked to the MVDC collector grid through an AC-DC stage, which is a passive rectifier. This passive rectifier offers elevated voltage ratings and protection against back power flow. The conventional neutral point clamped (NPC) converter concept has been thoroughly investigated and expanded upon to develop the proposed MMPC DC-DC converter. The proposed MMPC DC-DC converter integrates boosting capabilities, facilitating the connection of the generator’s rectified voltage to the MVDC collector grid while regulating variable rectified voltage to a fixed MVDC collector grid voltage. The MVDC collector grid is further interconnected with high-voltage DC (HVDC) through a DC-DC converter situated in an offshore substation. This paper further provides a comprehensive overview of the proposed MMPC DC-DC converter, detailing its operational modes and corresponding switching schemes. Through an in-depth examination of operational modes, duty cycles for each switch and mode are defined, subsequently establishing the relationship between rectified input voltage and MVDC output voltage for the MMPC DC-DC converter. Utilizing the middle point clamped architecture, this innovative converter offers several advantages, including low ripple voltage, a modular structure, and reduced switching stress because of the multilevel voltage and the incorporation of a hard point, which also facilitates the capacitor voltage balancing. Finally, the effectiveness of the proposed converter is evaluated via simulation studies of a wind turbine conversion system utilizing two cascaded MMPC DC-DC converters operating under variable input voltage conditions. The simulations confirm its efficacy, supported by promising results, and validating its performance.
Decoupling Analysis between Socio-Economic Growth and Air Pollution in Key Regions of China
Authors: Wei Manru , Chuai Xiaoming , Li Yisai , Han Jingwen , Zhang Chunxia
Published: September 2024

The coordinated development of atmospheric pollution and socio-economic growth plays a core role in the sustainable development of cities and regions. The relationship between socio-economic growth and air pollution can be described using decoupling analysis. The seven key regions of China (168 cities), including Beijing–Tianjin–Hebei and its surrounding areas (BTHSR), the Yangtze River Delta region (YRDR), the Fen-Wei Plain (FWP), the Chengdu–Chongqing region (CCR), the urban agglomeration of the middle reaches of the Yangtze River (MLRYR), the Pearl River Delta region (PRDR), and other provincial capitals and municipalities with specialized plans (OPCCSP) were taken as targets to investigate the spatiotemporal evolution characteristics of AQI values and PM2.5 concentrations from 2014 to 2022. Then, the decoupling relationship between the AQI/PM2.5 and the socio-economic growth index (SEGI) in these key regions was deeply researched by the Tapio decoupling model. The main results were as follows: (1) Although the continuous improvement in air quality was observed in these seven key regions in China, the PM2.5 concentration in the BTHSR and FWP was still higher than 35 μg·m−3. The AQI showed a spatial pattern of high in the north and low in the south, and the distribution of PM2.5 in China was high in the east and low in the west. (2) The decoupling degree between air pollution and socio-economic growth was relatively high in the PRDR and YRDR. In contrast, the degree of decoupling was poor in the FWP and OPCCSP. The decoupling states were primarily influenced by industrial structure, energy consumption, and urbanization. (3) The decoupling of air pollution from socio-economic growth was in a strong decoupling state throughout the majority of the study period, achieving a comparatively ideal decoupling state in 2018. However, the overall decoupling states of the seven regions were not sustainable, and the decoupling stability was relatively poor. During the research period, the decoupling state between socio-economic growth and air pollution changed and was unstable.
Two-Step Macromolecule Separation Process with Acid Pretreatment and High-Shear-Assisted Extraction for Microalgae-Based Biorefinery
Authors: Kim Donghyun , Kang Seul-Gi , Chang Yong Keun , Kwak Minsoo
Published: September 2024

A simple two-stage extraction and recovery method for macromolecules from microalgae biomass, termed CASS (concentrating the microalgae solution, acid pretreatment, high-shear-assisted lipid extraction, and separation), was developed. This method effectively processed the wet biomass of Chlorella sp. ABC-001 at a moderately low biomass concentration (50 g/L). The optimal conditions were acid pretreatment with 5 wt.% H2SO4 at 100 °C for 1 h, followed by high-shear extraction using hexane at 3000 rpm for 30 min. The acid pretreatment hydrolyzed carbohydrates and phospholipids, disrupting the cell wall and membrane, while high-shear mixing enhanced mass transfer rates between solvents and lipids, overcoming the hydraulic barrier at the cell surface. Within 10 min after completing the process, the extraction mixture achieved natural phase separation into water, solvent, and biomass residue layers, each enriched with carbohydrates, lipids, and proteins, respectively. The CASS process demonstrated high esterifiable lipid yields (91%), along with substantial recovery of glucose (90%) and proteins (100%). The stable phase separation prevented emulsion formation, simplifying downstream processing. This study presents the results on cell disruption, optimal acid treatment concentration, and high-shear mixing to achieve macromolecule separation, expanding the lipid-centric microalgal process to a comprehensive biorefinery concept.
Promoting Sustainable Development of Coal Mines: CNN Model Optimization for Identification of Microseismic Signals Induced by Hydraulic Fracturing in Coal Seams
Authors: Li Nan , Zhang Yunpeng , Zhou Xiaosong , Sun Lihong , Huang Xiaokai , Qiu Jincheng , Li Yan , Wang Xiaoran
Published: September 2024

Borehole hydraulic fracturing in coal seams can prevent dynamic coal mine disasters and promote the sustainability of the mining industry, and microseismic signal recognition is a prerequisite and foundation for microseismic monitoring technology that evaluates the effectiveness of hydraulic fracturing. This study constructed ultra-lightweight CNN models specifically designed to identify microseismic waveforms induced by borehole hydraulic fracturing in coal seams, namely Ul-Inception28, Ul-ResNet12, Ul-MobileNet17, and Ul-TripleConv8. The three best-performing models were selected to create both a probability averaging ensemble CNN model and a voting ensemble CNN model. Additionally, an automatic threshold adjustment strategy for CNN identification was introduced. The relationships between feature map entropy, training data volume, and model performance were also analyzed. The results indicated that our in-house models surpassed the performance of the InceptionV3, ResNet50, and MobileNetV3 models from the TensorFlow Keras library. Notably, the voting ensemble CNN model achieved an improvement of at least 0.0452 in the F1 score compared to individual models. The automatic threshold adjustment strategy enhanced the identification threshold’s precision to 26 decimal places. However, a continuous zero-entropy value in the feature maps of various channels was found to detract from the model’s generalization performance. Moreover, the expanded training dataset, derived from thousands of waveforms, proved more compatible with CNN models comprising hundreds of thousands of parameters. The findings of this research significantly contribute to the prevention of dynamic coal mine disasters, potentially reducing casualties, economic losses, and promoting the sustainable progress of the coal mining industry.
An Enhanced Continuation Power Flow Method Using Hybrid Parameterization
Authors: Kim Haelee , Woo Hyeon , Yoon Yeunggurl , Kim Hyun-Tae , Kim Yong Jung , Kang Moonho , Zhang Xuehan , Choi Sungyun
Published: September 2024

The rapid integration of renewable energy sources and the increasing complexity of modern power systems urge the development of advanced methods for ensuring power system stability. This paper presents a novel continuation power flow (CPF) method that combines two well-known parameterization techniques: natural parameterization and arc-length parameterization. The proposed hybrid approach significantly improves computational efficiency, reducing processing time by 32.76% compared to conventional methods while maintaining high accuracy. The method enables faster and more reliable stability assessments by efficiently managing the complexities and uncertainties, particularly in grids with high penetration of renewable energy.
An Analysis of the Relationship Linking Immersive Tourism Experiencescape and Emotional Experience to Tourists’ Behavioral Intentions
Authors: Zhou Mengzhen , Wang Xiaofeng
Published: September 2024

The sustainable development of tourism is a critical issue, and immersive tourism has emerged as a key market trend that significantly contributes to this goal. Experiencescape, a vital component of immersive tourism, plays a crucial role in shaping tourists’ experience and promoting sustainability within the tourism industry. Taking Chang’an Twelve Hours Theme Block as the research object, this paper investigates the composition and impact of immersive tourism experiencescape by utilizing grounded theory and hierarchical regression analysis on data derived from online reviews and tourist surveys. The findings reveal that immersive tourism experiencescape is divided into two main categories: physical and interpersonal. The physical experiencescape consists of three dimensions: functional facilities, thematic atmosphere, and basic environment. The interpersonal experiencescape, on the other hand, includes tourism performances, host-guest interaction, and personal service. The study demonstrates that immersive tourism experiencescape exerts a significant positive influence on tourists’ behavioral intentions, with emotional experience serving as a partial mediator in this relationship. These insights offer valuable theoretical and practical implications. They provide a perspective for enhancing the sustainability of tourism by improving the quality of immersive experiences.
The Relationship between Cardiomyocyte Action Potentials and Ion Concentrations: Machine Learning Prediction Modeling and Analysis of Spontaneous Spiral Wave Generation Mechanisms
Authors: Bai Jing , Zhang Chunfu , Liang Yanchun , Tavares Adriano , Wang Lidong , Gu Xue , Meng Ziyao
Published: September 2024

The changes in cardiomyocyte action potentials are related to variations in intra- and extracellular ion concentrations. Abnormal ion concentrations can lead to irregular action potentials, subsequently affecting wave propagation in myocardial tissue and potentially resulting in the formation of spiral waves. Therefore, timely monitoring of ion concentration changes is essential. This study presents a novel machine learning classification model that predicts ion concentration changes based on action potential variation data. We conducted simulations using a single-cell model, generating a dataset of 850 action potential variations corresponding to different ion concentration changes. The model demonstrated excellent predictive performance, achieving an accuracy of 0.988 on the test set. Additionally, the causes of spontaneous spiral wave generation in the heart are insufficiently studied. This study presents a new mechanism whereby changes in extracellular potassium ion concentration leads to the spontaneous generation of spiral waves. By constructing composite myocardial tissue containing both myocardial and fibroblast cells, we observed that variations in extracellular potassium ion concentration can either trigger or inhibit cardiomyocyte excitation. We developed three tissue structures, and by appropriately adjusting the extracellular potassium ion concentration, we observed the spontaneous generation of single spiral waves, symmetrical spiral wave pairs, and asymmetrical double spiral waves.
Ensemble Learning for Nuclear Power Generation Forecasting Based on Deep Neural Networks and Support Vector Regression
Authors: Simão Jorge Gustavo Sandoval , Coelho Leandro dos Santos
Published: September 2024

Forecasting nuclear energy production is essential for market operations such as security, economic efficiency, resource optimization, grid stability, and the integration of renewable energy sources. Forecasting approaches allow nuclear power plants to operate consistently, contributing to the overall reliability and long-term viability of the energy system. It is noted that energy systems researchers are increasingly interested in machine learning models used to face the challenge of time series forecasting. This study evaluates a hybrid ensemble learning of three time series forecasting models including least-squares support vector regression, gated recurrent unit, and long short-term memory models applied to nuclear power time series forecasting on the dataset of French power plants from 2009 to 2020. Furthermore, this research evaluates forecasting results in which approaches are directed towards the optimized RreliefF (Robust relief Feature) selection algorithm using a hyperparameter optimization based on tree-structured Parzen estimator and following an ensemble learning approach, showing promising results in terms of performance metrics. The suggested ensemble learning model, which combines deep learning and the RreliefF algorithm using a hold-out, outperforms the other nine forecasting models in this study according to performance criteria such as 75% for the coefficient of determination, a root squared error average of 0.108, and an average absolute error of 0.080.
Health Risk Assessment of Heavy Metals in Agricultural Soils Based on Multi-Receptor Modeling Combined with Monte Carlo Simulation
Authors: Wu Yundong , Xia Yan , Mu Li , Liu Wenjie , Wang Qiuying , Su Tianyan , Yang Qiu , Milinga Amani , Zhang Yanwei
Published: September 2024

The spatial characteristics, pollution sources, and risks of soil heavy metals were analyzed on Hainan Island. The results showed that the heavily polluted points accounted for 0.56%, and the number of mildly and above polluted points accounted for 15.27%, respectively, which were mainly distributed in the northern part of the study area. The principal component analysis–absolute principal component score–multiple linear regression (APCS-MLR) and the positive matrix factorization (PMF) revealed four sources of heavy metals: agricultural pollution sources for cadmium, (Cd), industrial and mining pollution sources for arsenic, (As), transportation pollution sources for zinc and lead (Zn and Pb), and natural pollution sources for chromium, nickel, and copper (Cr, Ni, and Cu). The human health risk assessment indicated that the average non-carcinogenic risk (HI) for both adults and children was within the safe threshold (<1), whereas Cr and Ni posed a carcinogenic risk (CR) to human health. In addition, the total non-carcinogenic risk (THI) indicated that heavy metals posed a potential non-carcinogenic risk to children, while the total carcinogenic risk (TCR) remained relatively high, mainly in the northern part of the study area. The results of the Monte Carlo simulation showed that the non-carcinogenic risk (HI) for all heavy metals was <1, but the total non-carcinogenic risk index (THI) for children was >1, indicating a potential health risk above the safe threshold. Meanwhile, nearly 100% and 99.94% of the TCR values exceeded 1 × 10−4 for children and adults, indicating that Cr and Ni are priority heavy metals for control. The research results provide the necessary scientific basis for the prevention and control of heavy metals in agricultural soils.
Multi-Walled Carbon Nanotubes Accelerate Leukaemia Development in a Mouse Model
Authors: Wang Qingqing , Han Jingdan , Wei Mujia , Miao Huikai , Zhang Min , Wu Biao , Chen Yao , Zheng Yanwen , Gale Robert , Yin Bin
Published: September 2024

Inflammation is associated with an increased risk of developing various cancers in both animals and humans, primarily solid tumors but also myeloproliferative neoplasms (MPNs), myelodysplastic syndromes (MDS), and acute myeloid leukemia (AML). Multi-walled carbon nanotubes (MWCNTs), a type of carbon nanotubes (CNTs) increasingly used in medical research and other fields, are leading to a rising human exposure. Our study demonstrated that exposing mice to MWCNTs accelerated the progression of spontaneous MOL4070LTR virus-induced leukemia. Additionally, similar exposures elevated pro-inflammatory cytokines such as interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α and induced reactive oxygen species (ROS) in a murine macrophage cell line. These effects were significantly reduced in immunodeficient mice and when mice were treated with methoxypolyethylene glycol amine (PEG)-modified MWCNTs. These findings underscore the necessity of evaluating the safety of MWCNTs, particularly for those with hematologic cancers.
Patterns of Transmitted Drug Resistance Mutations and HIV-1 Subtype Dynamics in ART-Naïve Individuals in Veneto, Italy, from 2017 to 2024
Authors: Geremia Nicholas , Basso Monica , De Vito Andrea , Scaggiante Renzo , Giobbia Mario , Battagin Giuliana , Dal Bello Federico , Giordani Maria Teresa , Nardi Stefano , Malena Marina , Cattelan Annamaria , Parisi Saverio Giuseppe
Published: September 2024

This study investigates the prevalence and patterns of transmitted drug resistance mutations (TDRMs) and HIV-1 subtypes among antiretroviral therapy (ART) naïve individuals in Veneto, Italy, from 2017 to 2024. This research aims to understand the dynamic landscape of TDRMs and HIV-1 genetic diversity to inform treatment strategies effectively. We included all adult ART-naïve people with HIV (PWH) from seven infectious disease units in Veneto, Italy. We collected the genotypic resistance testing conducted to predict drug susceptibility and subtype distribution using the Stanford HIVdb algorithm. We included 762 PWH, showing a slight but statistically significant decline in the B subtype among Italian PWH (p = 0.045) and an increase in non-B subtypes among foreigners, though it was not statistically significant (p = 0.333). The most frequent mutations were in Non-nucleoside Reverse Transcriptase Inhibitors (NNRTIs), especially in non-B subtypes, with a notable rise from 10.7% in 2017–2019 to 15.5% in 2020–2024. Notably, TDRMs were consistently detected, highlighting an ongoing challenge despite the stable prevalence observed over the years. In addition, the data revealed a concerning rise in mutations against newer drug classes, such as integrase inhibitors. Conclusively, the study underscores the necessity of continuous surveillance of HIV subtypes and resistance patterns to adapt ART regimens optimally. Despite the stable levels of drug resistance, the emergence of resistance against newer drugs necessitates ongoing vigilance and possible adjustment in treatment protocols to enhance clinical outcomes and manage HIV drug resistance effectively.
Israeli Acute Paralysis Virus Is an Emerging Pathogen Contributing to Brood Disease of Apis cerana
Authors: Xie Yanling , Wang Shuai , Liu Yao , Deng Jie , Su Xiaoling , Huang Zhichu , Zheng Huoqing
Published: September 2024

Larval mortality is the primary symptom of diseased Apis cerana colonies, often attributed to sacbrood virus (SBV) and Melissococcus plutonius. However, the impact of other common honeybee viruses is frequently overlooked, and their pathogenicity to A. cerana remains poorly understood. To investigate the causes of the increasing disease incidence in A. cerana brood, we conducted an epidemiological survey, collecting 70 samples from 19 sites across nine provinces in China. Furthermore, we examined the pathogenicity of Israeli acute paralysis virus (IAPV) in A. cerana brood through artificial inoculation experiments. Our results demonstrate that, besides SBV and M. plutonius, the infection rate and viral load of IAPV in diseased brood are significantly high. Brood artificially inoculated with high concentrations of IAPV exhibited a significant increase in mortality and displayed clinical symptoms similar to those observed in naturally infected colonies. Moreover, a limited resistance to IAPV was observed in A. cerana brood, with some individuals able to restrict viral proliferation. Our study highlights the previously unrecognized pathogenicity of IAPV to A. cerana brood, demonstrating that IAPV poses a significant threat similar to SBV and M. plutonius. We emphasize that IAPV should be recognized as an emerging pathogen causing brood disease in A. cerana and managed accordingly in beekeeping practices.
Outcomes of Corneal Transplantation for Herpetic Keratitis: A Narrative Review
Authors: Nardella Michele , Yu Angeli Christy , Busin Massimo , Rizzo Roberta , Zauli Giorgio
Published: September 2024

Herpes simplex virus (HSV) is one of the most common etiologic agents of corneal disease and a significant cause of corneal blindness worldwide. Although most cases can be successfully managed with medical therapy, HSV keratitis associated with visually significant stromal scarring often requires corneal transplantation for visual rehabilitation. While penetrating keratoplasty (PK) represented the traditional keratoplasty technique, the past few decades have seen a shift towards lamellar keratoplasty procedures, including deep anterior lamellar keratoplasty and mushroom keratoplasty. This paper describes the current surgical techniques and perioperative antiviral prophylaxis regimen for herpetic keratitis and reviews their postoperative clinical outcomes.
Automated Classification System Based on YOLO Architecture for Body Condition Score in Dairy Cows
Authors: Dandıl Emre , Çevik Kerim Kürşat , Boğa Mustafa
Published: September 2024

Body condition score (BCS) is a common tool used to assess the welfare of dairy cows and is based on scoring animals according to their external appearance. If the BCS of dairy cows deviates from the required value, it can lead to diseases caused by metabolic problems in the animal, increased medication costs, low productivity, and even the loss of dairy cows. BCS scores for dairy cows on farms are mostly determined by observation based on expert knowledge and experience. This study proposes an automatic classification system for BCS determination in dairy cows using the YOLOv8x deep learning architecture. In this study, firstly, an original dataset was prepared by dividing the BCS scale into five different classes of Emaciated, Poor, Good, Fat, and Obese for images of Holstein and Simmental cow breeds collected from different farms. In the experimental analyses performed on the dataset prepared in this study, the BCS values of 102 out of a total of 126 cow images in the test set were correctly classified using the proposed YOLOv8x deep learning architecture. Furthermore, an average accuracy of 0.81 was achieved for all BCS classes in Holstein and Simmental cows. In addition, the average area under the precision–recall curve was 0.87. In conclusion, the BCS classification system for dairy cows proposed in this study may allow for the accurate observation of animals with rapid declines in body condition. In addition, the BCS classification system can be used as a tool for production decision-makers in early lactation to reduce the negative energy balance.
A Reference Interval for CT-Based Liver Volume in Dogs without Hepatic Disease
Authors: Nishi Reo , Moore George , Murakami Masahiro
Published: September 2024

In both human and veterinary medicine, computed tomography (CT) volumetry provides a quantitative and accurate measure of liver volume. While CT volumetry is recognized as a useful method for assessing liver volume in dogs, a statistically significant reference interval for liver volume in dogs with no history of hepatic disease has not been reported. The purpose of the present study was to define a reference interval for liver volume with no history of hepatic disease using CT volumetry. Medical records from 2 June 2020 to 25 July 2022 were retrospectively reviewed, including 121 dogs that underwent abdominal CT scans and had no history of hepatic disease. Liver volumes were measured using CT volumetry and normalized by body weight. The median of normalized CT-based liver volume in 121 dogs was 22.2 cm3/kg. Based on these data, a weight-based reference interval lower limit of 11.1–15.5 (90% confidence interval [CI]) to an upper limit of 31.9–42.6 (90% CI) cm3/kg for CT-based liver volume was defined in dogs without hepatic disease. This study provides an accurate assessment of liver volume changes in dogs with various hepatic diseases.
Effects of Formulated Pellet Feed or Live Fish Food on the Intestinal and Aquaculture Water Microbial Communities in Goldfish, Carassius auratus
Authors: Huang Yi , Huang Qiang , Huang Zhiqiu , Hong Yuhang
Published: September 2024

This study investigates the impact of different diets on fish growth and bacterial community structure present in the intestine of goldfish (Carassius auratus) and their aquaculture water under recirculating water conditions. We assumed that different types of diet would form different intestinal microbiota that may affect host growth. Using Illumina MiSeq high-throughput sequencing, we analyzed bacterial communities in goldfish fed with formulated pellet feed, Tubifex worms (Limnodrilus hoffmeisteri), and an alternating diet of both. Over a 14-day feeding trial, no significant differences in juvenile goldfish growth were observed between groups. After 7 days, diet changes significantly influenced the abundance and diversity of intestinal bacteria, with the alternating diet notably enhancing bacterial diversity in both the intestines and water. However, these differences in bacterial diversity decreased by day 14. The results indicate that diet type affects microbial community diversity in the intestines and water of goldfish, and that goldfish intestines maintain a stable core bacterial community structure. This highlights the potential for optimizing diet types to enhance microbial health and stability in aquaculture systems and, in addition, provides an important scientific basis for alternative diets in goldfish aquaculture in the industry.
A novel feedforward narrow-broadband hybrid active noise control system for excavator interior noise control
Authors: Luo Ting , Sun Menglei , Liu Hao , Wang Yongliang , Shao Jiongyang , Yang Xingyao
Published: September 2024

Excavator interior noise is a mixture of engine noise and impulsive noise produced by working device. Hybrid narrow-broadband active noise control (HANC) systems can efficiently eliminate the traditional mixed broad-narrowband noise. However, these HANC systems have drawbacks such as
high computational complexity, unable to cope with impulsive noise and inability to obtain the best performance due to parameter selection method. To solve these problems, a novel feedforward narrow broadband HANC system consisting of four subsystems, namely, sinusoidal noise canceller (SNC)
subsystem, robust broadband active noise control (RBANC) subsystem, delay narrowband active noise control (DNANC) subsystem, and supporting error calculating subsystem, is proposed. Combining the advantages of delayed least mean square algorithm in DNANC subsystem and Versoria criterion-based
filtered-x least mean square algorithm in RBANC subsystem, both the computational efficiency and the robustness when encountering impulsive noise of the proposed HANC system are efficiently improved. In addition, the performance of the proposed HANC system is further improved by changing the
key parameters selection method form trial-and-error method to improved particle swarm optimization (IPSO) algorithm with active factor. Both the superiority of the proposed HANC system over existing counterparts and the advantage of the IPSO algorithm with active factor in determining the
key parameters are demonstrated by extensive simulations. Real-time HANC experiments in semi-anechoic chamber based on measured excavator interior mixed noise are conducted in this article. Experimental results illustrate that the proposed HANC system achieves good noise elimination performance
and also being robust when encountering impulsive noise.
Penerapan Metode Vikor Untuk Menentukan Kelayakan Penyewa Tempat Usaha Pada UIN Bukittinggi
Authors: Resnawita  , Yuhandri Y , Sumijan
Published: September 2024

Seiring kemajuan teknologi yang  berkembangan pesat, mendorong lahirnya inovasi-inovasi baru untuk memenuhi kebutuhan dunia kerja dan sebagai alat bantu manusia. Penggunaan teknologi dalam mengelola sebuah unit usaha kampus akan membantu instansi dalam melakukan  pekerjaannya. Unit usaha kampus merupakan bagian penunjang pembelajaran dan pelayanan kepada mahasiswa dan Masyarakat. Unit ini biasanya bertugas untuk mengelola pendapatan dan pengeluaran, mengembangkan strategi keuangan, mengelola layanan katering, toko buku, kantin,tempat parkir, serta menjalankan berbagai jenis usaha lainnya yang terkait dengan kebutuhan mahasiswa dan staf kampus. Pengelolan unit usaha kampus akan membutuhkan banyak pertimbangan untuk megelola unit usaha kampus seperti pengambilan keputusan untuk penyewa tempat usaha atau kantin yang sesuai dengan syarat yang terdapat dalam perguruan tinggi dalam pengambilan keputusan terdapat beberapa faktor ataupun kriteria yang diperlukan agar keputusan yang nantinya diperoleh sesuai dengan syarat yang dibutuhkan oleh unit usaha kampus. Sehingga penggunaan teknologi dibutuhkan untuk mepermudah kampus dalam menentukan keputusan yang akan diperoleh. Penelitian ini bertujuan untuk memberikan rekomendasi kelayakan penyewa tempat usaha di UIN Bukittinggi. Metode penelitian yang digunakan dalam penelitian adalah metode VIKOR (Visekriterijumsko Kompromisno Rangiranje). Data yang digunakan dalam penelitian merupakan data penyewa tempat usaha UIN Bukittinggi. Terdapat 5 kriteria penilaian dan 10 data penyewa yang digunakan dalam penelitian. Dari hasil perangkingan didapatkan hasil bahwa calon penyewa dengan ID P01 mendapatkan nilai terkecil yaitu 0 dan merupakan peringkat pertama dalam perhitungan vikor. Penelitian ini menunjukkan bahwa metode VIKOR efektif dalam memberikan rekomendasi yang berbasis data dan kriteria yang telah ditentukan, sehingga dapat digunakan sebagai alat pendukung keputusan yang handal dalam pemilihan penyewa tempat usaha di lingkungan kampus.
Perbandingan Algoritma Queue Type SFQ, RED,FIFO dan PCQ Pada Jaringan Nirkabel Berbasis Router Mikrotik
Authors: Auriga Wira , Yuhandri Y , Sumijan
Published: September 2024

Jaringan nirkabel menawarkan fleksibilitas, kecepatan transfer data tinggi yang menawarkan kecepatan transfer data yang jauh lebih tinggi, latensi lebih rendah, dan kemampuan untuk menghubungkan lebih banyak perangkat secara bersamaan. Selain itu, infrastruktur nirkabel memungkinkan fleksibilitas yang lebih besar dalam desain dan penataan ruang kerja, karena tidak memerlukan instalasi kabel fisik yang rumit dan mahal. Jaringan nirkabel juga mempunyai beberapa kelemahan, seperti interferensi sinyal dan jangkauan yang terbatas, yang dapat mempengaruhi kualitas koneksi jaringan nirkabel di lingkungan kampus Sekolah Tinggi Teknologi Payakumbuh, Kualitas jaringan nirkabel sangat penting untuk mendukung kegiatan pembelajaran online, transaksi data akademik, dan pertukaran informasi. Penelitian ini bertujuan untuk mengetahui kualitas infrastruktur jaringan nirkabel di kampus Sekolah Tinggi Teknologi Payakumbuh guna meningkatkan kualitas jaringan intenet untuk mendukung kegiatan pembelajaran online, transaksi data akademik dan pertukaran informasi. Metode yang digunakan dalam penelitian ini adalah perbandingan kinerja beberapa tipe antrian queue type pada router Mikrotik, seperti Stochastic Fairness Queue, Random Early Drop,  First In First Out dan Per Connection Queue. Penelitian ini juga melakukan pengukuran dan pengambilan data sample kualitas jaringan nirkabel menggunakan standar Quality of Service  Telecomunications and Internet Protocol Harmonization Over Network dengan indikator throughput, bandwidth, delay, dan packet loss untuk masing-masing trafik upload dan download dengan total 32 pengukuran sample upload dan download jaringan internet nirkabel Sekolah Tinggi Teknologi Payakumbuh menggunakan wireshark. Hasil penelitian metode SFQ menunjukkan peningkatan kinerja sebesar 6% dalam throughput upload, dengan penurunan delay dan jitter masing-masing sebesar 5.7% dan 5.6% dibandingkan FIFO. Sementara itu, metode FIFO unggul dalam mengurangi packet loss dan meningkatkan throughput download sebesar 1.7% dibandingkan metode lainnya. Metode RED, meskipun memperlihatkan beberapa peningkatan pada delay dan jitter download, memiliki trade-off  berupa peningkatan packet loss sebesar 0.06% pada sisi download dibandingkan FIFO dan SFQ. Secara keseluruhan SFQ menawarkan kinerja yang lebih seimbang dan andal.