bluuebunny/crossref_metadata_2025 huggingface dataset:
Challenges of Urologic Oncology in Low-to-Middle-Income Countries
Authors: Majdalany Sami E. , Butaney Mohit , Tinsley Shane , Corsi Nicholas , Arora Sohrab , Rogers Craig G. , Abdollah Firas
Published: October 2024

We performed a literature review to identify articles regarding the state of urological cancers in low-to-middle-income countries (LMICs). The challenges that LMICs face are multifactorial and can include poor health education, inadequate screening, as well as limited access to treatment options and trained urologists. Many of the gold standard treatments in high-income countries (HICs) are scarce in LMICs due to their poor socioeconomic status, leading to an advanced stage of disease at diagnosis and, ultimately, a higher mortality rate. These standards of care are vital components of oncological disease management; however, the current and sparse literature available from LMICs indicates that there are many obstacles delaying early diagnosis and management options in LMICs. In the era of evolving medical diagnosis and treatments, sufficient data must be gathered and understood in order to provide appropriate diagnostic and treatment options to curtail rising mortality rates and, therefore, help to alleviate the burden in LMICs.
Genitourinary Cancer Care in Low- and Middle-Income Countries: Disparities in Incidence and Access to Care
Authors: Shete Kanha , Ghoulian Joshua , Hu Brian , Alsyouf Muhannad
Published: October 2024

Despite the considerable global burden of urologic malignancies, Low- and middle-income countries (LMICs) often encounter significant challenges in caring for patients with urologic malignancies. Several interrelated factors impact cancer care in LMICs, which face significant challenges that hinder effective diagnosis, treatment, and management of disease. Socioeconomic and healthcare infrastructure limitations are fundamental issues leading to the disparity observed in cancer care across the globe. This review aims to evaluate the challenges and disparities in access to comprehensive urologic care in LMICs, emphasizing the impact of such global disparities on incidence rates, timely diagnoses, and access to comprehensive care as it relates to prostate, kidney, and bladder cancers.
Post-Graduate Urology Training in Low- and Middle-Income Countries
Authors: Baqain Laith , Haddad Sanad , Baqain Ronny , El Hout Yaser , Shahait Mohammed
Published: October 2024

Introduction: Urological conditions significantly impact global health, with increasing demand for urologists in both developed and developing countries. Disparities in access to surgical care between high-income countries (HICs) and low- and middle-income countries (LMICs) are evident. Despite advancements in urology, LMIC training programs often follow outdated curricula and traditional methods. Methodology: A comprehensive search strategy identified urology training programs in LMICs using the EduRank website, Google searches, and PubMed. Data were collected from the literature, official documents, and online resources, focusing on variables such as program duration, research requirements, and resident salaries. Results: The analysis revealed significant variability in program structures and requirements across LMICs. Residency training durations ranged from 4 to 6 years, with inconsistent research obligations and resident salaries averaging USD 12,857 annually, with a range from USD 5412 to USD 18,174. Fellowship opportunities were limited, with only a small number of programs achieving international accreditation. Conclusions: This study reveals disparities among urology training programs in LMICs, emphasizing the challenges faced by LMICs in providing comprehensive education. Outdated curricula, limited faculty, and insufficient resources contribute to the variability in training quality within LMICs. To bridge these gaps, there is a pressing need for standardized and locally tailored educational frameworks. Future research should focus on direct comparisons with programs in HICs to develop strategies that improve training opportunities and ensure equitable access to advanced urological education and care worldwide.
The Impact of Socioeconomic Factors on Kidney Transplantation: A Systematic Review of Low- and Middle-Income Countries
Authors: Duong Nguyen Xuong , Thai Minh Sam , Tran Ngoc Sinh , Hoang Khac Chuan , Chau Quy Thuan , Ngo Xuan Thai , Duong Trung Toan , Truong Tan Ho Trong , Ngo Hanh Thi Tuyet , Nguyen Dat Tien , Quy Khoa , Hoang Tien Dat , Nguyen David-Dan , Onder Narmina Khanmammadova , Mendiola Dinno Francis , Mai Anh Tuan , Hammad Muhammed A. Moukhtar , Vuong Huy Gia , Tiong Ho Yee , Choi Se Young , Nguyen Tuan Thanh
Published: October 2024

Kidney transplantation (KT) is a preferred treatment for end-stage renal disease (ESRD) because it offers better long-term survival and cost-effectiveness compared to dialysis. Significant global disparities persist in access to KT, particularly in low- and middle-income countries (LMICs). This study aims to assess the epidemiology and outcomes of KT in LMICs while examining the relationship between a country’s income level and its KT prevalence. A systematic review of the literature was conducted, with searches of PubMed, Scopus, and Web of Science from inception to 31 May 2024. Relevant articles reporting on the epidemiology and outcomes of KT or ESRD patients undergoing kidney replacement therapy (KRT) in LMICs were included. A total of 8054 articles were identified, with 972 articles selected for full-text screening after initial title and abstract review. Following full-text screening, 35 articles met the inclusion criteria. The data showed significant variation in KRT and KT prevalence across different geographical locations. Higher-income countries within LMICs tended to have higher KT prevalence rates. Barriers such as inadequate healthcare infrastructure, limited financial resources, and insufficient organ donation frameworks were identified as contributing factors to the low KT rates in these regions. The study highlights the disparities in KT access and prevalence in LMICs, underscoring the need for targeted interventions and international collaboration to address these gaps. Efforts to increase both living and deceased donor transplants, expand health system capacity, and incorporate KT in healthcare planning are needed to close this gap. Global partnerships spearheaded by organizations such as The Transplantation Society (TTS) and the International Society of Nephrology (ISN) are crucial for improving KT rates and outcomes in LMICs.
Hope, Adverse Childhood Experiences, and Resilience in the Criminal Justice System: Reevaluation of Relationships in the Turkish Context
Authors: Ozturk Burcu , Sualp Kenan , Barut-Bektas Bercem , McLeod David Axlyn
Published: October 2024

According to data from 2021, Turkey has the highest incarceration rate among European countries. The probation system in Turkey is managed by the government and includes programs, resources, and services to help prevent individuals from engaging in criminal activities. Hope is a crucial factor in coping with adversity, and studies have shown resilience can be the protector of those involved in the criminal justice system. Additionally, adverse childhood experiences (ACEs) can have a significant impact on future victimization and criminal behavior, as individuals with higher ACE scores are more likely to engage in criminal activities. This study was conducted among 107 individuals who were under probation in Turkey to examine the relationship between hope, resilience, and ACEs. The scores were analyzed using a regression model, and the results showed that ACEs did not notably moderate the relationship between hope and resilience. Additionally, having higher levels of hope or ACEs did not play a significant role in predicting the resilience of the individual, which contradicts the previous literature. The implications of these findings will be discussed in terms of cultural differences and the criminal justice system. Future studies should explore the impact of culture on the relationship between hope and resilience.
Correlation Between Broken Contact Fingers and I–V Characteristics of Partially Shaded Photovoltaic Modules
Authors: Atia Abdulhamid , Anayi Fatih , Bahr Ali , Min Gao
Published: October 2024

This paper reports on the correlation between broken contact fingers and the shape of the current–voltage (I–V) curve of a photovoltaic (PV) module. It was found that the broken contact fingers of a solar cell in the PV module cause a noticeable change in the I–V curve of the PV module when the solar cell was partially shaded. The broken contact fingers were inspected by microscopic imaging and electroluminescence (EL) imaging, and a further investigation was carried out using a single solar cell. The results show that the fill factor of the cell decreased from 0.75 of full contact to 0.47 after 16 contact fingers were broken, confirming the correlation between the I–V curve shape and broken contact fingers. This result reveals that the shape of the I–V curve of a PV module under individual-cell partial shading may be used as an indicator of broken contact fingers, which offers an alternative approach to EL imaging for detecting broken contact fingers in PV modules in daylight.
Analysing the Relation between Passion, Motivation, and Subjective Well-Being in Sport: A Systematic Review
Authors: Bento Teresa , Vitorino Anabela , Cid Luís , Monteiro Diogo , Couto Nuno
Published: October 2024

Both the Dualistic Model of Passion and Self-Determination Theory suggest that the persistence of a behaviour over time derives from the internalisation of the passion or motivation that the individual feels about the activity. However, the integration of these theoretical assumptions may lead to a better understanding of related outcomes, in particular on subjective well-being (SWB). In this context, this study aimed at systematically reviewing the relation between passion, behaviour regulation (i.e., self-determined motivation), and SWB in sport. The PRISMA 2020 protocol was used to guide the systematic review. Electronic searches were conducted in the Web of Science database and Pubmed. The following descriptors were used: SWB; passion; motivation; behavioural regulation; and sport. After the search, 12 studies were retrieved for analysis that show us the following results tendencies: harmonious passion (HP) and autonomous motivation (AM) (i.e., more self-determined forms of behaviour regulation) are positively related to SWB (i.e., life satisfaction and positive affect), while obsessive passion (OP) and controlled motivation (CM) (i.e., less self-determined forms of behaviour regulation) are negatively associated with SWB. However, no studies were found to simultaneously analyse the three theoretical constructs. These results show us the importance of developing conditions in sport contexts that promote positive feelings that take into account athletes’ development of harmonious passion and self-determined behaviour regulation, in order to achieve higher levels of well-being. Nevertheless, these results also lead us to the necessity for more studies to highlight the theoretical link between passion and motivation in the context of sport, especially regarding the mediating role of motivation in the relationship between passion and well-being.
Rebuilding Stability: Exploring the Best Rehabilitation Methods for Chronic Ankle Instability
Authors: Tedeschi Roberto , Ricci Vincenzo , Tarantino Domiziano , Tarallo Luigi , Catani Fabio , Donati Danilo
Published: October 2024

Background: Chronic Ankle Instability (CAI) is a common condition characterized by repeated episodes of ankle “giving way” and impaired balance, leading to functional limitations. Various rehabilitation techniques, including balance training, proprioceptive exercises, whole-body vibration (WBV), and novel approaches like stroboscopic vision, are used to address these deficits. This review evaluates the effectiveness of different rehabilitation interventions for CAI management. Methods: A review was conducted by analyzing 11 randomized controlled trials that investigated the impact of balance and proprioceptive training programs on CAI. The primary outcomes assessed were the Star Excursion Balance Test (SEBT), Cumberland Ankle Instability Tool (CAIT), and Foot and Ankle Ability Measure (FAAM). Methodological quality was assessed using the PEDro scale, and the risk of bias was evaluated with the ROB 2 tool. Results: All rehabilitation interventions demonstrated significant improvements in SEBT, CAIT, and FAAM scores. However, no single intervention was found to be consistently superior. Traditional balance training, strength exercises, BAPS, and WBV all provided meaningful functional gains. Stroboscopic vision training showed similar effectiveness compared to conventional approaches. The evidence supports a combination of balance and strength training for optimal recovery. Conclusions: Balance and proprioceptive exercises are effective in managing CAI, with improvements in both dynamic stability and subjective outcomes. No intervention stands out as the best, but personalized programs incorporating various methods are recommended. Future research should explore the long-term effects and potential synergies of combined interventions.
Oxygenation Kinetics of Three Quadriceps Muscles During Squatting Exercise in Trained Men
Authors: Mavridis Konstantinos , Petridou Anatoli , Chatzinikolaou Athanasios , Mougios Vassilis
Published: October 2024

This study aimed to monitor the oxygenation and blood supply in three quadriceps muscles [the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF)] during squatting exercise to exhaustion. Eighteen young resistance-trained males performed five sets of 15 back squats in a Smith machine, with two warm-up sets [at 14% and 45% of the 15-repetition maximum (15RM)] and three main sets at 100% of the 15RM. Three near-infrared spectroscopy devices were attached to the VL, VM, and RF to record the muscle oxygen saturation (SmO2) and total hemoglobin (tHb, an index of muscle blood supply). The blood lactate concentration was measured after each set with a portable analyzer. The SmO2 and tHb data were analyzed by repeated-measures two-way ANOVA (muscle × set). Lactate data were analyzed by repeated-measures one-way ANOVA. The statistical significance was set at α = 0.05. The SmO2 dropped during each set (hitting zero in many instances) and was reinstated during recovery. The three main sets caused severe deoxygenation in the VL and VM, as opposed to moderate deoxygenation in the RF. From one set to the next, the initial value and the drop in the SmO2 increased, whereas the final SmO2 value decreased. The tHb increased in the VL, did not change considerably in the VM, and decreased in the RF during each set. The blood lactate concentration increased gradually from one set to the next, reaching about 10 mmol/L. These findings show pronounced differences in the physiological and metabolic responses of three quadriceps muscles to squatting exercise, thus highlighting the importance of studying such responses at multiple sites.
Cross-Country Assessment of Socio-Ecological Drivers of COVID-19 Dynamics in Africa: A Spatial Modelling Approach
Authors: Salako Kolawole Valère , Sode Akoeugnigan Idelphonse , Dicko Aliou , Alaye Eustache Ayédèguè , Wolkewitz Martin , Glèlè Kakaï Romain
Published: October 2024

Understanding how countries’ socio-economic, environmental, health status, and climate factors have influenced the dynamics of COVID-19 is essential for public health, particularly in Africa. This study explored the relationships between African countries’ COVID-19 cases and deaths and their socio-economic, environmental, health, clinical, and climate variables. It compared the performance of Ordinary Least Square (OLS) regression, the spatial lag model (SLM), the spatial error model (SEM), and the conditional autoregressive model (CAR) using statistics such as the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Square Error (RMSE), and coefficient of determination (R2). Results showed that the SEM with the 10-nearest neighbours matrix weights performed better for the number of cases, while the SEM with the maximum distance matrix weights performed better for the number of deaths. For the cases, the number of tests followed by the adjusted savings, Gross Domestic Product (GDP) per capita, dependence ratio, and annual temperature were the strongest covariates. For deaths, the number of tests followed by malaria prevalence, prevalence of communicable diseases, adjusted savings, GDP, dependence ratio, Human Immunodeficiency Virus (HIV) prevalence, and moisture index of the moistest quarter play a critical role in explaining disparities across countries. This study illustrates the importance of accounting for spatial autocorrelation in modelling the dynamics of the disease while highlighting the role of countries’ specific factors in driving its dynamics.
Prepivoted Augmented Dickey-Fuller Test with Bootstrap-Assisted Lag Length Selection
Authors: Maitra Somak , Politis Dimitris N.
Published: October 2024

We investigate the application of prepivoting in conjunction with lag length selection to correct the size and power performance of the Augmented Dickey-Fuller test for a unit root. The bootstrap methodology used to perform the prepivoting is a residual based AR bootstrap that ensures that bootstrap replicate time series are created under the null irrespective of whether the originally observed series obeys the null hypothesis or not. Simulation studies wherein we examine the performance of our proposed method are given; we evaluate our method’s performance on ARMA(1,1) models with varying configurations for size and power performance. We also propose a novel data dependent lag selection technique that uses bootstrap data under the null to select an optimal lag length; the performance of our method is compared to existing lag length selection criteria.
Tourniquet Restriction of External Carotid Artery vs. Internal Maxillary Artery Ligation for Bleeding Control in Total Maxillectomy
Authors: Liu Yuan-Cheng , Chen Peir-Rong
Published: October 2024

Background/Objectives: Temporary artery ligation or compression is commonly used to reduce intraoperative blood loss in various surgeries, including uterine procedures. In head and neck surgery, the external carotid artery (ECA) typically branches into eight vessels, supplying most of the head and neck except for the brain. Severe and uncontrolled bleeding can occur if these branches are inadvertently damaged during surgery. However, limited research exists on temporary arterial ligation during head and neck surgeries. This study aimed to evaluate the effects of temporary ECA restriction and internal maxillary artery (IMA) ligation on minimizing intraoperative blood loss during head and neck surgery. Methods: This study involved 25 patients with terminal-stage maxillary tumors who underwent total maxillectomy. The effectiveness of IMA ligation and ECA restriction using a Rummel tourniquet in controlling intraoperative bleeding was compared. Results: The average blood loss was significantly lower in the ECA restriction (467 mL) and IMA ligation (461 mL) groups than in the control group (794 mL). However, no significant difference was observed between the IMA ligation and ECA restriction methods. Conclusions: Overall, our results suggest that either method is effective; however, ECA restriction is preferred for tumors involving the infratemporal fossa.
What About Land Uses in Mobility Hub Planning for Sustainable Travel Behavior?
Authors: Pimenta Allan , Kamruzzaman Liton (Md)
Published: October 2024

Mobility hubs (MHs), where various transport modes converge, are increasingly being implemented as a key policy strategy to promote sustainable travel behavior. The existing literature is rich with proposals for various types of MH and suitable siting locations for them. However, studies comparing the role of land use patterns on the performance of different types of MH are scarce. This study aims to fill this gap by analyzing transit patronage and active mode share as performance indicators of MHs. It compares the effects of land use patterns on the performance of different types of MH classified by the nature of transport integration (e.g., train-tram-bus, train-tram, and train-bus) in different contexts (e.g., city district and suburb) in the Greater Melbourne Area, Australia. Results show that MHs enhance the use of transit and active transport modes for commuting purposes by up to 279% and 17%, respectively, compared to a unimodal train station, with maximum usage observed in a train-tram-bus hub, followed by train-tram and train-bus hubs. However, the underlying land use patterns significantly affect their performance. Specifically, each additional hectare of commercial land within the catchment of a train-tram-bus MH in the city district, a train-tram-bus MH in a suburban area, a train-tram MH in a suburban area, and a train-bus MH in a suburban area increases transit patronage by 6%, 9%, 5%, and 4%, respectively. These findings suggest that MH typologies should be designed in tandem with supportive land uses to maximize sustainable travel behavior. The findings inform urban and transport planners in designing optimal land use patterns for different types of MH to maximize sustainable travel behavior. They also support the development of tailored land use zoning policies to enhance the effectiveness of MHs.
Characterization of Gas Seepage in the Mining Goaf Area for Sustainable Development: A Numerical Simulation Study
Authors: Li Bing , Li Hao , Tian Yuchen , Zhang Helong , Liao Qingfa , Chen Shiheng , Liu Yinghai , Liu Yanzhi , Liu Shiqi , Sang Shuxun , Zheng Sijian
Published: October 2024

An in-depth understanding of gas (oxygen and methane) seepage characteristics in coal mine goafs is essential for the safe production of mines and for advancing sustainable development practices within the mining industry. However, the gas distribution and its flow processes still remain ambiguous. In this article, we developed a three-dimensional porous media mining goaf mathematical model (considering the heterogeneity) to analyze the methane and oxygen flow features. Firstly, based on the variation laws of the “three zones”—the free caving zone, fracture zone, and subsidence zone—porosity changes in the vertical direction were set. A three-dimensional physical model of a fully mechanized caving mining area with a “U”-shaped ventilation system was established as the basis, and a COMSOL Multiphysics multi-field coupled model was built. Secondly, based on the established model, the characteristics of porosity distribution, mixed gas pressure changes, and the volume fraction of oxygen in the goaf were analyzed. The results show that as the distance from the working face increases, the compaction intensity in the mined-out area gradually rises, resulting in a decreasing porosity trend. The porosity distribution characteristics significantly impact the mechanical behavior and gas flow. The gas pressure inside the mined-out area is much higher than the surroundings, decreasing with depth. The upper and middle parts have the highest-pressure concentrations, requiring focused assessment and targeted monitoring measures based on the pressure characteristics of different regions. The oxygen concentration gradually decreases with depth due to poor ventilation, leading to potential explosive gas mixtures, necessitating ventilation system optimization, enhanced monitoring, and emergency preparedness. The gas exhibits vertical stratification, with higher concentrations in the upper and deep regions. Targeted drainage and ventilation methods can effectively control the gas concentration and ensure production safety.
Environmental Regulations, Green Marketing, and Consumers’ Green Product Purchasing Intention: Evidence from China
Authors: Li Xiaohuan , Wang Chenggang , Li Dongrong , Yang Dongxue , Meng Fan , Huang Yuan
Published: October 2024

With the strengthening of social environmental regulations, consumers’ green products purchasing intention is also increasing significantly. Simultaneously, green marketing activities have developed into a vital factor affecting consumers’ green products purchasing intention. The first research aim of this paper is to reveal the important relationship between environmental regulation and consumers’ green products purchasing intention. Furthermore, another research aim is to reveal the role of green marketing in environmental regulation and consumers’ green products purchasing intention. To achieve the above purpose, we primarily employ regression analysis, threshold effect analysis, spatial spillover effect analysis, and heterogeneity tests. We come up with some conclusions. First of all, environmental regulations could enhance consumers’ green product purchasing intention. With the reinforcement of environmental regulations, consumers’ green product purchasing intention could be effectively elevated. Secondly, green marketing is a positive mediator of the environmental regulations that affect the consumers’ green product purchasing intention. By enhancing their green marketing capabilities, businesses could also strengthen consumers’ green product purchasing intention. Lastly, in different regions of China, the impact of environmental regulations and green marketing on consumers’ green product purchasing intention varies. In the Eastern region, the influence of environmental regulations on consumers’ green product purchasing intention is most prominent. However, green marketing exerts the greatest impact on the consumers’ green product purchasing intention in the Western region. In addition, this paper provides significant insights for the managers in making management decisions. This is beneficial for enhancing consumers’ green product purchasing intention.
Implementing Antimony Supply and Sustainability Measures via Extraction as a By-Product in Skarn Deposits: The Case of the Chalkidiki Pb-Zn-Au Mines
Authors: Bussolesi Micol , Cavallo Alessandro , Gazea Vithleem , Tzamos Evangelos , Grieco Giovanni
Published: October 2024

Antimony is one of the world’s scarcest metals and is listed as a Critical Raw Material (CRM) for the European Union. To meet the increasing demand for metals in a sustainable way, one of the strategies that could be implemented would be the recovery of metals as by-products. This would decrease the amount of hazardous materials filling mining dumps. The present study investigates the potential for producing antimony as a by-product at the Olympias separation plant in Northern Greece. This plant works a skarn mineralization that shows interesting amounts of Sb. Boulangerite (Pb5Sb4S11) reports on Pb concentrate levels reached 8% in the analyzed product. This pre-enrichment is favorable in terms of boulangerite recovery since it can be separated from galena through froth flotation. Boulangerite distribution in the primary ore is quite heterogeneous in terms of the inclusion relationships and grain size. However, a qualitative assessment shows that the current Pb concentrate grain size is too coarse to successfully liberate a good amount of boulangerite. The use of image analysis and textural assessments is pivotal in determining shape factors and crystal size, which is essential for the targeting of flotation parameters during separation. The extraction of antimony as a by-product is possible through a two-step process; namely, (i) the preliminary concentration of boulangerite, followed by (ii) the hydrometallurgical extraction of the antimony from the boulangerite concentrate. The Olympias enrichment plant could therefore set a positive example by promoting the benefits of targeted Sb extraction as a by-product within similar sulfide deposits within the European territory.
A Fuzzy Multi-Criteria Approach for Selecting Sustainable Power Systems Simulation Software in Undergraduate Education
Authors: Babatunde Olubayo , Emezirinwune Michael , Adebisi John , Abdulsalam Khadeejah A. , Akintayo Busola , Olanrewaju Oludolapo
Published: October 2024

Selecting the most preferred software for teaching power systems engineering at the undergraduate level is a complex problem in developing countries, and it requires making an informed decision by compromising on various criteria. This study proposes a multi-criteria framework to determine the most preferred software solution for instructing undergraduate power system modules using the Fuzzy-ARAS (additive ratio assessment) method and expert opinions. Twelve evaluation criteria were used to evaluate eight widely used software packages. A questionnaire was designed to capture views from professionals in academia and industry on the criteria weights and ranking of software options. Linguistic terms were used to represent the experts’ judgment, and weights were assigned to each criterion. The Fuzzy-ARAS multi-criteria decision approach was applied to obtain ratings for each software alternative. Based on the result, MATLAB emerged as the most preferred software for instructing power systems analysis, whereas MATPOWER (V 8.0) was rated as the least preferred choice. In addition, the Fuzzy-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach was used, producing a separate ranking; the most preferred software was MATPOWER, while the least preferred software was NEPLAN (V 360 10.5.1). A new coefficient that combines the findings of the two approaches was suggested to reconcile the ranks. The combined ranking aligns with the result of the Fuzzy-TOPSIS method by returning MATLAB as the most preferred, while the least preferred software was NEPLAN. This study significantly contributes to the choice of software for undergraduate power systems analysis instruction by providing direction to educators and institutions looking for software solutions to improve undergraduate power systems analysis education.
Analysis of Technology Mergers and Acquisitions on Enterprises’ Green Technology Innovation: Moderating Effects of Environmental Regulation and Environmental Uncertainty
Authors: Chen Chao , Liu Jianmin , Tao Ying , Fan Wenye , Qian Jingjing
Published: October 2024

Enterprises’ green technology innovation is often subject to dilemmas related to resource limitations and innovation compensation. Technology mergers and acquisitions (M&A) may incentivize green innovation but may also have an inhibiting effect. We took A-share listed companies in China from 2007 to 2021 as a sample, using 1577 technology M&A samples to examine the impact of technology M&A on enterprises’ green technology innovation, including the moderating effects of environmental regulation, environmental uncertainty, and board members’ educational background. We found that technology M&A can effectively stimulate enterprises’ green technology innovation. We also found that as the diversity of board members’ educational background, environmental uncertainty, and environmental regulations increase, the effect of technology M&A on incentives for green technology innovation becomes clearer. The research results provide a theoretical basis for optimizing the market environment of technology M&A, reasonable M&A modes, and green technology innovation.
Quantitative Research of Traditional Village Morphology Based on Spatial Genes: A Case Study of Shaanxi Province, China
Authors: Zhang Weidi , Yang Hanyu
Published: October 2024

As urbanization accelerates, many traditional villages face the threat of destruction or disappearance. To better protect and utilize the cultural heritage of traditional villages, it is essential to deeply analyze the inherent patterns of their spatial morphology. This paper selects Nihegou Village in Yulin City, Shaanxi Province, China, as a case study. Utilizing the theory of spatial genes, a quantitative inheritance model was developed, integrating natural, physical, and intangible spatial factors. Through the collection of multidimensional spatial data, such as village topography, slope, and aspect, combined with GIS spatial analysis and the AHP-Fuzzy Comprehensive Evaluation method, the spatial morphological characteristics and genetic inheritance of Nihegou Village were identified, decoded, and quantitatively assessed. Based on the assessment results, corresponding conservation and development strategies were formulated. The findings show that the formation and development of Nihegou Village’s spatial pattern are closely related to factors like the natural environment, social policies, and economic technologies. The terrain and the process of urban modernization have impacted the inheritance and development of Nihegou Village’s intangible spatial genes. The application of spatial quantitative analysis methods to formulate strategies for the preservation and inheritance of traditional village spatial characteristics not only provides theoretical guidance for village planning and conservation rooted in cultural heritage, but also effectively safeguards and revitalizes the spatial gene inheritance of Nihegou Village, contributing to the village’s sustainable development.
Coupling and Coordination Analysis of High-Quality Agricultural Development and Rural Revitalization: Spatio-Temporal Evolution, Spatial Disparities, and Convergence
Authors: Wang Yaoyao , Lei Yifan , Shah Muhammad Haroon
Published: October 2024

The coupling and coordination of high-quality agricultural development (HQAD) and rural revitalization is an inevitable choice to accelerate the realization of Chinese-style agricultural and rural modernization. Based on system theory, this study reconstructs the indicator systems of both and conducts measurements by applying the improved AHP–entropy weight method. This study has extended the analytical methods of kernel density estimation, Dagum Gini coefficient, σ convergence, and spatial β convergence to further investigate the spatio-temporal evolution, regional disparities, and convergence effect of the coupling coordination degree (CCD) of HQAD and rural revitalization in China from 2010 to 2020. The results show that the CCD has a tendency to increase year by year, presenting the characteristics of ‘high coupling degree–low comprehensive development level–low coupling coordination degree’, and also has the spatial distribution pattern of ‘high in the east and low in the west’. In addition, most of the provinces have a tendency to jump to a higher stage of coupling coordination; the overall trend of the kernel density curves is favorable; the results of Dagum’s Gini coefficient show that inter-regional disparities contribute the most to regional spatial disparities; and there is a significant tendency towards σ convergence and spatial β convergence of the CCD in China and the four regions. This study stimulates a broader discussion of rural revitalization, with potential implications for decision making in practice.
The Usefulness of Infrared Spectroscopy for Elucidating the Degradation Mechanism of Metal Industrial Heritage Coatings
Authors: Konadu-Yiadom Ernest , Bontrager Ethan , Staerz Anna
Published: October 2024

As society moves away from heavy industry, large metallic structures will be abandoned. As an alternative to dismantling, these structures could be repurposed. Beyond being a practical solution, the conservation of these structures would serve as an ode to the role of these industries in shaping modern society. Conservation, however, requires suitable coatings that hinder corrosion long-term while not significantly altering the outward appearance. Traditionally, the stability of coatings has been tested by comparing fresh samples to those aged naturally or in a UV chamber. This method of testing provides no temporal information. Additionally, measuring many different conditions, e.g., UV, humidity, temperature, and pollutants, is tedious. In this review, we highlight how by implementing infrared spectroscopy in different configurations, temporally resolved information about the coating chemistry, the metal–coating interface chemistry, and gas emissions could be gained during degradation. These insights would be essential to enable the intentional design of coatings while simultaneously revealing their environmental impact.
Synthesis of BiOCl Colloidal Particles by Laser Ablation of Solids in Liquids
Authors: Vázquez Francisco Abril , Pérez-Centeno Armando , Rivera Laura P. , Quiñones-Galván José G.
Published: October 2024

Colloidal bismuth nanoparticles (NPs) were synthesized in sodium chloride (NaCl) solutions at different concentrations using the laser ablation of solids in liquids technique. The obtained materials were characterized using various techniques. The morphology, size, and crystalline phases were determined through scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and Fourier-transform infrared spectroscopy (FTIR). The optical properties were studied using UV–visible spectroscopy, employing the Tauc method to determine the band gap of the particles. Two types of materials were identified depending on the NaCl concentration: spherical nanoparticles of α-Bi2O3 and the coexistence of α-Bi2O3 and BiOCl particles with irregular morphology. NaCl concentrations higher than 11.6% enable the coexistence of α-Bi2O3 and BiOCl. The photocatalytic response of the colloids was evaluated by the degrading rhodamine B under visible light irradiation. The sample synthesized at a NaCl concentration of 31.6% showed the best photocatalytic activity.
Robust Harmonic Fuzzy Partition Local Information C-Means Clustering for Image Segmentation
Authors: Wu Chengmao , Zhou Siyu
Published: October 2024

Considering the shortcomings of Ruspini partition-based fuzzy clustering in revealing the intrinsic correlation between different classes, a series of harmonic fuzzy local information C-means clustering for noisy image segmentation are proposed. Firstly, aiming at the shortage of Zadeh’s fuzzy sets, a new concept of generalized harmonic fuzzy sets is originally introduced and the corresponding harmonic fuzzy partition is further defined. Then, based on the concept of symmetric harmonic partition, a new harmonic fuzzy local information C-means clustering (HLICM) is proposed and the local convergence of the algorithm is rigorously proved using Zangwill’s theorem. Finally, inspired by the improved fuzzy local information C-means clustering (IFLICM) and kernel-based weighted fuzzy local information C-means clustering (KWFLICM), two enhanced robust HLICM algorithms are constructed to further improve the ability of the algorithm to suppress noise. Compared with existing state-of-the-art robust fuzzy clustering-related algorithms, it has been confirmed that the two proposed algorithms have significant competitiveness and superiority.
Top-Oil Temperature Prediction of Power Transformer Based on Long Short-Term Memory Neural Network with Self-Attention Mechanism Optimized by Improved Whale Optimization Algorithm
Authors: Zou Dexu , Xu He , Quan Hao , Yin Jianhua , Peng Qingjun , Wang Shan , Dai Weiju , Hong Zhihu
Published: October 2024

The operational stability of the power transformer is essential for maintaining the symmetry, balance, and security of power systems. Once the power transformer fails, it will lead to heightened instability within grid operations. Accurate prediction of oil temperature is crucial for efficient transformer operation. To address challenges such as the difficulty in selecting model hyperparameters and incomplete consideration of temporal information in transformer oil temperature prediction, a novel model is constructed based on the improved whale optimization algorithm (IWOA) and long short-term memory (LSTM) neural network with self-attention (SA) mechanism. To incorporate holistic and local information, the SA is integrated with the LSTM model. Furthermore, the IWOA is employed in the optimization of the hyper-parameters for the LSTM-SA model. The standard IWOA is improved by incorporating adaptive parameters, thresholds, and a Latin hypercube sampling initialization strategy. The proposed method was applied and tested using real operational data from two transformers within a practical power grid. The results of the single-step prediction experiments demonstrate that the proposed method significantly improves the accuracy of oil temperature prediction for power transformers, with enhancements ranging from 1.06% to 18.85% compared to benchmark models. Additionally, the proposed model performs effectively across various prediction steps, consistently outperforming benchmark models.
Foliation-Generating Observers Under Lorentz Transformations
Authors: Blixt Daniel , Jiménez Cano Alejandro , Wojnar Aneta
Published: October 2024

In this work, we revise the concept of foliation and related aspects that are crucial when formulating the Hamiltonian evolution for various theories beyond General Relativity. In particular, we show the relation between the kinematic characteristics of timelike congruences (observers) and the existence of foliations orthogonal to them. We then explore how local Lorentz transformations acting on observers affect the existence of transversal foliations, provide examples, and discuss the implications of these results for the 3+1 formulation of tetrad modified theories of gravity.
Enhancing Autonomous Visual Perception in Challenging Environments: Bilateral Models with Vision Transformer and Multilayer Perceptron for Traversable Area Detection
Authors: Urrea Claudio , Vélez Maximiliano
Published: October 2024

The development of autonomous vehicles has grown significantly recently due to the promise of improving safety and productivity in cities and industries. The scene perception module has benefited from the latest advances in computer vision and deep learning techniques, allowing the creation of more accurate and efficient models. This study develops and evaluates semantic segmentation models based on a bilateral architecture to enhance the detection of traversable areas for autonomous vehicles on unstructured routes, particularly in datasets where the distinction between the traversable area and the surrounding ground is minimal. The proposed hybrid models combine Convolutional Neural Networks (CNNs), Vision Transformer (ViT), and Multilayer Perceptron (MLP) techniques, achieving a balance between precision and computational efficiency. The results demonstrate that these models outperform the base architectures in prediction accuracy, capturing distant details more effectively while maintaining real-time operational capabilities.
Particle Size Distribution in Holby–Morgan Degradation Model of Platinum on Carbon Catalyst in Fuel Cell: Normal Distribution
Authors: Kovtunenko Victor A.
Published: October 2024

The influence of particle size distribution in platinum catalysts on the aging of PEM fuel cells described by Holby–Morgan electrochemical degradation model is under investigation. The non-diffusive model simulates mechanisms of particle drop by Pt dissolution and particle growth through Pt ion deposition. Without spatial dependence, the number of differential equations can be reduced using the first integral of the system. For an accelerated stress test, a non-symmetric square-wave potential profile is applied according to the European harmonized protocol. The normal particle size distribution determined by two probability parameters of the expectation and the standard deviation is represented within finite groups. Numerical solution of the nonlinear diffusion equation justifies dispersion for small and narrowing for large distribution means, decrease or increase in amplitude, and movement of Pt particle diameters towards small sizes, which is faster for small particles.
An Efficient CNN-Based Intrusion Detection System for IoT: Use Case Towards Cybersecurity
Authors: Deshmukh Amogh , Ravulakollu Kiran
Published: October 2024

Today’s environment demands that cybersecurity be given top priority because of the increase in cyberattacks and the development of quantum computing capabilities. Traditional security measures have relied on cryptographic techniques to safeguard information systems and networks. However, with the adaptation of artificial intelligence (AI), there is an opportunity to enhance cybersecurity through learning-based methods. IoT environments, in particular, work with lightweight systems that cannot handle the large data communications typically required by traditional intrusion detection systems (IDSs) to find anomalous patterns, making it a challenging problem. A deep learning-based framework is proposed in this study with various optimizations for automatically detecting and classifying cyberattacks. These optimizations involve dimensionality reduction, hyperparameter tuning, and feature engineering. Additionally, the framework utilizes an enhanced Convolutional Neural Network (CNN) variant called Intelligent Intrusion Detection Network (IIDNet) to detect and classify attacks efficiently. Layer optimization at the architectural level is used to improve detection performance in IIDNet using a Learning-Based Intelligent Intrusion Detection (LBIID) algorithm. The experimental study conducted in this paper uses a benchmark dataset known as UNSW-NB15 and demonstrated that IIDNet achieves an outstanding accuracy of 95.47% while significantly reducing training time and excellent scalability, outperforming many existing intrusion detection models.
Thalassemia: Pathophysiology, Diagnosis, and Advances in Treatment
Authors: Sadiq Idris Zubairu , Abubakar Fatima Sadiq , Usman Hauwa Salisu , Abdullahi Aliyu Dantani , Ibrahim Bashiru , Kastayal Babangida Sanusi , Ibrahim Maryam , Hassan Hassan Aliyu
Published: October 2024

Thalassemia represents a diverse group of inherited hematological disorders characterized by defective globin chain synthesis, leading to chronic anemia and associated complications. The complicated pathophysiology of beta-thalassemia involves genetic mutations or rarely deletions of the beta-globin gene on chromosome 11 whereas alpha-thalassemia involves deletions in the HBA1 and HBA2 genes or occasionally alterations to the DNA sequence in or around these genes. These mutation and deletion effects disrupt the balance of α/β-globin chain production, resulting in ineffective erythropoiesis, hemolysis, and a cascade of clinical manifestations including anemia, bone deformities, and iron overload. Advances in diagnostic techniques have enhanced our ability to detect and characterize these mutations, facilitating early and accurate diagnoses. Current management strategies encompass regular blood transfusions, the use of hydroxyurea to improve hemoglobin levels, and iron chelation therapy to prevent iron-related organ damage. Moreover, other therapeutics such as thalidomide for those not responding to hydroxyurea, Sirolimus for patients with immunodeficiencies, and use of vitamin E as an antioxidant have proven to be effective. Innovative therapies such as gene therapy and bone marrow transplantation offer promising curative potential, opening a new era in the treatment of thalassemia. This review focuses on pathophysiological mechanisms underlying thalassemia, explores the diagnostic methodologies, and highlights recent advancements in therapeutic approaches.