bluuebunny/crossref_metadata_2025 huggingface dataset:
Neighborhood Rough Fuzzy Penetration Control Method with Variable Precision Based on GMAW
Authors: Xiang Xiaohong , Feng Zhiqiang , Yuan Hao , Zeng Xianping , Pan Zufu , Li Xin , Li Quan , Huang Xiaohu
Published: August 2023

Considering the nonlinear, time-varying, and multivariate coupling nature of the welding process, achieving excellent control of the welding process can be challenging. In addition, welding experience varies from person to person, making it difficult to establish a uniform standard. In this work, rough set theory is introduced and applied to arc welding process modeling and quality control to achieve effective online control of weld penetration during welding. A variable precision neighborhood rough-fuzzy method is proposed to enhance the efficiency and adaptability of rough set theory for information processing in the welding process. By designing welding experiments with different gaps and currents, descriptors such as the tail area coefficient and the length-width ratio of the melt pool have been proposed to characterize the melt pool. Rough set theory has been used to extract decision classification rules for welding percolation state information, and clustering analysis, fuzzy logic, and min-max fuzzy methods have been introduced for knowledge modeling. The proposed variable precision neighborhood rough-fuzzy control model is verified via three sets of experiments, and the results show that the model has excellent stability and effectiveness.
Intrusion Detection for Industrial Control Systems Based on Improved Contrastive Learning SimCLR
Authors: Li Chengcheng , Li Fei , Zhang Liyan , Yang Aimin , Hu Zhibin , He Ming
Published: August 2023

Since supervised learning intrusion detection models rely on manually labeled data, the process often requires a lot of time and effort. To make full use of unlabeled network traffic data and improve intrusion detection, this paper proposes an intrusion detection method for industrial control systems based on improved comparative learning SimCLR. Firstly, a feature extraction network is trained on SimCLR using unlabeled data; a linear classification layer is added to the trained feature extraction network model; and a small amount of labeled data is used for supervised training and fine-tuning of the model parameters. The trained model is simulated on the Secure Water Treatment (SWaT) dataset and the publicly available industrial control dataset from Mississippi State University, and the results show that the method has better results in all evaluation metrics compared with the deep learning algorithm using supervised learning directly, and the comparative learning has research value in industrial control system intrusion detection.
Flow Control, Active and Passive Applications
Authors: Bergadà Josep M. , Bugeda Gabriel
Published: August 2023

The Boundary Layer (BL) dynamic performance greatly affects the forces acting on any Bluff body [...]
Anatomy of the Mental Foramen: Relationship among Different Metrical Parameters for Accurate Localization
Authors: Cellina Michaela , Martinenghi Carlo , De Nardi Sandro , Palamenghi Andrea , Cè Maurizio , Sforza Chiarella , Cappella Annalisa , Gibelli Daniele
Published: August 2023

Purpose: The mental foramen (MF) is important in dental surgery procedures for preventing possible iatrogenic lesions and for anesthetic procedures. This paper aims at expanding knowledge on the metrical characteristics that are useful for the correct anatomical assessment of the MF. Materials and Methods: On 100 CBCT scans (50 males and 50 females), height, width, depth, linear distance from the inferior and superior mandibular edge and position according to teeth and dental apices were analyzed. Differences according to sex and the side for each metrical measurement and for teeth and dental apices were assessed through a two-way ANOVA test and Chi-square test, respectively. Pearson’s test and a one-way ANOVA test were used to test correlations among the chosen parameters (p < 0.01). Results: The depth and distance from the inferior and superior mandibular edges showed sexual dimorphism (p < 0.01). Height and width were positively related, as well as depth and distance from the inferior mandibular edge in females (p < 0.01). Conclusions: Novel data about the anatomical position of the mental foramen are described, which are useful for the management of surgical procedures.
A Flame Detection Algorithm Based on Improved YOLOv7
Authors: Yan Guibao , Guo Jialin , Zhu Dongyi , Zhang Shuming , Xing Rui , Xiao Zhangshu , Wang Qichao
Published: August 2023

Flame recognition is of great significance in fire prevention. However, current algorithms for flame detection have some problems, such as missing detection and false detection, and the detection accuracy cannot satisfy the requirements for fire prevention. In order to further the above problems, we propose a flame detection algorithm based on an improved YOLOv7 network. In our algorithm, we replace a convolution of the MP-1 module with a SimAM structure, which is a parameter-free attention mechanism. In this way, the missing detection problem can be improved. Furthermore, we use a ConvNeXt-based CNeB module to replace a convolution of the ELAN-W module for increasing detection accuracy and the false detection problem in complex environments. Finally, we evaluate the performance of our algorithm through a large number of test cases, and the data set used in our experiments was constructed by combining several publicly available data sets for various application scenarios. The experimental results indicate that compared with the original YOLOv7 algorithm, our proposed algorithm can achieve a 7% increase in the aspect of mAP_0.5 and a 4.1% increase in the aspect of F1 score.
Building Polygon Extraction from High-Resolution Remote Sensing Imagery Using Knowledge Distillation
Authors: Xu Haiyan , Xu Gang , Sun Geng , Chen Jie , Hao Jun
Published: August 2023

Building polygons plays an important role in urban management. Although leveraging deep learning techniques for building polygon extraction offers advantages, the models heavily rely on a large number of training samples to achieve good generalization performance. In scenarios with small training samples, the models struggle to effectively represent diverse building structures and handle the complexity introduced by the background. A common approach to enhance feature representation is fine-tuning a pre-trained model on a large dataset specific to the task. However, the fine-tuning process tends to overfit the model to the task area samples, leading to the loss of generalization knowledge from the large dataset. To address this challenge and enable the model to inherit the generalization knowledge from the large dataset while learning the characteristics of the task area samples, this paper proposes a knowledge distillation-based framework called Building Polygon Distillation Network (BPDNet). The teacher network of BPDNet is trained on a large building polygon dataset containing diverse building samples. The student network was trained on a small number of available samples from the target area to learn the characteristics of the task area samples. The teacher network provides guidance during the training of the student network, enabling it to learn under the supervision of generalization knowledge. Moreover, to improve the extraction of buildings against the backdrop of a complex urban context, characterized by fuzziness, irregularity, and connectivity issues, BPDNet employs the Dice Loss, which focuses attention on building boundaries. The experimental results demonstrated that BPDNet effectively addresses the problem of limited generalization by integrating the generalization knowledge from the large dataset with the characteristics of the task area samples. It accurately identifies building polygons with diverse structures and alleviates boundary fuzziness and connectivity issues.
Rural Farmers’ Perceptions for the Impacts of Climate Change and Adaptation Policies on Wheat Productivity: Insights from a Recent Study in Balochistan, Pakistan
Authors: Khan Nawab , Ma Jiliang , Zhang Huijie , Zhang Shemei
Published: August 2023

Climate change (CC) is a worldwide environmental issue affecting all economic sectors, especially agriculture. Pakistan is one of the countries most affected by CC due to the country’s vulnerability to catastrophic events and limited ability to adapt. Assessing existing activities for adaptation to CC at the farm level is critical to understanding their success and recommending additional government measures. This study analyzes possible farming practice modifications that Pakistani farmers may adopt to reduce the loss of agricultural output due to the rising prevalence of dangerous weather events by CC. Data for the current research were gathered from 432 wheat farmers in rural Pakistan. This article investigates many factors that impact farmers’ decisions to CC adaptation in crop production utilizing binary logit (BL) and multivariate probit (MVP) models. Gender, education level, farming experience, farm size, level of damage, access to finance, and training participation are characteristics that substantially affect farmers’ likelihood of adapting to CC. Farm size and participation in CC training were the most critical factors influencing farmers’ CC adaptation decisions. Policy recommendations were presented to increase the farmers’ resilience in the study areas to CC. These comprise expanding CC training courses, developing regulations to encourage agricultural integration, and integrating CC and adaptation to CC principles into the operations of regional organizations. Finally, based on the findings, policymakers will be better equipped to address the challenges posed by CC and create a more resilient agricultural sector. This, in turn, will contribute to improving food security, ensuring sustainable agricultural growth.
Assessing Spatiotemporal Characteristics and Driving Factors of Urban Public Buildings Carbon Emissions in China: An Approach Based on LMDI Analysis
Authors: Zhang Zhidong , Liu Yisheng , Ma Tian
Published: August 2023

Urban public buildings carbon emissions exhibit an upward trend and have a large potential in carbon emission reduction. The analysis of spatiotemporal characteristics and driving factors for urban public buildings carbon emissions is essential in formulating effective policies for carbon reduction, meeting commitments to peak carbon emissions and achieving carbon neutrality. This study takes China’s urban public buildings carbon emissions as the research object, employing methods such as spatial autocorrelation analyses, kernel density estimation analyses, and the LMDI decomposition methods to explore the spatiotemporal characteristics and regional disparities in carbon emissions from 2006 to 2019. Furthermore, it quantifies the contributions of driving factors to the spatiotemporal changes in urban public buildings carbon emissions. The results show the following: (1) Urban public buildings carbon emissions among provinces are consistently increasing, indicating an overall upward trend. The spatial distribution highlights significant regional disparities. (2) The spatial characteristics of urban public buildings carbon emissions were basically stable. The eastern coastal regions demonstrate a high-high cluster, while the western regions exhibit a low-low cluster. The overall cluster evolution showed a decreasing trend from east to west. (3) Per capita urban public building area, economic density, urbanization rate, and population size serve as driving factors for carbon emissions from urban public buildings, while energy efficiency and energy consumption intensity act as inhibitory factors. The findings of this research can assist policymakers in getting a deeper comprehension of urban public buildings carbon emissions and providing a scientific basis to formulate appropriate carbon emission reduction policies.
Discriminant Analysis of the Solar Input on the Danube’s Discharge in the Lower Basin
Authors: Mares Constantin , Mares Ileana , Dobrica Venera , Demetrescu Crisan
Published: August 2023

This paper presents the extent to which the combination of extra-atmospheric and hydroclimatic factors can be deciphered to record their contribution to the evolution and forecasting of the Danube discharge (Q) in the lower basin. A combination of methods such as wavelet filtering and deep learning (DL) constitutes the basic method for discriminating the external factors (solar activity through Wolf numbers) that significantly contribute to the evolution and prediction of the lower Danube discharge. An ensemble of some of the most important factors, namely, those representing the atmospheric components, i.e., the Greenland-Balkan Oscillation Index (GBOI) and the North Atlantic Oscillation Index (NAOI); the hydroclimatic indicator, the Palmer Hydrological Drought Index (PHDI); and the extra-atmospheric factor, constitutes the set of predictors by means of which the predictand, Q, in the summer season, is estimated. The external factor has to be discriminated in the Schwabe and Hale spectra to make its convolutional contribution to the Q estimation in the lower Danube basin. An interesting finding is that adding two solar predictors (associated with the Schwabe and Hale cycles) to the terrestrial ones give a better estimation of the Danube discharge in summer, compared to using only terrestrial predictors. Based on the Nash–Sutcliffe (NS) index, a measure of performance given by the extreme learning machine (ELM), it is shown that, in association with certain terrestrial predictors, the contribution of the Hale cycle is more significant than the contribution of the Schwabe cycle to the estimation of the Danube discharge in the lower basin.
Comment on Manchaiah et al. Social Representations of “Tinnitus” and “Health” among Individuals with Tinnitus Seeking Online Psychological Interventions. Audiol. Res. 2023, 13, 207–220
Authors: Aldè Mirko , Iannella Giannicola , Lechien Jerome Rene , Simon Francois , Maniaci Antonino
Published: August 2023

We read with pleasure the interesting paper titled “Social Representations of “Tinnitus” and “Health” among Individuals with Tinnitus Seeking Online Psychological Interventions” by Vinaya Manchaiah et al. [...]
Finsler Warped Product Metrics with Special Curvature Properties
Authors: Sun Lingen , Zhang Xiaoling , Wu Mengke
Published: August 2023

The class of warped product metrics can often be interpreted as key space models for the general theory of relativity and theory of space–time. In this paper, we study several non-Riemannian quantities in Finsler geometry. These non-Riemannian quantities play an important role in understanding the geometric properties of Finsler metrics. In particular, we find differential equations of Finsler warped product metrics with vanishing χ-curvature or vanishing H-curvature. Furthermore, we show that, for Finsler warped product metrics, the χ-curvature vanishes if and only if the H-curvature vanishes.
Stochastic Ordering Results on Implied Lifetime Distributions under a Specific Degradation Model
Authors: Kayid Mohamed , Alshagrawi Lolwa , Shrahili Mansour
Published: August 2023

In this paper, a novel strategy is employed in which a degradation model affects the implied distribution of lifetimes differently compared to the traditional method. It is recognized that an existing link between the degradation measurements and failure time constructs the underlying time-to-failure model. We assume in this paper that the conditional survival function of a device under degradation is a piecewise linear function for a given level of degradation. The multiplicative degradation model is used as the underlying degradation model, which is often the case in many practical situations. It is found that the implied lifetime distribution is a classical mixture model. In this mixture model, the time to failure lies with some probabilities between two first passage times of the degradation process to reach two specified values. Stochastic comparisons in the model are investigated when the probabilities are changed. To illustrate the applicability of the results, several examples are given in cases when typical degradation models are candidates.
The Developmental Implications of Muscle-Targeted Magnetic Mitohormesis: A Human Health and Longevity Perspective
Authors: Franco-Obregón Alfredo , Tai Yee Kit , Wu Kwan Yu , Iversen Jan Nikolas , Wong Craig Jun Kit
Published: August 2023

Muscle function reflects muscular mitochondrial status, which, in turn, is an adaptive response to physical activity, representing improvements in energy production for de novo biosynthesis or metabolic efficiency. Differences in muscle performance are manifestations of the expression of distinct contractile-protein isoforms and of mitochondrial-energy substrate utilization. Powerful contractures require immediate energy production from carbohydrates outside the mitochondria that exhaust rapidly. Sustained muscle contractions require aerobic energy production from fatty acids by the mitochondria that is slower and produces less force. These two patterns of muscle force generation are broadly classified as glycolytic or oxidative, respectively, and require disparate levels of increased contractile or mitochondrial protein production, respectively, to be effectively executed. Glycolytic muscle, hence, tends towards fibre hypertrophy, whereas oxidative fibres are more disposed towards increased mitochondrial content and efficiency, rather than hypertrophy. Although developmentally predetermined muscle classes exist, a degree of functional plasticity persists across all muscles post-birth that can be modulated by exercise and generally results in an increase in the oxidative character of muscle. Oxidative muscle is most strongly correlated with organismal metabolic balance and longevity because of the propensity of oxidative muscle for fatty-acid oxidation and associated anti-inflammatory ramifications which occur at the expense of glycolytic-muscle development and hypertrophy. This muscle-class size disparity is often at odds with common expectations that muscle mass should scale positively with improved health and longevity. Brief magnetic-field activation of the muscle mitochondrial pool has been shown to recapitulate key aspects of the oxidative-muscle phenotype with similar metabolic hallmarks. This review discusses the common genetic cascades invoked by endurance exercise and magnetic-field therapy and the potential physiological differences with regards to human health and longevity. Future human studies examining the physiological consequences of magnetic-field therapy are warranted.
Profound Non-Randomness in Dinucleotide Arrangements within Ultra-Conserved Non-Coding Elements and the Human Genome
Authors: Fedorova Larisa , Crossley Emily R. , Mulyar Oleh A. , Qiu Shuhao , Freeman Ryan , Fedorov Alexei
Published: August 2023

Long human ultra-conserved non-coding elements (UCNEs) do not have any sequence similarity to each other or other characteristics that make them unalterable during vertebrate evolution. We hypothesized that UCNEs have unique dinucleotide (DN) composition and arrangements compared to the rest of the genome. A total of 4272 human UCNE sequences were analyzed computationally and compared with the whole genomes of human, chicken, zebrafish, and fly. Statistical analysis was performed to assess the non-randomness in DN spacing arrangements within the entire human genome and within UCNEs. Significant non-randomness in DN spacing arrangements was observed in the entire human genome. Additionally, UCNEs exhibited distinct patterns in DN arrangements compared to the rest of the genome. Approximately 83% of all DN pairs within UCNEs showed significant (>10%) non-random genomic arrangements at short distances (2–6 nucleotides) relative to each other. At the extremes, non-randomness in DN spacing distances deviated up to 40% from expected values and were frequently associated with GpC, CpG, ApT, and GpG/CpC dinucleotides. The described peculiarities in DN arrangements have persisted for hundreds of millions of years in vertebrates. These distinctive patterns may suggest that UCNEs have specific DNA conformations.
Metabolic Heterogeneity, Plasticity, and Adaptation to “Glutamine Addiction” in Cancer Cells: The Role of Glutaminase and the GTωA [Glutamine Transaminase—ω-Amidase (Glutaminase II)] Pathway
Authors: Cooper Arthur J. L. , Dorai Thambi , Pinto John T. , Denton Travis T.
Published: August 2023

Many cancers utilize l-glutamine as a major energy source. Often cited in the literature as “l-glutamine addiction”, this well-characterized pathway involves hydrolysis of l-glutamine by a glutaminase to l-glutamate, followed by oxidative deamination, or transamination, to α-ketoglutarate, which enters the tricarboxylic acid cycle. However, mammalian tissues/cancers possess a rarely mentioned, alternative pathway (the glutaminase II pathway): l-glutamine is transaminated to α-ketoglutaramate (KGM), followed by ω-amidase (ωA)-catalyzed hydrolysis of KGM to α-ketoglutarate. The name glutaminase II may be confused with the glutaminase 2 (GLS2) isozyme. Thus, we recently renamed the glutaminase II pathway the “glutamine transaminase—ω-amidase (GTωA)” pathway. Herein, we summarize the metabolic importance of the GTωA pathway, including its role in closing the methionine salvage pathway, and as a source of anaplerotic α-ketoglutarate. An advantage of the GTωA pathway is that there is no net change in redox status, permitting α-ketoglutarate production during hypoxia, diminishing cellular energy demands. We suggest that the ability to coordinate control of both pathways bestows a metabolic advantage to cancer cells. Finally, we discuss possible benefits of GTωA pathway inhibitors, not only as aids to studying the normal biological roles of the pathway but also as possible useful anticancer agents.
Methods for Radiolabeling Nanoparticles (Part 3): Therapeutic Use
Authors: Bentivoglio Valeria , Nayak Pallavi , Varani Michela , Lauri Chiara , Signore Alberto
Published: August 2023

Following previously published systematic reviews on the diagnostic use of nanoparticles (NPs), in this manuscript, we report published methods for radiolabeling nanoparticles with therapeutic alpha-emitting, beta-emitting, or Auger’s electron-emitting isotopes. After analyzing 234 papers, we found that different methods were used with the same isotope and the same type of nanoparticle. The most common type of nanoparticles used are the PLGA and PAMAM nanoparticles, and the most commonly used therapeutic isotope is 177Lu. Regarding labeling methods, the direct encapsulation of the isotope resulted in the most reliable and reproducible technique. Radiolabeled nanoparticles show promising results in metastatic breast and lung cancer, although this field of research needs more clinical studies, mainly on the comparison of nanoparticles with chemotherapy.
Long-Term Culturing of FreeStyle 293-F Cells Affects Immunoglobulin G Glycome Composition
Authors: Lukšić Fran , Mijakovac Anika , Josipović Goran , Vičić Bočkor Vedrana , Krištić Jasminka , Cindrić Ana , Vinicki Martina , Rokić Filip , Vugrek Oliver , Lauc Gordan , Zoldoš Vlatka
Published: August 2023

Glycosylation of IgG regulates the effector function of this antibody in the immune response. Glycosylated IgG is a potent therapeutic used for both research and clinical purposes. While there is ample research on how different cell culture conditions affect IgG glycosylation, the data are missing on the stability of IgG glycome during long cell passaging, i.e., cell “aging”. To test this, we performed three independent time course experiments in FreeStyle 293-F cells, which secrete IgG with a human-like glycosylation pattern and are frequently used to generate defined IgG glycoforms. During long-term cell culturing, IgG glycome stayed fairly stable except for galactosylation, which appeared extremely variable. Cell transcriptome analysis revealed no correlation in galactosyltransferase B4GALT1 expression with galactosylation change, but with expression of EEF1A1 and SLC38A10, genes previously associated with IgG galactosylation through GWAS. The FreeStyle 293-F cell-based system for IgG production is a good model for studies of mechanisms underlying IgG glycosylation, but results from the present study point to the utmost importance of the need to control IgG galactosylation in both in vitro and in vivo systems. This is especially important for improving the production of precisely glycosylated IgG for therapeutic purposes, since IgG galactosylation affects the inflammatory potential of IgG.
Application of Intelligent Medical Sensing Technology
Authors: Fu Jie , Gao Qiya , Li Shuang
Published: August 2023

With the popularization of intelligent sensing and the improvement of modern medical technology, intelligent medical sensing technology has emerged as the times require. This technology combines basic disciplines such as physics, mathematics, and materials with modern technologies such as semiconductors, integrated circuits, and artificial intelligence, and has become one of the most promising in the medical field. The core of intelligent medical sensor technology is to make existing medical sensors intelligent, portable, and wearable with full consideration of ergonomics and sensor power consumption issues in order to conform to the current trends in cloud medicine, personalized medicine, and health monitoring. With the development of automation and intelligence in measurement and control systems, it is required that sensors have high accuracy, reliability, and stability, as well as certain data processing capabilities, self-checking, self-calibration, and self-compensation, while traditional medical sensors cannot meet such requirements. In addition, to manufacture high-performance sensors, it is also difficult to improve the material process alone, and it is necessary to combine computer technology with sensor technology to make up for its performance shortcomings. Intelligent medical sensing technology combines medical sensors with microprocessors to produce powerful intelligent medical sensors. Based on the original sensor functions, intelligent medical sensors also have functions such as self-compensation, self-calibration, self-diagnosis, numerical processing, two-way communication, information storage, and digital output. This review focuses on the application of intelligent medical sensing technology in biomedical sensing detection from three aspects: physical sensor, chemical sensor, and biosensor.
High-Accuracy Renal Cell Carcinoma Discrimination through Label-Free SERS of Blood Serum and Multivariate Analysis
Authors: Buhas Bogdan Adrian , Toma Valentin , Crisan Nicolae , Ploussard Guillaume , Maghiar Teodor Andrei , Știufiuc Rareș-Ionuț , Lucaciu Constantin Mihai
Published: August 2023

Renal cell carcinoma (RCC) represents the sixth most frequently diagnosed cancer in men and is asymptomatic, being detected mostly incidentally. The apparition of symptoms correlates with advanced disease, aggressive histology, and poor outcomes. The development of the Surface-Enhanced Raman Scattering (SERS) technique opened the way for investigating and detecting small molecules, especially in biological liquids such as serum or blood plasma, urine, saliva, and tears, and was proposed as a simple technique for the diagnosis of various diseases, including cancer. In this study, we investigated the use of serum label-free SERS combined with two multivariate analysis tests: Principal Component Analysis combined with Linear Discriminate Analysis (PCA-LDA) and Supported Vector Machine (SVM) for the discrimination of 50 RCC cancer patients from 45 apparently healthy donors. In the case of LDA-PCA, we obtained a discrimination accuracy of 100% using 12 principal components and a quadratic discrimination function. The accuracy of discrimination between RCC stages was 88%. In the case of the SVM approach, we obtained a training accuracy of 100%, a validation accuracy of 92% for the discrimination between RCC and controls, and an accuracy of 81% for the discrimination between stages. We also performed standard statistical tests aimed at improving the assignment of the SERS vibration bands, which, according to our data, are mainly due to purinic metabolites (uric acid and hypoxanthine). Moreover, our results using these assignments and Student’s t-test suggest that the main differences in the SERS spectra of RCC patients are due to an increase in the uric acid concentration (a conclusion in agreement with recent literature), while the hypoxanthine concentration is not statistically different between the two groups. Our results demonstrate that label-free SERS combined with chemometrics holds great promise for non-invasive and early detection of RCC. However, more studies are needed to validate this approach, especially when combined with other urological diseases.
Social Interaction, Survival Stress and Smoking Behavior of Migrant Workers in China—An Empirical Analysis Using CHARLS Data from 2013–2018
Authors: Kong Fanzhen , Chen Huiguang , Cheng Yu
Published: August 2023

Smoking is a major public health problem in most countries and usually occurs in marginalized groups. Analyzing the smoking behavior of migrant workers, a marginalized group in China, is of practical significance. Using panel data from the China Health and Retirement Longitudinal Study (CHARLS) database from 2013 to 2018, this study examined influence factors of smoking behavior (whether to smoke and smoking frequency) among migrant workers in China through the Heckman two-stage model. The results showed that the smoking rates of migrant workers were positively associated with social activity and a sense of loneliness, while smoking frequency was negatively associated with work stress and life satisfaction. Meanwhile, smoking behavior was associated with the demographic variables such as gender, age, and education level. Gender differences in smoking behavior were particularly notable among Chinese migrant workers. Furthermore, there was regional heterogeneity in smoking behavior among migrant workers. Smoking behavior in the eastern region was mainly influenced by psychological factors of wellbeing, such as social activity and life satisfaction, while it was affected by material conditions such as income in the central-western region. Effective strategies to control tobacco use among migrant workers are proposed in order to promote social integration between urban and rural residents, increase vocational education and training, and strengthen anti-smoking propaganda among migrant workers.
Towards Sustainable Construction: A Systematic Review of Circular Economy Strategies and Ecodesign in the Built Environment
Authors: Timm Janaine Fernanda Gaelzer , Maciel Vinícius Gonçalves , Passuello Ana
Published: August 2023

This review discusses the unsustainable nature of current production and consumption patterns, particularly in the civil construction sector. To address this, the circular economy model has been proposed as a solution, but the impact reduction of circular strategies (CS) is not well understood. Thus, aligning CS with ecodesign can help achieve sustainable development. We conducted a systematic review of studies on CS and ecodesign strategies (ES) in the built environment, which led us to identify 23 essential strategies, including reuse, recycling, design for disassembly, and design for life extension. This article expands on previous research by identifying 51 CS and ES, some of which are interconnected, and adopting one strategy may benefit another. The authors propose a framework based on the Plan-Do-Check-Act concept to support and manage trade-offs when selecting strategies and to facilitate a collaborative decision-making process. The framework can also help manage the effects of using these strategies on circularity and environmental, social, and economic performance, ultimately improving the construction sector’s environmental performance.
Roles of Artificial Intelligence and Machine Learning in Enhancing Construction Processes and Sustainable Communities
Authors: Kazeem Kayode O. , Olawumi Timothy O. , Osunsanmi Temidayo
Published: August 2023

Machine Learning (ML), a subset of Artificial Intelligence (AI), is gaining popularity in the architectural, engineering, and construction (AEC) sector. This systematic study aims to investigate the roles of AI and ML in improving construction processes and developing more sustainable communities. This study intends to determine the various roles played by AI and ML in the development of sustainable communities and construction practices via an in-depth assessment of the current literature. Furthermore, it intends to predict future research trends and practical applications of AI and ML in the built environment. Following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, this study highlights the roles that AI and ML technologies play in building sustainable communities, both indoors and out. In the interior environment, they contribute to energy management by optimizing energy usage, finding inefficiencies, and recommending modifications to minimize consumption. This contributes to reducing the environmental effect of energy generation. Similarly, AI and ML technologies aid in addressing environmental challenges. They can monitor air quality, noise levels, and waste management systems to quickly discover and minimize pollution sources. Likewise, AI and ML applications in construction processes enhance planning, scheduling, and facility management.
Examining the Relative Importance and Association between Safety Leadership Styles and Factors Affecting Organizational Safety Climate
Authors: Sankar S. Senthamizh , Anandh K. S. , Rajendran Sathyanarayanan , Ibrahim Che Khairil Izam Che , Szóstak Mariusz
Published: August 2023

This study identifies safety leadership factors affecting construction site safety and organizational safety climate, offering suggestions for adopting optimistic leadership styles and a zero-accident vision. The literature review is done exclusively for identifying factors and improving core knowledge. This study developed a questionnaire to examine the relationships between the organizational safety climate and the safety leadership styles. The questionnaire was distributed to construction companies from all over India. The statistical analysis encompassed 396 verified responses from the survey, yielding an impressive 79.20 percent response rate. The valid responses collected were analysed to find the relative importance index and the association between the categorical variables. The results showed that “personal safety knowledge” ranked the highest while performing the relative importance index analysis. Furthermore, the chi-square analysis found two pessimistic leadership styles, namely “laissez-faire leadership” and “management-by-exception”, significantly associated with the safety climate. The study implies that the target audience must avoid adopting the two pessimistic leadership styles to improve the organizational safety climate. This study examines the various safety leadership styles practised among construction professionals for the first time in India. Specifically, it identifies critical factors that affect the organizational safety climate and pessimistic leadership styles that diminish the safety outcomes of the construction site. The results act as an eye-opener for the targeted audience (like senior and middle-level management professionals, academicians, and upcoming researchers) to enhance the safety of construction sites by adopting optimistic leadership styles with an idea of a ‘zero accident’ construction premises.
Risk Analysis in Implementing Building Energy Performance Projects: Hybrid DANP-VIKOR Model Analysis—A Case Study in Iran
Authors: Naderi Hossein , Heydari Mohammad Hossein , Parchami Jalal Majid
Published: August 2023

Building energy performance contracts have emerged as a highly effective strategy for reducing energy consumption in both developed and developing markets. These projects inherently involve risks, and a comprehensive risk analysis can greatly enhance their successful implementation, especially in emerging markets. This research aims to analyze risks associated with building energy performance projects, considering their interrelationships, prioritization, and the ranking of optimal project types based on the analyzed risks. Given its position as the largest electrical energy consumer in the Middle East and its status as an emerging market, Iran was selected as the case study for conducting the risk analysis. Thirteen risk factors were classified into four distinct risk groups, and their relationships and priority weights were determined using a hybrid DANP approach. Subsequently, the VIKOR method was employed to rank the most-advantageous project types based on their risk priorities. The findings of this research identified project lifecycle risks as the highest-priority risks, while external risks were determined to be the most-influential among all identified risks. Moreover, the implementation of packaged public projects was identified as the most-favorable alternative for promoting building energy performance projects in Iran and similar emerging markets. By providing a comprehensive understanding of risks, this study offers valuable insights that can aid emerging and developing markets in successfully implementing energy performance projects and improving overall energy efficiency.
Palliative Care Clinician Perspectives on Person-Centered End-of-Life Communication for Racially and Culturally Minoritized Persons with Cancer
Authors: Rosa William E. , McDarby Meghan , Buller Haley , Ferrell Betty R.
Published: August 2023

The aim of this study was to examine interdisciplinary clinicians’ perceptions of priorities in serious illness communication and shared decision-making with racially and culturally minoritized persons at end of life. Clinicians (N = 152) read a detailed case study about a patient self-identifying as Black and American Indian who describes mistrust of the healthcare system. Participants then responded to three open-ended questions about communication strategies and approaches they would employ in providing care. We conducted a thematic analysis of participants’ responses to questions using an iterative, inductive approach. Interdisciplinary clinicians from nursing (48%), social work (36%), and chaplaincy (16%), responded to the study survey. A total of four themes emerged: (1) person-centered, authentic, and culturally-sensitive care; (2) pain control; (3) approaches to build trust and connection; and (4) understanding communication challenges related to racial differences. Significant efforts have been made to train clinicians in culturally inclusive communication, yet we know little about how clinicians approach “real world” scenarios during which patients from structurally minoritized groups describe care concerns. We outline implications for identifying unconscious bias, informing educational interventions to support culturally inclusive communication, and improving the quality of end-of-life care for patients with cancer from minoritized groups.
Association of Nasopharynx Cancer with Human Papillomavirus Infections
Authors: Hung Shih-Han , Yang Tzong-Hann , Cheng Yen-Fu , Chen Chin-Shyan , Lin Herng-Ching
Published: August 2023

This population-based study aims to examine the association between nasopharyngeal carcinoma and human papillomavirus infections. This study included 2747 individuals aged 20 years and older who were diagnosed with nasopharynx cancer as cases and 13,735 propensity-score-matching controls. Multivariate logistic regression models were employed to quantitatively assess the association of nasopharynx cancer with human papillomavirus infections while considering age, sex, monthly income, geographic location, and urbanization level of the patient’s residence as well as diabetes, hypertension, and hyperlipidemia. Our chi-squared test indicated a significant dissimilarity in previous human papillomavirus infection rates between nasopharynx cancer patients and controls (12.7% vs. 7.2%, p < 0.001). The adjusted odds ratio (OR) for prior human papillomavirus infections was found to be significantly higher for nasopharyngeal carcinoma cases compared to controls at a value of 1.869 with confidence interval ranging from 1.640 to 2.128. Among female participants, compared to controls, the adjusted OR of prior human papillomavirus infections was 2.150 (95% CI = 1.763–2.626) in patients with nasopharynx cancer. In male participants sampled in this study, we observed a statistically significant association between prior human papillomavirus infections and nasopharynx cancer (adjusted OR = 1.689; 95% CI = 1.421–2.008). Our study indicates a noteworthy association between previous human papillomavirus infections and nasopharyngeal carcinoma.
Dissecting Microbiome-Derived SCFAs in Prostate Cancer: Analyzing Gut Microbiota, Racial Disparities, and Epigenetic Mechanisms
Authors: Miya Thabiso Victor , Marima Rahaba , Damane Botle Precious , Ledet Elisa Marie , Dlamini Zodwa
Published: August 2023

Prostate cancer (PCa) continues to be the most diagnosed cancer and the second primary cause of fatalities in men globally. There is an abundance of scientific evidence suggesting that the human microbiome, together with its metabolites, plays a crucial role in carcinogenesis and has a significant impact on the efficacy of anticancer interventions in solid and hematological cancers. These anticancer interventions include chemotherapy, immune checkpoint inhibitors, and targeted therapies. Furthermore, the microbiome can influence systemic and local immune responses using numerous metabolites such as short-chain fatty acids (SCFAs). Despite the lack of scientific data in terms of the role of SCFAs in PCa pathogenesis, recent studies show that SCFAs have a profound impact on PCa progression. Several studies have reported racial/ethnic disparities in terms of bacterial content in the gut microbiome and SCFA composition. These studies explored microbiome and SCFA racial/ethnic disparities in cancers such as colorectal, colon, cervical, breast, and endometrial cancer. Notably, there are currently no published studies exploring microbiome/SCFA composition racial disparities and their role in PCa carcinogenesis. This review discusses the potential role of the microbiome in PCa development and progression. The involvement of microbiome-derived SCFAs in facilitating PCa carcinogenesis and their effect on PCa therapeutic response, particularly immunotherapy, are discussed. Racial/ethnic differences in microbiome composition and SCFA content in various cancers are also discussed. Lastly, the effects of SCFAs on PCa progression via epigenetic modifications is also discussed.
IMP3 Expression as a Potential Tumour Marker in High-Risk Localisations of Cutaneous Squamous Cell Carcinoma: IMP3 in Metastatic cSCC
Authors: Klein Maurice , Wefers Merle , Hallermann Christian , Fischer Henrike J. , Hölzle Frank , Wermker Kai
Published: August 2023

Background: High IMP3 expression is correlated with a worse outcome. Until now, there have been no data about IMP3 expression and clinical outcome for high-risk localisation of squamous cell carcinoma of the skin (cSCC). Methods: One-hundred twenty-two patients with cSCC of the lip and ear were included, and IMP3 expression in the tumours was immunohistochemically assessed in different evaluation approaches. Subsequently, subgroups were analysed in a matched pair approach and correlated with clinical pathologic parameters. In the following, different IMP3 analysis methods were tested for clinical suitability. Results: We found a significant correlation between IMP3 expression and risk for lymph node metastasis, local relapse, and progression-free survival. Conclusions: On basis of our data, we suggest a prognostic benefit cutoff value for high (>50%) and low (<50%) IMP3 expression. Thus, IMP3 expression has a high scientific potential for further studies and could potentially be used as a prognostic marker in diagnostic and therapeutic decision-making.
Exploring Opportunities to Enhance the Screening and Surveillance of Hepatocellular Carcinoma in Non-Alcoholic Fatty Liver Disease (NAFLD) through Risk Stratification Algorithms Incorporating Ultrasound Elastography
Authors: Taru Madalina-Gabriela , Lupsor-Platon Monica
Published: August 2023

Non-alcoholic fatty liver disease (NAFLD), with its progressive form, non-alcoholic steatohepatitis (NASH), has emerged as a significant public health concern, affecting over 30% of the global population. Hepatocellular carcinoma (HCC), a complication associated with both cirrhotic and non-cirrhotic NAFLD, has shown a significant increase in incidence. A substantial proportion of NAFLD-related HCC occurs in non-cirrhotic livers, highlighting the need for improved risk stratification and surveillance strategies. This comprehensive review explores the potential role of liver ultrasound elastography as a risk assessment tool for HCC development in NAFLD and highlights the importance of effective screening tools for early, cost-effective detection and improved management of NAFLD-related HCC. The integration of non-invasive tools and algorithms into risk stratification strategies could have the capacity to enhance NAFLD-related HCC screening and surveillance effectiveness. Alongside exploring the potential advancement of non-invasive tools and algorithms for effectively stratifying HCC risk in NAFLD, we offer essential perspectives that could enable readers to improve the personalized assessment of NAFLD-related HCC risk through a more methodical screening approach.
Editorial: Special Issue on “Photocatalysts for Pollutants Disposals, CO2 Reduction, Hydrogen Evolution Reaction”
Authors: Yang Kai , Yu Changlin
Published: August 2023

The global energy and environmental crisis are some of the most pressing challenges facing mankind [...]
Two-Stage Conversion of Used Cooking Oil to Biodiesel Using Ion Exchange Resins as Catalysts
Authors: Abidin Sumaiya Zainal , Mohammed Misbahu Ladan , Saha Basudeb
Published: August 2023

This study focuses on the development of a novel two-stage (esterification–transesterification) synthesis of biodiesel from used cooking oil (UCO) using ion exchange resins as catalysts. Esterification of the UCO has been conducted using various types of ion exchange resin catalysts. Purolite D5081, a hyper cross-linked resin, showed the best catalytic performance among all the catalysts investigated, with 92% of free fatty acid (FFA) conversion. The transesterification of pre-treated used cooking oil (P-UCO) was carried out sequentially using several acidic and basic ion exchange resin catalysts. In the screening process, the Diaion PA306s catalyst showed the best catalytic performance and was selected for the optimisation study. A triglyceride conversion of ca. 75% was recorded at the optimum reaction conditions (9% (w/w) catalyst loading, 328 K reaction temperature, 18:1 methanol to P-UCO feed mole ratio, and 350 rpm stirring speed). Furthermore, the reusability study of the Diaion PA306s catalyst gave a similar triglyceride conversion after a couple of cycles without losing its catalytic activity. A dry purification technique was found to give the lowest percentage of glycerides and glycerine content and, therefore, was chosen as the best biodiesel purification route.