bluuebunny/crossref_metadata_2025 huggingface dataset:
The Subjective Well-Being of the Staff at a Teaching Dental Center in a COVID-19 Epidemiological Surveillance System between the Years 2020 and 2022
Authors: Corituma-Basaldua Fabiola Antonella , Negrón-Saldaña Lucía Rafaela , Rojas-Susanibar Carola , Pérez-Alvarez Daniel Kevin , Garcés-Elías María Claudia , León-Manco Roberto A.
Published: September 2024

Subjective well-being (SW) is understood as the personal judgment that an individual has about their value, perception, and level of satisfaction with respect to his or her life and existence. The present study had the purpose of understanding how pandemics have affected subjective well-being; therefore, the objective was to determine the subjective well-being of the staff at a teaching dental center in a COVID-19 epidemiological surveillance system between the years 2020 and 2022. A cross-sectional design was applied and was based on data from two records of the Centro Dental Docente of the Universidad Peruana Cayetano Heredia, Lima, Peru, between the years 2021 and 2022. The results show that the mean SW did not significantly vary (p = 0.114) between 2021 (69.32; SD = 19.92) and 2022 (63.16; SD = 29.87). At a bivariate level, significant associations were also observed between SW and multiple variables such as the diagnosis and type of COVID-19, vaccination, contact with COVID-19 patients, systemic conditions, body mass index, educational level, gender, and age. Meanwhile, according to the regression analysis, not having COVID-19 was positively associated with higher levels of subjective well-being. This study highlights the impact of the COVID-19 pandemic on the mental and emotional states of dental healthcare personnel, emphasizing the need for strategies to mitigate stress and anxiety in such critical work environments.
The Prevalence of Gestational Diabetes Mellitus in Polycystic Ovary Disease—A Systematic Review, Meta-Analysis, and Exploration of Associated Risk Factors
Authors: Dube Rajani , Bambani Taniqsha , Saif Sahina , Hashmi Noha , Patni Mohamed Anas Mohamed Faruk , Kedia Noopur Ramesh
Published: September 2024

Polycystic ovary syndrome (PCOS) is a common condition in reproductive-age women. Women with PCOS are at higher risk of pregnancy complications, including gestational diabetes (GDM). The prevalence of PCOS and GDM varies according to the diagnostic criteria used. The mechanism for the occurrence of GDM in women with PCOS is still unclear. Materials and Methods: A systematic search of the electronic database was done using keywords like PCOS and GDM to include studies between April 2008 and March 2023 where uniform diagnostic criteria were used. After assessing the risk of bias, studies with a high risk (of bias) were excluded, and a meta-analysis was conducted using relative risks and confidence intervals. Results and Discussion: Out of 1896 search results, 95 were selected for full-text review. The quality of the studies was scrutinized and a total of 28 studies were included as they fulfilled the inclusion criteria. The incidence of GDM in women with PCOS was found to be 10.55% (2.9–54.9%) from pooled data involving 1,280,245 women. The prevalence of PCOS in women diagnosed with GDM, based on pooled data from 36,351 women across retrospective studies, was found to be 2.47% (ranging from 1.5% to 50.1%). Selection predominantly included cohort studies, most commonly from China. The meta-analysis found that the risk of GDM is higher in women with PCOS than in those without PCOS (HR: 1.59, 95% CI: 1.27–1.91, p < 0.001). Family history of diabetes, ethnicity, high pre-pregnancy BMI, insulin resistance, gestational weight gain, use of assisted reproductive techniques, and multifetal gestation were found to be associated with GDM in women with PCOS. Conclusion: The prevalence of GDM in patients with PCOS is high, but the causality is complex. The newer predictive models are promising in clarifying the causative relationships, yet use various parameters with different cut-offs. There is a need for the development of universally acceptable parameters for the early prediction of GDM in women with PCOS.
Estimating Methane Emissions in Rice Paddies at the Parcel Level Using Drone-Based Time Series Vegetation Indices
Authors: Song Yongho , Song Cholho , Choi Sol-E , Kim Joon , Kim Moonil , Hwang Wonjae , Roh Minwoo , Lee Sujong , Lee Woo-Kyun
Published: September 2024

This study investigated a method for directly estimating methane emissions from rice paddy fields at the field level using drone-based time-series vegetation indices at a town scale. Drone optical and spectral images were captured approximately 15 times from April to November to acquire time-series vegetation indices and optical orthoimages. An empirical regression model validated in previous international studies was applied to calculate cumulative methane emissions throughout the rice cultivation process. Methane emissions were estimated using the vegetation index and yield data were used as input variables for each growth phase. Methane emissions from rice paddies showed maximum values of 309 kg CH4 ha−1, within a 7% range compared to similar studies, and minimum values of 138 kg CH4 ha−1, with differences ranging from 29% to 58%. The average emissions were calculated at 247 kg CH4/ha, revealing slightly lower average values but individual field values within a similar range. The results suggest that drone-based remote sensing technology is an efficient and cost-effective alternative to traditional field measurements for greenhouse gas emission assessments. However, adjustments and validations according to rice varieties and local cultivation environments are necessary. Overcoming these limitations can help establish sustainable agricultural management practices and achieve local greenhouse gas reduction targets.
Score-Driven Interactions for “Disease X” Using COVID and Non-COVID Mortality
Authors: Blazsek Szabolcs , Dos Santos William M. , Edwards Andreco S.
Published: September 2024

The COVID-19 (coronavirus disease of 2019) pandemic is over; however, the probability of such a pandemic is about 2% in any year. There are international negotiations among almost 200 countries at the World Health Organization (WHO) concerning a global plan to deal with the next pandemic on the scale of COVID-19, known as “Disease X”. We develop a nonlinear panel quasi-vector autoregressive (PQVAR) model for the multivariate t-distribution with dynamic unobserved effects, which can be used for out-of-sample forecasts of causes of death counts in the United States (US) when a new global pandemic starts. We use panel data from the Centers for Disease Control and Prevention (CDC) for the cross section of all states of the United States (US) from March 2020 to September 2022 regarding all death counts of (i) COVID-19 deaths, (ii) deaths that medically may be related to COVID-19, and (iii) the remaining causes of death. We compare the t-PQVAR model with its special cases, the PVAR moving average (PVARMA), and PVAR. The t-PQVAR model provides robust evidence on dynamic interactions among (i), (ii), and (iii). The t-PQVAR model may be used for out-of-sample forecasting purposes at the outbreak of a future “Disease X” pandemic.
Balancing the Scale: Data Augmentation Techniques for Improved Supervised Learning in Cyberattack Detection
Authors: Medvedieva Kateryna , Tosi Tommaso , Barbierato Enrico , Gatti Alice
Published: September 2024

The increasing sophistication of cyberattacks necessitates the development of advanced detection systems capable of accurately identifying and mitigating potential threats. This research addresses the critical challenge of cyberattack detection by employing a comprehensive approach that includes generating a realistic yet imbalanced dataset simulating various types of cyberattacks. Recognizing the inherent limitations posed by imbalanced data, we explored multiple data augmentation techniques to enhance the model’s learning effectiveness and ensure robust performance across different attack scenarios. Firstly, we constructed a detailed dataset reflecting real-world conditions of network intrusions by simulating a range of cyberattack types, ensuring it embodies the typical imbalances observed in genuine cybersecurity threats. Subsequently, we applied several data augmentation techniques, including SMOTE and ADASYN, to address the skew in class distribution, thereby providing a more balanced dataset for training supervised machine learning models. Our evaluation of these techniques across various models, such as Random Forests and Neural Networks, demonstrates significant improvements in detection capabilities. Moreover, the analysis also extends to the investigation of feature importance, providing critical insights into which attributes most significantly influence the predictive outcomes of the models. This not only enhances the interpretability of the models but also aids in refining feature engineering and selection processes to optimize performance.
Palm Oil (Elaeis guineensis): A Journey through Sustainability, Processing, and Utilization
Authors: Alhaji Adamu Muhammad , Almeida Erislene S. , Carneiro Camila Rodrigues , da Silva César Augusto Sodré , Monteiro Simone , Coimbra Jane Sélia dos Reis
Published: September 2024

Palm oil, derived from Elaeis guineensis, is a critical component of the global edible oil and industrial fat market. This review provides a comprehensive overview of the sustainability of the palm oil chain, focusing on industrial applications, environmental implications, and economic sustainability. The processing of palm oil, from fruit pulp to refined oil, is detailed, highlighting the importance of refining in maintaining quality and extending application ranges. While palm oil offers health benefits because of its rich fatty acid composition and antioxidant properties, its production poses significant environmental challenges. This review underscores ongoing efforts to balance technological and culinary demands with environmental stewardship and sustainable economic growth. Emerging trends, including interspecific hybrids such as E. guineensis and E. oleifera, are discussed for their potential to increase sustainability and productivity.
Affective–Sexual Behaviors in Youth: Analysis of a Public Health Survey in the School Setting
Authors: Zafra-Agea José Antonio , Ramírez-Baraldes Estel·la , García-Salido Cristina , García-Gutiérrez Daniel , Vilafranca-Cartagena Mireia
Published: September 2024

Introduction: Adolescence is a critical period for the development of affectivity and sexuality. Adolescents begin to explore their sexual identities, form intimate relationships, and learn to manage their emotions in new and complex contexts. This study aims to analyze the prevalence of habits and behaviors related to the affective–sexual health of adolescents in the fourth year of ESO, identifying risk factors, comparing their behaviors and risks, monitoring these behaviors, analyzing their pornography consumption, and evaluating the use of the internet as a source of sexual information. Method: Descriptive cross-sectional study using questionnaires. Participants are fourth-year ESO students from a school in the Baix Llobregat province (Catalonia), aged between 14 and 18 years. Descriptive and bivariate statistical analyses are conducted using the chi-square test and p-value calculations with the R Project software. Frequency and percentage analyses are also used to describe the health behaviors of the participants. Results: The study reveals that girls have better knowledge of the contraceptive pill and male condom than boys. Sexual initiation and condom use management vary between the genders, with girls being more capable of persuading their partners to use them. Pornography consumption also shows significant differences in terms of the age of initiation and frequency between boys and girls. Conclusions: This study on adolescent affectivity and sexuality reveals knowledge about contraceptives, early sexual initiation, and high pornography consumption, highlighting the need for early and diverse affective–sexual education, youth empowerment, and media misinformation management to promote safer and healthier behaviors within municipal public health.
Sexual and Reproductive Health Rights and Service Use among Undocumented Migrants in the EU: A Systematic Literature Review
Authors: Mandroiu Alexandra , Alsubahi Nizar , Groot Wim , Pavlova Milena
Published: September 2024

Most EU member states fail to provide essential sexual and reproductive health services to undocumented migrants, a vulnerable population facing limited access, utilization, and worse health-related outcomes. This study systematically reviewed the literature on access to and use of these services, as well as related health, economic, and migratory outcomes for undocumented migrants in the EU-EFTA region. The systematic review is reported based on the PRISMA 2020 checklist and includes 37 studies published between 2017 and 2024. Included studies were based upon original quantitative, qualitative, or mixed-methods data; conducted in one or more European countries; and published in one or more of the following languages: English, Spanish, French, Portuguese, or Romanian. A quality assessment was conducted using the CASP checklist for qualitative studies and the NHLBI Study Quality Assessment Tools for quantitative studies. The findings revealed numerous access barriers, including refusal of care, lack of knowledge about national healthcare schemes, bureaucratic hurdles, and affordability issues. Even when care was available, stigma, fear of deportation, socio-economic precarity, and abuse further hindered utilization. These barriers contributed to generally worse reproductive health outcomes for undocumented migrants in Europe, though the findings may not generalize to all EU-EFTA countries.
Terminological Study for Scientific Hypothetical 3D Reconstruction
Authors: Fallavollita Federico , Foschi Riccardo , Apollonio Fabrizio Ivan , Cazzaro Irene
Published: September 2024

This paper presents preliminary findings from the ongoing Erasmus+ European project CoVHer, which focuses on the hypothetical virtual reconstructions of lost or unbuilt architecture. This contribution provides a critical assessment of the terminology specific to this field. A significant challenge lies in the absence of standardised terminology for many foundational aspects, which can lead to misconceptions and misunderstandings. The research begins with a comprehensive review of the relevant literature in the field, aiming to identify which terms are most widely accepted and appropriate to use and which are ambiguous or should be avoided. For concepts that lack a clear definition, new terminology is proposed. This paper analyses six key terms: reconstruction, uncertainty, raw model, informative model, digital representation methods, and 3D modelling techniques.
Sustainable Construction through Tradition: Inventory of Cob Buildings in the Guérande Peninsula (France)
Authors: Poullain Philippe , Miranda-Santos Marta , Hilton Alison , Hamard Erwan , Mouraud Corentin
Published: September 2024

This paper delves into the investigation and inventory of cob buildings within the Guérande Peninsula, employing an interdisciplinary framework merging academic inquiry, fieldwork, and digital cartographic methodologies. Against the backdrop of escalating environmental concerns within the construction sector, raw earth construction emerges as a compelling avenue for sustainable building practices due to its low embodied energy and reversible characteristics. Despite historical prevalence in regions such as northwest France, traditional earth-building techniques have experienced waning prominence with the advent of industrial materials. However, the resurgence of interest in raw earth’s minimal carbon footprint has catalyzed renewed attention towards earth-building methods. Through a meticulous investigation methodology, this study identifies and analyzes 802 potentially old cob buildings, with 46 structures confirmed as cob constructions. Employing statistical analyses of building characteristics, including wall and lift heights, preservation states, and geographical distributions, this research sheds light on the significance of preserving cob heritage amidst rapid urbanization. The findings underscore the imperative for ongoing research and awareness efforts to safeguard these vernacular architectural traditions. By illuminating centuries-old building practices, this research contributes to the scholarly discourse on sustainable construction methodologies and local cultural preservation. Moreover, it underscores the necessity of integrating traditional knowledge systems with contemporary sustainability initiatives to foster resilience and longevity within the built environment.
Bibliometric Analysis of River Erosion Control Measures: Examination of Practices and Barriers in Colombia
Authors: Calixto Nelson , Castaño Alberto , Contreras-Ropero Jefferson
Published: September 2024

This study presents a comprehensive bibliometric analysis of research on bank erosion and control measures, utilizing the Scopus database and VOSviewer software. Key terms such as “bank”, “erosion”, “control”, and “protection” frequently appear in the literature, underscoring their importance in studies on riverbank erosion. Since 2000, scientific production has steadily increased, particularly in disciplines such as Environmental Sciences and Earth and Planetary Sciences, driven by growing concerns about climate change and sustainable water resource management. Countries with substantial research resources, such as the United States and China, lead in the production of studies, reflecting their commitment to addressing this global issue. In parallel, the evaluation of erosion mitigation practices in Colombia revealed that, although effective techniques such as gabion walls and riparian vegetation exist, 40% of respondents do not implement specific measures. This lack of implementation is attributed to insufficient knowledge, limited resources, and misconceptions about the effectiveness of these techniques. The findings highlight the need to promote proven practices and enhance professional training. Future research should focus on developing more accurate predictive models, integrating interdisciplinary approaches, and assessing the impacts of climate change on bank erosion. Addressing barriers to applying effective techniques at the local level and improving access to resources and knowledge are critical steps to reducing bank erosion and ensuring sustainable water management.
Direct Cardiac Reprogramming in the Age of Computational Biology
Authors: Ambroise Rachelle , Takasugi Paige , Liu Jiandong , Qian Li
Published: September 2024

Heart disease continues to be one of the most fatal conditions worldwide. This is in part due to the maladaptive remodeling process by which ischemic cardiac tissue is replaced with a fibrotic scar. Direct cardiac reprogramming presents a unique solution for restoring injured cardiac tissue through the direct conversion of fibroblasts into induced cardiomyocytes, bypassing the transition through a pluripotent state. Since its inception in 2010, direct cardiac reprogramming using the transcription factors Gata4, Mef2c, and Tbx5 has revolutionized the field of cardiac regenerative medicine. Just over a decade later, the field has rapidly evolved through the expansion of identified molecular and genetic factors that can be used to optimize reprogramming efficiency. The integration of computational tools into the study of direct cardiac reprogramming has been critical to this progress. Advancements in transcriptomics, epigenetics, proteomics, genome editing, and machine learning have not only enhanced our understanding of the underlying mechanisms driving this cell fate transition, but have also driven innovations that push direct cardiac reprogramming closer to clinical application. This review article explores how these computational advancements have impacted and continue to shape the field of direct cardiac reprogramming.
The Effect of Statins on Carotid Intima–Media Thickness and C–Reactive Protein in Type 2 Diabetes Mellitus: A Meta–Analysis
Authors: Mashaba Given Reneilwe , Phoswa Wendy Nokhwezi , Mokgalaboni Kabelo
Published: September 2024

Background. The effect of statins on CIMT progression and C-reactive protein (CRP) in T2DM patients is widely reported. However, some studies demonstrated no effect of statins on CIMT and CRP in T2DM patients, while others reported otherwise. Thus, the current study comprehensively and quantitatively analyzes data from previous studies to evaluate the overall effect of statins on CIMT and CRP in T2DM to rule out any inconsistencies observed in previous clinical evidence. Therefore, the aim of this meta-oanalysis was to evaluate the effect of statins on CIMT progression and CRP in T2DM. Methods. A comprehensive search for studies was performed using PubMed, Scopus, Web of Sciences, and the Cochrane Library, for publications from their inception to 16 July 2024. The meta-analysis was conducted using Jamovi (version 4.2.8) and Review Manager (version 5.4), with the overall effect sizes reported as standardized mean differences (SMD) and 95% confidence intervals (CI). Results. Evidence from eleven studies (fifteen statin dosages) that met the inclusion criteria with a sample size of 983 T2DM patients on statin treatment was analyzed. The overall effect size from the random effect model meta-analysis showed a reduction in the CIMT status amongst T2DM patients post-statin treatment compared to at baseline [SMD = −0.47, 95%CI (−0.76, −0.18), p = 0.001]. Furthermore, there was a reduction in the level of CRP in T2DM patients post-treatment [SMD = −1.80, 95% CI (−2.76, −0.84), p < 0.001]. Conclusions. Evidence gathered in this study suggests that statin therapy effectively reduces CIMT and CRP levels among patients living with T2DM. Interestingly, this evidence suggests that 20 mg of atorvastatin is more effective in reducing CIMT and CRP. Therefore, we recommend conducting further trials with larger sample sizes and proper methodology for T2DM.
Underwater Acoustic Signal Detection against the Background of Non-Stationary Sea Noise
Authors: Khobotov Alexander Gennadievich , Kalinina Vera Igorevna , Khil’ko Alexander Ivanovich , Malekhanov Alexander Igorevich
Published: September 2024

In this paper, we further develop a novel, efficient approach to the problem of signal detection against background noise based on a nonlinear residual functional called the neuron-like criterion function (NCF). A detailed comparison of the NCF-based technique and the conventional correlation criterion function (CCF)-based matched-signal detection is performed. For this purpose, we calculated the detection performance curves for both techniques and found the range of the problem parameters in which the NCF-based detector shows a certain advantage. The latter consists of achieving a fixed value of detection probability at a lower threshold value of the input signal-to-noise ratio (SNR) compared to the CCF-based detector. Special attention is given to the practically important scenario of receiving a weak signal against the background of non-stationary noise with a certain trend (positive or negative) of its intensity. For these two specific cases, modified NCFs are given, which are then used for computer simulation. For both broadband and narrow-band signals, the quantitative bounds of the most effective use of the derived NCFs are established and interpreted. The real sea noise data obtained from two underwater acoustic arrays, one stationary on the sea bottom and the other towed near the sea surface, are used for experimental validation. The experimental data processing results confirm the simulation results and make it possible to demonstrate the advantage of the NCF if the noise intensity shows a significant trend over the signal observation interval. The latter case obviously corresponds to the use of the towed array in the coastal area.
Research on Intelligent Navigation Technology: Intelligent Guidance and Path-Following Control of USVs
Authors: Shang Xiaoyong , Zhang Guoqing , Lyu Hongguang , Tan Guifu
Published: September 2024

Research on unmanned surface vessels (USVs) has evolved significantly in recent decades. In particular, intelligent navigation technology has progressed from theoretical concepts to practical applications. As USV research in ocean engineering advances, there is an increasing demand for enhanced performance in intelligent guidance strategy and path-following control systems. This manuscript proposes future development directions for USVs by providing an overview of relevant standards for the intelligence level of these vessels and describing the current status of USV engineering practices. Based on practical ocean engineering requirements, safety considerations, and energy efficiency demands, this paper summarizes the current research status, future research challenges, and potential solutions for USV intelligent guidance and path-following control algorithms from the perspective of large ship intelligence. This manuscript provides a valuable reference for academic researchers and practitioners aiming to identify and position future development directions.
A Study on the Static and Dynamic Characteristics of the Spindle System of a Spiral Bevel Gear Grinding Machine
Authors: Huang Shuai , Wang Juxin , Huang Kaifeng , Yu Jianwu
Published: September 2024

To enhance the static and dynamic performance of the grinding wheel spindle system, with the gear grinding machine (YKF2060) as the research object, a static mechanics model of the spindle system was established based on Castigliano’s theorem, taking into account the equivalent effect of the triple-point contact ball bearing at the front end of the spindle. Meanwhile, based on the overall transfer matrix method, a dynamic model of the main spindle–eccentric shaft dual-rotor system was established, taking into account the effects of shear deformation and gyroscopic moments. On this basis, the effect of the spindle span, the front and rear overhang of the eccentric shaft, and the bearing stiffness on the static stiffness and first-order critical speed of the system was analyzed. Finally, static stiffness experiments, modal tests, and finite element simulation models were conducted to verify the static and dynamic models. The results show that the stiffness of the front outer bearing has the greatest influence on the static and dynamic performance of the system, while the stiffness of the rear inner bearing has the least influence. The relative errors of the static stiffness and the first two natural frequencies between static stiffness experiments, modal tests, and finite element simulation models are less than 10%, and the mode shapes match well. The established static and dynamic model can effectively reflect both the static and dynamic characteristics of the spindle system.
Relationship of Thyroid Volume and Function with Ankle-Brachial Index, Toe-Brachial Index, and Toe Pressure in Euthyroid People Aged 18–65
Authors: Jakubiak Grzegorz K. , Pawlas Natalia , Morawiecka-Pietrzak Małgorzata , Zalejska-Fiolka Jolanta , Stanek Agata , Cieślar Grzegorz
Published: September 2024

Background and Objectives: The interrelationship between thyroid function and the state of the cardiovascular system has been investigated both in preclinical and human studies. However, it remains unclear whether there is any association between thyroid hormones and features of subclinical cardiovascular dysfunction in euthyroid patients. Material and Methods: This study involved 45 people (females: 57.8%) with no thyroid disease who, during planned hospitalization, underwent thyroid ultrasound, determination of biochemical parameters of thyroid function, and measurement of ankle-brachial index (ABI) and toe-brachial index (TBI). People with signs of acute illness or a deterioration of their health were excluded. Results: Significant correlations were found between free triiodothyronine (FT3) and several parameters of both ABI (R = 0.347; p = 0.019 for the mean ABI taken from right side and left side values) and TBI (R = 0.396; p = 0.007 for the mean TBI taken from right side and left side values), as well as the maximal toe pressure (TP) taken from right side and left side values (R = 0.304; p = 0.045). Thyrotropin (TSH) was shown to be significantly correlated only with the maximal TBI value (taken from right side and left side values) (R = 0.318; p = 0.033), whereas free thyroxin (FT4) was shown to be significantly correlated only with the minimal TBI value (taken from right side and left side values) (R = 0.381; p = 0.01). Thyroid volume (TV) was shown to be correlated with TP (R = 0.4; p = 0.008 for the mean TP taken from right side and left side values) and some parameters of TBI value (R = 0.332; p = 0.028 for the mean TBI taken from right side and left side values), but no significant correlations were found between TVand ABI parameters. Patients with a mean ABI value ≤ 1.0 or a mean TBI value ≤ 0.75 have lower TSH, FT3, FT4, and TV than the rest of the study population, but the difference was statistically significant only for FT3. Conclusions: Even in a population of euthyroid patients with no diagnosed thyroid disease, there are some significant correlations between the volume and function of the thyroid gland and the selected features of subclinical cardiovascular dysfunction such as ABI and TBI.
Impact of Patient- and Surgeon-Related Factors on Weight Loss after Laparoscopic Sleeve Gastrectomy—A Single-Center Study
Authors: Wityk Mateusz , Dowgiałło-Gornowicz Natalia , Bobowicz Maciej
Published: September 2024

Background and Objectives: Surgical treatment for obesity is becoming increasingly popular. Surgeons have been trying to find a simple way to predict the type of surgical intervention that is best for a specific patient. This study aimed to determine the patient- and surgeon-related factors that affect weight loss after laparoscopic sleeve gastrectomy (LSG). Materials and Methods: A total of 129 patients underwent LSG in one surgical department. The following factors were analyzed: gender; age; highest preoperative and 6-month postoperative weight; the occurrence of obesity-related diseases, such as type 2 diabetes and hypertension; the number of surgeons involved in the surgery; and who performed the surgery, a resident or specialist. The outcomes also included length of hospital stay, operative time and complications. Statistical significance was defined as p ≤ 0.05. Results: A total of 129 patients (94 female) with a median age of 43 years and BMI of 43.1 kg/m2 underwent LSG, while a total of 109 (84.5%) patients achieved ≥50% of excess BMI loss (%EBMIL). Preoperative weight loss had no impact on %EBMIL (p = 0.95), operative time (p = 0.31) and length of hospital stay (p = 0.2). Two versus three surgeons in the operating team had no impact on surgery time (p = 0.1), length of stay (p = 0.98) and %EBMIL (p = 0.14). The operative time and length of hospital stay were similar for specialists and surgeons in training. %EBMIL was higher in the residents’ surgery without statistical significance (p = 0.19). Complications occurred in 3.9% without mortality or leaks. Conclusions: Preoperative comorbidities, surgeons’ experience and the number of surgeons in the operating team do not impact the complication rate, length of hospital stay, operative time and postoperative weight loss after LSG.
Development of Artificial Intelligence/Machine Learning (AI/ML) Models for Methane Emissions Forecasting in Seaweed
Authors: Louime Clifford Jaylen , Raza Tariq Asleem
Published: September 2024

This research project aimed to address the growing concern about methane emissions from seaweed by developing a Convolutional Neural Network (CNN) model capable of accurately predicting these emissions. The study used PANDAS to read and analyze the dataset, incorporating statistical measures like mean, median, and standard deviation to understand the dataset. The CNN model was trained using the ReLU activation function and mean absolute error as the loss function. The model performance was evaluated through MAPE graphs, comparing the mean absolute percentage error (MAPE) between training and validation sets and between true and predicted emissions, and analyzing trends in yearly greenhouse gas emissions. The results demonstrated that the CNN model achieved a high level of accuracy in predicting methane emissions, with a low MAPE between the expected and actual values. This approach should enhance our understanding of methane emissions from Sargassum, contributing to more accurate environmental impact assessments and effective mitigation strategies.
A Novel Bi-Directional Channel for Nutrient Uptake across Mycobacterial Outer Envelope
Authors: Liu Lei , Wen Chongzheng , Cai Xiaoying , Gong Weimin
Published: September 2024

Nutrients are absorbed by special transport proteins on the cell membrane; however, there is less information regarding transporters across the mycobacterial outer envelope, which comprises dense and intricate structures. In this study, we focus on the model organism Mycolicibacterium smegmatis, which has a cell envelope similar to that of Mycobacterium tuberculosis, as well as on the TiME protein secretion tube across the mycobacterial outer envelope. We present transcriptome results and analyze the protein compositions of a mycobacterial surface envelope, determining that more transporters and porins are induced to complement the deletion of the time gene in Mycolicibacterium smegmatis. The TiME protein is essential for nutrient utilization, as demonstrated in the uptake experiments and growth on various monosaccharides or with amino acids as the sole carbon source. Its deletion caused bacteria to be more sensitive to anti-TB drugs and to show a growth defect at an acid pH level, indicating that TiME promotes the survival of M. smegmatis in antibiotic-containing and acidic environments. These results suggest that TiME tubes facilitate bi-directional processes for both protein secretion and nutrient uptake across the mycobacterial outer envelope.
Serendipitous, Open Big Data Management and Analytics: The SeDaSOMA Framework
Authors: Cuzzocrea Alfredo , Ciancarini Paolo
Published: September 2024

This paper presents and delves into the architecture and intricacies of SeDaSOMA, a sophisticated framework supporting Serendipitous, Data-as-a-Service-oriented, Open big data Management and Analytics. SeDaSOMA meticulously addresses the multifaceted challenges inherent in open big data management and analytics. SeDaSOMA stands as a testament to the evolving landscape of big data management and analytics, embodying a commitment to harnessing advanced functionalities through a synthesis of innovative research findings and cutting-edge tools. In the context of this framework, the paper not only elucidates its structural components but also underscores its pivotal role in facilitating the seamless integration, processing, and analysis of massive and diverse datasets. By providing a comprehensive overview of SeDaSOMA, this paper contributes to the ongoing discourse within the field of big data management and analytics, shedding light on the intricate interplay between technological innovation and practical application. Moreover, as a complement to the discussion on SeDaSOMA, the paper offers a critical exploration of the emerging topics in the realm of big data research. By delineating current state-of-the-art methodologies and forecasting future research trajectories, this overview enriches the scholarly dialogue surrounding the evolving landscape of big data management and analytics, offering insights into the broader implications and potential advancements in the field.
High-Sensitivity SPR Sensor Based on the Theory of the Solution of Inventive Problems
Authors: Zhu Cui-lan , Liu Jin-da , Wang Fang
Published: September 2024

Fiber SPR biosensors have low sensitivity and accuracy in detecting biomolecules. In this study, the TRIZ is applied to molecules and optimization. By defining the prototype system, clarifying the components and interacting objects, and adopting a functional model analysis and causal analysis, we deeply explored the key points and root causes of leakage and used a variety of tools, such as technological contradiction, object-field analysis, the HOW-TO model and knowledge effect library, physical contradiction, and the villain method, to come up with different solutions. A novel multimode–single-mode–multimode fiber SPR sensor based on the structure of gold (Au)–molybdenum disulfide (MoS2)–gold nanoparticles was designed and manufactured by using the TRIZ systematically for the first time. Under the effective guidance of the TRIZ, the sensitivity of the novel sensor is significantly enhanced after the optimization and experimental verification. The new sensor provides an effective reduction in the cost of detection and production and at the same time has excellent stability, ease of preparation, and high reproducibility, which is of significant value and significance for practical applications.
Ultra-Compact Reflective Waveguide Mode Converter Based on Slanted-Surface and Subwavelength Metamaterials
Authors: Zhang Yanxia , Feng Rui , Shi Bojian , Li Xiaoxin , Gao Yanyu , Gao Wenya , Jia Qi , Sun Fangkui , Cao Yongyin , Ding Weiqiang
Published: September 2024

Mode converter (MC) is an indispensable element in the mode multiplexing and demultiplexing system. Most previously reported mode converters have been of the transmission type, while reflective mode converters are significantly lacking. In this paper, we propose an ultra-compact reflective mode converter (RMC) structure, which comprises a slanted waveguide surface coated with a metallic film and a subwavelength metamaterial refractive index modulation region. The results demonstrate that this RMC can achieve high-performance mode conversion within an extremely short conversion length. In the two-dimensional (2D) case, the conversion length for TE0–TE1 is only 810 nm, and the conversion efficiency reaches to 94.1% at the center wavelength of 1.55 μm. In a three-dimensional (3D) case, the TE0–TE1 mode converter is only 1.14 μm, with a conversion efficiency of 92.5%. Additionally, for TE0–TE2 mode conversion, the conversion size slightly increases to 1.4 μm, while the efficiency reaches 94.2%. The proposed RMC demonstrates excellent performance and holds great potential for application in various integrated photonic devices.
An Optimization Study of 3D Printing Technology Utilizing a Hybrid Gel System Based on Astragalus Polysaccharide and Wheat Starch
Authors: Xia Guofeng , Tao Lilulu , Zhang Shiying , Hao Xiangyang , Ou Shengyang
Published: September 2024

This study utilizes a lab-developed pneumatic-extrusion condensing 3D food printer to prepare astragalus–starch mixed gels by blending different ratios of astragalus polysaccharide and wheat starch and applies these gels to 3D printing experiments. The aim of this paper is to investigate the impacts of mixed-gel concentrations on printing outcomes in order to identify the optimal blending ratio. Under this rationale, the effects of printing layer height and nozzle diameter on print quality were studied. Single-factor analysis and response surface methodology were employed to optimize the experiments and determine the optimal printing process parameters for the astragalus–starch mixed gels. The results indicate that an increase in astragalus polysaccharide content leads to a decrease in the sedimentation rate of the mixed gels and a tendency towards a more fluid consistency. After storage of samples in a sealed space for equal durations, it was found that an increase in astragalus polysaccharide content enhances the textural properties of the mixed gels, with optimal printing effects achieved at a 2% polysaccharide content. The optimal print quality is achieved when the ratio of nozzle diameter to layer height is between 0.5 and 0.55. The influence order of printing process parameters on the overall completion rate of the samples is nozzle diameter > printing speed > fill rate. The predicted optimal printing parameters are a nozzle diameter of 0.6 mm, a printing speed of 767 mm/min, and a fill rate of 83%, with a predicted overall completion rate of the printed samples at 99.45%. Experimental validation revealed an actual overall completion rate of the printed samples at 99.52%, slightly higher than the predicted value. This discrepancy was attributed to the precision of the measurement methods and the variability in the printing process. The study demonstrates that the addition of astragalus polysaccharide significantly improves the 3D printing molding effect of wheat starch, and the printing parameter settings obtained by response surface optimization effectively enhance printing accuracy. This research provides experimental evidence and parameter optimization references for the application of non-starch polysaccharides in starch-based 3D food printing.
Study on Permeability Enhancement of Seepage–Damage Coupling Model of Gas-Bearing Coal by Water Injection
Authors: Wu Wenbin , Wang Zhen , Yao Zhuangzhuang , Qin Jianyun , Yu Xinglan
Published: September 2024

The use of high-pressure water injection technology in gas-bearing coal seams is an important method for effectively addressing coalbed methane issues. To explore the mechanisms and influencing factors of water injection and permeability enhancement, a model was established based on the theories of unstable seepage and elastic damage in coal and rock mass. Additionally, a mechanical model of elastic damage-based beams was established, taking into account rheological damage, and the mechanical property variation of the surrounding rock in the working face was analyzed. The study included numerical simulations and verification with practical examples. The results suggested that high-pressure water injection could cause damage to the coal body and deformation of the roof, resulting in changes in ground stress, which was a significant contributor to the increase in coal seam permeability. The study showed positive correlations between rheological effects, injection time, injection flow rate, coal seam depth, and the influence range of water injection. Case studies indicated that the long-term influence range of water injection was approximately 60 m, which aligned with field results. The paper introduces a mechanical model for calculating variations in ground stress. This model can help assess the impact of water injection and permeability enhancement, providing valuable insights for related engineering projects.
Economic Efficiency versus Energy Efficiency of Selected Crops in EU Farms
Authors: Boczar Paweł , Błażejczyk-Majka Lucyna
Published: September 2024

The goal of farmers operating in a market economy is to maximize profit. In view of the changing political situation, the main social interest, in addition to food security, should be energy security. Here is a refined version of that sentence: This article examines the production efficiency of selected crops grown in the EU and how well their production can ensure both the economic security of the producers, i.e., the farmers, and Europe’s energy security. In addition, it aims to determine which costs incurred in the production process have the greatest impact on productivity. The paper uses data obtained from the Cash Crop agricultural benchmarking database, covering 19 crops and 39 cost categories for each crop. The data (averaged for 2019–2021) came from 30 farms located in 11 EU member states. The DEA method and stepwise multiple regression were used. Research has shown that crops are already being grown in Europe that provide high energy efficiency in production without compromising farm performance (including oats, peas, and winter rye). Moreover, improving the involvement of certain inputs results in improved production efficiency (e.g., through spending on agricultural consulting services). In addition, crop economic efficiency, as assessed by profit with and without subsidies, was found to be strongly correlated with production efficiency. This could indicate that subsidies do not play a key role in farm efficiency within the EU. Crop productivity remains a key factor in achieving economic and energy efficiency. The significance of the findings presented in connection with the recent COVID-19 pandemic and the escalation of the armed conflict in Ukraine has led to renewed interest in EU energy security, i.e., generating as much EU energy as possible for food and non-food production.
Fatal Consequences of Safety Non-Compliance in Non-Commercial Ultralight Aviation: A Case Study
Authors: Glowinski Sebastian , Majdanik Slawomir
Published: September 2024

The popularity of ultralight planes in non-commercial aviation is on the rise; however, non-compliance with regulations and the use of faulty equipment poses significant risks. This study explores the consequences of such lapses in adherence to safety standards by thoroughly examining the conditions leading to an ultralight plane crash, focusing on data related to causative factors. The accident involved an unregistered ultralight aircraft, lacking proper inspection and the required license. The pilot’s error during takeoff led to a stall, resulting in a fatal crash. Upon impact with the ground, the pilot’s shoulder and lap belts were torn off, leading to immediate death. This case underscores the critical importance of compliance with safety regulations in ultralight aviation. The findings illuminate the dire consequences of non-compliance with safety regulations and the utilization of unregistered, uninspected ultralight aircraft in private aviation. The tragic accident analyzed herein underscores the pivotal role of adherence to safety standards in mitigating the risks associated with ultralight planes. The pilot’s fatal error during takeoff, compounded by the absence of proper inspection and licensing, serves as a stark reminder of the potential dangers inherent in neglecting established safety protocols.
Metaverse of Things (MoT) Applications for Revolutionizing Urban Living in Smart Cities
Authors: Alam Tanweer
Published: September 2024

The Metaverse of Things (MoT) is an advanced technology that has the potential to revolutionise urban living in the present era. This article explores the advantages, uses, and transformative outcomes of the MoT in smart cities. It encompasses sustainability, urban planning, citizen participation, infrastructure management, and more. MoT integrates the Internet of Things (IoT) with metaverse technologies. The ultimate objective is to develop virtual environments that are highly interactive, interconnected, and immersive while maintaining a high level of fidelity to reality. The IoT utilises virtual reality (VR), augmented reality (AR), and other digital technologies to gather data, facilitate communication, and automate certain processes, thereby enhancing several elements of urban living. The IoT will bring about a profound transformation in the way cities gather and utilise data to enhance services and optimise efficiency. Cities that can efficiently distribute this data can enhance public safety, optimise energy usage, regulate traffic, and manage waste properly. MoT apps that utilise immersive technologies and the IoT can be used to generate more intelligent and captivating cityscapes. The implementation of the MoT can greatly enhance the quality of life for residents of smart cities through improvements in transportation, healthcare, education, and community engagement. This study’s author examined how smart cities utilise the MoT to enhance the daily experiences of their inhabitants. This study examines the technical structure, possible advantages, and difficulties of implementing the MoT in urban settings, aiming to enhance the resilience, responsiveness, and adaptability of cities. The findings emphasise the importance of robust legislative frameworks, stringent security requirements, and well-developed infrastructure to facilitate the extensive use of MoT technology. These factors are crucial for establishing a highly interconnected and efficient urban environment.