bluuebunny/crossref_metadata_2025 huggingface dataset:
Cardiovascular Disease Screening in Primary School Children
Authors: Bagkaki Alena , Parthenakis Fragiskos , Chlouverakis Gregory , Galanakis Emmanouil , Germanakis Ioannis
Published: December 2024

Background: Screening for cardiovascular disease (CVD) and its associated risk factors in childhood facilitates early detection and timely preventive interventions. However, limited data are available regarding screening tools and their diagnostic yield when applied in unselected pediatric populations. Aims: To evaluate the performance of a CVD screening program, based on history, 12-lead ECG and phonocardiography, applied in primary school children. Methods: The methods used were prospective study, with voluntary participation of third-grade primary school children in the region of Crete/Greece, over 6 years (2018–2024). Personal and family history were collected by using a standardized questionnaire and physical evaluation (including weight, height, blood pressure measurement), and cardiac auscultation (digital phonocardiography (PCG)) and 12-lead electrocardiogram (ECG) were recorded at local health stations (Phase I). Following expert verification of responses and obtained data, assisted by designated electronic health record with incorporated decision support algorithms (phase II), pediatric cardiology evaluation at the tertiary referral center followed (phase III). Results: A total of 944 children participated (boys 49.6%). A total of 790 (83.7%) had Phase I referral indication, confirmed in 311(32.9%) during Phase II evaluation. Adiposity (10.8%) and hypertension (3.2%) as risk factors for CVD were documented in 10.8% and 3.2% of the total population, respectively. During Phase III evaluations (n = 201), the majority (n = 132, 14% of total) of children were considered as having a further indication for evaluation by other pediatric subspecialties for their reported symptoms. Abnormal CVD findings were present in 69 (7.3%) of the study population, including minor/trivial structural heart disease in 23 (2.4%) and 17 (1.8%), respectively, referred due to abnormal cardiac auscultation, and ECG abnormalities in 29 (3%), of which 6 (0.6%) were considered potentially significant (including 1 case of genetically confirmed channelopathy-LQT syndrome). Conclusions: CVD screening programs in school children can be very helpful for the early detection of CVD risk factors and of their general health as well. Expert cardiac auscultation and 12-lead ECG allow for the detection of structural and arrhythmogenic heard disease, respectively. Further study is needed regarding performance of individual components, accuracy of interpretation (including computer assisted diagnosis) and cost-effectiveness, before large-scale application of CVD screening in unselected pediatric populations.
Urinary Microbiota of Healthy Prepubescent Girls and Boys—A Pilot Study
Authors: Naboka Yulia L. , Kogan Mikhail I. , Mayr Johannes M. , Gudima Irina A. , Koliva Elizaveta M. , Kotieva Violetta M. , Chernytskaya Marina L. , Sizonov Vladimir V.
Published: December 2024

Background: The urinary microbiota of healthy children has rarely been studied, and potential differences between boys and girls have not been addressed. Thus, this study aimed to compare the urinary microbiota of healthy prepubescent girls and boys. Methods: We included healthy children aged between 4 and 10 years who were free of functional or organic urinary tract diseases and had no history of urinary tract infection. We collected the mean portion of morning urine during natural micturition and determined aerobic and anaerobic microbiota using HiCrome™ chromogenic growth media. We identified microorganisms on the basis of morphotinctural properties and analyzed α- and β-diversity of microorganisms isolated from the urine of boys and girls. Results: Mean age of the children was 6.1 ± 3.2 years. In general, four-component (28.1%) as well as two-component (15.6%), three-component (15.6%), and six-component (12.5%) combinations of microorganisms prevailed in the urine of children. The urine of boys exhibited four-component combinations significantly more often than that of girls (p ˂ 0.05), while the urine of girls contained seven-component microbial combinations significantly more often than that of boys (p ˂ 0.05). Comparison of multicomponent combinations of microorganisms in boys and girls revealed an overrepresentation of Enterococcus spp. in girls (p < 0.05). Furthermore, there was a trend towards higher microbial α-diversity in the urine of girls, but the difference between girls and boys was not significant. Conclusions: The urine of healthy prepubescent children contained various aerobic–anaerobic combinations of microorganisms. Their diversity in the urine of girls and boys did not differ significantly. However, the level of α-diversity of microorganisms was higher in girls than in boys. We noted differences in the prevalence of certain taxa of microorganisms in the urine of boys and girls. Our study showed a close functional relationship between aerobic and anaerobic microorganisms detected in the urine of children in more than half of the cases.
Impact of Soft Drink Intake on Bone Development and Risk of Fractures in a Danish Cohort of Schoolchildren
Authors: Hermansen Helene , Händel Mina Nicole , Heidemann Malene Søborg , Wedderkopp Niels
Published: December 2024

Background and Aims: Soft drink consumption is suspected to negatively impact bone health in children, but longitudinal evidence is limited. This study assessed the association between soft drink intake and bone health outcomes in Danish schoolchildren aged 7.7–12 years, within a physical activity intervention framework. Methods: This study was nested in the CHAMPS-DK trial, a quasi-experimental study. Participants (n = 529) were recruited from intervention schools offering 270 min of physical education (PE) per week (active arm) and control schools with 90 min of standard PE. Soft drink intake was assessed via a food-frequency questionnaire at baseline. Dual-energy X-ray absorptiometry (DXA) was used to measure Bone Mineral Content (BMC), Bone Area (BA), and Bone Mineral Density (BMD) at baseline and two-year follow-up (primary outcomes). Fracture incidence over a five-year period was recorded using the SMS-Track parental reporting system (secondary outcome). Multilevel mixed-effects linear regression and Weibull survival models were used to analyze associations. Results: Soft drink intake of more than twice per month did not significantly affect BMC, BA, or BMD over two years (Total body BMD: β = 0.004; 95% CI: (−0.007; 0.016). Adjustment for confounders such as age, sex, BMI, pubertal status, socioeconomic status, and physical activity did not change the results. Additionally, no significant difference in fracture risk was observed (HR = 0.86; 95% CI: [0.43; 1.71]). Conclusions: Soft drink intake had no measurable impact on bone health indices or fracture risk in children, irrespective of PE intervention. Future studies should investigate the effects of specific soft drink types (carbonated vs. non-carbonated) on bone development.
Navigating the (Im)mobility–Adaptation Nexus in the Context of Climate and Environmental Change: A Typological Discussion
Authors: Bernasconi Chiara
Published: December 2024

Since the 1990s, the academic discourse on climate change, migration, and adaptation has undergone significant shift. Individuals previously characterized as “climate refugees” are now cast as adaptable agents. Against this backdrop, academic explorations of the nexus between mobility and adaptation within the context of climate change have burgeoned, particularly in the latter half of the 2000s. The objective of this paper is to identify linkages between adaptation and different forms of (im)mobility situated on the spectrum of movement that has been conceptualized and discussed in theoretical and empirical material. To accomplish this, I undertake an exhaustive review of the extant literature on the subject of climate change-induced (im)mobility and adaptation. This paper suggests three possible types of relationships between (im)mobility and adaptation in the context of climate and environmental change: adaptation in situ, relocation, and migration as an adaptation strategy. These dimensions have so far been treated separately by scholars.
Spectroscopic Techniques for Identifying Pigments in Polychrome Cultural Relics
Authors: Liu Mihaela , Wang Zhigao , Liu Xinyou
Published: December 2024

This article explores recent advancements in non-destructive spectroscopic techniques for identifying pigments in polychrome cultural relics, emphasizing their significance for sustainability in cultural heritage preservation. Techniques such as infrared spectroscopy, Raman spectroscopy, and X-ray fluorescence spectroscopy facilitate the accurate identification of pigment compositions while ensuring the integrity of the artifacts is maintained. Our findings indicate that integrating multiple spectroscopic methods enhances the accuracy of pigment identification and deepens our understanding of the structural and preservation status of historical artifacts. We also outline future directions for spectroscopic analysis in the field of cultural heritage, including micro-area analysis, data fusion, and intelligent data processing, aimed at improving the efficiency and effectiveness of pigment identification, ultimately contributing to the sustainable preservation of cultural assets.
A Randomized, Double-Blind, Placebo-Controlled Study Evaluating a Novel Skin Care Cream with Olea europaea Stem Cell Extract Following Nd:YAG 1064 nm Laser Epilation
Authors: Gardiki Vassiliki , Varvaresou Athanasia , Papageorgiou Spyridon , Protopapa Evangelia , Pavlou Panagoula , Rallis Efstathios , Papadopoulos Apostolos , Chaniotis Dimitrios
Published: December 2024

The European Society for Laser Dermatology (ELSD) has established recommendations for safe and effective photo epilation; however, short-term common adverse effects occur as a result of laser treatment, such as edema and perifollicular erythema. Post-inflammatory hyperpigmentation also appears in certain skin types. Very few clinical studies have been conducted on the topical application of cosmetic skin care products aimed at decreasing the adverse effects on the skin epidermis following laser-assisted epilation procedures. Stem cells are found in plant and animal organisms and are responsible for the growth and restoration of damaged tissues. Plant stem cells divide throughout the life of the plant, creating new plant parts. Our aim was to develop a new cosmetic cream to decrease the intensity of some of the side effects of laser epilation and thus reduce the administration of topical medication. We developed a formulation with the active substance Olea europaea (Olive) Callus Culture Lysate (OLEA VITAE™ 02), which is derived from plant stem cells of the Mediterranean wild variety of Olea europaea, for application following laser epilation with an Nd:YAG 1064 nm laser. The new skin care cream was tested for its physicochemical and microbiological stability, according to the European Pharmacopoeia. The impacts of this substance on the potential side effects of Nd:YAG 1064 nm application, i.e., trans-epidermal water loss, keratin hydration, melanin, erythema, and skin elasticity, in comparison with the appropriate placebo, were investigated using biophysical measurements and a self-assessment questionnaire. Skin biopsies were also performed to evaluate the influence of the procedure and the application of the products on the epidermis and papillary dermis thickness. According to our findings, the incorporation of the plant stem cell extract of Olea europaea into our cream resulted in a stable cream with an appealing texture. Furthermore, the activity of erythema and hyperpigmentation was decreased when the cream was applied after Nd:YAG 1064 nm laser epilation.
Comparison of Durability and Gamma-Ray Shielding Performance of High-Velocity Oxygen Fuel Tungsten Carbide-Based Coatings on Cold-Rolled Steel Surface
Authors: Son Yeong-Ho , Baek Seung Heon , Kim Beom Kyu , Hwang Jeong Ho , Lee Jae Hun , Song Geun Dong
Published: December 2024

This paper provides a comparative evaluation of the mechanical properties, corrosion resistance, and gamma-ray shielding performance of four different types of tungsten carbide (WC)-NiCr coatings deposited on cold-rolled steel surfaces, which are used as materials for low- and intermediate-level radioactive waste (LILW) storage containers. The four types of coatings were classified as WC-85, WC-73, WC-66, and WC-39 according to their WC content and were applied to the cold-rolled steel surfaces using the High-Velocity Oxygen Fuel (HVOF) spraying process. The performance of the layered coatings was analyzed in terms of their microstructure, hardness, wear resistance, adhesion strength, corrosion properties, and gamma-ray shielding characteristics. Coatings with elevated WC contents showed enhanced mechanical properties and gamma-ray shielding effectiveness, whereas coatings with relatively lower WC contents and higher NiCr contents exhibited greater corrosion resistance. This paper discusses the performance of WC-NiCr coatings from the viewpoint of enhancing the durability and safety of commercial LILW storage containers.
A Compact and Fast Resonant Cavity-Based Encoder in Photonic Crystal Platform
Authors: Soroosh Mohammad , AL-Shammri Faris K. , Maleki Mohammad Javad , Balaji Venkatachalam Rajarajan , Adibnia Ehsan
Published: December 2024

A novel 4-to-2 photonic crystal encoder is proposed by modulating the intensity of four input optical signals, and four distinct output states are achieved. Nonlinear rods are employed to couple input waves into resonant cavities, directing the light to the desired output waveguides. The proposed design, with a footprint of 114 µm2, demonstrates efficient encoding operation at a wavelength of 1550 nm and is highly suitable for integrated photonics applications. A comprehensive comparative analysis revealed that the proposed 4-to-2 encoder exhibits a time response 176 fs faster than previously presented encoders. Furthermore, the contrast ratio of the designed structure is as high as 13.78 dB to distinguish between logic 0 and 1. These advancements hold significant potential for enhancing the performance of compact, high-speed digital circuits.
A Study on Cu Thin-Film Electroplated TiO2 Photoanodes for Applications in Natural Dye-Sensitized Solar Cells
Authors: Shakya M. D. P. A. , Jayathilaka K. M. D. C. , Fernando W. T. R. S. , Wanninayake W. T. M. A. P. K. , Kumara L. S. R. , Seo O. , Tang J. , Sakata O. , Siripala W. P. , Wijesundera R. P.
Published: December 2024

Improving the performance of TiO2 photoanodes via the inclusion of metal particles on the electrode surface could provide significant advantages for the development of dye-sensitized solar cells (DSSCs). We studied a TiO2/Cu film electrode prepared by electrodepositing Cu particles on a TiO2 film on an indium-doped tin oxide (ITO) substrate. Cu particles were electrodeposited on a TiO2 electrode at −700 mV vs. a Ag/AgCl electrode in an acetate bath, with the pH adjusted between 6.3 and 7.7 in 0.2 increments to optimize the deposition conditions. TiO2/Cu thin-film electrodes were tested as a photo anode in a natural DSSC consisting of a carbon counter electrode, Vitis vinifera dye, and a KI/I2-based electrolyte. Film characterization was performed using hard X-ray photoelectron spectroscopy (HAXPES), grazing incidence X-ray diffraction (GIXD), scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, electrochemical impedance spectroscopy (EIS), ultraviolet–visible spectroscopy (UV–Vis), and photocurrent density–voltage (J–V) measurements. DSSCs with Cu particles containing TiO2 electrodes prepared using an acetate bath of pH 7.3 resulted in a 370% improvement in efficiency compared to the DSSCs without Cu particles. Thus, this study revealed that incorporating Cu particles into the surface of the TiO2 electrode enhances the photovoltaic performance of DSSCs.
Optimization and Regression Analysis of Friction Stir Processing Parameters of AA5083/Coal Composites for Marine Applications
Authors: Muribwathoho Oritonda , Msomi Velaphi , Mabuwa Sipokazi
Published: December 2024

This study aimed to optimize friction stir processing parameters to enhance the mechanical properties of AA 5083/coal composites, a novel material combination with potential applications in marine environments. By systematically varying process parameters such as tilt angle, traverse speed, and rotational speed using a Taguchi experimental design, the FSP process was optimized. Signal-to-noise ratio and analysis of variance techniques were used to determine the most influential parameters on microhardness and ultimate tensile strength. A regression model was developed to predict composite behavior under these optimal conditions. This study found that a combination of 900 rpm, 60 mm/min, and a 2° tilt angle significantly improved mechanical properties. This research contributes to the advancement of FSP for producing high-performance, lightweight, and corrosion-resistant aluminum composites, particularly for marine applications.
Preparation and Microwave-Absorbing Property of Solid-Waste-Derived Ceramic Foam
Authors: Wang Zheng , Mu Minghao , Liu Xinqiang , Jiang Congcong
Published: December 2024

Recently, electromagnetic wave (EMW)-absorbing materials have obtained increasing attention for both military and civil applications. This study adopted the powder sintering method and the concept of recycled wastes in fabricating functional ceramic foam (CF). Firstly, a ceramic green body composed of pulverized granite residues, waste glass, and a foaming agent was sintered. The influence of the sintering temperature and SiC addition on CF was investigated, and then surface graphitization post-treatment of CF was performed as well. The truly enhanced compressive strength and EMW-absorbing property of surface graphitization ceramic foam (SG-CF) with a homogeneous porous structure was realized in the present work, which is promising as a candidate in EMW absorption systems.
Numerical Simulation of Surface Thermal Analysis and Cooling Optimization of Continuous Casting Rolls
Authors: Cheng Guangwei , Yin Ningxia , Zheng Qiaoxin , Qiu Yuming , Chen Junqi
Published: December 2024

In many steel mills, the working life of continuous casting machine rollers is relatively short, requiring frequent replacement and negatively impacting production efficiency. To effectively extend the service life of these rollers, this study focuses on a continuous casting machine at a steel mill in China. A numerical simulation was conducted, revealing that the rollers in contact with the high-temperature casting billet experience significant thermal and stress impacts. The traditional cooling channel struggles to sufficiently reduce both the surface temperature and stress, resulting in severe thermal fatigue damage to the roller surfaces. Observations of roller surface wear showed signs of adhesive wear, fatigue cracks, and spalling occurring in various regions of the roller, which aligned with the stress distribution predicted by the simulation. In response, the cooling channel structure was modified to enhance the cooling effect of the water. Optimization of both the cooling channel structure and its parameters was carried out using a coupled flow-heat-force numerical simulation method. The optimized cooling channel effectively improved the working condition of the continuous casting roll, as the maximum temperature of the roll surface was reduced from 810 K to 591 K, the circumferential temperature difference was reduced by 38%, and the maximum equivalent stress decreased from 791 MPa to 558 MPa. This adjustment also resulted in a more uniform surface temperature distribution, mitigating the sudden fluctuations in normal stress that are typical of conventional rollers.
Ab Initio Study of the Energetics, Electronic Properties, and Chlorine Migration Behavior of B2-FeAl (110) Surface by Microalloying
Authors: Chen Weiqian , La Peiqing , Yin Ruojiao , Wan Lei , Du Yong , Zheng Yibing
Published: December 2024

Ab initio methods based on DFT are utilized to study the formation energy, adsorption energy, and electronic properties of pure and X-doped (X = Mo, Ti, Ni) B2-FeAl (110) surface configurations. The effect of microalloying element doping on the corrosion resistance of B2-FeAl coating to molten chlorinated salts was evaluated by the CI-NEB method. Our results show that the Ni atom preferentially occupies the position of the Fe atom, while the Mo and Ti atoms preferentially replace the Al atom in the supercell. The Cl atom tends to be adsorbed at the SB-FeAl site on a pure B2-FeAl (110) surface. The adsorption energies of a single chlorine atom at stable adsorption sites of Ni-doped B2-FeAl (110) surface are small, which means that Ni doping reduces the possibility of corrosion. The PDOS diagrams confirm that for the chlorine adsorption model of Mo-doped B2-FeAl (110) surface, strong hybridization between Mo-d, Al-p, and Fe-d orbitals occur in the energy region of −4.5~−2 eV and 0.5~2.5 eV, while in the energy range of −7.0~4.8 eV, Cl-p interacts with Mo-d and Al-s, respectively, indicating that Cl bonds with Mo and Al atom, respectively. The addition of Mo and Ni hinders the diffusion of chlorine atoms on the surface, weakens the corrosion rate of B2-FeAl in chlorinated molten salt, and improves the corrosion resistance of B2-FeAl coating. However, Ti doping promotes the migration of chlorine atoms and increases the corrosion rate of B2-FeAl in chlorinated molten salt to a certain extent. The aim of this study is to reveal the corrosion resistance mechanism of FeAl coating from the atomic level and provide a theoretical basis for the application of chloride molten salt as an efficient heat storage medium in the field of photothermal.
Integrated Analysis of Cell-Free DNA and Novel Protein Biomarkers for Stratification and Therapy Monitoring in Stage IV Pancreatic Cancer: A Preliminary Study
Authors: Hussung Saskia , Hess Maria E. , Haghighi Elham Bavafaye , Wittel Uwe A. , Boerries Melanie , Fritsch Ralph M.
Published: December 2024

Background: Given the poor prognosis of metastatic pancreatic adenocarcinoma (mPDAC), closer disease monitoring through liquid biopsy, most frequently based on serial measurements of cell-free mutated KRAS (KRASmut cfDNA), has become a highly active research focus, aimed at improving patients’ long-term outcomes. However, most of the available data show only a limited predictive and prognostic value of single-parameter-based methods. We hypothesized that a combined longitudinal analysis of KRASmut cfDNA and novel protein biomarkers could improve risk stratification and molecular monitoring of patients with mPDAC. Methods: We prospectively collected 160 plasma samples from 47 patients with mPDAC at our institution. Highly sensitive single-target ddPCR assays were employed to detect and quantify KRASmut cfDNA. Additionally, analysis of ten protein biomarkers was performed through Enzyme-linked Immunosorbent Assay (ELISA), and Carbohydrate-Antigen 19-9 (CA 19-9) dynamics were registered. Results: KRASmut cfDNA was detectable in 37/47 (78.7%) patients throughout the course of study, and CA 19-9 levels were elevated in 40 out of 47 (85.1%) patients. KRASmut cfDNA increase at the time of the first follow-up could predict inferior progression-free survival (PFS) (Hazard ratio (HR) = 3.40, p = 0.0003) and overall survival (OS) (HR = 4.91, p < 0.0001). In contrast to CA 19-9 kinetics, which were not predictive of outcome, integrated analysis of KRASmut cfDNA combined with six evaluated circulating protein biomarkers allowed basal risk stratification at the time of the first follow-up (HR = 10.2, p = 0.0014). Conclusions: A combined longitudinal analysis of KRASmut cfDNA with selected protein biomarkers offers significantly improved prognostic value for patients with mPDAC compared to single-parameter methods. This innovative approach is a step forward in the molecular monitoring of mPDAC and should be validated in further prospective studies.
Triple Viral Infections in Advanced Breast Cancer: Insights from a Three-Case Report and Literature Review
Authors: Khasawneh Ashraf I. , Himsawi Nisreen , Alorjani Mohammed , Al-Momani Hadeel , Shahin Uruk , Sammour Ashraf , Saleh Tareq , Al-Momani Hafez , Khasawneh Rame , Al Shboul Sofian
Published: December 2024

Background and clinical significance: Viral infections are typically considered contributing or secondary factors in the development of breast cancer. Case presentation: This case report presents three instances of advanced breast cancer associated with triple viral infections. Case 1 involves a 78-year-old woman diagnosed with grade 2 invasive ductal carcinoma positive for HPV-18, CMV, and BLV. Case 2 describes a 39-year-old woman with grade 2 invasive ductal carcinoma, positive for HPV-16, CMV, and BLV. Case 3 is a 52-year-old woman with grade 3 invasive ductal carcinoma, positive for HPV-16, BLV, and MMTV. These cases suggest a possible correlation between viral co-infections and breast cancer aggressiveness, posing new questions about the role of viral infections in cancer development and prognosis. Conclusions: The findings contribute to growing evidence that viral infections may influence the progression and therapeutic response of breast cancer, warranting further investigation into targeted preventive measures including vaccinations.
A Hybrid Model for Psoriasis Subtype Classification: Integrating Multi Transfer Learning and Hard Voting Ensemble Models
Authors: Avcı İsmail Anıl , Zirekgür Merve , Karakaya Barış , Demir Betül
Published: December 2024

Background: Psoriasis is a chronic, immune-mediated skin disease characterized by lifelong persistence and fluctuating symptoms. The clinical similarities among its subtypes and the diversity of symptoms present challenges in diagnosis. Early diagnosis plays a vital role in preventing the spread of lesions and improving patients’ quality of life. Methods: This study proposes a hybrid model combining multiple transfer learning and ensemble learning methods to classify psoriasis subtypes accurately and efficiently. The dataset includes 930 images labeled by expert dermatologists from the Dermatology Clinic of Fırat University Hospital, representing four distinct subtypes: generalized, guttate, plaque, and pustular. Class imbalance was addressed by applying synthetic data augmentation techniques, particularly for the rare subtype. To reduce the influence of nonlesion environmental factors, the images underwent systematic cropping and preprocessing steps, such as Gaussian blur, thresholding, morphological operations, and contour detection. DenseNet-121, EfficientNet-B0, and ResNet-50 transfer learning models were utilized to extract feature vectors, which were then combined to form a unified feature set representing the strengths of each model. The feature set was divided into 80% training and 20% testing subsets and evaluated using a hard voting classifier consisting of logistic regression, random forest, support vector classifier, k-nearest neighbors, and gradient boosting algorithms. Results: The proposed hybrid approach achieved 93.14% accuracy, 96.75% precision, and an F1 score of 91.44%, demonstrating superior performance compared to individual transfer learning models. Conclusions: This method offers significant potential to enhance the classification of psoriasis subtypes in clinical and real-world settings.
The Non-Monotonic Relationship Between Income and Life Insurance Demand: A Case Study of Forty-One Countries
Authors: Rapi Kristio , Priyarsono Dominicus S. , Jahroh Siti , Bakhtiar Toni
Published: December 2024

Income is often viewed as the main determinant of life insurance demand. However, in the last two decades, the world’s life insurance penetration has continued to decrease even as income grows. This study investigates the relationship between income and life insurance demand using panel data from forty-one countries from 2013 to 2022, along with education and life expectancy as control variables. The study finds a non-monotonic relationship between income and life insurance penetration and between education and life insurance penetration, while life expectancy shows a monotonic relationship with life insurance penetration. This study provides significant policy implications for insurers to predict life insurance demand and suggests that non-high-income countries emphasize the improvement of their life insurance sector development.
Latina Community College Presidents: Drawing from Cultural Intuition to Disrupt Leadership Norms in Higher Education
Authors: Estrada Cynthia , Felix Eric R. , Vedar Erin Nicole Reyes , Perez Elizabeth Jimenez
Published: December 2024

This study documents the unique personal and professional experiences that Latina leaders bring to the role of community college president. Guided by a Chicana Feminist conceptual framework, we examined the tools, strategies, and assets that Latina presidents possess to persist as higher education leaders within a white patriarchal dominant culture. As a research collective, we conducted platicas as a Chicana Feminist methodology with five Latina community college presidents in California. Each platica lasted between 60 and 90 min. Findings exemplified four sources of cultural intuition that Latina community college presidents drew from to redefine higher education leadership and drive student equity on campus: (1) personal experiences with marginality in educational spaces, (2) accumulated professional knowledge, (3) scholarly training in graduate school, and (4) the process of leading itself. The study found that Latina presidents possessed important knowledge and distinct perspectives based on their experiences as Women of Color, children of immigrants, and former community college students to guide their leadership approaches in equity driven ways.
A Fire Detection Method for Aircraft Cargo Compartments Utilizing Radio Frequency Identification Technology and an Improved YOLO Model
Authors: Wang Kai , Zhang Wei , Song Xiaosong
Published: December 2024

During flight, aircraft cargo compartments are in a confined state. If a fire occurs, it will seriously affect flight safety. Therefore, fire detection systems must issue alarms within seconds of a fire breaking out, necessitating high real-time performance for aviation fire detection systems. In addressing the issue of fire target detection, the YOLO series models demonstrate superior performance in striking a balance between computational efficiency and recognition accuracy when compared with alternative models. Consequently, this paper opts to optimize the YOLO model. An enhanced version of the FDY-YOLO object detection algorithm is introduced in this paper for the purpose of instantaneous fire detection. Firstly, the FaB-C3 module, modified based on the FasterNet backbone network, replaces the C3 component in the YOLOv5 framework, significantly decreasing the computational burden of the algorithm. Secondly, the DySample module is used to replace the upsampling module and optimize the model’s ability to extract the features of small-scale flames or smoke in the early stages of a fire. We introduce RFID technology to manage the cameras that are capturing images. Finally, the model’s loss function is changed to the MPDIoU loss function, improving the model’s localization accuracy. Based on our self-constructed dataset, compared with the YOLOv5 model, FDY-YOLO achieves a 0.8% increase in mean average precision (mAP) while reducing the computational load by 40%.
Dual-Layer Path Planning Model for Autonomous Vehicles in Urban Road Networks Using an Improved Deep Q-Network Algorithm with Proportional–Integral–Derivative Control
Authors: Xu Guoji , Chen Lingling , Zhao Xiaohui , Liu Wengang , Yu Yue , Huang Fusen , Wang Yifan , Chen Yifan
Published: December 2024

With the continuous progress of intelligent transportation systems and automated driving technologies, complex urban road environments put forward higher requirements on the real-time characteristic and accuracy of path planning algorithms. Traditional single-layer path planning methods struggle to effectively handle the complexity of road and lane networks, leading to high computational complexity and suboptimal planning outcomes. To address this issue, we propose a dual-layer path planning model. First, at the road level, we employ the A* algorithm to efficiently determine the optimal macroscopic route, reducing computational overhead. At the lane level, we introduce a Proportional–Integral–Derivative Q-network (PIDQN) based on deep reinforcement learning, which leverages PID control mechanisms to enhance lane selection accuracy and adaptability. By incorporating proportional, integral, and derivative control, PIDQN effectively handles dynamic environments and avoids local optima, ensuring stable and faster convergence. Compared with traditional Deep Q-Network (DQN) and Q-learning algorithms, PIDQN demonstrates significant improvements in success rate and convergence speed in path planning tasks. Using high-precision maps in real-world environments and Python for simulation experiments, we verify the superiority of this approach in complex urban road networks, and we compare the performance of traditional A* algorithms and two-layer planning algorithms. The results show that the two-layer planning algorithm outperforms the traditional A* algorithm and provides a more robust and efficient solution for self-driving car navigation.
Stability Prediction Model of Transmission Tower Slope Based on ISCSO-SVM
Authors: Zhang Zilong , Liu Xiaoliang , Wang Yanhai , Li Enyang , Zhang Yuhao
Published: December 2024

Landslides induced by heavy rainfall are common in southern China and pose significant risks to the safe operation of transmission lines. To ensure the reliability of transmission line operations, this paper presents a stability prediction model for transmission tower slopes based on the Improved Sand Cat Swarm Optimization (ISCSO) algorithm and Support Vector Machine (SVM). The ISCSO algorithm is enhanced with dynamic reverse learning and triangular wandering strategies, which are then used to optimize the kernel and penalty parameters of the SVM, resulting in the ISCSO-SVM prediction model. In this study, a typical transmission tower slope in southern China is used as a case study, with the transmission tower slope database generated through orthogonal experimental design and Geo-studio simulations. In addition to traditional input features, an additional input—transmission tower catchment area—is incorporated, and the stable state of the transmission tower slope is set as the predicted output. The results demonstrate that the ISCSO-SVM model achieves the highest prediction accuracy, with the smallest errors across all metrics. Specifically, compared to the standard SVM, the MAPE, MAE, and RMSE values are reduced by 70.96%, 71.41%, and 57.37%, respectively. The ISCSO-SVM model effectively predicts the stability of transmission tower slopes, thereby ensuring the safe operation of transmission lines.
Optimizing Heat Pump Control in an NZEB via Model Predictive Control and Building Simulation
Authors: Baumann Christian , Wohlgenannt Philipp , Streicher Wolfgang , Kepplinger Peter
Published: December 2024

EU regulations get stricter from 2028 on by imposing net-zero energy building (NZEB) standards on new residential buildings including on-site renewable energy integration. Heat pumps (HP) using thermal building mass, and Model Predictive Control (MPC) provide a viable solution to this problem. However, the MPC potential in NZEBs considering the impact on indoor comfort have not yet been investigated comprehensively. Therefore, we present a co-simulative approach combining MPC optimization and IDA ICE building simulation. The demand response (DR) potential of a ground-source HP and the long-term indoor comfort in an NZEB located in Vorarlberg, Austria over a one year period are investigated. Optimization is performed using Mixed-Integer Linear Programming (MILP) based on a simplified RC model. The HP in the building simulation is controlled by power signals obtained from the optimization. The investigation shows reductions in electricity costs of up to 49% for the HP and up to 5% for the building, as well as increases in PV self-consumption and the self-sufficiency ratio by up to 4% pt., respectively, in two distinct optimization scenarios. Consequently, the grid consumption decreased by up to 5%. Moreover, compared to the reference PI controller, the MPC scenarios enhanced indoor comfort by reducing room temperature fluctuations and lowering the average percentage of people dissatisfied by 1% pt., resulting in more stable indoor conditions. Especially precooling strategies mitigated overheating risks in summer and ensured indoor comfort according to EN 16798-1 class II standards.
Using RES Surpluses to Remove Overburden from Lignite Mines Can Improve the Nation’s Energy Security
Authors: Jurdziak Leszek , Kawalec Witold , Kasztelewicz Zbigniew , Parczyk Pawel
Published: December 2024

The increasing use of renewable energy sources, such as wind and solar energy, presents challenges to the stability and efficiency of other energy sources due to their intermittent and unpredictable surpluses. The unintended consequence of stabilizing the power supply system is an increase in emissions and external costs from the suboptimal use of coal power plants. The rising number of RES curtailments needs to be addressed by either the adjusting energy supply from fossil fuel or the flexible energy consumption. In Poland’s energy mix, coal-fired power plants are a critical component in ensuring energy security for the foreseeable future. Using domestic lignite to generate a total power of 8.5 GW can stabilize the national power supply, as it is currently done in Germany, where 15 GW of lignite-fueled power units provide the power supply base for the country. The leading Belchatów power plant comprises 10 retrofitted units and one new unit, with a total rating of 5.5 GW. Access to the new coal deposit, Zloczew, is necessary to ensure its longer operation. The other domestic lignite power plants are located in Central Poland at Patnów (0.47 GW from the new unit and 0.6 GW from its three retrofitted counterparts) and located in the Lusatian lignite basin at Turów (operating a brand new unit rated at 0.5 GW and retrofitted units with a total rating of 1.5 GW). The use of this fuel is currently being penalized as a result of increasing carbon costs. However, the continuous surface mining technology that is used in lignite mines is fully electrified, and large amounts of electric energy are required to remove and dump overburden and mining coal and its conveying to power units (the transport of coal from the new lignite mine Zloczew to the Belchatów power plant would be a long-distance operation). A possible solution to this problem is to focus on the lignite fuel supply operations of these power plants, with extensive simulations of the entire supply chain. A modern lignite mine is operated by one control room, and it can balance the dynamic consumption of surplus renewable energy sources (RESs) and reduce the need for reduction. When a lignite supply chain is operated this way, a high-capacity power bank can be created with energy storage in the form of an open brown coal seam. This would enable an almost emission-free supply of cheap and domestic fossil fuel, making it insensitive to changes in the world prices of energy resources for power units operating at the base of the system. Furthermore, extending the life of relatively new and efficient lignite-fired units in Poland would facilitate the decommissioning of older and exhausted hard coal-fired units.
Evaluation of the Efficiency of Heat Exchanger Channels with Different Flow Turbulence Methods Using the Entropy Generation Minimization Criterion
Authors: Jasiński Piotr Bogusław , Górecki Grzegorz , Cebulski Zbigniew
Published: December 2024

This paper presents the results of an optimization analysis of two types of thermal fluid channels. The selected geometries were evaluated according to the criterion of the Entropy Generation Minimization method as suggested by Adrian Bejan, with reference to a smooth pipe of the same diameter. The aim of this research was to assess the effectiveness of two channels that intensify heat transfer in different ways: with an insert (disrupting the flow in the pipe core) and with internal fins (disrupting the flow at the pipe wall), and to compare the results using the same criterion: the EGM method. The tested insert consisted of spaced streamline-shaped flow turbulizing the elements fixed in the axis of the pipe and spaced at equal distances from each other. The second channel was formed by making a right-angled triangle (rib profile) on the deformation of the pipe wall perimeter. Using computer modeling, the effect of the two geometric parameters of the above-mentioned channels on the flux of entropy generated was studied. These are (a) the diameter of the disturbing element (“droplet”) and the distance between these elements for a channel with a turbulent insert, and (b) the height of the rib and the longitudinal distance between them for a finned channel. The novelty resulting from the research is the discovery that the turbulization of the flow in the pipe wall boundary layer generates significantly less irreversible entropy than the disturbance of the flow in the pipe axis by the insert.
Hydrologic Perturbation Is a Key Driver of Tree Mortality in Bottomland Hardwood Wetland Forests of North Carolina, USA
Authors: Aguilos Maricar , Carter Cameron , Middlebrough Brandon , Bulluck James , Webb Jackson , Brannum Katie , Watts John Oliver , Lobeira Margaux , Sun Ge , McNulty Steve , King John
Published: December 2024

Bottomland hardwood wetland forests along the Atlantic Coast of the United States have been changing over time; this change has been exceptionally apparent in the last two decades. Tree mortality is one of the most visually striking changes occurring in these coastal forests today. Using 2009–2019 tree mortality data from a bottomland hardwood forest monitored for long-term flux studies in North Carolina, we evaluated species composition and tree mortality trends and partitioned variance among hydrologic (e.g., sea level rise (SLR), groundwater table depth), biological (leaf area index (LAI)), and climatic (solar radiation and air temperature) variables affecting tree mortality. Results showed that the tree mortality rate rose from 1.64% in 2009 to 45.82% over 10 years. Tree mortality was primarily explained by a structural equation model (SEM) with R2 estimates indicating the importance of hydrologic (R2 = 0.65), biological (R2 = 0.37), and climatic (R2 = 0.10) variables. Prolonged inundation, SLR, and other stressors drove the early stages of ‘ghost forest’ formation in a formerly healthy forested wetland relatively far inland from the nearest coastline. This study contributes to a growing understanding of widespread coastal ecosystem transition as the continental margin adjusts to rising sea levels, which needs to be accounted for in ecosystem modeling frameworks.
Optimizing Multidimensional Spectral Indices and Ensemble Learning Methods for Estimating Nitrogen Content in Torreya grandis Leaves Based on UAV Hyperspectral
Authors: Jin Xiaochen , Xu Liuchang , Feng Hailin , Wang Ketao , Niu Junqi , Su Xinyuan , Chen Luyao , Zheng Hongting , Huang Jianqin
Published: December 2024

Ensuring sufficient nitrogen intake during the early growth stages of Torreya grandis is crucial for improving future fruit yield and quality. Hyperspectral remote sensing, enabled by unmanned aerial vehicle (UAV) platforms, provides extensive spectral information on forest canopies across large areas. However, the potential of combining multidimensional optimized spectral features with advanced machine learning models to estimate leaf nutrient stress has not yet been fully exploited. This study aims to combine optimized spectral indices and ensemble learning methods to enhance the accuracy and robustness of estimating leaf nitrogen content (LNC) in Torreya grandis. Initially, based on full-band spectral information, five spectral transformations were applied to the original spectra. Then, nine two-band spectral indices and twelve three-band spectral indices were optimized based on published formulas. This process created a total of 27 spectral features across three dimensions. Subsequently, spectral features of varying dimensions were combined with multiple linear regression (MLR), decision tree regression (DTR), random forest (RF), and eXtreme Gradient Boosting (XGBoost) to train base estimators for ensemble models. Using a stacking strategy, various modeling combinations were experimented with, resulting in the construction of 22 LNC estimation models. The results indicate that combining two-band and three-band spectral features can more comprehensively capture the subtle changes in the nitrogen status of Torreya grandis, with the optimized spectral index mNDVIblue (555, 569, 572) showing the highest correlation with LNC at −0.820. In the modeling phase, the base estimators used MLR, RF, and XGBoost, while the meta estimator employed MLR’s stacking model to achieve the highest accuracy and relatively high stability on the validation set (R2 = 0.846, RMSE = 1.231%, MRE = 3.186%). This study provides a reference for the efficient and non-destructive detection of LNC or other phenotypic traits in large-scale economic forest crops using UAV hyperspectral technology.
Impact of Urban Green Infrastructure on the Respiratory Health of Older Adults in Shenyang, China
Authors: Li Zhenxing , Chu Yaqi , Shi Yu , Huang Na , Shi Tiemao
Published: December 2024

As the global population ages, respiratory health among the elderly has become a key public health concern. Although urban green infrastructure (UGI) has the potential to improve air quality and promote health, research on how its layout patterns influence respiratory health among older adults remains limited. This study focuses on elderly residents aged 60 and above in the central urban area of Shenyang, China, to evaluate the relative importance and interactions of different features affecting respiratory health. We utilized the St. George’s Respiratory Questionnaire (SGRQ) to collect data on respiratory health and employed hierarchical regression and random forest (RF) models to analyze the impact of UGI factors across three spatial scales (300 m, 500 m, and 1000 m). The results indicate that UGI within a 300 m radius of participants’ residences contributes most significantly to respiratory health, with diminishing marginal effects as the spatial scale increases. Green space area (GSA) and the NDVI were identified as the most important factors influencing respiratory health, while green landscape pattern metrics had a greater influence at larger spatial extents. Additionally, a significant nonlinear marginal effect was observed between UGI and respiratory health. These findings provide key insights for health-oriented urban planning and green infrastructure design.