bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultrasonic Atomization as a Method for Testing Material Properties of Liquid Metals
Authors: Presz Wojciech , Szostak-Staropiętka Rafał , Dziubińska Anna , Kołacz Katarzyna
Published: December 2024

Ultrasonic atomization is an object of steadily increasing interest from metal powder manufacturers, both for additive manufacturing and powder metallurgy. Based on the analysis of available theoretical studies, simulations and experiments, it was noted that the average particle size after atomization and the final particle size distribution depend on the process parameters (e.g., frequency, amplitude) and the parameters of the atomized fluid (e.g., viscosity, surface tension). The objective of this study is to evaluate the feasibility of using ultrasonic atomization to study the properties of liquid metals. It attempts to close a gap in existing knowledge in searching for a new, possibly simple and cost-effective method to study the properties of liquid metals and clarify the relationship between ultrasonic atomization parameters (amplitude, frequency, metal spill on vibrating surface) and obtained atomization results (average particle size, particle size distribution, atomization time). Utilizing numerical modeling as a methodology, especially the finite element method, the possibilities of using ultrasonic atomization as an instrument to determine properties of liquid metals were considered as an introduction to a series of real experiments. Modeling was applied to liquids with different properties, atomized at a chosen specific constant frequency and amplitude. The results of the simulation are in line with the current state of knowledge about ultrasonic atomization. However, in the existing studies available to the authors, there are no data that can be compared directly, but indirect comparisons confirmed the conclusions of the preliminary literature analysis. The relationship between viscosity and surface tension and the average size of the atomization processes obtained in the simulation of particles was demonstrated, thus providing a tool for the development of the presented concept: ultrasonic atomization as a research method. Research and simulation results led to the final conclusion: ultrasonic atomization can be applied to study the properties of liquid metals and this will be the subject of further research and experimentation.
The Dual Hamilton–Jacobi Equation and the Poincaré Inequality
Authors: He Rigao , Wang Wei , Fang Jianglin , Li Yuanlin
Published: December 2024

Following the equivalence between logarithmic Sobolev inequalities and hypercontractivity shown by L. Gross, and applying the ideas and methods of the work by Bobkov, Gentil and Ledoux, we would like to establish a new connection between the logarithmic Sobolev inequalities and the hypercontractivity of solutions of dual Hamilton–Jacobi equations. In addition, Poincaré inequality is also recovered by the dual Hamilton–Jacobi equations.
Predictive Value of Varicocele Grade and Histopathology in Simultaneous Varicocelectomy and Sperm Retrieval in Non-Obstructive Azoospermia: A Retrospective Cohort Study
Authors: Kaltsas Aris , Dimitriadis Fotios , Chrisofos Michael , Sofikitis Nikolaos , Zachariou Athanasios
Published: December 2024

Background and Objectives: Varicocele repair in men with non-obstructive azoospermia (NOA) remains a subject of debate due to inconsistent outcomes. This study aimed to evaluate the impact of microsurgical varicocelectomy on sperm recovery rates in men with NOA and to assess the role of varicocele grade and testicular histopathology in predicting postoperative outcomes. Materials and Methods: A retrospective cohort study was conducted of 78 men diagnosed with NOA and clinical varicocele who underwent microsurgical subinguinal varicocelectomy with simultaneous diagnostic and therapeutic testicular biopsy at the Department of Urology of the University of Ioannina between September 2013 and December 2021. Varicoceles were graded I to III based on physical examination and Doppler ultrasound. Histopathological patterns were classified as hypospermatogenesis (HYPO), early maturation arrest (EMA), late maturation arrest (LMA), or Sertoli cell-only syndrome (SCOS). Patients were followed postoperatively at 3, 6, 9, and 12 months, with semen analyses performed according to World Health Organization guidelines to assess sperm presence. Results: At the 12-month follow-up, spermatozoa were detected in the ejaculate of 26 out of 78 patients, resulting in an overall sperm return to ejaculate rate of 33.3%. Varicocele grade significantly influenced outcomes: patients with Grade II varicoceles had the highest sperm return to ejaculate rate (45.2%, 14/31), followed by Grade III (39.1%, 9/23) and Grade I (12.5%, 3/24) (p-value < 0.05). The sperm retrieval rate (SRR) from testicular biopsies also varied with varicocele grade: Grade II had the highest SRR (54.8%, 17/31), followed by Grade III (47.8%, 11/23) and Grade I (33.3%, 8/24). Histopathological findings were significant predictors of sperm retrieval: patients with HYPO had an SRR of 84.8% (28/33) and a sperm return to ejaculate rate of 66.7% (22/33); those with LMA had an SRR of 47.1% (8/17) and a sperm return rate of 23.5% (4/17). No sperm retrieval was observed in patients with EMA (0%, 0/4) or SCOS (0%, 0/24) (p-value < 0.01). Multivariate logistic regression identified varicocele grade and histopathology as independent predictors of sperm retrieval, with higher grades and favorable histopathology associated with increased likelihood of success. Conclusions: Microsurgical varicocelectomy can induce spermatogenesis in a significant proportion of men with NOA, particularly those with higher-grade varicoceles and favorable histopathological patterns such as HYPO or LMA. Varicocele grade and histopathological findings are important predictors of postoperative outcomes and should inform patient selection and counseling. These findings provide valuable insights for optimizing fertility treatments in men with NOA undergoing varicocele repair.
An Analysis and Interpretation of Magnetic Data of the Qing-Chengzi Deposit in Eastern Liaoning (China) Area: Guide for Structural Identification and Mineral Exploration
Authors: Li Jianyu , Wang Jun , Meng Xiaohong , Fang Yuan , Li Weichen , Yang Shunong
Published: December 2024

Qing-Chengzi (QCZ) is an important silver-gold mining area in the eastern part of the Northeast China Craton. The shallow minerals in this area are almost completely depleted, leading to a demand for exploration to find deeper, concealed deposits. However, due to the rugged terrain, few high-precision ground surveys have been executed in this area, resulting in an insufficient understanding of the unexposed ores. To address this issue, this study implemented a high-precision ground magnetic survey to identify faults and potential rocks in this area. To achieve these goals, remanence was analyzed to reduce its adverse effect on processing. Then, lineament enhancement with directional derivatives was conducted on the pre-processed magnetic anomalies to highlight structural features. Based on the results, eight major and twenty-one minor faults were identified, among which three major faults correspond well to the known faults. Most of the major faults run N–S, and the others run NW/NE. Furthermore, 3D inversion was conducted to locate potential rocks. Our inversion results indicate that there are six hidden rocks in the underground, extending from a depth of a few hundred meters to no more than three km. Two of the rocks correspond well to the already mined areas. This study provides support for subsequent exploration in the QCZ area.
Efficient Photocatalytic Removal of Aqueous Ammonia Nitrogen by g-C3N4/CoP Heterojunctions Under Visible Light Illumination
Authors: Wang Dongxu , Mao Wanfeng , Zhao Lihong , Meng Duo , Tang Jiaqi , Wu Tengfei
Published: December 2024

With the development of industry, agriculture, and aquaculture, excessive ammonia nitrogen mainly involving ionic ammonia (NH4+) and molecular ammonia (NH3) has inevitable access to the aquatic environment, posing a severe threat to water safety. Photocatalytic technology shows great advantages for ammonia nitrogen removal, such as its efficiency, reusability, low cost, and environmental friendliness. In this study, CP (g-C3N4/CoP) composite materials, which exhibited high-efficiency ammonia nitrogen removal, were synthesized through a simple self-assembly method. For the optimal CP-10 (10% CoP) samples, the removal rate of ammonia nitrogen reached up to 94.8% within 80 min under visible light illumination. In addition, the nitrogen selectivity S(N2) is about 60% for all oxidative products. The high performance of the CP-10 photocatalysts can be ascribed to the effective separation and transmission of electron–hole pairs caused by their heterogeneous structure. This research has significance for the application of photocatalysis for the remediation of ammonia nitrogen wastewater.
Enhanced Energy Storage Performance in La-Doped CaBi4Ti4O15 Films Through the Formation of a Weakly Coupled Relaxor
Authors: Liu Quanlong , Zhang Lei , Ouyang Jun , Liu Yan , Tang Zhehong , Chen Jieyu , Guo Fei , Zhou Yunpeng
Published: December 2024

Relaxor ferroelectric film capacitors exhibit high power density with ultra-fast charge and discharge rates, making them highly advantageous for consumer electronics and advanced pulse power supplies. The Aurivillius-phase bismuth layered ferroelectric films can effectively achieve a high breakdown electric field due to their unique insulating layer ((Bi2O2)2+ layer)). However, designing and fabricating Aurivillius-phase bismuth layer relaxor ferroelectric films with optimal energy storage characteristics is challenging due to their inherently stable ferroelectric properties. In this work, lead-free CaBi4-xLaxTi4O15 films were synthesized using the sol–gel technique and a weakly coupled relaxor design. On one hand, the introduction of La3+ ions weaken the dipole–dipole interactions, thereby enhancing the relaxor behavior. Alternatively, the expansion of grain size is restricted to enhance the number of grain boundaries, which possess improved insulating properties. This leads to a higher breakdown electric field. The results indicate that CaBi4-xLaxTi4O15 (x = 1.0) films exhibit excellent recoverable energy storage density (70 J/cm3) and high energy efficiency (73%). Moreover, the film exhibited good temperature stability and frequency stability. This study not only identifies a promising material for dielectric film capacitors but also demonstrates that the energy storage capabilities of Aurivillius-phase bismuth layer ferroelectric films can be effectively modulated through a design incorporating weakly coupled relaxor characteristics.
Innovative One-Step Sustainable Process to Produce Simonkolleite Nanoparticles
Authors: Daniele Valeria , Mondelli Claudia , Turilli Laura , Taglieri Giuliana
Published: December 2024

The aim of the present paper is to propose an innovative, one-step and sustainable process allowing us to obtain almost 10 kg/week of pure and crystalline simonkolleite nanoparticles (SK NPs) in only 8 min of reaction, working in water, under ambient conditions of pressure/temperature, guaranteeing at the same time low environmental impact and a high yield of NP production. In addition, the obtained NPs can also act as ZnO precursors at ambient temperature, and this result supports the sustainability of the process considering that, generally, the production of ZnO from SK occurred via annealing at high temperatures. The SK NPs appeared pure and crystalline, characterized by a highly uniform hexagonal lamellar feature. Each lamella is composed of an ordered assembly of very small monodispersed primary NPs, with a size in the range 3–8 nm. The SK NPs exhibited a surface area of up to 41 m2/g, the highest value recorded in the literature, revealing that pore size distribution mainly peaked between 3 and 20 nm.
Studies on Morphological Evolution of Gravure-Printed ZnO Thin Films Induced by Low-Temperature Vapor Post-Treatment
Authors: Sico Giuliano , Guarino Vincenzo , Borriello Carmela , Montanino Maria
Published: December 2024

In recent years, the morphology control of semiconductor nanomaterials has been attracting increasing attention toward maximizing their functional properties and reaching their end use in real-world devices. However, the development of easy and cost-effective methods for preparing large-scale patterned semiconductor structures on flexible temperature-sensitive substrates remains ever in demand. In this study, vapor post-treatment (VPT) is investigated as a potential, simple and low-cost post-preparative method to morphologically modify gravure-printed zinc oxide (ZnO) nanoparticulate thin films at low temperatures. Exposing nanoparticles (NPs) to acidic vapor solution, spontaneous restructuring pathways are observed as a consequence of NPs tending to reduce their high interfacial energy. Depending on the imposed environmental conditions during the treatment (e.g., temperature, vapor composition), various ZnO thin-film morphologies are produced, from dense to porous ones, as a result of the activation and interplay of different spontaneous interface elimination mechanisms, including dissolution–precipitation, grain boundary migration and grain rotation–coalescence. The influence of VPT on structural/optical properties has been examined via XRD, UV–visible and photoluminescence measurements. Controlling NP junctions and network nanoporosity, VPT appears as promising cost-effective, low-temperature and pressureless post-preparative platform for preparing supported ZnO NP-based films with improved connectivity and mechanical stability, favoring their practical use and integration in flexible devices.
Associations of Coffee and Tea Consumption on Neural Network Connectivity: Unveiling the Role of Genetic Factors in Alzheimer’s Disease Risk
Authors: Li Tianqi , Fili Mohammad , Mohammadiarvejeh Parvin , Dawson Alice , Hu Guiping , Willette Auriel
Published: December 2024

Background: Coffee and tea are widely consumed beverages, but their long-term effects on cognitive function and aging remain largely unexplored. Lifestyle interventions, particularly dietary habits, offer promising strategies for enhancing cognitive performance and preventing cognitive decline. Methods: This study utilized data from the UK Biobank cohort (n = 12,025) to examine the associations between filtered coffee, green tea, and standard tea consumption and neural network functional connectivity across seven resting-state networks. We focused on networks spanning prefrontal and occipital areas that are linked to complex cognitive and behavioral functions. Linear mixed models were used to assess the main effects of coffee and tea consumption, as well as their interactions with Apolipoprotein E (APOE) genetic risk—the strongest genetic risk factor for Alzheimer’s disease (AD). Results: Higher filtered coffee consumption was associated with increased functional connectivity in several networks, including Motor Execution, Sensorimotor, Fronto-Cingular, and a Prefrontal + ‘What’ Pathway Network. Similarly, greater green tea intake was associated with enhanced connectivity in the Extrastriate Visual and Primary Visual Networks. In contrast, higher standard tea consumption was linked to reduced connectivity in networks such as Memory Consolidation, Motor Execution, Fronto-Cingular, and the “What” Pathway + Prefrontal Network. The APOE4 genotype and family history of AD influenced the relationship between coffee intake and connectivity in the Memory Consolidation Network. Additionally, the APOE4 genotype modified the association between standard tea consumption and connectivity in the Sensorimotor Network. Conclusions: The distinct patterns of association between coffee, green tea, and standard tea consumption and resting-state brain activity may provide insights into AD-related brain changes. The APOE4 genotype, in particular, appears to play a significant role in modulating these relationships. These findings enhance our knowledge of how commonly consumed beverages may influence cognitive function and potentially AD risk among older adults.
Nursing Students’ Experiences About Clinical Practice Tutoring: A Cross-Sectional Observational Study
Authors: Borrallo-Riego Álvaro , Magni Eleonora , Pérez-Jiménez José Miguel , Guerra-Martín María Dolores
Published: December 2024

Objective: Nursing students’ experiences about clinical practice tutoring in a public university from southern Spain and at its two attached educational centres were analysed. Methods: A cross-sectional observational study was carried out. The population was comprised of nursing students attending their fourth year of university during the 2023/2024 academic period, with a final sample of 179 subjects. Sociodemographic data were collected and a validated questionnaire on opinions about the figure of clinical practice tutors was applied, with 34 closed questions offering five answer options. The questions were categorized into 17 dimensions. A question on the students’ satisfaction with tutoring of the practices was included, in addition to an open question to gather the students’ comments and/or suggestions in relation to clinical practice tutoring. The analysis was performed through a data matrix in SPSS. The Kruskal–Wallis test was used to compare the centres according to the questionnaire dimensions, considering p-values < 0.05 to establish statistically significant differences. The open question was analysed using Atlas.ti. Results: Most of the students were women, with an approximate mean age of 23 years old. Significant differences were detected among the centres in almost all dimensions from the questionnaire. High satisfaction levels were obtained in the three centres. A total of 83 verbatims were collected in the open question and grouped into eight categories. Conclusion: Nursing students place significant importance on the role of the clinical tutor. Clinical tutors who demonstrate enthusiasm for teaching, foster a positive environment based on active listening, respect, and the encouragement of autonomy, are essential to enhancing the students’ experience during clinical placements.
Overweight and Obesity Contribute to Inflammation and Reduction in Mean Corpuscular Volume and Mean Corpuscular Hemoglobin in Schoolchildren
Authors: Fernandes Bárbara Leles , Cozer Alexandre Wallace Dias , Vasconcelos Souza Filipe Caldeira , Santiago Luana Dias , Lima Marlucy Rodrigues , Leite Pauline Martins , Silveira Alda Maria Soares , Enes Barbara Nery , Ottoni Marcelo Henrique Fernandes , Gama Rafael Silva , Gomides Thalisson Artur Ribeiro
Published: December 2024

Background: The inflammation associated with overweight and obesity seems to alter iron metabolism, but there are few studies evaluating those conditions in children. Thus, we aimed to evaluate the leukometric, immunological, and hematimetric parameters of overweight and obese schoolchildren. Methods: This is a cross-sectional study in which 39 children living in Chonim de Cima (Brazil) underwent anthropometric, hematological, and immunological assessments. The evaluated parameters were compared between the study group (overweight/obesity, n = 15) and the control group (n = 24). Unpaired t-test, Mann–Whitney test, and linear regression were used for statistical tests, and the panoramic profile was used to illustrate differences between groups. Results: The study group had lower mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) and higher TNF levels compared to the control group. Positive correlations were observed between BMI-for-age percentile and total leukocytes (r = 0.1493; p = 0.0151) or neutrophils (r = 0.1395; p = 0.0192). Negative correlations between the BMI-for-age percentile and MCV (r = 0.1464; p = 0.0162) and MCH (r = 0.1460; p = 0.0164) were found. Furthermore, through the panoramic profile, it was noted that the study group had a higher frequency of individuals with high levels of TNF and lower frequencies of individuals with increased hemoglobin and serum iron. Conclusions: Our data suggest that overweight and obesity contribute to a pro-inflammatory context (leukocytes, neutrophils, and TNF) and MCV and MCH reduction in schoolchildren.
In Vitro Dynamic Model Evaluation of Meropenem Alone and in Combination with Avibactam Against Carbapenemase-Producing Klebsiella pneumoniae
Authors: Strukova Elena N. , Portnoy Yury A. , Golikova Maria V. , Zinner Stephen H.
Published: December 2024

Background: A potential strategy to maintain the efficacy of carbapenems against carbapenemase-producing Klebsiella pneumoniae (CPKP) is their combination with carbapenemase inhibitors. To address these issues, the effectiveness of a novel combination of meropenem with avibactam against CPKP was studied. Additionally, the applicability of a pharmacokinetically-based approach to antibiotic/inhibitor minimum inhibitory concentration (MIC) determinations to better predict efficacy was examined. Methods: CPKP strains were exposed to meropenem alone or in combination with avibactam in an in vitro hollow-fiber infection model. Treatment effects were correlated with simulated antibiotic and antibiotic/inhibitor combination ratios of the area under the concentration–time curve (AUC) to the MIC (AUC/MIC). All MICs were determined at standard and at high inocula; combination MICs were determined using the conventional approach with fixed avibactam concentration or using the pharmacokinetic (PK)-based approach with a fixed meropenem-to-avibactam concentration ratio, equal to the respective drug therapeutic AUC ratios. Results: Meropenem alone was not effective even against a “susceptible” CPKP strain. The addition of avibactam significantly improved both meropenem MICs and its effectiveness. The effects of meropenem alone and in combination with avibactam (merged data) correlated well with AUC/MIC ratios only when MICs were determined at high inocula and using the PK-based approach (r2 0.97); the correlation was worse with the conventional approach (r2 0.73). Conclusions: The effectiveness of meropenem/avibactam against CPKP is promising. A single “effect–AUC/MIC” relationship useful for predicting meropenem efficacy (alone or in combination with avibactam) was obtained using MICs at high inocula and combination MICs determined using a PK-based approach.
Application of Microsponge Drug Platform to Enhance Methotrexate Administration in Rheumatoid Arthritis Therapy
Authors: Fiaschini Noemi , Hanieh Patrizia Nadia , Ariaudo Daniela , Cimino Rita , Abbate Carlo , Romano Elena , Cavalieri Francesca , Venanzi Mariano , Palumbo Valeria , Scimeca Manuel , Bernardini Roberta , Mattei Maurizio , Migliore Alberto , Rinaldi Antonio
Published: December 2024

Background/Objectives: This study aimed to develop a novel nanotechnological slow-release drug delivery platform based on hyaluronic acid Microsponge (MSP) for the subcutaneous administration of methotrexate (MTX) in the treatment of rheumatoid arthritis (RA). RA is a chronic autoimmune disease characterized by joint inflammation and damage, while MTX is a common disease-modifying antirheumatic drug (DMARD), the conventional use of which is limited by adverse effects and the lack of release control. Methods: MSP were synthesized as freeze-dried powder to increase their stability and allow for a facile reconstitution prior to administration and precise MTX dosing. Results: A highly stable and rounded-shaped micrometric MSP, characterized by an open porosity inner structure, achieved both a high MTX loading efficiency and a slow release of MTX after injection. Our drug release assays indeed demonstrated a characteristic drug release profile consisting of a very limited burst release in the first few hours, followed by a slow release of MTX sustained for over a month. By means of a preclinical rat model of RA, the administration of MTX-loaded MSP proved to nearly double the therapeutic efficacy compared to sole MTX, according to a steep reduction in arthritic score compared to control groups. The preclinical study was replicated twice to confirm this improvement in performance and the safety profile of the MSP. Conclusions: This study suggests that the MSP drug delivery platform holds significant potential for clinical use in improving RA therapy by enabling the sustained slow release of MTX, thereby enhancing therapeutic outcomes and minimizing side effects associated with conventional burst-release drug administration.
Optimizing Irrigation Strategies to Improve Yield and Water Use Efficiency of Drip-Irrigated Maize in Southern Xinjiang
Authors: Bian Qingyong , Dong Zhiduo , Fu Yanbo , Zhao Yupeng , Feng Yaozu , Wang Zhiguo , Zhu Jingquan
Published: December 2024

The contradiction between increased irrigation demand and water scarcity in arid regions has become more acute for crops as a result of global climate change. This highlights the urgent need to improve crop water use efficiency. In this study, four irrigation volumes were established for drip-irrigated maize under plastic mulch: 2145 m3 ha−1 (W1), 2685 m3 ha−1 (W2), 3360 m3 ha−1 (W3), and 4200 m3 ha−1 (W4). The effects of these volumes on soil moisture, maize growth, water consumption, crop coefficients, and yield were analyzed. The results showed that increasing the irrigation volume led to a 2.86% to 8.71% increase in soil moisture content, a 24.56% to 47.41% increase in water consumption, and a 3.43% to 35% increase in the crop coefficient. Maize plant height increased by 16.34% to 42.38%, ear height by 16.85% to 51.01%, ear length by 2.43% to 28.13%, and yield by 16.96% to 39.24%. Additionally, soil temperature was reduced by 1.67% to 5.67%, and the maize bald tip length decreased by 6.62% to 48%. The irrigation water use efficiency improved by 6.57% to 28.89%. A comprehensive evaluation using the TOPSIS method demonstrated that 3360 m3 ha−1 of irrigation water was an effective irrigation strategy for increasing maize yield under drip irrigation with plastic mulch in the southern border area. Compared to 4200 m3 ha−1, this strategy saved 840 m3 ha−1 of irrigation water, increased the irrigation water use efficiency by 23.96%, and resulted in only a 0.84% decrease in yield. The findings of this study provide a theoretical foundation for optimizing production benefits in the context of limited water resources.
Multi-Functional and Multi-Scale Aspects in Polymer Composites
Authors: Alam Md Najib , Kumar Vineet
Published: December 2024

Polymer composites have gained attention due to their multifunctionality and ability to tune properties at multiple scales [...]
Fight, Not Flight! Avoidant Goals Strengthen Attentional Biases During Increased Anxiety in Healthy Adults
Authors: Sakemoto Natsuki , Tanaka Hideyuki
Published: December 2024

Heightened anxiety can impair perceptual-motor performance, with detrimental effects potentially arising, in part, from threat-related attentional biases and interpretations. Shifting from a flight (i.e., threat) mindset to a fight (i.e., challenge) mindset may be an effective strategy for coping with anxiety and improving performance on perceptual-motor tasks. In this context, the present study examined how differences in fight-or-flight behavioral goals, represented by hit or avoidance actions, influence attentional control in response to threatening stimuli during heightened anxiety. Healthy adult participants performed a visual probe task, with half responding to a probe target in hit mode and the other half responding in avoidance mode. Anxiety levels were manipulated using the threat-of-shock (ToS) method, which significantly increased the participants’ anxiety. Participants with avoidance goals exhibited significantly delayed responses when avoiding a target in the presence of threat-related stimulus cues under the ToS condition. Conversely, no changes in response times were observed between the ToS and no ToS conditions in those with hit goals. These results suggest that when anxiety is heightened, avoidance goals induce attentional biases toward threat-related stimuli. In conclusion, encouraging avoidance of potential threat-related sources as an action mode may be counterproductive for coping with heightened anxiety, at least in healthy adults. The study’s principal implication for clinical practice is that adopting fight-like behavioral goals in response to threats may be an effective strategy for managing anxiety in everyday life.
A New Surface Waters Downscaling Approach Applicable at Global Scale
Authors: Nguyen Thu-Hang , Aires Filipe
Published: December 2024

A surface water extent downscaling framework was developed in the past using a floodability index based on topography. We presented here a new downscaling approach including several improvements. (1) The use of a new Floodability Index (FI), including better integration of auxiliary permanent waters (i.e., presence of water during the whole time record). By using this updated FI, the new downscaling became a true data-fusion with permanent water databases originating mainly from visible observations. (2) Some discontinuities between low resolution cells have been reduced thanks to a new smoothing algorithm. (3) Finally, a coastal extrapolation scheme has been presented to deal with coarse resolution data contaminated by the ocean. This new and complex downscaling framework was tested here on the GIEMS (Global Inundation Extent from Multi-Satellite) database but the approach is generalizable and any surface water database could be used instead. It was shown that this new downscaling procedure (including several processing steps, algorithms and data sources) is a significant improvement compared to the previous version thanks to the new floodability index and the downscaling processing chain. Compared to the previous version, the downscaling results (GIEMS-D) were more coherent with the permanent water database and preserved better the original low-resolution information (e.g., mean scare error water fraction (0–1) of 0.0041 for the old version, and 0.0018 for the new version, over flooded areas in the Amazon). GIEMS-D has also been evaluated at the global scale and over the Amazon basin using independent datasets, showing an overall good performance of the downscaling.
Cascaded Feature Fusion Grasping Network for Real-Time Robotic Systems
Authors: Li Hao , Zheng Lixin
Published: December 2024

Grasping objects of irregular shapes and various sizes remains a key challenge in the field of robotic grasping. This paper proposes a novel RGB-D data-based grasping pose prediction network, termed Cascaded Feature Fusion Grasping Network (CFFGN), designed for high-efficiency, lightweight, and rapid grasping pose estimation. The network employs innovative structural designs, including depth-wise separable convolutions to reduce parameters and enhance computational efficiency; convolutional block attention modules to augment the model’s ability to focus on key features; multi-scale dilated convolution to expand the receptive field and capture multi-scale information; and bidirectional feature pyramid modules to achieve effective fusion and information flow of features at different levels. In tests on the Cornell dataset, our network achieved grasping pose prediction at a speed of 66.7 frames per second, with accuracy rates of 98.6% and 96.9% for image-wise and object-wise splits, respectively. The experimental results show that our method achieves high-speed processing while maintaining high accuracy. In real-world robotic grasping experiments, our method also proved to be effective, achieving an average grasping success rate of 95.6% on a robot equipped with parallel grippers.
On the Feasibility of Detecting Faults and Irregularities in On-Load Tap Changers (OLTCs) by Vibroacoustic Signal Analysis
Authors: Ezzaidi Hassan , Fofana Issouf , Picher Patrick , Gauvin Michel
Published: December 2024

Unlike traditional tap changers, which require transformers to be de-energized before making changes, On-Load Tap Changers (OLTCs) can adjust taps while the transformer is in service, ensuring continuous power supply during voltage regulation. OLTCs enhance grid reliability and support load balancing, reducing strain on the network and optimizing power quality. Their importance has grown as the demand for stable voltage and the integration of renewables has increased, making them vital for modern and resilient power systems. While enhanced OLTCs often incorporate stronger materials and improved designs, mechanical components like contacts and diverter switches can still experience wear over time. This can result in longer maintenance intervals. In the era of digitalization, advanced diagnostic techniques capable of detecting early signs of wear or malfunction are essential to enable preventive maintenance for these important components. This contribution introduces a novel method for detecting faults and irregularities in OLTCs, leveraging vibroacoustic signals to enhance OLTC diagnostics. This paper proposes a tolerance-based approach using the envelope of vibroacoustic signals to identify faults. A significant challenge in this field is the limited availability of faulty signal data, which hinders the performance of machine learning algorithms. To address this, this study introduces a nonlinear model utilizing amplitude modulation with a Gaussian carrier to simulate faults by introducing controlled distortions. The dataset used in this study, with data recorded under real operating conditions from 2016 to 2023, is free of anomalies, providing a robust foundation for the analysis. The results demonstrate a marked improvement in the robustness of detecting simulated faults, offering a promising solution for enhancing OLTC diagnostics and preventive maintenance in modern power systems.
Stochastic H∞ Filtering of the Attitude Quaternion
Authors: Choukroun Daniel , Cooper Lotan , Berman Nadav
Published: December 2024

Several stochastic H∞ filters for estimating the attitude of a rigid body from line-of-sight measurements and rate gyro readings are developed. The measurements are corrupted by white noise with unknown variances. Our approach consists of estimating the quaternion while attenuating the transmission gain from the unknown variances and initial errors to the current estimation error. The time-varying H∞ gain is computed by solving algebraic and differential linear matrix inequalities for a given transmission threshold, which is iteratively lowered until feasibility fails. Thanks to the bilinear structure of the quaternion state-space model, the algorithm parameters are independent of the state. The case of a gyro drift is addressed, too. Extensive Monte-Carlo simulations show that the proposed stochastic H∞ quaternion filters perform well for a wide range of noise variances. The actual attenuation, which improves with the noise variance and is worst in the noise-free case, is better than the guaranteed attenuation by one order of magnitude. The proposed stochastic H∞ filter produces smaller biases than nonlinear Kalman or unscented filters and similar standard deviations at large noise levels. An essential advantage of this H∞ filter is that the gains are independent of the quaternion, which makes it insensitive to modeling errors. This desired feature is illustrated by comparing its performances against those of unmatched nonlinear optimal filters. When provided with too high or too low noise variances, the multiplicative Kalman filter and the unscented quaternion filter are outperformed by the H∞ filter, which essentially delivers identical error magnitudes.
Voice Analysis in Dogs with Deep Learning: Development of a Fully Automatic Voice Analysis System for Bioacoustics Studies
Authors: Karaaslan Mahmut , Turkoglu Bahaeddin , Kaya Ersin , Asuroglu Tunc
Published: December 2024

Extracting behavioral information from animal sounds has long been a focus of research in bioacoustics, as sound-derived data are crucial for understanding animal behavior and environmental interactions. Traditional methods, which involve manual review of extensive recordings, pose significant challenges. This study proposes an automated system for detecting and classifying animal vocalizations, enhancing efficiency in behavior analysis. The system uses a preprocessing step to segment relevant sound regions from audio recordings, followed by feature extraction using Short-Time Fourier Transform (STFT), Mel-frequency cepstral coefficients (MFCCs), and linear-frequency cepstral coefficients (LFCCs). These features are input into convolutional neural network (CNN) classifiers to evaluate performance. Experimental results demonstrate the effectiveness of different CNN models and feature extraction methods, with AlexNet, DenseNet, EfficientNet, ResNet50, and ResNet152 being evaluated. The system achieves high accuracy in classifying vocal behaviors, such as barking and howling in dogs, providing a robust tool for behavioral analysis. The study highlights the importance of automated systems in bioacoustics research and suggests future improvements using deep learning-based methods for enhanced classification performance.
Formal Security Reassessment of the 5G-AKA-FS Protocol: Methodological Corrections and Augmented Verification Techniques
Authors: Ko Yongho , Pawana I Wayan Adi Juliawan , You Ilsun
Published: December 2024

The 5G-AKA protocol, a foundational component for 5G network authentication, has been found vulnerable to various security threats, including linkability attacks that compromise user privacy. To address these vulnerabilities, we previously proposed the 5G-AKA-Forward Secrecy (5G-AKA-FS) protocol, which introduces an ephemeral key pair within the home network (HN) to support forward secrecy and prevent linkability attacks. However, a re-evaluation uncovered minor errors in the initial BAN-logic verification and highlighted the need for more rigorous security validation using formal methods. In this paper, we correct the BAN-logic verification and advance the formal security analysis by applying an extended SVO logic, which was adopted as it provides a higher level of verification compared to BAN logic, incorporating a new axiom specifically for forward secrecy. Additionally, we enhance the ProVerif analysis by employing a stronger adversarial model. These refinements in formal verification validate the security and reliability of 5G-AKA-FS, ensuring its resilience against advanced attacks. Our findings offer a comprehensive reference for future security protocol verification in 5G networks
The Association Between Safety Preference and Household Food Waste: Evidence from Chinese Households
Authors: Zhang Li , Ye Linxiang , Qian Long , Zheng Manli
Published: December 2024

Household food waste contributes to 60% of the total global food waste. Based on an online questionnaire survey on household food waste in China, this paper explores the association between food safety preference and household food waste. This demonstrates that (1) the excessive concern about food safety significantly increased the proportion of household food waste, the weight of food wasted, and the food waste ratio. The robustness tests supported this finding. (2) heterogeneity analysis showed that the impact of the safety preference on the likelihood of household food waste varied by the gender of respondents, household size, and urban–rural type. The effect of safety preference on the weight of food wasted in the household varied by the gender and education level, household size, income level, urban–rural type, and located region. Thus, the study provides evidence for reducing household food waste in Chinese households through the popularization of food safety knowledge, which has certain implications for reducing food waste and achieving sustainable food consumption in other developing countries.
Exploring the Synergy of Advanced Lighting Controls, Building Information Modelling and Internet of Things for Sustainable and Energy-Efficient Buildings: A Systematic Literature Review
Authors: Zocchi Gabriele , Hosseini Morteza , Triantafyllidis Georgios
Published: December 2024

Buildings are responsible for approximately 40% of global energy consumption, putting pressure on the construction industry to mitigate its environmental impact. Therefore, there is an urgent need for innovative solutions to reduce power consumption, particularly in lighting systems. This study’s primary objective was to investigate novel integrated lighting solutions that significantly reduce energy use, as well as to explore their enhancement through Building Information Modelling (BIM) and the Internet of Things (IoT) to improve energy efficiency further and reduce the carbon footprint of buildings. Hence, this literature review examined energy-saving actions, retrofitting practices and interventions across a range of multi-use buildings worldwide, focusing on research from 2019 to 2024. The review was conducted using Scopus and Web of Science databases, with inclusion criteria limited to original research. The objective was to diagnose the goals being undertaken and ultimately validate new actions and contributions to minimise energy consumption. After applying eligibility criteria, 48 studies were included in the review. First, daylight harvesting and retrofitting solutions were examined using the latest technologies and external shading. The review indicates a lack of proper coordination between daylight and electrical lighting, resulting in energy inefficiency. Secondly, it reviews how the integration of BIM facilitates the design process, providing a complete overview of all the building variables, thus improving indoor daylight performance and proper lighting with energy analysis. Lastly, the review addresses the role of the Internet of Things (IoT) in providing real-time data from sensor networks, allowing for continuous monitoring of building conditions. This systematic literature review explores the integration of these fields to address the urgent need for innovative strategies and sustainability in the built environment. Furthermore, it thoroughly analyses the current state of the art, identifying best practices, emerging trends and concrete insight for architects, engineers and researchers. The goal is to promote the widespread adoption of low-carbon systems and encourage collaboration among industry professionals and researchers to advance sustainable building design. Ultimately, a new parametric design framework is proposed, consisting of five iterative phases that cover all design stages. This framework is further enhanced by integrating BIM and IoT, which can be used together to plan, reconfigure, and optimise the building’s performance.
Modeling the Efficiency of Resource Consumption Management in Construction Under Sustainability Policy: Enriching the DSEM-ARIMA Model
Authors: Sutthichaimethee Pruethsan , Mentel Grzegorz , Voloshyn Volodymyr , Mishchuk Halyna , Bilan Yuriy
Published: December 2024

The aim of this research is to study the influence of factors affecting the efficiency of resource consumption under the sustainability policy based on using the DSEM-ARIMA (Dyadic Structural Equation Modeling based on the Autoregressive Integrated Moving Average) model. The study is performed using the Thailand experience. The research findings indicate that continuous economic growth aligns with the country’s objectives, directly contributing to continuous social growth. This aligns with the country’s efficient planning. It demonstrates that the management aligns with the goal of achieving Thailand 5.0. Furthermore, considering the environmental aspect, it is found that economic and social growth directly impacts the ecological aspect due to the significant influence of resource consumption in the construction. The resource consumption in construction shows a growth rate increase of 264.59% (2043/2024), reaching 401.05 ktoe (2043), which exceeds the carrying capacity limit set at 250.25 ktoe, resulting in significant long-term environmental degradation. Additionally, considering the political aspect, it is found to have the greatest influence on the environment, exacerbating environmental damage beyond current levels. Therefore, the DSEM-ARIMA model establishes a new scenario policy, indicating that resource consumption in construction leads to environmental degradation reduced to 215.45 ktoe (2043), which does not exceed the carrying capacity. Thus, if this model is utilized, it can serve as a vital tool in formulating policies to steer the country’s growth toward Thailand 5.0 effectively.
Gone with the Wind? An Assessment of Germany’s Onshore Wind Industry Amid Rising Chinese Competition
Authors: Paraschiv Florentina , Anderer Benedict , Ayari Rayan
Published: December 2024

This paper studies the relative competitiveness of Germany’s onshore wind industry compared to China’s and investigates whether an equally drastic value chain relocation, similar to Germany’s solar PV industry, is likely. Based on a comprehensive study of Germany’s domestic market, international competitiveness indicators like the world trade share (WTS), revealed comparative advantage (RCA), and relative export advantage (RXA), as well as an expert interview, we found that Germany’s industry has lost competitiveness in recent years, supply chain shifts to China are observable, and Chinese manufacturers are poised to enter the German market. However, the German onshore wind industry is still competitive, has a strong basis in its domestic market, and, with the right energy policy framework, it could brace the storm. The novelty of this study is threefold: it offers a comprehensive comparison of the German and Chinese wind industries, presents the first analysis of the 2017 EEG reform’s impact on Germany’s wind industry, and is the first study to trace the evolution of domestic and foreign market shares in Germany’s onshore wind market.
Research on the Estimation of Air Pollution Models with Machine Learning in Urban Sustainable Development Based on Remote Sensing
Authors: Chen Wenqian , Zhang Na , Bai Xuesong , Cao Xiaoyi
Published: December 2024

Air quality is directly related to people’s health and quality of life and has a profound impact on the sustainable development of cities. Good air quality is the foundation of sustainable development. To solve the current problem of air quality for sustainable development, we used high-resolution (1 km) satellite-retrieved aerosol optical depth (AOD), meteorological, nighttime light and vegetation data to develop a spatiotemporal convolution feature random forest (SCRF) model to predict the PM2.5 concentration in Shandong from 2016 to 2019. We evaluated the performance of the SCRF model and compared the results of other models, including neural network (BPNN), gradient boosting (GBDT), and random forest (RF) models. The results show that compared with the other models, the improved SCRF model performs best. The coefficient of determination (R2) and root mean square error (RMSE) are 0.83 and 9.87 µg/m3, respectively. Moreover, we discovered that the characteristic variables AOD and air temperature (TEM) data improved the accuracy of the model in Shandong Province. The annual average PM2.5 concentrations in Shandong Province from 2016 to 2019 were 74.44 µg/m3, 65.01 µg/m3, 58.32 µg/m3, and 59 µg/m3, respectively. The spatial distribution of air pollution increases from northeastern and southeastern to western Shandong inland. In general, our research has significant implications for the sustainable development of various cities in Shandong Province.