bluuebunny/crossref_metadata_2025 huggingface dataset:
Voluntary Attention Assessing Tests in Children with Neurodevelopmental Disorders Using Eye Tracking
Authors: Rebreikina Anna , Zakharchenko Dmitry , Shaposhnikova Antonina , Korotkov Nikita , Klimov Yuri , Batysheva Tatyana
Published: October 2024

Background/Objectives: The development of techniques for assessing cognitive functions using eye tracking is particularly important for children with developmental disabilities. In this paper, we present pilot results from the validation of two methods for assessing voluntary attention based on eye tracking. Methods: The study involved 80 children aged 3 to 8 years with neurodevelopmental disorders. Children performed two eye-tracking tests in which they had to ‘catch’ a stimulus by looking at it. They also completed the Attention Sustained subtest of the Leiter-3 International Performance Scale. In the first test, the stimuli were presented at different locations on the screen in subtests with stimuli onset asynchrony of 2 s and 1 s. A translucent blue marker marked the position of the gaze on the screen. The number of trials in which the gaze marker approached the stimulus was determined. In the second test, the location of the stimuli on the screen was changed based on gaze fixation in the ROI area. The time taken to complete the task was evaluated. Results: The results of both eye-tracking tests showed significant correlations with scores on the Attention Sustained Leiter-3 subtest and significant test–retest reliability. Conclusions: The results indicate that the present eye-tracking tests can be used for assessing voluntary attention in children with some neurodevelopmental disorders, and further research is warranted to assess the feasibility of these tests for a broader range of developmental disorders. Our findings could have practical implications for the early intervention and ongoing monitoring of attention-related issues.
Current Trends in the Treatment of Pediatric Hydrocephalus: A Narrative Review Centered on the Indications, Safety, Efficacy, and Long-Term Outcomes of Available Treatment Modalities
Authors: Panagopoulos Dimitrios , Stranjalis Georgios , Gavra Maro , Boviatsis Efstathios , Korfias Stefanos , Karydakis Ploutarchos
Published: October 2024

The pathophysiologic substrate of pediatric hydrocephalus has not been thoroughly elucidated. Valve-based shunt systems have constituted the main therapeutic option since the late 1950s. The initially used systems were concerning the ventricular system and the atrium. In the 1970s, VA shunts were not the main stay of treatment as the preferred option for the terminal end of the drainage system was the peritoneum. Our review analyzes these valve types and attempts a comparison, based on their functional characteristics. Nowadays, the only available surgical alternative for the treatment of hydrocephalus is ETV. This technique is associated with lower infection rates as well as, on average, a lower re-operation rate. Another term that deserves special mention is related to the outcome of ETV in children who had a medical history of previously incorporated shunts and who were subsequently suffering from shunt malfunction. Well-recognized predictive factors associated with secondary ETV failure include age, early onset of hydrocephalus, and prematurity. Although several attempts have been made in order to establish the optimum surgical treatment management in the different subgroups of patientswho are suffering from shunt dysfunction, there is no universal agreement. Therefore, this review attempts to identify the specific subpopulations of patients in whom the insertion of a drainage system as the preferred treatment modality is associated with an optimum long-term prognosis, compared to ETV, and vice versa. The objective of our study is to analyze the safety, efficacy, and outcomes of drainage devices and ETV in pediatric hydrocephalus patients.
Comment on Rodríguez-Cortés et al. Individual Circadian Preference, Eating Disorders and Obesity in Children and Adolescents: A Dangerous Liaison? A Systematic Review and a Meta-Analysis. Children 2022, 9, 167
Authors: López-Gil José Francisco , Barrada Juan Ramón
Published: October 2024

This commentary critically examines the article by Rodríguez-Cortés et al. on the links between circadian preferences, eating disorders, and obesity in pediatric populations, emphasizing the association between evening chronotypes and disordered eating behaviors. Key findings highlight the increased prevalence of food addiction (FA) and night eating syndrome (NES) among evening-oriented children and adolescents, though the article’s reliance on studies with adult samples limits the generalizability of its conclusions. Additionally, the ambiguous classification of FA and NES within broader eating disorder frameworks necessitates further investigation to delineate these behaviors from traditional disorders such as anorexia and bulimia nervosa. This commentary advocates for future research focusing on pediatric populations to explore the intersection of circadian misalignment with emotional regulation and environmental factors, aiming to develop tailored preventative strategies that incorporate chronobiological and lifestyle modifications.
Educational Strategies for Teaching Climate and Bioclimate in Response to Global Change
Authors: Cano-Ortiz Ana , Musarella Carmelo Maria , Cano Eusebio
Published: October 2024

This work establishes the relationship between climate, bioclimate, and forest ecosystems and highlights the need to teach these topics in educational institutions. It was found that such knowledge is not currently taught in universities, leading to scarce or non-existent teacher training in these areas. However, the teaching of bioclimatic aspects over a three-year period as a basis for land use planning, has shown highly positive results. The objective is to propose the teaching of bioclimatology to future managers and teachers in order to obtain a balanced environmental development. The analysis of bioclimatic diagrams makes it possible to stipulate the duration of the water reserve in the soil. This is essential for agricultural and forestry management. The edaphic factor and the bioclimatic ombrotclimatic (Io) and thermoclimatic (It/Itc) indexes condition the types of forests and crops that can exist in a territory, with the particularity that the ombrotype is conditioned by the edaphic factor, which allows a decrease in the ombrothermal index, expressed by the ombroedaphoboxerophilic index (Ioex). The humid ombrotypes condition the presence of Abies pinsapo, Quercus pyrenaica, Q. broteroi, and Q. suber, and the dry ones Q. rotundifolia and Olea sylvestris.
Optimized Design of Quinary High-Entropy Transition Metal Carbide Ceramics Based on First Principles
Authors: Han Xiuli , Li Wanying , Zhang Qiang , Wang Rui , Wang Yujin , Chen Lei , Wu Gaohui
Published: October 2024

In this paper, we developed models for 21 quinary high-entropy transition metal carbide ceramics (HETMCCs), composed of carbon and the transition metals Ti, Zr, Mo, V, Nb, W, and Ta, employing the Special Quasirandom Structures (SQS) method. We investigated how the transition metal elements influence lattice distortion, mixing enthalpy, Gibbs free energy of mixing, and the electronic structure of the systems through first-principles calculations. The calculations show that 21 systems can form a stable single phase, among which (TiMoVNbTa)C5, (ZrMoNbWTa)C5, and (MoVNbWTa)C5 exhibit superior stability. The formation energy and migration energy of carbon vacancies in systems with strong single-phase stability were calculated to predict their radiation resistance. The formation energy of carbon vacancies is closely related to the types of surrounding transition metal elements, with values ranging between the maximum and minimum formation energies observed in binary transition metal carbides (TMCs). The range of migration energy for carbon vacancies is wider than that observed in TMCs, which can hinder their long-range migration and enhance the radiation resistance of the materials.
Antibacterial Pure Magnesium and Magnesium Alloys for Biomedical Materials—A Review
Authors: Song Qingfeng , Yang Lingzhi , Yi Fang , Chen Chao , Guo Jing , Qi Zihua , Song Yihan
Published: October 2024

Implant-related infections are one of the major challenges faced by orthopedic surgeries. Developing implants with inherent antibacterial properties is an effective strategy to address this issue. Biodegradable magnesium and magnesium alloys have become a research hotspot due to their good bioactivity, mechanical properties, biocompatibility, and excellent antibacterial ability. However, magnesium and its alloys have rapid corrosion, and the difficulty in expelling harmful magnesium ions and hydrogen gas produced by degradation from the body. This review summarizes the mainstream surface modification techniques such as laser surface modification, friction stir processing, and micro-arc oxidation, along with their impact on the antimicrobial properties of magnesium-based materials. This paper reviews the latest research progress on improving the antibacterial properties of magnesium alloys through alloying and introduces the antibacterial effects of mainstream magnesium alloys and also elaborates on the antibacterial mechanism of magnesium alloy materials. It is expected to provide more basis and insights for the design of biodegradable magnesium alloys with antibacterial properties, thereby promoting their development and clinical application.
An Analytical Study for Explosive Grain Initiation
Authors: Gao Feng , Fan Zhongyun
Published: October 2024

The most common form of solidification of metals is heterogeneous nucleation, in which the particles, regardless of whether they are endogenous or exogenous, nucleate the primary crystal phase, becoming solid crystal particles and, subsequently, initiating into grains during solidification. Explosive grain initiation has been proposed recently for these particles, which have significant nucleation undercooling, in which once nucleation happens, a certain number of solid particles can initiate into grains simultaneously, resulting in recalescence. This is a different form of grain initiation and has high potential for more significant grain refinement in casting alloys. In this work, an analytical model is designed to describe explosive grain initiation, based on which the criteria for the three different grain initiation forms, explosive grain initiation (EGI), hybrid grain initiation (HGI), and progressive grain initiation (PGI), are derived. These criteria are employed to develop a grain initiation map for the Mg-Al alloy system inoculated with nucleant particles having a log-normal size distribution. This work can not only help us to understand the effect of each condition, such as the cooling rate and the solute concentration, on grain initiation behaviors, but also predict the grain size for alloy systems with relatively impotent nucleant particles during solidification.
Optimizing Contact-Less Magnetoelastic Sensor Design for Detecting Substances Accumulating in Constrained Environments
Authors: Kalyvas Ioannis , Dimogianopoulos Dimitrios
Published: October 2024

The optimization of a contact-less magnetoelastic sensing setup designed to detect substances/agents accumulating in its environment is presented. The setup is intended as a custom-built, low-cost yet effective magnetoelastic sensor for pest/bug detection in constrained places (small museums, labs, etc.). It involves a short, thin, and flexible polymer slab in a cantilever arrangement, with a short Metglas® 2826 MB magnetoelastic ribbon attached on part of its surface. A mobile phone both supports and supplies low-amplitude vibration to the slab’s free end. When vibrating, the magnetoelastic ribbon generates variable magnetic flux, thus inducing voltage in a contact-less manner into a pick-up coil suspended above the ribbon. This voltage carries specific characteristic frequencies of the slab’s vibration. If substances/agents accumulate on parts of the (suitably coated) slab surface, its mass distribution and, hence, characteristic frequencies change. Then, simply monitoring shifts of such frequencies in the recorded voltage enables the detection of accumulating substances/agents. The current work uses extensive testing via various vibration profiles and load positions on the slab, for statistically evaluating the sensitivity of the mass detection of the setup. It is shown that, although this custom-built substance/agent detector involves limited (low-cost) hardware and a simplified design, it achieves promising results with respect to its cost.
Assessment of Microcirculatory Dysfunction by Measuring Subcutaneous Tissue Oxygen Saturation Using Near-Infrared Spectroscopy in Patients with Circulatory Failure
Authors: Sato Jun , Sakurai Atsushi , Ihara Shingo , Nakagawa Katsuhiro , Chiba Nobutaka , Saito Takeshi , Kinoshita Kosaku
Published: October 2024

Background: Patients with circulatory failure have high mortality rates and require prompt assessment of microcirculation. Despite the improvement in hemodynamic parameters, microcirculatory dysfunction persists. We measured subcutaneous regional tissue oxygen saturation (rSO2) with near-infrared spectroscopy (NIRS), which can assess microcirculation in patients with circulatory failure. Methods: A finger-worn oximeter with NIRS measured rSO2 in the forehead, thenar eminence, thumb, and knees. First, the rSO2 was measured in healthy adult volunteers (n = 10). Circulatory failure was defined as a systolic blood pressure ≤ 90 mmHg and lactate ≥ 2 mmol/L. The study included 35 patients without circulatory failure and SOFA score of 0 at ICU admission and 38 patients with circulatory failure at ICU admission. Both groups included a single-center prospective study of patients who were transported to the ICU of the Nihon University Hospital. The rSO2 was measured only on ICU admission in the non-circulatory failure group and later in the circulatory failure group. Results: In the volunteer group, rSO2 at each site was approximately 58%. The rSO2 was significantly lower in the circulatory failure group than in the non-circulatory failure group (knee, p < 0.01). In the circulatory failure group, knee rSO2 showed a significant negative correlation with SOFA score (Day 0, ρ = −0.37, p = 0.02; Day 1, ρ = −0.53, p < 0.01; Day 2, ρ = −0.60, p < 0.01). Conclusions: Subcutaneous knee rSO2 was associated with SOFA score and was considered an indicator of microcirculatory dysfunction and organ damage.
Diagnostic Performance of Faecal Immunochemical Testing (FIT) in Patients with Lynch Syndrome Scheduled for Colonoscopic Surveillance
Authors: Gerrard Adam D. , Maeda Yasuko , Strachan Judith , Speake Doug , Dunlop Malcolm G. , Din Farhat V. N.
Published: October 2024

Background and Aims: Lynch syndrome (LS) carries a substantial lifetime risk of colorectal cancer which is currently mitigated by biennial colonoscopy surveillance. Paramount to the surveillance programme is the removal of adenomas before malignant transformation but there is an associated service burden and morbidity of repeated endoscopy. We investigated if faecal immunochemical testing (FIT) for faecal haemoglobin has the diagnostic performance to replace colonoscopy. Methods: In this retrospective cohort study, patients due to undergo planned surveillance for LS between November 2020 and April 2022 were sent two FIT kits prior to colonoscopy. Test diagnostic performance of colorectal cancer (CRC), advanced and non-advanced adenoma detection was calculated for single and double FIT strategies. A faecal-Hb of 10 µg Hb/g was considered positive. Results: In total, 78 patients, with 45 (57.7%) female, median age 52 years (IQR 41–63), completed at least one FIT and colonoscopy. The median time from FIT to colonoscopy was 47 days. A single FIT was positive in 7/30 cases of adenoma (2/3 advanced, 5/27 non-advanced). A total of 64 (82.1% of FIT1T returners) completed a second FIT. Using the greatest of the two FITs (FIT2TMAX) 8/26 (2/3 advanced, 4/23 non-advanced), patients with adenomas were identified. There were no cases of CRC. The sensitivity for adenoma detection was 23.3% and 23.1%, respectively. Conclusions: In patients with LS awaiting colonoscopy, FIT has a low sensitivity for detecting adenomas and advanced adenomas. This is not improved by the addition of a second FIT test.
Preparticipation Cardiovascular Screening of Athletes: Current Controversies and Challenges for the Future
Authors: Dores Hélder , Dinis Paulo , Viegas José Miguel , Freitas António
Published: October 2024

Sports cardiology is an evolving field in cardiology, with several topics remaining controversial. Beyond the several well-known benefits of regular exercise practice, the occurrence of adverse clinical events during sports in apparently healthy individuals, especially sudden cardiac death, and the described long-term adverse cardiac adaptations associated to high volume of exercise, remain challenging. The early identification of athletes with increased risk is critical, but the most appropriate preparticipation screening protocols are also debatable and a more personalized evaluation, considering individual and sports-related characteristics, will potentially optimize this evaluation. As the risk of major clinical events during sports is not zero, independently of previous evaluation, ensuring the capacity for cardiopulmonary resuscitation, especially with availability of automated external defibrillators, in sports arenas, is crucial for its prevention and to improve outcomes. As in other areas of medicine, application of new digital technologies, including artificial intelligence, is promising and could improve in near future several aspects of sports cardiology. This paper aims to review the methodology of athletes’ preparticipation screening, emphasizing current controversies and future challenges, in order to improve early diagnosis of conditions associated with sudden cardiac death.
Description Generation Using Variational Auto-Encoders for Precursor microRNA
Authors: Petković Marko , Menkovski Vlado
Published: October 2024

Micro RNAs (miRNA) are a type of non-coding RNA involved in gene regulation and can be associated with diseases such as cancer, cardiovascular, and neurological diseases. As such, identifying the entire genome of miRNA can be of great relevance. Since experimental methods for novel precursor miRNA (pre-miRNA) detection are complex and expensive, computational detection using Machine Learning (ML) could be useful. Existing ML methods are often complex black boxes that do not create an interpretable structural description of pre-miRNA. In this paper, we propose a novel framework that makes use of generative modeling through Variational Auto-Encoders to uncover the generative factors of pre-miRNA. After training the VAE, the pre-miRNA description is developed using a decision tree on the lower dimensional latent space. Applying the framework to miRNA classification, we obtain a high reconstruction and classification performance while also developing an accurate miRNA description.
TSRDet: A Table Structure Recognition Method Based on Row-Column Detection
Authors: Zhu Zixuan , Li Weibin , Yu Chenglong , Li Wei , Jiao Licheng
Published: October 2024

As one of the most commonly used and important data carriers, tables have the advantages of high structuring, strong readability and strong flexibility. However, in reality, tables usually present various forms, such as Excel, images, etc. Among them, the information in the table image cannot be read directly, let alone further applied. Therefore, the research related to image-based table recognition is crucial. It contains the table structure recognition and the table content recognition. Among them, table structure recognition is the most important and difficult task because the table structure is abstract and changeable. In order to address this problem, we propose an innovative table structure recognition method, named TSRDet (Table Structure Recognition based on object Detection). It includes a row-column detection method, named SACNet (StripAttention-CenterNet) and the corresponding post-processing. SACNet is an improved version of the original CenterNet. The specific improvements include the following: firstly, we introduce the Swin Transformer as the encoder to obtain the global feature map of the image. Then, we propose a plug-and-play row-column attention module, including a channel attention module and a row-column spatial attention module. It improves the detection accuracy of rows and columns by capturing long-range row-column feature maps in the image. After completing the row-column detection, this paper also designs a simple and fast post-processing to generate the table structure based on the row-column detection results. Experimental results show that for row-column detection, SACNet has high detection accuracy, even at a high IoU threshold. Specifically, when the threshold is 0.75, its mAP of row detection and column detection still exceeds 90%, which is 91.40% and 92.73% respectively. In addition, in the comparative experiment with the existing object detection methods, SACNet’s performance was significantly better than that of all others. For table structure recognition, the TEDS-Struct score of TSRDet is 95.7%, which shows competitive performance in table structure recognition, and verifies the rationality and superiority of the proposed method.
Attribute-Aware Graph Convolutional Network Recommendation Method
Authors: Wei Ning , Li Yunfei , Dong Jiashuo , Chen Xiao , Guo Jingfeng
Published: October 2024

In recent years, recommendation systems have made significant strides through the application of graph neural networks (GNNs). However, most of the existing methods primarily focus on modeling user–item interactions, often failing to account for the distinct roles of different types of neighboring nodes during the graph convolution process. Moreover, the intricate relationships between user and item attributes are frequently underexplored, which constrains further improvement in the performance of recommendation models. To overcome these challenges, this paper proposes an attribute-aware graph convolutional network recommendation model (AAGCNR). This model accounts for the complex interrelationships between user and item attributes while distinguishing between different types of neighboring nodes during graph convolution. First, a multi-head self-attention mechanism is applied to capture the semantic relationships among attributes across various semantic spaces. Additionally, a bilinear interaction module is employed to facilitate interactions between attributes. Since different neighboring nodes exert different influences on target nodes, the model performs convolutional aggregation by leveraging the interrelationships of these attributes throughout the graph convolution process. Experiments conducted on real-world datasets reveal that AAGCNR outperforms other benchmark algorithms, particularly in terms of RECALL and NDCG metrics.
Spiking Neural Networks for Real-Time Pedestrian Street-Crossing Detection Using Dynamic Vision Sensors in Simulated Adverse Weather Conditions
Authors: Sakhai Mustafa , Mazurek Szymon , Caputa Jakub , Argasiński Jan K. , Wielgosz Maciej
Published: October 2024

This study explores the integration of Spiking Neural Networks (SNNs) with Dynamic Vision Sensors (DVSs) to enhance pedestrian street-crossing detection in adverse weather conditions—a critical challenge for autonomous vehicle systems. Utilizing the high temporal resolution and low latency of DVSs, which excel in dynamic, low-light, and high-contrast environments, this research evaluates the effectiveness of SNNs compared to traditional Convolutional Neural Networks (CNNs). The experimental setup involved a custom dataset from the CARLA simulator, designed to mimic real-world variability, including rain, fog, and varying lighting conditions. Additionally, the JAAD dataset was adopted to allow for evaluations using real-world data. The SNN models were optimized using Temporally Effective Batch Normalization (TEBN) and benchmarked against well-established deep learning models, concerning their accuracy, computational efficiency, and energy efficiency in complex weather conditions. This study also conducted a comprehensive analysis of energy consumption, highlighting the significant reduction in energy usage achieved by SNNs when processing DVS data. The results indicate that SNNs, when integrated with DVSs, not only reduce computational overhead but also dramatically lower energy consumption, making them a highly efficient choice for real-time applications in autonomous vehicles (AVs).
A Provably Secure and Lightweight Two-Factor Authentication Protocol for Wireless Sensor Network
Authors: Feng Hao , Cai Bowen
Published: October 2024

Wireless Sensor Networks (WSNs) are rapidly being integrated into various fields, significantly impacting and facilitating many aspects of human life. However, the increasingly prominent security issues associated with WSNs have become a significant challenge. This paper provides an in-depth analysis of the security challenges faced by WSNs in resource constrained and open communication environments. As a key component of the Internet of Things (IoT), a WSN can perceive, collect and transmit physical environmental data in real-time, and is widely used in military, medical, agricultural and other fields. However, the insecurity of communication channels and unauthorized user access pose severe threats to network security and data integrity. To address these challenges, this paper proposes a provably secure two-factor authentication protocol. This protocol utilizes a Chebyshev chaotic map and a two-factor authentication mechanism, which not only enhances security in WSNs but also improves authentication efficiency. The protocol is validated through security proof and performance experiments, demonstrating excellent security, functionality and efficiency. This provides strong support for secure and efficient communication in WSNs across various application scenarios.
Model Reduction Method for Spacecraft Electrical System Based on Singular Perturbation Theory
Authors: Wang Lifeng , Peng Yelun , Luo Juan
Published: October 2024

Accurate and efficient modeling and simulation of spacecraft electrical systems are crucial because of their complexity. However, existing models often struggle to balance simulation efficiency and accuracy. This paper introduces a model reduction method based on singular perturbation theory to simplify the full-order model of spacecraft electrical systems. The experimental results show that the reduced-order simplified model saves 50% of the simulation time with almost no degradation in the simulation accuracy and can be applied to real-world scenarios, such as digital twins. This method offers a new approach for rapid simulation of spacecraft electrical systems and has broad application prospects.
Effect of Architecture and Inference Parameters of Artificial Neural Network Models in the Detection Task on Energy Demand
Authors: Tomiło Paweł , Oleszczuk Piotr , Laskowska Agnieszka , Wilczewska Weronika , Gnapowski Ernest
Published: October 2024

Artificial neural network models for the task of detection are used in many fields and find various applications. Models of this kind require adequate computational resources and thus require adequate energy expenditure. The increase in the number of parameters, the complexity of architectures, and the need to process large data sets significantly increase energy consumption, which is becoming a key sustainability challenge. Optimization of computing and the development of energy-efficient hardware technologies are essential to reduce the energy footprint of these models. This article examines the effect of the type of model, as well as its parameters, on energy consumption during inference. For this purpose, sensors built into the graphics card were used, and software was developed to measure the energy demand of the graphics card for different architectures of YOLO models (v8, v9, v10), as well as for different batch and model sizes. This study showed that the increase in energy demand is not linearly dependent on batch size. After a certain level of batch size, the energy demand begins to decrease. This dependence does not occur only for n/t size models. Optimum utilization of computing power due to the number of processed images for the studied models occurs at the maximum studied batch size. In addition, tests were conducted on an embedded device.
Development of a Hybrid AI Model for Fault Prediction in Rod Pumping System for Petroleum Well Production
Authors: Zhang Aoxue , Zhao Yanlong , Li Xuanxuan , Fan Xu , Ren Xiaoqing , Li Qingxia , Yue Leishu
Published: October 2024

Rod pumping systems are widely used in oil wells. Accurate fault prediction could reduce equipment fault rate and has practical significance in improving oilfield production efficiency. This paper analyzed the production journal of rod pumping wells in block X of Xinjiang Oilfield. According to the production journal, oil well maintenance operations are primarily caused by five types of faults: scale, wax, corrosion, fatigue, and wear. These faults make up approximately 90% of all faults. 1354 oil wells in the block that experienced workover operations as a result of the aforementioned factors were chosen as the research objects for this paper. To lower the percentage of data noise, wavelet threshold denoising and variational mode decomposition were used. Based on the bidirectional long short-term memory network, an intelligent model for fault prediction was built. It was trained and verified with the help of the sparrow search algorithm. Its efficacy was demonstrated by testing various deep learning models in the same setting and with identical parameters. The results show that the prediction accuracy of the model is the highest compared with other 11 models, reaching 98.61%. It is suggested that the model using artificial intelligence can provide an accurate fault warning for the oilfield and offer guidance for the maintenance of the rod pumping system, which is meant to reduce the occurrence of production stagnation and resource waste.
Combustion and Energy Parameters of Grape Pomace/Skin Waste in Wine Production—Regent Variety Grafted onto Rootstocks
Authors: Maj Grzegorz , Klimek Kamila E. , Kapłan Magdalena , Buczyński Kamil , Borkowska Anna
Published: October 2024

The study presents the potential use of winemaking residues, specifically grape pomace, for energy purposes. The pomace was obtained from the cultivation of the Regent grape variety on three different rootstocks—125AA, 161-49, and SO4—as well as a control group grown on its own roots. The research included determining the calorific value and combustion heat, conducting a technical and elemental analysis of the potential biofuel, as well as estimating emission indicators (CO, CO2, NOx, SO2, and particulate matter) and the theoretical volume of flue gases based on stoichiometric equations. The study revealed significant differences among the combustion heat, tested properties and calorific value, ash content, and the total volume of flue gases. The highest calorific value (17.7 MJ kg−1) and combustion heat (18.9 MJ kg−1) were obtained for pomace from the SO4SO4 rootstock, while the lowest values were observed in the control group (17.0 MJ·kg−1 and 15.8 MJ·kg−1, respectively). The highest ash content was also recorded for the SO4 rootstock (9.2%), with the lowest in the control group (6.7%). The control group exhibited the lowest CO2 emissions at 1390.50 kg·Mg−1, while the highest emissions were found in the pomace from the SO4 rootstock (1478.8 kg·Mg−1). Regarding the total flue gas volume, the highest volume was estimated for the pomace from the 125AA rootstock (7.8 m3·kg−1) and the lowest for the control group (7.3 m3·kg−1). The research demonstrated that grape pomace possesses favorable energy properties and could serve as a potential biofuel, contributing to the fuel and energy balance of agricultural production enterprises. The analyzed biomass exhibits properties similar to agrobiomass.
Demand Response Potential of an Educational Building Heated by a Hybrid Ground Source Heat Pump System
Authors: Xue Tianchen , Jokisalo Juha , Kosonen Risto
Published: October 2024

Demand response (DR) enhances building energy flexibility, but its application in hybrid heating systems with dynamic pricings remains underexplored. This study applied DR via heating setpoint adjustments based on dynamic electricity and district heating (DH) prices to a building heated by a hybrid ground source heat pump (GSHP) system coupled to a DH network. A cost-effective control was implemented to optimize the usage of GSHP and DH with power limitations. Additionally, four DR control algorithms, including two single-price algorithms based on electricity and DH prices and two dual-price algorithms using minimum heating price and price signal summation methods, were tested for space heating under different marginal values. The impact of DR on ventilation heating was also evaluated. The results showed that applying the proposed DR algorithms to space heating improved electricity and DH flexibilities without compromising indoor comfort. A higher marginal value reduced the energy flexibility but increased cost savings. The dual price DR control algorithm using the price signal summation method achieved the highest cost savings. When combined with a cost-effective control strategy and power limitations, it reduced annual energy costs by up to 10.8%. However, applying the same DR to both space and ventilation heating reduced cost savings and significantly increased discomfort time.
Heterogeneous Responses of Energy and Non-Energy Assets to Crises in Commodity Markets
Authors: Vortelinos Dimitrios , Menegaki Angeliki , Passas Ioannis , Garefalakis Alexandros , Viskadouros Georgios
Published: October 2024

In this study, we investigate the heterogeneity in energy and non-energy commodities by analyzing their four realized moments: returns, realized volatility, realized skewness and realized kurtosis. Utilizing monthly data, we examine two commodity categories over various crisis periods. This study examines a comparative approach to descriptive statistics across different crisis periods and the full sample and assesses the out-of-sample significance of heteroscedasticity using GARCH models. The findings reveal significant heterogeneity in both energy and non-energy commodities, with energy commodities exhibiting higher average returns and volatility. Crisis periods markedly influence the statistical properties of these commodities. GARCH models outperform ARMA models in forecasting realized moments, particularly for non-energy commodities. This research contributes to the literature by providing robust evidence of heterogeneity in commodity markets and highlights the importance of considering all four realized moments in such analyses.
Fault Diagnosis in Electrical Machines for Traction Applications: Current Trends and Challenges
Authors: Pastura Marco , Zigliotto Mauro
Published: October 2024

The widespread diffusion of electric vehicles poses new challenges in the field of fault diagnostics. Past studies have been focused mainly on machines designed for industrial applications, where the operating conditions and requirements are significantly different. This work presents a review of the most recent studies about fault diagnosis techniques in electrical machines feasible for traction applications, with a focus on the most adopted approaches of the last years and on the latest trends. Considerations about their applicability for electric vehicle purposes, along with some areas that require further research, are also provided.
Advances in Room Temperature of Indium Aluminum Nitride InAlN Deposition via Direct Current (DC) Co-Sputtering for Solar Energy Applications
Authors: Cañón-Bermúdez Juan David , Mulcué-Nieto Luis Fernando
Published: October 2024

This study presents an innovative method for the synthesis of indium aluminum nitride (InAlN) layers by direct current (DC) co-sputtering at room temperature, with the aim of reducing production costs of optoelectronic devices. Indium and aluminum targets are used, varying the power applied to the aluminum target. The results show that increasing the target power favors the formation of aluminum nitride (AlN), which modifies the chemical composition of the material. The layers obtained present smooth surfaces with a roughness of less than 3 nm, which is beneficial for applications requiring interfaces with low defect density. Regarding the optical properties, it is observed that the optical bandgap varies between 1.8 eV and 2.0 eV, increasing with the target power. Hall effect measurements indicate a decrease in the free carrier concentration and an increase in the resistivity with increasing power. This approach allows for the synthesis of InAlN with properties suitable for optoelectronic applications, solar cells, photocatalysis, and photoelectrocatalysis at low cost.
Development and Verification of a Multi-Physics Transport Code of Molten Salt Reactor Fission Products
Authors: Chen Liang , He Liaoyuan , Xia Shaopeng , Peng Minyu , Zhu Guifeng , Yan Rui , Zou Yang , Xu Hongjie
Published: October 2024

The transport of fission products in molten salt reactors has attracted much attention. However, few codes can completely describe the transport characteristic, though the migration of fission products in the molten salt reactor is essential to estimate the source term, decay heat, and radiation shielding. This study built a program named ThorFPMC (Thorium Fission Products Migration Code) that can handle the multi-physics transport characteristic based on the flow burnup code ThorMODEc (Thorium MOlten Salt Reactor Specific DEpletion Code). A problem-related depletion chain compression method was applied to decrease the order of the solve matrix. The matrix exponential and splitting methods were applied to solve the steady state and transient calculation, respectively. Error analysis showed that for a specific problem, the simplified depletion chain matrix index method could solve the fission products migration equation with an arbitrary time-step with high speed (s) and high precision (10−4); the splitting method could reach a precision of 10−2 level for the full fuel depletion chain, multi-nodes, and transient problems. Compared to the Strang splitting method, the perturbation splitting method has higher precision and less time consumption. In summary, the developed programmer could describe the migration effect of fission products in molten salt reactors, which provides a significant tool for the design of molten salt reactors.
Optimization of Stator Structure for Improved Accuracy in Variable Reluctance Resolvers Using Advanced Machine Learning Techniques
Authors: Li Wentao , Liu Qiankun , Ye Siyang , Huang Surong
Published: October 2024

This study presents an optimized design for a Segmented Sinusoidal Parameter Winding with Magnetic Wedge Variable Reluctance Resolver (SSPWMW-VRR), addressing challenges like winding asymmetry and harmonic distortion in conventional designs. By integrating particle swarm optimization (PSO) for winding design, magnetic equivalent circuit (MEC) analysis for leakage flux, and machine learning techniques (XGBoost and Multi-Layer Perceptron), the stator slot shape was fine-tuned for improved accuracy. XGBoost outperformed MLP in prediction accuracy with a mean absolute error (MAE) of 0.1172. Finite element analysis (FEA) simulations and experimental validation demonstrated a reduction in position errors from ±30′ in conventional VRRs to ±5′ in the optimized design, along with significant harmonic reduction.
One-Pot Fast Electrochemical Synthesis of Ternary Ni-Cu-Fe Particles for Improved Urea Oxidation
Authors: Wala-Kapica Marta , Gąsior Aleksander , Maciej Artur , Smykała Szymon , Kazek-Kęsik Alicja , Baghayeri Mehdi , Simka Wojciech
Published: October 2024

The climate crisis has become the most serious concern of human beings and environments worldwide in the 21st century. Global concerns about cancer epidemiology mainly originate from anthropogenic activities, particularly fossil-based operations. A key solution to this problem is the use of fuel cells—devices—capable of the direct conversion of fuel chemical energies like urea into electricity. To make their commercialization reasonable, one of the problems that needs to be solved is the development of anodic materials. The majority of investigations on urea oxidation are based on nickel, but its inadequate activity limits the efficiency of these devices. In this work, we propose and synthesize a Ni-Cu-Fe ternary electrocatalyst for urea oxidation through a fast and facile electrodeposition method. The properties of the synthesized material are examined by Scanning Electron Microscopy (SEM) conjugated with Energy Dispersive X-ray Spectroscopy (EDS), Transmission Electron Microscopy (TEM), and X-ray Diffraction (XRD). Its electrochemical properties were also examined in a 1 M KOH solution with and without 0.15 M urea. We found that the prepared powder is active in the electro-oxidation of urea, with 1.65 Vvs RHE required for a current density of 10 mA cm−2 and a stable potential of 2.38 Vvs RHE required for 3 h of polarization at 10 mA cm−2.
Experimental Study of Bifacial Photovoltaic Module Performance on a Sunny Day with Varying Backgrounds Using Exergy and Energy Analysis
Authors: Almarshoud A. F. , Abdel-halim M. A. , Almasri Radwan A. , Alshwairekh Ahmed M.
Published: October 2024

In this research, ethe performance of bifacial photovoltaic (PV) modules under varying background conditions is explored, specifically green grass, brown clay, and white gravel, on a sunny day. By leveraging both exergy and energy analysis, this research aims to provide a comprehensive evaluation of bifacial module efficiency compared to traditional monofacial modules. The experimental setup simulates diverse installation environments, including rooftops and ground-mounted systems, by varying background reflectance. Key performance metrics such as energy yield, exergy yield, and overall efficiency were measured. The findings reveal that bifacial modules installed over white gravel backgrounds achieve the highest exergy profile and efficiency during peak solar radiation periods, attributed to the enhanced reflectivity of white gravel. These insights can inform strategic decisions regarding the selection and placement of bifacial modules to optimize energy and exergy outputs in real-world scenarios. This study contributes valuable knowledge to the advancement of renewable energy technologies, offering guidance for researchers, developers, and policymakers focused on sustainable energy solutions.
Microscopic Remaining Oil Classification Method and Utilization Based on Kinetic Mechanism
Authors: He Yuhang , Zheng Xianbao , Wu Jiayi , Wang Zhiqiang , Wu Jiawen , Wang Qingyu , Gong Wenbo , Gai Xuecong
Published: October 2024

In reality, the remaining oil in the ultra-high water cut period is highly dispersed, so a thorough investigation is required to understand the microscopic remaining oil. This will directly influence the technological direction and allow for countermeasures such as enhanced oil recovery (EOR). Therefore, this study aims to investigate the state, classification method and utilization mechanism of the microscopic remaining oil in the late period of the ultra-high water cut. To achieve this, the classification of microscopic remaining oil based on mechanical mechanism was developed using displacement CT scan and micro-scale flow simulation methods. Three carefully selected mechanical characterization parameters were used: oil–water connectivity, oil–mass specific surface and oil–water area ratio. These give five types of microscopic remaining oil, which are as follows: A (capillary and viscous oil cluster type), B (capillary and viscous oil drop type), C (viscous oil film type), D (capillary force control throat type), and E (viscous control blind end type). The state of the microscopic remaining oil in classified oil reservoirs was defined after high-expansion water erosion. Based on micro-flow simulation and analysis of different forces during the displacement process, the main microscopic remaining oil recognized is in class-I, class-II and class-III reservoirs. Within the Eastern sandstone oilfields in China, the ultra-high water-cut stage is a good indicator that the class-I oil layer is dominated by capillary and viscous oil drop types distributed in large connected holes. The class-II oil layer has capillary and viscous force-controlled clusters distributed in small and medium pores with high connectivity. In the case of the class-III oil layer, it enjoys the support of capillary force control throats that are mainly distributed in small holes with high connectivity. Integrating mechanisms of different types of micro-remaining oil indicates that, enhancing utilization conditions requires increasing pressure gradient and shear force while reducing capillary resistance. An effective way to improve the remaining oil utilization is to increase the pressure gradient and change the flow direction during the water-drive development process. Hence, this forms a theoretical basis and a guide for the potential exploitation of remaining oil. Likewise, it provides a strategy for optimizing enhanced oil recovery in the ultra-high water-cut stage of mid-high permeability oil reservoirs worldwide.
Joint Influence of Forest Strata Attributes and Abiotic Factors on Herbaceous Plant Abundance in South Korean Forest Restoration Sites: Native Versus Alien Species
Authors: Woo Jun-Hyuk , Lee Min-Ki , Lee Hae-In , Lee Chang-Bae
Published: October 2024

The success of ecosystem restoration is often evaluated by the stable establishment and growth of native plants while preventing the spread of alien plants. However, research on the factors and mechanisms controlling the abundance (richness and coverage) of native and alien plants remains limited. To address this, we analyzed data from 167 plots (100 m2) in forest restoration sites in South Korea. We assessed the effects of abiotic factors (topography, climate, and soil), biotic factors, and the number of years integrally since restoration on both plant groups by using a piecewise structural equation model. Native plant abundance was influenced by shrub density (species richness: β = 0.19; coverage: β = 0.20) and available phosphorus (β = 0.19), while alien plant abundance was controlled by soil pH (species richness: β = 0.45), elevation (β = −0.15), species richness, and tree (β = −0.15) and shrub species richness (β = −0.16). The number of years since restoration has indirectly affected native and alien plants through shrub species richness and shrub coverage. Our results indicate that high resource availability, such as light, in the early stages of restoration may allow native and alien herbaceous plants to coexist. However, as vegetation and forest strata develop, reduced light availability can lead to a decline in alien species and the dominance of native plants. We also provide management strategies to suppress alien plants by promoting structural complexity within forest stands.