bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of sociodemographic and health aspects on cognitive performance in the older adult population in the republic of Serbia
Authors: Mirkovic Andrea , Radevic Svetlana , Radovanovic Snezana , Simic Vukomanovic Ivana , Janicijevic Katarina , Ilic Sanja , Djordjevic Ognjen , Djordjevic Gordana , Radovanovic Jovana , Selakovic Viktor , Savic Nikola , Gogic Andjela
Published: July 2024

The aim of this study was to investigate how sociodemographic and health factors contribute cognitive abilities in the older population of the Republic of Serbia, using data from the 2019 national health survey. The study included 3,743 participants, of whom 2,061 (55.1%) were women and 1,682 (44.9%) were men. The median age of all participants was 72 (10) years. Study used logistic regression on cross-sectional data to analyze how education, social support, and healthcare access affect cognitive abilities, while adjusting for demographic variables. The results revealed negative associations between higher levels of education and lower odds of experiencing memory and concentration problems, while recent visits to specialists were positively associated with increased risk for the same. The highest percentage of participants (22.6%) reporting major difficulties in memory and concentration were in the age group of 85–89 years (p < 0.001). A statistically significant relationship was found between social support and issues related to memory and concentration (p < 0.001). Social support emerged as a significant factor in preserving cognitive abilities. The discussion underscores the need for a comprehensive approach in promoting cognitive health, taking into account education, social integration, and access to healthcare as key factors. The study acknowledges its limitations, including its cross-sectional nature and potential subjective biases in self-assessment of cognitive abilities. Future research should incorporate longitudinal studies and more objective measures of cognitive abilities.
Robotont 3–an accessible 3D-printable ROS-supported open-source mobile robot for education and research
Authors: Mõtshärg Eva , Vunder Veiko , Raudmäe Renno , Muro Marko , Drikkit Ingvar , Tšigrinski Leonid , Köidam Raimo , Aabloo Alvo , Kruusamäe Karl
Published: July 2024

Educational robots offer a platform for training aspiring engineers and building trust in technology that is envisioned to shape how we work and live. In education, accessibility and modularity are significant in the choice of such a technological platform. In order to foster continuous development of the robots as well as to improve student engagement in the design and fabrication process, safe production methods with low accessibility barriers should be chosen. In this paper, we present Robotont 3, an open-source mobile robot that leverages Fused Deposition Modeling (FDM) 3D-printing for manufacturing the chassis and a single dedicated system board that can be ordered from online printed circuit board (PCB) assembly services. To promote accessibility, the project follows open hardware practices, such as design transparency, permissive licensing, accessibility in manufacturing methods, and comprehensive documentation. Semantic Versioning was incorporated to improve maintainability in development. Compared to the earlier versions, Robotont 3 maintains all the technical capabilities, while featuring an improved hardware setup to enhance the ease of fabrication and assembly, and modularity. The improvements increase the accessibility, scalability and flexibility of the platform in an educational setting.
Implementing concepts from green logistics in the turkey production supply chain
Authors: Wilson Griffin , Horsey Bazyl , Stone Richard
Published: July 2024

Introduction

The global turkey market represents a sector of increasing growth in the previous decade, and projections for the next decade reflect the probable continuation of this growth. Industry trends also indicate the globalization of turkey meat production, as the loci of production has continually shifted from one dominated by the United States to one with an increasing number of production units globally. In contrast with other popular meat products, comparatively fewer resources have been devoted to academic research concerning the growth, production, distribution, and sale of turkey and turkey products. This lack of research is particularly notable in the area of supply chain management and environmental sustainability. Given the increasing volume of turkey production and lower volume of academic interest, it stands to reason that there remain many opportunities for improvement across the value chain in this industry.

Methods

In this paper, we take a “green logistics” approach and use data provided by one of the largest turkey producers in the United States to formulate a mixed-integer program aimed at minimizing the environmental impact of turkey products in a segment of the product supply chain.

Results

Implementation of the resulting brooder-finisher farm assignments developed by the model would yield an average 50% decrease (184 metric ton) in greenhouse gas emissions at the operation under investigation while also addressing other areas of significant vulnerability for the industry (production costs, biosecurity risk, and animal wellbeing).

Discussion

As consolidated turkey meat production systems continue to expand globally, we argue that a similar approach could readily be deployed by these growing and emerging production systems.
Dealing With Wild Neighbors
Authors: Edelblutte Émilie , Anderson Robert , Casellas Connors John , Short Gianotti Anne
Published: July 2024

Even though neighborhoods are built for people, lots of wild animals also call these places home. You might have seen a squirrel, a fox, or a deer munching on your garden or running down your street. Living near people gives some animals food and places to live, but it can also cause problems for both animals and people. Sometimes people do not agree about what to do about the animals that live near them. We were curious about how people and wild animals live together and decided to investigate. We studied how people make decisions about deer in the suburbs of Massachusetts, where some people think there are too many deer and others are not so sure. We discovered that people often disagree, and politics matters. Paying attention to this disagreement can help people work together and make choices that let wild animals and people to live together with fewer problems.
Simulation of the impact of changes in the volume of production and export of products on the food security of the country: on the example of Ukraine
Authors: Shpak Nestor , Matviyishyn Yevhen , Dziurakh Yurii , Gvozd Maryana
Published: July 2024

Changes in the production of agricultural products in Ukraine are analyzed. Forecasting of the volume of exports of agricultural products from Ukraine until 2027 was carried out. The following factors were taken into account: projected changes in real GDP in those countries that are the main importers of these products; reduction of cultivated agricultural land caused by military actions; forecasted changes in the population of Ukraine during the forecast period. It was concluded that there are no threats to Ukraine's food security caused by changes in the production and export of agricultural products. The research was based on a forecasting method, which made it possible to take into account retrospective information and a number of internal and external factors affecting the processes of production and export of agricultural products. The sources of information were the data of the International Monetary Fund and the State Statistics Service of Ukraine. The hypotheses of the study were confirmed, and the results showed that the volume of production of agricultural products will be sufficient to support the population of the country, while maintaining the previous proportion of exports. At the same time, there is a potential for growth of the share of products that Ukraine can export. The forecast volumes of export of Ukrainian agricultural products obtained can serve as a guideline for regulating exports, taking into account the issue of food security in Ukraine.
Optimization of ultrasound-assisted extraction of two saponins from Paris polyphylla var. yunnanensis leaves using response surface methodology
Authors: Guo Xianming , Qiao Qing , Jin Yutian , Lei Huaxiong , Guo Kunyao , Zhao Zhengxiong , Li Ping , Liu Aizhong , Sun Rui
Published: July 2024

Paris polyphylla var. yunnanensis is one of the famous Chinese herbs, in which two saponins (polyphyllin II and polyphyllin VII) have anticancer effects. The endangerment of Paris polyphylla var. yunnanensis, makes the study of optimizing the extraction of polyphyllin II and polyphyllin VII from the leaves of Paris polyphylla var. yunnanensis more important. The study established and optimized the process of ultrasound-assisted extraction for polyphyllin II and polyphyllin VII using the Box Behnken Design method of response surface methodology. The results showed that the optimum extraction conditions for polyphyllin II and polyphyllin VII are ethanol concentration of 73 and 70%, extraction temperature of 43 and 50°C, and number of extraction 3, respectively. Under the above conditions, the contents of polyphyllin II and polyphyllin VII were measured to be 6.427 and 19.015 mg/g (DW). The results showed that the experimental model fitted well, and the response surface methodology (RSM) was feasible to optimize the extraction process of polyphyllin II and polyphyllin VII from Paris polyphylla var. yunnanensis leaves. This method provides an effective approach for the comprehensive development and utilization of non-medicinal parts of Paris polyphylla var. yunnanensis.
Development of multiplex real-time PCR for simultaneous detection of SARS-CoV-2, CCoV, and FIPV
Authors: Liu Yan , Zhu Zhen , Du Jige , Zhu Xiaojie , Pan Chenfan , Yin Chunsheng , Sun Weidong
Published: July 2024

Introduction

Coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), canine coronavirus (CCoV), and feline infectious peritonitis virus (FIPV), have the potential for interspecies transmission. These viruses can be present in complex environments where humans, dogs, and cats coexist, posing a significant threat to both human and animal safety.

Methods and results

In this study, we developed a novel multiplex TaqMan-probe-based real-time PCR assay for the simultaneous detection and differentiation of SARS-CoV-2, CCoV, and FIPV. Specific primers and TaqMan fluorescent probes were designed based on the N region of SARS-CoV-2 and FIPV, as well as the S region of CCoV, which demonstrated a remarkable sensitivity and specificity toward the targeted viruses, as few as 21.83, 17.25 and 9.25 copies/μL for SARS-CoV-2, CCoV and FIPV, respectively. The standard curve constructed by the optimized method in our present study showed a high amplification efficiency within or near the optimal range of 91% to 116% and R(2) values were at least 0.95 for the abovementioned coronaviruses. A total of 91 samples, including six plasmid mixed mock samples, four virus fluid mixing simulated samples, and 81 clinical samples, were analyzed using this method. Results demonstrated strong agreement with conventional approaches.

Discussion

By enabling the simultaneous detection of three viruses, this method enhances testing efficiency while decreasing costs. Importantly, it provides a valuable tool for the prevalence and geographical distribution of suspected and co-infected animals, ultimately contributing to the advancement of both animal and public health.
Climate Disaster and Cognitive Ability: Evidence From Wildfire
Authors: Du Ran , Liu Ke , Zhao Dangru , Fang Qiyun
Published: July 2024

Objectives

We investigate the impact of wildfire disasters on cognitive health (i.e., thinking and language skills) in individuals aged 10 years and older using 2014 and 2018 wildfire and cognitive ability survey data from China.

Methods

We distinguished wildfires in each county at different wind directions each day by exogenous wind direction changes, and analyzed the effects of wildfires on cognitive abilities through upwind and non-upwind wildfires.

Results

Our analysis shows that for every 10-unit increase in upwind wildfires compared to non-upwind wildfires, respondents’ scores on word and math tests decrease by 0.235 and 0.236 standard deviations, respectively. Furthermore, we find that the impact of wildfire on cognitive ability is more pronounced in younger individuals, and those with lower defensive expenditures experience more severe impacts. Additionally, wildfires negatively affect individuals’ cognitive abilities by generating air pollution.

Conclusion

Wildfires significantly reduce individuals’ cognitive abilities. Two recommendations are as follows: 1) governments should follow the principle of green development, introduce relevant regulations, and increase investment in adaptive technologies. 2) Individuals should raise awareness of climate hazards preparedness and strengthen defensive protection.
From prenatal diagnosis to surgical treatment: two case reports of congenital granular cell epulis
Authors: Han Yibing , Qiu Wen , Zhang Yu , Hua Mengmeng , Liu Shaohua , Dong Zuoqing
Published: July 2024

Herein, we detail a multidisciplinary approach and sequential treatment for two infants with congenital granular cell epulis (CGCE). Ultrasonic examinations at 34 weeks of gestation revealed prominent oral masses in both fetuses. To devise a carefully considered treatment strategy, a comprehensive multidisciplinary consultation including oral and maxillofacial surgeons, pediatricians, obstetricians, and anesthesiologists was convened. Following cesarean sections, the lesions were successfully removed, measuring approximately 30 × 15 mm and 30 × 20 mm in size, respectively. Immunohistochemical analysis showed that vimentin was positive, S-100 protein was negative, and NSE protein and CD68 protein were negative. These findings underscore the importance of prenatal diagnosis of congenital granular cell epulis for the effective management of these rare benign conditions.
Antibody Mediated Rejection and T-cell Mediated Rejection Molecular Signatures Using Next-Generation Sequencing in Kidney Transplant Biopsies
Authors: Cortes Garcia Esteban , Giarraputo Alessia , Racapé Maud , Goutaudier Valentin , Ursule-Dufait Cindy , de la Grange Pierre , Adoux Lucie , Raynaud Marc , Couderau Clément , Mezine Fariza , Dagobert Jessie , Bestard Oriol , Moreso Francesc , Villard Jean , Halleck Fabian , Giral Magali , Brouard Sophie , Danger Richard , Gourraud Pierre-Antoine , Rabant Marion , Couzi Lionel , Le Quintrec Moglie , Kamar Nassim , Morelon Emmanuel , Vrtovsnik François , Taupin Jean-Luc , Snanoudj Renaud , Legendre Christophe , Anglicheau Dany , Budde Klemens , Lefaucheur Carmen , Loupy Alexandre , Aubert Olivier
Published: July 2024

Recently, interest in transcriptomic assessment of kidney biopsies has been growing. This study investigates the use of NGS to identify gene expression changes and analyse the pathways involved in rejection. An Illumina bulk RNA sequencing on the polyadenylated RNA of 770 kidney biopsies was conducted. Differentially-expressed genes (DEGs) were determined for AMR and TCMR using DESeq2. Genes were segregated according to their previous descriptions in known panels (microarray or the Banff Human Organ Transplant (B-HOT) panel) to obtain NGS-specific genes. Pathway enrichment analysis was performed using the Reactome and Kyoto Encyclopaedia of Genes and Genomes (KEGG) public repositories. The differential gene expression using NGS analysis identified 6,141 and 8,478 transcripts associated with AMR and TCMR. While most of the genes identified were included in the microarray and the B-HOT panels, NGS analysis identified 603 (9.8%) and 1,186 (14%) new specific genes. Pathways analysis showed that the B-HOT panel was associated with the main immunological processes involved during AMR and TCMR. The microarrays specifically integrated metabolic functions and cell cycle progression processes. Novel NGS-specific based transcripts associated with AMR and TCMR were discovered, which might represent a novel source of targets for drug designing and repurposing.
Compound Control Design of Near-Space Hypersonic Vehicle Based on a Time-Varying Linear Quadratic Regulator and Sliding Mode Method
Authors: Wang Huan , Zhou Di , Zhang Yiqun , Lou Chaofei
Published: July 2024

The design of a hypersonic vehicle controller has been an active research field in the last decade, especially when the vehicle is studied as a time-varying system. A time-varying compound control method is proposed for a hypersonic vehicle controlled by the direct lateral force and the aerodynamic force. The compound control method consists of a time-varying linear quadratic regulator (LQR) control law for the aerodynamic rudder and a sliding mode control law for the lateral thrusters. When the air rudder cannot continuously produce control force and torque, the direct lateral force is added to the system. To solve the problem that LQR cannot directly obtain the analytical solution of the time-varying system, a novel approach to approximate analytical solutions using Jacobi polynomials is proposed in this paper. Finally, the stability of the time-varying compound control system is proven by the Lyapunov–Krasovskii functional (LKF). The simulation results show that the proposed compound control method is effective and can improve the fast response ability of the system.
Hybridizing Long Short-Term Memory and Bi-Directional Long Short-Term Memory Models for Efficient Classification: A Study on Xanthomonas axonopodis pv. phaseoli (XaP) in Two Bean Varieties
Authors: Kursun Ramazan , Gur Aysegul , Bastas Kubilay Kurtulus , Koklu Murat
Published: July 2024

This study was conducted on Xanthomonas axonopodis pv, which causes significant economic losses in the agricultural sector. Here, we study a common bacterial blight disease caused by the phaseoli (XaP) bacterial pathogen on Üstün42 and Akbulut bean genera. In this study, a total of 4000 images, healthy and diseased, were used for both bean breeds. These images were classified by AlexNet, VGG16, and VGG19 models. Later, reclassification was performed by applying pre-processing to the raw images. According to the results obtained, the accuracy rates of the pre-processed images classified by the VGG19, VGG16 and AlexNet models were determined as 0.9213, 0.9125 and 0.8950, respectively. The models were then hybridized with LSTM and BiLSTM for raw and pre-processed images and new models were created. When the performance of these hybrid models was evaluated, it was found that the models hybridized with LSTM were more successful than the simple models, while the models hybridized with BiLSTM gave better results than the models hybridized with LSTM. In particular, the VGG19+BiLSTM model attracted attention by achieving 94.25% classification accuracy with pre-processed images. This study emphasizes the effectiveness of image processing techniques in agriculture in the field of disease detection and is important as a new dataset in the literature for evaluating the performance of hybridized models.
Monitoring and Prediction of Ground Surface Settlement in Kunming Urban Area by Building GWO-LSTM Model Based on TS-InSAR
Authors: Li Jianhua , Li Bolin , Peng Yilong , Tang Shaofan , Chen Yongzhi , Pei Wenjuan
Published: July 2024

Long-term series monitoring of ground surface settlement by remote sensing has become an effective method. Based on TS-InSAR (time series Interferometric Synthetic Aperture Radar) interferometry, this paper proposes a new model based on the Grey Wolf Optimizer (GWO) and Long Short-Term Memory (LSTM) to monitor and predict the ground surface settlement in Kunming City. The results show that the MAPE (mean absolute percentage error), RMSE (root mean square error), and MAE (mean absolute error) of GWO-LSTM are significantly reduced. R2 (goodness of fit) in the six sub-study areas of Kunming City is improved in comparison to the LSTM model. The problem of manual parameter selection in the LSTM model is solved by the GWO algorithm to select parameters automatically. This approach not only significantly reduces the model’s training time but also identifies the most suitable network parameters. This can bring the best performance. Based on TS-InSAR data, the prediction of urban ground surface settlement by the GWO-LSTM model has good accuracy and robustness, which offers a scientific foundation for monitoring and issuing early warnings about urban land disasters.
Macadamia (Macadamia integrifolia) Nut-Based Beverage: Physicochemical Stability and Nutritional and Antioxidant Properties
Authors: Camacho-Teodocio Juan Daniel , Gallardo-Velázquez Tzayhri , Osorio-Revilla Guillermo , Castañeda-Pérez Eduardo , Velázquez-Contreras Claudia , Cornejo-Mazón Maribel , Hernández-Martínez Diana Maylet
Published: July 2024

The present work presents an investigation of the effects of xanthan gum (XG) and soy lecithin (SL) on the physicochemical stability, fatty acid profile (FAP), and antioxidant capacity (AC) of macadamia nut-based beverages with thermal treatment (TT), as well as physicochemical changes during storage and sensorial acceptability. An extreme vertices mixture design was used, varying the macadamia nut, SL, and XG. The results show that adding XG and SL decreased the Sauter (D[3,2]) and Brouckere (D[4,3]) diameters of particles in macadamia beverages and increased the zeta potential (ZP), which represents greater stability. After applying TT in beverages, D[3,2], D[4,3], and ZP increased. After processing and TT, the FAP and fat nutritional indices changed due to reducing SFA and PUFA and increasing MUFA relative to macadamia nut. No significant difference (p ≥ 0.05) was observed in the FAP of beverages with and without TT. The AC determined by DPPH and ABTS decreased in most beverages upon TT application. During storage for two months, the beverage particle size increased, there was a decrease in brightness, and no significant difference (p ≥ 0.05) was observed in ZP. Sensory analysis showed that the most stable beverage was not the most acceptable due to its viscosity.
Insight into IL-5 as a Potential Target for the Treatment of Allergic Diseases
Authors: Antosz Katarzyna , Batko Joanna , Błażejewska Marta , Gawor Antoni , Sleziak Jakub , Gomułka Krzysztof
Published: July 2024

Interleukin-5 functions as a B-cell differentiation factor, but more importantly, in the context of this review, it plays a variety of roles in eosinophil biology, including eosinophil differentiation and maturation in the bone marrow, and facilitates eosinophil migration to tissue sites, usually in the context of an allergic reaction. Given the availability of selective anti-IL-5 drugs such as mepolizumab and reslizumab, as well as the IL-5 receptor antagonist benralizumab, it is worth investigating whether they could be used in some cases of allergic disease. Asthma has a well-documented involvement of IL-5 in its pathophysiology and has clear benefits in the case of anti-IL-5 therapy; therefore, current knowledge is presented to provide a reference point for the study of less-described diseases such as atopic dermatitis, chronic rhinosinusitis, chronic spontaneous urticaria, and its association with both IL-5 and anti-IL-5 treatment options. We then review the current literature on these diseases, explain where appropriate potential reasons why anti-IL-5 treatments are ineffective, and then point out possible future directions for further research.
Biological Basis and Computer Vision Applications of Image Phase Congruency: A Comprehensive Survey
Authors: Tian Yibin , Wen Ming , Lu Dajiang , Zhong Xiaopin , Wu Zongze
Published: July 2024

The concept of Image Phase Congruency (IPC) is deeply rooted in the way the human visual system interprets and processes spatial frequency information. It plays an important role in visual perception, influencing our capacity to identify objects, recognize textures, and decipher spatial relationships in our environments. IPC is robust to changes in lighting, contrast, and other variables that might modify the amplitude of light waves yet leave their relative phase unchanged. This characteristic is vital for perceptual tasks as it ensures the consistent detection of features regardless of fluctuations in illumination or other environmental factors. It can also impact cognitive and emotional responses; cohesive phase information across elements fosters a perception of unity or harmony, while inconsistencies can engender a sense of discord or tension. In this survey, we begin by examining the evidence from biological vision studies suggesting that IPC is employed by the human perceptual system. We proceed to outline the typical mathematical representation and different computational approaches to IPC. We then summarize the extensive applications of IPC in computer vision, including denoise, image quality assessment, feature detection and description, image segmentation, image registration, image fusion, and object detection, among other uses, and illustrate its advantages with a number of examples. Finally, we discuss the current challenges associated with the practical applications of IPC and potential avenues for enhancement.
3D Printing and Surface Engineering of Ti6Al4V Scaffolds for Enhanced Osseointegration in an In Vitro Study
Authors: Ma Changyu , de Barros Natan Roberto , Zheng Tianqi , Gomez Alejandro , Doyle Marshall , Zhu Jianhao , Nanda Himansu Sekhar , Li Xiaochun , Khademhosseini Ali , Li Bingbing
Published: July 2024

Ti6Al4V superalloy is recognized as a good candidate for bone implants owing to its biocompatibility, corrosion resistance, and high strength-to-weight ratio. While dense metal implants are associated with stress shielding issues due to the difference in densities, stiffness, and modulus of elasticity compared to bone tissues, the surface of the implant/scaffold should mimic the properties of the bone of interest to assure a good integration with a strong interface. In this study, we investigated the additive manufacturing of porous Ti6Al4V scaffolds and coating modification for enhanced osteoconduction using osteoblast cells. The results showed the successful fabrication of porous Ti6Al4V scaffolds with adequate strength. Additionally, the surface treatment with NaOH and Dopamine Hydrochloride (DOPA) promoted the formation of Dopamine Hydrochloride (DOPA) coating with an optimized coating process, providing an environment that supports higher cell viability and growth compared to the uncoated Ti6Al4V scaffolds, as demonstrated by the higher proliferation ratios observed from day 1 to day 29. These findings bring valuable insights into the surface modification of 3D-printed scaffolds for improved osteoconduction through the coating process in solutions.
Assessing Psychological Disorders in Turkish Adolescents with Transfusion-Dependent Thalassemia
Authors: Yetim Şahin Aylin , Kandemir Ibrahim , Dağ Hüseyin , Türkkan Emine , Tuğrul Aksakal Melike , Sahin Memduh , Baş Firdevs , Karakaş Zeynep
Published: July 2024

We investigated depression and anxiety levels and related psychological disorders in adolescents with transfusion-dependent thalassemia (TDT) in this study. The study was conducted in two pediatric hematology outpatient clinics and included adolescents with TDT (14.8 ± 2.4 years, n = 40) in the study and compared them with the healthy age-matched control group (14.3 ± 2.3 years, n = 62). The Turkish version of the Revised Child Anxiety and Depression Scale (RCADS) was used to determine depression, anxiety, and related psychologic disorders (obsession, panic disorder, social phobia). Depression, anxiety, obsession, panic disorder, and social phobia scores were significantly higher in the patient group compared with the control (all p < 0.05). Ferritin levels were positively correlated with total depression, general anxiety, separation anxiety, and social phobia scores, but transfusion frequency and young age were the confounding factors. Patients in early adolescence and those who require more frequent blood transfusions are at higher risk of developing psychological disorders; routine screening for mood disorders should be warranted. Serum ferritin level may be a good warning indicator for early recognition of psychologic disorders in TDT patients.
Acute Effect of Simultaneous Exercise and Cognitive Tasks on Cognitive Functions in Elderly Individuals with Mild Cognitive Impairment
Authors: Ben Ayed Ines , Ammar Achraf , Boujelbane Mohamed Ali , Salem Atef , Naija Salma , Amor Sana Ben , Trabelsi Khaled , Jahrami Haitham , Chtourou Hamdi , Trabelsi Yassine , El Massioui Farid
Published: July 2024

The increasing prevalence of age-related cognitive decline, alongside the aging global population, underscores the urgent need for innovative and effective preventative strategies. While the advantages of combining physical and cognitive exercises have been recognized as a promising approach to address these socioeconomic challenges, the acute effects of such interventions on cognitive functions remain understudied. This study aimed to investigate whether simultaneous physical and cognitive exercise has a greater beneficial impact on the cognitive functions of older adults with mild cognitive impairment (MCI) than physical exercise alone or reading activities. A total of 44 MCI patients (75% females aged between 65 and 75 years) were randomly assigned to one of three groups: aerobic exercise alone (EG group, n = 15), aerobic combined with cognitive exercises (CEG group, n = 15), or a reading task for controls (CG group, n = 14). Attention, memory, and problem solving were assessed before and after the acute intervention using the Tower of Hanoi, Digit Span, and Stroop tasks, respectively. Statistical analysis revealed that both of the experimental interventions appeared to enhance cognitive function scores (p < 0.05), except for the number of moves in the Tower of Hanoi task, where no improvement was noted. In contrast, no significant differences in any cognitive performance measures were observed following the reading session. Notably, the CEG group exhibited a more pronounced positive impact, especially on working memory. This advantage was specifically evident in the digit span tasks, where significantly greater percentage gains were found in the CEG than in the CG (p = 0.02), while no significant difference existed between the EG and CG. Simultaneous combined exercise has proven to be a more effective method than aerobic physical exercise alone for improving cognitive function. The results of this study are recommended for inclusion in clinical practice guidelines to maintain the mental health of older adults, as simultaneous exercise seems to offer a time-efficient strategy to enhance cognitive performance in adults with MCI.
A Conditional Privacy-Preserving Identity-Authentication Scheme for Federated Learning in the Internet of Vehicles
Authors: Xu Shengwei , Liu Runsheng
Published: July 2024

With the rapid development of artificial intelligence and Internet of Things (IoT) technologies, automotive companies are integrating federated learning into connected vehicles to provide users with smarter services. Federated learning enables vehicles to collaboratively train a global model without sharing sensitive local data, thereby mitigating privacy risks. However, the dynamic and open nature of the Internet of Vehicles (IoV) makes it vulnerable to potential attacks, where attackers may intercept or tamper with transmitted local model parameters, compromising their integrity and exposing user privacy. Although existing solutions like differential privacy and encryption can address these issues, they may reduce data usability or increase computational complexity. To tackle these challenges, we propose a conditional privacy-preserving identity-authentication scheme, CPPA-SM2, to provide privacy protection for federated learning. Unlike existing methods, CPPA-SM2 allows vehicles to participate in training anonymously, thereby achieving efficient privacy protection. Performance evaluations and experimental results demonstrate that, compared to state-of-the-art schemes, CPPA-SM2 significantly reduces the overhead of signing, verification and communication while achieving more security features.
Unraveling the Degradation Mechanisms of Lithium-Ion Batteries
Authors: Rufino Júnior Carlos Antônio , Sanseverino Eleonora Riva , Gallo Pierluigi , Amaral Murilo Machado , Koch Daniel , Kotak Yash , Diel Sergej , Walter Gero , Schweiger Hans-Georg , Zanin Hudson
Published: July 2024

Lithium-Ion Batteries (LIBs) usually present several degradation processes, which include their complex Solid-Electrolyte Interphase (SEI) formation process, which can result in mechanical, thermal, and chemical failures. The SEI layer is a protective layer that forms on the anode surface. The SEI layer allows the movement of lithium ions while blocking electrons, which is necessary to prevent short circuits in the battery and ensure safe operation. However, the SEI formation mechanisms reduce battery capacity and power as they consume electrolyte species, resulting in irreversible material loss. Furthermore, it is important to understand the degradation reactions of the LIBs used in Electric Vehicles (EVs), aiming to establish the battery lifespan, predict and minimise material losses, and establish an adequate time for replacement. Moreover, LIBs applied in EVs suffer from two main categories of degradation, which are, specifically, calendar degradation and cycling degradation. There are several studies about battery degradation available in the literature, including different degradation phenomena, but the degradation mechanisms of large-format LIBs have rarely been investigated. Therefore, this review aims to present a systematic review of the existing literature about LIB degradation, providing insight into the complex parameters that affect battery degradation mechanisms. Furthermore, this review has investigated the influence of time, C-rate, depth of discharge, working voltage window, thermal and mechanical stresses, and side reactions in the degradation of LIBs.
Transient Emissions Forecasting of Off-Road Construction Machinery Based on Long Short-Term Memory Network
Authors: Li Tengteng , Jing Xiaojun , Wang Fengbin , Wang Xiaowei , Gao Dongzhi , Cai Xianyang , Tang Bin
Published: July 2024

Off-road machinery is one of the significant contributors to air pollution due to its large quantity. In this study, a deep learning model was developed to predict the transient engine emissions of CO, NO, NO2, and NOx, which are the main pollutants emitted by off-road machinery. A portable emission measurement system (PEMS) was used to measure the exhaust emission features of four types of construction machinery. The raw PEMS data were preprocessed using data compensation, local linear regression, and normalization to ensure that the data could handle transient conditions. The proposed model utilizes the preprocessing PEMS data to estimate the CO, NO, NO2, and NOx emissions from off-road machinery using a recurrent neural network (RNN) based on a long short-term memory (LSTM) model. The experimental results show that the proposed method can effectively predict the emissions from off-road construction machinery under transient conditions and can be applied to controlling the emissions from off-road construction machinery.
Research on the Coordinated Trading Mechanism of Demand-Side Resources and Shared Energy Storage Based on a System Optimization Model
Authors: Li Xiuping , Yang Li , Xu Yi , Luo Xiaohu , Yang Xi , Fang Jugang , Lu Yuhao
Published: July 2024

With the development of the economy and society, the importance of a secure and stable electricity supply continues to increase. However, the power grid is facing the test of excess installed capacity, the waste of renewable energy, and a low comprehensive utilization rate. This problem stems from the inconsistent peak–valley differences between power production and consumption, and the lack of clear electricity price signals, which disrupts the safe and stable operation of the power market. This paper combines the interactive transactions among clean energy power generation companies, users, and energy storage, explores how the system optimization model can be reflected in the power market through regulatory measures, and formulates the optimal output scheme of the system under the constraints of clean energy power generation forecast data, user base load forecast data, demand-side resource regulation ability, and energy storage system regulation ability to achieve the goals of comprehensive clean energy power consumption and minimum cost for users. A comprehensive analysis of the proposed model was conducted using actual data from a certain province in China, the results show that the consumption of clean energy will increase by 3% to full consumption and the total cost of users will be 32% lower than that of time-of-use (TOU) power prices, which proves the potential of the proposed joint optimization model in absorbing clean energy and the effectiveness of the market mechanism.
Exploitation of Mineral Resources in Conditions of Volatile Energy Prices: Technical and Economic Analysis of Low-Quality Deposits
Authors: Krysa Zbigniew , Bodziony Przemysław , Patyk Michał
Published: July 2024

In mining projects and production operations, energy carrier costs (fuel, electricity) constitute the primary component of variable costs. This study outlines a methodology for projecting operating costs in a surface mine or quarry in order to find the optimal configuration of mining equipment to extract low-grade secondary deposits, taking into account volatile energy prices. For illustration, the operating costs of five variants of mining equipment deployed to mine low-grade products were analysed, with the price of energy and fuels being the key cost component and the main risk factor. There were differences between the initial investment outlays and operating costs involved in all analysed variants, whilst the starting point for estimating the technical and economic parameters involved in the respective solutions was the predefined configuration of the mining equipment. Further, the decision to commence or discontinue mining operations could be supported by the simulation procedure based on the economic model. The results provided valuable insights into the cost-effectiveness of low-grade deposit extraction scenarios, depending on the projected unit costs of fuels and energy.
Facilitating a Sustainable Aviation Fuel Transition in Italy
Authors: Erriu Riccardo , Marcucci Edoardo , Gatta Valerio
Published: July 2024

Civil aviation significantly contributes to “hard-to-abate” emissions, responsible for 2% of global CO2 emissions. This paper examines the most effective policies to promote Sustainable Aviation Fuels (SAFs) in Italy, using a multi-level policy analysis and a stakeholder-based case study approach. The policies reviewed comprise the international, European, and national level. The paper analyses at the international level, ICAO CORSIA and, at the European level, the Renewable Energy Directive (RED), ReFuel EU, and the EU Emissions Trading System (EU ETS) for aviation. Italy has not yet implemented specific policies targeting SAF transition, which is challenging due to commercialization issues and policy inconsistencies. These include the price gap between SAF and conventional fuels, different definitions adopted, and environmental objectives pursued with respect to sustainable fuels by ICAO and the EU. Other challenges include double-counting risks and fuel tankering practices. This article contributes to Italy’s SAF policymaking by developing a stakeholder-based quantitative survey, whose results suggest that three measures are key: tax subsidies for technology and infrastructure users, tax credits for upgrading production infrastructure, and tax breaks for SAF-using companies, fuel handlers, and distributors.
A Review of Thermochemical Energy Storage Systems for District Heating in the UK
Authors: Roger-Lund Sarah , Darkwa Jo , Worall Mark , Calautit John , Boukhanouf Rabah
Published: July 2024

Thermochemical energy storage (TCES) presents a promising method for energy storage due to its high storage density and capacity for long-term storage. A combination of TCES and district heating networks exhibits an appealing alternative to natural gas boilers, particularly through the utilisation of industrial waste heat to achieve the UK government’s target of Net Zero by 2050. The most pivotal aspects of TCES design are the selected materials, reactor configuration, and heat transfer efficiency. Among the array of potential reactors, the fluidised bed emerges as a novel solution due to its ability to bypass traditional design limitations; the fluidised nature of these reactors provides high heat transfer coefficients, improved mixing and uniformity, and greater fluid-particle contact. This research endeavours to assess the enhancement of thermochemical fluidised bed systems through material characterisation and development techniques, alongside the optimisation of heat transfer. The analysis underscores the appeal of calcium and magnesium hydroxides for TCES, particularly when providing a buffer between medium-grade waste heat supply and district heat demand. Enhancement techniques such as doping and nanomaterial/composite coating are also explored, which are found to improve agglomeration, flowability, and operating conditions of the hydroxide systems. Furthermore, the optimisation of heat transfer prompted an evaluation of heat exchanger configurations and heat transfer fluids. Helical coil heat exchangers are predominantly favoured over alternative configurations, while various heat transfer fluids are considered advantageous depending on TCES material selection. In particular, water and synthetic liquids are compared according to their thermal efficiencies and performances at elevated operating temperatures.
An Improved Control Method of DC Voltage for Series Hybrid Active Power Filter
Authors: Liu Jianben , Ni Yuan , Zhao Jun
Published: July 2024

DC voltage is one of the important parameters of active power filters. Since the series hybrid active power filter does not withstand the fundamental voltage, it cannot absorb energy from the power grid, making it too difficult to control its DC voltage. In order to solve the DC voltage control problem, an improved control method for the series hybrid active power filter with magnetic flux compensation is proposed in this paper. In this improved method, the fundamental magnetic flux compensation coefficient is equal to 1, meeting the condition of fundamental magnetic flux compensation. This improved method does not rely on the precise detection and phase-locking of the fundamental voltage at the port of the series transformer. A phase-fixed active current component is generated directly by the inverter, enabling the active power filter (APF) to absorb active power from the power grid. Consequently, the active power absorbed by the APF from the power grid has a linear relationship with the active current component. Both simulation and experimentation verified the correctness and effectiveness of this proposed method.
Influence of Wind and Rainfall on the Performance of a Photovoltaic Module in a Dusty Environment
Authors: Stankov Borislav , Terziev Angel , Vassilev Momchil , Ivanov Martin
Published: July 2024

This study presents an analysis of the influence of weather conditions on the performance of a multicrystalline silicon photovoltaic module, which operates under constant resistive load and is situated near a limestone quarry. The quarry is a significant source of dust, and hence the focus of the study is on the weather factors influencing the presence of soiling on the module’s surface. The analysis encompasses a three-week period, during which the global horizontal irradiance and wind speed were recorded at 10-min intervals by an on-site weather station. The current, voltage, and back temperature of the module were also measured. Supplementary weather data were obtained from the Copernicus Atmosphere Monitoring Service and the NASA POWER databases. The primary objective is to assess whether any influence of the observed weather conditions on the presence of soiling can be inferred from the recorded data. The contribution is in part intended to test how different techniques can be used to extract useful information on the weather-related effects from somewhat limited data, assembled from various sources, while dealing with the underlying uncertainties. The analysis indicates a persistent deterioration of the module’s performance because of soiling and its subsequent improvement due to a favourable weather event.
Forecasting Electric Vehicles’ Charging Behavior at Charging Stations: A Data Science-Based Approach
Authors: Amezquita Herbert , Guzman Cindy P. , Morais Hugo
Published: July 2024

The rising adoption of electric vehicles (EVs), driven by carbon neutrality goals, has prompted the need for accurate forecasting of EVs’ charging behavior. However, this task presents several challenges due to the dynamic nature of EVs’ usage patterns, including fluctuating demand and unpredictable charging durations. In response to these challenges and different from previous works, this paper presents a novel and holistic methodology for day-ahead forecasting of EVs’ plugged-in status and power consumption in charging stations (CSs). The proposed framework encompasses data analysis, pre-processing, feature engineering, feature selection, the use and comparison of diverse machine learning forecasting algorithms, and validation. A real-world dataset from a CS in Boulder City is employed to evaluate the framework’s effectiveness, and the results demonstrate its proficiency in predicting the EVs’ plugged-in status, with XGBoost’s classifier achieving remarkable accuracy with an F1-score of 0.97. Furthermore, an in-depth evaluation of six regression methods highlighted the supremacy of gradient boosting algorithms in forecasting the EVs’ power consumption, with LightGBM emerging as the most effective method due to its optimal balance between prediction accuracy with a 4.22% normalized root-mean-squared error (NRMSE) and computational efficiency with 5 s of execution time. The proposed framework equips power system operators with strategic tools to anticipate and adapt to the evolving EV landscape.
The Utilization and Roles of Nitrogen in Plants
Authors: Wang Qian , Li Shasha , Li Junrong , Huang Dong
Published: July 2024

Nitrogen (N) is an essential mineral element for plants and is the main component of protein, nucleic acid, phospholipid, chlorophyll, hormones, vitamins and alkaloids. It is involved in all stages of plant growth and development. Low-N stress seriously hinders plant growth and reduces yield and quality. Plants have evolved a series of elaborate regulatory mechanisms for N uptake and assimilation to cope with different soil N states. After N is absorbed and utilized by plants, it plays important regulatory roles in phytohormones, microRNA (miRNA), root development and mycorrhizal symbiosis to cope with environmental stress. Here, we highlight the research progress on the regulation mechanisms for N absorption and assimilation. Then, we emphasize the regulation roles of N regarding hormone signals, miRNA, lateral root growth, drought resistance, anthocyanin synthesis and mycorrhizal symbiosis. A thorough understanding of N uptake, utilization and interaction with other biological processes is helpful to improve N use efficiency and to breed plants with “less-input-more-output”.