bluuebunny/crossref_metadata_2025 huggingface dataset:
From Life-Skills Research and Training to Sustainability: A Case Study from a Spanish University
Authors: Posadas de Julián Pilar , Verdejo Lucas Carmen , de Rueda Villén Belén , Haro-Soler María del Mar , Gijón-Puerta José , Cámara Aguilera Elvira , García de Quesada Mercedes
Published: July 2024

We are currently facing a potential ‘polycrisis’, a critical inflection point that requires a holistic response aimed at building collective foresight and preparedness for short-, medium-, and long-term risks. The role of higher education institutions and social stakeholders is decisive for sustainability goals. This paper presents a case study where academia, governance, and industry have aligned to challenge, inspire, and encourage universities to enhance student growth and bind macro-scale measures leading to a sustainable future. A teaching innovation project has served as a transforming lever, in combination with the private sector, to create a platform that reaches more than 50,000 undergraduate students and teaching staff. This structure, rooted in the 2031 Strategic Plan of the University of Granada, has also served to channel local and regional initiatives, establish effective partnerships with broad social members, raise awareness, and promote actions to advance in the pursuit of Sustainable Development Goals. A comprehensive overview is provided, which details its chronology, materials, results, challenges, impact, and descriptions of the various courses, programs, and actions. The paper concludes with recommendations for future research, policy and cooperation among stakeholders.
A Rapidly Self-Healing Superhydrophobic Coating Made of Polydimethylsiloxane and N-nonadecane: Stability and Self-Healing Capabilities
Authors: Hu Qin , Hu Ziyuan , Jiang Xingliang , Yang Hang , Liu Yuhao , An Yaya
Published: July 2024

Superhydrophobic surfaces have garnered significant attention in various industrial applications, such as photovoltaic power generation, anti-icing, and corrosion resistance, due to their exceptional water-repellent properties. However, the poor durability of conventional superhydrophobic coatings has severely impeded their practical implementation. To achieve the dual self-recovery of microscale and nanoscale surface structures and maintain low surface energy after damage to superhydrophobic coatings, thereby enhancing their durability, a rapidly self-healing superhydrophobic coating was developed using polydimethylsiloxane (PDMS) and n-nonadecane in this study. The coating surface demonstrated exceptional hydrophobic characteristics, as evidenced by a water contact angle (WCA) of 157.5° and a sliding angle (SA) of 4.2° achieved at optimized proportions. Through scanning electron microscopy, it was observed that the coating surface exhibited a rough structure at both the microscale and nanoscale. The stability test results showed that the WCA only decreases by 5.7° and the SA only increases by 3.6° after 100 instances of external friction. The stability test results demonstrated that the superhydrophobic coating maintains excellent hydrophobicity under mechanical external forces and in acidic and alkaline environments. The results of the self-healing capability test showed that the WCA rebounded to 151.5° and 149.5° after we subjected the samples to 20 MPa of vertical pressure damage and chloroform exposure for 4 h, respectively. The coating regained a robust hydrophobic state even after experiencing repeated mechanical and chemical damage. The above results indicate that the resulting coating demonstrates outstanding durability, including high resistance to friction, stability against acids and alkalis, and the ability to self-recover hydrophobicity after repeated damage.
Research on Film Formation Characteristics by Spraying on Unidiameter Vertical Interpenetrating Cylindrical Surfaces
Authors: Wu Zhaojie , Chen Yan , Chen Shiming , Duan Jimiao , Li Jiang
Published: July 2024

Unidiameter Vertical Interpenetrating Cylindrical Surfaces (UVICS, also called T-pipe surfaces) are a type of typical complex surface that exists in facilities or equipment such as oil storage tanks and industrial pipelines. The shape and surface characteristics of a component undergoing spraying will have a significant impact on the spray flow field and the resulting coating film. In order to optimize the coating effects of complex surfaces, the Euler-Euler approach was utilized to model a spray film formation process that encompasses both a spray flow field model and a wall adhesion model. Subsequently, the influence of the geometric features, geometric dimensions, lateral air pressure of the spray gun, and spraying distance on the coating film characteristics of this kind of surface were systematically investigated. It is determined that the film thickness uniformity could be enhanced by decreasing the dimensions of the workpiece or increasing the lateral air pressure and spraying distance in an appropriate manner when spraying at the location with the most complex geometric features of UVICS. Furthermore, the optimal parameters under varying spraying conditions were identified. The experiments validated the accuracy of the numerical simulation results and demonstrated the feasibility of this simulation model. The study is of significant value in addressing the challenges associated with film formation during spraying on complex surfaces, developing a comprehensive theoretical framework for air spraying, and expanding the scope of applications for automatic spraying technology.
Numerical Simulation and Comparison of Different Steady-State Tumble Measuring Configurations for Internal Combustion Engines
Authors: Theodorakakos Andreas
Published: July 2024

To enhance air–fuel mixing and turbulence during combustion, spark ignition internal combustion engines commonly employ tumble vortices of the charge inside the cylinder. The intake phase primarily dictates the generated tumble, which is influenced by the design of the intake system. Utilizing steady-state flow rigs provides a practical method to assess an engine’s cylinder head design’s tumble-generating characteristics. This study aims to conduct computational fluid dynamics (CFD) numerical simulations on various configurations of steady-state flow rigs and compare the resulting tumble ratios. The simulations are conducted for different inlet valve lifts of a four-valve cylinder head with a shallow pent-roof. The findings highlight variations among these widely adopted configurations.
Genetic Differentiation and Population Structure of Two Bulgarian Local Goat Breeds Using Microsatellite Markers
Authors: Yordanov Georgi , Kalaydzhiev Georgi , Palova Nadezhda , Salkova Delka , Lozanova Lyudmila , Dundarova Heliana , Odjakova Tsonka , Todorov Pavel , Radoslavov Georgi , Hristov Peter
Published: July 2024

Establishing genetic diversity in the population is an essential first step for the sustainable conservation of valuable genetic resources under threat of extinction. Two local goat breeds, Kalofer long-haired (KLH) and Bulgarian screw-horned long-haired (BSHL), were genotyped using a panel of 14 microsatellite markers to determine their population structure and differentiation. The overall mean number of alleles was 8.82, higher in BSHL (9.71) as compared with KLH (7.92). The Ho and He values were almost equal for BSHL (0.75; 0.76, respectively) and KLH goats (0.74; 0.76, respectively). The value of the coefficient of population differentiation (FST) was very low (0.024), indicating only 2% genetic differentiation between the two goat breeds. The structure and PCoA analyses revealed considerable overlap between the two breeds, although some flocks of each breed differentiated from the common genetic pool. The results obtained in the present study can serve to differentiate purebred animals that are the basis of a selection process and a breeding strategy with a view to the conservation of these two local goat breeds.
Stratigraphic Reassessment of the Mexican Chasmosaurine Coahuilaceratops magnacuerna as the First Diagnostic Dinosaur Remains from the Cerro Huerta Formation (Lower Maastrichtian) Supporting the Southern Origin of the Triceratopsini
Authors: Barrera Guevara Daniela , Espinosa Chávez Belinda , Serrano Brañas Claudia Inés , de León Dávila Claudio , Posada Martinez Daniel , Freedman Fowler Elizabeth , Fowler Denver
Published: July 2024

Very few remains of ceratopsid dinosaurs have been recovered so far from the Difunta Group of Coahuila, Mexico. The enigmatic chasmosaurine Coahuilaceratops magnacuerna was previously described on the basis of two partial skulls purportedly derived from the Cerro del Pueblo Formation (~73–72.5 Ma?). On the basis of a new measured section and lithological identification of the host rock, we reassign Coahuilaceratops to the overlying Cerro Huerta Formation (~71.5–70.5 Ma?). Thus, we formally assign the first dinosaur taxon to the Cerro Huerta Formation. This reassignment is more consistent with the relatively derived phylogenetic position of Coahuilaceratops, with implications for the southern Laramidia hypothesis concerning the origin of the Triceratopsini.
Utilizing Deep Learning for Diagnosing Radicular Cysts
Authors: Rašić Mario , Tropčić Mario , Pupić-Bakrač Jure , Subašić Marko , Čvrljević Igor , Dediol Emil
Published: July 2024

Objectives: The purpose of this study was to develop a deep learning algorithm capable of diagnosing radicular cysts in the lower jaw on panoramic radiographs. Materials and Methods: In this study, we conducted a comprehensive analysis of 138 radicular cysts and 100 normal panoramic radiographs collected from 2013 to 2023 at Clinical Hospital Dubrava. The images were annotated by a team comprising a radiologist and a maxillofacial surgeon, utilizing the GNU Image Manipulation Program. Furthermore, the dataset was enriched through the application of various augmentation techniques to improve its robustness. The evaluation of the algorithm’s performance and a deep dive into its mechanics were achieved using performance metrics and EigenCAM maps. Results: In the task of diagnosing radicular cysts, the initial algorithm performance—without the use of augmentation techniques—yielded the following scores: precision at 85.8%, recall at 66.7%, mean average precision (mAP)@50 threshold at 70.9%, and mAP@50-95 thresholds at 60.2%. The introduction of image augmentation techniques led to the precision of 74%, recall of 77.8%, mAP@50 threshold to 89.6%, and mAP@50-95 thresholds of 71.7, respectively. Also, the precision and recall were transformed into F1 scores to provide a balanced evaluation of model performance. The weighted function of these metrics determined the overall efficacy of our models. In our evaluation, non-augmented data achieved F1 scores of 0.750, while augmented data achieved slightly higher scores of 0.758. Conclusion: Our study underscores the pivotal role that deep learning is poised to play in the future of oral and maxillofacial radiology. Furthermore, the algorithm developed through this research demonstrates a capability to diagnose radicular cysts accurately, heralding a significant advancement in the field.
Sex Determination via the Second Cervical Vertebra and Odontoid Process: A Case Report and a Review of the Literature
Authors: Stan Emanuela , Muresan Camelia-Oana , Dumache Raluca , Ciocan Veronica , Ungureanu Stefania , Daescu Ecaterina , Enache Alexandra
Published: July 2024

Determining an individual’s sex is crucial in several fields, such as forensic anthropology, archaeology, and medicine. Accurate sex estimation, alongside the estimation of age at death, stature, and ancestry, is of paramount importance for creating a biological profile. This profile helps narrow the potential pool of missing persons and aids identification. Our research focuses on the second cervical vertebra and odontoid process, which is particularly valuable due to their high sexual dimorphism. This brief research is structured as follows: we provide an overview of morphometric analysis of the second cervical vertebra for accurate sex estimation in forensic anthropology. We then delve into a case report to explore sexual dimorphism of the C2 vertebrae. Moreover, we discuss some of these studies that showed a significant correlation between the dimensions of the second cervical vertebrae and height, suggesting that the C2 can be used as a reliable indicator for stature estimation. The high accuracy rate of sex estimation using the second cervical vertebrae suggests that this method is a valuable tool for forensic anthropologists. Its practical application can significantly contribute to identifying and profiling individuals in a forensic context, thereby aiding in the identification process.
Diagnostic Value of SALL4 and OCT3/4 in Pediatric Testicular Tumors
Authors: Bîcă Ovidiu , Ciongradi Carmen Iulia , Ivănuță Marius , Ianole Victor , Sârbu Ioan , Cojocaru Elena , Bîcă Delia Elena , Lozneanu Ludmila
Published: July 2024

Testicular tumors (TTs) are rare in children, posing diagnostic and therapeutic challenges. This retrospective study evaluates the diagnostic and prognostic utility of SALL4 and OCT3/4 in pediatric TTs. We analyzed 18 cases of different types of TTs using immunohistochemistry (IHC) to assess SALL4 (Spalt-like transcription factor 4) and OCT3/4 (Octamer binding transcription factor 3/4) expression. SALL4 was positive in 83.3% of tumors, while OCT3/4 was positive in 38.9% of tumors, with a significantly higher prevalence in patients aged 12–18 years compared to those aged 0–11 years (p = 0.013). Mixed germinal cell tumors were significantly more frequently associated with OCT3/4 (p = 0.003), and a high immunostaining expression for SALL4 was observed primarily in yolk sac tumors and embryonal carcinoma. Our findings suggest that SALL4 and OCT3/4 immunostaining can aid in accurate diagnosis and treatment planning, and underscores the importance of OCT3/4 as a predictive factor in pediatric testicular tumors, highlighting its substantial correlation with tumor type and its impact on treatment response. These markers may guide personalized therapeutic strategies, potentially improving patient outcomes.
The Outcomes of Colorectal Endoscopic Submucosal Dissection in Patients with Chronic Kidney Disease: A Honam Association for the Study of Intestinal Disease (HASID) Multicenter Study
Authors: Jin Byung Chul , Kim Dong Hyun , Seo Geom-Seog , Kim Sang-Wook , Oh Hyung-Hoon , Song Hyo-Yeop , Kim Seong-Jung , Joo Young-Eun , Lee Jun , Kim Hyun-Soo
Published: July 2024

Colorectal neoplasms are prevalent in patients with chronic kidney disease (CKD); however, the safety and efficacy of colorectal endoscopic submucosal dissection (ESD) are not well understood. This retrospective analysis included ESD procedures performed in 1266 patients with CKD across five tertiary medical institutions from January 2015 to December 2020. Patients were categorized based on their estimated glomerular filtration rate (eGFR), which ranged from CKD1 to CKD5 (including those on dialysis). We found that en bloc resection rates remained high across all CKD stages, affirming the procedural efficacy of ESD. Notably, the prevalence of cardiovascular comorbidities, such as ischemic heart disease and diabetes mellitus, significantly increased with an advancing CKD stage, with a corresponding increase in the Charlson Comorbidity Index, highlighting the complexity of managing these patients. Despite these challenges, the complete resection rate was lower in the CKD5 group (50%) than in the CKD1 group (83.4%); however, procedural complications, such as perforation and bleeding, did not significantly differ among the groups. The predictive models for complete resection and major complications showed no significant changes with a decreasing eGFR. These findings underscore that ESD is a feasible and safe treatment for colorectal neoplasms in patients with CKD, successfully balancing the inherent procedural risks with clinical benefits.
Prevalence and Patterns of Positional Dental Anomalies in First Permanent Molars: Insights from a Study in Oradea, Romania
Authors: Moca Rahela Tabita , Moca Abel Emanuel , Juncar Raluca Iulia , Vaida Luminița Ligia , Janosy Anna-Maria , Juncar Mihai
Published: July 2024

Tooth position anomalies, influenced by both genetic and environmental factors, can significantly impact oral health and play a critical role in establishing proper occlusion. The aim of this study was to identify the most prevalent tooth position anomalies in first permanent molars among Romanian patients and to evaluate additional variables as well. This retrospective study utilized digital study models to identify all existing tooth position anomalies. The study included patients aged 12 to 40 years with complete permanent dentition. Axial changes (buccal tilting, oral tilting, mesial tilting, and distal tilting) as well as rotational changes (mesio-buccal rotation and disto-buccal rotation) were investigated. After applying the exclusion criteria, 103 patients remained in the study. Our findings revealed a notable prevalence of positional anomalies, with disto-buccal rotations being most common in upper molars (tooth 1.6–22.3%, tooth 2.6–31.1%) and oral tilting predominating in lower molars (tooth 3.6–6.8%, tooth 4.6–14.6%). Interestingly, neither gender nor malocclusion type significantly influenced the occurrence of tooth position anomalies. Symmetrical patterns in positional changes were observed, with patients having tooth position anomalies at 1.6 significantly more frequently associated with anomalies at 2.6. Similarly, anomalies at 3.6 were significantly more frequently associated with anomalies at 4.6. Additionally, for molars 2.6 and 3.6 on the left side, the differences were statistically significant, with patients having anomalies at 2.6 significantly more frequently associated with anomalies at 3.6. This pattern was not observed for the molars situated on the right side of the dental arches. While this study provides insights into positional anomalies in first permanent molars among the Romanian population, its retrospective design and focus on a specific demographic may limit generalizability. In conclusion, the study underscores the significant prevalence of positional anomalies in first permanent molars among adolescents and adults in Oradea, Romania. Early detection and targeted interventions are crucial to address these anomalies and improve orthodontic outcomes. Comprehensive assessment and treatment planning are essential to achieve optimal dental harmony and function. Further research is needed to elucidate the underlying factors contributing to these positional changes and their long-term impact on oral health and occlusal stability.
Non-Equilibrium Enhancement of Classical Information Transmission
Authors: Zeng Qian , Wang Jin
Published: July 2024

Information transmission plays a crucial role across various fields, including physics, engineering, biology, and society. The efficiency of this transmission is quantified by mutual information and its associated information capacity. While studies in closed systems have yielded significant progress, understanding the impact of non-equilibrium effects on open systems remains a challenge. These effects, characterized by the exchange of energy, information, and materials with the external environment, can influence both mutual information and information capacity. Here, we delve into this challenge by exploring non-equilibrium effects using the memoryless channel model, a cornerstone of information channel coding theories and methodology development. Our findings reveal that mutual information exhibits a convex relationship with non-equilibriumness, quantified by the non-equilibrium strength in transmission probabilities. Notably, channel information capacity is enhanced by non-equilibrium effects. Furthermore, we demonstrate that non-equilibrium thermodynamic cost, characterized by the entropy production rate, can actually improve both mutual information and information channel capacity, leading to a boost in overall information transmission efficiency. Our numerical results support our conclusions.
‘Unlock the Complexity’: Understanding the Economic and Political Pathways Underlying the Transition to Climate-Smart Smallholder Forage-Livestock Systems: A Case Study in Rwanda
Authors: Perelli Chiara , Cacchiarelli Luca , Mupenzi Mutimura , Branca Giacomo , Sorrentino Alessandro
Published: July 2024

The livestock-dairy sector in Sub-Saharan Africa, particularly in Rwanda, is experiencing rapid growth due to population expansion, urbanisation, and changing food preferences. The unmet local production demands are causing soil and water pollution, competition for biomass, land, and water, but also grassland degradation, biodiversity loss, and increased GHGs emissions. Rwanda has the lowest productivity in the region, largely due to inadequate and poor-quality livestock feed resources. To increase animal productivity, promoting forage species with higher nutritional value and better adaptation to drought-prone and poor-fertility soils could be beneficial. Using a mixed-methods approach, the study explores Brachiaria forage adoption and profitability and analyses policy objectives and measures to overcome adoption barriers and promote the transition from subsistence to market-oriented systems. Results show that Brachiaria, although advantageous from an economic point of view, is characterised by very low adoption rates. Furthermore, access to extension programmes is limited and often not supported by adequate incentives. To overcome such barriers, policy interventions should be harmonised and information and knowledge management prioritised, public and private extension and advisory services (EASs) programmes coordinated, agricultural input subsidies increased, and institutional coordination promoted to enhance climate-smart animal feeding.
Enhancing Bilingual/ESL Teachers’ STEM Instruction with Targeted Content and Disciplinary Literacy Professional Development: A Study on Knowledge and Practice Outcomes
Authors: Aguirre-Muñoz Zenaida , Pando Magdalena , Liu Chen
Published: July 2024

Background: The increasing presence of English learners (ELs) in U.S. schools underscores the need for effective instructional strategies tailored to their diverse needs, especially in STEM subjects. Previous research primarily focused on self-reported teacher knowledge and specific curricular programs, often neglecting the integration of content and language knowledge. The study aimed to evaluate the impact of a professional development (PD) program aligned with a previously reported teacher training knowledge framework aimed at improving bilingual/ESL teachers’ subject matter knowledge (SMK), pedagogical knowledge (PK), and disciplinary literacy knowledge (DLK). Methods: This study employed a quasi-experimental design involving 30 teachers in three cohorts, each experiencing different levels of subject matter and disciplinary literacy knowledge. The program was assessed over four time points using multiple-choice tests on math and science knowledge and an instructional strategy rubric to evaluate teaching quality. Results: Significant improvements were observed in both content knowledge and instructional quality across all cohorts, with the greatest gains in cohorts that started the PD with a focus on SMK. Teachers’ understanding of disciplinary literacy and its integration with subject matter knowledge significantly enhanced their teaching effectiveness. Conclusions: The findings suggest that structured PD programs that integrate disciplinary literacy with content knowledge effectively enhance teacher professional knowledge and classroom practices. Starting PD with a strong focus on content knowledge prepares teachers to better apply disciplinary literacy strategies, thereby supporting more effective instruction for ELs. Implications: This study highlights the importance of considering the sequence of professional learning and the integration of content and disciplinary literacy strategies in PD programs. Future PD efforts should focus on these elements to maximize the impact on teacher development and student outcomes in bilingual/ESL settings.
Computation Offloading with Privacy-Preserving in Multi-Access Edge Computing: A Multi-Agent Deep Reinforcement Learning Approach
Authors: Dai Xiang , Luo Zhongqiang , Zhang Wei
Published: July 2024

The rapid development of mobile communication technologies and Internet of Things (IoT) devices has introduced new challenges for multi-access edge computing (MEC). A key issue is how to efficiently manage MEC resources and determine the optimal offloading strategy between edge servers and user devices, while also protecting user privacy and thereby improving the Quality of Service (QoS). To address this issue, this paper investigates a privacy-preserving computation offloading scheme, designed to maximize QoS by comprehensively considering privacy protection, delay, energy consumption, and the task discard rate of user devices. We first formalize the privacy issue by introducing the concept of privacy entropy. Then, based on quantified indicators, a multi-objective optimization problem is established. To find an optimal solution to this problem, this paper proposes a computation offloading algorithm based on the Twin delayed deep deterministic policy gradient (TD3-SN-PER), which integrates clipped double-Q learning, prioritized experience replay, and state normalization techniques. Finally, the proposed method is evaluated through simulation analysis. The experimental results demonstrate that our approach can effectively balance multiple performance metrics to achieve optimal QoS.
THz Wave Power Enhancement Using a Microstrip Line-Based Combiner Integrated with Arrayed UTC-PDs
Authors: Ssali Hussein , Kamiura Yoshiki , Doi Ryo , Agemori Hiroki , Che Ming , Mikami Yuya , Kato Kazutoshi
Published: July 2024

Advancements in semiconductor devices, such as Uni-travelling-carrier photodiodes (UTC-PDs), have played a significant role in the development of Terahertz communication technology. However, the persistent challenge is the limited output power from a single UTC-PD required for practical transmission distances. To enhance the output power, we propose and demonstrate a novel Terahertz wave power combining technique using a photomixer device comprising two arrayed UTC-PDs monolithically integrated with a microstrip line-based 2 × 1 Wilkinson power combiner and a patch antenna on a Silicon Carbide (SiC) substrate at 300 GHz. When the two UTC-PDs are activated at photocurrents of 8 mA and 10 mA, the device exhibits a 7.3 dB increase in power relative to the power obtained when only the 8 mA UTC-PD is activated, and a 4.4 dB increase in power relative to the power obtained with the 10 mA UTC-PD. This implies that power can be enhanced by a factor of N2 if the photocurrent is multiplied by N. Additionally, we demonstrate that the UTC-PD output saturation depends on the space charge effect, which modulates the electric field in the depletion region and results from critical charge density of about 80 kA/cm2 for the device in this work.
Efficient SFC Protection Method against Network Attack Risks in Air Traffic Information Networks
Authors: Yang Yong , Wang Buhong , Tian Jiwei , Luo Peng
Published: July 2024

With the continuous development of the civil aviation industry toward digitalization and intelligence, the closed architecture of traditional air traffic information networks struggles to meet the rapidly growing demands for air traffic services. Network function virtualization (NFV) is one of the key technologies that can address the rigidity of traditional air traffic information networks. NFV technology has facilitated the flexible deployment of air traffic services, but it has also expanded the attack surface of the network. In addressing the network attack risks faced by service function chains (SFCs) in NFV environments, a SFC protection method based on honeypots and backup technology (PBHB) is proposed to reduce the resource cost of protecting air traffic information networks while enhancing network security. Initially, PBHB utilizes the TAPD algorithm to deploy the primary VNFs as closely as possible to the shortest path between the source and destination endpoints, thus aiming to reduce SFC latency and save bandwidth resource costs. Subsequently, the RAHDR algorithm is employed to install honeypot VNFs in each physical platform that is at risk of side-channel attacks, thus updating the deployment status of honeypot VNFs in real time based on the VNF lifecycle in order to offer primary protection for SFCs. Lastly, the BDMPE algorithm was used to calculate the backup scheme with the highest protection efficiency to implement secondary protection for the SFCs that still do not meet the security requirements. Through experiments, the maximum backup limit for SFCs in PBHB was determined, confirming its satisfactory performance across various SFC arrival rates. Furthermore, performance comparisons with other SFC protection methods revealed that PBHB achieves optimizations in resources cost while ensuring SFC security and latency.
Integrated Neural Network Approach for Enhanced Vital Signal Analysis Using CW Radar
Authors: Yoon Won Yeol , Kwon Nam Kyu
Published: July 2024

This study introduces a novel approach for analyzing vital signals using continuous-wave (CW) radar, employing an integrated neural network model to overcome the limitations associated with traditional step-by-step signal processing methods. Conventional methods for vital signal monitoring, such as electrocardiograms (ECGs) and sphygmomanometers, require direct contact and impose constraints on specific scenarios. Conversely, our study primarily focused on non-contact measurement techniques, particularly those using CW radar, which is known for its simplicity but faces challenges such as noise interference and complex signal processing. To address these issues, we propose a temporal convolutional network (TCN)-based framework that seamlessly integrates noise removal, demodulation, and fast Fourier transform (FFT) processes into a single neural network. This integration minimizes cumulative errors and processing time, which are common drawbacks of conventional methods. The TCN was trained using a dataset comprising preprocessed in-phase and quadrature (I/Q) signals from the CW radar and corresponding heart rates measured via ECG. The performance of the proposed method was evaluated based on the L1 loss and accuracy against the moving average of the estimated heart rates. The results indicate that the proposed approach has the potential for efficient and accurate non-contact vital signal analysis, opening new avenues in health monitoring and medical research. Additionally, the integration of CW radar and neural networks in our framework offers a robust and scalable solution, enhancing the practicality of non-contact health monitoring systems in diverse environments. This technology can be leveraged in healthcare robots to provide continuous and unobtrusive monitoring of patients’ vital signs, enabling timely interventions and improving overall patient care.
The Role of Machine Learning in Advanced Biometric Systems
Authors: Ghilom Milkias , Latifi Shahram
Published: July 2024

Today, the significance of biometrics is more pronounced than ever in accurately allowing access to valuable resources, from personal devices to highly sensitive buildings, as well as classified information. Researchers are pushing forward toward devising robust biometric systems with higher accuracy, fewer false positives and false negatives, and better performance. On the other hand, machine learning (ML) has been shown to play a key role in improving such systems. By constantly learning and adapting to users’ changing biometric patterns, ML algorithms can improve accuracy and performance over time. The integration of ML algorithms with biometrics, however, introduces vulnerabilities in such systems. This article investigates the new issues of concern that come about because of the adoption of ML methods in biometric systems. Specifically, techniques to breach biometric systems, namely, data poisoning, model inversion, bias injection, and deepfakes, are discussed. Here, the methodology consisted of conducting a detailed review of the literature in which ML techniques have been adopted in biometrics. In this study, we included all works that have successfully applied ML and reported favorable results after this adoption. These articles not only reported improved numerical results but also provided sound technical justification for this improvement. There were many isolated, unsupported, and unjustified works about the major advantages of ML techniques in improving security, which were excluded from this review. Though briefly mentioned, we did not touch upon encryption/decryption aspects, and, accordingly, cybersecurity was excluded from this study. At the end, recommendations are made to build stronger and more secure systems that benefit from ML adoption while closing the door to adversarial attacks.
Location Privacy Protection in Edge Computing: Co-Design of Differential Privacy and Offloading Mode
Authors: Zhang Guowei , Zhang Shengjian , Man Zhiyi , Cui Chenlin , Hu Wenli
Published: July 2024

Edge computing has emerged as an innovative paradigm that decentralizes computation to the network’s periphery, empowering edge servers to manage user-initiated complex tasks. This strategy alleviates the computational load on end-user devices and increases task processing efficiency. Nonetheless, the task offloading process can introduce a critical vulnerability, as adversaries may infer a user’s location through an analysis of their offloading mode, thereby threatening the user’s location privacy. To counteract this vulnerability, this study introduces differential privacy as a protective mechanism to obscure the user’s offloading mode, thereby safeguarding their location information. This research specifically addresses the issue of location privacy leakage stemming from the correlation between a user’s location and their task offloading ratio. The proposed strategy is based on differential privacy. It aims to increase the efficiency of offloading services and the benefits of task offloading. At the same time, it ensures privacy protection. An innovative optimization technique for task offloading that maintains location privacy is presented. Utilizing this technique, users can make informed offloading decisions, dynamically adjusting the level of obfuscation in response to the state of the wireless channel and their privacy requirements. This study substantiates the feasibility and effectiveness of the proposed mechanism through rigorous theoretical analysis and extensive empirical testing. The numerical results demonstrate that the proposed strategy can achieve a balance between offloading privacy and processing overhead.
Ultra-Broadband Minuscule Polarization Beam Splitter Based on Dual-Core Photonic Crystal Fiber with Two Silver Wires
Authors: Ji Yuxiang , Zou Hui , Du Yuhang , Wang Ningyi
Published: July 2024

This paper presents a polarizing beam splitter (PBS) based on a hexagonal lattice silver-filled photonic crystal fiber (PCF) with two silver wires, which possesses advantages such as a short splitting length, high extinction ratio (ER), and an ultra-wide bandwidth in commonly used communication bands. Utilizing the full-vector finite element method (FV-FEM), thorough investigations were conducted on lasers within the wavelength range of 1.1 to 1.9 μm. The PBS demonstrates a working bandwidth of 725 nm (1.14 to 1.865 μm) under an ultra-short splitting length of 55.3 μm, with an ER exceeding 20 dB, covering all bands of O + E + S + C + L + U optical communication, and achieving a maximum ER of 74.65 dB, where the surface plasmon resonance (SPR) effect of silver metal plays a significant role. It not only features an ultra-short splitting length and an ultra-wide splitting bandwidth but also exhibits excellent manufacturing tolerances and anti-interference capabilities. This polarizing beam splitter represents a promising candidate in communication and may find various applications in optical communication.
A High-Performance and Ultra-Low-Power Accelerator Design for Advanced Deep Learning Algorithms on an FPGA
Authors: Gundrapally Achyuth , Shah Yatrik Ashish , Alnatsheh Nader , Choi Kyuwon Ken
Published: July 2024

This article addresses the growing need in resource-constrained edge computing scenarios for energy-efficient convolutional neural network (CNN) accelerators on mobile Field-Programmable Gate Array (FPGA) systems. In particular, we concentrate on register transfer level (RTL) design flow optimization to improve programming speed and power efficiency. We present a re-configurable accelerator design optimized for CNN-based object-detection applications, especially suitable for mobile FPGA platforms like the Xilinx PYNQ-Z2. By not only optimizing the MAC module using Enhanced clock gating (ECG), the accelerator can also use low-power techniques such as Local explicit clock gating (LECG) and Local explicit clock enable (LECE) in memory modules to efficiently minimize data access and memory utilization. The evaluation using ResNet-20 trained on the CIFAR-10 dataset demonstrated significant improvements in power efficiency consumption (up to 22%) and performance. The findings highlight the importance of using different optimization techniques across multiple hardware modules to achieve better results in real-world applications.
Smart and Sustainable Energy Consumption: A Bibliometric Review and Visualization
Authors: Buri Zsolt , Sipos Csanád , Szűcs Edit , Máté Domicián
Published: July 2024

This paper presents a comprehensive bibliometric review and visualization of smart and sustainable energy consumption, delving into the challenges and opportunities of developing renewable and non-renewable energy sources. The study examines research trends and emerging themes about integrating smart solutions and sustainable energy resource consumption. The analytical methods used involve thoroughly analyzing empirical data, case studies, and review papers to map the research landscape. The results highlight dominant research topics, influential authors, and publication timelines in this field. The review identifies the key challenges in harnessing renewable and non-renewable energy sources, including the need for reliable energy sources, energy storage systems, and smart grid technologies. The paper concludes with insights into the most effective practices for promoting smart and energy-efficient methods while emphasizing the complexity of sustainable energy solutions.
Fuel Cell-Based and Hybrid Power Generation Systems Modelling
Authors: Barbera Orazio
Published: July 2024

The World Economic Forum’s Global Risks Report 2022 identifies climate change as a paramount threat to humanity [...]
Research on the Effect of Fracture Angle on Neutron Logging Results of Shale Gas Reservoirs
Authors: Zhang Xueang , Yang Zhichao , Li Xiaoyan
Published: July 2024

Fracture structures are important natural gas transport spaces in shale gas reservoirs, and their storage state in shale gas reservoirs seriously affects gas production and extraction efficiency. This work uses numerical modeling techniques to investigate the logging response law of the thermal and epithermal neutrons in the gas-containing fracture environment at various angles, applying neutron logging as a technical method. To increase the precision of the evaluation of the natural gas storage condition in shale gas reservoirs, the angle of the fractures’ neutron logging data is analyzed. It is found that even in an environment with the same porosity of the fractures, there are significant differences in the logging results due to the different angles of the fracture alignment: 1. the neutron counts in the high-angle (70–90°) fracture environment are 2.25 times higher than in the low-angle (0–20°), but the diffusion area of the neutrons is only 10.58% of that in the low-angle (0–20°); 2. in the neutron energy spectrum, neutron counts are spreading to the high-energy region (7–13 MeV) along with the increase in the angle of the fracture, and the feature is especially prominent in the approximately vertical (60–90°) fracture environment, which is an increase of 528.12% in comparison with the counts in the approximately horizontal angle (0–30°) environment. The main reason for these differences is the variation in the volume of the fracture within the source radiation. This volumetric difference results from the variation in fracture angles (even though the fracture porosity is the same). In view of the above phenomenon, this paper proposes the concept of “effective fracture volume”, which can intuitively reflect the degree of influence of fracture angle on neutron logging results. Further, based on the unique characteristics of shale gas reservoirs and neutrons, this paper provides important theoretical support for the modification of the porosity of the field operation, the evaluation of the physical characteristics of the gas endowment space, and the assessment.
Optimization of the Performance of PCM Thermal Storage Systems
Authors: Fabbri Giampietro , Greppi Matteo , Amati Federico
Published: July 2024

In this article, we present some optimised geometries for a thermal storage system previously proposed exploiting Phase-changing materials (PCMs). The optimization has been carried out by using a genetic algorithm. We demonstrate that a simple single-parental, mutation-based, single-objective genetic algorithm can be conveniently employed to optimize the geometry of the proposed PCM thermal energy storage system. Optimization I was the one with the least restrictive conditions and, therefore, with the greatest possibility of variation in the channel geometry. While the one with the worst results is Optimization II because of the most restrictive conditions, primarily constant solid/liquid volume. A metal frame increases the surface area by 6.
An Experimental Investigation of Surfactant-Stabilized CO2 Foam Flooding in Carbonate Cores in Reservoir Conditions
Authors: Koyanbayev Madiyar , Hazlett Randy Doyle , Wang Lei , Hashmet Muhammad Rehan
Published: July 2024

Carbon dioxide (CO2) injection for enhanced oil recovery (EOR) has attracted great attention due to its potential to increase ultimate recovery from mature oil reservoirs. Despite the reported efficiency of CO2 in enhancing oil recovery, the high mobility of CO2 in porous media is one of the major issues faced during CO2 EOR projects. Foam injection is a proven approach to overcome CO2 mobility problems such as early gas breakthrough and low sweep efficiency. In this experimental study, we investigated the foam performance of a commercial anionic surfactant, alpha olefin sulfonate (AOS), in carbonate core samples for gas mobility control and oil recovery. Bulk foam screening tests demonstrated that varying surfactant concentrations above a threshold value had an insignificant effect on foam volume and half-life. Moreover, foam stability and capacity decreased with increasing temperature, while variations in salinity over the tested range had a negligible influence on foam properties. The pressure drop across a brine-saturated core sample increased with an increasing concentration of surfactant in the injected brine during foam flooding experiments. Co-injection of CO2 and AOS solution at an optimum concentration and gas fractional flow enhanced oil recovery by 6–10% of the original oil in place (OOIP).
Leveraging Optimal Sparse Sensor Placement to Aggregate a Network of Digital Twins for Nuclear Subsystems
Authors: Karnik Niharika , Wang Congjian , Bhowmik Palash K. , Cogliati Joshua J. , Balderrama Prieto Silvino A. , Xing Changhu , Klishin Andrei A. , Skifton Richard , Moussaoui Musa , Folsom Charles P. , Palmer Joe J. , Sabharwall Piyush , Manohar Krithika , Abdo Mohammad G.
Published: July 2024

Nuclear power plants (NPPs) require continuous monitoring of various systems, structures, and components to ensure safe and efficient operations. The critical safety testing of new fuel compositions and the analysis of the effects of power transients on core temperatures can be achieved through modeling and simulations. They capture the dynamics of the physical phenomenon associated with failure modes and facilitate the creation of digital twins (DTs). Accurate reconstruction of fields of interest (e.g., temperature, pressure, velocity) from sensor measurements is crucial to establish a two-way communication between physical experiments and models. Sensor placement is highly constrained in most nuclear subsystems due to challenging operating conditions and inherent spatial limitations. This study develops optimized data-driven sensor placements for full-field reconstruction within reactor and steam generator subsystems of NPPs. Optimized constrained sensors reconstruct field of interest within a tri-structural isotropic (TRISO) fuel irradiation experiment, a lumped parameter model of a nuclear fuel test rod and a steam generator. The optimization procedure leverages reduced-order models of flow physics to provide a highly accurate full-field reconstruction of responses of interest, noise-induced uncertainty quantification and physically feasible sensor locations. Accurate sensor-based reconstructions establish a foundation for the digital twinning of subsystems, culminating in a comprehensive DT aggregate of an NPP.
Aloe vera―An Extensive Review Focused on Recent Studies
Authors: Catalano Alessia , Ceramella Jessica , Iacopetta Domenico , Marra Maria , Conforti Filomena , Lupi Francesca R. , Gabriele Domenico , Borges Fernanda , Sinicropi Maria Stefania
Published: July 2024

Since ancient times, Aloe vera L. (AV) has attracted scientific interest because of its multiple cosmetic and medicinal properties, attributable to compounds present in leaves and other parts of the plant. The collected literature data show that AV and its products have a beneficial influence on human health, both by topical and oral use, as juice or an extract. Several scientific studies demonstrated the numerous biological activities of AV, including, for instance, antiviral, antimicrobial, antitumor, and antifungal. Moreover, its important antidepressant activity in relation to several diseases, including skin disorders (psoriasis, acne, and so on) and prediabetes, is a growing field of research. This comprehensive review intends to present the most significant and recent studies regarding the plethora of AV’s biological activities and an in-depth analysis exploring the component/s responsible for them. Moreover, its morphology and chemical composition are described, along with some studies regarding the single components of AV available in commerce. Finally, valorization studies and a discussion about the metabolism and toxicological aspects of this “Wonder Plant” are reported.