bluuebunny/crossref_metadata_2025 huggingface dataset:
DNA Gene’s Basic Structure as a Nonperturbative Circuit Quantum Electrodynamics: Is RNA Polymerase II the Quantum Bus of Transcription?
Authors: Riera Aroche Raul , Ortiz García Yveth M. , Sánchez Moreno Esli C. , Enriquez Cervantes José S. , Machado Sulbaran Andrea C. , Riera Leal Annie
Published: October 2024

Previously, we described that Adenine, Thymine, Cytosine, and Guanine nucleobases were superconductors in a quantum superposition of phases on each side of the central hydrogen bond acting as a Josephson Junction. Genomic DNA has two strands wrapped helically around one another, but during transcription, they are separated by the RNA polymerase II to form a molecular condensate called the transcription bubble. Successive steps involve the bubble translocation along the gene body. This work aims to modulate DNA as a combination of n-nonperturbative circuits quantum electrodynamics with nine Radio-Frequency Superconducting Quantum Interference Devices (SQUIDs) inside. A bus can be coupled capacitively to a single-mode microwave resonator. The cavity mode and the bus can mediate long-range, fast interaction between neighboring and distant DNA SQUID qubits. RNA polymerase II produces decoherence during transcription. This enzyme is a multifunctional biomolecular machine working like an artificially engineered device. Phosphorylation catalyzed by protein kinases constitutes the driving force. The coupling between n-phosphorylation pulses and any particular SQUID qubit can be obtained selectively via frequency matching.
A Pilot Study of the Total Cholesterol/High-Density Lipoprotein Ratio as a Prognostic Indicator of Hyperlipidemia-Related Diseases in Dogs and Cats
Authors: Choi Kyuhyung
Published: October 2024

In veterinary medicine, the significance of high-density lipoprotein (HDL) measurements is not as well documented as it is in humans. The HDL level can be measured in dogs as well and, through referring to the normal range, it is possible to find out what this means in relation to various endocrine diseases and hyperlipidemia diseases. The aim of this study is to measure the HDL levels in dogs with various conditions and to evaluate whether the total cholesterol (TC)-to-HDL ratio is effective as a prognostic indicator in various hyperlipidemia and endocrine diseases, which is significant since it is the first trial in dogs. Through a retrospective study design, sixteen client-owned dogs and cats visiting a local private practice were divided into three groups: five dogs without hyperlipidemia or metabolic disease (Group 1), eight dogs with Cushing’s, hypothyroidism, and gallbladder sludge (Group 2), and three cats, including one with diabetes, one with a urinary disorder, and one healthy cat (Group 3). In two dogs, the TC/HDL values were between 2 and 3; in two dogs, the values were between 3 and 4; and in two dogs, the values were between 4 and 5. In three dogs, the TC/HDL values were between 5 and 6 and in three dogs the ratio values were between 6 and 7. The other value was higher than 8. Except for two dogs that showed lower values than 3, all dogs in Group 1 and Group 2 had concurrent endocrine disease. This means that TC/HDL values can be an excellent indicator of endocrine disease in dogs as well. In cats, although it is a very small batch of samples, a high TC/HDL value of 9 points was shown in the cat that had diabetes mellitus. However, for more statistically significant results, a larger sample group for further investigation is needed.
Correction: Jones et al. The Development of a Novel Thin Film Test Method to Evaluate the Rain Erosion Resistance of Polyaspartate-Based Leading Edge Protection Coatings. Coatings 2023, 13, 1849
Authors: Jones Stephen M. , Rehfeld Nadine , Schreiner Claus , Dyer Kirsten
Published: October 2024

In the original publication [...]
Josephson Critical Currents and Related Effects in Ultracold Atomic Superfluid Sytems
Authors: Piselli Verdiana , Pisani Leonardo , Strinati Giancarlo Calvanese
Published: October 2024

The Josephson and Proximity effects play a pivotal role in the design of superconducting devices for the implementation of quantum technology, ranging from the standard Al based to the more exotic twisted high-Tc junctions. Josephson critical currents have been recently investigated also in ultracold atomic systems where a potential barrier acts as a weak link. The unifying feature of the above systems, apart from being superconducting/superfluid, is the presence of spatial inhomogeneity, a feature that has to be properly taken into account in any theoretical approach employed to investigate them. In this work, we review the novel (dubbed LPDA for Local Phase Density Approximation) approach based on a coarse graining of the Bogoliubov–de Gennes (BdG) equations. Non-local and local forms of this coarse graining were utilized when investigating Proximity and Josephson effects. Moreover, the LPDA approach was further developed to include pairing fluctuations at the level of the non-self-consistent t-matrix approximation. The resulting approach, dubbed mLPDA (modified LPDA), can be used whenever inhomegeneity and fluctuations effects simultaneously play an important role.
Integrative Systematics Reveals Cryptic Diversity in Paraphrynus Whip Spiders (Amblypygi: Phrynidae) from Southwestern North America
Authors: Cazzaniga Nicolas , Prendini Lorenzo
Published: October 2024

Due to their continuous growth, reclusive nature, and low vagility, the distributions and species limits of many whip spiders (Amblypygi Thorell, 1883) remain poorly understood, and much cryptic diversity remains unrecognized. Past attempts to separate the historical “forms” of Paraphrynus Moreno, 1940 into morphologically diagnosable species resulted, for example, in the division of Paraphrynus mexicanus (Bilimek, 1867) into three species—the nominotypical form, Paraphrynus cubensis Quintero, 1983, and Paraphrynus carolynae Armas, 2012. Nevertheless, the limitations of conservative morphology continue to hinder progress towards clarifying the diversity of Paraphrynus. One such example concerns P. carolynae, distributed from Arizona to central Mexico as currently defined. Through the acquisition of new, freshly collected material, the discovery of novel morphological characters, and molecular systematics analyses, it became apparent that P. carolynae comprises at least two morphologically diagnosable species. In this present contribution, the northernmost population of P. carolynae occurring in Arizona and California is described as a new species, Paraphrynus tokdod, sp. nov., raising the number of species in the genus to 22. This investigation also revealed more variation than expected in the secondary spine counts of the pedipalps and the trichobothrial counts of leg IV, previously used for species delimitation in Paraphrynus, suggesting that such characters should be used with caution.
Exploring the Feasibility of Opportunistic Diabetic Retinopathy Screening with Handheld Fundus Cameras in Primary Care: Insights from Doctors and Nurses
Authors: Rêgo Sílvia , Monteiro-Soares Matilde , Dutra-Medeiros Marco , Camila Dias Cláudia , Nunes Francisco
Published: October 2024

Aims: This study aims to assess the perspective of doctors and nurses regarding the clinical settings and barriers to implementing opportunistic diabetic retinopathy screening with handheld fundus cameras. Design: This study was a cross-sectional, online questionnaire study. Methods: An online survey was distributed to doctors and nurses working in Portuguese primary care units and hospitals between October and November 2021. The survey assessed current fundus observation practices, potential contexts, and barriers to using handheld fundus cameras. Results: We received 299 eligible responses. About 87% of respondents (n = 255) believe in the clinical utility of handheld fundus cameras to increase patients’ access to diabetes-related retinopathy screening, and 74% (n = 218) attribute utility to identify other eye or systemic diseases. More than a third of participants (37%, n = 111) envisioned using such devices multiple times per week. The main potential barriers identified included limited time (n = 90), equipment cost (n = 48), or the lack of skills in retinal image acquisition (n = 47). Most respondents (94%, n = 275) expected a follow-up recommendation to accompany the telemedicine diagnosis. Conclusions: Doctors and nurses support the use of handheld fundus cameras. However, to optimize their implementation, some strategies should be considered, including training, telemedicine-based diagnosis, and support for follow-up through accessible, user-friendly, and efficient information systems.
Advances in Diagnosis of Skin and Superficial Tissue Disorders—“Old and Emerging” Diagnostic Tools
Authors: Ricci Costantino
Published: October 2024

Skin and superficial tissue disorders (SSTDs) are some of the most common diseases affecting humans [...]
Exploring the Role of Genetic and Environmental Features in Colorectal Cancer Development: An Agent-Based Approach
Authors: Ledda Marco , Pluchino Alessandro , Ragusa Marco
Published: October 2024

The complexity of issues in cancer research has led to the introduction of powerful computational tools to help experimental in vivo and in vitro methods. These tools, which typically focus on studying cell behavior and dynamic cell populations, range from systems of differential equations that are solved numerically to lattice models and agent-based simulations. In particular, agent-based models (ABMs) are increasingly used due to their ability to incorporate multi-scale features, ranging from the individual to the population level. This approach allows for the combination of statistically aggregated assumptions with individual heterogeneity. In this work, we present an ABM that simulates tumor progression in a colonic crypt, to provide an experimental in silico environment for testing results achieved in traditional laboratory research and developing alternative scenarios of tumor development. The model also allows some speculations about causal relationships in biologically inspired systems.
A Three-Dimensional Time-Varying Channel Model for THz UAV-Based Dual-Mobility Channels
Authors: Zhang Kai , Zhang Fenglei , Li Yongjun , Wang Xiang , Yang Zhaohui , Liu Yuanhao , Zhang Changming , Li Xin
Published: October 2024

Unmanned aerial vehicle (UAV) as an aerial base station or relay device is a promising technology to rapidly provide wireless connectivity to ground device. Given UAV’s agility and mobility, ground user’s mobility, a key question is how to analyze and value the performance of UAV-based wireless channel in the terahertz (THz) band. In this paper, a three-dimensional (3D) time-varying channel model is proposed for UAV-based dual-mobility wireless channels based on geometric channel model theory in THz band. In this proposed channel model, the small-scale fading (e.g., scattering fading and reflection fading) on rough surfaces of communication environment and the atmospheric molecule absorption attenuations are considered in THz band. Moreover, the statistical properties of the proposed channel model, including path loss, time autocorrelation function (T-ACF) and Doppler power spectrum density (DPSD), have been derived and the impact of several important UAV-related and vehicle-related parameters have been investigated and compared to millimeter wave (mm-wave) band. Furthermore, the correctness of the proposed channel model has been verified via simulation, and some useful observations are provided for the system design of THz UAV-based dual-mobility wireless communication systems.
Pseudo-Quantum Electrodynamics: 30 Years of Reduced QED
Authors: Marino Eduardo C. , Nascimento Leandro O. , Alves Van Sérgio , Alves Danilo T.
Published: October 2024

Charged quasiparticles, which are constrained to move on a plane, interact by means of electromagnetic (EM) fields which are not subject to this constraint, living, thus, in three-dimensional space. We have, consequently, a hybrid situation where the particles of a given system and the EM fields (through which they interact) live in different dimensions. Pseudo-Quantum Electrodynamics (PQED) is a U(1) gauge field theory that, despite being strictly formulated in two-dimensional space, precisely describes the real EM interaction of charged particles confined to a plane. PQED is completely different from QED(2 + 1), namely, Quantum Electrodynamics of a planar gauge field. It produces, for instance, the correct 1/r Coulomb potential between static charges, whereas QED(2 + 1) produces lnr potential. In spite of possessing a nonlocal Lagrangian, it has been shown that PQED preserves both causality and unitarity, as well as the Huygens principle. PQED has been applied successfully to describe the EM interaction of numerous systems containing charged particles constrained to move on a plane. Among these are p-electrons in graphene, silicene, and transition-metal dichalcogenides; systems exhibiting the Valley Quantum Hall Effect; systems inside cavities; and bosonization in (2 + 1)D. Here, we present a review article on PQED (also known as Reduced Quantum Electrodynamics).
Hybrid Boson Sampling
Authors: Kocharovsky Vitaly
Published: October 2024

We propose boson sampling from a system of coupled photons and Bose–Einstein condensed atoms placed inside a multi-mode cavity as a simulation process testing the quantum advantage of quantum systems over classical computers. Consider a two-level atomic transition far-detuned from photon frequency. An atom–photon scattering and interatomic collisions provide interactions that create quasiparticles and excite atoms and photons into squeezed entangled states, orthogonal to the atomic condensate and classical field driving the two-level transition, respectively. We find a joint probability distribution of atom and photon numbers within a quasi-equilibrium model via a hafnian of an extended covariance matrix. It shows a sampling statistics that is ♯P-hard for computing, even if only photon numbers are sampled. Merging cavity-QED and quantum-gas technologies into a hybrid boson sampling setup has the potential to overcome the limitations of separate, photon or atom, sampling schemes and reveal quantum advantage.
Routing Algorithms for SDM Flexible Optical Networks
Authors: Olszewski Ireneusz , Szcześniak Ireneusz , Woźna-Szcześniak Bożena
Published: October 2024

This paper considers the online routing, modulation, spectrum, and core allocation problem in elastic optical networks. Three algorithms are proposed to minimize the bandwidth blocking probability while taking into account the impact of interference from established lightpaths. These algorithms are based on a sequence of alternative paths, ordered in terms of increasing lengths, determined by Yen’s algorithm. Each of the algorithms for the selected single or dual lightpath enforces the constraints of spectrum continuity, contiguity of the slots, and non-overlapping of the spectra with the established lightpaths, maximizes the number of bits per symbol, and selects a specific core on each link of the path. Simulation studies performed for two sample networks showed that the crosstalk has a significant impact on the bandwidth blocking probability. The best results were obtained by iterating over all paths and all slots, selecting the lightpath with the lowest average crosstalk per slot, consisting of the most loaded cores.
Employment Subsidies and Job Insertion of Higher Education Graduates in the Labor Market
Authors: Khayati Anis , Hani Umme , Alam Md Shabbir , Sha Nadia , Terzi Chokri
Published: October 2024

This paper uses data from the 24 governorates in Tunisia over the period 2012–2020 to study the relationship between job insertion of higher education graduates into the formal labor market and a number of independent variables, namely active labor supply, labor demand, an active labor market policy program (named the CIVP program), and the waiting time for job insertion. The balanced panel, which includes 216 observations for each variable, was the basis of different tests and estimations. The results of the tests allowed the assessment of a fixed effects model and a long-term relationship using FMOLS and VECM models. Results show that, in the long term, active labor supply and the CIVP program have positive effects on the job insertion of higher education graduates. In contrast, the results in the short term do not appear significant, with a negative effect of the CIVP program that reflects the fact that companies exploit most of the benefits of this wage subsidy program on job insertion before final recruitment. Using the ARDL model, the individual results by governate show specific differences across areas.
Investigating Teachers’ Use of an AI-Enabled System and Their Perceptions of AI Integration in Science Classrooms: A Case Study
Authors: Shi Lehong , Ding Ai-Chu (Elisha) , Choi Ikseon
Published: October 2024

Recent research indicates the significant potential of artificial intelligence (AI) in enhancing teachers’ instructional practices in areas such as lesson planning, personalized teacher intervention and feedback, and performance assessment. To fully realize the potential of AI in teaching, it is crucial to understand how teachers innovatively apply and critically evaluate AI applications in their teaching practices. However, there is a research gap in investigating how teachers use various features of an AI-enabled system and their perceptions of AI integration in teaching to promote teachers’ effective AI integration practices. Employing an exploratory case study design, we investigated how six science teachers utilized an AI-enabled inquiry intelligent tutoring system (Inq-ITS) within their teaching and examined their perceptions of AI integration. Classroom observations and teacher interview data were collected. When using Inq-ITS functionalities, two teachers with a pedagogical orientation of teacher-guided scientific inquiry mainly engaged with its virtual tutor and teacher report summary features. Conversely, four teachers, practicing the pedagogical orientation of AI-guided scientific inquiry, relied on the AI system to guide student learning, interacting intensively with its features, particularly real-time teacher alerts and teacher inquiry practice support. Regardless of the differences in using Inq-ITS features, all teachers recognized the potential benefits of pedagogical change and encountered various challenges. This analysis also revealed that teachers exhibited distinct perceptions regarding the role of Inq-ITS integration in their teaching. Teachers who adopted a teacher-guided pedagogical orientation perceived the Inq-ITS as a supporting tool that enhanced traditional teaching methods. In contrast, those with an AI-guided pedagogical orientation viewed the Inq-ITS as akin to a teaching assistant and a pedagogical collaborator. The findings underscored the importance of enhancing teachers’ realization of the pedagogical affordance of AI in teaching through their use of AI functionalities. It is essential to consider teachers’ diverse perceptions of AI integration when promoting their integration of AI into teaching practices.
Correction: Roy, K.; Kim, M.-K. Applying Quantum Search Algorithm to Select Energy-Efficient Cluster Heads in Wireless Sensor Networks. Electronics 2023, 12, 63
Authors: Roy Kripanita , Kim Myung-Kyun
Published: October 2024

In the original publication [...]
Design of a Fast Robotic Total Station Through Ad Hoc Virtual Experiments and Its Digital Twin
Authors: Simas Henrique , Di Gregorio Raffaele , Simoni Roberto
Published: October 2024

The dynamic performances of an innovative robotic total station (RTS) are assessed while tracking a moving target; also, the results of these performance evaluations are exploited to design its control system. The proposed methodology is novel and uses ad hoc virtual experiments implemented on the digital twin of the studied RTS. This methodology is general and is also applicable for the design of other mechatronic systems. The proposed ad hoc virtual experiments constitute a benchmark for assessing the tracking performances of pointing systems. The application of this methodology to the studied RTS will help complete the RTS’s design by determining the most suitable actuators and the control system constants necessary to obtain the assigned dynamic performances. A 3D-printed prototype of the designed RTS was built and is shown in this paper.
Transformer-Based GAN with Multi-STFT for Rotating Machinery Vibration Data Analysis
Authors: Lee Seokchae , Jeong Hoejun , Kwon Jangwoo
Published: October 2024

Prognostics and health management of general rotating machinery have been studied over time to improve system stability. Recently, the excellent abnormal diagnosis performance of artificial intelligence (AI) was demonstrated, and therefore, AI-based intelligent diagnosis is now being implemented in these systems. AI models are trained using large volumes of data. Therefore, we propose a transformer-based generative adversarial network (GAN) model with a multi-resolution short-time Fourier transform (multi-STFT) loss function to augment the vibration data of rotating machinery to facilitate the successful learning of deep learning models. We constructed a model with a conditional GAN structure, which is transformer based, for learning the feature points of vibration data in the time-series domain. In addition, we applied the multi-STFT loss function to capture the frequency features of the vibration data. The generated data, which adequately captured the frequency features, were used to augment the training data to improve the performance of a deep learning classifier. Furthermore, by visualizing the generated vibration data and comparing the visualizations to those of the vibration data obtained from real machinery, we demonstrated that the generated data were indistinguishable from the actual data.
Hardware Implementation of a 2D Chaotic Map-Based Audio Encryption System Using S-Box
Authors: Elrefai Hisham M. , Sayed Wafaa S. , Said Lobna A.
Published: October 2024

This paper presents a hardware-based audio encryption system using a 2D chaotic map and dynamic S-box design implemented on an Artix-7 FPGA platform. Three distinct chaotic maps—logistic–fraction (2D-LF), logistic–sine (2D-LS), and fraction–sine (2D-FS)—were investigated and implemented on an FPGA. The 2D-LF map was employed in the encryption system for its throughput and power efficiency performance. The proposed encryption system benefits from the randomness of chaotic sequences for block permutation and S-box substitution to enhance the diffusion and confusion properties of the encrypted speech signal. The system’s encryption strength is validated through performance evaluations, using the mean squared error (MSE), signal-to-noise ratio (SNR), correlation coefficients, and NIST randomness tests, which confirm the unpredictability of the encrypted speech signal. The hardware implementation results show a throughput of 2880 Mbps and power consumption of 0.13 W.
An Arrhenius-Based Simulation Tool for Predicting Aging of Lithium Manganese Dioxide Primary Batteries in Implantable Medical Devices
Authors: Doosthosseini Mahsa , Khajeh Talkhoncheh Mahdi , Silberberg Jeffrey L. , Ghods Hamed
Published: October 2024

This article presents a novel aging-coupled predictive thermo-electrical dynamic modeling tool tailored for primary lithium manganese dioxide (Li-MnO2) batteries in active implantable medical devices (AIMDs). The aging mechanisms of rechargeable lithium batteries are well documented using computationally intensive physics-based models, unsuitable for real-time onboard monitoring in AIMDs due to their high demands. There is a critical need for efficient, less demanding modeling tools for accurate battery health monitoring and end-of-life prediction as well as battery safety assessment in these devices. The presented model in this article simulates the battery terminal voltage, remaining capacity, temperature, and aging during active discharge, making it suitable for real-time health monitoring and end-of-life prediction. We incorporate a first-order dynamic for internal resistance growth, influenced by time, temperature, discharge depth, and load current. By adopting Arrhenius-type kinetics and polynomial relationships, this model effectively simulates the combined impact of these variables on battery aging under diverse operational conditions. The simulation handles both the continuous micro-ampere-level demands necessary for device housekeeping and periodic high-rate pulses needed for therapeutic functions, at a constant ambient temperature of 37 °C, mimicking human body conditions. Our findings reveal a gradual, nonlinear increase in internal resistance as the battery ages, rising by an order of magnitude over a period of 5 years. Sensitivity analysis shows that as the battery ages and load current increases, the terminal voltage becomes increasingly sensitive to internal resistance. Specifically, at defibrillation events, the ∂V∂R trajectory dramatically increases from 10−12 to 10−8, indicating a fourth-order-of-magnitude enhancement in sensitivity. A model verification against experimental data shows an R2 value of 0.9506, indicating a high level of accuracy in predicting the Li-MnO2 cell terminal voltage. This modeling tool offers a comprehensive framework for effectively monitoring and optimizing battery life in AIMDs, therefore enhancing patient safety.
EV Smart-Charging Strategy for Power Management in Distribution Grid with High Penetration of Distributed Generation
Authors: Maia Geraldo L. , Santos Caio C. L. , Nunes Paulo R. M. , Castro José F. C. , Marques Davidson C. , Medeiros Luiz H. A. De , Limongi Leonardo R. , Brito Márcio E. C. , Dantas Nicolau K. L. , Filho Antônio V. M. L. , Fernandes Amanda L. , Chai Jiyong , Zhang Chenxin
Published: October 2024

Accelerated environmental impacts are a growing concern in the modern world. Electric mobility and the transition to a cleaner energy matrix have become increasingly discussed topics. In this context, this work presents a framework for controlling an electric vehicle (EV)-charging station integrated into a microgrid application as a basis for creating the infrastructure integrated into a smart grid concept. Considering the electrification of the transportation sector future perspectives, a brief review is conducted on the impacts of EV fleet growth in different countries and how smart-charging technologies are identified as solutions for mitigating the negative effects of energy and power consumption associated with EV-charging stations. An analysis of the technical characteristics and the tools that enable the deployment of a fleet-charging operator are examined, specifically focusing on the communication protocol for EVs, such as the OCPP (Open Charge Point Protocol) parameterization/configuration. A new EV-charging station control method is proposed to manage the impacts of distributed solar photovoltaic generation and mitigate the effects of the duck curve. Finally, an integration architecture via IEC 61850 for these elements is proposed, in a practical implementation for variable power control, considering different strategies to deal with distributed generation impact using EV-fleet-charging power demand dynamic management.
The Enhancement of Machine Learning-Based Engine Models Through the Integration of Analytical Functions
Authors: Brusa Alessandro , Shethia Fenil Panalal , Petrone Boris , Cavina Nicolò , Moro Davide , Galasso Giovanni , Kitsopanidis Ioannis
Published: October 2024

The integration of analytical functions into machine learning-based engine models represents a significant advancement in predictive performance and operational efficiency. This paper focuses on the development of hybrid approaches to model engine combustion and temperature indices and on the synergistic effects of combining traditional analytical methods with modern machine learning techniques (such as artificial neural networks) to enhance the accuracy and robustness of such models. The main innovative contribution of this paper is the integration of analytical functions to improve the extrapolation capabilities of the data-driven models. In this work, it is demonstrated that the integrated models achieve superior predictive accuracy and generalization performance across dynamic engine operating conditions, with respect to purely neural network-based models. Furthermore, the analytical corrective functions force the output of the complete model to follow a physical trend and to assume consistent values also outside the domain of values assumed by the input features during the training procedure of the neural networks. This study highlights the potential of this integrative approach based on the implementation of the effects superposition principle. Such an approach also allows us to solve one of the intrinsic issues of data-driven modeling, without increasing the complexity of the training data’s collection and pre-processing.
Autonomous and Electric Vehicles in Urban Living Labs: Smart Mobility Strategies for the Future
Authors: Mendoza-Armenta Axel A. , Félix-Herrán Luis C. , Silvestri Bartolomeo , Valderrama-Solano Andrea C. , Tudon-Martínez Juan C. , Roccotelli Michele , Lozoya-Santos Jorge de J.
Published: October 2024

The deployment of electric, connected, and autonomous vehicles on public roads presents a significant challenge that can be addressed through previously established frameworks developed globally for implementing these technologies as part of an urban living lab (ULL). This systematic review, based on records from four distinct databases, focuses on projects that have conducted deployments of self-driving technologies in streets within urban environments. The review describes relevant information about various initiatives, including a classification of the stages of development reached according to the urban area covered, safety considerations, and lessons learned for optimal deployment. On-board sensing technology, digital infrastructure, and energy and communication systems emerge as the essential components of a ULL with autonomous vehicles (AVs). A crucial goal for smart cities is ensuring the scalability of large-scale deployments of such ULLs for safe, clean, and future mobility experimentation. This can only be achieved through effective coordination among academia, government, industry, and society to guarantee the successful integration of multiple projects in a unique environment.
Measurement and Modeling of Self-Directed Channel (SDC) Memristors: An Extensive Study
Authors: Bednarz Karol , Garda Bartłomiej
Published: October 2024

This study systematically addresses the challenge of accurately modeling memristors, focusing on four distinct types doped with tungsten, tin, chromium, and carbon, fabricated by Knowm Inc. A comprehensive characterization is performed by subjecting the devices to sinusoidal excitations with varying frequencies and amplitudes, followed by data averaging and high-frequency filtering. The resulting measurements are fitted using three prominent memristor models: VTEAM, MMS, and Yakopcic. Additional bespoke modifications are assessed. These models, typically formulated as coupled algebraic differential equations integrating electrical quantities (voltage and current) with internal state variables governing device dynamics, are optimized using two robust approaches: (1) interior-point optimization with gradient-based search, and (2) Nelder–Mead gradient-free optimization, both with box constraints applied. A thorough comparison and discussion of the optimized model parameters ensue, accompanied by an examination of the sensitivity to diverse frequency and amplitude ranges. The findings inform conclusions and provide a foundation for future refinements, underscoring the importance of multi-model evaluation and advanced optimization strategies in precise memristor modeling. The presented methodology offers a valuable framework for elucidating optimal modeling paradigms tailored to specific memristor architectures and operating regimes, ultimately enhancing their integration in emerging neuromorphic and computational applications.
Climate Change and the Impacts on Power and Energy Systems
Authors: Mohammadi Younes , Polajžer Boštjan , Palstev Aleksey , Khodadad Davood
Published: October 2024

This collection, extracted from the Special Issue “Climate Change and the Impacts on Power and Energy Systems”, features ten papers that address key topics related to the resilience and adaptation of electrical power and energy systems in response to climate change [...]
An Empirical Study of the Economic Net-Zero Energy Mix in Industrial Complexes
Authors: Kang MinHyeok , Park SooJin , Cho KangWook
Published: October 2024

This study examines the optimal energy mix for industrial complexes by incorporating renewable energy systems, decarbonization strategies, and sector coupling technologies. Using data from the Balan Industrial Complex in Korea, five energy scenarios were evaluated, ranging from conventional systems (Scenario 1) to advanced renewable configurations (Scenario 5). The results show that Scenario 5, which integrates sector coupling systems and decarbonization technologies, is the most cost-effective and environmentally sustainable. Scenario 5 achieves the lowest Net Present Cost (NPC), and significantly reduces CO2 emissions. Furthermore, an analysis of electricity prices and CO2 costs from Korea, the United States, and Germany highlights the critical role of regional electricity tariffs and carbon pricing in determining the economic feasibility of energy systems. While renewable setups require higher initial investments, Scenario 5 proves to be the most economically viable over time, offering both cost savings and environmental benefits. These findings provide valuable insights for policymakers and industry leaders, emphasizing the importance of customized strategies to optimize energy systems in industrial applications.
Optimization of Hydrogen Production System Performance Using Photovoltaic/Thermal-Coupled PEM
Authors: Li Guorong , Song Chen , Han Guang , Chen Zihao , Huang Jiwei
Published: October 2024

A proton exchange membrane electrolyzer can effectively utilize the electricity generated by intermittent solar power. Different methods of generating electricity may have different efficiencies and hydrogen production rates. Two coupled systems, namely, PV/T- and CPV/T-coupling PEMEC, respectively, are presented and compared in this study. A maximum power point tracking algorithm for the photovoltaic system is employed, and simulations are conducted based on the solar irradiation intensity and ambient temperature of a specific location on a particular day. The simulation results indicate that the hydrogen production is relatively high between 11:00 and 16:00, with a peak between 12:00 and 13:00. The maximum hydrogen production rate is 99.11 g/s and 29.02 g/s for the CPV/T-PEM and PV/T-PEM systems. The maximum energy efficiency of hydrogen production in CPV/T-PEM and PV/T-PEM systems is 66.7% and 70.6%. Under conditions of high solar irradiation intensity and ambient temperature, the system demonstrates higher total efficiency and greater hydrogen production. The CPV/T-PEM system achieves a maximum hydrogen production rate of 2240.41 kg/d, with a standard coal saving rate of 15.5 tons/day and a CO2 reduction rate of 38.0 tons/day. Compared to the PV/T-PEM system, the CPV/T-PEM system exhibits a higher hydrogen production rate. These findings provide valuable insights into the engineering application of photovoltaic/thermal-coupled hydrogen production technology and contribute to the advancement of this field.
Correction: Melgaard et al. Fault Detection and Diagnosis Encyclopedia for Building Systems: A Systematic Review. Energies 2022, 15, 4366
Authors: Melgaard Simon P. , Andersen Kamilla H. , Marszal-Pomianowska Anna , Jensen Rasmus L. , Heiselberg Per K.
Published: October 2024

Error in Table [...]
The Analysis of the Thermal Processes Occurring in the Contacts of Vacuum Switches During the Conduction of Short-Circuit Currents
Authors: Nowak Karol , Nowak Krzysztof , Rabczak Slawomir
Published: October 2024

This article presents the results of research on the thermal state of vacuum switch contacts during the conduction of short-circuit currents. This state is directly related to the value of the flowing current and the operating conditions of the switch. These conditions are mildest in the case of the conduction of operating currents through closed contacts. The situation worsens significantly when short-circuit currents are conducted, and the greatest destructive effects occur during commutation processes. Exceeding a certain level of contact destruction usually leads to the loss of the switching capacity of the switch. In vacuum switches, tracking the thermal state of the contacts is particularly difficult due to the inaccessibility of transducers or measurement sensors inside the chamber. In such a case, simulation studies verified by experimental results are important. This paper presents the results of such studies, directed at their practical implementation in the design and operation of vacuum switches. Simulation studies were conducted to analyze the thermal processes occurring in the contacts of vacuum switches during the conduction of short-circuit currents. Special attention was paid to the influence of contact parameters on the thermal processes occurring during the conduction of short-circuit currents. In addition to simulations, experimental studies were carried out to verify the simulation results. Ultimately, the research results presented are intended to provide practical knowledge of the design and operation of vacuum switches, particularly with regard to the contact heating processes during the conduction of short-circuit currents.
Elephant Grass Cultivar BRS Capiaçu as Sustainable Biomass for Energy Generation in the Amazon Biome of the Mato Grosso State
Authors: Beber Roberto Carlos , Turini Camila da Silva , Beber Vinicius Carrillo , Nogueira Roberta Martins , Pires Evaldo Martins
Published: October 2024

Sustainable biomasses are vital to ensure preservation of the Amazon biome within the Mato Grosso State whilst enabling energy generation for the region and its population. Here, the potential of the elephant grass cultivar BRS Capiaçu as an alternative to replace native forest wood as biomass for energy generation is investigated, considering the whole process from plant cultivation to biomass characterisation in terms of productivity of green and dry mass per hectare; density, moisture, ash, volatile and fixed carbon content, as well as higher heating value (HHV). MANOVA indicates that the effects of plant parts and age on density and proximate analysis parameters are influenced by the plant parts and age interaction, whereas HHV can be considered similar between them. The cultivar BRS Capiaçu showed suitable energetic values (17,922 < HHV < 18,918 kJ.kg−1) compared to that of native Amazon wood. Energetic results combined with cultivation outputs of high productivity (dry mass production of 44.1 tonnes.ha−1 at 180 days) with a short cutting interval (3 months), adaptation to the region’s climate and soil, and the possibility of cultivation in areas currently consolidated for agriculture demonstrate the potential of BRS Capiaçu as biomass to reduce native wood usage and deforestation rates.
Water Status Detection Method Based on Water Balance Model for High-Power Fuel Cell Systems
Authors: Zhong Yiyu , Yang Yanbo , Yao Naiyuan , Ma Tiancai , Lin Weikang
Published: October 2024

With the gradually accelerating pace of global decarbonization, highly efficient and clean proton exchange membrane fuel cells (PEMFCs) are considered to be an energy solution for the future. During the operation of a fuel cell, it is necessary to keep the internal proton exchange membrane in a good state of hydration, so an appropriate method of detecting the hydration state is essential. At present, fuel cell systems are rapidly developing towards high power, but methods for detecting the hydration state of high-power fuel cell systems are still relatively lacking. Therefore, this paper studies the hydration state of high-power fuel cell systems and builds a condensation tail-gas water collection device for calculating the water flow out of a fuel cell system, deriving the hydration status inside the high-power fuel cell system. To verify the proposed water balance model, a series of experiments were conducted based on controlled variables such as working temperature, air metering ratio, and load current. Experiments were conducted on a 100 KW fuel cell system to collect water flow from the fuel cell system. Finally, based on the experimental data, the change rate of the internal water content of the fuel cell system under different conditions was calculated. The results show that, under the same load current, as the working temperature and air metering ratio increase, the change rate of the internal water content of the fuel cell system gradually decreases. Therefore, at low power, it is necessary to maintain an appropriate working temperature, while at high power, maintaining an appropriate air metering ratio is more important.
WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images
Authors: Nieradzik Lars , Stephani Henrike , Sieburg-Rockel Jördis , Helmling Stephanie , Olbrich Andrea , Wrage Stephanie , Keuper Janis
Published: October 2024

Wood species identification plays a crucial role in various industries, from ensuring the legality of timber products to advancing ecological conservation efforts. This paper introduces WoodYOLO, a novel object detection algorithm specifically designed for microscopic wood fiber analysis. Our approach adapts the YOLO architecture to address the challenges posed by large, high-resolution microscopy images and the need for high recall in localization of the cell type of interest (vessel elements). Our results show that WoodYOLO significantly outperforms state-of-the-art models, achieving performance gains of 12.9% and 6.5% in F2 score over YOLOv10 and YOLOv7, respectively. This improvement in automated wood cell type localization capabilities contributes to enhancing regulatory compliance, supporting sustainable forestry practices, and promoting biodiversity conservation efforts globally.
Exploring Effects of Nutrient Availability, Species Composition, Stand Age, and Mesofaunal Exclusion on Leaf Litter Decomposition in Northern Hardwood Forests
Authors: Young Alexander R. , Innusa Brianne N. , Biché Rick , Yanai Ruth D.
Published: October 2024

In northern hardwood forests, litter decomposition might be affected by nutrient availability, species composition, stand age, or access by decomposers. We investigated these factors at the Bartlett Experimental Forest in New Hampshire. Leaf litter of early and late successional species was collected from four stands that had full factorial nitrogen and phosphorus additions to the soil and were deployed in bags of two mesh sizes (63 µm and 2 mm) in two young and two mature stands. Litter bags were collected three times over the next 2 years, and mass loss was described as an exponential function of time represented by a thermal sum. Litter from young stands had higher initial N and P concentrations and decomposed more quickly than litter from mature stands (p = 0.005), regardless of where it was deployed. Litter decomposed more quickly in fine mesh bags that excluded mesofauna (p < 0.001), which might be explained by the greater rigidity of the large mesh material making poor contact with the soil. Neither nutrient addition (p = 0.94 for N, p = 0.26 for P) nor the age of the stand in which bags were deployed (p = 0.36) had a detectable effect on rates of litter decomposition.
Savanna Plants Have a Lower Hydraulic Efficiency than Co-Occurring Species in a Rainforest
Authors: Peng Xiaorong , Yang Da , Wang Qin , Tian Yu , Yan Ke , Zhang Yunbing , Yang Shijian , Zhang Jiaolin
Published: October 2024

A plant species can have diverse hydraulic strategies to adapt to different environments. However, the water transport divergence of co-occurring species in contrasting habitats remains poorly studied but is important for understanding their ecophysiology adaptation to their environments. Here, we investigated whole-branch, stem and leaf water transport strategies and associated morphology traits of 11 co-occurring plant species in Yuanjiang valley-type savanna (YJ) with dry–hot habitats and Xishuangbanna tropical seasonal rainforest (XSBN) with wet–hot habits and tested the hypothesis that plants in YJ have a lower water transport efficiency than co-occurring species in XSBN. We found high variation in whole-branch, stem and leaf hydraulic conductance (Kshoot; Kstem and Kleaf) between YJ and XSBN, and that Kstem was significantly higher than Kleaf in these two sites (Kstem/Kleaf: 16.77 in YJ and 6.72 in XSBN). These plants in YJ with significantly lower Kshoot and Kleaf but higher sapwood density (WD) and leaf mass per area (LMA) showed a lower water transport efficiency regarding less water loss and the adaptation to the dry–hot habitat compared to co-occurring species in XSBN. In contrast, these co-occurring plants in XSBN with higher Kshoot and Kleaf but lower WD and LMA tended to maximize water transport efficiency and thus growth potential in the wet–hot habitat. Our findings suggest that these co-occurring species employ divergent hydraulic efficiency across YJ and XSBN so that they can benefit from the contrasting hydraulic strategies in adaptation to their respective habitats.
The Role of Urban Forest Policies in Driving Green Innovation: Evidence from Chinese Cities
Authors: Xia Xingneng , Hui Yuji , Chen Yaqian , Zhang Sheng
Published: October 2024

Urban forest policies have garnered increasing global attention for their critical role in providing key ecosystem services such as carbon sequestration, air pollution control, microclimate regulation, and biodiversity enhancement, as well as their potential to drive green innovation and sustainable urban development. This study utilized panel data from 273 Chinese cities between 2000 and 2022, employing a quasi-natural experiment and a difference-in-differences (DID) model to systematically evaluate the impact of the National Forest City Policy (NFCP) on urban green innovation. The results indicate that NFCP significantly enhances urban green innovation, with these findings remaining robust across a series of validation tests. Mechanism analysis revealed that the policy fosters green innovation by increasing environmental attention, facilitating talent aggregation, and reducing carbon emissions. Furthermore, heterogeneity analysis showed that the policy’s effects are more pronounced in small- and medium-sized cities, non-transportation hub cities, and economically developed regions. Based on these findings, this paper offers recommendations for optimizing policy implementation across different city types to further promote sustainable urban green economic development. This study broadens the research perspective on the relationship between urban policies and green innovation, providing more precise decision-making guidance for policymakers while also highlighting the important role urban forests play in enhancing ecosystem services and driving sustainable urban growth.