bluuebunny/crossref_metadata_2025 huggingface dataset:
Commodity Prices and the Brazilian Stock Market: Evidence from a Structural VAR Model
Authors: Ekanayake E. M.
Published: December 2024

Brazil is a resource-rich economy that relies heavily on the exports of several important commodities. The variability of commodity prices affects both the economy and the stock market. This study investigates the relationship between commodity price shocks and stock returns in Brazil using a structural vector autoregressive (SVAR) model. This study uses monthly data on prices of five major export commodities, stock returns, and several control variables, covering the period from January 2010 to December 2022. To account for the Brazilian economic crisis between 2014 and 2016, we have analyzed the effects of commodity prices on stock prices in three different time periods, namely, before the economic crisis (January 2010–March 2014), during the economic crisis (April 2014–December 2016), and after the economic crisis (January 2017–December 2022). The empirical results of this study provide evidence to conclude that stock returns increase following a positive global commodity price shock or a positive exchange rate shock. The effects are more noticeable during the economic crisis in Brazil. The results also show that the volatility of Brazilian stock returns is mostly explained by global oil prices and exchange rate movements in the long run.
New Predictive Models for the Computation of Reinforced Concrete Columns Shear Strength
Authors: Ioannou Anthos I. , Galbraith David , Bakas Nikolaos , Markou George , Bellos John
Published: December 2024

The assessment methods for estimating the behavior of the complex mechanics of reinforced concrete (RC) structural elements were primarily based on experimental investigation, followed by the collective evaluation of experimental databases from the available literature. There is still a lot of uncertainty in relation to the strength and deformability criteria that have been derived from tests due to the differences in the experimental test setups of the individual research studies that are being fed into the databases used to derive predictive models. This research work focuses on structural elements that exhibit pronounced strength degradation with plastic deformation and brittle failure characteristics. The study’s focus is on evaluating existing models that predict the shear strength of RC columns, which take into account important factors including the structural element’s ductility and axial load, as well as the contributions of specific resistance mechanisms like that of concrete, transverse, and longitudinal reinforcement. Significantly improved predictive models are proposed herein through the implementation of machine learning (ML) algorithms on refined datasets. Three ML models, LREGR, POLYREG-HYT, and XGBoost-HYT-CV, were used to develop different predictive models that were able to compute the shear strength of RC columns. According to the numerical findings, POLYREG-HYT- and XGBoost-HYT-CV-derived models outperformed other ML models in predicting the shear strength of rectangular RC columns with the correlation coefficient having a value R greater than 99% and minimal errors. It was also found that the newly proposed predictive model derived a 2-fold improvement in terms of the correlation coefficient compared to the best available equation in international literature.
Syntheses and Crystal Structures of Two Metal–Organic Frameworks Formed from Cd2+ Ions Bridged by Long, Flexible 1,7-bis(4-Pyridyl)heptane Ligands with Different Counter-Ions
Authors: Plater M. John , De Silva Ben M. , Foreman Mark R. St J. , Harrison William T. A.
Published: December 2024

The ethanol–water layered syntheses and crystal structures of the coordination polymers [Cd(C17H22N2)2(H2O)2]·2(ClO4)·C17H22N2·C2H5OH 2 and [Cd(C17H22N2)2(NO3)2] 3 are reported, where C17H22N2 is a flexible spacer, 1,7-bis(4-pyridyl)heptane. In compound 2, trans-CdO2N4 octahedral nodes are linked by pairs of bridging ligands to result in [001] looped polymeric chains. The chains stack in the [100] direction to form (010) pseudo layers. Sandwiched between them are secondary sheets of free ligands, perchlorate ions and ethanol solvent molecules. Hydrogen bonds between these species help to consolidate the structure. Compound 3 contains trans-CdO2N4 octahedral nodes as parts of regular 44 nets, which propagate in the (103) plane. Three independent nets are interpenetrated.
Effect of Process Pressure on the Properties of Cu2O Thin Films Deposited by RF Magnetron Sputtering
Authors: Park Junghwan , Son Chang-Sik , Son Young-Guk , Hwang Donghyun
Published: December 2024

Cu2O thin films were deposited on soda-lime glass substrates using RF magnetron sputtering under various process pressures, and their structural, morphological, compositional, and optical properties were investigated. X-ray diffraction (XRD) revealed that the films crystallized in the cubic Cu2O phase, with the highest crystallinity observed at 5 mTorr, as evidenced by the sharp and intense (111) peak. Raman spectroscopy confirmed the predominance of Cu2O vibrational modes across all samples, with improved phase purity and crystallinity at 5 mTorr and 10 mTorr. Field-emission scanning electron microscopy (FE-SEM) showed that the films deposited at 5 mTorr and 10 mTorr exhibited densely packed, well-defined grains, while those at 1 mTorr and 15 mTorr displayed irregular or poorly defined morphologies. X-ray photoelectron spectroscopy (XPS) confirmed the presence of Cu(I) without significant secondary phases, with slight surface oxidation observed at higher pressures. Optical characterization revealed that transmittance increased with pressure, reaching ~90% in the NIR range at 15 mTorr. The optical band gap (Eg) values increased from 2.34 eV at 1 mTorr to 2.43 eV at 15 mTorr with higher process pressure. Cu2O films deposited at 5 mTorr and 10 mTorr exhibited an optimal balance between high transparency and band gap values. These findings highlight the critical role of process pressure in determining the properties of Cu2O thin films and identify 5 mTorr as the optimal deposition condition for achieving high-quality films with superior structural and optical performance.
Unraveling a Rare Polygonal Gold–Pyrite Assemblage: Insights from the Lena Province, Bodaibo Mining District (Russia)
Authors: Pignatelli Isabella , Giuliani Gaston , Morlot Christophe , Bayle Louis-Dominique
Published: December 2024

A rare polygonal gold assemblage from the Bodaibo mining district (Russia) was analyzed in this study. It resembles cubic native gold from the same area described as a gold pseudomorph after pyrite. The polygonal assemblage differs from these cubic gold samples by the absence of striations, its stepped morphology, and the presence of euhedral pyrite. It was analyzed with non-destructive techniques (SEM, VSI, and X-ray CT) in order to preserve the integrity of this exceptional sample. The experimental data allowed us to understand how this rare sample could be formed. A formation of secondary deposits, i.e., eluvial placers, is compatible with the mobilization and precipitation of gold by surface effects on primary pyrite, as well as oxidation episodes producing iron oxides/hydroxides. The redox condition in the geological environment caused the pyrite dissolution and release of gold in its structure, leading to the formation of a thin layer of gold on pyrite by epitaxy rather than pseudomorphism.
Mammals in the Collection of the National Museum of Natural History and Science (University of Lisbon, Portugal): A Contribution to Research and Conservation
Authors: Mathias Maria da Luz , Monarca Rita I. , Neves Tomé , Tapisso Joaquim T. , Alves Maria Judite , Ramalhinho Maria da Graça
Published: December 2024

Museum collections serve as valuable repositories of biodiversity, offering a substantial amount of data and specimens for scientific research. This study describes the intrinsic value of the mammal collection at the National Museum of Natural History and Science of the University of Lisbon (Portugal) (MUHNAC), and its nationwide representativeness, with the final aim of revealing its potential to support research and conservation initiatives. The collection includes 6158 specimens, from 131 species, across 10 orders, the great majority collected within Portugal, although a small dataset mostly from other parts of Europe and Africa is also available. The most represented orders are Rodentia, Eulipotyphla, and Carnivora, in contrast to Chiroptera, Cetacea, and Artiodactyla. Approximately 40% of the species within these groups are of conservation concern according to both national and international conventions, with nearly 20% at risk of extinction based on IUCN criteria. Additionally, the representativity of species in MUHNAC reflects the museum’s coverage of species records across the country, with smaller, non-threatened species being more prominently represented and larger, at-risk species being comparatively underrepresented. The influence of conservation, economic, legal, and ethical factors on the species spatial coverage is discussed, providing insights into the variability observed in museum collections.
Insulin-Related Skin Lipohypertrophy in Type Two Diabetes: A Clinical Study of a Case Series, with Ultrasonographic and Histopathologic Implications
Authors: Gentile Sandro , Strollo Felice , Guarino Giuseppina , Ronchi Andrea , Satta Ersilia , Della-Corte Teresa , Fulgione Elisabetta , Babino Graziella , Mattera Edi , Martedì Emilia , Di Martino Roberta , Fiorentino Raffaella , Porcini Roberta , Romano Carmine , Chiarello Maria , Caccavale Giuseppe , Franco Renato , Argenziano Giuseppe
Published: December 2024

Introduction: The most frequent local complication of insulin injection is the occurrence of subcutaneous nodules due to incorrect injection technique. Injection into nodules negatively impacts metabolic compensation and the requirement for greater insulin doses due to its partial and erratic absorption. Despite these concepts being accepted by the scientific community, it is not yet clear whether injection into nodules is causally related to worsening chronic diabetes (DM) complications and the morphological nature of such nodules. Aim: This multicenter study aimed to evaluate the associations between structural characteristics of skin nodules and chronic DM complications. A secondary endpoint was to evaluate the histological structure of those nodules, looking for differences between lipohypertrophies (LH) and amyloid nodules (LIDA). Methods: For this purpose, 816 DM patients with LH and 1033 without LH underwent a clinical and ultrasound study comparing metabolic data, injection habits, and frequency of complications. Excisional biopsies of the skin nodules were performed in a small series of eight subjects. Results: Data observed confirm a strong relationship between LH and diabetes chronic complications other than poor glycemic control. Histology of biopsies from the skin nodules showed mild foreign-body-like inflammation, prevailing mega-adipocytes (65%), apoptosis, and fibrosis but could not detect any amyloid fibrils. In four cases, intra-nodular fluid was present with an insulin concentration several times higher than in blood. Conclusions: We confirmed LHs to be significantly associated with insulin administration errors, duration of insulin therapy, greater daily doses and duration of insulin administration, and the presence of micro- and macro-vascular DM complications. LH nodules displayed no typical morphological features and were indistinguishable from LIDA nodules with which they shared several histologic similarities, albeit within the frame of a general picture of LIDA inhomogeneity. Further targeted studies are warranted to clarify the remaining doubts.
Toward Robust Lung Cancer Diagnosis: Integrating Multiple CT Datasets, Curriculum Learning, and Explainable AI
Authors: Bouamrane Amira , Derdour Makhlouf , Bennour Akram , Elfadil Eisa Taiseer Abdalla , M. Emara Abdel-Hamid , Al-Sarem Mohammed , Kurdi Neesrin Ali
Published: December 2024

Background and Objectives: Computer-aided diagnostic systems have achieved remarkable success in the medical field, particularly in diagnosing malignant tumors, and have done so at a rapid pace. However, the generalizability of the results remains a challenge for researchers and decreases the credibility of these models, which represents a point of criticism by physicians and specialists, especially given the sensitivity of the field. This study proposes a novel model based on deep learning to enhance lung cancer diagnosis quality, understandability, and generalizability. Methods: The proposed approach uses five computed tomography (CT) datasets to assess diversity and heterogeneity. Moreover, the mixup augmentation technique was adopted to facilitate the reliance on salient characteristics by combining features and CT scan labels from datasets to reduce their biases and subjectivity, thus improving the model’s generalization ability and enhancing its robustness. Curriculum learning was used to train the model, starting with simple sets to learn complicated ones quickly. Results: The proposed approach achieved promising results, with an accuracy of 99.38%; precision, specificity, and area under the curve (AUC) of 100%; sensitivity of 98.76%; and F1-score of 99.37%. Additionally, it scored a 00% false positive rate and only a 1.23% false negative rate. An external dataset was used to further validate the proposed method’s effectiveness. The proposed approach achieved optimal results of 100% in all metrics, with 00% false positive and false negative rates. Finally, explainable artificial intelligence (XAI) using Gradient-weighted Class Activation Mapping (Grad-CAM) was employed to better understand the model. Conclusions: This research proposes a robust and interpretable model for lung cancer diagnostics with improved generalizability and validity. Incorporating mixup and curriculum training supported by several datasets underlines its promise for employment as a diagnostic device in the medical industry.
Correction: Huhtanen et al. Discrepancies between Radiology Specialists and Residents in Fracture Detection from Musculoskeletal Radiographs. Diagnostics 2023, 13, 3207
Authors: Huhtanen Jarno T. , Nyman Mikko , Sequeiros Roberto Blanco , Koskinen Seppo K. , Pudas Tomi K. , Kajander Sami , Niemi Pekka , Löyttyniemi Eliisa , Aronen Hannu J. , Hirvonen Jussi
Published: December 2024

Regarding our publication, entitled “Discrepancies between Radiology Specialists and Residents in Fracture Detection from Musculoskeletal Radiographs” [...]
The Role of TORS in the Management of Benign Pathology of the Base of Tongue: A Systematic Review
Authors: Nocini Riccardo , Arietti Valerio , Arsie Athena , Zampieri Erica , Sacchetto Luca
Published: December 2024

Objective: Transoral robotic surgery (TORS) is becoming increasingly popular in head and neck surgery. Its applications have expanded beyond oncologic indications to obstructive sleep apnea syndrome (OSAS) and, more recently, to benign pathologies. Data Sources: A systematic search for articles published in the PubMed and Google Scholar databases between January 2003 and December 2023 was performed using the following combined search query (robot OR sleep OR apnea OR syndrome) AND (robot OR tongue OR base). Review methods: Given the limited literature, we conducted a systematic review focusing on the outcomes of TORS for benign pathologies of the base of the tongue. Our search methodology followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: We found 16 articles that met our inclusion criteria. These were mainly case reports and a few case series. Conclusions: Compared to other transoral techniques, TORS offers better exposure, visualization, and access to the oropharynx, especially the base of the tongue, even in benign pathology. TORS should be considered a feasible, safe, and effective technique. Several more studies are needed to effectively evaluate the role of TORS in benign pathology that does not correlate with OSAS.
Serum α1-AT Levels and SERPINA1 Molecular Analysis in Breast Cancer: An Experimental and Computational Study
Authors: Ávalos-Navarro Guadalupe , Bautista-Herrera Luis A. , Garibaldi-Ríos Asbiel Felipe , Ramírez-Patiño Ramiro , Gutiérrez-García Marisol , Briseño-Álvarez Perla , Jave-Suárez Luis Felipe , Reyes-Uribe Emmanuel , Gallegos-Arreola Martha Patricia
Published: December 2024

Background/Objectives: Breast cancer (BC) is a heterogeneous disease with multifactorial origins, including environmental, genetic, and immunological factors. Inflammatory cytokines, such as alpha 1 antitrypsin (α1-AT), are increased in BC and affect physiological and pathological conditions. This study aimed to evaluate the serum levels of α1-AT and perform a computational analysis of SERPINA1 in BC, as well as their association with molecular subtypes and clinical features. Methods: For the experimental analysis, we evaluated 255 women with BC and 53 healthy women (HW) in a cross-sectional study. Molecular subtypes were identified by immunohistochemistry and TNM was used for clinical staging. Soluble levels of α1-AT were quantified by ELISA. Computational analysis of SERPINA1 expression was performed using GEPIA and cBioPortal. Results: α1-AT was increased in BC women versus HW (75.8 ng/mL vs. 532.2 ng/mL). Luminal A had higher concentration (547.5 ng/mL) than Triple Negative (TN) (484.1 ng/mL), but the levels were not associated with clinical stage. The computational analysis showed that SERPINA1 is overexpressed in BC with differential expression among subtypes; its overexpression is associated with a better prognosis, longer disease-free survival, and overall survival. Conclusions: α1-AT levels are increased in women with BC women compared to HW. The Luminal A subtype shows higher soluble protein levels than the TN one. Furthermore, SERPINA1 mRNA overexpression in BC is linked to a protective effect.
Anatomical Facial Characteristics of Teeth and Tooth Analysis
Authors: de Bruin Sybrand Gerhard , Ishwarkumar-Govender Sundika , Pillay Pamela
Published: December 2024

Background: This study aimed to document the angulation, inclination, and facial anatomical characteristics of teeth in a select South African population to determine if there are any population norms. Digital intra-oral scans were used, to analyze the morphology of teeth and measure the facial clinical crown. Methods: A quantitative observational research design with 60 3D intra-oral scans of a select South African population group was used. Morphometric analysis of 3D intra-oral scans was performed for a select South African population group, measuring the clinical crown height, width, angulation, and inclination of each tooth. Results: Significant differences in crown widths between male and female subjects were observed for several teeth in the maxillary and mandibular arches: males exhibited larger mean widths and larger crown dimensions than females. The South African Black group showed more sexual dimorphism compared to the South African Indian group. Clinical crown length and tooth angulation differed significantly between South African Indian and South African Black populations, while crown width and inclination remained consistent across these population groups and crown inclination between sex groups. Conclusions: Certain teeth exhibited notable variations between South African Indian and South African Black population groups; specifically, crown length and angulation had significant differences, whereas crown inclination and width remained consistent across these population groups.
The Role of Mandibular Thickness in Determining Anteroposterior Skeletal Relationships
Authors: Tsuboi Akihiro , Koizumi So , Takahashi Masahiro , Hikita Yu , Yamaguchi Tetsutaro
Published: December 2024

Objectives: This study aimed to explore the association between the ANB angle and mandibular bone thickness in individuals with skeletal malocclusion. Methods: We analyzed 224 adults, with a gender imbalance noted (68 men and 156 women), and an age range between 18.0 and 65.1 years. The thicknesses of the ramus (RT) and the body of the mandible (BT) were measured at 25 sites on each side (left and right) of the jaw, using CT images. The main focus was on the statistical associations between the ANB angle and the ratio (BT-RT)/volume of the mandible (V). Results: Results revealed a significant negative association between (BT-RT)/V and the ANB angle (p < 0.001), while a positive association was found for RT/V (p < 0.001). No significant association emerged for BT/V. Conclusions: The findings indicated that with increased mandibular protrusion, the ramus thickness decreased, whereas the body thickness remained unchanged. The differing relationships in mandibular thickness underscore the significance of CT imaging in predicting craniofacial growth patterns, particularly in observing discrepancies between the mandibular body and ramus as they relate to the anterior–posterior jaw relationship.
Small Change, Big Difference
Authors: Muijs Daniel
Published: December 2024

Sometimes a small change can make a big difference [...]
Assessing Complex Skills in a Virtual Reality Context: Capturing the Development of Pre-Service Teachers’ Classroom Management Strategies
Authors: Mouw Jolien M. , Fokkens-Bruinsma Marjon , Snippe Andrea
Published: December 2024

Simulation-based learning environments such as virtual reality (VR) can be promising to help pre-service teachers develop kindergarten-specific classroom management strategies. However, the successful integration of VR in higher education is impeded by limitations regarding the assessment of multifaceted skills such as classroom management strategies. In this paper, we aimed to understand how different assessment instruments lead to aligning or diverging conclusions regarding pre-service teachers’ VR-supported over-time development of classroom management strategies in terms of behaviors and beliefs. With a variety of self-reported and observational measures, we gauged distinct aspects of pre-service teachers’ classroom management strategies conceptualized as behaviors and beliefs at two time points: before and after practicing in a VR kindergarten classroom. Most measures captured an over-time development of behaviors and beliefs—except for pre-service teachers’ self-reported usage of classroom management strategies. Alignment was observed between measures gauging pre-service teachers’ classroom management strategies beliefs and between most, but not all, measures of classroom management strategies behaviors: Pre-service teachers’ self-reported usage of classroom management strategies do not align with the observations of strategy usage. Our findings emphasize the importance of using multiple instruments to capture, assess, and appraise VR-supported development of distinct aspects of pre-service teachers’ kindergarten-specific classroom management strategies.
Designing a Digital Flash Reading Test for Data-Based Decisions in Inclusive Classrooms: Duration and Word Length as Difficulty-Generating-Item Characteristics
Authors: Zellner Judith , Ebenbeck Nikola , Gebhardt Markus
Published: December 2024

Standardized assessment tools are essential for informed, data-driven decision-making. Reading speedily is a crucial early skill that all students should have the opportunity to develop in inclusive classrooms. To facilitate classroom-based reading diagnostics in this area of reading, we developed a flash reading test that reliably measures the performance of students with and without learning disabilities and intellectual disabilities. This test can be administered in the classroom and completed independently by students, taking only a few minutes, without requiring them to read aloud. The test is designed to provide an accurate assessment of the speed of lexical recall for all students. To evaluate the difficulty-generating-item characteristics of the new instrument, 400 primary and special school students participated in the test. The results indicate that students with low abilities and disabilities are particularly differentiated by the combination of a short display duration and short words. We provide information for test developers interested in designing similar assessments and teachers who can use this instrument to make informed decisions in the classroom.
Advanced Network and System Security Teaching
Authors: Ogrizović Mihajlo , Vuletić Pavle , Stanisavljević Žarko
Published: December 2024

In an attempt to address the growing shortage of cybersecurity specialists in the country, the School of Electrical Engineering, University of Belgrade, started the course entitled Advanced Network and System Security (ANS) in the 2019/2020 school year. The ANS course covers the topics of computer system and network security, intrusion detection and prevention, and ethical hacking methodologies. This paper presents the course organization and associated laboratory environment and exercises and aims to prove that providing such a multidisciplinary laboratory leads to successful learning outcomes and directly improves gained knowledge in cybersecurity. The ANS course differs from all other related courses by covering various cybersecurity topics ranging from hardware through to network to web security. The analysis showed that 13 out of 19 Cyber Security Body of Knowledge classification Knowledge Areas are covered in the ANS course, unlike other related courses which cover up to 8 Knowledge Areas. Ultimately, the students’ practical skills improvement evaluation was performed through quantitative and qualitative analysis in order to prove that improving practical skills in the ANS laboratory resulted in the overall improvement of the gained knowledge.
RF Fingerprinting Using Transient-Based Identification Signals at Sampling Rates Close to the Nyquist Limit
Authors: Taşcıoğlu Selçuk , Kalaycıoğlu Aykut , Köse Memduh , Soysal Gokhan
Published: December 2024

Radio frequency (RF) fingerprinting is regarded as a promising solution to improve wireless security, especially in applications where resource-limited devices are employed. Unlike steady-state signals, such as preambles or data, the use of short-duration transient signals for RF fingerprinting offers distinct advantages for systems with low latency and low complexity requirements. One of the challenges associated with transient-based methods in practice is achieving high performance while utilizing low-cost receivers. In this study, we demonstrate for the first time that the performance of transient-based RF fingerprinting can be enhanced by designing the filter chain in a software defined radio (SDR) receiver, taking into account the relevant signal characteristics. The performance analysis is conducted using transient-based identification signals captured by the SDR receiver, focusing on the sampling rate and duration of the identification signal. In the experiments, signals collected from twenty IEEE 802.11 transmitters are used. Experimental results indicate that so long as the receiver filter parameters and the duration of the identification signal are properly determined, a high classification performance exceeding 92% can be achieved for transient-based RF fingerprinting, even at sampling rates approaching the Nyquist limit.
A Diffusion Model-Based Character Synthesis Using a Blank Face
Authors: Choi Wooseok , Yang Heekyung , Min Kyungha
Published: December 2024

In this study, we propose a framework for synthesizing new characters by applying the features of a reference face to a source face using a diffusion model-based image editing technique. For an effective synthesis, a blank face of the sample is first generated by removing all features except the hairstyle, face shape, and skin tone. Then, facial features such as the eyes, eyebrows, nose, and mouth from the reference face are applied to the blank face of the source face. This strategy allows the creation of a new character that reflects the reference face’s features on the source face without producing unwanted artifacts or undesired blending of facial features.
CFGAN: A Conditional Filter Generative Adversarial Network for Signal Modulation Mode Recognition
Authors: Zhou Fan , Wang Jiayi , Zhang Lan , Wang Yang , Chen Xi , Zhang Peiying
Published: December 2024

Currently, in the application scenario of generative adversarial networks, determining how to improve the quality of the generated signals and ensure the modulation recognition accuracy of convolutional neural networks are important problems. In this paper, a generative sample quality screening method for the problem of low-quality samples generated by generative adversarial networks under few-shot conditions has been proposed, which innovatively establishes a sample expansion mode without fixing the network parameters, realizes the learning of the real data distribution by constantly updating the network weights, and enhances the quality of the expanded samples by adopting the quality screening method with two quality screenings. A generative adversarial network has been designed for this method, which reduces the time investment required for generating samples by extracting different features of few-shots of signals. The experimental results show the few-shot conditions, under the signal-to-noise ratio of −8∼12 dB and three expansion ratios of 1:1, 1:2 and 1:3. Compared with the general method expansion, the average modulation mode recognition accuracy of the QCO-CFGAN method expanded with the quality screening method is improved by 2.65%, 2.46% and 2.73%, respectively, which proves the effectiveness under this condition.
Efficiency Design of a Single-Phase Bidirectional Rectifier for Home Energy Management Systems
Authors: Esteve Vicente , Bellido Juan L. , Jordán José
Published: December 2024

This paper examines the current state of Home Energy Management Systems (HEMSs), highlighting the key role of the single-phase bidirectional rectifier (SPBR). It provides a detailed design process for the converter used in HEMSs, with a particular focus on the bidirectional charge and discharge of high-voltage batteries. The converter’s operating conditions were determined through a comprehensive evaluation of its components, which were designed and assessed to enable accurate power loss calculations. This approach ensures proper component sizing and a clear understanding of the converter’s efficiency. A specialized electronic control circuit manages two operating modes of the converter: a boost rectifier with power factor correction (PFC) and a sinusoidal pulse width modulation (SPWM) inverter. To validate the design, a 7.4 kW prototype was developed using silicon carbide (SiC) metal oxide semiconductor field effect transistors (MOSFETs). The prototype achieved a peak efficiency of nearly 98% in both modes, with a unity power factor (PF) and total harmonic distortion (THD) below 7% at full power.
Synergistic Development Pathways: An Exploratory Study on the Urban–Rural Mutual Assistance Model and Low-Carbon Transformation of Henan’s Power Supply Industry Towards Dual-Carbon Goals
Authors: Tang Xinfa , Hao Guozu , Wang Yonghua , Wan Youwei , Wang Jingjing , Luo Yan , Nubea Musa Dirane
Published: December 2024

In the midst of the push for dual-carbon goals, urban centers are faced with the imperative of reducing emissions and conserving energy, while rural regions are harnessing their abundant new energy resources to promote balanced urban–rural development. Photovoltaic (PV) power generation, known for its cleanliness, safety, and emission-free nature, is playing a crucial role in the evolution of Henan Province’s power supply industry. This paper delves into the current state of Henan’s power supply infrastructure, the trajectory of its low-carbon development, and the policies that shape the PV sector. It also examines the establishment of an urban–rural mutual aid model through the lens of alternative energy technologies. By utilizing a combination of case studies and systematic theoretical research, this paper uncovers the economic potential that remains untapped of new energy sources in rural areas and presents strategies for synergistic development in alignment with dual-carbon goals within the power supply industry. The research underscores the significance of an urban–rural mutual assistance model in achieving carbon neutrality, addressing urban–rural development gaps, fostering shared prosperity, and contributing Chinese insights to global climate governance frameworks.
Anaerobic Biohythane Production in an Internal Two-Stage Bioreactor: Kitchen Waste Concentration Optimization
Authors: Abdul Peer Mohamed , Lay Chyi-How , Lin Chiu-Yue , Vo Tan-Phat , Chang Chia-Min
Published: December 2024

An internal two-stage bioreactor constructed with a hydrogen chamber and a methane chamber with a working volume of 300 mL and 4700 mL, respectively, was operated using various kitchen waste (KW) concentrations from 10 to 80 g COD/L with a hydraulic retention time of 2 days to characterize the biomethane production performance. The results showed that daily biohythane production exhibited a similar increasing trend at KW concentrations of 10 to 40 g COD/L. The peak biomethane production was 2481 mL/day at a KW concentration of 40 g COD/L. The KW concentration could also affect the COD, carbohydrate, lipid, and protein removal efficiencies. These removal efficiencies were somehow dependent on the KW concentration, with two notable KW concentration groups of 10–20 g COD/L and 40–80 g COD/L. After 80 days of cultivation, Firmicutes dominated the hydrogen chamber, and Methanobacteriaceae and Methanomicrobiaceae dominated the methane chamber. This study presents the optimal KW concentration for high biohythane production efficiency in a novel internal two-stage bioreactor and reveals the dominant microorganisms in its microbial community.
Review of Progress on Printing Techniques Towards Commercialization of Perovskite Solar Cells
Authors: Alharbi Mai Ali , Bhandari Shubhranshu , Mallick Tapas
Published: December 2024

Perovskite solar cells (PSCs) offer a number of key advantages over silicon solar cells. These include their low-cost materials, high efficiency, simplicity of fabrication, and inexpensive manufacturing techniques. To commercialize PSCs, there are many methods to develop the quality of the cells, one of them being printing techniques. Different printing techniques deposition have been developed for the perovskite solar cell, such as blade coating, slot die coating, inkjet printing, screen printing, spray coating, flexographic printing, and gravure printing. These techniques have a substantial impact on the performance of PSCs and controlling film formation to commercialize PSCs. This review summarizes a comprehensive overview of various deposition printing techniques used to fabricate PSCs during different years and different techniques, such as using different preparation methods, novel drying techniques, and ink engineering. In addition, the challenges that are faced by using these, such as material stability, reproducibility of printing processes, and cost-effectiveness techniques, are reviewed. Future research should focus on optimizing printing techniques to improve the stability and scalability of PSCs. Exploring novel perovskite materials, deposition techniques, and innovative fabrication methods may further enhance the PSCs and facilitate their commercialization.
Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management Strategies
Authors: Gómez-Barroso Álvaro , Makazaga Iban Vicente , Zulueta Ekaitz
Published: December 2024

Rising greenhouse gas emissions stemming from road transport have intensified the need for efficient and environmentally friendly propulsion technologies. Hybrid and fuel cell electric vehicles have emerged as a viable solution, integrating internal combustion engines and fuel cells with electric motors to optimize fuel efficiency and reduce emissions. This article reviews and analyzes energy management strategies for the principal powertrain topologies of hybrid electric vehicles, focusing on achieving solution optimality in real-time applications. A thorough and comprehensive overview of rule-based, optimization-based, and learning-based energy management strategies is presented, highlighting their main attributes and providing a comparative analysis in terms of fuel economy improvements, real-time implementation feasibility, and computational complexity, while simultaneously identifying and uncovering areas requiring further research in the field. We found that while rule-based methods offer simplicity and real-time capability, their adaptability remains limited. Optimization-based and learning-based approaches, although often achieving near-optimal solutions, face challenges due to their high computational demands and integration complexities. Our analysis also revealed the importance of leveraging vehicle connectivity and intelligent transportation systems for future energy management developments, which will contribute to broader sustainability goals in the automotive sector.
Leveraging Harris Hawks Optimization for Enhanced Multi-Objective Optimal Power Flow in Complex Power Systems
Authors: Alsokhiry Fahad
Published: December 2024

The utilization of Harris Hawks Optimization (HHO) for Multi-Objective Optimal Power Flow (MaO-OPF) challenges presented in this paper is both novel and compelling, as this approach has not been previously applied to these types of optimization problems. HHO, which shares characteristics with ant behavior, demonstrates significant strength in addressing high-dimensional, nonlinear optimization issues within power systems. In this study, HHO is implemented on an IEEE 30-bus power system, optimizing six competing objectives: minimizing total fuel cost, emissions, active power loss, reactive power loss, reducing voltage deviation, and enhancing voltage steady state. The effectiveness of HHO is assessed by comparing its performance to two alternative methods, MOEA/D-DRA and NSGA-III. Experimental results reveal that solutions derived from HHO exhibit superior convergence, enhanced diversity maintenance, and higher quality Pareto-optimal solutions compared to the MOEA/D trail algorithms. The research breaks new ground in the application of the Harris Hawks Optimization (HHO) algorithm to the Multi-Objective Optimal Power Flow (MaO-OPF) problem. The restructuring not only incorporates self-adaptive constraint-handling techniques and dynamic exploration exploitation strategies, but also addresses the more pressing requirements of modern power systems with even better convergence, and both sequential and global computational efficiency than existing skill. This approach proves to be a powerful and effective solution for addressing the complex challenges associated with MaO, enabling power systems to manage multiple conflicting objectives more efficiently.
Review and Prospects of Key Technologies for Integrated Systems in Hydrogen Production from Offshore Superconducting Wind Power
Authors: Shen Liufei , Zhang Cheng , Shan Feiyue , Chen Long , Liu Shuai , Zheng Zhiqiang , Zhu Litong , Wang Jinduo , Wu Xingzheng , Zhai Yujia
Published: December 2024

Hydrogen production from renewable energy sources is a crucial pathway to achieving the carbon peak target and realizing the vision of carbon neutrality. The hydrogen production from offshore superconducting wind power (HPOSWP) integrated systems, as an innovative technology in the renewable energy hydrogen production field, holds significant market potential and promising development prospects. This integrated technology, based on research into high-temperature superconducting generator (HTSG) characteristics and electrolytic water hydrogen production (EWHP) technology, converts offshore wind energy (OWE) into hydrogen energy locally through electrolysis, with hydrogen storage being shipped and controlled liquid hydrogen (LH2) circulation ensuring a stable low-temperature environment for the HTSGs’ refrigeration system. However, due to the significant instability and intermittency of offshore wind power (OWP), this HPOSWP system can greatly affect the dynamic adaptability of the EWHP system, resulting in impure hydrogen production and compromising the safety of the LH2 cooling system, and reduce the fitness of the integrated system for wind electricity–hydrogen heat multi-field coupling. This paper provides a comprehensive overview of the fundamental structure and characteristics of this integrated technology and further identifies the key challenges in its application, including the dynamic adaptability of electrolytic water hydrogen production technology, as well as the need for large-capacity, long-duration storage solutions. Additionally, this paper explores the future technological direction of this integrated system, highlighting the need to overcome the limitations of electrical energy adaptation within the system, improve product purity, and achieve large-scale applications.
Energy-Efficient and Fault-Tolerant Control of a Six-Axis Robot Based on AI Models
Authors: Nowak Patryk , Pandilov Zoran
Published: December 2024

This paper describes the task of controlling a robot to enable energy savings in the case of one- or two-axis failure. The proposed algorithms are tested in a task similar to “pick and place” but without gripping. Obstacles are present in the robot’s workspace. The goal of the algorithm is to control the robot in such a way that energy consumption is minimized while also avoiding obstacles and ensuring fault tolerance in the event of axis failures. The algorithm uses a developed torque model of the robot, which is employed to calculate the energy requirements for each possible movement step in the robot’s position. In the robot’s control system, artificial intelligence methods are also applied. Specifically, a genetic algorithm is used to generate learning data for the selection of the optimal kinematic configuration of the robot, and a multilayer perceptron is utilized to predict the parameters of the defined reward function. This function is crucial for selecting the optimal action at each time step. The study demonstrates that the application of the algorithm leads to a reduction in robot energy consumption. Studies conducted in simulation and verified on a real robot for 10 different obstacle and target positions and 22 possible kinematic configurations of the robot, consisting of all axes active, any one axis inactive, or any two axes inactive, confirm the energy-saving possibilities.
Upcycling of Eggshell Waste into Calcium Phosphates for Use in Sustainable Biomedical Engineering Applications
Authors: Pagonis Nikolaos , Flegkas Dimitrios , Itziou Aikaterini , Kountouras Konstantinos , Stimoniaris Adam , Samaras Petros , Karayannis Vayos
Published: December 2024

Eggshells are an inorganic waste, and their accumulation rate is increasing globally, complicating waste management. However, the European Union defines eggshells as low-risk material that can be recycled and reused safely in other applications. Their chemical composition renders them an attractive precursor of calcium phosphate materials (CaPs). Because of their remarkable biocompatibility and capacity for natural degradation, CaPs are frequently employed in biomedical engineering applications. In this research, the wet precipitation method was employed for fabricating CaP powder. Initially, the eggshells were processed into CaCO3 powder and then reacted with HCl to obtain CaCl2 (aq). This reacted with Na2HPO4 to obtain a precipitate that was filtered and dried. The precipitate in powder form underwent X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) analysis to evaluate its microstructure, and elemental and phase composition. The results indicated that the recovered powder was brushite.
Examining South Tyrol’s Experience: Digital Health Adoption and Workforce Issues in Implementing Italy’s Primary Care Reform Under Ministerial Decree No. 77/2022
Authors: Wiedermann Christian J. , Mahlknecht Angelika , Barbieri Verena , Ausserhofer Dietmar , Plagg Barbara , Felderer Carla , Marino Pasqualina , Engl Adolf , Piccoliori Giuliano
Published: December 2024

Background: Ministerial Decree (D.M.) 77/2022 aims to reform Italy’s primary care system by establishing community health centres and integrating digital tools to address healthcare access disparities and workforce shortages. This review focuses on frailty assessment tools, digital health innovations, and workforce challenges in the Autonomous Province of Bolzano, South Tyrol, emphasising interprofessional trust and collaboration issues. Methods: Using a narrative custom review approach guided by the SANRA checklist, this study synthesised findings from PubMed, official health websites, and regional surveys on frailty, workforce dynamics, interprofessional collaboration, and digital infrastructure in South Tyrol. Results: General practitioners (GPs) exhibited high professional motivation but expressed concerns about autonomy and administrative burdens in collaborative care models. Trust issues between GPs and specialists hinder workforce cohesion and care coordination, highlighting the need for structured inter-professional communication. Frailty assessments, such as the PRISMA-7 tool, identify over 33% of community-dwelling individuals aged 75 years and older as frail, necessitating targeted interventions. Digital health adoption, particularly electronic health records and telemedicine, is slow because of workforce shortages and infrastructure limitations. Conclusions: The successful implementation of D.M. 77/2022 in South Tyrol requires addressing workforce challenges, improving interprofessional trust, expanding digital infrastructure, and integrating frailty assessment findings into care strategies. These measures are critical for achieving a more resilient, equitable, and effective primary healthcare system.
Structural Yield of Fast-Growing Hardwood vs. Softwood Glulam Beams
Authors: Baño Vanesa , Pérez-Gomar Carolina , Godoy Daniel , Moya Laura
Published: December 2024

This paper focuses on analysing the structural performance of fast-grown hardwood versus softwood glued laminated timber (GLT or glulam) beams with the aim to evaluate the potential structural use of the two main species planted in the country. In Uruguay, the first forest plantations date from the 1990s and are comprised mainly of Eucalyptus ssp. and Pinus spp. No one species were planted for a specific industrial purpose. However, while eucalyptus was primarily destined for the pulp industry, pine, which is now reaching its forest rotation, had no specific industrial destination. Timber construction worldwide is mainly focused on softwood species with medium and long forest rotation. The objective of the present work is, therefore, to analyse and compare the potential of eucalyptus (Eucalyptus grandis) and loblolly/slash pine (Pinus elliottii/taeda) to produce glulam beams for structural purposes. Experimental tests were made on sawn timber and GLT beams manufactured under laboratory conditions for both species. The relationship between the physical and mechanical properties of sawn timber showed that, for similar characteristic values of density (365 kg/m3 for pine and 385 kg/m3 for eucalyptus), and similar years of forest rotation (20–25 years for pine and around 20 years for eucalyptus) and growth rates, the structural yield of eucalyptus was higher compared to that of pine. The superior values of modulus of elasticity found in the hardwood species explained this result. Since there is no strength classes system for South American wood species, the European system was the basis for estimating and assigning theoretical strength classes from the visual grades of Uruguayan timbers. For sawn timber, a C14 strength class for pine and C20 for eucalyptus were assigned. Results showed that pine GLT could be assigned to a strength class GL20h, and eucalyptus glulam to GL24h and GL28h, demonstrating the potential of both species for producing glulam beams. Even though eucalyptus showed a better yield than pine, the technological process of manufacturing eucalyptus glulam was more challenging in terms of drying time and gluing than in the case of pine, which derivates in higher economic costs.