bluuebunny/crossref_metadata_2025 huggingface dataset:
MutaPT: A Multi-Task Pre-Trained Transformer for Classifying State of Disorders of Consciousness Using EEG Signal
Authors: Wang Zihan , Yu Junqi , Gao Jiahui , Bai Yang , Wan Zhijiang
Published: July 2024

Deep learning (DL) has been demonstrated to be a valuable tool for classifying state of disorders of consciousness (DOC) using EEG signals. However, the performance of the DL-based DOC state classification is often challenged by the limited size of EEG datasets. To overcome this issue, we introduce multiple open-source EEG datasets to increase data volume and train a novel multi-task pre-training Transformer model named MutaPT. Furthermore, we propose a cross-distribution self-supervised (CDS) pre-training strategy to enhance the model’s generalization ability, addressing data distribution shifts across multiple datasets. An EEG dataset of DOC patients is used to validate the effectiveness of our methods for the task of classifying DOC states. Experimental results show the superiority of our MutaPT over several DL models for EEG classification.
Evaluating Human Expert Knowledge in Damage Assessment Using Eye Tracking: A Disaster Case Study
Authors: Saleem Muhammad Rakeh , Mayne Robert , Napolitano Rebecca
Published: July 2024

The rising frequency of natural disasters demands efficient and accurate structural damage assessments to ensure public safety and expedite recovery. Human error, inconsistent standards, and safety risks limit traditional visual inspections by engineers. Although UAVs and AI have advanced post-disaster assessments, they still lack the expert knowledge and decision-making judgment of human inspectors. This study explores how expertise shapes human–building interaction during disaster inspections by using eye tracking technology to capture the gaze patterns of expert and novice inspectors. A controlled, screen-based inspection method was employed to safely gather data, which was then used to train a machine learning model for saliency map prediction. The results highlight significant differences in visual attention between experts and novices, providing valuable insights for future inspection strategies and training novice inspectors. By integrating human expertise with automated systems, this research aims to improve the accuracy and reliability of post-disaster structural assessments, fostering more effective human–machine collaboration in disaster response efforts.
Solar Radiation Measurement Tools and Their Impact on In Situ Testing—A Portuguese Case Study
Authors: Oliveira Marta , Silva Lopes Hélder , Mendonça Paulo , Tenpierik Martin , Silva Lígia Torres
Published: July 2024

Accurate knowledge of solar radiation data or its estimation is crucial to maximize the benefits derived from the Sun. In this context, many sectors are re-evaluating their investments and plans to increase profit margins in line with sustainable development based on knowledge and estimation of solar radiation. This scenario has drawn the attention of researchers to the estimation and measurement of solar radiation with a low level of error. Various types of models, such as empirical models, time series, artificial intelligence algorithms and hybrid models, for estimating and measuring solar radiation have been continuously developed in the literature. In general, these models require atmospheric, geographical, climatic and historical solar radiation data from a specific region for accurate estimation. Each analysis model has its advantages and disadvantages when it comes to estimating solar radiation and, depending on the model, the results for one region may be better or worse than for another. Furthermore, it has been observed that an input parameter that significantly improves the model’s performance in one region can make it difficult to succeed in another. The research gaps, challenges and future directions in terms of solar radiation estimation have substantial impacts, but regardless of the model, in situ measurements and commercially available equipment consistently influence solar radiation calculations and, subsequently, simulations or estimates. This article aims to exemplify, through a case study in a multi-family residential building located in Viana do Castelo, a city in the north of Portugal, the difficulties of capturing the spectrum of radiations that make up the total radiation that reaches the measuring equipment or site. Three pieces of equipment are used—a silicon pyranometer, a thermopile pyranometer and a solar meter—on the same day, in the same place, under the same meteorological conditions and with the same measurement method. It is found that the thermopile pyranometer has superior behavior, as it does not oscillate as much with external factors such as the ambient temperature, which influence the other two pieces of equipment. However, due to the different assumptions of the measurement models, the various components of the measurement site make it difficult to obtain the most accurate and reliable results in most studies. Despite the advantages of each model, measurement models have gained prominence in terms of the ease of use and low operating costs rather than the rigor of their results.
Treatment, Prognostic Markers, and Survival in Thymic Neuroendocrine Tumors, with Special Reference to Temozolomide-Based Chemotherapy
Authors: Cheng Zixuan , Yu Fuhuan , Chen Ruao , Cui Lingjun , Chen Yingying , Deng Chao , Shi Yanfen , Tan Huangying
Published: July 2024

Background: Thymic neuroendocrine tumors (Th-NETs) are rare and aggressive, with a scarcity of research on predicting patient prognosis. Our study aimed to assess the impact of prognostic markers and temozolomide (TMZ)-based chemotherapy on survival in Th-NETs. Methods: We retrospectively reviewed the medical records of patients diagnosed with Th-NETs between 2013 and 2023 at our institution. We collected clinicopathological data, including tumor pathological grading, staging, serum concentrations of neuron-specific enolase (NSE) and pro-gastrin-releasing peptide, levels of inflammatory factors, and expression of oxygen 6-methylguanine-DNA methyltransferase (MGMT). Treatment details (such as surgery and chemotherapy) and survival outcomes were also documented. Results: A total of 32 patients were included in our study after excluding those without complete available information. The median progression-free survival (PFS) was 12.5 months (95%CI, 8–16 months) for 19 patients who received TMZ-based chemotherapy. Twenty-one patients underwent surgery as the primary treatment, demonstrating a median disease-free survival (DFS) of 51.0 months. The inflammatory factor neutrophil-to-lymphocyte ratio (NLR) was an independent prognostic indicator of DFS in postoperative patients and PFS in TMZ-treated patients. The overall 3-, 5-, and 10-year survival rates were 86.6%, 69.5%, and 33.8%, respectively. Ki67 level exceeding 10% (p = 0.048) and absence of surgical resection (p = 0.003) were significantly associated with worse overall survival (OS). Conclusion: Surgical treatment was currently the primary method for treating Th-NETs, and postoperative adjuvant therapy was an essential consideration for specific patient cohorts. Despite widespread positive MGMT expression, TMZ-based chemotherapy showed promise. Some potential prognostic biomarkers such as NLR and NSE need more attention.
IC Regimen: Delaying Resistance to Lorlatinib in ALK Driven Cancers by Adding Repurposed Itraconazole and Cilostazol
Authors: Kast Richard E.
Published: July 2024

Lorlatinib is a pharmaceutical ALK kinase inhibitor used to treat ALK driven non-small cell lung cancers. This paper analyses the intersection of past published data on the physiological consequences of two unrelated drugs from general medical practice—itraconazole and cilostazol—with the pathophysiology of ALK positive non-small cell lung cancer. A conclusion from that data analysis is that adding itraconazole and cilostazol may make lorlatinib more effective. Itraconazole, although marketed worldwide as a generic antifungal drug, also inhibits Hedgehog signaling, Wnt signaling, hepatic CYP3A4, and the p-gp efflux pump. Cilostazol, marketed worldwide as a generic thrombosis preventative drug, acts by inhibiting phosphodiesterase 3, and, by so doing, lowers platelets’ adhesion, thereby partially depriving malignant cells of the many tumor trophic growth factors supplied by platelets. Itraconazole may enhance lorlatinib effectiveness by (i) reducing or stopping a Hedgehog-ALK amplifying feedback loop, by (ii) increasing lorlatinib’s brain levels by p-gp inhibition, and by (iii) inhibiting growth drive from Wnt signaling. Cilostazol, surprisingly, carries minimal bleeding risk, lower than that of aspirin. Risk/benefit assessment of the combination of metastatic ALK positive lung cancer being a low-survival disease with the predicted safety of itraconazole-cilostazol augmentation of lorlatinib favors a trial of this drug trio in ALK positive lung cancer.
Beyond the Coagulation Cascade: Vitamin K and Its Multifaceted Impact on Human and Domesticated Animal Health
Authors: Sadler Rebecka A. , Shoveller Anna K. , Shandilya Umesh K. , Charchoglyan Armen , Wagter-Lesperance Lauraine , Bridle Byram W. , Mallard Bonnie A. , Karrow Niel A.
Published: July 2024

Vitamin K (VK) is an essential micronutrient impacting many systems in the body. This lipid-soluble vitamin is found in various plant and animal products and is absorbed via the lymphatic system. This biomolecule’s importance to human health includes but is not limited to its promotion of brain, cardiovascular, bone, and immune functions. These biological properties are also necessary for maintaining domesticated animal health. The synergistic impact of both VK and vitamin D (VD) maximizes these health benefits, specifically for the circulatory and skeletal systems. This manuscript reviews VK’s properties, molecular structures, nutrikinetics, mechanisms of action, daily requirements, safety in supplemental form, biomarkers used for its detection, and impacts on various organs. The purpose of synthesizing this information is to evaluate the potential uses of VK for the treatment or prevention of diseases.
Expression and Functional Analysis of Immuno-Micro-RNAs mir-146a and mir-326 in Colorectal Cancer
Authors: Farc Ovidiu , Budisan Liviuta , Zaharie Florin , Țăulean Roman , Vălean Dan , Talvan Elena , Neagoe Ioana Berindan , Zănoagă Oana , Braicu Cornelia , Cristea Victor
Published: July 2024

Micro-RNAs (miRNAs) are non-coding RNAs with importance in the development of cancer. They are involved in both tumor development and immune processes in tumors. The present study aims to characterize the behavior of two miRNAs, the proinflammatory miR-326-5p and the anti-inflammatory miR-146a-5p, in colorectal cancer (CRC), to decipher the mechanisms that regulate their expression, and to study potential applications. Tissue levels of miR-326-5p and miR-146a-5p were determined by qrt-PCR (real-time quantitative reverse transcription polymerase chain reaction) in 45 patients with colorectal cancer in tumoral and normal adjacent tissue. Subsequent bioinformatic analysis was performed to characterize the transcriptional networks that control the expression of the two miRNAs. The biomarker potential of miRNAs was assessed. The expression of miR-325-5p and miR-146a-5p was decreased in tumors compared to normal tissue. The two miRNAs are regulated through a transcriptional network, which originates in the inflammatory and proliferative pathways and regulates a set of cellular functions related to immunity, proliferation, and differentiation. The miRNAs coordinate distinct modules in the network. There is good biomarker potential of miR-326 with an AUC (Area under the curve) of 0.827, 0.911 sensitivity (Sn), and 0.689 specificity (Sp), and of the combination miR-326-miR-146a, with an AUC of 0.845, Sn of 0.75, and Sp of 0.89. The miRNAs are downregulated in the tumor tissue. They are regulated by a transcriptional network in which they coordinate distinct modules. The structure of the network highlights possible therapeutic approaches. MiR-326 and the combination of the two miRNAs may serve as biomarkers in CRC.
Secondary Analysis of Human Bulk RNA-Seq Dataset Suggests Potential Mechanisms for Letrozole Resistance in Estrogen-Positive (ER+) Breast Cancer
Authors: Sutherland Lincoln , Lang Jacob , Gonzalez-Juarbe Norberto , Pickett Brett E.
Published: July 2024

Estrogen receptor-positive (ER+) breast cancer is common among postmenopausal women and is frequently treated with Letrozole, which inhibits aromatase from synthesizing estrogen from androgens. Decreased estrogen slows the growth of tumors and can be an effective treatment. The increase in Letrozole resistance poses a unique problem for patients. To better understand the underlying molecular mechanism(s) of Letrozole resistance, we reanalyzed transcriptomic data by comparing individuals who responded to Letrozole therapy (responders) to those who were resistant to treatment (non-responders). We identified SOX11 and S100A9 as two significant differentially expressed genes (DEGs) between these patient cohorts, with “PLK1 signaling events” being the most significant signaling pathway. We also identified PRDX4 and E2F8 gene products as being the top mechanistic transcriptional markers for ER+ treatment resistance. Many of the significant DEGs that we identified play a known role in ER+ breast cancer or other types of cancer, which partially validate our results. Several of the gene products we identified are novel in the context of ER+ breast cancer. Many of the genes that we identified warrant further research to elucidate the more specific molecular mechanisms of Letrozole resistance in this patient population and could potentially be used as prognostic markers with further wet lab validation. We anticipate that these findings could contribute to improved detection and therapeutic outcomes in aromatase-resistant ER+ breast cancer patients.
The Effect of Removal of External Proteins PsbO, PsbP and PsbQ on Flash-Induced Molecular Oxygen Evolution and Its Biphasicity in Tobacco PSII
Authors: Krysiak Sonia , Burda Kvetoslava
Published: July 2024

The oxygen evolution within photosystem II (PSII) is one of the most enigmatic processes occurring in nature. It is suggested that external proteins surrounding the oxygen-evolving complex (OEC) not only stabilize it and provide an appropriate ionic environment but also create water channels, which could be involved in triggering the ingress of water and the removal of O2 and protons outside the system. To investigate the influence of these proteins on the rate of oxygen release and the efficiency of OEC function, we developed a measurement protocol for the direct measurement of the kinetics of oxygen release from PSII using a Joliot-type electrode. PSII-enriched tobacco thylakoids were used in the experiments. The results revealed the existence of slow and fast modes of oxygen evolution. This observation is model-independent and requires no specific assumptions about the initial distribution of the OEC states. The gradual removal of exogenous proteins resulted in a slowdown of the rapid phase (~ms) of O2 release and its gradual disappearance while the slow phase (~tens of ms) accelerated. The role of external proteins in regulating the biphasicity and efficiency of oxygen release is discussed based on observed phenomena and current knowledge.
The Impact of HIV and Parasite Single Infection and Coinfection on Telomere Length: A Systematic Review
Authors: Macamo Engelinah D. , Mkhize-Kwitshana Zilungile L. , Mthombeni Julian , Naidoo Pragalathan
Published: July 2024

HIV and parasite infections accelerate biological aging, resulting in immune senescence, apoptosis and cellular damage. Telomere length is considered to be one of the most effective biomarkers of biological aging. HIV and parasite infection have been reported to shorten telomere length in the host. This systematic review aimed to highlight work that explored the influence of HIV and parasite single infections and coinfection on telomere length. Using specific keywords related to the topic of interest, an electronic search of several online databases (Google Scholar, Web of Science, Scopus, Science Direct and PubMed) was conducted to extract eligible articles. The association between HIV infection or parasite infection and telomere length and the association between HIV and parasite coinfection and telomere length were assessed independently. The studies reported were mostly conducted in the European countries. Of the 42 eligible research articles reviewed, HIV and parasite single infections were independently associated with telomere length shortening. Some studies found no association between antiretroviral therapy (ART) and telomere length shortening, while others found an association between ART and telomere length shortening. No studies reported on the association between HIV and parasite coinfection and telomere length. HIV and parasite infections independently accelerate telomere length shortening and biological aging. It is possible that coinfection with HIV and parasites may further accelerate telomere length shortening; however, this is a neglected field of research with no reported studies to date.
Assessment of 2′-Fucosyllactose and Lacto-N-Neotetraose Solution as an Irrigant in E. faecalis-Infected Root Canals: An In Vitro Study
Authors: Puleio Francesco , Pirri Rosario , Tosco Vincenzo , Lizio Angelo Sergio , Tripodi Paola , La Spina Isabella , La Fauci Vincenza , Squeri Raffaele
Published: July 2024

Background: Given the lack of an ideal endodontic irrigant on the market, this study evaluates the antimicrobial potential of a formulated solution of 2′-fucosyllactose and lacto-N-neotetraose against E. faecalis within infected root canals, and explores any associated impacts related to the duration of irrigation. Methods: 32 single-rooted teeth extracted for periodontal reasons were infected with Enterococcus faecalis, and subsequently subjected to endodontic treatment with two different irrigation systems: sodium hypochlorite or a solution of 2′-fucosyllactose and lacto-N-neotetraose. These samples were then incubated in sterile culture media at 37 °C to observe microbial activity through turbidity. The culture broth of each individual sample was assessed as positive or negative by observing the turbidity or lack of turbidity in the culture at the time of evaluation. Results: the analysis of the results obtained from the comparison of groups irrigated with sodium hypochlorite or a solution of 2′-fucosyllactose and lacto-N-neotetraose demonstrates that the case solution has no bactericidal effect against E. faecalis inoculated in the endodontic system. Conclusions: the HMOs used in this study do not have a bactericidal effect on E. faecalis inoculated in an endodontic system.
Hybrid Nanofluid Flow over a Shrinking Rotating Disk: Response Surface Methodology
Authors: Yahaya Rusya Iryanti , Arifin Norihan Md , Pop Ioan , Ali Fadzilah Md , Isa Siti Suzilliana Putri Mohamed
Published: July 2024

For efficient heating and cooling applications, minimum wall shear stress and maximum heat transfer rate are desired. The current study optimized the local skin friction coefficient and Nusselt number in Al2O3-Cu/water hybrid nanofluid flow over a permeable shrinking rotating disk. First, the governing equations and boundary conditions are solved numerically using the bvp4c solver in MATLAB. Von Kármán’s transformations are used to reduce the partial differential equations into solvable non-linear ordinary differential equations. The augmentation of the mass transfer parameter is found to reduce the local skin friction coefficient and Nusselt number. Higher values of these physical quantities of interest are observed in the injection case than in the suction case. Meanwhile, the increase in the magnitude of the shrinking parameter improved and reduced the local skin friction coefficient and Nusselt number, respectively. Then, response surface methodology (RSM) is conducted to understand the interactive impacts of the controlling parameters in optimizing the physical quantities of interest. With a desirability of 66%, the local skin friction coefficient and Nusselt number are optimized at 1.528780016 and 0.888353037 when the shrinking parameter (λ) and mass transfer parameter (S) are −0.8 and −0.6, respectively.
Gemological Characteristics of Blue-Violet Cordierite
Authors: Yan Wenjie , Zhou Zhiyi , Rao Yinghua , Guo Qingfeng
Published: July 2024

Cordierite is a violet-blue gem mineral primarily composed of magnesium aluminum silicate. This study employed three samples of Mg-cordierite and conducted tests on their gemological characteristics, spectroscopic features, and chemical composition using Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, ultraviolet spectrophotometry, X-ray photoelectron spectroscopy (XPS), and electron microprobe. The study also explored and analyzed the polychroism and coloration mechanisms of the samples. The results indicate that the lattice vibrations of the Mg-cordierite samples differ along the directions parallel to the a, b, and c crystallographic axes, leading to certain variations in spectral characteristics among these directions. The article provides experimental evidence for the reasons for the polychroism of cordierite in different crystal axes, which is of great significance in the quality evaluation of cordierite.
The Role of Artificial Intelligence in Early Diagnosis and Molecular Classification of Head and Neck Skin Cancers: A Multidisciplinary Approach
Authors: Semerci Zeliha Merve , Toru Havva Serap , Çobankent Aytekin Esra , Tercanlı Hümeyra , Chiorean Diana Maria , Albayrak Yalçın , Cotoi Ovidiu Simion
Published: July 2024

Cancer remains a significant global health concern, with increasing genetic and metabolic irregularities linked to its onset. Among various forms of cancer, skin cancer, including squamous cell carcinoma, basal cell carcinoma, and melanoma, is on the rise worldwide, often triggered by ultraviolet (UV) radiation. The propensity of skin cancer to metastasize highlights the importance of early detection for successful treatment. This narrative review explores the evolving role of artificial intelligence (AI) in diagnosing head and neck skin cancers from both radiological and pathological perspectives. In the past two decades, AI has made remarkable progress in skin cancer research, driven by advances in computational capabilities, digitalization of medical images, and radiomics data. AI has shown significant promise in image-based diagnosis across various medical domains. In dermatology, AI has played a pivotal role in refining diagnostic and treatment strategies, including genomic risk assessment. This technology offers substantial potential to aid primary clinicians in improving patient outcomes. Studies have demonstrated AI’s effectiveness in identifying skin lesions, categorizing them, and assessing their malignancy, contributing to earlier interventions and better prognosis. The rising incidence and mortality rates of skin cancer, coupled with the high cost of treatment, emphasize the need for early diagnosis. Further research and integration of AI into clinical practice are warranted to maximize its benefits in skin cancer diagnosis and treatment.
Sequential Comparison of Knee Muscle Strength after Anterior Cruciate Ligament Reconstruction between Hamstring Autograft and Tibialis Anterior Allograft: Propensity Score Matched Pair Analysis
Authors: Jung Se-Han , Choi Chong Hyuk , Kim Sung-Hwan , Chung Kwangho , Moon Hyun-Soo , Sim Woongseob , Jung Min
Published: July 2024

Among the graft options for anterior cruciate ligament reconstruction (ACLR), hamstring autografts are widely regarded as the preferred choice for primary ACLR among orthopedic surgeons worldwide. However, concerns persist regarding postoperative knee flexor weakness. We aimed to compare knee extensor and flexor strengths between hamstring autograft and tibialis anterior allograft groups in ACLR patients, who were propensity score-matched based on baseline characteristics. A retrospective analysis included 58 matched pairs who underwent isokinetic strength tests at 6 and 12 months post operation. Isokinetic muscle strength tests found no significant difference in knee extensor and flexor strength at 6 months post operation between the hamstring autograft and tibial anterior allograft groups. At 12 months, the hamstring autograft group exhibited significantly greater knee flexor deficit (total work and average power) compared to the allograft group, despite no differences in extensor strength or patient-reported outcomes. This study highlights the impact of hamstring autograft harvesting on muscle strength and recovery following ACLR in short-term period.
Association of Number of Comorbid Conditions and Pain among United States Adults
Authors: Axon David R. , Eckert Becka
Published: July 2024

Studies have explored the association of particular conditions, or combinations of conditions, and pain among specific populations. However, there is limited information regarding the association of the number of comorbid conditions, as well as other demographic, economic, health, and limitation variables, with pain among adults in the United States. This cross-sectional database study aimed to examine the relationships between number of comorbid conditions (including cancer, arthritis, joint pain, stroke, heart attack, angina, coronary heart disease, high cholesterol, high blood pressure, other heart diseases, diabetes, asthma, chronic bronchitis, and emphysema), demographic, economic, health, and limitation variables with pain among United States adults using 2021 Medical Expenditure Panel Survey data. A multivariable logistic model assessed the association between the number of comorbid conditions (≥6, 5, 4, 3, 2, 1, versus 0 conditions) and quite a bit/extreme (versus little/moderate) pain, adjusting for demographic, economic, health, and limitation variables. The study found that greater numbers of comorbid conditions were associated with higher odds of quite a bit or extreme pain. In addition, age, education, employment, income, overall health, regular physical activity, and three limitation variables were each associated with pain in the multivariable model. These findings offer insight into the association between number of comorbid conditions and other variables with pain and suggest areas where interventions may be helpful to help improve pain outcomes for United States adults.
Investigation of Oral Health in Children from Urban Slums of Nairobi, Kenya
Authors: Di Giorgio Gianni , De Pasquale Simona , Battaglia Enrico , Zumbo Giulia , Mollica Cristina , D’Ecclesia Rita , Polimeni Antonella , Bossù Maurizio
Published: July 2024

For children living in the urban slums of Nairobi (Kenya), primary health conditions are not guaranteed, and oral diseases add further concern at social and institutional levels beyond the general poverty conditions. This study aims at determining the factors that influence the oral health status of children living in Nairobi slums. A cross-sectional study on school-aged subjects was conducted in June 2022 in three urban slum areas of Nairobi through a pediatric dental screening. The PI (Plaque Index), CPITN (Community Periodontal Index of Treatment Needs), and dmft (decayed, missing, and filled teeth index—deciduous) were considered as primary outcomes of dental health. Multivariate statistical analysis, based on ordinal and zero-inflated negative binomial regression models, was conducted to identify determinants of the oral outcomes in a wide set of potential predictors. A sample of 359 children aged 2–17 was examined. The PI was significantly associated with age, the type of bite, and the use of a toothbrush. The CPITN is influenced by different types of malocclusions, abnormal frenulum, dental trauma, and fluorosis. Dietary habits were found to significantly impact the susceptibility to dental caries. Fluorosis and a dental visit in the last year were highlighted as risk and protective factors, respectively, against higher rates of caries. The oral health features of children living in Nairobi slums are differently affected by socio-demographic conditions, dietary habits, dental characteristics, and oral care practices.
Fed4UL: A Cloud–Edge–End Collaborative Federated Learning Framework for Addressing the Non-IID Data Issue in UAV Logistics
Authors: Zhang Chong , Liu Xiao , Yao Aiting , Bai Jun , Dong Chengzu , Pal Shantanu , Jiang Frank
Published: July 2024

Artificial intelligence and the Internet of Things (IoT) have brought great convenience to people’s everyday lives. With the emergence of edge computing, IoT devices such as unmanned aerial vehicles (UAVs) can process data instantly at the point of generation, which significantly decreases the requirement for on-board processing power and minimises the data transfer time to enable real-time applications. Meanwhile, with federated learning (FL), UAVs can enhance their intelligent decision-making capabilities by learning from other UAVs without directly accessing their data. This facilitates rapid model iteration and improvement while safeguarding data privacy. However, in many UAV applications such as UAV logistics, different UAVs may perform different tasks and cover different areas, which can result in heterogeneous data and add to the problem of non-independent and identically distributed (Non-IID) data for model training. To address such a problem, we introduce a novel cloud–edge–end collaborative FL framework, which organises and combines local clients through clustering and aggregation. By employing the cosine similarity, we identified and integrated the most appropriate local model into the global model, which can effectively address the issue of Non-IID data in UAV logistics. The experimental results showed that our approach outperformed traditional FL algorithms on two real-world datasets, CIFAR-10 and MNIST.
Compact Internally Matched High-Power Power Amplifier with a Wide Frequency Band of 0.8–2 GHz
Authors: Li Caoyu , Zhang Ziliang , Su Xiang , Li Yue , Liang Xinru , Pei Yi , Chen Changchang , Xu Yuehang
Published: July 2024

In this paper, a GaN high-electron-mobility transistor (HEMT) compact high-power wide-band power amplifier with an operation frequency from 0.8 GHz to 2 GHz is proposed. In order to realize a compact design, an internally matched method is employed. A wide-band matching strategy with an LC network and a multi-stage wide-band power combiner/divider is introduced in this design to achieve a wide bandwidth. A power combination structure is applied to have high output power. Wire-spiral inductance and film capacitors are employed to construct the compact matching network. The equivalent inductance of the bonding wire is also involved in the matching network. Experimental results show that the PAE (power-added efficiency) during the whole operation’s bandwidth (0.8 GHz to 2.0 GHz) is from 40% to 57%. The output power can reach from 48.3 dBm to 49.8 dBm with a circuit size of 30.8×27.4mm2.
Centralized Finite State Machine Control to Increase the Production Rate in a Crusher Circuit
Authors: da Silva Moisés T. , Bitarães Santino M. , Yamashita Andre S. , Torre Marcos P. , Moreira Vincius da S. , Euzébio Thiago A. M.
Published: July 2024

Crushing is a critical operation in mineral processing, and its efficient performance is vital for minimizing energy consumption, maximizing productivity, and maintaining product quality. However, due to variations in feed material characteristics and safety constraints, achieving the intended circuit performance can be challenging. In this study, a centralized control strategy based on a finite state machine (FSM) is developed to improve the operations of an iron ore crushing circuit. The aim is to increase productivity by manipulating the closed-side-setting (CSS) of cone crushers and the speed of an apron feeder while considering intermediate storage silo levels and cone crusher power limits, as well as product quality. A dynamic simulation was conducted to compare the proposed control strategy with the usual practice of setting CSS to a constant value. Four scenarios were analyzed based on variations in bond work index (BWI) and particle size distribution. The simulation results demonstrate that the proposed control strategy increased average productivity by 6.88% and 48.77% when compared to the operation with a constant CSS of 38 mm and 41 mm, respectively. The proposed strategy resulted in smoother oscillation without interlocking, and it maintained constant flow rates. This ultimately improved circuit reliability and predictability, leading to reduced maintenance costs.
Towards Sustainable Energy Communities: Integrating Time-of-Use Pricing and Techno-Economic Analysis for Optimal Design—A Case Study of Valongo, Portugal
Authors: Dobric Goran , Zarkovic Mileta
Published: July 2024

This paper presents a comprehensive analysis of optimal energy community design, leveraging time-of-use pricing mechanisms and techno-economic parameters. Focusing on a case study of Valongo, Portugal, this study explores the intricate interplay between energy infrastructure planning, economic considerations, and pricing dynamics. Through a systematic approach, various factors, such as renewable energy integration, demand–response strategies, and investment costs, are evaluated to formulate an efficient and sustainable energy community model. Time-of-use pricing schemes are incorporated to reflect the dynamic nature of energy markets and consumer behavior. By integrating techno-economic analyses, this study aims to optimize energy resource allocation while ensuring cost-effectiveness and environmental sustainability. The influence of optimized sizes of photovoltaics (PV), battery storage, and electrical vehicles (EVs) on self-sufficiency rates, self-consumption rates and CO2 savings is analyzed. The findings offer valuable insights into the design and implementation of energy communities in urban settings, highlighting the importance of adaptive strategies in the transition towards a resilient and low-carbon energy future. The novelty of this paper lies in its comprehensive approach to energy community design, which integrates time-of-use pricing mechanisms with techno-economic parameters. By focusing on the specific case of Valongo, Portugal, it addresses the unique challenges and opportunities present in urban settings. Additionally, the analysis considers the interaction between renewable energy production, demand profiles and investment costs, providing valuable insights for optimizing resource allocation and achieving both cost-effectiveness and environmental sustainability.
Towards Sustainable Consumption: Generation Z’s Views on Ownership and Access in the Sharing Economy
Authors: Surmacz Tomasz , Wierzbiński Bogdan , Kuźniar Wiesława , Witek Lucyna
Published: July 2024

The sharing economy substitutes owning with accessing, promoting sustainable development by reducing excessive consumption and resource overuse, which harm the environment. Sharing reduces resource and energy use, lowering emissions and waste disposal costs, thus reducing environmental damage. This study identifies key factors that encourage Generation Z to embrace the sharing economy for goods and services, emphasizing its role in sustainable development. Conducted in May 2023, the study surveyed 442 Polish Generation Z individuals to examine their attitudes and behaviours regarding climate change. The research focused on this demographic due to their crucial role in addressing global issues. Data was collected using the CAWI method and analyzed with IBM SPSS and AMOS software through structural equation modelling (SEM). The analysis revealed three factors: Willingness to Share for Savings (WSS), Digital Customer Engagement (DCE), and Environmental Concern (EC). The results show that ecological concerns and digital engagement significantly influence people’s willingness to share, boosting environmental awareness and cost-saving behaviours. Generation Z’s sharing propensity and environmental consciousness are significantly shaped by digital engagement.
Investigation of Split Diesel Injections in Methanol/Diesel Dual-Fuel Combustion in an Optical Engine
Authors: Zhang Hongyi , Zhao Zhonghui , Wu Jun , Wang Xinyan , Ouyang Weihao , Wang Zhaowen
Published: July 2024

Methanol is a promising alternative fuel due to its wide availability of raw materials, mature production processes, and low production cost. However, because of the low cetane number, methanol must include a more reactive fuel to assist with combustion when used in compression ignition (CI) engines. In this study, based on the optical CI engine platform, methanol is injected into the intake port, and diesel is directly injected into the cylinder to achieve dual-fuel combustion. The effects of the methanol energy ratios and diesel split injection strategies on combustion are investigated. The results show that the premixed blue flame was mainly concentrated in the near wall region, whereas the yellow flame produced by diesel combustion tended to concentrate in the central region as the methanol energy ratio increased. When the methanol energy ratio exceeded 50%, the ignition delay was significantly prolonged, while the flame area was greatly reduced. Meanwhile, the peak values for the cylinder pressure and heat release rate decreased significantly, indicating a significant deterioration in combustion. At the earlier diesel pre-injection timing at −58°, the overall dual-fuel combustion at each main injection timing exhibited low-temperature premixed combustion characteristics, with a lower peak exothermic rate and flame brightness. At the later pre-injection timing at −33°, the spray flame at all main injection timings could be observed, with higher peak heat release rates and indications of thermal efficiency. Combustion at later main injection timings was characterized by diffusion combustion, and the main injection timing could effectively regulate the combustion process through phase adjustment.
Development of a MELCOR Model for LVR-15 Severe Accidents Assessment
Authors: Flores y Flores Alain , Mazzini Guido , Dambrosio Antonio
Published: July 2024

LVR-15 is a light-water-tank-type research reactor placed in a stainless-steel vessel under a shielding cover located in the Research Centre Rez (CVR) near Prague. It is operated at a steady-state power of up to 10 MWt under atmospheric pressure and is cooled by forced circulation. In 2011, the fuel was replaced, going from high-enriched uranium (HEU) to low-enriched uranium (LEU). After 2017, the State Office for Nuclear Safety (SUJB) asked CVR to evaluate the LVR-15 under Design Extended Conditions B (DEC-B). For this reason, a new model was developed in the MELCOR code, which allows for modelling the progression of a severe accident (SA) in light-water nuclear power plants and estimating the behaviour of the reactor under SA conditions. The model was built by collecting information about the LVR-15. Since the research reactor can have different core configurations according to the location of the core components, the core configuration with the most fuel (hottest campaign K221) was selected. Then, to create the radial nodalisation, the details of the core components were obtained and grouped in five radial rings and 27 axial levels. The simulation was run with the boundary conditions collected from campaign K221, and the results were compared with the reference values of the campaign with a negligible percentage of error. For the coolant inlet and outlet temperature, the reference values were 318.18 K and 323.5 K, respectively, while for the simulation, the steady state reached 319 K for the inlet temperature and 324 K for the outlet temperature. Additionally, the cladding temperature of the hottest assembly was compared with the reference value (353.72 K) and the steady-state simulation results (362 K). In future work, different transients leading to severe accidents will be simulated. When simulating the LVR-15 reactor with MELCOR, specific attention is required for the aluminium-cladded fuel assemblies, as the model requires some assumptions to cope with the phenomenological limitations.
Linear Quadratic Gaussian Controller for Single-Ended Primary Inductor Converter via Integral Linear Quadratic Regulator Merged with an Offline Kalman Filter
Authors: El Haj Youssef , Sood Vijay K.
Published: July 2024

This paper introduces a Linear Quadratic Gaussian (LQG) controller for a Single-Ended Primary Inductor Converter (SEPIC). The LQG design is based on merging an integral Linear Quadratic Regulator (LQR) with an offline Kalman Filter (commonly referred to as a Linear Quadratic Estimator (LQE)). The robustness of the LQG controller is guaranteed based on the separation principle. This manuscript addresses the need to use observer-based systems for the fourth-order SEPIC, which needs a sensor reduction as an essential requirement. This paper provides a comprehensive, yet systematic, approach to designing the LQG system. The work validates the convergences of the states in an LQG system to an actual value. Furthermore, it compares the performance of an LQG system with a benchmark Type-II industrial controller by means of a simulation of the switched converter model in the Simulink/MATLAB 2023a environment.
Single-Sensor Global MPPT for PV System Interconnected with DC Link Using Recent Red-Tailed Hawk Algorithm
Authors: Almousa Motab Turki , Gomaa Mohamed R. , Ghasemi Mostafa , Louzazni Mohamed
Published: July 2024

The primary disadvantage of solar photovoltaic systems, particularly in partial shadowing conditions (PSC), is their low efficiency. A power–voltage curve with a homogenous distribution of solar irradiation often has a single maximum power point (MPP). Without a doubt, it can be extracted using any conventional tracker—for instance, perturb and observe. On the other hand, under PSC, the situation is entirely different since, depending on the number of distinct solar irradiation levels, the power–voltage curve has numerous MPPs (i.e., multiple local points and one global point). Conventional MPPTs can only extract the first point since they are unable to distinguish between local and global MPP. Thus, to track the global MPP, an optimized MPPT based on optimization algorithms is needed. The majority of global MPPT techniques seen in the literature call for sensors for voltage and current in addition to, occasionally, temperature and/or solar irradiance, which raises the cost of the system. Therefore, a single-sensor global MPPT based on the recent red-tailed hawk (RTH) algorithm for a PV system interconnected with a DC link operating under PSC is presented. Reducing the number of sensors leads to a decrease in the cost of a controller. To prove the superiority of the RTH, the results are compared with several metaheuristic algorithms. Three shading scenarios are considered, with the idea of changing the shading scenario to change the location of the global MPP to measure the consistency of the algorithms. The results verified the effectiveness of the suggested global MPPT based on the RTH in precisely capturing the global MPP compared with other methods. As an example, for the first shading situation, the mean PV power values varied between 6835.63 W and 5925.58 W. The RTH reaches the highest PV power of 6835.63 W flowing through particle swarm optimization (6808.64 W), whereas greylag goose optimizer achieved the smallest PV power production of 5925.58 W.
Does Crime Influence Investment in Renewable Energy Sources? Empirical Evidence from Italy
Authors: Scandurra Giuseppe , Carfora Alfonso , Thomas Antonio
Published: July 2024

The Sustainable Development Goals are significantly increasing investments in the production of energy from renewable sources (RESs). To this end, the supply of monetary incentives by public institutions has increased sharply. This flow of money inevitably attracts the attention of criminal organizations (henceforth COs) that use their power to increase the volumes of investments, while public authorities might react by deciding not to make investments in RESs in areas at risk of distorted use of incentives. In this context, the research question is as follows: does the presence of COs slow down or encourage investment in RESs? Until now, this topic has received little attention from researchers, at least in the European Union. In particular, the presence of COs is particularly pervasive in the economic system of Italy. Given the heterogeneity of this country, a spatial econometric approach was used, taking into account geographical dependency relationships and their impact on the relevant variables. The main result of the research shows a negative relationship between Italian areas with higher CO levels and RES investments. In other words, investments are discouraged in these regions. This situation is detrimental to the target regions in terms of sustainable development and increasing the gross national product (GNP). Furthermore, we found that micro-crime cannot in any way influence investments in RESs.
Correction: Hankin et al. Second-Entry Burns Reduce Mid-Canopy Fuels and Create Resilient Forest Structure in Yosemite National Park, California. Forests 2022, 13, 1512
Authors: Hankin Lacey E. , Anderson Chad T.
Published: July 2024

In the original publication [...]
Modeling Forest Response to Climate Change
Authors: Marano Gina , Dalmonech Daniela , Collalti Alessio
Published: July 2024

In an era marked by unprecedented climate shifts, understanding the intricate responses of forest ecosystems to these changes is of paramount importance [...]
Incorporating Spatial Autocorrelation into GPP Estimation Using Eigenvector Spatial Filtering
Authors: Xu Rui , Chen Yumin , Han Ge , Guo Meiyu , Wilson John P. , Min Wankun , Ma Jianshen
Published: July 2024

Terrestrial gross primary productivity (GPP) is a critical part of land carbon fluxes. Accurately quantifying GPP in terrestrial ecosystems and understanding its spatiotemporal dynamics are essential for assessing the capability of vegetation to absorb carbon from the atmosphere. Nevertheless, traditional remote sensing estimation models often require complex parameters and data inputs, and they do not account for spatial effects resulting from the distribution of monitoring sites. This can lead to biased parameter estimation and unstable results. To address these challenges, we have raised a spatial autocorrelation light gradient boosting machine model (SA-LGBM) to enhance GPP estimation. SA-LGBM combines reflectance information from remote sensing observations with eigenvector spatial filtering (ESF) methods to create a set of variables that capture continuous spatiotemporal variations in plant functional types and GPP. SA-LGBM demonstrates promising results when compared to existing GPP products. With the inclusion of eigenvectors, we observed an 8.5% increase in R2 and a 20.8% decrease in RMSE. Furthermore, the residuals of the model became more random, reducing the inherent spatial effects within them. In summary, SA-LGBM represents the first attempt to quantify the impact of spatial autocorrelation and addresses the limitations of underestimation present in existing GPP products. Moreover, SA-LGBM exhibits favorable applicability across various vegetation types.