bluuebunny/crossref_metadata_2025 huggingface dataset:
The Global Epidemiology of Bovine Leukemia Virus: Current Trends and Future Implications
Authors: Lv Guanxin , Wang Jianfa , Lian Shuai , Wang Hai , Wu Rui
Published: January 2024

Bovine leukemia virus (BLV) is a retrovirus that causes enzootic bovine leucosis (EBL), which is the most significant neoplastic disease in cattle. Although EBL has been successfully eradicated in most European countries, infections continue to rise in Argentina, Brazil, Canada, Japan, and the United States. BLV imposes a substantial economic burden on the cattle industry, particularly in dairy farming, as it leads to a decline in animal production performance and increases the risk of disease. Moreover, trade restrictions on diseased animals and products between countries and regions further exacerbate the problem. Recent studies have also identified fragments of BLV nucleic acid in human breast cancer tissues, raising concerns for public health. Due to the absence of an effective vaccine, controlling the disease is challenging. Therefore, it is crucial to accurately detect and diagnose BLV at an early stage to control its spread and minimize economic losses. This review provides a comprehensive examination of BLV, encompassing its genomic structure, epidemiology, modes of transmission, clinical symptoms, detection methods, hazards, and control strategies. The aim is to provide strategic information for future BLV research.
Analyzing Cattle Activity Patterns with Ear Tag Accelerometer Data
Authors: Hu Shuwen , Reverter Antonio , Arablouei Reza , Bishop-Hurley Greg , McNally Jody , Alvarenga Flavio , Ingham Aaron
Published: January 2024

In this study, we equip two breeds of cattle located in tropical and temperate climates with smart ear tags containing triaxial accelerometers to measure their activity levels across different time periods. We produce activity profiles when measured by each of four statistical features, the mean, median, standard deviation, and median absolute deviation of the Euclidean norm of either unfiltered or high-pass-filtered accelerometer readings over five-minute windows. We then aggregate the values from the 5 min windows into hourly or daily (24 h) totals to produce activity profiles for animals kept in each of the test environments. To gain a better understanding of the variation between the peak and nadir activity levels within a 24 h period, we divide each day into multiple equal-length intervals, which can range from 2 to 96 intervals. We then calculate a statistical measure, called daily differential activity (DDA), by computing the differences in feature values for each interval pair. Our findings demonstrate that patterns within the activity profile are more clearly visualised from readings that have been subject to high-pass filtering and that the median of the acceleration vector norm is the most reliable feature for characterising activity and calculating the DDA measure. The underlying causes for these differences remain elusive and is likely attributable to environmental factors, cattle breeds, or management practices. Activity profiles produced from the standard deviation (a feature routinely applied to the quantification of activity level) showed less uniformity between animals and larger variation in values overall. Assessing activity using ear tag accelerometers holds promise for monitoring animal health and welfare. However, optimal results may only be attainable when true diurnal patterns are detected and accounted for.
Farmstead-Specific Weather Risk Prediction Technique Based on High-Resolution Weather Grid Distribution
Authors: Kim Dae-Jun , Kim Jin-Hee , Yun Eun-Jeong , Kang Dae Gyoon , Ban Eunhye
Published: January 2024

In recent years, the importance and severity of weather-related disasters have escalated, attributed to rising temperatures and the occurrence of extreme weather events due to global warming. The focus of disaster management has shifted from crisis management (e.g., repairing and recovering from damage caused by natural disasters) to risk management (e.g., prediction and preparation) while concentrating on early warning, thanks to the development of media and communication conditions. The Rural Development Administration (Korea) has developed the “early warning service for weather risk management in the agricultural sector” that detects weather risks for crops from high-resolution weather information in advance and provides customized information to respond to possible disaster risks in advance in response to the increasing number of extreme weather events. The core technology of this service is damage prediction technology that determines the overall agricultural weather risk level by quantifying the current growth stage of cultivated crops and the probability of possible weather disasters according to the weather conditions of the farm. Agrometeorological disasters are damages caused by weather conditions that can affect crops and can be predicted by estimating the probability of damage that may occur from the interaction between hazardous weather and crop characteristics. This review introduces the classification of possible weather risks by their occurrence mechanisms, based on the developmental stage of crops and prediction techniques that have been developed or applied to date. The accumulated crop growth and weather risk information is expected to be utilized as support material for farming decision-making, which helps farmers proactively respond to crop damage due to extreme weather events by providing highly reliable disaster forecasts through the advancement of prediction technology.
Dosimetric Comparison Study of Proton Therapy Using Line Scanning versus Passive Scattering and Volumetric Modulated Arc Therapy for Localized Prostate Cancer
Authors: Takagi Masaru , Hasegawa Yasuhiro , Tateoka Kunihiko , Takada Yu , Hareyama Masato
Published: January 2024

Background: The proton irradiation modality has transitioned from passive scattering (PS) to pencil beam scanning. Nevertheless, the documented outcomes predominantly rely on PS. Methods: Thirty patients diagnosed with prostate cancer were selected to assess treatment planning across line scanning (LS), PS, and volumetric modulated arc therapy (VMAT). Dose constraints encompassed clinical target volume (CTV) D98 ≥ 73.0 Gy (RBE), rectal wall V65 < 17% and V40 < 35%, and bladder wall V65 < 25% and V40 < 50%. The CTV, rectal wall, and bladder wall dose volumes were calculated and evaluated using the Freidman test. Results: The LS technique adhered to all dose limitations. For the rectal and bladder walls, 10 (33.3%) and 21 (70.0%) patients in the PS method and 5 (16.7%) and 1 (3.3%) patients in VMAT, respectively, failed to meet the stipulated requirements. The wide ranges of the rectal and bladder wall volumes (V10-70) were lower with LS than with PS and VMAT. LS outperformed VMAT across all dose–volume rectal and bladder wall indices. Conclusion: The LS method demonstrated a reduction in rectal and bladder doses relative to PS and VMAT, thereby suggesting the potential for mitigating toxicities.
Artificial Intelligence Analysis Using MRI and PET Imaging in Gliomas: A Narrative Review
Authors: Alongi Pierpaolo , Arnone Annachiara , Vultaggio Viola , Fraternali Alessandro , Versari Annibale , Casali Cecilia , Arnone Gaspare , DiMeco Francesco , Vetrano Ignazio Gaspare
Published: January 2024

The lack of early detection and a high rate of recurrence/progression after surgery are defined as the most common causes of a very poor prognosis of Gliomas. The developments of quantification systems with special regards to artificial intelligence (AI) on medical images (CT, MRI, PET) are under evaluation in the clinical and research context in view of several applications providing different information related to the reconstruction of imaging, the segmentation of tissues acquired, the selection of features, and the proper data analyses. Different approaches of AI have been proposed as the machine and deep learning, which utilize artificial neural networks inspired by neuronal architectures. In addition, new systems have been developed using AI techniques to offer suggestions or make decisions in medical diagnosis, emulating the judgment of radiologist experts. The potential clinical role of AI focuses on the prediction of disease progression in more aggressive forms in gliomas, differential diagnosis (pseudoprogression vs. proper progression), and the follow-up of aggressive gliomas. This narrative Review will focus on the available applications of AI in brain tumor diagnosis, mainly related to malignant gliomas, with particular attention to the postoperative application of MRI and PET imaging, considering the current state of technical approach and the evaluation after treatment (including surgery, radiotherapy/chemotherapy, and prognostic stratification).
Predicting Immunotherapy Outcomes in Glioblastoma Patients through Machine Learning
Authors: Mestrallet Guillaume
Published: January 2024

Glioblastoma is a highly aggressive cancer associated with a dismal prognosis, with a mere 5% of patients surviving beyond five years post diagnosis. Current therapeutic modalities encompass surgical intervention, radiotherapy, chemotherapy, and immune checkpoint inhibitors (ICBs). However, the efficacy of ICBs remains limited in glioblastoma patients, necessitating a proactive approach to anticipate treatment response and resistance. In this comprehensive study, we conducted a rigorous analysis involving two distinct glioblastoma patient cohorts subjected to PD-1 blockade treatments. Our investigation revealed that a significant portion (60%) of patients exhibit persistent disease progression despite ICB intervention. To elucidate the underpinnings of resistance, we characterized the immune profiles of glioblastoma patients with continued cancer progression following anti-PD1 therapy. These profiles revealed multifaceted defects, encompassing compromised macrophage, monocyte, and T follicular helper responses, impaired antigen presentation, aberrant regulatory T cell (Tregs) responses, and heightened expression of immunosuppressive molecules (TGFB, IL2RA, and CD276). Building upon these resistance profiles, we leveraged cutting-edge machine learning algorithms to develop predictive models and accompanying software. This innovative computational tool achieved remarkable success, accurately forecasting the progression status of 82.82% of the glioblastoma patients in our study following ICBs, based on their unique immune characteristics. In conclusion, our pioneering approach advocates for the personalization of immunotherapy in glioblastoma patients. By harnessing patient-specific attributes and computational predictions, we offer a promising avenue for the enhancement of clinical outcomes in the realm of immunotherapy. This paradigm shift towards tailored therapies underscores the potential to revolutionize the management of glioblastoma, opening new horizons for improved patient care.
Exploring Helium Ions’ Potential for Post-Mastectomy Left-Sided Breast Cancer Radiotherapy
Authors: Bonaccorsi Santa Gabriella , Tessonnier Thomas , Hoeltgen Line , Meixner Eva , Harrabi Semi , Hörner-Rieber Juliane , Haberer Thomas , Abdollahi Amir , Debus Jürgen , Mairani Andrea
Published: January 2024

Proton therapy presents a promising modality for treating left-sided breast cancer due to its unique dose distribution. Helium ions provide increased conformality thanks to a reduced lateral scattering. Consequently, the potential clinical benefit of both techniques was explored. An explorative treatment planning study involving ten patients, previously treated with VMAT (Volumetric Modulated Arc Therapy) for 50 Gy in 25 fractions for locally advanced, node-positive breast cancer, was carried out using proton pencil beam therapy with a fixed relative biological effectiveness (RBE) of 1.1 and helium therapy with a variable RBE described by the mMKM (modified microdosimetric kinetic model). Results indicated that target coverage was improved with particle therapy for both the clinical target volume and especially the internal mammary lymph nodes compared to VMAT. Median dose value analysis revealed that proton and helium plans provided lower dose on the left anterior descending artery (LAD), heart, lungs and right breast than VMAT. Notably, helium therapy exhibited improved ipsilateral lung sparing over protons. Employing NTCP models as available in the literature, helium therapy showed a lower probability of grade ≤ 2 radiation pneumonitis (22% for photons, 5% for protons and 2% for helium ions), while both proton and helium ions reduce the probability of major coronary events with respect to VMAT.
Detection of Genomic Structural Variations Associated with Drug Sensitivity and Resistance in Acute Leukemia
Authors: Finlay Darren , Murad Rabi , Hong Karl , Lee Joyce , Pang Andy Wing Chun , Lai Chi-Yu , Clifford Benjamin , Burian Carol , Mason James , Hastie Alex R. , Yin Jun , Vuori Kristiina
Published: January 2024

Acute leukemia is a particularly problematic collection of hematological cancers, and, while somewhat rare, the survival rate of patients is typically abysmal without bone marrow transplantation. Furthermore, traditional chemotherapies used as standard-of-care for patients cause significant side effects. Understanding the evolution of leukemia to identify novel targets and, therefore, drug treatment regimens is a significant medical need. Genomic rearrangements and other structural variations (SVs) have long been known to be causative and pathogenic in multiple types of cancer, including leukemia. These SVs may be involved in cancer initiation, progression, clonal evolution, and drug resistance, and a better understanding of SVs from individual patients may help guide therapeutic options. Here, we show the utilization of optical genome mapping (OGM) to detect known and novel SVs in the samples of patients with leukemia. Importantly, this technology provides an unprecedented level of granularity and quantitation unavailable to other current techniques and allows for the unbiased detection of novel SVs, which may be relevant to disease pathogenesis and/or drug resistance. Coupled with the chemosensitivities of these samples to FDA-approved oncology drugs, we show how an impartial integrative analysis of these diverse datasets can be used to associate the detected genomic rearrangements with multiple drug sensitivity profiles. Indeed, an insertion in the gene MUSK is shown to be associated with increased sensitivity to the clinically relevant agent Idarubicin, while partial tandem duplication events in the KMT2A gene are related to the efficacy of another frontline treatment, Cytarabine.
Dkk1 as a Prognostic Marker for Neoadjuvant Chemotherapy Response in Breast Cancer Patients
Authors: Kasoha Mariz , Steinbach Anna K. , Bohle Rainer M. , Linxweiler Barbara , Haj Hamoud Bashar , Doerk Merle , Nigdelis Meletios P. , Stotz Lisa , Zimmermann Julia S. M. , Solomayer Erich-Franz , Kaya Askin C. , Radosa Julia C.
Published: January 2024

Purpose: To investigate the role of Dkk1 as a predictor of response to NACT in BC patients. Methods: This retrospective monocentric study included 145 women who had undergone NACT followed by breast surgery. Dkk1 protein expression was assessed using immunohistochemistry staining in core needle biopsies and mammary carcinoma specimens. Results: Dkk1 levels were lower in treated BC tumours than in untreated tumours. The outcomes of 68 matched pre- and post-therapy tissues showed that Dkk1 levels in mammary carcinoma tissues were significantly predicted by levels in core needle biopsies and that Dkk1 expression was reduced in 83% of cases. Smaller cT stage, positive Her2 expression, and decreased Dkk1-IRS in core needle biopsy tissues were all independent predictors of regression grade (R4), according to Sinn. However, the percentage of Dkk1 expression differences prior to and following NACT had no effect on PFS or OS. Conclusions: In this study, we demonstrated for the first time that Dkk1 could be identified as an independent predictor of NACT response in BC patients, particularly those with TNBC. Further research with a multicentric expanded (pre-/post-therapy) sample set and better-defined populations in terms of molecular subtypes, therapy modality, and long-term follow-up is recommended to obtain more solid evidence.
Surface Modification of Fe-ZSM-5 Using Mg for a Reduced Catalytic Pyrolysis Temperature of Low-Density Polyethylene to Produce Light Olefin
Authors: Li Yincui , Liu Ting , Deng Shengnan , Liu Xiao , Meng Qian , Tang Mengxue , Wu Xueying , Zhang Huawei
Published: January 2024

Although the catalytic pyrolysis of low-density polyethylene (LDPE) to produce light olefin has shown potential industrial application advantages, it has generally suffered when using higher pyrolysis temperatures. In this work, Mg-modified Fe-ZSM-5 was used for catalytic conversion of LDPE to obtain light olefin in a fixed bed reactor. The effects of catalyst types, pyrolysis temperatures, and Mg loading on the yield of light olefin were investigated. The 1 wt% Mg loading slightly improved the yield of light olefin to 38.87 wt% at 395 °C, lowering the temperature of the pyrolysis reaction. We considered that the higher light olefin yield of Fe-Mg-ZSM-5 was attributed to the introduction of Mg, where Mg regulated the surface acidity of the catalyst, inhibited the secondary cracking reaction, and reduced coking during the pyrolysis process. Furthermore, the addition of Mg also dramatically reduced the average particle size of Fe oxides from 40 nm to 10 nm, which is conducive to a lower catalytic reaction temperature. Finally, the spent catalyst could be easily regenerated at the conditions of 600 °C in airflow with a heating rate of 10 °C/min for 1 h, and the light olefin yield remained higher than 36.71 wt% after five cycles, indicating its excellent regeneration performance.
Food Systems and Planetary Health Nexus Elective: A Novel Approach to A Medical Education Imperative for the 21st Century
Authors: Goldman Modan , Vaidyam Aditya , Parupalli Sindhu , Rosencranz Holly , Ramkumar Davendra , Ramkumar Japhia
Published: January 2024

This is a report on an inaugural medical student elective, Microbiomes Matter: The Path to Regenerative Systems of Farm, Food, and Health, from the perspective of the student participants. Recognizing food as medicine is gaining support across many settings. However, little is known about how medical schools engage in this holistic approach. Integrating food systems and the connections to soil and human health through microbiomes into medical education represents a transformative shift towards more holistic healthcare practices. We describe the course content and impact of a medical school elective in food systems. This elective employed a systems lens and planetary health perspective to explore the impact of climatic factors and environmental degradation on farms, nutrition, and non-communicable lifestyle diseases. Through the two-week course, medical students gained insights into sustainable food systems, supply chains, and the importance of regenerative agriculture. The course also provided a comprehensive overview of the gut microbiome, nutrition, technologies, and the economics of food systems, including their impact on lifestyle diseases. By fostering a systems-oriented mindset, this elective better equips medical students to address the complex challenges of human and planetary health and promote regenerative, sustainable, culturally sensitive, and robust systems of farm, food, and health.
Improved Heat Dissipation of Dip-Coated Single-Walled Carbon Nanotube/Mesh Sheets with High Flexibility and Free-Standing Strength for Thermoelectric Generators
Authors: Miura Katsuma , Amezawa Takuya , Tanaka Saburo , Takashiri Masayuki
Published: January 2024

Single-walled carbon nanotubes (SWCNTs) are promising thermoelectric materials used in thermoelectric generators (TEGs) to power sensors. However, the limitation of SWCNTs is their high thermal conductivity, which makes it difficult to create a sufficient temperature difference. In this study, we fabricated dip-coated SWCNT/mesh sheets using an SWCNT dispersion. Several types of mesh materials were tested, and the most suitable material was polyphenylene sulfide (PPS). SWCNTs were uniformly deposited on the PPS mesh surface without filling the mesh openings. The SWCNT/PPS mesh sheets exhibited flexibility and free-standing strength. When the edge of the SWCNT/PPS mesh sheets were heated, a higher temperature gradient was produced compared with that of the conventional SWCNT film owing to the increase in heat dissipation. A flexible and free-standing TEG with an area of 1200 mm2, fabricated using SWCNT/PPS mesh sheets, exhibited an output voltage of 31.5 mV and maximum power of 631 nW at a temperature difference of 60 K (Tlow: 320 K). When the TEG was exposed to wind at 3 m/s, temperature difference further increased, and the performance of the TEG increased by a factor of 1.3 for output voltage and 1.6 for maximum power. Therefore, we demonstrated that the TEG’s performance could be improved using SWCNT/PPS mesh sheets.
Effects of Fibre-Reinforced Plastic Wedge-Stick Slope on the Performance of Wind-Turbine Blade Root Connections
Authors: Sun Yuanrong , Qu Yihang , Hu Congli , Qi Peiyu , Liu Huawei , Li Jianbo
Published: January 2024

Bushing-insert connections have emerged as efficient blade root connection designs. Bushing-insert connections with fibre-reinforced plastic (FRP) wedge-sticks enhance the strength and stability of the blade root, prevent stress concentration at the blade root, and improve the service life and reliability of the blade. However, studies on the failure mechanisms of the FRP wedge-sticks in bushing-insert connections are scarce. Hence, in this study, the influence of the FRP wedge-stick on the structural performance of the blade root was analysed by changing the slope of the FRP wedge-stick’s inclined surface at a constant thickness. The finite element method, sample testing, and full-size blade testing method were employed, and structural verification was conducted using an 84.5 m blade. The results reveal that the contact area of the inclined surface can be increased by reducing the slope of the FRP wedge-stick. This increase in area reduces the stress transmitted to each node of the FRP wedge-stick and blade root, prevents delamination of the FRP wedge-stick and blade root, and enhances the reliability of the blade root connection.
Anemia and Iron Deficiency Predict All-Cause Mortality in Patients with Heart Failure and Preserved Ejection Fraction: 6-Year Follow-Up Study
Authors: Köseoğlu Fatoş Dilan , Özlek Bülent
Published: January 2024

Aims: The aim of this study was to assess the prevalence of anemia and iron deficiency in patients with heart failure with preserved ejection fraction (HFpEF) and its impact on clinical outcomes. Methods: We retrospectively analyzed 212 patients with HFpEF and identified anemia as a serum hemoglobin level of less than 13 g/dL in men and less than 12 g/dL in women. Additionally, ID was defined as a serum ferritin concentration < 100 ng/mL or 100–299 ng/mL with transferrin saturation < 20%. Patients were followed up for an average of 66.2 ± 12.1 months, with the endpoint being all-cause mortality among patients with HFpEF, both with and without anemia and iron deficiency. Furthermore, we explored other predictors of all-cause mortality. Results: The average age of the entire group was 70.6 ± 10.5 years, with females comprising 55% of the patients. Anemia was present in 81 (38.2%) patients, while 108 (50.9%) had iron deficiency. At the end of the follow-up period, 60 (28.3%) of the patients had passed away. Patients with anemia displayed more heart failure (HF) symptoms, diastolic dysfunction, higher NT-pro-BNP levels, and worse baseline functional capacity than those without. Similarly, patients with iron deficiency showed more pronounced HF symptoms and worse functional capacity than those without. The results from the multivariable analyses revealed that anemia (hazard ratio [HR]: 5.401, 95% confidence interval [CI]: 4.303–6.209, log-rank p = 0.001), advanced age, iron deficiency (HR: 3.502, 95% CI: 2.204–6.701, log-rank p = 0.015), decreased left ventricular ejection fraction, chronic kidney disease, and paroxysmal nocturnal dyspnea were all independently associated with all-cause mortality. Conclusions: It is essential to consider anemia and iron deficiency as common comorbidities in managing and prognosis HFpEF, as they significantly increase mortality risk.
Quantum Secure Multi-Party Summation with Graph State
Authors: Lu Yaohua , Ding Gangyi
Published: January 2024

Quantum secure multi-party summation (QSMS) is a fundamental problem in quantum secure multi-party computation (QSMC), wherein multiple parties compute the sum of their data without revealing them. This paper proposes a novel QSMS protocol based on graph state, which offers enhanced security, usability, and flexibility compared to existing methods. The protocol leverages the structural advantages of graph state and employs random graph state structures and random encryption gate operations to provide stronger security. Additionally, the stabilizer of the graph state is utilized to detect eavesdroppers and channel noise without the need for decoy bits. The protocol allows for the arbitrary addition and deletion of participants, enabling greater flexibility. Experimental verification is conducted to demonstrate the security, effectiveness, and practicality of the proposed protocols. The correctness and security of the protocols are formally proven. The QSMS method based on graph state introduces new opportunities for QSMC. It highlights the potential of leveraging quantum graph state technology to securely and efficiently solve various multi-party computation problems.
Spatial and Temporal Hierarchy for Autonomous Navigation Using Active Inference in Minigrid Environment
Authors: de Tinguy Daria , Van de Maele Toon , Verbelen Tim , Dhoedt Bart
Published: January 2024

Robust evidence suggests that humans explore their environment using a combination of topological landmarks and coarse-grained path integration. This approach relies on identifiable environmental features (topological landmarks) in tandem with estimations of distance and direction (coarse-grained path integration) to construct cognitive maps of the surroundings. This cognitive map is believed to exhibit a hierarchical structure, allowing efficient planning when solving complex navigation tasks. Inspired by human behaviour, this paper presents a scalable hierarchical active inference model for autonomous navigation, exploration, and goal-oriented behaviour. The model uses visual observation and motion perception to combine curiosity-driven exploration with goal-oriented behaviour. Motion is planned using different levels of reasoning, i.e., from context to place to motion. This allows for efficient navigation in new spaces and rapid progress toward a target. By incorporating these human navigational strategies and their hierarchical representation of the environment, this model proposes a new solution for autonomous navigation and exploration. The approach is validated through simulations in a mini-grid environment.
Microchannel Gas Flow in the Multi-Flow Regime Based on the Lattice Boltzmann Method
Authors: Li Xiaoyu , Ning Zhi , Lü Ming
Published: January 2024

In this work, a lattice Boltzmann method (LBM) for studying microchannel gas flow is developed in the multi-flow regime. In the LBM, by comparing previous studies’ results on effective viscosity in multi-flow regimes, the values of the rarefaction factor applicable to multi-flow regions were determined, and the relationship between relaxation time and Kn number with the rarefaction factor is given. The Kn number is introduced into the second-order slip boundary condition together with the combined bounce-back/specular-reflection (CBBSR) scheme to capture the gas flow in the multi-flow regime. Sensitivity analysis of the dimensionless flow rate to adjustable parameters using the Taguchi method was carried out, and the values of adjustable parameters were determined based on the results of the sensitivity analysis. The results show that the dimensionless flow rate is more sensitive to j than h. Numerical simulations of Poiseuille flow and pulsating flow in a microchannel with second-order slip boundary conditions are carried out to validate the method. The results show that the velocity profile and dimensionless flow rate simulated by the present numerical simulation method in this work are found in the multi-flow regime, and the phenomenon of annular velocity profile in the microchannel is reflected in the phases.
Hourly Photovoltaic Production Prediction Using Numerical Weather Data and Neural Networks for Solar Energy Decision Support
Authors: Nicoletti Francesco , Bevilacqua Piero
Published: January 2024

The day-ahead photovoltaic electricity forecast is increasingly necessary for grid operators and for energy communities. In the present work, the hourly PV production is estimated using two models based on feedforward neural networks (FFNNs). Most existing models use solar radiation as an input. Instead, the models proposed here use numerical weather prediction (NWP) data: ambient temperature, relative humidity, and wind speed, which are easily accessible to anyone. The first proposed model uses multiple inputs, while the second one uses only the necessary information. A sensitivity analysis allows for the identification of the variables that are most influential on the estimation accuracy. This study concludes that the hourly temperature trend is the most important variable for prediction. The models’ accuracy was tested using experimental and NWP data, with the second model having almost the same accuracy as the first despite using fewer input data. The results obtained using experimental data as inputs show a coefficient of determination (R2) of 0.95 for the hourly PV energy produced. The RMSE is about 6.4% of the panel peak power. When NWP data are used as inputs, R2 is 0.879 and the RMSE is 10.5%. These models can have a significant impact by enabling individual energy communities to make their forecasts, resulting in energy savings and increased self-consumed energy.
Insulation Condition Assessment in Inverter-Fed Motors Using the High-Frequency Common Mode Current: A Case Study
Authors: Saeed Mariam , Fernández Daniel , Guerrero Juan Manuel , Díaz Ignacio , Briz Fernando
Published: January 2024

The use of the common mode current for stator winding insulation condition assessment has been extensively studied. Two main approaches have been followed. The first models the electric behavior of ground-wall insulation as an equivalent RC circuit; these methods have been successfully applied to high-voltage high-power machines. The second uses the high frequency of the common mode current which results from the voltage pulses applied by the inverter. This approach has mainly been studied for the case of low-voltage, inverter-fed machines, and has not yet reached the level of maturity of the first. One fact noticed after a literature review is that in most cases, the faults being detected were induced by connecting external elements between winding and stator magnetic core. This paper presents a case study on the use of the high-frequency common mode current to monitor the stator insulation condition. Insulation degradation occurred progressively with the machine operating normally; no exogenous elements were added. Signal processing able to detect the degradation at early stages will be discussed.
Optimal Design of a Submodule Capacitor in a Modular Multilevel Converter for Medium Voltage Motor Drives
Authors: Nguyen Van-Thang , Kim Ji-Won , Lee Jae-Woon , Park Byoung-Gun
Published: January 2024

This paper proposes an algorithm for determining the optimal capacitance by utilizing a mathematical model of a submodule (SM) capacitor in a modular multilevel converter (MMC) specifically for medium voltage motor drives (MVDs). By approximating the voltage fluctuation of the SM capacitor during low-frequency operation, it is feasible to ascertain the minimum capacitance required for the SM capacitor, ensuring that its voltage fluctuations remain within an acceptable limit that is predefined as a specified value. Moreover, the study considered the injection of both a high-frequency common-mode voltage (CMV) and a circulating current to alleviate the SM voltage fluctuation during the acceleration of motor drives. The effectiveness of the proposed method is validated through verification using time-domain simulation results obtained using the MATLAB/SIMULINK software and real-time simulation results acquired using the OPAL-RT simulator platform.
Prediction Model of Electric Power Carbon Emissions Based on Extended System Dynamics
Authors: Wu Zhenfen , Wang Zhe , Yang Qiliang , Li Changyun
Published: January 2024

In response to global climate change, China has committed to peaking carbon emissions by 2030 and achieving carbon neutrality by 2060, commonly known as the “30–60 Dual Carbon”. Under the background of “30–60 Dual Carbon”, this article takes the electric power industry, which is the main industry contributing to China’s carbon emission, as the research object, explores the time and peak value of the carbon peak of the electric power industry, and analyzes whether carbon neutrality can be realized under the peak method, so as to get the carbon neutrality path of the electric power industry and serve as the theoretical basis for the formulation of relevant policies. The Environmental Kuznets Curve inspection and the relationship analysis are carried out, then the system dynamics model is constructed, the carbon emissions from 2020 to 2040 are simulated, and the peak time is predicted. Three different scenarios are set to explore the path of electricity carbon neutralization under the premise of a fixed peak. It is shown that Gross Domestic Product per capita index factors have the largest positive contribution, and thermal power share index factors have the largest negative contribution to electricity carbon emissions. Based on the current efforts of the new policy, carbon emissions can achieve the peak carbon emissions’ target before 2030, and it is expected to peak in 2029, with a peak range of about 4.95 billion tons. After the power industry peaks in 2029, i.e., Scenario 3, from coal 44%, gas 9% (2029) to coal 15%, gas 7% (2060), where the CCUS technology is widely used, this scenario can achieve carbon neutrality in electricity by 2060. Adjusting the power supply structure, strictly controlling the proportion of thermal power, optimizing the industrial structure, and popularization of carbon capture, utilization, and storage technology will all contribute to the “dual carbon” target of the power sector.
Enhancing the Efficiency of Failure Recognition in Induction Machines through the Application of Deep Neural Networks
Authors: Pietrowski Wojciech , Górny Konrad
Published: January 2024

The objective of the investigation was to increase the effectiveness of damage detection in the stator of the squirrel-cage induction machine. The analysis aimed to enhance the operational trustworthiness of the squirrel-cage induction machine by employing nonintrusive diagnostic methods based on a current signal and modern artificial intelligence methods. The authors of the study introduced a diagnostic technique for identifying multiphase interturn short circuits of stator winding. These short circuits are one of the most common faults in induction machines. The proposed method focusses on deriving a diagnostic signal from the phase-current waveforms of the machine. The noninvasive nature of the diagnostic technique presented is attributed to the application of the field model of electromagnetic phenomena to determine the diagnostic signal. For this purpose, a field model of a squirrel-cage machine was developed. The waveforms of phase currents obtained from the field model were used as input into an elaborated machine failure neural classifier. A deep neural network was used to develop a neural classifier. The effectiveness of the developed classifier has been experimentally verified, and the obtained results have been presented, concluded, and discussed. The scientific novelty presented in the article is the presentation of research results on the use of a neural classifier to detect damage in all phases of the stator winding at an early stage of its appearance. The features of this type of damage are very difficult to observe in signal waveforms such as a phase current or torque.
Sodium Channel Gene Variants in Fetuses with Abnormal Sonographic Findings: Expanding the Prenatal Phenotypic Spectrum of Sodium Channelopathies
Authors: Hadjipanteli Andrea , Theodosiou Athina , Papaevripidou Ioannis , Evangelidou Paola , Alexandrou Angelos , Salameh Nicole , Kallikas Ioannis , Kakoullis Kyriakos , Frakala Sofia , Oxinou Christina , Marnerides Andreas , Kousoulidou Ludmila , Anastasiadou Violetta C. , Sismani Carolina
Published: January 2024

Voltage-gated sodium channels (VGSCs) are responsible for the initiation and propagation of action potentials in the brain and muscle. Pathogenic variants in genes encoding VGSCs have been associated with severe disorders including epileptic encephalopathies and congenital myopathies. In this study, we identified pathogenic variants in genes encoding the α subunit of VGSCs in the fetuses of two unrelated families with the use of trio-based whole exome sequencing, as part of a larger cohort study. Sanger sequencing was performed for variant confirmation as well as parental phasing. The fetus of the first family carried a known de novo heterozygous missense variant in the SCN2A gene (NM_001040143.2:c.751G>A p.(Val251Ile)) and presented intrauterine growth retardation, hand clenching and ventriculomegaly. Neonatally, the proband also exhibited refractory epilepsy, spasms and MRI abnormalities. The fetus of the second family was a compound heterozygote for two parentally inherited novel missense variants in the SCN4A gene (NM_000334.4:c.4340T>C, p.(Phe1447Ser), NM_000334.4:c.3798G>C, p.(Glu1266Asp)) and presented a severe prenatal phenotype including talipes, fetal hypokinesia, hypoplastic lungs, polyhydramnios, ear abnormalities and others. Both probands died soon after birth. In a subsequent pregnancy of the latter family, the fetus was also a compound heterozygote for the same parentally inherited variants. This pregnancy was terminated due to multiple ultrasound abnormalities similar to the first pregnancy. Our results suggest a potentially crucial role of the VGSC gene family in fetal development and early lethality.
Association between Short Stature at Grade 1 and Permanent Teeth Caries at Grade 6 in Elementary School Children in Japan: A Population-Based Cohort Study
Authors: Suzuki Ayako , Tani Yukako , Anzai Tatsuhiko , Isumi Aya , Doi Satomi , Ogawa Takuya , Moriyama Keiji , Fujiwara Takeo
Published: January 2024

Short stature in children is a marker of low nutritional status and has been suggested to be associated with dental caries. However, longitudinal studies on this topic are scarce. Data from a longitudinal study of elementary school children in Adachi City, Tokyo, Japan, were analyzed. In 2015, caregivers of children at grade 1 answered questionnaires, and information on dental caries and height measured at school health checkups was merged and followed to grade 6 (N = 3576; follow up rate = 83.3%). The association between short stature at grade 1 (−2.01 standard deviation (SD)–−3.00 SD, or <−3.00 SD in height-for-age according to the World Health Organization criteria) and the number of decayed, missing, or filled permanent teeth (DMFT) at grade 6 was examined using multivariable Poisson regression with robust standard error. After adjusting for confounders, children with a short stature at grade 1 had a higher DMFT number at grade 6: the mean ratios (95% confidence interval) were 1.17 (0.89–1.54) and 2.18 (1.03–4.64) for children with a height-for-age −2.01 SD–−3.00 SD, and those with a height-for-age < −3.00, respectively. Short stature at grade 1 could be a marker of future dental caries in the permanent teeth at grade 6.
Self-Objectification, Disordered Eating and Sexual Orientation in Men
Authors: Bachner-Melman Rachel , Lev-Ari Lilac , Tiram Hadar , Zohar Ada H.
Published: January 2024

The interplay between disordered eating, depressive symptoms and self-objectification differs between genders and sexual orientations, and merits further study in homosexual and heterosexual men. We examined disordered eating, depressive symptoms and self-objectification in a sample of Israeli heterosexual and homosexual men. Participants were 215 men aged 19–65, 108 of whom were classified by the Kinsey scale as being heterosexual and 107 as homosexual. They completed online measures of self-objectification, disordered eating and depressive symptoms. Heterosexual men reported lower levels of disordered eating and self-objectification than homosexual men, however the difference in depressive symptoms was not statistically significant. Correlations between disordered eating, self-objectification and depressive symptoms when controlling for age, BMI and number of children were all significant, with similar patterns of association for heterosexual and homosexual men. Self-objectification partially mediated the association between sexual orientation and disordered eating. However, contrary to our hypothesis, sexual orientation (homosexual/heterosexual) did not moderate the association between disordered eating and self-objectification. The tendency of homosexual men towards self-objectification is linked to unhealthy eating habits. Self-objectification helps explain the propensity of homosexual versus heterosexual men to develop disordered eating and possibly eating disorders. It should therefore be targeted in prevention and in therapy.
Migrant Men Living in Brazil during the Pandemic: A Qualitative Study
Authors: Santos Ramon Vinicius Peixoto da Silva , Cruz Neto João , Bacelo Sidiane Rodrigues , José Oscar Yovani Fabian , Vergara-Escobar Oscar Javier , Machuca-Contreras Felipe , Moraes Maria Cecilia Leite de , Lourenção Luciano Garcia , Sousa Álvaro Francisco Lopes de , de Oliveira Layze Braz , Mendes Isabel Amélia Costa , de Sousa Anderson Reis
Published: January 2024

This study aims to analyze the repercussions of the ongoing COVID-19 pandemic on the health of male immigrants, refugees, and asylum seekers in Brazil. A qualitative study involving 307 adult men living in Brazil during the COVID-19 pandemic was conducted. Data were collected between August 2021 and March 2022 and interpreted based on the Transcultural Nursing Theory. Cultural care repercussions were identified in various dimensions: technological: changes in daily life and disruptions in routine; religious, philosophical, social, and cultural values: changes stemming from disrupted social bonds, religious practices, and sociocultural isolation; political: experiences of political partisanship, conflicts, government mismanagement, a lack of immigration policies, human rights violations, and xenophobia; educational/economic: challenges arising from economic impoverishment, economic insecurity, unemployment, language difficulties, and challenges in academic and literacy development during the pandemic. The persistence of the COVID-19 pandemic in Brazil had significant repercussions for the health of migrant men, resulting in a transcultural phenomenon that requires sensitive nursing care. Implications for nursing: the uniqueness of cultural care in nursing and health, as most of the repercussions found were mostly negative, contributed to the increase in social and health vulnerabilities.
School Satisfaction and Self-Efficacy in Adolescents and Intention to Drop Out of School
Authors: Pedditzi Maria Luisa
Published: January 2024

School dropout is a risky behaviour that is a threat to well-being in adolescence. This study aimed to analyse school satisfaction and self-efficacy in school activities in a sample of adolescents attending secondary school in an Italian region at high risk of school dropout. The objective was to investigate whether differences exist among students on the basis of school dropout intention, gender, and career choices. Another aim was to identify, among the students’ satisfaction variables, the main psychosocial predictors of dropout intention. Students (N = 1340) attending secondary schools in Sardinia completed Soresi’s questionnaires on life satisfaction and self-efficacy. The data were analysed with a multivariate analysis of variance and logistic regression analysis. The results indicated that students intending to drop out of school scored lower on satisfaction with perceived support and satisfaction with peer and teacher relationships than their peers not at risk of dropping out. The logistic regression analysis showed that the most significant predictors of dropout intention were academic performance, satisfaction with the school experience, satisfaction in the relationships with teachers and with family members, and satisfaction with perceived support (26.9% of model variance). The results of this research thus indicate which areas could be addressed through prevention to improve well-being conditions in education.
Magnesium and Vascular Calcification in Chronic Kidney Disease: Current Insights
Authors: Zaslow Shari J. , Oliveira-Paula Gustavo H. , Chen Wei
Published: January 2024

Magnesium (Mg) plays crucial roles in multiple essential biological processes. As the kidneys are the primary organ responsible for maintaining the blood concentration of Mg, people with chronic kidney disease (CKD) may develop disturbances in Mg. While both hyper- and hypomagnesemia may lead to adverse effects, the consequences associated with hypomagnesemia are often more severe and lasting. Importantly, observational studies have shown that CKD patients with hypomagnesemia have greater vascular calcification. Vascular calcification is accelerated and contributes to a high mortality rate in the CKD population. Both in vitro and animal studies have demonstrated that Mg protects against vascular calcification via several potential mechanisms, such as inhibiting the formation of both hydroxyapatite and pathogenic calciprotein particles as well as limiting osteogenic differentiation, a process in which vascular smooth muscle cells in the media layer of the arteries transform into bone-like cells. These preclinical findings have led to several important clinical trials that have investigated the effects of Mg supplementation on vascular calcification in people with CKD. Interestingly, two major clinical studies produced contradictory findings, resulting in a state of equipoise. This narrative review provides an overview of our current knowledge in the renal handling of Mg in health and CKD and the underlying mechanisms by which Mg may protect against vascular calcification. Lastly, we evaluate the strength of evidence from clinical studies on the efficacy of Mg supplementation and discuss future research directions.