bluuebunny/crossref_metadata_2025 huggingface dataset:
Rilpivirine Activates STAT1 in Non-Parenchymal Cells to Regulate Liver Injury in People Living with HIV and MASLD
Authors: Moragrega Ángela B. , Busca Carmen , Apostolova Nadezda , Olveira Antonio , Martín-Carbonero Luz , Valencia Eulalia , Moreno Victoria , Bernardino José I. , Abadía Marta , González-García Juan , Esplugues Juan V. , Montes María L. , Blas-García Ana
Published: July 2024

Liver fibrosis is a key determinant of the progression of metabolic dysfunction-associated steatotic liver disease (MASLD). Its increasing prevalence and a lack of effective treatments make it a major health problem worldwide, particularly in people living with HIV, among whom the prevalence of advanced fibrosis is higher. We have published preclinical data showing that Rilpivirine (RPV), a widely used anti-HIV drug, selectively triggers hepatic stellate cell (HSC) inactivation and apoptosis through signal transducer and activator of transcription (STAT)1-mediated pathways, effects that clearly attenuate liver fibrosis and promote regeneration. We performed a retrospective, cross-sectional study of RPV-induced effects on steatosis, inflammation, and fibrosis in liver biopsies from well-controlled HIV-infected subjects diagnosed with MASLD. Patients on RPV exhibited similar levels of HIV-related parameters to those not receiving this drug, while showing a tendency toward improved liver function and lipid profile, as well as an enhanced activation of STAT1 in hepatic non-parenchymal cells in those with identified liver injury. This protective effect, promoting STAT1-dependent HSC inactivation, was observed at different stages of MASLD. Our results suggest that RPV-based therapy is especially indicated in HIV-infected patients with MASLD-derived liver injury and highlight the potential of RPV as a new therapeutic strategy for liver diseases.
Sympathetic Activation Promotes Sodium Glucose Co-Transporter-1 Protein Expression in Rodent Skeletal Muscle
Authors: Matthews Jennifer R. , Herat Lakshini Y. , Schlaich Markus P. , Matthews Vance B.
Published: July 2024

The hyperactivation of the sympathetic nervous system (SNS) is linked to obesity, hypertension, and type 2 diabetes, which are characterized by elevated norepinephrine (NE) levels. Previous research has shown increased sodium-dependent glucose cotransporter 1 (SGLT1) protein levels in kidneys of hypertensive rodents, prompting investigation into the expression of SGLT1 in various tissues, such as skeletal muscle. This study aimed to assess (i) whether skeletal muscle cells and tissue express SGLT1 and SGLT2 proteins; (ii) if NE increases SGLT1 levels in skeletal muscle cells, and (iii) whether the skeletal muscle of neurogenically hypertensive mice exhibits increased SGLT1 expression. We found that (i) skeletal muscle cells and tissue are a novel source of the SGLT2 protein and that (ii) NE significantly elevated SGLT1 levels in skeletal muscle cells. As SGLT2 inhibition (SGLT2i) with Empagliflozin increased SGLT1 levels, in vivo studies with the dual inhibitor SGLT1/2i, Sotagliflozin were warranted. The treatment of neurogenically hypertensive mice using Sotagliflozin significantly reduced blood pressure. Our findings suggest that SNS activity upregulates the therapeutic target, SGLT1, in skeletal muscle, potentially worsening cardiometabolic control. As clinical trial data suggest cardiorenal benefits from SGLT2i, future studies should aim to utilize SGLT1i by itself, which may offer a therapeutic strategy for conditions with heightened SNS activity, such as hypertension, diabetes, and obesity.
The Re-Emergence of Mpox: Old Illness, Modern Challenges
Authors: Zinnah Mohammad Ali , Uddin Md Bashir , Hasan Tanjila , Das Shobhan , Khatun Fahima , Hasan Md Hasibul , Udonsom Ruenruetai , Rahman Md Masudur , Ashour Hossam M.
Published: July 2024

The Mpox virus (MPXV) is known to cause zoonotic disease in humans. The virus belongs to the genus Orthopoxvirus, of the family Poxviridae, and was first reported in monkeys in 1959 in Denmark and in humans in 1970 in the Congo. MPXV first appeared in the U.S. in 2003, re-emerged in 2017, and spread globally within a few years. Wild African rodents are thought to be the reservoir of MPXV. The exotic trade of animals and international travel can contribute to the spread of the Mpox virus. A phylogenetic analysis of MPXV revealed two distinct clades (Central African clade and West African clade). The smallpox vaccine shows cross-protection against MPXV infections in humans. Those who have not previously been exposed to Orthopoxvirus infections are more vulnerable to MPXV infections. Clinical manifestations in humans include fever, muscle pain, headache, and vesicle formation on the skin of infected individuals. Pathognomonic lesions include ballooning degenerations with Guarnieri-like inclusions in vesicular epithelial cells. Alterations in viral genome through genetic mutations might favor the re-emergence of a version of MPXV with enhanced virulence. As of November 2023, 92,783 cases and 171 deaths have been reported in 116 countries, representing a global public health concern. Here, we provide insights on the re-emergence of MPXV in humans. This review covers the origin, emergence, re-emergence, transmission, pathology, diagnosis, control measures, and immunomodulation of the virus, as well as clinical manifestations. Concerted efforts of health professionals and scientists are needed to prevent the disease and stop its transmission in vulnerable populations.
Innovative Semi-Nested Realtime PCR Assay with Extendable Blocking Probe for Enhanced Analysis of SEPT9 Methylation in Colorectal Cancer
Authors: Duong Linh Thuy , Dao Trang Thuy , Bui Hoai Thi , Nguyen Ung Dinh , Hoang Ung Tien , Tran Duc Viet , Nguyen Ba Van , Ho Tho Huu
Published: July 2024

(1) Background: The detection of methylated SEPT9 (mSEPT9) in plasma is a promising approach to non-invasive colorectal cancer (CRC) screening. Traditional approaches have limitations in sensitivity and cost-effectiveness, particularly in resource-limited settings. (2) Methods: We developed a semi-nested realtime PCR assay utilizing extendable blocking probes (ExBP) to enhance the detection of low-level mSEPT9 based on DNA melting. This assay allows for the discrimination of mSEPT9 in the presence of high concentrations of non-methylated SEPT9 (up to 100,000 times higher). (3) Results: The assay demonstrated a sensitivity of 73.91% and specificity of 80%, showcasing its ability to detect very low levels of methylated DNA effectively. The innovative use of ExBP without costly modified probes simplifies the assay setup and reduces the overall costs, enhancing its applicability in diverse clinical settings. (4) Conclusions: This novel assay significantly improves the detection of mSEPT9, offering a potential advance in CRC screening and monitoring. Its cost-efficiency and high sensitivity make it particularly suitable for the early detection and management of CRC, especially in settings with limited resources. Future studies are encouraged to validate this assay in larger populations to establish its clinical benefits and practical utility.
Design of Heavy-Load Soft Robots Based on a Dual Biomimetic Structure
Authors: Yang Liu , Zhang Zhilei , Zhang Zengzhi , Lou Yuzhong , Han Shijie , Liu Jiaqi , Fang Liu , Zhang Shangsheng
Published: July 2024

This study first draws inspiration from the dual biomimetic design of plant cell walls and honeycomb structures, drawing on their structural characteristics to design a flexible shell structure that can achieve significant deformation and withstand large loads. Based on the staggered bonding of this flexible shell structure, we propose a new design scheme for a large-load pneumatic soft arm and establish a mathematical model for its flexibility and load capacity. The extension and bending deformation of this new type of soft arm come from the geometric variability of flexible shell structures, which can be controlled through two switches, namely, deflation and inflation, to achieve extension or bending actions. The experimental results show that under a driving pressure within the range of 150 kpa, the maximum elongation of the soft arm reaches 23.17 cm, the maximum bending angle is 94.2 degrees, and the maximum load is 2.83 N. This type of soft arm designed based on dual bionic inspiration can have both a high load capacity and flexibility. The research results provide new ideas and methods for the development of high-load soft arms, which are expected to expand from laboratories to multiple fields.
CMRLCCOA: Multi-Strategy Enhanced Coati Optimization Algorithm for Engineering Designs and Hypersonic Vehicle Path Planning
Authors: Hu Gang , Zhang Haonan , Xie Ni , Hussien Abdelazim G.
Published: July 2024

The recently introduced coati optimization algorithm suffers from drawbacks such as slow search velocity and weak optimization precision. An enhanced coati optimization algorithm called CMRLCCOA is proposed. Firstly, the Sine chaotic mapping function is used to initialize the CMRLCCOA as a way to obtain better-quality coati populations and increase the diversity of the population. Secondly, the generated candidate solutions are updated again using the convex lens imaging reverse learning strategy to expand the search range. Thirdly, the Lévy flight strategy increases the search step size, expands the search range, and avoids the phenomenon of convergence too early. Finally, utilizing the crossover strategy can effectively reduce the search blind spots, making the search particles constantly close to the global optimum solution. The four strategies work together to enhance the efficiency of COA and to boost the precision and steadiness. The performance of CMRLCCOA is evaluated on CEC2017 and CEC2019. The superiority of CMRLCCOA is comprehensively demonstrated by comparing the output of CMRLCCOA with the previously submitted algorithms. Besides the results of iterative convergence curves, boxplots and a nonparametric statistical analysis illustrate that the CMRLCCOA is competitive, significantly improves the convergence accuracy, and well avoids local optimal solutions. Finally, the performance and usefulness of CMRLCCOA are proven through three engineering application problems. A mathematical model of the hypersonic vehicle cruise trajectory optimization problem is developed. The result of CMRLCCOA is less than other comparative algorithms and the shortest path length for this problem is obtained.
Shungite Paste Electrodes: Basic Characterization and Initial Examples of Applicability in Electroanalysis
Authors: Bártová Michaela , Bartoš Martin , Švancara Ivan , Sýs Milan
Published: July 2024

This article introduces a new type of carbon paste electrode prepared from black raw shungite. In powdered form, this carbonaceous material was mixed with several nonpolar binders. The resulting shungite pastes were microscopically and electrochemically characterized. Mixtures of several pasting liquids with different contents of shungite powder were tested to select the optimal composition and compared with other types of carbon paste-based electrodes made of graphite and glassy carbon powder. In terms of physical and mechanical properties, shungite paste electrodes (ShPEs) formed a composite mass being like dense pastes from glassy carbon microspheres, having harder consistency than that of traditional graphitic carbon pastes. The respective electrochemical measurements with ShPEs were based on cyclic voltammetry of ferri-/ferro-cyanide redox pairs, allowing us to evaluate some typical parameters such as electrochemically active surface area, double-layer capacitance, potential range in the working media given, heterogeneous rate constant, charge-transfer coefficient, exchange current density, and open-circuit potential. The whole study with ShPEs was then completed with three different examples of possible electroanalytical applications, confirming that the carbon paste-like configuration with powdered shungite represents an environmentally friendly (green) and low-cost electrode material with good stability in mixed aqueous-organic mixtures, and hence with interesting prospects in electroanalysis of biologically active organic compounds. It seems that similar analytical parameters of the already established variants of carbon paste electrodes can also be expected for their shungite analogues.
Study on the Characterization and Degradation Pattern of Circular RNA Vaccines Using an HPLC Method
Authors: Cheng Feiran , Li Ji , Hu Chaoying , Bai Yu , Liu Jianyang , Liu Dong , He Qian , Jin Qiuheng , Mao Qunying , Liang Zhenglun , Xu Miao
Published: July 2024

Circular RNA (circRNA) vaccines have attracted increasing attention due to their stable closed-loop structures and persistent protein expression ability. During the synthesis process, nicked circRNAs with similar molecular weights to those of circRNAs are generated. Analytical techniques based on differences in molecular weight, such as capillary electrophoresis, struggle to distinguish between circRNAs and nicked circRNAs. The characteristic degradation products of circRNAs and their biological activities remain unclear. Therefore, developing methods to identify target circRNAs and non-target components and investigating degradation patterns will be beneficial to gaining an in-depth understanding of the properties and quality control of circRNAs vaccines. The reversed-phase HPLC (RP-HPLC) method was established for identification of target circRNAs, product-related substances, and impurities. Subsequently, we investigated the degradation patterns of circRNAs under thermal acceleration conditions and performed biological analysis of degradation products and linear precursors. Here, RP-HPLC method effectively identified circRNAs and nicked circRNAs. With thermal acceleration, circRNAs exhibited a “circular→nicked circRNAs→degradation products” degradation pattern. Biological analysis revealed that the immunogenicity of degradation products significantly decreased, whereas linear precursors did not possess immunogenicity. Thus, our established RP-HPLC method can be used for purity analysis of circRNA vaccines, which contributes to the quality control of circRNA vaccines and promoting the development of circRNA technology.
Factors, Prediction, and Explainability of Vehicle Accident Risk Due to Driving Behavior through Machine Learning: A Systematic Literature Review, 2013–2023
Authors: Lacherre Javier , Castillo-Sequera José Luis , Mauricio David
Published: July 2024

Road accidents are on the rise worldwide, causing 1.35 million deaths per year, thus encouraging the search for solutions. The promising proposal of autonomous vehicles stands out in this regard, although fully automated driving is still far from being an achievable reality. Therefore, efforts have focused on predicting and explaining the risk of accidents using real-time telematics data. This study aims to analyze the factors, machine learning algorithms, and explainability methods most used to assess the risk of vehicle accidents based on driving behavior. A systematic review of the literature produced between 2013 and July 2023 on factors, prediction algorithms, and explainability methods to predict the risk of traffic accidents was carried out. Factors were categorized into five domains, and the most commonly used predictive algorithms and explainability methods were determined. We selected 80 articles from journals indexed in the Web of Science and Scopus databases, identifying 115 factors within the domains of environment, traffic, vehicle, driver, and management, with speed and acceleration being the most extensively examined. Regarding machine learning advancements in accident risk prediction, we identified 22 base algorithms, with convolutional neural network and gradient boosting being the most commonly used. For explainability, we discovered six methods, with random forest being the predominant choice, particularly for feature importance analysis. This study categorizes the factors affecting road accident risk, presents key prediction algorithms, and outlines methods to explain the risk assessment based on driving behavior, taking vehicle weight into consideration.
Candlestick Pattern Recognition in Cryptocurrency Price Time-Series Data Using Rule-Based Data Analysis Methods
Authors: Uzun Illia , Lobachev Mykhaylo , Kharchenko Vyacheslav , Schöler Thorsten , Lobachev Ivan
Published: July 2024

In the rapidly evolving domain of cryptocurrency trading, accurate market data analysis is crucial for informed decision making. Candlestick patterns, a cornerstone of technical analysis, serve as visual representations of market sentiment and potential price movements. However, the sheer volume and complexity of cryptocurrency price time-series data presents a significant challenge to traders and analysts alike. This paper introduces an innovative rule-based methodology for recognizing candlestick patterns in cryptocurrency markets using Python. By focusing on Ethereum, Bitcoin, and Litecoin, this study demonstrates the effectiveness of the proposed methodology in identifying key candlestick patterns associated with significant market movements. The structured approach simplifies the recognition process while enhancing the precision and reliability of market analysis. Through rigorous testing, this study shows that the automated recognition of these patterns provides actionable insights for traders. This paper concludes with a discussion on the implications, limitations, and potential future research directions that contribute to the field of computational finance by offering a novel tool for automated analysis in the highly volatile cryptocurrency market.
Mathematical Modeling of the Drug Particles Deposition in the Human Respiratory System—Part 1: Development of Virtual Models of the Upper and Lower Respiratory Tract
Authors: Menshutina Natalia , Mokhova Elizaveta , Abramov Andrey
Published: July 2024

In order to carry out mathematical modeling of the drug particles or drop movement in the human respiratory system, an approach to reverse prototyping of the studied areas based on the medical data (computed tomography) results is presented. To adapt the computational grid, a mathematical model of airflow in channels of complex geometry (respiratory system) has been developed. Based on the data obtained, the results of computational experiments for a single-phase system are presented.
Novel Methods for Synthesizing Self-Checking Combinational Circuits by Means of Boolean Signal Correction and Polynomial Codes
Authors: Efanov Dmitry V. , Abdullaev Ruslan B. , Plotnikov Dmitry G. , Bolsunovskaya Marina V. , Odoevsky Alexey S. , Vasilyanov Georgy S.
Published: July 2024

This paper proposes the use of a polynomial code for synthesizing self-checking digital devices. The code is chosen for its error detection characteristics in data symbols and is used for Boolean signals correction in embedded control circuits. In practice, it is possible to equip the device with the ability to detect faults. In contrast to the approaches found in the world literature to solve this problem, this proposal suggests identifying groups of structurally independent outputs to distinguish between convertible and non-convertible outputs of the diagnosed block in the embedded control circuit. The only outputs that can be converted are those that are used as checking symbols for the polynomial code in the embedded control circuit. The other functions remain unchanged. The polynomial codes are used to select them. The authors present algorithms for synthesizing fault detection devices using the proposed approach.
Pediatric Narcolepsy Type 1: A State-of-the-Art Review
Authors: Baldini Valentina , Biscarini Francesco , Varallo Giorgia , Pizza Fabio , Plazzi Giuseppe
Published: July 2024

Narcolepsy is a chronic central disorder of hypersomnolence most frequently arising during childhood/adolescence. This review article examined the literature concerning the etiology, prevalence, clinical course, and treatment of children with type 1 narcolepsy (NT1). Core symptoms of pediatric NT1 include excessive daytime sleepiness (EDS) and cataplexy, together with disrupted night sleep, sleep paralysis, and hypnagogic and hypnopompic hallucinations that can also occur. This disease frequently presents several comorbidities, such as obesity and precocious puberty, conditions ranging from psychological distress to psychiatric disorders, and cognitive aspects that further worsen the clinical picture. NT1 impairs the quality of life of children, thus calling for an early diagnosis and adequate treatment. To date, pharmacological treatments have been registered for childhood NT1 and can improve symptoms. Non-pharmacological approaches are also essential to improve patients’ well-being, ranging from behavioral treatments (e.g., planned napping) to psychosocial interventions (e.g., school programs). Multidisciplinary treatment management and early diagnosis are key factors in order to allow for adequate quality of life and development in children with NT1.
Succession as a Natural Tool for Restoration of Oak—Lime Forests on Aspen-Covered Clearcuts
Authors: Nasibullina Alina , Tiebel Katharina , Wagner Sven
Published: July 2024

The genus Quercus, including species like pedunculate oak (Quercus robur L.), can play a key role in maintaining climate-resistant mixed forests due to its broad ecological spectrum and drought tolerance. Unfortunately, in some parts of Europe, clearcutting has drastically reduced the oak population. An example of this event is our survey of heritage Oak—Lime forests in European Russia, which were transformed into pure aspen stands. The aim of our study was to provide forecasts and silvicultural recommendations for the passive restoration of these forests. We took a chronosequence approach to assess changes associated with natural succession over 60 years. In our survey of the development of oaks, limes and accompanying tree species (aspen, birches, maples, elms), we used 190 plots ranging across a wide spectrum of forest disturbance due to clearcutting. We demonstrate that aspen reproduce rapidly by root suckers after cutting and occupy more than 60% of the space. But the dominance of aspen decreases continuously from the age of 30, and then the lime trees begin to dominate. Oak does not show successful natural regeneration. Therefore, we recommend planting oak seedlings or sowing acorns, i.e., active restoration, in combination with the natural restoration of lime.
Migratory Ecology of Pseudoplatystoma fasciatum in the Amazon Basin Revealed by Otolith Microchemistry
Authors: Pereira Luciana A. , Castello Leandro , Hallerman Eric , Orth Donald , Duponchelle Fabrice
Published: July 2024

Fish migrate for varied reasons, including to avoid predators and to access feeding, spawning, and nursery habitats, behaviors that enhance their survival and reproductive rates. However, the migratory ecology of many important fishes, especially those in river–floodplain ecosystems, remains poorly understood. One fish of the Amazon Basin whose migratory behavior is poorly understood is the catfish Pseudoplatystoma fasciatum. Here, we used otolith elemental microchemistry to characterize the migration ecology of P. fasciatum in the Amazon Basin. The main research questions of this study were: (1) does P. fasciatum move between waters with different Sr isotopic signatures (87Sr/86Sr) and chemical compositions? (2) What distance do they migrate? (3) Is the migration of P. fasciatum related to age? And (4) does P. fasciatum migrate mainly upstream, downstream, or in both directions? We assessed whether P. fasciatum migrates between waters with different 87Sr/86Sr values, comparing the Sr isotopic signature of otolith transects of each individual with the range of Sr isotopic signatures within the respective rivers. We found that 34% of the 71 fish analyzed migrated between rivers with different Sr isotopic signatures and 66% did not. The mean migration distance migrated was 126 km, with most specimens migrating between 72 and 237 km. Apparently, no fish of age one or age six or older migrated. All fish that migrated were between two and five years of age, with 20% of the specimens that migrated being two years old, 40% three years old, 30% four years old, and 20% five years old. Sixty-six percent of all individuals that migrated between rivers with different Sr signatures did so bidirectionally, while 33% moved unidirectionally. According to our definition of homing behavior in which fish migrated back to the same river where they were born, 41% of all fish that migrated displayed apparent homing behavior. Our findings provide insights into the migratory ecology of P. fasciatum, corroborating and refining knowledge reported in the literature. Our results on the migratory ecology of P. fasciatum have implications for sustainable fisheries conservation and management: conserving P. fasciatum requires habitat maintenance and suitable fishing practices in spawning and nursery habitats, and managers must consider large geographic areas for effective fishery management and conservation.
Machine Learning Model Construction and Testing: Anticipating Cancer Incidence and Mortality
Authors: Ding Yuanzhao
Published: July 2024

In recent years, the escalating environmental challenges have contributed to a rising incidence of cancer. The precise anticipation of cancer incidence and mortality rates has emerged as a pivotal focus in scientific inquiry, exerting a profound impact on the formulation of public health policies. This investigation adopts a pioneering machine learning framework to address this critical issue, utilizing a dataset encompassing 72,591 comprehensive records that include essential variables such as age, case count, population size, race, gender, site, and year of diagnosis. Diverse machine learning algorithms, including decision trees, random forests, logistic regression, support vector machines, and neural networks, were employed in this study. The ensuing analysis revealed testing accuracies of 62.17%, 61.92%, 54.53%, 55.72%, and 62.30% for the respective models. This state-of-the-art model not only enhances our understanding of cancer dynamics but also equips researchers and policymakers with the capability of making meticulous projections concerning forthcoming cancer incidence and mortality rates. Considering sustainability, the application of this advanced machine learning framework emphasizes the importance of judiciously utilizing extensive and intricate databases. By doing so, it facilitates a more sustainable approach to healthcare planning, allowing for informed decision-making that takes into account the long-term ecological and societal impacts of cancer-related policies. This integrative perspective underscores the broader commitment to sustainable practices in both health research and public policy formulation.
Computerized Axiographic Findings in a Cohort of Migraine Patients: A Cross-Sectional Study
Authors: Zokaris Nikolaos , Greven Marcus , Tzakis Michail , Psarras Vasileios
Published: July 2024

Background: The objective of this work was to investigate the association between the function of the stomatognathic system and migraine presence through an instrumental functional analysis in a group of diagnosed migraine patients and a control group. Methods: This study included 50 individuals in each group. A jaw-tracking analysis was performed using Cadiax 4. Tracings of the following movements were recorded: open/close, protrusion/retrusion, mediotrusion, speech, bruxing, and mastication. The tracings were evaluated for their quantity, quality, transversal characteristics, speed, curvature pattern, and condylar stability. Results: Statistically significant differences between the groups were established for several aspects of the evaluation. Migraineurs presented with (a) higher values of mandibular lateral translation in protrusion/retrusion (p = 0.001), open/close (p = 0.031), and mastication (p = 0.016); (b) transient velocity losses in open/close (p = 0.001) and protrusive movements (p = 0.018); (c) a compromised condylar stability for protrusion/retrusion (p = 0.001) and mediotrusion (p = 0.003); (d) a compromised quality for protrusion/retrusion (p < 0.001) and mediotrusion (p = 0.003); and (e) a more frequent “figure-eight” curvature in open/close (p = 0.012). Conclusions: The importance of the stomatognathic function in migraine pathogenesis and treatment should be considered by using a patient-centered and interdisciplinary approach.
On Entropic Learning from Noisy Time Series in the Small Data Regime
Authors: Bassetti Davide , Pospíšil Lukáš , Horenko Illia
Published: July 2024

In this work, we present a novel methodology for performing the supervised classification of time-ordered noisy data; we call this methodology Entropic Sparse Probabilistic Approximation with Markov regularization (eSPA-Markov). It is an extension of entropic learning methodologies, allowing the simultaneous learning of segmentation patterns, entropy-optimal feature space discretizations, and Bayesian classification rules. We prove the conditions for the existence and uniqueness of the learning problem solution and propose a one-shot numerical learning algorithm that—in the leading order—scales linearly in dimension. We show how this technique can be used for the computationally scalable identification of persistent (metastable) regime affiliations and regime switches from high-dimensional non-stationary and noisy time series, i.e., when the size of the data statistics is small compared to their dimensionality and when the noise variance is larger than the variance in the signal. We demonstrate its performance on a set of toy learning problems, comparing eSPA-Markov to state-of-the-art techniques, including deep learning and random forests. We show how this technique can be used for the analysis of noisy time series from DNA and RNA Nanopore sequencing.
Tail Risk Dynamics under Price-Limited Constraint: A Censored Autoregressive Conditional Fréchet Model
Authors: Xu Tao , Shu Lei , Chen Yu
Published: July 2024

This paper proposes a novel censored autoregressive conditional Fréchet (CAcF) model with a flexible evolution scheme for the time-varying parameters, which allows deciphering tail risk dynamics constrained by price limits from the viewpoints of different risk preferences. The proposed model can well accommodate many important empirical characteristics of financial data, such as heavy-tailedness, volatility clustering, extreme event clustering, and price limits. We then investigate tail risk dynamics via the CAcF model in the price-limited stock markets, taking entropic value at risk (EVaR) as a risk measurement. Our findings suggest that tail risk will be seriously underestimated in price-limited stock markets when the censored property of limit prices is ignored. Additionally, the evidence from the Chinese Taiwan stock market shows that widening price limits would lead to a decrease in the incidence of extreme events (hitting limit-down) but a significant increase in tail risk. Moreover, we find that investors with different risk preferences may make opposing decisions about an extreme event. In summary, the empirical results reveal the effectiveness of our model in interpreting and predicting time-varying tail behaviors in price-limited stock markets, providing a new tool for financial risk management.
Assessment of the Heat Transfer Conditions in the Cavity of a Rotating Circular Saw
Authors: Stegmann Jan , Baumert Moritz , Kabelac Stephan , Menze Christian , Ramme Johannes , Möhring Hans-Christian
Published: July 2024

To improve machining processes concerning the usage of lubricants, knowledge of the thermo-mechanical and thermo-fluid interactions at the cutting zone is of great importance. This study focuses on the description of the convective heat transfer which occurs during circular sawing when the lubricant is provided via an internal coolant supply. The highly complex flow field inside the cavity of the sawing process is separated into two distinct flow forms, an impingement and a channel flow. With the aid of experimental and numerical studies, the heat transfer characteristics of these two flow forms have been examined for water and a lubricant used in the circular sawing process. Studies have been conducted over a wide range of Reynolds numbers (impingement flow: 2×103<Re<17×103, channel flow: 1×103<Re<30×103). Additionally, the variation in the inlet temperature of the fluid, as well as the variation in heating power, has been studied. Overall, the impingement flow yields a significantly higher heat transfer than the channel flow with Nußelt-numbers ranging from 120 to 230, whereas the Nußelt-numbers in the case of the channel flow range from 20 to 160. For both flow forms, the use of the lubricant results in a better heat transfer compared with the usage of water. With the aid of these studies, correlations to describe the heat transfer have been derived. The provided correlations are to be used in a coupled numerical model of the chip formation process which also includes the effects of the heat transfer to the coolant lubricant.
Turning Food Loss and Food Waste into Watts: A Review of Food Waste as an Energy Source
Authors: Economou Florentios , Voukkali Irene , Papamichael Iliana , Phinikettou Valentina , Loizia Pantelitsa , Naddeo Vincenzo , Sospiro Paolo , Liscio Marco Ciro , Zoumides Christos , Țîrcă Diana Mihaela , Zorpas Antonis A.
Published: July 2024

Food loss (FL) and food waste (FW) have become severe global problems, contributing to resource inefficiency and environmental degradation. Approximately 6% of greenhouse gas emissions (GHGs) are derived from FW, which is usually discarded in landfills, emitting methane, a gas that is 28 times more harmful than CO2. Diverting the path of FW towards the energy industry represents a promising avenue to mitigate the environmental impact and save resources while generating energy substitutes. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was utilized to conduct a systematic literature review on 10 different conversion processes used to convert FL and FW into energy. Anaerobic bioconversion integrated with pyrolysis emerges as a potential eco-friendly and promising solution for FW management, nutrient recovery and energy production in various forms, including biogas, heat, biohydrogen and biochar. Despite its potential, the anaerobic digestion of FW still faces some challenges related to the production of intermediate harmful compounds (VOCs, NH3, H2S), which necessitate precise process control and optimization. Nonetheless, converting FW into energy can provide economic and environmental benefits in the context of the circular economy. This review offers insightful information to stakeholders, academics and policymakers who are interested in utilizing FW as a means of producing sustainable energy by summarizing the important findings of ten different waste-to-energy processing methods and their potential for improved energy recovery efficiency.
A Grid-Wide Comprehensive Evaluation Method of Power Quality Based on Complex Network Theory
Authors: Xiang Yang , Lin Yan , Zhang Yan , Lan Jinchen , Hao Meimei , Wang Lianhui , Wang Jiang , Qin Liang
Published: July 2024

To achieve a hierarchical and quantitative evaluation of grid-wide power quality in the distribution network, reflecting the overall power quality level of the distribution network, a comprehensive evaluation method for power quality in a grid-wide system based on complex network theory is proposed. Firstly, based on the propagation characteristics of power quality disturbances, a power quality evaluation index system is constructed. Secondly, to reflect the constraint effect of the local power quality level of nodes on the overall power quality level of the distribution system, corresponding indices such as improved node degree, improved node electrical betweenness, and node self-healing capability are proposed based on complex network theory, and the power quality influence degree of nodes is calculated. Then, the GRA-ANP (Grey Relational Analysis–Analytic Network Process) subjective weight calculation method is improved by introducing grey relational analysis to address the impact of differences in different decision-making results. Based on power quality monitoring data, the entropy weight method is used for objective weighting. To avoid the partiality of a single weight evaluation result, the game equilibrium algorithm is employed to calculate the comprehensive weight of each power quality index. Subsequently, considering the correlation and dependency among indices, the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) method is used to obtain the power quality grade of each node. Combining this with the calculation of the power quality influence degree of nodes, the overall power quality grade of the distribution network is determined, achieving a hierarchical and quantitative evaluation of power quality in the entire distribution system. Finally, through a case study analysis of an improved 13-node distribution network, it is verified that the proposed method can fully extract data information and produce comprehensive and accurate power quality assessment results by comparing it with other methods. This provides strong support for the safe and stable operation of the distribution system and the subsequent optimization and management of power quality.
Photovoltaic Capacity Management for Investment Effectiveness
Authors: Brzęczek Tomasz , Hadaś Łukasz
Published: July 2024

The production of photovoltaic utility varies within the day/night cycle. At night, photovoltaic cells do not produce anything. However, their day-light production, unconsumed on a current basis and exported to the grid, is compensated for with supply from the grid at night. This scheme of exploitation is called net-metering and is considered herein. Solar energy produced by a prosumer and fed into the grid has to be equal to the electricity supplied from the grid at night; otherwise, a shortage or waste of photovoltaic production occurs. The above finding leads us to the proposition for the optimal solution of photovoltaic capacity. We derived a closed-form capacity solution to the maximized non-linear profit function. It solves harmonic and 2-point production functions that vary symmetrically around the mean production. To verify the solution methodology, harmonic and 2-point models from empirical production data are estimated. Then, the solution is presented together with its return rate and internal return rate. The main finding is that the unit cost of the grid electricity, photovoltaic capacity unit cost and exploitation time all affect the total profit and return rate values while not impacting the optimal capacity of the photovoltaics. The optimal capacity depends on the prosumer’s energy consumption volume and on the natural conditions of production captured here by the technology efficiency coefficient estimated from the production time series.
Design of Battery Energy Storage System Torsional Damper for a Microgrid with Wind Generators Using Artificial Neural Network
Authors: Lee Kuei-Yen , Hsu Yuan-Yih
Published: July 2024

Ancillary frequency controllers such as droop controllers are beneficial for frequency regulation of a microgrid with high penetration of wind generators. However, the use of such ancillary frequency controllers may cause torsional oscillation in the doubly fed induction generator (DFIG). In this paper, a supplementary torsional damper in a battery energy storage system (BESS) is designed to improve the damping ratio for the DFIG torsional mode. Since the optimal damper gain depends on system variables such as the number of diesel generators, the number of wind generators, and BESS droop gain, an artificial neural network (ANN) is trained using these system variables as inputs and the desired BESS damper gain as the output. After the ANN has been trained with the training patterns, it can provide the desired BESS damper gain in an accurate and efficient manner. The effectiveness of the proposed ANN approach for BESS damper design is demonstrated by MATLAB/SIMULINK R2022b simulations.
Effectiveness of Daytime Radiative Sky Cooling in Constructions
Authors: Cannavale Alessandro , Pugliese Marco , Stasi Roberto , Liuzzi Stefania , Martellotta Francesco , Maiorano Vincenzo , Ayr Ubaldo
Published: July 2024

In this paper, we have carefully studied the scientific literature dealing with the use of passive radiative surfaces within the construction industry. The aim of this paper is to highlight technologies and materials for daylight radiative cooling under study today—or already on the market—and to report their main characteristics, performance and, where possible, costs. Following a review of the available scientific literature, the advantages and limitations of such an option were highlighted, seeking to capture opportunities and future lines of research development. This review also provides the physical laws that evaluate the energy balance of passive radiative surfaces as well as the criteria to quantify all the terms of these equations.
Sensorless Capability Expansion for SPMSM Based on Inductance Parameter Identification
Authors: Chen Peng , Ma Ruiqing , Song Shoujun , Chen Zhe
Published: July 2024

Pulsating high-frequency voltage injection can be used for the sensorless control of a surface-mounted permanent magnet synchronous motor (SPMSM) at zero- and low-speed ranges. However, the sensorless capability still faces challenges to the requirements of industrial application, especially at heavy load status. Aiming at this issue, this article proposes a sensorless capability expansion method for an SPMSM based on inductance parameter identification. Firstly, incremental inductances at the d-q-axis and cross-coupling inductance are identified offline by three steps combining the rotating high-frequency voltage injection and pulsating high-frequency voltage injection. Using a polynomial curve fitting algorithm, apparent inductances are calculated. Secondly, positive DC current injection at the d-axis is proposed to enhance the saliency ratio based on the analysis of parameter identification results. Compared with the conventional id = 0 or id < 0 method, the saliency ratio is enhanced obviously when a positive DC current is injected at the d-axis. Then, the convergence region of the sensorless control method at heavy load status is expanded and the accuracy of rotor position estimation is improved using the proposed method. Finally, the experimental results validate that the sensorless capability of the SPMSM is expanded.
Photo-Thermal Optimization of a Parabolic Trough Collector with Arrayed Selective Coatings
Authors: Shokrnia Mehdi , Cagnoli Mattia , Grena Roberto , D’Angelo Antonio , Lanchi Michela , Zanino Roberto
Published: July 2024

This work aims at enhancing the photo-thermal performance of a parabolic trough collector (PTC) system by implementing multiple coatings arrayed along the receiver tube. For this purpose, a lumped-parameter model was developed in the radial direction of the receiver tube to compute absorber tube wall temperature and heat losses at various heat transfer fluid (HTF) temperatures. The HTF is a mixture of molten salt (60%wt. NaNO3 + 40%wt. KNO3). The lamped-parameter model was exploited by a 1D model developed in the axial direction to determine the HTF temperature profile along the tube. The 1D model was employed to calculate photo-thermal efficiency at different HTF temperatures considering six selective coating formulations. Consequently, the most photo-thermally efficient configuration of the PTC system was determined, encompassing three HTF temperature ranges characterized by three different selective coating formulations. These temperature ranges were 290–436 °C (low temperature), 436–517 °C (medium temperature) and 517–550 °C (high temperature). The respective tube lengths were computed to be 792 m, 566 m and 293 m, considering the reference operational conditions. The optimal configuration enhanced the overall photo-thermal efficiency by 0.5–1.9% compared to the single-coated configurations. Furthermore, receiver cost could be reduced because of the employment of the more expensive coating only at the final segment.
Research on Failure Characteristics of Electric Logistics Vehicle Powertrain Gearbox Based on Current Signal
Authors: Tang Qian , Shu Xiong , Wang Jiande , Yuan Kainan , Zhang Ming , Zhou Honguang
Published: July 2024

As a core component of the powertrain system of Electric Logistics Vehicles (ELVs), the gearbox is crucial for ensuring the reliability and stability of ELV operations. Traditional fault diagnosis methods for gearboxes primarily rely on the analysis of vibration signals during operation. This paper presents research on diagnosing gear tooth wear faults in ELV powertrains using motor current signals. Firstly, an experimental test platform was constructed based on the structural principle of the powertrain of ELV models. Subsequently, a pure electric light truck powertrain gearbox with tooth wear was tested. Time–frequency domain analysis, amplitude analysis, ANOVA analysis, kurtosis analysis, and zero−crossing points analysis were used to analyze the U−phase current of the motor connected to the gearbox to study the characteristics of the phase current of the drive motor after tooth wear. The results indicate that while the time–frequency domain characteristics of the U−phase currents are not significantly altered by tooth wear faults, the amplitude, variance, and kurtosis of the current increase with the severity of the wear. Conversely, the number of zero−crossing points decreases. These findings provide valuable insights into new methodologies for diagnosing faults in ELV powertrain systems, potentially enhancing the efficiency and effectiveness of troubleshooting processes.
Three-Dimensional Modeling of Anion Exchange Membrane Electrolysis: A Two-Phase Flow Approach
Authors: Tardy Erwan , Bultel Yann , Druart Florence , Bonnefont Antoine , Guillou Melaine , Latour Benoit
Published: July 2024

Anion exchange membrane water electrolyzers (AEMWEs) are attracting growing interest as a green hydrogen production technology. Unlike proton exchange membrane (PEM) systems, AEMWEs operate in an alkaline environment, allowing one to use less expensive, non-noble materials as catalysts for the reactions and non-fluorinated anion exchange polymer membranes. However, the performance and stability of AEMWEs strongly depend on the alkaline electrolyte concentration. In this work, a three-dimensional multi-physics model considering two-phase flow effects is applied to understand the impact of KOH electrolyte concentration and its flow rate on AEMWE performance, as well as on the current and gas volume fraction distributions. The numerical results were compared to experimental data published in the literature. For current densities above 1 A/cm2, a strongly non-uniform H2 and O2 gas volume distribution could be evidenced by the 3D simulations. Increasing the KOH electrolyte flow rate from 10 to 100 mL/min noticeably improves cell performance for current densities above 1 A/cm2. These results show the importance of accounting for the three-dimensional geometry of an AEMWE and two-phase flow effects to accurately describe its operation and performance.