bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Unmanned Aerial Vehicle Navigation and Warehouse Inventory System Based on Reinforcement Learning
Authors: Lin Huei-Yung , Chang Kai-Lun , Huang Hsin-Ying
Published: May 2024

In this paper, we present the exploration of indoor positioning technologies for UAVs, as well as navigation techniques for path planning and obstacle avoidance. The objective was to perform warehouse inventory tasks, using a drone to search for barcodes or markers to identify objects. For the indoor positioning techniques, we employed visual-inertial odometry (VIO), ultra-wideband (UWB), AprilTag fiducial markers, and simultaneous localization and mapping (SLAM). These algorithms included global positioning, local positioning, and pre-mapping positioning, comparing the merits and drawbacks of various techniques and trajectories. For UAV navigation, we combined the SLAM-based RTAB-map indoor mapping and navigation path planning of the ROS for indoor environments. This system enabled precise drone positioning indoors and utilized global and local path planners to generate flight paths that avoided dynamic, static, unknown, and known obstacles, demonstrating high practicality and feasibility. To achieve warehouse inventory inspection, a reinforcement learning approach was proposed, recognizing markers by adjusting the UAV’s viewpoint. We addressed several of the main problems in inventory management, including efficiently planning of paths, while ensuring a certain detection rate. Two reinforcement learning techniques, AC (actor–critic) and PPO (proximal policy optimization), were implemented based on AprilTag identification. Testing was performed in both simulated and real-world environments, and the effectiveness of the proposed method was validated.
Disparity in the Burden of Caring for Older Persons between Families Living in Housing Estates and Traditional Communities in Thailand
Authors: Mulati Nadila , Aung Myo Nyein , Moolphate Saiyud , Aung Thin Nyein Nyein , Koyanagi Yuka , Supakankunti Siripen , Yuasa Motoyuki
Published: May 2024

Thailand’s rapid population aging and reliance on family-based long-term care requires research into disparities in family caregiver burden. Since the type of residence matters to the caregiving outcome, this research aimed to examine the difference in caregiver burden between residents of private housing estates and traditional village communities. This cross-sectional study was conducted with 1276 family caregivers of community-dwelling Thai older adults, in Chiang Mai province, Thailand. The caregiver burden was examined using the Caregiver Burden Inventory (CBI), and the care recipients’ dependency status was examined using Barthel’s Activity of Daily Living (ADL). Descriptive analysis, multivariate analysis of variance test, and multiple logistic regression analysis were performed. Family caregivers living in a traditional village community were 1.607 times more likely to experience emotional burden (adj. OR 1.607, 95% CI: 1.049, 2.462) and 2.743 times more likely to experience overall caregiver burden (adj. OR: 1.163, 95% CI: 1.163, 6.471) compared to those in the private housing estate group. Our findings showed significant differences in caregiver burden based on residential area, contributing with insights to evidence-based policies, interventions, and programs to minimize disparities and promote family caregivers’ health and well-being.
Optimal Voltage Recovery Learning Control for Microgrids with N-Distributed Generations via Hybrid Iteration Algorithm
Authors: Li Lüeshi , Song Ruizhuo , Dong Shuqing
Published: May 2024

Considering that the nonlinearity and uncertainty of the microgrid model complicate the derivation and design of the optimal controller, an adaptive dynamic programming (ADP) algorithm is designed to solve the model-free non-zero-sum game. By combining the advantages of policy iteration and value iteration, an optimal learning control scheme based on hybrid iteration is constructed to provide stringent real power sharing for the nonlinear and coupled microgrid systems with N-distributed generations. First, using non-zero-sum differential game strategy, a novel distributed secondary voltage recovery consensus optimal control protocol is built using a hybrid iteration method to realize the voltage recovery of microgrids. Then, the data of the system state and input are gathered along a dynamic system trajectory and a data-driven optimal controller learns the game solution without microgrid physics information, enhancing convenience and efficiency in practical applications. Furthermore, the convergence analysis is given in detail, and it is proved that the control protocol can converge to the optimal solution so as to ensure the stability of the voltage recovery of the microgrid system. Convergence analysis proves the convergence of the the protocol to the optimal solution, ensuring voltage recovery stability. Simulation results validate the feasibility and effectiveness of the proposed scheme.
Stochastic and Extreme Scenario Generation of Wind Power and Supply–Demand Balance Analysis Considering Wind Power–Temperature Correlation
Authors: Li Fan , Liu Dong , Sun Ke , Hong Shidong , Peng Fangzheng , Zhang Cheng , Tao Taikun , Qin Boyu
Published: May 2024

In the context of large-scale wind power access to the power system, it is urgent to explore new probabilistic supply–demand analysis methods. This paper proposes a wind power stochastic and extreme scenario generation method considering wind power–temperature correlations and carries out probabilistic supply–demand balance analysis based on it. Firstly, the influence of temperature on wind power output is analyzed via Pearson coefficient to obtain the correlation between wind power and temperature. Secondly, based on the historical wind power curve, a large number of wind power output scenarios are randomly generated while fully preserving its characteristics, and probabilistic supply–demand analysis is carried out. Thirdly, for the extreme case of continuous multi-day extreme heat without wind, extreme scenarios are selected from the generated scenarios for supply–demand balance analysis. Finally, a practical example in a province in central-eastern China is used to verify the effectiveness of the proposed method. The results indicate that the scenario generation method can effectively capture the historical wind power characteristics and can be better applied to the diversified supply and demand balance analysis to obtain more accurate analysis results.
Learning to Diagnose: Meta-Learning for Efficient Adaptation in Few-Shot AIOps Scenarios
Authors: Duan Yunfeng , Bao Haotong , Bai Guotao , Wei Yadong , Xue Kaiwen , You Zhangzheng , Zhang Yuantian , Liu Bin , Chen Jiaxing , Wang Shenhuan , Ou Zhonghong
Published: May 2024

With the advancement of technologies like 5G, cloud computing, and microservices, the complexity of network management systems and the variety of technical components have greatly increased. This rise in complexity has rendered traditional operations and maintenance methods inadequate for current monitoring and maintenance demands. Consequently, artificial intelligence for IT operations (AIOps), which harnesses AI and big data technologies, has emerged as a solution. AIOps plays a crucial role in enhancing service quality and customer satisfaction, boosting engineering productivity, and reducing operational costs. This article delves into the primary tasks involved in AIOps, such as anomaly detection, and log fault analysis and classification. A significant challenge identified in many AIOps tasks is the scarcity of fault sample data, indicating a natural alignment of these tasks with few-shot learning. Inspired by model-agnostic meta-learning (MAML), we propose a new anomaly detector, MAML-KAD, for application in various AIOps tasks. Observations confirm that meta-learning algorithms effectively enhance AIOps tasks, showcasing the wide-ranging application prospects of meta-learning algorithms in the field of AIOps. Moreover, we introduced an AIOps platform that embeds meta-learning within its diagnostic core and features streamlined log collection, caching, and alerting to automate the AIOps workflow.
Analysis of Model Predictive Control-Based Energy Management System Performance to Enhance Energy Transmission
Authors: Chowdhury Israth Jahan , Yusoff Siti Hajar , Gunawan Teddy Surya , Zabidi Suriza Ahmad , Hanifah Mohd Shahrin Bin Abu , Sapihie Siti Nadiah Mohd , Pranggono Bernardi
Published: May 2024

A supervisory control system using Model Predictive Control (MPC) has been designed to evaluate the efficiency of wind and solar power and is consistent with the cost function in the supervisory MPC optimization problem. A two-layer Economic Model Predictive Control (EMPC) framework has been developed and has improved results such as cost reductions compared to recent advanced methods. A speed Generalized Predictive Control (GPC) scheme intended for wind energy conversion systems was developed last year, with simulation results indicating superior performance over previous models. A Hierarchical Distributed Model Predictive Control (HDMPC) can work under different weather conditions with improved economic performance and keep a good balance between power delivery and load demand. An energy management system (EMS), built on the basis of MPC, can be quite lucrative for the sphere in the present climate scenario, with the selection and testing of suitable algorithms, controlled processes, cost functions, and a set of constraints as well as with proper optimizations carried out. Previous research indicates that an MPC-based EMS has the potential to be a good solution to manage energy well and also introduced it to the world experimentally. The key intention of this research study is to explore the existing advances that have been introduced and to analyze their performance in terms of cost function, different sets of constraints, variant conversion processes, and scalability to achieve more optimized operation of MPC-based EMS.
Life Cycle Assessment of a Wood Biomass Gasification Plant and Implications for Syngas and Biochar Utilization
Authors: Arfelli Francesco , Tosi Cristian , Ciacci Luca , Passarini Fabrizio
Published: May 2024

The growing attention regarding the environmental challenges in the energy sectors pushes the industrial system toward the investigation of more sustainable and renewable energy sources to replace fossil ones. Among the promising alternatives, biomass is considered a valid source to convert the system and to reduce the fossil fraction of the national energy mixes, but its multiple potential uses need an environmental evaluation to understand the actual benefit when it is used as an energy resource. For this purpose, life cycle assessment (LCA) is applied to a wood biomass gasification system aimed to produce electricity and heat generated after the combustion of the produced syngas and the management of the biochar. The aim is to provide a quantitative comparison of (i) a baseline scenario where wood biomass is sourced from waste and (ii) a second scenario where wood biomass is drawn from dedicated cultivation. A further evaluation was finally applied to investigate the environmental implications associated with the biochar composition, assuming it was used on land. The proposed strategies resulted in an environmental credit for both the examined scenarios, but the outcomes showed a net preference for the baseline scenario, resulting in better environmental performances for all the examined categories with respect to the second one. It underlines the potentialities of using waste-sourced biomass. However, according to the Climate Change category, if on-site dedicated biomass cultivation is assumed for the second scenario, the baseline is considered preferable only if the biomass transportation distance is <600 km, which is estimated as a theoretical distance for scenarios to break even. Finally, biochar composition proved a particular concern for toxicity-related categories. This study highlights the importance of applying objective and standardized methodologies such as LCA to evaluate energy production systems based on alternative sources and to support decision-making toward achieving sustainability goals.
Research on Influencing Factors and Wind Deflection Warning of Transmission Lines Based on Meteorological Prediction
Authors: Liu Yong , Guo Yufeng , Wang Bohan , Li Qiran , Gao Qun , Wan Yuanhao
Published: May 2024

Transmission lines are affected by external environmental factors such as strong winds and ice cover. In recent years, extreme weather events have increased, leading to recurrent disturbances in transmission lines because of wind deflection. These incidents have resulted in significant financial losses and have disrupted regular industrial and domestic activities. In this paper, the ANSYS Workbench 2020 R2 finite element analysis platform was used to establish a transmission line-hanging insulator string system model. Calculations on transmission lines were conducted considering variations in different stall spacing, height differences, wind speed, and the wind attack angle. The impact of these diverse factors on the wind deflection of insulators was scrutinized, leading to the derivation of patterns describing how the wind deflection angle shifts in response to changes in stall spacing, height differences, wind speed, and the wind attack angle. Based on the generalized linear regression network and particle swarm improved support vector machine algorithm, a meteorological prediction-based early warning method for wind deflection of transmission lines was proposed, a transmission line wind deflection early warning model was established, and the practical effect of the model was evaluated. The outcomes of this study provide crucial data for the formulation and development of ultra-high voltage (UHV) and extra-high voltage (EHV) transmission networks. Furthermore, they can contribute to the advanced detection of wind deflection issues.
RSV Infection in Refugees and Asylum Seekers: A Systematic Review and Meta-Analysis
Authors: Riccò Matteo , Corrado Silvia , Bottazzoli Marco , Marchesi Federico , Gili Renata , Bianchi Francesco Paolo , Frisicale Emanuela Maria , Guicciardi Stefano , Fiacchini Daniel , Tafuri Silvio
Published: May 2024

Respiratory diseases, including respiratory syncytial virus (RSV) infections, are common reasons for seeking healthcare among refugees and asylum seekers. A systematic review with meta-analysis was designed to appraise all the available evidence on RSV infections among individuals in refugee camps. Three medical databases (PubMed, Embase, and Scopus) as well as the preprint repository medRxiv.org were searched for eligible observational studies, and the collected cases were pooled in a random-effects meta-analysis model. Heterogeneity was assessed using the I2 statistics. Funnel plots and a regression analysis were calculated for analyzing reporting bias. Eventually, six studies were retrieved from three areas (Bangladesh, Thailand, and Kenya), with pooled estimates of 129.704 cases per 1000 samples (95% CI 66.393 to 237.986) for RSV compared to 110.287 per 1000 people for influenza A (95% CI 73.186 to 162.889), 136.398 cases per 1000 people (95% CI 84.510 to 212.741) for human adenovirus (HAdV), 69.553 per 1000 people (95% CI 49.802 to 96.343) for parainfluenzavirus (PIFV), and 60.338 per 1000 people (95% CI 31.933 to 111.109) for human metapneumovirus (hMPV). Using influenza A as a reference group, the risk for a positive specimen was greater for RSV (relative risk [RR] 1.514, 95% CI 1.396 to 1.641) and HAdV (RR 1.984, 95% CI 1.834 to 2.146) and lower for influenza B (RR 0.276, 95% CI: 0.239 to 0.319), PIFV (RR: 0.889, 95% CI 0.806 to 0.981), and hMPV (RR 0.594, 95% CI 0.534 to 0.662). In summary, high rates of RSV infections were documented among individuals sheltered in refugee camps, stressing the importance of specifically designed preventive strategies.
Forest Worker Households in the NFPP: Enhancing Sustainable Livelihoods through Capital and Transformation
Authors: Yu Bo , Cao Bo , Zhu Hongge
Published: May 2024

The persistent conflict between strict conservation and community welfare highlights the growing need to address sustainable livelihoods in forest protection programs. The Natural Forest Protection Program (NFPP) is a comprehensive forest protection program spearheaded by the Chinese government. It is designed to facilitate the conservation and restoration of forest ecosystems through a range of interventions, including logging ban, management, tending, and afforestation efforts. Drawing upon longitudinal micro-level household survey data spanning five consecutive years from 2017 to 2021, this research quantifies the sustainable livelihood levels of frontline participants in the NFPP by examining two dimensions: livelihood capital stock and livelihood transformation capacity. Additionally, it investigates the internal differentiation phenomenon within this cohort. The findings suggest that forest worker households engaged in tasks related to forest management, tending, and afforestation are the frontline participants in the NFPP, in contrast to management, technical, and service personnel. Moreover, these forest worker households exhibit a pattern characterized by a higher livelihood capital stock but a lower livelihood transformation capacity compared to non-forest worker households. Furthermore, within forest worker households, there is a significant group differentiation phenomenon, resulting in inter-group differentials in the sustainable livelihood levels based on geographical and seniority stratification criteria. The developers of the global forest protection program should prioritize addressing the sustainable livelihood issues of frontline participants in the program, especially the real problem of mismatches between livelihood capital stock and livelihood transformation capacity. This can be achieved through designing income incentives, stimulating consumption, and other means to enhance the relatively disadvantaged position of frontline participants while balancing the coordination and fairness of the protection program based on the aspects of both protection and development.
Global Overview of the Application of the Braun-Blanquet Approach in Research
Authors: Ivanova Natalya
Published: May 2024

Environmental classifications are of paramount importance for assessing the impacts of land-use changes, for prioritizing conservation efforts, and for developing effective management strategies to mitigate the negative impacts of human activities. The aim of our research was to provide as complete an analysis as possible of the studies that have been carried out using the Braun-Blanquet approach. The global review of studies based on the Braun-Blanquet approach includes 1168 papers and was conducted using the PRISMA 2009 methodological recommendations, strict criteria for the selection/quality of papers, and modern methods of data analysis and visualization using VOSviewer software developed by Nees Jan van Eck and Ludo Waltman (Centre for Science and Technology Studies (CWTS) of Leiden University in the Netherlands) (version 1.6.18), which ensures a representative sample, minimization of subjective judgements, and reliability of conclusions. It was noted that the number of publications on Braun-Blanquet is growing exponentially. This is an indication of the scientific interest in this methodology and its continuous further development. Based on a detailed analysis of the keywords, the main research directions and challenges are identified. These include improving the conceptual and methodological foundations of the Braun-Blanquet approach; improvement in regional vegetation classifications, synthesizing them and producing a comprehensive classification for large areas as a basis for biodiversity conservation and sustainable land use; expansion of the geography; compilation and updating of databases of phytosociological data; management of dynamics and vegetation; discussion of the important problem of continuity and discreteness of vegetation in the context of ecological classifications; and vegetation mapping. The top 20 journals publishing the most cited articles were identified, as well as the top 20 most cited journals whose high citation rate is due to the large number of high-quality articles. The analysis of the bibliographic network of papers in dynamics has shown that the structure of relationships is not constant and has changed significantly. The analysis of the authors’ publication activity showed that the vast majority of researchers have a low publication activity and have published only one to three papers. A peculiarity also emerges: if all the most cited authors are concentrated in Eurasia, then most of the most actively published authors are outside Eurasia. The importance of the Braun-Blanquet approach for the study and classification of forest vegetation should be emphasized. In this case, the Braun-Blanquet approach is integrated into forest typologies, increasing their ecological validity and environmental relevance.
The Impact of Lactobacillus delbrueckii Hepatic Metabolism in Post-Weaning Piglets
Authors: Wang Xiaolong , Ma Longteng , Liu Zhuying , Huang Xinguo
Published: May 2024

Lactobacillus delbrueckii garners interest for its contributions to gut microecological balance, diarrheal prevention and treatment, immune modulation, growth promotion, and meat quality enhancement in livestock. However, its impact on the gut microbiota and liver metabolism in weaned piglets is less documented. This study involved 80 Duroc-Landrace-Yorkshire weaned piglets aged 28 days, randomized into two groups with four replicates each and ten piglets per replicate. Over a 28-day period, the piglets were fed either a basal diet (control group) or the same diet supplemented with 0.1% Lactobacillus delbrueckii microcapsules (≥1.0 × 1010 CFU/g) (Lactobacillus delbrueckii group). The principal findings are as follows: During the initial phase of the experiment, supplementation with Lactobacillus delbrueckii increased the levels of L-phenylalanine and L-lysine in the liver while reducing the L-alanine levels, thereby enhancing the aminoacyl–tRNA synthesis pathway in weaned piglets. In the later phase, Lactobacillus delbrueckii supplementation boosted the liver arachidonic acid content, strengthening the arachidonic acid metabolic pathway in the piglets. The gut microbiota and their metabolites likely play a role in regulating these processes. These results indicate that, compared to the control group, Lactobacillus delbrueckii reduced weaning stress-induced liver damage and metabolic disorders, increased liver glycogen content, and enhanced liver antioxidant function by improving the metabolism of lipids and carbohydrates. Consequently, the liver functioned more healthily.
Influence of Cuttlefish-Ink Extract on Canned Golden Seabream (Sparus aurata) Quality
Authors: Martínez Beatriz , Trigo Marcos , Rodríguez Alicia , Aubourg Santiago P.
Published: May 2024

Four different concentrations of an aqueous extract of cuttlefish (Sepia spp.) ink (CI) were introduced, respectively, into the packing medium employed during golden seabream (Sparus aurata) canning. The quality parameters of the resulting canned fish were determined and compared to the initial fish and the control canned muscle. An important effect of the CI concentration introduced in the packing medium was proved. The presence in the packing medium of a relatively low CI concentration (CI-2 batch) led to a lower (p < 0.05) lipid oxidation development (fluorescent compound formation), lower (p < 0.05) changes of colour parameters (L* and a* values), and lower (p < 0.05) trimethylamine values in canned fish when compared to control canned samples. Additionally, the two lowest CI concentrations tested led to higher average values of C22:6ω3, ω3/ω6 ratios, and polyene index. On the contrary, the use of the most concentrated CI extract (CI-4 condition) led to a prooxidant effect (higher fluorescence ratio value). In agreement with environmental sustainability and circular economy requirements, the study can be considered the first approach to a novel and valuable use of the current marine byproduct for the quality enhancement of canned fish. On-coming research focused on the optimisation of the CI-extract concentration is envisaged.
A Comprehensive View of Food Microbiota: Introducing FoodMicrobionet v5
Authors: Parente Eugenio , Ricciardi Annamaria
Published: May 2024

Amplicon-targeted metagenomics is now the standard approach for the study of the composition and dynamics of food microbial communities. Hundreds of papers on this subject have been published in scientific journals and the information is dispersed in a variety of sources, while raw sequences and their metadata are available in public repositories for some, but not all, of the published studies. A limited number of web resources and databases allow scientists to access this wealth of information but their level of annotation on studies and samples varies. Here, we report on the release of FoodMicrobionet v5, a comprehensive database of metataxonomic studies on bacterial and fungal communities of foods. The current version of the database includes 251 published studies (11 focusing on fungal microbiota, 230 on bacterial microbiota, and 10 providing data for both bacterial and fungal microbiota) and 14,035 samples with data on bacteria and 1114 samples with data on fungi. The new structure of the database is compatible with interactive apps and scripts developed for previous versions and allows scientists, R&D personnel in industries and regulators to access a wealth of information on food microbial communities.
Challenges of the Application of In Vitro Digestion for Nanomaterials Safety Assessment
Authors: Vital Nádia , Gramacho Ana Catarina , Silva Mafalda , Cardoso Maria , Alvito Paula , Kranendonk Michel , Silva Maria João , Louro Henriqueta
Published: May 2024

Considering the increase in the production and use of nanomaterials (NM) in food/feed and food contact materials, novel strategies for efficient and sustainable hazard characterization, especially in the early stages of NM development, have been proposed. Some of these strategies encompass the utilization of in vitro simulated digestion prior to cytotoxic and genotoxic assessment. This entails exposing NM to fluids that replicate the three successive phases of digestion: oral, gastric, and intestinal. Subsequently, the resulting digestion products are added to models of intestinal cells to conduct toxicological assays, analyzing multiple endpoints. Nonetheless, exposure of intestinal cells to the digested products may induce cytotoxicity effects, thereby posing a challenge to this strategy. The aim of this work was to describe the challenges encountered with the in vitro digestion INFOGEST 2.0 protocol when using the digestion product in toxicological studies of NM, and the adjustments implemented to enable its use in subsequent in vitro biological assays with intestinal cell models. The adaptation of the digestion fluids, in particular the reduction of the final bile concentration, resulted in a reduced toxic impact of digestion products.
Phenolic and Metabolic Profiles, Antioxidant Activities, Glycemic Control, and Anti-Inflammatory Activity of Three Thai Papaya Cultivar Leaves
Authors: Chaijan Sirinet , Chaijan Manat , Uawisetwathana Umaporn , Panya Atikorn , Phonsatta Natthaporn , Shetty Kalidas , Panpipat Worawan
Published: May 2024

This study thoroughly examined the proximate composition, bioactive composition, and in vitro biological activities of three different cultivars of papaya leaf extracts (PLEs) as potential functional ingredients and nutraceuticals. The dark green leaves of three papaya cultivars, Khaek Dam (KD), Holland (H), and Thai Local (L), were used in this study. The protein content of the leaves ranged from 25.96 to 32.18%, the fat content ranged from 7.34 to 11.66%, the carbohydrate content ranged from 5.80 to 17.91%, the moisture content ranged from 6.02 to 6.49%, the ash content ranged from 11.23 to 12.40%, and the fiber content ranged from 23.24 to 38.48%. The L cultivar possessed significantly higher protein and carbohydrate contents, whereas the H cultivar had the highest ash content (p < 0.05). The total phenolic content (TPC) ranged from 113.94 to 173.69 mg GAE/g extract, with the KD cultivar having the highest TPC (p < 0.05). Several metabolic compounds such as phenolic compounds (particularly kaempferol, isorhamnetin, quercetin, ferulic acid, isoferulic acid, salicylic acid, sinapic acid, syringic acid, and vanillin), terpenoids (such as eucalyptol), glycosides, and indole were identified. The PLE from the KD cultivar had the highest levels of DPPH• inhibition, metal chelation, reducing power, and antidiabetic activity (p < 0.05), suggesting superior biological activity. All three PLEs reduced the proliferation of RAW 264.7 cells in a dose-dependent manner with low nitric oxide formation. These results indicate that the papaya leaf, particularly from the KD cultivar, could be a promising source of functional food ingredients.
Rational Approximations for the Oscillatory Two-Parameter Mittag–Leffler Function
Authors: Honain Aljowhara H. , Furati Khaled M. , Sarumi Ibrahim O. , Khaliq Abdul Q. M.
Published: May 2024

The two-parameter Mittag–Leffler function Eα,β is of fundamental importance in fractional calculus, and it appears frequently in the solutions of fractional differential and integral equations. However, the expense of calculating this function often prompts efforts to devise accurate approximations that are more cost-effective. When α>1, the monotonicity property is largely lost, resulting in the emergence of roots and oscillations. As a result, current rational approximants constructed mainly for α∈(0,1) often fail to capture this oscillatory behavior. In this paper, we develop computationally efficient rational approximants for Eα,β(−t), t≥0, with α∈(1,2). This process involves decomposing the Mittag–Leffler function with real roots into a weighted root-free Mittag–Leffler function and a polynomial. This provides approximants valid over extended intervals. These approximants are then extended to the matrix Mittag–Leffler function, and different implementation strategies are discussed, including using partial fraction decomposition. Numerical experiments are conducted to illustrate the performance of the proposed approximants.
Experimental Investigation on the Effect of Heating Oil and Tyre Pyrolysis Oil Combustion in an Evaporative Combustion Chamber
Authors: Kondor István Péter
Published: May 2024

This research aims to delve into the intricacies of combustion processes, specifically focusing on heating oil and a blend of heating oil with Tire Pyrolysis Oil (TPO) in a self-developed evaporative combustion chamber featuring steam injection. The primary objective is to scrutinize the impact of steam injection on the combustion dynamics. Conducting a series of tests, the investigation involved the meticulous manipulation of stoichiometric ratios while introducing ambient air through gravity fuel flow. Subsequent iterations of these tests incorporated the introduction of steam into the ambient air stream. The examination encompassed the combustion of both heating oil and the TPO blend within the combustion chamber. The evaluation criteria comprised an in-depth analysis of flame characteristics, temperature distribution within the combustion chamber, and the quantification of emissions such as particulate matter (PM), nitrogen oxides (NOx), carbon dioxide (CO2), carbon monoxide (CO), and water vapor (H2O). Throughout the experimentation phase, commercially available diesel fuel served as the primary fuel source. To facilitate the tests, the combustion chamber under scrutiny was seamlessly integrated into an AVL engine test bench system. Essential parameters, including fuel consumption, were meticulously gauged using an AVL 735 fuel flow meter, while fuel temperature was monitored using the AVL 745 fuel temperature conditioning system. The intake air, a crucial element in the combustion process, was quantified with precision using an AVL Flowsonix sensor. Emission measurements were conducted meticulously using state-of-the-art equipment, with gaseous emissions analyzed using an AVL FTIR AMA i60 exhaust gas analyzer. Simultaneously, soot emissions were quantified through employment of an AVL Micro Soot sensor. This comprehensive approach not only delves into the fundamental aspects of combustion but also extends its reach to the exploration of innovative techniques, such as steam injection, to enhance combustion efficiency and reduce emissions. The integration of advanced measurement tools ensures a robust and thorough analysis of the combustion process and its environmental implications.
Application of Hybrid Deep Reinforcement Learning for Managing Connected Cars at Pedestrian Crossings: Challenges and Research Directions
Authors: Brunoud Alexandre , Lombard Alexandre , Gaud Nicolas , Abbas-Turki Abdeljalil
Published: May 2024

The autonomous vehicle is an innovative field for the application of machine learning algorithms. Controlling an agent designed to drive safely in traffic is very complex as human behavior is difficult to predict. An individual’s actions depend on a large number of factors that cannot be acquired directly by visualization. The size of the vehicle, its vulnerability, its perception of the environment and weather conditions, among others, are all parameters that profoundly modify the actions that the optimized model should take. The agent must therefore have a great capacity for adaptation and anticipation in order to drive while ensuring the safety of users, especially pedestrians, who remain the most vulnerable users on the road. Deep reinforcement learning (DRL), a sub-field that is supported by the community for its real-time learning capability and the long-term temporal aspect of its objectives looks promising for AV control. In a previous article, we were able to show the strong capabilities of a DRL model with a continuous action space to manage the speed of a vehicle when approaching a pedestrian crossing. One of the points that remains to be addressed is the notion of discrete decision-making intrinsically linked to speed control. In this paper, we will present the problems of AV control during a pedestrian crossing, starting with a modelization and a DRL model with hybrid action space adapted to the scalability of a vehicle-to-pedestrian (V2P) encounter. We will also present the difficulties raised by the scalability and the curriculum-based method.
A Mouse Model of X-Linked Chronic Granulomatous Disease for the Development of CRISPR/Cas9 Gene Therapy
Authors: Sevim-Wunderlich Seren , Dang Tu , Rossius Jana , Schnütgen Frank , Kühn Ralf
Published: May 2024

Chronic granulomatous disease (CGD) is an inherited immunodeficiency disease mainly caused by mutations in the X-linked CYBB gene that abrogate reactive oxygen species (ROS) production in phagocytes and microbial defense. Gene repair using the CRISPR/Cas9 system in hematopoietic stem and progenitor cells (HSPCs) is a promising technology for therapy for CGD. To support the establishment of efficient and safe gene therapies for CGD, we generated a mouse model harboring a patient-derived mutation in the CYBB gene. Our CybbC517del mouse line shows the hallmarks of CGD and provides a source for Cybb-deficient HSPCs that can be used to evaluate gene-therapy approaches in vitro and in vivo. In a setup using Cas9 RNPs and an AAV repair vector in HSPCs, we show that the mutation can be repaired in 19% of treated cells and that treatment restores ROS production by macrophages. In conclusion, our CybbC517del mouse line provides a new platform for refining and evaluating novel gene therapies and studying X-CGD pathophysiology.
Leveraging Sentinel-2 and Geographical Information Systems in Mapping Flooded Regions around the Sesia River, Piedmont, Italy
Authors: Petropoulos George P. , Georgiadi Athina , Kalogeropoulos Kleomenis
Published: May 2024

Sentinel-2 data are crucial in mapping flooded areas as they provide high spatial and spectral resolution but under cloud-free weather conditions. In the present study, we aimed to devise a method for mapping a flooded area using multispectral Sentinel-2 data from optical sensors and Geographical Information Systems (GISs). As a case study, we selected a site located in Northern Italy that was heavily affected by flooding events on 3 October 2020, when the Sesia River in the Piedmont region was hit by severe weather disturbance, heavy rainfall, and strong winds. The method developed for mapping the flooded area was a thresholding technique through spectral water indices. More specifically, the Normalized Difference Water Index (NDWI) and the Modified Normalized Difference Water Index (MNDWI) were chosen as they are among the most widely used methods with applications across various environments, including urban, agricultural, and natural landscapes. The corresponding flooded area product from the Copernicus Emergency Management Service (EMS) was used to evaluate the flooded area predicted by our method. The results showed that both indices captured the flooded area with a satisfactory level of detail. The NDWI demonstrated a slightly higher accuracy, where it also appeared to be more sensitive to the separation of water from soil and areas with vegetation cover. The study findings may be useful in disaster management linked to flooded-area mapping and area rehabilitation mapping following a flood event, and they can also valuably assist decision and policy making towards a more sustainable environment.
Functional Tic-like Behaviors: From the COVID-19 Pandemic to the Post-Pandemic Era
Authors: Cavanna Andrea Eugenio , Spini Laura , Ferrari Silvia , Purpura Giulia , Riva Anna , Nacinovich Renata , Seri Stefano
Published: May 2024

During the COVID-19 pandemic, there have been multiple reports about an unforeseen surge in adolescents and young adults exhibiting sudden onset functional tic-like behaviors. This phenomenon has been mainly associated with the female gender and occasionally after exposure to social media content featuring similar patterns of functional tic-like behaviors. A significant portion of these individuals have been directed to specialist clinics for movement disorders with initial misdiagnoses of late-onset refractory Tourette syndrome. Distinguishing between rapid onset functional tic-like behaviors and neurodevelopmental tics as part of Tourette syndrome can be challenging; however, the differential diagnosis is facilitated by focusing on specific clinical and demographic factors, which we have explored in a systematic literature review. Compared to neurodevelopmental tics, functional tic-like behaviors typically present with a more abrupt and intense manifestation of symptoms, onset at a later age, higher prevalence among females, inability to suppress tics, coexisting anxiety and depression, and sometimes a history of exposure to social media content portraying tic-like behaviors of a similar nature. This novel manifestation of a functional neurological disorder may thus be viewed as an emerging neuropsychiatric condition potentially triggered/exacerbated by the psychosocial repercussions of the COVID-19 crisis.
Virtual Reality Applied to Heritage in Higher Education—Validation of a Questionnaire to Evaluate Usability, Learning, and Emotions
Authors: Corrales-Serrano Mario , Merchán Pilar , Merchán María José , Pérez Emiliano
Published: May 2024

Cultural heritage is one of the areas where Extended Reality is having a significant impact nowadays. Although often associated with entertainment, this technology has enormous educational potential when applied to heritage. Therefore, it is essential to implement monitoring tools in educational practice to assess its actual effectiveness. This article presents the process of generating and validating a statistical data collection instrument developed to evaluate a virtual reality experience created using the archaeological heritage of the ancient Roman city of Augusta Emerita (Mérida, Spain). It can be easily adapted to evaluate similar experiences. The aim is to gauge the effectiveness of these experiences as a didactic resource. The questionnaire was subjected to an evaluation of its three dimensions. Content validity was analyzed through expert judgments, while applicability was tested by students. Finally, a series of statistical tests were conducted to verify construct reliability and internal consistency. Based on the results obtained and cross-referenced with the data provided by the literature, the suitability of this tool for collecting data on usability, learning, and emotions in virtual reality experiences is confirmed.
Impact of Specific Bioactive Collagen Peptides on Joint Discomforts in the Lower Extremity during Daily Activities: A Randomized Controlled Trial
Authors: Schulze Claas , Schunck Michael , Zdzieblik Denise , Oesser Steffen
Published: May 2024

The intake of specific collagen peptides (SCPs) has been shown to decrease activity-related knee pain in young, physically active adults. This trial investigated the effect of a 12-week SCP supplementation in a wider age range of healthy men and women over 18 years with functional knee and hip pain during daily activities. A total of 182 participants were randomly assigned to receive either 5 g of specific collagen peptides (CP-G) or a placebo (P-G). Pain at rest and during various daily activities were assessed at baseline and after 12 weeks by a physician and participants using a 10-point numeric rating scale (NRS). The intake of 5 g SCP over 12 weeks significantly reduced pain at rest (p = 0.018) and during walking (p = 0.032) according to the physician’s evaluation. Participants in the CP-G also reported significantly less pain when climbing stairs (p = 0.040) and when kneeling down (p < 0.001) compared to the P-G. Additionally, after 12 weeks, restrictions when squatting were significantly lower in the CP-G compared with the P-G (p = 0.014). The daily intake of 5 g of SCP seems to benefit healthy adults with hip and knee joint discomforts by reducing pain during daily activities.
Patient Perspectives on Portal-Based Anxiety and Depression Screening in HIV Care: A Qualitative Study Using the Consolidated Framework for Implementation Research
Authors: Walker Jacob A. , Staab Erin M. , Ridgway Jessica P. , Schmitt Jessica , Franco Melissa I. , Hunter Scott , Motley Darnell , Laiteerapong Neda
Published: May 2024

Electronic patient portals represent a promising means of integrating mental health assessments into HIV care where anxiety and depression are highly prevalent. Patient attitudes toward portal-based mental health screening within HIV clinics have not been well described. The aim of this formative qualitative study is to characterize the patient-perceived facilitators and barriers to portal-based anxiety and depression screening within HIV care in order to inform implementation strategies for mental health screening. Twelve adult HIV clinic patients participated in semi-structured interviews that were audio recorded and transcribed. The transcripts were coded using constructs from the Consolidated Framework for Implementation Research and analyzed thematically to identify the barriers to and facilitators of portal-based anxiety and depression screening. Facilitators included an absence of alternative screening methods, an approachable design, perceived adaptability, high compatibility with HIV care, the potential for linkage to treatment, an increased self-awareness of mental health conditions, the ability to bundle screening with clinic visits, and communicating an action plan for results. The barriers included difficulty navigating the patient portal system, a lack of technical support, stigmatization from the healthcare system, care team response times, and the novelty of using patient portals for communication. The patients in the HIV clinic viewed the use of a portal-based anxiety and depression screening tool as highly compatible with routine HIV care. Technical difficulties, follow-up concerns, and a fear of stigmatization were commonly perceived as barriers to portal use. The results of this study can be used to inform implementation strategies when designing or incorporating portal-based mental health screening into other HIV care settings.
The Role of Parenting Behaviors and Their Influence on Adolescent Drunk and Drugged Driving: 2016–2019, USA
Authors: Yockey R. Andrew , Barroso Cristina S. , Hoopsick Rachel A.
Published: May 2024

Drugged driving, the act of driving a vehicle under the influence of illicit drugs, by adolescents is a serious public health concern. Many factors contribute to this risk behavior, but much less is known regarding the role of parenting behaviors in this phenomenon. The purpose of this study was to examine specific parenting behaviors and their influence among a nationally representative sample of adolescents. Pooled data from the 2016–2019 National Survey on Drug Use and Health (NSDUH) among 17,520 adolescents ages 16–17 years old were analyzed. Differences were found in specific parenting behaviors and adolescent drugged/drunk driving, with parents not checking homework and not telling their children they are proud of them being the most influential. Findings from the present study may inform drugged driving prevention programs for parents and adolescents and enhance road safety interventions.
Epstein-Barr Virus Lytic Transcripts Correlate with the Degree of Myocardial Inflammation in Heart Failure Patients
Authors: Baumeier Christian , Harms Dominik , Altmann Britta , Aleshcheva Ganna , Wiegleb Gordon , Bock Thomas , Escher Felicitas , Schultheiss Heinz-Peter
Published: May 2024

The Epstein-Barr virus (EBV) is frequently found in endomyocardial biopsies (EMBs) from patients with heart failure, but the detection of EBV-specific DNA has not been associated with progressive hemodynamic deterioration. In this paper, we investigate the use of targeted next-generation sequencing (NGS) to detect EBV transcripts and their correlation with myocardial inflammation in EBV-positive patients with heart failure with reduced ejection fraction (HFrEF). Forty-four HFrEF patients with positive EBV DNA detection and varying degrees of myocardial inflammation were selected. EBV-specific transcripts from EMBs were enriched using a custom hybridization capture-based workflow and, subsequently, sequenced by NGS. The short-read sequencing revealed the presence of EBV-specific transcripts in 17 patients, of which 11 had only latent EBV genes and 6 presented with lytic transcription. The immunohistochemical staining for CD3+ T lymphocytes showed a significant increase in the degree of myocardial inflammation in the presence of EBV lytic transcripts, suggesting a possible influence on the clinical course. These results imply the important role of EBV lytic transcripts in the pathogenesis of inflammatory heart disease and emphasize the applicability of targeted NGS in EMB diagnostics as a basis for specific treatment.