bluuebunny/crossref_metadata_2025 huggingface dataset:
Natural Compounds with Antifungal Properties against Candida albicans and Identification of Hinokitiol as a Promising Antifungal Drug
Authors: Camaioni Louis , Ustyanowski Bastien , Buisine Mathys , Lambert Dylan , Sendid Boualem , Billamboz Muriel , Jawhara Samir
Published: November 2023

Candida albicans is an opportunistic yeast that causes most fungal infections. C. albicans has become increasingly resistant to antifungal drugs over the past decade. Our study focused on the identification of pure natural compounds for the development of antifungal medicines. A total of 15 natural compounds from different chemical families (cinnamic derivatives, aromatic phenols, mono- and sesquiterpenols, and unclassified compounds) were screened in this study. Among these groups, hinokitiol (Hi), a natural monoterpenoid extracted from the wood of the cypress family, showed excellent anti-C. albicans activity, with a MIC value of 8.21 µg/mL. Hi was selected from this panel for further investigation to assess its antifungal and anti-inflammatory properties. Hi exhibited significant antifungal activity against clinically isolated fluconazole- or caspofungin-resistant C. albicans strains. It also reduced biofilm formation and hyphal growth. Treatment with Hi protected Caenorhabditis elegans against infection with C. albicans and enhanced the expression of antimicrobial genes in worms infected with C. albicans. Aside from its antifungal activities against C. albicans, Hi challenge attenuated the LPS-induced expression of pro-inflammatory cytokines (IL-6, IL-1β, and CCL-2) in macrophages. Overall, Hi is a natural compound with antifungal and anti-inflammatory properties, making Hi a promising platform with which to fight against fungal infections.
Silicon versus Superbug: Assessing Machine Learning’s Role in the Fight against Antimicrobial Resistance
Authors: Coxe Tallon , Azad Rajeev K.
Published: November 2023

In his 1945 Nobel Prize acceptance speech, Sir Alexander Fleming warned of antimicrobial resistance (AMR) if the necessary precautions were not taken diligently. As the growing threat of AMR continues to loom over humanity, we must look forward to alternative diagnostic tools and preventive measures to thwart looming economic collapse and untold mortality worldwide. The integration of machine learning (ML) methodologies within the framework of such tools/pipelines presents a promising avenue, offering unprecedented insights into the underlying mechanisms of resistance and enabling the development of more targeted and effective treatments. This paper explores the applications of ML in predicting and understanding AMR, highlighting its potential in revolutionizing healthcare practices. From the utilization of supervised-learning approaches to analyze genetic signatures of antibiotic resistance to the development of tools and databases, such as the Comprehensive Antibiotic Resistance Database (CARD), ML is actively shaping the future of AMR research. However, the successful implementation of ML in this domain is not without challenges. The dependence on high-quality data, the risk of overfitting, model selection, and potential bias in training data are issues that must be systematically addressed. Despite these challenges, the synergy between ML and biomedical research shows great promise in combating the growing menace of antibiotic resistance.
Antibiotic Resistance of Haemophilus influenzae in Nasopharyngeal Carriage of Children with Acute Otitis Media and in Middle Ear Fluid from Otorrhea
Authors: Assad Zein , Cohen Robert , Varon Emmanuelle , Levy Corinne , Bechet Stéphane , Corrard François , Werner Andreas , Ouldali Naïm , Bonacorsi Stéphane , Rybak Alexis
Published: November 2023

Haemophilus influenzae (Hi) is one of the leading bacteria implicated in childhood acute otitis media (AOM). Recent concerns have been raised about the emergence of Hi-resistant strains. We aimed to analyze the evolution of β-lactam resistance to Hi among strains isolated from nasopharyngeal carriage in children with AOM and in mild ear fluid (MEF) after the spontaneous perforation of the tympanic membrane (SPTM) in France. In this national ambulatory-based cohort study over 16 years, we analyzed the rate of Hi nasopharyngeal carriage and the proportion of β-lactam-resistant Hi strains over time using a segmented linear regression model. Among the 13,865 children (median [IQR] age, 12.7 [9.3–17.3] months; 7400 [53.4%] male) with AOM included from November 2006 to July 2022, Hi was isolated in 7311 (52.7%) children by nasopharyngeal sampling. The proportion of β-lactamase-producing and β-lactamase-negative, ampicillin-resistant (BLNAR) Hi strains in nasopharyngeal carriage remained stable during the study period. Among the 783 children (median [IQR] age, 20 [12.3–37.8] months; 409 [52.2%] male) with SPTM included from October 2015 to July 2022, Hi was isolated in 177 (22.6%) cases by MEF sampling. The proportions of β-lactamase-producing and BLNAR Hi strains did not significantly differ between nasopharyngeal (17.6% and 8.8%, respectively) and MEF (12.6% and 7.4%) samples. Accordingly, amoxicillin remains a valid recommendation as the first-line drug for AOM in France.
Partial Substitution of Wheat Flour with Palm Flour in Pasta Preparation
Authors: Rodrigues David Santos , Cavalcanti Mônica Tejo , Gomes Cristiano Alves , Araújo Jucilene Silva , Lima Renato Pereira , Moreira Inacia dos Santos , Monteiro Shênia Santos , Pereira Emmanuel Moreira
Published: November 2023

Pasta, a globally cherished staple food, is consumed on a wide scale. However, conventional wheat-based pasta often lacks nutrients that can be incorporated to add value to the new product. To address this nutritional deficiency and enhance the health benefits for consumers, a promising approach is to incorporate Opuntia ficus-indica flour as a partial substitute for wheat flour. The primary objective of this study was to craft enriched tagliatelle pasta using Opuntia ficus-indica flour. The evaluation encompassed an assessment of physical-chemical attributes, color quality, cooking properties, texture profile analysis (TPA), and the analysis of bioactive compounds within the pasta products. Upon conclusion of the experiments, the F10 formulation, comprising 10% Opuntia ficus-indica flour, emerged as the most favorable pasta option. It exhibited an acceptable acidity level of 3.71% and demonstrated remarkable nutritional characteristics. These findings suggest that this formulation could serve as a promising alternative for the production of health-conscious pasta.
The Study of the Performance of the Diamond Wheel’s Steel and CFRP Hubs in Tungsten Carbide (WC) Grinding
Authors: Lin Yao-Tsung , Chen Kai-Jung , Chen Chun-Yen , Lin You-Xhiang , Tsai Ming-Yi
Published: November 2023

Tungsten carbide (WC) has been widely utilized in recent years in the hardware, mechanical, and chemical industries and in national defense because of its high hardness, anti-wear, low temperature, and anti-corrosion properties. However, using it for grinding is also challenging because the WC material has high hardness and brittle characteristics. The typical hub of a diamond wheel is made of steel. In high-speed grinding, the steel hub of the diamond wheel is subjected to gravity and centrifugal forces, which cause grinding wheel vibration, poor workpiece processing quality, and a short machine life. Therefore, this study used a carbon-fiber-reinforced thermoplastic (CFRP) hub to replace the steel hub when grinding the WC workpiece. It aimed to investigate methods to reduce oscillation, improve chip efficiency, and increase accuracy in the WC workpiece. The research results demonstrated that using a CFRP hub in the grinding wheel can reduce the oscillation when the peripheral speed of the grinding wheel is at 20–100 m/s. Additionally, the surface roughness average (Ra) of the workpiece can be reduced to 3.2–25.4% and the ten-point height of irregularities (Rz) can be reduced to 18.9–44% compared to using a steel hub in the grinding wheel.
Approach to Modernizing Residential-Dominated District Heating Systems to Enhance Their Flexibility, Energy Efficiency, and Environmental Friendliness
Authors: Boyko Ekaterina , Byk Felix , Ilyushin Pavel , Myshkina Lyudmila , Filippov Sergey
Published: November 2023

The need to modernize existing district heating systems is due to increased requirements for their flexibility, energy efficiency, and environmental friendliness. The technical policy on district heating pursued in different countries centers on the listed goals and takes account of historical, climatic, and regional features of the resource, technology, and economic availability of various thermal energy sources. This study aims to analyze methods designed to improve the flexibility, energy efficiency, and environmental friendliness of district heating systems. The focus of the study is district heating system, which provides heating and hot water supply to consumers and consists of various types of thermal energy sources. The work shows the possibility for the heating system to transition from the third generation to the fourth one, which differ in their level of intellectualization. The establishment of an intelligent control system will ensure the interaction of various heat sources, but this is a separate strand of research. In this study, a model and a methodology were developed to optimize the structure of thermal energy sources and their operating conditions when covering the heat load curve of a territory with a predominance of household consumers. Gas-reciprocating and gas-turbine cogeneration plants are considered as the main thermal energy sources, whose efficiency is boosted through their joint operation with electric boilers, thermal energy storage systems, low-grade heat sources, and absorption chillers. The primary emphasis of the study is on the assessment of the environmental benefit to be gained by using cogeneration plants as a factor of enhancing the investment appeal of the district heating systems. The findings suggest that the transition of district heating systems to the next generation is impossible without changing the institutional environment, strengthening the role of active consumers, and introducing intelligent control for district heating systems.
Ellipsoidal Trajectory Optimization for Minimizing Latency and Data Transmission Energy in UAV-Assisted MEC Using Deep Reinforcement Learning
Authors: Sadia Rabeya , Akter Shathee , Yoon Seokhoon
Published: November 2023

Due to their flexible deployment and movement capability, unmanned aerial vehicles (UAVs) are being utilized as flying mobile edge computing (MEC) platforms, offering real-time computational resources and low-latency data processing for a wide range of applications. This article aims to explore a UAV-assisted MEC system where multiple UAVs provide MEC services to mobile devices (MDs) using an ellipsoidal trajectory. Depending on the position, size, and orientation of the ellipsoidal trajectories, the coverage area of the UAV, the energy consumption, and the task transmission latency of MDs change. This has rarely been investigated in the existing works. Furthermore, unlike other studies, we consider that each MD has varying task offloading rates, which, together with varying user densities, makes the problem more challenging. Therefore, we formulate an optimization problem that finds the center position, major radius, minor radius, and rotation angle of the ellipsoidal trajectory of UAV-assisted MEC servers, to minimize the total transmission latency and energy consumption of mobile devices while taking into account the required data transmission rate, task transmission time, and energy consumption constraints. Then, we transform this optimization problem into a Markov decision process and propose a deep Q-learning-based ellipsoidal trajectory optimization (DETO) algorithm, to resolve it. The results from our simulations demonstrate that DETO efficiently computes the optimal position and trajectory for each UAV, and can achieve better performance compared to other baselines, leading to the reduced data transmission latency and energy consumption of mobile devices across a range of simulation scenarios.
The Influence of Supply Channel Design on the Gas-Dynamic Structure of Air Flow in a Vertical Conical Diffuser
Authors: Plotnikov Leonid , Ryzhkov Alexander
Published: November 2023

Vertical conical diffusers are used in power engineering, chemical industry, technological processes, and other industries. The efficiency of many machines and pieces of equipment is determined by the gas-dynamic and heat-exchange perfection of processes in diffusers. This study assesses the influence of the air supply method on flow structure in a diffuser. The studies were carried out on a test bench with thermal imaging for air flow rates ranging from 0.018 to 0.057 m3/s (42,500 < Re < 150,000). Two designs were examined: (1) a conventional air supply through one channel from below and (2) a nozzle air supply through four tubes at an angle of 45° to the vertical axis. In addition, the influence of the cross-sectional shape of the supply channels of both designs was studied. It is established that the use of a conventional air supply through one channel leads to the generation of a pronounced central flow along the vertical axis (all configurations of the supply channel) and the creation of stagnant zones in the corners of the diffuser (round and triangular channels; the use of a square supply channel causes the most uniform air distribution throughout the entire volume of the diffuser (while maintaining the central flow). It is found that with nozzle air supply, there are no stagnant zones in the corners and intense air movement generation in the centre of the diffuser (round and triangular tubes) can be observed; the use of square nozzle tubes causes intense flow movement at the base of the diffuser, which quickly collapses upstream, uniformly filling the entire volume of the diffuser’s cylindrical part. The presented data can be useful for designing various machines and pieces of equipment with vertical conical diffusers.
Fuzzy Algorithm Applied to Factors Influencing Competitiveness: A Case Study of Brazil and Peru through Affinities Theory
Authors: Barcellos-Paula Luciano , Castro-Rezende Aline , Alvares Daniela Fantoni
Published: November 2023

Innovation plays a crucial role in the economy of nations worldwide. In Latin America, countries foster competitiveness through public and private incentives to support innovation. Moreover, entrepreneurship incentives seek to improve countries’ performance, although factors such as low business growth rates and informality can compromise it. Despite the efforts, there are several difficulties in achieving competitiveness, and few studies in developing countries. Therefore, the article explores the relationship between the factors that influence competitiveness, especially the role of innovation and entrepreneurship in Brazil and Peru. The research uses quantitative-qualitative methodology through modeling and simulation and a case study. The authors use the Affinities Theory to verify the relationship between the indicators that make up the competitiveness landscape and its most significant and attractive factors, adapting the methodology established by the International Institute for Management Development (IMD) World Competitiveness ranking. As a result, this algorithm allows us to know the relationships between five factors of economic attractiveness and four competitiveness indicators. As its main contributions, the study advances the frontier of knowledge about innovation and entrepreneurship, as few studies explore competitiveness in developing countries. Also, it offers a detailed explanation of the application of this algorithm, allowing researchers to reproduce this methodology in other scenarios. Practically, it might support policymakers in formulating development strategies and stimuli for business competitiveness. In addition, academic and business leaders can strengthen university-business collaboration with applied research in innovation and entrepreneurship. One limitation would be the number of countries participating in the research. The authors suggest future lines of research.
Solution of Two-Dimensional Solute Transport Model for Heterogeneous Porous Medium Using Fractional Reduced Differential Transform Method
Authors: Maisuria Manan A. , Tandel Priti V. , Patel Trushitkumar
Published: November 2023

This study contains a two-dimensional mathematical model of solute transport in a river with temporally and spatially dependent flow, explicitly focusing on pulse-type input point sources with a fractional approach. This model is analyzed by assuming an initial concentration function as a declining exponential function in both the longitudinal and transverse directions. The governing equation is a time-fractional two-dimensional advection–dispersion equation with a variable form of dispersion coefficients, velocities, decay constant of the first order, production rate coefficient for the solute at the zero-order level, and retardation factor. The solution of the present problem is obtained by the fractional reduced differential transform method (FRDTM). The analysis of the initial retardation factor has been carried out via plots. Also, the influence of initial longitudinal and transverse dispersion coefficients and velocities has been examined by graphical analysis. The impact of fractional parameters on pollution levels is also analyzed numerically and graphically. The study of convergence for the FRDTM technique has been conducted to assess its efficacy and accuracy.
Vitreous Levels of Vascular Endothelial Growth Factor and Platelet-Derived Growth Factor in Patients with Proliferative Diabetic Retinopathy: A Clinical Correlation
Authors: Al-Dwairi Rami , El-Elimat Tamam , Aleshawi Abdelwahab , Al Sharie Ahmed H. , Abu Mousa Balqis M. , Al Beiruti Seren , Alkazaleh Ahmad , Mohidat Hasan
Published: November 2023

Background: The global epidemic status of diabetic retinopathy (DR) and its burden presents an ongoing challenge to health-care systems. It is of great interest to investigate potential prognostic biomarkers of DR. Such markers could aid in detecting early stages of DR, predicting DR progression and its response to therapeutics. Herein, we investigate the prognostic value of intravitreal concentrations of vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF) in a DR cohort. Materials and methods: Vitreous sample acquisition was conducted at King Abdullah University Hospital (KAUH) between December 2020 and June 2022. Samples were obtained from any patient scheduled to undergo a pars plana vitrectomy (PPV) for any indication. Included patients were categorized into a DR group or a corresponding non-diabetic (ND) control group. Demographics, clinicopathological variables, standardized laboratory tests results, and optical coherence tomography (OCT) data were obtained for each included individual. Intravitreal concentrations of VEGF and PDGF were assessed using commercial enzyme-linked immunosorbent assay (ELISA). Results: A total of 80 eyes from 80 patients (DR group: n = 42 and ND control group: n = 38) were included in the analysis. The vitreous VEGF levels were significantly higher in the DR group compared to the ND control group (DR group 5744.06 ± 761.5 pg/mL versus ND control group 817.94 ± 403.1 pg/mL, p = 0.0001). In addition, the vitreous PDGF levels were also significantly higher in the DR group than those in the ND control group (DR group 4031.51 ± 410.2 pg/mL versus ND control group 2691.46 ± 821.0 pg/mL, p = 0.001). Bassline differences between test groups and clinical factors impacting VEGF and PDGF concentrations were investigated as well. Multiple regression analysis indicated PDGF as the sole independent risk factor affecting best-corrected visual acuity (BCVA) at the last follow-up visit: the higher the PDGF vitreous levels, the worst the BCVA. Conclusions: Vitreous concentrations of VEGF and PDGF are correlated with DR severity and may exhibit a possible prognostic potential value in DR. Further clinical and experimental data are warranted to confirm the observed findings and to help incorporate them into daily practice.
Optimizing Dental Bond Strength: Insights from Comprehensive Literature Review and Future Implications for Clinical Practice
Authors: Fan-Chiang Yung-Shin , Chou Peng-Chen , Hsiao Yu-Wen , Cheng Yu-Hsuan , Huang Yi , Chiu Yu-Chieh , Lin Yu-Ju , Mine Yuichi , Feng Sheng-Wei , Lee I-Ta , Peng Tzu-Yu
Published: November 2023

This review examines the modifying factors affecting bond strength in various bonding scenarios, particularly their relevance to the longevity of dental restorations. Understanding these factors is crucial for improving clinical outcomes in dentistry. Data were gathered from the PubMed database, ResearchGate, and Google Scholar resources, covering studies from 1992 to 2022. The findings suggest that for dentin-resin bonds, minimizing smear layers and utilizing MMP inhibitors to prevent hybrid layer degradation are essential. In the case of resin-resin bonds, reversing blood contamination is possible, but preventing saliva contamination is more challenging, underscoring its critical importance during clinical procedures. Additionally, while pretreatment on ceramics has minimal impact on bond strength, the influence of specific colorings should be carefully considered in treatment planning. This comprehensive review highlights that although established practices recognize significant bond strength factors, ongoing research provides valuable insights to enhance the clinical experience for patients. Once confirmed through rigorous experimentation, these emerging findings should be swiftly integrated into dental practice to improve patient outcomes.
The Mental Health Impacts of a Pandemic: A Multiaxial Conceptual Model for COVID-19
Authors: Neto David Dias , Silva Ana Nunes da
Published: November 2023

The COVID-19 pandemic substantially impacted the mental health of the general population and particularly vulnerable individuals and groups. A wealth of research allows for estimating this impact and identifying relevant factors contributing to or mitigating it. The current paper presents and synthesizes this evidence into a multiaxial model of COVID-19 mental health impacts. Based on existing research, we propose four axes: (1) Exposure to COVID-related events; (2) Personal and social vulnerability, such as previous mental health problems or belonging to a vulnerable group; (3) Time, which accounts for the differential impacts throughout the development of the pandemic; and (4) Context, including healthcare and public policies, and social representations of the illness influencing individual emotional reactions and relevant behaviors. These axes help acknowledge the complexity of communities’ reactions and are pragmatic in identifying and prioritizing factors. The axes can provide individual information (i.e., more exposure is harmful) and account for interactions (e.g., exposure in an early phase of the pandemic differs from a later stage). This model contributes to the reflections of the evidence and informs the mental health response to the next pandemic.
Comparison of Single-Port Laparoscopy with Other Surgical Approaches in Endometrial Cancer Surgical Staging: Propensity-Score-Matched Analysis
Authors: Cho Sang Hyun , Lee Jung-Yun , Nam Eun Ji , Kim Sunghoon , Kim Young Tae , Kim Sang Wun
Published: November 2023

This single-institution, retrospective study aimed to compare the surgical outcomes of single-port, multi-port, and robot-assisted laparoscopy, as well as laparotomy, in patients with endometrial cancer who underwent surgical staging between January 2006 and December 2017. This study evaluated various parameters, including disease-free survival (DFS), overall survival (OS), recurrence rate (RR), recurrence site, and intra- and postoperative complications. Propensity score matching was performed to account for baseline characteristics, and a total of 881 patients were included in the analysis. The 3-year DFS of single-port laparoscopy was similar to that of the other groups, but laparotomy exhibited a lower 3-year DFS compared to multi-port (p = 0.001) and robot-assisted (p = 0.031) laparoscopy. Single-port laparoscopy resulted in a significantly higher 3-year OS than laparotomy (p = 0.013). After propensity score matching, the four groups demonstrated similar survival outcomes (3-year DFS: p = 0.533; 3-year OS: p = 0.328) and recurrence rates (10.3%, 12.1%, 10.3%, and 15.9% in the single-port, multi-port, and robot-assisted laparoscopy and laparotomy groups, respectively, p = 0.552). Recurrence most commonly occurred in distant organs. The single-port laparoscopy group had the longest operative time (205.1 ± 76.9 min) but the least blood loss (69.5 ± 90.8 mL) and the shortest postoperative hospital stay (5.2 ± 2.3 days). In contrast, the laparotomy group had the shortest operative time (163.4 ± 51.0 min) but the highest blood loss (368.3 ± 326.4 mL) and the longest postoperative hospital stay (10.3 ± 4.6 days). The transfusion rate was 0% in the single-port laparoscopy group and 3.7% in the laparotomy group. Notably, the laparotomy group had the highest wound complication rate (p = 0.001), whereas no wound hernias were observed in the three minimally invasive approaches. In conclusion, the survival outcomes were comparable between the methods, with the benefit of lower blood loss and shorter hospital stay observed in the single-port laparoscopy group. This study suggests that single-port laparoscopy is a feasible approach for endometrial cancer surgical staging.
Multiparametric Magnetic Resonance Imaging of Penile Cancer: A Pictorial Review
Authors: Switlyk Marta D. , Hopland Andreas , Reitan Edmund , Sivanesan Shivanthe , Brennhovd Bjørn , Axcrona Ulrika , Hole Knut H.
Published: November 2023

The role of multiparametric magnetic resonance imaging (mpMRI) in assessing penile cancer is not well defined. However, this modality may be successfully applied for preoperative staging and patient selection; postoperative local and regional surveillance; and assessments of treatment response after oncological therapies. Previous studies have been mostly limited to a few small series evaluating the accuracy of MRI for the preoperative staging of penile cancer. This review discusses the principles of non-erectile mpMRI, including functional techniques and their applications in evaluating the male genital region, along with clinical protocols and technical considerations. The latest clinical classifications and guidelines are reviewed, focusing on imaging recommendations and discussing potential gaps and disadvantages. The development of functional MRI techniques and the extraction of quantitative parameters from these sequences enables the noninvasive assessment of phenotypic and genotypic tumor characteristics. The applications of advanced techniques in penile MRI are yet to be defined. There is a need for prospective trials and feasible multicenter trials due to the rarity of the disease, highlighting the importance of minimum technical requirements for MRI protocols, particularly image resolution, and finally determining the role of mpMRI in the assessment of penile cancer
Multiphasic Personality Assessment in a Case Series of Adolescent Patients with Suicidal Ideation and/or Attempts
Authors: Cossu Giulia , Vecchio Arianna , Orlandi Marika , Casini Erica , Borgatti Renato , Mensi Martina Maria ,   The Mondino Foundation Suicidality Research Group
Published: November 2023

Suicide is an important public health issue. To examine the differences in personality characteristics between a group of adolescents with suicidal ideation (SI) and a group with a history of suicidal attempts (SA), we conducted a cross-sectional study. We enrolled 55 adolescents (51 females; 12–18 y.o.) who presented SI and/or SA. Using the Columbia Suicide Severity Rating Scale, we divided the sample into two groups: adolescents with SI and adolescents with SA. All participants filled in the Minnesota Multiphasic Personality Inventory—Adolescent (MMPI-A). Adolescents in the SA group had greater difficulties in social relations, risky behaviors, and more intense suicidal ideation compared to those in the SI group. Adolescents in the SA group scored higher in Omission, in the Lie Scale, the Conduct Problem Scale, the Less Aspirations Scale, the Repression Scale in the MMPI-A, and item 283 of the MAST compared to the other group. The results suggest that using the MMPI-A to assess certain features (e.g., tendency to lie, repression) may be helpful in identifying young people who are at high risk of suicide. However, further research is required to determine the effectiveness of using this instrument.
Plant Metabolomics: Current Initiatives and Future Prospects
Authors: Manickam Sudha , Rajagopalan Veera Ranjani , Kambale Rohit , Rajasekaran Raghu , Kanagarajan Selvaraju , Muthurajan Raveendran
Published: November 2023

Plant metabolomics is a rapidly advancing field of plant sciences and systems biology. It involves comprehensive analyses of small molecules (metabolites) in plant tissues and cells. These metabolites include a wide range of compounds, such as sugars, amino acids, organic acids, secondary metabolites (e.g., alkaloids and flavonoids), lipids, and more. Metabolomics allows an understanding of the functional roles of specific metabolites in plants’ physiology, development, and responses to biotic and abiotic stresses. It can lead to the identification of metabolites linked with specific traits or functions. Plant metabolic networks and pathways can be better understood with the help of metabolomics. Researchers can determine how plants react to environmental cues or genetic modifications by examining how metabolite profiles change under various crop stages. Metabolomics plays a major role in crop improvement and biotechnology. Integrating metabolomics data with other omics data (genomics, transcriptomics, and proteomics) provides a more comprehensive perspective of plant biology. This systems biology approach enables researchers to understand the complex interactions within organisms.
A GIS-Based Assessment of Flood Hazard through Track Records over the 1886–2022 Period in Greece
Authors: Evelpidou Niki , Cartalis Constantinos , Karkani Anna , Saitis Giannis , Philippopoulos Kostas , Spyrou Evangelos
Published: November 2023

This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country’s climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling.
Authority Transfer According to a Driver Intervention Intention Considering Coexistence of Communication Delay
Authors: Lim Taeyoon , Hwang Myeonghwan , Kim Eugene , Cha Hyunrok
Published: November 2023

Recently, interest and research on autonomous driving technology have been actively conducted. However, proving the safety of autonomous vehicles and commercializing autonomous vehicles remain key challenges. According to a report released by the California Department of Motor Vehicles on self-driving, it is still hard to say that self-driving technology is highly reliable. Until fully autonomous driving is realized, authority transfer to humans is necessary to ensure the safety of autonomous driving. Several technologies, such as teleoperation and haptic-based approaches, are being developed based on human-machine interaction systems. This study deals with teleoperation and presents a way to switch control from autonomous vehicles to remote drivers. However, there are many studies on how to do teleoperation, but not many studies deal with communication delays that occur when switching control. Communication delays inevitably occur when switching control, and potential risks and accidents of the magnitude of the delay cannot be ignored. This study examines compensation for communication latency during remote control attempts and checks the acceptable level of latency for enabling remote operations. In addition, supplemented the safety and reliability of autonomous vehicles through research that reduces the size of communication delays when attempting teleoperation. It is expected to prevent human and material damage in the actual accident situation.
The Determinants of Carbon Intensities of Different Sources of Carbon Emissions in Saudi Arabia: The Asymmetric Role of Natural Resource Rent
Authors: Mahmood Haider
Published: November 2023

Natural resource rent (NRR) can be a blessing for the economic growth of resource-rich economies but may cause environmental problems. The present research explores the effects of NRR, economic growth, trade openness (TO), and foreign direct investment (FDI) on the carbon intensities of different sources of carbon emissions in Saudi Arabia from 1968 to 2021. The environmental Kuznets curve (EKC) is substantiated in the relationship between economic growth and the carbon intensities of gas emissions and cement emissions in the long run. The EKC is also validated in models of the carbon intensities of oil emissions, gas flaring emissions, and aggregated CO2 emissions in the short run. TO reduces the carbon intensities of oil emissions, gas emissions, and cement emissions in the long run. FDI mitigates the carbon intensity of gas flaring emissions but increases the carbon intensity of cement emissions. NRR increases the carbon intensities of all investigated sources of emissions in a linear analysis. In a nonlinear analysis, increasing NRR increases and decreasing NRR reduces the carbon intensities of all sources of emissions except aggregated CO2 emissions. In the short-run results, TO decreases the carbon intensity of gas flaring emissions and increases the carbon intensities of gas emissions and cement emissions. FDI decreases the carbon intensities of all sources of emissions. In a linear analysis, NRR reduces the carbon intensities of oil emissions and cement emissions and increases the carbon intensities of gas emissions and gas flaring emissions. In a nonlinear analysis, increasing NRR reduces the carbon intensity of cement emissions and increases the carbon intensities of gas emissions and gas flaring emissions. Moreover, decreasing NRR reduces the carbon intensities of gas emissions, gas flaring emissions, and aggregated CO2 emissions and increases the carbon intensities of oil emissions and cement emissions. The effect of NRR is asymmetrical in models of the carbon intensities of aggregated CO2 emissions, oil emissions, and gas flaring emissions and symmetrical in models of the carbon intensities of gas emissions and cement emissions.
A Measurement Method for the Charging Potential of Conductors in the Vicinity of HVDC Overhead Lines Based on a Non-Contact Electrometer
Authors: Shi Jinpeng , Guo Xingxin , Wang Donglai , Chen Bo , Zhao Yan , Zhang Aijun
Published: November 2023

Charging potential appears when a conductor insulated to the ground is exposed to an electrostatic field. A modified measurement method based on a non-contact electrometer is presented in this article. This system is appropriate for measuring the charging potential of a conductor near high-voltage direct-current (HVDC) overhead lines. Compared with the contact measurement method, the modified method is hardly affected by the internal resistance of the electrometer, which helps ensure measurement accuracy in the electrostatic field. In contrast with the traditional non-contact electrometer, the electric field generated by HVDC lines and the space charges around the electrometer probe are shielded using a grounding cage. The effectiveness of the modified measurement method was verified via experiments. The impacts of the structure and position of the measurement system on the measured charging potential are discussed.
Adaptive Gaussian Kernel-Based Incremental Scheme for Outlier Detection
Authors: Zhang Panpan , Wang Tao , Cao Hui , Lu Siliang
Published: November 2023

An outlier, known as an error state, can bring valuable cognitive analytic results in many industrial applications. Aiming at detecting outliers as soon as they appear in data streams that continuously arrive from data sources, this paper presents an adaptive-kernel-based incremental scheme. Specifically, the Gaussian kernel function with an adaptive kernel width is employed to ensure smoothness in local measures and to improve discriminability between objects. The dynamical Gaussian kernel density is presented to describe the gradual process of changing density. When new data arrives, the method updates the relevant density measures of the affected objects to achieve outlier computation of the arrived object, which can significantly reduce the computational burden. Experiments are performed on five commonly used datasets, and experimental results illustrate that the proposed method is more effective and robust for incremental outlier mining automatically.
Enhanced Dual–Vector Model Predictive Control for PMSM Drives Using the Optimal Vector Selection Principle
Authors: Huang Zhen , Wei Qiang , Xiao Xuechun , Xia Yonghong , Rivera Marco , Wheeler Patrick
Published: November 2023

The Dual–Vector model predictive control (DV–MPC) method can improve the steady–state control performance of motor drives compared to using the single–vector method in one switching cycle. However, this performance enhancement generally increases the computational burden due to the exponential increase in the number of vector selections, lowering the system’s dynamic response. Alternatively, limiting the vector combinations will sacrifice system steady–state performance. To address this issue, this paper proposes an enhanced DV–MPC method that can determine the optimal vector combinations along with their duration time within minimized calculation times. Compared to the existing DV–MPC methods, the proposed enhanced technique can achieve excellent steady–state performance while maintaining a low computational burden. These benefits have been demonstrated in the results from a 2.5k rpm permanent magnet synchronous motor drive.
Influence of the Parameters of Used Biochar on the Dark Fermentation Process
Authors: Kozłowski Kamil , Dach Jacek , Czekała Wojciech , Malińska Krystyna , Świechowski Kacper , Pulka Jakub , Lewicki Andrzej
Published: November 2023

The aim of the work was to analyze the impact of biochar produced under various production conditions on the course of the dark (hydrogen) fermentation process. A series of experiments were planned, in which the starting material was digestate from a functioning agricultural biogas plant. Changes in the physicochemical properties and microstructure of biochar obtained in the manufacturing process with different parameters were also analyzed. Another issue analyzed was the size and dynamics of the gas production during dark fermentation with the use of various types of auxiliary material. This work showed that increasing the temperature and holding time during the production of biochar from digestion pulp improved the dynamics of biohydrogen production during the process of dark fermentation. The results of this research can be used in industrial research to optimize the process of biohydrogen production using biochar.
A Review and Analysis of Green Energy and the Environmental Policies in South Asia
Authors: Qudrat-Ullah Hassan
Published: November 2023

This paper explores the challenges and opportunities for green energy and environment transition in South Asia, a region that faces the dilemma of meeting its growing energy demand while reducing its greenhouse gas emissions and environmental vulnerability. The region has rich renewable energy sources and potential for energy efficiency improvement, but it also relies heavily on fossil fuels and suffers from various barriers and constraints that hinder its green energy development. The region needs policies that can achieve economic growth, social welfare, and environmental sustainability coherently and effectively. Utilizing the thematic literature review approach, this paper examines the literature on four main topics: (1) the estimation of green energy resources potential and scenarios in South Asia; (2) the comparison of green energy targets and policies in the South Asian Association for Regional Cooperation (SAARC) countries; (3) the evaluation of green energy deployment and performance in different sectors; and (4) the identification of green energy transition challenges and opportunities in South Asia. This paper fills some research gaps in the literature by providing a comprehensive, comparative, holistic, and integrated analysis of green energy and environment policies in South Asia, using various data sources, methods, frameworks, criteria, indicators, scenarios, impacts, trade-offs, drivers, barriers, best practices, lessons learned, and policy recommendations. This paper also develops a conceptual model for the green energy transition in South Asia, which consists of five key variables: green energy potential, green energy policies, green energy deployment, green energy performance, and green energy transition. The main findings and implications of this paper are that South Asia has a huge opportunity to pursue a green energy and environment transition that can address its multiple challenges and aspirations, but this requires overcoming various obstacles and constraints that hinder its progress. This paper suggests some policy options and strategies to enhance the green energy and environment policies in South Asia, such as developing a clear and consistent policy framework, enhancing regional cooperation and collaboration, leveraging information technology and data analytics, emphasizing sustainability and resilience, and engaging with other stakeholders and partners.
Numerical Investigations of Synthetic Jet Control Effects on Iced Airfoils
Authors: Chen Xi , Bian Wei , Zhao Qijun , Zhao Guoqing
Published: November 2023

Based on the numerical method, the effects of synthetic jet control (SJC) on the aerodynamic characteristics of iced airfoils are systematically analyzed for the first time. First, an analysis method for the airfoil flowfield under SJC in icing conditions is developed, which contains the CFD method, the icing prediction method, and the boundary conditions of the synthetic jet. Then, the variation in the aerodynamic characteristics of different iced airfoils under the SJC are analyzed, and the flow separation near the ice shape is discussed in detail. Finally, parameters, such as the jet position and angle, are quantified, and conclusions are obtained. The synthetic jet can reduce the separation area on the upper surface induced by the ice accretion. When the energy of the jet is sufficient, it interacts with the mainstream, reducing the separation vortex downstream of the jet orifice and greatly improving the aerodynamic characteristics of the iced airfoil. These results provide valuable insights for the application of synthetic jet technology in mitigating the adverse effects of ice accretion on the airfoil’s aerodynamic characteristics.
An Evaluation System of Robotic End-Effectors for Food Handling
Authors: Qiu Zhe , Paul Hannibal , Wang Zhongkui , Hirai Shinichi , Kawamura Sadao
Published: November 2023

Owing to Japan’s aging society and labor shortages, the food and agricultural industries are facing a significant demand for robotic food handling technologies. Considering the large variety of food products, available robotic end-effectors are limited. Our primary goal is to maximize the applicability of existing end-effectors and efficiently develop novel ones, and therefore, it is necessary to categorize food products and end-effectors from the viewpoint of robotic handling and establish their relationships through an effective evaluation approach. This study proposes a system for evaluating robotic end-effectors to identify appropriate ones and develop new ones. The evaluation system consists of food categorization based on food properties related to robotic handling, categorization of robotic end-effectors based on their grasping principles, a robotic system with visual recognition based on Robot Operating System 2 (ROS 2) to conduct handling tests, a scoring system for performance evaluation, and a visualization approach for presenting the results and comparisons. Based on food categorization, 14 real food items and their corresponding samples were chosen for handling tests. Seven robotic end-effectors, both commercialized and under development, were selected for evaluation. Using the proposed evaluation system, we quantitatively compared the performance of different end-effectors in handling different food items. We also observed differences in the handling of real food items and samples. The overall performance of an end-effector can be visualized and quantitatively evaluated to demonstrate its versatility in handling various food items.
A Systematic Review of the Application of Road Safety Valuation Methods in Assessing the Economic Impact of Road Traffic Injuries
Authors: Nankunda Charity , Evdorides Harry
Published: November 2023

Road traffic injuries (RTIs) are increasingly claiming lives, particularly of those living in low- and middle-income countries (LMICs). To evaluate the economic consequences of RTIs, their financial impact on Gross Domestic Product (GDP) has been investigated by several studies using road safety valuation methods. This in turn has been used to quantify the resources required for investment on appropriate countermeasures to reduce the severity and frequency of RTIs. To investigate the frequency of use of road safety valuation methods in assessing the economic impact of road injuries, a robust systematic review was carried out with the aid of EPPI-reviewer software. The analysis of the evidence gathered showed that 55% of the included studies used the willingness-to-pay (WTP) method, 29% used human capital (HC), 11% used restitution cost and 5% used other methods. In high-income countries (HICs), the predominant method used was WTP, while HC was more common for middle-income countries. In addition, it was found that 49% of the studies in this field were conducted on HICs, whilst 4% focused on low-income countries (LICs). This indicates that there is a gap in the use of road safety valuation methods for LICs in the literature and therefore a need for further research.