bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation and Improvement of the Flexibility of Biomass Blended Burning Units in a Virtual Power Plant
Authors: Zheng Qiwei , Chen Heng , Gou Kaijie , Pan Peiyuan , Xu Gang , Zhang Guoqiang
Published: August 2024

Aiming at the problems of small thermal power units and biomass mixed combustion units with small generation loads and insufficient primary frequency modulation capability, which cannot be connected to the virtual power plant, this paper adopts a variety of flexibility retrofit methods for the units and explores the peak load capability of the units. Then, multiple units are coupled, and the unit coupling scheme with better economy and environmental protection is screened using comprehensive evaluation indexes. While evaluating the peaking load space of multiple unit coupling, the units’ primary frequency regulation capability and new energy consumption capability are improved. According to the calculation results, the low-pressure cylinder zero-output retrofit has the largest peaking potential among different technical paths, in which unit #3 has 27.55 MW of peaking space. The compression heat pump decoupling retrofit has the best economy, in which the daily profit of unit #3 increases from 0.93 to 1.02 million CNY with an increase of 0.09 million CNY. After the unit has been retrofitted with steam extraction, the three units can be coupled to meet the national feed-in standards. The multiple unit coupling can accommodate up to 203.44 MW of other energy sources while meeting the standard.
An Improved SPWM Strategy for Effectively Reducing Total Harmonic Distortion
Authors: Zhang Shaoru , Li Huixian , Liu Yang , Liu Xiaoyan , Lv Qing , Du Xiuju , Zhang Jielu
Published: August 2024

In the inverter circuit, the speed at which the MOSFET is impacted by the presence of a parasitic inductor within the printed circuit board (PCB) leads to a delay in the switching process. Furthermore, the parasitic inductor within the circuit can easily form an LC oscillation with the parasitic capacitor of the MOSFET. These two issues result in an inconsistency between the actual output of the MOSFET and the driving signal waveform, leading to distortion in the sinusoidal pulse width modulation (SPWM) waveform and an increase in total harmonic distortion (THD). It is a common practice to mitigate gate oscillation by introducing a resistor at the gate of the MOSFET. However, elevating the resistance leads to deceleration in the charging process of the MOSFET’s parasitic capacitor, consequently causing an increase in the switching delay, and thereby increasing THD. Therefore, an effective strategy to reduce THD is proposed in this paper, while augmenting the gate resistance, computing the MOSFET switching delay, and applying corrective compensation. In this way, the inherent issues of the switch are addressed, resulting in inverter output waveforms that closely resemble sine waves and reduced THD. Through a combination of simulation and empirical experimentation, the efficacy of the proposed approach in significantly reducing THD in the inverter’s output waveform has been empirically substantiated.
Determining the Optimal Window Duration to Enhance Emotion Recognition Based on Galvanic Skin Response and Photoplethysmography Signals
Authors: Bamonte Marcos F. , Risk Marcelo , Herrero Victor
Published: August 2024

Automatic emotion recognition using portable sensors is gaining attention due to its potential use in real-life scenarios. Existing studies have not explored Galvanic Skin Response and Photoplethysmography sensors exclusively for emotion recognition using nonlinear features with machine learning (ML) classifiers such as Random Forest, Support Vector Machine, Gradient Boosting Machine, K-Nearest Neighbor, and Decision Tree. In this study, we proposed a genuine window sensitivity analysis on a continuous annotation dataset to determine the window duration and percentage of overlap that optimize the classification performance using ML algorithms and nonlinear features, namely, Lyapunov Exponent, Approximate Entropy, and Poincaré indices. We found an optimum window duration of 3 s with 50% overlap and achieved accuracies of 0.75 and 0.74 for both arousal and valence, respectively. In addition, we proposed a Strong Labeling Scheme that kept only the extreme values of the labels, which raised the accuracy score to 0.94 for arousal. Under certain conditions mentioned, traditional ML models offer a good compromise between performance and low computational cost. Our results suggest that well-known ML algorithms can still contribute to the field of emotion recognition, provided that window duration, overlap percentage, and nonlinear features are carefully selected.
Leveraging Time-Critical Computation and AI Techniques for Task Offloading in Internet of Vehicles Network Applications
Authors: Liang Peifeng , Chen Wenhe , Fan Honghui , Zhu Hongjin
Published: August 2024

Vehicular fog computing (VFC) is an innovative computing paradigm with an exceptional ability to improve the vehicles’ capacity to manage computation-intensive applications with both low latency and energy consumption. Moreover, more and more Artificial Intelligence (AI) technologies are applied in task offloading on the Internet of Vehicles (IoV). Focusing on the problems of computing latency and energy consumption, in this paper, we propose an AI-based Vehicle-to-Everything (V2X) model for tasks and resource offloading model for an IoV network, which ensures reliable low-latency communication, efficient task offloading in the IoV network by using a Software-Defined Vehicular-based FC (SDV-F) architecture. To fit to time-critical data transmission task distribution, the proposed model reduces unnecessary task allocation at the fog computing layer by proposing an AI-based task-allocation algorithm in the IoV layer to implement the task allocation of each vehicle. By applying AI technologies such as reinforcement learning (RL), Markov decision process, and deep learning (DL), the proposed model intelligently makes decision on maximizing resource utilization at the fog layer and minimizing the average end-to-end delay of time-critical IoV applications. The experiment demonstrates the proposed model can efficiently distribute the fog layer tasks while minimizing the delay.
Green Energy Management in Manufacturing Based on Demand Prediction by Artificial Intelligence—A Review
Authors: Rojek Izabela , Mikołajewski Dariusz , Mroziński Adam , Macko Marek
Published: August 2024

Energy efficiency in production systems and processes is a key global research topic, especially in light of the Green Deal, Industry 4.0/5.0 paradigms, and rising energy prices. Research on improving the energy efficiency of production based on artificial intelligence (AI) analysis brings promising solutions, and the digital transformation of industry towards green energy is slowly becoming a reality. New production planning rules, the optimization of the use of the Industrial Internet of Things (IIoT), industrial cyber-physical systems (ICPSs), and the effective use of production data and their optimization with AI bring further opportunities for sustainable, energy-efficient production. The aim of this study is to systematically evaluate and quantify the research results, trends, and research impact on energy management in production based on AI-based demand forecasting. The value of the research includes the broader use of AI which will reduce the impact of the observed environmental and economic problems in the areas of reducing energy consumption, forecasting accuracy, and production efficiency. In addition, the demand for Green AI technologies in creating sustainable solutions, reducing the impact of AI on the environment, and improving the accuracy of forecasts, including in the area of optimization of electricity storage, will increase. A key emerging research trend in green energy management in manufacturing is the use of AI-based demand forecasting to optimize energy consumption, reduce waste, and increase sustainability. An innovative perspective that leverages AI’s ability to accurately forecast energy demand allows manufacturers to align energy consumption with production schedules, minimizing excess energy consumption and emissions. Advanced machine learning (ML) algorithms can integrate real-time data from various sources, such as weather patterns and market demand, to improve forecast accuracy. This supports both sustainability and economic efficiency. In addition, AI-based demand forecasting can enable more dynamic and responsive energy management systems, paving the way for smarter, more resilient manufacturing processes. The paper’s contribution goes beyond mere description, making analyses, comparisons, and generalizations based on the leading current literature, logical conclusions from the state-of-the-art, and the authors’ knowledge and experience in renewable energy, AI, and mechatronics.
Estimation of NPP in Huangshan District Based on Deep Learning and CASA Model
Authors: Wang Ziyu , Zhou Youfeng , Sun Xinyu , Xu Yannan
Published: August 2024

Net primary productivity (NPP) is a key indicator of the health of forest ecosystems that offers important information about the net carbon sequestration capacity of these systems. Precise assessment of NPP is crucial for measuring carbon fixation and assessing the general well-being of forest ecosystems. Due to the distinct ecological characteristics of various forest types, accurately understanding and delineating the distribution of these types is crucial for studying NPP. Therefore, an accurate forest-type classification is necessary prior to NPP calculation to ensure the accuracy and reliability of the research findings. This study introduced deep learning technology and constructed an HRNet-CASA framework that integrates the HRNet deep learning model and the CASA model to achieve accurate estimation of forest NPP in Huangshan District, Huangshan City, Anhui Province. Firstly, based on VHR remote sensing images, we utilized the HRNet to classify the study area into six forest types and obtained the forest type distribution map of the study area. Then, combined with climate data and forest type distribution data, the CASA model was used to estimate the NPP of forest types in the study area, and the comparison with the field data proved that the HRNet-CASA framework simulated the NPP of the study area well. The experimental findings show that the HRNet-CASA framework offers a novel approach to precise forest NPP estimation. Introducing deep learning technology not only enables precise classification of forest types but also allows for accurate estimation of NPP for different types of forests. This provides a more effective tool for forest ecological research and environmental protection.
Nitrate, Nitrite, and Iodine Concentrations in Commercial Edible Algae: An Observational Study
Authors: Casas-Agustench Patricia , Hayter Jade M. , Ng Odelia S. B. , Hallewell Lauren V. , Clark Nathaniel J. , Bescos Raul
Published: August 2024

Edible algae are a natural source of nutrients, including iodine, and can also contain nitrogen in the form of nitrate (NO3−) and nitrite (NO2−) as they can fix nitrogen from seawater. This study aimed to analyse the NO3−, NO2−, and iodine concentrations in eighteen macroalgae and five microalgae species commercially available in the United Kingdom. NO3− and NO2− concentrations were measured using high-performance liquid chromatography (HPLC), and iodine was determined using inductively coupled plasma mass spectrometry (ICP-MS). NO3− and iodine concentrations in macroalgae (NO3−: 4050.13 ± 1925.01 mg/kg; iodine: 1925.01 ± 1455.80 mg/kg) were significantly higher than in microalgae species (NO3−: 55.73 ± 93.69 mg/kg; iodine: 17.61 ± 34.87 mg/kg; p < 0.001 for both). In the macroalgae group, nori had the highest NO3− (17,191.33 ± 980.89 mg/kg) and NO2− (3.64 ± 2.38 mg/kg) content, as well as the highest iodine content. Among microalgae, Dunaliella salina had the highest concentration of NO3− (223.00 ± 21.93 mg/kg) and iodine (79.97 ± 0.76 mg/kg), while Spirulina had the highest concentration of NO2− (7.02 ± 0.13 mg/kg). These results indicate that commercially available edible algae, particularly macroalgae species, could be a relevant dietary source of NO3− and iodine.
Health Outcomes Associated with Olive Oil Intake: An Umbrella Review of Meta-Analyses
Authors: Chiavarini Manuela , Rosignoli Patrizia , Giacchetta Irene , Fabiani Roberto
Published: August 2024

Several studies suggested a negative association between olive oil (OO) consumption and the risk of several chronic diseases. However, an attempt to systematically search, organize, and evaluate the existing evidence on all health outcomes associated with OO consumption is lacking. The objective of this review is to describe the multiple health outcomes associated with OO consumption. The Medline, Scopus, and Web of Science databases were searched through 5 April 2024. The selected studies met all of the following criteria: (1) a meta-analysis of both observational (case–control and cohort studies) and interventional studies (trials), (2) an evaluation of the association between OO consumption, mortality, and/or the incidence of non-communicable/chronic degenerative diseases, and (3) a study population ≥18 years old. Two independent reviewers extracted the relevant data and assessed the risk of bias of individual studies. The PRISMA statement and guidelines for the Integration of Evidence from Multiple Meta-Analyses were followed. The literature search identified 723 articles. After selection, 31 articles were included in this umbrella review. The primary health benefits of OO were observed in cardiovascular diseases and risk factors, cancer, mortality, diabetes, and specific biomarkers related to anthropometric status and inflammation. As a key component of the Mediterranean diet, OO can be considered a healthy dietary choice for improving positive health outcomes.
Are Socio-Economic Indicators Associated with Food Safety in Public Schools? A Study in Sergipe State, Brazil
Authors: Canuto Isabela Gomes , da Cunha Diogo Thimoteo , Buarque Paula Ribeiro , de Carvalho Izabela Maria Montezano
Published: August 2024

The Brazilian National School Feeding Programme aims to ensure food security and the right to food for public school students. To protect these fundamental rights, a comprehensive approach is needed that includes ensuring food safety. Recognising that low socio-economic conditions, inadequate food safety and child vulnerability can pose a cumulative burden on child development, this study examined food safety in public schools in Sergipe, Brazil, in the context of local socio-economic indicators. All state public schools in Sergipe (n = 314) were included. Food safety and socio-economic data were analysed using secondary sources and geographical maps. The cluster analysis identified two different groups of schools based on socio-economic indicators. While most schools presented regular foodborne illness risks, food production and temperature control had particularly high levels of non-compliance. Schools in areas with higher socio-economic indicators (Cluster 2) had better overall food safety scores (p < 0.001) compared to schools in areas with lower socio-economic indicators (Cluster 1). Cluster 1 schools also had a higher FBI risk when analysing temperature-controlled equipment violations (p = 0.001), food handlers (p = 0.005) and process and production (p = 0.004), which emerged as critical areas. These results emphasise the urgent need for targeted interventions to improve food safety in schools located in areas with lower socio-economic conditions.
The Antecedents of Positive Emotion and Continuous Usage of In-Flight Meals with Respect to Food Quality Using Structural Equation Modeling
Authors: Lee Won Seok , Moon Joonho
Published: August 2024

This work aimed to explore the food quality attributes of in-flight meals and to examine the antecedents of positive emotion and continuous usage of these meals. As a subdimension, this study uses multiple attributes: menu diversity, familiarity, temperature, nutrition, and presentation. Another purpose of this work is to examine the moderating effect of menu diversity on the relationship between nutrition and continuance usage. A survey via clickworker was used to collect the data for this work. There were 317 valid observations for statistical inference. This study used a structural equation model to test the hypotheses, and the Hayes process model macro 1 was adopted to test the moderating effect. The results showed that all independent variables other than familiarity significantly accounted for positive emotion. Moreover, all of these attributes had a positive impact on continuous usage. This work unveiled a significant moderating effect of menu diversity on the relationship between nutrition and continuance usage. This research elucidates the literature by clarifying the influential attributes of emotion and continuous usage intention in the domain of in-flight meal products and discussing practical implications.
Comparison of Different Deodorizing Treatments on the Flavor of Paddy Field Carp, Analyzed by the E-Nose, E-Tongue and Gas Chromatography–Ion Mobility Spectrometry
Authors: Fu Chenying , Zou Yiming , Zhang Yixiang , Liao Mengxiang , Chen Duhuang , Guo Zebin
Published: August 2024

Changes in the flavor and taste profiles of Paddy Field Carp after deodorization with perilla juice (PJ), cooking wine (CW) and a mixture of the two (PJ-CW) were analyzed using the E-nose, E-tongue, gas chromatography–ion mobility spectrometry (GC-IMS), free amino acid analysis and taste nucleotide analysis. The E-nose and E-tongue revealed that deodorization reduced the content of sulfur-containing compounds, enhanced umami, bitterness, sourness and astringency, and decreased saltiness. PCA and OPLS-DA analysis successfully distinguished between the effects of the treatments. Free amino acids increased from 8777.67 to 11,125.98 mg/100 g and umami amino acids increased from 128.24 to 150.37 mg/100 g after PJ-CW deodorization (p < 0.05). Equivalent umami concentration (EUC) comparisons showed that PJ-CW treatment produced the greatest synergistic umami enhancement (to 3.15 g MSG equiv./100 g). GC-IMS detected 52 aroma compounds; PJ treatment produced the greatest diversity of aldehydes, including heptanal, nonanal, hexanal, 3-methylbutanal, (E)-2-heptenal and (E,E)-2,4-heptadienal. The total content of volatile flavor compounds was the highest after PJ-CW treatment, and the content of many characteristic flavor substances (3-hydroxy-2-butanone, benzaldehyde, 5-methyl-2(3H)-furanone) increased. These findings provided a theoretical basis for the further development of deodorization methods for Paddy Field Carp.
Ultra-Processed Food Intake and Increased Risk of Obesity: A Narrative Review
Authors: Monda Antonietta , de Stefano Maria Ida , Villano Ines , Allocca Salvatore , Casillo Maria , Messina Antonietta , Monda Vincenzo , Moscatelli Fiorenzo , Dipace Anna , Limone Pierpaolo , Di Maio Girolamo , La Marra Marco , Di Padova Marilena , Chieffi Sergio , Messina Giovanni , Monda Marcellino , Polito Rita
Published: August 2024

The prevalence of obesity has become a global health concern, with significant impacts on quality of life and mortality rates. Recent research has highlighted the role of ultra-processed foods (UPFs) in driving the obesity epidemic. UPFs undergo extensive processing, often containing high levels of sugars, fats, and additives, while lacking essential nutrients. Studies have linked UPF consumption to obesity and cardiometabolic diseases, underscoring the importance of dietary patterns rich in whole foods. Thus, the aim of this narrative review is to elucidate the correlation between ultra-processed foods and the increased trend of obesity and its related complications. These foods, prevalent in modern diets, contribute to nutritional deficiencies and excessive caloric intake, exacerbating obesity rates. Lifestyle factors such as busy schedules and quick meal management further drive UPF consumption, disrupting hunger regulation and promoting overeating. UPF consumption correlates with adverse health outcomes, including dyslipidemia, hypertension, and insulin resistance. Promoting whole, minimally processed foods and implementing school-based nutrition education programs are crucial steps. Also, numerous challenges exist, including unequal access to healthy foods, the industry’s influence, and behavioral barriers to dietary change. Future research should explore innovative approaches, such as nutrigenomics and digital health technologies, to personalize interventions and evaluate policy effectiveness. Collaboration across disciplines and sectors will be vital to develop comprehensive solutions and improve public health outcomes globally.
Susceptibility of Foodborne Pathogens to Milk-Origin Lactic Acid Bacteria Supernatants: A Comprehensive Meta-Regression Study
Authors: Fernandes Nathália , Loforte Yara , Cadavez Vasco , Gonzales-Barron Ursula
Published: August 2024

This systematic review and meta-analysis compile the in vitro antimicrobial efficacy of lactic acid bacteria (LAB) supernatants against three common pathogenic bacteria found in dairy products: Salmonella spp., L. monocytogenes, and Staphylococcus aureus. After screening and analysis of full papers, identified by searches in PubMed, Scopus, and Web of Science databases, thirty-nine studies were regarded as relevant, and a total of 510 observations were recorded. The effects of moderators on inhibition diameters were assessed by adjusting three pathogen-specific meta-regression models. Results showed that, in general terms, strains from the Enterococcus genus displayed the highest inhibition values against L. monocytogenes (15.90 ± 2.138 mm), whereas Lacticaseibacillus strains were more effective against S. aureus (11.89 ± 0.573 mm). The well diffusion test outperformed the spot and disk diffusion tests, and more acidic LAB supernatants resulted in higher measurements of inhibition diameters (p < 0.001). Meta-regression models incorporating LAB genus, pathogen concentration, and incubation time explained 33.8%, 52.3%, and 19.8% of the total variance in inhibition diameters for L. monocytogenes, Salmonella spp., and S. aureus, respectively. None of the three models showed evidence of publication bias. This meta-regression study demonstrated that LAB strains present in dairy products possess a variable capacity to inhibit any of the three foodborne pathogens. Overall, L. monocytogenes was found to exhibit greater susceptibility than Salmonella spp. and S. aureus; thus, the antilisterial capacity of the selected LAB strains could be exploited in developing biocontrol strategies for cheese-making.
Elderly Resistance vs. Youthful Acceptance: A Study on Insect Consumption across Age Groups
Authors: Castro-Alija María José , Zolfaghari Ghazal , Fernandez Carla Gutierrez , Álvarez Carlos , Ramón-Carreira Luis Carlos , Jiménez José María , Albertos Irene
Published: August 2024

Insects have recently received much attention as sustainable protein sources due to their nutritional value and eco-friendliness. Unlike conventional livestock, insects require minimal resources and produce fewer greenhouse gas emissions. Moreover, insects offer high-quality protein, essential amino acids, and various vitamins and minerals. This study in Spain, specifically in Castilla y León, investigated insect consumption acceptance across age groups, particularly among older individuals, shedding light on factors influencing adoption. The findings inform strategies to address global protein deficiencies and advocate sustainable food practices, with implications for broader European research amidst challenges like water scarcity. Methods: A survey-based research approach collected data on attitudes, preferences, and motivations regarding insect consumption. Statistical analyses were conducted to identify demographic trends and significant associations. Results: Elderly participants expressed reluctance towards insect consumption but showed openness in survival scenarios. Younger individuals exhibited greater willingness to try insects, influenced by factors such as education and previous experiences. Conclusion: Understanding demographic variations in attitudes towards entomophagy is vital for fostering its acceptance. This study demonstrated that older individuals exhibit greater resistance to incorporating insects into their diets compared with younger individuals. Recommended strategies include incorporating insects discreetly into familiar foods and highlighting their nutritional advantages. Collaboration between researchers and stakeholders is essential for harnessing the potential of insects as a sustainable protein source.
The Origins of the Hydrogen Sulphide (H2S) Gas in the Triassic Montney Formation, British Columbia, Canada
Authors: Chalmers Gareth , Silva Pablo Lacerda , Bustin Amanda , Sanlorenzo Andrea , Bustin Marc
Published: August 2024

The inexplicable distribution of souring wells (presence of H2S gas) of the unconventional Montney Formation hydrocarbon resource (British Columbia; BC) is investigated by analysing sulphur and oxygen isotopes, coupled with XRD mineralogy, scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDX). The sulphur isotopic analysis indicates that the sulphur isotopic range for Triassic anhydrite (δ34S 8.9 to 20.98‰ VCDT) is the same as the H2S sulphur that is produced from the Montney Formation (δ34S 9.3 to 20.9‰ VCDT). The anhydrite in the Triassic rocks is the likely source of the sulphur in the H2S produced in the Montney Formation. The deeper Devonian sources are enriched in 34S and are not the likely source for sulphur (δ34S 17.1 and 34‰ VCDT). This is contradictory to studies on Montney Formation producers in Alberta, with heavier (34S-enriched) sulphur isotopic signatures in H2S gas of all souring Montney Formation producers. These studies conclude that deep-seated faults and fractures have provided conduits for sulphate and/or H2S gas to migrate from deeper sulphur sources in the Devonian strata. There are several wells that show a slightly heavier (34S-enriched) isotopic signature (δ34S 18 to 20‰ VCDT) within the Montney Formation H2S gas producing within close proximity to the deformation front. This variation may be due to such deep-seated faults that acted as a conduit for Devonian sulphur to migrate into the Montney Formation. Our geological model suggests the sulphate-rich fluids have migrated from the Charlie Lake Formation prior to hydrocarbon generation in the Montney Formation (BC). Sulphate has concentrated in discrete zones due to precipitation in conduits like fracture and fault systems. The model fits the observation of multi-well pads containing both sour- and sweet-producing wells indicating that the souring is occurring in very narrow and discrete zones with the Montney Formation (BC). Government agencies and operators in British Columbia should map the anhydrite-rich portions of the Charlie Lake Formation, together with the structural elements from three-dimensional seismic to reduce the risk of encountering unexpected souring.
Spatiotemporal Variability Analysis of Rainfall and Water Quality: Insights from Trend Analysis and Wavelet Coherence Approach
Authors: Farzana Syeda Zehan , Paudyal Dev Raj , Chadalavada Sreeni , Alam Md Jahangir
Published: August 2024

An understanding of the trend and relationship between rainfall patterns and water quality dynamics can provide valuable guidelines for the effective management of water resources. The aim of this study was to reveal the synchronous trends in rainfall and water quality and to explore the potential connection between seasonal variation in rainfall volume and the water quality index. This study scrutinised the seasonal temporal trends of rainfall and water quality parameters of three water supply reservoirs in the Toowoomba region of Australia by applying the modified Mann–Kendall (MMK) test and innovative trend analysis (ITA) methods from data collected over 22 years (2002–2022). The models showed a significant increasing trend of rainfall in two rainfall stations during autumn season. The water quality parameters, such as PO43−, exhibited a significant decreasing trend in all seasons in three reservoirs. On the other hand, the water quality index (WQI) showed a decreasing trend in the Cooby and Cressbrook reservoirs, excepting the Perseverance reservoir, which exhibited an increasing trend. In addition to the detection of trends, this study investigated the potential correlation between seasonal variation of rainfall volume and the water quality index using the wavelet transform coherence (WTC) method. The data of twelve rainfall stations were brought into this analysis. The WTC analysis displayed an apparent correlation between the water quality index and rainfall pattern for 70% of the rainfall stations across 8–16 periods. The highest coherency was noticed in 8–16 periods from 2002–2022, as observed at both the Cooby Creek rainfall station and in the WQI of the Cooby reservoir. This evaluation revealed the intertwined dynamics of rainfall patterns and water quality, providing a deeper understanding of their interdependence and implications, which might be useful for environmental and hydrological management practices.
Flood Susceptibility Mapping Using GIS-Based Frequency Ratio and Shannon’s Entropy Index Bivariate Statistical Models: A Case Study of Chandrapur District, India
Authors: Sharma Asheesh , Poonia Mandeep , Rai Ankush , Biniwale Rajesh B. , Tügel Franziska , Holzbecher Ekkehard , Hinkelmann Reinhard
Published: August 2024

Flooding poses a significant threat as a prevalent natural disaster. To mitigate its impact, identifying flood-prone areas through susceptibility mapping is essential for effective flood risk management. This study conducted flood susceptibility mapping (FSM) in Chandrapur district, Maharashtra, India, using geographic information system (GIS)-based frequency ratio (FR) and Shannon’s entropy index (SEI) models. Seven flood-contributing factors were considered, and historical flood data were utilized for model training and testing. Model performance was evaluated using the area under the curve (AUC) metric. The AUC values of 0.982 for the SEI model and 0.966 for the FR model in the test dataset underscore the robust performance of both models. The results revealed that 5.4% and 8.1% (FR model) and 3.8% and 7.6% (SEI model) of the study area face very high and high risks of flooding, respectively. Comparative analysis indicated the superiority of the SEI model. The key limitations of the models are discussed. This study attempted to simplify the process for the easy and straightforward implementation of FR and SEI statistical flood susceptibility models along with key insights into the flood vulnerability of the study region.
Infrared Light Annealing Effect on Pressure Sensor Fabrication Using Graphene/Polyvinylidene Fluoride Nanocomposite
Authors: Samoei Victor K. , Takeda Katsuhiko , Sano Keiichiro , Bharadwaz Angshuman , Jayasuriya Ambalangodage C. , Jayatissa Ahalapitiya H.
Published: August 2024

This paper reports the designing and testing, as well as the processing and testing, of a flexible piezoresistive sensor for pressure-sensing applications, utilizing a composite film of graphene/polyvinylidene fluoride (Gr/PVDF). Graphene serves as the conductive matrix, while PVDF acts as both the binder and a flexible polymer matrix. The composite film was fabricated using the solution casting technique on a flexible polyethylene substrate. We investigated the impact of post-infrared annealing on the pressure response of the Gr/PVDF films. The experimental results indicated that the films IR-annealed for 2 min exhibited improved pressure sensitivity compared with the as-deposited films. The stability and durability of the sensors were assessed through the application of pressure over more than 1000 cycles. The mechanical properties of the films were examined using a universal tensile testing machine (UTM) for scenarios both with and without infrared light annealing. Raman spectroscopy was employed to analyze the quality and characteristics of the prepared nanocomposites. This study enhances our understanding of the interplay between the Gr/PVDF composite, the IR annealing effect, and the hysteresis effect in the pressure-sensing mechanism, thereby improving the piezoresistance of the Gr/PVDF nanocomposite through the infrared annealing process.
Takotsubo Syndrome and Gender Differences: Exploring Pathophysiological Mechanisms and Clinical Differences for a Personalized Approach in Patient Management
Authors: Giubilato Simona , Francese Giuseppina Maura , Manes Maria Teresa , Rossini Roberta , Della Bona Roberta , Gatto Laura , Di Monaco Antonio , Zilio Filippo , Gasparetto Nicola , Sorini Dini Carlotta , Borrello Francesco , Mannarini Antonia , Scardovi Angela Beatrice , Pavan Daniela , Amico Francesco , Geraci Giovanna , Riccio Carmine , Colivicchi Furio , Grimaldi Massimo , Gulizia Michele Massimo , Oliva Fabrizio
Published: August 2024

Takotsubo syndrome (TTS), also known as the broken-heart syndrome, is a reversible condition typically observed in female patients presenting for acute coronary syndromes (ACS). Despite its increasing incidence, TTS often remains undiagnosed due to its overlap with ACS. The pathophysiology of TTS is complex and involves factors such as coronary vasospasm, microcirculatory dysfunction, increased catecholamine levels, and overactivity of the sympathetic nervous system. Diagnosing TTS requires a comprehensive approach, starting with clinical suspicion and progressing to both non-invasive and invasive multimodal tests guided by a specific diagnostic algorithm. Management of TTS should be personalized, considering potential complications, the presence or absence of coronary artery disease (CAD), diagnostic test results, and the patient’s clinical course. The current data primarily derive from case series, retrospective analyses, prospective registries, and expert opinions. In recent years, there has been growing recognition of gender differences in the pathophysiology, presentation, and outcomes of TTS. This review provides an updated overview of gender disparities, highlighting the importance of tailored diagnostic and management strategies.
Associations between Late Lactate Clearance and Clinical Outcomes in Adults with Hyperlactataemia in the Setting of Diabetic Ketoacidosis
Authors: Kumar Aashish , Anstey Christopher , Doola Ra’eesa , Mcllroy Philippa , Whebell Stephen , Shekar Kiran , Attokaran Antony , Marella Prashanti , White Kyle , Luke Stephen , Tabah Alexis , Laupland Kevin , Ramanan Mahesh
Published: August 2024

Objective: This study aimed to determine the associations between lactate clearance in hyperlactataemic patients with diabetic ketoacidosis (DKA) and intensive care unit (ICU), hospital length of stay (LOS), and case-fatality. Methods: A retrospective, multicentre, cohort study of adult patients admitted to ICU with hyperlactataemia and a primary diagnosis of DKA from twelve sites in Queensland, Australia was conducted utilising pre-existing datasets that were linked for research purposes. The patients were divided into early and late lactate clearance groups; the early lactate clearance group included patients whose lactate returned to <2.0 mmol/L within 12 h, and the remainder were classified as late lactate clearance group. Results: The final dataset included 511 patients, 427 in the early lactate clearance group and 84 in the late lactate clearance group. Late lactate clearance was associated with increasing ICU LOS (β = +15.82, 95% CI +0.05 to +31.59, p < 0.049), increasing hospital LOS (β = +7.24, 95% CI +0.11 to 14.37, p = 0.048) and increasing Acute Physiology and Chronic Health Evaluation(APACHE) III score (ICU LOS outcome variable β = +1.05, 95% CI +0.88 to +1.22, p < 0.001; hospital LOS outcome variable β = +3.40, 95% CI +2.22 to 4.57, p < 0.001). Hospital case-fatality was not significantly different (2.2% in the early clearance group vs. 1.7% in the late clearance group, p = 0.496). Conclusions: In hyperlactataemic patients with DKA, late lactate clearance was associated with a statistically significant increase in both ICU and hospital LOS, though the clinical significance in both is minor.
Could Obesity Be Related to the Increasing Incidence of Warthin Tumors?
Authors: Gontarz Michał , Bargiel Jakub , Gąsiorowski Krzysztof , Marecik Tomasz , Szczurowski Paweł , Hramyka Andrei , Kuczera Joanna , Wieczorkiewicz Agata , Wyszyńska-Pawelec Grażyna
Published: August 2024

Background: The number of patients diagnosed with Warthin tumors (WTs) has increased significantly in recent years. The association of obesity as measured by body mass index (BMI) with the incidence of WTs remains unclear. This retrospective study aims to compare the BMI and other clinical factors of patients diagnosed with WTs to those with other benign epithelial parotid gland tumors. Methods: Over a 24-year period, 465 cases of benign epithelial parotid gland tumors were treated in our department. Of these, 155 (33.3%) were diagnosed as WTs. The results of the WT group were compared with those of another benign epithelial parotid gland tumor. Results: The mean BMI of WT patients was 27.3, which was significantly higher than in other benign tumors (25.52; p < 0.001). Furthermore, statistically significant correlations were observed, including a higher incidence of WT in males (p < 0.001), in the elderly (p < 0.001), and in cigarette smokers (p < 0.001). Additionally, a higher prevalence of other head and neck cancers was confirmed in patients with WTs (p = 0.004); Conclusions: This study supports the multifactorial etiology of WT development. Among these factors, smoking, advanced age, and obesity have been identified as factors associated with the development of WT, which might be due to chronic inflammation linked to obesity.
Comparison of Recovery Rates of Sudden Sensorineural Hearing Loss by Age Group
Authors: Ha Yeo Ra , Kim Dokyoung , Kim Sung Soo , Lee Jae Min , Kim Sang Hoon , Yeo Seung Geun
Published: August 2024

Background: While numerous studies have been conducted on sudden sensorineural hearing loss (SSNHL), research on how treatment outcomes and prognosis vary by age remains insufficient. This study aims to investigate the differences in recovery rates among SSNHL patients divided by age groups. Methods: A retrospective study was conducted on 177 patients diagnosed with SSNHL from 2020 to 2023. The patients were categorized into four age groups: under 20, 30–40, 50–60, and over 70. Recovery rates and associated symptoms were compared across these groups. Results: Significant recovery rates were observed in all age groups except for those over 70 (p = 0.006, p = 0.003, p = 0.009). No significant differences were found in recovery rates based on gender (p > 0.75) or symptoms such as tinnitus, ear fullness, and dizziness (p > 0.05). Conclusions: The study revealed that younger and middle-aged adults showed statistically significant improvements in recovery rates, while the elderly exhibited relatively lower recovery rates.
Ensuring Operational Performance and Environmental Sustainability of Marine Diesel Engines through the Use of Biodiesel Fuel
Authors: Sagin Sergii , Kuropyatnyk Oleksiy , Matieiko Oleksii , Razinkin Roman , Stoliaryk Tymur , Volkov Oleksandr
Published: August 2024

This article considers the issues of ensuring operational performance and environmental sustainability of marine diesel engines by using biodiesel fuel. This research was conducted on 5S60ME-C8 MAN-B&W Diesel Group and 6DL-16 Daihatsu Diesel marine diesel engines, which are operated using RMG380 petroleum fuel and B10 and B30 biodiesel fuels. The efficiency of biofuel usage was assessed based on environmental (reduced nitrogen oxide concentration in exhaust gases) and economic (increased specific effective fuel consumption) criteria. It was found that the use of B10 and B30 biofuels provides a reduction in nitrogen oxide concentration in exhaust gases by 14.71–25.13% but at the same time increases specific effective fuel consumption by 1.55–6.01%. Optimum fuel injection advance angles were determined that ensure the best thermal energy, economic and environmental performance of diesel engines. The optimum angle of biofuel supply advance is determined experimentally and should correspond to the limits recommended by the diesel engine operating instructions. It has been proven experimentally that the use of biofuel increases the environmental sustainability of marine diesel engines by 13.75–29.42%. It increases the diesel engines environmental safety in case of emergency situations as well as accidental and short-term emissions of exhaust gases with an increased content of nitrogen oxides into the atmosphere phenomena that are possible in starting modes of diesel engine operation as well as in modes of sudden load changes. It is the increase in the environmental friendliness of marine diesel engines in the case of using biofuel that is the most positive criterion and contributes to the intensity of biofuel use in power plants of sea vessels.
An Experimental Study of Pulp-Lift Characteristics Using a High-Viscous Fluid Simulating Deep Muddy Seawater
Authors: Onishi Sakai , Itagaki Yurie , Nakatani Naoki , Ohara Kyara , Katayama Hiroyuki , Yamazaki Tetsuo
Published: August 2024

Rare-earth mud and manganese nodules coexist on the seafloor around Minamitorishima Island. To investigate the feasibility of a pulp-lift system that can ensure economic efficiency by pumping manganese using rare-earth mud as the working fluid, we conducted pulp-lift experiments at a head of 5.0 m using a squeeze pump for mortar pumping. In the study, we used carboxymethylcellulose (CMC) as the working fluid, which is a pseudo-plastic fluid like deep muddy seawater. We investigated the effects of the viscosity of the working fluid and the pump pulsation characteristics on lifting. The results revealed that the drag force acting on the pumped ore increased as the fluid became more viscous and the pulsation period became higher, while the reverse flow rate increased due to the negative pulsation pressure. This suggests that there is an optimum value for the viscosity of the working fluid.
Sustainable Transportation Assessment Index (SusTAIN) Framework for Mixed-Use Neighborhoods in India
Authors: Bahale Swati , Schuetze Thorsten
Published: August 2024

Neighborhood sustainability assessment (NSA) systems assess neighborhood sustainability through different themes. Most NSA systems originated from developed countries, with limitations in assessing micro-level transportation infrastructure. The NSA systems lack alignment with Indian regulations and policies and have limitations in assessing informal transportation modes, affordability, and street-vending-related issues. This research developed the sustainable transportation assessment index (SusTAIN) framework to assess mixed-use neighborhoods in India and overcome the limitations of NSA systems. The method was to identify and evaluate qualitative and quantitative indicators and sub-indicators from NSA systems, Indian transportation regulations and policies, and transportation system studies from the literature. Indicators were integrated into the four subthemes of (i) accessibility, (ii) mobility nodes and network, (iii) external factors associated with mobility, and (iv) land-use and socioeconomic factors’ assessment. The authors evaluated the framework through the Geographical Information System (GIS), site surveys, and benchmark values from the literature. This research demonstrated the interrelationship of indicators and the sub-indicators between them. Finally, the authors discussed the SusTAIN composite index formation method. The framework is vital for the local application of national sustainable urban development policies. The SusTAIN framework application enables local governments to evaluate the transportation sustainability of neighborhoods and identify potential optimization areas.
Digital Walking Tours as a Tool for Assessing Place Attachment and Community Responses to Regional Environmental Change
Authors: Simmons Frances , Hennig Benjamin D. , Kokorsch Matthias
Published: August 2024

Understanding a community’s place attachment is vital for effective land-use planning and disaster risk management that aligns with local needs and priorities. This study examines the methodologies employed to grasp these values, emphasising the significance of meaningful participatory approaches. It sheds light on the challenges encountered due to COVID-19 restrictions, which prevented direct face-to-face engagement with community members. To address this issue, researchers devised “digital walking tours” as an alternative to traditional walking transect methods, aiming to investigate the relationship between place attachment and perceptions of the landscape in Patreksfjörður, a small fishing community in the Westfjords, during the pandemic. The evaluation of this method demonstrated its suitability for conducting comprehensive and cost-effective community consultations. Participants expressed enjoyment and found the technology (online video calls and StreetView imagery) user-friendly and engaging. To further enhance the method, several recommendations are proposed, including the integration of virtual tours with in-person methods whenever feasible, incorporating additional sensory input, adopting a slower pace, and offering more opportunities for participants to divert to personally significant locations. Other contextual considerations encompass the use of participants’ native language and the facilitation of digital walking tours with pairs or small groups of participants.
Evaluation of Water–Carbon–Ecological Footprint and Its Spatial–Temporal Changes in the North China Plain
Authors: Lyu Keyi , Tian Jin , Zheng Jiayu , Zhang Cuiling , Yu Ling
Published: August 2024

The North China Plain (NCP) serves as the main grain production land in China, functioning as a critical region for ensuring China’s food security. To address the multifaceted challenges confronting food security in the NCP, the study embarked on a comprehensive analysis of the synergistic interactions between agricultural water usage, carbon emissions, and ecosystem health. By proposing footprint family indicators and using the bottom-up IPCC coefficient approach, this study quantitatively evaluates the spatial–temporal changes of water–carbon–ecological footprints in NCP from 2003 to 2020. Furthermore, a coupling coordination degree model that focuses on the coordination of water–carbon–ecological footprints is established. The findings are as follows: (1) The total water footprint in the NCP showed a striking increasing trend with an increase of 1.52 × 1011 m3, and the carbon footprint increased by 1.27 × 109 t, with significant ecological impacts. (2) The NCP’s ecological footprint exhibited an “M”-shaped trend. The land structure maintained stable with negligible changes in the proportion of ecological footprints. (3) The coupling degree between the footprints of water, carbon, and ecology in the NCP is high, revealing a noteworthy interaction effect. This research can provide data support for effective resources allocation and sustainable social–economic development, offering reasonable insights for China to formulate more scientific policies of green transition in land use and ecological civilization construction.