bluuebunny/crossref_metadata_2025 huggingface dataset:
Occurrence of Differences between Alkali and Alkaline Earth Metals (AAEMs), Including Sodium, Potassium, Calcium, and Magnesium, in the Maceral Groups of the Xiheishan Coal, Zhundong Coalfield, Xinjiang, China
Authors: Che Kexin , Li Jiaxin , Lu Qingfeng , Shao Fengjun , Wang Wenlong , Wang Wenfeng , He Xin
Published: May 2024

This study investigated the differences and correlation between the occurrence characteristics of alkali and alkaline earth metals (AAEMs) among different maceral groups in high-alkali, high-inertinite coal, and provides scientific guidance for the co-separation of AAEMs and inertinite groups in Xinjiang coal. The total AAEMs of inertinite-enriched samples were significantly higher than those in raw coals and vitrinite-enriched samples. Five-step sequential extraction showed that Na mainly occurs as water-soluble sodium (Na-Water) in raw coal and inertinite-enriched samples, accounting for about 53% of the total content, while it exists as organic sodium (Na-NH4Cl and Na-EDTA) in vitrinite-enriched samples, accounting for about 52% of the total content. Ca and Mg are both mainly present in organic form (Ca/Mg-NH4Cl and Ca/Mg-EDTA) in all the samples, with slightly higher proportions present in vitrinite-enriched samples. The contents of K are low in all the samples, which exist in an insoluble state (K-I). Combined microscopy and SEM-EDS analyses have revealed that the localized enrichment of Na in raw coal and inertinite-enriched samples occurs in the inertinite cell cavity, which primarily exists as NaHCO3 combined with quartz crystals, with a maximum content of up to 5.85 wt%. In this study, although EDS spectra could not directly characterize organic Ca and Mg, dolomite and calcite minerals were repeatedly found in the inertinite cell cavity. Moreover, the contents of Ca and Mg in the vitrinite-enriched samples were significantly lower than those in the other samples, which suggests that Ca and Mg are enriched with the inertinite groups. The localized enrichment of AAEMs could not be detected in any of the vitrinite-enriched samples. In summary, though there are significant differences between the occurrence modes of AAEMs in different maceral groups of high-alkali coal, AAEMs have a strong affinity with inertinite, which may be due to the inertinite’s abundant pore structures.
Dietary Supplementation with an Extract of Aloysia citrodora (Lemon verbena) Improves Sleep Quality in Healthy Subjects: A Randomized Double-Blind Controlled Study
Authors: Pérez-Piñero Silvia , Muñoz-Carrillo Juan Carlos , Echepare-Taberna Jon , Muñoz-Cámara Macarena , Herrera-Fernández Cristina , García-Guillén Ana I. , Ávila-Gandía Vicente , Navarro Pau , Caturla Nuria , Jones Jonathan , López-Román Francisco Javier
Published: May 2024

Seventy-one healthy subjects with sleep disturbances participated in a randomized, double-blind controlled trial in which dietary supplementation with an extract of Aloysia citrodora (lemon verbena) (n = 33) or placebo (n = 38) was administered for 90 days. There were between-group differences in favor of the experimental group in the visual analogue scale (VAS) for sleep quality (6.5 ± 1.6 vs. 5.5 ± 2.1, p = 0.021) as well as in the overall score (5.8 ± 2.4, p = 0.008) and scores for sleep latency (1.6 ± 1.0 vs. 1.9 ± 0.7, p = 0.027) and sleep efficiency (84.5 ± 12.8 vs. 79.8 ± 13.6, p = 0.023) in the Pittsburgh Sleep Quality Index (PSQI). Sleep-related variables (latency, efficiency, wakefulness after sleep onset, awakenings) assessed by actigraphy also showed better scores in the experimental group (p = 0.001). Plasma nocturnal melatonin levels also increased significantly in the experimental group (199.7 ± 135.3 vs. 174.7 ± 115.4 pg/mL, p = 0.048). Changes in anthropometric parameters and physical activity levels were not found. In summary, a dietary supplement of lemon verbena administered for 3 months was associated with a significant improvement in sleep quality as compared with placebo in a population of healthy subjects with sleep problems.
The Quality of Menu Offerings in Independently Owned Restaurants in Baltimore, Maryland: Results from Mixed-Methods Formative Research for the FRESH Trial
Authors: Hua Shuxian , Tucker Anna Claire , Santos Sydney R. , Thomas Audrey E. , Mui Yeeli , Velez-Burgess Veronica , Poirier Lisa , Cheskin Lawrence J. , Matsuzaki Mika , Williamson Stacey , Colon-Ramos Uriyoan , Gittelsohn Joel
Published: May 2024

(1) Background: Independently owned restaurants (IORs) are prevalent in under-resourced racial and ethnic minority communities in the US and present a unique setting for public health nutrition interventions. (2) Methods: We conducted 14 in-depth interviews with IOR owners in Baltimore about their perceptions of healthy food, and customers’ acceptance of healthier menus and cooking methods and concurrent observations of the availability of healthy options on their menus. Qualitative data were coded and analyzed using ATLAS.ti. Observations were analyzed with statistical analysis performed in R. (3) Results: Owners perceived non-fried options, lean proteins, and plant-based meals as healthy. While open to using healthier cooking fats, they had mixed feelings about reducing salt, adopting non-frying methods for cooking, and adding vegetables and whole grains to the menu, and were reluctant to reduce sugar in recipes and beverages. Only 17.5% of 1019 foods and 27.6% of 174 beverages in these IORs were healthy, with no significant differences in the healthfulness of restaurant offerings within low-healthy-food-access/low-income neighborhoods and those outside. (4) Conclusion: Healthy options are generally scarce in Baltimore’s IORs. Insights from owners inform future interventions to tailor healthy menu offerings that are well-received by customers and feasible for implementation.
The Therapeutic Potential of Harpagophytum procumbens and Turnera subulata and Advances in Nutraceutical Delivery Systems in Neurodegenerative Diseases
Authors: Vital Júnior Antonio Carlos , da Silva Mikaelly Batista , Monteiro Shênia Santos , Pasquali Matheus Augusto de Bittencourt
Published: May 2024

This review article covers the therapeutic potential of the plants Harpagophytum procumbens and Turnera subulata in the treatment of neurodegenerative diseases. Despite the recognition of their beneficial properties, there is notable shortage of specific clinical and in vitro studies on these species regarding neurodegenerative diseases. Compounds such as harpagosides and vite-xin-2-O-rhamnoside, found in Harpagophytum procumbens and Turnera subulata, respectively, as well as other antioxidants and anti-inflammatory agents, are associated with mechanisms of action that involve reducing oxidative stress and modulating the inflammatory response, indicating their therapeutic potential in these pathologies. Additionally, the use of nutraceuticals derived from medicinal plants has emerged as a promising approach, offering natural therapeutic alternatives. However, the pressing need for studies focusing on the pharmacokinetics, safety, and pharmacological interactions of these extracts for the treatment of neurodegenerative diseases is emphasized. This review also evaluated advances in nutraceutical delivery systems, highlighting technological innovations that can optimize the precise delivery of these compounds to patients. Such findings highlight the gaps in the study of these plants for the treatment of neurodegenerative diseases and, at the same time, the potential for opening new perspectives in the treatment of neurodegenerative diseases, providing expectations for innovative solutions in this critical domain of medicine.
Effects of Nozzle Retraction Elimination on Spray Distribution in Middle-Posterior Turbinate Regions: A Comparative Study
Authors: Seifelnasr Amr , Si Xiuhua , Xi Jinxiang
Published: May 2024

The standard multi-dose nasal spray pump features an integrated actuator and nozzle, which inevitably causes a retraction of the nozzle tip during application. The retraction stroke is around 5.5 mm and drastically reduces the nozzle’s insertion depth, which further affects the initial nasal spray deposition and subsequent translocation, potentially increasing drug wastes and dosimetry variability. To address this issue, we designed a new spray pump that separated the nozzle from the actuator and connected them with a flexible tube, thereby eliminating nozzle retraction during application. The objective of this study is to test the new device’s performance in comparison to the conventional nasal pump in terms of spray generation, plume development, and dosimetry distribution. For both devices, the spray droplet size distribution was measured using a laser diffraction particle analyzer. Plume development was recorded with a high-definition camera. Nasal dosimetry was characterized in two transparent nasal cavity casts (normal and decongested) under two breathing conditions (breath-holding and constant inhalation). The nasal formulation was a 0.25% w/v methyl cellulose aqueous solution with a fluorescent dye. For each test case, the temporospatial spray translocation in the nasal cavity was recorded, and the final delivered doses were quantified in five nasal regions. The results indicate minor differences in droplet size distribution between the two devices. The nasal plume from the new device presents a narrower plume angle. The head orientation, the depth at which the nozzle is inserted into the nostril, and the administration angle play crucial roles in determining the initial deposition of nasal sprays as well as the subsequent translocation of the liquid film/droplets. Quantitative measurements of deposition distributions in the nasal models were augmented with visualization recordings to evaluate the delivery enhancements introduced by the new device. With an extension tube, the modified device produced a lower spray output and delivered lower doses in the front, middle, and back turbinate than the conventional nasal pump. However, sprays from the new device were observed to penetrate deeper into the nasal passages, predominantly through the middle-upper meatus. This resulted in consistently enhanced dosing in the middle-upper turbinate regions while at the cost of higher drug loss to the pharynx.
Development and Validation of a 1D Dynamic Model of an Injection Moulding Process and Design of a Model-Based Nozzle Pressure Controller
Authors: Hertz Rasmus Aagaard , Therkelsen Ole , Kristiansen Søren , Christensen Jesper Kjærsgaard , Hansson Frederik Agervig , Schmidt Lasse
Published: May 2024

A 1D model describing the dynamics of an injection moulding machine and the injection process is presented. The model describes an injection cylinder actuated by a dual-pump electro–hydraulic speed-variable drive and the filling, holding and cooling phases of the injection moulding process utilising amorphous polymers. The model is suggested as the foundation for the design of model-based pressure controllers of, e.g., the nozzle pressure. The focus is on using material, mould and machine properties to construct the model, making it possible to analyse and design the dynamic system prior to manufacturing hardware or conducting experiments. Both the presented model and the developed controller show good agreement with experimental results. The proposed method is general in nature and enables the design, analysis and evaluation of the machine, material and mould dynamics for controller design based solely on the physical properties of the system.
Anionic Effect on Electrical Transport Properties of Solid Co2+/3+ Redox Mediators
Authors: Gupta Ravindra Kumar , Imran Ahamad , Khan Aslam
Published: May 2024

In a solid-state dye-sensitized solar cell, a fast-ion conducting (σ25°C > 10−4 S cm−1) solid redox mediator (SRM; electrolyte) helps in fast dye regeneration and back-electron transfer inhibition. In this work, we synthesized solid Co2+/3+ redox mediators using a [(1 − x)succinonitrile: x poly(ethylene oxide)] matrix, LiX, Co(tris-2,2′-bipyridine)3(bis(trifluoromethyl) sulfonylimide)2, and Co(tris-2,2′-bipyridine)3(bis(trifluoromethyl) sulfonylimide)3 via the solution-cast method, and the results were compared with those of their acetonitrile-based liquid counterparts. The notation x is a weight fraction (=0, 0.5, and 1), and X represents an anion. The anion was either bis(trifluoromethyl) sulfonylimide [TFSI−; ionic size, 0.79 nm] or trifluoromethanesulfonate [Triflate−; ionic size, 0.44 nm]. The delocalized electrons and a low value of lattice energy for the anions made the lithium salts highly dissociable in the matrix. The electrolytes exhibited σ25°C ≈ 2.1 × 10−3 (1.5 × 10−3), 7.2 × 10−4 (3.1 × 10−4), and 9.7 × 10−7 (6.3 × 10−7) S cm−1 for x = 0, 0.5, and 1, respectively, with X = TFSI− (Triflate−) ions. The log σ–T−1 plot portrayed a linear curve for x = 0 and 1, and a downward curve for x = 0.5. The electrical transport study showed σ(TFSI−) > σ(Triflate−), with lower activation energy for TFSI− ions. The anionic effect increased from x = 0 to 1. This effect was explained using conventional techniques, such as Fourier transform infrared spectroscopy (FT-IR), X-ray diffractometry (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), UV–visible spectroscopy (UV-vis), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA).
Study on Nutrient Carrier of Mulch Based on Hydrogel @SiO2
Authors: Qin Dan , Ma Yujie , Wang Mei , Shan Zhihua
Published: May 2024

Soil conservation is one of the best methods to improve soil fertility and enhance crop growth efficiency. Replacing plastic mulch with biomass is an environmentally friendly strategy. Innovative encapsulated soil granules (ESGs) were developed using PVA/PC film as the wall material and rural soil as the core. The PVA/PC was synthesized using 60% protein polypeptide (PC) from leather waste scrap and 35% poly (vinyl alcohol) (PVA), which was optimized for water absorption expansion and water retention performance. The ESG-10 granulated with 10% PVA/PC exhibited good water absorption, moisture retention, and resistance to water solubility. As an auxiliary material for soil improvement, the amount of ESGs mixed with the topsoil at ratios of 0 g/m2, 200 g/m2, and 400 g/m2 was proportional to the soil insulation and moisture retention. In rapeseed cultivation, the experimental results indicated that the soil mulched with ESG-10 can maintain seedling vitality for a long time under low water content conditions.
Selection and Optimization of Carbon-Reinforced Polyether Ether Ketone Process Parameters in 3D Printing—A Rotating Component Application
Authors: Subramani Raja , Vijayakumar Praveenkumar , Rusho Maher Ali , Kumar Anil , Shankar Karthik Venkitaraman , Thirugnanasambandam Arun Kumar
Published: May 2024

The selection of process parameters is crucial in 3D printing for product manufacturing. These parameters govern the operation of production machinery and influence the mechanical properties, production time, and other aspects of the final product. The optimal process parameter settings vary depending on the product and printing application. This study identifies the most suitable cluster of process parameters for producing rotating components, specifically impellers, using carbon-reinforced Polyether Ether Ketone (CF-PEEK) thermoplastic filament. A mathematical programming technique using a rating method was employed to select the appropriate process parameters. The research concludes that an infill density of 70%, a layer height of 0.15 mm, a printing speed of 60 mm/s, a platform temperature of 195 °C, an extruder temperature of 445 °C, and an extruder travel speed of 95 mm/s are optimal process parameters for manufacturing rotating components using carbon-reinforced PEEK material.
Commemoration of the Dead in the Context of Alternative Spirituality: Collective and Solitary Rituals
Authors: Bužeková Tatiana
Published: May 2024

The ritualised commemoration of the deceased belongs to the most common forms of communication with the dead. The meaning that people ascribe to a religious commemoration ritual is determined by a concrete religious doctrine, although it can be influenced by a broader cultural tradition. However, in the context of alternative spiritual currents, there can be many possible interpretations of communication with the dead, as there is no “official” doctrine supported by established institutions. In addition, alternative spirituality is marked by the emphasis on individuality, which results in the predominance of solitary practice. Yet, in various contexts, the tension between individuality and community can be manifested in different forms of ritualised behaviour, ranging from strictly private performances to prescribed group rituals. The paper addresses different levels of individual and collective practice in the context of alternative spirituality in Slovakia, a post-socialist country with a predominantly Christian, mostly Catholic, population. It makes use of the theoretical tools of Mary Douglas’ theory relating to the connection between cosmological beliefs and particular forms of social life. Rituals and ritualised behaviour are considered in the case of the triduum of All Saints’ Eve, All Saints’ Day, and All Souls’ Day. The results of ethnographic research on spiritual circles operating in Bratislava, the capital of Slovakia, have shown that these holidays are perceived and practiced differently by people with different religious or spiritual affiliation. The individual interpretation and the degree of associated ritualised behaviour depend on personal background, as well as the social organisation of a circle to which a practitioner belongs.
Lightweight Super-Resolution Generative Adversarial Network for SAR Images
Authors: Jiang Nana , Zhao Wenbo , Wang Hui , Luo Huiqi , Chen Zezhou , Zhu Jubo
Published: May 2024

Due to a unique imaging mechanism, Synthetic Aperture Radar (SAR) images typically exhibit degradation phenomena. To enhance image quality and support real-time on-board processing capabilities, we propose a lightweight deep generative network framework, namely, the Lightweight Super-Resolution Generative Adversarial Network (LSRGAN). This method introduces Depthwise Separable Convolution (DSConv) in residual blocks to compress the original Generative Adversarial Network (GAN) and uses the SeLU activation function to construct a lightweight residual module (LRM) suitable for SAR image characteristics. Furthermore, we combine the LRM with an optimized Coordinated Attention (CA) module, enhancing the lightweight network’s capability to learn feature representations. Experimental results on spaceborne SAR images demonstrate that compared to other deep generative networks focused on SAR image super-resolution reconstruction, LSRGAN achieves compression ratios of 74.68% in model storage requirements and 55.93% in computational resource demands. In this work, we significantly reduce the model complexity, improve the quality of spaceborne SAR images, and validate the effectiveness of the SAR image super-resolution algorithm as well as the feasibility of real-time on-board processing technology.
Monitoring Volcanic Plumes and Clouds Using Remote Sensing: A Systematic Review
Authors: Mota Rui , Pacheco José M. , Pimentel Adriano , Gil Artur
Published: May 2024

Volcanic clouds pose significant threats to air traffic, human health, and economic activity, making early detection and monitoring crucial. Accurate determination of eruptive source parameters is crucial for forecasting and implementing preventive measures. This review article aims to identify the most common remote sensing methods for monitoring volcanic clouds. To achieve this, we conducted a systematic literature review of scientific articles indexed in the Web of Science database published between 2010 and 2022, using multiple query strings across all fields. The articles were reviewed based on research topics, remote sensing methods, practical applications, case studies, and outcomes using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our study found that satellite-based remote sensing approaches are the most cost-efficient and accessible, allowing for the monitoring of volcanic clouds at various spatial scales. Brightness temperature difference is the most commonly used method for detecting volcanic clouds at a specified temperature threshold. Approaches that apply machine learning techniques help overcome the limitations of traditional methods. Despite the constraints imposed by spatial and temporal resolution and optical limitations of sensors, multiplatform approaches can overcome these limitations and improve accuracy. This study explores various techniques for monitoring volcanic clouds, identifies research gaps, and lays the foundation for future research.
How Representative Are European AERONET-OC Sites of European Marine Waters?
Authors: Cazzaniga Ilaria , Mélin Frédéric
Published: May 2024

Data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) have been extensively used to assess Ocean Color radiometric products from various satellite sensors. This study, focusing on Ocean Color radiometric operational products from the Sentinel-3 Ocean and Land Colour Instrument (OLCI), aims at investigating where in the European seas the results of match-up analyses at the European marine AERONET-OC sites could be applicable. Data clustering is applied to OLCI remote sensing reflectance RRS(λ) from the various sites to define different sets of optical classes, which are later used to identify class-based uncertainties. A set of fifteen classes grants medium-to-high classification levels to most European seas, with exceptions in the South-East Mediterranean Sea, the Atlantic Ocean, or the Gulf of Bothnia. In these areas, RRS(λ) spectra are very often identified as novel with respect to the generated set of classes, suggesting their under-representation in AERONET-OC data. Uncertainties are finally mapped onto European seas according to class membership. The largest uncertainty values are obtained in the blue spectral region for almost all classes. In clear waters, larger values are obtained in the blue bands. Conversely, larger values are shown in the green and red bands in coastal and turbid waters.
Deep Blind Fault Activity—A Fault Model of Strong Mw 5.5 Earthquake Seismogenic Structures in North China
Authors: Liu Guanshen , Lu Renqi , He Dengfa , Fang Lihua , Zhang Yang , Su Peng , Tao Wei
Published: May 2024

North China is one of the high-risk areas for destructive and strong earthquakes in mainland China and has experienced numerous strong historical earthquakes. An earthquake of magnitude MW 5.5 struck Pingyuan County, Dezhou city, in Shandong Province, China, on 6 August 2023. This earthquake was the strongest in the eastern North China Craton since the 1976 Tangshan earthquake. Since the earthquake did not produce surface ruptures, the seismogenic structure for fault responsible for the Pingyuan MW 5.5 earthquake is still unclear. To reveal the subsurface geological structure near the earthquake epicenter, this study used high-resolution two-dimensional (2D) seismic reflection profiles and constructed a three-dimensional (3D) geometric model of the Tuqiao Fault by interpreting the faults in the seismic reflection profiles. This study further combined focal mechanism solutions, aftershock clusters, and other seismological data to discuss the seismogenic fault of the Pingyuan MW 5.5 earthquake. The results show that the Tuqiao Fault is not the seismogenic fault of the MW 5.5 earthquake. The actual seismogenic structure may be related to the NE-oriented high-angle strike-slip blind fault developed in the basement. We further propose three possible fault models for the strong seismogenic structure in North China to discuss the potential seismotectonics in this region.
Radiometric Calibration of the Near-Infrared Bands of GF-5-02/DPC for Water Vapor Retrieval
Authors: Xie Yanqing , Zhu Qingyu , Zhu Sifeng , Hou Weizhen , Zhang Liguo , Lei Xuefeng , Zhang Miaomiao , Li Yunduan , Liu Zhenhai , Wen Yuan , Li Zhengqiang
Published: May 2024

The GaoFen (GF)-5-02 satellite is one of the new generations of hyperspectral observation satellites launched by China in 2021. The directional polarimetric camera (DPC) is an optical sensor onboard the GF-5-02 satellite. The precipitable water vapor (PWV) is a key detection parameter of DPC. However, the existing PWV data developed using DPC data have significant errors due to the lack of the timely calibration of the two bands (865, 910 nm) of DPC used for PWV retrieval. In order to acquire DPC PWV data with smaller errors, a calibration method is developed for these two bands. The method consists of two parts: (1) calibrate the 865 nm band of the DPC using the cross-calibration method, (2) calibrate the 910 nm band of the DPC according to the calibrated 865 nm band of the DPC. This method effectively addresses the issue of the absence of a calibration method for the water vapor absorption band (910 nm) of the DPC. Regardless of whether AERONET PWV data or SuomiNET PWV data are used as the reference data, the accuracy of the DPC PWV data developed using calibrated DPC data is significantly superior to that of the DPC PWV data retrieved using data before recalibration. This means that the calibration method for the NIR bands of the DPC can effectively enhance the quality of DPC PWV data.
Inverse Synthetic Aperture Radar Imaging of Space Targets Using Wideband Pseudo-Noise Signals with Low Peak-to-Average Power Ratio
Authors: Anger Simon , Jirousek Matthias , Dill Stephan , Peichl Markus
Published: May 2024

With the number of new satellites increasing dramatically, comprehensive space surveillance is becoming increasingly important. Therefore, high-resolution inverse synthetic aperture radar (ISAR) imaging of satellites can provide an in-situ assessment of the satellites. This paper demonstrates that pseudo-noise signals can also be used for satellite imaging, in addition to classical linear frequency-modulated chirp signals. Pseudo-noise transmission signals offer the advantage of very low cross-correlation values. This, for instance, enables the possibility of a system with multiple channels transmitting instantaneously. Furthermore, it can significantly reduce signal interference with other systems operating in the same frequency spectrum, which is of particular interest for high-bandwidth, high-power systems such as satellite imaging radars. A new routine has been introduced to generate a wideband pseudo-noise signal with a peak-to-average power ratio (PAPR) similar to that of a chirp signal. This is essential for applications where the transmit signal power budget is sharply limited by the high-power amplifier. The paper presents both theoretical descriptions and analysis of the generated pseudo-noise signal as well as the results of an imaging measurement of a real space target using the introduced pseudo-noise signals.
A Soil Moisture and Vegetation-Based Susceptibility Mapping Approach to Wildfire Events in Greece
Authors: Chaleplis Kyriakos , Walters Avery , Fang Bin , Lakshmi Venkataraman , Gemitzi Alexandra
Published: May 2024

Wildfires in Mediterranean areas are becoming more frequent, and the fire season is extending toward the spring and autumn months. These alarming findings indicate an urgent need to develop fire susceptibility methods capable of identifying areas vulnerable to wildfires. The present work aims to uncover possible soil moisture and vegetation condition precursory signals of the largest and most devastating wildfires in Greece that occurred in 2021, 2022, and 2023. Therefore, the time series of two remotely sensed datasets–MAP L4 Soil Moisture (SM) and Landsat 8 NDVI, which represent vegetation and soil moisture conditions—were examined before five destructive wildfires in Greece during the study period. The results of the analysis highlighted specific properties indicative of fire-susceptible areas. NDVI in all fire-affected areas ranged from 0.13 to 0.35, while mean monthly soil moisture showed negative anomalies in the spring periods preceding fires. Accordingly, fire susceptibility maps were developed, verifying the usefulness of remotely sensed information related to soil moisture and NDVI. This information should be used to enhance fire models and identify areas at risk of wildfires in the near future.
Statistical Analysis of Multi-Year South China Sea Eddies and Exploration of Eddy Classification
Authors: Jin Yang , Jin Meibing , Wang Dongxiao , Dong Changming
Published: May 2024

Mesoscale eddies are structures of seawater motion with horizontal scales of tens to hundreds of kilometers, impact depths of tens to hundreds of meters, and time scales of days to months. This study presents a statistical analysis of mesoscale eddies in the South China Sea (SCS) from 1993 to 2021 based on eddies extracted from satellite remote sensing data using the vector geometry eddy detection method. On average, about 230 eddies with a wide spatial and temporal distribution are observed each year, and the numbers of CEs (52.2%) and AEs (47.8%) are almost similar, with a significant correlation in spatial distribution. In this article, eddies with a lifetime of at least 28 days (17% of the number of total eddies) are referred to as strong eddies (SEs). The SEs in the SCS that persist for several years in similar months and locations, such as the well-known dipole eddies consisting of CEs and AEs offshore eastern Vietnam, are defined as persistent strong eddies (PSEs). SEs and PSEs affect the thermohaline structure, current field, and material and energy transport in the upper ocean. This paper is important as it names the SEs and PSEs, and the naming of eddies can facilitate research on specific major eddies and improve public understanding of mesoscale eddies as important oceanic phenomena.
Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features
Authors: Bahameish Mariam , Stockman Tony , Requena Carrión Jesús
Published: May 2024

Stress recognition, particularly using machine learning (ML) with physiological data such as heart rate variability (HRV), holds promise for mental health interventions. However, limited datasets in affective computing and healthcare research can lead to inaccurate conclusions regarding the ML model performance. This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. To account for limitations associated with small datasets, robust strategies were implemented based on methodological recommendations for ML with a limited dataset, including data segmentation, feature selection, and model evaluation. Our findings highlight that the random forest model achieved the best performance in distinguishing stress from non-stress states. Notably, it showed higher performance in identifying stress from relaxation (F1-score: 86.3%) compared to neutral states (F1-score: 65.8%). Additionally, the model demonstrated generalizability when tested on independent secondary datasets, showcasing its ability to distinguish between stress and relaxation states. While our performance metrics might be lower than some previous studies, this likely reflects our focus on robust methodologies to enhance the generalizability and interpretability of ML models, which are crucial for real-world applications with limited datasets.
Multitask Learning Strategy with Pseudo-Labeling: Face Recognition, Facial Landmark Detection, and Head Pose Estimation
Authors: Lee Yongju , Jang Sungjun , Bae Han Byeol , Jeon Taejae , Lee Sangyoun
Published: May 2024

Most facial analysis methods perform well in standardized testing but not in real-world testing. The main reason is that training models cannot easily learn various human features and background noise, especially for facial landmark detection and head pose estimation tasks with limited and noisy training datasets. To alleviate the gap between standardized and real-world testing, we propose a pseudo-labeling technique using a face recognition dataset consisting of various people and background noise. The use of our pseudo-labeled training dataset can help to overcome the lack of diversity among the people in the dataset. Our integrated framework is constructed using complementary multitask learning methods to extract robust features for each task. Furthermore, introducing pseudo-labeling and multitask learning improves the face recognition performance by enabling the learning of pose-invariant features. Our method achieves state-of-the-art (SOTA) or near-SOTA performance on the AFLW2000-3D and BIWI datasets for facial landmark detection and head pose estimation, with competitive face verification performance on the IJB-C test dataset for face recognition. We demonstrate this through a novel testing methodology that categorizes cases as soft, medium, and hard based on the pose values of IJB-C. The proposed method achieves stable performance even when the dataset lacks diverse face identifications.
Muscle Synergy during Wrist Movements Based on Non-Negative Tucker Decomposition
Authors: Chen Xiaoling , Feng Yange , Chang Qingya , Yu Jinxu , Chen Jie , Xie Ping
Published: May 2024

Modular control of the muscle, which is called muscle synergy, simplifies control of the movement by the central nervous system. The purpose of this study was to explore the synergy in both the frequency and movement domains based on the non-negative Tucker decomposition (NTD) method. Surface electromyography (sEMG) data of 8 upper limb muscles in 10 healthy subjects under wrist flexion (WF) and wrist extension (WE) were recorded. NTD was selected for exploring the multi-domain muscle synergy from the sEMG data. The results showed two synergistic flexor pairs, Palmaris longus–Flexor Digitorum Superficialis (PL-FDS) and Extensor Carpi Radialis–Flexor Carpi Radialis (ECR-FCR), in the WF stage. Their spectral components are mainly in the respective bands 0–20 Hz and 25–50 Hz. And the spectral components of two extensor pairs, Extensor Digitorum–Extensor Carpi Ulnar (ED-ECU) and Extensor Carpi Radialis–Brachioradialis (ECR-B), are mainly in the respective bands 0–20 Hz and 7–45 Hz in the WE stage. Additionally, further analysis showed that the Biceps Brachii (BB) muscle was a shared muscle synergy module of the WE and WF stage, while the flexor muscles FCR, PL and FDS were the specific synergy modules of the WF stage, and the extensor muscles ED, ECU, ECR and B were the specific synergy modules of the WE stage. This study showed that NTD is a meaningful method to explore the multi-domain synergistic characteristics of multi-channel sEMG signals. The results can help us to better understand the frequency features of muscle synergy and shared and specific synergies, and expand the study perspective related to motor control in the nervous system.
Three-Dimensional Numerical Field Analysis in Transformers to Identify Losses in Tape Wound Cores
Authors: Koteras Dariusz , Tomczuk Bronislaw
Published: May 2024

To find the total core losses in 1-phase medium-frequency transformers, a 3D numerical field analysis was carried out. The proposed numerical modeling was based on the extended iterative homogenization method (IHM) developed by the authors. The achieved calculation results were validated by the corresponding values obtained experimentally, and a reasonably close agreement was obtained.
Amphibious Multifunctional Hydrogel Flexible Haptic Sensor with Self-Compensation Mechanism
Authors: Sun Zhenhao , Yin Yunjiang , Liu Baoguo , Xue Tao , Zou Qiang
Published: May 2024

In recent years, hydrogel-based wearable flexible electronic devices have attracted much attention. However, hydrogel-based sensors are affected by structural fatigue, material aging, and water absorption and swelling, making stability and accuracy a major challenge. In this study, we present a DN-SPEZ dual-network hydrogel prepared using polyvinyl alcohol (PVA), sodium alginate (SA), ethylene glycol (EG), and ZnSO4 and propose a self-calibration compensation strategy. The strategy utilizes a metal salt solution to adjust the carrier concentration of the hydrogel to mitigate the resistance drift phenomenon to improve the stability and accuracy of hydrogel sensors in amphibious scenarios, such as land and water. The ExpGrow model was used to characterize the trend of the ∆R/R0 dynamic response curves of the hydrogels in the stress tests, and the average deviation of the fitted curves ϵ¯ was calculated to quantify the stability differences of different groups. The results showed that the stability of the uncompensated group was much lower than that of the compensated group utilizing LiCl, NaCl, KCl, MgCl2, and AlCl3 solutions (ϵ¯ in the uncompensated group in air was 276.158, 1.888, 2.971, 30.586, and 13.561 times higher than that of the compensated group in LiCl, NaCl, KCl, MgCl2, and AlCl3, respectively; ϵ¯ in the uncompensated group in seawater was 10.287 times, 1.008 times, 1.161 times, 4.986 times, 1.281 times, respectively, higher than that of the compensated group in LiCl, NaCl, KCl, MgCl2 and AlCl3). In addition, for the ranking of the compensation effect of different compensation solutions, the concentration of the compensation solution and the ionic radius and charge of the cation were found to be important factors in determining the compensation effect. Detection of events in amphibious environments such as swallowing, robotic arm grasping, Morse code, and finger–wrist bending was also performed in this study. This work provides a viable method for stability and accuracy enhancement of dual-network hydrogel sensors with strain and pressure sensing capabilities and offers solutions for sensor applications in both airborne and underwater amphibious environments.
Research on a Wind Turbine Gearbox Fault Diagnosis Method Using Singular Value Decomposition and Graph Fourier Transform
Authors: Chen Lan , Zhang Xiangfeng , Li Zhanxiang , Jiang Hong
Published: May 2024

Gearboxes operate in challenging environments, which leads to a heightened incidence of failures, and ambient noise further compromises the accuracy of fault diagnosis. To address this issue, we introduce a fault diagnosis method that employs singular value decomposition (SVD) and graph Fourier transform (GFT). Singular values, commonly employed in feature extraction and fault diagnosis, effectively encapsulate various fault states of mechanical equipment. However, prior methods neglect the inter-relationships among singular values, resulting in the loss of subtle fault information concealed within. To precisely and effectively extract subtle fault information from gear vibration signals, this study incorporates graph signal processing (GSP) technology. Following SVD of the original vibration signal, the method constructs a graph signal using singular values as inputs, enabling the capture of topological relationships among these values and the extraction of concealed fault information. Subsequently, the graph signal undergoes a transformation via GFT, facilitating the extraction of fault features from the graph spectral domain. Ultimately, by assessing the Mahalanobis distance between training and testing samples, distinct defect states are discerned and diagnosed. Experimental results on bearing and gear faults demonstrate that the proposed method exhibits enhanced robustness to noise, enabling accurate and effective diagnosis of gearbox faults in environments with substantial noise.
GPR Mapping of Cavities in Complex Scenarios with a Combined Time–Depth Conversion
Authors: Persico Raffaele , Catapano Ilaria , Esposito Giuseppe , Morelli Gianfranco , De Martino Gregory , Capozzoli Luigi
Published: May 2024

The paper deals with a combined time–depth conversion strategy able to improve the reconstruction of voids embedded in an opaque medium, such as cavities, caves, empty hypogeal rooms, and similar targets. The combined time–depth conversion accounts for the propagation velocity of the electromagnetic waves both in free space and in the embedding medium, and it allows better imaging and interpretation of the underground scenario. To assess the strategy’s effectiveness, ground penetrating radar (GPR) data referred to as an experimental test in controlled conditions are accounted for and processed by two different approaches to achieve focused images of the scenario under test. The first approach is based on a classical migration algorithm, while the second one faces the imaging as a linear inverse scattering approach. The results corroborate that the combined time–depth conversion improves the imaging in both cases.
Research on Assimilation of Unmanned Aerial Vehicle Remote Sensing Data and AquaCrop Model
Authors: Li Wei , Li Manpeng , Awais Muhammad , Ji Leilei , Li Haoming , Song Rui , Cheema Muhammad Jehanzeb Masud , Agarwal Ramesh
Published: May 2024

Taking the AquaCrop crop model as the research object, considering the complexity and uncertainty of the crop growth process, the crop model can only achieve more accurate simulation on a single point scale. In order to improve the application scale of the crop model, this study inverted the canopy coverage of a tea garden based on UAV multispectral technology, adopted the particle swarm optimization algorithm to assimilate the canopy coverage and crop model, constructed the AquaCrop-PSO assimilation model, and compared the canopy coverage and yield simulation results with the localized model simulation results. It is found that there is a significant regression relationship between all vegetation indices and canopy coverage. Among the single vegetation index regression models, the logarithmic model constructed by OSAVI has the highest inversion accuracy, with an R2 of 0.855 and RMSE of 5.75. The tea yield was simulated by the AquaCrop-PSO model and the measured values of R2 and RMSE were 0.927 and 0.12, respectively. The canopy coverage R2 of each simulated growth period basically exceeded 0.9, and the accuracy of the simulation results was improved by about 19.8% compared with that of the localized model. The results show that the accuracy of crop model simulation can be improved effectively by retrieving crop parameters and assimilating crop models through UAV remote sensing.
Utilisation of Machine Learning in Control Systems Based on the Preference of Office Users
Authors: Bilésimo Thayane L. , Ghisi Enedir
Published: May 2024

Reducing energy consumption is vital to save natural resources and contribute to the sustainable development in any sector of society. In the building sector, there are many well-known energy efficiency strategies currently being applied. However, considering the advances in technology and in comfort studies, it is possible to see that the current building sector scenario demands new energy efficiency strategies. Such strategies need to be capable of identifying and assuring comfortable environments according to users’ perceptions. Machine learning techniques can be a useful alternative to identify users’ preferences and control lighting and heating, ventilation and air-conditioning systems in buildings. This paper shows a systematic literature review on the use of machine learning algorithms on preference identification and environmental adequacy according to users’ demands. Its contribution is to explore beyond the performance and configurations of the algorithms, addressing users’ preference aspects as well. The strategies found in the literature provided promising results. The most used approach was supervised learning because data can be treated as categories. In general, the control systems have shown good performance, and so have the algorithms. Users were mostly satisfied with environmental conditions. Situations of dissatisfaction were associated with the occupant’s willingness to use the system more than with the control system’s performance. Furthermore, it is also possible to ally user-centred control and energy savings but this relies on occupants’ characteristics and the control strategies used. We underline the importance of identifying whether the users are willing to deal with an automatic control system before making any decision, even if the operation of the system is based on their preferred environmental conditions.
Sustainable CO2 Refrigeration System for Fish Cold Storage Facility Using a Renewable Integrated System with Solar, Wind and Tidal Energy for Cape Verde—Analyzing Scenarios
Authors: Garcia João , Semedo Arian
Published: May 2024

This study compares four feasible alternative solutions for an integrated cold storage system in the city of Tarrafal, Santiago, Cape Verde. Integrated systems using grid electricity are compared with autonomous systems generating electrical energy from renewable sources, alongside various types of refrigeration facility systems. Its objective is to assess the energy efficiency, financial feasibility, and environmental impact across four scenarios. Scenario 1 utilizes two R134a refrigeration units powered by the public grid. Scenario 2 employs a transcritical R744 (CO2) system using grid electricity. Scenario 3 incorporates R744 and autonomous renewable energy. Scenario 4 employs R744 for refrigeration with seawater heat exchange and autonomous renewable energy sources. The findings favor Scenario 4, emitting 15,882 kg CO2 eq with a 5-year return on investment. Autonomous electricity production in this scenario reduces emissions by 95%. Despite an initial cost of EUR 769,172.00, Scenario 3 demonstrates financial viability, contributing to energy sustainability. This autonomous production reduces emissions by 360,697 kg CO2 compared to conventional systems, highlighting the positive impact of local renewable energy integration.
Developing an Efficient Model for Online Grocery Order Fulfillment
Authors: Alrasheed Moaad Abdulaziz , Rehman Ateekh Ur , Alharkan Ibrahim M.
Published: May 2024

Due to the convenience of online grocery apps and home delivery, online grocery shopping has become popular in recent years. Globally, consumer behavior has significantly changed the consumption and purchase patterns of online grocery shopping. This study aimed to develop an efficient model for online grocery order fulfillment that both reduces costs and increases supply chain efficiency and sustainability. This study first aimed to develop the current picking model by adopting real-world data from a store in Riyadh, Saudi Arabia. Subsequently, four proposed models were developed to improve the efficiency and sustainability of the online grocery order fulfillment process. The results show a significant improvement in all models over the current picking model. The percentage improvements in fulfillment time per product are as follows: single order picking—8.33%; batch order picking—6.78%; zone order picking—3.08%; and hybrid order picking—13.20%, which combines zone and batch order picking. Retailers and online grocery apps could adopt these models to increase efficiency and sustainability. Also, these models have great potential for future research and improvement by optimizing product placement, in addition to picking methods and picking routes, which are the focus of this study.