bluuebunny/crossref_metadata_2025 huggingface dataset:
Design, Synthesis, Antibacterial, and Antifungal Evaluation of Phenylthiazole Derivatives Containing a 1,3,4-Thiadiazole Thione Moiety
Authors: Mao Guoqing , Tian Yao , Shi Jinchao , Liao Changzhou , Huang Weiwei , Wu Yiran , Wen Zhou , Yu Linhua , Zhu Xiang , Li Junkai
Published: January 2024

To effectively control the infection of plant pathogens, we designed and synthesized a series of phenylthiazole derivatives containing a 1,3,4-thiadiazole thione moiety and screened for their antibacterial potencies against Ralstonia solanacearum, Xanthomonas oryzae pv. oryzae, as well as their antifungal potencies against Sclerotinia sclerotiorum, Rhizoctonia solani, Magnaporthe oryzae and Colletotrichum gloeosporioides. The chemical structures of the target compounds were characterized by 1H NMR, 13C NMR and HRMS. The bioassay results revealed that all the tested compounds exhibited moderate-to-excellent antibacterial and antifungal activities against six plant pathogens. Especially, compound 5k possessed the most remarkable antibacterial activity against R. solanacearum (EC50 = 2.23 μg/mL), which was significantly superior to that of compound E1 (EC50 = 69.87 μg/mL) and the commercial agent Thiodiazole copper (EC50 = 52.01 μg/mL). Meanwhile, compound 5b displayed the most excellent antifungal activity against S. sclerotiorum (EC50 = 0.51 μg/mL), which was equivalent to that of the commercial fungicide Carbendazim (EC50 = 0.57 μg/mL). The preliminary structure-activity relationship (SAR) results suggested that introducing an electron-withdrawing group at the meta-position and ortho-position of the benzene ring could endow the final structure with remarkable antibacterial and antifungal activity, respectively. The current results indicated that these compounds were capable of serving as promising lead compounds.
Thermal Conductivity Calculation in Organic Liquids: Application to Poly-α-Olefin
Authors: Severin Jonathan , Loehlé Sophie , Jund Philippe
Published: January 2024

In this work, we aim to understand and predict the thermal properties of automotive lubricants using non-equilibrium molecular dynamics. After a previous study on model materials for the mechanical parts of a car engine, we now focus on the thermal conductivity κ of the poly-α-olefin base oil (PAO4) using the well-known sink and source method to study the response of the system to an imposed heat flux. We present a detailed methodology for the calculation of κ, taking into account specific constraints related to the system under study, such as large steady-state fluctuations and rapidly growing stationarization times. We provide thermal conductivity results using four different force fields, including OPLS-AA, PCFF and COMPASS, in a temperature range of 300 to 500 K, which corresponds to the typical operating range of a car engine. The results are compared to experimental measurements performed on the commercial compound using the laser flash method. Agreement at room temperature is shown to be excellent for our in-house force field.
The Effect of Peppermint and Thyme Oils on Stabilizing the Fatty Acid Profile of Sunflower Oil
Authors: Kowalski Radosław , Kowalska Grażyna , Mitura Przemysław , Rowiński Rafał , Pankiewicz Urszula , Hawlena Joanna
Published: January 2024

Presently, there is an increasing shift towards the utilization of natural antioxidants and compounds with protective attributes for fatty acids in order to replace synthetic counterparts that may pose health risks. This transition aligns with the growing emphasis on promoting healthy and organic food choices. Essential oils stand out in this context due to scientific validations of their antioxidant properties. There are few published research results concerning changes in the fatty acid composition in model systems with the addition of essential oils. This study aims to investigate the impact of incorporating peppermint and thyme oils on inhibiting changes in the fatty acid profile of sunflower oil stored at both room temperature with exposure to daylight and in a thermostat set at 40 °C. The experimental procedure involved the addition of peppermint and thyme oils, along with butylated hydroxyanisole (BHA), to batches of sunflower oil. The samples were then stored for 11 months. The study observed a detrimental influence of storage conditions on the quantitative changes in the fatty acid profile of the sunflower oil. The addition of BHA stabilized the content of linoleic acid in the sunflower oil (approximately 53 g/100 g of linoleic acid compared to approximately 58 g/100 g in the control sample). Meanwhile, the model system of sunflower oil with the addition of peppermint and thyme oils (40 °C) exhibited a statistically significant decrease in the concentration of linoleic acid to approximately 8 g/100 g after eleven months of thermostating. Similar trends to those observed for linoleic acid were noted for the total fatty acid content in the sunflower oil. Notably, the efficacy of the selected substances in inhibiting adverse transformations in fats was contingent upon their concentration and the storage temperature.
Transport of Nanoparticles into Plants and Their Detection Methods
Authors: Sembada Anca Awal , Lenggoro I. Wuled
Published: January 2024

Nanoparticle transport into plants is an evolving field of research with diverse applications in agriculture and biotechnology. This article provides an overview of the challenges and prospects associated with the transport of nanoparticles in plants, focusing on delivery methods and the detection of nanoparticles within plant tissues. Passive and assisted delivery methods, including the use of roots and leaves as introduction sites, are discussed, along with their respective advantages and limitations. The barriers encountered in nanoparticle delivery to plants are highlighted, emphasizing the need for innovative approaches (e.g., the stem as a new recognition site) to optimize transport efficiency. In recent years, research efforts have intensified, leading to an evendeeper understanding of the intricate mechanisms governing the interaction of nanomaterials with plant tissues and cells. Investigations into the uptake pathways and translocation mechanisms within plants have revealed nuanced responses to different types of nanoparticles. Additionally, this article delves into the importance of detection methods for studying nanoparticle localization and quantification within plant tissues. Various techniques are presented as valuable tools for comprehensively understanding nanoparticle–plant interactions. The reliance on multiple detection methods for data validation is emphasized to enhance the reliability of the research findings. The future outlooks of this field are explored, including the potential use of alternative introduction sites, such as stems, and the continued development of nanoparticle formulations that improve adhesion and penetration. By addressing these challenges and fostering multidisciplinary research, the field of nanoparticle transport in plants is poised to make significant contributions to sustainable agriculture and environmental management.
Factors Associated with Provider Practices Related to Infant Feeding in Primary Care Settings: Results from a Pilot Survey
Authors: Lima Hope K. , Ganio Molinari Meghan , Hoffman Jessie B. , Akers Lisa , Evans Karin I. , Licata Ashley
Published: January 2024

In 2020, only 25.6% of dyads in the US were exclusively breastfeeding at six months. Previous research has shown that breastfeeding continuation improves when patients receive both prenatal and postpartum support. Additionally, breastfeeding self-efficacy can be directly impacted by interactions with primary healthcare providers. To facilitate improved lactation support and positive interactions with providers related to infant feeding in the primary care setting, a 49-question survey was utilized to conduct a retrospective, cross-sectional study. Using multiple regression analysis, the researchers tested a model to determine if certain factors could predict patients receiving lactation education in the primary care setting. The full model was statistically significant and accounts for 81.8% of the variance (R2 = 0.818, F (7, 21) = 9.015, p < 0.001, CI = 0.728 to 0.910). Variables that contributed significantly to the model included provider age, provider years of experience in maternal-child health, population density of the practice, and average provider preparedness and comfort with lactation support and medical management. As the only modifiable predictor significantly contributing to the model, future research is necessary to develop educational interventions to improve provider preparedness and comfort with lactation support and medical management. Such interventions may significantly improve the frequency of lactation education in primary care settings.
Associations between Maternal Nutritional Status, Hemodynamic Parameters, and Delivery Outcomes in Low-Risk Pregnancies: A Prospective Observational Study
Authors: Lubrano Chiara , Parisi Francesca , Coco Chiara , Marelli Elisabetta , Burello Eleonora , Cetin Irene
Published: January 2024

Maternal nutritional status represents a pivotal predictor of pregnancy outcome. This prospective observational study investigates the associations between maternal characteristics and nutritional habits at term, hemodynamic parameters, and pregnancy outcomes. Healthy women with singleton uncomplicated pregnancies were enrolled at 36–41 gestational weeks. At enrollment, a nutritional score (0–10) was calculated in order to quantify maternal adherence to a healthy diet and lifestyle. Maternal hemodynamic parameters were assessed by using the Ultrasonic Cardiac Output Monitor (USCOM), including cardiac output (CO), systemic vascular resistance (SVR) and Smith–Madigan inotropy index (SMII). Pregnancy outcomes were recorded at delivery. Associations between maternal characteristics and nutritional score, hemodynamic parameters, and pregnancy outcomes were investigated by using multi-adjusted generalized linear models. In total, 143 pregnancies were enrolled. Pregestational body mass index (BMI) was positively associated with SVR, and negatively associated with CO and SMII. Additionally, a positive association was detected between the nutritional score and SMII. Finally, CO was positively associated with birth and placental weight, while RVS showed a negative association with birth and placental weight. This study shows that maternal derangements in nutritional status and habits are associated with a compromised hemodynamic profile at term, with additional impacts on intrauterine growth.
Chinese Sumac (Rhus chinensis Mill.) Fruits Prevent Hyperuricemia and Uric Acid Nephropathy in Mice Fed a High-Purine Yeast Diet
Authors: Ma Nan , Cai Shengbao , Sun Yilin , Chu Chuanqi
Published: January 2024

Hyperuricemia (HUA) is a prevalent chronic disease, characterized by excessive blood uric acid levels, that poses a significant health risk. In this study, the preventive effects and potential mechanisms of ethanol extracts from Chinese sumac (Rhus chinensis Mill.) fruits on HUA and uric acid nephropathy were comprehensively investigated. The results demonstrated a significant reduction in uric acid levels in hyperuricemia mice after treatment with Chinese sumac fruit extract, especially in the high-dose group, where the blood uric acid level decreased by 39.56%. Visual diagrams of the kidneys and hematoxylin and eosin (H&E)-stained sections showed the extract’s effectiveness in protecting against kidney damage caused by excessive uric acid. Further investigation into its mechanism revealed that the extract prevents and treats hyperuricemia by decreasing uric acid production, enhancing uric acid excretion, and mitigating the oxidative stress and inflammatory reactions induced by excessive uric acid in the kidneys. Specifically, the extract markedly decreased xanthine oxidase (XOD) levels and expression in the liver, elevated the expression of uric acid transporters ABCG2, and lowered the expression of uric acid reabsorption proteins URAT1 and SLC2A9. Simultaneously, it significantly elevated the levels of endogenous antioxidant enzymes (SOD and GSH) while reducing the level of malondialdehyde (MDA). Furthermore, the expression of uric-acid-related proteins NLRP3, ACS, and Caspase-3 and the levels of IL-1β and IL-6 were significantly reduced. The experimental results confirm that Chinese sumac fruit extract can improve HUA and uric acid nephropathy in mice fed a high-purine yeast diet. This finding establishes a theoretical foundation for developing Chinese sumac fruit as a functional food or medicine for preventing and treating HUA.
The Design and Characterization of an Ultra-Compact Asymmetrical Multimode Interference Splitter on Lithium Niobate Thin Film
Authors: Li Dechen , Li Jinye , Li Run , Liu Jianguo
Published: January 2024

We propose and demonstrate a high-performance asymmetrical multimode interference splitter on X-cut lithium niobate on insulator (LNOI) with an ultra-compact size of 5.8 μm × (26.4–35.6) μm. A rectangle with a small region is removed from the upper left corner of the multimode interference (MMI) coupler to achieve a variable splitting ratio. Here, we design and characterize MMIs in six different distribution ratios ranging from 50:50 to 95:5 on a 600 nm thick LNOI. Based on the cascade structure, the linear fitting method accurately shows the device loss (~0.1–0.9 dB). Our fabricated devices demonstrate robustness across a 30 nm optical bandwidth (1535–1565 nm). In addition, we numerically simulate the Z-cut LNOI, showing that the structure corresponding to the TM mode can also achieve a good variable splitting ratio.
Investigating the Effects of Full-Spectrum LED Lighting on Strawberry Traits Using Correlation Analysis and Time-Series Prediction
Authors: Lu Yuze , Gong Mali , Li Jing , Ma Jianshe
Published: January 2024

In crop cultivation, particularly in controlled environmental agriculture, light quality is one of the most critical factors affecting crop growth and harvest. Many scholars have studied the effects of light quality on strawberry traits, but they have used relatively simple light components and considered only a small number of light qualities and traits in each experiment, and the results were not complete or objective. In order to comprehensively investigate the effects of different light qualities from 350 nm to 1000 nm on strawberry traits to better predict the future growth trend of strawberries under different light qualities, we proposed a new approach. We introduced Spearman’s rank correlation coefficient to handle complex light quality variations and multiple traits, preprocessed the cultivation data through the CEEDMAN method, and predicted them using the Informer network. We took 500 strawberry plants as samples and cultivated them in 72 groups of dynamically changing light qualities. Then, we recorded the growth changes and formed training and testing sets. Finally, we discussed the correlation between light quality and plant trait changes in consistency with current studies, and the proposed prediction model achieved the best performance in the prediction task of nine plant traits compared with the comparison models. Thus, the validity of the proposed method and model was demonstrated.
Comprehensive Identification of the β-Amylase (BAM) Gene Family in Response to Cold Stress in White Clover
Authors: Li Manman , Chen Xiuhua , Huang Wangqi , Wu Kaiyue , Bai Yan , Guo Donglin , Guo Changhong , Shu Yongjun
Published: January 2024

White clover (Trifolium repens L.) is an allopolyploid plant and an excellent perennial legume forage. However, white clover is subjected to various stresses during its growth, with cold stress being one of the major limiting factors affecting its growth and development. Beta-amylase (BAM) is an important starch-hydrolyzing enzyme that plays a significant role in starch degradation and responses to environmental stress. In this study, 21 members of the BAM gene family were identified in the white clover genome. A phylogenetic analysis using BAMs from Arabidopsis divided TrBAMs into four groups based on sequence similarity. Through analysis of conserved motifs, gene duplication, synteny analysis, and cis-acting elements, a deeper understanding of the structure and evolution of TrBAMs in white clover was gained. Additionally, a gene regulatory network (GRN) containing TrBAMs was constructed; gene ontology (GO) annotation analysis revealed close interactions between TrBAMs and AMY (α-amylase) and DPE (4-alpha-glucanotransferase). To determine the function of TrBAMs under various tissues and stresses, RNA-seq datasets were analyzed, showing that most TrBAMs were significantly upregulated in response to biotic and abiotic stresses and the highest expression in leaves. These results were validated through qRT-PCR experiments, indicating their involvement in multiple gene regulatory pathways responding to cold stress. This study provides new insights into the structure, evolution, and function of the white clover BAM gene family, laying the foundation for further exploration of the functional mechanisms through which TrBAMs respond to cold stress.
The Mechanisms of Regulated Cell Death: Structural and Functional Proteomic Pathways Induced or Inhibited by a Specific Protein—A Narrative Review
Authors: Fernández-Lázaro Diego , Sanz Begoña , Seco-Calvo Jesús
Published: January 2024

Billions of cells die in us every hour, and our tissues do not shrink because there is a natural regulation where Cell Death (CD) is balanced with cell division. The process in which cells eliminate themselves in a controlled manner is called Programmed Cell Death (PCD). The PCD plays an important role during embryonic development, in maintaining homeostasis of the body’s tissues, and in the elimination of damaged cells, under a wide range of physiological and developmental stimuli. A multitude of protein mediators of PCD have been identified and signals have been found to utilize common pathways elucidating the proteins involved. This narrative review focuses on caspase-dependent and caspase-independent PCD pathways. Included are studies of caspase-dependent PCD such as Anoikis, Catastrophe Mitotic, Pyroptosis, Emperitosis, Parthanatos and Cornification, and Caspase-Independent PCD as Wallerian Degeneration, Ferroptosis, Paraptosis, Entosis, Methuosis, and Extracellular Trap Abnormal Condition (ETosis), as well as neutrophil extracellular trap abnormal condition (NETosis) and Eosinophil Extracellular Trap Abnormal Condition (EETosis). Understanding PCD from those reported in this review could shed substantial light on the processes of biological homeostasis. In addition, identifying specific proteins involved in these processes is mandatory to identify molecular biomarkers, as well as therapeutic targets. This knowledge could provide the ability to modulate the PCD response and could lead to new therapeutic interventions in a wide range of diseases.
DeepRED Based Sparse SAR Imaging
Authors: Zhao Yao , Liu Qingsong , Tian He , Ling Bingo Wing-Kuen , Zhang Zhe
Published: January 2024

The integration of deep neural networks into sparse synthetic aperture radar (SAR) imaging is explored to enhance SAR imaging performance and reduce the system’s sampling rate. However, the scarcity of training samples and mismatches between the training data and the SAR system pose significant challenges to the method’s further development. In this paper, we propose a novel SAR imaging approach based on deep image prior powered by RED (DeepRED), enabling unsupervised SAR imaging without the need for additional training data. Initially, DeepRED is introduced as the regularization technique within the sparse SAR imaging model. Subsequently, variable splitting and the alternating direction method of multipliers (ADMM) are employed to solve the imaging model, alternately updating the magnitude and phase of the SAR image. Additionally, the SAR echo simulation operator is utilized as an observation model to enhance computational efficiency. Through simulations and real data experiments, we demonstrate that our method maintains imaging quality and system downsampling rate on par with deep-neural-network-based sparse SAR imaging but without the requirement for training data.
Large-Scale Spatial–Temporal Identification of Urban Vacant Land and Informal Green Spaces Using Semantic Segmentation
Authors: Hu Xinlei , Zhuang Shuo
Published: January 2024

The large-scale identification of urban vacant land (UVL) and informal green spaces (IGSs) using conventional identification methods is challenged by the high cost of time and resources as well as inconsistent outcomes. Moreover, the spatial–temporal changes of UVL and IGSs have received limited academic attention. We introduce a methodological framework for the large-scale automatic identification of UVL and IGSs in Hangzhou, China, based on semantic segmentation. We construct and release a large-scale dataset for UVL identification, containing five different UVL categories, and one of them is IGS, with 3096 patches for training and 128 patches for evaluation. We then train five different semantic segmentation networks using the dataset and utilise Segformer to predict UVL and IGSs within the whole urban area of Hangzhou. The presented segmentation model has a hierarchically structured Transformer encoder and a multilayer perceptron decoder, which incorporates local and global information to obtain effective feature representations. Extensive experiments have been conducted to evaluate the segmentation performance of the applied Segformer. Experimental results show the good identification performance of Segformer for UVL and IGSs. Results also verify that the proposed identification framework can be effectively used to analyse the spatial–temporal changes of UVL and IGSs in Hangzhou.
Flood Risk Assessment of Areas under Urbanization in Chongqing, China, by Integrating Multi-Models
Authors: Li Yuqing , Gao Jiangbo , Yin Jie , Liu Lulu , Zhang Chuanwei , Wu Shaohong
Published: January 2024

In the context of urbanization, frequent flood event have become the most common natural disasters, posing a significant challenge to human society. Considering the effects of urbanization on flood risk is critical for flood risk reduction and reasonable land planning strategies at the city scale. This study proposes an integrated approach based on remote sensing data using CA, Markov, and simplified hydrodynamic (FloodMap) models to accurately and effectively assess flood risk under urbanization. Taking Chongqing City as a case study, this paper analyzes the temporal and spatial variations in land use/land cover (LULC) in 2010, 2015, and 2018 and predicts the LULC for 2030, based on historic trends. Flood risk is assessed by combining the hazard, exposure, and modified vulnerability. The results suggest that the area of built-up land will increase significantly from 19.56% in 2018 to 25.21% in 2030. From 2010 to 2030, the area of medium and high inundation depths will increase by 10 and 16 times, respectively. Flood damage varies remarkably according to the LULC and return period. The expected annual damage (EAD) has been estimated to increase from USD 68 million in 2010 to USD 200 million in 2030. Flood risk is proportional to population and is significantly inversely proportional to socioeconomic level. The approach used here can provide a comprehensive understanding of flood risk and is significant for land-use policymaking and the management of flood control facilities.
The Study of Internal Gravity Waves in the Earth’s Atmosphere by Radio Occultations: A Review
Authors: Gorbunov Michael , Kan Valery
Published: January 2024

Internal gravity waves (IGWs) in the middle atmosphere are the main source of mesoscale fluctuations of wind and temperature. The parameterization of IGWs and study of their climatology is necessary for the development of global atmospheric circulation models. In this review, we focus on the application of Radio Occultation (RO) observations for the retrieval of IGW parameters. (1) The simplest approach employs the retrieved temperature profiles. It is based on the fact that IGWs are highly anisotropic structures and can be accurately retrieved by RO. The basic assumption is that all the temperature fluctuations are caused by IGWs. The smoothed background temperature profile defines the the Brunt–Väisälä frequency, which, together with the temperature fluctuations, defines the IGW specific potential energy. Many studies have derived the distribution and climatology of potential energy, which is one of the most important characteristics of IGWs. (2) More detailed analysis of the temperature profiles is based on the derivation of the temperature fluctuation spectra. For saturated IGWs, the spectra must obey the power law with an exponent of −3. Such spectra are obtained by using Wave Optical (WO) processing. (3) More advanced analysis employs space–frequency analysis. It is based on phase-sensitive techniques like cross S- or wavelet transforms in order to identify propagating IGWs. (4) Another direction is the IGW parameter estimate from separate temperature profiles applying the stability condition in terms of the Richardson number. In this framework, a necessary condition is formulated that defines whether or not the temperature fluctuations can be related to IGW events. The temperature profile retrieval involves integral transforms and filtering that constitute the observation filter. (5) A simpler filter is implemented by the analysis of the RO amplitude fluctuation spectra, based on the diffraction theory in the framework of the phase screen and weak fluctuation approximations. The two spectral parameters, the external scale and the structural characteristic, define the specific potential energy. This approach allows the derivation of the spacial and seasonal distributions of IGW activity. We conclude that the success of IGW study by RO is stimulated by a large number of RO observations and advanced techniques based on Fourier and space–time analysis, physical equations describing IGWs, and diffraction theory.
Synchronized and Co-Located Ionospheric and Atmospheric Anomalies Associated with the 2023 Mw 7.8 Turkey Earthquake
Authors: Haider Syed Faizan , Shah Munawar , Li Bofeng , Jamjareegulgarn Punyawi , de Oliveira-Júnior José Francisco , Zhou Changyu
Published: January 2024

Earth observations from remotely sensed data have a substantial impact on natural hazard surveillance, specifically for earthquakes. The rapid emergence of diverse earthquake precursors has led to the exploration of different methodologies and datasets from various satellites to understand and address the complex nature of earthquake precursors. This study presents a novel technique to detect the ionospheric and atmospheric precursors using machine learning (ML). We examine the multiple precursors of different spatiotemporal nature from satellites in the ionosphere and atmosphere related to the Turkey earthquake on 6 February 2023 (Mw 7.8), in the form of total electron content (TEC), land surface temperature (LST), sea surface temperature (SST), air pressure (AP), relative humidity (RH), outgoing longwave radiation (OLR), and air temperature (AT). As a confutation analysis, we also statistically observe datasets of atmospheric parameters for the years 2021 and 2022 in the same epicentral region and time period as the 2023 Turkey earthquake. Moreover, the aim of this study is to find a synchronized and co-located window of possible earthquake anomalies by providing more evidence with standard deviation (STDEV) and nonlinear autoregressive network with exogenous inputs (NARX) models. It is noteworthy that both the statistical and ML methods demonstrate abnormal fluctuations as precursors within 6 to 7 days before the impending earthquake over the epicenter. Furthermore, the geomagnetic anomalies in the ionosphere are detected on the ninth day after the earthquake (Kp > 4; Dst < −70 nT; ap > 50 nT). This study indicates the relevance of using multiple earthquake precursors in a synchronized window from ML methods to support the lithosphere–atmosphere–ionosphere coupling (LAIC) phenomenon.
Effects of Minimalist vs. Traditional Running Shoes on Abdominal Lumbopelvic Muscle Activity in Women Running at Different Speeds: A Randomized Cross-Over Clinical Trial
Authors: García-Arrabé María , de la Plaza San Frutos Marta , Bermejo-Franco Alberto , del Prado-Álvarez Rebeca , López-Ruiz Javier , del-Blanco-Muñiz José Angel , Giménez María-José
Published: January 2024

This study aimed to investigate if the characteristics of different running shoes could influence intra-abdominal pressure during running. A single-centre, randomized, prospective cross-over clinical trial was performed measuring activity patterns of internal oblique (IO), lumbar erector (LE), and gluteus maximus (GM) muscles in healthy women when running with minimalist shoes (MS). Participants were randomly allocated into two-sequence (MS/TS or TS/MS) treadmill running at six, nine, and eleven km/h. The surface electromyographic activity of IO, LE, and GM muscles were recorded while running. A repeated measures ANOVA explored the interaction effects of three-muscle x three speeds x two shoes. Significance was set at p ≤ 0.05. Fifty-one healthy nulliparous women (mean age: 26.55 ± 5.11 years; body mass index: 21.29 ± 2.07 Kg/m2) were included. Our findings revealed lower activations of the LE compared to the internal oblique IO and GM, irrespective of running speed and footwear used. Electromyographic activation significantly increased with higher running speeds (p < 0.001) for all muscles, regardless of the type of footwear. Although electromyographic records with MS consistently showed higher values than those with TS, the differences were not statistically significant for all muscles at all speeds. Our results indicate that electromyographic activation patterns vary according to the muscle group, exhibiting higher values with increased running speed. No significant differences were observed between MS and TS.
Study on a Pig Vocalization Classification Method Based on Multi-Feature Fusion
Authors: Hou Yuting , Li Qifeng , Wang Zuchao , Liu Tonghai , He Yuxiang , Li Haiyan , Ren Zhiyu , Guo Xiaoli , Yang Gan , Liu Yu , Yu Ligen
Published: January 2024

To improve the classification of pig vocalization using vocal signals and improve recognition accuracy, a pig vocalization classification method based on multi-feature fusion is proposed in this study. With the typical vocalization of pigs in large-scale breeding houses as the research object, short-time energy, frequency centroid, formant frequency and first-order difference, and Mel frequency cepstral coefficient and first-order difference were extracted as the fusion features. These fusion features were improved using principal component analysis. A pig vocalization classification model with a BP neural network optimized based on the genetic algorithm was constructed. The results showed that using the improved features to recognize pig grunting, squealing, and coughing, the average recognition accuracy was 93.2%; the recognition precisions were 87.9%, 98.1%, and 92.7%, respectively, with an average of 92.9%; and the recognition recalls were 92.0%, 99.1%, and 87.4%, respectively, with an average of 92.8%, which indicated that the proposed pig vocalization classification method had good recognition precision and recall, and could provide a reference for pig vocalization information feedback and automatic recognition.
Dual-Polarized Metal Vivaldi Array Using Independent Structural Elements
Authors: Chen Bo , Wang Wei , Liu Juan , Ji Jianmin
Published: January 2024

In this letter, a dual-polarized metal Vivaldi phased array antenna composed of independent structural elements is proposed, covering 6–18 GHz. By designing Vivaldi elements with a flexible and complementary structure, arrays of arbitrary shapes and scales can be constructed. The resonance caused by structural discontinuity is critically studied and eliminated to ensure good performance across the entire band. The antenna elements are fed by 50-Ohm SSMP connectors and manufactured from 2A12 aluminum alloy. An array prototype consisting of 8 × 8 dual-polarized metal has been fabricated and tested with active transmit/receive (T/R) modules to demonstrate the design concept. The array exhibits excellent beam-scanning characteristics in both the E-plane and H-plane, within the scanning range without grating lobes, which shows good agreement with the simulated results. The measured gain results are within the range of 15.2 to 24.8 dBi, and the aperture efficiencies are greater than 91% in the entire operating band. The wideband antenna technology involved in this study can effectively help increase the capacity of communication systems and meets the intentions of the Special Issue.
Leveraging Generative Design and Point Cloud Data to Improve Conformance to Passing Lane Layout
Authors: Momeni Rad Faeze , Sydora Christoph , El-Basyouny Karim
Published: January 2024

Inadequate highway design is a leading cause of traffic accidents, underscoring the importance of adhering to guidelines and regulations for highway design. These standards exist to safeguard road users by addressing crucial factors, like road geometry, signage, and lane markings. Thus, emphasis is placed on computational methods that can optimize towards higher levels of safety, capacity, efficiency, and sustainability in highway designs. Building Information Modeling (BIM) enhances this process by creating a digital model with physical and operational attributes. In this study, a user-friendly, logic-based language is utilized to encode rules for designing highway passing lanes by which designs are automatically evaluated and generated in the BIM-kit software toolkit. This approach is applied to 16 real-world passing lanes in Alberta, showcasing its utility in transportation. The analysis reveals significant enhancements, with rule compliance increasing from 61.82% to 91.31% after employing generative design techniques. These findings underscore the significance of generative design in transportation, offering engineers an efficient tool to create innovative, compliant solutions for highway projects.
A Segmented Cross-Correlation Algorithm for Dynamic North Finding Using Fiber Optic Gyroscopes
Authors: Fang Shuwei , Mao Shanjun , Chen Yanjun , Zhu Lanxin
Published: January 2024

Fiber optic gyroscope (FOG)-based north finding is extensively applied in navigation, positioning, and various fields. In dynamic north finding, an accelerated turntable speed shortens the time required for north finding, resulting in a rapid north-finding response. However, with an increase in turntable speed, the turntable’s jitter contributes to signal contamination in the FOG, leading to a deterioration in north-finding accuracy. This paper introduces a divide-and-conquer algorithm, the segmented cross-correlation algorithm, designed to mitigate the impact of turntable speed jitter. A model for north-finding error is established and analyzed, incorporating FOG’s self-noise and the turntable’s speed jitter. To validate the feasibility of our method, we implemented the algorithm on a FOG. The simulation and experimental results exhibited a strong concordance, affirming the validity of our proposed north-finding error model. The experimental findings indicate that, at a turntable speed of 180°/s, the north-finding bias error within a 360 s duration is 0.052°, representing a 64% improvement over the traditional algorithm. These results indicate the effectiveness of the proposed algorithm in mitigating the impact of unstable turntable speeds, offering a solution for north finding with both prompt response and enhanced accuracy.
Enhancing Water Safety: Exploring Recent Technological Approaches for Drowning Detection
Authors: Jalalifar Salman , Belford Andrew , Erfani Eila , Razmjou Amir , Abbassi Rouzbeh , Mohseni-Dargah Masoud , Asadnia Mohsen
Published: January 2024

Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection systems. However, the image-processing approach requires substantial resources and sophisticated MLAs, making it costly and complex to implement. Conversely, sensor-based approaches offer practical, cost-effective, and widely applicable solutions for drowning detection. These approaches involve data transmission from the swimmer’s condition to the processing unit through sensing technology, utilising both wired and wireless communication channels. This paper explores the recent developments in drowning detection systems while considering costs, complexity, and practicality in selecting and implementing such systems. The assessment of various technological approaches contributes to ongoing efforts aimed at improving water safety and reducing the risks associated with drowning incidents.
Gender Discrimination in Prison: The Perception of Women Inmates and Prison Professionals
Authors: Quiroga-Carrillo Anaïs , Ferraces Otero María José , Lorenzo Moledo Mar
Published: January 2024

The prejudices that have traditionally been held against female delinquency and the numerical minority of women in the prison system have led to the invisibility of their needs and characteristics as well as to many situations of inequality while they are incarcerated. This study is aimed at exploring the gender discrimination perceived by women in Spanish prisons. To this end, a scale for perception of gender discrimination is applied to a sample of incarcerated women. Qualitative data from a questionnaire administered to prison professionals and field notes are also used. The results show that incarcerated women perceive the existence of several situations of discrimination related to socio-educational intervention and to the adaptation of prisons to their unique needs, especially for those housed in male prisons. Prison professionals hold similar views and express their concern about the feminization of activities. The study has implications for the prison system and policy makers, including the implementation of gender-responsive programming in women’s prisons, the development of periodic assessments of the experiences faced by incarcerated women, and the training of prison staff.
Tillage and Cover Crop Systems Alter Soil Particle Size Distribution in Raised-Bed-and-Furrow Row-Crop Agroecosystems
Authors: Jacobs Alayna A. , Stout Evans Rachel , Allison Jon K. , Kingery William L. , McCulley Rebecca L. , Brye Kristofor R.
Published: January 2024

Conservation alternatives that include no-tillage (NT) and cover crops (CCs) reduce soil erosion in row-crop agroecosystems. However, little information is available about how these alternatives affect soil textural properties responsible for soil fertility. This study evaluated the soil particle size distribution and volumetric water content after three years of consistent management in a raised bed system. There were four treatment systems in a dryland maize/soybean rotation on a silt loam soil (Oxyaquic Fraglossudalfs) that included: NT + CCs, conventional tillage (CT) + CCs, CT + winter weeds, and CT + bare soil in winter in northwest Mississippi. The NT + CC system retained 62% more coarse sand in the furrow than the other systems (2.1% compared to 1.3%; p = 0.02). Regardless of the location, the NT + CC system (2.5%) retained 39% more fine sand than the CT + CC system (1.8%; p = 0.01), suggesting that coarse and fine sands were being trapped in furrows combining NT + CC systems, minimizing their off-site transport. In furrows, CCs increased soil volumetric water content by 47% compared to other winter covers. In beds, NT + CCs increased bed water contents by 20% compared to CT + CCs (17.1 to 14.3%; p < 0.01). Implementing conservation alternatives may promote the retention of sand fractions in silty loam soils that are important in supporting soil fertility and crop sustainability.
Selenium and Heavy Metals in Soil–Plant System in a Hydrogeochemical Province with High Selenium Content in Groundwater: A Case Study of the Lower Dniester Valley
Authors: Sheshnitsan Sergey , Golubkina Nadezhda , Sheshnitsan Tatiana , Murariu Otilia Cristina , Tallarita Alessio Vincenzo , Caruso Gianluca
Published: January 2024

The bioaccumulation of selenium (Se) and heavy metals (HMs) in plants is important because it can affect plant health and human nutrition. Recognizing the factors affecting Se accumulation in plants may have important implications for agricultural practices and human health in selenium-rich regions. The study primarily focused on the interactions between Se and HMs in the soil–plant system of the Lower Dniester Valley. Total concentrations of HMs (Cu, Mn, Zn) were determined by atomic absorption spectrometry, while Se concentrations were determined by a sensitive single-test-tube fluorometric method in solutions and extracts. Water-soluble Se (0.09 ± 0.03 mg·kg−1) in soils was 32.1% of the total Se (0.33 ± 0.13 mg·kg−1) and increased with the total rising Se content (r = 0.845). The results indicated that plants had a greater Zn accumulation capacity than that of the other HMs, suggesting its importance as a trace element for plant requirements. Se also had a high bioaccumulation rate. Se and Zn accumulation varied in different soil types, reflecting differences in bioavailability. In contrast, Mn and Cu showed low bioaccumulation, which varied with soil conditions and anthropogenic Cu pollution. Despite the Cu contamination of the soils in the investigated region, it can be inferred that the hydrogeochemical province with high Se content in groundwater has favorable conditions for Se mobilization in soils. The absence of antagonistic interactions with HMs in the soil–plant system contributes to the enhanced Se accumulation in plants in the Lower Dniester Valley. These results emphasize the complexity of the interactions between Se and HMs in the soil–plant system and their potential impact on agricultural practices.
Medicalization of Sport? A Mixed-Method Study on the Use of Medications in Elite Ice Hockey
Authors: Christensen Sofie , Gjelstad Astrid , Björnsdottir Ingunn , Lauritzen Fredrik
Published: January 2024

Ice hockey is a high-risk sport known for its dominant macho culture. The purpose of this study was to examine experiences surrounding medication use among male, elite ice hockey players in Norway. A mixed-method design was employed, which first examined medications registered on doping control forms (DCFs) (n = 177) and then involved semi-structured focus group interviews (n = 5) with elite athletes (n = 25). Overall, 68% of the DCFs contained information about ≥1 medication. Among the most registered medications were NSAIDs and hypnotics (20% and 19% of all DCFs, respectively). During the interviews, numerous athletes reported using analgesics to manage injuries and pain caused by the sport, often being motivated by sacrificing themselves for the team during important matches and playoffs. Hypnotics were used due to high cumulative stress due to heavy training and competition load, late-night matches, and playing in a semi-professional league. Athlete support personnel (ASP), including physicians and trainers, were the athletes’ main sources of information. The athletes often displayed a profound and non-critical trust in the advice and products provided to them by their team physician. The findings indicate that male, elite ice hockey players, through their excessive and somewhat ignorant use of medications, expose themselves to health risks and inadvertent doping.
Competition in Remanufacturing with Asymmetric Demand Information
Authors: Sun Yaqin , Shen Wenjing , Li Jiacan , Liao Yi
Published: January 2024

This paper examines remanufacturing decisions in the context of outsourcing, which have important implications for environmental and economic sustainability. Specifically, we model the competition between an experienced Original Equipment Manufacturer (OEM) and an emerging Independent Remanufacturer (IR). The OEM can decide the manufacturing quantities of a brand-new product, and the IR can collect the OEM’s used products and remanufacture them for resale. The information structure is asymmetric, as only the OEM knows the market size. We identify the equilibrium quantities of both firms, which are shown to be strongly influenced by the IR’s cost efficiency and the consumers’ willingness to pay for the IR’s products. Asymmetric information also plays an important role. Is it always better to hide information? Interestingly, the OEM makes the most profit when the IR has full information on the market size. We find that when the market size is high, the OEM’s and IR’s production and encroachment decisions are the same as when both parties have equal information. The OEM also does not benefit from hiding market information from the IR when the market size is low. Indeed, if the IR’s cost efficiency is moderate and the market size is low, the OEM’s profits are actually hurt by hiding market information. Here, the diminished profits from hiding market information arises from the OEM’s substantially reduced production quantity to prevent IR encroachment. The OEM’s production quantity is higher if the OEM shares market information and the IR encroaches on the market. Thus, by sharing information, the OEM’s benefit gained from increased production quantity outweighs the cost of losing its monopoly. Additionally, consumer surplus increases when the IR engages in remanufacturing, while social surplus increases only when either the OEM’s or IR’s product is strongly favored. Even if the IR does not engage in remanufacturing, the resulting OEM monopoly can still lead to a higher environmental impact under certain market conditions. This arises when the OEM lowers production quantities when the IR encroaches on the market, thereby improving the overall environmental impact. Therefore, policymakers seeking to improve environmental and economic sustainability by encouraging IRs must consider these complex competition dynamics and consumer preferences, as they indirectly influence OEMs’ production decisions.
Integrated Value Model for Sustainable Assessment of Modular Residential Towers: Case Study: Ten Degrees Croydon and Apex House in London
Authors: Maleki Bahareh , Casanovas-Rubio Maria del Mar , Tsavdaridis Konstantinos Daniel , de la Fuente Antequera Albert
Published: January 2024

Modular construction can become sustainable by making all aspects of the design and construction process more effective during all phases. This paper aims to develop and use a sustainability assessment model for modular residential buildings in two case studies. This research uses the Integrated Value Model for Sustainable Assessment (MIVES), which is a multi-criteria decision-making model for sustainability assessment. This model considers all aspects of sustainability, environmental, economic and social, and helps stakeholders make decisions. Few previous studies have assessed all these aspects in full and MIVES make this assessment possible. For assessment purposes, two modular buildings have been chosen, namely “Ten Degrees Croydon” as the tallest high-rise modular residential building in the world and “Apex House” as the second tallest modular building in the world, both in London. These residential towers were assessed using MIVES, demonstrating a very satisfactory sustainability index in all the above aspects.