bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Alternative Nutritional Source Hawthorn Vinegar: How It Interacts with Protein, Glucose and GLP-1
Authors: Seyidoglu Nilay , Karakçı Deniz , Ergin Eğritağ Hale , Yıkmış Seydi
Published: July 2024

(1) Background: There is a balance between nutrition, glycemic control, and immune response. Their roles in physiological mechanisms are essential for maintaining life quality. This study aimed to evaluate hawthorn vinegar’s metabolic effects, and describe its possible mechanism. We also pointed out several vinegar production methods to clarify the antioxidant features. (2) Methods: In the study, three vinegar techniques were applied to vinegar: traditional production of hawthorn vinegar (N), thermal pasteurization (P), and ultrasound method (U). Thirty-two female adult Wistar albino rats were randomly separated into four groups: Control, N1 (regular vinegar; 1 mL/kg bw), P1 (pasteurized vinegar; 1 mL/kg bw), and U1(ultrasound treated vinegar; 1 mL/kg bw). Vinegar was administered by oral gavage daily for 45 days. Initial and final weights, the percentage changes of body weight gains, and Gamma-Glutamyl Transferase (GGT) values of plasma and liver were measured. The total protein, globulin, and albumin values of plasma, liver, and intestinal tissue were determined. In addition, plasma glucagon-like peptide-1 (GLP-1) and glucose concentrations were evaluated. (3) Results: There was a statistical increase in total intestinal protein value and an increasing tendency in total protein in plasma and liver in group U1 compared to group Control. However, the GGT concentrations in plasma and liver were slightly lower in group U1 than in group Control. In addition, there were significant increases in plasma GLP-1 values in all experimental groups compared to the Control group (p: 0.015; 576.80 ± 56.06, 773.10 ± 28.92, 700.70 ± 17.05 and 735.00 ± 40.70; respectively groups control, N1, P1, and U1). Also, liver GLP-1 concentrations in groups P1 and U1 were higher than in group Control (p: 0.005; 968.00 ± 25.54, 1176 ± 17.54 and 1174.00 ± 44.06, respectively groups control, P1 and U1). On the other hand, significant decreases were found in plasma glucose concentrations in groups N1 and U1 as to the Control group (p: 0.02; Control: 189.90 ± 15.22, N1: 133.10 ± 7.32 and U1: 142.30 ± 4.14). Besides, liver glucose levels were lower in all experimental groups than in group Control statistically (p: 0.010; 53.47 ± 0.97, 37.99 ± 1.46, 44.52 ± 4.05 and 44.57 ± 2.39, respectively groups control, N1, P1, and U1). (4) Conclusions: The findings suggest that hawthorn vinegar can balance normal physiological conditions via intestinal health, protein profiles, and glycemic control. Additionally, ultrasound application of vinegar may improve the ability of hawthorn vinegar, and have positive effects on general health.
Citrullus mucosospermus Extract Reduces Weight Gain in Mice Fed a High-Fat Diet
Authors: Kang He Mi , Park Sun Young , Kim Ji Eun , Lee Ki Won , Hwang Dae Youn , Choi Young-Whan
Published: July 2024

This study aimed to investigate the therapeutic potential of Citrullus mucosospermus extract (CME) in counteracting adipogenesis and its associated metabolic disturbances in murine models. In vitro experiments utilizing 3T3-L1 preadipocytes revealed that CME potently inhibited adipocyte differentiation, as evidenced by a dose-dependent reduction in lipid droplet formation. Remarkably, CME also attenuated glucose uptake and intracellular triglyceride accumulation in fully differentiated adipocytes, suggesting its ability to modulate metabolic pathways in mature adipose cells. Translating these findings to an in vivo setting, we evaluated the effects of CME in C57BL/6N mice fed a high-fat diet (HFD) for 10 weeks. CME administration, concomitantly with the HFD, resulted in a significant attenuation of body weight gain compared to the HFD control group. Furthermore, CME treatment led to substantial reductions in liver weight, total fat mass, and deposits of visceral and retroperitoneal adipose tissue, underscoring its targeted impact on adipose expansion. Histological analyses revealed the remarkable effects of CME on hepatic steatosis. While the HFD group exhibited severe lipid accumulation within liver lobules, CME dose-dependently mitigated this pathology, with the highest dose virtually abolishing hepatic fat deposition. An examination of adipose tissue revealed a progressive reduction in adipocyte hypertrophy upon CME treatment, culminating in a near-normalization of adipocyte morphology at the highest dose. Notably, CME exhibited potent anti-inflammatory properties, significantly attenuating the upregulation of pro-inflammatory cytokines’ mRNA levels (TNF-α, IL-1β and IL-6) in the livers of HFD-fed mice. This suggests a potential mechanism through which CME may exert protective effects against inflammation associated with obesity and fatty liver disease.
Unveiling Moroccan Nature’s Arsenal: A Computational Molecular Docking, Density Functional Theory, and Molecular Dynamics Study of Natural Compounds against Drug-Resistant Fungal Infections
Authors: Yamari Imane , Abchir Oussama , Nour Hassan , Khedraoui Meriem , Rossafi Bouchra , Errougui Abdelkbir , Talbi Mohammed , Samadi Abdelouahid , Kouali MHammed El , Chtita Samir
Published: July 2024

Candida albicans and Aspergillus fumigatus are recognized as significant fungal pathogens, responsible for various human infections. The rapid emergence of drug-resistant strains among these fungi requires the identification and development of innovative antifungal therapies. We undertook a comprehensive screening of 297 naturally occurring compounds to address this challenge. Using computational docking techniques, we systematically analyzed the binding affinity of each compound to key proteins from Candida albicans (PDB ID: 1EAG) and Aspergillus fumigatus (PDB ID: 3DJE). This rigorous in silico examination aimed to unveil compounds that could potentially inhibit the activity of these fungal infections. This was followed by an ADMET analysis of the top-ranked compound, providing valuable insights into the pharmacokinetic properties and potential toxicological profiles. To further validate our findings, the molecular reactivity and stability were computed using the DFT calculation and molecular dynamics simulation, providing a deeper understanding of the stability and behavior of the top-ranking compounds in a biological environment. The outcomes of our study identified a subset of natural compounds that, based on our analysis, demonstrate notable potential as antifungal candidates. With further experimental validation, these compounds could pave the way for new therapeutic strategies against drug-resistant fungal pathogens.
Isolation of Alpha-Glucosidase Inhibitors from the Panamanian Mangrove Plant Mora oleifera (Triana ex Hemsl.) Ducke
Authors: Cherigo Lilia , Liao-Luo Javier , Fernández Juan , Martínez-Luis Sergio
Published: July 2024

Panama boasts an expansive mangrove area and stands as one of the most biodiverse countries in America. While mangrove plants have long been utilized in traditional medicine, there are still unstudied species whose potential medicinal applications remain unknown. This study aimed to extract bioactive compounds from Mora oleifera (Triana ex Hemsl.) Ducke, an understudied mangrove species. Through bioassay-guided fractionation of the crude extract, we isolated seven active compounds identified as lupenone (1), lupeol (2), α-amyrin (3), β-amyrin (4), palmitic acid (5), sitosterol (6), and stigmasterol (7). Compound structures were determined using spectroscopic analyses, including APCI-HR-MS and NMR. Compounds 1–7 displayed concentration-dependent inhibition of the alpha-glucosidase enzyme, with IC50 values of 0.72, 1.05, 2.13, 1.22, 240.20, 18.70, and 163.10 µM, respectively. Their inhibitory activity surpassed acarbose, the positive control (IC50 241.6 µM). Kinetic analysis revealed that all compounds acted as competitive inhibitors. Docking analysis predicted that all triterpenes bonded to the same site as acarbose in human intestinal alpha-glucosidase (PDB: 3TOP). A complementary metabolomic analysis of M. oleifera active fractions revealed the presence of 64 compounds, shedding new light on the plant’s chemical composition. These findings suggest that M. oleifera holds promise as a valuable botanical source for developing compounds for managing blood sugar levels in individuals with diabetes.
A Dynamic and Effective Peptide-Based Strategy for Promptly Addressing Emerging SARS-CoV-2 Variants of Concern
Authors: Murdocca Michela , Romeo Isabella , Citro Gennaro , Latini Andrea , Centofanti Federica , Bugatti Antonella , Caccuri Francesca , Caruso Arnaldo , Ortuso Francesco , Alcaro Stefano , Sangiuolo Federica , Novelli Giuseppe
Published: July 2024

Genomic surveillance based on sequencing the entire genetic code of SARS-CoV-2 involves monitoring and studying genetic changes and variations in disease-causing organisms such as viruses and bacteria. By tracing the virus, it is possible to prevent epidemic spread in the community, ensuring a ‘precision public health’ strategy. A peptide-based design was applied to provide an efficacious strategy that is able to counteract any emerging viral variant of concern dynamically and promptly to affect the outcomes of a pandemic at an early stage while waiting for the production of the anti-variant-specific vaccine, which require longer times. The inhibition of the interaction between the receptor-binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and one of the cellular receptors (DPP4) that its receptors routinely bind to infect human cells is an intriguing therapeutic approach to prevent the virus from entering human cells. Among the other modalities developed for this purpose, peptides surely offer unique advantages, including ease of synthesis, serum stability, low immunogenicity and toxicity, and small production and distribution chain costs. Here, we obtained a potent new inhibitor based on the rearrangement of a previously identified peptide that has been rationally designed on a cell dipeptidyl peptidase 4 (DPP4) sequence, a ubiquitous membrane protein known to bind the RBD-SPIKE domain of the virus. This novel peptide (named DPP4-derived), conceived as an endogenous “drug”, is capable of targeting the latest tested variants with a high affinity, reducing the VSV* DG-Fluc pseudovirus Omicron’s infection capacity by up to 14%, as revealed by in vitro testing in human Calu-3 cells. Surface plasmon resonance (SPR) confirmed the binding affinity of the new DPP4-derived peptide with Omicron variant RBD.
Physicochemical Compatibility of Ceftolozane-Tazobactam with Parenteral Nutrition
Authors: De Pourcq Jan Thomas , Riera Adria , Gras Laura , Garin Noe , Busquets Maria Antònia , Cardenete Joana , Cardona Daniel , Riera Pau
Published: July 2024

Ceftolozane-tazobactam (CT) is used for the treatment of complicated infections and for multidrug-resistant strains of Pseudomonas aeruginosa and extended-spectrum beta-lactamase-producing enterobacteria. In certain cases, simultaneous administration of CT and parenteral nutrition (PN) may be required, but compatibility of Y-site co-administration is unknown. The aim of this study was to analyse the physicochemical compatibility of CT Y-site administered with PN. We evaluated a protocolized PN approach for critical patients in our center. We studied both bolus infusion (2 g ceftolozane/1 g tazobactam in 1 h) and continuous infusion (CI) (6 g ceftolozane/3 g tazobactam) strategies. Samples were visually observed against light, microscopically inspected, and pH was analysed using a pH meter. The mean lipid droplet diameter (MDD) was determined via dynamic light scattering. CT concentration was quantified using HPLC–HRMS. No alterations were observed through visual or microscopic inspection. Changes in pH were ≤0.2, and changes in osmolarity were less than 5%. MDD remained below 500 nm (284.5 ± 2.1 for bolus CT and 286.8 ± 7.5 for CI CT). CT concentrations at t = 0 h and t = 24 h remained within prespecified parameters in both infusion strategies. CT is physiochemically compatible with PN during simulated Y-site administration at the tested concentration and infusion rates.
Pregnancy Recommendations Solely Based on Preclinical Evidence Should Be Integrated with Real-World Evidence: A Disproportionality Analysis of Certolizumab and Other TNF-Alpha Inhibitors Used in Pregnant Patients with Psoriasis
Authors: Gaio Mario , Vastarella Maria Giovanna , Sullo Maria Giuseppa , Scavone Cristina , Riccardi Consiglia , Campitiello Maria Rosaria , Sportiello Liberata , Rafaniello Concetta
Published: July 2024

Treatment for pregnant women with psoriasis is limited by the lack of information typically related to clinical trials. While anti-tumor necrosis factor (TNF) drugs offer therapeutic benefits, their safety during pregnancy is a concern. Notably, certolizumab is comparatively safer than adalimumab, etanercept, infliximab, and golimumab according to the current recommendations. Thus, this study aimed to conduct a pharmacovigilance comparative analysis of maternal and neonatal outcomes associated with certolizumab versus other anti-TNF drugs by using data from EudraVigilance. A descriptive analysis was performed of Individual Case Safety Reports (ICSRs) associated with an anti-TNF drug and related to the pregnant patients with psoriasis from 2009 and 2023, focusing our analysis on the specific pregnancy outcomes and fetal/neonatal disorders. The most common pregnancy-related adverse event was spontaneous abortion, predominantly related to adalimumab and certolizumab. Certolizumab was also reported in cases of caesarean section, gestational diabetes, abortion, fetal death, fetal distress syndrome, pre-eclampsia, and premature separation of placenta. Generally, the findings from our study depicted a safety profile that overlapped for each anti-TNF drug, both in maternal/neonatal outcomes and other adverse events, suggesting no substantial differences between treatments. We advocate for further investigations before making concrete recommendations.
Design of Thermosensitive Niosomes by Eutectic Mixture of Natural Fatty Acids
Authors: Mazzotta Elisabetta , Romeo Martina , Hafidi Zakaria , Perez Lourdes , Perrotta Ida Daniela , Muzzalupo Rita
Published: July 2024

In the current study, a smart release system responsive to temperature was developed to improve the efficiency of tetracycline (TC) in antibacterial therapy. The nanovesicles designed consist of a non-ionic surfactant, SPAN60, cholesterol and a phase change material (PCM) as a thermoresponsive gating material. Niosomes were prepared using an increasing amount of PCM and characterized in terms of size, zeta potential, colloidal stability and thermoresponsive properties. The vesicles that developed were homogenous in size, had good biocompatibility and stability for up to 3 months and demonstrated thermoresponsive behavior. A low drug leakage was observed at 37 °C, while a rapid release occurred at 42 °C, due to the faster diffusion rate of the drug trough the melted PCM. This controllable drug release capacity allows us to avoid premature drug release, minimizing unwanted and toxic effects and ensuring a long retention time in the nanodevice so that it reaches the infected sites. In addition, TC-loaded niosomes were screened to investigate their antibacterial activity against various Gram-positive and Gram-negative bacteria by minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assays. An interesting temperature-dependent antibacterial activity was observed against some bacterial strains: the niosomes activity against S. epidermis, for example, was improved by the temperature increase, as suggested by a reduction in MIC values from 112.81 to 14.10 μM observed at 37 and 42 °C, respectively. Taken together, the thermoresponsive platform developed allows us to use lower antibiotic amounts while ensuring therapeutic efficacy and, so, will advance the development of a novel antibacterial agent in clinical practice.
Flexible Resistive Gas Sensor Based on Molybdenum Disulfide-Modified Polypyrrole for Trace NO2 Detection
Authors: Zhao Kuo , Shi Yunbo , Cui Mingrui , Tang Bolun , Zheng Canda , Chen Qinglong , Hu Yuhan
Published: July 2024

High sensitivity and selectivity and short response and recovery times are important for practical conductive polymer gas sensors. However, poor stability, poor selectivity, and long response times significantly limit the applicability of single-phase conducting polymers, such as polypyrrole (PPy). In this study, PPy/MoS2 composite films were prepared via chemical polymerization and mechanical blending, and flexible thin-film resistive NO2 sensors consisting of copper heating, fluorene polyester insulating, and PPy/MoS2 sensing layers with a silver fork finger electrode were fabricated on a flexible polyimide substrate using a flexible electronic printer. The PPy/MoS2 composite films were characterized using X-ray diffraction, Fourier-transform infrared spectroscopy, and field-emission scanning electron microscopy. A home-built gas sensing test platform was built to determine the resistance changes in the composite thin-film sensor with temperature and gas concentration. The PPy/MoS2 sensor exhibited better sensitivity, selectivity, and stability than a pure PPy sensor. Its response to 50 ppm NO2 was 38% at 150 °C, i.e., 26% higher than that of the pure PPy sensor, and its selectivity and stability were also higher. The greater sensitivity was attributed to p–n heterojunction formation after MoS2 doping and more gas adsorption sites. Thus, PPy/MoS2 composite film sensors have good application prospects.
Effect of Glycerol and Sisal Nanofiber Content on the Tensile Properties of Corn Starch/Sisal Nanofiber Films
Authors: de Vilhena Mailson Batista , Paula Marcos Vinícius da Silva , de Oliveira Raul Costa , Estumano Diego Cardoso , Viegas Bruno Marques , Rodrigues Emerson Cardoso , Macêdo Emanuel Negrão , Souza José Antônio da Silva , Cunha Edinaldo José de Sousa
Published: July 2024

Currently, petroleum-derived plastics are widely used despite the disadvantage of their long degradation time. Natural polymers, however, can be used as alternatives to overcome this obstacle, particularly cornstarch. The tensile properties of cornstarch films can be improved by adding plant-derived nanofibers. Sisal (Agave sisalana), a very common low-cost species in Brazil, can be used to obtain plant nanofibers. The goal of this study was to obtain sisal nanofibers using low concentrations of sulfuric acid to produce thermoplastic starch nanocomposite films. The films were produced by a casting technique using commercial corn starch, glycerol, and sisal nanofibers, accomplished by acid hydrolysis. The effects of glycerol and sisal nanofiber content on the tensile mechanical properties of the nanocomposites were investigated. Transmission electron microscopy findings demonstrated that the lowest concentration of sulfuric acid produced fibers with nanometric dimensions related to the concentrations used. X-ray diffraction revealed that the untreated fibers and fibers subjected to acid hydrolysis exhibited a crystallinity index of 61.06 and 84.44%, respectively. When the glycerol and nanofiber contents were 28 and 1%, respectively, the tensile stress and elongation were 8.02 MPa and 3.4%. In general, nanocomposites reinforced with sisal nanofibers showed lower tensile stress and higher elongation than matrices without nanofibers did. These results were attributed to the inefficient dispersion of the nanofibers in the polymer matrix. Our findings demonstrate the potential of corn starch nanocomposite films in the packaging industry.
Towards Sustainable Temperature Sensor Production through CO2-Derived Polycarbonate-Based Composites
Authors: Martín-Ayerdi Ane , Rubio-Peña Luis , Peřinka Nikola , Oyarzabal Itziar , Vilas José L. , Costa Pedro , Lanceros-Méndez Senentxu
Published: July 2024

The steep increase in carbon dioxide (CO2) emissions has created great concern due to its role in the greenhouse effect and global warming. One approach to mitigate CO2 levels involves its application in specific technologies. In this context, CO2 can be used for a more sustainable synthesis of polycarbonates (CO2-PCs). In this research, CO2-PC films and composites with multiwalled carbon nanotubes (MWCNTs, ranging from 0.2 to 7.0 wt.%) have been prepared to achieve more sustainable multifunctional sensing devices. The inclusion of the carbonaceous fillers allows for the electrical conductivity to be enhanced, reaching the percolation threshold (Pc) at 0.1 wt.% MWCNTs and a maximum electrical conductivity of 0.107 S·m−1 for the composite containing 1.5 wt.% MWCNTs. The composite containing 3.0 wt.% MWCNTs was also studied, showing a stable and linear response under temperature variations from 40 to 100 °C and from 30 to 45 °C, with a sensitivity of 1.3 × 10−4 °C−1. Thus, this investigation demonstrates the possibility of employing CO2-derived PC/MWCNT composites as thermoresistive sensing materials, allowing for the transition towards sustainable polymer-based electronics.
Preparation and Structure–Property Relationship Study of Piezoelectric–Conductive Composite Polymer Nanofiber Materials for Bone Tissue Engineering
Authors: Jin Zhengyang , Wei Suiyan , Jin Wenyang , Lu Bingheng , Xu Yan
Published: July 2024

This study aimed to develop Janus-, cross-network-, and coaxial-structured piezoelectric–conductive polymer nanofibers through electrospinning to mimic the piezoelectricity of bone and facilitate the conduction of electrical signals in bone tissue repair. These nanofibers were constructed using the piezoelectric polymer polyvinylidene fluoride, and the conductive fillers reduced graphene oxide and polypyrrole. The influence of structural features on the electroactivity of the fibers was also explored. The morphology and components of the various structural samples were characterized using SEM, TEM, and FTIR. The electroactivity of the materials was assessed with a quasi-static d33 meter and the four-probe method. The results revealed that the piezoelectric–conductive phases were successfully integrated. The Janus-structured nanofibers demonstrated the best electroactivity, with a piezoelectric constant d33 of 24.5 pC/N and conductivity of 6.78 × 10−2 S/m. The tensile tests and MIP measurements showed that all samples had porosity levels exceeding 70%. The tensile strength of the Janus and cross-network structures exceeded that of the periosteum (3–4 MPa), with average pore sizes of 1194.36 and 2264.46 nm, respectively. These properties indicated good mechanical performance, allowing material support while preventing fibroblast invasion. The CCK-8 and ALP tests indicated that the Janus-structured samples were biocompatible and significantly promoted the proliferation of MC3T3-E1 cells.
Sound Absorption Performance of Ultralight Honeycomb Sandwich Panels Filled with “Network” Fibers—Juncus effusus
Authors: Liu Zhao , Dong Chenhao , Tong Lu , Rudd Chris , Yi Xiaosu , Liu Xiaoling
Published: July 2024

This study investigates lightweight and efficient candidates for sound absorption to address the growing demand for sustainable and eco-friendly materials in noise attenuation. Juncus effusus (JE) is a natural fiber known for its unique three-dimensional network, providing a viable and sustainable filler for enhanced sound absorption in honeycomb panels. Microperforated-panel (MPP) honeycomb absorbers incorporating JE fillers were fabricated and designed, focusing on optimizing the absorber designs by varying JE filler densities, geometrical arrangements, and MPP parameters. At optimal filling densities, the MPP-type honeycomb structures filled with JE fibers achieved high noise reduction coefficients (NRC) of 0.5 and 0.7 at 20 mm and 50 mm thicknesses, respectively. Using an analytical model and an artificial neural network (ANN) model, the sound absorption characteristics of these absorbers were successfully predicted. This study demonstrates the potential of JE fibers in improving noise mitigation strategies across different industries, offering more sustainable and efficient solutions for construction and transportation.
Introduction to the Soundscapes of Religion
Authors: Povedák Kinga , Kajanová Yvetta
Published: July 2024

When listening to religious music, what do you perceive more: aesthetics or spirituality [...]
The Intersection of Resonant Listening and Preaching That Resonates Daily, Alluding to Listeners’ Memories and Their Meaning-Making Efforts
Authors: Kruger Ferdi Petrus
Published: July 2024

This article explores resonant listening as an integral aspect of preaching, transcending physical church spaces. It underscores the active engagement of listeners in participatory listening to grasp the essence of a sermon. Resonant listening, characterised by an attentive disposition intertwined with individuals’ recollections of God’s redemptive acts and everyday experiences, is crucial for sense-making in life. The research question guiding this exploration is: “How can an elucidation of resonant listening connected to listeners’ remembrances and their endeavour to make sense of life enable them to find meaning?” Drawing on Osmer’s research methodology, the article begins with the descriptive empirical phase, investigating the dynamics of resonant listening among listeners. It then delves into insights from communication sciences and social psychology, elucidating the significance of resonant listening and memory in decision-making processes. Moreover, it offers normative perspectives through an examination of John 4, analysing cognitive triggers, memories, and the outcomes of resonant listening in Jesus’s interaction with the Samaritan woman. Finally, the article concludes by intertwining hermeneutical reflections with homiletical perspectives, highlighting the indispensable role of resonant listening in effective preaching.
Religious/Spiritual Abuse, Meaning-Making, and Posttraumatic Growth
Authors: Perry Sarah
Published: July 2024

While religion and spirituality (R/S) have been broadly studied for their positive mental health impacts, instances of abuse within religious or spiritual contexts remain under-researched. This scoping review aims to elucidate how individuals experiencing such abuse navigate their trauma, find meaning, and foster posttraumatic growth (PTG). The research was conducted using a scoping review methodology as a guide, and 10 articles were selected based on predefined inclusion and exclusion criteria. Synthesizing these articles revealed the following three central themes: recognizing abuse, relaying one’s story, and redefining spirituality. Survivors often face disbelief and stigma, hindering their ability to process their experiences. However, narrative sharing enables many to reclaim agency and healing through validation and the integration of the narrative into one’s life story. Additionally, survivors often transform spirituality, shifting from rigid frameworks to more nuanced and flexible understandings of the Divine and self. These findings underscore the importance of trauma-informed, spiritually sensitive clinical approaches that validate survivors’ experiences, facilitate narrative sharing, and support spiritual redefining. Future research must address knowledge gaps, including the development of improved assessment tools, exploration of effective treatment strategies, and the unifying of terms to better support survivors’ healing journeys and promote meaning-making and PTG in the aftermath of R/S abuse.
Polar Sea Ice Monitoring Using HY-2B Satellite Scatterometer and Scanning Microwave Radiometer Measurements
Authors: Zeng Tao , Shi Lijian , Shi Yingni , Lu Dunwang , Wang Qimao
Published: July 2024

The Ku band microwave scatterometer (SCA) and scanning microwave radiometer (SMR) onboard HaiYang-2B (HY-2B) can simultaneously supply active and passive microwave observations over the polar region. In this paper, a polar ice water discrimination model and Arctic sea-ice-type classification model based on the support vector machine (SVM) method were established and used to produce a daily sea ice extent dataset from 2019 to 2021 with data from SCA and SMR. First, suitable scattering and radiation parameters are chosen as input data for the discriminant model. Then, the sea ice extent was obtained based on the monthly ice water discrimination model, and finally, the ice over the Arctic was classified into multiyear ice (MYI) and first-year ice (FYI). The 3-year ice extent and MYI extent products were consistent with the similar results of the National Snow and Ice Data Center (NSIDC) and Ocean and Sea Ice Satellite Application Facility (OSISAF). Using the OSISAF similar product as validation data, the overall accuracies (OAs) of ice/water discrimination and FYI/MYI discrimination are 99% and 97%, respectively. Compared with the high spatial resolution classification results of the Moderate Resolution Imaging Spectroradiometer (MODIS) and SAR, the OAs of ice/water discrimination and FYI/MYI discrimination are 96% and 86%, respectively. In conclusion, the SAC and SMR of HY-2B have been verified for monitoring polar sea ice, and the sea ice extent and sea-ice-type products are promising for integration into long-term sea ice records.
A Robust Tie-Points Matching Method with Regional Feature Representation for Synthetic Aperture Radar Images
Authors: Zhang Yifan , Zhu Yan , Liu Liqun , Du Xun , Han Kun , Wu Junhui , Li Zhiqiang , Kong Lingshuai , Lin Qiwei
Published: July 2024

The precise tie-points (TPs) on synthetic aperture radar (SAR) images are a critical cornerstone in the global digital elevation model (DEM) and digital ortho map (DOM) production process. While there are abundant studies on SAR TPs matching, improvement opportunities persist in large areas. The correspondences have pixel-level errors during geocoding, which result in misalignment between global products. Consequently, this paper proposed a robust method for SAR images TPs matching, which consists of three key steps: (1) interest point extraction based on the dynamic Harris area entropy (DHAE) grid; (2) adaptive determination of template size; (3) normalized cross correlation (NCC) template matching. DHAE is a regional texture information grid based on the SAR-Harris map, and it is achieved through dynamic block division. Generating the DHAE grid over SAR images enables the extraction of interest points that have regional feature representation and distribution uniformity. A variable-size matching template is adaptively determined based on DHAE to enhance template quality while maintaining computational efficiency. Subsequently, the NCC algorithm is employed to find subpixel-precise correspondences. The proposed method is applied on TPs matching in 57 Terra-SAR images, which cover a large geographical area. Furthermore, the overlapping area is partitioned into five segments according to different coverage types. The experimental results demonstrate that the proposed method outperforms other template matching methods. For all coverage types, the proposed method exhibits high-precision sub-pixel results that reach up to 38.64% in terms of the relative positioning error (RPE), particularly in texture-weak and large areas.
2D3D-DescNet: Jointly Learning 2D and 3D Local Feature Descriptors for Cross-Dimensional Matching
Authors: Chen Shuting , Su Yanfei , Lai Baiqi , Cai Luwei , Hong Chengxi , Li Li , Qiu Xiuliang , Jia Hong , Liu Weiquan
Published: July 2024

The cross-dimensional matching of 2D images and 3D point clouds is an effective method by which to establish the spatial relationship between 2D and 3D space, which has potential applications in remote sensing and artificial intelligence (AI). In this paper, we propose a novel multi-task network, 2D3D-DescNet, to learn 2D and 3D local feature descriptors jointly and perform cross-dimensional matching of 2D image patches and 3D point cloud volumes. The 2D3D-DescNet contains two branches with which to learn 2D and 3D feature descriptors, respectively, and utilizes a shared decoder to generate the feature maps of 2D image patches and 3D point cloud volumes. Specifically, the generative adversarial network (GAN) strategy is embedded to distinguish the source of the generated feature maps, thereby facilitating the use of the learned 2D and 3D local feature descriptors for cross-dimensional retrieval. Meanwhile, a metric network is embedded to compute the similarity between the learned 2D and 3D local feature descriptors. Finally, we construct a 2D-3D consistent loss function to optimize the 2D3D-DescNet. In this paper, the cross-dimensional matching of 2D images and 3D point clouds is explored with the small object of the 3Dmatch dataset. Experimental results demonstrate that the 2D and 3D local feature descriptors jointly learned by 2D3D-DescNet are similar. In addition, in terms of 2D and 3D cross-dimensional retrieval and matching between 2D image patches and 3D point cloud volumes, the proposed 2D3D-DescNet significantly outperforms the current state-of-the-art approaches based on jointly learning 2D and 3D feature descriptors; the cross-dimensional retrieval at TOP1 on the 3DMatch dataset is improved by over 12%.
Impact of Plasma Bubbles on OTHR Shortwave Propagation in Different Backgrounds
Authors: Ma Xin , Guo Peng , Yang Ding , Wu Mengjie , Yue Hengyi
Published: July 2024

Plasma bubbles represent notable ionospheric irregularities primarily observed in low latitudes, characterized by plasma depletions exhibiting large spatial scales, which can make a significant impact on the propagation of OTHR (over-the-horizon radar) waves. Firstly, we constructed a three-dimensional model of plasma bubbles, which is modulated by Gaussian function distribution in the horizontal direction, and then we analyzed the impact of EPBs (Equatorial Plasma Bubbles) on the ray path of OTHR shortwaves. When radio waves propagate through EPBs with different RMS ΔN/N, there is a significant difference in the propagation path of OTHR waves. For the EPB with an RMS ΔN/N of 75%, radio waves exhibit more pronounced refraction than those with lower RMS values, the focusing effect of radio waves is more obvious, and the focusing point is relatively lower. In terms of different seasons, OTHR shortwaves propagating through EPBs exhibit different degrees of refraction. In addition, radio waves show the effect of inward focusing in different seasons: the focusing effect is the most pronounced in spring, followed by autumn, then summer, and the weakest in winter. For different solar activities, the impact of EPBs on OTHR shortwaves is more significant in the high-solar-activity year.
Remote Sensing Guides Management Strategy for Invasive Legumes on the Central Plateau, New Zealand
Authors: Peterson Paul G. , Shepherd James D. , Hill Richard L. , Davey Craig I.
Published: July 2024

Remote sensing was used to map the invasion of yellow-flowered legumes on the Central Plateau of New Zealand to inform weed management strategy. The distributions of Cytisus scoparius (broom), Ulex europaeus (gorse) and Lupinus arboreus (tree lupin) were captured with high-resolution RGB photographs of the plants while flowering. The outcomes of herbicide operations to control C. scoparius and U. europaeus over time were also assessed through repeat photography and change mapping. A grid-square sampling tool previously developed by Manaaki Whenua—Landcare Research was used to help transfer data rapidly from photography to maps using manual classification. Artificial intelligence was trialled and ruled out because the number of false positives could not be tolerated. Future actions to protect the natural values and vistas of the Central Plateau from legume invasion were identified. While previous control operations have mostly targeted large, highly visible legume patches, the importance of removing outlying plants to prevent the establishment of new seed banks and slow spread has been underestimated. Outliers not only establish new, large, long-lived seed banks in previously seed-free areas, but they also contribute more to range expansion than larger patches. Our C. scoparius and U. europaeus change mapping confirms and helps to visualise the establishment and expansion of uncontrolled outliers. The power of visualizing weed control strategies through remote sensing has supported recommendations to improve outlier control to achieve long-term, sustainable landscape-scale suppression of invasive legumes.
Predicting the Arousal and Valence Values of Emotional States Using Learned, Predesigned, and Deep Visual Features
Authors: Joudeh Itaf Omar , Cretu Ana-Maria , Bouchard Stéphane
Published: July 2024

The cognitive state of a person can be categorized using the circumplex model of emotional states, a continuous model of two dimensions: arousal and valence. The purpose of this research is to select a machine learning model(s) to be integrated into a virtual reality (VR) system that runs cognitive remediation exercises for people with mental health disorders. As such, the prediction of emotional states is essential to customize treatments for those individuals. We exploit the Remote Collaborative and Affective Interactions (RECOLA) database to predict arousal and valence values using machine learning techniques. RECOLA includes audio, video, and physiological recordings of interactions between human participants. To allow learners to focus on the most relevant data, features are extracted from raw data. Such features can be predesigned, learned, or extracted implicitly using deep learners. Our previous work on video recordings focused on predesigned and learned visual features. In this paper, we extend our work onto deep visual features. Our deep visual features are extracted using the MobileNet-v2 convolutional neural network (CNN) that we previously trained on RECOLA’s video frames of full/half faces. As the final purpose of our work is to integrate our solution into a practical VR application using head-mounted displays, we experimented with half faces as a proof of concept. The extracted deep features were then used to predict arousal and valence values via optimizable ensemble regression. We also fused the extracted visual features with the predesigned visual features and predicted arousal and valence values using the combined feature set. In an attempt to enhance our prediction performance, we further fused the predictions of the optimizable ensemble model with the predictions of the MobileNet-v2 model. After decision fusion, we achieved a root mean squared error (RMSE) of 0.1140, a Pearson’s correlation coefficient (PCC) of 0.8000, and a concordance correlation coefficient (CCC) of 0.7868 on arousal predictions. We achieved an RMSE of 0.0790, a PCC of 0.7904, and a CCC of 0.7645 on valence predictions.
Feature Extraction Methods for Underwater Acoustic Target Recognition of Divers
Authors: Sun Yuchen , Chen Weiyi , Shuai Changgeng , Zhang Zhiqiang , Wang Pingbo , Cheng Guo , Yu Wenjing
Published: July 2024

The extraction of typical features of underwater target signals and excellent recognition algorithms are the keys to achieving underwater acoustic target recognition of divers. This paper proposes a feature extraction method for diver signals: frequency−domain multi−sub−band energy (FMSE), aiming to achieve accurate recognition of diver underwater acoustic targets by passive sonar. The impact of the presence or absence of targets, different numbers of targets, different signal−to−noise ratios, and different detection distances on this method was studied based on experimental data under different conditions, such as water pools and lakes. It was found that the FMSE method has the best robustness and performance compared with two other signal feature extraction methods: mel frequency cepstral coefficient filtering and gammatone frequency cepstral coefficient filtering. Combined with the commonly used recognition algorithm of support vector machines, the FMSE method can achieve a comprehensive recognition accuracy of over 94% for frogman underwater acoustic targets. This indicates that the FMSE method is suitable for underwater acoustic recognition of diver targets.
Graph Feature Refinement and Fusion in Transformer for Structural Damage Detection
Authors: Hu Tianjie , Ma Kejian , Xiao Jianchun
Published: July 2024

Structural damage detection is of significance for maintaining the structural health. Currently, data-driven deep learning approaches have emerged as a highly promising research field. However, little progress has been made in studying the relationship between the global and local information of structural response data. In this paper, we have presented an innovative Convolutional Enhancement and Graph Features Fusion in Transformer (CGsformer) network for structural damage detection. The proposed CGsformer network introduces an innovative approach for hierarchical learning from global to local information to extract acceleration response signal features for structural damage representation. The key advantage of this network is the integration of a graph convolutional network in the learning process, which enables the construction of a graph structure for global features. By incorporating node learning, the graph convolutional network filters out noise in the global features, thereby facilitating the extraction to more effective local features. In the verification based on the experimental data of four-story steel frame model experiment data and IASC-ASCE benchmark structure simulated data, the CGsformer network achieved damage identification accuracies of 92.44% and 96.71%, respectively. It surpassed the existing traditional damage detection methods based on deep learning. Notably, the model demonstrates good robustness under noisy conditions.
Adaptive Disturbance Suppression Method for Servo Systems Based on State Equalizer
Authors: Li Jinzhao , Li Yonggang , Li Xiantao , Mao Dapeng , Zhang Bao
Published: July 2024

Disturbances in the aviation environment can compromise the stability of the aviation optoelectronic stabilization platform. Traditional methods, such as the proportional integral adaptive robust (PI + ARC) control algorithm, face a challenge: once high-frequency disturbances are introduced, their effectiveness is constrained by the control system’s bandwidth, preventing further stability enhancement. A state equalizer speed closed-loop control algorithm is proposed, which combines proportional integral adaptive robustness with state equalizer (PI + ARC + State equalizer) control algorithm. This new control structure can suppress high-frequency disturbances caused by mechanical resonance, improve the bandwidth of the control system, and further achieve fast convergence and stability of the PI + ARC algorithm. Experimental results indicate that, in comparison to the control algorithm of PI + ARC, the inclusion of a state equalizer speed closed-loop compensation in the model significantly increases the closed-loop bandwidth by 47.6%, significantly enhances the control system’s resistance to disturbances, and exhibits robustness in the face of variations in the model parameters and feedback sensors of the control object. In summary, integrating a state equalizer speed closed-loop with PI + ARC significantly enhances the suppression of high-frequency disturbances and the performance of control systems.
Research on Gate Opening Control Based on Improved Beetle Antennae Search
Authors: Wang Lijun , Wang Yibo , Kang Yehao , Shen Jie , Cheng Ruixue , Zhang Jianyong , Shi Shuheng
Published: July 2024

To address the issues of sluggish response and inadequate precision in traditional gate opening control systems, this study presents a novel approach for direct current (DC) motor control utilizing an enhanced beetle antennae search (BAS) algorithm to fine-tune the parameters of a fuzzy proportional integral derivative (PID) controller. Initially, the mathematical model of the DC motor drive system is formulated. Subsequently, employing a search algorithm, the three parameters of the PID controller are optimized in accordance with the control requirements. Next, software simulation is employed to analyze the system’s response time and overshoot. Furthermore, a comparative analysis is conducted between fuzzy PID control based on the improved beetle antennae search algorithm, and conventional approaches such as the traditional beetle antennae search algorithm, the traditional particle swarm algorithm, and the enhanced particle swarm algorithm. The findings indicate the superior performance of the proposed method, characterized by reduced oscillations and accelerated convergence compared to the alternative methods.
Decision-Making Approach to Design a Sustainable Photovoltaic Closed-Loop Supply Chain Considering Market Share for Electric Vehicle Energy
Authors: Shenabi Hadi , Sahraeian Rashed
Published: July 2024

This study aims to develop a model for the closed-loop supply chain of photovoltaic (PV) systems. The primary objective addresses strategic and tactical decision-making using a two-stage approach. To pinpoint suitable locations for solar power plants, the PROMETHEE II method is utilized, which is a component of multi-attribute decision making (MADM) approaches. Next, a multi-objective modeling of the closed-loop PV supply chain is conducted. This model aims to minimize total supply chain costs, reduce environmental impacts, mitigate adverse social effects, maximize the on-time delivery (OTD) of manufactured products, and maximize market share. Additionally, a robust fuzzy mathematical model is introduced to examine the model’s sustainability under various uncertainties. An evaluation of the effectiveness and utility of this model is conducted in Tehran city. Furthermore, a comprehensive analysis of various supply chain costs indicates that production centers have the highest costs, while separation centers have the lowest costs.
Synergistic Effects of Azospirillum brasilense and Nitrogen Doses on Wheat Flour Characteristics and Yields of Reducing Sugars Obtained by Subcritical Water Hydrolysis from Bran
Authors: Zabot Giovani L. , Martins Luciano O. , Oro Carolina E. Demaman , dos Santos Maicon S. N. , Wancura João H. , Pfeifenberg Renan , Machado Tainah da R. , Rusch Leonardo , Friedrich Larissa , Assunção Rafaela M. , da Rosa Ricardo B. , Bittencourt João M. L. , Knies Alberto E. , da Silva Francini B. , Tres Marcus V.
Published: July 2024

The synergistic interactions between nitrogen doses and microbial inoculation in crops indicate the potential for integrated nutrient management strategies in plant cultivation. Therefore, this study investigated the interactive effects of nitrogen doses and Azospirillum brasilense inoculation on wheat flour characteristics in terms of the falling number and color parameters and yields of reducing sugars obtained by subcritical water hydrolysis (SWH) from wheat bran. The strip-plot experimental design, bifactorial with three replications, was applied. Factor A was three wheat cultivars: ORS Agile (AGI), ORS Feroz (FER), and TSZ Dominadore (DOM). Factor D was five nitrogen doses in the topdressing: 0, 20, 40, 60, and 80 kg ha−1. The lowest value of falling number of 332 s was achieved with flour from FER cultivar using a nitrogen dose of 80 kg ha−1 with A. brasilense inoculation. The SWH produced yields of reducing sugars (YRS) from wheat bran of up to 6.74 ± 0.18 g (100 g of wheat bran)−1 for the cultivar DOM when using a nitrogen dose of 60 kg ha−1 associated with A. brasilense inoculation. In this cultivation condition, the falling number was 408 s and the color parameters were L* of 92.49, a* of −0.26, and b* of 11.91. In the other conditions, the YRS ranged from 2.93 ± 0.63 to 6.52 ± 0.04 g (100 g of wheat bran)−1. Both flour and bran are nutritional products with high application potential, and this study indicated SWH as a promising technique to dissociate the lignocellulosic complex of wheat bran without using hazardous solvents.