bluuebunny/crossref_metadata_2025 huggingface dataset:
Insights into Catechin–Copper Complex Structure and Biologic Activity Modulation
Authors: Lungu Ionut I. , Cioanca Oana , Mircea Cornelia , Tuchilus Cristina , Stefanache Alina , Huzum Riana , Hancianu Monica
Published: October 2024

Compounds of natural origin found in varying quantities in plant-based products constitute a highly significant category, possessing structural significance as well as the capacity to regulate oxidative processes. The activity of these compounds may be modulated by the composition of the biological environment in which they operate, the pH of the environment, or the presence of metal cations in plants or plant extracts. A successful complexation reaction was mainly confirmed by FT-IR, observing the shift from the original transmittance of catechin bonds, especially O-H ones. This work shows the synthetic methodology and the optimization process that took place to synthesize a catechin–copper complex, which demonstrated antioxidant activity. It was tested for iron chelation ability, hydroxyl radicals, and the inhibition of lipoxygenase (15-LOX). An antidiabetic assay was performed by determining the inhibition of alpha-amylase and alpha-glucosidase, finding that the synthesized complex had similar inhibitory potential as pure catechin. The antibacterial tests showed results against Staphylococcus aureus and the antifungal properties of the complex against Candida albicans.
A Review of Stoichiometric Nickel Sulfide-Based Catalysts for Hydrogen Evolution Reaction in Alkaline Media
Authors: Choi Yeji , Lee Jun-Hee , Youn Duck Hyun
Published: October 2024

Efficient and cost-effective catalysts for hydrogen evolution reaction (HER) are essential for large-scale hydrogen production, which is a critical step toward reducing carbon emissions and advancing the global transition to sustainable energy. Nickel sulfide-based catalysts, which exist in various stoichiometries, show promise for HER in alkaline media. However, as single-phase materials, they do not demonstrate superior activity compared to Pt-based catalysts. This review highlights recent strategies to enhance the HER performance of nickel sulfides, including heteroatom doping, heterostructure construction, and vacancy engineering, tailored to their different stoichiometric ratios. The study also examines synthesis methods, characterizations, and their impact on HER performance. Furthermore, it discusses the challenges and limitations of current research and suggests future directions for improvement.
Development and Pilot Study of myfood24 West Africa—An Online Tool for Dietary Assessment in Nigeria
Authors: Uzokwe Chinwe Adaugo , Nkwoala Chiaka Charles , Ebenso Bassey E. , Beer Sarah , Williams Grace , Iheme Gideon Onyedikachi , Opara Chihurumnanya Gertrude , Sanusi Rasaki A. , Ene-Obong Henrietta Nkechi , Cade Janet E.
Published: October 2024

Background and objective: Tools to accurately and efficiently measure dietary intake in Nigeria are lacking. We aimed to develop and assess the usability of a new online dietary assessment tool for Nigeria—myfood24 West Africa. Methods: We developed the myfood24 West Africa database using data from existing food composition tables, packaged foods labels and research articles. The development followed seven steps: identified data sources, selected foods, processed/cleaned the data, calculated the nutrient content of recipes, created and allocated portion sizes, quality-checked the database and developed food accompaniments. To pilot the tool, we recruited 179 university staff in Nigeria using a cross-sectional design. Usability was assessed using a questionnaire that included the System Usability Scale (SUS) and a feedback session. Results: The database included 924 foods, with up to 54 nutrients and 35 portion-size images allocated to foods. Sixty percent of the data were sourced from the 2019 West Africa Food Composition Table, 17% from back-of-pack labels of packaged foods, 14% from the 2017 Nigerian Food Composition Table, 5% from generated recipes and 4% from the published literature. Of the participants, 30% (n = 53) self-recorded their food intake, with a total of 1345 food and drink entries from both self- and interviewer-collected data. The mean SUS score of 74 (95% CI: 68,79) indicated good usability. The feedback showed that the tool was user-friendly, educational and included a variety of local foods. Conclusions: This new tool will enhance the dietary assessment of the Nigerian population. More work will expand coverage to include more foods from the region.
Metabolite, Biochemical, and Dietary Intake Alterations Associated with Lifestyle Interventions in Obese and Overweight Malaysian Women
Authors: Saparuddin Fatin , Mohd Nawi Mohd Naeem , Ahmad Zamri Liyana , Mansor Fazliana , Md Noh Mohd Fairulnizal , Omar Mohd Azahadi , Abdul Aziz Nur Shahida , Wahab Norasyikin A. , Mediani Ahmed , Rajab Nor Fadilah , Sharif Razinah
Published: October 2024

Differences in metabolic regulation among obesity phenotypes, specifically metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) women, may lead to varied responses to interventions, which could be elucidated through metabolomics. Therefore, this study aims to investigate the differences in metabolite profiles between MHO and MUO women and the changes following a lifestyle intervention. Serum samples from 36 MHO and 34 MUO women who participated in a lifestyle intervention for weight loss were analysed using untargeted proton nuclear magnetic resonance spectroscopy (1H NMR) at baseline and 6 months post-intervention. Anthropometric, clinical, and dietary intake parameters were assessed at both time points. Both groups showed differential metabolite profiles at baseline and after six months. Seven metabolites, including trimethylamine-N-oxide (TMAO), arginine, ribose, aspartate, carnitine, choline, and tyrosine, significantly changed between groups post-intervention, which all showed a decreasing pattern in MHO. Significant reductions in body weight and body mass index (BMI) in the MUO correlated with changes in the carnitine and tyrosine levels. In conclusion, metabolite profiles differed significantly between MHO and MUO women before and after a lifestyle intervention. The changes in carnitine and tyrosine levels in MUO were correlated with weight loss, suggesting potential targets for therapeutic intervention.
Phenome-Wide Analysis of Coffee Intake on Health over 20 Years of Follow-Up Among Adults in Hong Kong Osteoporosis Study
Authors: Mak Jonathan K. L. , Chau Yin-Pan , Tan Kathryn Choon-Beng , Kung Annie Wai-Chee , Cheung Ching-Lung
Published: October 2024

Background/Objectives: There has been limited evidence on the long-term impacts of coffee intake on health. We aimed to investigate the association between coffee intake and the incidence of diseases and mortality risk over 20 years among community-dwelling Chinese adults. Methods: Participants were from the Hong Kong Osteoporosis Study who attended baseline assessments during 1995–2010. Coffee intake was self-reported through a food frequency questionnaire and was previously validated. Disease diagnoses, which were mapped into 1795 distinct phecodes, and mortality data were obtained from linkage with territory-wide electronic health records. Cox models were used to estimate the association between coffee intake and the incidence of each disease outcome and mortality among individuals without a history of the respective medical condition at baseline. All models were adjusted for age, sex, body mass index, smoking, alcohol drinking, and education. Results: Among the 7420 included participants (mean age 53.2 years, 72.2% women), 54.0% were non-coffee drinkers, and only 2.7% consumed more than one cup of coffee per day. Over a median follow-up of 20.0 years, any coffee intake was associated with a reduced risk of dementia, atrial fibrillation, painful respirations, infections, atopic dermatitis, and dizziness at a false discovery rate (FDR) of <0.05. Furthermore, any coffee intake was associated with an 18% reduced risk of all-cause mortality (95% confidence interval = 0.73–0.93). Conclusion: In a population with relatively low coffee consumption, any coffee intake is linked to a lower risk of several neurological, circulatory, and respiratory diseases and symptoms, as well as mortality.
Stakeholder Perspectives on the School Food Environment: Insights from South African Learners—A Pilot Study
Authors: Pal Imana , Naicker Ashika , Tshitaudzi Gilbert , Singh Evonne Shanita , Grobbelaar Heleen , Vilakazi Nokuthula
Published: October 2024

Leveraging learner-driven insights to enhance the SFE can significantly influence food choices by decreasing the consumption of unhealthy foods and increasing access to healthier options. Using learners’ voices as important stakeholders in the school food environment (SFE), this qualitative research study aimed to gain a deeper understanding of their perspectives, identify barriers and enablers to fostering a healthy SFE in South African public schools, and explore the link between the SFE and learners’ food choices. Six focus group discussions (FGDs) with 4–6 participants were held in six schools, including three primary and three secondary schools in the KwaZulu-Natal Department of Education’s iLembe district, SA, with learners aged 12–14 and 15–18 years, respectively. Learners were asked how schools could help them eat healthier and how their SFE benefitted them. The data were analysed using thematic data analysis methods. The FGDs generated 14 themes and subthemes. Emerging information suggests a lack of control over the sale of unhealthy food despite the existence of guidelines. This is further exacerbated by the marketing of unhealthy foods, which prevents learners from selecting healthier options. Furthermore, they stated that promoting the school food programme (SFP) and changing attitudes towards healthy food intake through comprehensive nutrition education are useful ways to enhance the SFE. The findings of this study underscore the critical role of learner insights in shaping effective strategies to improve the SFE.
Nutritional and Microbial Strategies for Treating Acne, Alopecia, and Atopic Dermatitis
Authors: Borrego-Ruiz Alejandro , Borrego Juan J.
Published: October 2024

Background/Objectives: Diet is one of the major determinants of the composition and function of the gut microbiome, and diverse studies have established directional connections between gut microbiome dysbiosis and skin dyshomeostasis. Furthermore, a significant link between the gut and certain skin-related disorders has been reported. This work reviews the mechanisms underlying the relationship between nutritional factors, gut microbiome, and certain skin diseases such as acne vulgaris, alopecia, and atopic dermatitis. In addition, it explores how the modulation of the gut microbiome and human skin through diet and various microbial strategies, including probiotics, synbiotics, postbiotics, and fecal microbiota transplantation, may serve as future treatments for skin diseases, possibly replacing traditional methods such as antibiotic, topical corticosteroid, and laser therapies. Results: The adequate intake of certain foods can promote a balanced gut microbiome, potentially reducing skin inflammation and improving overall skin health, while poor dietary choices may lead to worse outcomes by disrupting gut homeostasis. In this regard, diets high in antioxidants, fiber, and phytonutrients appear to be beneficial for enhancing skin health and preventing associated comorbidities. In addition, the administration of probiotics, synbiotics, and postbiotics in the treatment of cutaneous diseases has been shown to restore skin dyshomeostasis and to improve the symptoms of the reviewed skin conditions. Conclusions: Consuming a healthy, plant-based diet can reduce skin inflammation and enhance overall skin health. Although the application of probiotics, synbiotics, and postbiotics has demonstrated promise in modulating inflammation, enhancing tissue regeneration, and inhibiting pathogenic colonization, further research is required.
Proteins and Peptides from Food Sources with Effect on Satiety and Their Role as Anti-Obesity Agents: A Narrative Review
Authors: Ignot-Gutiérrez Anaís , Serena-Romero Gloricel , Guajardo-Flores Daniel , Alvarado-Olivarez Mayvi , Martínez Armando J. , Cruz-Huerta Elvia
Published: October 2024

Background/Objective: Obesity, clinically defined as a body mass index (BMI) of 30 kg/m2 or higher, is a medical condition characterized by the excessive accumulation of body fat, which can lead to adverse health consequences. As a global public health issue with an escalating prevalence, controlling appetite and satiety is essential for regulating energy balance and managing body weight. Dietary proteins and peptides have gained interest in their potential to prevent and treat obesity by modulating satiety signals. This narrative review analyzes scientific evidence highlighting the role of dietary proteins and peptides in regulating satiety signals and investigates their therapeutic potential in preventing and treating obesity. Methods: A comprehensive literature search was conducted in multiple electronic databases, including PubMed, Scopus, and Web of Science. The search focused on articles examining the impact of dietary proteins and peptides on satiety and obesity, encompassing both preclinical and clinical trials. Results: Several studies have demonstrated a correlation between the intake of specific proteins or peptides from plant and animal sources and satiety regulation. These investigations identified mechanisms where amino acids and peptides interact with enteroendocrine cell receptors, activating intracellular signaling cascades that promote the release of anorexigenic gut hormones such as cholecystokinin (CCK), glucagon-like peptide-1 (GLP-1), and peptide YY (PYY). Both in vitro and in vivo assays have shown that these interactions contribute to appetite regulation and the sensation of satiety. Conclusions: Using proteins and peptides in the diet may be an effective strategy for regulating appetite and controlling body weight. However, more research—including clinical trials—is needed to understand the underlying mechanisms better and optimize the application of these bioactive compounds in preventing and treating obesity.
Auranofin as a Novel Anticancer Drug for Anaplastic Thyroid Cancer
Authors: An Seung-Chan , Jun Hak Hoon , Kim Kyeong Mi , Kim Issac , Choi Sujin , Yeo Hyunjeong , Lee Soonchul , An Hyun-Ju
Published: October 2024

Background/Objectives: Anaplastic thyroid cancer (ATC) is an aggressive and rare cancer with a poor prognosis, and traditional therapies have limited efficacy. This study investigates drug repositioning, focusing on auranofin, a gold-based drug originally used for rheumatoid arthritis, as a potential treatment for ATC. Methods: Auranofin was identified from an FDA-approved drug library and tested on two thyroid cancer cell lines, 8505C and FRO. Antitumor efficacy was evaluated through gene and protein expression analysis using Western blot, FACS, and mRNA sequencing. In vivo experiments were conducted using subcutaneous injections in nude mice to confirm the anticancer effects of auranofin. Results: Auranofin induced reactive oxygen species (ROS) production and apoptosis, leading to a dose-dependent reduction in cell viability, G1/S phase cell cycle arrest, and altered expression of regulatory proteins. It also inhibited cancer stem cell activity and suppressed epithelial–mesenchymal transition. mRNA sequencing revealed significant changes in the extracellular matrix–receptor interaction pathway, supported by Western blot results. In vivo xenograft models demonstrated strong antitumor activity. Conclusions: Auranofin shows promise as a repurposed therapeutic agent for ATC, effectively inhibiting cell proliferation, reducing metastasis, and promoting apoptosis. These findings suggest that auranofin could play a key role in future ATC treatment strategies.
The Impact of Pdcd4, a Translation Inhibitor, on Drug Resistance
Authors: Wang Qing , Yang Hsin-Sheng
Published: October 2024

Programmed cell death 4 (Pdcd4) is a tumor suppressor, which has been demonstrated to efficiently suppress tumorigenesis. Biochemically, Pdcd4 binds with translation initiation factor 4A and represses protein translation. Beyond its role in tumor suppression, growing evidence suggests that Pdcd4 enhances the chemosensitivity of several anticancer drugs. To date, numerous translational targets of Pdcd4 have been identified. These targets govern important signal transduction pathways, and their attenuation may improve chemosensitivity or overcome drug resistance. This review will discuss the signal transduction pathways regulated by Pdcd4 and the potential mechanisms through which Pdcd4 enhances chemosensitivity or counteracts drug resistance.
Novel Deep Sea Isoindole Alkaloid FGFC1 Exhibits Its Fibrinolytic Effects by Inhibiting Thrombin-Activatable Fibrinolysis Inhibitor
Authors: Zhang Haixing , Diao Xiaozhen , Jiang Tingting , Wei Mingjun , Su Yue , Shen Jingjing , Bao Chunlin , Wu Wenhui
Published: October 2024

Background: The thrombin-activatable fibrinolysis inhibitor (TAFI) is an important regulator in the balance between blood clot formation (coagulation) and dissolution (fibrinolysis), which is mainly activated by thrombin bonded with thrombomodulin (TM). Methods: In this study, the investigation focused on the unique target TAFI of fungi fibrinolytic compound 1 (FGFC1), a novel fibrinolytic compound sourced from the deep sea. In this sense, the regulation of TAFI by FGFC1, in comparison to established TAFI inhibitors such as DS-1040 and PCTI in hPPP, was investigated, which was validated through the molecular docking of FGFC1 to TAFI. The inhibitory effect of FGFC1 on TAFI-mediating coagulation (ex vivo and in vitro) and its fibrinolytic effect (ex vivo) were investigated in hPPP and hCMEC/D3 cells, respectively, followed by SEM. Results: FGFC1 solutions ranging from 0.023 to 0.736 mM effectively inhibited TAFI activation. Notably, the 0.023 mM concentration demonstrated significant suppression, comparable to DS-1040 and PCTI. These inhibitory effects of FGFC1 (0.023–0.368 mM) were further validated through the enhancement in TAFI (TAFIa) activation by fibrins in the coagulum prior to proteolysis, resulting in the cleavage of TAFIa from 33 kDa to 28 kDa. Furthermore, these regulatory effects of FGFC1 on TAFI were demonstrated to have minimal association with TM-mediated control, as confirmed through a molecular docking analysis. FGFC1 (0.023–0.092 mM) was suggested to have obstructive effects on TAFI-mediated coagulation in the hPPP, which was demonstrated by the inhibition of clot aggregation, protein crystallization, and platelet anchoring, as observed through SEM. Simultaneously, FGFC1 (0.023 to 0.368 mM) significantly enhanced TAFI-mediated fibrinolysis, which was also supported by increased levels of t-PA, u-PA, and plasmin. Conclusions: From the above findings, FGFC1 is identified as a novel dual-target bioactive compound participating in blood formation/dissolution that demonstrates anti-coagulation and fibrinolytic effects by regulating TAFI activation, inhibiting TAFIa–fibrin combination, and initiating proteolysis. It also provided convincing evidence that TAFI plays a critical role in thrombolysis as a molecular link between coagulation and fibrinolysis. Furthermore, the application of FGFC1 was indicated as a potential therapeutic strategy in thromboembolic and hemorrhagic diseases.
Evaluation of Mucoadhesive Nano-Bilosomal In Situ Gels Containing Anti-Psychotic Clozapine for Treatment of Schizophrenia: In Vitro and In Vivo Studies
Authors: Abdallah Marwa H. , Shahien Mona M. , El-Horany Hemat El-Sayed , Ahmed Enas Haridy , El-Nahas Hanan M. , Abdulla Nourhan A. , Ibrahim Tarek M.
Published: October 2024

Background/Objectives: Patients with schizophrenia have significant challenges in adhering to and complying with oral medicines, resulting in adverse consequences such as symptom worsening and psychotic relapse. Methods: This study aimed to develop clove oil-based bilosomes using definitive screening design (DSD) to maximize the anti-schizophrenic action of clozapine and promote its nose-to-brain delivery. The target was to optimize the physicochemical properties of bilosomes and incorporate them into mucoadhesive intranasal in situ gels, searching for augmented ex vivo and in vivo clozapine delivery. Results: The bilosomes’ particle size was decreased by increasing the span, SDC, and clove oil amounts. In addition to using a high lipid amount, the aforementioned components also helped increase the entrapment efficiency values. Increased zeta potential was only observed by increasing surfactant amount and reducing clozapine concentration. After incorporation of optimized liquid clove oil-based bilosomes, which had a spherical nano-sized vesicular shape, into P 407-dependent gels, an HPMC (2% w/w)/P 407 (20% w/w)-containing formulation (G6) was selected as an optimized gel owing to its acceptable gelation time (13.28 s), gel strength (27.72 s), viscosity (12,766.67 cP), and mucoadhesive strength (4273.93 dyne/cm2). The optimized G6 exhibited higher Jss (50.86 μg/cm2·h−1) through the nasal mucosa compared to the control gel (23.03 μg/cm2·h−1). Compared to the control gel, G6 displayed higher relative bioavailability (491.37%) than a commercial tablet (264.46%). Following ELISA analysis, dopamine and serotonin were significantly reduced, while BDNF was remarkably increased after administration of optimized G6 into schizophrenic rats. Conclusion: Our study indicates the potential of intranasal bilosomal gels in upgrading the anti-schizophrenic and neuroprotective activity of clozapine.
Antidepressant-like Effects of Cannabis sativa L. Extract in an Lipopolysaccharide Model: Modulation of Mast Cell Activation in Deep Cervical Lymph Nodes and Dura Mater
Authors: Shin Joonyoung , Kim Dong-Uk , Bae Gi-Sang , Han Ji-Ye , Lim Do-Won , Lee Young-Mi , Kim Eunjae , Kwon Eunjeong , Han Dongwoon , Kim Sungchul
Published: October 2024

Background: Lipopolysaccharide (LPS)-induced neuroinflammation is a well-established model for studying depression-like behavior, driven by pro-inflammatory cytokines such as TNF-α and IL-1β. Mast cells (MCs) contribute to neuroinflammation by releasing mediators that exacerbate depressive-like symptoms. This study evaluates the antidepressant-like and anti-inflammatory effects of Cannabis sativa L. inflorescence extract (CSL) in an LPS-induced neuroinflammation model. Methods: Male C57BL/6 mice were intraperitoneally injected with CSL at doses of 10, 20, and 30 mg/kg, 30 min prior to LPS (0.83 mg/kg) administration. Depressive behaviors were assessed using the sucrose preference test (SPT), tail suspension test (TST), and forced swimming test (FST). The neutrophil-to-lymphocyte ratio (NLR) was measured to assess systemic inflammation. Cytokine levels in the prefrontal cortex (PFC) were measured, and mast cell degranulation in the lymph nodes and dura mater was analyzed histologically (approval number: WKU24-64). Results: CSL significantly improved depressive-like behaviors and decreased the NLR, indicating reduced systemic inflammation. CSL also significantly reduced TNF-α and IL-1β levels in the PFC. Furthermore, CSL inhibited MC degranulation in the deep cervical lymph nodes and dura mater, with the strongest effects observed at 30 mg/kg. Conclusions: CSL demonstrated antidepressant-like and anti-inflammatory effects in an LPS-induced neuroinflammation model, likely through the modulation of cytokine expression and mast cell activity. These results suggest the potential of CSL as a therapeutic option for treating inflammation-related depression.
Development of a Multilayer Film Including the Soluble Eggshell Membrane Fraction for the Treatment of Oral Mucosa Lesions
Authors: Neduri Karthik , Ailuno Giorgia , Zuccari Guendalina , Bassi Anna Maria , Vernazza Stefania , Schito Anna Maria , Caviglioli Gabriele , Baldassari Sara
Published: October 2024

Background/Objectives: Oral diseases causing mucosal lesions are normally treated with local or systemic anti-inflammatory, analgesic and antimicrobial agents. The development of topical formulations, including wound-healing promoters, might speed up the recovery process, improving patients’ quality of life, and reduce the risk of deterioration in health conditions. In this study, a mucoadhesive multilayer film, including a novel biocompatible substance (solubilized eggshell membrane, SESM), was rationally designed. Methods: The SESM preparation procedure was optimized and its biological effects on cell proliferation and inflammation marker gene expression were evaluated in vitro; preformulation studies were conducted to identify the most promising polymers with film-forming properties; then, trilayer films, consisting of an outer layer including chlorhexidine digluconate as a model drug, a supporting layer and a mucoadhesive layer, incorporating SESM, were prepared using the casting method and their mechanical, adhesion and drug release control properties were evaluated. Results: SESM proved to possess a notable wound-healing capacity, inducing a wound closure of 84% in 24 h without inhibiting blood clotting. The films revealed a maximum detachment force from porcine mucosa of approx. 1.7 kPa and maximum in vivo residence time of approx. 200–240 min; finally, they released up to 98% of the loaded drug within 4 h. Conclusions: The formulated trilayer films were found to possess adequate properties, making them potentially suitable for protecting oral lesions and favoring their rapid healing, while releasing antimicrobial substances that might be beneficial in reducing the risk of bacterial infections.
Recent Advances in the Drugs and Glucose-Responsive Drug Delivery Systems for the Treatment of Diabetes: A Systematic Review
Authors: Liu Junyu , Yi Xudong , Zhang Jinrui , Yao Yiman , Panichayupakaranant Pharkphoom , Chen Haixia
Published: October 2024

Diabetes is a common chronic metabolic disease. Different types of drugs play important roles in controlling diabetes and its complications, but there are some limitations. The glucose-responsive drug delivery system is a novel technology with potential in diabetes treatment. It could automatically release drugs in response to changes in glucose levels in the body to maintain blood glucose within a normal range. The emergence of a glucose-sensitive drug delivery system provides a more intelligent and precise way to treat diabetes. The review is carried out according to the Preferred Reporting Items for Systematic Reviews (PRISMA 2020) guidelines This review focuses on the recent advances in the drugs and different systems of glucose-sensitive drug delivery, including glucose oxidase, phenylboronic acid, Concanavalin A, and other glucose-reactive systems. Furthermore, the glucose-responsive drug delivery system combined with the application applied in hydrogels, microneedles, and nanoparticles is also explored and summarized. The new platforms to sustain the release of anti-diabetic drugs could be desirable for patients. It could lead to increased adherence and glycemic outcomes for the detection and treatment of diabetes. Furthermore, given the limitations of glucose-responsive drug delivery systems, solutions and perspectives are proposed to help the understanding and application of these systems. This review will be helpful for drug discovery and treatment of diabetes from a new perspective.
Unraveling the Electrochemical Insights of Cobalt Oxide/Conducting Polymer Hybrid Materials for Supercapacitor, Battery, and Supercapattery Applications
Authors: Annu  , Park Sang-Shin , Alam Md Najib , Yewale Manesh , Shin Dong Kil
Published: October 2024

This review article focuses on the potential of cobalt oxide composites with conducting polymers, particularly polypyrrole (PPy) and polyaniline (PANI), as advanced electrode materials for supercapacitors, batteries, and supercapatteries. Cobalt oxide, known for its high theoretical capacitance, is limited by poor conductivity and structural degradation during cycling. However, the integration of PPy and PANI has been proven to enhance the electrochemical performance through improved conductivity, increased pseudocapacitive effects, and enhanced structural integrity. This synergistic combination facilitates efficient charge transport and ion diffusion, resulting in improved cycling stability and energy storage capacity. Despite significant progress in synthesis techniques and composite design, challenges such as maintaining structural stability during prolonged cycling and scalability for mass production remain. This review highlights the synthesis methods, latest advancements, and electrochemical performance in cobalt oxide/PPy and cobalt oxide/PANI composites, emphasizing their potential to contribute to the development of next-generation energy storage devices. Further exploration into their application, especially in battery systems, is necessary to fully harness their capabilities and meet the increasing demands of energy storage technologies.
Kinetics of Polyampholyte Dimerization: Influence of Charge Sequences
Authors: Kim Seowon , Lee Nam-Kyung , Jung Youngkyun , Johner Albert
Published: October 2024

Polyampholytes (PAs) exhibit complex behaviors in various environments influenced by their charge distribution. This study focuses on the kinetics of dimerization of PAs, aiming to elucidate the underlying mechanisms and clarify relevant characteristics of the charge sequence. We focus on PAs with non-zero net charges, employing molecular dynamics simulations and theoretical analyses to examine how charge sequences influence the rates of dimer formation and dissociation. Our findings reveal that the charge sequence of tails and the blockiness of the minority charge group markedly influence the kinetics of dimerization: large blockiness and tails with a high number of majority-type charges slow down the dissociation of dimers. Additionally, the presence of an extended (central) block of the majority charge promotes structural diversity. Within dimer states, blocks alternate between intra- and inter-chain contacts. The duration times in the dimer states are significantly longer than the typical dwell times of block inter-contacts, with a notable extension when multiple blocks are engaged. Intrinsically disordered proteins (IDPs) play crucial roles in cellular functions, primarily due to their ability to undergo rapid conformational changes and form transient complexes. These properties largely depend on the sequence of charged residues. We provide insights into the fundamental principles governing the structural and dynamical properties of polyampholytic IDP, emphasizing the importance of sequence-specific effects on both aggregation and dissociation.
Role of Sterilization on In Situ Gel-Forming Polymer Stability
Authors: Bakhrushina Elena O. , Afonina Alina M. , Mikhel Iosif B. , Demina Natalia B. , Plakhotnaya Olga N. , Belyatskaya Anastasiya V. , Krasnyuk Ivan I. , Krasnyuk Ivan I.
Published: October 2024

In recent years, stimulus-sensitive drug delivery systems have been developed for parenteral administration as a depot system. In situ systems incorporate smart polymers that undergo a phase transition at the site of administration. All parenteral and ocular dosage forms must meet sterility requirements. Careful selection of the sterilization method is required for any type of stimuli-sensitive system. Current sterilization methods are capable of altering the conformation of polymers or APIs to a certain extent, ultimately causing the loss of pharmacological and technological properties of the drug. Unfortunately, the issues of risk assessment and resolution regarding the sterilization of stimuli-sensitive systems, along with ways to stabilize such compositions, are insufficiently described in the scientific literature to date. This review provides recommendations and approaches, formulated on the basis of published experimental data, that allow the effective management of risks arising during the development of in situ systems requiring sterility.
Landslide Hazard Prediction Based on UAV Remote Sensing and Discrete Element Model Simulation—Case from the Zhuangguoyu Landslide in Northern China
Authors: Li Guangming , Zhang Yu , Zhang Yuhua , Guo Zizheng , Liu Yuanbo , Zhou Xinyong , Guo Zhanxu , Guo Wei , Wan Lihang , Duan Liang , Luo Hao , He Jun
Published: October 2024

Rainfall-triggered landslides generally pose a high risk due to their sudden initiation, massive impact force, and energy. It is, therefore, necessary to perform accurate and timely hazard prediction for these landslides. Most studies have focused on the hazard assessment and verification of landslides that have occurred, which were essentially back-analyses rather than predictions. To overcome this drawback, a framework aimed at forecasting landslide hazards by combining UAV remote sensing and numerical simulation was proposed in this study. A slow-moving landslide identified by SBAS-InSAR in Tianjin city of northern China was taken as a case study to clarify its application. A UAV with laser scanning techniques was utilized to obtain high-resolution topography data. Then, extreme rainfall with a given return period was determined based on the Gumbel distribution. The Particle Flow Code (PFC), a discrete element model, was also applied to simulate the runout process after slope failure under rainfall and earthquake scenarios. The results showed that the extreme rainfall for three continuous days in the study area was 151.5 mm (P = 5%), 184.6 mm (P = 2%), and 209.3 mm (P = 1%), respectively. Both extreme rainfall and earthquake scenarios could induce slope failure, and the failure probabilities revealed by a seepage–mechanic interaction simulation in Geostudio reached 82.9% (earthquake scenario) and 92.5% (extreme rainfall). The landslide hazard under a given scenario was assessed by kinetic indicators during the PFC simulation. The landslide runout analysis indicated that the landslide had a velocity of max 23.4 m/s under rainfall scenarios, whereas this reached 19.8 m/s under earthquake scenarios. In addition, a comparison regarding particle displacement also showed that the landslide hazard under rainfall scenarios was worse than that under earthquake scenarios. The modeling strategy incorporated spatial and temporal probabilities and runout hazard analyses, even though landslide hazard mapping was not actually achieved. The present framework can predict the areas threatened by landslides under specific scenarios, and holds substantial scientific reference value for effective landslide prevention and control strategies.
NDVI or PPI: A (Quick) Comparison for Vegetation Dynamics Monitoring in Mountainous Area
Authors: Charrière Dimitri , Francon Loïc , Giuliani Gregory
Published: October 2024

Cold ecosystems are experiencing a warming rate that is twice as fast as the global average and are particularly vulnerable to the consequences of climate change. In mountain ecosystems, it is particularly important to monitor vegetation to understand ecosystem dynamics, biodiversity conservation, and the resilience of these fragile ecosystems to global change. Hence, we used satellite data acquired by Sentinel-2 to perform a comparative assessment of the Normalized Difference Vegetation Index (NDVI) and the Plant Phenology Index (PPI) in mountainous regions (canton of Valais-Switzerland in the European Alps) for monitoring vegetation dynamics of four types: deciduous trees, coniferous trees, grasslands, and shrublands. Results indicate that the NDVI is particularly noisy in the seasonal cycle at the beginning/end of the snow season and for coniferous trees, which is consistent with its known snow sensitivity issue and difficulties in retrieving signal variation in dense and evergreen vegetation. The PPI seems to deal with these problems but tends to overestimate peak values, which could be attributed to its logarithmic formula and derived high sensitivity to variations in near-infrared (NIR) and red reflectance during the peak growing season. Concerning seasonal parameters retrieval, we find close concordance in the results for the start of season (SOS) and end of season (EOS) between indices, except for coniferous trees. Peak of season (POS) results exhibit important differences between the indices. Our findings suggest that PPI is a robust remote sensed index for vegetation monitoring in seasonal snow-covered and complex mountain environments.
The Characterization of Electric Field Pulses Observed in the Preliminary Breakdown Processes of Normal and Inverted Intracloud Flashes
Authors: Shi Dongdong , Zhang Jinlai , Gao Panliang , Zheng Dong , Qi Qi , Shao Jie , Kan Shiqi , Wang Daohong , Wu Ting
Published: October 2024

We have studied the parameters of preliminary breakdown (PB) pulses in 395 normal and 319 inverted intracloud (IC) flashes observed in Gifu, Japan, and Ningxia, China, respectively, by using a low-frequency mapping system called fast antenna lightning mapping array (FALMA). These parameters are extracted from the first half of the PB pulses. It is found that compared to normal IC flashes, inverted IC flashes exhibited PB pulses with slower rise times (6.8 vs. 3.1 μs), wider half-peak widths (3.8 vs. 2.5 μs), longer zero-crossing times (26.2 vs. 14 μs), and extended fall times (4 vs. 3.2 μs). We further demonstrated that such discrepancies between normal and inverted IC flashes should not be caused by subjective factors, like noise threshold setting, or objective factors, like signal propagation distance. Based on this analysis, finally, we inferred that the discrepancies should be a reflection of the PB channel properties of normal and inverted IC flashes.
An Efficient Ship Detection Method Based on YOLO and Ship Wakes Using High-Resolution Optical Jilin1 Satellite Imagery
Authors: Mou Fangli , Fan Zide , Ge Yunping , Wang Lei , Li Xinming
Published: October 2024

In this study, we propose a practical and efficient scheme for ship detection in remote sensing imagery. Our method is developed using both ship body detection and ship wake detection and combines deep learning and feature-based image processing. A deep convolutional neural network is used to achieve ship body detection, and a feature-based processing method is proposed to detect ship wakes. For better analysis, we model the sea region and evaluate the quality of the image. Generally, the wake detection result is used to assist ship detection and obtain the sailing direction. Conventional methods cannot detect ships that are covered by clouds or outside the image boundary. The method proposed in this paper uses the wake to detect such ships, with a certain level of confidence and low false alarm probability in detection. Practical aspects such as the method’s applicability and time efficiency are considered in our method for real applications. We demonstrate the effectiveness of our method in a real remote sensing dataset. The results show that over 93.5% of ships and over 70% of targets with no visible ship body can be successfully detected. This illustrates that the proposed detection framework can fill the gap regarding the detection of sailing ships in a remote sensing image.
A New Self-Sensing Fiber Optic Anchor to Monitor Bolt Axial Force and Identify Loose Zones in the Surrounding Rock of Open TBM Tunnels
Authors: Kang Xin , Xie Xiongyao , Zeng Kun
Published: October 2024

TBM has been widely used in underground engineering and construction, but there is no precedent for the application of open TBM in the inclined shafts of coal mines, which brings new challenges to the support system. The distribution of the axial forces on anchors and the range of loosening of the surrounding rock are crucial considerations in tunnel support design. Existing methods for measuring the axial forces in anchors and determining the extent of loosening in the surrounding rock typically remain at the inspection level, lacking long-term and real-time monitoring capabilities. This paper presents a new self-sensing anchor with embedded optical fibers (made using an improved stirrer) and proposes an intelligent tunnel rock monitoring system. The paper also outlines a method for identifying loosening zones in surrounding rock based on monitoring data and theoretical analysis. Installing self-sensing anchors in the deep sections of the rock surrounding a tunnel provides three-dimensional, round-the-clock real-time monitoring of the axial forces acting on the anchors, using new technology and methods to recognize the deformation characteristics of loosening zones within the surrounding rock. This new self-sensing fiber optic anchor was first applied to an open TBM tunneling project in an inclined shaft in the Kekegai coal mine, and monitoring data indicate that self-sensing optical fiber anchors can accurately reflect stress patterns in real time. The axial force curve can be divided into four segments: the borehole area, the loosening zone, the stable zone, and the anchoring zone. Consequently, it accurately identifies the thickness of loosening zones at different positions within the tunnel’s surrounding rock. This information is compared and verified against results obtained from bolt dynamometers and borehole inspection. On this basis, an intelligent monitoring system was established to provide a basis for making engineering construction decisions, which makes tunnel construction smarter and helps technicians timely adjust TBM driving and support parameters.
Contribution-Based Resource Allocation for Effective Federated Learning in UAV-Assisted Edge Networks
Authors: Xiong Gang , Guo Jincheng
Published: October 2024

This paper considers UAVs as edge computing nodes and investigates a novel network resource allocation method for federated learning within a three-layer wireless network architecture containing cloud, edges (UAVs), and clients. To address the issue of fair bandwidth resource allocation among clients participating in federated learning, a contribution calculation strategy based on the Shapley value (SV) used as the weight for model aggregation is proposed. On this basis, a client selection and wireless resource allocation method based on model contribution is further designed. By reducing the training and aggregation frequency of the low-contribution clients during the asynchronous aggregation phase, the limited bandwidth resources are allocated to high-contribution clients, thus improving the convergence speed and accuracy of the global model. Simulation experiments demonstrate that the proposed method can significantly reduce the system delay and total energy consumption with gains between 15% and 50% while also improving the final accuracy of the global model by 0.3% and 2% on both short-term and long-term perspectives, respectively.
Remote Sensing Inversion of Water Quality Grades Using a Stacked Generalization Approach
Authors: Zhao Ziqi , Wan Luhe , Wang Lei , Che Lina
Published: October 2024

Understanding water quality is crucial for environmental management and policy formulation. However, existing methods for assessing water quality are often unable to fully integrate with multi-source remote sensing data. This study introduces a method that employs a stacking algorithm within the Google Earth Engine (GEE) for classifying water quality grades in the Songhua River Basin (SHRB). By leveraging the strengths of multiple machine learning models, the Stacked Generalization (SG) model achieved an accuracy of 91.67%, significantly enhancing classification performance compared to traditional approaches. Additionally, the analysis revealed substantial correlations between the normalized difference vegetation index (NDVI) and precipitation with water quality grades. These findings underscore the efficacy of this method for effective water quality monitoring and its implications for understanding the influence of natural factors on water pollution.
Multi-Class Detection of Neurodegenerative Diseases from EEG Signals Using Lightweight LSTM Neural Networks
Authors: Falaschetti Laura , Biagetti Giorgio , Alessandrini Michele , Turchetti Claudio , Luzzi Simona , Crippa Paolo
Published: October 2024

Neurodegenerative diseases severely impact the life of millions of patients worldwide, and their occurrence is more and more increasing proportionally to longer life expectancy. Electroencephalography has become an important diagnostic tool for these diseases, due to its relatively simple procedure, but it requires analyzing a large number of data, often carrying a small fraction of informative content. For this reason, machine learning tools have gained a considerable relevance as an aid to classify potential signs of a specific disease, especially in its early stages, when treatments can be more effective. In this work, long short-term memory-based neural networks with different numbers of units were properly designed and trained after accurate data pre-processing, in order to perform a multi-class detection. To this end, a custom dataset of EEG recordings from subjects affected by five neurodegenerative diseases (Alzheimer’s disease, frontotemporal dementia, dementia with Lewy bodies, progressive supranuclear palsy, and vascular dementia) was acquired. Experimental results show that an accuracy up to 98% was achieved with data belonging to different classes of disease, up to six including the control group, while not requiring particularly heavy computational resources.
Bidirectional Planning for Autonomous Driving Framework with Large Language Model
Authors: Ma Zhikun , Sun Qicong , Matsumaru Takafumi
Published: October 2024

Autonomous navigation systems often struggle in dynamic, complex environments due to challenges in safety, intent prediction, and strategic planning. Traditional methods are limited by rigid architectures and inadequate safety mechanisms, reducing adaptability to unpredictable scenarios. We propose SafeMod, a novel framework enhancing safety in autonomous driving by improving decision-making and scenario management. SafeMod features a bidirectional planning structure with two components: forward planning and backward planning. Forward planning predicts surrounding agents’ behavior using text-based environment descriptions and reasoning via large language models, generating action predictions. These are embedded into a transformer-based planner that integrates text and image data to produce feasible driving trajectories. Backward planning refines these trajectories using policy and value functions learned through Actor–Critic-based reinforcement learning, selecting optimal actions based on probability distributions. Experiments on CARLA and nuScenes benchmarks demonstrate that SafeMod outperforms recent planning systems in both real-world and simulation testing, significantly improving safety and decision-making. This underscores SafeMod’s potential to effectively integrate safety considerations and decision-making in autonomous driving.