bluuebunny/crossref_metadata_2025 huggingface dataset:
Scoping Review of Climate Change Adaptation Interventions for Health: Implications for Policy and Practice
Authors: Brink Nicholas , Mansoor Kehkashan , Swiers Joost , Lakhoo Darshnika P. , Parker Craig , Nakstad Britt , Sawry Shobna , Aunan Kristin , Otto Ilona M. , Chersich Matthew F.
Published: November 2024

Climate change is among the greatest threats to health in the 21st century, requiring the urgent scaling-up of adaptation interventions. We aim to summarise adaptation interventions that were funded by the Belmont Forum and the European Union, the largest global funders of climate change and health research. A systematic search was conducted (updated February 2023) to identify articles on adaptation interventions for health within this funding network. The data extracted included study characteristics, types of interventions, and study outcomes. The results were synthesised narratively within the PRISMA-ScR guidelines. A total of 197 articles were screened, with 37 reporting on adaptation interventions. The majority of interventions focused on the general population (n = 17), with few studies examining high-risk populations such as pregnant women and children (n = 4) or migrants (n = 0). Targeted interventions were mostly aimed at behavioural change (n = 8) and health system strengthening (n = 6), while interventions with mitigation co-benefits such as nature-based solutions (n = 1) or the built environment (n = 0) were limited. The most studied climate change hazard was extreme heat (n = 26). Several studies reported promising findings, principally regarding interventions to counter heat impacts on workers and pregnant women and improving risk awareness in communities. These findings provide a platform on which to expand research and public health interventions for safeguarding public health from the effects of climate change.
St. John’s Wort Extract Ze 117 and Escitalopram Alter Plasma and Hippocampal Lipidome in a Rat Model of Chronic-Stress-Induced Depression
Authors: Bussmann Hendrik , Bremer Swen , Hernier Anne Marie , Drewe Jürgen , Häberlein Hanns , Franken Sebastian , Freytag Virginie , Boonen Georg , Butterweck Veronika
Published: November 2024

Chronic stress is a key factor in the development of depression. It leads to hyperactivation of the hypothalamic–pituitary–adrenal (HPA) axis, which in turn increases the formation of glucocorticoids (GCs). Chronically elevated GC levels disrupt neuroplasticity and affect brain lipid metabolism, which may, ultimately, contribute to the development of depression. This study aimed to investigate the effects of the antidepressants St. John’s Wort extract and escitalopram on lipid metabolism in vivo. Therefore, repeated corticosterone injections were used to induce depression-like behavior in rats. Male Sprague–Dawley rats were stressed with corticosterone injections (40 mg/kg, s.c.) over 22 consecutive days and were concomitantly treated with varying doses of the St. John’s wort extract Ze 117 (30, 90 or 180 mg/kg, p.o.) or escitalopram (10 mg/kg, p.o.) and behavioral changes were evaluated using a modified forced swim test. The results indicate that repeated corticosterone injections significantly decreased the latency to first immobility. Furthermore, co-treatment of corticosterone with Ze 117 increased latency to first immobility significantly compared to rats treated with corticosterone alone. To further investigate the biochemical effects of corticosterone-induced stress, as well as the possible counter-regulation by antidepressants, the lipidomes of the plasma and hippocampus samples were analyzed by shotgun mass spectrometry. Corticosterone-induced stress significantly altered key lipid metabolites in the plasma but not in the hippocampal samples. In the hippocampus, however, specific glycerophospholipids such as lysophosphatidylethanolamines (LPEs) increased with escitalopram treatment and with Ze 117, both showing significant correlations with behavioral parameters. In summary, our study shows significant behavioral- and lipidome-altering processes with Ze 117 and escitalopram in rat plasma and hippocampal samples, thereby providing new targets and biomarker ideas for clinical diagnosis and antidepressant intervention.
Sex-Related Differences in Pancreatic Ductal Adenocarcinoma Progression and Response to Therapy
Authors: Grahovac Jelena , Đurić Ana , Tanić Miljana , Krivokuća Ana
Published: November 2024

Pancreatic ductal adenocarcinoma (PDAC) is one of the most deadly malignancies with an increasing incidence rate and limited therapeutic options. Biological sex has an impact on many aspects of PDAC development and response to therapy, yet it is highly unappreciated in both basic and translational research, and worryingly in PDAC clinical trials. In this review, we summarize how biological sex influences PDAC incidence and mortality, genetic and epigenetic landscapes, anti-tumor immunity, responses to hormones, cachexia, and the efficacy of therapy. We highlight the importance of sex as a variable and discuss how to implement it into preclinical and clinical research. These considerations should be of use to researchers aiming at improving understanding of PDAC biology and developing precision medicine therapeutic strategies.
Vesicles: New Advances in the Treatment of Neurodegenerative Diseases
Authors: Nuzzo Domenico , Girgenti Antonella , Palumbo Laura , Naselli Flores , Bavetta Martina , Marfia Giovanni , Picone Pasquale
Published: November 2024

Neurodegenerative diseases are characterized by brain lesions that limit normal daily activities and represent a major challenge to healthcare systems worldwide, with a significant economic impact. Nanotechnology is the science of manipulating matter at the nanoscale, where materials exhibit unique properties that are significantly different from their larger counterparts. These properties can be exploited for a wide range of applications, including medicine. Among the emerging therapeutic approaches for the treatment of neurodegenerative diseases, nanotechnologies are gaining prominence as a promising avenue to explore. Here, we review the state of the art of biological and artificial vesicles and their biological properties in the context of neurodegenerative diseases. Indeed, nanometric structures such as extracellular vesicles and artificial vesicles represent a promising tool for the treatment of such disorders due to their size, biocompatibility, and ability to transport drugs, proteins, and genetic material across the blood–brain barrier to target specific cells and brain areas. In the future, a deeper and broader synergy between materials science, bioengineering, biology, medicine, and the discovery of new, increasingly powerful delivery systems will certainly enable a more applied use of nanotechnology in the treatment of brain disorders.
Silencing of the MP Gene via dsRNA Affects Root Development and Growth in the Invasive Weed Mikania micrantha
Authors: Ou Zhenghui , Zhang Yuantong , Wu Qiang , Wang Kangkang , Zhang Guangzhong , Qiao Xi , Yan Ying , Qian Wanqiang , Wan Fanghao , Liu Bo
Published: November 2024

Mikania micrantha (“mile-a-minute” weed) is a global invasive alien weed that can cause severe damage to agroforestry ecosystems and significant agricultural losses worldwide. Although chemical, manual, or mechanical control methods are widely used to control M. micrantha, RNA interference (RNAi)-based biocontrol methods have rarely been reported for this species. The MONOPTEROS (MP) gene, encoding an auxin response factor, plays an essential role in embryonic root initiation in Arabidopsis thaliana. In this study, we identified the MP gene from M. micrantha via orthologous gene analysis. A total of 37 MP orthologous genes was identified in 4 plants, including 9 MP candidate genes in M. micrantha, 13 in Helianthus annuus, 6 in Chrysanthemum nankingense, and 9 in Lactuca sativa. Phylogenetic analysis revealed that an MP candidate gene in M. micrantha (Mm01G000655, named MmMP) was clustered into one clade with the MP gene in A. thaliana (AtMP). In addition, both MmMP and AtMP contain a B3-DNA binding domain that is shared by transcription factors that regulate plant embryogenesis. To study gene function, dsRNA against MmMP (dsMmMP) was applied to the roots of M. micrantha. Compared with those of the controls, the expression of MmMP was reduced by 43.3%, 22.1%, and 26.2% on the first, third, and fifth days after dsMmMP treatment, respectively. The dsMmMP-treated plants presented several morphological defects, mostly in the roots. Compared with water-treated plants, the dsMmMP-treated plants presented reduced developmental parameters, including root length, number of adventitious roots, root fresh and dry weights, plant height, and aboveground biomass. Additionally, safety assessment suggested that this dsMmMP treatment did not silence MP genes from non-target plants, including rice and tomato; nor did it inhibit root growth in those species. Collectively, these results suggest that MmMP plays an important role in root development in M. micrantha and provides a potential target for the development of species-specific RNAi-based herbicides.
The Genetic Variants Influencing Hypertension Prevalence Based on the Risk of Insulin Resistance as Assessed Using the Metabolic Score for Insulin Resistance (METS-IR)
Authors: Shine Bo-Kyung , Choi Ja-Eun , Park Young-Jin , Hong Kyung-Won
Published: November 2024

Insulin resistance is a major indicator of cardiovascular diseases, including hypertension. The Metabolic Score for Insulin Resistance (METS-IR) offers a simplified and cost-effective way to evaluate insulin resistance. This study aimed to identify genetic variants associated with the prevalence of hypertension stratified by METS-IR score levels. Data from the Korean Genome and Epidemiology Study (KoGES) were analyzed. The METS-IR was calculated using the following formula: ln [(2 × fasting blood glucose (FBG) + triglycerides (TG)) × body mass index (BMI)]/ ln [high-density lipoprotein cholesterol (HDL-C)]. The participants were divided into tertiles 1 (T1) and 3 (T3) based on their METS-IR scores. Genome-wide association studies (GWAS) were performed for hypertensive cases and non-hypertensive controls within these tertile groups using logistic regression adjusted for age, sex, and lifestyle factors. Among the METS-IR tertile groups, 3517 of the 19,774 participants (17.8%) at T1 had hypertension, whereas 8653 of the 20,374 participants (42.5%) at T3 had hypertension. A total of 113 single-nucleotide polymorphisms (SNPs) reached the GWAS significance threshold (p < 5 × 10−8) in at least one tertile group, mapping to six distinct genetic loci. Notably, four loci, rs11899121 (chr2p24), rs7556898 (chr2q24.3), rs17249754 (ATP2B1), and rs1980854 (chr20p12.2), were significantly associated with hypertension in the high-METS-score group (T3). rs10857147 (FGF5) was significant in both the T1 and T3 groups, whereas rs671 (ALDH2) was significant only in the T1 group. The GWASs identified six genetic loci significantly associated with hypertension, with distinct patterns across METS-IR tertiles, highlighting the role of metabolic context in genetic susceptibility. These findings underscore critical genetic factors influencing hypertension prevalence and provide insights into the metabolic–genetic interplay underlying this condition.
Characterization of HPMC and PEG 400 Mucoadhesive Film Loaded with Retinyl Palmitate and Ketorolac for Intravaginal Administration
Authors: Hernández-González Maryel E. , Rodríguez-González Claudia A. , Valencia-Gómez Laura E. , Hernández-Paz Juan F. , Jiménez-Vega Florida , Salcedo Mauricio , Olivas-Armendáriz Imelda
Published: November 2024

Intravaginal drug administration offers several advantages over other routes, primarily bypassing the initial stages of metabolism. Additionally, this route has demonstrated both local and systemic effects. Mucoadhesive polymeric systems can be utilized to prevent dose loss due to the mucous barriers and the formation of wet cavities. This study employed various techniques to evaluate the performance and characteristics of a mucoadhesive film composed of HPMC-PEG 400 containing retinyl palmitate and ketorolac molecules. Scanning Electron Microscopy (SEM) was employed to analyze the porous structure of the film. Thermogravimetric Analysis (TGA) was conducted at different temperatures to assess thermal stability. Fourier Transform Infrared Spectroscopy (FTIR) was used to analyze the functional groups and intermolecular interactions between the film and the drug. Swelling and weight loss tests indicated that the film disintegrated within 3–4 days. UV-VIS spectroscopy was used for drug release evaluation based on the Higuchi equation. Additionally, the surface wetting properties were assessed through contact angle measurements. The system’s biocompatibility was confirmed using the MTT assay. Finally, adhesion and glide tests demonstrated the film’s interaction with porcine uterine tissue. This study shows that the HPMC-PEG 400 film containing retinyl palmitate molecules interacts effectively with tissue and could be considered a novel tool for treating damaged epithelial tissues.
Ubiquitin-Activating Enzyme E1 (UBA1) as a Prognostic Biomarker and Therapeutic Target in Breast Cancer: Insights into Immune Infiltration and Functional Implications
Authors: Feng Mingtao , Cui Huanhuan , Li Sen , Li Liangdong , Zhou Changshuai , Chen Lei , Cao Yiqun , Gao Yang , Li Deheng
Published: November 2024

Ubiquitin-Activating Enzyme E1 (UBA1), an E1 enzyme involved in the activation of ubiquitin enzymes, has been involved in the onset and progression of different cancers in humans. Nevertheless, the precise contribution of UBA1 in breast cancer (BC) is still poorly characterized. In this study, a thorough investigation was carried out to elucidate the significance of UBA1 and validate its functionality in BC. Through the analysis of mRNA sequencing data of BC patients, the mRNA expression of UBA1 was observed to be notably enhanced in cancer tissues relative to controls, and high UBA1 expression was linked to worse overall survival (OS), disease-specific survival (DSS), and progress-free survival (PFS). Moreover, UBA1 exhibited potential as an independent prognostic and diagnostic biomarker for individuals with BC. Additionally, functional enrichment analysis revealed the involvement of UBA1 in inflammation-linked pathways, like the TNF-α signaling pathway, the IL-6 signaling pathway, and various immune-related biological processes. Notably, single-sample gene set enrichment analysis (ssGSEA) aided in the identification of a negative link between UBA1 expression and the levels of infiltrating mast cells, Th1 cells, iDC cells, B cells, DC cells, Tem cells, Cytotoxic cells, T cells, CD8T cells, and pDC cells. Finally, this study demonstrated that silencing UBA1 significantly impeded the growth and development of BC cell lines. These findings highlight UBA1 as a potential prognostic biomarker linked to immune infiltration in BC, thereby depicting its potential as a new therapeutic target for individuals with BC.
Accumulation of Anthocyanin in the Aleurone of Barley Grains by Targeted Restoration of the MYC2 Gene
Authors: Egorova Anastasiya A. , Zykova Tatyana E. , Hertig Christian W. , Hoffie Iris , Morozov Sergey V. , Chernyak Elena I. , Rogachev Artem D. , Korotkova Anna M. , Vikhorev Alexander V. , Vasiliev Gennady V. , Shoeva Olesya Y. , Kumlehn Jochen , Gerasimova Sophia V. , Khlestkina Elena K.
Published: November 2024

Blue barley grain pigmentation results from anthocyanin accumulation in the aleurone layer. Anthocyanins are known for their beneficial effects on human health. The gene encoding the MYELOCYTOMATOSIS 2 (MYC2) transcription factor is potentially responsible for the blue coloration of the aleurone. In non-pigmented barley, a single nucleotide insertion in this gene causes a frameshift mutation with a premature stop codon. It was hypothesized that restoring the MYC2 reading frame could activate anthocyanin accumulation in the aleurone. Using a targeted mutagenesis approach in the present study, the reading frame of MYC2 was restored in the non-pigmented cultivar Golden Promise. Genetic constructs harboring cas9 and gRNA expression units were developed, pre-validated in protoplasts, and then functional MYC2 alleles were generated at the plant level via Agrobacterium-mediated transformation. Anthocyanin accumulation in the aleurone layer of grains from these mutants was confirmed through microscopy and chemical analysis. The expression of anthocyanin biosynthesis genes was analyzed, revealing that the restoration of MYC2 led to increased transcript levels of F3H and ANS genes. These results confirm the critical role of the MYC2 transcription factor in the blue aleurone trait and provide a biotechnological solution for enriching barley grain with anthocyanins.
Anorectal Remodeling in the Transitional Zone with Increased Expression of LGR5, SOX9, SOX2, and Keratin 13 and 5 in a Dextran Sodium Sulfate-Induced Mouse Model of Ulcerative Colitis
Authors: Kobayashi Mio , Usui Tatsuya , Elbadawy Mohamed , Kigata Tetsuhito , Kaneda Masahiro , Murakami Tomoaki , Kozono Takuma , Itoh Yoshiyuki , Shibutani Makoto , Yoshida Toshinori
Published: November 2024

Although hyperplasia of the anorectal transitional zone (TZ) has been reported in mouse models of ulcerative colitis, the mechanisms underlying this phenomenon are not fully understood. We characterized keratin subtypes and examined the expression of stem cell markers in the TZ. Dextran sodium sulfate-treated mice showed abnormal repair of the anorectal region, which consisted of mixed hyperplastic TZ and regenerating crypts. Liquid chromatography-tandem mass spectrometry from the paraffin-embedded TZ in the treated mice revealed that the major keratins were type I cytokeratin (CK)13 and type II CK5, but notable expression of type I CK10 and CK42 and type II CK1, CK4, CK6a, CK8, and CK15 was also detected. Hyperplastic TZ was characterized by the expression of tumor protein 63, sex-determining region Y-box 2 (SOX2), SOX9, and leucine-rich repeat-containing G-protein coupled receptor 5 (Lgr5). Lgr5 was highly expressed in the TZ in the early stages of colitis, followed by higher expression levels of SOX2. The TZ-derived organoids expressed LGR5, SOX2, and SOX9. The present study suggests that transitional zones showing abnormal keratin assembly and stem cell activation may interfere with rectal crypt regeneration, leading to pathological anorectal remodeling in severe colitis.
Effect of Chloroplast ATP Synthase on Reactive Oxygen Species Metabolism in Cotton
Authors: Zhang Li , Jing Panpan , Geng Biao , Zhang Jinlong , Shi Jinjiang , Liang Dong , Yang Yujie , Qu Yunfang , Huang Jinling
Published: November 2024

Abnormal programmed cell death in the tapetum is induced by reactive oxygen species (ROS), which are the main factors leading to cytoplasmic male sterility (CMS). These abnormalities are caused by genetic interactions between nuclear and cytoplasmic genes. To explore the role of chloroplast genes in ROS metabolism, next-generation and single-molecule real-time sequencing of the chloroplast genome were performed in the cotton CMS line Jin A (Jin A-CMS). Our results showed that the chloroplast genome is 160,042 bp in length and consists of 131 genes, including 112 functional genes. An analysis of the functional annotation and sequence comparison with the Gossypium hirsutum chloroplast genome as a reference revealed that 29 genes in Jin A-CMS have single-nucleotide polymorphisms, including subunits of ATP synthase, NAD(P)H-quinone redox reductase, and photosystem complexes. Compared to the Jin B maintainer, the anthers of Jin A-CMS at the microspore abortion stage have significantly lower expression of atpB, atpE, and atpF. The relative expression of these genes is significantly higher in the three-line F1 hybrids compared to Jin A-CMS. The ROS levels in the leaves increased in response to the silencing of atpE and atpF in cotton plants. In summary, the results of our study show that the ATP synthase subunit genes atpE and atpF are closely linked with ROS metabolism. These results provide basic information for the functional analysis of ATP synthase in cotton.
Chitosan-Electrospun Fibers Encapsulating Norfloxacin: The Impact on the Biochemical, Oxidative and Immunological Profile in a Rats Burn Model
Authors: Coman Corneliu-George , Anisiei Alexandru , Cibotaru Sandu , Ailincai Daniela , Pasca Sorin Aurelian , Chabot Caroline , Gardikiotis Ioannis , Mititelu-Tartau Liliana
Published: November 2024

This study investigates the impact of chitosan-based nanofibers on burn wound healing in a rat model. Two formulations of chitosan nanofibers were prepared through electrospinning. The formulations were then incorporated with different amounts of norfloxacin and underwent surface modifications with 2-formylphenylboronic acid. The burn model was applied to Wistar male rats by the contact method, using a heated steel rod attached to a thermocouple. The effectiveness of the nanofibers was tested against a negative control group and a standard commercial dressing (Atrauman Ag) on the described model and evaluated by wound diameter, histological analysis and biochemical profiling of systemic inflammatory markers. The results showed that chitosan-based dressings significantly accelerated burn healing compared to the control treatments. The high-concentration norfloxacin-infused chitosan coated with 2-formylphenylboronic acid’ groups exhibited significant improvements in wound closure and reduced inflammation compared to the other groups; antioxidant enzymes SOD and GPx expression was significantly higher, p < 0.05, whereas pro-oxidative markers such as cortisol were lower (p < 0.05). Macroscopically, the wound area itself was significantly diminished in the chitosan-treated groups (p < 0.05). Furthermore, a histological evaluation indicated enhanced epithelialization and granulation tissue formation within the experiment time frame, while the biochemical panel revealed lower levels of inflammatory cytokines and lower leukocyte counts in the treated groups. These findings highlight the potential of the studied chitosan nanofibers as novel nanosystems for next-generation wound therapies, as well as the clinical utility of the novel chitosan fibers obtained by electrospinning technique.
Dolphin Health Classifications from Whistle Features
Authors: Jones Brittany , Sportelli Jessica , Karnowski Jeremy , McClain Abby , Cardoso David , Du Maximilian
Published: November 2024

Bottlenose dolphins often conceal behavioral signs of illness until they reach an advanced stage. Motivated by the efficacy of vocal biomarkers in human health diagnostics, we utilized supervised machine learning methods to assess various model architectures’ effectiveness in classifying dolphin health status from the acoustic features of their whistles. A gradient boosting classifier achieved a 72.3% accuracy in distinguishing between normal and abnormal health states—a significant improvement over chance (permutation test; 1000 iterations, p < 0.001). The model was trained on 30,693 whistles from 15 dolphins and the test set (15%) totaled 3612 ‘normal’ and 1775 ‘abnormal’ whistles. The classifier identified the health status of the dolphin from the whistles features with 72.3% accuracy, 73.2% recall, 56.1% precision, and a 63.5% F1 score. These findings suggest the encoding of internal health information within dolphin whistle features, with indications that the severity of illness correlates with classification accuracy, notably in its success for identifying ‘critical’ cases (94.2%). The successful development of this diagnostic tool holds promise for furnishing a passive, non-invasive, and cost-effective means for early disease detection in bottlenose dolphins.
A Fast Adaptive AUV Control Policy Based on Progressive Networks with Context Information
Authors: Xu Chunhui , Fang Tian , Xu Desheng , Yang Shilin , Zhang Qifeng , Li Shuo
Published: November 2024

Deep reinforcement learning models have the advantage of being able to control nonlinear systems in an end-to-end manner. However, reinforcement learning controllers trained in simulation environments often perform poorly with real robots and are unable to cope with situations where the dynamics of the controlled object change. In this paper, we propose a DRL control algorithm that combines progressive networks and context as a depth tracking controller for AUVs. Firstly, an embedding network that maps interaction history sequence data onto latent variables is connected to the input of the policy network, and the context generated by the network gives the DRL agent the ability to adapt to the environment online. Then, the model can be rapidly adapted to a new dynamic environment, which was represented by the presence of generalized force disturbances and changes in the mass of the AUV, through a two-stage training mechanism based on progressive neural networks. The results showed that the proposed algorithm was able to improve the robustness of the controller to environmental disturbances and achieve fast adaptation when there were differences in the dynamics.
Improvement of Monacolin K and Pigment Production in Monascus by 5-Azacytidine
Authors: Zhang Chan , Wang Haijiao , Sun Qing , Ablimit Arzugul , Dong Huijun , Wang Congcong , Zhai Duchen , Zhang Bobo , Hu Wenlin , Liu Chengjian , Wang Chengtao
Published: November 2024

Monascus species are known to produce various secondary metabolites with polyketide structures, including Monacolins, pigments, and citrinin. This study investigates the effects of 5-azacytidine on Monascus M1 and RP2. The dry weight, red, yellow, and orange pigment values, and Monacolin K yield of both Monascus strains were measured, and their hyphae observed through electron microscopy. The experimental group showed higher dry weights and pigment values than the control group for both strains. However, Monacolin K production increased substantially only for Monascus M1. Electron micrographs revealed surface wrinkles and large protrusions in both strains after 5-azacytidine treatment. As a potent DNA methylation-promoting agent, 5-azacytidine is very useful for epigenetic and cancer biology studies and for studying secondary metabolism in fungi.
Research on the Mechanism and Identification of Key Influencing Elements for Releasing the Value of Data Elements in Smart Cities
Authors: Hu Mo , Zhang Yunchao , Sheng Fan
Published: November 2024

The development of new information technology makes more people and things connected to the network, expanding the scale of data elements in smart cities; it also makes data a new production factor to drive the development of smart cities, greatly increasing the potential value of smart city data elements. However, this does not mean that smart city data elements can directly provide better products and services. The key to making smart city data elements truly contribute to the efficient operation of smart cities is to release their value. Given this, this paper defined the concept of smart city data element value release, analyzed the mechanism of data element value release in smart cities combined with DPSIR theory, identified five dimensions and 47 influencing factors that affect the data element value release in smart cities, and used the fuzzy-DEMATEL method to further identify 11 key influencing factors from 47 influencing factors. This research helps clarify the mechanism for releasing the value of data elements in smart cities and identify the factors that play a key role in releasing the value of data elements in smart cities in order to maximize the value of data elements in smart cities.
Risk Evaluation of Urban Subway Site Selection: Balance, Attractiveness, and Financing Models
Authors: Liu Yun , Xie Zhiqiang , Wen Ping , Ji Chunhou , Zhu Ling , Wang Qisheng , Zhang Zheng , Xiao Zhuoqian , Ning Bojin , Zhu Quan , Yang Yan
Published: November 2024

As a crucial form of public transportation, subways are becoming essential infrastructure that cities in China increasingly prioritize for development. However, there is a lack of effective risk assessment methods for subway station and line siting. To address this gap, this paper uses the subway system in Kunming, China, as a case study, establishing a subway site risk evaluation framework (SIRE-BAF) that integrates three dimensions: balance (B), attractiveness (A), and financing mode (F). An extended NP-RV model is proposed to assess the balance (or imbalance) characteristics of subway stations based on sub-dimensions of traffic supply, land use, and urban vitality. Findings indicate that (1) the balance (or imbalance) of subway stations is distinctly distributed along the line and simultaneously exhibits a spatial pattern radiating from the urban core to the periphery. (2) Stations with high urban vitality and minimal imbalance are highly attractive and tend to face “undersupply” during operation, whereas stations with lower attractiveness are more prone to “oversupply”. A higher level of BAF coupling coordination suggests a more suitable subway site selection and lower investment risk, while lower coupling coordination indicates increased risk. (3) Excessive reliance on the “subway + real estate” model, without considering urban vitality, may lead to high vacancy rates and reduced efficiency in subway service. This paper further assesses the site selection risks for the proposed Kunming subway. This study contributes to risk assessments of existing subway operations and maintenance in Chinese cities, enhances planning rationality and site selection for proposed subways, and holds potential applicability for other cities.
From an Ideal Village to a Cultural Landscape: Rediscovering People’s Commune Heritage
Authors: Yu Fei , Yu Yue , Wang Rui , Shen Chaoran
Published: November 2024

As an important ideal social practice in world history, the people’s commune system and its organized architectural activities took the first step in promoting rural modernization in modern China and had a significant impact on the built environment of urban and rural areas. This study aims to discuss how to view the legacy of rural people’s communes in service of contemporary society. Taking the Weixing Commune, which was the earliest established commune in China in 1958, as an example, through a comparative study of relevant planning and construction archives and the literature, combined with onsite investigations and through the perspective of the cultural landscape, this study delves into the history of local rural construction and sorts out the types, specific compositions, and value elements of the commune’s remains from four dimensions: environment, industry, architecture, and memory. The heritage of the people’s commune is unique. It was a comprehensive transformation of land to farmland, water conservancy, and other natural environmental patterns carried out by residents and related professionals to realize the ideal life of socialism and ultimately resulted in the shaping of a unique type of cultural landscape, presenting the coexistence of political landscapes that hold ideals and vernacular landscapes that carry life.
Machine Learning-Based Predictions of Metal and Non-Metal Elements in Engine Oil Using Electrical Properties
Authors: Pourramezan Mohammad-Reza , Rohani Abbas , Abbaspour-Fard Mohammad Hossein
Published: November 2024

This study investigates the influence of six metallic and non-metallic elements (Fe, Cr, Pb, Cu, Al, Si) on the quality of engine oil under normal, cautious, and critical conditions. To achieve this, the research employs the Design of Experiments (DoE) approach, specifically the Box–Behnken Design (BBD) method, for designing experiments. The electrical properties of 70 engine oil samples prepared under varying conditions were analyzed. Machine learning models, including RBF, ANFIS, MLP, GPR, and SVM, were utilized to predict the concentrations of the six pollutants in the lubricant oil samples based on their electrical characteristics. The models’ performance was assessed using RMSE and R2 indicators during train, test, and All stages. The results revealed that the Radial Basis Function (RBF) model exhibited the best overall performance (RMSE = 0.01, R2 = 0.99). The study proceeds with optimizing RBF model parameters, such as hidden size (best = 17), spread (best = 0.4 or higher), and training algorithm (best = trainlm), to estimate each pollutant individually. The generalizability of the model was assessed by reducing the training data percentage and increasing the testing data percentage. The results demonstrated the model’s proper performance for all pollutants in various training sizes (RMSE = 0.01, R2 = 0.99). However, as the training data ratio reduced to 60:40 and 50:50, the model’s performance in estimating Cu deteriorated, resulting in increased RMSE values (10.76 or 11.85) and decreased R2 values (0.89 or 0.87) across the All step. This academic research hopes to contribute to the field of applied studies, considering the inherent complexities of lubricants and the challenges in measuring small-scale electrical properties.
Toward Sustainable 3D-Printed Sensor: Green Fabrication of CNT-Enhanced PLA Nanocomposite via Solution Casting
Authors: Sharifi Javid , Rizvi Ghaus , Fayazfar Haniyeh (Ramona)
Published: November 2024

The current study explores, for the first time, an eco-friendly solution casting method using a green solvent, ethyl acetate, to prepare feedstock/filaments from polylactic acid (PLA) biopolymer reinforced with carbon nanotubes (CNTs), followed by 3D printing and surface activation for biosensing applications. Comprehensive measurements of thermal, electrical, rheological, microstructural, and mechanical properties of developed feedstock and 3D-printed parts were performed and analyzed. Herein, adding 2 wt.% CNTs to the PLA matrix marked the electrical percolation, achieving conductivity of 8.3 × 10−3 S.m−1, thanks to the uniform distribution of CNTs within the PLA matrix facilitated by the solution casting method. Rheological assessments paralleled these findings; the addition of 2 wt.% CNTs transitioned the nanocomposite from liquid-like to a solid-like behavior with a percolated network structure, significantly elevating rheological properties compared to the composite with 1 wt.% CNTs. Mechanical evaluations of the printed samples revealed improvement in tensile strength and modulus compared to virgin PLA by a uniform distribution of 2 wt.% CNTs into PLA, with an increase of 14.5% and 10.3%, respectively. To further enhance the electrical conductivity and sensing capabilities of the developed samples, an electrochemical surface activation treatment was applied to as-printed nanocomposite samples. The field-emission scanning electron microscopy (FE-SEM) analysis confirmed that this surface activation effectively exposed the CNTs to the surface of 3D-printed parts by removing a thin layer of polymer from the surface, thereby optimizing the composite’s electroconductivity performance. The findings of this study underscore the potential of the proposed eco-friendly method in developing advanced 3D-printed bio-nanocomposites based on carbon nanotubes and biopolymers, using a green solution casting and cost-effective material extrusion 3D-printing method, for electrochemical-sensing applications.
Reversed Cyclic Behavior of Carbon Nanofiber-Reinforced Concrete Shear Walls
Authors: Lu Liang , Suliman Musaab , Xia Wanqiu
Published: November 2024

This study investigates the effects of integrating carbon nanofibers (CNF) into concrete to enhance the mechanical properties and reversed cyclic behavior of framed shear walls, addressing the need for improved seismic performance and durability. Despite the known benefits of CNF in improving concrete properties and enabling structural health monitoring, its application in framed shear walls has been limited. Through the design and testing of nineteen CNFC formulations, this research established a constitutive relationship allowing the Cyclic Softened Membrane Model (CSMM) to be applied to CNFC. Finite element analysis of shear walls under reversed cyclic loading revealed notable improvements in shear force capacity and ductility when CNF was incorporated. These findings highlight the dual role of CNFC in advancing both material performance and structural resilience, offering a significant contribution to the fields of material science and earthquake engineering.
Crop-Derived Biochar for Removal of Alachlor from Water
Authors: Zawierucha Iwona , Lagiewka Jakub , Gajda Aleksandra , Kwiatkowska-Malina Jolanta , Kulawik Damian , Ciesielski Wojciech , Zarska Sandra , Girek Tomasz , Konczyk Joanna , Malina Grzegorz
Published: November 2024

The presence of various pesticides in natural streams and wastewater is a significant environmental issue due to their high toxicity, which causes harmful consequences even at low quantities. One cost-effective method to remove these pollutants from water could be through adsorption using an inexpensive, easily obtained adsorbent—biochar. The presented research demonstrates the efficacy of applying biochar obtained from wheat grains to eliminate alachlor from water. The sorption properties of the biochar and the likely removal mechanisms are defined. The study found that the biochar removed 76–94% of alachlor, depending on the initial concentration of the pesticide in water. The maximum removal of alachlor (94%) using biochar occurred at an initial pesticide content of 1 mg/L. Both the pseudo-second-order kinetic (R2 = 0.999) and the Langmuir isotherm models (R2 = 0.996) effectively characterized the elimination of alachlor by wheat grain biochar. The biochar’s maximum adsorption capacity for alachlor was 1.94 mg/g. The analyzed biochar, with its micropores and various surface functional groups, was able to effectively adsorb alachlor and trap it within its structure.
A Biochemistry-Inspired Algorithm for Path Planning in Unmanned Ground Vehicles
Authors: Almoaili Eman , Kurdi Heba
Published: November 2024

Unmanned ground vehicles (UGVs) have gained significant attention due to their extensive applications in both military and civilian sectors. For effective UGV deployment, path planning algorithms must prioritize computational efficiency, solution reliability, and runtime performance while maintaining path quality. Autonomous path planning remains a critical challenge in UGV navigation, as conventional methods, while effective, often suffer from considerable computational overhead. To address this issue, we propose a novel biochemistry-inspired path planning algorithm designed specifically for static grid-based scenarios. MetaPath demonstrates remarkable computational efficiency while maintaining solution quality across different obstacle densities in benchmark environments. Specifically, the algorithm achieves path lengths within ±5% of all benchmark algorithms while dramatically reducing the exploration space, visiting up to 10% of the cells explored by conventional approaches such as A*. This superior efficiency translates into exceptional runtime performance, executing up to 3000 times faster than bio-inspired algorithms like Ant Colony Optimization (ACO) and the Genetic Algorithm (GA), performing nearly three times faster than the widely used A* algorithm, and maintaining competitive performance with efficient algorithms like Breadth-First Search (BFS) and Particle Swarm Optimization (PSO), thereby establishing the algorithm as a highly efficient pathfinding solution. Most notably, MetaPath introduces a novel approach as the first chemistry-inspired pathfinding algorithm, guaranteeing path discovery when one exists within reasonable computational time, a crucial advantage over some benchmark algorithms that may fail to converge or require excessive computational resources in complex scenarios.
Modeling of the Solid Stress Tensor in the MP-PIC Method: A Review of Methods and Applications
Authors: Henríquez-Vargas Luis , Donoso-García Pablo , Lackey Lawrence , Bravo-Gutiérrez Mauricio , Cajas Benjamín , Reyes Alejandro , Pailahueque Nicolás , Díaz-Aburto Isaac , Bubnovich Valeri
Published: November 2024

In recent years, the fast growth of computational power has allowed the application of computational fluid dynamics (CFD) in a wide range of areas of interest, such as gas–solid unit operations. In this context, the multiphase particle-in-cell (MP-PIC) method appears as an option to represent fluid–particle and particle–particle interactions, avoiding the complexity of tracking each particle and the high computational cost derived from this. The MP-PIC method can represent the particles as a group with the same characteristics, allowing the simulation of gas–solid systems at different scales. To achieve this, the particle–particle interactions are simplified using the solid stress tensor to represent them; this does not require explicit expressions. This approach has a low computational cost, allowing the simulation of industrial cases using just workstations. This paper provides a review of the literature on the solid stress tensor and its commercial and non-commercial applications, including its historical and mathematical development in the description of particle–particle interactions. In addition, to consolidate the knowledge and advancing understanding in this crucial aspect of multiphase flow simulations, this review identifies the current challenges and opportunities for future research in multiphase systems based on the solid stress tensor. In addition, this review identifies the current challenges and opportunities for future research in multiphase systems based on the solid stress tensor.
General Approach to Function Approximation
Authors: Liptaj Andrej
Published: November 2024

Applying a predefined set of functionals to a function provides a set of numbers which characterize the function. One can then interpret an approximation very generally as a construction of some function form which reproduces these numbers if the same functionals are used. A large number of existing approximations can be interpreted in this way, and we review some of them. In addition, we construct several new expansion types including three rational approximations.
Approximation of Time-Frequency Shift Equivariant Maps by Neural Networks
Authors: Lee Dae Gwan
Published: November 2024

Based on finite-dimensional time-frequency analysis, we study the properties of time-frequency shift equivariant maps that are generally nonlinear. We first establish a one-to-one correspondence between Λ-equivariant maps and certain phase-homogeneous functions and also provide a reconstruction formula that expresses Λ-equivariant maps in terms of these phase-homogeneous functions, leading to a deeper understanding of the class of Λ-equivariant maps. Next, we consider the approximation of Λ-equivariant maps by neural networks. In the case where Λ is a cyclic subgroup of order N in ZN×ZN, we prove that every Λ-equivariant map can be approximated by a shallow neural network whose affine linear maps are simply linear combinations of time-frequency shifts by Λ. This aligns well with the proven suitability of convolutional neural networks (CNNs) in tasks requiring translation equivariance, particularly in image and signal processing applications.
Precision Denoising in Medical Imaging via Generative Adversarial Network-Aided Low-Noise Discriminator Technique
Authors: Alanazi Turki M. , Mercorelli Paolo
Published: November 2024

Medical imaging is significant for accurate diagnosis, and here, noise often degrades image quality, thus making it challenging to identify important information. Denoising is a component of traditional image pre-processing that helps prevent incorrect disease diagnosis. Mitigating the noise becomes difficult if there are differences in the low-level segment features. Therefore, a Generative Adversarial Network (GAN)-aided Low-Noise Discriminator (LND) is introduced to improve the denoising effectiveness in medical images with a balanced image resolution with noise mitigation. The LND function is a key that distinguishes between high- and low-noise areas based on segmented features, which are also achieved by tuning the peak signal-to-noise ratio (PSNR). Considering the training sequences, the LND-identified intervals lessen the sequences to improve the changes in pixel reconstruction. The generator function in this method is responsible for increasing the PSNR improvements over the different pixels cumulatively. The proposed method successfully improves the pixel reconstruction by 11.05% and PSNR by 9.75%, with 9.75% less reconstruction time and 13.11% less extraction error for the higher pixel distribution ratios than other contemporary methods.
Evaluating Self-Directed Rehabilitation for Knee and Hip Arthroplasty During the COVID-19 Pandemic: A Multicenter Study
Authors: Miner Todd M. , Anderson Mike B. , Van Andel David C. , Neher Robert E. , Redfern Roberta E. , Duwelius Paul J.
Published: November 2024

The COVID-19 pandemic has triggered the adoption of new technologies to reduce the need for in-person physical therapy (PT). This study evaluated the impact of the COVID-19 pandemic on PT utilization and outcomes of patients prescribed a smartphone-based care management platform (sbCMP) for self-directed rehabilitation (SDR). A secondary analysis of data collected in a multicenter, prospective cohort trial investigating a mobile platform to deliver SDR after arthroplasty was performed. Patients who used the sbCMP for 2 weeks prior to undergoing partial knee arthroplasty (PKA), total knee arthroplasty (TKA), or total hip arthroplasty (THA) and provided 3 months of post-operative data were included. Use of adjunct PT at 3 months, step counts, and KOOS JR and HOOS JR scores were compared during the early versus late pandemic period. The cohort data was available for 1665 patients. Use of SDR without adjunct PT was higher in the early period of the COVID-19 pandemic in TKA (35.3% vs. 27.6%, p = 0.03) and THA (72.5% vs. 59.3%, p < 0.001), but not in the PKA cohort (58.9% vs. 53.3%, p = 0.53). Post-operative step counts improved at 3 months compared to pre-operative levels in all procedure types. Change in HOOS JR and KOOS JR scores from pre-operative to post-operative levels were similar by pandemic period in all cohorts. Use of SDR increased early during the COVID-19 pandemic, corresponding to pandemic restrictions, without negatively impacting patient outcomes. SDR facilitated via a sbCMP may be beneficial for patients unable or unwilling to participate in traditional PT visits.
Correction: Shehabeldine et al. Antimicrobial, Antibiofilm, and Anticancer Activities of Syzygium aromaticum Essential Oil Nanoemulsion. Molecules 2023, 28, 5812
Authors: Shehabeldine Amr M. , Doghish Ahmed S. , El-Dakroury Walaa A. , Hassanin Mahmoud M. H. , Al-Askar Abdulaziz A. , AbdElgawad Hamada , Hashem Amr H.
Published: November 2024

In the original publication [...]
Identification and Reconstitution of the First Two Enzymatic Steps for the Biosynthesis of Bioactive Meroterpenoids from Hericium erinaceus (Lion’s Mane Mushroom)
Authors: Iacovelli Riccardo , Poon Fons , Haslinger Kristina
Published: November 2024

Hericium erinaceus (Lion’s Mane mushroom) is widely consumed for its numerous reported benefits for brain health. A growing body of evidence suggests that these benefits are likely attributable to aromatic compounds contained in its fruiting bodies, including the meroterpenoids hericenones. Here, we report the identification and reconstitution of the first two steps of the biosynthetic pathway of hericenones via heterologous expression of the polyketide synthase HerA and the carboxylic acid reductase HerB in Aspergillus oryzae. Furthermore, we investigated a putative prenyltransferase that might be responsible for the following biosynthetic step. Ongoing efforts to reconstitute the full pathway will enable large-scale production of hericenones and other meroterpenoids in heterologous hosts.