bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanically-Adaptive, Resveratrol-Eluting Neural Probes for Improved Intracortical Recording Performance and Stability
Authors: Mueller Natalie N. , Ocoko Mali Ya Mungu , Kim Youjoung , Li Kate , Gisser Kaela , Glusauskas Gabriele , Lugo Isabella , Dernelle Peter , Hermoso Anna Clarissa , Wang Jaime , Duncan Jonathan , Capadona Jeffrey R. , Hess-Dunning Allison
Published: December 2024

Intracortical microelectrodes are used for recording activity from individual neurons, providing both a valuable neuroscience tool and an enabling medical technology for individuals with motor disabilities. Standard neural probes carrying the microelectrodes are rigid silicon-based structures that can penetrate the brain parenchyma to interface with the targeted neurons. Unfortunately, within weeks after implantation into the brain, neural recording quality from microelectrodes degrades, owing largely to a neuroinflammatory response. Key contributors to the neuroinflammatory response include mechanical mismatch at the device-tissue interface and a state of oxidative stress. We developed a mechanically-adaptive, resveratrol-eluting (MARE) neural probe to mitigate both mechanical mismatch and oxidative stress and thereby promote improved neural recording quality and longevity. In this work, we demonstrate that compared to rigid silicon controls, highly-flexible MARE probes exhibit improved recording performance, more stable impedance, and a healing tissue response. With further optimization, MARE probes can serve as long-term, robust neural probes for brain-machine interface applications.
Comparison of Ensemble Techniques for Early Prediction of Alzhiemer Disease
Authors: Orlunwo Placida Orochi , Onuodu Friday Eleonu
Published: December 2024

Alzheimer's disease (AD) is a progressive neurological condition characterized by a loss in cognitive functions, with no disease-modifying medication now available. It is crucial for early detection and treatment of Alzheimer's disease before clinical manifestation. The stage between cognitively healthy older persons and AD is known as mild cognitive impairment (MCI). To predict the transition from one-stage MCI to probable AD, five ensemble learning approach was used (Stacking, Gradient boost Bagging, Adaptive boost and Voting), an integrated model that combines not only cross-sectional neuroimaging biomarkers at baseline but also longitudinal cerebrospinal fluid (CSF) and cognitive performance biomarkers from the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI). The adaptive boost, stacking and bagging ensemble approach has shown potential to identify those at risk of developing Alzheimer's disease, this would benefit them the most from a clinical trial or to use as a stratification approach inside clinical trials.
Adaptive hybrid potential evapotranspiration (PET) prediction method based on automatic machine learning
Authors: Chenjia Zhang , Tianxin Xu , Yan Zhang , Abullimiti Abdu Kaimu , Yutong Zhang , Lirui Guo , Daokun Ma
Published: December 2024

In arid areas, estimation of crop water demand through potential evapotranspiration (PET) forecast has a guiding effect on water-saving irrigation, to cope with the crisis of water shortage. Neural network-based PET prediction methods is considered to have huge application potential because of its small prediction error. However, the physical conditions and data quality in different regions make the choice of neural network different, making it difficult to provide a general PET prediction method. So an adaptive hybrid model based on automatic machine learning for short-term PET prediction is proposed coupling neural network and PET formula. Process is divided into two stages: learning and forecasting. Learning stage includes three modules: meteorological data reconstructing, adaptive data set generation and adaptive hybrid model (PET calculation formula + neural network) selecting. Forecast stage includes two modules: adaptive data set generation and rolling prediction. 105 standard weather stations in Xinjiang were used as data sets (43 of them had missing data) to test model. According to modules, networks and PET formulas used in the prediction process, corresponding labels were generated in each dataset forecast result. Ratio of training set and test set for each data set was 8:2. Grid search was used to optimize the best hyperparameter combination. In test set, the average absolute error (MAE) and average squared error (MSE) of the model prediction were 0.338mm and 0.270, achieving high prediction accuracy. The mean prediction error is smaller to any single mixed model. We demonstrate that the neural network applicability varies among the used data sources, and Gate Recurrent Unit (GRU) and 1 Dimension convolutional neural network (1DCNN) are more suitable for the selected datasets, while Long Short Term Memory network (LSTM) and Multilayer Perceptron (MLP) are not applicable. Combined with the analysis of the labels, We find evidences that applicability of neural networks and PET formulas is independent of geographic region and degree of drought. In 2023, method of rolling prediction for 1-15 days is verified, and the verification results show that PET prediction error based on neural network is significantly smaller than useing weather forecast data to calculate PET. In addition, by comparison,we determined that adaptive input length can effectively reduce the prediction error, MAE was 27.52% smaller than fixed input length, and MSE was 45.76% smaller than fixed input length. The proposed method realized the automatic machine learning of PET forecast, can predict PET more accurately, and can be further expanded by adding neural networks and PET formulas to improve its generalization ability.
Examination of new clinical dental caries in school children using real intra oral photos with artificial intelligence model YOLO-V8x
Authors: Fadilah Rina Putri Noer , Rikmasari Rasmi , Akbar Saiful , Setiawan Arlette Suzy Puspa Pertiwi
Published: December 2024

Background Dental caries is one of the most common chronic diseases in school-aged children, with a prevalence above 80% in Indonesia. Traditional diagnostic practices are time-consuming and dependent on the number of healthcare professionals available, and as such, have led to the creation of AI-based alternatives, such as the HI Bogi application. This research used the YOLO-v8 model to assist in the detection of dental caries, which is faster, more efficient, and highly accurate, and can be developed to enhance existing dental health programs in schools in IndonesiaMaterials and Methods A dataset of 3,221 JPG images labeled using the ICDAS D0 to D1 method was prepared and processed using Roboflow labeling software, and the images were resized to 640×640 pixels to standardize the input for model training. The dataset was divided into training (2,266 images), validation (635 images), and testing (320 images) subsets. The YOLOv8x algorithm was used for deep learning and the performance of the model was evaluated using confusion matrix analysis to calculate True Positive (TP), False Positive (FP), and False Negative (FN) values. Statistical Mann–Whitney tests were conducted to compare the classification accuracy between the AI model and dentists across the ICDAS categories, whereas a diagnostic speed test assessed the efficiency of the AI model relative to dentists.Results The YOLO-v8 model showed encouraging results, with a recall of 41.1%, accuracy of 72.6%, and mAP of 45.8%. P-values of 0.301 for D1, 0.690 for D2, 0.621 for D3, 0.693 for D4, 0.634 for D5, and 0.302 for D6 were obtained from comparative testing with dentists. These results showed no significant variations in the sensitivity, specificity, PPV, or NPV among the ICDAS categories (p > 0.05). Furthermore, AI performed much faster than the dentists during the examinations (p = 0.000). AI may improve the efficiency and efficacy of early caries diagnosis as demonstrated by these findings.Conclusion The YOLO-v8 model integrated into the application showed promising results in early caries detection, comparable to those of dentists across all ICDAS criteria. AI significantly outperformed dentists in terms of examination speed and completed tasks four times faster. Future research should explore transformer-based models to improve accuracy and expand the datasets to enhance the ability of the model to identify diverse caries categories, including rare lesions.
Mutation of the LRG1 Rho-GAP gene is responsible for the hyper branching C-variant phenotype in the Quorn mycoprotein fungus Fusarium venenatum A3/5
Authors: Connell John , Bates Helen J. , Geoghegan Ivey , Wilson Fiona , Harrison Richard J. , Price R. Jordan
Published: December 2024

Background
Quorn mycoprotein, a protein-rich meat alternative, is produced through large-scale fermentation of the fungus Fusarium venenatum. However, a major challenge during F. venenatum fermentation is the consistent appearance of mutants called colonial variants (C-variants). These C-variants have a highly branched morphology, which ultimately lead to a less desirable final product and early termination of the fermentation process. This study aimed to identify the genetic mutations responsible for C-variant morphology.
Results
We first isolated both C-variant and wild-type strains from commercial fermentation samples and characterised radial growth rates on solid media. Whole genome sequencing facilitated the identification of mutations in a gene called jg4843 in 11 out of 12 C-variant isolates, which was not observed in the wild-type isolates. The jg4843 gene was identified as the ortholog of LRG1, a Rho-GTPase activating protein that regulates the Rho1 signalling pathway affecting fungal growth.
Notably, the mutations in jg4843 were primarily located in the RhoGAP domain responsible for LRG1 activity. To confirm the role of these mutations, we used CRISPR/Cas9-mediated homology-directed recombination to introduce the C-variant mutations into the wild-type isolate, which successfully recapitulated the characteristic C-variant morphology.
Conclusions
This study identified mutations in the LRG1 ortholog jg4843 as the genetic cause of C-variant morphology in commercial fermentation F. venenatum isolates. Understanding this genetic basis paves the way for developing strategies to prevent C-variants arising, potentially leading to more efficient and sustainable production of Quorn mycoprotein.
RSGM: A Multimodal Image Matching Scheme Guided by Regional Semantics
Authors: Jin Fangwei , Liao Yun , Liu Junhui , Qian Xu , Li YunPeng , Teng RongRui , Hu ZongXiao , Duan Qing
Published: December 2024

Multimodal image feature matching technology plays an important role in computer vision research, and a lot of work has been done to improve the matching performance. However, existing matching methods lack sufficient extraction of descriptor information and clear semantic guidance during the matching process. Most descriptors only contain pixel information, neglecting region-based and inter-image information. While some approaches attempt to incorporate semantic information into descriptors, they do not utilize this information during the actual matching stage, leading to potential incorrect matches when similar object types are present in the images. In order to solve these problems, We put forward a new multimodal local image feature matching method that includes a novel descriptor extraction method and a new matching scheme. During the feature extraction and fusion stage, similarity information, regional semantic information of image pairs, as well as neighboring pixel information of corresponding match points from different images are fused to enrich the feature descriptors. In the matching stage, a method guided by regional semantic information(RSGM) is employed to enhance the overall matching effect. Finally, extensive experiments demonstrate that RSGM performs exceptionally well on multimodal image datasets. The code for RSGM is available at: https://github.com/LiaoYun0x0/RSGM.
Perceptions of voluntary workers in cancer organisations on the knowledge of secondary breast cancer symptoms , healthcare communication and diagnostic referral pathways among the patients they support in Northern Ireland
Authors: Boma Charity Ibiyekaribo , Flannagan Carrie , Warwick Jacque
Published: December 2024

Background: In secondary breast cancer (SBC) cancer cells spread to other areas of the body and at this stage treatment is no longer curative. Studies show increase in SBC prevalence in the United Kingdom (UK) and also linked early detection to lower mortality rates and better prognosis. Studies have reflected that adequate healthcare communication can enhance early diagnosis and improve patients' quality of life.
Aim: Explore perceptions of voluntary workers in cancer organisations on knowledge of SBC symptoms, healthcare communication and diagnosis impact among patients they support in Northern Ireland (NI). Method: Descriptive exploratory approach using semi-structured interviews with a purposive sample of five voluntary workers from breast cancer organisations between June-August 2023. Data was analysed using thematic analysis to develop descriptive themes.
Results: Themes developed include: Lack of awareness and knowledge of SBC; Communication gap in breast cancer care provision; Impact of diagnosis; Gaps in SBC cancer care. Findings suggest limited support for SBC patients, healthcare communication is not optimal, and impacts patients' experiences and delayed diagnosis. Awareness of patients, public, HCPs is unclear and there are limited SBC nurses, support groups, information on SBC, limited access to clinical trials, and treatment options for SBC patients.
Conclusions: SBC awareness is limited in NI, therefore efforts to provide more information and better support for SBC patients through provision of more SBC nurses, support groups and accessibility to clinical trial can facilitate better experiences through their illness journey. HCPs training on person-centred communication can influence better outcomes for SBC patients.
Decoding Hotel Ratings: A Cultural and Developmental Lens on Traveler Behavior
Authors: Marukhlenko Daria , Lensky Artem , Feroz Gohar
Published: December 2024

Using a large dataset of 545,000 reviews from 27,000 hotels, this study investigates how travelers’ nationalities influence hotel review ratings and their relationship with cultural dimensions and human development indicators. The presented analysis shows that hotel ratings can serve as predictors of components of the Human Development Index, with the Education Index showing the strongest association (adjusted R2 is 42.6%). The predictive power of hotel ratings was also compared to Hofstede’s dimensions in the context of predicting Human Development Index components.
In terms of Hofstede’s dimensions we discovered that ”Individualism vs Collectivism” and ”Long-Term Orientation” dimensions exhibit the strongest associations with hotel ratings (adjusted R2 is 44.9% and 30.1% correspondingly), though the study’s focus on European hotels may limit generalizability.
In terms of rating patterns, English-speaking countries and Israel use narrower score ranges with higher means (8.66±1.46), while predominantly Muslim countries employ wider ranges, resulting in lower means (7.96 ± 1.79). European and Asian countries generally fall between these extremes.
The paper concludes with practical implications of the presented findings to the tourist recommender systems.
Quantification of mechanical fields inside invasive cancer cells: Description of a new method using Digital Volume Correlation and Confocal Microscopy
Authors: Gangneux Aurélie , Gaboriau Aymerick , Caille Laetitia , Mesnil Marc , Bokam Prasanth , Vendeuvre Tanguy , Sebille Stéphane , Defamie Norah , Germaneau Arnaud
Published: December 2024

Cell invasion process, which appears in the progression of tumors, such as glioblastoma, is highly dependent on cellular mobility. Cellular movement results from the interaction of chemical, biological and mechanical factors both inside and outside the invasive cancer cell. To identify and understand the relationship between these factors, it is necessary to quantify and visualise the extra- and intracellular kinematic fields during cell movement. This study proposes a new methodology for the experimental measurement of full kinematic fields inside cancer cells and the use of a digital twin simulation of the cell to obtain the stress and force fields. This approach combines confocal microscopy, Digital Volume Correlation (DVC), and the Finite Element Method (FEM) to achieve precise and comprehensive measurements. To demonstrate the efficiency of this methodology, highly invasive cells from human glioblastomas have been used as a model, and their mechanical behaviour on a substrate was studied over time during their development.
Development of fuzzy logic-based expert systems for optimizing TIG welding parameters of low carbon steel plates
Authors: Aloraier Abdulkareem , Ikpe Aniekan
Published: December 2024

The complex experimental procedure involved in TIG welding sequence, selection of ideal input parameters and further challenges during tensile testing to obtain the ultimate tensile strength (UTS) value of a given material may lead to inaccurate output depending on the experimental and test procedures. Moreover, while traditional optimization techniques which is sometimes based on trial and error, or prolonged experimental process may be time-consuming and costly, fuzzy logic-based expert systems offer a more effective solution to optimizing welding input variables for optimal output response. In this study, TIG welding input parameters derived from design of experiment for 20 weld runs were employed in welding AISI 1015 low carbon steel plate, and the welded samples were subjected to tensile testing to determine the UTS values. UTS of the control sample was obtained as 385 MPa, while UTS values of 409.670, 412.265, 410.256, 414.624, 415.563, 413.314, 411.432 and 408.306 MPa were obtained from the tensile test with corresponding welding input parameters (voltage, current, welding speed and gas flow rate, from weld runs No. 4, 5, 7, 8, 13, 14, 15 and 18. However, optimal UTS values of 407.923, 411.186, 408.874, 414.123, 415.116, 411.874, 409.702 and 406.827 MPa were obtained from the fuzzy logic optimization at the same No. of weld runs. Regression plot of the experimental and fuzzy logic predicted output response revealed R2 value of 0.9892 which is very close to 1, indicating the accuracy of the optimization sequence. This was further confirmed from a correlation plot which clearly indicated a strong positive correlation between the experimental and fuzzy optimized UTS values. The robust results of the study demonstrate the effectiveness and reliability of the fuzzy logic-based expert system in optimizing TIG welding parameters for low carbon steel plates.
Design and Application of Fluorescent Probes Based on Flavonoid Dyes for Cysteine Detection
Authors: Liu Jing , Cao Xiaorui , Liu Tiantian , Zhang Yang , Jiao Xiaomeng , Zhang Hongpeng , Bai Yinjuan
Published: December 2024

As an important reactive sulfur species, cysteine plays a crucial role in maintaining the body's redox homeostasis and regulating protein function. Its content in organisms can serve as signaling molecules to directly or indirectly detect certain diseases. Therefore, based on the Michael addition mechanism, five flavonoid fluorescent probes HFL1-5 were designed and synthesized to detect cysteine. Through specific descriptions of IR, 1H NMR, and HRMS experiments, the recognition mechanism of cysteine by HFL was studied, demonstrating that HFL1-5 could generate flavonol derivatives with strong fluorescence emission through addition-cyclization-removal. The probes were evaluated for sensitivity, stability, specificity, and cytotoxicity, and the reasons for the differences in response effects were explained based on their structures. Finally, the best performing HFL5 was selected for cell imaging experiments and successfully applied to the imaging of endogenous and exogenous cysteine in L929 cells. This study indicates that HFL has great potential for application in detecting cysteine.
Design and Application of Algae Light Sensing Circuit Based on Memristor
Authors: Sun Jingru , Ma Wenjing , Li Xiaosong , Sun Yichuang , Hong Qinghui , Zhang Jiliang
Published: December 2024

Visual perception systems are of great significance in AI, robotics, and IoT. Despite the satisfactory results achieved by existing photography and camera equipment, issues such as high cost, slow sensing speed, complex structures, and high power consumption remain due to the limitations of their circuit structures. Over hundreds of millions of years of evolution, algae have developed a photosensitive system with a simple structure but high sensitivity and fast response speed. In recent years, significant progress has also been made in the study of algal photosensitivity. Inspired by the photosensitive system of algae, this paper presents an algal photoreceptors model and designs an algal light sensing circuit (ALSC) based on memristors. The ALSC mimics the photosensitive neurons of green algae to perceive optical intensity and accomplishes the high-speed conversion of light signals to spike signals. ALSC has characteristics like a simple structure, high robustness, high nonlinearity, and low power consumption. To evaluate the performance of the proposed ALSC, we implemented it in the spiking camera optic perception module. The simulation and experimental results indicate that, in comparison with the traditional spiking cameras, the structure of the spiking camera based on ALSC is simpler, the conversion speed is increased by 200\%, the power consumption is reduced by 50\%, and it has the characteristics of high robustness and sensitivity. In addition, the circuit structure of visual neurons has high universality. It can be applied to various sensor devices, including touch, smell, temperature, and others, which is significant for the manufacturing of new sensor technologies.
Integrative analysis of taurine metabolism-related genes prognostic signature with immunotherapy and identification of ABCB1 and GORASP1 as key genes in nasopharyngeal carcinoma
Authors: Feng Zhang , Yang Yuhang , Luo Wenqi , Li Jinqing , Xie Zhenlian , Zuo Long , Duan Meijiao , Zuo Dongzhi , MO Ruwei , Tang Xuejing , Yi Shijiang , He Xiaosong , Liu Fangxian , Ma Ning , He Feng
Published: December 2024

Background: Nasopharyngeal carcinoma (NPC) is a highly aggressive malignancy prevalent in Southeast Asia and Southern China, and is characterized by a lack of effective early diagnostic and therapeutic approaches. The 5-year survival rate of patients with advanced NPC remains dismally low (<40%). Therefore, the development of a novel predictive model for prognostic risk of NPC is of paramount importance.
Methods: We integrated data from the Genecards, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Expression Omnibus (GEO) databases to identify differentially expressed genes associated with taurine metabolism in NPC patients. Gene Ontology (GO) and KEGG analyses were conducted to investigate the underlying mechanisms. Subsequently, Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct a taurine metabolism-related prognostic signature. Survival, medication sensitivity, and immunological microenvironment evaluations were performed to assess the prognostic utility of the model. Finally, immunohistochemistry (IHC) experiments were performed to validate the model’s prognostic reliability.
Results: Our prognostic model was based on three pivotal taurine metabolism-related genes (TMRGs) (ABCB1, GORASP1, and EZH2). Functional analysis revealed a strong association between TMRGs and miRNAs in cancer. Notably, increased risk scores correlated with worsening tumor malignancy and prognosis. Significant disparities in immune microenvironment, immune checkpoints, and drug sensitivity were observed between the high- and low-risk groups. The protein expression patterns of the selected genes in clinical NPC samples were validated using immunohistochemistry.
Conclusions: A taurine metabolism-related prognostic model for NPC was established based on three genes that effectively predicted the prognosis and response to immunotherapy in patients with NPC. This model offers the potential for improved NPC management.
Aboveground biomass in smallholder Eucalyptus plantations throughout stand rotation in Madagascar: influence of low starter fertilization and weed competition
Authors: Ramanandraibe Iaviantsoa , Bordron Bruno , Sarron Julien , Razafindrakoto Fenitra , Epron Daniel , Rasoarinaivo Angelina , Razafimbelo Tantely Maminiaina , Bouillet Jean-Pierre
Published: December 2024

Smallholder Eucalyptus plantations (EP) in Madagascar Central Highlands (MCH) address substantial fuelwood demand and reduce pressure on natural forests. However, their sustainability is challenged by low soil fertility and inadequate management. While fertilization increases tree growth, high mineral fertilizer costs limit its use by smallholder farmers. Both biomass estimating equation and impact of fertilization on smallholder EP in MCH remain poorly documented. This study aimed to evaluate the impact of low starter mineral fertilization (15 kg.ha-1 N, 12 kg.ha-1 P, and 17 kg.ha-1 K) and weed competition on smallholder Eucalyptus robusta growth and aboveground biomass (AGB) while providing allometric equations for AGB estimation. Dendrometric data were collected from six stands aged 2 to 6 years, with fertilized and non-fertilized parts. AGB of 16 trees per stand (8 fertilized, 8 non-fertilized) were destructively measured. AGB of trees were estimated by regression based on tree circumference, height and their combinations. The results indicated circumference as the best single variable predictor (R2 > 0.90) for all tree compartments and stands Fertilization significantly improved global tree survival by 7% and increased height by 3.1 m and circumference by 8.3 cm in 6-year-old stands AGB per hectare globally doubled with fertilization, reaching 55.3 Mg.ha-1at 6 yo compared to 29.2 Mg.ha-1 in non-fertilized plots. Weed cover and biomass had significant negative linear relationships with AGB and survival rate. This study provides robust allometric equations for biomass estimation and highlights that even low fertilizer application combined with effective weed control can significantly enhance AGB production in smallholder EP.
Solid-phase pyrolysis synthesis of nitrogen-doped carbon dots as logic-gate fluorescent probes for dual detection of Cu²⁺ and glutathione
Authors: Yao Zhuoru , Wang Cunjin , Ma Zixin , Zhang Jing , Zhao Xiaoliang , Zhang Weijie , Shi Huanxian
Published: December 2024

This study introduces the synthesis of nitrogen-doped carbon dots (N-L-Ser-CDs) from L-serine and urea through a straightforward and economical one-step solid-phase pyrolysis process. The incorporation of nitrogen into the carbon dots resulted in a remarkable 27.6-fold increase in fluorescence intensity, featuring a peak emission at 405 nm when excited at 330 nm and a significant fluorescence quantum yield of 22.5%. These N-L-Ser-CDs displayed a specific binding affinity for Cu2+, leading to a pronounced fluorescence quenching effect. However, upon interaction with glutathione (GSH), the fluorescence of the N-L-Ser-CDs + Cu2+ complex was selectively restored. This restoration was attributed to the displacement of Cu2+ from the surface of the N-L-Ser-CDs due to the strong interaction between GSH and Cu2+. The mechanism underlying this fluorescence quenching was elucidated as an electron transfer process from the excited state of the N-L-Ser-CDs to Cu2+. Additionally, the sensor developed in this study exhibited a linear detection range of 0–90 µM for Cu2+ with a detection limit of 3 µM, and a linear detection range of 0-120 µM with a detection limit of 3 µM for GSH. By integrating the detection capabilities for both Cu2+ and GSH, a successful logic-gated fluorescent probe was developed. Most importantly, this proposed method offers simplicity, affordability, and ease of use, while also showing potential for practical GSH detection in real urine samples.
Comparative effects of selenium and N-Acetyl cysteine on oxidative stress in Nω-Nitro-L-arginine methyl ester hydrochloride (L-NAME) induced preeclamptic wistar albino rats
Authors: Yelleti Geethika , Aroor Annayya Rao , Shenoy Revathi P , karmakar Abhibroto , Rao Ashwini V , Lewis Cheryl Rhea , Asok Arjun , Maripini Nihaal , Biswas Monalisa , Varier Veena , Roy Arpita , BS Varashree
Published: December 2024

Background/Objectives: Preeclampsia (PE) is a hypertensive disorder in pregnancy affecting multiple organ systems, leading to significant maternal and perinatal morbidity and mortality. While the exact mechanisms remain unclear, oxidative stress and inflammatory responses are key factors. This study hypothesized that these factors contribute to pathogenesis of preeclampsia, and that selenium and N-acetylcysteine (NAC) could mitigate these effects.
Methods: Twenty-four female Wistar rats were divided equally into four groups. Group I served as controls, while Groups II, III, and IV received Nω-Nitro-L-arginine methyl aster hydrochloride (L-NAME) to induce hypertension from day 4 to 20 ofgestation. Additionally, Group III received selenium (240 μg/kg/day) and Group IV received NAC (160 mg/kg). On day 20, blood and urine samples were collected to measure malondialdehyde (MDA) and interleukin-6 (IL-6) levels, as markers of oxidative stress and inflammation, respectively. Serial blood pressure measurements were recorded for all the group.
Results: Selenium improved L-NAME-induced hypertension and proteinuria and significantly reduced the inflammatory response but had little effect on oxidative stress. NAC did not lower blood pressure but significantly reduced proteinuria, IL-6 levels, and oxidative stress.
Conclusions: These findings suggest that selenium and NAC have distinct protective roles, potentially offering combined benefits for cardiovascular and kidney health in hypertensive pregnancies.
Overexpression of MIR-302C-3P Leads to Apoptosis in Human Renal Mesangial Cells
Authors: Huang Wentao , Hao Baojun , Chen Yongqiang , Lin Jinyan , Wu Ting-Ting , Liu Shiwen , Xu Dan , Liang Huixin , Lin Ying , Huang Yingzhen , Wang Qun , Le Jiong , Qian Yi , Qin Shulan
Published: December 2024

Objective: The apoptosis of glomerular mesangial cells is closely related to the occurrence and development of diabetic nephropathy (DN). However, the mechanism remains unclear. In the present study, we found that the high-glucose cultures induced the upregulation of the miRNA-302c-3p. This study aimed to investigate the effects of over expression of miR-302c-3p on human glomerular mesangial cells (HRMCs).
Materials and Methods: HRMCs were cultured in vitro and divided into 2 groups: ①: siRNA-NC group, ② siRNA-TIMP3 group. The miR-302c-3p expression was up-regulated in HRMCs by using miR-302c-3p mimic. We measured the expression of MDA, SOD, CAT, and ROS to examine the oxidative stress of cells. The apoptosis rate of cells was determined by flow cytometry, and the mitochondrial membrane potential (MMP) was examined by the JC-1 detection kit. Real-time polymerase chain reaction (PCR) was used to detect the relative expression of p53 and Survivin. Protein expression of Bcl-2, BAX, caspase-3, p27, Apaf-1, Cytochrome C, and β-actin was analyzed by Western blot.
Results: Compared with the control group, we found that the overexpression of miR-302c-3p significantly increased the oxidative stress and apoptosis on HRMCs. The level of p53 was significantly increased (p<0.01), and the level of Survivin was reduced significantly (p<0.05) in the miR-302c-3p mimic group. Western blot results showed that the expression of BAX, p27, Apaf-1 and Cytochrome C was significantly up-regulated; the expression of Bcl-2 was significantly down-regulated in the HRMCs in miR-302c-3p mimic group.
Conclusions: These findings indicated that overexpression of miR-302c-3p induced the apoptosis of HRMCs, and might be associated with the oxidative stress.
Use of a companion robot at home by older people with cognitive decline and psychosis: A case series with 18-month follow-up
Authors: Nagata Yuma , Satake Yuto , Yamazaki Ryuji , Nishio Shuichi , Ishiguro Hiroshi , Ikeda Manabu
Published: December 2024

Objectives
Although studies have reported the efficacy of companion robots for psychological support in older people, most are limited to short-term use or use within nursing home settings. In this study, we describe the five cases using a companion robot to elucidate the benefits and challenges of deploying conversational, autonomous humanoid robots for community-dwelling older adults with cognitive decline over an extended period.
Methods
Case series. Participants were recruited between July and November 2020 from patients visiting memory clinics in Japan who were 1) aged 60 or more, 2) living alone, and 3) with a Clinical Dementia Rating score of 0.5 or 1. In participants ' homes, we placed a commercially available companion robot, RoBoHoN (Sharp), which was autonomous, conversational, and humanoid. After an exploratory two to five months’ use and a further two months’ wash-out, we installed the robot at their homes for one and a half years. We longitudinally assessed participants with scales assessing their psychological state and ease of robot use. At the four-month assessment, an interview about the pros and cons of the robots was also conducted.
Results
Participants were five female patients aged 85 to 90 with mild cognitive impairment or late-onset psychosis. All could use the robot by themselves with minimum support from the research team. The scale assessing usability showed high levels of satisfaction and ease of use. Although the psychological measures did not show any specific trends during the study period, participants generally enjoyed verbal communication with the robot, and four out of the five wanted to continue using the robot after the study period.
Conclusion
This study suggests that conversational companion robots have the potential to be accepted over the long term by community-dwelling older adults with mild cognitive impairment or psychosis.
A Method for Uncovering Tokenisation Archetypes and their Effects: Thus Spoke Switzerland
Authors: Plepi Anisa , Schwendner Peter
Published: December 2024

This paper proposes a framework for aggregating and categorising viewpoints on fundamental issues concerning tokenisation and assessing the causal effects of tokenisation on market outcomes, using bonds as a case in point. The framework starts with a taxonomy for classifying bond tokenisation use cases according to the tokenisation model, which is fed into a causal model to assess the question: If a bond had been tokenised instead of using the traditional infrastructure, how would the outcomes, characterising its lifecycle processes, change? Or, alternatively, how would the outcomes of interest change if a bond had been exchanged in the traditional infrastructure instead of being tokenised? The paper then proposes an outcomes matrix to estimate the effects of tokenisation on particular outcomes for which there are 25 metrics. The framework is then employed to conceptualise Switzerland’s tokenisation approach and evaluate present bond tokenisation effects on efficiency and liquidity.
JEL Classification: C18, C21, C81, G10.
Coherent Bunching of Anyons and their Dissociation in Interference Experiments
Authors: Heiblum Moty , Ghosh Bikash , Labendik Maria , Umansky Vladimir , Mross David
Published: December 2024

Aharonov-Bohm (AB) interference in fractional quantum Hall states generally reveals the fractional charge e* of their elementary quasiparticles. Indeed, flux periods of ΔΦ=(e/e*)Φ0 were observed in interference of ‘particle-like’ fractional states. Here, we report interference measurements of ‘particle-hole conjugated’ states at filling factors ν=2/3, 3/5, and 4/7, revealing the unexpected periodicities, ΔΦ=ν-1Φ0. Moreover, the measured shot noise Fano factor (F) of partitioned quasiparticles in the interferometer’s quantum point contacts (QPCs) was F=ν and not the expected F=e*/e. These combined observations indicate that fractional quasiparticles tunnel in the QPCs and interfere as coherently bunched pairs, triples, and quadruplets, respectively. Charging a small metallic gate in the center of the two-path interferometer forms an antidot (or a dot) and introduces local quasiparticles, leading, unexpectedly, to a dissociation of the bunched quasiparticles, thus restoring the flux periodicity set by the elementary quasiparticle charge. The surprising observations of bunching and dissociation, unsupported by current theory, suggest similar effects in particle-like states at lower temperatures.
Assessing the Impact of India's No-Employment Policy for International Students: Financial Wellbeing and Career Development Consequences
Authors: Noori Mohammad Ozair , Mohammady Khanullah
Published: December 2024

This study investigates the impact of India’s no-employment policy on the financial wellbeing and career development of foreign students, including their perceptions of the no-employment policy. Descriptive statistics are used to analyse the quantitative data. Based on survey responses from 150 international students from different disciplines and different level of study, findings indicate significant financial challenges associated with the policy, leading to dependence on external support, frequent financial stress, and negative effects on mental health and academic success. Most students (82.7%) believe their financial wellbeing would improve if they could work part-time, while 64.7% reported borrowing funds to manage expenses, and 60.7% experienced mental health impacts from financial stress. Additionally, many students feel disadvantaged in career readiness, with 84.6% stating that the inability to gain work experience leaves them unprepared for future opportunities. Qualitative responses further reveal that policy restrictions drive some students toward informal, unregulated work, exposing them to lower wages and exploitation. A majority (over 80%) consider the policy unfair and isolating, with some unaware of these restrictions until after arrival. The study recommends allowing part-time work, paid internships, and research or teaching assistant roles for doctoral students to mitigate these issues, enhancing students’ financial stability and professional development in India.
Baula – die digitale Studienplanungsassistentin an der Universität Bamberg
Authors: Hirmer Tobias , Ochs Michaela , Henrich Andreas
Published: December 2024

Während die Pandemie die digitale Transformation in der Lehre beschleunigt hat, besteht bei der Studienorganisation noch Nachholbedarf. Diese Innovationslücke sollen digitale Studienassistenten (DSA) füllen. Der vorliegende Beitrag stellt die aktuelle und weitere geplante Entwicklung eines DSA an der Universität Bamberg vor, welcher Studierenden auf Basis heterogener Datenquellen eine zentrale, flexible und umfassende Möglichkeit zur individuellen, eigenständigen Studienplanung bieten soll. Eine erste Evaluation (  zeigt das positive Feedback Studierender und verdeutlicht das Potenzial eines solchen Systems, dessen Entwicklung vor dem Hintergrund organisatorischer Hürden des Hochschulkontexts betrachtet wird.
Self-le@rning an der Universität Hildesheim: Entwicklung einer Selbstlernplattform
Authors: Beste Meeri-Liisa , El-Sharkawy Sascha , Enders Natalie , Schmid Klaus , Wolff Bianca , Zaepernick-Rothe Ute
Published: December 2024

Die Universität Hildesheim reagiert auf Herausforderungen der Hochschullehre, wie eine heterogene Studierendenschaft und den Bedarf an flexiblem, individuell unterstütztem Selbststudium. Dafür entwickelt das Teilprojekt SELF-le@rning im Projekt Digital C@MPUS-le@rning eine Plattform für maßgeschneiderte Lernprozesse. Kernelemente sind die Verwendung von Nanomodulen und eine kompetenzbasierte Modellierung zur Erstellung individueller Lernpfade. Ergänzt werden diese durch Learning Analytics und ein Lerntagebuch zur optimalen Förderung des selbstgesteuerten Lernens. In diesem Beitrag wird ein Einblick in den aktuellen Entwicklungsstand der Selbstlernplattform gegeben.
Etnoespécies vegetais utilizadas pelo povo xukuru do ororubá para fins medicinais
Authors: Guênes Gyselle Tenório , Guênes Gymenna Maria Tenório , Oliveira Filho Abrahão Alves de , Sette-de-Souza Pedro Henrique Henrique , Correia Ana Carolina de Carvalho
Published: December 2024

O Brasil é o país de maior biodiversidade do planeta e detém de um valioso conhecimento tradicional associado ao uso de plantas medicinais pela sua população, em especial por comunidades indígenas. Este trabalho objetivou realizar um levantamento de plantas medicinais pela comunidade indígena Xukuru do Ororubá, no município de Pesqueira-PE, bem como descrever suas indicações terapêuticas e modos de uso. Trata-se de uma pesquisa aplicada, de caráter exploratório com análise descritiva e abordagem quanti-qualitativa, através de um formulário semiestruturado. Foram entrevistados 300 indígenas, entre 18 e 87 anos, sendo 56,33% do gênero feminino. Quase a totalidade dos informantes (99,0%) utilizavam plantas medicinais para fins terapêuticos. Quanto ao local de obtenção das plantas destacam-se no domicílio (58,2%) e mata (24,6%); a família é a principal fonte de conhecimento com 87,7% dos entrevistados. Foram relatadas na pesquisa 135 etnoespécies, as mais citadas foram o Capim Santo que apresentou (123) indicações, seguido da Erva Cidreira (73); Hortelã da folha miúda (47); Quixabeira (37) e Aroeira (35). O uso de folhas nas preparações prevalece com 58,04%, sendo o chá a forma de administração mais usada com 67,55%. Esse estudo aponta que a comunidade indígena Xukuru do Ororubá utiliza uma grande quantidade de plantas medicinais para tratamento e cura das doenças de seu povo e mantém viva a tradição de passar seus conhecimentos para seus familiares, preservando sua cultura.
Intellectual capital, bank longevity, and size: Pathways to sustainable growth in Saudi banking through competitive advantage
Authors: Sidahmed Abdelrahim Selma
Published: December 2024

This study aims to investigate the role of Intellectual Capital (IC), Sustainable Competitive Advantage (SCA), Duration Since Firm Establishment (DSE), and Bank Size (S) in fostering Sustainable Growth (SG) in Saudi Arabia’s banking sector. Data were collected from 2012 to 2022 from 10 commercial banks operating in the Saudi Arabian economy and listed on the Saudi Stock Exchange (Tadawul). The research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze these relationships. Findings indicate that IC significantly enhances SCA (β = 0.639, p < 0.001), which robustly promotes SG (β = 0.473, p < 0.001). Additionally, a significant direct effect of IC on SG was observed (β = 0.674, p < 0.001). A significant relationship is also observed between DSE and SG (β = 0.956, p < 0.001), highlighting the advantage of longstanding establishments in leveraging accumulated resources for growth. However, the anticipated mediating role of IC in the relationship between DSE and SG was not supported statistically (p = 0.075), suggesting the potential for other variables to influence this dynamic relation. The study underscores the pivotal role of intellectual resources in driving competitive advantages and growth sustainability in the banking industry, particularly within the rapidly evolving economic landscape of Saudi Arabia. These findings offer valuable insights for policymakers and banking institutions looking to leverage intellectual assets and competitive positioning for long-term success.
The impact of social ties on customer loyalty: Mediating effects of satisfaction and moderating commitment
Authors: Juharsah Juharsah
Published: December 2024

Social bonding tactics help companies and their customers develop friendships by focusing, maintaining relationships, and interacting personally. This study was conducted to determine whether consumer satisfaction is an effective mediator in the relationship between trust, brand image and social ties to consumer loyalty, as well as the evaluation of consumer commitment as a moderator variable at BNI Bank in Southeast Sulawesi Province, Indonesia. Purposive sampling was used to select 152 respondents who had to be adults at least 17 years old and customers who had been with the company for at least six months. Questionnaires were distributed based on the number of responders in order to gather primary data. Sixty-nine clients (45.4%) were female, while 83 customers (54.6%) were male. The data were then examined using structural equation modelling. The findings show how social connections, brand perception, and trust affect customer satisfaction. Additionally, the results demonstrate that commitment positively moderates the effect of satisfaction on customer loyalty, which is influenced by social relationships at 0.137 with a p-value of 0.008 and customer satisfaction at 0.117 with a p-value of 0.043. It makes sense that commitment positively moderates the effect of customer satisfaction on customer loyalty and that customer satisfaction is a useful intervening variable. This demonstrates how raising customer commitment, brand image, social connections, consumer trust, and contentment may all result in increased levels of loyalty. Developing stronger social ties will lead to more loyal, satisfied, and repeat business from customers.
¿Es la fenomenología husserliana un correlacionismo?
Authors: Arriaga Arroyo José Pedro
Published: December 2024

En el presente artículo se aborda la cuestión de si la fenomenología husserliana puede ser considerada un correlacionismo en el sentido en que Quentin Meillassoux lo caracteriza en Después de la finitud y textos relacionados. Se sostiene que la respuesta debe ser negativa strictu sensu, aunque se añade que la fenomenología de Husserl sí puede ser entendida como un correlacionismo, pero uno sui generis que cae fuera de la concepción de Meillassoux. Al contestar a esta interrogante se busca brindar una vía de aclaración a posibles malentendidos sobre la fenomenología husserliana que pudieran suscitarse a propósito de los planteamientos de Meillassoux y, a su vez, se pretende contribuir al diálogo de dicha forma de fenomenología con otras corrientes filosóficas contemporáneas.
¿Un libertarianismo medioambientalista? Propiedad, utopía y política medioambiental en las teorías libertarias
Authors: Schwember Felipe , Loewe Daniel
Published: December 2024

Este artículo examina los modos en que el iusnaturalismo libertario ha afrontado los desafíos medioambientales que suscita la adquisición de la propiedad. Se persiguen tres propósitos: primero, discutir algunos de los supuestos libertarios acerca de la naturaleza y la tecnología; segundo, explorar el potencial medioambientalista de la estipulación de Locke/Nozick; tercero, indicar algunas de las dificultades a que conduce dicha estipulación cuando se la aplica a la resolución de problemas medioambientales. Sostengo que la estipulación conduce a dos resultados, según como se la interprete. El primero ofrece la posibilidad de desarrollar efectivamente un libertarianismo medioambiental robusto, pero solo al precio de imponer severas restricciones a las adquisiciones; el segundo evita tales restricciones, al precio de renunciar a una política medioambiental significativa. Concluyo con algunas reflexiones acerca de la relación entre teoría de la propiedad y medioambientalismo.
A relação entre o a priori da fenomenologia, a pergunta pelo sentido de ser e a ontologia fundamental no pensamento de Heidegger
Authors: Costa de Matos Fernandes Christiane
Published: December 2024

A proposta desse trabalho é relacionar momentos do percurso investigativo de Heidegger, durante os anos 1920, a fim de descrever o que parece ser uma relação decisiva a partir da qual toda a arquitetura de Ser e tempo pode ser compreendida enquanto projeto filosófico, a saber: o nexo entre aquilo que o autor indica como o verdadeiro a priori da fenomenologia, a pergunta pelo sentido de ser e, finalmente, a necessidade de uma ontologia fundamental.