bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiple Objectives Escaping Bird Search Optimization and Its application in Stock Market Prediction Based on Transformer Model
Authors: Wei Dedai , Wang Zimo , Qiu Minyu , Yu Juntao , Yu Jiaquan , Jin Yurun , Sha Xinye , OuYang Kaichen
Published: October 2024

Stock market prediction is a popular topic in both academia and industry due to its potential to offer significant financial returns, while transformer model is a cutting-edge tool in this task. However, how to fine-tune the hyperparameters in a reasonable timeframe without excessive computational resources remains a challenge. This paper purposes an innovative algorithm which extends the Escaping Bird Search optimization (EBS) into the area of multi-objective optimization, namely MOEBS, for efficient and effective hyperparameter fine-tuning of Transformer to predict stock prices. Initially, we validate MOEBS by conducting benchmark testing built upon widely used problem sets like ZDT, DTLZ, WFG, etc., together with numerical experiments based on evaluation of 4 recognized metrics, GD, Spacing, IGD, and HV. Next, we apply MOEBS to optimal hyperparameter searching for Transformer, such as Learning rate, Number of Heads and L2 regularization coefficient. The fine-tuned Transformer models by MOEBS and other competing algorithms are then applied to training and predicting on Google's historical stock price data set from 2016 to 2021. Comparative experiments demonstrate the extraordinary excellence of MOEBS-Transformer in terms of RMSE, RPD, and R2 metrics, matching and surpassing the performance of the state-of-the-art competitors. As a novel and powerful stock price prediction model, MOEBS-Transformer has potential to become a reliable and accurate predictor for stock prices. The fine-tuned Transformer models by MOEBS and other competing algorithms are then applied to training and predicting on Google's historical stock price data set from 2016 to 2021. The Google stock data set used in this research can be accessed publicly through Kaggle at the following link: https://www.kaggle.com/datasets/varpit94/google-stock-data.
Design and Implementation of a Facility Intelligent Carbon Dioxide Incubator Control System Based on Improved POA Optimized Fuzzy PID for the Incubation of Termitomyces mushrooms
Authors: Luo Qiangke , Zhao Zeneng , Zhang Huanbo , Lin Guan , Gao Juntao , Liu Yong , Kong Lingxue
Published: October 2024

To address the issue of accurately controlling the carbon dioxide environment required for the cultivation of Termitomyces mushrooms in traditional carbon dioxide incubators, and improve the cultivation environment of Termitomyces mushrooms, this study designed an intelligent carbon dioxide incubator control system suitable for the laboratory cultivation of Termitomyces mushrooms. The system was based on an improved POA to optimize fuzzy PID control, regulating the opening of the solenoid valve to precisely control the carbon dioxide concentration in the incubator. Simulation and comparison tests of the improved POA-based optimized fuzzy PID control, PID control, and fuzzy PID control were carried out by MATLAB/Simulink software, which indicated that the system’s overshoot was reduced by 11.7%, the adjustment time was shortened by 71.1 s, and the steady-state error was reduced by 0.1%. The reductions in overshoot, adjustment time, and steady-state error showed that POA-optimized fuzzy PID control was superior to fuzzy PID control in terms of accuracy, response, and stability, with better robustness. In addition, the growth of the Termitomyces eurrhizus MLY19 strain in the incubator environment was compared to that of a traditional carbon dioxide incubator, and we found that the diameters of the cultured Termitomyces mushroom MLY19 cell colonies in the improved incubator were 45.3% and 73.8% larger at 7 and 14 days, respectively. Therefore, the carbon dioxide control system of the Termitomyces mushroom incubator offered a high practical application value.
Comparative Analysis of DeepLabv3+ for Urban Waterbody Mapping: Enhancing Policy-Making and Sustainable Urban Development
Authors: Rajeswari S. , Rathika P.
Published: October 2024

Waterbody extraction plays a crucial role in various applications such as environmental monitoring, urban planning, and disaster management. Over the past decade, numerous convolutional neural networks (CNNs) have been developed specifically for the accurate segmentation of waterbodies. However segmenting tiny branch-like structures of waterbodies observed in images remains challenging. DeepLabV3 + is indeed one of the top segmentation models excelling in the task of segmenting tiny waterbody structure. However, its computational demands are a major drawback. Therefore, this paper investigates the performance of deepLabV3 + using various backbone networks such as EfficientNet, MobileNet, ResNet50, DenseNet121, and YOLOv8. Among the selected backbone networks, EfficientNet achieves excellent accuracy with relatively efficient computation time because of its compound scaling approach. It surpasses DenseNet by 1.2%, outperforms ResNet50 by 1.62%, achieves 1.86% higher accuracy than MobileNet, and significantly exceeds YOLOv8 by 3.71%. Experimental results demonstrate that deepLabV3 + using EfficientNet stands out as the most effective segmentation model, achieving the highest Structural Similarity Index (SSIM) value of 0.963 and lowest mean absolute distance (MAD) value of 0.891, particularly for customized data segmentation of water bodies with tiny branch-like patterns.
A Qualitative Exploration on Understanding Progression Patterns and Nursing Implications of Chronic Kidney Disease
Authors: Saguban Reynita , AlAbd Asmaa Mohamed  Ali , Rondilla Evalynn , Buta Joyce , Marzouk Salwa Ali , Maestrado Richard , Aljarboa Bader Emad , Mosto Romeo Jr , Alshammari Mubarak
Published: October 2024

Introduction: Despite the alarming increase in the prevalence of Chronic Kidney Disease (CKD) worldwide owing to high-risk factors, little information is available on patients who experience consistent CKD progression. The purpose of this qualitative study was to explore the diverse courses of chronic kidney disease and understand illness perspectives from patients, fostering customized nursing approaches.
Methods: This qualitative study employed purposive and snowball sampling techniques to recruit 15 patients with CKD (stages 1 and 2) from the outpatient department of King Khalid Hospital. Data were collected through semi-structured interviews that lasted between 45 and 60 minutes, each with the participants’ consent for audio recording. Data were collected between March and April 2024. Thematic analysis was employed to analyze the transcriptions of the interviews.
Results: Four themes, including five subthemes, emerged from the verbatim accounts obtained from all 15 participants involved in this research. These are: (1) slow creep (The Range of Experiences in Early Stage CKD), (2) Balancing Act of Hope and Uncertainty (navigating a new reality), (3) turning point (contributory factors), and (4) CKD progression patterns (challenges managing CKD; Hopes, Fears, and Living with Uncertainty).
Conclusion: “slow creep,” which includes various experiences during initial diagnosis; “Balancing Act of Hope and Uncertainty” where emotional contradictions were raised, “Turning point marking an essential period in the progression of the illness; and lastly, “CKD Progression Patterns” which shows how difficult it is for someone to manage uncertainty through one’s emotions. This understanding offers a framework for understanding early stage CKD, but more studies need to be conducted before any conclusive statements can be made about them.
Learning Risk Preferences Through Social Interaction: An Active Inference Approach
Authors: Tehrani-Safa Amir Hossein , Ghaderi Reza , Sarabi-Jamab Atiye
Published: October 2024

Social learning involves the ability to make assumptions about a person's attitudes and preferences on the basis of their observed behaviors. These characteristics are then used to make predictions and influence how one interacts with individuals in various social contexts. In this research, we used an active inference framework to explore how humans can assess another person's risk preferences. The active inference learner uses a probabilistic generative model to model others' decision making process and then employs a Variational Bayesian method based on the free-energy principle to invert the generative model. On a trial-by-trial basis, the observer updates the posterior estimate of the other's hidden characteristic via social prediction error, a mismatch between what we predicted and what they chose. The model begins with a high learning rate and gradually reduces it as more trials occur. This reflects that humans learn from examples sequentially, exploring and using the information as they progress. As more data are accumulated from someone who follows a consistent decision-making process, the observer's faith in his own judgments should grow, and he should be less affected by each new observation. Understanding others' risk preference is a complex example of social reasoning. We employed a sequential scenario where an observer watched the other person's choices between a high-risk gamble and a guaranteed small reward. We discovered that the inferential uncertainty that the learner has in trying to estimate the agent's risk attitude, is largely based on the prediction uncertainty accumulated by the observer when attempting to guess the agent's choices.
A New Differential Gene Expression Based Simulated Annealing for Solving Gene Selection Problem: A Case Study on Eosinophilic Esophagitis and Few Other Gastro-Intestinal Diseases
Authors: Sinha Koushiki , Chakraborty Sanchari , Bardhan Arohit , Saha Riju , Chakraborty Srijan , Biswas Surama
Published: October 2024

Identifying the set of genes collectively responsible for causing a disease from differential gene expression data is called gene selection problem. Though many complex methodologies have been applied to solve gene selection, formulated as an optimization problem, this study introduces a new simple, efficient and biologically plausible solution procedure where the collective power of the targeted gene set to discriminate between diseased and normal gene expression profiles was focused. It uses Simulated Annealing to solve the underlying optimization problem and termed here as Differential Gene Expression Based Simulated Annealing (DGESA). The Ranked Variance (RV) method has been applied to prioritize genes to form reference set to compare with the outcome of DGESA. In a case study on EoE and other gastrointestinal diseases, RV identified the top 40 high-variance genes, overlapping with disease-causing genes from DGESA. DGESA identified 40 gene pathways each for EoE, Crohn's Disease (CD), and Ulcerative Colitis (UC), with 10 genes for EoE, 8 for CD, and 7 for UC confirmed in literature. For EoE, confirmed genes include KRT79, CRISP2, IL36G, SPRR2B, SPRR2D, and SPRR2E. For CD, validated genes are NPDC1, SLC2A4RG, LGALS8, CDKN1A, XAF1, and CYBA. For UC, confirmed genes include TRAF3, BAG6, CCDC80, CDC42SE2, and HSPA9. RV and DGESA effectively elucidate molecular signatures in gastrointestinal diseases. Validating genes like SPRR2B, SPRR2D, SPRR2E, and STAT6 for EoE demonstrates DGESA's efficacy, highlighting potential targets for future research.
The impact of beachface morphology on habitat suitability and breeding success of least terns and snowy plovers
Authors: de Alegría-Arzaburu Amaia Ruiz , Garcia-Walther Julian , Serrato Liliana Ortiz , Vega Jonathan Vargas , Senner Nathan R
Published: October 2024

Beach-nesting birds rely on predictable and stable beach conditions for successful breeding, yet the complex impacts of climatic events, wave action, and variation in beach morphology on nest site selection remain underexplored. This study examines how variations in beach morphology influence nest site selection and breeding success in two conservation-priority species —the least tern (Sterna antillarum) and the snowy plover (Anarhynchus nivosus)—at Barra del Estero Beach, Baja California, Mexico. This beach, formed in the mid-to-late 1990s, likely due to alongshore sediment transport from neighboring beaches during energetic El Niño events, reveals that nest abundance correlates strongly with supratidal beach morphology. Both species exhibited significantly higher survival rates when nesting on berms compared to other areas. They presented highest nest densities on stable profiles featuring prominent berms extending approximately 40 m horizontally from the dune toe at elevations exceeding 2.8 m, 0.5 m above the highest spring high-tide level. While berms erode in winter due to high-energy waves, they serve as secure nesting platforms in summer, protecting nests from flooding. Thus, the ability of the beach to rebuild wide berms after the winter is crucial for nesting success. As sea-level rise and extreme weather events increasingly alter beach morphology, species with greater flexibility in nest site selection may more successfully identify higher-quality nesting sites. This research highlights the urgent need for comprehensive solutions to mitigate the growing risk of nest flooding in beach-nesting birds.
Designing selective fruit fly lures by combining odors that stimulate antennal and palpal neurons
Authors: Biasazin Tibebe Dejene , Miano Raphael Njurai , Cheseto Xavier , Ndlela Shepard , Mohamed Samira A. , Dekker Teun
Published: October 2024

The oriental fruit fly Bactrocera dorsalis, is a highly destructive and invasive pest that threatens global horticulture, causing economic losses through fruit damage and quarantine regulations. While attract-and-kill baits are widely used to suppress fly populations, these baits also impact many non-target species. To achieve ecological sustainability, our study aimed to develop a method that selectively targets female fruit flies. Using gas chromatography coupled electro-antennal or palpal detection (GC-EAD / GC-EPD), we identified compounds that elicited responses in the maxillary palp and antenna of three different fruit flies including B. dorsalis, Ceratitis capitata and Zeugodacus cucurbitae. As previous studies indicated the significance of compounds whose detection was shared among fruit fly species, we composed blends of such ‘shared compounds’. To test the idea that compounds active on the palps and antennae are complementary and synergize attraction, we thus formulated three blends, a palpal, an antennal and a combined blend. Compounds were formulated in a wax emulsion for slow release and tested on B. dorsalis fruit flies in six-choice and large room laboratory assays, as well as field trials. A blend of both antenna and maxillary palp active compounds attracted more B. dorsalis than blends based on either antennae or palps alone, and exhibited a female-bias in captures. Furthermore, the blend was highly selective, capturing very few non-target organisms compared to torula yeast, a lure considered to be selective. Such lures are important in advancing targeted pest control strategies, ultimately contributing to more effective management of the devastating B. dorsalis population, and safeguarding global horticulture productivity.
Prevalence of Protozoan in HIV/AIDS Patients with Gastrointestinal Symptoms in Zinder National Hospital, Niger Republic
Authors: Lamine MAHAMAN MOUSTAPHA , Mahamadou DOUTCHI , Mahamadou MOUSSA AMADOU , Hassane BOUREIMA , Ousmane ABDOULAYE , FILS SOULEYMANE ADOUM , Yacouba ABDOURAHAMANE , Adehossi ERIC
Published: October 2024

Background
Intestinal parasitic infections constitute one of the stubborn public health issues, particularly in low- and middle-income countries. This study aimed to investigate the prevalence and diversity of intestinal parasites among patients in a medical center in Zinder, Niger Republic.
Methods
A prospective study of 93 patients and a retrospective study of 131 patients were conducted. Stool samples were examined for the presence of parasites using standard microscopic techniques.
Results
In this prospective study, 83.7% of stool samples were tested positive for parasites, with the cystic form of Entamoeba histolytica (25.8%) and Cryptosporidium spp. (30.1%) being the most prevalent. Four patients had vegetative forms of protozoa, including two with Giardia intestinalis (2.1%) and two with E. histolytica (2.1%), and one patient was positive for Strongyloides stercoralis. In the retrospective study, 46.9% of stool samples were positive for parasites, with the E. histolytica and Pentatrichomonas hominis being the most prevalent 26.1% and 7.1%, respectively. Trophozoite of E. histolytica and G. intestinalis were present respectively in 3.2% and 2.8% of positive samples as well. Oocysts of two protozoans were identified. Cryptosporidium spp., is characterized by 28 oocysts, constituted 30.1% of the observed entities. Simultaneously, Cystoisospora belli, represented by 12 oocysts, accounted for 12.9% of the total.
Conclusion
Our findings reveal a high prevalence of intestinal protozoan parasites in HIV/AIDS patients in Niger. This points at the need for effective interventions to prevent and treat these infections. In addition, the results of this study provide important preliminary data that could inform public health policy and decision makers in the region.
How much does electric vehicle adoption contribute to the transportation sector’s GHG emissions reduction?
Authors: Tan Xiaomei , Rose Tyler
Published: October 2024

This study examines the impact of electric vehicle (EV) adoption on greenhouse gas (GHG) emissions in California's transportation sector from 2000-2021. Using data from the California Air Resources Board's GHG Emissions Inventory, the analysis focuses on three primary factors affecting transportation emissions: EV population, fuel economy of light-duty vehicles, and gasoline sales. Through correlation and regression analyses, the study finds that gasoline sales have the most substantial impact on emissions. Improvements in fuel economy and increases in EV population both contribute to reducing emissions, with fuel economy showing a stronger impact than EV adoption. Specifically, for every 1 MPG increase in fuel economy, emissions decrease by approximately 1.7644 MMTCO2e, while for every 1,000 increase in EV population, emissions decrease by about 0.0416 MMTCO2e. The findings suggest that while promoting EV adoption is important, it should be complemented with policies that enhance fuel economy and reduce gasoline consumption to achieve more significant and immediate reductions in transportation emissions. The study concludes that a multifaceted approach addressing fuel economy, gasoline consumption, and EV adoption is needed to substantially reduce transportation emissions and achieve California's long-term climate goals.
Aerobic exercise attenuates high-fat diet-induced glycometabolism abnormalities in skeletal muscle of rats via EGR-1/PTP1B signaling pathway
Authors: Zhang Liangzhi , Liu Xiaojie , Hu Jing , Quan Helong , Lee Sang Ki , Korivi Mallikarjuna , Wang Lifeng , Li Ting , Li Wei
Published: October 2024

Objective
Defects in glycogen anabolism led to the development of insulin resistance (IR). Aerobic exercise ameliorates IR by augmenting insulin signaling, yet, the precise mechanism behind this improvement remains unclear. This study explored whether 6 weeks aerobic exercise enhances glycogen anabolism and insulin sensitivity via EGR-1/PTP1B signaling pathway in skeletal muscle.
Methods
Sprague-Dawley rats fed a high-fat diet (HFD) performed treadmill exercise, and were examined for an oral glucose tolerance test and IR. PAS staining and anthrone colorimetry were used to assess the skeletal muscle glycogen content. RT-qPCR, western blot and immunofluorescence were used to detect EGR-1/PTP1B pathway and associated signaling molecules.
Results
Results showed that exercise reduced blood glucose levels and HOMA-IR, increased muscle glycogen content, inhibited EGR-1, PTP1B, and GSK-3β mRNA and protein levels, and promoted IRS-1, AKT, and GLUT4 protein and mRNA expression.
Conclusion
In summary, aerobic exercise facilitates skeletal muscle glycogen anabolism and improves insulin sensitivity in HFD rats through the EGR-1/PTP1B pathway, with significant implications for preventing IR.
MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data
Authors: Arturi Katarzyna , Harris Eliza Jane , Gasser Lilian , Escher Beate I , Bosshard Robin , Hollender Juliane
Published: October 2024

MLinvitroTox is an automated Python pipeline developed for high-throughput hazard-driven prioritization of toxicologically relevant features detected in complex environmental samples through nontarget high-resolution mass spectrometry (NTS HRMS/MS). MLinvitroTox is a machine learning (ML) framework comprising 490 independent XGBoost classifiers trained on molecular fingerprints from chemical structures and target-specific endpoints from the ToxCast/Tox21 invitroDBv4.1 database. For each analyzed feature, MLinvitroTox generates a 490-bit bioactivity fingerprint used as a basis for prioritization, focusing the time-consuming molecular identification efforts on features most likely to cause adverse effects. The practical advantages of MLinvitroTox are demonstrated for groundwater HRMS data. Among the 874 features for which molecular fingerprints were derived from spectra, including 630 nontargets, 185 spectral matches, and 59 targets, around 4\% of the feature/endpoint relationship pairs were predicted to be active. Cross-checking the predictions for targets and spectral matches with invitroDB data confirmed the bioactivity of 120 active and 6,791 nonactive pairs while mislabelling of 88 active and 56 non-active relationships. By applying the provided scores and metrics, the number of potentially toxic features was further reduced by at least one order of magnitude. This refinement makes the analytical confirmation of the toxicologically most relevant features feasible, offering significant benefits for cost-efficient chemical risk assessment.
Scientific Contribution: In contrast to the classical ML-based approaches for toxicity prediction, MLinvitroTox predicts bioactivity for HRMS features based on MS2 fragmentation spectra rather than the chemical structures from the identified features. While the original proof of concept study was accompanied by the release of a MLinvitroTox v1 KNIME workflow, in this study, we release a Python MLinvitroTox v2 package, which, in addition to automation, expands functionality to include predicting toxicity from structures, cleaning up and generating chemical fingerprints, customizing models, and retraining on custom data. Furthermore, as a result of improvements in bioactivity data processing, realized in the concurrently released pytcpl Python package for the custom processing of invitroDBv4.1 input data used for training MLinvitroTox, the current release introduces enhancements in model accuracy, coverage of biological mechanistic targets, and overall interpretability.
Model and Evaluation: Towards Fairness in Multilingual Text Classification
Authors: Lin Nankai , He Junheng , Tang Zhenghang , Fang Jiajun , Yang Aimin , Zhou Dong
Published: October 2024

Recently, more and more research has focused on addressing bias in text classification models. However, existing research mainly focuses on the fairness of monolingual text classification models, and research on fairness for multilingual text classification is still very limited. In this paper, we focus on the task of multilingual text classification and propose a debiasing framework for multilingual text classification based on contrastive learning. Our proposed method does not rely on any external language resources and can be extended to any other languages. In addition, the existing research on the fairness of multilingual text classification is relatively simple in the evaluation mode. The evaluation method of fairness is the same as the monolingual equality difference evaluation method, that is, the evaluation is performed on a single language. We propose a multi-dimensional fairness evaluation framework for multilingual text classification, which evaluates the model’s monolingual equality difference, multilingual equality difference, multilingual equality performance difference, and negative gain of the fairness strategy. We hope that our work can provide a more general debiasing method and a more comprehensive evaluation framework for multilingual text fairness tasks.
Breeding water parameters are important determinants of Microsporidia MB prevalence in the aquatic stages of Anopheles mosquitoes
Authors: Akorli Esinam A. , Andoh Nana Efua , Egyirifa Richardson K. , Dorcoo Christopher , Otoo Sampson , Tetteh Seraphim N.A. , Pul Reuben Mwimson , Sackitey Derrick B. , Oware Stephen K.D , Dadzie Samuel K. , Akorli Jewelna
Published: October 2024

The fungus, Microsporidia MB disrupts Plasmodium development in Anopheles mosquitoes. It has been associated with An. gambiae and An. coluzzii (Ghana), and An. arabiensis (Kenya) from rice fields. As a tool for vector/disease control, its ecological distribution and factors that determine their occurrence must be defined. We investigated the prevalence of Microsporidia MB in Anopheles mosquitoes across selected sites in Ghana, and the breeding water physicochemical parameters that are associated with the occurrence of the fungus by fitting regression models. DNA was extracted from the abdomens of 4255 adult Anopheles mosquitoes that emerged from larvae and pupae collected from selected sites in northern and southern Ghana between August and October of 2021 and 2022. Detection of Microsporidia MB was achieved using qPCR, while species were molecularly identified using SINE, RFLP methods, and the ANOSPP algorithm. Overall Microsporidia MB prevalence was 2.2%. Male mosquitoes exhibited higher prevalence of infections and had increased predicted probability of infection 85% higher than females. Sawla, in Ghana's Savannah zone had the highest MB prevalence (56.52%) despite lacking rice fields. Biochemical oxygen demand in mosquito breeding water was estimated to be positively associated with and, significantly predicts MB prevalence in mosquitoes with an accuracy of 94%. According to our data, all Anopheles species were at equal probability of MB infection. These results provide preliminary information on micro-ecological factors that could support the sustainability of MB infection in mosquitoes during their aquatic life stages. It will be important, therefore, to explore the impact of strategies for larval source management on these factors to ensure that the symbiont's persistence during the host's aquatic stages may not be adversely affected should it be used as an integrated approach for mosquito/disease control.
Elucidating the mitogenomic blueprint of Pomadasys perotaei from the Eastern Atlantic: Characterization and matrilineal phylogenetic insights into haemulid grunts (Teleostei: Lutjaniformes)
Authors: Wujdi Arief , Bang Gyurim , Amin Muhammad Hilman Fu'adil , Jang Yengju , Kim Hyun-Woo , Kundu Shantanu
Published: October 2024

The parrot grunt fish, Pomadasys perotaei, has a limited distribution in the eastern Atlantic Ocean and is an important species in marine capture fisheries across several West African countries. Despite its ecological and economic significance, the mitogenomic information for this species is lacking. This study utilized next-generation sequencing to generate the de novo mitogenome of P. perotaei from eastern Atlantic Sea. The resulting mitogenome is 16,691 base pairs and includes 13 protein-coding genes (PCGs), 22 transfer RNAs, two ribosomal RNAs, and an AT-rich control region (CR). Most of the PCGs exhibit nonsynonymous (Ka) and synonymous (Ks) substitution rates of less than ‘1’, indicating strong negative selection across haemulid fishes. The control region of Pomadasys species contains four conserved domains, as seen in other teleost’s, with polymorphic nucleotides that can be used to study population structures through the amplification of short mitochondrial gene fragments. Additionally, Bayesian phylogenetic analysis based on PCGs revealed a non-monophyletic clustering pattern of Pomadasys within the haemulid matrilineal tree. Overall, the structural characterization and phylogenetic analysis enhance our understanding of the genetic composition and evolutionary history of Pomadasys species from the Indo-West Pacific and eastern Atlantic Oceans.
Design and Optimization of Multi-Band Nano-Structured Antenna Arrays for Gynecological Medical Applications: A Theoretical and Simulation Study
Authors: Lamzouri O. , Laamara R. Ahl , Drissi L. B
Published: October 2024

This study explores the theoretical design, simulation, and optimization of nano-structured antenna arrays for multi-band operation in medical applications, with a focus on gynecological diagnostics and therapeutics. Utilizing advanced computational models and simulations, the research addresses key challenges such as biocompatibility, impedance matching, and specific absorption rate (SAR) optimization. The results demonstrate that these nano-structured antennas can achieve high efficiency, low return loss, and minimal SAR across multiple frequency bands, including the Medical Implant Communication Service (MICS), Industrial, Scientific, and Medical (ISM) bands, and higher frequencies up to 60 GHz. The optimized design ensures robust performance and safety within biological environments, making it highly suitable for integration into implantable medical devices. This work not only contributes to the advancement of nano-structured antennas in gynecological applications but also provides a solid foundation for their adaptation in other medical fields, potentially revolutionizing diagnostic and therapeutic procedures.
Detection Range Adjustable D-shaped Photonic Crystal Fiber Plasmonic Sensor: A comparative Study on Materials Effect
Authors: Zhao Zihong , Pan Honggang , Zhang Ailing , You Qingcheng , Zhu Yukun , Li Rupeng , Chen Chunqi
Published: October 2024

In this paper, a high-performance plasmonic surface plasmon resonance (SPR) sensor with adjustable detection range is proposed using Au in combination with TiO2 and Si3N4 as the adhesive layer, respectively. We simulated and compared the effect of two attachment enhancement materials on the performance of the sensor. The results show that for the Au - TiO2 combination, the maximum wavelength sensitivity (WS) is 65,000 nm/RIU at the refractive index (RI) of 1.39–1.40, the wavelength interrogation resolution of 1.54 × 10− 6 RIU, the sensor reaches the amplitude sensitivity (AS) of 2,429 RIU− 1 at RI = 1.34 and the resolution of 4.12 × 10− 6 RIU with amplitude interrogation method, and the RI detection range is 1.34–1.40. For the Au - Si3N4 combination, the maximum WS is 76,000 nm/RIU at RI between 1.39–1.40, the resolution of 1.32 × 10− 6 RIU− 1 with wavelength interrogation and the AS is 3,040 RIU− 1 when RI = 1.34, the amplitude interrogation resolution of 3.29 × 10− 6 RIU, and a RI range of 1.40–1.34. The sensor has an ultra-high WS and AS as well as the adjustable detection ranges of 1.31–1.41 and 1.33–1.43 by filling the supporting analyte with certain RI. We also present the fabrication process of the sensor, our sensors show great potential in different scenarios due to its superior performance and easiness of manufacturing.
Higher wildfire incidence, severity and population exposure in protected areas within fire-prone Temperate and Mediterranean biomes
Authors: de Dios Víctor Resco , Schütze Simon , Camprubí Àngel Cunill , Balaguer-Romano Rodrigo , Boer Matthias , Fernandes Paulo
Published: October 2024

The European Union has recently passed the Nature Restoration Law (NRL) which, among others, seeks to increase the cover of forest reserves protected for biodiversity and, globally, the Kunming-Montreal Global Biodiversity Framework similarly seeks to expand protected areas. Here we test whether a trade-off exists between protected areas expansion and fire activity, leading to a higher exposure to fire for the population in protected areas, because they often harbour more biomass and occur in remote areas. We analysed forest fires affecting 14,892,174 ha, and intersecting 10,999 protected areas, across fire-prone European Temperate and Mediterranean forest biomes, and in similar ecosystems within California, Chile and Australia. Protected areas were being disproportionally affected by fire within most Temperate biomes, and fire severity was 20% higher within protected areas also in Mediterranean biomes. Population in the periphery of forest areas was up to 16 times more likely to be exposed to large wildfires when their environment was within, or near, protected areas. Enhanced fire activity in protected areas was driven by a combination of fuel loads, accessibility and abiotic factors. Wildfire prevention and mitigation must be central goals in the development of the NRL and other conservation/restoration programs to diminish population exposure and fire severity.
Influence of Surface Modification, Fabric Structures and Stitch Length on Physico-Mechanical and Comfort Properties of 100% cellulose based Knit Fabric
Authors: Akter Nasrin , Repon Md. Reazuddin , Pranta Arnob Dhar , Hosen Md. Imran , Islam Shaima , Akter Nahida
Published: October 2024

Most of the fabric properties of knitted fabric could be controlled by stitch length and fabric structures. Stitch length is the principal fabric parameter for knitted fabric. This study investigated the effect of surface modification, stitch length and fabric structures on the fundamental fabric properties of knitted fabric. In this study, three different stitch lengths (2.6, 2.65 and 2.7 mm) and two different fabric structures were used for producing the samples, keeping the yarn count and other machine parameters similar. While comparing the properties between the different stitch lengths and fabric structures, the different physical properties of fabric were examined, like stitch density (CPI, WPI), GSM, bursting strength, thickness, shrinkage%, spirality and comfort properties of fabric like air permeability and water vapor transmission rate. The results showed that all the fabric parameters were directly affected by stitch length and the fabric structures. The fabric WPI, CPI, GSM, thickness and bursting strength decreased with the increase in fabric stitch length (2.7 <2.65 <2.6 mm) and the presence of tuck loops and miss loops in the single jersey (SJ) derivatives. The fabric spirality, shrinkage and air permeability increased with the increase in fabric stitch length and the presence of tuck loops and miss loops in the fabric structures. Fabric stitch length and fabric structures have no significant effect on the water vapor transmission rate.
ATR and TopBP1 oppose to control dormant origin building, providing a first defence against replication stress
Authors: Debatisse Michelle , Koundrioukoff Stéphane , Kim Sujung , Alary Nathan , Toffano Antoine , Melendez-Garcia Rodrigo , Wu Xia , Liu Yaqun , Gnan Stefano , El-Hilali Sami , Brison Olivier , Rosselli Filippo , Chen Chun-Long
Published: October 2024

Replication stress, a major hallmark of cancers, sources from replication fork slowing or blocking. In response, activation of extra-origins, otherwise dormant, supports the replication rate. Whether the DNA replication checkpoint drives this compensation process remained unclear. Here, DNA combing analyses show that a linear relationship ties inter-origin distances to fork speeds and that the slope of this line, called stressline, accurately quantifies compensation efficiency. Comparison of the slopes in human cells with different genotypes elicits a model whereby TopBP1 locks the step-wise building of dormant origins at the pre-initiation complex step. Under stress, ATR triggers TopBP1 eviction from this complex, independently of CHK1, allowing building to proceed. We also developed ATRAP-seq, a genome-wide procedure whose data support the model and strongly suggest that compensation efficiency and limiting factors jointly govern the pace of replication domain activation. Altogether our results provide a comprehensive mechanism accounting for genome protection through loose replication checkpoint activation.
Repairing the retinal ischemic microenvironment with an engineered exosome-loaded dehydroepiandrosterone peptide hydrogel
Authors: Yang Zhimou , Peng Shenjun , Zhang Ying , Zhang Mengjia , Zhang Wen , Wang Lu , Zhang Yating , Jiang Feng , Zhang Jiacheng , Yang Chang , Ji Wenxuan , Zhang Wenyan , Gu Jiakuo , Gao Jie , Zhang Zhuhong
Published: October 2024

Retinal ischemia-reperfusion (RIR) injury creates a complex retinal pathological microenvironment (RPMe), contributing to vision-threatening diseases. Current research predominantly focuses on intracellular issues like oxidative stress and inflammation, while often neglecting extracellular matrix (ECM) fibrosis and angiogenesis. Here we developed an engineered exosome-loaded self-assembling peptide hydrogel to synergistically regulate both intracellular and extracellular events of RIR injury-induced RPMe. Engineered exosomes derived from retinal precursor cells, pre-treated with berberine and hypoxia, enhance cell repair and immune modulation. These exosomes are encapsulated in a hydrogel composed of dehydroepiandrosterone and insulin-like growth factor-I mimetic peptide, which not only possesses anti-inflammatory and antioxidant properties but also serves as a sustained exosome release system. Transcriptomic analysis reveals inhibition pathways including Wnt, PI3K/AKT (associated with oxidative stress and inflammation), and TGF-β/Smad3 and Notch3/Ang2 (related to ECM fibrosis and angiogenesis). Our multifunctional hydrogel provides a comprehensive treatment for retinal diseases by targeting both intracellular and extracellular RPMe events.
The practices of an integrated infrastructure planning in Ethiopian metropolitan cities, the case of Addis Ababa and Sheger cities
Authors: Worku Geremew , Adugna Dagnachew
Published: October 2024

When properly planned and managed, urbanization can offer improved access to social amenities and job possibilities. On the other hand, disjointed approaches to infrastructure investment and development could lead to unsustainable urban sprawl, traffic jams, poor public service delivery, environmental degradation, inefficiencies, and inequality. Therefore developing infrastructure strategically is necessary to meet the changing needs of expanding metropolitan areas. Purposive sampling was employed in the study to implement a mixed-methods strategy for explanatory and descriptive research designs. The research attempts to identify possibilities, risks, flaws, and strengths in the current integrated infrastructure planning system by a thorough examination of policy frameworks, stakeholder involvement procedures, and implementation techniques. The results of this study will provide suggestions for improving cooperation, allocating resources as efficiently as possible, and utilizing technological advancements to promote resilient and inclusive urban settings. In creating resilient and inclusive cities, it also emphasizes the significance of coordinated efforts among stakeholders, efficient use of technology, and sustainable development principles. By looking at this, the study adds to the conversation about integrated infrastructure planning and provides information to stakeholders, legislators, and urban planners who are involved in determining the future of Ethiopian and other metropolitan regions.
A MODERN VIEW ON REPARATIVE OSTEOGENESIS: MAIN STAGES AND THEIR PATTERNS
Authors: Sukhonos Olha , Korenkov Oleksii , Sukhodub Leonid
Published: October 2024

Introduction. Reparative osteogenesis is a staged mechanism that ensures the restoration of damaged bone tissue. The study and summarization of current data about bone defect regeneration is the basis for the search and development of methods to improve this process. The aim of the study is to analyze and systematize the current data about reparative osteogenesis, describe the main stages and their patterns.
Materials and methods. Searching the relevant sources using online scientific databases and keywords. Selection of publications for review. Further analysis and synthesis of information.
The results. Despite different interpretations of the stages of reparative osteogenesis by researchers, they all describe the same coordinated process. The following key stages have been identified: haematoma formation, inflammation, MSC involvement and angiogenesis, cartilage, connective and bone tissue formation, their subsequent reorganisation, ossification and remodelling. Each of these stages involves specific cellular elements, local and general regulatory factors. The development of osteogenic cells and mechanisms of intercellular interaction, as well as the main signalling pathways and molecules (Wnt, RANK/RANKL/OPG, BMPs, HIF, etc.) that regulate osteo- and angiogenesis are described. The role of hypoxia in the process of bone regeneration and angiogenesis is highlighted. The H-type vessels and their participation in the regulation of osteogenesis are considered. Attention is paid to the phenomenon of ‘chondrocyte transdifferentiation’, which is one of the sources of osteoblasts during endochondral ossification. In the context of remodelling, the law of bone biomechanics and piezoelectric adaptive remodelling, as well as bone multicellular units as microsystems that ensure the restructuring of coarse fibrous bone tissue into lamellar bone tissue, are described.
Conclusions. Reparative osteogenesis is a complicated and coordinated process at both the cellular and molecular levels. The regeneration process depends on numerous local and systemic factors and the optimization search is carried out at each stage
Differential Expression of Phosphate Starvation-responsive Genes among Sweetpotato Cultivars during Establishment and Onset of Storage Root Formation
Authors: Arce Lisa I. , Labonte Don , Villordon Arthur , Gregorie Jeffrey C.
Published: October 2024

It has been documented that sweetpotato (Ipomoea batatas L.) cultivars vary in morphological and physiological adaptations to low phosphorus (P) availability but knowledge of the underlying molecular mechanisms is largely unknown. The objective of this research was to generate cultivar-specific information about phosphate starvation response (PSR) genes to variations in inorganic phosphate (Pi) availability at the onset of storage root formation among sweetpotato cultivars. Cultivars Bayou Belle (BB), Evangeline (EV), and Orleans (OR) were grown under varying Pi levels: 0 mg·L−1 (low Pi), 15 mg·L−1 (Pi-sufficient), and 31 mg·L−1 (high Pi). Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) analysis of PSR genes IbPHR1, IbSPX1, IbSPX3, IbPHT1;4, IbPHT1;5, and IbNLA was performed at 5 and 10 days after planting (DAP), corresponding to adventitious root system establishment and the onset of storage root formation, respectively. The cultivar BB grown under low Pi showed significantly higher expression of all genes except IbPHR1. The cultivar OR grown in both low and high Pi exhibited upregulation of IbPHR1. On the other hand, EV grown under low Pi revealed no response for all genes investigated. Exposure of BB to high Pi resulted in a decrease in expression for all genes except IbNLA. The cultivar EV grown in high Pi conditions showed increase in expression for IbSPX1, IbPHT1;5, and IbNLA. Expression pattern difference among cultivars relative to Pi levels corroborates field observations showing that BB, EV, and OR have different Pi requirements. The increased activity of BB PSR genes grown under low Pi supports the hypothesis that BB requires low P fertilizer input relative to OR and EV. Results from this study corroborate findings from well-characterized crop species and model systems and pave the way for the development of tools and practices to increase phosphorus use efficiency in sweetpotato.
Kastamonu İlinin Api-Turizm Potansiyelini Belirlemeye Yönelik Bir Çalışma (A Study on Determining the Api-Tourism Potential of Kastamonu Province)
Authors: GÜLEÇ Enes , OKTAY Kutay , ÇILGINOĞLU Hakkı , GÜLEÇ Nezahat
Published: October 2024

Alternatif ve deneyimsel arayışlar içerisinde olan turistler için api-turizm doğayla iç içe bir deneyim sunmaktadır. Bu turizm biçimi, doğal yaşamı koruma, biyoçeşitliliği teşvik etme ve yerel ekonomiyi güçlendirme gibi önemli etkilere sahiptir. Bu çalışma ile Kastamonu ilinin api-turizm potansiyelinin belirlenmesi amaçlanmıştır. Çalışmada nitel araştırma desenlerinden görüşme tekniği kullanılmıştır. Bu doğrultuda, Kastamonu ilinde api-turizm hakkında bilgi sahibi arıcılık faaliyeti gösteren katılımcılar ile görüşmeler sağlanmıştır. Araştırmacılar tarafından geliştirilen yarı yapılandırılmış görüşme formu kullanılarak elde edilen veriler nitel veri analiz programı kullanılarak içerik analizine tabi tutulmuştur. Araştırmada Kastamonu'nun yıl boyunca süren arıcılık faaliyetleri ile önemli bir api-turizm destinasyonu olma potansiyelini taşıdığı görülmüştür. Özellikle Küre, Doğanyurt ve İnebolu ilçeleri bu alanda öne çıkmaktadır. Api-turizmin uygulanması için arıcılara eğitim verilmesi ve altyapının güçlendirilmesi gerekmektedir. Ayrıca, arı ürünlerinin markalaşması ve api-terapi uygulamalarının artırılması önemlidir. Yerel halkın katılımı eğitim ve finansal desteklerle teşvik edilmelidir. Api-turizm, diğer turizm türleriyle entegre edilmeli ve kamu kurumları arasında iş birliği sağlanmalıdır. Bu çalışma TÜBİTAK Bilim İnsanı Destekleme Daire Başkanlığı tarafından 2209-A Üniversite Öğrencileri Araştırma Projeleri Destekleme Programı kapsamında 1919B012109094 başvuru numarasıyla desteklenmiştir.
Turist Tipolojisine Göre Tur Planlamasında Yapay Zekâ Teknolojisinin Kullanımı: Sürdürülebilir Yaratıcı Turizm ve Eko-Gastronomi Deneyimi Üzerine Karşılaştırmalı Bir Uygulama (Use of Artificial Intelligence Technology in Tour Planning According to Tourist Typology: A Comparative Application on Sustainable Creative Tourism and Eco Gastronomy Experience)
Authors: TÜRKAY Bahar
Published: October 2024

Sürdürülebilir turizm, doğal kaynakların korunmasını, yerel halkın refahını ve kültürel mirasın yaşatılmasını hedeflerken, eko-gastronomi yerel ve organik gıdaların tüketimini teşvik ederek çevreye olan zararı azaltmakta ve yerel ekonomiye katkıda bulunmaktadır. Yaratıcı turizm ise ziyaretçilere yerel kültüre derinlemesine katılım fırsatı sunarak, kültürel etkileşimi arttırmaktadır. Bu üç yaklaşım bir araya geldiğinde, turistlerin doğayla uyumlu bir şekilde seyahat etmeleri, yerel mutfak kültürünü keşfetmeleri ve yaratıcı deneyimlerle yerel kültüre daha yakın olmaları sağlanabilmektedir. Günümüzde teknoloji hızla gelişmekte ve yapay zekânın turizmde kullanılması turistler için kişiselleştirilmiş, özelleştirilmiş ve farklılaştırılmış deneyimler yaratma açısından imkânlar sağlamaktadır. Çalışmada, “sürdürülebilir turizm”, “yaratıcı turizm”, “eko-gastronomi” deneyimi odaklarını kapsayacak ve farklı turist tipolojilerine göre planlama oluşturabilecek yapay zekâ desteğinin turizm sektöründeki olası rolü incelenmiştir. Çalışmanın amacı, tur planlamasında kişiselleştirilmiş deneyimler sunmak adına Cohen’in turist tipolojileri bağlamında farklı değişkenlerle birlikte yapay zekâ sohbet robotlarının tur deneyimi yaratma konusundaki yeterlilikleri açısından karşılaştırmalı bir uygulama sunmaktır.