bluuebunny/crossref_metadata_2025 huggingface dataset:
Bacteriological Profile of Lower Respiratory Tract Infections and Antibiotic Susceptibility Pattern in Patients Visiting a Tertiary Care Hospital in Kathmandu
Authors: Gaire Manoj , Pangeni Bishnu , Dahal Sushant , Adhikari Anima , Timilsena Dip Kumar , Kandel Nabin , Koirala Sudhir
Published: September 2024

Background
Lower respiratory tract infections are among the major causes of morbidity and mortality in the world. This study aims to analyze the bacteriological profile of lower respiratory tract infections in the patients visiting Shukraraj Tropical and Infectious Disease Hospital in Kathmandu during three-month period from April to June 2023 and the antibiotic susceptibility pattern of the isolated pathogens.
Method
312 sputum samples were examined through Gram staining, microscopy, culture and various biochemical tests and significant bacterial isolates were identified. Antibiotic susceptibility testing was done by modified Kirby-Bauer disc diffusion method using different sets of antibiotics for different bacteria and Multi-drug Resistant (MDR) isolates were identified. The Methicillin Resistant S. aureus (MRSA) isolates were determined via antibiotic susceptibility testing against 30µg-Cefoxitin disc in Mueller Hinton Agar.
Results
34 out of the total 312 sputum samples examined showed significant growth. Gram-negative bacilli (85.29%) had a significant proportion compared to Gram-positive (14.71%). The most prevalent bacteria causing LRTI was found to be Klebsiella pneumoniae (32.35%) followed by Pseudomonas aeruginosa(29.41%), Acinetobacter spp.(17.65%), Staphylococcus aureus(14.71%), Enterobacter spp.(2.94%), and Citrobacter spp.(2.94%). Gentamicin exhibited the highest sensitivity rate of 75.86% in case of Gram-negative isolates and it showed highest resistance to Amoxicillin (86.21%). For Staphylococcus aureus, Linezolid, Vancomycin and Teicoplanin showed highest susceptibility rate of 100% followed by Gentamicin (60%). 20.70% of Gram-negative isolates were Multi-drug Resistant among which the predominant one was found to be Acinetobacter spp. (83.33%) followed by Klebsiella pneumoniae(16.67%). For S. aureus, all the isolates (100%) were found to be multi-drug resistant. 80% of S. aureus isolates were found to be Methicillin Resistant Staphylococcus aureus.
Conclusion
Gram-negative bacteria were found to be leading causative agents (85.29%) of lower respiratory tract infections. Antibiotics like Ciprofloxacin and Gentamicin were found to be effective against majority of Gram-negative bacteria. Similarly, Linezolid, Vancomycin and Teicoplanin were useful against Methicillin resistant S. aureus. The study recommends a periodic analysis on bacteriological agents of such infections and their antibiotic susceptibility pattern in order to assess the increasing anti-microbial resistance in pathogens and adjust the empirical therapy accordingly.
Efficient fMRI and Textual Alignment for ImageReconstruction from Human Brain Activity
Authors: Pham Bich-Nga , Vu Trong-Tai Dam , Vu Anh-Khoa Nguyen , Nguyen Vinh-Tiep
Published: September 2024

In neural decoding research, reconstructing natural images from fMRI signalsposes a captivating yet challenging problem. Conventional approaches use basiclinear mapping functions to project fMRI signals into a prior latent space (e.g.,image and text embeddings) and subsequently utilize a pre-trained image gener-ation model to create images conditioned on the embedding. While effective atcapturing low-level features like layout, texture, and shape, these methods oftenfail to capture high-level features such as object categories, spatial positions, andthe number of objects. These failures are often due to the insufficient seman-tic information carried by the text embeddings. To address these challenges, wefocus on improving text conditioning for image generation and enhancing the in-formativeness of the text embeddings used in the process. We propose the MDIRframework, which employs a unified and deep neural network called MindMap-per to align fMRI signals with text embeddings more effectively. Our approachenhances the consistency between reconstructed images and the semantic infor-mation in text captions, including object categories and their relationships. Thismethod achieves superior semantic fidelity, producing images closely resemblingthe ground truth in fine-grained detail.
WITHDRAWN: Implementation of UPFC and Renewable Energy Resources using Chaotic African Vulture Optimization Algorithm to Study the sustainablity of power system under Economical and Environmental Aspect
Authors: Mondal Basudeb , Biswas Soumen , Bhattacharya Anagha , Dutta Susanta , Chatterjee Rajesh Kumar , Akhtar Md Amir Khusru , Kumar Mohit , Chatterjee Mukesh Kumar , Verma Sahil , Khurma Ruba Abu , Mallik Saurav , Shah Mohd Asif
Published: September 2024

The optimal power flow (OPF) problem is of paramount interest and challenge for researchers in Electrical power systems. The problem becomes more challenging when Renewable Energy Sources (RES) like solar wind, etc. are integrated with the traditional interconnected network The main goal of this paper is the cost reduction of a hybrid system comprising both conventional and RES with the integration of Flexible AC transmission Systems (FACTs), considering system limitations in emission loss, in transmission line, to cater voltage fluctuations such that the overall system stability is improved. The classic problem of OPF itself is extremely complex and nonlin-ear, coupled with convex, intermittent constraints. The issue’s complexity increases when the unpredictable behaviour of solar and wind energy is considered. Using solar and wind power in traditional thermal power generations in the particular test system, this research suggests an analysis of the OPF problem by using a metaheuristic optimization technique Chaotic African Vulture Optimization Algorithm (CAVOA.) The suggested method was tested using a modified IEEE 30-bus system and executed using MATLAB in sixteen cases via multi-objective functions. The proposed problem is mitigated by computational intelligence tools to solve OPF problems like tuning grid voltages, transformer tap setting, allocation and sizing of FACTs devices, capacitor bank rating, etc. Compared to the outcomes of the (insert full form) FDBAGDE methods and those found in the literature, the simulation outcomes obtained through the suggested approach successfully identified the best solution. Additionally, the suggested algorithm’s superiority is assessed using a statistical method known as the one-way analysis of variance (ANOVA) test.
The Relationship between Intimate Partner Violence and Parenting Styles with Mediated Attachment Styles in Iranian Women
Authors: sadeghmohammadi Fatemeh , Spencer Chelsea
Published: September 2024

Purpose
The primary aim of this study was to investigate the role of attachment styles as intermediaries in the relationship between intimate partner violence (IPV) and parenting styles among Iranian women.
Methods
Data for this study was collected between September and December 2020. The participants consisted of 102 women who had been referred to Social Emergency Centers in Isfahan due to their experiences with domestic violence. Participants filled out the Haj-Yahia Violence Questionnaire, Baumrind Parenting Styles Questionnaire (BPSQ), and the Attachment Styles Questionnaire (AAQ). To examine the hypothesized relationships, Structural Equation Modeling (SEM) was used.
Results
Economic IPV victimization was negatively related to secure attachment (β = -0.309, p = 0.019) and positively related with authoritative parenting (β = 0.422, p = 0.019) and avoidant attachment style (β = 0.563, p = 0.000). There was a significant, positive relationship between sexual IPV victimization with secure and avoidant attachment styles (β = 0.351, p = 0.011; β = 0.407, p = 0.000). Authoritative parenting style was related to avoidant attachment (β = -0.524, p = 0.015) and secure attachment (β = 0.371, p = 0.000).
Conclusions
Iranian IPV victims with secure attachment style were more likely to utilize authoritative parenting and those who have avoidant attachment were less likely to use authoritative parenting. Attachment styles may influence the relationship between IPV and parenting styles in Iranian women who have experienced IPV.
An electro-mechanical co-optimization platform for MEMS devices with freeform geometry based on a genetic algorithm
Authors: Wang Chen , Wu Xinyu , Sadeghpour Sina , Shojaeian Milad , Wang Linlin , Quan Aojie , Guan Yangyang , LIU Huafeng , Wang Yuan , Zhang Pan , Martins Rui P. , Mak Pui-In
Published: September 2024

This paper describes a novel, system-level design methodology based on a genetic algorithm (GA) using freeform geometries for microelectromechanical systems (MEMS) devices. The proposed method can concurrently design and co-optimize the electronic and mechanical part of a MEMS device comprising freeform geometries to achieve a better system performance, i.e., higher sensitivity, better system stability and larger fabrication tolerances. Also, the introduction of freeform geometries allows higher degrees of freedom in the design process, improving the diversity and potentially the performance of the MEMS devices. A MEMS accelerometer comprising a freeform mechanical motion preamplifier in a closed-loop control system is presented to demonstrate the effectiveness of the design approach. The optimization process shows the main figure-of-merit (FOM) is improved by 482%. For the mechanical part, there is an improvement of the product of sensitivity and bandwidth by 151 %, and by 276 % for sensitivity. For closed-loop performance, there is an improvement of 120% for the ratio of open and closed-loop displacements. Excellent immunities to fabrication errors and parameter mismatch are achieved. Experiments show that the displacement of the MEMS accelerometer in the closed-loop system is decreased by 86 % with 4.85 V feedback voltage compared with that in the open-loop system under a 1g 100 Hz acceleration input. The static and dynamic nonlinearity in the closed-loop system is improved by 64 % and 61 %, respectively, compared with those in the open-loop, in the ±1 g acceleration input range. Besides, the closed-loop system improves the cross-axis sensitivity by 18.43%, compared with that in the open-loop. It is the first time, a closed-loop system for a MEMS accelerometer comprising a mechanical motion preamplifier is successfully implemented experimentally.
Deep learning to estimate response of concurrent chemoradiotherapy in non-small-cell lung carcinoma
Authors: Peng Jie , Zhang Xudong , Hu Yong , He Tianchu , Huang Jun , Zhao Mingdan , Meng Jimei
Published: September 2024

Background
Concurrent chemoradiotherapy (CCRT) is a crucial treatment for non-small cell lung carcinoma (NSCLC). However, the use of deep learning (DL) models for predicting the response to CCRT in NSCLC remains unexplored. Therefore, we constructed a DL model for estimating the response to CCRT in NSCLC and explored the associated biological signaling pathways.
Methods
Overall, 229 patients with NSCLC were recruited from six hospitals. Based on contrast-enhanced computed tomography (CT) images, a three-dimensional ResNet50 algorithm was used to develop a model and validate the performance in predicting response and prognosis. An associated analysis was conducted on CT image visualization, RNA sequencing, and single-cell sequencing.
Results
The DL model exhibited favorable predictive performance, with an area under the curve of 0·86 (95% confidence interval [CI]: 0·79–0·92) in the training cohort and 0·84 (95% CI: 0·75–0·94) in the validation cohort. The DL model (low score vs. high score) was an independent predictive factor; it was significantly associated with progression-free survival and overall survival in both the training (hazard ratio [HR] = 0·54 [0·36−0·80], P = 0·002; 0·44 [0·28−0·68], P < 0·001) and validation cohorts (HR = 0·46 [0·24−0·88], P = 0·008; 0·30 [0·14−0·60], P < 0·001). Also, it was positively related to the pathways involved in cell adhesion molecules, the P53 signaling pathway, and natural killer cell-mediated cytotoxicity. Single-cell analysis revealed that differentially expressed genes were enriched in different immune cells.
Conclusion
The DL model demonstrated a strong predictive ability for determining the response in patients with NSCLC undergoing CCRT; our findings contribute to understanding the potential biological mechanisms.
FGF19 is a biomarker associated with prognosis and immunity in colorectal cancer
Authors: Wang Peng , Zhu Zhenpeng , Hou Chenyang , Xu Dandan , Guo Fei , Zhi Xuejun , Liang Weizheng , Xue Jun
Published: September 2024

The aim of this study was to investigate the relationship between fibroblast growth factor 19 (FGF19) and the prognosis and immune infiltration of colorectal cancer (CRC), and to find the related genes and pathways affecting the occurrence and development of CRC, providing an important molecular basis for the early diagnosis and immunotherapy of CRC. We performed Venn overlap analysis on prognosis-related genes of CRC and up-regulated differentially expressed genes (DEGs) of CRC and immune-related gene sets to obtain the final DEGs. We investigated the relationship between the target genes and pathological parameters, immune infiltration, and immune checkpoints. The relevant functions and signaling pathways of target genes were analyzed by enrichment analysis. We investigated the genetic variation of the target genes. We analyzed the association of target genes with tumor heterogeneity and drug sensitivity. Finally, we performed single-cell analysis of the target genes. The results indicate that FGF19 is a target gene associated with immunity and prognosis in CRC patients. By exploring the relationship between FGF19 and neutrophil extracellular traps (NETs), and the relationship between NETs and the immune microenvironment, we found that FGF19 may have an effect on the progression of CRC by promoting NETs expression leading to immune cell suppression.
Identifying the Source of the Dust Storm in Rainy Conditions and Determining the Effects of Dust on the Physical Structure of Clouds in the West and Southwest of Iran
Authors: rostami dana , Lashkari Hassan , Mohammadi Zainab
Published: September 2024

Dust storms have direct and indirect effects on the climate and the environment under their influence. During the last two decades, due to climate changes and land use changes in the west and southwest of Iran, dust storms with precipitation have been observed, which certainly greatly impact the cloud structure and subsequent precipitation in this region. This research aims to identify the origin of dust storms and investigate the effects of these storms on the physical structure of clouds in rainy conditions and unstable atmospheres in the study area. This research used thematic maps, the HYSPLIT model, and satellite images to identify the source of these types of storms. Also, SIVIRI sensor images and dust data from the CAMS global reanalysis EAC4 have been used to investigate the effects of dust on the cloud structure. Based on model tracking and satellite images, five regions, including the Nafud desert and Rub al-Khali in Saudi Arabia, desert regions of North East Africa, western regions of Syria, and western Iraq, were identified as the most important source of this phenomenon. Also, the effects of dust on cloud structure showed a strong positive correlation between the amount of dust and the parameters of optical depth and liquid water path, at a significant level of 95% in the sample of heavy rains. There is no significant correlation in the relationship between other parameters of cloud structure in the event of heavy precipitation. Also, the results showed no significant relationship between the amount of dust and cloud parameters in light rain. Identifying the source areas and routes of dust storms, as well as investigating the effects of dust on the structure of clouds, will improve our understanding of the mechanisms and effects of dust storms on the climate and environment of the region.
A multivariate model for the prediction of pregnancy following laparoscopic artificial insemination of sheep.
Authors: Spanner E.A. , de Graaf S.P. , Rickard J.P.
Published: September 2024

The causes of variation in the success of laparoscopic artificial insemination (AI) in sheep are not well understood. As such, this study incorporated the contributions of multiple male and female factors relevant to the success of AI into a comprehensive prediction model for pregnancy success. Data from Merino ewes (N = 30 254) including age, uterine tone (1; pale/flaccid-5; turgid/pink), intra-abdominal fat (1; little to no fat present-5; high fat), time of insemination and sire used, were recorded during AI. A subset of semen per sire (N = 388) was thawed and assessed for volume, subjective motility, sperm concentration, and morphology. Sperm motility (CASA), viability and acrosome integrity (FITC-PNA/PI), membrane fluidity (M540/Yo-Pro), mitochondrial superoxide production (Mitosox Red/Sytox Green), lipid peroxidation (Bodipy C11), level of intracellular reactive oxygen species (H2DCFDA) and DNA fragmentation (Acridine Orange) were also assessed 0, 3 and 6h post-thaw. Logistic binomial regression revealed sperm concentration (P < 0.001), CASA parameters at 0h (PCA3; P = 0.03), viable acrosome intact sperm at 6h (P = 0.02), abnormal morphology (P < 0.001), uterine tone (P < 0.001) and intra-abdominal fat (P = 0.03) of ewes influenced likelihood of pregnancy. Results generated will help standardise the pre-screening and selection of semen and ewes prior to artificial breeding programs, reducing variation in the success of sheep AI.
Effect of fractional carbon dioxide laser combined with recombinant bovine basic fibroblast growth factor gel in the treatment of mature scar after facial scald burns: a retrospective cohort study
Authors: Yang Qing , Yin Yue , Dou Wenjie , Fan Xing , Xue Ping , Li Tong
Published: September 2024

Objectives
To assess the safety and clinical effect of fractional carbon dioxide (CO2) laser combined with recombinant bovine basic fibroblast growth factor (rb-bFGF) in the treatment of mature scars after facial scald burns.
Methods
We collected 123 patients with mature scars after facial scald burns who received fractional CO2 laser treatment in our department for a retrospective cohort study. According to whether the rb-bFGF gel was used during the treatment, patients were divided into CO2 + rb-bFGF group and CO2 group. The modified Patient and Observer Scar Assessment Scale (POSAS) scar score was used to evaluate the clinical effect. Patient satisfaction and adverse events were also assessed.
Results
At the last follow-up visit, the PSAS score was statistically different between the two groups (7.74 ± 2.15 vs. 9.41 ± 1.97; P < 0.01), including color (1.79 ± 0.77 vs. 2.80 ± 1.15; P < 0.01), stiffness (1.75 ± 0.62 vs. 2.00 ± 0.50; P < 0.01), and thickness (1.96 ± 0.48 vs. 2.16 ± 0.51; P < 0.01); the OSAS score was statistically different between the two groups (11.34 ± 3.21 vs. 12.96 ± 3.12; P < 0.01), including pigmentation (1.75 ± 0.78 vs. 2.61 ± 1.20; P < 0.01), thickness (1.92 ± 0.51 vs. 2.10 ± 0.42; P < 0.05), relief (1.64 ± 0.60 vs. 1.86 ± 0.50; P < 0.05), and pliability (1.96 ± 0.62 vs. 2.24 ± 0.52; P < 0.05). For patient satisfaction and adverse events, patients in the CO2 + rb-bFGF group had faster wound healing, lower incidences of persistent erythema and hyperpigmentation, and higher satisfaction.
Conclusions
The effect of fractional CO2 laser combined with rb-bFGF gel in the treatment of mature scar after facial scald burn is better than that of laser alone.
Construct validity and reliability of the Thai version of the Brief Illness Perception Questionnaire and its association with overall functioning and health in patients with ankylosing spondylitis
Authors: Chiowchanwisawakit Praveena , Ratta-apha Woraphat , Meannui Nutwara
Published: September 2024

Objectives
This cross-sectional study investigated the construct validity and reliability of a Thai-language version of the Brief Illness Perception Questionnaire (Thai-BIPQ) and its association with health in ankylosing spondylitis (AS) patients, as measured by the ASAS–Health Index (ASAS-HI)
Methods
AS patients receiving treatment at Siriraj Hospital were recruited. Reliability was assessed using Cronbach’s alpha coefficient and the intraclass correlation coefficient (ICC). Construct validity was determined by Spearman correlation with the Ankylosing Spondylitis Disease Activity Score (ASDAS), ASAS-HI, and Hospital Anxiety and Depression Scale (HADS). Linear regression was used to analyze the associations between the ASAS-HI (dependent variable) and the Thai-BIPQ (independent variable).
Results
We recruited 61 patients, 63.9% male, with a mean age of 47.9 years and a mean disease duration of 16 years. The median Thai-BIPQ score was 2. Cronbach’s alpha was 0.53 but increased to 0.73 after deleting the items “timeline,” “treatment control,” and “coherence.” The ICC was 0.95 with no missing data. The Thai-BIPQ showed moderate correlations with the ASDAS, ASAS-HI, and HADS (Spearman’s rho 0.44–0.56). According to multivariate regression, Thai-BIPQ (P = 0.006) and ASDAS ≥ 2.1 (P < 0.001) were positively associated with the ASAS-HI.
Conclusions
The Thai-BIPQ is a valid, reliable, and feasible tool for evaluating illness perception in AS patients. Low disease activity and positive illness perception are associated with better functionality and health. Further research is necessary to explore strategies for modifying illness perceptions in AS patients.
Dietary Vitamin A Intake and Associated Factors among Lactating Women in Wondo Genet District, Sidama Region, Southern Ethiopia
Authors: Bolka Amelo , Sikuare Selamawit , Dona Aregahegn , Philipos Assefa
Published: September 2024

Background: Vitamin A deficiency remains a public health problem in Ethiopia, despite the implementation of the national nutrition program. However, evidence on the dietary vitamin A intake adequacy among lactating women is limited. This study was aimed at assessing dietary vitamin A intake and associated factors among lactating women in Wondo Genet district of Sidama Region, Southern Ethiopia.
Methods: A community-based cross-sectional study was conducted among 411 lactating women from January 1 to 28, 2024. A simple random sampling method was followed to select the study respondents. Data were collected using a structured pretested questionnaire. Vitamin A inadequacy was defined as a dietary intake below the recommended daily allowance (RDA). Associated factors of dietary vitamin A inadequacy were identified using a logistic regression model. The outputs were presented using adjusted odds ratios (AOR) with 95% confidence intervals (CI).
Results: The study presented 36.9% (95% CI: 32.2%-41.6%) prevalence of inadequate intake of vitamin A. Large family size (AOR =2.73, 95% CI: 1.70, 4.39), food insecurity (AOR =2.08, 95% CI: 1.29, 3.32), poor knowledge on vitamin A (AOR: 1.81, 95% CI: 1.09, 2.98), not received nutritional counselling (AOR =3.61, 95% CI: 2.17, 6.03) and consumed fewer than three meals per day (AOR =3.56, 95% CI: 2.20, 5.75) were significantly associated with inadequate vitamin A intake.
Conclusion: The study found a high prevalence of inadequate dietary vitamin A intake among lactating women in the area. Independent predictors of inadequate intake included large family size, food insecurity, lack of nutritional counseling, knowledge of vitamin A, and the number of meals consumed per day. We strongly recommend educating lactating women to consume foods rich in vitamin A and participate in income generating activities.
Validation of A Novel Whole Blood Coagulometer Sensitive to the Direct Oral Anticoagulants
Authors: Bakhru Sasha H. , Jiang Xuan , Chen Lirong , Osmani Dardan , Kronen Kelly , Mootoo Daryl , Zappe Stefan , Ansell Jack
Published: September 2024

Readily available and rapid turn-around, bedside assays to measure the effect of the direct oral anticoagulants (DOACs) are not available. This study evaluates a new point-of-care (PoC) coagulometer to assess the anticoagulant effects of the DOACs and low molecular weight heparin. Studies were done in fresh spiked blood from healthy volunteers. PoC coagulometer baseline clotting times were half that of the manual whole blood clotting time (WBCT, legacy method) and exhibited a sensitivity to DOAC anticoagulation approximately twice that of WBCT. All %CV values for both methods were < 10% with most being < 5% indicating acceptable precision of both methods. R2 values for both clotting time and percent rise from baseline were > 0.98 indicating a strong correlation between the two methods. Replicate measurements for all subjects showed a maximum upper %CV value of 5.56% and a maximum upper value of all absolute %Differences of 5.5%, with both criteria meeting predefined acceptance criteria. The dose-response curves for all subjects were linear across the entire tested concentration ranges. The Perosphere Technology PoC coagulometer detects a range of therapeutic levels of the DOACs apixaban, rivaroxaban, edoxaban, as well as the low molecular weight heparin, enoxaparin, with high precision and sensitivity.
Surgical management of small intestinal foreign bodies in children -5 years of experience in a tertiary hospital
Authors: Chen Faling , Lv Zhibao , Liu Jiangbin
Published: September 2024

Objective
To explore the surgical treatment experience of small intestinal foreign bodies (FBs) in children.
Methods
Retrospective analysis of clinical data of 27 patients with surgical treatment of small intestinal FBs from February 2019 to March 2024.
Results
There were 15 males and 12 females with an average age of 4.3 years, and an average duration of 6.9 days. Only 12 patients had a clear history of ingestion of FBs. All patients underwent preoperative X-ray examination, only 17 cases of metal FBS were found, and the remaining 10 cases of non-metallic FBS were accurately diagnosed by CT examination. All patients underwent surgical treatment, including 24 patients who underwent emergency surgery on the day of admission. Intestinal perforation was found in 21 cases (21/27, 77.8%). FBS included magnetic beads or squares, jujube pits, fecaliths, trichobezoar, super absorbent polymer (SAP) beads. FBS were removed from all 26 patients except 1 case who pushed the fecal stone causing obstruction into the colon. The average hospitalization time for patients was 12.4 days, and there were three cases of postoperative complications, including severe intra-abdominal infection, incision infection, and adhesive ileus. All patients had good prognosis during follow-up.
Conclusion
FBs in the small intestine of children often lead to intestinal perforation and can be accompanied by severe systemic infection, with atypical clinical manifestations. CT scanning can detect non-metallic FBs that cannot be visualized by X-ray, and assist in locating the position of the FBs. Surgical intervention is safe and effective, and can achieve good outcome.
Digital Accessibility in Disaster Periods in Turkey: Investigation of Accessibility of Web Pages and Mobile Applications of the Relevant Organisations
Authors: Kalac Mustafa Ozhan , Kilinc Murat , Yilmaz Engin , Yesilada Yeliz
Published: September 2024

Digital accessibility during disasters is critical for people with disabilities to access information in emergencies. The research, which evaluates the accessibility of the relevant web and mobile applications in Turkey in this field, aims to emphasise the importance of digital accessibility in disaster periods and to provide suggestions for improvement. Within the scope of the research, websites and mobile applications provided by relevant governmental and non-governmental organisations were examined. In the evaluation process, factors such as compliance with accessibility standards, user experience, access to information and features for the needs of individuals with disabilities were taken into consideration. The results reveal that there are various accessibility problems in the digital platforms of the relevant organisations in Turkey. In line with the findings, recommendations such as strengthening accessibility policies, complying with standards and increasing awareness raising activities are presented. Facilitating the access of disabled individuals to information during emergency periods is a critical step in supporting inclusiveness. In this context, this research provides an important basis for future studies and policy developments, and aims to raise awareness to public institutions, non-governmental organisations and the private sector that they should make more efforts to make their applications accessible to meet the needs of people with disabilities.
Comparative Analysis of Different Machine Learning Techniques on Traffic Signs Dataset
Authors: MP Ayyoob. , Mehthab P K
Published: September 2024

The rapid advancements in intelligent transportation systems have highlighted the critical importance of accurate and efficient traffic sign recognition for road safety. Traditional methods relying on handcrafted features and classical machine learning techniques have shown limited accuracy and robustness under varying environmental conditions. This study explores the potential of deep learning, specifically Convolutional Neural Networks (CNNs), for traffic sign recognition. We conduct a comparative analysis of various CNN architectures, including custom models and well-established networks like VGG16, VGG19, EfficientNetB0, and ResNet50. Additionally, we investigate hybrid models that combine features from different architectures to enhance accuracy and robustness. Using the GTSRB dataset, we evaluate the performance of these models based on metrics such as test accuracy, test score, and F1-score. Our findings indicate that custom CNN models and certain hybrid combinations, such as Custom CNN x VGG16, achieve superior performance. This research contributes to the academic understanding of machine learning techniques in traffic sign recognition and holds practical significance for improving the safety and efficiency of modern transportation networks.
Hotspot mapping of pest introductions in the EU: A regional analysis of environmental, anthropogenic and spatial effects
Authors: Rosace Maria Chiara , Conesa David V. , López-Quílez Antonio , Marini Lorenzo , Martinez-Beneito Miguel A. , Nardi Davide , Rossi Vittorio , Vicent Antonio , Cendoya Martina
Published: September 2024

Plant pests pose a significant threat to global agriculture, natural ecosystems and biodiversity, causing severe ecological and economic damage. Identifying regions more susceptible to pest introductions is crucial for developing effective prevention, early detection and outbreak response strategies. While historical data on pest introductions in the European Union (EU) exist, they are typically reported at the regional level. This broad aggregation poses a challenge for accurate analysis in plant health research. This study addresses this gap by leveraging existing regional data to identify hotspots for pest introductions within the EU and the UK, through a Bayesian hierarchical spatial model. Specifically, we employed the Besag, York, and Mollié (BYM) model to identify higher risk regions by incorporating covariates and spatial effects to borrow information from neighbouring areas. The results showed a positive effect of annual average temperature, annual average precipitation, and human population density on the risk of pest introduction, highlighting the relevance of the spatial component. Our analysis pinpoints high-risk regions in southern Europe, particularly northern Italy. Additionally, the high human population density and documented pest introductions in the Netherlands contributed to its elevated risk. While limitations exist due to the regional nature of the data, this study represents a methodological advancement, demonstrating the effectiveness of spatial models and offering a robust framework for future studies using regional data. It also provides insights that can inform targeted prevention, early detection and preparedness strategies, ultimately contributing to safeguarding agriculture, natural ecosystems and biodiversity in Europe.
A Review on EEG-based Multimodal Learning for Emotion Recognition
Authors: Pillalamarri Rajasekhar , Shanmugam Udhayakumar
Published: September 2024

Emotion recognition from electroencephalography (EEG) signal is crucial for human-computer interaction, yet poses significant challenges. While various techniques exist for detecting emotions through EEG signals, contemporary studies have explored multimodal approaches as a promising advancement. This paper offers an overview of multimodal techniques in EEG-based emotion identification and discusses recent literature in this area. But these models are computational hungry, which is necessary to address through our research, highlighting the need for further research. A relatively unexplored avenue is combining EEG data with behavioral modalities, considering unpredictable levels of reliability. The suggested review examines the strengths and pitfalls of existing multimodal emotion recognition approaches from 2017 to 2024. Key contributions include a systematic survey on EEG features, exploration of EEG integration with behavioral modalities, and investigation of fusion methods like conventional and deep learning techniques. Finally, key challenges and future research directions in implementing multi-modal emotion identification systems.
Improving data interpretability with new differential sample variance gene set tests
Authors: Rahmatallah Yasir , Glazko Galina
Published: September 2024

Background
Gene set analysis methods have played a major role in generating biological interpretations from omics data such as gene expression datasets. However, most methods focus on detecting homogenous pattern changes in mean expression and methods detecting pattern changes in variance remain poorly explored. While a few studies attempted to use gene-level variance analysis, such approach remains under-utilized. When comparing two phenotypes, gene sets with distinct changes in subgroups under one phenotype are overlooked by available methods although they reflect meaningful biological differences between two phenotypes. Multivariate sample-level variance analysis methods are needed to detect such pattern changes.
Results
We use ranking schemes based on minimum spanning tree to generalize the Cramer-Von Mises and Anderson-Darling univariate statistics into multivariate gene set analysis methods to detect differential sample variance or mean. We characterize these methods in addition to two methods developed earlier using simulation results with different parameters. We apply the developed methods to microarray gene expression dataset of prednisolone-resistant and prednisolone-sensitive children diagnosed with B-lineage acute lymphoblastic leukemia and bulk RNA-sequencing gene expression dataset of benign hyperplastic polyps and potentially malignant sessile serrated adenoma/polyps. One or both of the two compared phenotypes in each of these datasets have distinct molecular subtypes that contribute to heterogeneous differences. Our results show that methods designed to detect differential sample variance are able to detect specific hallmark signaling pathways associated with the two compared phenotypes as documented in available literature.
Conclusions
The results in this study demonstrate the usefulness of methods designed to detect differential sample variance in providing biological interpretations when biologically relevant but heterogeneous changes between two phenotypes are prevalent in specific signaling pathways. Software implementation of the developed methods is available with detailed documentation from Bioconductor package GSAR. The available methods are applicable to gene expression datasets in a normalized matrix form and could be used with other omics datasets in a normalized matrix form with available collection of feature sets.
When to vaccinate for seasonal influenza? Check the peak forecast
Authors: Spencer Julie A , Smith Manhong Z , Osthus Dave , Alexander Prescott C , Valle Sara Y Del
Published: September 2024

Background: Seasonal influenza infects 5-20% of people every year in the United States, resulting in hospitalizations, deaths, and adverse economic impacts. To mitigate these impacts, influenza vaccines are developed and distributed annually; however, growing evidence suggests that vaccine effectiveness (VE) wanes over the course of a flu season. Delaying influenza vaccination for older adults has attracted attention as a potential public health strategy. However, given the uncertainties in seasonal peak, vaccine effectiveness, and waning rates, postponing vaccination could also lead to increased morbidity, motivating an evaluation of a range of potential scenarios.
Methods: We systematically investigated a broad range of vaccination start times for five age groups under six combinations of initial effectiveness and waning rates, based on influenza cases and vaccine uptake data from 10 influenza seasons. We defined the most favorable vaccination schedule as the one that resulted in the greatest reduction in disease burden.
Results: In scenarios with fast waning, all age groups benefit from delaying vaccination regardless of initial VE and peak timing. In scenarios with slower waning, results are mixed. For the 65+ group, high initial VE and slow waning suggests that in early-peaking seasons, early vaccination most effectively reduces disease burden, while in late-peaking seasons delaying vaccination is most effective. For the 65+ group in medium and low initial VE, and slow waning scenarios, delaying vaccination appears to prevent the greatest number of cases, regardless of whether the season peaks early or late.
Conclusion: The most favorable vaccination schedule is sensitive to changes in initial VE, waning rate, and peak timing. Given estimates of these quantities from statistical and immunological models and observations, our methods can inform vaccination recommendations in order to most effectively reduce the annual disease burden caused by seasonal influenza. Specifically, accurate peak timing forecasts for the upcoming season have the potential to guide decisions on when to vaccinate.
Comparative study of the Thermogravimetric Analysis (TGA) and Differential Thermal Analysis (DTA) of Bio-synthesized Magnesium Oxide Nanoparticles Using Rubber (Hevea braziliensis), Awolowo (Chromolaena odorata), and Oil palm (Elaeis guineensis) leaves Extract
Authors: Otabor Godfrey Osatohanmwen , Ikhuoria Esther Uwidia , Onaifo Joshua Osaretin , Ifijen Hilary Ikhazuagbe , Ehigie Aiyevbekpen Clinton
Published: September 2024

Thermogravimetric Analysis (TGA) and Differential Thermal Analysis (DTA) were used to assess the thermal stability of bio-synthesized MgO nanoparticles (MgONPs). TGA revealed that Rubber leaf MgONPs had a multi-step degradation process: initial weight loss at 220°C-325°C, significant loss at 330°C-625°C, with 24.36% residue. Palm Oil leaf (POLE) MgONPs showed initial loss at 300°C-460°C, further decomposition up to 575°C, and 25.5% residue. Awolowo leaf MgONPs had a single degradation phase from 480°C to 790°C, with 28.9% residue, indicating higher stability. DTA analysis showed exothermic peaks at 240°C, 360°C, and 600°C for Rubber leaf MgONPs; 470°C and 560°C for POLE; and 590°C and 660°C for Awolowo leaf MgONPs, highlighting Awolowo's superior thermal stability
Selective Detection of Avian Influenza Virus Subtypes in the Terahertz Region using Array of Gold Cross-shaped Absorber
Authors: Bagheri Mohammad Kazem , Bahadoran Mahdi , Hosseini Mehdi , AhmadNoorden Ahmad Fakhrurrazi
Published: September 2024

Three subtypes of Avian Influenza Viruses (AIVs) - H1N1, H9N2, and H5N2 - were detected in 1.4 THz using metamaterial absorptive biosensor. The proposed sensor was consisted of an array of gold cross-shaped resonator on a silica-gold-silicon wafer. The sensor operates based on the interaction between the virus-infected cells and incident electromagnetic (EM) waves under room temperature condition, resulting in resonance peaks in the absorption spectrum within the terahertz frequency range of 1-2THz. The results were simulated using finite element method (FEM), achieving an ultra-high sensitivity of 53.6 µm/RIU, which corresponds to a figure of merit as high as 28.84. The proposed sensor holds great potential in reducing economic damages in the poultry industry, ensuring public health safety and can also be utilized for the identification of other biological agents or environmental contaminants.
Identification of serum glycan signatures in three major gastrointestinal cancers by high-throughput N-glycome profiling
Authors: Liu Si , Huang Jianmin , Liu Yuanyuan , Lin Jiajing , Zhang Haobo , Cheng Liming , Ye Weimin , Liu Xin
Published: September 2024

Background
Alternative N-glycosylation of serum proteins has been observed in colorectal cancer (CRC), esophageal squamous cell carcinoma (ESCC) and gastric cancer (GC), while comparative study among those three major gastrointestinal cancers has not been reported before. We aimed to identify cancer-specific serum N-glycan signatures and introduce a discriminative model between cancers in the same system.
Methods
The study population was initially screened according to the exclusion criteria process. Serum N-glycan profiling was characterized by a high-throughput assay based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Diagnostic model was built by random forest, and unsupervised machine learning was performed to illustrate the differentiation between the three major gastrointestinal (GI) cancers.
Results
We have found that three major gastrointestinal cancers strongly associated with significantly decreased mannosylation and mono-galactosylation, as well as increased sialylation of serum glycoproteins. A highly accurate discriminative power (> 0.90) for those gastrointestinal cancers was obtained with serum N-glycome based predictive model. Additionally, serum N-glycome profile was differentially distributed among those three cancer groups, and several altered N-glycans were unique to the specific cancer type.
Conclusions
Serum N-glycome profile was differentially expressed in three major gastrointestinal cancers, providing a new clinical tool for cancer diagnosis and throwing a light upon the cancer-specific molecular signatures.
A Study on the Site Selection of Urban Logistics Centers Utilizing Public Infrastructure
Authors: Chen Jiarong , Lee Jungwook , Lee Hyangsook
Published: September 2024

The COVID-19 pandemic has significantly increased logistics demand, necessitating efficient urban logistics infrastructure. In response, the Korean government plans to utilize vacant spaces within Seoul’s subway vehicle bases and develop large-scale logistics complexes in strategic locations. This study focuses on site selection for urban logistics centers within the Seoul Metropolitan Subway area using Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies. Key criteria for site selection are categorized into facility, geographical, environmental, and social factors. AHP results indicate geographical factors are most significant, followed by facility, social, and environmental factors. TOPSIS rankings show Sinnae as the most suitable site, followed by Godeok and Cheonwang. Recommendations include strategic infrastructure investment, fostering cooperation between logistics companies and local governments, integrating advanced technologies, implementing green logistics, workforce development, and community engagement. Limitations include reliance on current data and the need for future research incorporating updated data, environmental sustainability, and social equity.
Small leucine zipper protein regulates glucose metabolism of prostate cancer cells via induction of phosphoglycerate kinase 1
Authors: Han Sila , Park Sungyeon , Kim Suhyun , Kwon Sujin , Ko Jesang
Published: September 2024

Background Cancer cells exhibit an altered metabolism, whereby glucose is preferentially utilized to produce lactate through aerobic glycolysis. Increased lactate production creates an acidic microenvironment that supports tumor progression and metastasis. Human small leucine zipper protein (sLZIP) is involved in the transcriptional regulation of genes related to the migration and invasion of prostate cancer cells. However, the role of sLZIP in modulating glucose metabolism in prostate cancer remains unclear. This study investigated whether sLZIP regulates the transcription of glycolysis-related genes to promote metabolic reprogramming in prostate cancer.Methods Quantitative RT-PCR, western blotting, and immunohistochemistry were performed to determine gene or protein expression. JASPAR and luciferase activity assays were performed to investigate the role of sLZIP in regulating phosphoglycerate kinase 1 (PGK1) promoter activity. The extracellular acidification rate, lactate production, and ATP production assays were performed to determine the levels of aerobic glycolysis. MTT and colony formation assays were performed to examine cell proliferation and growth. Mouse xenograft experiments were conducted to investigate the effects of sLZIP-mediated PGK1 on tumor growth.Results Depletion of sLZIP resulted in the downregulation of several glycolytic genes, including glucose transporter 1, phosphofructokinase liver type, PGK1, and lactate dehydrogenase. Among these, only PGK1 showed a prominent dose-dependent decrease in mRNA and protein expression after sLZIP silencing. Mechanistically, increasing or decreasing sLZIP affected the promoter activity of PGK1 in a similar manner. Moreover, absence of sLZIP attenuated the maximum glycolytic rate in prostate cancer cells. These results were further supported by reduction in lactate secretion, glucose uptake, and ATP production in sLZIP-knockout prostate cancer cells. The sLZIP deficiency hindered cancer growth as demonstrated by proliferation assays. However, overexpression of PGK1 in sLZIP knockout cells resulted in recovery of aerobic glycolysis. Results of the xenograft experiment revealed that mice injected with sLZIP knockout cells exhibited a decrease in tumor mass compared to those injected with control cells.Conclusion These findings suggest that sLZIP contributes to the metabolic reprogramming of prostate cancer cells via the transcriptional regulation of PGK1.
Dynamic relocation policy for one-way electric carsharing systems considering space flexibility
Authors: Jiang Ronghang , Su Qiang , Zhu Lei , Yang Wei
Published: September 2024

Carsharing systems have attracted considerable market interest owing to their positive impact on resolving social and environmental pollution problems such as traffic congestion, lack of parking spaces, and greenhouse gas emissions. However, one-way carsharing systems often struggle with vehicle imbalance issues, which can affect customer satisfaction. To address this, a one-way electric carsharing model was designed to maximize operator revenue by introducing customer space flexibility. A mixed integer nonlinear program was formulated to optimize consumer flexibility, relocation, and employee-hiring decisions. The variation in the average vehicle charge at each station was captured using the state of change (SOC) model. Real data from the Evo carsharing company in Vancouver, Canada, were used to conduct numerical tests, verifying the effectiveness of the rolling horizon method in producing high-quality solutions. The results indicate that customer space flexibility can enhance the operational efficiency of carsharing systems without increasing the number of vehicles or parking spaces. This approach can also boost total system revenue and customer satisfaction, with departure space flexibility showing a significantly greater impact than arrival space flexibility.