bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring Sexual Health and HIV-Related Challenges in an Individual with Intellectual Disability: A Case Report
Authors: Würfel Lina M. , Potthoff Anja , Nambiar Sandeep , Skaletz-Rorowski Adriane 
Published: February 2024

Abstract
Background: HIV testing remains an important tool in identifying people living with HIV/AIDS (PLWHA). An early diagnosis of HIV can lead to a prolonged life expectancy if treatment is initiated promptly. Indicator illnesses can be the first sign of an HIV infection and should therefore be recognised and consequently a HIV test should be carried out. Testing should occur in all individuals as sexuality can be experienced by everyone, and stigma can lead to the exclusion of vulnerable groups, leading to a gap in diagnosis and treatment.
Case presentation: A 63-year-old man, who identifies as bisexual and has had an intellectual disability since birth, presented at our health care centre for HIV testing. A decade ago, the patient was diagnosed with Stage III Diffuse Large B-cell Non-Hodgkin Lymphoma, an AIDS defining cancer. The patient presented at a Haematology and Oncology department 3 months prior, due to a weight loss of 10 kg over the past 5 months. Oral thrush, an HIV-indicator condition, had been diagnosed by the otolaryngologists shortly before. During this medical evaluation, pancytopenia was identified. Despite the presence of indicator illnesses, the patient was never tested for HIV in the past. Staff members from the care facility for intellectually disabled suggested conducting a HIV test in our clinic through the public health department, where HIV positivity was revealed. The AIDS-defining diagnosis, along with a CD4+ cell count of 41/µl, suggests a prolonged period of HIV positivity.
Conclusion: Due to the presence of existing indicator illnesses, an earlier HIV diagnosis was possible. We contend that the patient was never asked about his sexual life likely due to his mental handicap. Patients presenting with AIDS indicator illnesses, including those with mental disabilities, should be given the opportunity to be tested for HIV. HIV/AIDS trainings should be made available to health care professionals as well as to personnel interacting with vulnerable groups.
Involvement of Adenozine A2a Receptors in Anxiety-like Behaviors in Tetrahydrocannabinol Treated Mice
Authors: ÜN Burçin , AKARSAKARYA Zeki , ÖZÜ Özlem YORULMAZ , ILGAZ Nermin Seda , YILMAZ Mehmet Bertan , SEÇİLMİŞ Mehmet Ata 
Published: February 2024

Abstract
Previous studies have suggested that adenosinergic system in the central nervous system (CNS), may play a role in both behavioral changes and the physiopathology of addiction induced by THC, and this is thought to be mediated by adenosine A2A receptors (A2AR). However, contribution of adenosinergic system isn’t well understood. In this study, we aimed to investigate the possible role of the adenosinergic system in THC-treated mice. For that purpose, THC (10 mg kg− 1), Adenosine A2AR agonist CGS-21680 (2.5 mg kg− 1), Adenosine A2AR antagonist Istradefylline (3 mg kg− 1), THC + Istradefylline, and THC + CGS-21680 were all given to male Swiss albino mice, once daily for five days. The same methods were used to administer the drug solvents to the sham groups. Anxiety-like behaviors were examined through the open field (OF) and elevated plus maze (EPM) tests in all groups. The expression levels of cannabinoid CB1R and adenosine A2AR genes in hippocampal tissues were assessed using real-time PCR (qPCR). THC treatment decreased the frequency of center crossings and rearing behavior in the OF test. In the EPM test, there was a notable decrease in the time spent in the open arm, alongside an increase in the time spent in the closed arm. Similar effects were obtained by the administration of CGS-21680 or THC + CGS-21680. Conversely istradefylline significantly prevented THC-induced anxiety-like behaviors. Also, THC caused a significant increase in the expression of adenosine A2AR genes in hippocampal tissues, while resulting in a partial decrease in CB1R expression. These results suggest that adenosine A2AR has a potential role in anxiety-like behaviors in THC-treated mice.
Hybridization of Support Vector Regression and Arima Models with Genetic Algorithms for Predicting Crude Oil Price
Authors: Bello Yusuf Olatunji , Olubusoye Olusanya Elisa 
Published: February 2024

Abstract
Crude oil plays a pivotal role in global economics, serving as a crucial raw material for manufacturing and a primary ingredient in transportation gasoline. Accurate forecasting of crude oil prices is essential for various sectors. Conventional statistical and econometric models often struggle with the non-linear and inconsistent nature of crude oil price data, leading to poor prediction performance. In this study, we propose a novel hybrid approach combining Support Vector Regression (SVR), a nonlinear machine learning model, with Autoregressive Integrated Moving Average (ARIMA), a linear econometric model. Genetic Algorithms (GA) was employed to optimize the parameters of both models. Our hybrid models, namely SVRGA_ARIMA and SVRGA_ARIMAGA, outperform individual models such as ARIMA and SVR, as well as the hybrid model SVR_ARIMA, in terms of forecasting accuracy. The proposed hybrid models achieve a significantly lower root mean square error compared to other models. Overall, our findings suggest that the hybrid SVRGA_ARIMA and SVRGA_ARIMAGA models, optimized with GA, offer a reliable framework for forecasting weekly crude oil prices.
Blood Vessels Segmentation of Coronary X-Rays Angiography Images Including Edge based Features and Artificial Intelligence Approaches
Authors: OSAMA MOHD , Kumar Rajesh , SHAHID MOHAMMAD 
Published: February 2024

Abstract
In present Era, the cardiovascular disease is the most common disease in human. According to the World Health organization reports 2022, there are 70% of Human death from the Heart attack. Most of the Indian peoples suffering from heart disease having the age group of 30–60 years. Xray Coronary angiography imaging is a primary procedure for diagnosis of heart disease. Manual Segmentation of heart vessels by cardiologists are typical and time-consuming process. Manual segmentation facing the problem of variations in results due to experience and expertise of the medical professionals. Segmentation of coronary vessels angiography provides important information for the expert and patient suffering from cardiovascular disease. Therefore, different types of computer-aided Tools have been designed and developed for automatic segmentation of coronary vessels angiography images. An automatic segmentation of coronary arteries can be improved by computer vision and artificial intelligence approaches. In this paper an automatic segmentation of coronary angiography images has been designed and implemented using edge-based feature and artificial intelligence approaches. For this purpose, dominating and prominent edges of cardiovascular arteries system has been detected using traditional edge detection algorithms like Sobel, Prewitt, Robert’s and Canny. The strong edges from the above-mentioned algorithms are selected using Artificial Intelligence (Random Forest) algorithm. Experimental results shows that proposed model provides accuracy, Positive Prediction Value, Sensitivity and Dice Coefficient as 99%, 96%, 94% and 95% respectively.
Poroelastic Effects of Chemical Loading in Consolidation of Residual Soils
Authors: Irheren Dada , Onyia Michael Ebie , Okafor Fidelis Onyebuchi 
Published: February 2024

Abstract
An analytical chemo-hydromechanical model of residual soils was presented in this study. The modeling procedure utilized a unique phenomenological approach, which highlighted some of the macro-mechanical influences responsible for the behavior of residual soils. The macromechanical analysis yielded an extended poroelastic theory. The developed model was applied in solving a typical civil engineering problem of soil consolidation. For a chemical loading treatment, the problem was using requisite boundary conditions. Thereafter, the mathematical software “Mathematica” was used for solving the ensuing diffusion equations using physico-chemical properties typical of a residual soil sample. Even though the chemical loading was instantaneous, it took some time before its effect could be felt everywhere according to the poroelastic theory. From obtained results, the evolution of the generated pore pressure showed increasing segments of the soil returning to their initial state after the passage of the pore pressure front. The vertical displacement showed a slight increase or elevation of the soil surface. The flux of water flow in the soil was initially positive before turning negative, which can be explained by initial successful penetration of the infiltrating liquid until it met increasingly tortuous paths as result of lower permeability. The water volume (per unit area) leaving the soil after chemical loading demonstrated that a portion of the water flux associated with the infiltrating liquid ends up leaving the soil through the sides.
Construction of eukaryotic expression vector of Apoptin-etag and TAT-Apoptin-etag and their effects on human esophageal squamous cell carcinoma in vitro
Authors: Zhu Jin-xiang , Zhang Ming-xin , Zhou Su-na , jia Zhang , Wang Jian-sheng 
Published: February 2024

Abstract
Esophageal carcinoma is one of the six most common carcinomas in the world, known for its late clinical presentation, rapid progression and poor survival. Compared with developed countries, the prevalence of esophageal cancer has significant differences in pathology, with significantly higher mortality and regional incidence. Esophageal squamous cell carcinoma (ESCC) is the most common type in China and in recent years, the incidence has shown an upward trend in the county. Considering the characteristics of esophageal cancer in China, seeking new treatments for esophageal squamous cell carcinoma is of great concern to clinicians. Apoptin, which is derived from chicken anemia, and has tumor-specific killing effects, is composed of 121 amino acids. Although the mechanism is not yet explained, it has been extensively studied and used in the treatment of malignant tumors. Here, we selected two human squamous cell carcinoma lines and constructed eukaryotic expression vectors of apoptin and TAT-apoptin fusion protein to investigate their effect on cell proliferation and cell cycle in transfection cells.
Enhancing Depression Predictive Models: a Comparative Study of Hybrid Ai, Machine Learning and Deep Learning Techniques
Authors: Kanchapogu Naga Raju` , Mohanty Sachi Nandan 
Published: February 2024

Abstract
In the quest to enhance predictive models for depression, this study introduces a novel comparative analysis of machine learning (ML) and deep learning (DL) techniques, further innovating with the development of hybrid AI models. Leveraging a dataset comprising 2,000 participants, enriched with demographic, socio-economic, behavioral, and clinical variables, including pre- and post-treatment Montgomery-Åsberg Depression Rating Scale (MADRS) scores, we embarked on a comprehensive exploration of factors influencing depression outcomes. Through meticulous data collection, we harmonized diverse variables ranging from basic demographic details to intricate clinical outcomes, paired with a rigorous feature selection process employing Recursive Feature Elimination (RFE) and Principal Component Analysis (PCA). Our analytical journey was underpinned by a robust hyper parameter tuning phase, ensuring the optimization of each model's predictive capacity. The study's core contribution lies in its exhaustive comparison of standalone ML and DL models against our crafted hybrid AI models, revealing a marked superiority of the latter in predicting depression with unparalleled accuracy. The hybrid models, through their synergetic integration of ML and DL methodologies, demonstrated a profound ability to navigate the complexity of depression's multifactorial nature, achieving a perfect prediction accuracy rate in our tests. Our findings advocate for a paradigm shift in predictive analytics for depression, underscoring the potential of hybrid AI models in transcending the limitations of traditional standalone approaches. This research not only paves the way for more nuanced and effective predictive tools in mental health care but also sets a benchmark for future studies at the intersection of biology, psychology, and artificial intelligence. The implications of this work are vast, offering a beacon of hope for personalized and preemptive mental health interventions.
Flexible electrochemical paper-based device for detection of breast cancer- derived exosome using nickel nanofoam 3D nanocomposite
Authors: Sahraei Nafiseh , Mazloum-Ardakani Mohammad , Moradi Alireza , Hoseynidokht Farzaneh 
Published: February 2024

Abstract
Exosomes as new biomarkers for cancer diagnosis have attracted attention because they are highly released by tumor cells in various biological fluids. In this study, an electrochemical paper-based immunosensor device (Exo-sensing paper) is introduced for the detection of exosome in the serum. The Exo-sensing paper is a three electrode system that is prepared using pattern paper and carbon and silver inks. The sensor part of this immunosensor contains a three-dimensional porous nanocomposite of nickel nanofoam coupled with graphene oxide and gold nanoparticles. The high specific surface area of this nanocomposite increases the antibody loading on the sensor surface significantly and consequently leads to obtaining a wide linear range of 500–1 × 10 7 Exospore/µL with a detection limit of 110 Exosome/µL. Due to some advantages of this constructed Exo-sensing paper such as easy storage, simple application, low cost and good selectivity in the real samples, this system has a good potential to be used as a point of care testing for in situ detection of the exosomes and is a promising strategy for minimally invasive liquid biopsy.
TongueTransUNet: Toward Effective Tongue Contour Segmentation Using Small Dataset
Authors: Al-hammuri Khalid , Gebali Fayez , Kanan Awos 
Published: February 2024

Abstract
Medical image segmentation is important for extracting desired objects among complex human structures to enable further analysis. In the case of lingual ultrasound, it is important to extract tongue contour to understand the language behaviour, which enables lingual ultrasound to act as a biofeedback. In order to segment tongue from ultrasound images, we need to train the deep-learning model on a large dataset, which made it challenging to generalize it using a wide variety of images as it is difficult to collect this huge data. In this research, we are proposing a strategy and generalized model that can work effectively using a well-managed small dataset. This article presents a hybrid architecture using UNet, Vision Transformer (ViT) and Contrastive loss to build a foundation model cumulatively. The process starts with building a reference representation in the embedding space using human experts to validate any new input for training data. UNet and ViT encoders are used to extract the input feature representations. The contrastive loss was then used to compare the new feature embedding with the reference in the embedding space. The UNet-based decoder is used to reconstruct the image to its original size. Before releasing the final results, a quality control process is used to assess the value of the segmented contour, and if rejected, the algorithm requests an action from a human expert to annotate it manually. The results show an improved accuracy over the traditional techniques and can be generalized as it contains only high-quality and relevant features related to the tongue in the embedding space.
q− Fibonacci Statistical Convergence
Authors: Atabey Koray 
Published: February 2024

Abstract
In this paper, we use the $q-$Fibonacci band matrix $\widehat{F}_{q}=\left(\widehat{F}_{nk}(q)\right)$ to introduce the notions of $q-$Fibonacci summability, $q-$Fibonacci statistical convergence, strongly $\widehat{F}_{q}[p]-$Ces\'{a}ro summability and give some inclusion relations about these concepts.
Mathematics Subject Classification (2010). 40G15. 40C05. 46A35. 42B08.
Early Postoperative Complications in Colorectal Cancer Patients Following Colorectal Surgery: A Prospective Study
Authors: Al-Amry Ali Lotf , Obadiel Yasser Abdurabo , Al-Shehari Mohammed Mohammed , Gailan Waleed Mohammed , Bajubair Mohammed Hadi , Jowah Haitham Mohammed 
Published: February 2024

Abstract
Purpose: This prospective study aimed to investigate the early outcomes of colorectal surgery in patients with colorectal cancer and determine their relationships with specific risk factors and comorbidities.
Patients and Methods: This study was conducted at AL-Thawra Modern General Hospital and AL-Kuwait University Hospital in Sana'a, Yemen, from January 2021 to December 2022. All consecutive patients who underwent surgical intervention for colorectal cancer were included. Data on patient demographics, comorbidities, tumor characteristics, surgical procedures, and postoperative outcomes were collected. Statistical methods were used to analyze the risk factors associated with operative complications.
Results: A total of 73 patients, with a mean age of 52.5 years (SD = 14.3), were included in the study. Among the patients, 44 (60.3%) were male, and 29 (39.7%) were female. The most frequent complication observed was surgical site infection, which occurred in 13 (17.8%) patients, primarily as superficial infections in 11 (15.1%) patients. Other local complications included wound dehiscence (4.1%), anastomotic leakage (2.7%), paralytic ileus (4.1%), and abdominal sepsis (2.7%). Additionally, systemic complications, including pneumonia (4.1%), deep vein thrombosis (4.1%), acute myocardial infarction (2.7%), and urinary tract infection (1.4%), were observed in 9 patients. Significant associations were found between the development of early postoperative complications and various factors. Patients aged 65 years and above had a greater rate of complications than did those aged younger than 65 years (55% vs. 22.6%, p value = 0.008). Furthermore, the presence of diabetes mellitus and low serum ALB levels (<35 g/L) were associated with increased complication rates (60% vs. 24.1%, p value = 0.01 and 42.9% vs. 8.3%, p value = 0.02, respectively).
Conclusion: Our study demonstrated favorable outcomes with no mortality and a comparable complication rate to other studies, despite the smaller sample size. The significant associations between postoperative complications, advanced age, diabetes mellitus, and low serum ALB levels highlight the importance of a multidisciplinary approach to enhancing overall patient outcomes.
Effects of Nitrogen Fertilizer Types and Application Rates on Fertilizer Utilization Efficiency and Yield of Dryland Maize
Authors: li wu ri ji musi 
Published: February 2024

Abstract
Dry farming areas are pivotal to agricultural production in China, and agronomic measures, such as tillage and fertilization, markedly influence crop yields. Ditch rain-harvesting planting, an effective water conservation technique, has proven beneficial for enhancing grain production in these regions. Because of the topographical changes from ridges and ditches, combined with moisture retention by mulching films, rainwater harvesting planting technology significantly influences soil water and heat dynamics, promoting temperature and moisture. In this study, "Xianyu 335" was used as the experimental material. Eight different fertilization regimens were tested: no fertilization (control, CK), nitrogen and phosphorus (NP), phosphorus and potassium (PK), nitrogen and potassium (NK), nitrogen (N: diammonium phosphate 24%, ordinary urea 76%), phosphorus potassium fertilizer (NPK1), nitrogen application (N: slow-release urea 40%, diammonium phosphate 20%, ordinary urea 40%), phosphorus-potassium fertilizer (NPK2), nitrogen application (70%N: slow-release urea), urea release 40%, diammonium phosphate 26%, ordinary urea 34%), phosphorus and potassium fertilizer (NPK3), and nitrogen (85%N: slow-release urea 40%, diammonium phosphate 23%, ordinary urea 37%), phosphorus, and potassium fertilizer (NPK4). These treatments were used to investigate their effects on maize grain yield, agronomic efficiency, and fertilizer utilization rate under full-film-covered ridge and furrow rainwater harvesting. The results from 2015 to 2016 indicated that the distinct fertilization methods significantly affected the physiological metrics and leaf area index of maize throughout the growth period, as well as grain yield and dry matter accumulation. Notably, the NPK3 treatment, which employed slow-release fertilizers, outperformed the other treatments. Its average grain yield stood at 8.66 t·hm-2, demonstrating an increase of 2.15 t·hm-2 (or 28.8%) compared with the control group. Moreover, NPK3 exhibited superior agronomic efficiency and fertilizer utilization. The findings indicate that integrating slow-release fertilizers into ridge and furrow rainwater harvesting systems can enhance maize growth and yield.
Understanding Land Use Dynamics and Environmental Impacts of Urbanization in Thimphu, Bhutan: A Satellite-Based Analysis
Authors: Chhetri Indra Bahadur , Gyeltshen Sangay , Dema Kelzang 
Published: February 2024

Abstract
The ability of land surface temperature (LST) and normalized difference vegetation index (NDVI) to examine the land surface change is regarded as important climate variables. However, no significant systematic examination of urbanization concerning environmental variables has been undertaken in the narrow valley of Thimphu, Bhutan, explicitly. Therefore, this study investigates the impact of land use and land cover (LULC) dynamics on LST, NDVI, and elevation, using Moderate-resolution Imaging Spectroradiometer (MODIS) data in Thimphu, Bhutan from 2000 to 2020. The results showed that LSTs varied substantially among different land use types, with the highest in built-up areas and the lowest in forests. There was a strong negative linear correlation between LST and NDVI in built-up areas, indicating the impact of anthropogenic activities. Moreover, elevation had a noticeable effect on both LST and NDVI exhibiting very strong opposite patterns at lower elevation. In summary, LULC dynamics have a significant influence on LST and NDVI, highlighting the importance of understanding the spatiotemporal pattern and its effects on ecological processes for effective land management and environmental conservation. Moreover, the study also demonstrated the applicability of relatively low-cost, moderate spatial resolution satellite imagery in examining the impact of urban development on the urban environment in Thimphu City.
Helping Medical Doctors Diagnose Cervical Cancer Using Decision Making based Deep Learning System
Authors: Alshareef Sedigh Essam 
Published: February 2024

Abstract
Cervical cancer is a leading cancer in the female population. This disease is considered dangerous as its slow and unpredicted growth. The prevention of such cancer can be mostly achieved by screening its transformation zones. The cervical pre-cancerous zones can be considered as three types: type 1, type 2, and type 3. Screening and analyzing these three stages can be crucial for preventing their transformation into cancer. Hence, it is essentially important to have an automated and intelligent system that can grade the cervical pre-cancerous colposcopy images into one of the three types. This can help in providing the right treatment and prevent cancer transformation. In this paper, we develop a residual learning-based model (ResNet-18) to be trained for classifying the type of a colposcopy cervical image into type 1, type 2, and type 3. Experimentally, the model was fine-tuned and evaluated on a public dataset of colposcopy cervical images and achieved promising results in cervical cancer screening of accuracy of 77% and F1-score of 79%.