bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Deep Learning Models for Traffic Flow Prediction
Authors: Guo Xuanchen
Published: November 2024

The issue of urban traffic congestion is becoming increasingly severe, highlighting the need for accurate traffic flow prediction to facilitate effective traffic management. Traditional prediction methods often struggle to address the complex spatiotemporal dependencies and external factors inherent in traffic data. This paper reviews existing deep learning models applied to traffic flow prediction, categorizing them into spatial and temporal types based on their dependencies. Spatial dependency models include those based on Euclidean space, such as CNN-based models, and non-Euclidean space models that combine Graph Convolutional Networks (GCN) with attention mechanism. These models effectively capture spatial variations in traffic flow data. Temporal dependency models, such as Recurrent Neural Network (RNN) and Temporal Graph Convolutional Network (T-GCN), focus on capturing long-term dependencies and time series dynamics. The selection of models depends on specific tasks and data characteristics. The article concludes with a summary and outlook on the entire discussion.
Research on Music Neighborhood-Based Recommendation Algorithms
Authors: Li Jinxu
Published: November 2024

This paper presents a comprehensive review of recommendation algorithms in the music domain. Music recommendation systems play a crucial role in delivering personalized content to users by analyzing patterns and preferences. We analyze several prominent recommendation algorithms, including collaborative filtering, content-based filtering, and hybrid models, each of which has been extensively applied to music recommendation tasks. The study also delves into the emerging techniques of deep learning and reinforcement learning in improving recommendation accuracy. A comparative analysis is provided, highlighting the strengths and limitations of each algorithm in terms of scalability, accuracy, and computational efficiency. Special attention is given to the challenges of balancing personalization and diversity in music recommendations. Furthermore, we explore how hybrid recommendation systems, which combine multiple methods, can overcome the limitations of individual models. The review concludes by identifying future research directions in the field of music recommendation systems, particularly the potential of leveraging more advanced machine learning techniques.
End-to-End Roadway Disease Recognition Based on Transformer Architecture
Authors: Deng Zhouheng
Published: November 2024

Road disease is a significant factor causing traffic accidents. Timely detection and recognition of road disease is significant for maintaining road safety and reducing traffic accidents. Therefore, it is urgent to study an automatic pavement disease recognition method with accuracy and real-time. However, existing real-time target detectors generally use a convolutional neural network-based architecture, and these detectors usually require post-processing of NMS, which makes the detectors difficult to optimize and unstable, resulting in a delay in reasoning speed. Therefore, we design a target detection model based on Transformer, which uses MobileNet as the backbone network to simplify the network structure and enables interaction and integration of features through an efficient hybrid encoder, which reduces the computational load and does not reduce the detection accuracy. Iou-aware query selection optimizes the object query vector in the Transformer structure and reduces the number of candidate boxes that the model needs to process. The experimental results show that we have achieved good results on the RDD2022 dataset.
Application of Improved Visual SLAM in Intraoperative Navigation of Robotic-Assisted Laparoscopic Surgery
Authors: Lin Ziying
Published: November 2024

In robot-assisted laparoscopic surgery, precise intraoperative navigation is essential to enhance the accuracy, safety, and efficiency of the procedure. By extracting feature points from the environment, Visual Simultaneous Localization and Mapping (V-SLAM) technology has been widely employed to accomplish self-localization and map generation. In laparoscopic surgery, V-SLAM offers high-precision real-time positional data for surgical robots, thereby improving the accuracy of operative navigation. Nonetheless, the performance of conventional V-SLAM algorithms is significantly compromised by the extremely dynamic characteristics of surgical environments. Widely used visual SLAM systems, such as ORB-SLAM, are susceptible to inaccurate feature point tracking in the presence of dynamic objects and variations in lighting, hence compromising navigation precision and surgical safety. This study assessed the efficacy of visual V-SLAM technology in enhancing intraoperative navigation during robot-assisted laparoscopic surgery, pointing out its contribution to surgical precision, safety, and operational efficiency. The research enhanced the ORB-SLAM2 algorithm to adapt to the dynamically changing conditions encountered during surgical procedures. The experiment validated the efficacy of the enhanced method within a simulated laparoscopic surgery setting and assessed the impact of three variables: light intensity, instrument occlusion, and dynamic tissue deformation, on trajectory error (ATE and RPE) and mapping accuracy. The findings indicated that under situations of low illumination, significant occlusion, and substantial deformation, ATE and RPE mistakes escalated by over 50%, while map accuracy diminished by approximately 40%, leading to heightened potential surgical risks.
Human-Computer Interaction on Facial Recognition and Emotional Feedback
Authors: Han Jinze
Published: November 2024

The advancement of science and technology has resulted in the growing prevalence of facial recognition technology in human-computer interaction, particularly in the domain of emotion recognition, where it shows significant potential. By identifying the user's facial expressions and emotional responses, the system is capable of conducting further analysis and prediction of the user's needs, thereby optimizing the emotion recognition experience of human-computer interaction. This article will elucidate the principles of facial recognition technology, with a particular focus on its practical applications and technical realization in emotion recognition. Furthermore, this article will examine the current limitations of the technology, discuss potential avenues for improvement, and speculate on the future development of facial recognition technology in the field of human-computer interaction. The technology is currently being used in a variety of areas, including smart home technology, medical rehabilitation and public services. The technology has the potential to improve the user experience by increasing the intelligence of devices and providing more personalised services to users through sentiment analysis.
Dynamic Obstacle Avoidance Technology Based on Multi-Sensor Fusion in Autonomous Driving
Authors: Chen Luyou
Published: November 2024

With the booming development of artificial intelligence and sensor technology, various types of devices are widely used in daily life and industry. This paper reviews the current state and prospects of multi-sensor fusion technology for dynamic obstacle avoidance in autonomous systems. The purpose of this paper is to discuss the application status and future development direction of multi-sensor fusion technology in dynamic obstacle avoidance. By analyzing the current research results and technical challenges, this paper will summarize how multi-sensor fusion technology can improve the performance of dynamic obstacle avoidance systems, and discuss the application of intelligent algorithms and future research directions The limitations of traditional single-sensor approaches are demonstrated through a single-sensor versus multi-sensor comparison, emphasizing the advantages of combining data from various sensors (e.g. lidar, cameras, and IMUs) to enhance environmental perception. This fusion improves obstacle detection accuracy and system robustness, particularly in complex urban environments. Despite significant advancements, challenges remain, including data management, real-time processing, and computational efficiency.
Leveraging LSTM Neural Networks for Stock Price Prediction and Trading Strategy Optimization in Financial Markets
Authors: Ju Chengru , Shen Qi , Ni Xin
Published: November 2024

In the Artificial Intelligence development market in recent years, the atmosphere felt by the financial field will be relatively strong, and some, especially in the deep learning model, widely exist in the performance of complex financial data, which has certain advantages. Therefore, as one of the most prominent models of deep learning, LSTM neural network models are just good at processing some complex financial data of the rest of the time series, such as stock price prediction and trading strategy, optimization, and so on. However, in the actual application process, the stock price prediction of such models still has certain data quality, historical data market fluctuations, complex, non-linear data and other related factors, so there are certain challenges and development space in the process of processing.Nevertheless, by properly addressing these issues and combining them with best practices, LSTM algorithms are a powerful tool to help uncover underlying patterns in financial markets and optimize trading decisions.
Analyzing Student Online Learning Behaviors and Academic Performance in Science Education Using Machine Learning Techniques
Authors: Feng Cheng
Published: November 2024

This study investigates the factors influencing student engagement and performance in online science education through the application of machine learning models, specifically Random Forests, Decision Trees, and Support Vector Machines (SVM). With the rapid growth of online education, understanding students' adaptability and learning behaviors has become increasingly critical. A systematic analysis of features such as study duration, daily study habits, and demographic factors revealed significant insights into their impact on academic achievement in science subjects. The Random Forest model outperformed others in classification accuracy, achieving an accuracy of 81%. The findings emphasize the importance of tailored educational strategies that foster consistent study practices and address the unique needs of diverse learners, ultimately enhancing learning outcomes in online science education.
A Review of the State of the Art 3D Generative Models and Their Applications
Authors: Qiu Zimeng
Published: November 2024

Ever since 2022, there has been a large number of 3D generative models that have been devised and published, such as AvatarGen, CityDreamer, and HOLOFUSION. Generally speaking, these models can perform tasks such as generating a 3D human model, creating an unbounded city scene, and constructing a 3D object. And it is not a surprise that 3D generative models are very popular these years because there has been a witness of huge need for 3D models in the global market and the models themselves also serve as both convenient and productive tools for the relevant industries. For instance, 3D generative models can utilize a combination of Generative Adversarial Network (GAN) and Multi-Layer Perceptron (MLP) or Neural Radiance Field (NeRF) or Diffusion Model to produce 3D human model; Autoregressive Model or Feature Extraction + Volume Rendering to generate 3D scenes; Diffusion Model or GAN + MLP to produce 3D objects. This paper tries to present a taxonomy of the main 3D generative models from the angle of the kinds of outputs and strategies employed by different models.
Research and Application Analysis of Global Path Planning Method Based on Radar and Vision in Robot SLAM
Authors: Lan Tianxiang
Published: November 2024

In recent years, the production scale of robots has become larger and larger, involving all aspects of society. Many industries are beginning to introduce robots and use them to better development and production. At the same time, autonomous driving is also a promising research direction, which is expected to reach 8 million autonomous vehicles by 2030, and the passenger car market will account for about 13% of total passenger miles. Autonomous driving will also bring many benefits to people, such as freeing up an average of 50 minutes of extra time for drivers per day, which can reduce accidents by more than 90%. Whether it is a robot or a self-driving car, the most important and critical goal is to ensure that the target task can be completed safely and quickly. Simultaneous localization and mapping (SLAM) technology can better help robots achieve this goal. In this paper, laser SLAM, visual SLAM and laser-visual SLAM algorithms are introduced, and then some related applications are shown. Finally, the future development prospect of SLAM should pay more attention to multi-sensor fusion algorithm.
Employee Turnover Prediction based on Particle Swarm Optimization - Support Vector Machine
Authors: Yao Yiran
Published: November 2024

Employee turnover is getting more and more attention in the human resources field. Unexpected turnover of employees is blamed for the loss of work handover. As a result, predicting whether employees would leave has become a crucial problem. This research aims to exploit a method combining particle swarm optimization with a support vector machine to address the employee departure prediction problem. In this study, the particle swarm optimization algorithm is used to optimize the parameter selection of the support vector machine to improve the performance of the latter. Moreover, employee information of a dataset is subject to correlation analysis before being transformed into standardization form to accelerate convergence and improve the accuracy of the support vector machine. Eventually, the support vector machine combined with particle swarm optimization is of best performance in accuracy score, precision score and F1 score, respectively reaching 0.873, 0.947 and 0.784. In conclusion, this method addresses the employee turnover prediction problem effectively which also provides a new direction for applying swarm intelligence algorithms.
Employee Role Transformation and Adaptation in Digital Transformation: Barriers, Misalignments, and Solutions in Digital Tool Application
Authors: Xiao Huilian
Published: November 2024

Employees must adapt to new digital tools and workflows as part of this digital transformation, but this process often faces significant barriers, including resistances to change, inadequate training and the complexity of technological tools themselves. This paper will focus on these challenges, including how misaligned leadership goals and rigid organisational cultures can further impede successful adaptation. It will examine case studies from retail and healthcare, and how tiered training programs, leadership involvement and culture play a role in this process. The findings reveal that addressing technological and human factors are important in allowing employees to not only adopt digital tools, but to actually applicable. Some practical recommendations to overcome these barriers include training employees on a case-by-case basis, and having leadership advocate for this digital transformation. Leaders should create an environment where employees feel empowered and supported.
Evaluating the Parameters Influencing Plastic Recycling
Authors: Pan Xinyi
Published: November 2024

The long-term and excessive utilization of plastic significantly contribute to environmental degradation and potential contamination. Notably, plastic undergoes various degradation processes, including photodegradation, thermo-oxidative degradation, and mechanical fragmentation, ultimately resulting in the generation of microplastics (MPs). Recent studies pointed out that MPs could accumulate in multiple human organs, such as the lungs, liver, and pancreas, leading to oxidative stress and cellular toxicity. Our investigation with indicators such as GDP, education, pricing, and cultural attitudes revealed that price as the predominant factor influencing the recycling of plastic bags. We analyzed the relationship between price and recycling rates through a linear regression model with the R packages broom and dplyr, which aims to inform the formulation of new regulatory measures designed to enhance plastic reuse and plastic waste mitigation.
AI Ethics and Transparency in Operations Management: How Governance Mechanisms Can Reduce Data Bias and Privacy Risks
Authors: Li Zuowei
Published: November 2024

The use of artificial intelligence (AI) in operations management holds the key to efficiency, precision and agility in business decision-making, yet it also involves ethical challenges such as fairness, accountability, transparency and privacy that can undermine trust in AI. This paper examines the ethical considerations of AI use in operations, paying particular attention to data bias, privacy risks and governance. Drawing on major governance frameworks such as the OECD AI Principles and the EUs Ethics Guidelines for Trustworthy AI, this paper proposes a hybrid governance model to address the unique challenges of operational contexts. A case study in the financial sector is used to further explain how privacy-preserving techniques can safeguard the sensitive customer data needed for AI-driven customer service. Extensive experimentation conducted in that case has shown that privacy-preserving methods such as differential privacy and federated learning can reduce the incidence of unauthorised data-access events by as much as 30 per cent and can improve customer satisfaction by more than 20 per cent. This paper contributes to the dynamic discourse on ethical AI by offering practical recommendations to organisations on how to conduct AI operations in a way that is responsible and compliant.
乡村振兴战略背景下智慧乡村健康管理站的建设研究
Authors: 李 灿
Published: November 2024

乡村振兴战略背景下智慧乡村健康管理站的建设旨在利用现代信息技术，如互联网、大数据、云计算等，对乡村的健康服务进行智能化管理和服务，以提升乡村的健康服务水平，满足乡村居民日益增长的健康需求。这一建设不仅有助于改善乡村医院和卫生站的就医环境，还能提高乡村居民的生活便利性和幸福感，为乡村的可持续发展奠定坚实基础。通过分析目前智慧乡村健康管理站面临的困境，提出以打造智慧乡村健康管理站为突破口筑牢乡村振兴健康基石的对策建议。
Designing Undergraduate Chemistry Experiments to Address Public Concerns: Exploring the Properties of Expired and Expiring Ibuprofen
Authors: Li Zhijie , Li Guoxing , Xu Yihan , Wang Zejun
Published: November 2024

The outbreak of the COVID-19 pandemic has led to the irrational hoarding of medicine, resulting in public confusion over the safety of expired medicine in the post-pandemic era. This paper aims to stimulate the interest of chemistry students through an undergraduate teaching experiment and employs the knowledge acquired to address societal concerns. It centers on ibuprofen, a typical antipyretic medication. We employed a range of analytical methods to qualitatively and quantitatively analyze the changes after medicine expires. The experiment is designed to evoke theoretical knowledge such as analytical chemistry, pharmaceutical chemistry, and spectral analysis acquired by undergraduate students with a chemistry major background and demonstrates how to apply these professional skills to solve realistic problems. First, we utilized Infrared Absorption Spectrometry (IR) to detect the fundamental structure of ibuprofen. Based on the obtained Infrared Spectra, we confirmed that the basic structures of ibuprofen remained intact both before and after expiration. However, IR could only facilitate qualitative analysis and did not provide information on content changes. Therefore, we also employed Ultraviolet-Visible Absorption Spectrometry (UV/Vis) and Acid-Base Titration to quantitatively analyze the benzyl and carboxyl groups in ibuprofen molecules. And uncovered the molecular-level changes that occur during medicine expiration. The structure of ibuprofen post-expiration remained, but the content of benzyl and carboxylic groups decreased, with the reduction becoming more pronounced as expiration time increased. This experimental teaching attempt provides an example of exploring the chemical properties of substances related to public health, which fits into analytical chemistry experimental courses.
GAMBARAN KELAINAN REFRAKSI BERDASARKAN PEMERIKSAAN VISUS PADA SISWA SMK YADIKA 5 TANGERANG TAHUN 2024
Authors: Bakti Fahrezi , Maryani Febri , Habiba Putri Ghanim Septia , Budiana Wahyu , Supandi Hanie , Azhar , Hafidz Al , Setiawan Teguh , Kurniawan Najwa Aqila , Sari Annadira Nabilla
Published: November 2024

Pemeriksaan visus adalah bagian yang sangat penting untuk mengetahui kelainan refraksi seseorang. Visual acuity yang normal disebut sebagai 20/20, yang berarti seseorang dapat melihat detail yang sama dari jarak 20 kaki seperti orang dengan penglihatan normal. Penelitian ini bertujuan untuk mengetahui kelainan refraksi berdasarkan pemeriksaan visus. Penelitian ini dilakukan di SMK Yadika 5 Tangerang, dengan responden kelas XI total sampel 56 siswa. Metode yang digunakan yaitu metode deskriptif, dengan pemeriksaan visus untuk mengetahui kelainan refraksi yang dialami, wawancara kepada informan sebanyak 5. Pada tahap akhir juga dilakukan edukasi kesehatan untuk mengetahui seberapa besar pengetahuan siswa. Hasil penelitian ini menunjukkan bahwa sebanyak 41 siswa (80%) mengalami kelainan refraksi. Berdasarkan wawancara diperoleh penyebab kelainan refraksi yaitu durasi penggunaan gadget, pencahayaan layar gadget, kondisi pencahyaan ruangan, dan pengetahuan. Oleh karena itu, pemberian edukasi tidak hanya dilakukan kepada siswa, tetapi juga kepada guru dan orang tua atau wali siswa. Dengan demikian, kelainan refraksi tidak berlanjut pada kondisi yang lebih buruk.
Diagnosis and Treatment of Infectious Coryza in a Peacock (Pavo cristatus): A Case Report
Authors: Rehman Fazal Ur , Ahmad Khalil , Awais Muhammad , Mushtaq Samia , Parmina . , Mohsin Muhammad , Ullah Zabeeh , Khan Aatif Masood Ahmad , Raza Baqir , Asif Muhammad
Published: November 2024

Infectious Coryza (IC) was a contagious respiratory bacterial infection in peacocks. The current study evaluated the outcomes of treating infectious coryza in a peacock. The adult peacock at the age of 2 years was presented with a history of anorexia, difficulty breathing, sticky eyes, nasal and ocular discharge, and semi-solid swelling under the eyes. Clinical examination confirmed respiratory depression, a swollen head and face, gasping, occluded eyelids, sticky purulent discharge from the eyes and nostrils, moist rales, depression, and recumbency. Treatment included the use of injection of gentamicin, meloxicam, and multivitamins therapy, along with surgical debridement of facial edematous swelling. The peacock successfully recovered after 5 days of treatment. It was concluded that infectious coryza was a treatable disease, and an antibiotic sensitivity test was highly recommended for selecting a suitable antibiotic against bacterial infections.
The use of machine learning method in Covid-19 patient management
Authors: Cebeci Z , Baykan mer , kun lker , anakc Ebru
Published: November 2024

The world is grappling with the COVID-19 outbreak, which first appeared in Wuhan, China in December 2019 and was declared a pandemic by the World Health Organization in March 2020(1). In particular, the sudden increase in Covid cases requiring hospitalization and long-term hospitalizations has turned into a chaos that inpatient health institutions cannot predict and have difficulty managing.
The aim of this study was to show whether modelling using machine learning (ML) techniques can be used to make decisions about the hospitalisation of COVID-19 patients.
Our Experience with Closed Reduction Management in Pavlik Harness Failure Cases
Authors: IR Ahmet , KAYA Ramazan , CEYLAN Mehmet , ALTUNKILI Tar , SE Harun
Published: November 2024

Aim: Developmental Hip Dysplasia (DDH) refers to a set of abnormalities involving the developing hip. These abnormalities range from mild instability to overt dislocation of the joint. It is important to treat this condition effectively to promote normal development of the hip and achieve good long-term results. Surgical and non-surgical methods are available as treatment methods. The purpose of this article is to share the clinical and radiological results of the patients we treated with closed reduction and casting in our clinic.
Materials and Methods: Radiological and clinical evaluation of 176 hips of 117 patients who applied to Inönü University Faculty of Medicine Department of Orthopedics and Traumatology between January 2010 and October 2017 and were treated with closed reduction and pelvipedal casting was performed retrospectively. Of the 117 patients participating in the study, 12 were boys and 105 were girls. 19 patients had right involvement, 39 patients had left involvement, and 59 patients had bilateral involvement. The patient age range was between 6-22 months. Pre-reduction radiographs of the patients participating in the study were examined, and the dislocation levels of these hips were grouped according to the Tönnis classification. Modified MacKay criteri were used for postoperative clinical evaluation of the patients, and Kalamchi MacEwen criteria were used for radiological evaluation of avascular necrosis. SPSS program (version: 16) was used for statistical evaluation. Student's t-test, and differences with a "p" value of 0.005 were considered statistically significant.
Results:.The average preoperative acetabular index of the operated hips was 35.88 degrees, and the final follow-up acetabular index values were 22.09 degrees. Avascular necrosis was detected in 2 of the patients. According to the modified McKay classification, very good results were obtained in 105 (90%) of 117 patients followed for closed reduction, good results were obtained in 11 (9%), and fair results were obtained in one. From the patients included in the study, 19 patients had right, 39 patients had left and 59 patients had bilateral involvement. In our study group, 74 patients underwent arthrography and 19 patients underwent tenotomy. When closed reduction and pelvipedal plaster application were started, the mean age of the patients was 7,5 (2 - 22) months. Our mean follow-up was 35,7 (9 - 100) months.

Conclusion: This study shows that closed reduction and pelvipedal hip Spica cast application is a simple, reliable, and successful method for patients who do not respond to conservative treatment and that avascular necrosis rates are very low when excessive strain avoided from.
Evaluation of patients who underwent computed tomography angiography with the pre-diagnosis of pulmonary embolism
Authors: c Olga , Abu Sabri , ay Ahmet , Ayhan Sel , a Meral , kl Kadir , Markirt Sezer , Markirt Erkan
Published: November 2024

Aim: Pulmonary embolism (PE) is a disease that develops as a result of occlusion of the pulmonary artery or its divisions by thrombus deriving from the systemic deep venous system. PE ranks third among deaths caused by cardiovascular disease. PE is a preventable illness with elevated mortality and morbidity, repetitive and hard to diagnose. In this study, computed tomography angiography (CTA) images and blood parameters of patients who underwent CTA with a prediagnosis of PE in Adiyaman Training and Research Hospital between 01/03/2020-01/09/2022 were examined.

Materials and Methods: Patients who underwent CTA with suspected PE were analyzed, and a comparison was made between the sociodemographic and laboratory data of those diagnosed with PE and those who were not.

Results: The mean age of PE patients was importantly higher than non-PE patients, and there was no statistical variance in the gender distribution of the groups. Monocyte count was markedly higher in the PE group, and the CAR value remarkably higher in the non-PE group than in the PE group. According to the ROC analysis, the AUC value was the highest when the D-dimer and troponin I value were considered together. Two different cut-offs were found for D-dimer. When D-dimer was 655 mg/dL, the specificity was 96.5%, while when D-dimer was 438.5 mg/dL, the sensitivity was 92.2%. The highest specificity was found with troponin I (97.4%). The likelihood ratio (LR) was the highest, at 26.08, when D-dimer was 655 mg/dL and above.

Conclusion: As a result, the main message of our study is that when making differential diagnosis in patients who apply to the emergency department with dyspnea and chest pain, better diagnostic accuracy can be achieved with the combined evaluation of tomographic findings and laboratory findings. Therefore, evaluation of laboratory values such as D-dimer, hemogram parameters and troponin I is important in diagnosis and risk classification.
Definitive Chemoradiotherapy versus Upfront Surgery in Locoregional Esophageal Squamous Cell Cancer
Authors: Kalkan Nurhan , MERT ASLIHAN , LU UMUT , R MEHMET , KOTAN ET
Published: November 2024

BACKGROUND

Previous studies have indicated that definitive chemoradiotherapy and upfront surgery have comparable survival rates, and definitive chemoradiotherapy is a more applicable treatment option in resectable locally advanced esophageal squamous cell cancer (ESCC). We compared definitive chemoradiotherapy to upfront surgery for survival in locally advanced ESCC patients who denied the standard treatment approach, receiving definitive chemoradiotherapy or upfront surgery.
MATERIALS AND METHODS

One hundred eighty eight locoregional ESCC patients with thoracic and distal involvement who had upfront surgery were compared with those who received chemoradiotherapy but declined surgery, although their tumor was resectable at presentation. Patients who underwent upfront surgery with negative surgical margins were included. The upfront surgery group received no adjuvant treatment (chemotherapy or radiotherapy). The definitive chemoradiotherapy group received standard therapy with 50.4 Gray/28 fractions/6 weeks concomitantly with weekly Paclitaxel 50 mg/m2 and Carboplatin AUC 2 combination regimen.
RESULTS

A total of 102 patients (54.3%) underwent surgery up front, whereas 86 patients (45.7%) had definitive chemoradiotherapy.The median follow-up of the study was 31 months. Definitive chemoradiotherapy had a median disease-free survival (DFS) of 39 months compared to 16 months for upfront surgery (p:0.005). Median overall survival (OS) was 29 months in upfront surgery and 47 months in definitive chemoradiotherapy (p=0.01). Although the multivariate Cox regression analysis found no difference in DFS between upfront surgery and definitive chemoradiotherapy groups, OS was greater with the latter (HR, 0.69; 95% CI, 0.47 to 1.00; p=0.05).
CONCLUSIONS

In this non-randomized retrospective analysis, definitive chemoradiotherapy improved overall survival compared to upfront surgery in locally advanced ESCC patients.
Smoking Status and factors influencing Smoking Cessation among primary school parents: A Cross-sectional study
Authors: Evcen Arife , Evcen Recep , lu Kamile
Published: November 2024

Objective: This study aims to determine smoking status among primary school parents and identify factors influencing smoking cessation. Additionally, the study seeks to increase awareness about the transtheoretical model and examine its role in the smoking cessation process.
Materials and Methods: The study was conducted with 2,354 parents of students from a primary school in Konya. Participants completed surveys assessing smoking status, attitudes towards quitting, and levels of awareness. Factors related to smoking status, including age, gender, education level, occupation, and alcohol use, were analyzed. Smokers quit attempts were associated with the stages of the transtheoretical model, and whether they sought professional help was evaluated.
Results: Of the participants, 33.1% (n=780) were smokers. The average age of smokers was 36.6±4.61, and the frequency of smoking was higher among men than women. 39% of the participants were low-level smokers. Significant associations were observed between smoking status and factors such as age, gender, education level, occupation, and alcohol use (p<0.001). The majority of smokers attempted to quit using the "sudden cessation" method, with a low rate of seeking professional help. Most of those who successfully quit also used the "sudden cessation" method. 31.4% of participants had never attempted to quit smoking. As the number of quit attempts increased, participants were observed to become more prepared to quit smoking (p<0,001). According to the transtheoretical model, most individuals were in the precontemplation stage.
Conclusion: The frequency of smoking is higher among men and decreases as education level increases. Most participants attempted to quit smoking on their own, with a low level of seeking professional help. Multiple attempts to leave have been shown to increase the likelihood of success, and awareness of the harms of passive smoking has significantly influenced smoking behavior.
Erica arborea L. induces G2/M cell cycle arrest and apoptosis by regulating the CDK signaling pathway through the ROS generation in breast cancer cells
Authors: r Muhammet
Published: November 2024

Aim: The anticancer effect of any Erica L. genus member has not yet been investigated. Hence, this study investigated the anticancer effect of Erica arborea, a high-level flavanone producer, in mouse breast cancer 67NR and 4T1 cells.
Materials and Methods: Healthy mouse fibroblast L929, mouse primary breast cancer 67NR and mouse metastatic breast cancer 4T1 cells were treated with Erica arborea methanol and ethanol extracts to investigate the cellular toxicity, apoptosis, gene expression level and oxidative stress effect on cells.
Results: According to our data, the methanol and ethanol extracts of Erica arborea caused G2/M phase arrest of the cell cycle and apoptosis. Also, the methanol and ethanol extracts of Erica arborea further increased the accumulation of reactive oxygen species (ROS), especially higher levels in mouse breast cancer 67NR and 4T1 cells, according to the healthy mouse fibroblast L929 cells. The treatment of the cells with Erica arborea extracts causes up-regulation of the pro-apoptotic Caspase-3, Caspase-9, Bax, and Bak genes and down-regulation of the anti-apoptotic Bcl-2 and Bcl-xL genes. Moreover, treatment with Erica arborea extract up-regulated the expression levels of cyclin-dependent kinase (CDK) inhibitor P21 and P27 genes while down-regulating the expression levels of cyclin A and cyclin B1 genes in cells. However, the mRNA expression level changes of these genes are significantly higher in breast cancer 67NR and 4T1 cells, according to the healthy mouse fibroblast L929 cells.
Conclusion: The result of the present study indicated that Erica arborea stimulated apoptosis induction in mouse breast cancer 67NR and 4T1 cells, which was associated with G2/M phase cell cycle arrest by regulating the CDK signaling pathway through ROS generation.
Comparison of Pan-immune inflammation value, Systemic inflammatory response index and Systemic immune inflammation index in singleton and twin pregnancies: A retrospective cohort study
Authors: Firatligil Fahri , Sucu Sadun , Tuncdemir Sitare , Ozkan Sadullah , Sucu Serap , Dereli Murat , PAY Ramazan , Yucel Kadriye
Published: November 2024

Aim: To evaluate Pan-immune inflammation value (PIV), Systemic inflammatory response index (SIRI) and Systemic immune inflammation index (SII) for the comparison of twin pregnancies with singleton pregnancies.
Material-method: The cohort study was conducted retrospectively in the Ankara Etlik City Hospital Obstetrics and Perinatology Clinics between October 2022 and August 2024. Women with singleton pregnancies whose follow-up and delivery took place in the same tertiary center were included in the control group (Group I). Women with twin pregnancies who were followed up and delivered at the same tertiary center were included in the case group (Group II). The inflammation-based indices (PIV, SIRI and SII) of the two groups were compared with each other.
Results: 221 twin pregnancies were identified after screening according to the inclusion/exclusion criteria, the remaining 138 pregnancies were sorted chronologically by date of birth. The first 115 twin pregnancies in the ranking list that were eligible for the study according to the power analysis were included in group II. For each twin pregnancy that was eligible for Group II, the first singleton pregnancy in the rank order of files that met the inclusion criteria was selected for Group I as the control group. The groups differed significantly in hemoglobin and PIV values (p=0.045 vs. 0.007). There were no significant differences in demographic and inflammatory indices in mono- and di-chorionic pregnancies.
Conclusion: Low PLT and high LYM in twins lead to a statistically significant decrease in PIV, even if this is not statistically significant. We can say that this reflects the physiological inflammatory/immune response of pregnancy. However, our findings need to be supported by multicenter and prospective randomized controlled trials.
The Relationship Between Predominant Negative Symptoms and Self-Stigmatization in Clinically Stable Schizophrenia Patients
Authors: r Emre , Cengisiz Cengiz
Published: November 2024

Objective: Internalized stigma and negative symptoms have deteriorating effects on prognosis and treatment adherence. Therefore, it is important to recognize the interaction between internalized stigma and negative symptoms in patients with schizophrenia. However, the relationships between negative symptom dimensions and internalized stigma are unclear. In this study, we examined the relationship between self-stigmatization and negative symptoms in a homogeneous subgroup of patients with predominant negative symptoms (PNS). At the same time, the relationships between depression severity and perceived social support and self-stigmatization were evaluated.
Methods: Clinically stable schizophrenia patients who were being followed up in a Community Mental Health Center were included in this cross-sectional study. The Positive and Negative Symptom Scale (PANSS), the Brief Negative Symptom Scale (BNSS), the Calgary Depression Scale for Schizophrenia (CDSS) were applied by the clinician to the patients. In addition, the Internalized Stigma of Mental Illness Inventory (ISMI) and Multidimensional Scale of Perceived Social Support (MSPS), which are self-report scales, were given. Scale scores were compared between PNS and non-PNS (NPNS) groups. Correlations between the ISMI scale scores (perceived discrimination, alienation, stereotype endorsement, social withdrawal, and resistance to stigma) and demographic and clinical variables and other scale scores were evaluated. ANCOVA analysis was used to assess the effect of years of education, employment status, and insight level in intergroup comparisons.
Results: The study included 117 patients [mean age = 43.4 (SD = 11.8); 35 females], with 88.9% experiencing self-stigma. The PNS group (n=58) had lower levels of insight, perceived discrimination, and ISMI total score, but higher negative symptoms and BNSS scores, whereas the NPNS group had higher scores on the positive and general subscales of the PANSS. Correlation analysis revealed negative relationships between alienation and perceived discrimination scores, years of education, and all negative symptom scores. ANCOVA results indicated that, after adjusting for education, employment status, and insight level, the difference in perceived discrimination between PNS and NPNS groups remained significant, while the difference in ISMI total score did not. Insight level was the only significant variable affecting ISMI total score in the model.
Conclusion: Patients with PNS have a unique profile in terms of the relationships between self-stigma and negative symptom dimensions. At the same time, an increase in self-stigma was found as the level of insight increased.
Multivariate Association Between Personality Beliefs and Enneagram Personality Theory: A Canonical Correlation Analysis
Authors: a Erdo , n Sena , am Cansun , Yanarta mer
Published: November 2024

Objective: Personality disorders (PDs) are characterized by specific sets of dysfunctional personality beliefs which can result in distinctive behavioral patterns associated with the PD. Dysfunctional personality beliefs are maladaptive thought patterns related to people’s sense of self, interpersonal relationships, and worldview. The Enneagram Personality Theory (EPT) categorizes personality into nine interconnected types, each with distinct patterns of thinking, feeling, and behaving. Enneagram subtypes represent a different focus or emphasis within the main type’s core motivations and behaviors. The association of EPT with various personality approaches has been studied. However, we aim to assess the relationship between EPT and personality beliefs, which has not been previously studied.
Method: A sociodemographic form, Personality Belief Questionnaire-Short Form (PBQ-SF), and Enneagram Types and Subtypes Inventory (ETASI) were applied to 203 participants.
Results: A canonical correlation analysis was conducted to investigate the multivariate association between nine Enneagram types and subtypes and ten personality belief variables. The analysis unveiled four significant functions for the association between Enneagram types and personality beliefs. Function 1 was contributed by Types 3, 8, and 5 and was negatively related to borderline and dependent beliefs, and positively related to schizoid beliefs. Function 2 featured obsessive-compulsive beliefs and was related to Types 1 and 6. Function 3 was related to histrionic, narcissistic, and antisocial beliefs and Types 2,3,7, and 8. Function 4 presented schizoid, borderline, and narcissistic beliefs, with Type 4 as the predominant predictor. Among the subtypes, only the self-preservation subtype was correlated with schizoid beliefs.
Conclusions: The results revealed that EPT comprises multidimensional layers that vary according to specific personality beliefs and types. Personality beliefs were found to be aligned with the core characteristics of the respective types.
Lahore Wheel Spoke Injury Classification
Authors: Ishaque Usman , Haq Ata , Riaz Ahsan , Khalid Usman , Tarar Moazzam
Published: November 2024

Summary: This study aims to critically evaluate the classifications used to describe wheel spoke injury and define the subtypes that these classifications did not cater for. Thus, proposing a new classification of wheel spoke injuries (Lahore Classification) along with management of all subtypes.
Patients and Methods: Retrospective study of a total 156 wheel spoke injuries of foot was undertaken to categorize/classify these injuries in terms of injured structures. Wheel spoke injury patients of all ages and both genders; evaluated and admitted in Jinnah Burn & reconstructive surgery Centre (JB&RSC), Jinnah hospital/AIMC, Lahore, Pakistan were included in this study from January 2019 to December 2023.
Results: A total of 156 “Wheel Spoke Injury” patients involving feet presented to our department. Injury mechanism and structures involved were noted. There were 42 patients who did not fit in specific grades of the existing classifications. A modification in the existing classification for the wheel spoke injury was devised and management of different subtypes was undertaken. The proposed algorithm for management ranges from conservative care to the need for free flap to cover the defect.
Conclusion: Wheel spoke injuries of the foot can be managed more effectively with the help of a practical grading system. We propose a revised classification that will guide the management plan and a treatment algorithm which will ultimately improve the patient’s outcome.
Aufgabenteilung in der Eisenzeit – Zum Aussagewert der Situlenkunst
Authors: Schaller Clara
Published: November 2024

Die im 7. bis 4. vorchristlichen Jahrhundert in Norditalien, Österreich, Slowenien und Kroatien verbreitete Situlenkunst bietet sich auf den ersten Blick aufgrund ihrer umfangreichen, narrativen Darstellungen für eine Betrachtung von Arbeitsteilung und Geschlechterrollen besonders an.Die Analyse der Bilder und der ausgeführten Arbeiten in der Situlenkunst zeigt neben einem binären Geschlechterverständnis eine sehr klare Aufteilung von Arbeiten zwischen Frauen und Männern, wobei Männer sehr viel häufiger dargestellt werden und ein breiteres Tätigkeitsfeld zugewiesen bekommen als Frauen. Der Vergleich mit den Inventa-ren der zeitgleichen Gräber und gleichzeitigen anderen Kunstäußerungen zeigt jedoch ein weniger klares Bild. Aufga-benteilungen entlang von Geschlechterlinien treten teils weniger deutlich hervor und zudem sind weitere Rollen greif-bar, die in der Situlenkunst nicht auftreten. Das anhand der Grabinventare und der Situlenkunst gezeichnete Bild ist zudem unvollständig. So finden zum Beispiel viele sicherlich ausgeübte Handwerkstätigkeiten keinen oder nur sehr wenig Widerhall in der eisenzeitlichen Kunst und den Gräbern. Die dargestellten Tätigkeitsfelder sind somit stark se-lektiert worden und kaum als ein Abbild der Realität zu sehen. Vielmehr sind die Bilder als Versuch der Durchsetzung von Vorstellungen einzelner elitärer Gruppen zu interpretieren, entsprechen also eher deren Idealvorstellungen als Auskunft über eine reale Arbeitsteilung zu geben.
СРАВНИТЕЛЬНЫЙ АНАЛИЗ РЕЗУЛЬТАТОВ ПОВТОРНЫХ ОПЕРАЦИЙ ПРИ ДЕГЕНЕРАТИВНО-ДИСТРОФИЧЕСКИХ ЗАБОЛЕВАНИЙ ПОЯСНИЧНО-КРЕСТЦОВОГО ОТДЕЛА ПОЗВОНОЧНИКА С ПРИМЕНЕНИЕМ ТЕХНОЛОГИЙ OLIF И TLIF
Authors: С.Т. Мамырбаев , С.А. Джумабеков , М.Д. Абакиров , Ж.Д. Сулайманов , И.А. Жумабеков
Published: November 2024

Настоящее исследование посвящено повторным операциям при дегенеративных заболеваниях пояснично-крестцового отдела позвоночника. В исследование вошли 65 пациентов которые разделены на две сравнительные группы. I группа состояла из 36 пациентов в возрасте от 29 до 60 средний возраст 43 года, оперированных по методике TLIF. Мужчин было 17 (47,3%), женщин 19 (52,7%). Группа II включала 30 пациента в возрасте от 23 до 67 лет средний возраст 43,3 года прооперированных по методике OLIF. Соотношение мужчин и женщин в этой группе составило 14 (46,6%): 16 (44,4%). В результате сравнительного анализа во II группе показатели ВАШ и ODI лучше, чем в I группе, р < 0,001. Таким образом, OLIF как метод повторной операции дает возможность тотально удалить диск при рецидиве грыжи диска, избегает повторного разреза паравертебральных мышц, отмечается меньшая послеоперационная боль и кровопотеря во время операции, низкий риск травмы спинного мозга и корешков в результате тракции.

Бул изилдөө бел-айкашкан омуртканын бузулган (дегенеративдик) ооруларына кайталанган операцияларга арналат. Изилдөө эки салыштырма топко бөлүнгөн 65 бейтапты камтыды. I группага TLIF ыкмасы менен операция жасалган 29 жаштан 60 жашка чейинки, орточо жашы 43 жаштагы 36 бейтап кирген. Эркектер 17 (47,3%), аялдар 19 (52,7%) болгон. II топко OLIF ыкмасы менен операция жасалган 23 жаштан 67 жашка чейинки, орточо жашы 43,3 жаштагы 30 бейтап кирген. Бул топтогу эркектер менен аялдардын катышы 14 (46,6%): 16 (44,4%) түздү. Салыштырмалуу анализдин натыйжасында II топтогу VAS жана ODI упайлары I топко караганда жакшыраак, p <0,001. Ошентип, OLIF кайра операция ыкмасы катары диск грыжасынын кайталануусу учурунда дискти толугу менен алып салууга мүмкүндүк берет, паравертебралдык булчуңдарды кайра-кайра кесүүдөн сактайт, операциядан кийинки оору жана операция учурунда кан жоготуу азаят, ошондой эле дененин жаракат алуу коркунучу төмөн. тартуунун натыйжасында жүлүн жана тамырлар.

This study is devoted to repeated operations for degenerative diseases of the lumbosacral spine. The study included 65 patients who were divided into two comparative groups. Group I consisted of 36 patients aged from 29 to 60, average age 43 years, operated on using the TLIF technique. There were 17 men (47.3%), 19 women (52.7%). Group II included 30 patients aged from 23 to 67 years, average age 43.3 years, operated on using the OLIF technique. The ratio of men to women in this group was 14 (46.6%): 16 (44.4%). As a result of a comparative analysis, VAS and ODI scores in group II are better than in group I, p < 0.001. Thus, OLIF as a method of reoperation makes it possible to completely remove the disc in case of recurrent disc herniation, avoids repeated incision of the paravertebral muscles, there is less postoperative pain and blood loss during surgery, and a low risk of injury to the spinal cord and roots as a result of traction.