bluuebunny/crossref_metadata_2025 huggingface dataset:
Del “derecho a tener derechos” a la biopolítica: perspectivas críticas sobre el Estado nación y el nacionalismo en la obra de Hannah Arendt
Authors: Gracia Landaeta Óscar , Laguna-Tapia Andrés
Published: December 2024

Este artículo rastrea las conexiones entre Los orígenes del totalitarismo y La condición humana con respecto a los conceptos de “nación”, “Estado nación” y “nacionalismo”. Con ello, se amplían las ideas más conocidas de Hannah Arendt sobre estos temas a partir de perspectivas propias de su reflexión sobre la vita activa. Con tal propósito, tanto la reconstrucción de la postura crítica arendtiana frente al capitalismo como el concepto de “biopolítica” (no mencionado explícitamente por Arendt en su trabajo) permiten releer La condición humana desde un enfoque centrado en la tematización hecha por Arendt de “lo nacional”. Dicho análisis apunta no solamente a ampliar las posibilidades de la reflexión de Arendt sobre la nación y el nacionalismo, sino también a renovar las perspectivas filosóficas sobre estos fenómenos contemporáneos.
Microstructure of High-Barrier Film for Dairy Packaging
Authors: Myalenko Dmitriy , Fedotova Olga , Sirotin Sergey
Published: December 2024

High-filled, or high-barrier packaging materials are a promising direction of dairy packaging. These films provide safety, quality, and operational stability. In addition, they require no sophisticated equipment for recycling. Mineral calcium carbonate remains the most popular inorganic chemical filler. However, mineral-filled polymer compositions are understudied from the perspective of their structure and properties. These properties depend on the polymer base (binder), the mineral filler, its grinding, the technology of combining in the melt during extrusion, the dispersion of the filler in uncertain environment, etc. By studying the effect of filler concentration on the microstructure of polyethylene film samples, one can assess the dispersion of calcium carbonate in the polymer to reveal the processes behind the changes in the physical and mechanical properties of films. A series of previous studies featured a polyethylene film filled with 20–70% calcium carbonate. In this research, dihydroquercetin in concentrations of 0.5 and 1.0% served as an additional modifying component with antioxidant properties. The film samples were visually homogeneous. The method of scanning electron microscopy indicates a relatively uniform distribution of filler particles (50 wt%). The samples with 70 wt% showed a rather loose and uneven distribution of particles under the X-ray spectroscopy. The micrographs revealed crystalline particles of dihydroquercetin diffusing onto the surface of the packaging material.
Performance Comparison of Deep Learning Lane Detection Models for Autonomous Vehicles
Authors: Ataş Muhammed Said , Doğan Yahya , Özdemir Cüneyt
Published: December 2024

Recent advancements in the field of deep learning have significantly improved the driving capabilities of autonomous vehicles. This study focuses on the lane detection abilities of autonomous vehicles and examines the use of deep learning-based approaches in this context. The research compares the lane detection performance of various deep learning models, including U-Net, SCNN, ENet, and ENet-SAD, utilizing the TuSimple dataset. The models were evaluated using various quantitative metrics such as accuracy, precision, sensitivity, F1 score, and IoU. Extensive experiments have determined that the U-Net model exhibited the highest performance with an accuracy rate of 98.3%. The SCNN model, on the other hand, stood out in terms of precision, sensitivity, F1 score, and IoU metrics. In terms of inference time, the U-Net model was identified as the fastest lane detection model with a time of 20.12 ms. These results indicate that the U-Net model is particularly suitable for real-time systems requiring low computational power. Additionally, a qualitative assessment of lane detection success revealed that the SCNN and U-Net models more accurately detected pixels where lanes are present, whereas the ENet and ENet-SAD models were more prone to false-negative errors.
Bir Tekstil Boyasının Çevre Dostu Bir Oksidant Olan CaO2 ile Sulu Fazdan Giderimi
Authors: Balcı Behzat
Published: December 2024

Tekstil boyar maddelerini içeren atıksuların alıcı ortamlarda varlığı, çevre sağlığı için önemli sakıncalar oluşturmaktadır. Boyar maddelerin etkili bir şekilde giderimini sağlayan yöntemler arasında ileri oksidasyon prosesleri yer almaktadır. Yaygın kullanılan yöntemler arasında Fenton prosesleri bulunsa da, bu yöntem metal içerikli çok miktarda çamur oluşturması nedeniyle önemli bir dezavantaj teşkil etmektedir. CaO2, çevre dostu ve güçlü oksidasyon potansiyeline sahip bir kimyasaldır. Bu çalışmada, değişken deneysel koşullar altında CaO2 ile Crystal Violet boyar maddesinin sulu fazda oksidasyonu araştırılmıştır. CaO2, demir gibi aktivatör olmadan yüksek oksidasyon verimleri göstermiştir. Süreç sonunda çamur oluşumunun önüne geçilmiştir. CV oksidasyonu için optimum pH değerinin 10 olduğu tespit edilmiştir. Oksidasyon çalışmaları, düşük CaO2 dozlarıyla kısa reaksiyon sürelerinde yüksek oksidasyon verimlerinin elde edilebileceğini ortaya koymuştur. 200 mg/L CV'nin %99,9 oranında giderimi için 0,1 gram CaO2 kullanılarak 25 dakikalık bir reaksiyon süresinin yeterli olduğu belirlenmiştir.
Farklı İlave Metallerin AW 6061 Kaynaklı Bağlantıların Mekanik ve Mikroyapı Özelliklerine Etkisi
Authors: Bağlan Aybars , Tümer Mustafa
Published: December 2024

Havacılık endüstrisi, malzeme alanında meydana gelen değişimlere paralel olarak ağırlık azaltımı, mukavemet ve maliyet açısından aluminyum alaşımlarını giderek artan bir kullanım alanında tercih etmektedir. Ancak benzersiz özelliklerine rağmen aluminyum malzemelerin birleştirilmesinin kendine has zorlukları vardır. Kaynak yöntemi, kaynak parametreleri, doğru ilave metal seçimi ve ana malzemenin kapsamlı temizliği için belirli tekniklerin belirlenmesi gerekir. Isıl işlem uygulanabilen alüminyum alaşımlarından AW 6061 uygun işlemler neticesinde sergiledikleri mekanik özellikler ve korozyon dayanımları ile uçak gövde ve yapı elemanlarında tercih edilirler. Havacılık tamir-bakım kaynak işlemlerinde aluminyum alaşımlarında meydana gelen hasarların kaynak prosesleri ile giderilmesi yaygın bir uygulamadır. Bu çalışmada AW 6061'in Tungsten Inet Gas (TIG) kaynak yöntemi ile birleştirilmesi ve elde edilen kaynak metallerinde ilave metalin yapısal performansa etkisini belirlemek amacı ile mekanik ve mikroyapısal karakterizasyon gerçekleştirilmiştir. Birleştirme performansı açısından ER 4190 ilave metal ile elde edilen kaynak metali ER5356’ya göre daha iyi mekanik özellikler elde edilmiştir. Kaynaklı numunelere uygulanan çekme testi sonrasında tüm kopmalar ana malzemede meydana gelmiştir. ER 5356’nın çekme testi ile uyumsuz olarak sertlik açısından daha yüksek değerler elde edilmesinin nedeni geniş bir alanda oluşan kaynak havuzunun ısı etkisi altındaki bölgede intermetalik fazlarda meydana getirdiği çözünmeden kaynaklanmaktadır.
The Impact of Conjugate Heat Transfer in Flow Over a Vertical Plate and Application of Artificial Neural Network
Authors: Yağlıca Pınar , Çermik Özdeş
Published: December 2024

Heat conduction properties are important in the flow area for the simulation of engineering applications where heat transfer is needed between both liquid and solid. Conjugate Heat Transfer (CHT) refers to thermal problems involving both conduction within the wall and convection within the fluid. CHT is crucial for heat exchangers, gas turbine blades, nuclear reactor cooling pipes, aircraft engines, and spacecraft. Additionally, the influence of the magnetic field is significant in fields such as electrostatic precipitation, MHD power generators and pumps, aeroheating, and polymer science. The motivation for this study is to understand the combined effects of CHT, mixed convection, magnetic fields, and viscous dissipation on velocity, temperature profiles, local skin friction, and heat transfer parameters over a vertical plate. The boundary layer equations have been derived from the Navier-Stokes and energy equations using similarity methods and solved numerically with the Keller Box technique. A new correlation for local skin friction and heat transfer parameters has been developed. Moreover, Artificial Neural Network (ANN) models have been applied to forecast desired numerical values. The optimal ANN model for local heat transfer has one hidden layer and nine neurons, achieving an R² value of 0.9077607 and an MSE of 0.0003101. For local skin friction, the best-performing model has one hidden layer and fifteen neurons, with an R² value of 0.9470261 and an MSE of 0.0250369.
Design and Realization of a Novel Programmable Tobacco Smoking Simulator
Authors: İstanbullu Mustafa , Polat Abdurrahman Özgür , Soygun Koray , Yuva Deniz
Published: December 2024

Cigarette smoke significantly impacts teeth and dental composites, making smoking simulators vital for studying discoloration, staining, surface roughness, and topography. Conventional simulators face challenges such as incomplete process simulation, inadequate smoke exposure unit design, and improper specimen positioning. This study presents a novel, accurate, and automatic tobacco smoking simulator addressing these issues. The simulator includes a life-sized artificial mouth unit, 3D-printed jaw models for natural dental sample positioning, a vacuum system to simulate positive/negative pressure, and a reprogrammable microcontroller for customizable smoking profiles. Tested with 140 cigarettes over 14 days, the system effectively demonstrated color changes in dental materials. Adjustable parameters such as puff volume, inhalation/exhalation time, smoke density, and smoking speed allow replication of low, moderate, and high-intensity smoking profiles. Portable, low-cost, and versatile, the simulator provides a robust solution for research and education, enabling investigations into the effects of smoke on teeth and dental materials under realistic conditions.
Investigation of Dyestuff Recycled from Wastewater Containing Indigo/Sulfur Dyes
Authors: Uluçay Aslı , Ceyhan Gökhan , Balcı Onur , Işık Ceren , Yavuz Sıddık
Published: December 2024

Turkey is one of the important centers of denim fabric production in the world. Warp yarn is usually dyed using indigo and/or sulfur dyes according to the impregnation method. The common feature of these two dyes is that they are insoluble in water and dye temporarily with a reduction reaction. The recovery of dyes in wastewater is targeted. Wastewater containing indigo and sulfur dyes taken from İskur Denim was sedimented using the chemical flocculation technique and solid material was obtained after drying. The sedimentation process was affected by the pH of the environment, the mixing speed and the concentration of sedimentation chemicals. The best sedimentation was achieved by adding flocculators supplied by AKKİM to the wastewater sample in the pH range of 8-8.5. The obtained sludge was subjected to condensation reaction with the developed binding agent. The energy levels of the highest occupied molecular orbital and the lowest unoccupied molecular orbital of the dyes obtained from indigo and sulfur wastewater were determined as -4.78 eV and -4.04 eV, respectively, by cyclic voltammetry. These values are very close to the original dyes and give hope for dyeing performance.
Multi-Model Predictive Maintenance: Overview and A Linear System Perspective
Authors: Yıldırım Uğur , Mammadov Shahin , Afşer Hüseyin
Published: December 2024

Multi-model predictive maintenance is a recently trending approach where information from different inputs and models are processed in a unified fashion in order to provide better failure prognostics. Multi-model systems aim to make clever use of labeled or unlabeled sensor observations, knowledge bases and device specific constraints. In this paper we present an overview for both single and multi-model approaches and provide a linear system perspective. The proposed system leverages linear classification and prediction methods such that the measurement space is partitioned via linear boundaries into nominal and failure operation regions and the distances from boundaries are tracked for providing remaining useful life calculations. The adopted linear approach simplifies the design process and it can efficiently incorporate different modalities in order to enhance the prediction performance. Also, the proposed method is simulated in generated dataset.
Crime Prediction with DistilBERT-based Feature Extraction and Machine Learning
Authors: Çolakoğlu Emel , Hızlısoy Serhat , Arslan Recep Sinan
Published: December 2024

Crime is all actions and behaviors that harm societies and have a legal and criminal counterpart. Although the fight against crime is basically interpreted as the duty of the state, practices similar to this study are important in order to support the struggle. Because it can create situations that can be interpreted with different analyzes made on crime data. From this point of view, additional measures taken will be an auxiliary element in the fight against crime. Being able to predict the crime that may occur ensures that it is prevented before the crime situation occurs. Therefore, the analysis and prediction of crimes is important in identifying and reducing future crimes. In this research, a model in which features are obtained with DistilBERT and 8 different machine learning algorithms are used as classifiers is proposed. The San Francisco crime dataset, which was used for an online competition managed by Kaggle Inc, was used as the dataset. Unlike the literature, all crime categories (39 categories) in the dataset were included in the study. In addition, obtaining features with DistilBERT is another point that differentiates the study. GridSearchCV was preferred for parameter optimization and a general improvement was observed in the range of 1-2% compared to the default parameters. The highest accuracy rate was accomplished with the Support Vector Machine (SVM) with 99.78%. In addition, with 10-fold cross-validation, higher accuracy values were achieved in SVM and Logistic Regression (LR) classifiers.
Musical Features of Ulsan Area Sangyeosor
Authors:   Dong Nam Eo-Mun-Hak-Hoi, Hwang SooIm
Published: December 2024

This study examines the characteristics of funeral rituals by exploring the music performed during the funeral rituals in Ulsan, South Korea, which were introduced in the original data sites Funeral Songs of the Busan Ulsan Gyeongnam & Jeju, A collection of verbal Korean literature, Ulsan Ulju Local Folk Song Collection, Korean Folk Song Collection. First, we looked at local stories and ritual procedures in Ulsan to understand the sentiments of the local people in Ulsan regarding funerals. Next, we looked at the current state of Ulsan's Sangyeosori, and transcribed the songs into sheet music to visualize them. Based on this, we analyzed the rhythm, speed, constituent sounds, termination sounds, pitch range, major melodic forms, phrases, and song content, and examined the musical characteristics of Ulsan Area Sangyeosori. We interviewed local residents who grew up in Ulsan and experienced the tradition of funeral culture as a community to learn more about the reality and characteristics of the local Sangyeosori.
Songdo's filial piety is revered as a model for the promotion of filial piety culture and the inculcation of the virtue of filial piety, and has had a profound impact on the funeral culture of Ulsan. We found that Sangyeosori in the Ulsan area were divided into sangyeonorisori, a bier carryingsori, and Karajilsori depending on their nature. Interviews with local residents and literature data showed that the reason for the lack of a widespread dalgu song in the nearby area is that Ulsan did not use dalgu. In addition, the chorus of Ulsan Area Sangyeosori, tabulo style and sugiyo style, have a strong Buddhist color, but the gananbosal style, which has a distinctly Buddhist color and is universal, has not been identified. In the process of singing Sangyeosori, yaoleeng, buk and kwaenggwari were used, and the lyrics of the songs were mainly composed of the lamentations of the dead, the grief of the bereaved family, and prayers for the dead and their descendants, and were often improvised to describe the personality, character, and merits of the deceased. Most of them were sung in the way that one person first called and then several people called a fixed chorus, and it was composed of Mi, Sol, La, Do, and Re, and ended in Mi and ra. The range of notes sung is between 4 and 8 degrees, with a distinctive melodic progression Menaritori that descends through the sols(la-sol-mi). In the case of Hoishimgok, which was sung during the Sangyeo carrying process, we find a mix of musical forms popularized by folk singers and local sound habits.
I realized that the Ulsan locals' ideas of life after death, as reflected in the song, were developed from the perspective of the present world. The attitude of wishing for the prosperity of their descendants is a reflection of the Ulsan people's view of the afterlife. The Ulsan Area Sangyeosori served as a medium to transform the grief of loss into a strong will to live.
VÍNCULOS INTERPESSOAIS DE HOMOSSEXUAIS / BISSEXUAIS: A IMPORTÂNCIA DA CONEXÃO FAMILIAR E SOCIAL DURANTE O ISOLAMENTO DA COVID-19
Authors: Moraes Filho Iel Marciano de , Rocha Lucas da Silva Rocha , Silva Rakel de Jesus da , Silva Rodrigo Marques da , Tavares Viviane Rodrigues , Carvalho Filha Francidalma Soares Sousa , Sousa Thais Vilela de
Published: December 2024

Introdução: Estudar vínculos interpessoais - familiares e sociais - de pessoas homossexuais e bissexuais durante o isolamento da COVID-19 é crucial para entender seu impacto na saúde mental, oferecendo suporte emocional, reduzindo solidão e aumentando resiliência de um grupo que já enfrenta altos níveis de discriminação e exclusão. Objetivo: Analisar as relações familiares e interpessoais de pessoas homossexuais e bissexuais durante o período de isolamento social na pandemia da COVID-19. Método: Estudo transversal e analítico realizado com 1411 homossexuais e bissexuais das cinco macrorregiões brasileiras, de junho a julho de 2020. Aplicou-se um questionário estruturado com questões sociodemográficas, um questionário a respeito das emoções vivenciadas na COVID-19, além do instrumento de Avalição da Tolerância nas Relações de Amizade. As variáveis foram apresentadas em valores absolutos e percentuais, sendo expostas em medidas descritivas e para comparar os grupos quanto as variáveis de tolerância de amizade no relacionamento familiar e nível geral de tolerância, utilizou-se o teste de qui-quadrado. Valores de p<0,05 foram considerados estatisticamente significativos. Resultados: Não houve diferença estatística significativa entre os grupos no que tange às relações de amizade; a tolerância no ambiente familiar foi satisfatória, ambos receberam ajuda dos amigos para superar as tensões relacionadas à pandemia; e os indivíduos dos dois grupos acreditam ter ocorrido mudança nas relações de amizade durante o período pandêmico. O avanço da idade (p=0,031) contribui para o aumento da tolerância nas relações de amizade (p<0,001). Mas ser bissexual (p=0,021), apresentar nível superior (p=0,01), possuir faixa de renda entre 2 e 4 salários mínimos (p<0,001) e ter sofrido mudança nas relações de amizade desde o início da pandemia (p= 0,001) contribuem para menores níveis de tolerância. Conclusão: Embora haja diversos fatores que interferem nas relações interpessoais deste grupo, elas foram imprescindíveis para a superação das adversidades enfrentadas pela pandemia.
Palavras-Chave: Minorias Sexuais e de Gênero; COVID-19; Relações-Familiares; Relações Interpessoais; Mensuração das Desigualdades em Saúde.
ATUAÇÃO DA EQUIPE DE ENFERMAGEM NO PARTO HUMANIZADO: REVISÃO INTEGRATIVA
Authors: Santos Andressa Thauany Charão dos , Figueira Maura Cristiane e Silva , Ribeiro Karina Angélica Alvarenga , Oliveira Vinícius Soares de , Anastácio Thaís de Oliveira
Published: December 2024

Introdução: A assistência à saúde da parturiente vem sendo discutida no Brasil, sendo que a humanização do processo está intimamente ligada ao nascer e, a equipe de enfermagem atua diretamente na promoção da saúde das parturientes. Objetivo: Compreender a importância do enfermeiro e da equipe de enfermagem no procedimento e prática de parto e pós-parto humanizado.  Metodologia: Utilizando uma revisão integrativa da literatura, foram analisados artigos científicos nas bases de dados Scielo, PubMed e BVS. Após a aplicação de inclusão e exclusão, foram selecionados nove artigos científicos.  Resultados: Os estudos destacam a importância de práticas não invasivas e a atuação dos enfermeiros obstetras na humanização do parto. Exemplos incluem o parto na água, participação das mulheres nas decisões de parto, e o modelo colaborativo que reduz intervenções desnecessárias. Conclusões: Enfatiza-se a necessidade de cuidados respeitosos, autonomia da mulher e formação em práticas humanizadoras para melhorar a qualidade da assistência obstétrica.
Palavras-Chave: Centros de assistência a gravidez e ao parto, Enfermeiros obstétricos, Parto normal.
The Role of Dapagliflozin in the Modulation of Hypothermia and Renal Injury Caused by Septic Shock in Euglycemic and Hyperglycemic Rat Models
Authors: Alanazi Wael A. , Alharbi Turki , Bin Anzan Khalid M. , Alyahiya Musab K. , El-Nagar Doaa M. , Alanazi Mohammed M. , Almutairi Mohammed M. , Alhamami Hussain N. , Albogami Abdullah M. , Mohany Mohamed
Published: December 2024

Background:

Recent research has validated the efficacy of sodium-glucose cotransporter-2 inhibitors (SGLT2i) in reducing glucose levels and exerting a
nephroprotective role.

Objective:

This study aimed to examine the impact of dapagliflozin in preventing sepsis-induced acute kidney injury (AKI) and related consequences. The
study used both normal and diabetic rat models to investigate whether the effectiveness of dapagliflozin is influenced by glycemia levels.

Methods:

Normal and diabetic Wistar albino rats were treated with dapagliflozin for two weeks and then received a single dose of lipopolysaccharide (LPS).
After sepsis induction, skin and deep body temperatures were recorded every two hours. Blood and kidneys were collected for analysis using
histological examination and biochemical assays.

Results:

Dapagliflozin attenuated the consequences of sepsis through mitigation of LPS-induced hypothermia and AKI in the normal and diabetic septic
groups. Dapagliflozin regulated the serum levels of AKI markers, including creatinine and blood urea nitrogen, as well as ion levels. Dapagliflozin
attenuated LPS-induced AKI through modulation of renal inflammation and oxidative stress, which showed well-abundant glomeruli. These results
indicated the protective effect of dapagliflozin against LPS-induced hypothermia and AKI, which was likely unrelated to its glucose-lowering
properties, as evidenced in the non-diabetic septic group.

Conclusion:

The outcomes suggest that dapagliflozin has a potential impact in preventing sepsis-induced hypothermia and AKI via modulation of inflammation
and oxidative stress, irrespective of glycemic levels.
Syndrome of moderate cognitive disorders in occlusal-stenotica lesions of the brachiocephal arteries (analysis of clinical observations)
Authors: Kovaleva N. S. , Zabaznov K. G.
Published: December 2024

This article analyzes two clinical observations of patients with stenotic and occlusive atherosclerotic lesions of the brachiocephalic arteries in various combinations. Both patients had a stroke-free course and early formation of the syndrome of moderate cognitive disorders. In the course of working with patients, a thorough analysis of complaints, anamnesis of the disease, clinical and neuropsychological examination was carried out, an expanded volume of studies was performed: general clinical, biochemical, ultrasound, magnetic resonance, angiographic. Based on the data obtained, a diagnosis was made and surgical treatment was performed. A subsequent detailed neurological examination, which included a neuropsychological examination, revealed an increase in the total score on the Montreal cognitive function assessment scale and a positive trend in indicators of control functions. The results of the analysis of these cases emphasize the importance of early detection and an integrated approach to therapy to improve the quality of life of patients and prevent further progression of cognitive deficits.
Peripheral arterial atherosclerosis and heart failure: state of the art review
Authors: Genkel V. V. , Latysheva O. V. , Ershov S. V. , Lebedev E. V. , Kuznetsova A. S. , Salashenko A. O. , Shaposhnik I. I.
Published: December 2024

Heart failure is considered as a terminal stage of the cardiovascular continuum, beginning with exposure to risk factors followed by the development of asymptomatic cardiovascular damage, progressing to clinically manifest disease. Conventional risk factors such as arterial hypertension, dyslipidemia, obesity, and diabetes mellitus, on the one hand, directly cause structural and functional changes in the heart, and on the other hand, contribute to the development and progression of atherosclerosis. Despite the fact that the multifocal nature of atherosclerosis is well known, research data on the role of peripheral arterial atherosclerosis in the development of heart failure are extremely limited. The study of potential relationships between atherosclerosis of peripheral arteries and heart failure is relevant in all sex and age groups of patients.
Galectin-3 as an independent predictor of postoperative atrial fibrillation
Authors: Tatarintseva Z. G. , Sinelnikova M. G. , Bratova A. V. , Barbuhatti K. O.
Published: December 2024

Objective: to evaluate the significance of preoperative plasma galectin-3 levels for predicting postoperative atrial fibrillation (AFP) in a cohort of patients who underwent elective heart surgery.

Materials and methods: this prospective observational single-center cohort study was conducted at the Research Institute – Regional Clinical Hospital No. 1 n. a. prof. S.V. Ochapovsky, Krasnodar. In the period from September 1, 2023 to February 1, 2024, all patients admitted for elective coronary artery bypass grafting and/or valve surgery (valve replacement or reconstruction) were included in this study. In the early postoperative period, POAF developed in 158 patients, who formed the main group A, and from 436 patients with sinus rhythm, a control group B was generated using a random number generator, comparable with the main group in the number of observed patients and amounted to 160 patients.

Results: the onset of POAF from the beginning of the operation is 66.2±41.7 hours (on average, on the 3rd day, minimum 1 hour, maximum 166.5 hours, i.e. on the 7th day). When comparing laboratory data in patients before the operation (blood sampling was performed 12–24 hours before cardiac surgery), a statistically significant factor associated with the development of POAF was the level of galectin-3 in the blood (2.1±1.99 ng/ml in patients from group A, 1.87±1.64 ng/ml in patients from group B, p 0.01). Moreover, the blood galectin-3 level in patients with POAF significantly increased in the early postoperative period (up to 2.75±2.1 ng/ml, p <0.001), which was confirmed by the ROC curve (the area under the AUC curve was 0.522 (AUC: 0.522, 95% CI: 0.457–0.588; P =0.033)).

Conclusions: preoperative plasma galectin-3 levels have an independent value for predicting POAF and can serve as a useful prognostic parameter in a multimodal approach to risk assessment in the era of personalized treatment.
Dyspnea in patients with cardiovascular diseases: clinical, diagnostic and pathophysiologic aspects
Authors: Yupatov V. D. , Karoli N. A.
Published: December 2024

Dyspnea is one of the most common symptoms in patients with various diseases. Dyspnea in stable ischemic heart disease (IHD), especially in a patient with prior myocardial infarction, is in most cases considered as a manifestation of congestive heart failure (CHF). And often practicing physicians do not think about the possibility of another genesis of dyspnea in their patients. This may lead to overdiagnosis of CHF. The review presents data on the occurrence, prognostic significance, classification features, as well as methods of dyspnea evaluation in therapeutic patients. The peculiarities of dyspnea genesis in patients with IHD, CHF, as well as in elderly patients are described. The absence of a universal and accessible method of dyspnea assessment complicates its differential diagnosis, especially in patients with a combination of pathology of respiratory and cardiovascular systems. Further research is needed to develop methods of complex assessment of dyspnea in patients with cardiovascular and other diseases in different age groups.
Features of the course of non-alcoholic fatty liver disease after COVID-19
Authors: Zhuk K. S. , Tarlovskaya E. I. , Vlasova T. V.
Published: December 2024

Objective: to assess the effect of COVID-19 on the progression of NAFLD.

Materials and methods: a retrospective cohort study included 73 patients with NAFLD, of whom 22 had COVID-19 between March 2020 and February 2021. The diagnosis of NAFLD was established on the basis of clinical, laboratory and instrumental data. Anthropometric parameters, indicators of lipid and carbohydrate metabolism, markers of liver damage and systemic inflammation were evaluated. Transient elastography was used to determine the stage of liver fibrosis. 

Results: in patients with NAFLD who underwent COVID-19, there was a significant increase in body mass index (BMI) by 1.8 ± 0.9 kg/m2 (p<0.001) and waist circumference by 4.3 ± 2.1 cm (p<0.001) compared with baseline values. At the same time, in the control group, the increase in BMI was only 0.4 ± 0.6 kg/m2 (p= 0.132), and FROM — 1.1 ± 1.4 cm (p=0.083). The differences in the dynamics of anthropometric parameters between the main and control groups were statistically significant (p<0.001). ALT and AST levels in the group of patients with COVID-19 were higher than in the control group by 32.4% (p=0.002) and 28.7% (p=0.007), respectively. HOMA-IR and triglyceride indices also showed a statistically significant increase, compared with baseline data, by 38.6% (p<0.001) and 21.9% (p=0.011). The proportion of patients with liver fibrosis progression at stage 1 was 29.6% in the COVID-19 group versus 12.4% in the control group (HR=2.93; 95% CI: 1.76-4.88; p<0.001). Multivariate analysis showed that the severity of COVID-19 (HR=2.17; 95% CI: 1.24-3.79; p=0.006) and the initial stage of fibrosis (HR=1.84; 95% CI: 1.11-3.05; p=0.018) are independent predictors of NAFLD progression. 

Conclusion: The study demonstrated a significant impact of previous COVID-19 coronavirus infection on the course of NAFLD
Building a Human Digital Twin (HDTwin) Using Large Language Models for Cognitive Diagnosis: Algorithm Development and Validation (Preprint)
Authors: Sprint Gina , Schmitter-Edgecombe Maureen , Cook Diane
Published: December 2024

BACKGROUND

Human digital twins have the potential to change the practice of personalizing cognitive health diagnosis because these systems can integrate multiple sources of health information and influence into a unified model. Cognitive health is multifaceted, yet researchers and clinical professionals struggle to align diverse sources of information into a single model.

OBJECTIVE

This study aims to introduce a method called HDTwin, for unifying heterogeneous data using large language models. HDTwin is designed to predict cognitive diagnoses and offer explanations for its inferences.

METHODS

HDTwin integrates cognitive health data from multiple sources, including demographic, behavioral, ecological momentary assessment, n-back test, speech, and baseline experimenter testing session markers. Data are converted into text prompts for a large language model. The system then combines these inputs with relevant external knowledge from scientific literature to construct a predictive model. The model’s performance is validated using data from 3 studies involving 124 participants, comparing its diagnostic accuracy with baseline machine learning classifiers.

RESULTS

HDTwin achieves a peak accuracy of 0.81 based on the automated selection of markers, significantly outperforming baseline classifiers. On average, HDTwin yielded accuracy=0.77, precision=0.88, recall=0.63, and Matthews correlation coefficient=0.57. In comparison, the baseline classifiers yielded average accuracy=0.65, precision=0.86, recall=0.35, and Matthews correlation coefficient=0.36. The experiments also reveal that HDTwin yields superior predictive accuracy when information sources are fused compared to single sources. HDTwin’s chatbot interface provides interactive dialogues, aiding in diagnosis interpretation and allowing further exploration of patient data.

CONCLUSIONS

HDTwin integrates diverse cognitive health data, enhancing the accuracy and explainability of cognitive diagnoses. This approach outperforms traditional models and provides an interface for navigating patient information. The approach shows promise for improving early detection and intervention strategies in cognitive health.
Identifying Asthma-related Symptoms from Electronic Health Records within a Large Integrated Healthcare System: Hybrid Natural Language Processing Approach (Preprint)
Authors: Xie Fagen , Zeiger Robert S , Saparudin Mary , Al-Salman Sahar , Puttock Eric J , CRAWFORD WILLIAM , Schatz Michael , Xu Stanley , Vollmer William M , Chen Wansu
Published: December 2024

BACKGROUND

Asthma-related symptoms are significant predictors of asthma exacerbation. Most of these symptoms are documented in clinical notes in free text format. Methods that can effectively capture the asthma-related symptoms from the unstructured data are lacking.

OBJECTIVE

The study aims to develop a natural language process (NLP) algorithm and process to identify symptoms associated with asthma from clinical notes within a large integrated healthcare system.

METHODS

We used unstructured data within two years prior to asthma diagnosis visits in 2013-2018 and 2021-2022 to identify four common asthma-related symptoms. Related terms and phrases were first compiled from publicly available resources and then recursively reviewed and enriched with inputs from clinicians and chart review. A rule-based NLP algorithm was first iteratively developed and refined via multiple rounds of chart review followed by adjudication, and then transformer-based deep learning algorithms were developed and validated using the same manually annotated datasets. Subsequently, a hybrid algorithm was generated by combining the rule-based and the transformer-based algorithms. Finally, the developed algorithms were implemented in all the study notes.

RESULTS

A total of 11,374,552 eligible study clinical notes with 128,211,793 sentences were retrieved. At least one symptom was identified in 1,663,450 (1.30%) sentences and 858,350 (7.55%) notes, respectively. Cough had the highest frequency at both sentence (1.07%) and note (5.81%) levels while chest tightness had the lowest one at both sentence (0.11%) and note (0.57%) levels. The frequencies of concomitant symptoms ranged from 0.03% to 0.38% at the sentence level and 0.10% to 1.85% at the note level. The validation of the hybrid algorithm against the annotated result of 1,600 clinical notes yielded a positive predictive value ranging from 96.53% (wheezing) to 97.42% (chest tightness) at the sentence level and 96.76% (wheezing) to 97.42% (chest tightness) at the note level, sensitivity ranged from 93.90% (dyspnea) to 95.95% (cough) at the sentence level and 96.00% (chest tightness) to 99.07% (cough) at the note level. The corresponding F1 scores of all four symptoms were > 0.95 at both sentence and note levels regardless of NLP algorithms.

CONCLUSIONS

The developed NLP algorithms could effectively capture asthma-related symptoms from unstructured notes. These algorithms could be utilized to examine asthma burden and prediction of asthma exacerbation.
Enhancing MRI Report Comprehension in Spinal Trauma: An Analysis of AI-Generated Explanations for Thoracolumbar Fractures (Preprint)
Authors: Sing David C. , Shah Kishan S. , Pompliano Michael , Yi Paul H. , Velluto Calogero , Bagheri Ali , Eastlack Robert K. , Stephan Stephen , Mundis Gregory M.
Published: December 2024

BACKGROUND

MRI reports are challenging for patients to interpret and may potentially subject patients to unnecessary anxiety. The advent of advanced artificial intelligence (AI) language models such as GPT-4 hold promise in translating complex medical information into layman terms.

OBJECTIVE

To evaluate the accuracy, helpfulness, and readability of GPT-4 in explaining MRI reports of patients with thoracic or lumbar fracture.

METHODS

MRI reports of 20 patients presenting with thoracic or lumbar fracture were obtained. GPT-4o was prompted to explain the MRI report in layman’s terms. The generated explanations were then presented to 7 spine surgeons for evaluation. The MRI report text and GPT-4o explanations were then analyzed to grade the readability of the texts using Flesch Readability Score and Flesch-Kincaid Grade Level Scale.

RESULTS

The layman explanations provided by GPT-4o were found to be helpful by all surgeons in 17 cases, with 6 of 7 surgeons finding the information helpful in 3 cases. The GPT-4o explanations were considered accurate by all surgeons in 11 cases, with 6 surgeons considering the information accurate in 5 cases, and 4 or 5 surgeons considering the information accurate in 4 cases. Review of surgeon feedback on inaccuracies revealed that the radiology reports were often insufficiently detailed. The mean readability score of the MRI reports was significantly lower than the GPT-4o explanations (32.2 +/- 16.3 vs 53.9 +/- 8.1, p<0.001). The mean reading grade level score of the MRI reports trended higher compared to the GPT-4o explanations (11-12th grade vs 10-11th grade level, p=0.11).

CONCLUSIONS

Overall helpfulness and readability ratings for AI-generated summaries of MRI reports were high, with few inaccuracies recorded. This study demonstrates the potential of GPT-4o as a valuable tool for enhancing patient comprehension of MRI report findings.
Artificial Intelligence Can Translate and Simplify Spanish Orthopedic Medical Text: Instrument Validation Study (Preprint)
Authors: Andalib Saman , Spina Aidin Christopher , Picton Bryce Gifford , Solomon Sean S. , Scolaro John A. , Nelson Ariana M.
Published: December 2024

BACKGROUND

Language barriers contribute significantly to healthcare disparities in the United States, where a sizeable proportion of patients are exclusively Spanish-speaking. In orthopedic surgery, such barriers impact both patient comprehension and patient engagement with available resources. Previous studies have explored the utility of large language models (LLMs) for medical translation but have yet to robustly evaluate AI-driven translation and simplification of orthopedic materials for Spanish speakers.

OBJECTIVE

This study utilizes the Bilingual Evaluation Understudy (BLEU) method to assess translation quality and investigates the ability of AI to simplify patient education materials (PEMs) in Spanish.

METHODS

PEMs (n = 78) from the American Academy of Orthopaedic Surgery (AAOS) were translated from English to Spanish using two LLMs (GPT-4 and Google Translate). The BLEU methodology was applied to compare AI translations with professional human-translated PEMs. Friedman’s test and Dunn’s multiple comparisons test were used to statistically quantify differences in translation quality. Readability analysis and feature analysis were subsequently performed to evaluate text simplification success and the impact of English text features on BLEU scores. The capability of an LLM to simplify medical language written in Spanish was also assessed.

RESULTS

As measured by BLEU scores, GPT-4 showed moderate success in translating PEMs into Spanish but was less successful than Google Translate. Simplified PEMs demonstrated improved readability compared to original versions (P<.001) but were unable to reach the targeted grade-level simplification. Feature analysis revealed that total syllables and average syllables per sentence had the highest impact on BLEU scores. GPT-4 was able to significantly reduce the complexity of medical text written in Spanish (P <.001).

CONCLUSIONS

While Google Translate outperformed GPT-4 in translation accuracy, LLMs such as GPT-4 may provide significant utility in translating and simplifying medical texts into Spanish. We recommend considering a dual approach of using Google Translate for translation and GPT-4 for simplification in order to improve Spanish-speaking patient accessibility and education in orthopedic surgery.
Sürdürülebilirlik Raporlamasının Firmaların Kârlılığı Üzerindeki Etkisi: Üretim Sektöründe Bir Analiz
Authors: Ayvaz Ednan , Awale Abdirahman Abdinur
Published: December 2024

Bu çalışma, BORSA İstanbul'da (BIST) işlem gören üretim işletmelerinin sürdürülebilirlik raporlaması ile finansal performansı arasındaki ilişkiyi incelemektedir. Sürdürülebilirlik raporlamasından ikincil veri elde etmek için içerik analizi kullanılmıştır. Ayrıca sürdürülebilirlik raporlamasının finansal performans üzerinde etkisinin olup olmadığı konusunda tanımlayıcı istatistikler ve regresyon analizi kullanılmıştır. Bunlara ek olarak, firma büyüklüğünün etkisini kontrol ederek genel sürdürülebilirliğin ve sürdürülebilirliğin çevresel boyutunun şirketin varlık getirisi üzerindeki etkisi incelemiştir. Üretim işletmelerinin %14'ünün Küresel Raporlama Girişimi kılavuzlarını takip ederek bağımsız sürdürülebilirlik raporları yayınladığı görülmüştür. Sonuçlar ayrıca şirketlerin Küresel Raporlama Girişimine özgü standartların ortalama %50'sini açıklama düzeyine ulaştığını göstermiştir. Bu çalışma aynı zamanda toplam analizde genel sürdürülebilirlik raporlaması ile kârlılık arasında pozitif ancak anlamsız bir ilişki bulmuştur. Öte yandan, sürdürülebilirlik raporlamasını yayınlayan şirketlerin finansal performans açısından aktif kârlılığı arasında anlamlı bir pozitif ilişki olduğunu gösterirken, sosyal performans açıklamalarının aktif kârlılığı ile anlamlı bir negatif ilişkisi olduğunu göstermiştir. Bu çalışma, şirketlerin itibarlarını iyileştirmek için çevresel faaliyetlerini açıklamaya öncelik vermeye devam etmeleri gerektiğini ve bunun da kârlılıklarını artıracağını göstermektedir.
Hastane Öncesi Acil Sağlık Hizmetlerinde Çalışan Personelin Afetlere Hazırlık Algıları ile Kaygı Düzeyleri Arasındaki İlişkinin İncelenmesi
Authors: Akman Dömbekci Hilal , Sağlam Şengül , Kırlı Gamze
Published: December 2024

Afet; toplumun olağan yaşam düzenini bozan, yanıt verme ve uyum sağlama kapasitesini aşarak, dış yardım gereksinimi doğuran, can ve mal kaybıyla sonuçlanan ekolojik olaylardır. Kaygı ise genel olarak yaygın bir tehdide odaklanan geleceğe yönelik, uzun etkili bir tepki olarak kabul edilirken, korku, açıkça tanımlanabilir ve spesifik bir tehdide karşı uygun, şimdiki zamana yönelik ve kısa ömürlü bir tepkidir. Bu çalışmada, hastane öncesi acil sağlık hizmetlerinde çalışan personelin afetlere hazırlık algıları ile kaygı düzeyleri arasındaki ilişkinin incelenmesi amaçlanmaktadır. Araştırmanın evrenini Kocaeli ilinin Gebze ve Çayırova ilçesinde hizmet vermekte olan 11 adet 112 Acil Sağlık Hizmetleri istasyonunda görev yapmakta olan 165 hastane öncesi acil sağlık çalışanından oluşmaktadır. Araştırma gerekli evren ve örneklem hesaplaması yapılarak 111 hastane öncesi acil sağlık çalışanı ile gerçekleştirilmiştir. Toplanan verilerin analizinde SPSS programı kullanılmıştır. Yapılan analizlere göre dikkat çeken bulgular; katılımcıların %36,9’u (41 kişi) 35-50 yaş arası olduğu; %65,8’i (73 kişi) kadın olduğu; %52,3’ü (58 kişi) evli olduğu; %40,5’i (45 kişi) lisans mezunu olduğu %50.5’inin (56 kişi) gelir durumunun asgari ücretin iki katı olduğu tespit edilmiştir. Araştırma kapsamında yapılan korelasyon analizi sonucunda afet hazırlık algısı ve kaygı düzeyi arasında negatif yönlü düşük seviyede anlamlı bir ilişki tespit edilmiştir. Araştırma sonucunda, araştırmaya katılan hastane öncesi acil sağlık hizmeti çalışanlarının medeni durumları, eğitim durumu ve cinsiyetleri ile ölçek ortalaması ve alt boyutları arasında anlamlı bir farklılık tespit edilmezken gelir durumu ve yaşları arasında anlamlı farklılık tespit edilmiştir.
Đánh giá hoạt tính xúc tác loại bỏ thuốc nhuộm acid fuchsin của vật liệu lưỡng kim FeZn-ZIFs dựa trên quy trình oxy hóa nâng cao
Authors: Lê Thị Anh Thư , Ngô Trương Ngọc Mai , Lương Huỳnh Vủ Thanh , Hồ Ngọc Tri Tân , Cao Lưu Ngọc Hạnh , Đặng Huỳnh Giao
Published: December 2024

Nghiên cứu này được thực hiện nhằm đánh giá hoạt tính xúc tác của vật liệu lưỡng kim FeZn-ZIFs đối với việc loại bỏ tồn dư thuốc nhuộm khỏi môi trường nước. Trong đó, cấu trúc tinh thể, nhóm chức đặc trưng, độ bền nhiệt, thành phần nguyên tố và hình thái của FeZn-ZIFs được xác định thông qua các phương pháp phân tích hiện đại gồm nhiễu xạ tia X dạng bột, quang phổ hồng ngoại biến đổi Fourier, nhiệt trọng lượng, phổ tán sắc năng lượng tia X và kính hiển vi điện tử quét. Khả năng loại bỏ thuốc nhuộm acid fuchsin dựa trên hoạt tính xúc tác của FeZn-ZIFs đối với chất oxy hóa potassium peroxydisulfate (PDS) cũng được đánh giá bằng phương pháp UV-Vis. Kết quả cho thấy hệ xúc tác FeZn-ZIFs/PDS có khả năng loại bỏ đến 93,3% acid fuchsin tại nhiệt độ phòng chỉ sau 30 phút.
Định hướng và điều khiển Robot di động dựa trên công nghệ định vị GPS và cảm biến la bàn
Authors: Lưu Trọng Hiếu , Nguyễn Chí Ngôn , Hà Tấn Đạt , Phạm Quang Thế
Published: December 2024

Nghiên cứu này trình bày một giải pháp tích hợp hệ nhiều cảm biến định vị vào robot di động để điều khiển robot đến vị trí mong muốn trong môi trường bên ngoài. Trái tim của hệ là một vi điều khiển esp8266 có thể tính toán được nhiều phương trình theo thời gian thực. Vi điều khiển nhận tín hiệu từ cảm biến la bàn đề xác định góc quay đến vị trí mong muốn và cập nhật giá trị cảm biến GPS được dùng để định vị và cập nhật dữ liệu liên tục trong suốt quá trình di chuyển trong môi trường bên ngoài. Thí nghiệm đươc tiến hành một sân trống tại trường Bách Khoa, Trường Đại học Cần Thơ trong điều kiện thời tiết tương đối thuận lợi. Kết quả cho thấy robot có thể di chuyển đến các vị trí mong muốn. Nghiên cứu này là tiền đề cho các nhóm sau áp dụng thêm các giải thuật và công nghệ cao cấp vào robot di động trong điều kiện bên ngoài.
Estimating the contents of Chlorophyll, Nitrogen, and Yields on Rice through Sentinel-2 Vegetation Indices in Heterogeneous Land Management
Authors: Wijayanto Yagus , Safitri Mahardika , Purnamasari Ika , Budiman Subhan Arif , Saputra Tri Wahyu , Regar Arthur FC , Ristiyana Suci
Published: December 2024

Addressing the global food demand is an urgent priority for governments worldwide. Efficient and effective methods for gauging crop production are crucial. Relying solely on ground-based measurements proves inefficient and expensive, prompting exploration of remote sensing using vegetation indices as a viable alternative. This study sought to achieve three objectives: estimating chlorophyll content in paddy fields, evaluating leaf nitrogen content, and predicting yields. The investigation utilized Sentinel-2A satellite imagery, Soil Plant Analysis Development (SPAD) for chlorophyll measurement, and employed statistical and accuracy analyses. Findings revealed an increase in chlorophyll and leaf nitrogen content from the vegetative to maturity phases, followed by a decline at maturity. NDVI and GNDVI emerged as superior to SAVI and VARI for chlorophyll estimation, attributed to their spectral sensitivity. Likewise, nitrogen prediction showed similar trends, with NDVI and GNDVI exhibiting better RMSE values compared to SAVI and VARI, albeit marginally. However, yield prediction accuracy varied, with NDVI proving most accurate, followed by SAVI, VARI, and GNDVI, indicating the latter's reduced predictive precision due to nitrogen sensitivity. In scenarios where nitrogen is not the predominant yield-limiting factor, NDVI could outperform GNDVI in forecasting yield. Received: 2023-07-22 Revised: 2024-04-18 Accepted: 2024-08-24 Published: 2024-10-10