bluuebunny/crossref_metadata_2025 huggingface dataset:
PREVALENCE AND STRUCTURE OF DENTO-MAXILLOFACIAL ANOMALIES IN CHILDREN
Authors: Byala O.-Kh.A.
Published: March 2024

The high level of dental morbidity in the children's population of Ukraine remains one of the urgent problems of modern dentistry. Dental health is largely characterized by the correctness of the structure of the mandibular system, its proper functioning and balance, and its condition is one of the preventive and quite clearly fixed indicators of health/ ill health of the human body in general. The pathology of the maxillofacial system affects not only the state of health, but also the quality of life of the patient, his emotional and social well-being.

In this context, information on the prevalence of dentomandibular abnormalities and the overall need for orthodontic treatment is essential to provide objective information to health care stakeholders in order to make an adequate allocation of health care resources based on objective epidemiological data. In addition, dento-mandibular anomalies, which are not detected and not eliminated in childhood, in the process of growth and development of the facial skeleton over time acquire more severe forms, which become more pronounced and are less amenable to treatment. Therefore, the analysis of the prevalence and severity of ASD in children is an important stage in the process of planning preventive and therapeutic measures.

Data from literary sources indicate a high prevalence of dento-maxillofacial anomalies among children in different age periods and depending on the characteristics of the area of residence. In particular, the results of the examination of children aged eight months to seventeen years, residents of different regions of Ukraine, given in scientific works of recent years, indicate a high prevalence of dento-jaw anomalies (41%77.9%).

The high prevalence of dento-mandibular anomalies indicates the need for timely diagnosis at the early stages of the development of orthodontic pathology, which will contribute to timely treatment, which will subsequently be able to ensure the normal development of the child's dento-mandibular system and improve the quality of life.
USING OF THE MODELS IN PRACTICE-ORIENTED EDUCATION DURING LEARNING OF PEDIATRIC DENTISTRY
Authors: Kaskova L.F. , Yanko N.V. , Novikova S.Ch. , Chupryna L.F. , Artemyev A.V.
Published: March 2024

Teachers of clinical departments of establishments of higher medical education are faced with the problem of practical training of students, and many methods have been proposed for its improvement.

The purpose of the study was to consider the models of practice-oriented education that can be used

during the teaching of pediatric therapeutic dentistry.

One Minute Preceptor model is used by the teacher during a 1-5-minute conversation with the student to guide diagnostic and treatment processes; initially a student examines a patient, then presents the clinical case, after which the teacher manages his behavioral reactions.

SNAPPS model (Summarize + Narrow + Analyze + Probe + Plan + Select) describes 6 stages of the clinical training. The model includes analysis of the medical history and examination methods, choice of the diagnoses for differential diagnostic, proper differential diagnosis, questions to the teacher about uncertainties, discussion of patient’s treatment plan and questions and sources related to the clinical case for independent processing.

Within the framework of pattern recognition and reproduction model (standard cases), student talks about the main problem that worries the patient and offers his diagnosis based on key symptoms during 30 seconds. Teacher personally examines patient, makes a diagnosis or discusses why it cannot be made with certainty, and evaluates the student’s actions.

All described models of practice-oriented learning improve the expression of reasoning without much impact on the time spent for case presentation. Pattern recognition and reproduction model is especially useful in dentistry to recognize widespread clinical cases. One Minute Preceptor model, which involves the initiative and mentoring role of the teacher, fits well for beginners, while SNAPPS model, that focused on independent work of students, for strong students.
HİBRİT ELEKTRİKLİ ARAÇLAR İÇİN DÜŞÜK ÇALIŞMA GERİLİMİNDE İÇ ROTORLU FIRÇASIZ DOĞRU AKIM MOTORU TASARIMI
Authors: Erdoğan Gökhan , Taşkın Yener , Tiryaki Hasan
Published: March 2024

Bu çalışmada, hibrit araçlar için paralel yapıda kullanılabilmeye yönelik yüksek güç, yüksek verim ve yüksek moment özelliklerini sağlayan yüksek çalışma gerilimindeki (300 V) iç rotorlu fırçasız doğru akım motor tasarımı yerine tehlikeli sınırın altında kalan bir gerilimde (96 V) yeniden tasarlanması amaçlanmıştır. Bu tasarım çalışmaları ve sonlu eleman analizleri ANSYS Electronics Desktop paket programıyla yapılmıştır. Deney aracı olarak seçilen bir hafif ticari araç verileri kullanılarak uygulama esnasında ihtiyaç duyulacak olan parametreler (moment, güç, devir) hesaplanmış ve motor tasarımları bu parametreler göz önünde bulundurularak yapılmıştır. Elektrikli ve hibrit araçlarda kullanılan elektrik motorları, yüksek devirlerde yüksek güç ve moment ihtiyacını karşılayabilmek amacıyla genellikle 400 V gibi yüksek çalışma gerilimlerinde üretilmektedir. Yüksek gerilimlerdeki elektrik motor ve sürücülerinde çekilen güce bağlı olarak hat üzerinden geçen akım değerinin düşük olması fayda sağlarken, motor sürücünün geliştirilmesinde kullanılan komponentlerin maliyetlerinin ve elektrik çarpması riskinin artmasına neden olmaktadır. Bu çalışma ile üretilecek olan fırçasız doğru akım motorunun sürücü kısmındaki komponent maliyetlerinin azaltılması ve araç içerisindeki DC bara geriliminin tehlikeli alt sınırın altında olması amaçlanarak tasarımı yapılan yüksek gerilimdeki motorun çalışma gerilimlerinin düşürülmesi sağlanmıştır.
ASSESSING THE UNIVERSITY ON-CAMPUS TRANSPORT MODES: A PRELIMINARY STUDY
Authors: Keleş Furkan , Özgül Hasan , Haktanırlar Ulutaş Berna
Published: March 2024

Transportation management on a university campus is critical to enable the efficient movement of students, faculty members, staff, and visitors as to minimize traffic congestion, environmental impact, and parking issues. The choice of on-campus transport mode can vary based on the campus’s size, location, and available infrastructure. In this study, a questionnaire is introduced to assess the factors that may affect on-campus transport mode choice of students. A group of 60 undergraduate students who must travel to one of the furthest locations from the entrance gates of a campus is considered. The convenience of on-campus roads and the distance of the accommodation to the campus are examined. The results illustrated that weather conditions and air temperature were the critical factors for the transport mode choice, specifically for cycling and walking. The most preferred on-campus transport mode was determined as the ring line, especially during exam periods. Walking was only preferred if the student resides close to the campus. Both genders stated that the bicycle roads were narrow. This preliminary study has a potential to be applied for larger group of participants and is expected to inspire decisionmakers of the universities to improve the infrastructure of the university campus and help to develop cost efficient and sustainable travel options.
KAMERA HATA ENJEKSİYON ARACI İLE KAMERA TABANLI ROBOTİK DENETLEME SİSTEMİNİN DOĞRULANMASI VE ONAYLANMASI
Authors: Erdoğmuş Alim Kerem , Yayan Uğur
Published: March 2024

Günümüzde, gelişen görüntü işleme teknikleri ile birlikte kamera tabanlı robotik inceleme sistemleri oldukça popülerlik kazanmıştır. Bu tür sistemler gıdadan, askeriyeye birçok sektörde yoğun olarak kullanılmaktadır. Bu sistemler geliştirilirken gerekli olan doğrulama ve onaylama süreçleri oldukça uzun ve maliyetli olmaktadır. Bu çalışma, kamera tabanlı endüstriyel robotik sistemler üzerinde doğrulama ve onaylama faaliyetlerini gerçekleştirmek ve iyileştirmek amacıyla geliştirilmiştir. RGB ve TOF kameralara farklı türlerde (Open, Close, Dilation, Erosion, Gradient, Motionblur, Tuz&Biber, Gaussian ve Poisson) hata enjeksiyon yöntemleri kullanılmasını mümkün Kamera Hata Enjeksiyon Aracı (CamFITool) ile gerçekleştirilmiş testler ve sonuçlar açıklanmıştır. Yapılan çalışma, VALU3S projesi kapsamında, OTOKAR’ın ROKOS robotik sistemine, CamFITool ile gerçek ortamdan alınmış kamera görüntülerinden oluşan kitaplıklara, çeşitli konfigürasyonlarda hatalar enjekte edilip, bu enjeksiyonun sisteme etkilerinin incelenmesine odaklanmıştır. Bu kapsamda 49 farklı test komfigürasyonunda hata enjeksiyonu gerçekleştirilmiştir. Sonuç olarak, kamera tabanlı endüstriyel robotik sistemlerin daha güvenli ve stabil çalışmalarının sağlanması için, bu sistemlerin hataya dayanıklı olup olmadıklarını test eden açık kaynaklı bir hata enjeksiyon aracı olan CamFITool önerilmiştir.
"Megyimurszki-szlovenszki" — nevjerojatna sudbina “međimurskoga jezika” (2. dio)
Authors: Dončec Akoš Anton
Published: March 2024

Josip Margitaj (1854.-1934.), učitelj i mađaron, bio je utemeljitelj pojma “međimurskoga jezika”. Godine 1884. počeo je izdavati dvojezični tjednik Medjimurje/Murakoz. Jezična inačica, koju Margitaj zove „međimurskim“, zaista u maloj mjeri predstavlja međimurski dijalekt. U većoj mjeri pokazuje jezičnu srodnost s kasnijim djelima kajkavskoga književnog jezika, koja su bila prožeta utjecajem hrvatskoga književnog jezika štokavske osnovice. Neposredan je uzor Margitajevu jeziku bila susjedna slovenska pokrajina u Ugarskoj (danas Prekmurje u Sloveniji i Porabje u Mađarskoj), gdje je ostvaren književni jezik prema lokalnom dijalektu u 18. stoljeću, a koji je u Ugarskoj službeno bio nazvan “vendski”; taj se jezik, prema tzv.“ vendskoj teoriji“, nastojalo razlikovati od slovenskog jezika. Po oslobođenju Međimurja (1918.) prestali su pokušaji pisanja „na međimurskome“, za razliku od Prekomurja (slov., Prekmurja), gdje je još bila aktivna lokalna književnost do 1945. godine. Međimursko je pitanje bilo oživljavano u doba mađarske okupacije (1941. - 1944.), ponovno zbog propagandističkih i mađarizacijskih ciljeva, kao i 1942. godine, kad su napisane dvije kratke standardne gramatike (međutim, te gramatike nisu mogle stvoriti pravi normativni jezik). Krajem Drugoga svjetskog rata (1939.-1945.) jednom zauvijek dovršeni su „pokusi“ tzv. međimurskog jezika. Zaista lažan, „međimurski jezik“ nema nikakva traga u međimurskoj kulturnoj baštini, dok prekomurski jezik ipak ima živu tradiciju podjednako u Sloveniji i Mađarskoj. Ovaj rad Akoša Antona Dončeca - čiji je domicil Verica-Ritkarovci (Ketvolgy/Mađarska) - drugi je dio cjelovite studije (u dva nastavka) - koji razmatra program tzv. „međimurskog jezika“ Josipa Margitaja u kontekstu nekolikih prijelomnih momenata tematiziranog područja: u periodu priključenja Međimurja i Prekomurja Kraljevini SHS 1918. – 1919. te u uvjetima mađarske okupacije 1941. – 1944. Rad detektira smjerove pokušaja kodifikacije međimurskoga i prekomurskoga jezika u kontekstu znanstvenih proučavanja, te, na kraju, obrazlaže razloge sloma i baštine „međimurskoga jezika“. Rad je na hrvatski preveo dr. sc. Elod Dudaš.
Nepoznati Josip
Horvat
Authors: Vegh Željko
Published: March 2024

Hrvatski novinar Josip Horvat (1896. – 1968.) bio je vojnik u Prvom svjetskom ratu; kao austrougarski vojnik bio je u Galiciji, gdje ga je 1916. ruska vojska zarobila. Vratio se iz zarobljeništva u rujnu 1918. Godine 1919. vraća se u novine „Obzor“, s kojim je surađivao od 1913. U razdoblju od prosinca 1920. do ljeta 1923. Horvat je u „Obzoru“ objavio petnaestak članaka, od kojih većinu tijekom 1922. U objavljenim člancima Horvat, na primjerima pojedinih književnih djela iz europskih književnosti, ukazuje na dekadenciju i stvaralačku nemoć, koja je prema njegovom mišljenju zahvatila europske književnike nakon Velikog rata. U tim se člancima Horvat pokazuje kao anglofil, pristalica britanske kolonijalne politike te ujedno vidimo kakve je posljedice sudjelovanje u ratu ostavilo na njega: iz rata se Horvat vraća kao cinik, koji je uvjeren kako rat može biti ipak koristan za narode koji su njime zahvaćeni.
Immigrationspolitik in Großbritannien: Von Funktionalität zu Postfunktionalität?
Authors: Berg Sebastian
Published: March 2024

Der Beitrag beginnt mit einer Bestandsaufnahme aktueller Migration ins Vereinigte Königreich. Danach werden jüngste Verschiebungen im Verhältnis von funktionaler und postfunktionaler Immigrationspolitik beleuchtet. Schließlich fragt der Autor nach deren Auswirkungen und diskutiert die Möglichkeiten einer nicht ökonomisch verengten, sondern gesellschaftspolitisch funktionalen Strategie, die Immigration nicht primär als Problem behandelt.
Refinement of Trimap for Portrait Matting
Authors: Xu Yangjun , Hui Xiaodong , Zhang Kun , Jin Xin
Published: March 2024

Portrait matting refers to separating the portrait part from the background in an image. The difficulty of the problem lies in accurately identifying the pixels of the person and also maintaining the contour details. In this paper, we propose a fully automatic deep learning approach to achieve portrait matting. Firstly, semantic segmentation is used to predict the probabilities of pixels belonging to portrait, background, and unknown region, then a trimap is obtained. In order to remove the misclassification of pixels, we refine the portion of head contour for the trimap. The method used is to introduce the result of facial landmark detection, and erosion operation is performed on the head region while maintaining the integrity of the facial contour of the portrait. After that, we use deep matting method to predict the alpha value in the image to get the matting results at the details. We then propose a novel framework that integrates the optimised trimap, the deep matting result, and the original image to obtain the final matting result. Both qualitative and quantitative experiments verify the effectiveness of the proposed method.
Gradient-Based Adversarial Example Generation with Root Mean Square Propagation
Authors: Hong Dian , Chen Deng
Published: March 2024

Nowadays, the security of neural networks has attracted more and more attention. Adversarial examples are one of the problems that affect the security of neural networks. The gradient-based attack method is a typical attack method, and the Momentum Iterative Fast Gradient Sign Method (MI-FGSM) is a typical attack algorithm among the gradient-based attack algorithms. However, this method may suffer from the problems of excessive gradient growth and low efficiency. In this paper, we propose a gradient-based attack algorithm RMS-FGSM based on Root Mean Square Propagation (RMSProp). RMS-FGSM algorithm avoids excessive gradient growth by Exponential Weighted Moving Average method and adaptive learning rate when gradient updates. Experiments on MNIST and CIFAR-100 and several models show that the attack success rate of our approach is higher than the baseline methods. Above all, our generated adversarial examples have a smaller perturbation under the same attack success rate.
A Semantic Segmentation Algorithm in Workshop Scenarios
Authors: Yin Hongmei , Jin Gege , Li Zhijun , Chen Chen , Hua Jiyong
Published: March 2024

The classification of workshop objectives based on deep learning is the foundation of intelligent workshop management. There are various types of targets in the workshop, with variable geometric shapes and disorderly distribution of targets. In this article, we propose a deep learning based solution that can improve the speed and accuracy of target classification. A deep neural network model can train specialized models for specific work environments. The experiment has shown that the scheme has significant improvements in accuracy and visual effects.
The Composite Multi-Level Prediction Model for Stock Market Time Series
Authors: Chang Zhichao , Zhang Zuping
Published: March 2024

For a long time, investors have always been influenced by their own experience and investment expert advice. Machine Learning method in Quantitative Investment is an advanced method that replaces subjective judgments with artificial intelligence models to improve transaction accuracy. The authors have implemented a composite stock price prediction model based on multi-layer training networks, which is more suitable for predicting future stock prices compared to traditional methods. This model starts from the time series of stock data and deeply integrates the characteristics of stocks with artificial intelligence. The deep training sub-model is a combination of machine learning models and traditional statistical methods. This unique design cleverly solves the one-sidedness of machine learning methods and the petrification of classical financial methods. Through comparative experiments on multiple prediction models within the same time period, the model proposed in this paper has been proven to be the most effective model.
Research on Stock Index Prediction Model Based on Deep Reinforcement Learning
Authors: Yu Chuanwei , Zhang Liang
Published: March 2024

Stock market prediction and trading strategies have been extensively studied in finance and AI. Due to market volatility, it’s challenging for investors to achieve high returns. To address this, we explore deep reinforcement learning using LSTM-DQN and FC-DQN models for stock trading. LSTM-DQN combines Recurrent Neural Networks and Q-learning to capture stock data patterns, while FC-DQN uses a fully connected neural network. After applying discrete wavelet transform to the raw stock data for denoising and smoothing purposes, experiments were conducted. When comparing these two models in terms of accuracy and cumulative returns, the LSTM-DQN model outperforms the FC-DQN model. It’s evident that the LSTM-DQN model generates greater profits in terms of investment returns, making it a more suitable choice for investors. Finally, this paper conducts an analysis and discussion of the experimental results.
Empirical Evaluation of a YOLOv5 Model Enhanced with Deformable Convolution for Real-Time Cigarette Quality Inspection
Authors: Yu Jing , Liu Yingbo , Peng Yong , Yu Qian , Wu Shichao , Gong Yunyu
Published: March 2024

In the domain of cigarette manufacturing, traditional methods for inspecting product appearance quality have relied on conventional image-processing techniques and human judgment, both of which exhibit limitations in identifying optimizing detection efficiency and mitigating human-induced variability. To overcome these challenges, our research employs a technologically advanced approach that utilizes a modified YOLOv5 model integrated with deformable convolution layers. This architectural enhancement enables the neural network to dynamically adapt to defects across various scales in cigarettes, resulting in a 1.4% improvement in mAP@0.5:0.95 compared to the baseline YOLOv5 model and achieves up to a 7.3% accuracy improvement for the defects of warped edge in real-world cigarette datasets. By training on an extensive defect dataset, the improved model not only increases detection accuracy but also possesses the capability to identify previously unnoticed imperfections, thereby offering a robust technical solution for stringent quality control in cigarette production.
Machine Learning Approach to the Classification of Tensiometric Blood Test Results for Chronic Heart Failure Diagnosis
Authors: Alqezweeni Mohie M. , Gribkov Dmitry N. , Gorbachenko Vladimir I. , Potapov Vladimir V. , Miltykh Ilia , Zenin Oleg
Published: March 2024

Early diagnosis of chronic heart failure (CHF) is an urgent task in modern medicine. Previously, the authors presented the results of early diagnosis of CHF using neural network classification of static characteristics of plasma and serum. This article aims to solve the problem of classifying the dynamic characteristics of a tensiometric study of the liquid part (plasma and serum) of blood by classifying multidimensional time series. For training the neural network, a database of results of tensiometric studies of the liquid part of the blood (plasma and serum) of healthy volunteers and people suffering from CHF was used in the form of Excel tables containing data on the values of surface tension and dilatational viscoelasticity, which characterize viscoelastic properties of surface (interfacial) layers. Baseline data also included the sex and age of the patient. The problem of classifying time series, which arises when analyzing the results of tensiometric analysis, is solved. For the classification of time series, it is proposed to use a neural network. An analysis of neural network methods for classifying time series has been carried out. Using the Keras library, a recurrent neural network was implemented, which ensured a classification accuracy of 99%. The presented approach has demonstrated better performance in terms of accuracy compared to the existing machine learning approaches. The use of the developed neural network model in medical practice will significantly increase the reliability of diagnosing CHF. In addition, the results of the study indicate the possibility of upgrading tensiometers by eliminating the technical elements that provide forced oscillations of the drop, which will significantly reduce the cost of the device and reduce the time of the experiment.
Anti-attack algorithm of cloud storage attribute base based on dynamic authorized access
Authors: Zhao Xixi , Gu Liang , Duan Xiaorong , Wang Liguo , Li Zhenxi
Published: March 2024

Cloud storage attribute libraries usually store a large amount of sensitive data such as personal information and trade secrets. Attackers adopt diverse and complex attack methods to target the cloud storage attribute database, which makes the defense work more challenging. In order to realize the secure storage of information, an attribute based cloud storage anti-attack algorithm based on dynamic authorization access is proposed. According to the characteristic variables of the sample, the data correlation matrix is calculated, and the principal component analysis method is adopted to reduce the dimension of the data, build the anti-attack code model, simulate the dynamic authorization access rights, and calculate the packet loss rate according to the anti-attack flow. Design the initialization stage, cluster stage and cluster center update stage to realize the attack prevention of cloud storage attribute database. The experimental results show that the proposed algorithm can accurately classify the anti-attack code, has good packet processing ability, relatively short page request time, and anti-attack success rate is higher than 90%, which can effectively ensure the stability of the algorithm.
A hybrid short-term load forecasting method using CEEMDAN-RCMSE and improved BiLSTM error correction
Authors: Ning Yi , Liu Meiyu , Guo Xifeng , Liu Zhiyong , Wang Xinlu
Published: March 2024

Accurate load forecasting is an important issue for safe and economic operation of power system. However, load data often has strong non-stationarity, nonlinearity and randomness, which increases the difficulty of load forecasting. To improve the prediction accuracy, a hybrid short-term load forecasting method using load feature extraction based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and refined composite multi-scale entropy (RCMSE) and improved bidirectional long short time memory (BiLSTM) error correction is proposed. Firstly, CEEMDAN is used to separate the detailed information and trend information of the original load series, RCMSE is used to reconstruct the feature information, and Spearman is used to screen the features. Secondly, an improved butterfly optimization algorithm (IBOA) is proposed to optimize BiLSTM, and the reconstructed components are predicted respectively. Finally, an error correction model is constructed to mine the hidden information contained in error sequence. The experimental results show that the MAE, MAPE and RMSE of the proposed method are 645 kW, 0.96% and 827.3 kW respectively, and MAPE is improved by about 10% compared with other hybrid models. Therefore, the proposed method can overcome the problem of inaccurate prediction caused by data and inherent defects of models and improve the prediction accuracy.
Advanced CoCoSo method for uncertain MAGDM: Evaluating college students’ entrepreneurial skills
Authors: Li Lijun , Xiao Zhuolin
Published: March 2024

With the in-depth implementation of the innovative development-driven strategy of “mass innovation and entrepreneurship” put forward by the state, colleges and universities, as the main positions for cultivating innovative and entrepreneurial talents, have set up a multi-level and all-round training system for college students’ innovative and entrepreneurial ability according to the relevant policies and implementation opinions of the state for deepening innovation and entrepreneurship education in colleges and universities, and actively promoted the improvement of college students’ innovative and entrepreneurial ability. The college students’ innovation and entrepreneurship ability evaluation could be regarded as the classical multiple attribute group decision making (MAGDM) issue. The PULTSs could well depict uncertain information during the college students’ innovation and entrepreneurship ability evaluation and the combined compromise solution (CoCoSo) method is appropriate to stable the decision-making results. In this paper, the probabilistic uncertain linguistic combined compromise solution (PUL-CoCoSo) method based on the probabilistic uncertain linguistic sets (PULTSs) and combined compromise solution method is proposed for multiple attribute group decision making (MAGDM). The weights of attribute based on the CRITIC method are obtained under PULTSs. Finally, an application related to the college students’ innovation and entrepreneurship ability evaluation is utilized to demonstrate the usage of the developed algorithms.
The Fourier approach and testing for cointegration in LSTAR model
Authors: Sedefoğlu Gülşah , Güriş Burak
Published: March 2024

This paper proposes a new logistic smooth transition autoregressive (LSTAR) cointegration test by combining the Fourier function to catch the structural changes that occur over time and the LSTAR model to consider the nonlinearity. Logistic and exponential functions are the main transition functions defining the nonlinearity in STAR models since the exponential smooth transition autoregressive (ESTAR) and LSTAR models can explain the different structures of economic variables. The Fourier approach is a simple and effective way to model the structural changes in time series as an alternative to dummy variables. The most significant advantage of the method is that it does not require prior knowledge about the date, number of breaks, or forms. Monte Carlo simulation results show that the proposed test has good size and power properties for different sample sizes and parameters. The results also revealed that the power performance of the proposed test and the Fourier ESTAR test offered by Güriş and Sedefoğlu (2022) are close to each other. The steps of the Fourier-based tests are illustrated by providing an empirical example of testing the validity of the purchasing power parity (PPP) hypothesis in Türkiye.
A validity test for a multivariate linear measurement error model
Authors: Kukush Alexander , Mandel Igor
Published: March 2024

A criterion is proposed for testing the hypothesis about the nature of the error variance in the dependent variable in a linear model, which separates correctly and incorrectly specified models. In the former one, only the measurement errors determine the variance (i.e., the dependent variable is correctly explained by the independent ones, up to measurement errors), while the latter model lacks some independent covariates (or has a nonlinear structure). The proposed MEMV (Measurement Error Model Validity) test checks the validity of the model when both dependent and independent covariates are measured with errors. The criterion has an asymptotic character, but numerical simulations outlined approximate boundaries where estimates make sense. A practical example of the test’s implementation is discussed in detail – it shows the test’s ability to detect wrong specifications even in seemingly perfect models. Estimations of the errors due to the omission of the variables in the model are provided in the simulation study. The relation between measurement errors and model specification has not been studied earlier, and the proposed criterion may stimulate future research in this important area.
Factors influencing blood tumor marker concentrations in the absence of neoplasia
Authors: Trapé Jaume , Fernández-Galán Esther , Auge Josep Maria , Carbonell-Prat Marina , Filella Xavier , Miró-Cañís Sílvia , González-Fernández Carolina ,   on behalf of Oncology Biomarkers Section of the Catalan Association of Clinical Laboratory Science
Published: March 2024

BACKGROUND:

Tumor markers (TMs) are a heterogeneous group of molecules used in the diagnosis, prognosis and follow-up of cancer patients. During neoplastic differentiation, cells can either directly synthesize or induce the synthesis of TMs, and the release of these molecules into the bloodstream allows their quantification in biological fluids. Although very small concentrations of TMs are usually present in the serum or plasma of healthy subjects, increased concentrations may also be found in the presence of benign diseases or due to technical interference, producing false positive results.

MATERIAL AND METHODS AND RESULTS:

Our review analyses the causes of false positives described between January 1970 to February 2023 for the TMs most frequently used in clinical practice: α-fetoprotein (AFP), β2-microglobulin (β2-M), cancer antigen 15-3 (CA 15-3), cancer antigen CA 19-9 (CA 19-9), cancer antigen CA 72-4 (CA 72-4), cancer antigen 125 (CA 125), carcinoembryonic antigen (CEA), chromogranin A (CgA), choriogonadotropin (hCG), cytokeratin 19 fragment (CYFRA 21-1), neuron-specific enolase (NSE), human epididymis protein 4 (HE4), serum HER2 (sHER2), squamous cell carcinoma antigen (SCCA), protein induced by vitamin K absence-II (PIVKA-II), Pro-gastrin-releasing peptide (Pro-GRP), prostate-specific antigen (PSA), Protein S-100 (S-100) and thyroglobulin (Tg). A total of 247 references were included.

CONCLUSIONS:

A better understanding of pathophysiological processes and other conditions that affect the concentration of TMs might improve the interpretation of results and their clinical application.
Common Security Policy vs. Sovereignty
Authors: Mercz Mónika
Published: March 2024

In light of the recent war that thrust Europe into upheaval, taking a look at the European Union’s common security policy is of paramount importance. In my paper, I shall examine how essential state functions play a role in ensuring national security and sovereignty, while also taking part in the EU’s policies regarding this vital area of cooperation. My research focuses on what security entails on the level of the EU. In addition, I would like to explore what the boundaries of cooperation are, and how this policy was created. Of course, nations need each other in trying times, but does that leave no room for autonomous decisions? What are the limits, which allow no more freedom for state functions to take effect?
Enlargement Lesson from the Schengen Zone
Authors: Sigér Fruzsina
Published: March 2024

In this opinion article, we aim to draw a parallel between the enlargement of the Schengen area and of the European Union itself. We will argue that both processes suffer from enlargement fatigue, and some of the impeding factors are identical.
FaceScan: Unmasking Identity Beyond the Surface
Authors: Gupta Atul A. , Bhavsar Khushbu , Tekwani Dhrashti C. , Jenna Deepak , Soni Kanishka , Vaghela Rajdipsinh
Published: March 2024

Biometrics, focusing on human behavior and features, encompasses face recognition as a vital technique. This paper offers a survey of face recognition methods, analyzing algorithms and approaches. Face recognition, crucial for security, is explored, emphasizing its computer-based recognition mechanisms. The paper provides an overview of face recognition methodology, recent techniques, and their efficacy under various conditions. Investigating potential biases in current deep learning systems, particularly towards children, reveals performance disparities. Strategies to mitigate this bias are evaluated, identifying effective fusion techniques. Recent advancements in face recognition, fueled by technological progress, have made automated systems practical and widely applicable. This review assesses the strengths, weaknesses, and current/future applications of face recognition technology, including IBM's system and its domains of application.
ЗАРУБІЖНИЙ ДОСВІД ЗДІЙСНЕННЯ ДЕРЖАВНОГО НАГЛЯДУ (КОНТРОЛЮ) ЗА БЕЗПЕКОЮ НА АВТОМОБІЛЬНОМУ ТРАНСПОРТІ ЗАГАЛЬНОГО КОРИСТУВАННЯ
Authors: ГРИБАН М.М.
Published: March 2024

У статті наголошено на тому, що в більшості провідних держав світу функціонують досить ефективні системи державного нагляду (контролю) за безпекою на автомобільному транспорті загального користування. Акцентовано увагу на необхідності вдосконалення напрямку безпеки на автомобільному транспорті загального користування в ході співпраці країн-учасниць Східного партнерства Європейського Союзу, розробки відповідних напрямків міжнародного співробітництва та спільних проєктів, у тому числі наукових ініціатив та програм задля налагодження спільних досліджень проблем транспортної безпеки, надання грантів та стипендій для підтримки дослідницьких проєктів.Наголошено на необхідності функціонування в Україні органу подібного до Французького агентства з фінансування транспортної інфраструктури, яке є національним державним органом, місія якого полягає в тому, щоб від імені держави сприяти фінансуванню великих проектів транспортної інфраструктури та мобільності, дотримуючись при цьому цілей сталого розвитку.
ЗАРУБІЖНИЙ ДОСВІД РЕАЛІЗАЦІЇ ОКРЕМИХ ЕЛЕМЕНТІВ ПЕРЕХІДНОГО ПРАВОСУДДЯ В КОНТЕКСТІ КРИМІНОЛОГІЧНОГО ЗАБЕЗПЕЧЕННЯ ДЕОКУПАЦІЇ ТЕРИТОРІЇ УКРАЇНИ
Authors: ЛУЦЕНКО Б.Г
Published: March 2024

Стаття присвячена дослідженню окремих елементів перехідного правосуддя повоєнного періоду, що застосовувалися іноземними державами для подолання наслідків конфліктів та вчинених правопорушень з метою досягнення примирення у суспільстві та недопущення повторення конфлікту та правопорушень у майбутньому. В контексті питання притягнення винних до відповідальності проаналізовано досвід подолання наслідків режиму воєнної диктатури Аргентини, в якому одну з провідних ролей на шляху до примирення відведено аргентинському суспільству. Аналіз Боснійського досвіду свідчить про ранні заходи зі сфери правосуддя перехідного періоду за участю міжнародних організацій, які сталися вже під час війни. Відшкодування шкоди постраждалим від конфлікту, як складової перехідного правосуддя, розглянуто на досвіді Республіки Чилі, яким доволі вдало використано широкий спектр репараційних заходів щодо різних категорій осіб, визнаних жертвами правопорушень. В результаті аналізу міжнародного досвіду застосування окремих елементів перехідного правосуддя окреслені ризики та перспективи для українського сценарію перехідного правосуддя.
Traumatic Ulcer Associated with Iatrogenic Trauma After Basal Cell Adenoma Surgery
Authors: Siregar Fitri Dona , Setiadhi Riani
Published: March 2024

Traumatic ulcer is an oral cavity lesion characterized by loss of epithelial lining, reaching the lamina propria. This condition presents a single lesion with irregular borders, surrounded by diffuse erythema, and covered with pseudo-membrane. In specific case, the traumatic ulcer was caused by iatrogenic trauma after basal cell adenoma surgery. This case report aimed to discuss the causes of traumatic ulcer. A 39-year-old female was referred to the Oral Medicine Clinic from the Ear, Nose, and Throat Department, complaining of pain in the oral mucosa after basal cell adenoma surgery. On extraoral examination, the facial symmetry was intact along with dry and exfoliative lips. A solitary, oval, yellowish-white intraoral ulcer covered with pseudomembrane, irregular borders surrounded by diffuse erythema on the palate, left buccal mucosa and upper labial mucosa was present. The patient was diagnosed with traumatic ulcer due to iatrogenic trauma after surgery for basal cell adenoma located within the parotid gland that extended to the left palate. The treatment administered comprised instructions to clean the oral cavity using gauze and a cotton stick soaked in 0.2% chlorhexidine gluconate. Additionally, compressing the affected areas with gauze soaked in 0.9% NaCl and applying a thin coating of Vaseline album on the lips were part of the therapeutic measures. Given the iatrogenic nature of traumatic cancer, comprehensive therapy was considered essential to prevent secondary infection and address issues related to speech, appearance, and masticatory functions.
Parental Knowledge, Attitude, and Practice towards Dental Care Visits for Children 6-12 Years of Age during the Covid-19 Pandemic Period
Authors: Octiara Essie , Rizky Agneschita
Published: March 2024

Covid-19 is an infectious disease that is growing rapidly throughout the world. Dental care carries a risk of infection, as the procedure involves face-to-face communication with the patient, exposure to saliva, blood, other body fluids and the use of sharp instruments. Parents are afraid to take their children to visit the dentist because it will affect the child's oral and dental health. The aim of this study was to examine the relationship between parents' knowledge, attitudes and practices regarding children's dental care visits during the Covid-19 pandemic and parents' age and education level. Descriptive research with a cross-sectional design. The research subjects were 106 parents of children aged 6-12 years. Sampling was taken using the interview method with 11 questions. Analysis using Chi square. Research results: 26.4% of parents from the 30-39 year age group stated that dental care could cause children to be infected with the Covid-19 virus (p<0.05), based on the level of knowledge, parents with a postgraduate level of knowledge answered that dental care could cause 19.8% of children were infected with the Covid virus (p<0.05). There were no differences in parental attitudes based on age and parental education level in taking their children to the dentist (p>0.05). It was concluded that there was no relationship between age and parents' level of knowledge regarding children's dental care visits during the Covid-19 pandemic.
The Study of Erosion on Varoious Land Use in Paluh Besar Sub Watershed Using Geographic Information System
Authors: Tarigan Sepriadi , Nasution Delima Lailan Sari
Published: March 2024

Erosion could be a sign of natural resources damage. It’s important to prevent the erosion that had to predict in each land cover to sustainability of natural resources. This study aimed to predict the erosion value in each land cover unit using Universal Soil Loss Equation (USLE) Method with Geographic Information System. The study showed that the highest erosion occurs in residential area which valued 138.11 ton/ha/year and the lowest occur in pond that valued 0.3 ton/ha/year. The highest erosion hazard level occur in residential area that classify moderate (III) and the lowest erosion hazard level is pond that classify low hazard level (I).
Navigating Legal Awareness in the Digital Era: Cultivating A Digital Culture in Indonesia
Authors: Hafizhah Annisa
Published: March 2024

This research investigates the various impacts of digital transformation on legal culture and societal norms in present-day Indonesia. By examining the convergence of legal changes, technological progress, and cultural shifts, the study underscores the significance of maintaining traditional values in the face of rapid digital advancements. Emphasizing the importance of legal literacy, the paper advocates for innovative educational initiatives, such as those utilizing film and podcasts, to improve public comprehension of legal concepts. The analysis highlights the careful equilibrium needed for Indonesia to embrace digital culture while preserving its diverse cultural legacy.
Implementation of the State of Law Principles from the Constitutional Law Perspective: A Case Study of Legislative Aspects in Law Enforcement in Indonesia
Authors: Pakpahan Zainal Abidin , Yasmin Ananda Sabillah , Safitri Indri Tiya , Nainggolan Elian S Christoper , Nasution Thorique Akbar Maulana
Published: March 2024

The Fourth Amendment to the 1945 Constitution of the Republic of Indonesia, enacted in 2002, officially established the concept of the State of Law, or "Rechtsstaat," which was previously only mentioned in the Explanation of the 1945 Constitution. This concept was solidified in Article 1, paragraph (3), which states, "The State of Indonesia is a State of law." This study utilizes a normative legal research method, focusing on document analysis using various secondary data sources such as legal literature, court decisions, legal doctrines, and expert opinions. The research's analysis centers on the implementation of the rule of law principles within the constitutional framework, with a specific focus on legislation and law enforcement in Indonesia, particularly in the legislative domain. Despite efforts to reform legislation, there are still deficiencies in the legislative process that may hinder the effective implementation of the rule of law principles. Some challenges include inconsistencies in laws, the intricate nature of the legislative process, and potential political interventions that could compromise the independence of legislative bodies.
The Relationship between Knowledge and Attitude with Behavior of Preventing Leptospirosis in Healthcare Workers at the Binjai City
Authors: Hanalena Yolanda , Mayasari Evita
Published: March 2024

Leptospirosis is an infectious disease caused by spirochete from the genus Leptospira, namely Leptospira interrogans which is pathogenic for both humans and animals. L. interrogans infection is often associated with flooding, where L. interrogans is carried from soil contaminated with animal urine reservoirs and settles in water. Leptospirosis is estimated to cause 1030000 cases and 58900 deaths annually worldwide. Until now, Leptospirosis is still a threat to public health because it causes Extraordinary Events (KLB) in several regions in Indonesia. Leptospirosis outbreaks are related to the presence of risk factors, namely the high population of rats as reservoirs of Leptospira spp., poor environmental sanitation, and the increasing number of flood areas in Indonesia. The purpose of this study was to determine the relationship between knowledge and attitude with the behavior of preventing Leptospirosis in healthcare workers at the Sub-District Health Center, Binjai Timur, Binjai City, against Leptospirosis. This research is an analytic study with a cross sectional design. The research was conducted using a questionnaire instrument of knowledge level about Leptospirosis, attitudes towards Leptospirosis, and preventive behavior towards Leptospirosis.
Identification Of Acanthamoeba spp. In Used Contact Lens Solution
Authors: Chan Michelle , Saputri Dewi
Published: March 2024

Contact lenses are the most popular devices used by many people around the world for vision correction, aesthetics, and therapeutic purposes. Poor contact lens hygiene can cause various complications. One of the concerns regarding the use of contact lenses is the presence of Acanthamoeba spp. Acanthamoeba spp. is a free-living amoeba that can be found in many places including untreated fresh water, treated fresh water and unconventional water sources. One of the complications caused by Acanthamoeba spp. is Acanthamoeba keratitis which is an eye infection that is often caused by the use of contact lenses and contaminated contact lens solutions. Objective. The purpose of this study is to determine the description of Acanthamoeba spp. found in contact lens solution and contact lens care of Universitas Sumatera Utara students. Method. This study used univariate analysis. Data were obtained from the results of contact lens solution examination and questionnaire interviews. Result. Most of the samples (98%) did not have Acanthamoeba spp. Some respondents (60.8%) had fairly clean contact lens care behaviour and the rest (39.2%) had very clean contact lens care behaviour. Conclusion. One sample was found positive with Acanthamoeba spp. The positive sample had Acanthamoeba spp. cyst. Contact lens care was generally done well.
Breast Cancer Clinicopathology based on Neutrophil Levels at Adam Malik Hospital Medan in 2018-2021
Authors: Mario Saragih Tonggo , Hermansyah Dedy , Rifsal Siregar Denny , Aprillia Ariestine Dina
Published: March 2024

Introduction: Breast cancer is the most frequently diagnosed cancer in the world. Breast cancer occurs due to abnormal cell growth in breast tissue so that it becomes malignant. In Indonesia, breast cancer is the most common cancer in women. That way, many markers are needed as prognostic and predictive of breast cancer. One of the prognostic factors for breast cancer is neutrophil levels combined with clinicopathological factors. Objective: Knowing the clinicopathology of breast cancer based on neutrophil levels at the Haji Adam Malik Medan General Hospital in 2018-2021. Methods: The research design is observational with a descriptive method and calculated using the Lemeshow formula. Results: Majority aged 40-49 years (39.6%), high school (44.8%), housewives (67.7%), no family history (97.9%), tumor grade II (38.5%) %), Tumor Infiltrating Lymphocytes (TILs) severe (47.9 %), mitotic score 1 (38.5 %), metastatic positive lymph node status (87.5 %), tumor size T1 (36.5 %), The number of positive and negative Estrogen Receptors is the same (50.0%), Progesterone Receptor is negative (56.3%), HER2 is 1+ (60.4%), Ki-67 is positive (84 .4 %), positive angioinvasion (63.5 %), Invasive Ductal Carcinoma (90.6 %), high neutrophil levels (77.1 %). Conclusion: High levels of neutrophils tend to result in severe Tumor Infiltrating Lymphocytes (TILs) which will increase tumor growth, occurrence of metastases, increased positive angioinvasion, negative Estrogen Receptor status, negative Progesterone Receptor status, HER2 1+ status, positive Ki-67 status.
Herbal Therapies in Cancer Patients: Managing Side Effects and Improving Quality of Life
Authors: Anand Keshav , Kaur Massaon Harpreet , Prabhakar P. K.
Published: March 2024

Introduction: This comprehensive review explores the role of herbal therapies in managing the side effects of cancer treatments and enhancing the quality of life for cancer patients. As conventional cancer treatments often induce a myriad of adverse effects, ranging from nausea and fatigue to pain and emotional distress, the integration of herbal therapies has gained attention as a potential complementary approach. Methods: The review synthesizes existing literature, drawing upon both preclinical and clinical studies, to evaluate the efficacy and safety of various herbs in alleviating common side effects associated with cancer therapies. Special emphasis is placed on the potential benefits of herbal interventions in addressing physical symptoms, such as nausea and pain, as well as psychological and emotional challenges faced by cancer patients. Furthermore, the review explores the mechanisms of action behind these herbal interventions and potential synergies with conventional treatments. Insights into patient perspectives and experiences with herbal therapies contribute to a holistic understanding of their impact on overall well-being. Conclusion: By providing a critical analysis of the current state of knowledge, this review aims to guide healthcare professionals, researchers, and patients in making informed decisions regarding the integration of herbal therapies into cancer care, ultimately improving the supportive care and quality of life for individuals undergoing cancer treatment.