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Clinical and radiographic assessment of the association between orthodontic mini-screws and periodontal health
No full textObjectives: Proper anchorage control is crucial for predictable tooth movement and preventing inadequate torque during orthodontic treatment. Through clinical and radiographic parameters; this study assesses the association between mini-screws and periodontal health.
Materials and methods: A prospective observational study included 16 systemically healthy non-smoking individuals requiring mini-screws. Mini-screws with a rough, titanium oxide-coated surface were placed. Periodontal assessments (Plaque index, gingival index, probing pocket depth, gingival recession, bleeding on probing, mucosal discomfort, mucosal redness, keratinized tissue width, supracrestal tissue height, and transmucosal soft tissue thickness) were performed at 2nd week and 3 months post-placement. Radiographic evaluations measured distances between mini-screws and adjacent teeth using Image J software.
Results: The study included 13 females and 3 males (mean age 21.9 ± 1.8 years) with 24 mini-screws. Early mini-screw loss was not observed. Significant reductions in site-level Gingival Index and bleeding on probing (p < 0.05) and full-mouth bleeding on probing (p < 0.05) were noted over time. Absence of significant differences was found in mucosal discomfort and redness, keratinized tissue width, or transmucosal soft tissue thickness, but supracrestal tissue height decreased significantly (p < 0.05). Radiographically, significant bone reduction around mini-screws was observed at 3 months, with torque gauge values significantly decreased as well (p < 0.05).
Conclusions: Orthodontic mini-screws can be effectively utilized in orthodontic treatment with proper planning and monitoring. While improvements in gingival health were observed with targeted oral care, the study underscores the need for careful consideration of potential risks to periodontal tissues, such as reductions in supracrestal tissue height and bone levels. A balanced approach that integrates preventive strategies with precise screw placement is essential to maximize the benefits of mini-screws while minimizing potential periodontal complications.
Clinical relevance: While proper oral hygiene can help control inflammation around mini-screw sites, clinicians must also be mindful of potential risks, such as reductions in bone levels and tissue height. Careful patient selection, precise placement, and regular follow-up are crucial to ensure the stability of mini-screws' stability and to prevent complications, ultimately contributing to better treatment outcomes in orthodontic care.
Trial registration: This study was registered on ClinicalTrials.gov with the registration number NCT06491849 on June 28, 2024
Adaptive lossy color image compression system based on hybrid algorithm
No full textAs the digital age progresses, multimedia technologies have become commonplace, with users expecting high-quality audio, video, and image content across various platforms and devices. As a result, the quantity of data produced by these multimedia programs has grown substantially. Also, the explosive growth in the use of multimedia has led to a rise in the quantity of images that are used and created, which creates challenges, in relation to the requirement for increased storage capacity and enhanced data transport speed. To address these challenges, image compression has emerged as a critical solution by decreasing the volume of the image without significantly degrading their quality. As technology advances further, the need for more image compression techniques will become more important. This paper presents a hybrid lossy image compression system by using four compression techniques which are Bit plane slicing, Discrete wavelet transform (DWT), Discrete cosine transform (DCT), and Arithmetic coding. To implement this proposed method three experiments were performed by using images of varying dimensions, namely (256 * 256), (512 * 512), and (1024 * 1024) and four different quantization coefficients. For efficiency performance measurement of the proposed system, three metrics were used: Peak signal-to-noise ratio (PSNR), Structural similarity index (SSIM), and compression ratio (CR). The results showed that the proposed hybrid system was successful in raising the compression ratio in comparison with standard JPEG as the CR when using jpeg reached 35%, while the suggested system provided a higher CR of 62% with keeping a satisfactory level of image quality
Evaluating machine learning algorithms for early detection of GDM
No full textThrough the use of the Gestational Diabetes Mellitus (GDM) Data Set, this research conducts an in-depth analysis of machine learning methods for the early diagnosis of GDM. The effectiveness of various algorithms is evaluated by the use of metrics such as recall, accuracy, precision, and F1 score. There are several algorithms that fall under this category, such as Logistic Regression, Long Short-Term Memory (LSTM), Gradient Boosting Classifier, Random Forest, and K-Nearest Neighbors. It is necessary to do meticulous data preparation in order to find the best models for GDM prediction. Some examples of this preparation include feature scaling and principal component analysis (PCA). Should this research prove to be effective, it has the potential to provide insight on how machine learning may be used to enhance the diagnosis and management of GDM
RETRACTED: Cancer detection using deep learning techniques (Retracted Article)
No full textBreast cancer has become the most common form of cancer in world recently having overtaken cervical cancer in urban cities. Immense research has been carried out on breast cancer and several automated machines for detection have been formed, however, they are far from perfection and medical assessments need more reliable services. Computer Assisted Diagnostics programs have been developed over the past 2 decades to help radiologists interpret mammogram screening. Deep convolutional neural networks (CNN), which have surpassed human output since 2012, have been an immense success in image recognition. Deep CNNs will revolutionize the analysis of medical images. We propose a method for breast cancer detection based on Faster R-CNN, the most common frameworks for object detection. In a non-human interference mammogram, the device detects and categorizes malignant or benign lesions. The method proposed sets the current status of the INbreast database public classification scheme, AUC = 0.95. In the digital mammography challenge DREAM with AUC = 0.85, the method mentioned here was second. When the device is used as a sensor, the accuracy of the INbreast data set is extremely low with very false positive image points
Exploring free amino acid profiles in Crimean-Congo hemorrhagic fever patients: Implications for disease progression
No full textThis study investigated the intricate interplay between Crimean-Congo hemorrhagic fever virus infection and alterations in amino acid metabolism. The primary aim is to elucidate the impact of Crimean-Congo hemorrhagic fever (CCHF) on specific amino acid concentrations and identify potential metabolic markers associated with viral infection. One hundred ninety individuals participated in this study, comprising 115 CCHF patients, 30 CCHF negative patients, and 45 healthy controls. Liquid chromatography-tandem mass spectrometry techniques were employed to quantify amino acid concentrations. The amino acid metabolic profiles in CCHF patients exhibit substantial distinctions from those in the control group. Patients highlight distinct metabolic reprogramming, notably characterized by arginine, histidine, taurine, glutamic acid, and glutamine metabolism shifts. These changes have been associated with the underlying molecular mechanisms of the disease. Exploring novel therapeutic and diagnostic strategies addressing specific amino acids may offer potential means to mitigate the severity of the disease.Research Fund of Erciyes University; [TSG-2021-10912]This study was supported by the Research Fund of Erciyes University (TSG-2021-10912). The funders had no role in study design, data collection and analysis, publication decisions, or manuscript preparation
The quality and content analysis of YouTube videos about chemotherapy for children
No full textPurpose: This study undertook a systematic examination of YouTube videos about chemotherapy for pediatric patients, with a primary focus on assessing the videos' quality, content, and reliability.Method: The research was conducted by searching YouTube using the keywords "chemotherapy for children" and "chemotherapy for pediatric," employing filters for "worldwide" and "all categories." The top 100 videos, based on popularity, were selected for evaluation according to the power analysis calculation. Two independent experts in pediatric oncology reviewed these videos. Video characteristics were recorded: length, view count, likes, dislikes, view ratio, and video-like ratio. The Video Power Index was calculated to measure video popularity. The modified DISCERN and Global Quality Scale (GQS) assessed the videos for quality and reliability.Results: The 100 videos were analyzed. Official health institutions uploaded 54%, while independent users contributed 46%. Independent user uploads garnered significantly more views than official health institutions (p = .006). The number of likes, view ratio, and Video Power Index of independent users' videos were significantly higher than official health institutions' videos (respectively, p = .007, .007, and .008). On the other hand, the modified DISCERN score and GQS were significantly higher in YouTube videos of official health institutions than in independent users (p < .001). A strong correlation was observed between the modified DISCERN score and GQS (r = .879, p < .001).Conclusion: This study provides valuable insights into the YouTube videos on pediatric chemotherapy, emphasizing the need to improve the quality and reliability of online health information for this vulnerable population
Enhancing facial recognition accuracy and efficiency through integrated CNN, PCA, and SVM techniques
No full textFacial recognition, as a paradigmatic instance of biometric identification, has witnessed escalating utilization across diverse domains, encompassing security, surveillance, human-computer interaction, and personalized user experiences. The fundamental premise underlying this technology resides in its capacity to extract discriminative features from facial images and subsequently classify them accurately. However, the precision and efficiency of such systems remain subject to an array of intricate challenges, necessitating innovative solutions. The overarching aim of this thesis is to enhance the performance and efficacy of facial recognition systems through the seamless integration of Convolutional Neural Networks (CNNs) for feature extraction, Principal Component Analysis (PCA) for dimensionality reduction, and Support Vector Machines (SVMs) for classification. This holistic approach seeks to optimize the accuracy, efficiency, and robustness of facial recognition, thereby contributing to the advancement of computer vision and biometric identification technologies
Köylerin aydınlanma mabedi: Köy enstitüleri
Get PDFTürkiye Cumhuriyeti’nin ilerici devrimlerinin sonucu olarak kurulan Köy Enstitülerinin
kuruluşu, katkıları ve dağıtılması konusu günümüzde de tartışma konusu olarak güncelliğini
koruyor. Köy Enstitüleri aniden ve spontane bir şekilde kurulmamıştır. Osmanlı
İmparatorluğu’nda yapılan Tanzimat Reformları dönemine kadar gidip çıkan tartışmaların
1930’lara, 1940’lara gelip çıkan ve pratiğe uygulanan bir sonucu olmuştur. Cumhuriyet
kurulduktan sonra yapılan 1923 İzmir İktisat Kongresi kararlarında kökleri, 1936 yılında
kurulan Köy Eğitmen Kursları ile birlikte ilk adımları atılmıştır. Köy Enstitülerinin
kurulmasındakı başlıca sebep, Kurtuluş Savaşı’ndan sonra ekonomik olarak çökmüş devletin
yeniden ayağa kaldırılması ve bunun için de yoksul köylülere okuma-yazma götürülmesinin
amaçlanması olmuştur. Köy Enstitüleri bilgiyi bir araç olarak benimseyerek köylülere
sadece yeni devrimci düşünceleri değil, eğitimi, laikliği, demokrasiyi, yönetme inisyatifini
de taşımıştır. Köy Enstitüleri, zihni emekle kol emeğinin, yani teori ile pratiğin sentezinin
can bulmuş hali olmuştur. Bu tezin amacı Köy Enstitülerinin kuruluşu, onu yaratan
konjonktürleri, dağıtılması ve daha sonrasında Türkiye’ye etkilerini araştırmaktır. Bu
çalışmanın çıkış noktası temel olarak şu soruyla ifade edilebilir: Köy Enstitüleri, köylerin
kalkınmasına nasıl katkıda bulunmuştur. Bu çalışmada, bu argümanları desteklemek için
tarihi belgeler, istatistikler, anılar ve röportajlar gibi çeşitli kaynaklardan yararlanılacaktır
A robust hybrid control model implementation for autonomous vehicles
No full textThis work presents a robust control strategy for controlling autonomous vehicles under various conditions. This approach makes use of two controllers to guarantee excellent performance and a few faults when the car is traveling. Model Predictive and Stanley based controller (MPS) is the name of the new control system. This combines the functionality of a Stanley controller with a model predictive controller. The suggested approach tries to address these issues and provides a high-performance control system. Utilizing the finest aspects of both controllers and attempting to improve the other, this hybrid approach to integrating two well-known controllers provides advantages. The MPS is put to the test on straight and curvy roads in a variety of scenarios for both path-following and vehicle control. This controller has demonstrated excellent performance and adaptability to handle various autonomous driving conditions. When the findings are compared to earlier controller kinds, the suggested system performs better
Kronik migren tedavisinde tekrarlanan botulinum toksin enjeksiyonunun yıpranma payı (wear-off fenomeni): Retrospektif çalışma
No full textObjectives: This study aimed to evaluate the efficacy, predictors of response, clinical considerations, and analysis of patient-reported wear-off events during injection periods of onabotulinumtoxinA (Onabot-A). Patients and methods: This retrospective study was conducted with 30 adult chronic migraine patients (26 females, 4 males; mean age: 37.9±9.3 years; range, 24 to 72 years) followed between January 2017 and December 2022. All patients received Onabot-A injections at different frequencies throughout their treatment and responded to Onabot-A. The duration between cycles was 3 months in 26 patients, and this period varied in four patients. The Visual Analog Scale scores were measured before and after the injection, all patients responded to Onabot-A. Results: Nine patients stated that they experienced wear-off at least once during their treatment cycles. In some patients, the duration of action lasted less than 12 weeks, resulting in a wear-off phenomenon. Although sex and age were not significant variables in terms of the presence or absence of wear-off phenomenon, the number of Onabot-A injections (Onabot-A treatment cycles) among patients was found to be a statistically significant variable in terms of the presence of wear-off (p<0.011). Conclusion: Repeated treatments using Onabot-A appear to be safe and well-tolerated, but the effectiveness of the drug appears to be affected by wear-off phases that may occur during long-term treatment with Onabot-A