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Seismic Foresight: A Novel Multi-Input 1D Convolutional Mixer Model for Earthquake Prediction Using Ionospheric Signals
No full textThis study proposes a novel deep learning approach for predicting significant earthquakes (Mw ≥ 5.0) in Turkey using ionospheric Total Electron Content (TEC) data and space weather indices. ConvMixer is a lightweight CNN architecture that blends spatial and channel information using depthwise convolutions and pointwise layers. Inspired by vision transformers, it offers efficient image classification with fewer parameters and high performance. We developed a multi-input one-dimensional convolutional mixer (MI-1D-ConvMixer) model to classify TEC data from the preceding five consecutive days as either precursory to an earthquake on the 6th day or normal. The model incorporates six inputs: five 1D TEC signals and one 1D space-weather index array, including the global geomagnetic index (Kp), storm duration distribution (Dst), sunspot number (R), geomagnetic storm index (Ap-index), solar wind speed (Vsw), and solar activity index (F10.7) are also utilized to reveal non-seismic related pre-earthquake ionospheric variations. Our methodology involves two stages: (1) a preprocessing stage to enhance TEC signals, and (2) an end-to-end training of the MI-1D-ConvMixer model. The model architecture features depth-wise and point-wise convolutions with patch embedding, utilizing four tunable variables: network depth, hidden dimension size, kernel size, and patch size. We used 196 earthquakes data from Turkey from 2010-2023, and TEC data from the TNPGN-Active GNSS stations. The dataset was split into 75% for training and 25% for testing. Performance metrics, including classification accuracy, sensitivity, specificity, and F1-score, are used for evaluation. Our model achieved a classification accuracy of 97.49%, demonstrating its potential for earthquake prediction systems. This research contributes to the field by introducing a novel deep learning architecture specifically designed for integrating TEC and space weather data for earthquake prediction. Future work should focus on validating the model’s performance in different geographical regions and investigating its limitations
International Compilation of Research and Studies in ECONOMİCS AND ADMINISTRATIVE SCIENCES
No full textDenetim Kalitesi ve Firma Değeri İlişkisi: Borsa İstanbul (BIST) İmalat Sektöründe Bir Uygulama
No full text
Predictive Factors for HBsAg Seroconversion Following Acute Hepatitis B Virus Infection: A Multicenter BUHASDER Study
No full textExperience with the effect of antiviral therapy on HBsAg seroconversion in acute hepatitis B is limited. We aimed to evaluate the factors affecting HBsAg seroconversion in patients with acute hepatitis B (AHB) receiving antiviral treatment. We performed a retrospective and multicenter study involving 107 adult patients who received antiviral treatment for AHB between January 2018 and December 2024. The median age was 48 (min-max, 18-91) years, and 66.3% of the patients were male; 70 patients with 24-week follow-up (15 patients without HBsAg seroconversion versus 55 patients with HBsAg seroconversion) were compared based on HBsAg seroconversion status. Multivariate logistic regression analysis revealed that age was independently associated with HBsAg seroconversion (odds ratio = 0.926; 95% confidence interval (CI) 0.874 to 0.981; p = 0.009). A one-year increase in age was associated with a 0.926-fold decrease in HBsAg seroconversion. In conclusion, age was an independent predictor of HBsAg seroconversion following acute hepatitis B virus infection
DENİZYOLU VE KIYI YAPILARINDA YENİ YAKLAŞIMLARIN ÇEVRESEL SÜRDÜRÜLEBİLİRLİK PERSPEKTİFİNDEN DEĞERLENDİRİLMESİ
No full textDenizyolu taşımacılığı ve kıyı yapıları, küresel deniz ticaretinin temel bileşenleri arasında yer almakta ve artan çevresel kaygılar sonucu IMO (Uluslararası Denizcilik Örgütü) ve AB (Avrupa Birliği)’nin yürürlüğe koyduğu sıkı emisyon tedbirleri doğrultusunda sürdürülebilirlik odaklı bir dönüşüm sürecine girmektedir. Bu çalışma, dünya genelinde denizyolu taşımacılığı ve liman faaliyetlerinde geliştirilen ve hayata geçirilen yeni yaklaşımları çevresel sürdürülebilirlik perspektifinden incelemeyi amaçlamaktadır. Özellikle farklı ülkeler, limanlar veya politikalar kıyaslanarak kavramsal ve karşılaştırılmalı literatür analizi sonucu güncel uygulamaların durum değerlendirmesi neticesinde, alternatif yakıtlar (LNG, metanol, amonyak vb.), dijitalleşme ve akıllı denizcilik uygulamaları, enerji verimliliği tedbirleri ile yeşil liman girişimlerinin çevresel sürdürülebilirliğin sağlanmasında kritik rol oynadığı tespit edilmiştir. Bununla birlikte, alternatif yakıtların arz güvenliği, yüksek yatırım maliyetleri ve metan kaçağı gibi sınırlılıklar ile dijital altyapı yatırımlarının özellikle gelişmekte olan ülkelerde yetersiz kalabileceği görülmüştür. Bulgular, sektörel dönüşümün yalnızca teknolojik yeniliklerle değil, aynı zamanda politika yapıcıların öngörülebilir düzenlemeleri, finansal teşvik mekanizmaları ve paydaşların ortak bir tavırla hareketi ile mümkün olabileceğini ortaya koymaktadır. Çalışma, denizcilik firmaları, liman otoriteleri ve politika yapıcılar için stratejik karar alma süreçlerinde yol gösterici nitelikte olup, çevresel sürdürülebilirlik hedeflerine yönelik bütüncül çözümlerin önemini vurgulamaktadır.</p
Bilateral cervical plexus block in a pediatric patient undergoing thyroglossal duct cyst excision.
No full textDose-Dependent Application of Silver Nanoparticles Modulates Growth, Physiochemicals, and Antioxidants in Chickpeas (Cicer arietinum) Exposed to Cadmium Stress
No full textThe present study was intended to investigate the effects of silver nanoparticles (Ag NPs) on chickpea plants grown in cadmium (Cd)-contaminated soil. Chickpea seeds sown in earthen pots (filled with soil) were subjected to Cd stress (100 mu M) in the form of CdCl2 (10 mL) 10 days after sowing (DAS). Exogenous applications with Ag NP concentrations 50, 100, and 200 mu M were used to observe their effects on Cd-stressed plants. Growth, biochemical, and stress parameters were studied. Results showed that Ag NPs positively affected plant growth and ameliorated the toxic effects of Cd stress. Plant height, fresh weight, dry weight, total carotenoid content, rubisco activity, and net photosynthetic rate (P N) were significantly decreased by Cd stress but enhanced by 28, 29, 31, 30, 33, and 35%, respectively, by foliar application of Ag NPs. Similarly, Ag NPs increased the activity of superoxide dismutase (61%), catalase (58%), and peroxidase (68%) and reduced the malondialdehyde (28%) and hydrogen peroxide (23%) in chickpea plants. Protein content was also increased by the application of Ag NPs (16%). Furthermore, the addition of Ag NPs decreased the plant Cd content. According to the current study, adding Ag NPs to plants under Cd stress improved their growth and photosynthesis by reducing Cd absorption and improving plant stress tolerance
New Horizons in Biomedical and Surgical Applications
No full textIn this study, NDIR (Non-Dispersive Infrared) sensor technology in the field of biomedical engineering is examined in detail according to the principle of infrared light absorption. Firstly, the structure and working principle of NDIR sensors and the relationship between IR light and gas detection are explained, then analog and digital sensor types are compared. Concentration calculation methods based on Beer-Lambert's law are analyzed both theoretically and practically. The effects on the accuracy and reproducibility of these approaches are discussed in detail. Its use in environmental monitoring, capnography, building automation, industrial security and IoT systems is supported by examples, especially in application areas. The study discusses in depth both the evolution and development of NDIR sensors and their potential. It also sheds light on current trends and market projections for the future of sensor technologies. The findings demonstrate this and the long-term, precise, reliable monitoring that NDIR sensors offer in the biomedical field.</p