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Intelligent Transportation Systems (ITS) first appeared in 1868 with traffic lights. With developing technology, the need to bring a smart approach to transportation applications within the scope of speed and environmental protection has emerged. Protecting ITS infrastructure against cyber attacks has become a matter of reputation for states. It is essential to provide the necessary technological infrastructure for the integrated operation of the systems used in ITS, especially geographical location, communication, and mapping. These technological developments bring cyber attacks, risks, and many dangers that should be avoided, especially on the systems used. This study examines ITS architecture, applications, communication technologies, and new trend technologies in detail. This study includes contributing to studies in the field of ITS and preventing attacks and incidents that may occur in terms of cyber security. The most important cyber attacks that may occur in ITS applications are included. In addition, the minimum security requirements that can be taken in ITS applications and infrastructures against these attacks are included.

Transportation has an essential place in societies and importance to people in terms of its social and economic aspects. Innovative rail systems need to be integrated with developing technologies for transportation. Systemic failures, personnel errors, sabotage, and cyber-attacks in the techniques used will cause a damaged corporate reputation and revenue losses. In this study, cybersecurity attack methods in smart rail systems were determined, and cyber events occurring worldwide through these technologies were analyzed. Risk analysis in terms of transportation safety in smart rail systems was determined by considering the opinions of 10 different experts along with the Analytic Hierarchical Process (AHP) performance criteria. Informatics experts were selected from a group of people with at least 5–15 years of experience. According to these risk analysis calculations, cybersecurity stood out as the most critical security risk at 27.74%. Other risky areas included physical security, calculated at 14.59%, operator errors at 16.20%, and environmental security at 10.93%.

The promotion of equity and access for all children to learn science is critical in early childhood settings. Considering the benefits of teaching science, technology, engineering, arts, and mathematics (STEAM), it is important that educators embed this pedagogy across early childhood settings. In order to promote access in inclusive early childhood settings that include young children from birth to 8 years of age with or without disabilities to STEAM pedagogy, educators need to be intentional about their practice. This article provides a four-step approach to using an intentional framework, universal design for learning (UDL), to plan for and implement STEAM pedagogy in the inclusive classroom. Practical implications are illustrated through examples of an early childhood educator and a child with autism in an inclusive urban education setting.

Background and Objectives: In this study, we investigated the frequency and type of second primary malignant tumors (SPMTs) accompanying gastrointestinal stromal tumors (GISTs), patient and tumor characteristics, and follow-up and survival data. Materials and Methods: We included 20 patients with SPMTs from a total of 103 patients with GISTs in a single center in Turkey. At the time of GIST diagnosis, patient age, sex, presentation symptoms, localization, pathological features of the tumor, stage, recurrence risk scoring for localized disease, treatments received, time of SPMT association, follow-up times, and survival analysis were recorded for each patient. Localization, histopathology, and stage of SPMT accompanying GISTs were also recorded accordingly. Results: SPMT was detected in 19.4% of patients with GISTs. Of the patients, 50% were men and 50% were women. The mean age at the time of diagnosis of GIST was 63.8 ± 10.81 years (range: 39–77 years). Of the GISTs, 60% were localized in the stomach, 25% in the small intestine, and 70% were at low risk. Of the SPMTs, 60% were in the gastrointestinal system. SPMTs were diagnosed as synchronous with GISTs in 50% of the patients. The mean follow-up period of the patients from the diagnosis of GIST was 45.6 (0.43–129.6) months. When the data were finalized, 5% died due to GIST, 35% died due to SPMT, and 15% died due to non-disease-related causes. Conclusions: SPMT was detected in 19.4% of patients with GISTs. GISTs were frequently located in the stomach, and most of them were at low risk. The most common SPMTs were gastrointestinal system tumors, and their coexistence was found to be synchronous. Most patients died due to SPMT during follow-up.

Preparation of bisbenzofuran-2-yl-methanone (1), the corresponding ketoxime 4, semicarbazone and thiosemicarbazone 3a and 3b, ether derivatives of the ketoximes 5a-j and the alcohol 2 are described. These substances have been prepared in excellent yields. All the synthesized compounds except 5i have been tested against five different microorganisms and some of them were found to be active against some of the species studied.

Preparation in excellent yields of cyclobutyl benzofuran-2-yl- and naphthofuran- 2-yl-ketones, the corresponding ketoximes and thiosemicarbazones, ether derivatives of the ketoximes and thiazoles derived from the thiosemicarbazones are described. Two of the synthesized compounds have been tested against eight different microorganisms and found to be active against some of the species studied.

Incidental spinal bone lesions, potential indicators of malignancies, are frequently underreported in abdominal and thoracic CT imaging due to scan focus and diagnostic bias towards patient complaints. Here, we evaluate a deep-learning algorithm (DLA) designed to support radiologists’ reporting of incidental lesions during routine clinical practice. The present study is structured into two phases: unaided and AI-assisted. A total of 32 scans from multiple radiology centers were selected randomly and independently annotated by two experts. The U-Net-like architecture-based DLA used for the AI-assisted phase showed a sensitivity of 75.0% in identifying potentially malignant spinal bone lesions. Six radiologists of varying experience levels participated in this observational study. During routine reporting, the DLA helped improve the radiologists’ sensitivity by 20.8 percentage points. Notably, DLA-generated false-positive predictions did not significantly bias radiologists in their final diagnosis. These observations clearly indicate that using a suitable DLA improves the detection of otherwise missed potentially malignant spinal cases. Our results further emphasize the potential of artificial intelligence as a second reader in the clinical setting.