To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

Introduction: Although soap industry is known from hundreds of years, the development accompanied with this industry was little. The development implied the mechanical equipment and the additive materials necessary to produce soap with the best specifications of shape, physical and chemical properties. Objectives: This research studies the use of vacuum reactive distillation VRD technique for soap production. Methods: Olein and Palmitin in the ratio of 3 to 1 were mixed in a flask with NaOH solution in stoichiometric amount under different vacuum pressures from -0.35 to -0.5 bar. Total conversion was reached by using the VRD technique. The soap produced by the VRD method was compared with soap prepared by the reaction - only method which

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

Doxorubicin (DOX) is a potent antineoplastic drug used to treat many types of human tumor. The long-term adverse effect is cardiomyopathy. Chromium is an essential trace element mostly used to regulate glucose levels and enhance the response to insulin, especially in diabetes. Current study aimed to evaluate the cardioprotective effect of chromium picolinate against doxorubicin-induced cardiotoxicity in 28 male rats divided into four groups. Group I (Control group): received distilled water orally for 8 days. Group II (Doxorubicin group): received distilled water orally for 7 days, followed by a single doxorubicin dose (25 mg/kg) intraperitoneally. Group III (Chromium 2 mg): received chromium picolinate at a dose

Cancer remains a leading cause of mortality and morbidity worldwide. Advances in cancer therapies—including immunotherapies (e.g., checkpoint inhibitors, gene-targeted therapies), antibody-based cancer toxins, chemotherapy, radiotherapy, and surgery—have significantly improved survival rates 1,2. However, this progress has led to a surge in the prevalence of cardiovascular disease (CVD) among cancer survivors, now recognised as a leading cause of mortality in this population 3,4. These intersecting burdens highlight the growing need to prevent, detect, and manage cardiovascular complications in cancer care pathways and call for important initiatives in establishing cardio-oncology services globally.

Pluripotent stem cells (PSC) possess unlimited proliferation, self-renewal, and a differentiation capacity spanning all germ layers. Appropriate culture conditions are important for the maintenance of self-renewal, pluripotency, proliferation, differentiation, and epigenetic states. Oxygen concentrations vary across different human tissues depending on precise cell location and proximity to vascularisation. The bulk of PSC culture-based research is performed in a physiologically hyperoxic, air oxygen (21% O2) environment, with numerous reports now detailing the impact of a physiologic normoxia (physoxia), low oxygen culture in the maintenance of stemness, survival, morphology, proliferation, differentiation potential, and epigenetic