Human rights in the stage of criminal investigation: a comparison between Law and practice in Saudi Arabia and England and Wales

This thesis is a comparative study of the pre-trial procedures of England and Wales and Saudi Arabia. Its aim is to show how the pre-trial procedures of Saudi Arabia could be re-designed in order to conform to both the standards set by international human rights and the norms of Shari’ah law and argues that there is much common ground between the two. It addresses the human rights relevant to pre-trial procedures and explores in-depth how these are expressed in international human rights legislation and in the current legislation of England and Wales with particular reference to the Police and Criminal Evidence Act (1984). They are contrasted with the relevant articles of the Code of Criminal Procedure 2001 (CCP) of Saudi Arabia. Individual rights such as the right to liberty, the right silence, the right to privacy, the right to bail and the right to an effective remedy are examined in depth and relevant case law is cited throughout. The history of pre-trial procedures and regulations in England and Wales and Saudi Arabia is explored in order to understand how these have developed into what exists today. The former is traced from the Norman period to the present day and the latter from the pre-Islamic era of the Arabian Peninsula. The actual practice of these procedures is explored comparatively through a fieldwork project involving semi-structured interviews with police officers and lawyers in England and police officers, police officers, prosecutors and lawyers in Saudi Arabia. The thesis ends with a thorough examination of how pre-trial procedures in Saudi Arabia could be regulated and monitored so as to bring them in line with the standards required by international human rights legislation and international practice and with the demands of Islamic law

Pioglitazone enhances cisplatin’s impact on triple-negative breast cancer: Role of PPARγ in cell apoptosis

Peroxisome proliferator-activated receptor-gamma (PPARγ) has been recently shown to play a role in many cancers. The breast tissue of triple-negative breast cancer (TNBC) patients were found to have a significantly lower expression of PPARγ than the other subtypes. Furthermore, PPARγ activation was found to exert anti-tumor effects by inhibiting cell proliferation, differentiation, cell growth, cell cycle, and inducing apoptosis. To start with, we performed a bioinformatic analysis of data from OncoDB, which showed a lower expression pattern of PPARγ in different cancer types. In addition, high expression of PPARγ was associated with better breast cancer patient survival. Therefore, we tested the impact of pioglitazone, a PPARγ ligand, on the cytotoxic activity of cisplatin in the TNBC cell line. MDA-MB-231 cells were treated with either cisplatin (40 μM) with or without pioglitazone (30 or 60 μM) for 72 h. The MTT results showed a significant dose-dependent decrease in cell viability as a result of using cisplatin and pioglitazone combination compared with cisplatin alone. In addition, the protein expression of Bcl-2, a known antiapoptotic marker, decreased in the cells treated with cisplatin and pioglitazone combination at doses of 40 and 30 μM, respectively. On the other hand, cleaved- poly-ADP ribose polymerase (PARP) and -caspase-9, which are known as pro-apoptotic markers, were upregulated in the combination group compared with the solo treatments. Taken together, the addition of pioglitazone to cisplatin further reduced the viability of MDA-MB-231 cells and enhanced apoptosis compared with chemotherapy alone

A novel hybrid attention based deep learning framework for textual emotion recognition using natural language processing technologies for disabled persons

Abstract A disability is a significant problem that has posed and proceeds to pose a challenge. Disability is frustrating because it is noted as a constraint, mental, physical, and cognitive handicap, which prevents the individual’s involvement and growth. Therefore, significant effort is brought into eliminating these types of restrictions. These plans deal with the problems that disabled people face. People with disabilities are frequently required to depend on others to fulfil their needs. Machine learning (ML) is outshining in making smart cities and providing a protected environment for disabled people. Emotional detection is an essential field of study that presents numerous recognized inputs. Emotion is phrased differently through facial and speech gestures, expressions, and written medium. Emotion detection in a text document is a content-based classification task using deep learning (DL) techniques, intricate methods, and natural language processing (NLP). This study proposes a Novel Hybrid Attention-Based Deep Learning for Textual Emotion Recognition Using Natural Language Processing Technologies (HADLTER-NLPT) technique. The HADLTER-NLPT technique aims to recognize emotions from textual data, improving assistive technologies and emotional understanding for disabled persons. Initially, the HADLTER-NLPT model performs text pre-processing at different levels to clean and normalize the input text. The Word2Vec model converts the textual data into dense vector representations that capture semantic meaning for the word embedding process. Furthermore, the hybrid attention-based long short-term memory (HA-LSTM) classifier effectively recognizes emotional expressions from text. The oscillating chaotic sunflower optimization (OCSFO) approach is employed for hyperparameter tuning to optimize the performance of the HA-LSTM approach. An extensive experimental study is performed on the HADLTER-NLPT method under Emotion detection from the text dataset. The performance validation of the HADLTER-NLPT method portrayed a superior accuracy value of 98.86% over existing models

Factors influencing high school students’ decision in applying to Medical School

Background: Many factors influence high school students’ future profession choices, which differ by culture and other variables such as the students’ background, social differences, and financial status, all of which culminate in a student pursuing their higher education in a single field. As a result, the factors that influenced that choice must be addressed in order to achieve better outcomes for both the educational programs and the health system. Methods: A cross-sectional study was conducted in Riyadh city among high school students. Sociodemographic characteristics, preferred study specialties, GPA, and performances were obtained using a self-administered questionnaire. Results: The age of the students was between 16-19 years old. Most selected specialties were medicine, followed by engineering, information technology and Nursing, however, Pharmacy was in the least selected specialty. Findings showed that the top perceived barrier was the high aptitude score required for entry into medicine (23.3%); another group of the students (23.1%) indicated that the English Language competency test/skills were the second obstacle. Offering health care and motivation were the most important factor for the majority of students. The majority had remarkably agreed or strongly agreed to the humanitarian context about studying medicine (90.4%). Conclusion: A higher percentage of high school students choose to attend medical school, with the primary obstacles to admission being the high aptitude score required for admission, followed by English language competency examinations. Finally, there is a considerable disparity between genders when it comes to medical school preferences and reasons. Keywords: Medicine, medical student, Saudi Arabia, healthcare, medical schools</jats:p

Training medical students in physical examination and point-of-care ultrasound: An assessment of the needs and barriers to acquiring skills in point-of-care ultrasound

BACKGROUND: With growth of the use of point of care ultrasound (PoCUS) around the world, some medical schools have incorporated this skill into their undergraduate curricula. However, because of epidemiology of disease and regional differences in approaches to patient care, global application of PoCUS might not be possible. Before creating a PoCUS teaching course, it is critical to perform a needs analysis and recognize the training obstacles. MATERIALS AND METHODS: A validated online questionnaire was given to final-year medical students at our institution to evaluate their perceptions of the applicability of specific clinical findings, and their own capability to detect these signs clinically and with PoCUS. The skill insufficiency was assessed by deducting the self-reported clinical and ultrasound skill level from the perceived usefulness of each clinical finding. RESULTS: The levels of expertise and knowledge in the 229 students who participated were not up to the expected standard. The applicability of detection of abdominal aortic aneurysm (AAA) (3.9 ± standard deviation [SD] 1.4) was the highest. However, detection of interstitial syndrome (3.0 ± SD 1.1) was perceived as the least applicable. The deficit was highest in the detection of AAA (mean 0.95 ± SD 2.4) and lowest for hepatomegaly (mean 0.57 ± SD 2.3). Although the majority agreed that training of preclinical and clinical medical students would be beneficial, 52 (22.7%) showed no interest, and 60% (n = 136) reported that they did not have the time to develop the skill. CONCLUSION: Although medical students in Saudi Arabia claim that PoCUS is an important skill, there are significant gaps in their skill, indicating the need for PoCUS training. However, a number of obstacles must be overcome in the process

Integrating Explainable Artificial Intelligence With Advanced Deep Learning Model for Crowd Density Estimation in Real-World Surveillance Systems

Crowd Density Detection in Smart Video Surveillance involves advanced computer vision (CV) techniques to improve the efficiency and accuracy of crowd monitoring. The system assists in detecting and analyzing crowd density in real-time by utilizing artificial intelligence and machine learning (ML) models on surveillance videos. It detects crowded areas, manages crowd flow, and combines automated analysis with human oversight for improved public safety and early intervention. Explainable Artificial Intelligence (XAI) improves the interpretability and transparency of crowd management methods. Incorporating XAI models provides clear, understandable insights into predictions, ensuring more actionable and reliable crowd management. This study proposes an Osprey Optimization Algorithm with Deep Learning Assisted Crowd Density Detection and Classification (OOADL-CDDC) technique for smart video surveillance systems. The aim of the OOADL-CDDC technique is to enable the automated and efficient detection of distinct kinds of crowd densities. To achieve this, the OOADL-CDDC technique primarily utilizes a bilateral filtering (BF) approach for noise removal process. The OOADL-CDDC technique utilizes an advanced DL method, employing the SE-DenseNet model for feature extraction, while the hyperparameter selection is performed by using the OOA model. Finally, the detection and classification of the crowd density is accomplished by using the attention bidirectional gated recurrent unit (ABiGRU) model. A series of experiments are performed to demonstrate the improved performance of the OOADL-CDDC method. The performance validation of the OOADL-CDDC technique portrayed a superior accuracy value of 98.30% over existing models in terms of distinct measures

Investigating medical students’ perceptions of point-of-care ultrasound integration into preclinical education

Abstract Introduction Recent international consensus statements advocate for the integration of Point-of-Care Ultrasound (PoCUS) into the global undergraduate medical curriculum. Some medical schools outside Saudi Arabia have already incorporated PoCUS into their undergraduate curricula to enhance anatomy, physiology and pathology instruction. However, there are no data on the potential role of PoCUS in the preclinical training of medical students in Saudi Arabia. Given constraints on resources for medical education, a formal needs assessment was conducted to evaluate the potential utility of PoCUS within the basic science curriculum at our institution. Methods All final year medical students at our institution were invited to complete a validated online survey. The questionnaire utilized a 5-point Likert scale to assess student perceptions of the potential for PoCUS to improve their understanding of basic sciences and their desire for its incorporation into the preclinical curriculum. Results A total of 229 students participated (response rate 76%; male 134/200; female 95/100). Our survey demonstrated good internal consistency (Cronbach’s alpha: learning basic sciences 0.81, need for curriculum integration 0.83). The vast agreed that learning PoCUS would enhance their understanding of anatomy (95%) and pathology (75%). While only 52% agreed that learning PoCUS would improve their understanding of physiology, a substantial majority (80%) agreed that all medical schools should incorporate PoCUS into their undergraduate curricula. Furthermore, 62% agreed that offering PoCUS training would make the medical school more attractive to prospective applicants. No significant differences were observed between the responses of male and female students. The results of a confirmatory factor analysis provide strong support for the hypothesized three-factor model. All factor loadings are significant (P < 0.001), Conclusions Medical students in Saudi Arabia perceive that PoCUS would be a valuable tool to learn anatomy and pathology, aligning with the recommendations of the consensus conference on PoCUS integration in undergraduate medical education organized by the World Interactive Network Focused on Critical Ultrasound (WINFOCUS) and the Society of Ultrasound in Medical Education (SUSME). Introducing PoCUS training into preclinical medical curricula may also enhance the attractiveness of medical schools to potential applicants

Quality of life among pediatric residents in Riyadh

Background: Until now, no locally based study has evaluated quality of life among pediatric residents, especially pediatric residents in Saudi Arabia, Riyadh. The objective of this study was to evaluate quality of life (QoL) of the pediatric residents and report the factors affecting their quality of life.Methods: A cross-sectional study, a self-administered questionnaire depending study that was distributed electronically to pediatrics resident to assess the quality of life in Riyadh, Saudi Arabia. The study depended on self-reported questionnaire in which the questions were gathered specifically, from work-related quality of life (WRQoL) scale. To collect data, the self- administered questionnaire was sent through social media (twitter, WhatsApp).Results: In this study, we were able to collect data from 260 residents where 54.2% of them were females. In general, we found that 51.9% of the participants showed good level of QoL while 47.7% showed moderate level of quality of life and only 0.4% showed low levels of QoL. The percentage of residents who showed good quality of life among the six categories; CAW, JCS, HWI, SAW, GWB and WCS were 53.8%, 49.2%, 45.0%, 48.6%, 38.1% and 56.9% respectively. We did not find any significant factors that had impact on quality of working life among the residents.Conclusions: We found that 48.2% of the pediatric residents working in Al Riyadh region, Saudi Arabia showed moderate to low level of work-related QoL. Further studies are needed to determine the causes and improve the work-related quality of life among pediatric residents.</jats:p