In the title compound, C22H24N4O 2S2, the two thiourea segments of the side-arm groups are inclined at a dihedral angle of 73.09 (9)°. The central cyclohexane bridge adopts a chair conformation. The molecule is stabilized by N-H⋯O intramolecular hydrogen bonds forming S(6) rings, and N-H⋯O and N-H⋯S intermolecular hydrogen bonds forming infinite chains developing parallel to the b axis.

Medical experiments on humans are among the most dangerous that a person can be exposed to, especially in light of the tremendous scientific and technological progress that the health field is witnessing, which harms the human right to health safety, the problem of the study stems from the jurisprudential difference about the legality of medical experiments on the human body According to the traditional view, there is no legitimacy for medical experiments when they are stripped of the intention of treatment and cure, and therefore the doctor is asked about errors in the medical experiments that he conducts for the purposes of scientific research, while the modern jurisprudential view legitimizes medical experiments whenever they are for the purposes of healing, treatment and scientific research if they are abstract From the material character, and this requires the approval of rules and regulations for these experiments through the approval of legislation for this type of experiments, similar to many developed countries, such as the French law, and from this problem the objectives of the study are reflected, which is to clarify what is meant by non-therapeutic medical experiments, and to discuss the legitimacy of medical experiments other than Curative treatment on the human body, as well as clarifying the legislative position on non-therapeutic medical experiences on the human body, as well as explaining the responsibility for To violate the rules for conducting these experiments, and to facilitate the achievement of the objectives of the study, its approach is inductive approach based on extrapolating and analyzing texts, in order to reach effective solutions to the study problem.

There is a misconception that 21st century education is all about using the right online tools. However, the premise of 21st century education requires the integration of relevant content, skills and instructional support to enhance knowledge processes in line with the requirement of 21st century learning to arrive at meaningful learning experience and not merely the use of online tools. To enhance the integration, an Online Multiliteracies Project Approach (eMULPA) framework is designed by incorporating teachers’ presence, online tools, learning materials, collaborative efforts while fulfilling the syllabus requirement so that the interconnectedness in these elements would give learners a learning experince that is worthwhile and meaningful. The framework which encompases the knowledge processes: exploration, contexualization, investigation, delibration and consolidation is expected to assist learners to have meaningful learning. This paper focuses on the learners’experiences while undergoing the knowledge processes in eMULPA. Data collection tools were interviews, teaching documents and learners’ reflective journals. For this paper, only data from learners’ reflective journal were drawn, coded for themes and explicated because reflective journal is one of the reliable means to gather information on the metacognitive processes undergone by learners. The preliminary findings demonstrated learners’ have undergone meaningful learning experiences through the eMULPA knowledge processes higlighted above. Thus, the implementation of eMULPA is expected to assist learners to acquire the 21st century skills.

Teaching practicum is an essential part of teacher-training that provides real classroom engagement for a beginner teacher. It is considered as one of the most critical components of teacher preparation with the greatest impact on teacher quality (Mtika, 2011; Zeichner, 2010; Graham, 2006; Tang, 2003) and is significant for the development of their pedagogical skills (Kauffman, 1992). The sudden upsurge of the Covid -19 infections around the world in the first quarter of 2020, witnessed massive closure of schools worldwide in order to contain the spread of the pandemic. This unexpected turn of events had flipped the more traditional face-to-face method of teaching and learning into distance learning that requires 21st. Century technology and skills. This paper explores the experience of a group of trainee teachers from an institute of higher learning in Malaysia, at managing this unprecedented challenge in delivering education remotely via technology. Data were collected from interviews and supplemental written records in the form of lesson plans, teaching evidence, and online tools employed for teaching and learning. The findings show that the trainee teachers undergo varied and often challenging experiences in ensuring the continuity of curriculum-based education and the students’ progress in learning. Their successes in delivering the lessons amidst the novel encounters are the epitome of resilient and flexible teachers in the making.

The study aims to identify possible ways and methods of guiding investments and selecting projects. It must undergo in-depth studies to prove its feasibility in development. There should also be a set of legitimate, economic, and social criteria for preference between investment projects and economic activities shall be arranged based on the priorities of the Islamic interest (Maslahah). Then such projects shall have criteria and foundations on which to evaluate and measure development performance and social impact to achieve inclusive and sustainable development of our Islamic communities. The researcher concluded that the system of investment priorities should be adhered to in all investment policies and processes and that social responsibility should be activated as one of the most important factors for enhancing development performance. The study also recommends a vigorous pursuit toward creating new standards and indicators that enhance the developmental role of Islamic institutions.

This study aims to identify the research progress and trends in orang asli scientific publications indexed in the Scopus database with the help of the Biblioshiny (Rstudio). The bibliometric analysis of 685 articles was focused on describing the characteristics and trend of the publications performance, word co-occurence, authors and journal. The main results show that the research publications on orang asli were limited but experienced a positive growth trend from 1968 to 2022. The existing publications in the orang asli research domain are mainly discussed in subject categories of medicine, social sciences, agricultural and biological science,and also the arts and humanities related to orang asli. This study found that the most frequently used words in the publications on orang asli center around health, encompassing a broad range of themes. “Child” and “rural areas” were widely used to conclude that the research on children was quite extensive in various aspects such as illness, genetics and school. This finding will benefit future studies on creating a solid insight on similar areas or to fill the knowledge gaps in the current literature on orang asli research over time.

Purpose: This study aims to provide a comprehensive bibliometric analysis of the literature on unemployment Takaful, job loss protection, and unemployment insurance from 2012 to 2023, illuminating trends, key contributions, and focal areas within the realm of insurance. Design/Methodology/Approach: Using the Scopus database, a systematic search was conducted using the keywords "unemployment takaful", "job loss protection", "unemployment insurance", and "insurance". Publications were then analyzed to determine their distribution by year, contributing authors and institutions, citation frequency, keyword co-occurrence, and more. Findings: The period 2012 to 2023 witnessed a significant increase in research concerning unemployment protection mechanisms. "Unemployment Insurance" emerges as a central topic, underscoring the focus on mechanisms to support individuals during joblessness, with major contributions from Friedman, 2014. Geographic distribution indicated a pronounced focus in United States (USA). Research Limitations/Implications: The analysis is constrained by the scope of the Scopus database and the selected keywords, potentially omitting relevant studies indexed elsewhere or under different terms. The findings underscore the need for interdisciplinary approaches in studying unemployment protection mechanisms and suggest potential avenues for future research. Practical Implications: The findings of this study showed there is a gap of the research in takaful discussing on the issues of employment safety. Most of the research conducted in developed nations and insurance company. This is suggested that, takaful should explored the are of unemployment takaful by providing an alternative for Muslim customers. Originality/Value: This bibliometric analysis presents a holistic overview of the literature landscape on unemployment protection mechanisms during a pivotal period. It serves as a foundational reference for researchers, policymakers, and industry stakeholders keen on understanding the evolution, trends, and gaps in this field.

This study seeks to develop a roadmap for (Human Resource Management [HRM] in Small and Medium Size [SMEs]) using bibliometric analysis techniques. It also seeks to examine elements have affected HRM in last two decades. The study examined 612 of 825 documents from Scopus database. Bibliometric analysis comprises three primary techniques such as performance analysis, science mapping, and network analysis. We utilize VOSviewer software to examine authorship, co-occurrence, co-citations, and thematic mapping. Based on results obtained, 2023 is most productive year with 104 publications. Surya, Batara has got the most influential author based on total citation, and University of Lincoln, UK, is most prominent organization. Additionally, USA is most influential country. “Sustainability (Switzerland)” is most influential journal in its category. Furthermore, top cited article, A structured review of Lean Six Sigma in various industrial sectors. This study has found five themes’ clusters of “human resource management practices in small and medium sized enterprises.”

The Malaysia Madani concept, introduced as a framework for national development, encapsulates a vision for a society rooted in ethical governance, inclusivity, and sustainable progress. The core values include sustainability (kemampanan), prosperity (kesejahteraan), innovation (daya cipta), respect (hormat), trust (keyakinan) and compassion (ihsan). This conceptual study explores the Malaysia Madani concept, which presents an integrated approach to Islamic business ethics and applies to marketing practices. This is particularly pertinent in today's globalized economy when ethical concerns are becoming more intricate. The research data gathering is based on a literature review of prior and recent reports and studies including Al-Quran and hadith on the Madani concept, Islamic business ethics, and Islamic marketing practices, The findings discussed the practical implications of the Madani concept and Islamic business ethics, as well as their relevance to contemporary marketing practices. By adopting this approach, Malaysian businesses can achieve both economic prosperity and make significant contributions to the ethical and sustainable advancement of society.

One of the biggest breakthroughs in Malaysia's financial ecosystem is the introduction of financial robo-advisors (FRAs), an artificial intelligence or AI-powered tools that automate investor portfolio management. FRAs, despite being new in Malaysia, are rapidly advancing with untapped research potential. In addition, FRAs are gaining popularity among the financial consumers in a tech-driven world. Unfortunately, there is a lack of research focusing on retail investors on FRAs. Malaysia, the global Islamic finance hub, employs FRAs for Islamic financial product advisory services, but research on their use in educating retail advisors is limited. This paper proposes a simple yet comprehensive conceptual model that expands the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) to identify the main determinants influencing the intention to use FRAs for Islamic financial products among retail investors in Malaysia.

A Maturity Model (MM) is essential for laboratories aiming to improve and compete globally. Despite being accredited for over 20 years, some laboratories lack evidence of system maturity necessary for international competitiveness. A higher maturity level indicates a robust quality management system, leading to improved efficiency, accuracy, and customer satisfaction, while also assuring stakeholders, such as customers and regulatory bodies, of the laboratory's commitment to continuous improvement. The MM is designed to assess the success of laboratory processes, management styles, and the development of quality management practices, based on the 4M model (Manpower, Method, Machine, Material). The MM was developed using Analytes Accurate Certain Score (AACS) for the ten most common tests and System Maturity Scores (SMS), which incorporate proficiency testing and audit scores over two accreditation cycles (six years). While the model identifies inefficiencies, it helps organizations pinpoint areas of improvement and devise strategies to enhance their operations. This study applied the MM to a commercial laboratory, ABC (anonymized), accredited since the early 1990s and having undergone eight assessment cycles. The laboratory was found to be at a “leading” maturity level with a score above 80%, although improvements are still needed. Key areas for improvement include: 1) **Manpower**: maintaining competent staff by adjusting management strategies, 2) **Method**: validating all in-house methods according to Analytical Laboratory Accreditation Criteria Committee (ALACC) guidelines, 3) **Machine**: applying good laboratory practices (GLP) for equipment sharing, especially for specific analytes, and 4) **Material**: ensuring metrologically traceable reference materials and proficiency testing for all analytes. These improvements will help the laboratory further enhance its global competitiveness.

The target of botnet attacks has shifted from the personal computers to smartphones and mobile devices due to computational power and functionality of the mobile devices. Mobile botnet is a network consists of compromised mobile devices controlled by a botmaster through a command and control (C&C) network. Nowadays mobile botnets attacks are increasingly being used for advanced political or financial interest. Due to its popularity amongst the mobile operating system, Android has become the most targeted platform by the mobile botnets. The popularity of Android attracts the attackers to develop malicious applications with the botnet capability to hijack users devices. In this paper, a new Android botnet classification based on GPS exploitation based on permissions and API calls is proposed using feature selection. The training was carried out using malware dataset from the Drebin and tested using 800 mobile apps from the Google Play store. The experiment was conducted using static analysis and open source tools in a controlled lab environment. This new classification can be used as a reference for other researchers in the same field to secure against GPS exploitation from Android botnet attacks. Springer International Publishing AG 2018.

Currently, mobile botnet attacks have shifted from computers to smartphones due to its functionality, ease to exploit, and based on financial intention. Mostly, it attacks Android due to its popularity and high usage among end users. Every day, more and more malicious mobile applications (apps) with the botnet capability have been developed to exploit end users' smartphones. Therefore, this paper presents a new mobile botnet classification based on permission and Application Programming Interface (API) calls in the smartphone. This classification is developed using static analysis in a controlled lab environment and the Drebin dataset is used as the training dataset. 800 apps from the Google Play Store have been chosen randomly to test the proposed classification. As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. This new classification can be used as the input for mobile botnet detection for future work, especially for financial matters. 2017 IEEE.

Currently, there are many attacks and exploitation to Android smartphones by the attackers all over the world. These attacks are based on profit and caused loss of money and productivity to the victim. This exploitation can be done via camera, SMS, call, audio, image or location exploitation by attacking the system call, permission or API inside the Android smartphone. Therefore, this paper presents 32 mobile malware classification based on system call and permission to detect camera exploitation for Android smartphone. The experiment was conducted in a controlled lab environment, by applying reverse engineering with 5560 training dataset from Drebin, where both static and dynamic analyses were used to identify and extract the permission and system call from the mobile applications (apps). These 32 classification have been evaluated with 500 mobile apps from Google Play Store and 19 mobile apps matched with the classification. This new classification can be used as the database and input for the development of new mobile malware detection model for camera exploitation. Copyright International Association of Engineers.

Despite spending a significant number of resources and years developing a medical system, Patients with underlying comorbidities who have SARS-nCoV-2 carry a heavy financial burden that necessitates significant medical expenditures and resources for patient care. Clinical management cost uncertainty paralyzes the healthcare system and causes deficits in annual national budgets. This research will be focusing the necessary steps in developing the protocol. Overall, this article will include intervention logic mapping, questionnaires, recorded consultations, in-depth interviews, focus group discussions, and contextual data recording will be used as methods. The best effective AI-based technique for medical expense prediction and estimation for COVID-19 patients with comorbidities was identified. Regarding medical perspective and user acceptance, a better grasp of the issues and barriers confronting Malaysia's healthcare system. Deep learning techniques created a CNN-based model for predicting medical costs. Validation of the proposed model using real-world data and demonstration of its capacity to appropriately anticipate expenses. Using a relevant performance indicator such as RMSE, compare the constructed model to existing cost prediction approaches. Insights about the economic impact of COVID-19 on patients with comorbidities and healthcare practitioners in Malaysia. This research on the economic impact of COVID-19 on patients with comorbidities and healthcare practitioners, along with the development of a CNN-based cost prediction model, has significant implications for healthcare management, policy-making, and AI advancement in healthcare. The findings will inform more efficient resource allocation, guide public health policies, and contribute to the ongoing development of AI applications in healthcare.

Leptospirosis is an endemic disease worldwide and its incidence is increasing with outbreaks and mortality. It is caused by Leptospires interrogans which are very thin,spiral-shaped, tightly coiled, gram-negative aerobic, spirochetes. It can cause several infection to human including organs such as the kidneys, liver, lungs, heart and the central nervous system. The organism can give rise to several ocular manifestations and when it affect the eyes, it causes Leptospirosisneuroretinitis. The present case illustrated a case of 9 year-old boy succumbed withleptospirosisinfection presenting as neuroretinitis. The unique of the case is that the boy had noobvious systemic manifestation of leptospirosis which caused a challenge to a physician to arrive at the diagnosis. Other important differentials had be entertained namely toxoplasmosis and ocular tuberculosis.,Further management had been discussed until the boy was discharged and being followed up as an outpatient. This is followed by the discussion on leptospirosis neuroretinitis.

Primary cerebral lymphoma in immunocompromised patients is rare and challenging to diagnose. Its presentation can have similarities with other opportunistic diseases like cerebral toxoplasmosis and tuberculoma, to name a few, which may affect the subsequent management. Here, we report a case of a gentleman with human immunodeficiency virus (HIV) who presented with clinical features of fever, confusion, and generalized lethargy. His imaging features mimicked those of central nervous system (CNS) tuberculosis (TB), and he was treated for one. Unfortunately, the patient failed to respond to the antituberculosis treatment and continued to deteriorate eventually succumbing to his illness. Brain histopathology biopsy confirmed the diagnosis of diffuse large B-cell lymphoma. We aim to illustrate the importance of a high index of suspicion with timely action taken whenever the anticipated finding or response to treatment is not observed. Multiple imaging modalities coupled with biochemistry and histopathological investigations should be considered in discriminating competing diagnoses.

Artificial Intelligence (AI) has spread quickly throughout Malaysia's business, education, healthcare, and security sectors. AI provides strong tools for evaluating customer data, improving user experiences, and refining targeted advertisements in digital advertising. But there are some drawbacks to this quick expansion as well, most notably the abuse of AI in cybercrimes. These days, technologies like DeepFake make it possible to produce incredibly lifelike yet fake content, which raises moral and legal questions. Since Malaysia does not yet have particular laws to handle the complexity of crimes involving artificial intelligence, it is difficult for law enforcement to find and bring charges against criminals. This study aims to investigate the effects of artificial intelligence (AI) manipulation in digital advertising, evaluate the efficacy of Malaysia's current legal system, and suggest ways to overcome its limitations. In order to tackle these problems effectively and ensure safeguards, against AI misuse in the realm of advertising in Malaysia this study uses document analysis to pinpoint key gaps in the current legal framework. The research underscores the necessity for guidelines to govern AI altered content as the absence of a legal structure hinders effective regulation. As a solution, the study proposes the establishment of a framework for AI alongside measures such as improving law enforcement training and investing in cutting edge technological infrastructure. It's crucial to follow these suggestions to uphold secure advertising practices while safeguarding individuals and businesses from potential risks associated with AI driven offenses.

The impact of rain weather in the images will make it complicated to distinguish in the environment surroundings using an outdoor camera. Moreover, single image plays important role in numerous areas such as in object recognition and detection, enhancement, noise removal and weather condition removal. Rainy weather of outdoor images and videos reduces the visibility, performance of computer vision algorithms and other outdoor activities, which use for extracting features and information from images. Most of the previous review papers focus on the video techniques and raindrops which adherent on the surface and in the images. This paper presents a review of restoration rain streaks detection and removal from single image which has different techniques used in video and includes the result of the implemented experiments using three images. 2006-2016 Asian Research Publishing Network (ARPN).

Skew detection and correction of documents is a problematic step in document image analysis. Many methods have been proposed by researchers for estimating the angle at which a document image is rotated (document skew) in binary image documents. Therefore, this paper aims to evaluate the most frequently skew detection techniques cited in the literature which are (i) Projection Profile Analysis (PP), (ii) Hough Transform (HT) and (iii) Nearest Neighbour (NN). This study points out the weaknesses and the strengths of each method and compares the performance of these methods in term of speed and accuracy. The evaluation result shows that in term of speed, the NN technique achieves the fastest time. However, NN performs poorly for the accuracy estimation. PP gives the best angle estimation even though it takes the longest time to execute. Hence, this finding can be used as the basis evaluation review for image analysis researchers in improving the existing technique of skew detection and recommend algorithm with a better accuracy in a shorter time. 2015 IEEE.