Abstract

This study analyzes the role of sports media in shaping public impressions of Video Assistant Referee (VAR) technology and its impact on refereeing justice, framed by the Uses and Gratifications Theory. Through content analysis of media coverage and interviews, the research reveals that sports media significantly influences fan perceptions, amplifying both support for VAR’s accuracy in critical decisions and criticism over game interruptions and interpretive subjectivity. Findings highlight media’s power to foster transparency and trust when providing clear explanations, while biased reporting exacerbates controversy. The study recommends enhanced media protocols for balanced coverage to improve public acceptance and perceived fairness.

Abstract

In an increasingly globalized society, bilingualism has become a defining characteristic of modern identity, presenting unique phonological challenges for children navigating dual linguistic registers. While pronunciation errors are a natural and developmental stage of language acquisition, bilingual children often exhibit higher error rates than their monolingual peers due to the cognitive and physical complexities of mastering two sets of phonetic structures simultaneously. In the Kingdom of Bahrain, a notable shift toward English-medium instruction in private schools has increased early exposure to both Arabic and English. This educational landscape creates a unique environment where language dominance and exposure levels may significantly influence speech accuracy and communicative competence. This study investigates the specific pronunciation error patterns in the spontaneous speech of Bahraini bilingual Arabic-English children aged five to seven. The research addresses three primary questions: (1) What are the most common pronunciation error patterns observed in this demographic? (2) Do these children produce a higher frequency of errors in Arabic or English? and (3) To what extent does gender influence the distribution and type of these errors? Adopting a qualitative research design, the study utilized naturalistic, unstructured observation of six children (three boys and three girls) within their home environments. Spontaneous speech samples were recorded, phonetically transcribed, and analyzed using an Error Analysis (EA) framework. This framework was supplemented by a basic statistical analysis to determine error frequencies across languages and genders. The analysis identified thirty distinct mispronunciations, which were classified into four main categories: substitution, omission, addition, and suppletion. Substitution emerged as the most frequent error pattern among the participants. Notably, the findings revealed that subjects made significantly more errors in Arabic than in English, likely reflecting the pedagogical emphasis on English in private school settings. Furthermore, gendered disparities were observed: girls exhibited a higher frequency of English mispronunciations, whereas boys displayed more errors in Arabic. The significance of these findings lies in their challenge to traditional assumptions of native-language dominance; suggesting that intensive English-medium immersion in early childhood can lead to a “dominance shift” where the phonological accuracy of the mother tongue (Arabic) begins to lag behind the second language. By identifying that social interaction styles, such as gendered play patterns, directly correlate with language-specific errors, this study underscores that phonological development is as much a social process as it is a cognitive one. In terms of disciplinary connections, this research bridges Applied Studies and Education by providing empirical data for “Balanced Bilingualism.” Within Applied Linguistics, it contributes to the study of phonetic interference and language attrition in Gulf-based bilingual contexts. For the field of Education, these insights are vital for curriculum designers in Bahrain, highlighting the need for restorative L1 (Arabic) phonetics support to ensure that high English proficiency does not result in the erosion of native language precision. Ultimately, the study provides a framework for targeted early intervention strategies that address both the linguistic and social variables of the bilingual classroom.

Abstract

This paper presents a comparative analysis of language acquisition in human children and African Grey Parrots (Psittacus Erithacus), drawing primarily on two empirical studies: Roubalová et al. (2024), who compared the productive vocabularies of 21 grey parrots and 21 Czech-acquiring children aged 8-18 months matched by vocabulary size, and Colbert-White, Beyer, and Kuczaj’s study of private speech in a two-year-old child (Emily) and a home-reared parrot (Cosmo). The paper situates these findings within two major theoretical frameworks: Vygotsky’s (1978) sociocultural theory and Chomsky’s (1965) innateness hypothesis, to examine what cross-species similarities and differences reveal about the nature of human language. Both species demonstrated functional parallels: contextual word use, sound and word play, and repetitive practice suggesting intrinsic motivation. However, profound compositional differences emerged: children showed greater use of object labels, emotional expressions, and grammatical function words, whereas parrots produced more conversational phrases, greetings, and formulaic multi-word strings. These findings are interpreted as evidence that, while vocal learning mechanisms may be partially shared across species, the sociocognitive architecture underpinning human language, including conceptual word-meaning mapping, referential intent, and generative syntax, remains distinctively human.

Abstract

This study aims to identify the impact of artificial intelligence (AI) and its tools on the desire of Gulf University students for traditional reading and research, according to the uses and gratifications theory. With the rapid development of AI and the widespread use of its tools among university students, these technologies have become a primary means of obtaining information for research and assignments due to their speed and ease. This has raised questions about the impact on students’ interest in in-depth reading and reliance on traditional sources such as books and academic references, and whether this impact is positive or negative. The study adopted a quantitative approach and was applied to a sample of Gulf University students using a survey method during 2025 to measure their reliance on AI tools for acquiring information and to reveal their impact on their motivation for self-directed research through books and traditional academic research. The study also sought to explore differences in students’ preferences according to demographic variables and to identify the benefits and challenges associated with using AI in the educational journey. The results showed that more than half of Gulf University students (52%) regularly use AI tools in their university studies, indicating the widespread use of these tools and students’ reliance on them for learning and academic research.

Abstract

This study investigates the impact of Artificial Intelligence on graphic designers, examining its benefits such as faster production, improved output quality, and enhanced creativity alongside its risks, including job insecurity, reduced creative control, and dependence on algorithms. The research adopts a descriptive analytical method using an online survey targeting designers in Bahrain. Findings indicate that AI is generally viewed as a supportive tool that enhances performance, yet concerns remain regarding job stability and the evolving role of designers in an automated future. The study recommends a responsible and balanced integration of AI to maximize benefits and minimize risks to the graphic design profession

Abstract

In recent years, the Kingdom of Saudi Arabia has witnessed remarkable cultural and media transformations, most notably the resurgence of cinema as a key element supporting cultural life and creative industries, in line with the goals of Vision 2030. This study aimed to identify the stages of development of Saudi cinema and examine the role of traditional and digital media in supporting this development and enhancing public acceptance of cinema and its local content. The study employed a quantitative methodology using a survey approach. Data was collected through an online questionnaire administered to a sample of young people to measure their engagement with cinematic content and determine the role of media in shaping their attitudes towards Saudi cinema. The sample was selected randomly, and appropriate statistical tools were used to analyze the data and draw conclusions. The study concluded that Saudi cinema has undergone several developmental stages, most notably a limited beginning, a period of stagnation and societal debate, and then a phase of openness and institutional empowerment after 2018. The results also showed that digital media, particularly social media, has significantly contributed to increasing young people’s interest in Saudi cinema, improving its public image, and supporting the dissemination of local productions. In light of these results, the study recommended the need to enhance integration between media and film institutions, intensify awareness content related to film culture, and support youth participation in the Saudi film industry.

Abstract

This research examines the demand for a UI/UX-focused mobile application designed to enhance university transportation services, specifically through the ‘Tawseela’ application. The study explores the challenges faced by students in accessing reliable and efficient transportation to and from the university and assesses their willingness to adopt a localised digital solution to address these issues. A survey was conducted to gather data from potential users regarding their current transportation experiences, pain points, and the potential impact of an improved UI/UX design in streamlining their commuting process. The ‘Tawseela’ application aims to facilitate coordination among students, enabling them to connect and share rides to and from the university. Additionally, the app offers a source of income for students who are heading to the university and can offer rides to others. This helps reduce overall transportation costs for students while providing an opportunity for those driving to earn extra income. Thestudy highlights the key benefits of implementing such an application, including increased convenience, cost savings, optimised route planning, improved communication with fellow students, and reduced waiting times. Furthermore, it helps minimise the risks associated with relying on unknown service providers by enabling users to easily access reviews and ratings from fellow students.

Abstract

The Dilmun civilization, one of the earliest in the Arabian Gulf, holds a rich artistic heritage that continues to influence contemporary Bahraini art. Today’s artists reinterpret its symbols and motifs through modern practices, creating a balance between cultural authenticity and innovation. This study examines how Dilmun heritage shapes a distinct artistic identity in Bahrain, reflecting a continuous dialogue between past and present.

Abstract

Crude oil is one of the most critical energy commodities, and thus understanding its price dynamics remains a central issue for researchers. This paper applies innovative methods to predict crude oil prices over the period 2019-2025. Daily crude oil price data obtained from Yahoo Finance are employed to develop and compare two forecasting approaches: Monte-Carlo simulation and Prophet model. The Monte Carlo simulation was chosen because of its nature in dealing with uncertain events by following a stochastic framework that depicts thousands of random events that rely on past crude oil price behaviors, macroeconomic conditions, and other factors through generating multiple price paths. In contrast, the long term trends, seasonality and non-linearity in the model were handled by utilizing the Prophet model. Empirical results indicate that the Prophet model outperforms the Monte Carlo simulation in terms of predictive accuracy and systematic trend identification. However, Monte Carlo remains more effective for understanding uncertain events. Combining both models provides a comprehensive analytical framework that enhances long-term forecasting reliability and supports informed decision making for investors and market stakeholders.

Abstract

Crude oil is one of the most critical energy commodities, and thus understanding its price dynamics remains a central issue for researchers. This paper applies innovative methods to predict crude oil prices over the period 2019-2025. Daily crude oil price data obtained from Yahoo Finance are employed to develop and compare two forecasting approaches: Monte-Carlo simulation and Prophet model. The Monte Carlo simulation was chosen because of its nature in dealing with uncertain events by following a stochastic framework that depicts thousands of random events that rely on past crude oil price behaviors, macroeconomic conditions, and other factors through generating multiple price paths. In contrast, the long term trends, seasonality and non-linearity in the model were handled by utilizing the Prophet model. Empirical results indicate that the Prophet model outperforms the Monte Carlo simulation in terms of predictive accuracy and systematic trend identification. However, Monte Carlo remains more effective for understanding uncertain events. Combining both models provides a comprehensive analytical framework that enhances long-term forecasting reliability and supports informed decision making for investors and market stakeholders.

Abstract

Precious metals have long been considered safe havens for investors due to their anti-inflationary nature and ability to store value. In 2025, silver was put under the spotlight due to its dramatic price change, hitting new historical records and increasing investors’ attention to the commodity. This study is conducted to provide a comparative analysis between Monte Carlo simulation and the Prophet model using historical data from January 2019 to October 2025, to generate two-year silver price forecasts. Monte Carlo simulation generated results for different seniors showing uncertainty and price fluctuation under various market circumstances, while the hybrid model provided more accurate and reliable results. The key discoveries included the significance of combining multiple techniques to generate better predictions and to estimate trends and market directions. This study also contributes to the evolving discussions on forecasting silver prices by providing the groundwork for further studies in this area. Keywords: Silver Price Prediction, Monte Carlo Simulation, Prophet, Random Forest, Time Series Forecasting, Machine

Abstract

This paper presents a systematic review of how Artificial Intelligence (AI) and Machine Learning (ML) have transformed marketing practices between 2001 and 2025. Through the analysis of 439 peer-reviewed studies, we map the intellectual progression of AI/ML in marketing, identifying dominant themes, influential works, and emerging gaps in the literature. The findings reveal a significant surge in research output after 2017, with notable contributions from countries such as India, China, and the United States. Key focus areas include personalized consumer engagement, predictive analytics, programmatic advertising, and the ethical implications of automated marketing systems. Our review highlights the prevalent use of established theoretical frameworks like the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), indicating a strong foundation in adoption-focused studies. However, newer innovations such as generative AI, real-time adaptive marketing, and the integration of AI in small and medium enterprises (SMEs) remain underexplored. Importantly, ethical considerations including algorithmic transparency, data privacy, and bias mitigation-are increasingly acknowledged but require deeper empirical and practical attention. By synthesizing 25 years of research, this study not only charts the evolution of AI/ML in marketing but also proposes actionable directions for future inquiry. These include fostering cross-cultural studies, developing scalable AI solutions for SMEs, and advancing ethical frameworks for responsible AI deployment. This review serves as an essential resource for students, academics, and marketing professionals seeking to understand the current state and future potential of AI-driven marketing in an increasingly digital and data-centric business landscape.

Abstract

This paper presents a simple yet practical conceptual model for understanding how artificial intelligence (AI) transforms raw customer data into personalized marketing experiences across digital touchpoints. As businesses increasingly adopt AI tools in marketing, there is a need for accessible frameworks that clarify how data collection, algorithmic processing, and content delivery work together to create individualized customer journeys. The power asymmetry between the traders and the customers enables exploitation
using complex data analytics & sentiment mapping. This model breaks down the AI-driven personalization process into three core stages: data ingestion and integration, AI-driven insight generation, and personalized content delivery. We explain how first, second, and third-party data are aggregated and cleaned, then analyzed using machine learning techniques such as clustering, recommendation algorithms, and predictive analytics to segment audiences and predict behaviors. Finally, we illustrate how these insights are applied in real time to customize email campaigns, social media ads, website content, and product recommendations. The paper also discusses practical considerations for implementation, including data privacy, algorithmic transparency, and system integration challenges. Designed for students, early-career marketers, and small business owners, this model demystifies the technical process of AI personalization and provides a clear, step-by-step guide for leveraging AI to enhance customer engagement and marketing ROI in digital environments.

Abstract

This paper examines the potential for energy conservation in Bahrain’s architectural landscape by focusing on the Almoayyed Tower, the Kingdom’s first skyscraper. As electricity demand in Bahrain rises—driven largely by cooling and HVAC systems—there is an urgent need for high-efficiency building envelopes [1]. This study investigates the integration of passive design measures and renewable energy technologies, specifically Building-Integrated Photovoltaics (BIPV). Through simulation using DesignBuilder, the research evaluates how highperformance glazing and solar integration can reduce energy consumption. Findings indicate that a comprehensive envelope retrofit can reduce annual energy use by 20-30%, potentially generating 3 million kWh of solar electricity annually and reducing CO2 emissions by approximately 3,000 tons [2].

Abstract

With the increasing demand for sustainability and explicit environmental protection, especially in the medical field, the interest in bio-based alternatives for antimicrobial finishes in the textile industry had been steadily growing since the recent global pandemic, to further promote eco-friendly solutions. Hence, the project aims to create a bio-based antimicrobial finish for textiles through the extraction of basil essential oil, a renowned and globally cultivated herb. There are four extraction methods that were used throughout the experimental period: steam distillation, solvent extraction, Soxhlet extraction and cold pressing, using both the seeds and leaves of the herb. Steam distillation and solvent extraction both provided a yield too insignificant to be considered, whilst the cold press extraction produced a yield of 15.0% the weight of the seeds used. Soxhlet extraction, using n-hexane and ethyl acetate as solvents, produced the highest yield of essential oil of the weight of seeds and leaves used throughout the experiment at 18.7% and 16.7%, respectively. The essential oil produced from the cold press extraction and the Soxhlet extraction were tested and compared against a commercially available basil essential oil using the well diffusion test, where both gram negative (E. coli) and gram positive (S. aureus) bacteria were deployed, as well as gas chromatography to observe and verify the presence of antimicrobial active compounds. It was concluded that the extract produced with cold press had no considerable antimicrobial activity, while the n-hexane and ethyl acetate extracts collected through Soxhlet extraction exhibited great antimicrobial behaviour, with inhibition zones that ranged from 15 mm to 50 mm, greater than the commercial oil, which averaged at 10 mm.  Additionally, the gas chromatography further confirmed the presence of the main antimicrobial components found in basil.
The n-hexane and ethyl acetate extracts were then mixed to create a hybrid, to study the synergistic effects of the two extracts, and maximize the antimicrobial activity when applied as a finish for textiles. The standard process of application of the finish in the textile industry is through pad-dry curing, where the fabric will be exposed to high temperatures to fix onto the textile surface. Due to the extract being adversely affected by high temperatures, the finished fabric samples initially did not show antimicrobial activity after undergoing the heat intensive application process. To tackle the issue of degradation and preserve antimicrobial properties, the application process was modified to run at room temperature. Fabric samples were coated with the hybrid extract solution at concentrations of 3%, 6% and 9%, and were tested using the parallel streak method, with the results confirming that 6% was the minimum effective concentration required for observable antimicrobial activity. Fabric samples of the same concentration were washed once and retested using the same method; and while exhibiting lower inhibition zones, all concentrations retained their antimicrobial activities.

Abstract

Brain–Computer Interfaces (BCIs) enable direct communication between our human brain and external systems by interpreting neural signals without relying on conventional neuromuscular pathways. Among different BCI technologies, electroencephalography (EEG)-based systems are widely adopted due to their non-invasive nature, low cost, and ease of implementation, making them suitable for both engineering and medical applications.We will provide a comprehensive review of EEG-based brain–computer interface systems from both engineering and medical perspectives. Examining the main components of BCI systems, including EEG signal acquisition, electrode placement, artifact and noise removal, feature extraction techniques, and classification methods used for decoding brain activity.a small experimental analysis using a multi-channel EEG dataset is presented to illustrate how engineering-based signal processing techniques can be applied to real EEG data.. In addition, several important applications are discussed, such as neurorehabilitation, assistive robotic control, and communication systems for individuals with severe motor impairments. Medical applications including epilepsy detection and seizure prediction, sleep monitoring and sleep stage analysis, the diagnosis and monitoring of neurodegenerative diseases such as Alzheimer’s disease are also reviewed. The results of this review highlight the significant role of EEG-based BCI systems in bridging engineering technologies with medical applications by enabling more effective brain signal analysis and supporting assistive and diagnostic solutions. However, several challenges remain, low signal-to-noise ratio, inter-subject variability, and real-time performance limitations. Future research directions focus on improving EEG acquisition techniques and integrating advanced machine learning methods to enhance the reliability, accuracy, and practical usability of EEG-based brain–computer interface systems.

Abstract

This paper presents an FPGA-based constant voltage-to-frequency (V/f) control system for threephase induction  otors using the Altera DE0-Nano development board. The V/f control technique maintains a constant voltage-to-frequency ratio to preserve optimal motor flux and torque characteristics across the operating range. The complete control algorithm was developed in Verilog HDL using Quartus Prime Lite, generating sinusoidal PWM signals with programmable dead-time insertion for inverter protection and featuring UART communication for real-time speed control with ramping capabilities. Simulation and experimental testing validated accurate V/f ratio maintenance, precise speed control, and stable motor operation across multiple speed references. The key achievement is demonstrating that low-cost FPGA platforms
integrated with low-cost UART modules can deliver professional-grade motor control with real-time responsiveness and implementation flexibility, avoiding the limitations of platform-specific tools like Simulink.  The system establishes FPGA technology as a viable, economical alternative to traditional DSP-based or high-range FPGA drives.

Abstract

The need for wellness and healing spaces has emerged as a key concern in contemporary architectural practice, particularly in response to physical stress, mental fatigue, and the weakening relationship between humans and their natural environments. Wellness architecture is fundamentally concerned with healing, creating spaces that support physical, psychological, and emotional well-being through carefully designed spatial experiences. This research paper examines the architectural challenge of designing a wellness centre that facilitates healing while operating within a sustainable built environment. While environmental sustainability is an essential requirement of contemporary architecture, this study positions healing as the primary architectural issue, with sustainability addressed as an integrated and supportive aspect.
The issue examined in this paper is the relationship between healingoriented spatial design and environmentally responsive architecture. This investigation is explored through the development of an architectural proposal for the Thalassa Wellness Centre, informed by the Ancient Greek Asklepion healing philosophy, which emphasized harmony between body, mind, nature, and water. The methodology involves developing an understanding of healing environments, formulating an appropriate conceptual framework, and translating this framework into an architectural design. This process includes site analysis, spatial organization, form development, and material selection, alongside the application of climateresponsive strategies such as passive cooling, shaded circulation, natural ventilation, courtyards, and controlled microclimates. These strategies are employed not as isolated technical solutions, but as spatial tools that enhance comfort and reinforce the healing experience. The outcome of this research is a climate-responsive waterfront wellness centre that functions as both a therapeutic retreat and a community-oriented health facility. The project demonstrates how healing-driven architectural concepts can be effectively integrated with sustainable design strategies to create environments that promote physical restoration, mental well-being, and sensory engagement.
Ultimately, this research highlights architecture’s potential to support holistic healing while responding responsibly to environmental and climatic conditions, offering an approach applicable to similar contexts.

Abstract

Pharmaceutical contaminants in aquatic environments pose a significant risk to ecosystems and human health, necessitating the development of efficient and sustainable remediation strategies. This study evaluates the photocatalytic degradation of doxycycline hyclate using in-house synthesized sulfur-doped graphitic carbon nitride (S-g-C₃N₄) nanoparticles under UV-light irradiation activated by hydrogen peroxide.
Degradation experiments were conducted in a fixed-volume reaction mixture containing 60 mg/L doxycycline solution. The reaction was found to follow pseudo-first-order kinetics with a rate constant of 0.0958 min⁻¹. Four key parameters (catalyst dosage, pH, H₂O₂ dosage, and temperature) were optimized using Response Surface Methodology (RSM) with a central composite design. The developed quadratic model exhibited strong predictive ability (R² = 0.922), with all linear terms, two-way interactions, and non-linear temperature squared effect found to be significant. Optimal conditions were determined to be 643.8 mg/L catalyst dosage, pH 3.56, 4.70 mM H₂O₂, and 42.68 °C, achieving an experimentally validated degradation efficiency of 94.75 %. This work demonstrates the efficiency of simple metal-free S-g-C₃N₄ nanoparticles for the removal of persistent pharmaceutical pollutants and provides a robust predictive model to support practical wastewater treatment applications, directly fulfilling the purpose of this study. Future investigations will examine performance in real wastewater matrices, scale up the experimental setup, and perform thorough economic analysis.

Abstract

Building operations have a substantial share in worldwide energy consumption. Retrofitting existing buildings is therefore a critical climate change mitigation strategy. This study evaluates strategies for improving the energy efficiency of Bahraini public schools through simulations, aligning them with the Kingdom’s energy plan.

Methods: An existing Bahraini public school using a widely replicated model was researched as a case study. Its building relied on strategies like shading and thermal mass to cool the building passively; however, it ended up having high mechanical cooling and lighting loads. It was modeled to simulate its energy usage, then had adjustments made to it to see how its energy performance could be improved. Calculations to confirm the viability of using renewable energy sources, and solar power in particular, were conducted.

Results: The solution was exemplified in adjusting the building envelope, improving glazing, replacing inefficient appliances, and enhancing internal conditions. Overall, a reduction of 27.3% of energy consumption was achieved, with around 130,000 kWh saved. Additionally, among the possible renewable energy sources for the school, solar power was considered the optimal choice. Calculating energy generation found that it could offset the entire building usage with surplus (affording an extra 67% for the rest of the areas in the school).

Conclusion: This study highlighted the importance of simulations in retrofitting. It is recommended that the strategies discussed be applied to schools during maintenance to reap the benefits of the energy conservation. Moreover, applying the study in the real world and testing it on existing schools can help validate its results.

Practice implications: Because the school uses a prevalent standard model, the energy efficiency practices presented can be applied to a multitude of buildings across the country.

Abstract

This paper presents El-Mostawsaf, an innovative dual-modality AI healthcare assistant designed to enhance accessible diagnosis. The system integrates a sophisticated Retrieval-Augmented Generation (RAG) engine, leveraging the Gemini API and Chroma DB, trained on an extensive dataset of 136,000 medical records. This allows for highly accurate and contextually relevant responses to medical inquiries.
Furthermore, El-Mostawsaf incorporates IoT integration for real-time patient monitoring, providing proactive care and early detection capabilities. The project is currently in its final development phase, demonstrating robust performance in preliminary evaluations.

Abstract

The global rise in herbal medicine use has prompted increased scrutiny of specific herbs like marjoram (Origanum majorana), yet its utilization patterns in Bahrain, middle east, and globally remain underexplored. This study sought to investigate the extent, knowledge, perceptions, and behaviors associated with marjoram use among Bahraini adults. Employing a cross-sectional design, data were gathered from 387 individuals aged 18–65 years through a digitally administered questionnaire, distributed via a random sampling technique. The survey, consisting of 18 questions organized into four thematic sections, captured sociodemographic details, views, attitudes, and practices related to marjoram. Predominantly female (80.62%), 81.91% of participants used marjoram for therapeutic purposes, with 82.69% targeting stomach pain relief. A significant 89.9% perceived marjoram as safer than pharmaceuticals, and 73.4% sought additional knowledge about its benefits. Efficacy was rated as partially successful by 59.17% and fully effective by 37.47%. Tradition drove usage for 51.68%, with 84.24% sourcing marjoram from herbal shops. Information was primarily obtained from friends (41.86%), family (18.35%), and media (17.05%). Age and educational attainment significantly shaped usage patterns, with younger and more educated individuals exhibiting distinct tendencies. The prevalent reliance on marjoram, rooted in cultural practices and perceived safety, highlights the necessity for targeted educational initiatives to promote informed and safe use within Bahrain’s population.

Abstract

The availability and use of contraceptives in Bahrain have shifted significantly in recent years, highlighting the need to examine women’s knowledge, attitudes, and usage patterns. Oral contraceptive pills remain a widely used birth control method, especially among women in their twenties.

Aim: This study aimed to assess Bahraini women’s knowledge, attitudes, and practices regarding contraceptives.

Method: A descriptive, cross-sectional study was conducted in Bahrain in 2025 using an online questionnaire completed by 550 participants. The survey covered sociodemographic, attitudes, knowledge, prior experience, and contraceptive use. Data were analyzed using SPSS v20. Furthermore, the questionnaire consisted of four distinct sections that assessed attitudes, knowledge, previous experience, and patterns of oral contraceptive use.

Results: Most participants (97.6%) were aware of contraceptives, but only 44.2% indicated that they used them. Oral contraceptive pills were used the most (55.8%), followed by intrauterine devices (12.4%) and condoms (10.3%). 68.6% of them consulted a healthcare provider before use. Prevention of pregnancy was the primary reason for use (43.8%), and the perceived lack of need was the most frequent reason for not using (56%). Common side effects included irregular bleeding (25.2%) and weight gain (20.2%). Attitudes varied: 71.7% found contraceptives accessible, 48.3% were neutral on the role of educational institutions, and 40.8% rated contraceptive effectiveness as average. Statistical correlations were found among age, marital status, and use of contraceptives (p < 0.0001), with married women and women aged 25–34 years more likely to use contraceptives.

Conclusion: Despite high awareness, contraceptive use remains low among Bahraini women. Perceptions of availability were generally positive, but views on effectiveness and education varied, indicating the influence of multiple factors and the need for further research.

Abstract

This paper aims to investigate the impact of project governance on project outcomes within CyberCrest Consulting, a company based in the Kingdom of Bahrain. The primary goal of this paper is to outline the advantages of applying project governance in organizations, promoting the continuous adoption of ever-improving practices that contribute to project success and enhance operations and results, thereby having a lasting effect across numerous fields.

A qualitative single-case study approach was employed, utilizing a method triangulation research strategy along with qualitative thematic interpretation as an analysis method. The primary data point consisted of survey data obtained from the organization, while published documents and publicly available information sources served as secondary data points. The case is of a cybersecurity and IT consulting firm that provides solutions for its clients through security projects.

Conclusions regarding the impact of project governance on project outcomes were drawn. To extend current existing governance thinking, a conceptual adaptive strategic alignment governance model (CASAGM) was also developed and proposed based on findings, comprising four interdependent components: strategic alignment, governance clarity, stakeholder integration, and adaptive governance enablers. This is to emphasize the importance of adaptability in contemporary governance.

Abstract

Home-based Physiotherapy; Stroke Rehabilitation; Internet of Medical Things (IoMT); Real-time Monitoring

Stroke is one of the diseases that causes long-term disability all over the world, because motor weakness in the upper extremities affects a large percentage of stroke survivors. This project presents the HOPE system, which is a smart, task-oriented system for rehabilitation and evaluation of the upper extremities, especially the hand, designed to support recovery after stroke and monitor the patient’s condition.

The system integrates a smart glove with all existing sensors, manufactured using 3D printing technology. The rule-based assessment framework translates raw sensor data into clinically meaningful performance indicators using pre-defined thresholds based on rehabilitation principles. This framework bases the assessment on measuring actual movement time, coordination, range of motion, grip strength, force modulation, and bilateral symmetry during task-oriented exercises.

The system is supported by a phone application that provides instant feedback, session summaries, progress tracking, and remote monitoring by therapists. By integrating assessment directly into functional training assignments, the HOPE program bridges the gap between patient assessment and traditional assessment methods, enhances patient monitoring, and supports longitudinal monitoring in both clinical and home settings.

Abstract

Mangroves are critical coastal ecosystems, particularly in arid regions like Bahrain where Avicennia marina predominates. Studying bacterial diversity in natural and planted mangrove soils is vital because microbes drive nutrient cycling and ecosystem functioning. This study isolated and characterized bacteria from four mangrove sites, examining the influence of soil factors such as pH, salinity, temperature, and conductivity on microbial communities. Soil temperatures ranged from 26.5 to 32.8 °C, with Ras Tubli showing the highest temperature. Measured salinity and conductivity values were unusually low compared to typical Avicennia marina and Bahrain mangrove conditions, likely due to delays in sample analysis, and therefore are not reliable. Soil pH was consistently alkaline (8.0–8.3), typical of coastal environments.

Natural mangrove soils appeared to have higher bacterial diversity compared to planted sites, suggesting that ecosystem maturity could influence microbial community composition. Based on biochemical tests including IMViC (for Gram-negative bacteria), isolates were tentatively affiliated with genera such as Staphylococcus among Gram-positive cocci; Bacillus, Lactobacillus, and Clostridium among Gram-positive bacilli; and Citrobacter, Enterobacter, Klebsiella, Acinetobacter, Moraxella, and possibly Neisseria among Gram-negative bacteria.

Antibiotic susceptibility testing of coccoid isolates revealed variable sensitivity patterns. However, culture-dependent methods limited the scope of bacterial identification and did not allow for specific species-level identification. These findings contribute to understanding microbial diversity in Bahrain’s mangrove soils and highlight the value of molecular approaches such as 16S rRNA sequencing, for further investigation.