Search results for: Saudi Arabia Vision 2030

Authors: Afnan T. Bagasi, Donia M. Bettaieb, Abeer Alsobahi

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The wayfinding system is related to the course of the museum journey for visitors directly and indirectly. The design aspects of this system play an important role, making it an effective and communication system within the museum space. However, translating the concepts that pertain to its design, such as Intelligibility that is based on integration and connectivity in museum space design, needs more customization in the form of specific design considerations with reference to the most important approaches. Those approaches link the organizational and practical aspects to the semiotic and semantic aspects related to the space syntax by targeting the visual and perceived consistency of visitors. In this context, the study aims to identify how to apply the concept of intelligibility and clarity by employing integration and connectivity to design a wayfinding system in museums as a kind of composite interior space. Using the available plans and images to extrapolate the design considerations used to design the wayfinding system in the Saudi National Museum as a case study, a descriptive-analytical method was used to understand the basic organizational and morphological principles of the museum space through four main aspects in space design: morphological, semantic, semiotic, and pragmatic. The study's findings will assist designers, professionals, and researchers in the field of museum design in understanding the significance of the wayfinding system by delving into it through museum spaces by highlighting the essential aspects using a clear analytical method.

Keywords: wayfinding system, museum journey, intelligibility, integration, connectivity

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Authors: Sarah Alshehri, Messedah Alqahtani

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Reading instruction in EFL classes is still challenging for teachers, and many students are still behind their expected level. Due to the Covid-19 pandemic, there was a shift in teaching English from face-to face to online classes. This paper will discover how the digital shift during and post pandemic has influenced English literacy instruction and what methods seem to be effective or challenging. Specifically, this paper will examine English language teachers' perspectives on the workable approaches and challenges that encountered them when teaching reading using E-Learning platform in Saudi Arabian Secondary and intermediate schools. The study explores public secondary school EFL teachers’ instructional practices and the challenges encountered when teaching reading online. Quantitative data will be collected through a 28 -item Likert type survey that will be administered to Saudi English teachers who work in public secondary and intermediate schools. The quantitative data will be analyzed using SPSS by conducting frequency distributions, descriptive statistics, reliability tests, and one-way ANOVA tests. The potential outcomes of this study will contribute to better understanding of digital literacy and technology integration in language teaching. Findings of this study can provide directions for professionals and policy makers to improve the quality of English teaching and learning. Limitations and results will be discussed, and suggestions for future directions will be offered.

Keywords: EFL reading, E-learning- EFL literacy, EFL workable approaches, EFL reading instruction

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Authors: Mohammed Asiri, Saleh Alsuwayt, Mohammed Bin Mugren, Abdulmalik Almufarrih, Tariq Alotaibi, Saad Almodameg

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Background: End-stage renal disease is a major public health concern with high incidence and mortality rate. Most of ESRD patients are on hemodialysis therapy which is a long-term treatment that disturbs patients’ lifestyle. As a result, he will be susceptible to develop psychiatric disorders like anxiety that may direct him to non-compliance on physician instructions and hemodialysis therapy. Although there are studies conducted on psychiatric issues in hemodialysis patients, but few studies focused on the effect of anxiety disorder and the patient’s compliance. Hence, we are interested in determining the prevalence of anxiety disorder among hemodialysis patients in Saudi Arabia, as well as in defining the correlation between anxiety disorder and compliance on physician instructions and hemodialysis therapy. We hypothesize that our study will show a higher prevalence of anxiety in hemodialysis patients than in general population. Also, we expect the anxiety to have a negative impact on their compliance. Methodology: We used a cross-sectional study design carried out at dialysis unit of four major hospitals in Riyadh, KSA. We interviewed 235 End Stage Renal Disease male and female patients who are on hemodialysis. We divided the patients into two categories according to their compliance. we used modified general questionnaire to get their demographic data, then we used a psychometric response scale called visual analog scale (VAS) to assess patient’s compliance to hemodialysis and physician’s instructions. Also, we used the Arabic validated version of the hospital anxiety and depression scale (HAD scale) used mainly for anxiety assessment. Results: The overall response rate was 54%. Respondents included 147 (62.6%) males and 88 (37.4%) females. The prevalence of anxiety among hemodialysis patients is 13.3%. According to visual analog scale, we found that 189 compliant patients and 45 non-compliant patients. For HAD scale, the mean ± standard deviation of the total score for females was (4.44 ± 4.7) and it’s higher than males which was 2.65 ± 3.08 (P-value= 0.002). The mean ± standard deviation of HAD score in the non-compliant group was (5.88  4.88) and it was higher than the compliant group (2.7  3.32) (P-value= 0.004). Among non-complaint group, 33.3% of anxious patients were males and 66.6% were females. There was a negative correlation between HAD score of anxiety and visual analog scale (R= - 0.285). Conclusion: We conclude that there is a high prevalence of anxiety among patients with End Stage Renal Disease that was higher in females with association of non-compliance to physician’s instructions and hemodialysis therapy.

Keywords: anxiety, end-stage renal disease, renal failure, anxiety disorder

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Authors: Ali Showail Ali Alasmari

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Introduction: Cataract is the loss of transparency of the lens inside the eye. It is the most common cause of visual loss and blindness worldwide. This study provides a systemic review of the recent findings on the association of vitamin D, and vitamin B12, and their possible role in preventing cataracts in senile (S) and diabetic mellitus (DM) patient groups. Objective: This study was intended to establish and investigate if there is any role between vitamin D and vitamin B12? Secondly, the connection between serum level of vitamin D and vitamin B12 in cataract incidence senile (s) vs. diabetic mellitus (DM) cataract patient groups. Furthermore, to evaluate and analyze cataract occurrence regarding vitamin D and vitamin B12 levels with other risk factors. Finally, to evaluate lens opacities pre and post treatment with vitamin D and vitaminB12 linked to age and visual acuity loss in both senile(S) and diabetic mellitus (DM) cataract patients’ groups. Methods: This study conducted at the ophthalmology clinic at Muhyail General Hospital. Select a prospective case-control to study the effect of vitamin D and Vit B12 on senile(S) cataracts that caused by age and diabetic mellitus (DM)cataract patients; then we compare these two groups. This study prospectively enrolled a total of 50 samples, 25 with senile cataract and 25 with diabetic cataract, from ophthalmology clinic at Muhyail General Hospital. Measuring 25-hydroxy vitamin D and vitamin B12 level concentrations in the assigned samples. Analyses were performed using SAS (statistical analysis software) program. Results: The most important finding in this study was that the senile(s) cataract patients’ group greatly benefited by the combination therapy of vitamin D, and Vitamin B12 reached (28.5±1.50 and 521.1±21.10) respectively; on the contrary, the diabetic cataract patient group hardly shows any significant improvement (21.5 ± 1.00 and 197.2 ± 7.20) respectively. This is because of the Metformin, the first line drug for treating diabetes, has been reported to potentially decrease vitamin B-12 status. This epigenetic modification was correlated with the diabetic mellitus (DM) cataract patients’ group not responding. Vitamin B12 deficiency also leads to an impairment of the conversion of methylmalonyl-CoA to succinyl-CoA, which has been associated with insulin resistance. There was no significant difference between the age, body mass index (BMI), the mean of Vit-D pre-treatments, and the mean values of Hemoglobin A1C of both senile (S) and diabetic mellitus (DM) cataract patient groups. On other hand, there was a highly significant difference between the mean values of glucose levels in both senile (S) and diabetic mellitus (DM) cataract patient groups. Conclusion: Here we conclude that diabetic mellitus (DM) cataract patient group hardly benefited from this combination therapy vitamin D and vitamin B12; on the other hand senile patient group (s) benefited a lot from the therapy.

Keywords: cataract patients, senile, diabetes mellitus, vitamin B12, vitamin D, Muhyail General Hospital, Saudi Arabia

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Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Alexandre Faure, Yoko Mizokami, éRic Dinet

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These recent years, the potential of light in assisting visually impaired people in their indoor mobility has been demonstrated by different studies. Implementing smart lighting systems for selective visual enhancement, especially designed for low-vision people, is an approach that breaks with the existing visual aids. The appearance of the surface of an object is significantly influenced by the lighting conditions and the constituent materials of the objects. Appearance of objects may appear to be different from expectation. Therefore, lighting conditions lead to an important part of accurate material recognition. The main objective of this work was to investigate the effect of the spatial distribution of light on object identification in the context of low vision. The purpose was to determine whether and what specific lighting approaches should be preferred for visually impaired people. A psychophysical experiment was designed to study the ability of individuals to identify the smallest cube of a pair under different lighting diffusion conditions. Participants were divided into two distinct groups: a reference group of observers with normal or corrected-to-normal visual acuity and a test group, in which observers were required to wear visual impairment simulation glasses. All participants were presented with pairs of cubes in a "miniature room" and were instructed to estimate the relative size of the two cubes. The miniature room replicates real-life settings, adorned with decorations and separated from external light sources by black curtains. The correlated color temperature was set to 6000 K, and the horizontal illuminance at the object level at approximately 240 lux. The objects presented for comparison consisted of 11 white cubes and 11 black cubes of different sizes manufactured with a 3D printer. Participants were seated 60 cm away from the objects. Two different levels of light diffuseness were implemented. After receiving instructions, participants were asked to judge whether the two presented cubes were the same size or if one was smaller. They provided one of five possible answers: "Left one is smaller," "Left one is smaller but unsure," "Same size," "Right one is smaller," or "Right one is smaller but unsure.". The method of constant stimuli was used, presenting stimulus pairs in a random order to prevent learning and expectation biases. Each pair consisted of a comparison stimulus and a reference cube. A psychometric function was constructed to link stimulus value with the frequency of correct detection, aiming to determine the 50% correct detection threshold. Collected data were analyzed through graphs illustrating participants' responses to stimuli, with accuracy increasing as the size difference between cubes grew. Statistical analyses, including 2-way ANOVA tests, showed that light diffuseness had no significant impact on the difference threshold, whereas object color had a significant influence in low vision scenarios. The first results and trends derived from this pilot experiment clearly and strongly suggest that future investigations could explore extreme diffusion conditions to comprehensively assess the impact of diffusion on object identification. For example, the first findings related to light diffuseness may be attributed to the range of manipulation, emphasizing the need to explore how other lighting-related factors interact with diffuseness.

Keywords: Lighting, Low Vision, Visual Aid, Object Identification, Psychophysical Experiment

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Authors: Ali H.Alyami, Hussam Darraj, Faisal Hakami, Mohammed Awaf, Sulaiman Hamdi, Nawaf Bakri, Abdulaziz Saber, Khalid Hakami, Almuhanad Alyami, Mohammed khashab

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Introduction: Adolescents frequently self-report pain, according to epidemiological research. The knee is one of the sites where the pain is most common. One of the main factors contributing to the number of years people spend disabled and having substantial personal, societal, and economic burdens globally are musculoskeletal disorders. Adolescents may have knee pain due to an abrupt, traumatic injury or an insidious, slowly building onset that neither the adolescent nor the parent is aware of. Objectives: The present study’s authors aimed to estimate the prevalence of knee pain in Saudi adolescents. Methods: This cross-sectional survey, carried out from June to November 2022, included 676 adolescents ages 10 to 18. Data are presented as frequencies and percentages for categorical variables. Analysis of variance (ANOVA) was used to compare means between groups, while the chi-square test was used for the comparison of categorical variables. Statistical significance was set at P< 0.05.Result: Adolescents were invited to take part in the study. 57.5% were girls, and 42.5% were males,68.8% were 676 aged between 15 and 18. The prevalence of knee pain was considerably high among females (26%), while it was 19.2% among males. Moreover, age was a significant predictor for knee pain; also BMI was significant for knee pain. Conclusion: Our study noted a high rate of knee pain among adolescents, so we need to raise awareness about risk factors. Adolescent knee pain can be prevented with conservative methods and some minor lifestyle/activity modifications.

Keywords: knee pain, prevalence of knee pain, exercise training, physical activity

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Jamilah Ahmad

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In 2023, Malaysia's International Trade and Industry Ministry (MITI) introduced the i-ESG framework to establish environmental, social, and governance (ESG) standards to enhance organisations' ethical conduct and social responsibility. The role of education, particularly universities, is crucial in preparing future generations to understand the significance of ESG and confront sustainability challenges. This study employs a mixed-methods approach, utilizing semi-structured interviews with university leaders and students to investigate the implementation of University Social Responsibility (USR) in Malaysian universities and the impact of ESG on sustainable development in alignment with Malaysia's SDG Agenda 2030. The findings underscore the critical role of USR and ESG in fostering sustainable development, ensuring that graduates are well-equipped to address environmental and sustainability issues in Malaysia.

Keywords: USR, ESG, sustainability, higher education in Malaysia, Malaysia

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Authors: Naser B. Almari, Salem S. Alghamdi, Muhammad Afzal, Mohamed Helmy El Shal

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Wheat landraces are a rich genetic resource for boosting agronomic qualities in breeding programs while also providing diversity and unique adaptation to local environmental conditions. These genotypes have grown increasingly important in the face of recent climate change challenges. This research aimed to look at the genetic diversity of Saudi Durum wheat landraces using morpho-phenological and molecular data. The principal components analysis (PCA) analysis recorded 78.47 % variance and 1.064 eigenvalues for the first six PCs of the total, respectively. The significant characters contributed more to the diversity are the length of owns at the tip relative to the length of the ear, culm: glaucosity of the neck, flag leaf: glaucosity of the sheath, flag leaf: anthocyanin coloration of auricles, plant: frequency of plants with recurved flag leaves, ear: length, and ear: shape in profile in the PC1. The significant wheat genotypes contributed more in the PC1 (8, 14, 497, 650, 569, 590, 594, 598, 600, 601, and 604). The cluster analysis recorded an 85.42 cophenetic correlation among the 22 wheat genotypes and grouped the genotypes into two main groups. Group, I contain 8 genotypes, however, the 2nd group contains 12 wheat genotypes, while two genotypes (13 and 497) are standing alone in the dendrogram and unable to make a group with any one of the genotypes. The second group was subdivided into two subgroups. The genotypes (14, 602, and 600) were present in the second sub-group. The genotypes were grouped into two main groups. The first group contains 17 genotypes, while the second group contains 3 (8, 977, and 594) wheat genotypes. The genotype (602) was standing alone and unable to make a group with any wheat genotype. The genotypes 650 and 13 also stand alone in the first group. Using the Mantel test, the data recorded a significant (R2 = 0.0006) correlation (phenotypic and genetic) among 22 wheat durum genotypes.

Keywords: durum wheat, PCA, cluster analysis, SRAP, genetic diversity

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Authors: Huda Arshadlamphon

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Advancing frontiers of technology and industry is moving rapidly fast influenced by the economic and political phenomena. One vital phenomenon,which has had consolidated the world to a one single village, is Globalization. In response, architecture and the built-environment have faced numerous changes, adjustments, and developments. Tall-buildings, as a product of globalization, represent prestigious icons, symbols, and landmarks for highly economics and advanced countries. Despite the fact, this trend has been encountering several design challenges incorporating architectural identity, traditions, and characteristics that enhance the built-environments' sociocultural values and traditions. The necessity of these values and traditionsform self-solitarily, leading to visual and spatial creativity, independency, and individuality. In other words, they maintain the inherited identity and avoid replications in all means and aspects. This paper, firstly, defines globalization phenomenon, architectural identity, and the concerns of sociocultural values in relation to the traditional characteristics of the built-environment. Secondly, through three case-studies of tall-buildings located in Jeddah city, Saudi Arabia, the Queen's Building, the National Commercial Bank Building (NCB), and the Islamic Development Bank Building; design strategies and methodologies in acclimating architectural identity and characteristics in tall-buildings are discussed. The case-studies highlight buildings' sites and surroundings, concepts and inspirations, design elements, architectural forms and compositions, characteristics, issues, barriers, and trammels facing the designs' decisions, representation of facades, and selection of materials and colors. Furthermore, the research will elucidate briefs of the dominant factors that shape the architectural identity of Jeddah city. In conclusion, the study manifests four tall-buildings' design standards guideline in preserving and developing architectural identity in Jeddah city; the scale of urban and natural environment, the scale of architectural design elements, the integration of visual images, and the creation of spatial scenes and scenarios. The prosed guideline will encourage the development of architectural identity aligned with zeitgeist demands and requirements, supports the contemporary architectural movement toward tall-buildings, and shoresself-solitarily in representing sociocultural values and traditions of the built-environment.

Keywords: architectural identity, built-environment, globalization, sociocultural values and traditions, tall-buildings

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Authors: Mai Alharthy, Agnes Shiel, Hynes Sinead

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Objectives: The objectives of the study are to translate and culturally adapt the RBMT-3 to be appropriate for use within an Arabic-speaking population and to achieve maximum equivalency between the translated and original versions and to evaluate the psychometric properties of the Arabic version of the RBMT-3. Participants' numbers are 16 (10 females and 6 males). All participants are bilingual speakers of Arabic and English, above 18 years old and with no current nor past memory impairment. Methods: The study was conducted in two stages: Translation and cultural adaptation stage: Forward and backward translations were completed by professional translators. Five out of the 14 RBMT-3 subtests required cultural adaptations. Half of the faces in the face recognition subtests were replaced with Arabic faces by a professional photographer. Pictures that are irrelevant to the Arabic culture in the picture recognition subtests were replaced. Names, story and orientations subtests were also adapted to suit the Arabic culture. An expert committee was formed to compare the translated and original versions and to advise on further changes required for test materials. Validation of the Arabic RBMT-3- pilot: 16 Participants were tested on version 1 of the English version and the two versions of the Arabic RBMT-3 ( counterbalanced ). The assessment period was 6 weeks long, with two weeks gap between tests. All assessments took place in a quiet room in the National University of Ireland Galway. Two qualified occupational therapists completed the assessments. Results: Wilcox signed-rank test was used to compare between subtest scores. Significant differences were found in the story, orientation and names subtests between the English and Arabic versions. No significant differences were found in subtests from both Arabic versions except for the story subtest. Conclusion: The story and orientation subtests should be revised by the expert committee members to make further adaptations. The rest of the Arabic RBMT-3 subtests are equivalent to the subtests of the English version. The psychometric properties of the Arabic RBMT-3 will be investigated in a larger Arabic-speaking sample in Saudi Arabia. The outcome of this research is to provide clinicians and researchers with a reliable tool to assess memory problems in Arabic speaking population.

Keywords: memory impairment, neuropsychological assessment, cultural adaptation, cognitive assessment

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Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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Authors: Shuruq Ghazi Nahhas

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Islamic art is a decorative art that depends on repeating motifs in various shapes to cover different surfaces. Each motif has its own characteristics and style that may reflect different Islamic periods, such as Umayyad, Abbasid, Fatimid, Seljuk, Nasrid, Ottoman, and Safavid. These periods were the most powerful periods which played an important role in developing the Islamic motifs. Most of these motifs of the Islamic heritage were not used in new applications. This research focused on reviving the vegetal Islamic motifs found on Islamic heritage and redesign them in a new format to decorate various products, including scarfs, cushions, coasters, wallpaper, wall art, and boxes. The scarf is chosen as one element of these decorative products because it is used as accessories to add aesthetic value to fashion. A descriptive-analytical method is used for this research. The process started with extracting and analyzing the original motifs. Then, creating the new motifs by simplifying, deleting, or adding elements based on the original structure. Then, creating repeated patterns and applying them to decorative products. The findings of this research indicated: repeating patterns based on different structures creates unlimited patterns. Also, changing the elements of the motifs of a pattern adds new characteristics to the pattern. Also, creating frames using elements from the repeated motifs adds aesthetic and contemporary value to decorative products. Finally, using various methods of combining colors creates unlimited variations of each pattern. At the end, reviving the Islamic motifs in contemporary vision enriches decorative products with aesthetic, artistic, and historical values of different Islamic periods. This makes the decorative products valuable that adds uniqueness to their surroundings.

Keywords: Islamic motifs, contemporary patterns, scarfs, decorative products

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Authors: Bander Mohayya Alotaibi

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The valuable partnerships between parents and teachers may develop positive and effective interactions between home and school. This will help these stakeholders share information and resources regarding student academics during ongoing interactions. Thus, partnerships will build a solid foundation for both families and schools to help children succeed in school. Parental involvement can be seen as an effective tool that can change homes and communities and not just schools’ systems. Seeking parents and stakeholders’ attitudes toward learning and learners can help schools design a curriculum. Subsequently, this information can be used to find ways to help improve the academic performance of students, especially in low performing schools. There may be some conflicts when designing curriculum. In addition, designing curriculum might bring more educational expectations to all the sides. There is a lack of research that targets the specific attitude of parents toward specific concepts on curriculum contents. More research is needed to study the perspective that parents of children with learning disabilities (LD) have regarding early reading curriculum. Parents and stakeholders’ perspectives on early reading intervention implemented as a curriculum for children with LD was studied through an advanced quantitative research. The purpose of this study seeks to understand stakeholders and parents’ perspectives of key concepts and essential early reading skills that impact the design of curriculum that will serve as an intervention for early struggler readers who have LD. Those concepts or stages include phonics, phonological awareness, and reading fluency as well as strategies used in house by parents. A survey instrument was used to gather the data. Participants were recruited through 29 schools and districts of the metropolitan area of the northern part of Saudi Arabia. Participants were stakeholders including parents of children with learning disability. Data were collected using distribution of paper and pen survey to schools. Psychometric properties of the instrument were evaluated for the validity and reliability of the survey; face validity, content validity, and construct validity including an Exploratory Factor Analysis were used to shape and reevaluate the structure of the instrument. Multivariate analysis of variance (MANOVA) used to find differences between the variables. The study reported the results of the perspectives of stakeholders toward reading strategies, phonics, phonological awareness, and reading fluency. Also, suggestions and limitations are discussed.

Keywords: stakeholders, learning disability, early reading, perspectives, parents, intervention, curriculum

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Hana Aljumayi, Mohammed Issa

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The aim of this study was to investigate the effect of the training program for professional athletes at the Saudi Archery Federation on the electrical activity of the muscles involved in pulling the bowstring, maximum muscle strength (MVC) and to identify the relationship between the electrical activity of these muscles and accuracy in shooting among female archers. The researcher used a descriptive approach that was suitable for the nature of the study, and a sample of nine female archers was selected using purposive sampling. An EMG device was used to measure signal amplitude, signal frequency, spectral energy signal, and MVC. The results showed statistically significant differences in signal amplitude among muscles, with F(8,1)=5.91 and a significance level of 0.02. There were also statistically significant differences between muscles in terms of signal frequency, with F(8,1)=8.23 and a significance level of 0.02. Bonferroni test results indicated statistically significant differences between measurements at a significance level of 0.05, with anterior measurements showing an average difference of 16.4 compared to other measurements. Furthermore, there was a significant negative correlation between signal amplitude in the calf muscle and accuracy in shooting (r=-0.78) at a significance level of 0.02. There was also a significant positive correlation between signal frequency in the calf muscle and accuracy in shooting (r=0.72) at a significance level of 0.04. In conclusion, it appears that the training program for archery athletes focused more on skill development than physical aspects such as muscle activity and strength development. However, it did have a statistically significant effect on signal amplitude but not on signal frequency or MVC development in muscles involved in pulling the bowstring.

Keywords: electrical activity of muscles, archery sport, shooting accuracy, muscles

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Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

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Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: M. A. Zaki Ewiss, S. Afifi

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Nahda University (NUB) believes that internationalisation of higher educational is able to provide global society with an education that meets current needs and that can respond efficiently to contemporary demands and challenges, which are characterized by globalisation, interdependence, and multiculturalism. In this paper, we will discuss the the challenges of the Egyptian Higher Education system and the future vision to improve this system> In this report, the following issues will be considered: Increasing knowledge on the development of specialized programs of study at the university. Developing international cooperation programs, which focus on the development of the students and staff skills, and providing academic culture and learning opportunities. Increasing the opportunities for student mobility, and research projects for faculty members. Increased opportunities for staff, faculty and students to continue to learn foreign universities, and to benefit from scholarships in various disciplines. Taking the advantage of the educational experience and modern teaching methods; Providing the opportunities to study abroad without increasing the period of time required for graduation, and through greater integration in the curricula and programs; More cultural interaction through student exchanges.Improving and providing job opportunities for graduates through participation in the global labor market. This document sets out NUB strategy to move towards that vision. We are confident that greater explicit differentiation, greater freedom and greater collaboration are the keys to delivering the further improvement in quality we shall need to retain and strengthen our position as one of the world’s leading higher education systems.

Keywords: technology transfer higher education, knowledge transfer, internationalisation, mobility

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Authors: Khulud Alhussain, Anna Gavine, Stephen Macgillivray, Sushila Chowdhry

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Background: Estimates show that by the year 2030, mental illness will account for more than half of the global economic burden, second to non-communicable diseases. Often, the perinatal period is characterised by psychological ambivalence and a mixed anxiety-depressive condition. Maternal mental disorder is associated with perinatal anxiety and depression and affects breastfeeding behaviors. Studies also indicate that maternal mental health can considerably influence a baby's health in numerous aspects and impact the newborn health due to lack of adequate breastfeeding. However, studies reporting factors associated with breastfeeding behaviors are predominantly quantitative. Therefore, it is not clear what literature is available to understand the factors affecting breastfeeding and perinatal women’s perspectives and experiences. Aim: This review aimed to explore the perceptions and experiences of women with perinatal anxiety and depression, as well as how these experiences influence their breastfeeding behaviours. Methods: A systematic literature review of qualitative studies in line with the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ). Four electronic databases (CINAHL, PsycINFO, Embase, and Google Scholar) were explored for relevant studies using a search strategy. The search was restricted to studies published in the English language between 2000 and 2022. Findings from the literature were screened using a pre-defined screening criterion and the quality of eligible studies was appraised using the Walsh and Downe (2006) checklist. Findings were extracted and synthesised based on Braun and Clark. The review protocol was registered on PROSPERO (Ref: CRD42022319609). Result: A total of 4947 studies were identified from the four databases. Following duplicate removal and screening 16 studies met the inclusion criteria. The studies included 87 pregnant and 302 post-partum women from 12 countries. The participants were from a variety of economic, regional, and religious backgrounds, mainly from the age of 18 to 45 years old. Three main themes were identified: Barriers to breastfeeding, breastfeeding facilitators, emotional disturbance, and breastfeeding. Seven subthemes emerged from the data: expectation versus reality, uncertainly about maternal competencies, body image and breastfeeding, lack of sufficient breastfeeding support for family and caregivers’ support, influences positive breastfeeding practices, breastfeeding education, and causes of mental strain among breastfeeding women. Breastfeeding duration is affected in women with mental health disorders, irrespective of their desire to breastfeed. Conclusion: There is significant empirical evidence that breastfeeding behaviour and perinatal mental disturbance are linked. However, there is a lack of evidence to apply the findings to Saudi women due to lack of empirical qualitative information. To improve the psychological well-being of mothers, it is crucial to explore and recognise any concerns with their mental, physical, and emotional well-being. Therefore, robust research is needed so that breastfeeding intervention researchers and policymakers can focus on specifically what needs to be done to help mentally distressed perinatal women and their new-born.

Keywords: pregnancy, perinatal period, anxiety, depression, emotional disturbance, breastfeeding

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Authors: Ohud Adnan Saffar

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This study aims to know the effect of using universal design for learning (UDL) to improve the quality of vocational programme with intellectual disabilities (SID) and the challenges facing this method from the teachers' point of view. The significance of the study: There are comparatively few published studies on UDL in emerging nations. Therefore, this study will encourage the researchers to consider a new approaches teaching. Development of this study will contribute significant information on the cognitively disabled community on a universal scope. In order to collect and evaluate the data and for the verification of the results, this study has been used the mixed research method, by using two groups comparison method. To answer the study questions, we were used the questionnaire, lists of observations, open questions, and pre and post-test. Thus, the study explored the advantages and drawbacks, and know about the impact of using the UDL method on integrating SID with students non-special education needs in the same classroom. Those aims were realized by developing a workshop to explain the three principles of the UDL and train (16) teachers in how to apply this method to teach (12) students non-special education needs and the (12) SID in the same classroom, then take their opinion by using the questionnaire and questions. Finally, this research will explore the effects of the UDL on the teaching of professional photography skills for the SID in Saudi Arabia. To achieve this goal, the research method was a comparison of the performance of the SID using the UDL method with that of female students with the same challenges applying other strategies by teachers in control and experiment groups, we used the observation lists, pre and post-test. Initial results: It is clear from the previous response to the participants that most of the answers confirmed that the use of UDL achieves the principle of inclusion between the SID and students non-special education needs by 93.8%. In addition, the results show that the majority of the sampled people see that the most important advantages of using UDL in teaching are creating an interactive environment with using new and various teaching methods, with a percentage of 56.2%. Following this result, the UDL is useful for integrating students with general education, with a percentage of 31.2%. Moreover, the finding indicates to improve understanding through using the new technology and exchanging the primitive ways of teaching with the new ones, with a percentage of 25%. The result shows the percentages of the sampled people's opinions about the financial obstacles, and it concluded that the majority see that the cost is high and there is no computer maintenance available, with 50%. There are no smart devices in schools to help in implementing and applying for the program, with a percentage of 43.8%.

Keywords: universal design for learning, intellectual disabilities, vocational programme, the challenges facing this method

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Authors: Vladimir A. Rozov

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Comparative studies of religion and ritual could contribute better understanding of human culture universalities. Belief in supernatural beings seems to be a common feature of the religion. A significant part of the Islamic concepts that concern supernatural beings is based on a tradition based on the Hadiths. They reflect, among other things, his ideas about a proper way to interact with supernatural beings. These ideas to a large extent follow from the pre-Islamic religious experience of the Arabs and had been reflected in a number of ritual actions. Some of those beliefs concern a particular function of clothing. For example, it is known that Muhammad was wrapped in clothes during the revelation of the Quran. The same thing was performed by pre-Islamic soothsayers (kāhin) and by rival opponents of Muhammad during their trances. Muhammad also turned the clothes inside out during religious rituals (prayer for rain). Besides these specific ways of clothing which prove the external similarity of Muhammad with the soothsayers and other people who claimed the connection with supernatural forces, the pre-Islamic soothsayers had another characteristic feature which is physical flaws. In this regard, it is worth to note Muhammad's so-called "Seal the Prophecy" (h̠ ātam an- nubūwwa) -protrusion or outgrowth on his back. Another interesting feature of Muhammad's behavior was his attitude to eating onion and garlic. In particular, the Prophet didn`t eat them and forbade people who had tasted these vegetables to enter mosques, until the smell ceases to be felt. The reason for this ban on eating onion and garlic is caused by a belief that the smell of these products prevents communication with otherworldly forces. The materials of the Hadith also suggest that Muhammad shared faith in the apotropical properties of water. Both of these ideas have parallels in other cultures of the world. Muhammad's actions supposed to provide an interaction with the supernatural beings are not accidental. They have parallels in the culture of pre-Islamic Arabia as well as in many past and present world cultures. The latter fact can be explained by the similarity of the universal human beliefs in supernatural beings and how they should be interacted with. Later a number of similar ideas shared by the Prophet Muhammad was legitimized by the Islamic tradition and formed the basis of popular Islamic rituals. Thus, these parallels emphasize the commonality of human notions of supernatural beings and also demonstrate the significance of the pre-Islamic cultural context in analyzing the genesis of Islamic religious beliefs.

Keywords: hadith, Prophet Muhammad, ritual, supernatural beings

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Authors: Xi Liu, Fan Yuan

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In the evolving landscape of physics-based machine learning (PBML), particularly within fluid dynamics and its applications in electromechanical engineering, robot vision, and robot learning, achieving precision and alignment with researchers' specific needs presents a formidable challenge. In response, this work proposes a methodology that integrates neural transformation with a modified smoothed particle hydrodynamics model for generating transformed 3D fluid simulations. This approach is useful for nanoscale science, where the unique and complex behaviors of viscoelastic medium demand accurate neurally-transformed simulations for materials understanding and manipulation. In electromechanical engineering, the method enhances the design and functionality of fluid-operated systems, particularly microfluidic devices, contributing to advancements in nanomaterial design, drug delivery systems, and more. The proposed approach also aligns with the principles of PBML, offering advantages such as multi-fluid stylization and consistent particle attribute transfer. This capability is valuable in various fields where the interaction of multiple fluid components is significant. Moreover, the application of neurally-transformed hydrodynamical models extends to manufacturing processes, such as the production of microelectromechanical systems, enhancing efficiency and cost-effectiveness. The system's ability to perform neural transfer on 3D fluid scenes using a deep learning algorithm alongside physical models further adds a layer of flexibility, allowing researchers to tailor simulations to specific needs across scientific and engineering disciplines.

Keywords: physics-based machine learning, robot vision, robot learning, hydrodynamics

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Authors: Natalya G. Filimonova, Mariya G. Ozerova, Irina N. Ermakova

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The long-term strategy of the economic development of Russia up to 2030 is based on the concept of sustainable growth. The determining factor of such development is complex changes in the economic system which may be achieved by making progressive changes in its structure. The structural changes determine the character and the direction of economic development, as well as they include all elements of this system without exception, and their regulated character ensures the most rapid aim achievement. This article has discussed the industrial structure of the agriculture in Russia. With the use of the system of indexes, the article has determined the directions, intensity, and speed of structural shifts. The influence of structural changes on agricultural production development has been found out. It is noticed that the changes in the industrial structure are synchronized with the changes in the organisation and economic structure. Efficiency assessment of structural changes allowed to trace the efficiency of structural changes and elaborate the main directions for agricultural policy improvement.

Keywords: Russian agricultural sectors, sectoral structure, organizational and economic structure, structural changes

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Authors: Inas Hussein

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Communication in the modern world is increasingly becoming multimodal due to globalization and the digital space we live in which have remarkably affected how people communicate. Accordingly, Multimodal Discourse Analysis (MDA) is an emerging paradigm in discourse studies with the underlying assumption that other semiotic resources such as images, colours, scientific symbolism, gestures, actions, music and sound, etc. combine with language in order to  communicate meaning. One of the effective multimodal media that combines both verbal and non-verbal elements to create meaning is political cartoons. Furthermore, since political and social issues are mirrored in political cartoons, these are regarded as potential objects of discourse analysis since they not only reflect the thoughts of the public but they also have the power to influence them. The aim of this paper is to analyze some selected cartoons on the recognition of Jerusalem as Israel's capital by the American President, Donald Trump, adopting a multimodal approach. More specifically, the present research examines how the various semiotic tools and resources utilized by the cartoonists function in projecting the intended meaning. Ten political cartoons, among a surge of editorial cartoons highlighted by the Anti-Defamation League (ADL) - an international Jewish non-governmental organization based in the United States - as publications in different Arabic-language newspapers in Egypt, Saudi Arabia, UAE, Oman, Iran and UK, were purposively selected for semiotic analysis. These editorial cartoons, all published during 6^th–18^th December 2017, invariably suggest one theme: Jewish and Israeli domination of the United States. The data were analyzed using the framework of Visual Social Semiotics. In accordance with this methodological framework, the selected visual compositions were analyzed in terms of three aspects of meaning: representational, interactive and compositional. In analyzing the selected cartoons, an interpretative approach is being adopted. This approach prioritizes depth to breadth and enables insightful analyses of the chosen cartoons. The findings of the study reveal that semiotic resources are key elements of political cartoons due to the inherent political communication they convey. It is proved that adequate interpretation of the three aspects of meaning is a prerequisite for understanding the intended meaning of political cartoons. It is recommended that further research should be conducted to provide more insightful analyses of political cartoons from a multimodal perspective.

Keywords: Multimodal Discourse Analysis (MDA), multimodal text, political cartoons, visual modality

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Authors: Ghaleb Bin Huraib, Fahad Al Harthi, Misbahul Arfin, Abdulrahman Al-Asmari

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Atopic dermatitis (AD), also known as atopic eczema, is a chronic inflammatory skin disease characterized by severe itching and recurrent relapsing eczema-like skin lesions, affecting up to 20% of children and 10% of adults in industrialized countries. AD is a complex multifactorial disease, and its exact etiology and pathogenesis have not been fully elucidated. The aim of this study was to investigate the impact of gene polymorphisms of T helper cell subtype Th1 and Th2 cytokines, interferon-gamma (IFN-γ), interleukin-6 (IL-6) and transforming growth factor (TGF)-β1on AD susceptibility in a Saudi cohort. One hundred four unrelated patients with AD and 195 healthy controls were genotyped for IFN-γ (874A/T), IL-6 (174G/C) and TGF-β1 (509C/T) polymorphisms using ARMS-PCR and PCR-RFLP technique. The frequency of genotypes AA and AT of IFN-γ (874A/T) differed significantly among patients and controls (P 0.001). The genotype AT was increased while genotype AA was decreased in AD patients as compared to controls. AD patients also had higher frequency of T containing genotypes (AT+TT) than controls (P = 0.001). The frequencies of allele T and A were statistically different in patients and controls (P = 0.04). The frequencies of genotype GG and allele G of IL-6 (174G/C) were significantly higher while genotype GC and allele C were lower in AD patients than controls. There was no significant difference in the frequencies of alleles and genotypes of TGF-β1 (509C/T) polymorphism between patient and control groups. These results showed that susceptibility to AD is influenced by presence or absence of genotypes of IFN-γ (874A/T) and IL-6 (174G/C) polymorphisms. It is concluded that T-allele and T-containing genotypes (AT+TT) of IFN-γ (874A/T) and G-allele and GG genotype ofIL-6 (174G/C) polymorphisms are susceptible to AD in Saudis.On the other hand, the TGF-β1 (509C/T) polymorphism may not be associated with AD risk in Saudi population however further studies with large sample size are required to confirm these findings.

Keywords: atopic dermatitis, interferon-γ, interleukin-6, transforming growth factor-β1, polymorphism

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Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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Authors: Amrita Mishra, Tushar Kanti Das

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Agriculture is the backbone of the economy of Odisha. Sustainability of agriculture holds the key for the development of Odisha. The Sustainable Development Goals are a framework of 17 goals and 169 targets across social, economical and environmental areas of sustainable development. Among all the seventeen goals the second goal is focusing on the promotion of Sustainable Agriculture. In this research our main aim is also to contribute an understanding of effectiveness of sustainable agriculture as a tool for rural development in the selected tribal district (i.e. Koraput and Malkangiri) of Odisha. These two districts are comes under KBK districts of Odisha which are identified as most backward districts of Odisha. The objectives of our study are to investigate the effect of sustainable agriculture on the lives of tribal farmers, to study whether the farmers are empowered by their participation in sustainable agriculture initiatives to move towards their own vision of development and to study the investment and profit ratio in sustainable agriculture. This research will help in filling the major gaps in sociological studies of sustainable agriculture. This information will helpful for farmers, development organisations, donors and policy makers in formulating the development of effective initiatives and policies to support the development of sustainable agriculture. In this study, we have taken 210 respondents and used various statistical techniques like chi-square test, one-way ANOVA and percentage analysis. This research shows that sustainable agriculture is an effective development strategy that benefits the tribal farmers to move towards their own vision of Good Fortune. The poor farmers who struggle to feed their families and maintain viable livelihoods on shrinking land for them sustainable agriculture are really benefited. The farmers are using homemade pesticides, manure and also getting the seeds from different development organisations and Government. So the investment in Sustainable Agriculture is very less. All farmers said their lives are now better than before. The creation of farmers groups for training and marketing for the produces was shown to be very important for empowerment.

Keywords: sustainable, agriculture, tribal farmers, development, empowerment

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Authors: Faraj Alhamami

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The effects of classroom input through structured input activities have been addressing two main lines of inquiry: (1) measuring the effects of structured input activities as a possible causative factor of PI and (2) comparing structured input practice versus other types of instruction or no-training controls. This line of research, the main purpose of this classroom-based research, was to establish which type of activities is the most effective in processing instruction, whether it is the explicit information component and referential activities only or the explicit information component and affective activities only or a combination of the two. The instruments were: a) grammatical judgment task, b) Picture-cued task, and c) a translation task as pre-tests, post-tests and delayed post-tests seven weeks after the intervention. While testing is ongoing, preliminary results shows that the examination of participants' pre-test performance showed that all five groups - the processing instruction including both activities (RA), Traditional group (TI), Referential group (R), Affective group (A), and Control group - performed at a comparable chance or baseline level across the three outcome measures. However, at the post-test stage, the RA, TI, R, and A groups demonstrated significant improvement compared to the Control group in all tasks. Furthermore, significant difference was observed among PI groups (RA, R, and A) at post-test and delayed post-test on some of the tasks when compared to traditional group. Therefore, the findings suggest that the use of the sole application and/or the combination of the structured input activities has succeeded in helping Saudi learners of English make initial form-meaning connections and acquire RRCs in the short and the long term.

Keywords: input processing, processing instruction, MOGUL, structure input activities

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