Background: There are only a few case reports and small case series on neonatal-onset Dubin–Johnson syndrome (DJS), particularly from Far-East Asia, Iranian and Moroccan Jews, and Europe.Objectives: In this first study from the Arabs and the largest series reported to date, we characterized the clinical, laboratory, and molecular features and outcome of gene-confirmed neonatal-onset DJS.Methods: We reviewed our database of 533 cases of neonatal cholestasis that presented to our center during the period from 2008 to 2019. We identified neonates with a disease-causing mutation in ABCC2 gene.Results: Twenty-eight neonates with DJS were diagnosed (5.3%). All of the 28 were full-term, well looking neonates without hepatosplenomegaly, with cholestasis, and normal liver synthetic function since the 1 week of life that resolved within 3–6 months of age, followed by a benign course punctuated by recurrent episodes of jaundice in 43% during a median follow up period of 9.25 (range 2.5–14 years). Alanine aminotransferase levels were within normal range in 26 patients (92%) and mildly elevated in two patients. ALT levels were significantly lower in neonates with DJS than in other cases with neonatal cholestasis from other causes (p < 0.001). The median urinary coproporphyrin I% was 88% (IQ1–IQ3 = 84.2–92.7%). We identified four homozygous variants in the ABCC2 gene (from 22 unrelated families), one splicing variant (c.3258+1G>A; p.?), and three were missense variants; two of which were novel missense variants [c.1594G>A (p.Glu532Lys) and c.2439G>C (p.Lys813Asn)]. The p.Gly758Val mutation has occurred in 23 patients (from 19 unrelated families).Conclusions: Our study suggests that normal ALT-cholestasis in a well-looking neonate should trigger evaluation for DJS. The p.Gly758Val variant in ABCC2 is the most predominant mutation among Arabs with “founder effects.” Identification of the predominant ABCC2 variant in any population is likely to facilitate rapid molecular analysis by future targeting of that specific mutation.

Introduction Mental stigma is when patients of mental illness are labeled by their disorders, viewed negatively, and discriminated against due to their illness. This has a big impact on people's attitudes and behaviors toward the mentally ill. Moreover, mental stigma leads people to avoid patients with mental health issues, blame them for their conditions, and associate them with negative features like being dangerous, unpredictable, and hard to communicate with. The primary objective of this study is to assess the mental stigma among the population of the Al-Ahsa region in Saudi Arabia. Methods This is a cross-sectional study conducted in Al-Ahsa, Saudi Arabia, between June and August 2021. The target population of the study was people aged 18-65 years old whose place of residency during the time of the study was Al-Ahsa. The questionnaire used in this study contained a mental stigma scale called community attitudes toward mental illness (CAMI). Results A total of 758 participants were enrolled in the study. The mean of the stigma score was 99.24 ± 15.622, with a minimum of 53 and a maximum of 176. The means of the subscales were as follows: authoritarianism (26.18 ± 4.420), benevolence (23.26 ± 4.762), community mental health ideology (24.66 ± 5.896), and social restrictiveness (25.13 ± 4.6). There was a positive relationship between age and stigma score. Healthcare workers were found to have a lower level of stigma, as were those who spoke more languages. Also, being diagnosed with a mental illness and knowing someone who is diagnosed with a mental illness were associated with a lower level of stigma. Conclusion Most of the population (91.96%) had a low to medium-low level of stigma. The variables found to affect the level of stigma were age, career, number of spoken languages, being diagnosed with a mental illness, and knowing someone who is diagnosed with a mental illness. Mental stigma has a great impact on the person, as it can prevent the patient from seeking help, lead to isolation, and suicidal ideation. Future stigma-targeted campaigns are recommended.

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Mud motors are widely used in directional drilling and their failure during operation leads to costly non-productive time. There is currently no existing literature investigating the correlation between stalls detected using downhole sensors and concurrent signals produced in surface sensor data. Current motor stall detection algorithms using surface sensors are still rudimentary and error-prone. The objective of this study was to develop a robust stall detection algorithm using insights gained from correlating downhole and surface data. Previous studies have indicated that stalls are a major contributing factor to elastomer damage in a mud motor. Using downhole sensor datasets from multiple operators, we first identified all instances of motor stalls. These events are typically characterized by a sudden reduction in downhole vibration and rotation at the bit, accompanied by a sudden increase in torque. We then proceeded to map these stall events to time-synchronized surface data to identify the associated behavior of surface parameters during a stall, noting the differences in behavior during rotary and slide drilling periods. We analyzed 268 distinct stall events in the downhole data as well as several clusters of micro-stalls (characterized by a momentary spike in downhole torque coupled with a downward spike in downhole RPM that last less than one second, typically lasting for a few milliseconds at most). Mapping these events to the surface data helped identify a set of primary signals produced at the surface during every motor stall, and secondary signals that are produced in a majority of motor stalls. The primary surface signals we observed during a stall included a sharp spike in differential pressure and a sharp decline in weight on bit (WOB), typically within a 10-second window. Secondary surface signal observed in over 70% of motor stalls include decrease in rate of penetration (ROP). Statistical analysis of the downhole and surface signals demonstrated a strong correlation (p < 0.05) between the length of a motor stall and the magnitude of the differential pressure increase produced at the surface. Our analysis of stalls in downhole datasets demonstrated that the vast majority of surface-detectable stalls occurred during slide drilling, while rotary drilling contained significant clusters of micro-stall events that were too short to produce identifiable signals at the surface. This study builds upon existing literature and understanding of mud motor failure by correlating time-synchronized events in downhole and surface data. We have compiled our observations to create a comprehensive framework for detecting motor stalls at the surface using a set of surface signals. Our findings establish a robust way to detect motor stalls from surface data, which should be of significant value to lower-cost well construction operations and real-time monitoring of drilling operations.

Abstract-This paper presents a survey study that explores the difference between an educational software based on a narrative style and another based on a traditional style in terms of students' engagement. For this investigation, two different questionnaires were distributed to students in two different crucial stages. In the first stage, a questionnaire was given to students to find out information about the stories they are reading in general and their desired story characteristics. An educational software based on both the preferred character and narrative style was developed for the purpose of this study. Then, another questionnaire was distributed to explore students' perceptions about both software styles. It is found that the educational software based on the narrative style better facilitate students' engagement comparing with educational software based on traditional style taken into account the kind of the character and story.Index Terms-Educational software, narrative style, traditional style. I. INTRODUCTIONProviding an interactive educational environment is becoming increasingly important. Visualization, modelling, simulation, and 3D graphics in computer-based applications or educational software are becoming influential tools for teaching various subjects. Educational systems are continuing to increase the use of information technologies, both in terms of hardware and software, for courses taught in schools. However, interaction is one of the most essential principles in designing educational software [1]. The implementation of this principle can be dealt with as an art. It requires an inclusive range of skills which include an understanding of the nature of students, software engineering, the current design basics and learning methodologies in education, and knowledge of the aesthetic design principles for the multimedia application interfaces. This will create an interactive educational environment that will ensure the students" engagement [1]. The objective of educational software is to effectively enhance the knowledge of students.This paper compares the use of educational software based on a narrative style and another based on a traditional style in terms of students" engagement. It discusses a survey study exploring the perceptions of sixth elementary grade students regarding the use of narrative and traditional educational software in learning English as a foreign language. Manuscript received September 13, 2014; revised November 15, 2014. M. Alameer is with the Ministry of Higher Education, Riyadh, Saudi Arabia (e-mail: mameer@mohe.gov.sa).T. Alhussain is with Saudi Electronic University, Riyadh, Saudi Arabia (e-mail: talhussain@seu.edu.sa). II. LITERETURE REVIEW A. Educational SoftwareMacFarlane et al. present the general objective of educational software for students as providing "an engaging learning environment and keeping children"s attention by providing fun" [2]. Fun, particularly with children, is normally achieved through games. However, adopting Information technology into educa...