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Nuralam Sam,1 Irawan Yusuf,1 Irfan Idris,2 Endy Adnan,3 Ratna Darjanti Haryadi,4 Firdaus Hamid,5 Muhammad Andry Usman,6 Muhammad Phetrus Johan,6 Andi Alfian Zainuddin7 1Department of Physical Medicine and Rehabilitation, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia; 2Department of Physiology, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia; 3Rheumatology Division, Department of Internal Medicine, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia; 4Department of Physical Medicine and Rehabilitation, Faculty of Medicine, Airlangga University, Surabaya, Indonesia; 5Department of Microbiology, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia; 6Department of Orthopedic, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia; 7Department of Public Health, Faculty of Medicine, Hasanuddin University, Makassar, IndonesiaCorrespondence: Nuralam Sam, Department of Physical Medicine and Rehabilitation, Faculty of Medicine, Hasanuddin University, Perintis Kemerdekaan Street KM.11, Makassar, South Sulawesi, 90245, Indonesia, Email nuralamsam@unhas.ac.idAbstract: Frozen shoulder (FS) is a disease caused by an inflammatory condition that causes severe pain and decreased range of motion by loss of glenohumeral mobility. Frozen Shoulder restricts daily life’s functional aspect, increasing morbidity. Hypertension and diabetes mellitus are risk factors that make an FS poor prognosis during treatment because of the diabetes glycation process and hypertension-enhanced vascularization. Prolotherapy injects an irritant solution into the tendon, joints, ligaments, and joint spaces to release growth factors and collagen deposition, reducing pain, restoring joint stability, and increasing the quality of life. We report 3 cases of patients with confirmed FS. Patient A with no comorbidity, patient B with diabetes mellitus, and patient C with hypertension, with all patient’s chief complaints of shoulder pain and limited ROM, and symptoms affected the general quality of daily life. This patient was provided injection with Prolotherapy treatment combined with physical therapy intervention. Patient A had significantly improved ROM to maximum after 6 weeks with relieved pain and improved shoulder function. Patients B and C showed increased ROM, still tiny, decreased pain, and improved shoulder function. In conclusion, prolotherapy demonstrated a beneficial effect in a patient with FS with comorbidities, although not to the maximum extent in patients without comorbidity.Keywords: protherapy, frozen shoulder, comorbidity, range of motion, quality of life

Muhammad Sakti, Muhammad Andry Usman, Jansen Lee, Michael Benjamin, Qariah Maulidiah Department of Orthopaedic and Traumatology, Hasanuddin University Teaching Hospital, Makassar, Indonesia Abstract: Deposition of tophus is a common feature in chronic gout; however, signs and symptoms are not always well-pronounced in cases of uncommon sites. We report a case series of three patients, one with an acute locked knee suspected to be meniscus tear or intra-articular loose body, a second case with a lump on the dorsal hand suspected to be a benign lesion, and a third case with a finger flexion deformity with carpal tunnel syndrome; all three cases were later on found out to be tophaceous gout. White chalky monosodium urate crystal deposition was found to be the culprit of the symptoms of the patients. Keywords: gout, tophus, uric acid, knee, extensor tendon, flexor tendon, carpal tunnel syndrome

Abstract Background Mentoring plays a pivotal role in mentees’ professional advancement. However, the factors that affect career progression in informal mentoring relationships, especially with respect to faculty members, have not been extensively explored. This study aimed to explore the factors that affect career progression in informal faculty mentorings within mentor and mentee relationships. Methodology A Qualitative Exploratory Study was designed and conducted from May to October 2023. Faculty members with informal mentoring relationships were recruited through purposive sampling. Seven faculty mentors and eight faculty mentees from various institutions participated in the study. Semi-structured interviews were used to collect data, which were audio-recorded and verbatim transcribed. The transcripts were then analysed using NVivo Software and coded. Braun and Clark’s framework was used for the thematic analysis. The study adhered to the COREQ (Consolidated Criteria for Reporting Qualitative Research) checklist to ensure comprehensive and transparent reporting of the qualitative research process. Results A total of 76 codes emerged which were classified into six themes: (1) an ideal mentee, (2) an ideal mentor, (3) factors promoting the relationship, (4) the role of gender, (5) factors deteriorating the relationship, (6) overcoming barriers / trust-building strategies. Within each theme, mentor–mentee needs and behaviours were identified, which could lead to positive or deteriorating outcomes. Conclusion Factors affecting career progression in informal faculty mentoring sessions include mentees' positive mindset, internal motivation and clarity of vision, mentors' skills, reputation, and role modelling. Effective communication, trust, respect, and clear goals are also essential. Challenges, such as busy schedules, cross-gender mentoring, and societal biases, affect these relationships. Overcoming these barriers involves sharing experiences, psychosocial support, empathy, active listening, and feedback.

OBJECTIVE: To explore the impact of the COVID-19 pandemic on research in health professions. METHODS: It was a qualitative case study. Semi-structured interviews were done with researchers who were selected through purposive sampling. After thirteen interviews, data saturation was achieved. The interviews were recorded on zoom, transcribed verbatim, and analyzed manually for codes, categories, and themes. RESULTS: This study explored the impact of the COVID-19 pandemic on health research through interviews with researchers, revealing three major themes and thirteen subthemes. The themes encompass the challenges encountered by researchers, the research opportunities provided by the pandemic, and modifications in ongoing and planned projects. All participants expressed that the pandemic brought numerous hurdles, including reduced research opportunities, challenges in data collection, small sample sizes, quality assurance concerns, and delays in project completion. However, it also offered silver linings such as the development of new competencies, a shift in research priorities, and increased reliance on virtual platforms for collaboration and data collection. These findings highlight both the obstacles and innovations prompted by the pandemic in health research. CONCLUSION: The COVID-19 pandemic significantly impacted health research, acting as a catalyst for innovation, particularly through the increased use of digital tools and virtual platforms. While researchers faced substantial challenges like disruptions in methodologies and project timelines, these adaptations may persist as integral elements of the research paradigm in health professions, guiding future policy and practice beyond the pandemic.

Tamedan Village is one of the fish producing villages so obtaining raw materials for making fish floss is very easy to obtain. The partner for this activity is the coconut fish floss business group, which is still making shredded meat in a simple way due to a lack of knowledge about the shredded mixer tool which can speed up the processing process, the product packaging is also still very simple and has not been able to market its products widely due to limited knowledge about marketing activities and the lack of it. partner's understanding of business management and there is no bookkeeping yet. The aim of this service activity is Technology Transfer for using tools to make coconut fish floss to make it more practical. Carrying out counseling, training and demonstrations as well as assistance regarding the shredded production process using a shredded mixer, using labeled packaging and simple bookkeeping training. The results of this service activity can provide an understanding of shredded mixer tools, provide skills in processing fish floss and packaging with labels so that the product loks attractive and can increase sales and partner understanding in terms of financial recording.

Abstract The study aimed to investigate the molecular mechanisms underlying the effects of Vildagliptin on the healing of diabetic foot ulcers (DFUs). The research compared patients who received 12 weeks of Vildagliptin treatment to those who did not. Various molecular markers associated with wound healing were measured. Wound fluid samples were collected from DFUs using a filter paper absorption technique, and total RNA was extracted for quantitative real-time PCR (qPCR). The results showed that the autophagy marker NUP62 was significantly downregulated in the Vildagliptin group at week 12 compared to baseline (median expression 0.57 vs. 1.28; P = 0.0234). No significant change was observed in the placebo group (median expression 1.61 vs. 1.48; P = 0.9102). Both groups showed substantial downregulation of RIPK3, a necroptosis marker, at week 12 compared to their respective baselines. In addition to its effects on blood sugar levels, Vildagliptin may promote DFU healing by reducing autophagy in patients with diabetes.

Abstract Background Research evidence suggests gender-based differences in the extent and experiences of academic leaders across the globe even in developed countries like USA, UK, and Canada. The under-representation is particularly common in higher education organizations, including medical and dental schools. The current study aimed to investigate gender-based distribution and explore leaders’ experiences in the medical and dental institutes in a developing country, Pakistan. Methods A mixed-method approach was used. Gender-based distribution data of academic leaders in 28 colleges including 18 medical and 10 dental colleges of Khyber Pakhtunkhwa, Pakistan were collected. Qualitative data regarding the experiences of academic leaders (n = 10) was collected through semi-structured interviews followed by transcription and thematic analysis using standard procedures. Results Gender-based disparities exist across all institutes with the greatest differences among the top-rank leadership level (principals/deans) where 84.5% of the positions were occupied by males. The gender gap was relatively narrow at mid-level leadership positions reaching up to as high as > 40% of female leaders in medical/dental education. The qualitative analysis found gender-based differences in the experiences under four themes: leadership attributes, leadership journey, challenges, and support. Conclusions The study showed that women are not only significantly under-represented in leadership positions in medical and dental colleges in Pakistan, they also face gender-based discrimination and struggling to maintain a decent work life balance. These findings are critical and can have important implications for government, organizations, human resource managers, and policymakers in terms of enacting laws, proposing regulations, and establishing support mechanisms to improve gender-based balance and help current and aspiring leaders in their leadership journey.

Current neuroimaging studies frequently use complex machine learning models to classify human fMRI data, distinguishing healthy and disordered brains, often to validate new methods or enhance prediction accuracy. Yet, where prediction accuracy is a concern, our results suggest that precision in prediction does not always require such sophistication. When a classifier as simple as logistic regression is applied to feature-engineered fMRI data, it can match or even outperform more sophisticated recent models. Classification of the raw time series fMRI data generally benefits from complex parameter-rich models. However, this complexity often pushes them into the class of black-box models. Yet, we found that a relatively simple model can consistently outperform much more complex classifiers in both accuracy and speed. This model applies the same multi-layer perceptron repeatedly across time and averages the results. Thus, the complexity and black-box nature of the parameter rich models, often perceived as a necessary trade-off for higher performance, do not invariably yield superior results on fMRI.Given the success of straightforward approaches, we challenge the merit of research that concentrates solely on complex model development driven by classification. Instead, we advocate for increased focus on designing models that prioritize the explainability of fMRI data or pursue applicable objectives beyond mere classification accuracy, unless they significantly outperform logistic regression or our proposed model. To validate our claim, we explore possible reasons for the superior performance of our straightforward model by examining the innate characteristics of fMRI time series data. Our findings suggest that the sequential information hidden in the temporal order may be far less important for the accurate fMRI classification than the stand-alone pieces of information scattered across the frames of the time series.

Background and Objective: The labial frenum plays an important role in providing attachment between the lip and the alveolar process and at the same time contributes significantly to the maintenance of proper oral hygiene. The main objective of this study was to evaluate the labial frenum attachment in both the upper and lower jaw and investigate its potential association with the age, gender, and oral hygiene condition among individuals presenting to a local tertiary care hospital Methodology: This cross-sectional study was carried out at Lahore Medical and Dental College, Lahore over a period of six months. A total of 360 patients were included in the study after obtaining permission from the institutional ethical review committee The labial frenum type was identified and recorded for both mandible and maxilla. The oral hygiene status was accessed using the oral hygiene index (simplified). Assessment of both frenal attachment and oral hygiene was done by the same examiner to minimize the chances of any bias. Results: Our study included a total of 360 patients with 47% (171) males and 53% (189) females. Moreover, in our study, the most common type of frenal attachment was gingival (65%), followed by mucosal (19%) and less commonly the papillary (11%) and papillary penetrating (6%) types. A strong association was observed between the frenal attachment type and oral hygiene status among our study population (P value= 0.00). Conclusion: The association of frenal attachment with oral hygiene and gender is statistically significant.

الملخص: أهداف البحث: لقد ارتبطت استقلالية الاطباء المقيمين في غرفة العمليات ارتباطا مباشرا بسلامة المرضى في الرعاية الصحية. ومع ذلك، هناك ندرة في الأبحاث التي تركز على العوامل المتعلقة بالمقيمين لاتخاذ قرارات التكليف الجراحية في غرفة العمليات. كان الهدف من هذه الدراسة هو تحديد العوامل اللازمة لاتخاذ قرارات تكليف المقيمين من وجهة نظر المشرف / الاستشاري ووضع قائمة مرجعية لتقييم استعداد المقيمين للعمل المستقل. طريقة البحث: استخدمت هذه الدراسة منهج دلفي مختلط الطريقة. في المرحلة الأولى، أنتجت مراجعة شاملة للأدبيات ودراسة استكشافية نوعية قائمة من العوامل المتعلقة بالمقيمين. تضمنت المرحلة الثانية التحقق من صحة المحتوى من قبل لجنة مكونة من خمسة خبراء، تليها دراسة دلفي من جولتين مع 20 خبيرا. وقد أجريت هذه العملية لتحقيق توافق في الآراء بشأن العوامل الرئيسية التي تم تحديدها. النتائج: تم تحديد إجمالي 49 عاملا متعلقا بالإسناد، والتي تم تخفيضها إلى 46 بعد التحقق من صحة المحتوى. خلال جولة دلفي الأولى، تم قبول 17 عاملا بشكل كامل، وتم رفض 7 عناصر وتم قبول 22 عنصرا جزئيا. من بين 39 عنصرا تم إرسالها إلى جولة دلفي الثانية، تم قبول 23 عنصرا ورفض 16 عنصرا. تم تشكيل قائمة مرجعية نهائية مكونة من 23 عنصرا بناء على العوامل التالية: 6 عوامل معرفية (المعرفة، مدير المخاطر، الطبيب الآمن، المدير العام، مجال الاهتمام، التواصل)، 5 عوامل نفسية (تأدية العمليات سابقا، المختص، القدرة على اختيار النتائج الهامة، القدرة على التصرف الظرفي، صانع القرار) و 12 من العوامل العاطفية (المسؤول، القائد ، صادق، متعاطف، أخلاقي، متقبل، متواضع، ذكي عاطفيا، متحمس، مسؤول، لاعب فريق، منضبط). الاستنتاجات: وأسفرت الدراسة عن تكوين قائمة مرجعية تعتمد على العوامل اللازمة لاتخاذ قرار التكليف في غرف العمليات الجراحية. وكانت بعض العوامل السياقية الجديدة هي ''المدير العام''، و''مجال الاهتمام''، و''القدرة على اختيار النتائج المهمة''، و''المسؤول''، و''مدير المخاطر''، و'' تأدية العمليات سابقا ''. يقدم هذا الإطار إرشادات للمشرفين والمقيمين لتقييم التقدم خلال برنامج الإقامة. توضح الأداة المطورة صلاحية جيدة للمحتوى وهي مناسبة لتقييم الاعتماد بعد التحقق من صحة البناء. Abstract: Objective: Resident autonomy in an operation theatre has been directly linked with patient safety in healthcare. The objective of this study was to identify the factors necessary for making resident-entrustment decisions from the perspective of a supervisor/consultant viewpoint. The second objective was to develop a checklist for assessing resident readiness for independent work. Materials and methods: This study employed a mixed-method Delphi approach. In the first stage, a comprehensive literature review and a qualitative exploratory study produced a list of factors related to residents. The second phase involved content validation by a panel of experts, followed by a two-round Delphi study with 20 expert panelists. Results: A total of 49 resident-related factors for entrustment were identified, which were reduced to 46 after content validation. During Delphi Round I, 17 factors were fully accepted, 7 were rejected and 22 items were partially accepted. Out of the 39 items sent to Delphi Round II, 23 items were accepted and 16 were rejected. A final 23-item checklist was formed based on the following factors; 6 Cognitive (knowledgeable, risk manager, safe doctor, general manager, field of interest, communicator), 5 Psychomotor (past performer, competent, ability to pick critical findings, ability to act situationally, decision maker) and 12 affective (responsible, leader, honest, empathetic, ethical, receptive, humble, emotionally intelligent, motivated, accountable, team player, disciplined) factors. Conclusion: The study resulted in the formation of a checklist based on the factors necessary for entrustment decision-making in surgical operating rooms. Some of the novel contextual factors were ‘general manager’, ‘field of interest’, ‘ability to pick critical findings’, ‘accountable’, ‘risk manager’, and ‘past performer’. This framework offers a guideline for supervisors and residents to evaluate progress throughout the residency program. The developed tool demonstrates good content validity and is suitable for entrustment assessment following construct validation.

Abstract Background Medical education requires innovative strategies to enhance empathic skills and the formation of professional identities among students. However, evidence-based teaching of empathy and professional identity formation is inadequately represented, particularly in medical curricula. This study investigated the effectiveness of empathy portfolios in developing Professional Identity Formation (PIF) among medical students and the correlation between empathy and PIF. The objectives of this study were to determine the effectiveness of empathy portfolios for teaching and nurturing PIF in medical students and to investigate the correlation between empathy and PIF. Methods A randomized controlled trial was conducted at Peshawar Medical College, Pakistan. The protocol adhered to CONSORT guidelines. A total of 120 students participated in the study. Empathy and PIF were assessed using two validated questionnaires JSPE-S and PIQ before randomization. The participants were randomized in a stratified fashion into the experimental (n = 60) and control (n = 60) groups. The Participants in the intervention group attended a training workshop on portfolio use. Students maintained their portfolios and wrote reflections on incidents that evoked empathy. Independent t-tests were performed to determine whether the control and experimental groups differed in terms of mean empathy and PIF scores, and Pearson’s correlation analyses were used to investigate the relationships between pre- and post-empathy, and pre-post-PIF. Results The mean post-test scores on the Empathy and PIF showed a statistically insignificant difference of 0.75 +-17.6 for empathy and 0.45 ± 8.36 for PIF. The intervention had little influence on empathy and PIF scores, as evidenced by nonsignificant effect sizes of 0.32 and 0.36 for empathy and PIF respectively.A strong positive correlation was found between Pre-Empathy and the PIF-Total score (0.519), and between Post- empathy and the PIF-Total score (0.395) (p

Abstract Background History taking and clinical reasoning are important skills that require knowledge, cognition and meta-cognition. It is important that a trainee must experience multiple encounters with different patients to practice these skills. However, patient safety is also important, and trainees are not allowed to handle critically ill patients. To address this issue, a randomized controlled trial was conducted to determine the effectiveness of using Virtual Patients (VP) versus Standardized Patients (SP) in acquiring clinical reasoning skills in ophthalmology postgraduate residents. Methods Postgraduate residents from two hospitals in Lahore, Pakistan, were randomized to either the VP group or the SP group and were exposed to clinical reasoning exercise via the VP or SP for 30 min after the pretest. This was followed by a posttest. One month after this activity, a follow-up posttest was conducted. The data were collected and analysed using IBM-SPSS version 25. Repeated measures ANOVA was used to track the effect of learning skills over time. Results The mean age of the residents was 28.5 ± 3 years. The male to female ratio was 1:1.1. For the SP group, the mean scores were 12.6 ± 3.08, 16.39 ± 3.01 and 15.39 ± 2.95, and for the VP group, the mean scores were 12.7 ± 3.84, 16.30 ± 3.19 and 15.65 ± 3.18 for the pretest, posttest and follow-up posttest, respectively (p value

Background: Diabetic foot osteomyelitis (DFO) commonly occurs secondary to ulcerations of the skin. Empirical antibiotic agents are a key element of treatment and their use is dependent on local knowledge of the microbial spectrum of diabetic foot infections. This study aimed to retrospectively analyze the local microbiological profile, including bacterial culture/sensitivity results of DFO, and compare findings with literature. This study also aimed to review the concordance of microbiology results with national guidelines for the future treatment of DFO. Methods: A retrospective review of clinical records was performed on patients who presented to the high-risk foot clinic, Townsville University Hospital, between 2018 and 2022. All patients older than 18 years and diagnosed with DFO were included. Our exclusion criteria included all other foot presentations, including trauma, vasculitis, and neoplasms. Results: On the basis of the inclusion and exclusion criteria, 124 patients with DFO were selected. Most patients in the cohort were males (70.2%), non-Indigenous (68.5%), aged 50-69 years (55.6%), and with elevated HbA 1c levels (>8.6). Chronic kidney disease (39.5%) and ischemic heart disease (41.9%) were common comorbidities. Of the pertinent microbial results, Staphylococcus aureus (~76%) was the most commonly isolated Gram-positive organism. Gram-positive bacteria were significantly increased in the elderly population with DFO ( P < .05). All methicillin-resistant S aureus isolates were vancomycin- and cotrimoxazole-sensitive. Pseudomonas aeruginosa was the predominant Gram-negative organism isolated (39.3%). P aeruginosa exhibited low sensitivity to ciprofloxacin. Conclusion: This study has enhanced our understanding of the various microbial species underlying DFO at our center and may be generalizable. Level of Evidence: Level IV, retrospective case series.

The efficient and timely execution of tasks is a fundamental challenge in the realm of future Internet of Things (IoT) networks. To address this challenge, fog devices are often deployed close to end devices to facilitate task processing on behalf of IoT nodes. One strategy for improving task computational delay is to employ parallel task offloading, in which tasks are subdivided into subtasks and sent to different fog devices for execution in parallel. However, allocating computational resources to fog nodes and mapping these resources to IoT subtasks is a key challenge in this area. This work models the parallel task offloading problem as a graph-matching problem and utilizes a many-to-many matching technique to achieve a stable mapping of IoT subtasks to fog node resources. Unfortunately, the proposed solution is subject to the problem of externalities due to the dynamic preference profiling of fog nodes. To address this issue, we employ an iterative algorithm to resolve any blocking pairs that may arise. Our results demonstrate that the proposed technique reduces the task latency by 29% as compared to other matching-based techniques available in the literature.

Abstract Introduction Blended learning, which integrates classroom face-to-face teaching with both asynchronous and synchronous online learning elements, has swiftly gained acceptance in educational environments. However, the implementation of blended learning presents challenges that impact all stakeholders, necessitating thoughtful consideration. Teachers play a central role in shaping the instructional experience among these stakeholders. To fully realize the potential of comprehensive blended learning, it is imperative to identify the challenges faced by these teachers and develop strategies that sensibly address and overcome them. Methodology A qualitative exploratory study was conducted with twelve teachers involved in the postgraduate blended learning health professions program at Khyber Medical University, Peshawar in 2022. One-on-one semi-structured Interviews were conducted via WhatsApp/ZOOM, transcribed by Otter AI, coded on NVivo & analyzed using Braun/Clarke’s Thematic Analysis. Results Three themes of challenges faced by teachers of postgraduate blended learning programs were constructed namely (1) Skills, such as (i) digital, (ii) instructional, and (iii) online class management, and (2) Administrative barriers in terms of (iv) resources (iv) training, and (3) Faculty resistance. Conclusion This study provides profound insights into the daunting challenges that postgraduate blended learning program teachers encounter in terms of skills, administrative barriers, and faculty resistance. These findings offer a valuable opportunity for program directors to identify the critical requirements of these faculties in their pursuit of effective teaching and learning, ultimately transforming the landscape of blended education. This study emphasizes the need for ongoing faculty development and institutional support to address the identified challenges and improve the quality of postgraduate blended-learning programs.

Ubiquitous computing is a key component of future wireless communications and Internet of Things (IoT) applications. By using distributed fog computing, data obtained from sensors can be timely processed and different tasks can be computed efficiently. As a result, IoT applications can make timely decisions and improve application reliability. In this paper, we consider a Partial Offloading to Multiple Helper (POMH) scenario where IoT device divide their tasks into subtasks that can be computed in a parallel manner. We propose a modified many-to-many matching-based task offloading algorithm to reduce the task latency in a POMH scenario. To overcome the externalities due to the dynamic preference profile of fog nodes, an intelligent proposal-based scheme is also introduced. The performance analysis of the proposed techniques shows that they provide quicker task computation as compared to different techniques available in the literature.

The evaluation of various desirable traits in eggplant genotypes has facilitated the efficient process of selecting and improving them. Morphological parameters have proven to be valuable in assessing the similarities or differences among different accessions, while molecular data have been used to support the conclusions drawn from the morphological analysis. This study was conducted to evaluate the performance of 42 eggplant genotypes collected from Malaysia, China, and Thailand. The characteristics under investigation were shown to be highly significant (p < 0.01) by analysis of variance (ANOVA). It was noted that the plants TV17 (5.59 kg) and MV18 (5.97 kg) produced large yields per plant. The SSR markers used exhibited moderate average values for the number of alleles (2.53). The major allele frequency displayed a high average value (0.53) and a moderate average number of effective alleles (2.31). Additionally, the observed Shannon’s information index, expected heterozygosity, and PIC were high (0.84, 0.54, and 0.45, respectively). Using the unweighted pair-group approach with arithmetic averages based on similarity matrices (UPGMA) Dendrogram, 42 accessions were sorted into five primary groups based on similarities. The findings of this study indicate that the use of simple sequence repeat (SSR) markers can effectively estimate genetic diversity and analyze phylogenetic relationships. Moreover, these markers can assist eggplant breeders in selecting desirable quantitative traits within their breeding program.

We propose a novel deep learning architecture, called XcelNet17, for image classification in remote sensing. Comprising fourteen convolutional and three fully connected layers, XcelNet17 outperforms several benchmark architectures available in the literature in terms of classification accuracy. Additionally, we present BA-ABC, a new hybrid feature selection algorithm that inherits the strengths of the Bat Algorithm (BA) and the Artificial Bee Colony (ABC) algorithm. Together these contributions significantly enhance the performance and accuracy of remote sensing image classification tasks. The proposed framework is thoroughly trained and verified using five benchmark datasets typically used for remote sensing image classification, namely AID, RSSCN7, SIRI-WHU, UC Merced, and WHU RS-19. Our simulation results suggest that in terms of classification accuracy, XcelNet17 outperforms most of the well established networks including AlexNet, VGG16, VGG19, ResNet50, and DarkNet19 by obtaining accuracy values in the range of 94.6% and 99.9%. Furthermore, the proposed features selection method, when integrated with XcelNet17, yields much improved classification accuracy in comparison to various benchmarks including WOA, GWO, BA, ABC, and ACO algorithms. For example, an 8% superior performance on WHU-RS19 dataset has been observed. The attained results are further validated by an in-depth statistical analysis.

People are preoccupied with their own duties in today’s environment, making it tough to oversee and care for disabled people. Paralyzed and disabled people, on the other hand, have a powerful desire to move around freely. Different initiatives have been taken in the past to improve and preserve the self-esteem of such people, and various technologies have also been created to assist them in a better way. The primary advantage of a vision-based autonomous wheelchair is that it can provide greater independence to users with limited mobility. The methodology of other smart wheelchairs varies depending on the specific technology used. Some smart wheelchairs may use sensors to detect obstacles and provide feedback to the user, while others may incorporate GPS and other navigation technologies to assist with indoor and outdoor navigation. Our study proposes a revolutionary implementation of an autonomous system for fully handicapped people, allowing them to drive wheelchairs using just their eyes. The wheelchair’s orientation will be determined by the orientation of the eye. The camera will follow the movement of the eyes. Furthermore, sensors will be installed on the front side of the wheelchair to identify any obstacles along its path. The calibration of the camera with the human eye, without obstructing its vision, is the most challenging task in this research, besides controlling the wheels of the wheelchair.

This study proposes a novel semi-supervised multi-label emotion classification approach for French tweets based on pseudo-labeling. Human subjectivity in emotional expression makes it difficult for a machine to learn. Therefore, it necessitates training supervised learning models on large datasets annotated by multiple annotators. However, creating such datasets can be costly and time-consuming. Moreover, aggregating annotations from multiple annotators to capture their collective emotional state adds complexity to the task. Semi-supervised learning techniques have shown effectiveness with limited datasets. Furthermore, Large language Models (LLMs), particularly Chat-GPT, have demonstrated superior annotation accuracy compared to annotations obtained from crowdsourcing platforms, when both are evaluated against expert-annotated data. This work introduces a novel approach for multi-label emotion classification of French tweets by leveraging pseudo-labels generated through Chat-GPT, a robust large language model. Using zero-shot, one-shot, and few-shot learning techniques, Chat-GPT annotates the unlabelled part of our dataset. These Chat-GPT-annotated pseudo-labels are then merged with manual annotations, facilitating the training of a multi-label emotion classification model via semi-supervised learning. Furthermore, within the context of our research, we present a new French tweet dataset, containing testimonials from people affected by an urban industrial incident. This dataset features 2,350 tweets, each manually annotated by three human annotators based on 8 pre-identified emotions. Benchmark results are presented for multi-label emotion classification models employing both fully supervised and semi-supervised approaches with pseudo-labeling. Our findings demonstrate the superiority of our approach for multi-label emotion classification over standard pseudo-labeling and an established baseline.

Background: In Pakistan, every third baby is born small for gestational age (SGA). Early antenatal detection of SGA helps with birth planning and initial treatment of mother and baby, thereby reducing complications. Screening and diagnosis of SGA however are challenging, especially in low and middle-income countries where access to technological advances may be limited and there is a lack of routine antenatal screening. Aims: To explore the current practices, knowledge, and experiences of caring for SGA infants with women and health professionals in Pakistan. Design: A cross-sectional survey with healthcare professionals and focus groups or interviews with health professionals and mothers of SGA babies were undertaken. Survey data were analysed descriptively and integrated with the qualitative data using thematic data analysis. Subjects: 78 completed surveys were returned and eight FGDs and five interviews were undertaken with 77 participants – 67 healthcare professionals (gynecologists/obstetricians, neonatologists, Lady Health Workers, and Lady Health Visitors) and 10 mothers of SGA infants aged under 12 months. Results: The survey highlighted a general lack of training on SGA for all health care professionals, but particularly amongst community staff who often act as primary caregivers for women. Five qualitative themes described the challenges and issues faced in the management, treatment, and prevention of SGA in Pakistan: Lack of policies and training, Lack of resources, Lack of access to healthcare, Not following the guidance, and Lack of data and reporting. Conclusions: A whole system approach to improve service provision and outcomes is needed. This should include epidemiological research, country-specific policies, training for healthcare professionals and awareness raising amongst women and community members.

This study aims to determine the effect of giving EM4 probiotics on the growth and survival rate of snakehead (Channa striata). This research was carried out at the Fish Hatchery Laboratory, Faculty of Marine and Fisheries, Universitas Syiah Kuala. This study was conducted using a Complete Randomized Design (CRD) method with 4 treatments used, namely A (control), B (EM4 6 ml/kg of feed), C (EM4 8 ml/kg of feed), and D (EM4 10 ml/kg of feed). The results showed that the addition of 10 ml/kg of feed of EM4 probiotic resulted in an absolute length growth of 1.60±0.17 cm, an absolute weight growth of 1.85±0.18 gram, a specific growth rate of 1.97±0.10 % per day, a feed conversion ratio of 1.56±0.03, feed efficiency 64.19±1.41 % and survival rate 97.78±3.85 %. The results of this study can be concluded that the addition of probiotic EM4 10 ml/kg of feed can increase the growth and survival rate of snakehead (Channa striata). Keywords: Channa striata EM4 Commercial feed Growth Survival rate

Apples are usually bagged during the growing process, which can effectively improve the quality. Establishing an in situ nondestructive testing model for in-tree apples is very important for fruit companies in selecting raw apple materials for valuation. Low-maturity apples and high-maturity apples were acquired separately by a handheld tester for the internal quality assessment of apples developed by our group, and the effects of the two maturity levels on the soluble solids content (SSC) detection of apples were compared. Four feature selection algorithms, like ant colony optimization (ACO), were used to reduce the spectral complexity and improve the apple SSC detection accuracy. The comparison showed that the diffuse reflectance spectra of high-maturity apples better reflected the internal SSC information of the apples. The diffuse reflectance spectra of the high-maturity apples combined with the ACO algorithm achieved the best results for SSC prediction, with a prediction correlation coefficient (Rp) of 0.88, a root mean square error of prediction (RMSEP) of 0.5678 °Brix, and a residual prediction deviation (RPD) value of 2.466. Additionally, the fruit maturity was predicted using PLS-LDA based on color data, achieveing accuracies of 99.03% and 99.35% for low- and high-maturity fruits, respectively. These results suggest that in-tree apple in situ detection has great potential to enable improved robustness and accuracy in modeling apple quality.

Objectives: To identify the use of different emotion regulation strategies by medical trainees, and to determine the frequency and the predominant pattern of emotional response in emotion-triggering situations. Method: The descriptive cross-sectional study was conducted at 2 public and 1 private medical college in Lahore, Pakistan, from March to September 2019, and comprised postgraduate medical trainees of either gender from all clinical disciplines from years 1-4. Data was collected using a questionnaire based on the Gross theory of emotional regulation and the Situational model of emotion. Emotion regulation strategies included situation selection, situation modification, cognitive change, attention deployment, and response modulation. Data was analysed using SPSS 25. Results: Of the 377 trainees approached, 308(81.69%) participated; 206(67%) females and 102(33%) males. The overall mean age was 27.8+2.91 years. The majority of the trainees were from the Obstetrics and Gynaecology department 133(43.2%) and were in the first year of their training 116(37.7%). The most frequent emotion-triggering situation identified was prolonged working hours 292(95%), and the major emotional response was quietness in 5 out of ten situations (50%). The trainees used greater emotion regulation strategies in sad situations 3.49±1.79 (p

BackgroundZinc biofortified wheat may be a sustainable strategy to increase zinc intake in areas where fortification and dietary diversification are not feasible or are limited by household purchasing power. This convergent mixed methods study aimed to explore the farmers’ and millers’ experiences and attitudes towards the production and processing of zinc biofortified wheat in Pakistan.MethodsA telephone survey was conducted with farmers (n = 418) who were provided with Zincol-2016 biofortified wheat seed for the 2019–2020 growing season, as part of a wheat grain micronutrient mapping study across Punjab Province. The survey explored the farmers’ experiences of growing Zincol-2016 and whether they opted to grow it again in the subsequent season. Semi-structured focus group discussions were undertaken in a separate group of farmers in Khyber Pakhtunkhwa (KP) province (n = 12) who grew Zincol-2016 for the BiZiFED2 RCT. Millers were also interviewed in KP, both those who had processed Zincol-2016 for the trial (n = 12) and those who had no experience of processing biofortified wheat (n = 12). Survey data were analyzed using descriptive statistics and transcripts of focus groups were analyzed using thematic analysis.ResultsNearly half of farmers who responded to the survey (47%) re-cultivated Zincol-2016 in the following season. The drivers for Zincol-2016 re-cultivation were seed availability (100%), grain yield and growth resistance (98%), quality of the flour from the previous harvest (97%) and nutritional benefit (94.5%). Discussions with farmers suggested that the main motivators for potential scale-up of biofortified wheat were the perceived quality of the grain, wheat, and flour. Millers saw it as an opportunity to expand their business. Farmers and millers valued the health benefits of the wheat. Challenges for scale-up include the need of additional support to produce it, unfamiliarity with the biofortification process, production costs, and external threats to the supply chain.ConclusionFarmers and millers showed a strong implicit preference for Zincol-2016 over alternative varieties. Crop performance and product yield were the most cited motivators for growing Zincol-2016. Farmers and millers are willing to produce and process biofortified wheat if financial and educational support is provided.

Context: The current study, the first of its type, focuses on the ethnobotanical uses of 97 medicinal plant species by the inhabitants in the Soran area, Kurdistan region of Iraq. Aims: To evaluate local knowledge of medicinal plants and provision of preliminary data on the user-benefit of the accessible plant species in the area. Methods: Between October 2021 and May 2022, key informant interviews were conducted as part of an ethnobotanical survey. Information about a particular study through face-to-face interviews with 171 participants (98 males and 73 females) was collected. For the therapeutic plants considered in the study, quantitative indices such as use value (UV), family use value (FUV), the relative frequency of citation (RFC), fidelity level (FL), and informant consensus factor (ICF) were applied in addition to detailed notes on each plant species. Results: The survey discovered 97 plant species and 41 plant families. Leaves were the plant portion that was used the most (44%), while seeds were the least (12%). The most popular three methods of preparation were decoction (52%), row (36%), and crushed (6%). The Olea europaea species had the highest use values (0.82), while Vitex agnus-castus had (0.005). Amaryllidaceae had the highest family use value (1.218), while Asteraceae had (0.005). According to the consensus index, Ficus carica and Datura stramonium had (140.84%) and (1.011%). The digestive tract disease category was shown to have the highest informant consensus factor value out of all disease categories (0.57), while the lowest value ICF was (0.0) for tooth pain. Conclusions: As a result of the development of natural medicines, this study gives information on the indigenous medicinal plants utilized in the Soran district to treat common illnesses that are ready for additional pharmacological and phytochemical examination. For better use of natural resources, the traditional use of plants requires conservation methods and additional research.

Abstract Brain dynamics are highly complex and yet hold the key to understanding brain function and dysfunction. The dynamics captured by resting-state functional magnetic resonance imaging data are noisy, high-dimensional, and not readily interpretable. The typical approach of reducing this data to low-dimensional features and focusing on the most predictive features comes with strong assumptions and can miss essential aspects of the underlying dynamics. In contrast, introspection of discriminatively trained deep learning models may uncover disorder-relevant elements of the signal at the level of individual time points and spatial locations. Yet, the difficulty of reliable training on high-dimensional low sample size datasets and the unclear relevance of the resulting predictive markers prevent the widespread use of deep learning in functional neuroimaging. In this work, we introduce a deep learning framework to learn from high-dimensional dynamical data while maintaining stable, ecologically valid interpretations. Results successfully demonstrate that the proposed framework enables learning the dynamics of resting-state fMRI directly from small data and capturing compact, stable interpretations of features predictive of function and dysfunction.

Listening is a primary skill essential for learning and is positively correlated with academic achievement. It also enables a healthcare professional to fully explore patients' concerns in healthcare settings. There has been much discussion on how effective listening practices can facilitate students’ learning. A clear understanding of listening as a ‘process’ and planned listening activities can help exploit listening skills in formal and informal learning contexts. This paper explores strategies through which listening can be taught to undergraduate medical students in a small group setting. A planned tutorial is discussed, including methods that can be used to teach listening skills. The simple guidelines provided here can be used in most small group teaching methods. These teaching strategies are likely to allow undergraduate students to evolve into better listeners and, therefore, better lifelong learners and future physicians. Keywords: Medical students, Active listening skills, Teaching Methods, Small group teaching.

BackgroundCommunity engagement has shown to be fundamental component of the response to previous disease outbreaks. This study aimed co-design and implement a culturally appropriate COVID-19 risk communication and community engagement strategy with a resource-poor rural community in Northwest Pakistan.MethodsParticipatory Action Research (PAR) was conducted from January 2021 to March 2022. Five PAR meetings took place with community members (n = 30) to: (1) explore how the COVID-19 pandemic impacted on the community; (2) identify challenges to limit the spread of the virus; (3) identify and implement solutions to these challenges; and (4) highlight the enablers, challenges and knowledge of the cultural context needed to optimize safety during emergencies. Focus group discussions (N = 6) with community members not involved in the PAR meetings (N = 50) and children of the community (N = 26) were conducted following the PAR meetings. Thematic analysis of the PAR and focus group data was conducted.ResultsDelivery of messages on how to keep families safe, provision of personal protective equipment and improved water systems were part of the strategies taken by the community to create awareness and reduce the spread of COVID-19. Nine themes were identified: Attitudes to the pandemic: From skepticism to acceptance, Changing attitudes about vaccination: rumors and trust, COVID-19 and Faith, Social impact of the pandemic, Access to water, Resource mobilization: personal protective equipment, Spaces where collaborative effort can bring to solutions, Agents of change, and Empowerment of women.DiscussionThe participatory approach of this research allowed understanding of the challenges faced by the community to engage in behavior change strategies to reduce the spread of COVID-19 and enabled the community to find sustainable solutions. Engagement with the community empowered men and women to be agents of change and promoted necessary precautionary actions to reduce the risk of infection within their community.ConclusionParticipatory approach highlighted the importance of engaging with and integrating to local culture and values to overcome challenges such as gender imbalance and distrust. Findings of this study are relevant to others working in diverse cultural settings in similar crises events regardless of particular cultural variations.

OBJECTIVE: To determine the frequency of attributes of role modelling demonstrated by clinical trainers in teaching hospitals. METHODS: A pre-validated role model apperception tool (RoMAT) was used in this cross-sectional study to collect responses from trainees serving in seven teaching hospitals of Pakistan from January to December 2019. The questionnaire contained items on personal, teaching, and clinical attributes of role models. Responders were asked to recognize and respond to attributes of their identified clinical trainers on four-point Likert scale (strongly disagree to strongly agree). Descriptive statistics was carried out using SPSS 21. RESULTS: Out of the 900 questionnaires distributed; 740 post graduate trainees responded (response rate 82%); 540 (73%) recognized one role model, 185 (25%) identified two role models and the rest 15 (2%) did not identify any clinical trainer as a role model. Common attributes of trainers included: excellent clinical reasoning skills (97%), honesty and integrity (90%), awareness of role model status (86%), professionally competent (80%), communication skills (78%), positive interaction (84%), positive attitude (82%), making learning exciting (81%), understanding learners’ needs (73%), demonstrating enthusiasm (86%), easy to work with (85%), leadership qualities (72%). Less common attributes included empathy (38%), patience (36%) and rapport with students (33%). CONCLUSION: Trainers in teaching hospitals has to improve their less common characteristics which include empathy, patience and rapport with students.

Kinerja Komisi Pemberantasan Korupsi (KPK) selama lebih dari satu dekade telah menunjukkan signifikansi terhadap penurunan korupsi di Indonesia. Namun begitu Revisi Undang-Undang KPK serta pandemi terbukti memberikan berpengaruh terhadap memburuknya tingkat korupsi dalam beberapa tahun terakhir. Penelitian ini bertujuan untuk memberikan penjelasan mengenai upaya pemberantasan korupsi di Indonesia berdasarkan perspektif Principal Agent Theory (P-A) dan Collective Action Theory (C-A) serta intervensi yang dapat dilakukan berdasarkan kedua teori. Dengan menggunakan metode studi pustaka serta analisis struktural terhadap pembentukan perilaku, maka ditemukan bahwa upaya pemberantasan korupsi di Indonesia didominasi oleh perspektif P-A sehingga memerlukan upaya penguatan dari perspektif C-A melalui pelibatan masyarakat untuk menguatkan norma kolektif dan budaya anti-korupsi. Lebih lanjut analisa struktur menemukan bahwa intervensi pada level meso (norma kolektif) menjadi upaya paling rasional dan strategis untuk memberantas korupsi yang berada dalam jangkauan masyarakat serta memberikan pengaruh bagi pembenahan level mikro (karakter dan kepribadian individu) sekaligus menguatkan kepatuhan serta efektivitas dari level makro (tatanan kebijakan, aturan, dan hukum). Intervensi pada level meso dapat membentuk mekanisme kontrol sosial untuk memastikan akuntabilitas pelayanan publik, sekaligus menjadi integrasi pendekatan P-A dan C-A yang perlu dilakukan secara simultan sebagai upaya pemberantasan korupsi di Indonesia.

Abstract Background Experiential leadership development is well documented in the corporate sector, but those models cannot be applied as is, in the healthcare domain. The current study proposes a framework for the healthcare sector to enable experiential leadership development for young clinicians. The authors identify developmental assignments (DAs) and explore those characteristics [developmental assignment characteristics; DACs] therein that help develop leadership competencies in young clinicians. Methods As part of a qualitative exploratory study in Pakistan, the authors conducted 16 semi-structured interviews with senior clinicians in leadership positions with post-graduate residents under their supervision from different medical specialties. The participants were selected through purposive sampling, ensuring a maximum variation sample. Focusing on participants’ experiences and perspectives related to experience-driven leadership development, the authors used a multi-level theoretical framework for analysis. Results The thematic analysis resulted in 19 subthemes with four overarching themes for both objectives. The authors categorized the developmental assignments (DAs) into clinical, academic, and administrative assignments. These assignments can be utilized for leadership development by ensuring that they have the requisite characteristics built into their context and structure. These developmental assignment characteristics (DACs) can range from learner-driven to supervisor-driven. The learner-driven characteristics include autonomy, high levels of responsibilities, unfamiliar assignments, working across boundaries, managing diversity, making a commitment, and creating change. The supervisor-driven characteristics include briefing, debriefing, accountability, and learner-assignment matching. The authors also developed a learner-assignment matching (LAM) framework to guide supervisors in customizing and adjusting the level of each DAC in a DA. Conclusion A modern healthcare educational system can utilize studies like this to enable supervisors to develop required leadership skills in young clinicians along with clinical skills.

This research investigates the use of phase change materials (PCMs) in thermal energy storage (TES) unit-based cooling systems to increase the efficiency of air conditioners (ACs) by reducing the air inlet temperature. This study aims to evaluate different configurations of PCM enclosures, and different PCMs (paraffin and salt hydrate), by changing the speed of inlet air to achieve heat reduction of inlet air. The study includes experimental and simulation investigations. Every configuration simulates the hot-season atmospheric conditions of the UAE. A duct containing enclosures of paraffin RT-31 and salt hydrate (calcium chloride hexahydrate) was used for the simulation study using ANSYS/Fluent. A conjugate heat transfer model employing an enthalpy-based formulation is developed to predict the optimized PCM number of series and optimum airflow rate. Four designs of the AC duct were modelled and evaluated that contained one to four series of PCM containers subjected to different levels of supplied air velocities ranging from 1 m/s–4 m/s. The simulation study revealed that employing four series (Design 4) of PCM enclosures at a low air velocity of 1 m/s enhanced the pre-cooling performance and reduced the outlet air temperature to 33 °C, yielding a temperature drop up to 13 °C. The performance of salt hydrate (calcium chloride hexahydrate) was observed to be better than paraffin (RT-31) in terms of the cooling effect. Characterization of paraffin wax (RT-31) and salt hydrate was performed to establish the thermophysical properties. The experimental setup based on a duct with integrated PCM enclosures was studied. The experiment was repeated for three days as the repeatability test incorporating RT-31 as the PCM and a 3 °C maximum temperature drop was observed. The drop in the outlet air temperature of the duct system quantifies the cooling effect. Net heat reduction was around 16%.

Fog computing is a key technology that supports timely and efficient computation of different tasks in IoT networks. By using the nearby fog nodes for quick task computation, application related decisions by IoT devices can be taken within the delay requirements. Resource allocation in terms of task placement on the free computing resources of the fog nodes is a major challenge in IoT networks. In this paper, we consider task offloading from IoT devices to the logically partitioned fog computing resources known as Virtual Resource Units (VRUs) to reduce the number of task outages and energy consumption of the IoT and fog nodes. We propose a two phased task offloading algorithm to minimize the number of task outages. In the first phase, we utilize the task deadline to compute the minimum number of resources required for a task from the fog nodes. To meet the heterogeneous task computing requirements, we introduce the concept of variable sized VRUs in the fog nodes. Moreover, we propose a modified Deferred Acceptance Algorithm (DAA) for stable matching between IoT tasks and variable sized VRUs. In the second phase of the algorithm, the unmatched fog node resources are distributed among the previously matched IoT tasks. Simulation results show that the proposed algorithm outperforms available techniques in the literature in terms of task outages and energy efficiency.

Recent progress in innovation is making the life prosper, simpler and easier for common individual. The World Health Organization (WHO) statistics indicate that a large amount of people experience visual losses, because of which they encounter many difficulties in everyday jobs. Hence, our goal is to structure a modest, secure, wearable, and versatile framework for visually impaired to help them in their daily routines. For this, the plan is to make an effective system which will assist visually impaired people through obstacle detection and scenes classification. The proposed methodology utilizes Raspberry-Pi 4B, Camera, Ultrasonic Sensor and Arduino, mounted on the stick of the individual. We take pictures of the scene and afterwards pre-process these pictures with the help of Viola Jones and TensorFlow Object Detection algorithm. The said techniques are used to detect objects. We also used an ultrasonic sensor mounted on a servomotor to measure the distance between the blind person and obstacles. The presented research utilizes simple calculations for its execution, and detects the obstructions with a notably high efficiency. When contrasted with different frameworks, this framework is a minimal effort, convenient, and simple to wear.

This work presents a unidirectional, co-circularly polarized (CP), printed antenna with highly decoupled or isolated transmit (Tx) and receive (Rx) ports for 2.4 GHz in-band full duplex (IBFD) applications. The presented antenna topology is based on four similar and sequentially rotated trimmed patches with right hand circular polarized (RHCP) characteristics. The symmetrical placement of two Tx patches with respect to both Rx elements results in equal levels of self interference (SI) which was suppressed through balanced excitation of Tx mode. This mechanism results in effective suppression of SI at each Rx patch. The residual SI is suppressed further through a second balanced feeding network deployed at Rxport of proposed antenna topology. The employed balanced feeding networks provide superior performance of ≤ 0.5 dB and 6° magnitude and phase imbalances respectively between the two balanced output ports over the bandwidth of interest. The measured results for prototype of presented antenna achieve -10 dB bandwidth of better than 100 MHz for both Tx and Rxports. The measured interport coupling for validation model ≤ −70 dB across the entire bandwidth of 100 MHz. As per best of authors’ knowledge, the presented antenna is the first one to report such reduced levels of interport coupling over the whole impedance bandwidth of planar antenna with unidirectional radiation patterns and co-RHCP characteristics for both Tx and Rx modes across the overlapped bandwidth.

Earth's energy budget is a major force that drives global climate. The long-term pattern of land surface energy budget with pronounced biophysical effects on climate was normally ignored at a regional scale, particularly in Pakistan. In this article, the land surface energy budget from 2001 to 2018 was estimated and analyzed from Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud and the Earth's Radiant Energy System (CERES) observations over three geographical regions (northern highlands, Indus plains, and Bolochistan plateau) in Pakistan. Biophysical and energy budget parameters, such as Land Surface Temperature (LST), albedo, emissivity, and Normalized Difference Vegetation Index (NDVI), were obtained from MODIS, whereas the downward shortwave solar and longwave thermal radiation were obtained from CERES satellite data. Spatiotemporal trends of three energy budget parameters, i.e., net radiation, latent heat flux, and sensible heat flux, and three biophysical parameters, i.e., albedo, NDVI, and LST, were investigated from 2001 to 2018. The latent heat flux showed a significant increase with a trend of 0.24, whereas a decrease in sensible heat flux with a trend of −0.21 was observed over Pakistan. Net radiation showed an ignorable increase with a trend of 0.054 over the whole of Pakistan. A significant negative relation was found between net radiation and sensible heat flux with albedo, whereas a significant positive relation was found between latent heat flux and NDVI. Biophysical parameters, such as NDVI, albedo, and LST, successively explain the trends of radiative and nonradiative fluxes. This study comprehensively explains the mechanism and patterns of the regional energy budget.

Pada tahun 2020, penduduk miskin di Provinsi Banten mencapai 857.640 orang atau mengalami kenaikan dibandingkan dengan tahun sebelumnya sebesar 654.460 orang. Padahal Banten memiliki potensi pertanian, peternakan, perikanan, pertambangan, energi, dan pariwisata yang sebenarnya mampu mereduksi kemiskinan dan mengoptimalkan kesejahteraan rakyat. Pada masa lalu, Banten merupakan pelabuhan besar yang mengalami masa kejayaan pada masa pemerintahan Sultan Ageng Tirtayasa tahun 1651 sampai dengan tahun 1682. Implementasi strategi yang digunakan oleh Sultan Ageng Tirtayasa dalam membawa kejayaan Banten perlu dikaji sehingga diperlukan peninjauan kembali terhadap sejarah Banten pada masa Sultan Ageng Tirtayasa. Penulisan jurnal ini bertujuan untuk mengidentifikasi permasalahan yang dialami oleh Banten dengan mengacu pada masa Pemerintahan Sultan Ageng Tirtayasa yang mengimplementasikan strategi Defence Agency. Metode dalam penulisan jurnal ini adalah metode kualitatif yang diperkuat oleh metode sejarah berupa heuristik, kritik, interpretasi, dan historiografi dengan pengumpulan data melalui wawancara dan studi kepustakaan. Temuan dalam penelitian adalah kemampuan Sultan Ageng Tirtayasa dalam memahami konteks, membuat keputusan dengan mempertimbangkan risiko, dan mengeksekusi keputusan dalam keadaan sulit yang disebut sebagai Defence Agency membuat Banten tetap bertahan dalam menghadapi blokade ekonomi VOC. Kesimpulan penulisan jurnal ini adalah Banten berkembang pesat di bawah pimpinan Sultan Ageng Tirtayasa sebagai kerajaan besar dan pelabuhan internasional. Meskipun menghadapi blokade ekonomi oleh VOC dan konflik politik, strategi Defence Agency yang diterapkan oleh Sultan Ageng Tirtayasa nyatanya mampu membuat Banten mengalami masa kejayaan. Implementasi dari Defence Agency yang diterapkan oleh Sultan Ageng Tirtayasa tersebut dapat diterapkan pada masa sekarang guna membangkitkan kembali kejayaan Banten pasca Pandemi Covid-19.

PURPOSERadiotherapy (RT) treatment at public hospitals in Nigeria is often interrupted by prolonged periods of machine breakdown because of insufficient funds for maintenance and repair. These delays have prompted the uptake of public-private partnerships (PPPs) to acquire and maintain RT equipment. This study aimed to understand Nigeria's current RT capacity and the impact of PPPs on RT availability and cost.METHODSEleven radiation oncologists, each representing one of the 11 RT centers in Nigeria (eight public and three private), were invited to complete a survey on the type, status, acquisition, and maintenance plan of existing RT equipment, cost incurred by patients for external-beam radiation (EBRT) and brachytherapy treatment, and number of patients treated per year on each machine. Type and status of equipment at nonresponding facilities were obtained through literature review and confirmed with the facility.RESULTSA total of eight (81%) respondents completed the survey, all representing public centers, three of which reported PPP use. They reported 11 megavoltage units in total (seven linear accelerators [LINACs] and four Cobalt-60s) and 10 brachytherapy afterloaders. Of those, 57% (4/7) of the LINACs, 100% (4/4) of the Cobalt-60s, and 63% (7/11) of the afterloaders were in clinical use. All commissioned equipment supported by PPPs (three LINACs and one afterloader) were in operation. The public EBRT equipment were nonfunctional 35% of the year (resulting in 60% fewer patients treated per year). The PPP EBRT and afterloaders did not experience any periods of breakdown, but PPP costs were 338% higher than public equipment.CONCLUSIONThis study characterizes the use of PPP as a more reliable method of RT delivery in Nigeria, albeit at higher costs.

Abstract Background Online communication has taken over in the last 2 years due to the frequent lockdowns because of the COVID-19 pandemic. Overburdened physicians in this pandemic are struggling to get enough time to teach clinical skills online to the students. Also, due to student’s safety issues, the students cannot fully attend the clinics. Therefore, in this scenario, online PAL (Peer Assisted Learning) sessions for clinical skill teaching and learning can be an effective alternative for undergraduate medical students. The academic limitations caused by the COVID-19 related lockdown however can have a pleasurable outcome if certain challenges, related to online PAL, are overcome. Therefore, the present study aims to identify the challenges of Peer Assisted Learning (PAL) sessions during online clinical skills training in the Ophthalmology module of undergraduate medical students. Methods This qualitative exploratory study, utilizing online focus group discussions to explore the challenges of online PAL in training and learning of clinical skills were carried at the Ophthalmology department of Batterjee Medical College, Jeddah; Saudi Arabia. A purposive convenient sampling technique was used to collect data. Data were transcribed and analyzed using thematic analysis. Results The study identified six themes that were further divided into smaller subthemes. The subthemes derived from the collected data were organized under the following major themes; infrastructure, learning environment, psychological problems, interaction deficit, learning desires, and desire for feedback on performance. The major challenge reported by the medical student during online PAL sessions was infrastructure in terms of network connection, scheduling, and timing of the session. The unprofessional learning environment, psychological problems in terms of behavioral issues and personality changes, interaction deficit with peers, tutor, and patient, learning desires, and desire for feedback on performance were the other important challenges faced by the students. Conclusion The challenges explored by our study can be used by the medical educators to incorporate online PAL as an effective, efficient, and alternative teaching and learning modality in the curriculum especially in compromised circumstances like the current COVID-19 pandemic.

In the course of its history, Islam in Nusantara has struggled with sosial realities for approximately 8 centuries. Islam in Nusantara has participated in coloring the sosial life of the Nusantaran people. The development of Islam in Nusantara is so fast and peaceful. This is something unique in history. a number of orientalist experts say that the main and first motive for the spread of Islam is wealth and power. However, archaeological data informs that Islam in Nusantara states otherwise. Even though Islam in Nusantara does not hold the reins of power, it continues to develop well in society. The da'i when spreading Islam, without adequate financial rewards, they often have to sacrifice material for the smooth running of da'wah. They also adapt to local socio-cultural conditions. Due to a natural process, archaeological facts inform that Islam in Nusantara often holds the reins of power, although this is not the main goal.

Brain network interactions are commonly assessed via functional (network) connectivity, captured as an undirected matrix of Pearson correlation coefficients. Functional connectivity can represent static and dynamic relations, but often these are modeled using a fixed choice for the data window Alternatively, deep learning models may flexibly learn various representations from the same data based on the model architecture and the training task. However, the representations produced by deep learning models are often difficult to interpret and require additional posthoc methods, e.g., saliency maps. In this work, we integrate the strengths of deep learning and functional connectivity methods while also mitigating their weaknesses. With interpretability in mind, we present a deep learning architecture that exposes a directed graph layer that represents what the model has learned about relevant brain connectivity. A surprising benefit of this architectural interpretability is significantly improved accuracy in discriminating controls and patients with schizophrenia, autism, and dementia, as well as age and gender prediction from functional MRI data. We also resolve the window size selection problem for dynamic directed connectivity estimation as we estimate windowing functions from the data, capturing what is needed to estimate the graph at each time-point. We demonstrate efficacy of our method in comparison with multiple existing models that focus on classification accuracy, unlike our interpretability-focused architecture. Using the same data but training different models on their own discriminative tasks we are able to estimate task-specific directed connectivity matrices for each subject. Results show that the proposed approach is also more robust to confounding factors compared to standard dynamic functional connectivity models. The dynamic patterns captured by our model are naturally interpretable since they highlight the intervals in the signal that are most important for the prediction. The proposed approach reveals that differences in connectivity among sensorimotor networks relative to default-mode networks are an important indicator of dementia and gender. Dysconnectivity between networks, specially sensorimotor and visual, is linked with schizophrenic patients, however schizophrenic patients show increased intra-network default-mode connectivity compared to healthy controls. Sensorimotor connectivity was important for both dementia and schizophrenia prediction, but schizophrenia is more related to dysconnectivity between networks whereas, dementia bio-markers were mostly intra-network connectivity.

Abstract Background Curriculum viability is determined by the degree to which quality standards have or have not been met, and by the inhibitors that affect attainment of those standards. The literature reports many ways to evaluate whether a curriculum reaches its quality standards, but less attention is paid to the identification of viability inhibitors in different areas of the curriculum that hamper the attainment of quality. The purpose of this study is to develop and establish the reliability and validity of questionnaires that measure the presence of inhibitors in an undergraduate medical curriculum. Methods Teacher and student questionnaires developed by the authors were sent to medical educationalists for qualitative expert validation and to establish their content validity. To establish the response process validity, cognitive interviews were held with teachers and students to clarify any confusion about the meaning of items in the questionnaires. Reliability and construct validity of the questionnaires were established by responses from 575 teachers and 247 final-year medical students. Results Qualitative expert validation was provided by 21 experts. The initial teacher and student questionnaires containing respectively 62 items to measure 12 theoretical constructs, and 28 items to measure 7 constructs, were modified to improve their clarity and relevance. The overall scale validity index for the questionnaires was, in order, .95 and .94. Following the cognitive interviews, the resultant teacher and student questionnaires were reduced to respectively 52 and 23 items. Furthermore, after the confirmatory analysis, the final version of the teacher questionnaire was reduced to 25 items to measure 6 constructs and the student questionnaire was reduced to 14 items to measure 3 constructs. Good-for-fit indices were established for the final model and Cronbach alphas of, in order, .89 and .81 were found for the teacher and student questionnaire. Conclusion The valid and reliable curriculum viability inhibitor questionnaires for teachers and students developed in this study can be used by medical schools to identify inhibitors to achieve standards in different areas of the curriculum.