Potential of Indigenous Plants for Skin Healing and Care

The outer protective layer of body is skin which not only guards it from external fluctuations and effects but also performs its thermoregulation. Its functioning may get affected due to several factors like dermal wounds, injuries, aging and many other disorders. These dermal ailments can be cured with the help of indigenous flora to get economical pharamcognosal benefits with no side effects which is a serious concern of synthetic drugs now days. Furthermore, research efforts are necessary for their proper dose optimization and administration to achieve low cost and side effects free pharamcognosal skin cure and care gains

Discrimination of Seasonal Snow Cover in Astore Basin, Western Himalaya using Fuzzy Membership Function of Object-Based Classification

The temporal mapping of seasonal snow cover is generally being delineated through low resolution MODIS data (250-500m resolution) due to daily frequency of image acquisition; however, it sometimes compromises the mapping accuracies. In this study, the time-series of high resolution satellite imagery was used to evaluate the spatio-temporal changes in the snow covered area of Astore basin during summer and winter seasons from 1990 to 2017. The Object Based Image Analysis (OBIA) technique was applied on multi-spectral images of Landsat (TM and OLI sensors) of respective years (1990, 2000, 2010 and 2017) in order to discriminate the snow covered area in both seasons. Although OBIA is a strong technique that has been successfully applied in numerous research problems of remote sensing regarding cryosphere, but due to hindrances (i.e. Clouds and haze), it is sometimes not highly efficient to detect the snow accurately, therefore, Normalized Difference Snow Index (NDSI) has been calculated to distinguish snow covered area from snow free areas. The range of 0.4-1.0 was used as a threshold value for fuzzy membership function in OBIA to delineate the snow cover more precisely. The study suggested that the snow covered area is gradually increasing in winters during past few decades in the basin; however, in summer season as compared to winters, no specific trend has been observed

Precision Agriculture using Internet of thing with Artificial intelligence: A Systematic Literature Review

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this revie

The future of artificial intelligence in neurosurgery: a narrative review

Background: Artificial intelligence (AI) and machine learning (ML) algorithms are on the tremendous rise for being incorporated into the field of neurosurgery. AI and ML algorithms are different from other technological advances as giving the capability for the computer to learn, reason, and problem-solving skills that a human inherits. This review summarizes the current use of AI in neurosurgery, the challenges that need to be addressed, and what the future holds. Methods: A literature review was carried out with a focus on the use of AI in the field of neurosurgery and its future implication in neurosurgical research. Results: The online literature on the use of AI in the field of neurosurgery shows the diversity of topics in terms of its current and future implications. The main areas that are being studied are diagnostic, outcomes, and treatment models. Conclusion: Wonders of AI in the field of medicine and neurosurgery hold true, yet there are a lot of challenges that need to be addressed before its implications can be seen in the field of neurosurgery from patient privacy, to access to high-quality data and overreliance on surgeons on AI. The future of AI in neurosurgery is pointed toward a patient-centric approach, managing clinical tasks, and helping in diagnosing and preoperative assessment of the patients

Faculty Perspective on the Challenges Faced During Implementation of Integrated Curriculum

Background: Curriculum is a dynamic thing that has evolved over the years to ensure the competency of health care professionals. Due to guidelines issued by international accrediting agencies, University College of Medicine & Dentistry implemented an integrated modular curriculum in 2015 that is coordinated and coherent.  Objectives: The objective of this study was to explore the difficulties that the faculty faced while implementing an integrated curriculum for the undergraduate dental program (BDS) at the University College of Dentistry, The University of Lahore.   Methods: This descriptive exploratory study was conducted from September 2020 till January 2021 at University College of Dentistry, The University of Lahore. Thirty-five faculty members were interviewed. The interviews were analyzed thematically after being transcribed. Results: Six themes emerged from the analysis of interviews. These themes were: working environment, distribution of workload, communication, faculty development and retention, evaluation and leadership. Conclusions: Integrated curriculum may be the need of the hour; however, its implementation comes with a set of challenges, which include a non-conducive working environment, uneven distribution of workload, absence of a sound faculty development and retention program, or absence of adequate resources. These factors may hinder the implementation of the integrated curriculum

Construction of a Well-Defined S-Scheme Heterojunction Based on Bi-ZnFe₂O₄/S-g-C₃N₄ Nanocomposite Photocatalyst to Support Photocatalytic Pollutant Degradation Driven by Sunlight

Currently, organic dyes and other environmental contaminants are focal areas of research, with considerable interest in the production of stable, high-efficiency, and eco-friendly photocatalysts to eliminate these contaminants. In the present work, bismuth-doped zinc ferrite (Bi-ZnFe2O4) nanoparticles (NPs) and bismuth-doped zinc ferrites supported on sulfur-doped graphitic carbon nitride (Bi-ZnFe2O4/S-g-C3N4) (BZFG) photocatalysts were synthesized via a hydrothermal process. SEM, XRD, and FTIR techniques were used to examine the morphological, structural, and bonding characteristics of the synthesized photocatalysts. The photocatalytic competence of the functional BZFG nanocomposites (NCs) was studied against MB under sunlight. The influence of Bi (0.5, 1, 3, 5, 7, 9, and 11 wt.%) doping on the photocatalytic performance of ZnFe2O4 was verified, and the 9%Bi-ZnFe2O4 nanoparticles exhibited the maximum MB degradation. Then, 9%Bi-ZnFe2O4 NPs were homogenized with varying amounts of S-g-C3N4 (10, 30, 50, 60, and 70 wt.%) to further enhance the photocatalytic performance of BZFG NCs. The fabricated Bi-ZnFe2O4/30%S-g-C3N4 (BZFG-30) composite outperformed ZnFe2O4, S-g-C3N4 and other BZFG NCs in terms of photocatalytic performance. The enriched photocatalytic performance of the BZFG NCs might be ascribed to a more efficient transfer and separation of photo-induced charges due to synergic effects at the Bi-ZnFe2O4/S-g-C3N4 interconnection. The proposed modification of ZnFe2O4 using Bi and S-g-C3N4 is effective, inexpensive, and environmentally safe

Self-reported health and smoking status, and body mass index: a case-control comparison based on GEN SCRIP (GENetics of SChizophRenia In Pakistan) data

Introduction Individuals with schizophrenia are at a high risk of physical health comorbidities and premature mortality. Cardiovascular and metabolic causes are an important contributor. There are gaps in monitoring, documenting and managing these physical health comorbidities. Because of their condition, patients themselves may not be aware of these comorbidities and may not be able to follow a lifestyle that prevents and manages the complications. In many low-income and middle-income countries including Pakistan, the bulk of the burden of care for those struggling with schizophrenia falls on the families.Objectives To determine the rate of self-reported physical health disorders and risk factors, like body mass index (BMI) and smoking, associated with cardiovascular and metabolic disorders in cases of schizophrenia compared with a group of mentally healthy controls.Design A case-controlled, cross-sectional multicentre study of patients with schizophrenia in Pakistan.Settings Multiple data collection sites across the country for patients, that is, public and private psychiatric OPDs (out patient departments), specialised psychiatric care facilities, and psychiatric wards of teaching and district level hospitals. Healthy controls were enrolled from the community.Participants We report a total of 6838 participants’ data with (N 3411 (49.9%)) cases of schizophrenia compared with a group of healthy controls (N 3427 (50.1%)).Results BMI (OR 0.98 (CI 0.97 to 0.99), p=0.0025), and the rate of smoking is higher in patients with schizophrenia than in controls. Problems with vision (OR 0.13 (0.08 to 0.2), joint pain (OR 0.18 (0.07 to 0.44)) and high cholesterol (OR 0.13 (0.05 to 0.35)) have higher reported prevalence in controls. The cases describe more physical health disorders in the category ‘other’ (OR 4.65 (3.01 to 7.18)). This captures residual disorders not listed in the questionnaire.Conclusions Participants with schizophrenia in comparison with controls report more disorders. The access in the ‘other’ category may be a reflection of undiagnosed disorders