Content Analysis of General Science Text Book for 8th Grade

General science textbooks due to integrated contents of Biology, Chemistry, Physics and; Earth and Space, need special attention of curriculum developers. The contents in general science textbooks can be evaluated through different methods and curriculum analysis taxonomy (CAT) is one of these. This research paper explores the contents of general science textbook of 8th grade taught in all government schools and in some private schools of Punjab province. The contents of textbook were broken down in term of Piagetian developmental levels by using Curriculum Analysis Taxonomy (CAT). The findings show that majority of contents of General science textbook were at Concrete Operational level while a small number of contents demands Formal Operational level. This uneven distribution of contents at different Piagetian developmental levels were also observed when contents of Biology, Chemistry, Physics and; Earth and Space were separately studied. It is recommended that the distribution of contents should follow model based on Piagetian development levels and the selection of contents should be on the basis of breadth and depth of the concepts.

Improving diagnosis and prognosis of lung cancer using vision transformers: A scoping review

Vision transformer-based methods are advancing the field of medical artificial intelligence and cancer imaging, including lung cancer applications. Recently, many researchers have developed vision transformer-based AI methods for lung cancer diagnosis and prognosis. This scoping review aims to identify the recent developments on vision transformer-based AI methods for lung cancer imaging applications. It provides key insights into how vision transformers complemented the performance of AI and deep learning methods for lung cancer. Furthermore, the review also identifies the datasets that contributed to advancing the field. Of the 314 retrieved studies, this review included 34 studies published from 2020 to 2022. The most commonly addressed task in these studies was the classification of lung cancer types, such as lung squamous cell carcinoma versus lung adenocarcinoma, and identifying benign versus malignant pulmonary nodules. Other applications included survival prediction of lung cancer patients and segmentation of lungs. The studies lacked clear strategies for clinical transformation. SWIN transformer was a popular choice of the researchers; however, many other architectures were also reported where vision transformer was combined with convolutional neural networks or UNet model. It can be concluded that vision transformer-based models are increasingly in popularity for developing AI methods for lung cancer applications. However, their computational complexity and clinical relevance are important factors to be considered for future research work. This review provides valuable insights for researchers in the field of AI and healthcare to advance the state-of-the-art in lung cancer diagnosis and prognosis. We provide an interactive dashboard on lung-cancer.onrender.com/.Comment: submitted to BMC Medical Imaging journa

Spot the fake lungs: Generating Synthetic Medical Images using Neural Diffusion Models

Generative models are becoming popular for the synthesis of medical images. Recently, neural diffusion models have demonstrated the potential to generate photo-realistic images of objects. However, their potential to generate medical images is not explored yet. In this work, we explore the possibilities of synthesis of medical images using neural diffusion models. First, we use a pre-trained DALLE2 model to generate lungs X-Ray and CT images from an input text prompt. Second, we train a stable diffusion model with 3165 X-Ray images and generate synthetic images. We evaluate the synthetic image data through a qualitative analysis where two independent radiologists label randomly chosen samples from the generated data as real, fake, or unsure. Results demonstrate that images generated with the diffusion model can translate characteristics that are otherwise very specific to certain medical conditions in chest X-Ray or CT images. Careful tuning of the model can be very promising. To the best of our knowledge, this is the first attempt to generate lungs X-Ray and CT images using neural diffusion models. This work aims to introduce a new dimension in artificial intelligence for medical imaging. Given that this is a new topic, the paper will serve as an introduction and motivation for the research community to explore the potential of diffusion models for medical image synthesis. We have released the synthetic images on https://www.kaggle.com/datasets/hazrat/awesomelungs.Comment: 8 pages. Submitted to AICS 2022 conferenc

Moral Hazard, Monitoring and Punishment: Evidence from a Field Experiment

The existing literature establishes that there exists inefficiency in energy consumption in Pakistan. In particular, with regard to electricity consumption, the problem of moral hazard is prevalent in the public sector. In this study, we observe this aspect by focusing on the behaviour of consumers once they are held liable to monitoring with the associated punishment mechanism. By providing evidence from a field experiment, we make three conclusions. First, individuals respond to both the monetary and non-monetary punishments. Alternatively, with the introduction of punishments, they reduce moral hazard with respect to electricity consumption. Second, the habitual violators of rules reform their behaviour after they are made accountable for their actions. Third, if appropriate monitoring systems along with the associated punishment mechanism are introduced, we can have beneficial effects in terms of resolving the energy crisis on the aggregate level. JEL Classification: H83, D12, D00, D03, D04 Keywords: Moral Hazard, Monitoring, Punishment, Electricity Consumption, Public Secto

Efficient Algorithms to Compute Hierarchical Summaries from Big Data Streams

Many data stream applications have hierarchical data; containing time, geographic locations, product information, clickstreams, server logs, IP addresses. A hierarchical summary of such volumous data offers multiple advantages including compactness, quick understanding, and abstraction. The goal of this thesis is to design algorithmic approaches for summarizing hierarchical data streams. First, this thesis provides a theoretical analysis of the benchmark hierarchical heavy hitters' algorithms and uncovers their shortcomings such as requiring high theoretical memory, updates and coverage problem. To address these shortcomings, this thesis proposes efficient algorithms which offer deterministic estimation accuracy using O(η/ε) worst-case memory and O(η) worst-case time complexity per item, where ε ∈ [0,1] is a user defined parameter and η is a small constant derived from the data. The proposed hierarchical heavy hitters' algorithms are shown to have improved significantly over existing algorithms both theoretically as well as empirically. Next, this thesis introduces a new concept called hierarchically correlated heavy hitters, which is different from existing hierarchical summarization techniques. The thesis provides a formal definition of the proposed concept and compares it with existing hierarchical summarization approaches both at definition level and empirically. It also proposes an efficient hierarchy-aware algorithm for computing hierarchically correlated heavy hitters. The proposed algorithm offers deterministic estimation accuracy using O(η / (ε_p * ε_s )) worst-case memory and O(η) worst-case time complexity per item, where η is as defined previously, and ε_p ∈ [0,1], ε_s ∈ [0,1] are other user defined parameters. Finally, the thesis proposes a special hierarchical data structure and algorithm to summarize spatiotemporal data. It can be used to extract interesting and useful patterns from high-speed spatiotemporal data streams at multiple spatial and temporal granularities. Theoretical and empirical analysis are provided, which show that the proposed data structure is very efficient concerning data storage and response to queries. It updates a single item in O(1) time and responds to a point query in O(1) time. Importantly, the memory requirement of the proposed data structure is independent of the size of the data and only depends on user-supplied parameters ψ ⃗ and φ ⃗. In summary, this thesis provides a general framework consisting of a set of algorithms and data structures to compute hierarchical summaries of the big data streams. All of the proposed algorithms exploit a lattice structure built from the hierarchical attributes of the data to compute different hierarchical summaries, which can be used to address various data analytic issues in many emerging applications

Experience with the WHO Surgical Safety Checklist

Despite years of efforts by organizations throughout the world “wrong site” surgery has proven to be a resilient opponent. The purpose of present review article is to revisit the various tools that have been designed specially the WHO Surgical Safety Checklist (SSCL), the purpose of which is to improve patient safety and prevent errors in the site of surgery. Three items were the corner stone of this review. Firstly effectiveness of the tools specially the WHO SSCL, secondly approach of those responsible for implementation and thirdly adherence by organizations to the provided guideline. A general review of the available data showed a clear improvement in patient safety. As a whole medical personnel considered SSCl and other tools as a good addition but these tools have yet to prove their worth in the prevention of “wrong site” surgery. There is a need to strive continuously for improving patient safety and to capitalize on the advances made in this regard to prevent this menace. At our Rawalpindi Medical University affiliated Holy Family Hospital efforts are in place for improving ways and developing protocols to curb the evil of wrong site surgery. We currently adopted a new way proposed by Ragusa et al in which we experimented with keeping the surgical instruments and trolley outside the OR away from the surgery team members. Thus preventing distraction of team members till the completion of SSCl. Additionally the Anesthetist took the responsibility of the implementation of the SSCL. This method also prevented the hierarchal style seen in the operation theatres. 1,2 These sentinel events policy was published in 1996.3 By the Joint Commission. This commission is an independent body which has 20,500 health care facilities accredited with it in the USA. The aim of this policy was to help individuals and organizations to learn from their mistakes and achieve the objective of patient safety and zero rate of wrong site surgery4. Wrong site surgery mean surgery done on the wrong patient, surgery on the wrong site or may be a wrong surgery on the wrong patient.4 After review of the record the American Academy of Orthopedics claimed that the orthopedic surgeons have a 25% likelihood of operating a wrong site during their careers. After this claim a campaign “Sign Your Site” was started which proposed that surgeons should sign the surgical site before surgery is done.5 A similar scheme known as the “SMaX” which stands for signing, marking and X-ray of the spine segment was launched by the North American Spine Society in 2001.6     In 2004 The Joint Commission proposed a Universal Protocol. The Commission made it compulsory for all medical facilities under its accreditation to adopt it.7 This document included confirmation of patient and surgical site, its marking and time out before any elective surgery. The World Health Organization (WHO) a subsidiary of the United Nations, which is charged with managing the global health affairs, developed the “surgical Safety Checklist” in the year 2008. This checklist was a product of the “Safe Surgery Saves Lives” campaign. According to this document three phases have been identified in any surgery,. i.e., “Sign In” prior to the anesthesia induction, “Time Out” before incision and “Sign Out” before the patient leaves the operating room. 8-10 Unfortunately in 2009 Stahel et al found an increased number of wrong site surgery.  11 This was preceded by the Joint Commission report  with similar findings.10 Following these disappointing results the Commission further augmented the importance given to the issue by declaring the Universal Protocol as the National patient Safety Goal.12,13 This review article goes through the studies and literature recently published as SSCL and similar tools that have been developed over time to prevent wrong site surgery and improve patient care. The aim was to identify how effective is the SSCL in achieving its goals. Hurdles in the achieving maximum results were also identified. The thinking and view point of those involved in the implementation were sought, emphasis was also placed on how thoroughly organizations comply with the provided guideline

Zulfiqar Ali Bhutto Regime and Growth of the Baloch Nationalism in 1970s

Zulfiqar Ali Bhutto was the first elected prime minister of Pakistan His initial strategy of accommodation and power sharing with the regionalists in Balochistan had a positive impact on the national politics The regionalists started to distance themselves from secessionist tendencies However the policy of pacification was short-lived The central government instead of addressing political conflicts with consensus resorted to undemocratic means The process of democratization in Balochistan was disrupted and the provincial government was dissolved The autonomists were sidelined and were dubbed as anti-state elements The extremists within the autonomists fold were infuriated and started the armed insurgency The central government launched an army operation to cope with insurgents Bhutto s regime marked a tendency towards executive despotism Despite provincial government s alleged defiance of federal authority the central government could have treated them with patience and tolerance visualizing the sensitivity of the Balochistan crisi

Discourse and Power Relations: A Critical Discourse Analysis of a Pakistani Talk Show

The paper aims at studying the ways power and inequality are enacted in a Pakistani talk show aired on Capital TV on 14th August 2019. The research primarily focused on analyzing turn-taking patterns of the discussion held between the host of the program and three guests. The analysis revealed the unequal distribution of turns implying the unequal distribution of power between the host and guests as well as between the guests. The host of the program through her discourse asserted power as she was the one to control the topic of discussion throughout the program. Her power can be attributed to the power of media. Besides, one of the guest speakers, Jawwad asserted his power through his knowledge. The female speaker did not have enough representation and was not given enough chance to share her views, therefore, it can be concluded that gender was another element that played an important part in forming the power relations in the discussion that was observed.Keywords: Critical Discourse Analysis, Discourse Power Relations, Media Discourse and Talk Shows, Turn-takin

Inguinal Hernia Repair on Day Care Basis During Global COVID-19 Pandemic

  Abstract Background: COVID-19 has effected General Surgical Elective list and most of the surgical procedures are postpone. Inguinal hernia surgery can be performed under local anesthesia on day care basis in selected group of patients taking all necessary precautions for COVID-19. Patients & Methods: This prospective study was conducted at department of General Surgery Federal Hospital, Islamabad for a period of three months from 15th March 2020 to 15th June 2020. All patients were included in the study through purposive sampling and preference was given to patients elder than 50 years of age. This study included 59 adult patients with inguinal hernia who under mesh repair under local anaesthesia on day care basis. Results: A total of 59 patients were included in the study. All patients were male. The age range was from 37 to 82 years (SD=± 10.23).  30 (50.84%) patient had inguinal hernia on left side while 26 (44.06%) had hernia on right side. Mean Operative time was 35 min. Pain was chief complaint postoperatively 30 (50.8%) patients had moderate pain while 6 (10.1%) patients had severe pain in first 24 hours after surgery. Fever was present in 15 (25.42%) patients in first 24 hours. All patients were negative for COVID -19 preoperatively and after 2 weeks none of the patients develop any symptoms of COVID-19. 3 (5.08%) patients needed readmission within 24 hours for pain and some haemorrhage. There was no mortality in our study Conclusions: Inguinal Hernia Surgery under local anaesthesia on day care basis in a very good practice at this time of global pandemic of COVID-19. This is a safe and reliable strategy. Key words: Inguinal Hernia, COVID-19, Local Anaesthesia &nbsp