Image compression using discrete cosine transform and wavelet transform and performance comparison

Image compression deals with reducing the size of image which is performed with the help of transforms. In this project we have taken the Input image and applied wavelet techniques for image compression and have compared the result with the popular DCT image compression. WT provided better result as far as properties like RMS error, image intensity and execution time is concerned. Now a days wavelet theory based technique has emerged in different signal and image processing application including speech, image processing and computer vision. In particular Wavelet Transform is of interest for the analysis of non-stationary signals. In the WT at high frequencies short windows and at low frequencies long windows are used. Since discrete wavelet is essentially sub band–coding system, sub band coders have been quit successful in speech and image compression. It is clear that DWT has potential application in compression problem

Perverse Filtrations via Brylinski-Radon transformations

In this article, we prove the $t$-exactness of a Brylinski-Radon transformation taking values in sheaves on flag varieties. This implies several weak Lefschetz type results for cohomology. In particular, we obtain de Cataldo-Migliorini's P=Dec(F) and Beilinson's basic lemma, the latter was an important ingredient in their proof of P=Dec(F). Our methods also allow the sharpening of Esnault-Katz's cohomological divisibility theorem and estimates for the Hodge level. Finally, we upgrade P=Dec(F) to an equivalence of functors which is also valid over a base.Comment: Comments are welcome

Inferring landscape preferences from social media using data science techniques

People and societies attribute different values to landscapes, which are often derived from their preferences. Such preferences are shaped by aesthetics, recreational benefits, safety, and other services provided by landscapes. Researchers have found that more appealing landscapes can promote human health and well-being. Existing methods used to study landscape preferences, such as social surveys, create high quality data but have high cost of time and effort and are poorly suited to capture dynamic landscape-scale changes across large geographic scales. With the rapid rise in social media, a huge amount of user-generated data is now available for researchers to study emotions or sentiments (i.e., preferences) towards particular topics of interest. This dissertation investigates how social media data can be used to indirectly measure (Zanten et al., 2016) and learn features relevant to landscape preferences, focusing primarily on a specific landscape called green infrastructure (GI). The first phase of the work introduces a first-ever benchmark GI location dataset within the US (GReen Infrastructure Dataset, or GRID) and develops a computer vision algorithm for identifying GI from aerial images using Google/Bing Map API. The data collected from this object detection method is then used to re-train a human preference model developed previously (Rai, 2013) and it improved the prediction accuracy significantly. I found that with the framework introduced here, we can collect the landscape data, which is comparable to the current methods in terms of quality with much less efforts. Second phase uses GI images and textual comments from Flickr, Instagram, and Twitter to train a lexicon-based sentiment model for predicting people's sentiments for GI. Since almost 70 percent of US adults are using some social media platform to connect with their friends, families or to follow recent news and topic of interest (Pew research, 2015), it is imperative to understand whether people share, post, or comment about the landscape settings they live in or prefer. And the results show that social media information can be really useful in predicting people’s sentiments about landscape they live or visit. The third phase builds on the second phase to identify specific features that are correlated with higher and lower preferences. The findings demonstrate that we can learn features that impacts people’s preference about the landscape. These features are very descriptive that a layperson can understand and can also be useful for designers, storm-water engineers, city planners to incorporate in their landscape designs such that it improves human health and well- being. Finally, I will conclude and describe some follow up research that I think would be potential in understanding landscape: work on speeding up the object detection algorithms using more advanced computer vision methods and harnessing the power of GPUs and extension of the findings to other types of GI and landscape designs

Anatomical variation of the Psoas Valley: a scoping review

Abstract: Background: This scoping review aimed to investigate the literature on the anatomy of the psoas valley, an anterior depression on the acetabular rim, and propose a unified definition of the anatomical structure, describe its dimensions, anatomical variations and clinical implications. Methods: A systematic computer search of EMBASE, PubMed and Cochrane for literature related to the psoas valley was undertaken using Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Clinical outcome studies, prospective/retrospective case series, case reports and review articles that described the psoas valley and its synonyms were included. Studies on animals as well as book chapters were excluded. Results: Of the 313 articles, the filtered literature search identified 14 papers describing the psoas valley and its synonyms such as iliopsoas notch, a notch between anterior inferior iliac spine and the iliopubic eminence, Psoas-U and anterior wall depression. Most of these were cross-sectional studies that mainly analyzed normal skeletal hips. In terms of anatomical variation, 4 different configurations of the anterior acetabular rim have been identified and it was found that the curved type was the most frequent while the straight type may be nonexistent. Additionally, the psoas valley tended to be deeper in males as compared with females. Several papers established the psoas valley, or Psoas-U in a consistent location at approximately 3 o’clock on the acetabular rim which may have implications with labral pathology. Conclusion: This review highlights the importance of the anatomy of the psoas valley which is a consistent bony landmark. The anatomy and the anatomical variations of the psoas valley need to be well-appreciated by surgeons involved in the management of young adults with hip pathology and also joint replacement surgeons to ensure appropriate seating of the acetabular component

Occupational stress and burnout among young surgeons: a review

A surgeon's lifestyle is a multifaceted commitment that revolves around their workplace, physical, personal, emotional, and communal domains. Surgical training programs are competitive and challenging to match and provide a sense of gratification among medical school trainees. But they also report a much higher level of burnout when compared to their peers from other specialities. Workplace burnout has been a scorching issue since the COVID pandemic broke out in 2019. We did this review to understand the factors leading to workplace burnout, identify any East-West differences, and find possible solutions. We also tried to find the role of COVID-19 in worsening occupational stress among surgeons. We searched the PubMed and SCOPUS databases for studies between January 2000 to January 2022 on burnout, well-being, wellness, and practice improvement among surgeons. The search included studies on COVID-19 that were available either as full-text papers or abstracts. Burnout has affected younger surgeons owing to loss of professional control, inefficient work-life balance, administrative burdens, medico-legal problems, and the competitive nature of the job and tiresome training programs. Burnout is more common in South-Asian countries. Workplace stressors, including long hours and difficult interactions with co-workers, are linked to greater levels of burnout. The COVID-19 pandemic has only made matters worse

How e-Health Has Influenced Patient Care and Medical Education: Lessons Learned from the COVID-19 Pandemic

The concept of e-Health involves the application of information and communication technologies from off-site locations to various domains of healthcare ranging from patient care, public health, and administration to health education. It refers to health informatics, telemedicine, electronic health records, and clinical decision support systems. The e-health initiatives aim to improve health outcomes in terms of quality, access, affordability, and efficient monitoring. The application of e-health interventions has particularly expanded in recent times because of the restrictions imposed by the pandemic. It has been proven to be nearly as effective as in-person care along with high patient and provider satisfaction and at decreased costs. We present our experience from the use of various e-health interventions during the COVID-19 pandemic along with a review of related literature. This ranged from Internet-based services, interactive TV or Polycom’s, kiosks, online monitoring of patient’s vital signs, and remote consultations with experts. Our success and experience with various e-health interventions during the pandemic allow us to provide a more hybrid form of healthcare in the future both for patient care and medical education and training

Whole exome screening identifies novel and recurrent WISP3 mutations causing progressive pseudorheumatoid dysplasia in Jammu and Kashmir-India

We report identification and genetic characterization of a rare skeletal disorder that remained unidentified for decades in a village of Jammu and Kashmir, India. The population residing in this region is highly consanguineous and a lack of understanding of the disorder has hindered clinical management and genetic counseling for the many affected individuals in the region. We collected familial information and identified two large extended multiplex pedigrees displaying apparent autosomal recessive inheritance of an uncharacterized skeletal dysplasia. Whole exome sequencing (WES) in members of one pedigree revealed a rare mutation in WISP3:c.156C > A (NP-003871.1:p.Cys52Ter), that perfectly segregated with the disease in the family. To our surprise, Sanger sequencing the WISP3 gene in the second family identified a distinct, novel splice site mutation c.643+1G > A, that perfectly segregated with the disease. Combining our next generation sequencing data with careful clinical documentation (familial histories, genetic data, clinical and radiological findings), we have diagnosed the families with Progressive Pseudorheumatoid Dysplasia (PPD). Our results underscore the utility of WES in arriving at definitive diagnoses for rare skeletal dysplasias. This genetic characterization will aid in genetic counseling and management, critically required to curb this rare disorder in the families

The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study

Objective To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. Patients and Methods This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. Results Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3–34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1–30.2), UTUC (n = 128) 1.14% (95% CI 0.77–1.52), renal cancer (n = 107) 1.05% (95% CI 0.80–1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32–2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03–1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90–4.15; P < 0.001), male sex 1.30 (95% CI 1.14–1.50; P < 0.001), and smoking 2.70 (95% CI 2.30–3.18; P < 0.001). Conclusions A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer