Constellation Queries over Big Data

A geometrical pattern is a set of points with all pairwise distances (or, more generally, relative distances) specified. Finding matches to such patterns has applications to spatial data in seismic, astronomical, and transportation contexts. For example, a particularly interesting geometric pattern in astronomy is the Einstein cross, which is an astronomical phenomenon in which a single quasar is observed as four distinct sky objects (due to gravitational lensing) when captured by earth telescopes. Finding such crosses, as well as other geometric patterns, is a challenging problem as the potential number of sets of elements that compose shapes is exponentially large in the size of the dataset and the pattern. In this paper, we denote geometric patterns as constellation queries and propose algorithms to find them in large data applications. Our methods combine quadtrees, matrix multiplication, and unindexed join processing to discover sets of points that match a geometric pattern within some additive factor on the pairwise distances. Our distributed experiments show that the choice of composition algorithm (matrix multiplication or nested loops) depends on the freedom introduced in the query geometry through the distance additive factor. Three clearly identified blocks of threshold values guide the choice of the best composition algorithm. Finally, solving the problem for relative distances requires a novel continuous-to-discrete transformation. To the best of our knowledge this paper is the first to investigate constellation queries at scale

The Comparison of The Efficacy of Photobiomodulation and Ultrasound in the Treatment of Chronic Non-specific Neck Pain: A Randomized Single-Blind Controlled Trial

Introduction: Chronic neck pain is a common complaint among office workers. The aim of the present study was to compare the efficacy of a high-intensity laser and physiotherapy in office workers who were diagnosed with chronic non-specific neck pain.Methods: This study was a single-blind randomized controlled trial, with parallel allocation. Sixty office workers with chronic neck pain, aged between 25 and 55 years, participated in the study. The participants were randomly divided into two groups: photobiomodulation (by a high-level laser) and physiotherapy. Visual analog scale (VAS), Neck Disability Index (NDI), Neck Pain and Disability Scale (NPDS), and Bournemouth Questionnaire (BQN) were completed on three occasions (before, immediately, and 2 weeks after the intervention) to assess and compare the efficacy of the high-intensity laser and physiotherapy in neck pain. Data were analyzed by SPSS 23 software using the chi-square test, Student’s t-test, multivariate tests, and Fisher’s exact test.Results: The mean age of the participants was 37.53±9.52 and 41.16±7.85 years in physiotherapy and laser therapy respectively. The VAS score and NDI scores decreased after both kinds of interventions, and the effect of photobiomodulation was significantly higher than physiotherapy (P<0.001). Both treatment modalities significantly affect different aspects of chronic neck pain assessed by NDPS and BQN questionnaires and the effect of photobiomodulation was more prominent than physiotherapy.Conclusion: The findings of this study showed that photobiomodulation and physiotherapy can reduce chronic neck pain and its different aspects and the effect of laser therapy was significantly higher than physiotherapy DOI: 10.34172/jlms.2021.2

Foundation Metrics: Quantifying Effectiveness of Healthcare Conversations powered by Generative AI

Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will probably drive this patient-centered transformation in healthcare. Through the provision of various services, including diagnosis, personalized lifestyle recommendations, and mental health support, the objective is to substantially augment patient health outcomes, all the while mitigating the workload burden on healthcare providers. The life-critical nature of healthcare applications necessitates establishing a unified and comprehensive set of evaluation metrics for conversational models. Existing evaluation metrics proposed for various generic large language models (LLMs) demonstrate a lack of comprehension regarding medical and health concepts and their significance in promoting patients' well-being. Moreover, these metrics neglect pivotal user-centered aspects, including trust-building, ethics, personalization, empathy, user comprehension, and emotional support. The purpose of this paper is to explore state-of-the-art LLM-based evaluation metrics that are specifically applicable to the assessment of interactive conversational models in healthcare. Subsequently, we present an comprehensive set of evaluation metrics designed to thoroughly assess the performance of healthcare chatbots from an end-user perspective. These metrics encompass an evaluation of language processing abilities, impact on real-world clinical tasks, and effectiveness in user-interactive conversations. Finally, we engage in a discussion concerning the challenges associated with defining and implementing these metrics, with particular emphasis on confounding factors such as the target audience, evaluation methods, and prompt techniques involved in the evaluation process.Comment: 13 pages, 4 figures, 2 tables, journal pape

Integrated Electricity and Gas Systems Planning: New Opportunities, and a Detailed Assessment of Relevant Issues

Integrated electricity and gas systems (IEGS) with power-to-gas (PtG) units, as novel sector coupling components between electricity and gas systems, have been considered a promising solution for the reliable and economic operation of the integrated energy systems which can effectively reduce the challenges associated with the high penetration of renewable energy sources (RES). To confirm the economic viability and technical feasibility of the IEGS, its coordinated planning will play a crucial role. The more comprehensive the modeling and evaluation of IEGS planning studies are, the more precise and practical the results obtained will be. In this paper, an in-depth and up-to-date assessment of the available literature on the IEGS planning is presented by addressing critical concerns and challenges, which need further studies. A vast variety of related topics in the IEGS planning, including the impact of costs, constraints, uncertainties, contingencies, reliability, sector coupling components, etc., are also reviewed and discussed. In addition, the role of PtGs and their impacts on the coordinated IEGS planning are reviewed in detail due to their crucial role in increasing the penetration of RES in future energy systems as well as limiting greenhouse gas emissions. The literature review completed by this paper can support planners and policymakers to better realize the bottlenecks in the IEGS development, so that they can concentrate on the remaining unsolved topics as well as the improvement of existing designs and procedures

Crosstalk between Sleep Disturbance and Opioid Use Disorder:A Narrative Review

Recent studies have revealed a growing number of patients affected by opioid use disorders (OUDs).Comorbid disorders are suspected to increase the risk of opioid-related adverse effects or treatment failure.The correlation of opioid use with sleep disturbances has been reported in many different studies andsuggested to be linked to the brain regions involved in reward processing. This narrative review was intendedto discuss the most recent developments in our understanding of the intricate interaction between sleepdisturbance and OUD. In addition, in this study, the effects of sleep problems on the occurrence ofunpleasant consequences in addiction management, such as craving and relapse in OCD patients, werehighlighted. It has been shown that drug use may trigger the induction of sleep disturbances, and thosesuffering from difficulties in sleeping are prone to relapse to drug use, including opioids. Moreover,pharmaceutical sleep aids are likely to interfere with opiate use