Designing and implementation of robot mapping algorithm for mobile robot

.A mobile robot is an automatic machine that is capable of movement in any given environment [1]. The Capabilities of Mobile Robot(s) are: Moving around based on the user’s input, Avoiding obstacle in front of it and Calculating the path. The Criteria of Mobile Robot: Desktop size. A robot that can evolve on the desk near the computer improves drastically the student efficiency during experimentation. Wide range of possibilities from an engineering and educational point of view. To exploit this tool in various fields of education such as signal processing, automatic control, embedded programming, or distributed intelligent systems design, the robot should provide a wide set of functionalities in its basic version. User friendly. The user interface has to be simple, efficient, and intuitive. This is an important point for the acceptance of the system by the students. The broad introduction in engineering classes requires a large number of robots. Knowing that the budget of many schools is constant or decreasing, this is only feasible by reducing the cost of an individual robot. Open information. This robot has to be shared among professors, laboratories, schools and universities. An open source hardware/software development model is an effective way to achieve this goal

Implementation of Cognitive Mapping Algorithm for Robot Navigation System

Abstract—Mobile robot is a construction of robot that is equipped with wheel to move around its environment in finishing its specific task. Robot will be given some algorithm for certain task. In this project, we are going to build the cognitive mapping algorithm that can be implemented to the mobile robot. This mobile robot will be given some inputs which are horizontal and vertical value and start and goal point and a task which is to move from start point to goal point. Some obstacles are also located in the arena and the mobile robot must be able to avoid any given obstacles to reach the goal point. After doing all implementation, finally, some comparison between robot mapping and robot edge follower will be done to observe the differences between these algorithms in term of time and path needed

A bionomic study of parasitoids in the Taman Beringin landfill in Kepong and a poultry farm in Sungai Pelek, Selangor, Malaysia

A four-month cross-sectional study found five species of parasitoids parasitizing puparia of filth flies breeding at the Taman Beringin landfill in Kepong and a poultry farm in Sungai Pelek, Sepang, Selangor. Effect of monthly rainfalls towards density of flies and percentage of parasitoids emerging from collected puparia were also analyzed. Spalangia sp. was the most common, consisting of Spalangia endius Walker, S. cameroni Perkins and S. gemina Boucek. Other parasitoids collected were Pachycrepoideus vindemmiae Rondani and Exoristobia phillipinensis Ashmead. The parasitized fly hosts were Musca domestica Linn. and Chrysomya megacephala Fabricius. S. endius was the most common parasitoid attacking M. domestica at both locations. M. domestica was the most common fly found at the Sg. Pelek poultry farm whereas C. megacephala was the most numerous at the Taman Beringin landfill. During heavy rainfall month of November 2003, density of flies were high whereas the emerging parasitoids were low at both landfill and poultry farm. The present study revealed the endemic presence of parasitoids especially S. endius in both poultry farm and garbage landfill and the potential of the parasitoid species in fly control in Malaysia

Management of patients with advanced prostate cancer—metastatic and/or castration-resistant prostate cancer: report of the Advanced Prostate Cancer Consensus Conference (APCCC) 2022

Background: Innovations in imaging and molecular characterisation together with novel treatment options have improved outcomes in advanced prostate cancer. However, we still lack high-level evidence in many areas relevant to making management decisions in daily clinical practise. The 2022 Advanced Prostate Cancer Consensus Conference (APCCC 2022) addressed some questions in these areas to supplement guidelines that mostly are based on level 1 evidence. Objective: To present the voting results of the APCCC 2022. Design, setting, and participants: The experts voted on controversial questions where high- level evidence is mostly lacking: locally advanced prostate cancer; biochemical recurrence after local treatment; metastatic hormone-sensitive, non-metastatic, and metastatic castration- resistant prostate cancer; oligometastatic prostate cancer; and managing side effects of hormonal therapy. A panel of 105 international prostate cancer experts voted on the consensus questions. Outcome measurements and statistical analysis: The panel voted on 198 pre-defined questions, which were developed by 117 voting and non-voting panel members prior to the conference following a modified Delphi process. A total of 116 questions on metastatic and/or castration- resistant prostate cancer are discussed in this manuscript. In 2022, the voting was done by a web-based survey because of COVID-19 restrictions. Results and limitations: The voting reflects the expert opinion of these panellists and did not incorporate a standard literature review or formal meta-analysis. The answer options for the consensus questions received varying degrees of support from panellists, as reflected in this article and the detailed voting results are reported in the supplementary material. We report here on topics in metastatic, hormone-sensitive prostate cancer (mHSPC), non-metastatic, castration-resistant prostate cancer (nmCRPC), metastatic castration-resistant prostate cancer (mCRPC), and oligometastatic and oligoprogressive prostate cancer. Conclusions: These voting results in four specific areas from a panel of experts in advanced prostate cancer can help clinicians and patients navigate controversial areas of management for which high-level evidence is scant or conflicting and can help research funders and policy makers identify information gaps and consider what areas to explore further. However, diagnostic and treatment decisions always have to be individualised based on patient characteristics, including the extent and location of disease, prior treatment(s), co-morbidities, patient preferences, and treatment recommendations and should also incorporate current and emerging clinical evidence and logistic and economic factors. Enrolment in clinical trials is strongly encouraged. Importantly, APCCC 2022 once again identified important gaps where there is non-consensus and that merit evaluation in specifically designed trials. Patient summary: The Advanced Prostate Cancer Consensus Conference (APCCC) provides a forum to discuss and debate current diagnostic and treatment options for patients with advanced prostate cancer. The conference aims to share the knowledge of international experts in prostate cancer with healthcare providers worldwide. At each APCCC, an expert panel votes on pre-defined questions that target the most clinically relevant areas of advanced prostate cancer treatment for which there are gaps in knowledge. The results of the voting provide a practical guide to help clinicians discuss therapeutic options with patients and their relatives as part of shared and multidisciplinary decision-making. This report focuses on the advanced setting, covering metastatic hormone-sensitive prostate cancer and both non-metastatic and metastatic castration-resistant prostate cancer. Twitter summary: Report of the results of APCCC 2022 for the following topics: mHSPC, nmCRPC, mCRPC, and oligometastatic prostate cancer. Take-home message: At APCCC 2022, clinically important questions in the management of advanced prostate cancer management were identified and discussed, and experts voted on pre-defined consensus questions. The report of the results for metastatic and/or castration- resistant prostate cancer is summarised here

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Global, regional, and national burden of colorectal cancer and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Funding: F Carvalho and E Fernandes acknowledge support from Fundação para a Ciência e a Tecnologia, I.P. (FCT), in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy i4HB; FCT/MCTES through the project UIDB/50006/2020. J Conde acknowledges the European Research Council Starting Grant (ERC-StG-2019-848325). V M Costa acknowledges the grant SFRH/BHD/110001/2015, received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória DL57/2016/CP1334/CT0006.proofepub_ahead_of_prin

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.Peer reviewe