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Interconnection network topology is critical for the overall performance of HPC systems. While many regular and irregular topologies have been proposed in the past, recent work has shown the promise of shortcut-augmented topologies that offer multi-fold reduction in network diameter and hop count over conventional topologies. However, the large number of possible shortcuts creates an enormous design space for this new type of topology, and existing approaches are extremely slow and do not find shortcuts that are globally optimal. In this paper, we propose an efficient heuristic approach, called EdgeCut, which generates high-quality shortcut-augmented topologies. EdgeCut can identify more globally useful shortcuts by making its considerations from the perspective of edges instead of vertices. An additional implementation is proposed that approximates the costly all-pair shortest paths calculation, thereby further speeding up the scheme. Quantitative comparisons over prior work show that the proposed approach achieves a 1982× reduction in search time while generating better or equivalent topologies in 94.9% of the evaluated cases.

Recommender algorithms can guide users in a personalized way to interesting objects in a large space of possible options. The necessity of recommendations is increasing on cultural or entertainment and media industries, where the number of products is continuously increasing. Cultural and media platforms and digital markets are getting heavily benefitted from implementing, maintaining, and improving their recommender system. The process on how they retrieve cultural products like music, books, movies, news and enable easy access to the users can have a structural impact on how markets operate alongside how consuming trends change. The prospect of this project is to engineer a complete recommender system for noozy.tv, a new video-on-demand platform dedicated for the viewers of Grand Est region in France. The aim is to develop a framework maintaining standard and modern software development methodologies and tools to ensure seamless service, research scope on real data and diversity, evaluation, and delivering a platform for further improvement in system., Résumé Les algorithmes de recommandation peuvent guider les utilisateurs de manière personnalisée vers des objets intéressants dans un large espace d'options possibles. La nécessité de recommandations augmente sur les industries culturelles ou du divertissement et des médias, où le nombre de produits ne cesse d'augmenter. Les plateformes culturelles et médiatiques et les marchés numériques bénéficient grandement de la mise en oeuvre, de la maintenance et de l'amélioration de leur système de recommandation. Le processus sur la façon dont ils récupèrent les produits culturels comme la musique, les livres, les films, les actualités et permettent un accès facile aux utilisateurs peut avoir un impact structurel sur le fonctionnement des marchés parallèlement à l'évolution des tendances de consommation. La perspective de ce projet est de concevoir un système de recommandation complet pour noozy.tv, une nouvelle plateforme de vidéo à la demande dédiée aux téléspectateurs de la région Grand Est en France. L'objectif est de développer un cadre maintenant des méthodologies et des outils de développement de logiciels standard et modernes pour assurer un service transparent, une portée de recherche sur les données réelles et la diversité, l'évaluation et la fourniture d'une plate-forme pour une amélioration supplémentaire du système.

BACKGROUND: Sleep apnoea is a diagnosed condition in which appurtenances interrupt breathing whilst sleeping. The consequence of obstructive sleep apnoea (OSA) includes road traffic accidents due to drowsiness, systemic hypertension, heart disease, diabetes mellitus and neurocognitive disorders. This condition extends the duration of recovery phase after traumatic brain injury. OBJECTIVE: This study was intended to assess the knowledge and attitude towards OSA and compare it among dental and medical undergraduate students of University Sains Malaysia (USM). METHODS: In this study, a total of 216 clinical undergraduate students (36 from each year; 108 from medical and 108 from dental school) of University Sains Malaysia (USM) Health campus were recruited for the study by non-probability stratified random sampling method. Total study period was October 2017 to October 2018. A self-administered questionnaire was used to assess the sociodemographic status and OSAKA questionnaire was used to assess knowledge and attitude regarding sleep apnoea of the respondents. Descriptive analysis was carried out to assess the knowledge and attitude of OSA amongst dental and medical undergraduate students of USM. The Mann–Whitney U test was carried out to compare the knowledge and attitude of OSA amongst dental and medical undergraduate students of USM. RESULTS: Our study findings revealed that 0.9 %and 6.5 %of the dental undergraduate students and medical undergraduate students could answer all the questions correctly regarding knowledge of OSA. Based on the assessment of the difference between medical and dental students in terms of knowledge towards OSA patients, significant difference was observed at the significance level of 95%, where p

Palatal defects are rehabilitated by fabricating maxillofacial prostheses called obturators. The treatment incorporates taking deviously unpredictable impressions to facsimile the palatal defects into plaster casts for obturator fabrication in the dental laboratory. The casts are then digitally stored using expensive hardware to prevent physical damage or data loss and, when required, future obturators are digitally designed, and 3D printed. Our objective was to construct and validate an economic in-house smartphone-integrated stereophotogrammetry (SPINS) 3D scanner and to evaluate its accuracy in designing prosthetics using open source/free (OS/F) digital pipeline. Palatal defect models were scanned using SPINS and its accuracy was compared against the standard laser scanner for virtual area and volumetric parameters. SPINS derived 3D models were then used to design obturators by using (OS/F) software. The resultant obturators were virtually compared against standard medical software designs. There were no significant differences in any of the virtual parameters when evaluating the accuracy of both SPINS, as well as OS/F derived obturators. However, limitations in the design process resulted in minimal dissimilarities. With further improvements, SPINS based prosthetic rehabilitation could create a viable, low cost method for rural and developing health services to embrace maxillofacial record keeping and digitised prosthetic rehabilitation.

Objective: To determine the association of socio-demographic and clinic-pathological risk factors with oral cancer in Kelantan, Malaysia . Material and Methods: A 19-year cross-sectional survey was performed in Hospital Universiti Sains Malaysia (HUSM), Malaysia. Medical record of 301 oral cancer patients was retrieved from the Medical Records office. Results: The majority of the oral cancer cases were male (62.8%), non-smokers (57.5%), non-alcohol consumers (83.4%), non-betel quid chewers (96.7%), and belonged to Malay ethnicity (68.8%). At the time of diagnosis, most of the patients were at stage II (38.9%). Approximately one-third (30.6%) of the total OC patients experienced loco-regional/distant metastasis, whereas no metastasis was detected in around two-thirds of cases (69.4%). A combination of surgery and radiotherapy was the most commonly employed treatment modality (27.2%). At the time of this study, the survival status of most of the patients was alive (69.1%). The most frequently encountered oral cancer in the Kelantanese population was oral squamous cell carcinoma (70.1%), with the tongue being the most frequently involved oral cavity site (35.5%) . Conclusion: More than three-fourths of the cases were alive at follow-up, which included the cases that did not undergo any form of treatment.

In this essay, I reflect on the position of a postcolonized historian traversing space and time, thinking and linking to histories of European arrivals to Mexico and India. The essay is concerned with early seventeenth-century histories by Chimalpahin and Firishta, who documented their worlds before and after the arrival of Europeans. I argue for a transregional decolonial approach to thinking about historical violence and the formation of disciplinary histories.

Objective: To determine the association of socio-demographic and clinic-pathological risk factors with oral cancer in Kelantan, Malaysia. Material and Methods: A 19-year cross-sectional survey was performed in Hospital Universiti Sains Malaysia (HUSM), Malaysia. Medical record of 301 oral cancer patients was retrieved from the Medical Records office. Results: The majority of the oral cancer cases were male (62.8%), non-smokers (57.5%), non-alcohol consumers (83.4%), non-betel quid chewers (96.7%), and belonged to Malay ethnicity (68.8%). At the time of diagnosis, most of the patients were at stage II (38.9%). Approximately one-third (30.6%) of the total OC patients experienced loco-regional/distant metastasis, whereas no metastasis was detected in around two-thirds of cases (69.4%). A combination of surgery and radiotherapy was the most commonly employed treatment modality (27.2%). At the time of this study, the survival status of most of the patients was alive (69.1%). The most frequently encountered oral cancer in the Kelantanese population was oral squamous cell carcinoma (70.1%), with the tongue being the most frequently involved oral cavity site (35.5%). Conclusion: More than three-fourths of the cases were alive at follow-up, which included the cases that did not undergo any form of treatment.

Background: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. Objective : To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers. Design: This was an individual participant data meta-analysis of cohort studies. Setting: Source data from secondary and tertiary care. Predictors: We identified predictors from systematic reviews, and prioritised for importance in an international survey. Primary outcomes Early-onset (delivery at = 34 weeks' gestation) and any-onset pre-eclampsia. Analysis: We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration. We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C-statistics of >= 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using l(2) and tau(2). A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals. Result The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. Twenty-four of the 131 published prediction models could be validated in 11 UK cohorts. Summary C-statistics were between 0.6 and 0.7 for most models, and calibration was generally poor owing to large between-study heterogeneity, suggesting model overfitting. The clinical utility of the models varied between showing net harm to showing minimal or no net benefit. The average discrimination for IPPIC models ranged between 0.68 and 0.83. This was highest for the second-trimester clinical characteristics and biochemical markers model to predict early-onset pre-eclampsia, and lowest for the first-trimester clinical characteristics models to predict any pre-eclampsia. Calibration performance was heterogeneous across studies. Net benefit was observed for International Prediction of Pregnancy Complications first and second-trimester clinical characteristics and clinical characteristics and biochemical markers models predicting any pre-eclampsia, when validated in singleton nulliparous women managed in the UK NHS. History of hypertension, parity, smoking, mode of conception, placental growth factor and uterine artery pulsatility index had the strongest unadjusted associations with pre-eclampsia. Limitations: Variations in study population characteristics, type of predictors reported, too few events in some validation cohorts and the type of measurements contributed to heterogeneity in performance of the International Prediction of Pregnancy Complications models. Some published models were not validated because model predictors were unavailable in the individual participant data. Conclusion: For models that could be validated, predictive performance was generally poor across data sets. Although the International Prediction of Pregnancy Complications models show good predictive performance on average, and in the singleton nulliparous population, heterogeneity in calibration performance is likely across settings. Future work: Recalibration of model parameters within populations may improve calibration performance. Additional strong predictors need to be identified to improve model performance and consistency. Validation, including examination of calibration heterogeneity, is required for the models we could not validate.

BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. METHODS: IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. RESULTS: Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. CONCLUSIONS: The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice. TRIAL REGISTRATION: PROSPERO ID: CRD42015029349 .

More than 15,000 prescriptions and over the counter drugs are available according to the US Food and Drug Administration website. Moreover, several herbal medicines and dietary supplements are readily available to add to the list of possible drugs, which can potentially cause adverse drug interactions. These are a pressing concern for all as they can interfere with many dental procedures. Additionally, the number of geriatric patients seen in routine dental practice has increased over time. This implies that there are more patients with multiple diseases and health conditions like hypertension, diabetes, problems associated with the cardiovascular, renal and gastrointestinal systems, arthritis, osteoporosis, etc. All these require patients to be on certain medications. Furthermore, advancement in the dental field has led to more complex dental procedures (implants, grafts) being carried out in a general dental practice. These advanced and slightly more invasive treatments require the use of certain drugs before, during and after the treatment like local anesthetics, vasoconstrictors, anxiolytics, analgesics and antibiotics. All of these can possibly interact with medications a patient is already taking and can also interfere with the current dental treatment and create complications. This article aims to provide necessary information about commonly encountered systemic diseases and associated treating medications, their mechanism of action, possible complications and their management. The classes of drugs discussed include anti-platelet agents, vitamin K antagonists, novel oral anticoagulants, bisphosphonates, disease-modifying anti-rheumatic drugs and oral contraceptives.

Objective: Women with pre-eclampsia have elevated circulating levels of soluble fms-like tyrosine kinase-1 (sFlt-1). Statins can reduce sFlt-1 from cultured cells and improve pregnancy outcome in animals with a pre-eclampsia-like syndrome. We investigated the effect of pravastatin on plasma sFlt-1 levels during pre-eclampsia. Design: Blinded (clinician and participant), proof of principle, placebo-controlled trial. Setting: Fifteen UK maternity units. Population: We used a minimisation algorithm to assign 62 women with early-onset pre-eclampsia (24 +0–31 +6 weeks of gestation) to receive pravastatin 40 mg daily (n = 30) or matched placebo (n = 32), from randomisation to childbirth. Primary outcome: Difference in mean plasma sFlt-1 levels over the first 3 days following randomisation. Results: The difference in the mean maternal plasma sFlt-1 levels over the first 3 days after randomisation between the pravastatin (n = 27) and placebo (n = 29) groups was 292 pg/ml (95% CI −1175 to 592; P = 0.5), and over days 1–14 was 48 pg/ml (95% CI −1009 to 913; P = 0.9). Women who received pravastatin had a similar length of pregnancy following randomisation compared with those who received placebo (hazard ratio 0.84; 95% CI 0.50–1.40; P = 0.6). The median time from randomisation to childbirth was 9 days [interquartile range (IQR) 5–14 days] for the pravastatin group and 7 days (IQR 4–11 days) for the placebo group. There were three perinatal deaths in the placebo-treated group and no deaths or serious adverse events attributable to pravastatin. Conclusions: We found no evidence that pravastatin lowered maternal plasma sFlt-1 levels once early-onset pre-eclampsia had developed. Pravastatin appears to have no adverse perinatal effects. Tweetable abstract: Pravastatin does not improve maternal plasma sFlt-1 or placental growth factor levels following a diagnosis of early preterm pre-eclampsia #clinicaltrial finds.

Objective A systematic search was performed for the identification and analysis of the 100 most often cited articles on dental caries and to highlight the changing trends in the field of dentistry over time. Materials and Methods The search was performed without any restriction on the study design, publication year, or language using the Web of Science (WoS) group of Clarivate Analytics enabling the search through “All Databases.” Based on the citation count as available in WoS, the articles were sorted in a descending manner. Information regarding each article was then extracted, which included its authorship, counts of citation (in other databases), citation density, current citation index (2019), publication year, country of publication, journal of article, evidence level based on study design, and keywords description. Results The count of citation for each article varied in each database, that is, 175 to 2,003 in WoS, 89 to 1,981 in Scopus, and 126 to 3,492 when searched in Google Scholar. The highest number of articles (n = 10) related to dental caries were published in 2004. A total of 301 authors made valuable contributions to this field, out of which J.D. Featherstone had coauthored 6 articles. A significant negative correlation (p < 0.01) was found between the age of the article and the citation density (r =–0.545). However, a nonsignificant correlation (p = 0.952) occurred between the age of publication and the citation count (r = 0.006). Conclusion The results of this systematic review provide a critical appraisal of the context underpinning scientific developments in the field of dental caries and also highlighted trends in clinical management and research.

Additional file 1: Supplementary methods: Additional details for handling missing data and evaluating predictive performance of models. Table S1: Search strategy for pre-eclampsia prediction models. Table S2: Predictors evaluated in the models externally validated in the IPPIC-UK cohorts. Table S3: Prediction models and equations identified from the literature search. Table S4: Study level characteristics of IPPIC-UK cohorts. Table S5: Patient characteristics of IPPIC-UK cohorts. Table S6: Number and proportion missing for each predictor in each cohort used for external validation. Table S7: Risk of bias assessment of the IPPIC-UK cohorts using the PROBAST tool. Table S8: Summary of linear predictor values and predicted probabilities for each model in each cohort. Table S9: Predictive performance statistics for models in the individual IPPIC-UK cohorts. Table S10: Predictive performance statistics for models in nulliparous women in all cohorts and in the POP cohort. Fig. S1: Decision curves for early pre-eclampsia models in SCOPE, UPBEAT and POP. Fig. S2: Decision curves for late pre-eclampsia models in SCOPE, Allen 2017, UPBEAT and POP.

This chapter makes two broad claims. The first is to incorporate a longer history of statecraft in north India into our examination of Mughal regime. The second is to take medieval Indian Ocean texts as critical source material for understanding forms of state-making, negotiation of difference, and encounters between social actors. Toward these claims, the chapter reads a set of ninth- and tenth-century narratives linking Sindh and Gujarat to Aden and Cairo. Within these texts are representations of various forms of encounters between those understood as Arabs and Muslims and those labeled Hindi or Sindhi. The chapter explicates accounts of embeddedness of Islam in India, of crime and punishment as modes of statecraft, of everyday gendered lives, and of networks of exchange in order to provide a longer history of understanding pivotal concerns of the Mughal regime in the sixteenth century.

International audience; Human Action Recognition is one of the key tasks in video understanding. Deep Convolutional Neural Networks (CNN) are often used for this purpose. Although they usually perform impressively, their decision interpretation remains challenging. We propose a novel visual CNN features understanding technique. Its objective is to find salient features that played a key role in decision making of the network. The technique only uses the features from the last convolutional layer before the fully connected layers of a trained model and builds an importance map of features. The map is propagated to the original frame thus highlighting the regions in them that contribute to the final decision. The method is fast as it does not require gradient computation as many state-of-the-art methods do. Proposed technique is applied to the Twin Spatio-Temporal 3D Convolutional Neural Network (TSTCNN), designed for Table Tennis Actions recognition. Features visualization is performed at the RGB and Optical flow branches of the network. Obtained results are compared to other visualization techniques both in terms of human understanding and similarity metrics. The metrics show that generated maps are similar to those obtained with known Grad-CAM method, e.g. Pearson Correlation Coefficient between the maps generated of RGB data for Grad-CAM and our method is 0.7 ± 0.05 and 0.72 ± 0.06 on Optical Flow data.

Autism is a severe disorder affecting 1 in 160 children globally. Autism comprises of several development disabilities such as social, communicational and behavioural challenges. Children being diagnosed by the autism mainly face a hard time studying curriculum in inclusive classrooms based on their IQ level and the autism levels. Although, different strategies and learning teaching tools are available to support autistic children, only few systems aid them in learning efficiently, and are not highly interactive. Thus, the proposed Intelligent Education System primarily focuses on providing interactive learning experience to the autistic children with IQ level >50% and efficient teaching assistance to their tutors using augmented reality and machine learning in both English and Arabic The capability of the education system to perform an action, allows the autistic child to interact with the playable sand and gain interest. In learning stage, once the child scribbles on the sandbox, Kinect 3D camera captures and recognizes the drawn image. After the refinement and recognition of the image using OpenCV and classification model, the stored set of real world object are projected on the canvas. Besides, a webcam captures the facial expression of the child, and emotion detection algorithm determines the reaction of the child. Based on the child’s emotion, the current object is projected and pronounced three times to enforce better learning. Once the instructor chooses the language and character to be taught using the developed mobile application, the system displays it over the sandbox and further three objects that starts with the particular character are pronounced and projected. The system is tested rigorously with large set of users, and the results prove the efficiency of the system and happiness of the autistic children in better learning.

An essay on the process of Islamophobic response to COVID-19 in India. I draw upon a longer history of minoritizations, such as in Europe and in US to draw parallels to how Hindutva structures Muslim presences in 2020 India

A brief discussion of Area studies within European contexts

Objective. The aim of this systematic review was to evaluate the effectiveness of laser application in temporomandibular joint disorder. Methods. PubMed, SCOPUS, Science Direct, Web of Science, and Google Scholar electronic databases were searched systematically with restricting the languages to only English and year (January 2001 to March 2020), and studies were selected based on the inclusion criteria. Study quality and publication bias were assessed by using the Robvis, a software package of R statistical software. Results. This systematic review included 32 studies (1172 patients) based on the inclusion and exclusion criteria. Most of the studies reported significant reduction of pain by the use of the laser during TMD treatment. Two-thirds of the study (78.13%) found a better outcome comparing with conventional one. According to Robvis, 84.4% of the studies were high methodological studies with low risk of bias. Conclusion. TMD patients suffer with continuous pain for long time even after conventional treatment. Laser therapy shows a promising outcome of pain reduction for TMD patients. Therefore, laser therapy can be recommended for the TMD patients’ better outcome. This trial is registered with PROSPERO (CRD42020177562).