Scheduling access to shared space in multi-robot systems

Through this study, we introduce the idea of applying scheduling techniques to allocate spatial resources that are shared among multiple robots moving in a static environment and having temporal constraints on the arrival time to destinations. To illustrate this idea, we present an exemplified algorithm that plans and assigns a motion path to each robot. The considered problem is particularly challenging because: (i) the robots share the same environment and thus the planner must take into account overlapping paths which cannot happen at the same time; (ii) there are time deadlines thus the planner must deal with temporal constraints; (iii) new requests arrive without a priori knowledge thus the planner must be able to add new paths online and adjust old plans; (iv) the robot motion is subject to noise thus the planner must be reactive to adapt to online changes. We showcase the functioning of the proposed algorithm through a set of agent-based simulations

Do diagnostic delays in cancer matter?

background: The United Kingdom has poorer cancer outcomes than many other countries due partly to delays in diagnosing symptomatic cancer, leading to more advanced stage at diagnosis. Delays can occur at the level of patients, primary care, systems and secondary care. There is considerable potential for interventions to minimise delays and lead to earlier-stage diagnosis. methods: Scoping review of the published studies, with a focus on methodological issues. results: Trial data in this area are lacking and observational studies often show no association or negative ones. This review offers methodological explanations for these counter-intuitive findings. conclusion: While diagnostic delays do matter, their importance is uncertain and must be determined through more sophisticated methods

Role of anatomical sites and correlated risk factors on the survival of orthodontic miniscrew implants:a systematic review and meta-analysis

Abstract Objectives The aim of this review was to systematically evaluate the failure rates of miniscrews related to their specific insertion site and explore the insertion site dependent risk factors contributing to their failure. Search methods An electronic search was conducted in the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Knowledge, Scopus, MEDLINE and PubMed up to October 2017. A comprehensive manual search was also performed. Eligibility criteria Randomised clinical trials and prospective non-randomised studies, reporting a minimum of 20 inserted miniscrews in a specific insertion site and reporting the miniscrews’ failure rate in that insertion site, were included. Data collection and analysis Study selection, data extraction and quality assessment were performed independently by two reviewers. Studies were sub-grouped according to the insertion site, and the failure rates for every individual insertion site were analysed using a random-effects model with corresponding 95% confidence interval. Sensitivity analyses were performed in order to test the robustness of the reported results. Results Overall, 61 studies were included in the quantitative synthesis. Palatal sites had failure rates of 1.3% (95% CI 0.3–6), 4.8% (95% CI 1.6–13.4) and 5.5% (95% CI 2.8–10.7) for the midpalatal, paramedian and parapalatal insertion sites, respectively. The failure rates for the maxillary buccal sites were 9.2% (95% CI 7.4–11.4), 9.7% (95% CI 5.1–17.6) and 16.4% (95% CI 4.9–42.5) for the interradicular miniscrews inserted between maxillary first molars and second premolars and between maxillary canines and lateral incisors, and those inserted in the zygomatic buttress respectively. The failure rates for the mandibular buccal insertion sites were 13.5% (95% CI 7.3–23.6) and 9.9% (95% CI 4.9–19.1) for the interradicular miniscrews inserted between mandibular first molars and second premolars and between mandibular canines and first premolars, respectively. The risk of failure increased when the miniscrews contacted the roots, with a risk ratio of 8.7 (95% CI 5.1–14.7). Conclusions Orthodontic miniscrew implants provide acceptable success rates that vary among the explored insertion sites. Very low to low quality of evidence suggests that miniscrews inserted in midpalatal locations have a failure rate of 1.3% and those inserted in the zygomatic buttress have a failure rate of 16.4%. Moderate quality of evidence indicates that root contact significantly contributes to the failure of interradicular miniscrews placed between the first molars and second premolars. Results should be interpreted with caution due to methodological drawbacks in some of the included studies

Critical Role of NADPH Oxidase in Neuronal Oxidative Damage and Microglia Activation following Traumatic Brain Injury

BACKGROUND: Oxidative stress is known to play an important role in the pathology of traumatic brain injury. Mitochondria are thought to be the major source of the damaging reactive oxygen species (ROS) following TBI. However, recent work has revealed that the membrane, via the enzyme NADPH oxidase can also generate the superoxide radical (O(2)(-)), and thereby potentially contribute to the oxidative stress following TBI. The current study thus addressed the potential role of NADPH oxidase in TBI. METHODOLOGY/PRINCIPAL FINDINGS: The results revealed that NADPH oxidase activity in the cerebral cortex and hippocampal CA1 region increases rapidly following controlled cortical impact in male mice, with an early peak at 1 h, followed by a secondary peak from 24-96 h after TBI. In situ localization using oxidized hydroethidine and the neuronal marker, NeuN, revealed that the O(2)(-) induction occurred in neurons at 1 h after TBI. Pre- or post-treatment with the NADPH oxidase inhibitor, apocynin markedly inhibited microglial activation and oxidative stress damage. Apocynin also attenuated TBI-induction of the Alzheimer's disease proteins β-amyloid and amyloid precursor protein. Finally, both pre- and post-treatment of apocynin was also shown to induce significant neuroprotection against TBI. In addition, a NOX2-specific inhibitor, gp91ds-tat was also shown to exert neuroprotection against TBI. CONCLUSIONS/SIGNIFICANCE: As a whole, the study demonstrates that NADPH oxidase activity and superoxide production exhibit a biphasic elevation in the hippocampus and cortex following TBI, which contributes significantly to the pathology of TBI via mediation of oxidative stress damage, microglial activation, and AD protein induction in the brain following TBI

Nutraceutical agents with anti-inflammatory properties prevent dietary saturated-fat induced disturbances in blood-brain barrier function in wild-type mice

Background: Emerging evidence suggests that disturbances in the blood–brain barrier (BBB) may be pivotal to the pathogenesis and pathology of vascular-based neurodegenerative disorders. Studies suggest that heightened systemic and central inflammations are associated with BBB dysfunction. This study investigated the effect of the anti-inflammatory nutraceuticals garlic extract-aged (GEA), alpha lipoic acid (ALA), niacin, and nicotinamide (NA) in a murine dietary-induced model of BBB dysfunction. Methods: C57BL/6 mice were fed a diet enriched in saturated fatty acids (SFA, 40% fat of total energy) for nine months to induce systemic inflammation and BBB disturbances. Nutraceutical treatment groups included the provision of either GEA, ALA, niacin or NA in the positive control SFA-group and in low-fat fed controls. Brain parenchymal extravasation of plasma derived immunoglobulin G (IgG) and large macromolecules (apolipoprotein (apo) B lipoproteins) measured by quantitative immunofluorescent microscopy, were used as markers of disturbed BBB integrity. Parenchymal glial fibrillar acidic protein (GFAP) and cyclooxygenase-2 (COX-2) were considered in the context of surrogate markers of neurovascular inflammation and oxidative stress. Total anti-oxidant status and glutathione reductase activity were determined in plasma.Results: Brain parenchymal abundance of IgG and apoB lipoproteins was markedly exaggerated in mice maintained on the SFA diet concomitant with significantly increased GFAP and COX-2, and reduced systemic antioxidative status. The nutraceutical GEA, ALA, niacin, and NA completely prevented the SFA-induced disturbances of BBB and normalized the measures of neurovascular inflammation and oxidative stress. Conclusions: The anti-inflammatory nutraceutical agents GEA, ALA, niacin, or NA are potent inhibitors of dietary fat-induced disturbances of BBB induced by systemic inflammations

Deep Learning-Based Mobile Application Design for Smart Parking

In the era of Internet of Things (IoT) and smart city ecosystems, there is a need for innovative smart parking systems for more sustainable cities. With the increasing number of vehicles in the cities every year, it takes more time to find parking spaces. The solution methods developed are no longer sufficient. The time that passes while waiting for a parking space in traffic carries with it problems such as energy, environmental pollution and stress. In this study, a deep learning and cloud-based new mobile smart parking application was developed to minimize the problem of searching for parking spaces. Within the application, a service has been developed based on deep learning with Long short-term memory (LSTM) to predict the parking space. Here, dynamic access is provided to the LSTM-based model previously created through the mobile device of the user, and the process of displaying the occupancy rates of the parks at the desired place is accomplished on the mobile device by entering the relevant parameters. By this means, both energy and time savings have been achieved. With the real-time car parking data collected in the city of Istanbul in Turkey, high accuracy results were obtained. In order to demonstrate the effectiveness of the model proposed, it was compared with the Support Vector Machine, Random Forest and ARIMA methods. The results have confirmed the high accuracy and reliability that was promised.WOS:0006450716000012-s2.0-8510459240

Design and Implementation of a Prediction Approach Using Big Data and Deep Learning Techniques for Parking Occupancy

With the developing world, cities have begun to become smarter. Smart parking systems, with the ever-increasing number of vehicles, are among the important matters in smart cities. The reason for this is that the search for parking spaces that are already insufficient, brings along a serious cost, air pollution and stress issues. In this study, a new approach that attempts to forecast the parking lot occupancy rate in the short- and medium-term with its deep learning-based Gated Recurrent Units (GRU) model was proposed. Initially, data belonging to 607 carparks located in the city of Istanbul in Turkey, and weather data have been collected, and a multivariate time series data set has been created. In the second stage, to forecast the parking places that would be available in the short- and medium-term, the GRU model was used in the system proposed. To show the effectiveness of the model, the results obtained through the 27 different models were compared by means of the Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM), which were some other sequence models. According to the experimental results made on the weather data obtained from ISPARK dataset and AKOM, the our proposed GRU model achieves 99.11% accuracy gave the best results with 0.90 MAE, 2.35 MSE and 1.53 RMSE metric values. Experimental results obtained with various hyperparameters clearly demonstrate the success of the GRU deep learning model in prediction parking occupancy rates.WOS:0006933475000012-s2.0-8511414647