Edge Computing for Real-Time Inference in Internet of Things Environments: Challenges and Solutions

The role that the real-time inference model plays in the Internet of Things environment and the applications that correspond to it are demonstrated by this project. In order to provide an all-encompassing picture of networking technologies, the section on the literature review has provided a description of the research that came before this project as well as an evaluation of its overall quality. In this section, the methodology component of the evolution of computing techniques in the environment of IOT is also examined. As a result, the technique of edge computing is utilised to produce many answers to the difficulties presented by the Internet of Things environment. In this section, the thematic analysis is carried out by making use of real-time applications and examples that are connected to networking applications. Last but not least, the project session comes to a close with the inclusion of research recommendations for the development of IOT and further work in this research

Optimizing spatial throughput in device-to-device networks

6 pages, 4 figures. SubmittedInternational audienceResults are presented for optimizing device-to-device communications in cellular networks, while maintaining spectral efficiency of the base-station-to-device downlink channel. We build upon established and tested stochastic geometry models of signal-to-interference ratio in wireless networks based on the Poisson point process, which incorporate random propagation effects such as fading and shadowing. A key result is a simple formula, allowing one to optimize the device-to-device spatial throughput by suitably adjusting the proportion of active devices. These results can lead to further investigation as they can be immediately applied to more sophisticated models such as studying multi-tier network models to address coverage in closed access networks

Automated Detection of Ischemic Stroke and Subsequent Patient Triage in Routinely Acquired Head CT

Purpose!#!Advanced machine-learning (ML) techniques can potentially detect the entire spectrum of pathology through deviations from a learned norm. We investigated the utility of a weakly supervised ML tool to detect characteristic findings related to ischemic stroke in head CT and provide subsequent patient triage.!##!Methods!#!Patients having undergone non-enhanced head CT at a tertiary care hospital in April 2020 with either no anomalies, subacute or chronic ischemia, lacunar infarcts of the deep white matter or hyperdense vessel signs were retrospectively analyzed. Anomaly detection was performed using a weakly supervised ML classifier. Findings were displayed on a voxel-level (heatmap) and pooled to an anomaly score. Thresholds for this score classified patients into i) normal, ii) inconclusive, iii) pathological. Expert-validated radiological reports were considered as ground truth. Test assessment was performed with ROC analysis; inconclusive results were pooled to pathological predictions for accuracy measurements.!##!Results!#!During the investigation period 208 patients were referred for head CT of which 111 could be included. Definite ratings into normal/pathological were feasible in 77 (69.4%) patients. Based on anomaly scores, the AUC to differentiate normal from pathological scans was 0.98 (95% CI 0.97-1.00). The sensitivity, specificity, positive and negative predictive values were 100%, 40.6%, 80.6% and 100%, respectively.!##!Conclusion!#!Our study demonstrates the potential of a weakly supervised anomaly-detection tool to detect stroke findings in head CT. Definite classification into normal/pathological was made with high accuracy in > 2/3 of patients. Anomaly heatmaps further provide guidance towards pathologies, also in cases with inconclusive ratings

Poly(vinyl alcohol)-hyaluronic Acid Membranes for Wound Dressing Applications: Synthesis and in vitro Bio-Evaluations

Physically crosslinked poly(vinyl alcohol)-hyaluronic acid (PVA-HA) hydrogel membranes composed of different amounts of HA were prepared by freeze-thawing (F-T) method. F-T cycle was repeated for three consecutive cycles. HA was chosen and routinely utilized in the local treatment of chronic wounds, because of its advantages as, HA is endogenous and biodegradable polymer. Physicochemical properties of PVA-HA membranes such as, gel fraction (GF), swelling, mechanical properties, hydrolytic degradation and in vitro bio-evaluation tests were investigated. Results revealed that introducing HA into PVA structure affected significantly the physicochemical properties of membranes than the pristine PVA, because of its crosslinking interaction with PVA. With the increase of HA content in PVA hydrogel membranes, GF and mechanical stability of PVA-HA membranes decreased. However, the swelling behavior, mechanical flexibility, protein adsorption and hydrolytic degradation of PVA membrane increased. The HA content < 20% in PVA hydrogels showed high cell viability (%) and no toxicity was observed using microculture tetrazolium assay (MTT-assay). However, less cell viability was determined with high HA incorporation. PVA-HA-ampicillin free showed antimicrobial activity against Candida albicans as a result of HA presence. Thus, ampicillin-loaded wound dressing with PVA-HA membranes could be used as promising materials with easy forming and biologically evaluated for wound care

Synthesis, in vitro cytotoxicity activity against the human cervix carcinoma cell line and in silico computational predictions of new 4-arylamino-3-nitrocoumarin analogues

Halawa AH, Eliwa EM, Hassan AA, et al. Synthesis, in vitro cytotoxicity activity against the human cervix carcinoma cell line and in silico computational predictions of new 4-arylamino-3-nitrocoumarin analogues. JOURNAL OF MOLECULAR STRUCTURE. 2020;1200: UNSP 127047.A new series of 4-arylamino-3-nitrocoumarin analogues (4-18) have been synthesized and characterized by sophisticated spectroscopic techniques (H-1 NMR, C-13 NMR) and mass spectrometry. All the new synthesized compounds were evaluated for their in vitro cytotoxic activity against the human cervix carcinoma cell line (KB-3-1) using resazurin assay with (+)-griseofulvin as the positive control (IC50 = 19 mu M). Among them, thiazolidinylidene derivative 17a that bearing malononitrile unit displayed the best cytotoxic potency with IC50 value of 21 mu M. Also, in silico docking simulation studies were conducted on human DNA topoisomerase 1 (Top1) (PDB: 1T8I) to explore and interpret the interaction pattern between the selected compounds and target enzyme as well confirm the acquired cytotoxicity results. In addition to the above, in silico predictions of physicochemical properties, ADME (absorption, distribution, metabolism and excretion) parameters, oral toxicity and indication of toxicity targets were implemented for some title compounds. (C) 2019 Published by Elsevier B.V