A Detailed Analysis of Air Pollution Monitoring System and Prediction Using Machine Learning Methods

Predicting air quality is a complex task due to the dynamic nature, volatility, and high variability in the time and space of pollutants and particulates.Due to the presence of governing factors, varying land uses, and many sources for the elaboration of pollution, the forecast and analysis of air pollution is a difficult procedure. At the same time, being able to model, predict, and monitor air quality is becoming more and more relevant, especially in urban areas, due to the observed critical impact of air pollution on citizens’ health and the environment. In this paper, various air pollution monitoring and prediction models with respect to hardware interfacing modules and various classification approaches. The Air Quality Index (AQI) parameter is used in this paper to monitor the quality of air pollution in various regions of the world. The drawbacks of the conventional air pollution monitoring and prediction models have been stated in this paper with the methodologies used for air pollution prediction

A Multi-layer Guidance Approach for Submerged Sensor Networks Integrating Acoustic and Optical Technologies

Over the previous decade, there has been a significant focus on researching underwater acoustic sensor networks (UW-ASNs) for a diverse range of underwater applications, which in turn has facilitated human exploration of the expansive underwater environment. This research introduces an innovative architectural approach that signifies a noteworthy advancement. By combining both acoustic and optical components, it establishes an underwater wireless sensor network. Additionally, the research introduces an innovative multiple levels Q learning-grounded direction-finding procedure, denoted as the proposed system Multi-layer Guidance Approach (MLGA) which is meticulously tailored for such underwater networks. The network\u27s architecture encompasses both physical grouping and logical division into two tiers: the upper tier is overseen by group leaders responsible for managing routing within the lower tier, where group members execute the actual data packet routing. This design capitalizes on the wider viewpoint of upper-tier group leaders and the concurrent learning processes occurring across all groups, resulting in a substantial enhancement in routing efficiency in comparison with traditional methodologies. The empirical results obtained from experimental tests underscore the robustness of the proposed system when confronted with changes in network topology. Moreover, it showcases the system\u27s ability to achieve higher delivery rates and reduced delays in dynamic networks compared to the established approach of flat Q-learning routing. This innovative strategy holds the potential to significantly push the boundaries of underwater sensor networks, surpassing the constraints of conventional communication methods and providing a more effective and dependable means of transmitting data underwater. This advancement not only contributes to the technical aspects but also holds promise for fostering greater exploration and understanding of underwater environments

Peptide-based direct electrochemical detection of receptor binding domains of SARS-CoV-2 spike protein in pristine samples

RNA isolation and amplification-free user-friendly detection of SARS-CoV-2 is the need of hour especially at resource limited settings. Herein, we devised the peptides of human angiotensin converting enzyme-2 (hACE-2) as bioreceptor at electrode interface for selective targeting of receptor binding domains (RBD) of SARS-CoV-2 spike protein (SP). Disposable carbon-screen printed electrode modified with methylene blue (MB) electroadsorbed graphene oxide (GO) has been constructed as cost-efficient and scalable platform for hACE-2 peptide-based SARS-CoV-2 detection. In silico molecular docking of customized 25 mer peptides with RBD of SARS-CoV-2 SP were validated by AutoDock CrankPep. N-terminal region of ACE-2 showed higher binding affinity of − 20.6 kcal/mol with 15 H-bond, 9 of which were < 3 Å. Electrochemical biosensing of different concentrations of SPs were determined by cyclic voltammetry (CV) and chronoamperometry (CA), enabling a limit of detection (LOD) of 0.58 pg/mL and 0.71 pg/mL, respectively. MB-GO devised hACE-2 peptide platform exert an enhanced current sensitivity of 0.0105 mA/pg mL(−1) cm(−2) (R(2) = 0.9792) (CV) and 0.45 nA/pg mL(−1) (R(2) = 0.9570) (CA) against SP in the range of 1 pg/mL to 1 µg/mL. For clinical feasibility, nasopharyngeal and oropharyngeal swab specimens in viral transport medium were directly tested with the prepared peptide biosensor and validated with RT-PCR, promising for point-of-need analysis

Low plasma antioxidant status in patients with epilepsy and the role of antiepileptic drugs on oxidative stress

Background: Oxidative stress has been implicated in various disorders including epilepsy. We studied the antioxidant status in patients with epilepsy and aimed at determining whether there was any difference in the antioxidant levels between patients and controls, patients who are not on antiepileptic drugs (AEDs), and on treatment, between individual AEDs and patients on monotherapy and polytherapy. Materials and Methods: Antioxidant levels like catalase, glutathione peroxidase (GPx), vitamin E, glutathione (GSH), thiol group (SH), uric acid, and total antioxidant capacity (TAC) were compared between 100 patients with epilepsy and equal number of controls. Twenty-five patients who were not on AEDs were compared with patients on AEDs and the control group. Patients were divided into monotherapy and polytherapy group and antioxidant status was compared between the two groups and between individual drugs. Results: Catalase, SH, vitamin E, and TAC were significantly low in patients with epilepsy than those in the control group (P < 0.001). GSH and uric acid did not show any difference; GPx in patients was significantly higher than those in the control group There were no differences in the antioxidant levels between the treated and the untreated groups; however, it was lower in untreated patients than controls (P < 0.001), suggesting that AEDs do not modify the oxidative stress. Patients on Valproate (VPA) showed higher catalase and GPx levels. Catalase was higher in the monotherapy than polytherapy group (P < 0.04). Conclusion: Our study found significantly low levels of antioxidant in patients as compared to controls. AED did not influence the antioxidant status suggesting that seizures induce oxidative stress

Three different surgical techniques of crown lengthening: A comparative study

Introduction: A short clinical crown may lead to poor retention form thereby leading to improper tooth preparation. Surgical crown lengthening procedure is done to increase the clinical crown length without violating the biologic width. Several techniques have been proposed for clinical crown lengthening which includes gingivectomy, apically displaced flap with or without resective osseous surgery, and surgical extrusion using periotome. Objective: The aim of this paper is to compare clinically the three different surgical techniques of crown lengthening procedures. Materials and Methods: Fifteen patients who reported to the department of Periodontology, were included in the study. Patients were randomly divided into three groups, which include patients who underwent gingivectomy (Group A), apically repositioned flap (Group B) and surgical extrusion using periotome (Group C). Clinical measurements such as clinical crown length, gingival zenith, interdental papilla height were taken at baseline and at 3 rd month post-operatively. Results: Clinical and radiographic evaluation at 3 rd month suggest that surgical extrusion technique offers several advantages over the other conventional surgical techniques such as preservation of the interproximal papilla, gingival margin position and no marginal bone loss. Conclusions: This technique can be used to successfully treat a grossly damaged crown structure as a result of tooth fracture, dental caries and iatrogenic factors especially in the anterior region, where esthetics is of great concern

Plasma performance in JET Achievements and projections

Paper at 15. European Conf. on Controlled Fusion and Plasma Heating Dubrovnik (YU) 16-20 May 1988Available from British Library Document Supply Centre- DSC:4672.262(JET-P--(88)26) / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

OmpSs-OpenCL programming model for heterogeneous systems

The advent of heterogeneous computing has forced programmers to use platform specific programming paradigms in order to achieve maximum performance. This approach has a steep learning curve for programmers and also has detrimental influence on productivity and code re-usability. To help with this situation, OpenCL an open-source, parallel computing API for cross platform computations was conceived. OpenCL provides a homogeneous view of the computational resources (CPU and GPU) thereby enabling software portability across different platforms. Although OpenCL resolves software portability issues, the programming paradigm presents low programmability and additionally falls short in performance. In this paper we focus on integrating OpenCL framework with the OmpSs task based programming model using Nanos run time infrastructure to address these shortcomings. This would enable the programmer to skip cumbersome OpenCL constructs including OpenCL plaform creation, compilation, kernel building, kernel argument setting and memory transfers, instead write a sequential program with annotated pragmas. Our proposal mainly focuses on how to exploit the best of the underlying hardware platform with greater ease in programming and to gain significant performance using the data parallelism offered by the OpenCL run time for GPUs and multicore architectures. We have evaluated the platform with important benchmarks and have noticed substantial ease in programming with comparable performance.Postprint (published version

Bioadhesive Gauze Embedded with Chitosan-Butein Bioconjugate: A Redox-Active pH Sensor Platform

With the ever-growing global wound care market, demand for robust redox-active healthcare material is obvious for the construction of wearable sensor platforms. Surface reactive functional group-rich material like chitosan holds huge potential for electrochemical biosensor application. Herein, a metal-free redox-active chitosan–butein (CSB) bioconjugate is processed into epidermal bioadhesive electrode material useful for pH sensors promising toward wound site analysis. A two-electrode system devised for conducting carbon-reinforced silver chloride paste and CSB-modified carbon/silver chloride matrix was used as a reference and working electrodes, respectively. Dimensions of working and reference electrodes (4 mm) were designed by 2D cutter plotter-assisted stenciling. The cross-sectional topology of the constructed adhesive CSB-sensor platform exhibits an average surface thickness of 183 ± 2 μm. Cyclic voltammetric analysis revealed the inherent 2e−/2H+ transfer attributed to the catechol OH groups of graft polymerized CSB modified on adhesive gauze. As-fabricated modified electrode substrates exhibit distinguishable potential differences with respect to electrolytes of varied pH (between 5 to 9), promising for wound site analysis

OmpSs-OpenCL programming model for heterogeneous systems

The advent of heterogeneous computing has forced programmers to use platform specific programming paradigms in order to achieve maximum performance. This approach has a steep learning curve for programmers and also has detrimental influence on productivity and code re-usability. To help with this situation, OpenCL an open-source, parallel computing API for cross platform computations was conceived. OpenCL provides a homogeneous view of the computational resources (CPU and GPU) thereby enabling software portability across different platforms. Although OpenCL resolves software portability issues, the programming paradigm presents low programmability and additionally falls short in performance. In this paper we focus on integrating OpenCL framework with the OmpSs task based programming model using Nanos run time infrastructure to address these shortcomings. This would enable the programmer to skip cumbersome OpenCL constructs including OpenCL plaform creation, compilation, kernel building, kernel argument setting and memory transfers, instead write a sequential program with annotated pragmas. Our proposal mainly focuses on how to exploit the best of the underlying hardware platform with greater ease in programming and to gain significant performance using the data parallelism offered by the OpenCL run time for GPUs and multicore architectures. We have evaluated the platform with important benchmarks and have noticed substantial ease in programming with comparable performance

Scalability and parallel execution of OmpSs-OpenCL tasks on heterogeneous CPU-GPU environment

With heterogeneous computing becoming mainstream, researchers and software vendors have been trying to exploit the best of the underlying architectures like GPUs or CPUs to enhance performance. Parallel programming models play a crucial role in achieving this enhancement. One such model is OpenCL, a parallel computing API for cross platform computations targeting heterogeneous architectures. However, OpenCL is a low-level programming language, therefore it can be time consuming to directly develop OpenCL code. To address this shortcoming, OpenCL has been integrated with OmpSs, a task-based programming model to provide abstraction to the user thereby reducing programmer effort. OmpSs-OpenCL programming model deals with a single OpenCL device either a CPU or a GPU. In this paper, we upgrade OmpSs-OpenCL programming model by supporting parallel execution of tasks across multiple CPU-GPU heterogeneous platforms. We discuss the design of the programming model along with its asynchronous runtime system. We investigated scalability of four OmpSs-OpenCL benchmarks across 4 GPUs gaining speedup of up to 4x. Further, in order to achieve effective utilization of the computing resources, we present static and work-stealing scheduling techniques. We show results of parallel execution of applications using OmpSs-OpenCL model and use heterogeneous workloads to evaluate our scheduling techniques on a heterogeneous CPU-GPU platform.We thankfully acknowledge the support of the European Commission through the TERAFLUX project (FP7-249013) and the HiPEAC-2 Network of Excellence (FP7/ICT 217068),the support of the Spanish Ministry of Education (TIN-2007-60625, TIN-2012-34557, CSD2007-00050 and FI program) and the Generalitat de Catalunya (2009-SGR-980)Peer Reviewe