The Predominantly Inattentive (PI) and Combined (CB) subtypes of AD/HD differ in cognitive tempo, age of onset, gender ratio, and comorbidity, yet a differentiating endophenotype has not been identified. The aim of this study was to test rigorously diagnosed PI, CB, and typical children on measures selected for their potential to reveal hypothesized differences between the subtypes in specific neurocognitive systems (anterior vs. posterior attentional systems) and processes (arousal vs. activation). Thirty-four CB and 26 PI children meeting full DSM-IV criteria for subtype both in school and at home, without confounding reading disability or emotional disorder, were enrolled along with 20 typically developing children. Neurocognitive functions measured included attention, inhibitory control, working memory, learning, and executive functions. Tasks included the Stroop, Wisconsin Card Sorting Test, Continuous Performance Test (CPT). Buschke Selective Reminding Test, ad the Tower of London (TOL), as well as instruments developed by Posner and Sternberg, and tasks assessing the impact on reaction time of [corrected] varying preparatory intervals and stimulus/response complexity. After co-varying for IQ, subtypes differed primarily on measures of impulsivity during tests of vigilance (CPT) and executive function (TOL), with the CB group showing greater impulsivity than both other groups. In addition, the PI group showed worse performance than CB and control groups on the WISC-III Processing Speed Index. Whether analyzed with or without an IQ co-variate, there was no support in the data for hypothesized differences between subtypes in functioning of the anterior vs. posterior attentional systems, nor in involvement of arousal vs. activation processes. The results indicate that the PI and CB subtypes are best differentiated by ratings, observations and tests of cognitive tempo and behavioral impulsivity. Neuropsychological methods have yet to identify critical neuropsychological [corrected] substrates of these differences.

In the above-mentioned article there is an apostrophe in the middle of Sabrina's name that should not be there. Her name should read as follows: Sabrina Pope-Boyd. In addition to the above, the following two errors occurred in the abstract: (1) Top second column-should read: "and tasks assessing the impact on reaction time OF varying... ("OF " was omitted)" (2) Last line of abstract-"neurological" should be replaced by "neuropsychological".

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Integrating the internet of things (IoT) and healthcare monitoring systems is one of the most dynamic innovations in the research area. Since the tremendous number of IoT devices in smart healthcare systems is increasing exponentially, privacy and security issues related to the patient's data are significant concerns. The authors propose an access control for a healthcare monitoring system using blockchain-based smart contracts. They created four smart contract forms for user registration, authentication, access control including misbehavior detection and access revocation. The sensor automatically measures the patient's health data and filters the data before determining whether to write the data into the blockchain or not. The sensor detects abnormal data and alerts doctors and hospitals for immediate treatment. The efficiency of the proposed framework is verified by performance evaluation based on the Ethereum test environment. The proposed system outperforms existing approaches by reducing deployment and execution latency and average response latency in the real-time smart healthcare system.

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Wireless sensor network consumes large number of energy-constrained nodes that are used to monitor the external devices while transferring the information in the sensor networks. At the time of the information transmission process, node contains high energy, and battery of node may be recharged continuously, which leads to reduction of the entire information transmission system performance. This paper introduces the multiple input and multiple output (MIMO) method with energy-efficient protocol for reducing the energy consumption in the network. Initially, the network coverage is determined by applying the shadow fading sensing model, and the clusters are formed with the help of the particle dual clustering process. After the cluster is formed, the information has been transmitted with the help of the energyaware peering routing protocol (EPR), which reduces the network traffic and also improves the energy efficiency with efficient manner. Then, the efficiency of the system is analyzed with the help of experimental results in terms of coverage fraction, accuracy of the cluster, and energy consumption.KEYWORDS multiple input and multiple output (MIMO) method with energy-efficient protocol, particle dual clustering process, shade fading sensing model, the energy-aware peering routing protocol (EPR), wireless sensor network