Priority Data Research Articles

Involving patients as key stakeholders in the design of cardiovascular implantable electronic device data dashboards: Implications for patient care.

BackgroundData from remote monitoring (RM) of cardiovascular implantable electronic devices (CIEDs) currently are not accessible to patients despite demand. The typical RM report contains multiple pages of data for trained technicians to read and interpret and requires a patient-centered approach to be curated to meet individual user needs.ObjectiveThe purpose of this study was to understand which RM data elements are important to patients and to gain design insights for displaying meaningful data in a digital dashboard.MethodsAdults with implantable cardioverter–defibrillators (ICDs) and pacemakers (PMs) participated in this 2-phase, user-centered design study. Phase 1 included a card-sorting activity to prioritize device data elements. Phase 2 included one-on-one design sessions to gather insights and feedback about a visual display (labels and icons).ResultsTwenty-nine adults (mean age 71.8 ± 11.6 years; 51.7% female; 89.7% white) participated. Priority data elements for both ICD and PM groups in phase 1 (n = 19) were related to cardiac episodes, device activity, and impedance values. Recommended replacement time for battery was high priority for the PM group but not the ICD group. Phase 2 (n = 10) revealed that patients would like descriptive, nontechnical terms to depict the data and icons that are intuitive and informative.ConclusionThis user-centered design study demonstrated that patients with ICDs and PMs were able to prioritize specific data from a comprehensive list of data elements that they had never seen before. This work contributes to the goal of sharing RM data with patients in a way that optimizes the RM feature of CIEDs for improving patient outcomes and clinical care.

Systemic Administrations of Water-Dispersible Single-Walled Carbon Nanotubes: Activation of NOS in Spontaneously Hypertensive Rats

Priority data have been obtained on the effects of repeated systemic administrations of water-dispersible single-walled carbon nanotubes (SWCNTs) to spontaneously hypertensive rats with respect to constitutive NO-synthase (cNOS). As is known, NO is an inhibitory transmitter in the cardiovascular system. It was found that the systemic (i.p., subcutaneous, and i.m.) introductions of SWCNTs during two weeks resulted in considerable elevations of the NO2– level (a marker of NO bioavailability) in the blood of experimental hypertensive animals. Thus, SWCNTs may be used in the future for antihypertensive therapy as a novel agent capable of activating cNOS and, thus, increasing the NO production in central and peripheral elements of the cardiovascular system.

The Evaluation QS-WFQ Scheduling Algorithm For IoT Transmission To Cloud

This study using the Weighted Fair Queue scheduling algorithm when the weights can change and calculated based on changes in the average queue size in the buffer. This algorithm divides the priorities of each sensor into three priorities, namely high, medium and low priority. Each queue is given a weight that is adjusted to the resource requirements of each traffic. High priority data will take precedence, but medium and low priority data will remain underserved and guaranteed by network resources.The results of this study show packet loss ratio when the ratio of the number of buffers and the amount of data is 1: 3 with variations in the number of high, medium and low priority buffers 75: 75: 150 and 50: 50: 200 is 0%. The delay time in the high priority and the medium priority buffer has almost the same delay time when data is transmitted, whereas for the low priority buffer increased in the delay time.

Decision Support System for Multistore Online Sales Based on Priority Rules and Data Mining

The work is focused on the design and implantation of an intelligent multi store E-commerce platform able to manage the orders and the warehouse stock by mean of priority association rules and data mining algorithms. The proposed Decision Support System (DSS) is structured into two main levels: the first one is related to priority rule definition due to the online product requests according with the availability check in different warehouses of stores, and the second one provides important information about sales prediction thus facilitating stock management and consecutively logistic. Specifically, the prototype platform is able to manage the warehouse products of different stores by means a simultaneous comparison of products available in the different stores linked to the platform, and by means of a scalable end-to-end tree boosting system XGBoost algorithm able to predict online sales. The paper has been developed within the framework of an industry project.

PEERP: An Priority-Based Energy-Efficient Routing Protocol for Reliable Data Transmission in Healthcare using the IoT

Abstract The Internet of Things (IoT) connects huge number of devices using the internet to collect data. The IoT has a variety of application domains, including health care. In this scenario, the patients can use wearable or implanted medical sensors for measuring medical parameters anywhere and anytime. The medical sensors are typically equipped with batteries and have limited energy. In order to prolong the network lifetime, a powerful routing protocols are required. In this paper, we propose PEERP: An Priority-based Energy-Efficient Routing Protocol for Reliable Data Transmission in Healthcare using the IoT. We classify health information into two categories assigned corresponding priorities: Emergency Situation and Vital Health Data. The Emergency Situation is the highest priority data and should be successfully delivered as soon as required. The Vital Health data is the data requested by doctors for continuous monitoring of the patients. The direct communication is used for critical data while Multi-hop communication is used for vital health data delivery. The simulation results show that the routing protocol can improve the energy utilization of the sensor nodes and prolong the network lifetime while guaranteeing the delivery ratio and reliability.

Interference Aware Priority Based Packet Forwarding in Wireless Sensor Network using Bluetooth

Wireless Sensor Networks consists of several nodes that are distributed over a particular area. These sensor nodes are able to sense the changes in environmental parameters like temperature and carbon monoxide. Depending upon the ability each sensor node possess the type of wireless sensor networks may vary: that is either Homogeneous or Heterogeneous. This particular paper is concentrated on a homogeneous network. In this paper, an Interference Aware Priority based Packet Forwarding in Wireless Sensor Network using Bluetooth (IAPFB) scheme is proposed which helps in the congestion control in Wireless Sensor Network. The main idea behind this paper is that ; avoid the interference and collision between the nodes in the network while transmitting the data packets and also the higher priority data must forwarded first than a low priority one. The main application of this concept is the Body Sensor Networks. That is the body sensors for grabbing the signals from various body parts is used as the operating network. Signals from different body parts may have different priority levels and the proposed scheme can easily deal with the priorities. Simulated results shows comparatively good results for the proposed method.

QoS-aware traffic scheduling framework in cognitive radio based smart grids using multi-objective optimization of latency and throughput

To meet the diverse QoS requirements of future Smart Grid (SG) communication network, efficient traffic scheduling and optimization techniques to prioritize data from various SG applications are required. Recently, focus has only been on the latency and criticality based priority-aware policies for same channel bandwidth. Traffic scheduling and subsequent channel allocation are required to support both the differential throughput and latency requirements simultaneously for channels having different bandwidths and SNRs. In this paper, a QoS-aware framework for data traffic scheduling in cognitive radio based SG communication network is proposed. The channels available to smart grid Communication Nodes (SCNs) are categorized as low and high bandwidths. For each bandwidth, all SG applications are categorized into several priority-classes comprised of latency and throughput sub-classes. For both channel bandwidths, the scheduler maintains and updates two sets of priority queues based on weights associated with each class and its data type. The complete scheduling framework is formulated as a multi-objective optimization problem. The overall objective function is the weighted sum of individual utility functions of latency and throughput. A novel usage of Adam optimizer is proposed to minimize the latency and maximize the throughput by obtaining optimal system cost, resulting in optimal decision policy. Simulation results show that the proposed algorithm achieves desired QoS requirements in the presence of heavy PU traffic, whereas in case of no priority assignment, QoS requirements of lower priority applications are met by compromising the QoS of higher priority data.

The analysis of supply chain risk logistics in implementation of West Sumatera - Riau toll road development

The aim of this research is to develop a risk mitigation strategy in supply chain process of West Sumatra-Riau toll road pavement material. Data for this study was obtained through brainstorming techniques, questionnaires, field surveys and literature review. The data was analyzed using House of Risk (HOR) method. There were 18 items of risk event’s and 21 items of risk agent’s identified from the HOR phase 1, whereas risk agent handling priority data and risk mitigation actions are 19 items by using HOR phase 2. The results show that there are 2 (two) risk agents ranked 1 and 2 for the most critical, namely A1 (poor supplier performance) with ARP of 860 and A2 (Low of Contractor Capability) with ARP of 507, which can cause ± 80% of risk events where the remaining 20% is caused by other agents. There are 2 (two) mitigation actions were obtained from HOR phase 2, namely PA1 (appropriate supplier selection method) and PA4 (appropriate contractor selection method) which can prevent the emergence of ± 80% of these risk agents and ± 20% is overcome by 17 other mitigation actions.

Alternative Priority-based Queuing for WBAN

Wireless Body Area Network (WBAN) technology enables medical services to expand its scope. It allows medical expert to monitor physiological data of patients using wireless communication. Despite of the numerous advantages it provides, WBAN still incur issues on different metrics on quality of service (QoS) such as end-to-end delay, queuing delay, and reliability. QoS metrics of the WBAN is affected on the efficiency of its queuing system. Previous studies proposed different routing algorithms to address QoS metrics which implement multiple queues to enhance data transmission of different data types. These studies used strict priority logic which serves the highest priority queue first. However, the main problem of this approach is that lower priority data may be totally blocked by a higher priority data. This paper presents an alternative priority-based queuing to address issue on QoS metrics. The results showed that the proposed algorithm decreased the end-to-end delay and queuing delay and increased the reliability of QoS aware routing protocol. Based on the implementation result, it can be seen that the proposed algorithm can be implement on WBAN.

A lifetime enhancement protocol in cluster‐based wireless sensor networks with guaranteed delay

SummaryWireless sensor networks nowadays find application in all the fields of the world. Rare event detection is an important application in which the wireless sensor network is used. In the case of rare event detection, event of interest or the important event occurs very rarely. Battery‐powered sensor nodes are deployed to detect the event and report to the base station. Sensing and communicating the low priority events happen in major portion of the lifetime for the sensor nodes. However, if the event occurs, then it should be detected and communicated at the earliest to the base station or to the sink node. To reduce the network traffic due to low priority data, we propose a cross layered algorithm to improve the lifetime of the sensor nodes in the case of clustered architecture. In spite of the increase in the network lifetime, the time to detect and communicate to the base station is maintained as that of the traditional clustering approach. The proposed algorithm is simulated, and results show significant improvement in the lifetime of the sensor nodes with guaranteed latency. In this paper, we also suggest methods to support the latency to sensor nodes on priority basis for continuous reporting.

Priority Schemes for Life Extension and Data Delivery in Body Area Wireless Sensor Networks with Cognitive Radio Capabilities

Wireless sensor networks have recently been used to monitor bioelectric signals generated by the human body. However, since the dimensions and capabilities of the network nodes are small and limited, a problem is generated inherently by the energy consumption and radioelectric interference. In view of this, we propose two priority schemes to improve the performance of the network. In the first one, we aim at increasing the system lifetime by reducing the number of transmissions of nodes with low energy levels. In the second scheme, we aim at conveying priority data to the sink node as fast and efficient as possible. In the former scheme, users can be monitored for long time periods considering a low data generation. On the other hand, the latter scheme allows expediting transmission of important data when energy efficiency is not relevant. In this article, we mathematically model, analyze, and study the performance of the system for both priority schemes considering cognitive radio capabilities to make efficient use of resources and limit the radioelectric interference when the network transmits both continuous monitoring and event detection information. Numerical results provided in this work allow a careful parameter selection for practical implementation of BANETs.

Improvement strategy of S-MAC protocol for wireless sensors in IoT based on data and energy priorities

ABSTRACTWireless sensors are widely used in the Internet of things. In this paper, the S-MAC protocol is enhanced by extending IEEE802.11 data frame and combining data and energy priority, so as to solve the portability problem of priority data. The improved strategy enables the wireless sensor nodes to transmit data and energy according to the priority and network load in the process of data transmission competition window to reduce unnecessary conflicts. The improved protocol simulation test using NS2 simulation platform shows that the improved S-MAC protocol reduces the data transmission delay of sending different levels of priority information, achieves balanced network load, and prolongs the network life time.

Effect of taste receptor protein T1R3 on the development of islet tissue of the murine pancreas

Protein T1R3, the main subunit of sweet, as well as amino acid, taste receptor, is expressed in the epithelium of the tongue and gastro intestinal tract, in β–cells of the pancreas, hypothalamus, and numerous other organs. Recently, convincing witnesses of T1R3 involvement in control of carbohydrate and lipid metabolism, and control of production of incretines and insulin, have been determined. In the study on Tas1r3-gene knockout mouse strain and parent strain C57Bl/6J as control, priority data concerning the effect of T1R3 on the morphological characteristics of Langerhans islets in the pancreas, are obtained. In Tas1r3 knockout animals, it is found that the size of the islets and their density in pancreatic tissue are reduced, as compared to the parent strain. Additionally, a decrease of expression of active caspase-3 in islets of gene-knockouts is demonstrated. The obtained data show that the lack of a functional, gene encoding sweet-taste receptor protein causes a dystrophy of the islet tissue and associates to the development of pathological changes in the pancreas specific to type-2 diabetes and obesity in humans.

Moving Radiology Workflow to the Electronic Health Record: Quantitative and Qualitative Experience From a Large Academic Medical Center

To objectively and subjectively evaluate a large, academic radiology department's transition to electronic health record (EHR) centered workflow. Multiple metrics were compared from before and after the move to EHR-driven workflow. Examination ordering and reading priority data were obtained for 30 days both before and after the transition. Sixteen radiologists were observed opening a computed tomography (CT) examination, and time to open, mouse clicks, and keystrokes were recorded. Information available to the radiologist during interpretation was also compared. Additionally, a 12 question survey was sent out to the residents and faculty both before and after the transition. Implementation of an eight-level reading priority system increased worklist granularity and improved identification of more urgent studies to read. Radiologists opened CT studies in picture archiving and communications system-driven workflow in 52.4 ± 16.9 seconds using 9.5 ± 3.9 clicks and 6.3 ± 2.9 keystrokes, compared to 17.3 ± 9.5 seconds, 4.8 ± 1.5 clicks, and 0.1 ± 0.3 keystrokes in EHR-driven workflow (p < 0.001 for each measure). More information was available to the radiologist during examination interpretation, and 54.7% of radiologists rated the ease of use of the new system as good or very good (compared to 4.2% for the old system, p < 0.001). Transitioning to an EHR-driven workflow at a large academic medical center improved efficiency, was favorable to radiologists, and enhanced examination prioritization.

An Adaptive MAC Protocol Based on IEEE802.15.6 for Wireless Body Area Networks

The application carrier of wireless body area network (WBAN) is human; due to changes in people’s sports status or physical health and other reasons, the business traffic fluctuates greatly, which requires the network to have good adaptability. In addition, the energy consumption problem is also a key factor restricting the applications of the WBAN. At present, the proposed MAC protocol is not highly adaptive and has low energy efficiency. To solve this problem, this paper proposes an adaptive MAC protocol based on IEEE802.15.6 for WBAN (A-MAC). The protocol sets the data to three priorities according to the type of service; the superframe structure of IEEE802.15.6 is improved and reorganized into four phases: the beacon phase, the contention access phase, the noncontention access phase, and the inactive phase. The length of the contention access phase and the noncontention access phase is adjusted according to the proportion of nodes that generate each priority data. The contention access phase is further divided into three subphases, and the length of the subphase is dynamically adjusted according to the data priority. In the contention access phase, all nodes compete for access channel according to the channel access policy. The random data that competes successfully transmits data directly, and the periodic data that competes successfully transmits data in the allocated time slots of the noncontention access phase. Finally through the simulation of the proposed A-MAC protocol and IEEE 802.15.6 MAC protocol and CA-MAC protocol in network performance which were compared, the results show that in terms of throughput, power consumption, and the network time delay, the network performance using A-mac protocol is better than the network performance using IEEE802.15.6 MAC and CA-MAC protocols.

Improving risk assessment approaches for chemicals with both endogenous and exogenous exposures

To conduct risk assessments of exogenous chemicals for which there are also endogenous exposures, knowledge of the chemistry and biology of both types of exposures needs to be integrated into problem formulation and carried through to risk characterization. This issue is framed in a risk assessment context, highlighting the importance of quantifying increments of dose from all sources of the same or similar chemicals interacting with biological targets; understanding the influence of endogenous chemical concentrations on disease risk; and assessing total dose to targets in evaluating risk from incremental environmental exposures. Examples of recent assessments illustrate the importance of addressing this issue. Evaluations of data on blood or organ concentrations of ammonia, methanol, formaldehyde, acetaldehyde, and three gaseous signaling molecules (hydrogen sulfide, carbon monoxide, and nitric oxide) provide examples where current data are already informing perspectives on relative exposures at the portal of entry and systemically. To facilitate quality risk assessments of exogenous chemicals with endogenous exposures, a series of specific questions are presented that need to be addressed in systematic review to enhance problem formulation, improve the development of holistic conceptual models, and to facilitate the identification of priority data needs for improving risk assessments.

Процеси утворення позитивних іонів при взаємодії електронів з молекулами тиміну

The work is aimed to solve the key problems of modern biophysics related to the study of fundamental mechanisms of interaction of ionizing radiation on living cells and stability of biological systems to its influence. The obtained data and their generalizations create a basis for understanding the interaction mechanisms and stability of biological systems to its influence. Investigation is aimed on the obtaining the new priority data about the characteristics of the life important biological molecules, establishing the mechanisms and features of dissociative capture, excitation and ionization under the slow electrons; the study of the influence of intermolecular interactions on these processes and solution of some applications concerning the definition of physical stability of biomolecules in different states of aggregation. The AM1 method that was used in research is a semi-empirical method for the quantum calculation of molecular electronic structure in computational chemistry. It is based on the neglect of differential diatomic overlap integral approximation and investigates the processes of formation of positive ions, which are formed during the interaction of thymine molecules with slow electrons. Fragmentation model of thymine molecules under electron ipmpact is proposed. Six most likely bond breaks in the cyclic structure of thymine molecular ion are identified. The obtained results are in good agreement with experimental data.

THE (Temperature Heterogeneity Energy) Aware Routing Protocol for IoT Health Application

In this paper, we focus on an interesting E-Health monitoring system that efficiently utilizes the concept of the Internet of Things (IoT). Wireless body area network (WBAN) composed of a set of target-oriented sensors placed around the human body and transmit its collected data to a coordinator that carries it to some cloud system. WBAN standardized with the newly emerged IEEE802.15.6 with its specifications for Physical (PHY) and medium access control (MAC) layers only. Regrettably, the Network layer is not addressed by the standard where it plays an important role in the overall performance. In this paper, we design the temperature heterogeneity energy (THE) aware routing protocol for WBAN as a complement for the standard. “THE” aims to control the temperature raising caused by the on-body sensor and affects the skin comfortableness. In the meantime, “THE” maintains the network in high-performance conditions in terms of long node lifetime and high packet throughput. To fulfill these desired tradeoffs, the sensed data is classified into three data levels with variable transmission priority to each level, namely, emergency (abnormal) data priority 7 (highest priority), critical data priority 6, and normal data assigned priority 5. “THE” protocol is based on a utility function that chooses the WBAN's parent node (PN) that has the largest amount of remaining energy, the highest data rate, the minimum distance to the coordinator, and the minimum sensor's temperature. Hopping the data through the parent node (two-hops) is applicable for the data with normal priority while high priority data (critical and emergency) is transmitted to the coordinator in one-hop only. The proposed “THE” protocol's performance validation performed via Monte Carlo simulation analysis which proves that “THE” protocol achieved better performance against conventional protocols (SIMPLE and iM-SIMPLE) in terms of network lifetime, number of dead nodes, total remaining energy, and throughput.

Unified framework for data management in multi-cloud environment

With the recent emergence of multi-cloud environments, it has become crucial to manage data in them. This work proposes a data archival scheme which initially picks optimal clouds from a multi-cloud environment based on the data access patterns. The voluminous data obtained is then split into chunks and their access frequency is efficiently predicted. Depending on the prediction, suitable clouds are picked based on QoS attributes and weighted threshold coefficient. Further, the data is placed into the selected clouds by checking their resource availability. Data retention policies are proposed and applied to the data along with homomorphic encryption to provide security and to place the highest priority data into the appropriate cloud. The least frequently accessed data are also archived in suitable clouds. Results obtained in a heterogeneous cloud environment indicate the cost effectiveness of storing huge data in a multicloud environment to provide the best of services.

An Intelligent Packet Drop Mechanism in Wireless Body Sensor Network for Multiple Class Services Based on Congestion Control

Considering the impact of congestion on wireless body sensor network (WBSN), an intelligent packet drop mechanism for multi-class traffic based on exponential random early detection is presented to mitigate the network congestion. A learning automaton is set in mote for “learning” intelligently from outside network environments. Obtained the learning result, an exponential random early detection algorithm is used in interactive node to control congestion by dropping packet. Meanwhile, based on the characteristics of WBSN, we also subdivide the packet dropping probability by the different priority traffic. Eventually, the packet dropping probability of traffic under different network environments, queue lengths and priorities is obtained. In consideration of a large amount of redundant data in WBSN, the proposed mechanism is able to actively dropping some low priority data, which can not only mitigate network congestion but also ensure the transmission of important vital signals.