MDSplus remote data access over high latency connections

Measuring airborne fine particulate matter (PM2.5) in the context of health-based field research introduces many logistical challenges including remote equipment setup, data access, and maintenance by both researchers and participants. In preparation for a 17-site, 228-household clinical trial, we developed methods to validate low-cost, light-scattering PM2.5 sensors (model PAII-SD, PurpleAir, Inc, USA) against a Federal Equivalent Method instrument (model BAM 1020, Met One Instruments, USA) for remote measurement of indoor PM2.5 concentrations among participating households over 6 months. To allow real-time, remote data access by the research team, we developed procedures for pairing the light-scattering PM2.5 sensors for each household with a portable Wi-Fi hotspot device (model Solis Lite, Skyroam, Inc, USA) prior to shipping them to participants. Armed with this remote data access, we created a process for daily automated data extractions to ensure sensors remained online and to assess data quality. Our methods support the feasibility of obtaining long-term, continuous PM2.5 measurement reliably and accurately in the context of a research trial using low-cost, light-scattering sensors. The framework we describe in this methods paper can serve as a model for future environmental health research studies.

Visualization of remote data needs software that is fundamentally designed for distributed processing and high-speed networks. Motivated by and following the requirements of a distributed visualization application, this article describes the design and implementation of a fast and configurable remote data access system called eavivdata. Because wide-area networks may have a high latency, the remote data access system uses an architecture that effectively hides latency. Four remote data access architectures are analyzed and the results show that an architecture that combines bulk and pipeline processing is the best solution for high-throughput remote data access. The resulting system, also supporting high-speed transport protocols and configurable remote operations, is up to 400 times faster than a comparable existing remote data access system.

Conventional pessimistic architectures used in database systems may not suit mobile environments. These architectures require considerable computing power in addition to a permanent connection status. Unfortunately, even tough mobile devices are evolving in computing and communications capabilities, they can not bear such requirements. In the meantime, optimistic architectures that do not lock resources and can permit disconnections appear to be the natural choice for mobile applications. In this paper, we introduce an efficient replication algorithm that we call ERDA which is based on legacy mobile database synchronization architecture: MS RDA (remote data access). This paper presents a performance comparison of ERDA and the remote data access (RDA). Like RDA, ERDA make the most out of the MS.Net compact framework: a relatively new but very famous platform for the development of mobile and handheld devices. This paper analyzes synchronization architectures to provide the best (speed, network traffic and storage vs. robustness) scenario.

The 25+ laboratories of the European Fusion Development Agreement (EFDA) has been increasingly using remote participation technologies for collaborative work on several experiments. We present an overview of the technologies that are employed to provide remote data access, remote computer access, and teleconferencing. We also deal with computer network requirements, and support and documentation needs. The biggest application of these tools has been the joint scientific exploitation of the JET Facilities. Increasingly other experiments are operated as shared facilities, and the RP tools are being used in this context. For remote data access there is a clear trend towards MDSplus as common data access layer for multiexperiment data access. Secure remote computer access is converging on two different solutions. Videoconferencing is also converging on two partially interoperable solutions, whereas the sharing of presentation material is converging on one solution. Remote control room participation is being used in two laboratories. Network monitoring has been developed and is now in routine use. The RP work is being done at many laboratories and is co-ordinated by EFDA. A number of items in several fields need still to be tackled and an overview of these is presented.

Large-scale data transport for data-intensive sciences is a complex multidimensional challenge. The challenge includes optimizing the end-to-end Big Data movement performance in real-time, supporting direct remote data access using NVMe over Fabrics (NVMeoF) and deploying to existing research platforms. AIDTN is the first effort to provide a unique AI system designed to incorporate NVMe over Fabrics (NVMeoF) and optimize coordination among multiple components supporting large-scale, multi-domain Wide Area Network (WAN) data-intensive science. AIDTN's research objective is to integrate next-generation storage architecture using NVMeoF, specialized network design using high-performance network appliances, Data Transfer Nodes (DTNs), catalysts in driving data transport, and a unique AI system explicitly designed for high-performance data movement challenges. AIDTN is the first system that uses network and system features to predict the end-to-end performance of high-performance data movement and further extends the model with NVMe-specific features for NVMeoF remote data access. As a result, AIDTN improves data movement performance by up to 284% while minimizing packet loss compared to other heuristics approaches. It also has a prediction error rate as low as 0.16 compared to AI models with the only network (error rate = 0.29) or network and system features (error rate = 0.19).

The EPICS Channel Archiver is used to store data ex ported by EPICS I/O Controllers. The Channel Archiver acts as a Channel Access Client and stores recorded data, acquired via periodic scan or monitored, into indexed binary files. MDSplus is a data management system used in several Nuclear Fusion experiments to handle experimental and configuration data. A data access Application Programming Interface for local and remote data access is available for several languages, namely C, C++, Fortran, Java, Python, MATLAB and IDL, and a set of visualization tools is available for data browsing and display. The paper presents a new implementation of the EPICS Channel Archiver which uses MDSplus for data storage. In this way, it is possible to take advantage of the availability of the local and remote data access layers of MDSplus, widely used in the fusion community to handle large sets of data. A performance comparison between the original implementation and the new one is provided. In particular, the storage space requirements and the data access speed are considered.

TPS1613 Background: To increase the access of patients to precision oncology and personalized medicine, we need not only to undertake molecular profiling but rather we need to interlink patients, physicians and researchers using modern technological opportunities, increasing the likelihood of providing new therapies to patients with suitable targets. The PLATON Network (NCT05489250, IKF-T008) addresses these important issues. Methods: The PLATON Network (PLATON) is an interactive structure aiming at improving personalized medicine for all tumor entities (starting with upper GI tumors). The goal of the PLATON Network is to provide a platform for connecting medical practitioners, researchers and patients to personalized cancer treatments. The platform combines comprehensive molecular profiling, data on active clinical trials, remote data access with networking solutions, implemented substudies and associated educational and discussion forums. The main elements of PLATON are: a Platform-study design, an interactive Cloud-based WebApp, Networking, a Molecular Pathology Case Discussion Board, an educational forum, and a BioDataBank. The network will be composed of a global network of cancer centers and cancer specialists who can submit genomic data of their patients to PLATON. The WebApp allows members and associated scientists to view each other's current patients' clinical and molecular data and get into contact with the treating physicians or identify patients for ongoing biomarker-driven clinical trials using advanced algorithms. The PLATON Network also offers molecular testing via Foundation CDx and CDx Liquid for standardized NGS testing and functions as an umbrella for substudies within the platform design. PLATON enrolls patients during first line treatment and collects information on routine clinical data (baseline data, medical history, histopathology reports, treatment decisions, etc.). During follow up, all anti tumor therapy lines, tumor response and survival data are recorded. Importantly, quality of life data is captured monthly under therapy (with EORTC QLQ-30,-BIL21, -HCC18, -PAN26, -STO22 and EQ-5D-5L) and at further follow up (with EQ-5D-5L). So far, 110 cancer centers have joined the PLATON network. Over 200 patients with upper GI tumors received comprehensive molecular profiling and 162 cases were reviewed and discussed in the Molecular Pathology Case Discussion Board. Five sub-projects/-studies have been initiated under the umbrella of PLATON. The educational forum is in the planning stage. PLATON is conducted by the Institute of Clinical Cancer Research (IKF) in Frankfurt with the supervision of an independent scientific steering committee.

The design and implementation of a SIMD controller for a polymorphous array processor is presented in the paper. The polymorphous array processor is intended for graphics and multimedia applications. To meet the needs for efficient data level parallel computation, we use the state machine approach to design the row, column, and cluster controllers. A row controller dispatches SIMD instructions to processing elements; a column controller performs data and program loading as well as remote data access. The polymorphous machine employs two computation modes, the SIMD mode and the MIMD mode. The controllers are mainly used for SIMD mode of computation. A dedicated hardware circuit design improves the ability to handle parallel data of the processor.

With the exponential growth of LHC (Large Hadron Collider) data in the years 2010-2012, distributed computing has become the established way to analyse collider data. The ATLAS experiment Grid infrastructure includes more than 130 sites worldwide, ranging from large national computing centres to smaller university clusters. So far the storage technologies and access protocols to the clusters that host this tremendous amount of data vary from site to site. HTTP/WebDAV offers the possibility to use a unified industry standard to access the storage. We present the deployment and testing of HTTP/WebDAV for local and remote data access in the ATLAS experiment for the new data management system Rucio and the PanDA workload management system. Deployment and large scale tests have been performed using the Grid testing system HammerCloud and the ROOT HTTP plugin Davix.

Optimization of the interface between radiology, surgery, radiotherapy, and pathology in head and neck tumor surgery: a navigation-assisted multidisciplinary network

The literature on programming sensor networks has focused so far on providing higher-level abstractions for expressing local node behavior. Kairos is a natural next step in sensor network programming in that it allows the programmer to express, in a centralized fashion, the desired global behavior of a distributed computation on the entire sensor network. Kairos’ compile-time and runtime subsystems expose a small set of programming primitives, while hiding from the programmer the details of distributed-code generation and instantiation, remote data access and management, and inter-node program flow coordination. In this paper, we describe Kairos’ programming model, and demonstrate its suitability, through actual implementation, for a variety of distributed programs—both infrastructure services and signal processing tasks—typically encountered in sensor network literature: routing tree construction, localization, and object tracking. Our experimental results suggest that Kairos does not adversely affect the performance or accuracy of distributed programs, while our implementation experiences suggest that it greatly raises the level of abstraction presented to the programmer.

RATIONALE: Acute viral bronchiolitis is the most common reason for hospitalization of infants in the United States (US). Infants hospitalized for bronchiolitis are at higher risk for recurrent respiratory symptoms, wheeze, and persistent childhood asthma. Improvement in indoor air quality (IAQ) following bronchiolitis hospitalization may reduce respiratory symptom burden. BREATHE is a multi-center, parallel, double-blind, randomized controlled clinical trial in 17 sites across the US. The trial's primary aim is determining the efficacy of use of a high efficiency particulate air (HEPA) filtration unit in the infant's sleep space and common room, compared to use of a control unit, in increasing respiratory symptom-free days over 24 weeks. Indoor fine particulate matter (PM2.5) levels are a secondary endpoint. Between November 2022 and December 2023, 228 infants residing in non-smoking households were randomized. We present here pre-intervention (i.e., prior to HEPA unit use) indoor PM2.5 levels from a geographically diverse sample of homes. METHODS: PurpleAir PA-II-SD monitors continuously measured PM2.5 levels in both the infant's sleep space and a common room. Before deployment, each PurpleAir was collocated with a Federal Equivalent Method instrument (BAM 1020, Met One Instruments, USA) for ≥ 48 hours in an indoor laboratory to assess sensor performance. We paired 2 PurpleAir monitors with a portable Wi-Fi hotspot (Solis Lite, Skyroam, Inc., USA) in participants’ homes to allow remote data access by the research team. Following data retrieval, PM2.5 values were corrected using US Environmental Protection Agency correction equations. Mean hourly PM2.5 levels over the pre-intervention period were calculated for each monitor and summarized using medians and interquartile ranges (IQR). Wilcoxon rank sum tests were used to compare PM2.5 levels by demographics. RESULTS: By the end of the intervention period, 183 participants (80%) had returned their PurpleAir air monitors. Median (IQR) PM2.5 was 8.7 (18.9) in the common room and 9.4 (25.2) in the sleep space. Chronic asthma medication usage prior to hospitalization (p=0.054), wood stove use for heating (p=0.080), and lack of central air conditioning (p=0.141) were non-significantly associated with higher common room PM2.5. Generally similar results were observed for the infant's sleep space. CONCLUSIONS: There was substantial variability in indoor PM2.5 levels in BREATHE homes. Although there is no US indoor standard for PM2.5, the median of the hourly mean PM2.5 values in the infants’ sleep space exceeded the annual National Ambient Air Quality Standard for PM2.5 of 9 µg/m3, with some homes demonstrating exceptionally high levels.

Patient adherence to the protocol in clinical trials is a critical factor in determining the outcome of the trial. An investigational eFlow nebulizer was used with an eTrack controller featuring adherence-monitoring capability (PARI Pharma, Germany) to deliver drug to the lungs via inhalation and to objectively monitor adherence. The inhalation data were available via the PARItrack web portal and allowed evaluation and graphical visualization of each patient's adherence. The clinical trial involved 10 patients who self-administered drug in their homes twice a day for 6 weeks. The eTrack controller automatically transferred data of each nebulization via a Bluetooth connection to a 2netHub (Qualcomm) and via GSM to a server. The data could be accessed through the PARItrack web portal. The clinical trial nurses, investigators and CRO could remotely monitor adherence and an alert system was established for information on missed inhalations. This allowed individual adherence issues to be addressed immediately and corrective actions to be implemented to ensure ongoing adherence. This setup resulted in a high adherence rate over the duration of the clinical trial. The overall mean adherence rate was 96 %. Seven out of ten patients had an adherence rate of 100 %, two had 95 %, and one had 64 %. This compares with a reported adherence rate of 78 % in the first 4 weeks of another clinical trial using a monitoring nebulizer without remote data access and intervention [Fuchs et al. ECFC 2011]. The high adherence rates achieved in this study demonstrate the utility of remote monitoring and immediate intervention to achieve good adherence in a clinical trial.

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. While the open FITS file format is ubiquitous in astronomy, astronomical imaging shares many challenges with biological imaging, including the need to share large image sets using secure, cross-platform APIs, and the need for scalable applications for processing and visualization. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME tools include: an open data model for multidimensional imaging (OME Data Model); an open file format (OME-TIFF) and library (Bio-Formats) enabling free access to images (5D+) written in more than 145 formats from many imaging domains, including FITS; and a data management server (OMERO). The Java-based OMERO client-server platform comprises an image metadata store, an image repository, visualization and analysis by remote access, allowing sharing and publishing of image data. OMERO provides a means to manage the data through a multi-platform API. OMERO’s model-based architecture has enabled its extension into a range of imaging domains, including light and electron microscopy, high content screening, digital pathology and recently into applications using non-image data from clinical and genomic studies. This is made possible using the Bio-Formats library. The current release includes a single mechanism for accessing image data of all types, regardless of original file format, via Java, C/C++ and Python and a variety of applications and environments (e.g. ImageJ, Matlab and R).

Remote access of data using off-the-shelf technologies like internet and GSM/GPRS, is one of the fast growing application areas in industries, customer services, banking, entertainment services etc. This paper presents design and implementation of an auto-responder for educational institute. The design is based on GSM Short Message Service and is used for remote access to data related to examination, results and student’s attendance to be accessed by students or any stack holder, at their own wish. The complete application software, including database management, GSM communication and interactive GUI, is designed in MATLAB. The application provides a good example of the use of Information and Communication Technology (ICT) and illustrates how low cost off-the-shelf technologies like GSM can be meaningfully used for remote data access.