Random Access Capability Research Articles

Growth and characterization of germanium telluride nanowires via vapor–liquid–solid mechanism

Phase-change materials (PCMs), which can transition reversibly between crystalline and amorphous phases, have shown great promise for next-generation memory devices due to their nonvolatility, rapid switching periods, and random-access capability. Several groups have investigated phase-change nanowires for memory applications in recent years. The ability to regulate the scale of nanostructures remains one of the most significant obstacles in nanoscience. Herein, we describe the growth and characterization of germanium telluride (GeTe) nanowires, which are essential for phase-change memory devices. GeTe nanowires were produced by combining thermal evaporation and vapor–liquid–solid (VLS) techniques, using 8 nm Au nanoparticles as the metal catalyst. The influence of various growth parameters, including inert gas flow rate, working pressure, growth temperature, growth duration, and growth substrate, was examined. Ar gas flow rate of 30 sccm and working pressure of 75 Torr produced the narrowest GeTe nanowires horizontally grown on a Si substrate. Using scanning electron microscopy, the dimensions, and morphology of GeTe nanowires were analyzed. Transmission electron microscopy and energy-dispersive x-ray spectroscopy were utilized to conduct structural and chemical analyses. Using a SiO2/Si substrate produced GeTe nanowires that were thicker and lengthier. The current–voltage characteristics of GeTe nanowires were investigated, confirming the amorphous nature of GeTe nanowires using conductive atomic force microscopy. In addition, the effects of the VLS mechanism and the Gibbs–Thomson effect were analyzed, which enables the optimization of nanowires for numerous applications, such as memory and reservoir computing.

A-070 A fully automated HbA1c Assay on the DxC 500 AU Clinical Chemistry Analyser

Abstract Background Diabetes mellitus is a condition characterized by hyperglycemia resulting from the body’s inability to use blood glucose for energy. In Type-1 diabetes, the pancreas no longer makes insulin and blood glucose cannot enter the cells to be used for energy. In Type-2 diabetes, the pancreas does not make enough insulin or the body is unable to use insulin correctly. According to the World Health Organization (WHO), 422 million adults were living with diabetes globally in 2014 with an estimated 1.6 million deaths directly associated with diabetes annually. HbA1c is the major species of glycohemoglobin in human blood. HbA1c formation occurs through a non-enzymatic reaction, called glycation, which occurs between glucose and the n-terminal valine of the hemoglobin â-chain of HbA. A Schiff base intermediate product is formed, which rearranges to form a stable ketoamine in an irreversible reaction. The rate of glycation is proportional to the glucose concentration in the bloodstream and is an accurate reflection of average blood glucose over a period of eight to twelve weeks. HbA1c testing is recommended for the diagnosis of diabetes by the International Expert Committee (IEC), the American Diabetes Association (ADA), and the WHO, who recommended a diagnostic threshold of = 6.5% ( = 48 mmoL/moL) HbA1c and a range for pre-diabetes of 5.7%–6.4% (39–46 mmoL/moL) HbA1c. Methods The HbA1c Advanced assay on the DxC 500 AU* utilizes automatic sample pre-treatment, has batch and random access capability. No manual pre-treatment of the whole blood sample or additional washing steps are required. Firstly the red blood cells are hemolyzed automatically, total hemoglobin and glycated hemoglobin are then measured colorimetrically and immunoturbidimetrically respectively. Results Precision studies were conducted according to CLSI EP15-A3. Commercial controls and four native K2 EDTA whole blood samples ranging from 5.1% to 12.0% HbA1c, were run twice daily, over twenty days using three lots of reagent on three DxC500AU Clinical Chemistry analyzers at a single site. Repeatability ranged from 0.86% to 1.44% CV and Total Precision ranged from 1.55% to 2.43% CV. Linearity studies were conducted according to CLSI EP06-A, and verified an analytical measuring range of 4.0%–15.0% (NGSP) and 20–140 mmol/mol (IFCC). Method comparison and bias estimation was evaluated using CLSI EP09-A3. K2 EDTA patient samples (n = 150) across the analytical range were run vs a Secondary Reference method and yielded a slope of 1.031, intercept −0.147% HbA1c, correlation coefficient R = 0.997 for Weighted Deming regression, and slope 1.000 and intercept 0.06% HbA1c for Passing Bablok regression. Interference studies carried out demonstrated no significant interference from common endogenous interferences, a large panel of drugs, common Hb variants (HbC, HbD, HbE, HbA2 and HbS) and cross reactants (HbA0, HbA1a+b, acetylated hemoglobin, carbamylated hemoglobin, glycated hemoglobin, glycated albumin and labile HbA1c). Conclusion The HbA1c Advanced assay on the DxC 500 AU is a precise and accurate assay, requiring no manual pretreatment and can be used for monitoring and diagnosing diabetes. *Pending clearance by the United States Food and Drug Administration and achievement of CE compliance. Not currently available for in vitro diagnostic use.

Ultraviolet random access collaborative networking protocol based on time division multiple access

The ultraviolet network, with its advantages of high security, non-line-of-sight communication, and all-weather operation, has broad military application potential. This study proposes an ultraviolet random access collaborative networking protocol based on time division multiple access that combines the benefits of synchronous and asynchronous media access control protocols. Considering the physical layer characteristics, the frame structure of the protocol is constructed based on a cross-layer design. Compared with the time division multiple access protocol, the proposed protocol can achieve higher throughput with a lower delay and packet loss rate by the dynamic timeslot allocation mechanism. Then, the effects of maximum cache capacity and burst traffic on network performance are investigated. Finally, the conducted network experiments prove the cooperative forwarding and random access capabilities of the ultraviolet random access collaborative networking protocol. The proposed protocol provides a reliable and effective method for independent and flexible ultraviolet networks.

Performance Analysis and Energy Efficiency of MU- (OFDMA & MIMO) Based Hybrid MAC Protocol of IEEE 802.11ax WLANs

Future wireless networks are characterized by densely populated stations (STAs) with limited battery capacity. These networks demand high aggregate throughput, increased energy efficiency, and high Random Access (RA) capability, i.e., the system's ability to allow new STAs to join the network quickly. WiFi-6 (also known as IEEE 802.11 ax) is the new generation WLAN standard proposed to meet these diverse system requirements. In this paper, we analyze the effect of Multi-User Multi-Input Multi-Output (MU-MIMO) & MU-Orthogonal Frequency Division Multiple Access (MU-OFDMA)-based Hybrid Access (HA) mechanism of WiFi-6 systems. We propose a fixed Point model for analyzing this HA mechanism. By solving the system model, we investigate the impact on critical system metrics such as throughput, energy efficiency, Random Access capability, and delay due to a variation in (i) the number of resource units (RUs), (ii) the channel sounding interval, and (iii) the Target Wake-Up time interval. We have studied the effect of the non-saturated traffic model driven by the Poisson and Pareto arrival processes. Further, we have modeled the buffer status-based dynamic scheduling of RUs for the MU-OFDMA-based HA mechanism. We have also analyzed the novel Multi-Traffic Identifier-based frame aggregation feature. Further, we have analyzed the hand-off mechanism for a multi-BSS (Basic Service Set) scenario using the Stochastic geometry-based mathematical tool. We have used Matlab-based simulations for our study and found that the simulation results closely match the analytical results. Our study sheds light on the trade-off that exists between different performance metrics of the 802.11ax HA mechanism.

GVC: efficient random access compression for gene sequence variations

BackgroundIn recent years, advances in high-throughput sequencing technologies have enabled the use of genomic information in many fields, such as precision medicine, oncology, and food quality control. The amount of genomic data being generated is growing rapidly and is expected to soon surpass the amount of video data. The majority of sequencing experiments, such as genome-wide association studies, have the goal of identifying variations in the gene sequence to better understand phenotypic variations. We present a novel approach for compressing gene sequence variations with random access capability: the Genomic Variant Codec (GVC). We use techniques such as binarization, joint row- and column-wise sorting of blocks of variations, as well as the image compression standard JBIG for efficient entropy coding.ResultsOur results show that GVC provides the best trade-off between compression and random access compared to the state of the art: it reduces the genotype information size from 758 GiB down to 890 MiB on the publicly available 1000 Genomes Project (phase 3) data, which is 21% less than the state of the art in random-access capable methods.ConclusionsBy providing the best results in terms of combined random access and compression, GVC facilitates the efficient storage of large collections of gene sequence variations. In particular, the random access capability of GVC enables seamless remote data access and application integration. The software is open source and available at https://github.com/sXperfect/gvc/.

16-Bit (4 × 4) Optical Random Access Memory (RAM) Bank

During the past years, the limited access-times and memory bandwidth in electronic random-access memory (RAM) has triggered a concerted research effort towards deploying optical memory circuitry for exploiting the inherent high-bandwidth characteristics of light-based technologies. Yet the deployment of optical memory elements in functional optical RAM demonstrations has still been limited to single-bit capacity levels, with the few multi-bit demonstrations still offering only storage functionality without any true random-access capabilities. In this article, we demonstrate an experimental 16-bit all-optical RAM bank prototype that follows a 4 × 4 matrix organization and supports addressable random access storage of four 4-bit WDM-formatted optical Data Words at a 20 Gb/s memory-throughput. The proposed architecture constitutes of completely passive Row/Column decoding (RD/CD) subsystems, four Semiconductor Optical Amplifier Mach-Zehnder Interferometer (SOA-MZI) Access Gates (AGs) for enabling the access towards the 4 available Word Lines (WLs) and 16 all-optical Flip-Flops (AOFF) arranged in a 4 × 4 RAM bank. Each FF is incorporated in an indicative photonic integrated circuit (PIC). The experimental validation of the complete 16-bit RAM bank reveals error-free operation in Write mode with a peak power penalty between 8.3–10.2 dB at 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−9</sup> bit-error-rate (BER) measurements, indicating a roadmap for two-dimensional addressable (2D) RAM banks that can penetrate the optical computing application domain.

Performance Analyses of Uplink MU-OFDMA Hybrid Access MAC in IEEE 802.11ax WLANs

Future wireless local area networks (WLANs) are expected to have numerous stations (STAs) with diverse Quality of Service requirements. IEEE 802.11ax is the current WLAN standard proposed to meet these requirements. This article analyzes the uplink-multiuser-orthogonal frequency division multiple access-hybrid access (HA) mechanism of the 802.11ax system under error-prone channel conditions. We propose an enhanced Markov chain model for analyzing such a WLAN system. By solving the system model, we derive vital systems performance metrics, such as aggregate and per-STA throughput, random access (RA) capability packet loss probability, mean delay, jitter, fairness, and worst-case delay bounds. Our analysis also considers different physical (PHY) and medium access control (MAC) layer aspects, such as channel bandwidth, the number of resource units (RUs), packet aggregation feature, fading, path-loss, modulation and coding schemes (MCS), etc. Furthermore, we have studied the MCS link adaptation-based dynamic HA process where the RUs are dynamically adapted between scheduled access and RA mechanisms. Additionally, to capture the role of PHY and MAC layer parameters on multi-Basic service set scenarios, we have integrated the Markov chain-based modeling with the stochastic geometry-based model. Our analytical model has been validated against extensive simulations, and the tradeoff between the metrics is studied.

Hierarchical lossless coding of light fields with improved random access

The adoption of light field (LF) technology is often hindered by the large amount of data that is necessary to represent such information. To alleviate such burden, specific coding techniques have been under research in recent years. However, most of them require decoding the whole LF data, even in applications where only a region of the LF visual content needs to be accessed. Therefore, encoding schemes that incorporate scalability and random access capabilities would cater to a wider range of LF use cases, particularly those requiring lossless compression. To enable such type of functionalities, an encoder must be designed so that the decoding process can extract only specific views/regions of the complete LF, according to user options or application requirements. This paper proposes hierarchical Minimum Rate Predictors (H-MRP), a lossless light field codec that provides the aforementioned functionalities. The main contributions herein proposed are: (i) the lossless encoding the LF in multiple hierarchical layers; (ii) the flexible selection of reference images for prediction; and (iii) the use disparity compensation between the reference images. The experimental results show that the proposed encoder provides a good compromise in terms of compression efficiency versus random access penalty, surpassing its best competitor by 25% in terms of random access and by 1 bit-per-pixel in terms of compression efficiency. When optimised to provide the best compression efficiency, the method surpasses current state-of-the-art lossless encoding by up to 3 bits-per-pixel.

Comparison of Abbott COVID-19 testing Platforms for timely results- CMCVAMC experience

Introduction/ObjectiveCOVID-19 is a new disease, caused by the SARS-CoV-2 coronavirus capable of causing severe disease and death. The Alinity-m has a high throughput and random-access features that are not on the Abbott m2000, both of which had been validated and brought into clinical use for high throughput SARS-CoV-2 testing. The additional features of Alinity-m would be expected to improve turnaround time; however, there are no published reports in the English literature comparing the turnaround time between the Abbott m2000 and Alinity-m.Methods/Case ReportA retrospective quality assurance search for all SARS-CoV-2 tests performed on the Abbott m2000 and Alinity-m (both Chicago IL) between February 1st 2021 to March 1st, 2021, to capture the turnaround time differences for the Abbott m2000 versus the Alinity-m for the month after the Alinity-m was brought into clinical service after validation.Results (if a Case Study enter NA)There was a total of 318 tests performed on the Abbott m2000 and 1329 tests performed on the Alinity-m during this time period. The average turnaround time on the Alinity was 6 hours, compared with 11 hours on the Abbott m2000. This difference was statistically significant by the t-test (p-value = <0.01). Both the optimized throughput and random-access features of the Alinity-m contributed significantly to this improvement.The Alinity-m is capable of producing results within 115 minutes for the first specimen and then 3 minutes for each sequential specimen. On the other hand, the Abbott m2000 must be batched in limited 8-12 hour runs without random access capability. All the results were reported and communicated to the clinical teams, so the timely patient management can be administrated and surveillance of the same can be done in real time.ConclusionAlinity M has a significant advantage for a random access as well as improved TAT for detection of SARS-CoV-2, leading to prompt patient care and management.

Titchy: Online Time-Series Compression With Random Access for the Internet of Things

We introduce Titchy, which is a compression method for time-series data generated by the Internet of Things. Our proposed method is flexible and has several advantages when applied in the IoT ecosystem: 1) it is able to compress even when only a small amount of memory can be allocated to it; 2) it compresses data in tiny chunks, so it introduces very little latency during online operation and thus, enables frequent and timely updates with compressed data; and 3) it facilitates efficient data storage and retrieval by enabling low-cost random access to the compressed data, eliminating the need to decompress large chunks when only a small amount of data is requested. To evaluate each of these advantages, we have implemented the compressor and conducted extensive experiments with long-term real-world data captured over days or weeks. We also present results for seven state-of-the-art compression methods to act as a baseline. Our evaluation shows that Titchy not only outperforms all seven on random access capability and for frequent transmissions but also provides great compression ratios as well as high compression and decompression speeds.

Light field image coding with flexible viewpoint scalability and random access

This paper proposes a novel light field image compression approach with viewpoint scalability and random access functionalities. Although current state-of-the-art image coding algorithms for light fields already achieve high compression ratios, there is a lack of support for such functionalities, which are important for ensuring compatibility with different displays/capturing devices, enhanced user interaction and low decoding delay. The proposed solution enables various encoding profiles with different flexible viewpoint scalability and random access capabilities, depending on the application scenario. When compared to other state-of-the-art methods, the proposed approach consistently presents higher bitrate savings (44% on average), namely when compared to pseudo-video sequence coding approach based on HEVC. Moreover, the proposed scalable codec also outperforms MuLE and WaSP verification models, achieving average bitrate saving gains of 37% and 47%, respectively. The various flexible encoding profiles proposed add fine control to the image prediction dependencies, which allow to exploit the tradeoff between coding efficiency and the viewpoint random access, consequently, decreasing the maximum random access penalties that range from 0.60 to 0.15, for lenslet and HDCA light fields.

Efficient and Explicit Balanced Primer Codes

To equip DNA-based data storage with random-access capabilities, Yazdi et al. (2018) prepended DNA strands with specially chosen address sequences called primers and provided certain design criteria for these primers. We provide explicit constructions of error-correcting codes that are suitable as primer addresses and equip these constructions with efficient encoding algorithms. Specifically, our constructions take cyclic or linear codes as inputs and produce sets of primers with similar error-correcting capabilities. Using certain classes of BCH codes, we obtain infinite families of primer sets of length $n$ , minimum distance $d$ with $(d+1) \log _{4}\,\,n +O(1)$ redundant symbols. Our techniques involve reversible cyclic codes (1964), an encoding method of Tavares et al. (1971) and Knuth’s balancing technique (1986). In our investigation, we also construct efficient and explicit binary balanced error-correcting codes and codes for DNA computing.

Multicenter clinical evaluation of alinity m HBV assay performance.

Accurate molecular methods to detect and quantify hepatitis B virus (HBV) DNA are essential to diagnose chronic infections, guide treatment decisions, assess response to treatment, and determine risk of HBV-related complications. New generations of real-time HBV DNA assay platforms provide results in less than 2-3 h, with continuous loading of specimens and true random-access capability. We examined the clinical performance of the new Alinity m HBV assay, run on the fully automated, continuous, random-access Alinity m platform, to accurately detect and quantify HBV DNA in a large series of patient samples infected with different HBV genotypes frequently encountered in clinical practice. This international, multisite study assessed the precision and reproducibility of the Alinity m HBV assay and compared its performance to four HBV assays currently in clinical use. The Alinity m HBV assay demonstrated linear quantitation of HBV DNA in plasma samples, with high precision (coefficient of variation 4.1 %-8.8 %) and reproducibility. The Alinity m HBV assay showed excellent correlation (correlation coefficients ≥0.947) with comparator HBV assays, with an overall observed bias ranging from -0.07 to 0.17 Log10 IU/mL. 97 % of quantifiable patient results were <1 Log10 IU/mL different than the respective comparator assays, with comparable results across HBV genotypes. The newly developed real-time PCR-based Alinity m HBV assay is sensitive, reproducible, and accurately quantifies HBV DNA levels from HBsAg-positive patients across the full dynamic range of quantification.

A 2T-MONOS Embedded Flash Macro With 65-nm SOTB Technology Achieving 0.15-pJ/bit Read Energy With 80-MHz Access for IoT Applications

To expand Internet of Things application ranges, ultralow active energy operations are essential in edge devices. Especially, read energy reduction in embedded Flash (eFlash) memory is strongly required to enable real-time sensing with limited energy generated by energy harvesting (EH). In this letter, 1.5-MB and 256-KB 2T-MONOS eFlash macros are developed with 65-nm silicon-on-thin-box (SOTB) technology, adopting low-energy sense amplifier and data transmission circuit techniques which enhance intrinsic advantages of SOTB devices. These macros achieve read energy of 0.15-pJ/bit with 80-MHz random read access capability, which is low enough to utilize EH technologies as energy sources.

HMLFC: Hierarchical Motion‐Compensated Light Field Compression for Interactive Rendering

AbstractWe present a new motion‐compensated hierarchical compression scheme (HMLFC) for encoding light field images (LFI) that is suitable for interactive rendering. Our method combines two different approaches, motion compensation schemes and hierarchical compression methods, to exploit redundancies in LFI. The motion compensation schemes capture the redundancies in local regions of the LFI efficiently (local coherence) and the hierarchical schemes capture the redundancies present across the entire LFI (global coherence). Our hybrid approach combines the two schemes effectively capturing both local as well as global coherence to improve the overall compression rate. We compute a tree from LFI using a hierarchical scheme and use phase shifted motion compensation techniques at each level of the hierarchy. Our representation provides random access to the pixel values of the light field, which makes it suitable for interactive rendering applications using a small run‐time memory footprint. Our approach is GPU friendly and allows parallel decoding of LF pixel values. We highlight the performance on the two‐plane parameterized light fields and obtain a compression ratio of 30–800× with a PSNR of 40–45 dB. Overall, we observe a ∼2–5× improvement in compression rates using HMLFC over prior light field compression schemes that provide random access capability. In practice, our algorithm can render new views of resolution 512 × 512 on an NVIDIA GTX‐980 at ∼200 fps.

1773. Development and Evaluation of an Automated Adenovirus Quantitative Assay Using the Luminex ARIES® System

BackgroundThe quantification of circulating human adenovirus (HAdV) DNA is the recommended diagnostic method to predict disseminated disease. Most current HAdV quantitative assays are manually performed and lack the flexibility needed to provide rapid answers when required.The purpose of this study was to evaluate the application of MultiCode® HAdV PCR assay for use with the Luminex ARIES® system (Luminex Corporation, Austin, TX) as an automated and random access test for the quantitative detection of HAdV DNA in plasma.MethodsAnalytical performance characteristics including assay limit of detection/quantitation (LoD/LoQ), accuracy, and inter-, intra-reproducibility were studied using commercial panels (Exact Diagnostics, Fort Worth, TX). Assay specificity was determined usingHAdV reference strains obtained from the American Type Culture Collection (Manassas, VA) and plasma spiked with related Herpes viruses and pathogens commonly found in the blood. Assay accuracy was verified with analysis of 30 plasma samples spiked with different concentrations of control material that covered the full range of HAdV DNA levels. We also prospectively analyzed 180 plasma samples collected from 102 patients. DNA from all samples were extracted, amplified and detected on a single automated Luminex ARIES® system.ResultsThe assay has a wide linear range from 2.55 to 9.4 log10 HAdV DNA copies/mL (coefficient of determination; R2 = 0.995) with a detection limit of 1.82 log10 (95% positivity rate), and a limit of quantification of 2.55 log10 copies/mL. The assay detected HAdV DNA from Adenovirus groups A-F, although slight shifts in Tm peaks were observed. Inter- and intra-assay reproducibility was evaluated using 6 panels of commercial standards, producing variation coefficients of 5% and 2%, respectively. Assay accuracy results reflected a good correlation with a mean difference of 0.10 log10 copies/mL. The results of the prospective study showed 6/102 (5.8%) patients had HAdV viremia, including 4 (3.9%) patients with a viral load ≥4 log10/mL, which might necessitate therapy.ConclusionThe HAdV quantitative assay using the Luminex ARIES® system provides excellent performance for routine testing with the additional advantage of random access capabilities for urgent testing to identify patients at risk for disseminated disease.Disclosures All authors: No reported disclosures.

WBFQC: A new approach for compressing next-generation sequencing data splitting into homogeneous streams.

Genomic data nowadays is playing a vital role in number of fields such as personalized medicine, forensic, drug discovery, sequence alignment and agriculture, etc. With the advancements and reduction in the cost of next-generation sequencing (NGS) technology, these data are growing exponentially. NGS data are being generated more rapidly than they could be significantly analyzed. Thus, there is much scope for developing novel data compression algorithms to facilitate data analysis along with data transfer and storage directly. An innovative compression technique is proposed here to address the problem of transmission and storage of large NGS data. This paper presents a lossless non-reference-based FastQ file compression approach, segregating the data into three different streams and then applying appropriate and efficient compression algorithms on each. Experiments show that the proposed approach (WBFQC) outperforms other state-of-the-art approaches for compressing NGS data in terms of compression ratio (CR), and compression and decompression time. It also has random access capability over compressed genomic data. An open source FastQ compression tool is also provided here ( http://www.algorithm-skg.com/wbfqc/home.html ).

Evaluating the aptima HIV-1 quant Dx, HCV quant Dx and HBV quant assays against the Abbott HIV-1, HCV and HBV RealTime assays

BackgroundViral load measurement is routine for the management of patients infected with HIV, HCV or HBV, using sensitive, quantitative, nucleic acid amplification tests (NAATs). However, platforms are not equivalent in terms of turnaround time, random access capability and operator hands-on time. Objectives and study designWe compared the performance of the Hologic Panther transcription-mediated amplification based Aptima assays for HIV, HBV and HCV viral load measurement with the corresponding Abbott m2000 RealTime assays. All Aptima assays were run according to the manufacturer’s instructions, on archived patient samples for HIV (n = 251 including subtypes 01_AE, A (A1), B, BG recombinant, C CRF02_AG and G), HBV (n = 117 including genotypes A, B, C and D) and HCV (n = 82 including genotypes 1, 2, 3 and 4). Additional testing was performed with WHO international standards and expanded HIV-1 subtype and HCV NIBSC genotype panels. ResultsThe Hologic Panther Aptima assays for HIV-1 RNA, HBV DNA and HCV RNA viral load measurements performed equivalently to the Abbott m2000 RealTime assays. The performance of the Aptima assays was also acceptable on the WHO and NIBSC standards and subtype/genotype panels. ConclusionsThe Aptima Panther platform offers equivalent clinical performance for the viral load measurement of these three viruses, with the added benefits of reduced turnaround time, random access capability and reduced ‘hands-on time’ for staff, resulting in a potentially superior workflow for diagnostic laboratories.

GTRAC: fast retrieval from compressed collections of genomic variants.

The dramatic decrease in the cost of sequencing has resulted in the generation of huge amounts of genomic data, as evidenced by projects such as the UK10K and the Million Veteran Project, with the number of sequenced genomes ranging in the order of 10 K to 1 M. Due to the large redundancies among genomic sequences of individuals from the same species, most of the medical research deals with the variants in the sequences as compared with a reference sequence, rather than with the complete genomic sequences. Consequently, millions of genomes represented as variants are stored in databases. These databases are constantly updated and queried to extract information such as the common variants among individuals or groups of individuals. Previous algorithms for compression of this type of databases lack efficient random access capabilities, rendering querying the database for particular variants and/or individuals extremely inefficient, to the point where compression is often relinquished altogether. We present a new algorithm for this task, called GTRAC, that achieves significant compression ratios while allowing fast random access over the compressed database. For example, GTRAC is able to compress a Homo sapiens dataset containing 1092 samples in 1.1 GB (compression ratio of 160), while allowing for decompression of specific samples in less than a second and decompression of specific variants in 17 ms. GTRAC uses and adapts techniques from information theory, such as a specialized Lempel-Ziv compressor, and tailored succinct data structures. The GTRAC algorithm is available for download at: https://github.com/kedartatwawadi/GTRAC CONTACT: : kedart@stanford.edu Supplementary data are available at Bioinformatics online.

Spatial-Random-Access-Enabled Video Coding for Interactive Virtual Pan/Tilt/Zoom Functionality

High-spatial-resolution videos offer the possibility of viewing an arbitrary region-of-interest (RoI) interactively. Zoom functionality enables watching high-resolution content even on displays of lower spatial resolution. If arbitrary regions corresponding to arbitrary zoom factors can be served to the user, the transmission and/or decoding of the entire high-spatial-resolution video can be avoided. Moreover, if the video content can be encoded such that arbitrary RoIs corresponding to different zoom factors can be simply extracted from the compressed bitstream, we can avoid dedicated video encoding for each user. We propose such a video coding scheme that is vital in allowing the system to scale to large numbers of remote users as well as to encode and store the content for subsequent repeated playback. Apart from generating a multi-resolution representation, our coding scheme uses P slices from H.264/AVC. We study the tradeoff in the choice of slice size. A larger slice size enables higher coding efficiency for representing the entire scene but increases the number of pixels that have to be transmitted. The optimal slice size achieves the best tradeoff and minimizes the expected transmission bitrate. Experimental results confirm the optimality of our predicted slice size for various test cases. Furthermore, we propose an improvement based on background extraction and long-term memory motion-compensated prediction. Experiments indicate up to 85% bitrate reduction while retaining efficient random access capability.