Array Index Research Articles

Unipept in 2024: Expanding Metaproteomics Analysis with Support for Missed Cleavages and Semitryptic and Nontryptic Peptides.

Unipept, a pioneering software tool in metaproteomics, has significantly advanced the analysis of complex ecosystems by facilitating both taxonomic and functional insights from environmental samples. From the onset, Unipept's capabilities focused on tryptic peptides, utilizing the predictability and consistency of trypsin digestion to efficiently construct a protein reference database. However, the evolving landscape of proteomics and emerging fields like immunopeptidomics necessitate a more versatile approach that extends beyond the analysis of tryptic peptides. In this article, we present a significant update to the underlying index structure of Unipept, which is now powered by a Sparse Suffix Array index. This advancement enables the analysis of semitryptic peptides, peptides with missed cleavages, and nontryptic peptides such as those encountered in other research fields such as immunopeptidomics (e.g., MHC- and HLA-peptides). This new index benefits all tools in the Unipept ecosystem such as the web application, desktop tool, application programming interface (API), and command line interface. A benchmark study highlights significantly improved performance in handling missed cleavages, preserving the same level of accuracy.

The Hybrid AC-DC Dynamic Order-Reduced Modeling Method and Damping Enhancement Strategy Based on Improved ERAG

Decentralized control offers a more effective way to avoid the complexities and coordination challenges encountered in centralized control. In the decentralized design of additional controllers for multi-infeed DC transmission systems, it is crucial to focus on the interactions among the controllers. To solve this problem, this paper primarily discusses an enhanced damping characteristic method for hybrid AC-DC systems based on an improved Effective Relative Gain Array (ERGA) index. Initially, feedback signals with better control effects on existing oscillation modes are pre-screened. Subsequently, the ERGA-based interaction index is utilized to pair these feedback signals with control locations, aiming to identify the optimal pairing scheme with the minimum index value, indicating the least interaction effect. This approach minimizes the mutual influence between loops and reduces adverse interactions among controllers. Simulations of multi-DC additional damping controllers designed using the multi-stage Linear Quadratic Regulator (LQR) method in a multi-DC system demonstrate that the optimal pairing scheme significantly outperforms both uncontrolled and poorly paired schemes in controlling low-frequency oscillations, thereby validating the optimality of the proposed method. Furthermore, various disturbances are introduced to verify the effectiveness and robustness of the proposed control strategy against low-frequency oscillations.

Verification of Control System Runtime Using an Executable Semantic Model

The paper outlines a methodology for validating the accuracy of a control system’s runtime implementation. The runtime takes the form of a virtual machine executing portable code compliant with IEC 61131-3 standards. A formal model, comprising denotational semantics equations, has been devised to specify machine instruction decoding and operations, including arithmetic functions across various data types, arrays, and subprogram calls. The model also encompasses exception-handling mechanisms for runtime errors, such as division by zero and invalid array index access. This denotational model is translated into executable form using the functional F ♯ language. Verification involves comparing the actual implementation of the virtual machine against this executable model. Any disparities between the model and implementation indicate deviations from the specification. Implemented within the CPDev engineering environment, this approach ensures consistent and predictable control program execution across different target platforms.

Performance and degradation assessment of two different solar PV cell technologies in the remote region of eastern India

The sole reliance on conventional energy sources proves inadequate to meet the surging energy demand. To address this challenge, a self-sustainable hybrid system based on solar PV emerges as a promising solution. In light of this issue, it becomes important to analyze the performance of a solar PV array. The study aims to assess the performance and degradation of two distinct solar PV technologies, polycrystalline silicon PV (Poly-Si PV) and monocrystalline silicon PV (Mono-Si PV), under the tropical climatic conditions of eastern India. Various performance indices of solar PV arrays, such as reference yield, array yield, final yield, array capture loss, capacity factor (CF) and performance ratio (PR) for the two PV technologies, have been meticulously calculated to analyze the performance of solar PV arrays. The Linear regression (LR) method is employed to assess the degradation rate of both technologies. The results show better performance for Mono-Si PV in terms of yield outcomes and losses compared to its Poly-Si PV counterpart. The yield outcome of Mono-Si PV is approximately 12 % higher, whereas losses are around 32 % lower than Poly-Si PV. The annual average PR for Mono-Si PV and Poly-Si PV is obtained as 77.5 % and 72.42 %, respectively. Correspondingly, the average yearly CF is 16.78 % for Mono-Si PV and 15.44 % for Poly-Si PV. Results also show that Poly-Si PV degrades faster as compared to Mono-Si PV, with an annual average degradation rate of 0.67 % for Mono-Si PV and 0.73 % for Poly-Si PV. Finally, economic analysis of the two systems reveals that Mono-Si PV provides energy at a 9 % lower cost than Poly-Si PV, with a levelized cost of energy (LCOE) of 0.248 $/kWh for Mono-Si PV and 0.273 $/kWh for Poly-Si PV.

Fast data-dependence profiling through prior static analysis

Data-dependence profiling is a program-analysis technique for detecting parallelism opportunities in sequential programs. It captures data dependences that actually occur during program execution, filtering parallelism-preventing dependences that purely static methods assume only because they lack critical runtime information, such as the values of pointers and array indices. Profiling, however, suffers from high runtime overhead. In our earlier work, we accelerated data-dependence profiling by excluding polyhedral loops that can be handled statically using certain compilers and eliminating scalar variables that create statically-identifiable data dependences. In this paper, we combine the two methods and integrate them into DiscoPoP, a data-dependence profiler and parallelism discovery tool. Additionally, we detect reduction patterns statically and unify the three static analyses with the DiscoPoP framework to significantly diminish the profiling overhead and for a wider range of programs. We have evaluated our unified approaches with 49 benchmarks from three benchmark suites and two computer simulation applications. The evaluation results show that our approach reports fewer false positive and negative data dependences than the original data-dependence profiler and reduces the profiling time by at least 43%, with a median reduction of 76% across all programs. Also, we identify 40% of reduction cases statically and eliminate the associated profiling overhead for these cases.

Enhanced Wideband Frequency Estimation via FFT: Leveraging Polynomial Interpolation and Array Indexing

Enhanced Wideband Frequency Estimation via FFT: Leveraging Polynomial Interpolation and Array Indexing

Valorization of black grape pomace by pressurized hot water extraction and hydrolysis: Real-time online and in-line monitoring

The primary aim of this study was to maximize the value of black grape pomace by harnessing innovative and environmentally friendly extraction and hydrolysis technology on the biorefinery concept. This automated system seamlessly integrates pressurized hot water extraction (PHWE) and sequential subcritical water hydrolysis (SubCWH), complemented by inline purification through solid phase extraction (SPE) and online analysis via high-performance liquid chromatography (HPLC) equipped with photodiode array (PDA) and refractive index (RI) detectors. The results of this investigation revealed the presence of twelve anthocyanins, each exceeding a concentration of 3 mgEC3G gDBGP-1. By summing the concentration of these individual anthocyanins, a total yield of 47.6 mgEC3G gDBGP-1 was achieved, attributed to the utilization of acidified water as the solvent and adherence to optimal process conditions. The newly developed system demonstrated its efficacy in both PHWE and SubCWH of black grape pomace, coupled with inline SPE purification and real-time HPLC analysis of various natural compounds. The real-time monitoring capability facilitated swift and efficient responses, reducing processing time, minimizing solvent consumption, decreasing labor requirements, conserving energy, and mitigating environmental impact.

Impact of wrist-ankle acupuncture on propofol dosage under the dual monitoring of density spectrum array and anesthesia consciousness index in elderly patients undergoing urologic surgery: a sham-controlled randomized clinical trial.

Propofol is a widely used intravenous anesthetic in clinic. However, it is easy to cause serious circulatory fluctuation in elderly patients, so the dose should be reduced as appropriate. Studies have shown that wrist-ankle acupuncture (WAA) can reduce the dosage of propofol in patients undergoing painless endoscopy. Unfortunately, there is no report on whether WAA will reduce the dosage of propofol when used for anesthesia in elderly patients. The purpose of this study is to observe the effect of WAA on propofol dosage in elderly patients, and to provide a new method for maintaining circulatory stability in elderly patients under general anesthesia. From October 2022 to December 2022, Hebei Provincial Hospital of Traditional Chinese Medicine was selected. Forty-four elderly patients undergoing general anesthesia in urology department were randomly divided into two groups according to the complete random method with WAA group, consisting of 22 individuals, and non-WAA (NWAA) group, also consisting of 22 individuals. Both groups were treated with WAA or false needle acupuncture at the same site before anesthesia, respectively, and the needle was kept until the operation was finished. During the operation, the dosage of propofol was adjusted according to the depth of field monitoring density spectrum array (DSA) and anesthesia consciousness index (Ai) with anesthesia monitor. A total of 44 patients participated in this study, and all of them completed the experiment. There were no significant difference in sex, age, height, weight, duration of anesthesia, liver and kidney function, score of Fried frailty scale, activity of daily living (ADL), age-adjusted Charlson comorbidity index (aCCI) and mini-cognitive test (Mini-Cog) between the two groups (P>0.05), but the total dose of propofol (WAA =121.5, NWAA =170.5) mg and maintenance dose (WAA =1.02±0.55, NWAA =1.76±0.67) mg/kg/h, utilization rate of vasoactive drugs during operation, recovery time after anesthesia (WAA =2, NWAA =3) min and surgeon satisfaction (WAA =9, NWAA =8.5) had significant differences (P<0.05). Compared with NWAA group, WAA group could reduce the dosage of propofol in anesthesia for elderly patients with exocrine secretion and was beneficial to circulatory stability. Chinese Clinical Trial Registry (ID: ChiCTR2100054132).

Efficient Thermal-Stress Coupling Design of Chiplet-Based System with Coaxial TSV Array.

In this research, an efficient thermal-stress coupling design method for a Chiplet-based system with a coaxial through silicon via (CTSV) array is developed by combining the support vector machine (SVM) model and particle swarm optimization algorithm with linear decreasing inertia weight (PSO-LDIW). The complex and irregular relationship between the structural parameters and critical indexes is analyzed by finite element simulation. According to the simulation data, the SVM model is adopted to characterize the relationship between structural parameters and critical indexes of the CTSV array. Based on the desired critical indexes of the CTSV array, the multi-objective evaluation function is established. Afterwards, the structural parameters of the CTSV array are optimized through the PSO-LDIW algorithm. Finally, the effectiveness of the developed method is verified by the finite element simulation. The simulated peak temperature, peak stress of the Chiplet-based system, and peak stress of the copper column (306.16 K, 28.48 MPa, and 25.76 MPa) well agree with the desired targets (310 K, 30 MPa, and 25 MPa). Therefore, the developed thermal-stress coupling design method can effectively design CTSV arrays for manufacturing high-performance interconnect structures applied in Chiplet-based systems.

MM-FOOD: a high-dimensional index structure for efficiently querying content and concept of multimedia data

The semantic query problem is commonly called the semantic gap and is one of the significant problems in multimedia data retrieval. In this study, we focus on multimedia data retrieval by combining semantic information with data content to solve the semantic gap problem effectively. The main idea behind the combination of low-level content descriptors and the concept of multimedia data is to represent the content information with the semantic information by adding a low-level content descriptor as a new dimension to the index structure. This new dimension is represented by constructing an array index structure that uses a fuzzy clustering algorithm. Thus, a new high-dimensional index structure, named MM-FOOD, supporting querying of multimedia data, including fuzzy querying, is presented in this paper. This proposed index structure’s construction and query algorithms are explained throughout this paper. Our experiments show that our indexing mechanism is considerably efficient compared to the basic indexing approach, which stores low-level content and semantic concept descriptors in separate structures when the data size is large.

Realizing Mathematics of Arrays Operations as Custom Architecture Hardware-Software Co-Design Solutions

In embedded electronic system applications being developed today, complex datasets are required to be obtained, processed, and communicated. These can be from various sources such as environmental sensors, still image cameras, and video cameras. Once obtained and stored in electronic memory, the data is accessed and processed using suitable mathematical algorithms. How the data are stored, accessed, processed, and communicated will impact on the cost to process the data. Such algorithms are traditionally implemented in software programs that run on a suitable processor. However, different approaches can be considered to create the digital system architecture that would consist of the memory, processing, and communications operations. When considering the mathematics at the centre of the design making processes, this leads to system architectures that can be optimized for the required algorithm or algorithms to realize. Mathematics of Arrays (MoA) is a class of operations that supports n-dimensional array computations using array shapes and indexing of values held within the array. In this article, the concept of MoA is considered for realization in software and hardware using Field Programmable Gate Array (FPGA) and Application Specific Integrated Circuit (ASIC) technologies. The realization of MoA algorithms will be developed along with the design choices that would be required to map a MoA algorithm to hardware, software or hardware-software co-designs.

A type system for extracting functional specifications from memory-safe imperative programs

Verifying imperative programs is hard. A key difficulty is that the specification of what an imperative program does is often intertwined with details about pointers and imperative state. Although there are a number of powerful separation logics that allow the details of imperative state to be captured and managed, these details are complicated and reasoning about them requires significant time and expertise. In this paper, we take a different approach: a memory-safe type system that, as part of type-checking, extracts functional specifications from imperative programs. This disentangles imperative state, which is handled by the type system, from functional specifications, which can be verified without reference to pointers. A key difficulty is that sometimes memory safety depends crucially on the functional specification of a program; e.g., an array index is only memory-safe if the index is in bounds. To handle this case, our specification extraction inserts dynamic checks into the specification. Verification then requires the additional proof that none of these checks fail. However, these checks are in a purely functional language, and so this proof also requires no reasoning about pointers.

Towards Dynamic Verifiable Pattern Matching

Verifiable pattern matching enables users to obtain authenticated query results over outsourced data on an untrusted remote server. It is a fundamental problem in many security-critical big data applications, including big database search, human genome data search, text search, etc., especially when these applications are outsourced to third-party clouds. However, the state-of-the-art schemes do not yet support efficient data updates. In this work, we propose the first dynamic verifiable pattern matching scheme to support efficient data updates. The proposed scheme is built on two ideas: one is to embed unique randomness to decouple the character and its index in the outsourced data, enabling efficient data updates; the other is to reduce the verifiable pattern matching problem to a discrete set membership testing problem, which relies on the decoupling introduced in the first idea. Based on these two ideas, the proposed scheme first employs the suffix array index structure to search pattern matching queries. The scheme then authenticates the outsourced text using a newly designed authenticated data structure based on the RSA accumulator, which guarantees the verifiability of pattern matching query results. Data update is naturally supported using the RSA accumulator working on discrete sets. Based on the proposed design, we have prototyped a proof-of-concept for the proposed scheme and have conducted an extensive experimental evaluation. In addition to supporting efficient data update, our experimental results show that the proposed scheme incurs reduced verification cost in comparison with the baseline state-of-the-art scheme.

Bounds Checking on GPU

We present a simple compilation strategy for safety-checking array indexing in high-level languages on GPUs. Our technique does not depend on hardware support for abnormal termination, and is designed to be efficient in the non-failing case. We rely on certain properties of array languages, namely the absence of arbitrary cross-thread communication, to ensure well-defined execution in the presence of failures. We have implemented our technique in the compiler for the functional array language Futhark, and an empirical evaluation on 19 benchmarks shows that the geometric mean overhead of checking array indexes is respectively 4% and 6% on two different GPUs.

Integrated design and control of reactive distillation processes using the driving force approach

AbstractSuperior controllability of reactive distillation (RD) systems, designed at the maximum driving force (design‐control solution) is demonstrated in this article. Binary or multielement single or double feed RD systems are considered. Reactive phase equilibrium data, needed for driving force analysis and design of the RD system, is generated through an in‐house property prediction tool. Rigorous steady‐state simulation is carried out in ASPEN plus in order to verify that the predefined design targets and dynamics are met. A multiobjective performance function is employed to evaluate the performance of the RD system in terms of energy consumption, sustainability metrics (total CO2 footprint), and control performance. Controllability of the designed system is evaluated using indices like the relative gain array (RGA) and Niederlinski index (NI), to evaluate the degree of loop interaction, as well as through dynamic simulations using proportional‐integral (PI) controllers and model predictive controllers (MPC). The design‐control of the RD systems corresponding to other alternative designs that do not take advantage of the maximum driving force is also investigated. The analysis shows that the RD designs at the maximum driving force exhibit enhanced controllability and lower carbon footprint than the alternative RD designs.

STARE INTO THE FUTURE OF GEODATA INTEGRATIVE ANALYSIS.

Different kinds of observations feature different strengths, e.g. visible-infrared imagery for clouds and radar for precipitation, and when integrated better constrain scientific models and hypotheses. Even critical, fundamental operations such as cross-calibrations of related sensors operating on different platforms or orbits, e.g. spacecraft and aircraft, are integrative analyses. The great variety of Earth Science data types and the spatiotemporal irregularity of important low-level (ungridded) data has so far made their integration a customized, tedious process which scales in neither variety nor volume. Generic, higher-level (gridded) data products are easier to use, at the cost of being farther from the original observations and having to settle with grids, interpolation assumptions, and uncertainties that limit their applicability. The root cause of the difficulty in scalably bringing together diverse data is the current rectilinear geo-partitioning of Earth Science data into conventional arrays indexed using consecutive integer indices and then packaged into files. Such indices suffice for archival, search, and retrieval, but lack a common geospatial semantics, which is mitigated by adding on floating-point encoded longitude-latitude (lon-lat) information for registration. An alternative to floating-point lon-lat, the SpatioTemporal Adaptive Resolution Encoding (STARE) provides an encoding for geo-spatiotemporal location and neighborhood that transcends the use of files and native array indexing allowing diverse data to be organized on scalable, distributed computing and storage platforms.

LUT &amp; ATIM STUDY IN IMAGE PROCESSING TECHNIQUES

For real-time inspection of color, the LUT approach is the best of the techniques considered. In computer science, a lookup table is an array that replaces runtime computation with a simpler array indexing operation. The savings in terms of processing time can be significant, since retrieving a value from memory is often faster than undergoing an expensive computation or input &amp; output operation. The tables may be precalculated and stored in static program storage, as part of a program's initialization phase, or even stored in hardware in application-specific platforms. Lookup tables are also used extensively to validate input values by matching against a list of valid items in an array and, in some programming languages, may include pointer functions to process the matching input. The disadvantage of the LUT approach is the large memory size. The memory size has been reduced significantly by applying a multitude of ROM compression methods.

Static Checking of Array Index Out-of-Bounds Defects in C Programs Based on Taint Analysis

Static Checking of Array Index Out-of-Bounds Defects in C Programs Based on Taint Analysis

Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2.

Measurement of the location of molecules in tissues is essential for understanding tissue formation and function. Previously, we developed Slide-seq, a technology that enables transcriptome-wide detection of RNAs with a spatial resolution of 10 μm. Here we report Slide-seqV2, which combines improvements in library generation, bead synthesis and array indexing to reach an RNA capture efficiency ~50% that of single-cell RNA-seq data (~10-fold greater than Slide-seq), approaching the detection efficiency of droplet-based single-cell RNA-seq techniques. First, we leverage the detection efficiency of Slide-seqV2 to identify dendritically localized mRNAs in neurons of the mouse hippocampus. Second, we integrate the spatial information of Slide-seqV2 data with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex, identifying underlying genetic programs that were poorly sampled with Slide-seq. The combination of near-cellular resolution and high transcript detection efficiency makes Slide-seqV2 useful across many experimental contexts.

Abstract 16105: Depression Modulates Polygenic Risk of Cardiovascular and Cardiometabolic Disease

Introduction: Depression is associated with an increased risk of coronary artery disease (CAD). Whether depression modifies genetic risk of cardiovascular and cardiometabolic disease is unknown. Methods: We included genotyped, unrelated European ancestry individuals in the UK Biobank. Using genome-wide significant single nucleotide polymorphisms (SNPs) from studies external to the UK Biobank, we generated polygenic risk scores (PRS) for coronary artery disease (CAD, 74 SNPs), hypertension (75 SNPs), type 2 diabetes (T2D, 64 SNPs), atrial fibrillation (25 SNPs), and ischemic stroke (11 SNPs). Participants were stratified by PRS for each condition as low (quintile 1), intermediate (quintiles 2-4), and high (quintile 5) genetic risk. Cox models tested the association of depression frequency with each incident condition among individuals with high PRS, with adjustment for age, sex, the first 20 principal components, genotyping array, and Townsend deprivation index. Additional models further adjusted for health behaviors (exercise, tobacco and alcohol use, vegetable and fresh fruit intake) and tested associations across the PRS spectrum. Results: Among 348,083 individuals, 78,664 (22.6%) reported depression in the past 2 weeks, including 14,776 (4.2%) with depression more than half of days. Depression burden modified the risk of incident CAD across the spectrum of CAD polygenic risk (Figure 1A). Among individuals with high PRS, lack of depression was associated with lower risk of incident CAD (HR 0.70, 95% 0.58-0.86), hypertension (HR 0.58, 95% CI 0.50-0.67), T2D (HR 0.48, 95% CI 0.41-0.55), and atrial fibrillation (HR 0.74, 95% CI 0.62-0.89) compared to those with a high burden of depression. These risk reductions were minimally attenuated after further adjustment for health behaviors (Figure 1B). Conclusions: Lower burden of depression was associated was decreased risks of cardiovascular disease among individuals at high genetic cardiovascular risk.