Search Results (19)

Cucumber is a vegetable crop of economic importance in Mexico. In 2023, fresh or frozen cucumber and pickle international sales reached USD 783M, placing Mexico in second rank among countries with the highest currency inflow in the world. This crop is mostly grown under protected environments with new production technologies, including rootstocks that are tolerant to biotic and abiotic factors that limit the yield and quality of the harvest. Therefore, the goal of this work was to assess three cucurbits as rootstocks (Cucurbita maxima, Cucurbita moschata and Citrullus lanatus), as well as studying the response of cucumber crop to the tested rootstocks. The following treatments were assessed: T1:PSP = cucumber Cv. Paraizo F1 without rootstock; T2:P/MA = cucumber grafted over Cucurbita maxima; T3:P/MO = cucumber grafted over Cucurbita moschata; T4:P/CL = cucumber grafted over Citrullus lanatus Citroides Var. The assessed variables included the number of fruits per plant (NFPP), fruit weight per plant (PFPP), average fruit weight (PPF), plant dry weight (PSP), xylem vessel area (AVX), number of xylem vessels (NVX), vascular bundle area (AHV) and number of vascular bundles (NHV) in roots (R), basal stalk (TB) and apical stalk (AT). Significant differences among treatments were found in the results for variables: NFPP, highlighting that T2:P/MA was superior by 46.15% versus T1:PSP and by 67.69% versus T3:P/MO. Regarding PFPP, T2:P/MA achieved the highest weight (5445 g), as it proved superior by 99.45% than the cucumber without rootstock (T1:PSP). Regarding PSP, T2:P/MA achieved the highest weight (196.65 g), significantly exceeding T1 by 137.5%. Regarding AVXR, T4:P/CL had the highest value (30,063 µm²). Regarding NHVR, watermelon had (T4:P/CL) 39.33% more vascular bundles than the root system of cucumber (T1:PSP). Treatments T2:P/MA and T4:P/CL had the highest values at AVXTB, while for variable NVXTB, treatments T3:P/MO and T2:P/MA were almost equal, surpassing non-grafted cucumber by 175.47%. However, T2:P/MA showed the greatest AHVTB, and T1:PSP was significantly superior to T3:P/MO, by 34.93%, for NHVTB. Furthermore, positive and significant correlations were found among PFPP, AHVR, and AVXTB, as well as among PSP, AVXTB, and AHVTB. Therefore, we may say that having a larger area of vascular vessels in the roots and a larger area of xylem vessels in the basal stalk leads to higher fruit yields per plant. In the same vein, the use of rootstocks is a sustainable alternative to increase fruit yield. Full article

Currently, cryptographic hash functions are widely used in various applications, including message authentication codes, cryptographic random generators, digital signatures, key derivation functions, and post-quantum algorithms. Notably, they play a vital role in establishing secure communication between servers and clients. Specifically, servers often need to compute a large number of hash functions simultaneously to provide smooth services to connected clients. In this paper, we present highly optimized parallel implementations of Lightweight Secure Hash (LSH), a hash algorithm developed in Korea, on server sides. To optimize LSH performance, we leverage two parallel architectures: AVX-512 on high-end CPUs and NVIDIA GPUs. In essence, we introduce a word-level parallel processing design suitable for AVX-512 instruction sets and a data parallel processing design appropriate for the NVIDIA CUDA platform. In the former approach, we parallelize the core functions of LSH using AVX-512 registers and instructions. As a result, our first implementation achieves a performance improvement of up to 50.37% compared to the latest LSH AVX-2 implementation. In the latter approach, we optimize the core operation of LSH with CUDA PTX assembly and apply a coalesced memory access pattern. Furthermore, we determine the optimal number of blocks/threads configuration and CUDA streams for RTX 2080Ti and RTX 3090. Consequently, in the RTX 3090 architecture, our optimized CUDA implementation achieves about a 180.62% performance improvement compared with the initially ported LSH implementation to the CUDA platform. As far as we know, this is the first work on optimizing LSH with AVX-512 and NVIDIA GPU. The proposed implementation methodologies can be used alone or together in a server environment to achieve the maximum throughput of LSH computation. Full article

For classified and sensitive electronic documents within the scope of enterprises and organizations, in order to standardize and strengthen the confidentiality management of enterprises and meet the actual needs of secret text classification, a document automatic classification optimization method based on keyword retrieval and the kNN classification algorithm is proposed. The method supports keyword classification management, provides users with keywords of multiple risk levels, and then combines a matching scanning algorithm to label keywords of different levels. The text with labels is used as the training set of the kNN algorithm to classify the target text and realize the classification protection of text data. Aimed at solving the shortcomings of large feature vector dimension, low classification efficiency, and low accuracy in existing kNN text classification methods, an optimization method is proposed using a feature selection algorithm and a kNN algorithm based on an AVX instruction set to realize real-time classification of massive texts. By constructing a keyword dictionary and an optimized feature vector, parallel calculation of the feature vector weight and distance vector is realized, and the accuracy and efficiency of text classification are improved. The experimental results show that the multi-classification effect of the feature selection algorithm used in this paper, tf-DE, is better than that of the traditional tf-idf algorithm, and the classification effect of kNN is comparable to that of the support vector machine (SVM) algorithm. With the increase in feature vector dimensions, the classification effect of the text classification algorithm is improved and the classification time also increases linearly. The AVX-256 acceleration method takes about 55% of the time of the original version, thus verifying the effect of multi-classification of massive texts for document confidentiality management. Full article

In order to cope with the massive scale of traffic and reduce the memory overhead of traffic statistics, the traffic statistics method based on the Sketch algorithm has become a research hotspot for traffic statistics. This paper studies the problem of the top-k flow statistics based on the Sketch algorithm and proposes a method to estimate the flow heat from massive network traffic using the Sketch algorithm and identify the kth flow with the highest heat by using a bitonic sort algorithm. In view of the performance difficulties of applying multiple hash functions in the implementation of the Sketch algorithm, the Single-Instruction-Multiple-Data (SIMD) instruction set is adopted to improve the performance of the Sketch algorithm so that SIMD instructions can process multiple fragments of data in a single step, implement multiple hash operations at the same time, compare and sort multiple flow tables at the same time. Thus, the throughput of the execution task is improved. Firstly, the elements of data flow are described and stored in the form of vectors, while the construction, analysis, and operation of data vectors are realized by SIMD instructions. Secondly, the multi-hash operation is simplified into a single vector operation, which reduces the CPU computing resource consumption of the Sketch algorithm. At the same time, the SIMD instruction set is used to optimize the parallel comparison operation of the flow table in a bitonic sort algorithm. Finally, the SIMD instruction set is used to optimize the functions in the Sketch algorithm and top-k sorting algorithm program, and the optimized code is tested and analyzed. The experimental results show that the time consumed by the advanced vector extensions (AVX)-instructions-optimized version has a significant reduction compared to the original version. When the length of KEY is 96 bytes, the instructions consumed by multiple hash functions account for less in the entire Sketch algorithm, and the time consumed by the optimized version of AVX is about 67.2% of that in the original version. As the length of KEY gradually increases to 256 bytes, the time consumed by the optimized version of AVX decreases to 53.8% of the original version. The simulation results show that the AVX optimization algorithm is effective in improving the measurement efficiency of network flow. Full article

Background: Unripe avocados (Persea americana) are naturally enriched in mannoheptulose (MH), which is a candidate caloric restriction mimetic. Objectives: To evaluate the effects of a diet supplement made from unripe avocado on glucose tolerance, and cardiometabolic risk factors in free-living nondiabetic adults with obesity. Methods: In a double-blinded, randomised controlled trial, 60 adults (female n = 47, age 48 ± 13 years, BMI 34.0 ± 2.6 kg/m²) were stratified by sex and randomised to avocado extract (AvX, 10 g finely ground, freeze-dried unripe avocado) or placebo (10 g finely ground cornmeal plus 5% spinach powder) daily, for 12 weeks. The primary outcome was a change in glucose area under the curve (AUC) in response to a 75 g oral glucose tolerance test. A post-hoc analysis was subsequently performed in a subgroup with insulin AUC above the median of baseline values after removal of participants >2 SD from the mean. Results: There were no between-group differences in glucose AUC (p = 0.678), insulin AUC (p = 0.091), or cardiovascular outcomes. In the subgroup analysis, insulin AUC was lower in AxV versus placebo (p = 0.024). Conclusions: Daily consumption of unripe avocado extract enriched in MH did not alter glucose tolerance or insulin sensitivity in nondiabetic adults with obesity, but the data provided preliminary evidence for a benefit in insulin AUC in a subgroup of participants with elevated baseline postprandial insulin levels. Full article

As Mobile Communication and Internet Systems (MCIS) have rapidly developed, security issues related to MCIS have become increasingly important. Therefore, the development and research of security technologies for mobile communication and internet systems are actively being conducted. Hash-Based Signature (HBS) uses a hash function to construct a digital signature scheme, where its security is guaranteed by the collision resistance of the hash function used. To provide sufficient security in the post-quantum environment, the length of hash should be satisfied for the security requirement. Modern HBS can be classified into stateful and stateless schemes. Two representative stateful and stateless HBS are eXtended Merkle Signature Scheme(XMSS) and SPHINCS${}^{+}$, respectively. In this paper, we propose two HBS schemes: K-XMSS and K-SPHINCS${}^{+}$, which replace internal hash functions of XMSS and SPHINCS${}^{+}$ with Korean cryptography algorithms. K-XMSS is a stateful signature, while K-SPHINCS${}^{+}$ is its stateless counterpart. We showcase the reference implementation of K-XMSS and K-SPHINCS${}^{+}$ employing Lightweight Secure Hash (LSH) and two hash functions based on block ciphers (i.e., CHAM and LEA) as the internal hash function. In addition, K-XMSS and K-SPHINCS${}^{+}$ using Advanced Vector Extensions 2 (AVX2) have been provided, demonstrating that they can be optimized for better performance using advanced implementation techniques than previous approaches. Full article

Parallel implementations of algorithms are usually compared with single-core CPU performance. The advantage of multicore vector processors decreases the performance gap between GPU and CPU computation, as shown in many recent pieces of research. With the AVX-512 instruction set, there will be another performance boost for CPU computations. The availability of parallel code running on CPUs made them much easier and more accessible than GPUs. This article compares the performances of parallel implementations of the particle swarm optimization algorithm. The code was written in C++, and we used various techniques to obtain parallel execution through Advanced Vector Extensions. We present the performance on various benchmark functions and different problem configurations. The article describes and compares the performance boost gained from parallel execution on CPU, along with advantages and disadvantages of parallelization techniques. Full article

The generation of energy-efficient parallel scientific codes became very important in the time of carbon footprint reduction. In this paper, we briefly present our latest particle-in-cell code with the results of a numerical simulation of plasma dynamics in an open trap. This code can be auto-vectorized by the Fortran compiler for Intel Xeon processors with AVX-512 instructions such as Intel Xeon Phi and the highest series of all generations of Intel Xeon Scalable processors. Efficient use of processor architecture is the main feature of an energy-efficient solution. We present a step-by-step methodology of energy consumption calculation using Intel hardware features and Intel VTune software. We also give an estimated value of carbon footprint with the impact of high-performance water cooled hardware. The Power Usage Effectiveness (PUE) in the case of high-performance water cooled hardware is equal to 1.03–1.05, and is up to 1.3 in the case of air-cooled systems. This means that power consumption of liquid cooled systems is lower than that air-cooled ones by up to 25%. All these factors play an important role in the carbon footprint reduction problem. Full article

The paper presents a new hydrodynamical code, OMPEGAS, for the 3D simulation of astrophysical flows on shared memory architectures. It provides a numerical method for solving the three-dimensional equations of the gravitational hydrodynamics based on Godunov’s method for solving the Riemann problem and the piecewise parabolic approximation with a local stencil. It obtains a high order of accuracy and low dissipation of the solution. The code is implemented for multicore processors with vector instructions using the OpenMP technology, Intel SDLT library, and compiler auto-vectorization tools. The model problem of simulating a star explosion was used to study the developed code. The experiments show that the presented code reproduces the behavior of the explosion correctly. Experiments for the model problem with a grid size of $128\times 128\times 128$ were performed on an 16-core Intel Core i9-12900K CPU to study the efficiency and performance of the developed code. By using the autovectorization, we achieved a 3.3-fold increase in speed in comparison with the non-vectorized program on the processor with AVX2 support. By using multithreading with OpenMP, we achieved an increase in speed of 2.6 times on a 16-core processor in comparison with the vectorized single-threaded program. The total increase in speed was up to ninefold. Full article

Beginning at 16 weeks of age and continuing for 44 weeks, male C57BL/6J were fed either a control (CON) diet; a high-fat (HF) diet (60% unsaturated); or the HF diet containing an extract of unripe avocados (AvX) enriched in the 7-carbon sugar mannoheptulose (MH), designed to act as a glycolytic inhibitor (HF + MH). Compared to the CON diet, mice on the HF diet exhibited higher body weights; body fat; blood lipids; and leptin with reduced adiponectin levels, insulin sensitivity, VO2max, and falls from a rotarod. Mice on the HF + MH diet were completely protected against these changes in the absence of significant diet effects on food intake. Compared to the CON diet, oxidative stress was also increased by the HF diet indicated by higher levels of total reactive oxygen species, superoxide, and peroxynitrite measured in liver samples by electron paramagnetic resonance spectroscopy, whereas the HF + MH diet attenuated these changes. Compared to the CON, the HF diet increased signaling in the mechanistic target of the rapamycin (mTOR) pathway, and the addition of the MH-enriched AvX to this diet attenuated these changes. Beyond generating further interest in the health benefits of avocados, these results draw further new attention to the effects of this rare sugar, MH, as a botanical intervention for preventing obesity. Full article

Cytosolic phospholipase A2α (cPLA2α) is the rate-limiting enzyme in releasing arachidonic acid and biosynthesis of its derivative eicosanoids. Thus, the catalytic activity of cPLA2α plays an important role in cellular metabolism in healthy as well as cancer cells. There is mounting evidence suggesting that cPLA2α is an interesting target for cancer treatment; however, it is unclear which cancers are most relevant for further investigation. Here we report the relative expression of cPLA2α in a variety of cancers and cancer cell lines using publicly available datasets. The profiling of a panel of cancer cell lines representing different tissue origins suggests that hematological malignancies are particularly sensitive to the growth inhibitory effect of cPLA2α inhibition. Several hematological cancers and cancer cell lines overexpressed cPLA2α, including multiple myeloma. Multiple myeloma is an incurable hematological cancer of plasma cells in the bone marrow with an emerging requirement of therapeutic approaches. We show here that two cPLA2α inhibitors AVX420 and AVX002, significantly and dose-dependently reduced the viability of multiple myeloma cells and induced apoptosis in vitro. Our findings implicate cPLA2α activity in the survival of multiple myeloma cells and support further studies into cPLA2α as a potential target for treating hematological cancers, including multiple myeloma. Full article

Background: Recent cost-utility analysis (CUA) models for onasemnogene abeparvovec (Zolgensma^®, formerly AVXS-101) in spinal muscular atrophy type 1 (SMA1) differ on key assumptions and results. Objective: To compare the manufacturer’s proprietary CUA model to the model published by the Institute for Clinical and Economic Review (ICER), and to update the manufacturer’s model with long-term follow-up data and some key ICER assumptions. Study design: We updated a recent CUA evaluating value for money in cost per incremental Quality-adjusted Life Year (QALY) of onasemnogene abeparvovec versus nusinersen (Spinraza^®) or best supportive care (BSC) in symptomatic SMA1 patients, and compared it to the ICER model. Setting/Perspective: USA/Commercial payer. Participants: Children aged <2 years with SMA1. Interventions: Onasemnogene abeparvovec, a single-dose gene replacement therapy, versus nusinersen, an antisense oligonucleotide, versus BSC. Main outcome measure: Incremental-cost effectiveness ratio and value-based price using traditional thresholds for general medicines in the US. Results: Updated survival (undiscounted) predicted by the model was 37.60 years for onasemnogene abeparvovec compared to 12.10 years for nusinersen and 7.27 years for BSC. Updated quality-adjusted survival using ICER’s utility scores and discounted at 3% were 13.33, 2.85, and 1.15 discounted QALYs for onasemnogene abeparvovec, nusinersen, and BSC, respectively. Using estimated net prices, the discounted lifetime cost/patient was $3.93 M for onasemnogene abeparvovec, $4.60 M for nusinersen, and $1.96 M for BSC. The incremental cost per QALY gained for onasemnogene abeparvovec was dominant against nusinersen and $161,648 against BSC. These results broadly align with the results of the ICER model, which predicted a cost per QALY gained of $139,000 compared with nusinersen, and $243,000 compared with BSC (assuming a placeholder price of $2 M for onasemnogene abeparvovec), differences in methodology notwithstanding. Exploratory analyses in presymptomatic patients were similar. Conclusion: This updated CUA model is similar to ICER analyses comparing onasemnogene abeparvovec with nusinersen in the symptomatic and presymptomatic SMA populations. At a list price of $2.125 M, onasemnogene abeparvovec is cost-effective compared to nusinersen for SMA1 patients treated before age 2 years. When compared to BSC, cost per QALY of onasemnogene abeparvovec is higher than commonly used thresholds for therapies in the USA ($150,000 per QALY). Full article

AR-15512 (formerly known as AVX-012 and WS-12) is a TRPM8 receptor agonist currently in phase 2b clinical trials for the treatment of dry eye. This bioactive compound with menthol-like cooling activity has three stereogenic centers, and its final structure and absolute configuration, (1R,2S,5R), have been previously solved by cryo-electron microscopy. The route of synthesis of AR-15512 has also been reported, revealing that epimerization processes at the C-1 can occur at specific stages of the synthesis. In order to confirm that the desired configuration of AR-15512 does not change throughout the process and to discard the presence of the enantiomer in the final product due to possible contamination of the initial starting material, both the enantiomer of AR-15512 and the diastereomer at the C-1 were synthesized and fully characterized. In addition, the absolute configuration of the (1S,2S,5R)-diastereomer was determined by X-ray crystallographic analysis, and new HPLC methods were designed and developed for the identification of the two stereoisomers and their comparison with the clinical candidate AR-15512. Full article

As a regulator of cellular inflammation and proliferation, cytosolic phospholipase A₂ α (cPLA₂α) is a promising therapeutic target for psoriasis; indeed, the cPLA₂α inhibitor AVX001 has shown efficacy against plaque psoriasis in a phase I/IIa clinical trial. To improve our understanding of the anti-psoriatic properties of AVX001, we sought to determine how the compound modulates inflammation and keratinocyte hyperproliferation, key characteristics of the psoriatic epidermis. We measured eicosanoid release from human peripheral blood mononuclear cells (PBMC) and immortalized keratinocytes (HaCaT) and studied proliferation in HaCaT grown as monolayers and stratified cultures. We demonstrated that inhibition of cPLA₂α using AVX001 produced a balanced reduction of prostaglandins and leukotrienes; significantly limited prostaglandin E₂ (PGE₂) release from both PBMC and HaCaT in response to pro-inflammatory stimuli; attenuated growth factor-induced arachidonic acid and PGE₂ release from HaCaT; and inhibited keratinocyte proliferation in the absence and presence of exogenous growth factors, as well as in stratified cultures. These data suggest that the anti-psoriatic properties of AVX001 could result from a combination of anti-inflammatory and anti-proliferative effects, probably due to reduced local eicosanoid availability. Full article

Remote sensing data has known an explosive growth in the past decade. This has led to the need for efficient dimensionality reduction techniques, mathematical procedures that transform the high-dimensional data into a meaningful, reduced representation. Projection Pursuit (PP) based algorithms were shown to be efficient solutions for performing dimensionality reduction on large datasets by searching low-dimensional projections of the data where meaningful structures are exposed. However, PP faces computational difficulties in dealing with very large datasets—which are common in hyperspectral imaging, thus raising the challenge for implementing such algorithms using the latest High Performance Computing approaches. In this paper, a PP-based geometrical approximated Principal Component Analysis algorithm (gaPCA) for hyperspectral image analysis is implemented and assessed on multi-core Central Processing Units (CPUs), Graphics Processing Units (GPUs) and multi-core CPUs using Single Instruction, Multiple Data (SIMD) AVX2 (Advanced Vector eXtensions) intrinsics, which provide significant improvements in performance and energy usage over the single-core implementation. Thus, this paper presents a cross-platform and cross-language perspective, having several implementations of the gaPCA algorithm in Matlab, Python, C++ and GPU implementations based on NVIDIA Compute Unified Device Architecture (CUDA). The evaluation of the proposed solutions is performed with respect to the execution time and energy consumption. The experimental evaluation has shown not only the advantage of using CUDA programming in implementing the gaPCA algorithm on a GPU in terms of performance and energy consumption, but also significant benefits in implementing it on the multi-core CPU using AVX2 intrinsics. Full article