A High-performance ECC Processor over Curve448 based on a Novel Variant of the Karatsuba Formula for Asymmetric Digit Multiplier

In this paper, we present a high-performance architecture for elliptic curve cryptography (ECC) over Curve448, which to the best of our knowledge, is the fastest implementation of ECC point multiplication over Curve448 to date. Firstly, we introduce a novel variant of the Karatsuba formula for asymmetric digit multiplier, suitable for typical DSP primitive with asymmetric input. It reduces the number of required DSPs compared to previous work and preserves the performance via full parallelization and pipelining. We then construct a 244-bit pipelined multiplier and interleaved fast reduction algorithm, yielding a total of 12 stages of pipelined modular multiplication with four stages of input delay. Additionally, we present an efficient Montgomery ladder scheduling with no additional register is required. The implementation on the Xilinx 7-series FPGA: Virtex-7, Kintex-7, Artix-7, and Zynq 7020 yields execution times of 0.12, 0.13, 0.24, and 0.24 ms, respectively. It increases the throughput by 242% compared to the best previous work on Zynq 7020 and by 858% compared to the best previous work on Virtex-7. Furthermore, the proposed architecture optimizes nearly 63% efficiency improvement in terms of Area×Time tradeoff. Lastly, we extend our architecture with well-known side-channel protections such as scalar blinding, base-point randomization, and continuous randomization

PCSK9 inhibitor in acute ischemic stroke patient receiving mechanical thrombectomy: early outcomes and safety

BackgroundLipid-lowering therapies are mainstays in reducing recurrence after acute ischemic stroke (AIS). Evolocumab, a Proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitor, is a promising lipid-lowering agent known to decrease LDL cholesterol and mitigate vascular events alongside statins. However, its effects on the early functional outcomes post-mechanical thrombectomy (MT) remain unclear. This study aimed to assess the short-term effects and incidence of bleeding events after the early, off-label use of PCSK9 inhibitors in AIS patients undergoing MT.MethodsWe retrospectively analyzed patients who had MT at a Regional Stroke Center from December 2018 to April 2023. Our primary outcome was discharge functional outcomes. Secondary outcomes included early neurologic deterioration (END), symptomatic intracerebral hemorrhage (sICH), 3-month functional outcomes, 3-month recurrence rate, and lipid profiles.ResultsOf 261 patients (mean age 69.2 ± 11.7, men 42.9%), 42 were administered evolocumab peri-procedurally. While baseline characteristics were similar between the two groups, evolocumab group demonstrated improved discharge outcomes, with a lower mean NIHSS (8.8 ± 6.8 vs. 12.4 ± 9.8, p = 0.02) and a higher percentage of patients with discharge mRS ≤ 3 (52.4% vs. 35.6%, p = 0.041). The 3-month follow-up show a non-significant trend toward an improved outcome in the evolocumab group. Multivariable analysis indicated that evolocumab had a potential impact on favorable discharge outcomes (aOR 1.98[0.94–4.22] for mRS ≤ 3 and 0.47[0.27–0.84] for lower ordinal mRS). Notably, evolocuamb users exhibited fewer instances of END and sICH, although they do not reach statistical significance. Additionally, the evolocumab group demonstrated potential benefits in LDL cholesterol reduction over time.ConclusionEarly use of evolocumab in AIS patients undergoing MT appeared to be safe and associated with better early functional outcomes. The potential benefit of the PCSK9 inhibitor shown here warrants further prospective studies

Group IIA secreted phospholipase A2 controls skin carcinogenesis and psoriasis by shaping the gut microbiota

Besides promoting inflammation by mobilizing lipid mediators, group IIA secreted phospholipase A2 (sPLA2-IIA) prevents bacterial infection by degrading bacterial membranes. Here, we show that, despite the restricted intestinal expression of sPLA2-IIA in BALB/c mice, its genetic deletion leads to amelioration of cancer and exacerbation of psoriasis in distal skin. Intestinal expression of sPLA2-IIA is reduced after treatment with antibiotics or under germ-free conditions, suggesting its upregulation by gut microbiota. Metagenome, transcriptome, and metabolome analyses have revealed that sPLA2-IIA deficiency alters the gut microbiota, accompanied by notable changes in the intestinal expression of genes related to immunity and metabolism, as well as in the levels of various blood metabolites and fecal bacterial lipids, suggesting that sPLA2-IIA contributes to shaping of the gut microbiota. The skin phenotypes in Pla2g2a–/– mice are lost (a) when they are cohoused with littermate WT mice, resulting in the mixing of the microbiota between the genotypes, or (b) when they are housed in a more stringent pathogen-free facility, where Pla2g2a expression in WT mice is low and the gut microbial compositions in both genotypes are nearly identical. Thus, our results highlight a potentially new aspect of sPLA2-IIA as a modulator of gut microbiota, perturbation of which affects distal skin responses

Voluntary exercise does not increase gastrointestinal motility but increases spatial memory, intestinal eNOS, Akt levels, and Bifidobacteria abundance in the microbiome

The interaction between the gut and brain is a great puzzle since it is mediated by very complex mechanisms. Therefore, the possible interactions of the brain–exercise–intestine–microbiome axis were investigated in a control (C, N = 6) and voluntarily exercised (VE, N = 8) middle-aged rats. The endurance capacity was assessed by VO2max on the treadmill, spatial memory by the Morris maze test, gastrointestinal motility by EMG, the microbiome by 16S RNA gene amplicon sequencing, caveolae by electron microscopy, and biochemical assays were used to measure protein levels and production of reactive oxygen species (ROS). Eight weeks of voluntary running increased VO2max, and spatial memory was assessed by the Morris maze test but did not significantly change the motility of the gastrointestinal tract or production of ROS in the intestine. The protein kinase B (Akt) and endothelial nitric oxide synthase (eNOS) protein levels significantly increased in the intestine, while peroxisome proliferator–activated receptor gamma coactivator 1 alpha (PGC-1α), mitochondrial transcription factor A (TFAM), nuclear respiratory factor 1 (NFR1), SIRT1, SIRT3, nicotinamide phosphoribosyl transferase (NAMPT), and nuclear factor κB (NF-κB) did not change. On the other hand, voluntary exercise increased the number of caveolae in the smooth muscles of the intestine and relative abundance of Bifidobacteria in the microbiome, which correlated with the Akt levels in the intestine. Voluntary exercise has systemic effects and the relationship between intestinal Akt and the microbiome of the gastrointestinal tract could be an important adaptive response

Current Situation and Issue of Industrial Accident Compensation Insurance

Industrial Accident Compensation Insurance (IACI) has a history of about 50 yr, and is the oldest social insurance system in Korea. After more than 20 times of revision improvements in benefits, its contents and claim systems have been upgraded. It became the protector of injured workers and their families, and at the same time became the system which could cope with both financial burden of employers and their responsibilities. However, there are some issues to be reformed to upgrade the IACI: 1) the problems in the approval system of occupational diseases, 2) quality improvement of workers' compensation medical care, 3) vocational rehabilitation and return to work, 4) workers' compensation premiums and out-of-pocket money of injured workers, 5) issues in application of IACI. Growth of IACI cannot be achieved by an effort of an individual. Efforts by workers, owners, and government, in addition to physicians and welfare professionals toward the same goal are required for the next level improvement of IACI

Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor

Aggression among pigs adversely affects economic returns and animal welfare in intensive pigsties. In this study, we developed a non-invasive, inexpensive, automatic monitoring prototype system that uses a Kinect depth sensor to recognize aggressive behavior in a commercial pigpen. The method begins by extracting activity features from the Kinect depth information obtained in a pigsty. The detection and classification module, which employs two binary-classifier support vector machines in a hierarchical manner, detects aggressive activity, and classifies it into aggressive sub-types such as head-to-head (or body) knocking and chasing. Our experimental results showed that this method is effective for detecting aggressive pig behaviors in terms of both cost-effectiveness (using a low-cost Kinect depth sensor) and accuracy (detection and classification accuracies over 95.7% and 90.2%, respectively), either as a standalone solution or to complement existing methods

Aging Detection of Electrical Point Machines Based on Support Vector Data Description

Electrical point machines (EPM) must be replaced at an appropriate time to prevent the occurrence of operational safety or stability problems in trains resulting from aging or budget constraints. However, it is difficult to replace EPMs effectively because the aging conditions of EPMs depend on the operating environments, and thus, a guideline is typically not be suitable for replacing EPMs at the most timely moment. In this study, we propose a method of classification for the detection of an aging effect to facilitate the timely replacement of EPMs. We employ support vector data description to segregate data of “aged” and “not-yet-aged” equipment by analyzing the subtle differences in normalized electrical signals resulting from aging. Based on the before and after-replacement data that was obtained from experimental studies that were conducted on EPMs, we confirmed that the proposed method was capable of classifying machines based on exhibited aging effects with adequate accuracy

Noise-Robust Sound-Event Classification System with Texture Analysis

Sound-event classification has emerged as an important field of research in recent years. In particular, investigations using sound data are being conducted in various industrial fields. However, sound-event classification tasks have become more difficult and challenging with the increase in noise levels. In this study, we propose a noise-robust system for the classification of sound data. In this method, we first convert one-dimensional sound signals into two-dimensional gray-level images using normalization, and then extract the texture images by means of the dominant neighborhood structure (DNS) technique. Finally, we experimentally validate the noise-robust approach by using four classifiers (convolutional neural network (CNN), support vector machine (SVM), k-nearest neighbors(k-NN), and C4.5). The experimental results showed superior classification performance in noisy conditions compared with other methods. The F1 score exceeds 98.80% in railway data, and 96.57% in livestock data. Besides, the proposed method can be implemented in a cost-efficient manner (for instance, use of a low-cost microphone) while maintaining high level of accuracy in noisy environments. This approach can be used either as a standalone solution or as a supplement to the known methods to obtain a more accurate solution

GAN-Based Video Denoising with Attention Mechanism for Field-Applicable Pig Detection System

Infrared cameras allow non-invasive and 24 h continuous monitoring. Thus, they are widely used in automatic pig monitoring, which is essential to maintain the profitability and sustainability of intensive pig farms. However, in practice, impurities such as insect secretions continuously pollute camera lenses. This causes problems with IR reflections, which can seriously affect pig detection performance. In this study, we propose a noise-robust, real-time pig detection system that can improve accuracy in pig farms where infrared cameras suffer from the IR reflection problem. The system consists of a data collector to collect infrared images, a preprocessor to transform noisy images into clean images, and a detector to detect pigs. The preprocessor embeds a multi-scale spatial attention module in U-net and generative adversarial network (GAN) models, enabling the model to pay more attention to the noisy area. The GAN model was trained on paired sets of clean data and data with simulated noise. It can operate in a real-time and end-to-end manner. Experimental results show that the proposed preprocessor was able to significantly improve the average precision of pig detection from 0.766 to 0.906, with an additional execution time of only 4.8 ms on a PC environment

The role of late sulfide saturation in the formation of a Cu- and Au-rich Magma: Insights from the Platinum Group Element Geochemistry of Niuatahi-Motutahi Lavas, Tonga Rear Arc

Magmas enriched in Cu and Au are likely to be the most prospective for magmatic–hydrothermal deposits of these metals. However, the mechanism that leads to the formation of metal-rich magmas is not well constrained. We report major, trace and platinum group element (PGE) data for the Niuatahi–Motutahi lavas, Tonga rear arc, with the aim of studying their petrogenesis with special emphasis on the evolution of chalcophile elements during magmatic differentiation. Major and trace element contents, including S and Cl, were also measured in glasses, phenocrysts and melt inclusions to complement the whole-rock data. The Niuatahi–Motutahi lavas are associated with Cu and Au mineralization and therefore provide an opportunity to investigate the characteristics of an ore-associated magmatic system. They show a wide compositional variation from basalts to dacites with MgO contents that vary between ∼14 and 1 wt %. The dacites can be subdivided into high-K and low-K dacites. Geochemical modeling and their mineralogy suggest that the low-K dacites are comagmatic with the basalts and evolved by fractional crystallization. Copper, Au and Pd behave incompatibly in the basalts and andesitic glasses, whereas they become compatible in the low-K dacite. In contrast, Pt, Rh, Ru and Ir are moderately compatible in the basalts and correlate negatively with MgO, but become strongly compatible in the dacites. The Cu, Au and PGE trends can be explained by fractional crystallization of a Pt-rich alloy in the basalts and andesitic glasses, followed by sulfide saturation in the low-K dacites. The high-K dacites may have evolved from a slightly different magma source; however, their chalcophile elements fractionated in a similar manner. Chlorine and S data for melt inclusions and glasses from the basalts and dacites suggest that water-rich volatile saturation occurred during evolution of the dacites. The Niuatahi–Motutahi dacites were enriched in Cu from 80 to 200 ppm and in Au from <1 to 7 ppb by fractional crystallization as the magma evolved from basalt through andesite to dacite. We suggest that late sulfide saturation allowed Cu and Au to become enriched by a factor of two in the Niuatahi–Motutahi dacites before volatile saturation and that this played an important role in the formation of the Cu- and Au-rich mineralization. This sulfide saturation history contrasts with that of the Honshu arc volcanic rocks, Japan, where sulfide saturation occurred early. The Honshu arc volcanic rocks are not associated with porphyry Cu or Au deposits, which we suggest is due to loss of most of the Cu and Au to an early immiscible sulfide phase.This research was supported by an Australian Research Council Discovery grant to Ian Campbell and a fund from the Ministry of Oceans and Fisheries of Korea (PM57580). Three-month stipend for Jung-Woo Park was supported by Australian Research Council grant to Oliver Nebel in 2012