Optimized Vectorization Implementation of CRYSTALS-Dilithium

CRYSTALS-Dilithium is a lattice-based signature scheme to be standardized by NIST as the primary post-quantum signature algorithm. In this work, we make a thorough study of optimizing the implementations of Dilithium by utilizing the Advanced Vector Extension (AVX) instructions, specifically AVX2 and the latest AVX512. We first present an improved parallel small polynomial multiplication with tailored early evaluation (PSPM-TEE) to further speed up the signing procedure, which results in a speedup of 5\%-6\% compared with the original PSPM Dilithium implementation. We then present a tailored reduction method that is simpler and faster than Montgomery reduction. Our optimized AVX2 implementation exhibits a speedup of 3\%-8\% compared with the state-of-the-art of Dilithium AVX2 software. Finally, for the first time, we propose a fully and highly vectorized implementation of Dilithium using AVX-512. This is achieved by carefully vectorizing most of Dilithium functions with the AVX512 instructions in order to improve efficiency both for time and for space simultaneously. With all the optimization efforts, our AVX-512 implementation improves the performance by 37.3\%/50.7\%/39.7\% in key generation, 34.1\%/37.1\%/42.7\% in signing, and 38.1\%/38.7\%/40.7\% in verification for the parameter sets of Dilithium2/3/5 respectively. To the best of our knowledge, our AVX512 implementation has the best performance for Dilithium on the Intel x64 CPU platform to date.Comment: 13 pages, 5 figure

Object-fabrication Targeted Attack for Object Detection

Recent researches show that the deep learning based object detection is vulnerable to adversarial examples. Generally, the adversarial attack for object detection contains targeted attack and untargeted attack. According to our detailed investigations, the research on the former is relatively fewer than the latter and all the existing methods for the targeted attack follow the same mode, i.e., the object-mislabeling mode that misleads detectors to mislabel the detected object as a specific wrong label. However, this mode has limited attack success rate, universal and generalization performances. In this paper, we propose a new object-fabrication targeted attack mode which can mislead detectors to `fabricate' extra false objects with specific target labels. Furthermore, we design a dual attention based targeted feature space attack method to implement the proposed targeted attack mode. The attack performances of the proposed mode and method are evaluated on MS COCO and BDD100K datasets using FasterRCNN and YOLOv5. Evaluation results demonstrate that, the proposed object-fabrication targeted attack mode and the corresponding targeted feature space attack method show significant improvements in terms of image-specific attack, universal performance and generalization capability, compared with the previous targeted attack for object detection. Code will be made available

Recent Progress in the Fabrication of Low Dimensional Nanostructures via Surface-Assisted Transforming and Coupling

Polymerization of functional organics into covalently cross-linked nanostructures via bottom-up approach on solid surfaces has attracted tremendous interest recently, due to its appealing potentials in fabricating novel and artificial low dimensional nanomaterials. While there are various synthetic approaches being proposed and explored, this paper reviews the recent progress of on-surface coupling strategies towards the synthesis of low dimensional nanostructures ranging from 1D nanowire to 2D network and describes their advantages and drawbacks during on-surface process and phase transformations, for example, from molecular self-assembly to on-surface polymerization. Specifically, Ullmann reaction is discussed in detail and the mechanism governing nanostructures’ transforming effect by surface treatment is exploited. In the end, it is summarized that the hierarchical polymerization combined with Ullmann coupling makes it possible to realize the selection of different synthetic pathways and phase transformations and obtain novel organometallic nanowire with metalorganic bonding

RETRACTED: Relationship between serum TGF- β 1, MMP-9 and IL-1β and pathological features and prognosis in breast cancer

To investigate the levels of serum transforming growth factor-β 1 (TGF-β1), Matrix metalloproteinase-9 (MMP-9) and Interleukin-1 β (IL-1 β) in breast cancer (BC), and analyzing their relationship with pathological features and prognosis. Retrospective analysis of 86 subjects with BC (BC subgroup) and another 50 healthy subjects (control subgroup) during the same period were included. The clinical data were collected. In this research, in BC subgroup, The levels of serum TGF- β 1, MMP-9 and IL-1 β were significantly higher than those in control subgroup. The levels of TGF- β 1 and MMP-9 in serum of BC subjects was correlated with clinical stage, histological grade, lymph node metastasis and molecular classification, but not with age, tumor size and menopausal status. The level of serum IL-1 β was related to tumor size, clinical stage, histological grade and lymph node metastasis. Multivariate Logistic regression analysis showed that the high level of serum TGF- β1 and MMP-9 was independent risk factors for BC. High level of serum IL-1 β was not an independent risk factor for BC. The 3-year disease-free survival rate in high TGF- β1 subgroup and high MMP-9 subgroup was significantly lower than that in low TGF- β 1 subgroup and low MMP- 9 subgroup. To conclude, serum TGF- β 1, MMP-9 and IL-1β are highly expressed in BC, and the subjects with elevated serum levels of TGF- β 1 and MMP-9 suggests poor prognosis

Multi-layer model simulation and data assimilation in the Serangoon Harbor of Singapore

In June of 2009, a sea trial was carried out around Singapore to study and monitor physical, biological and chemical oceanographic parameters. Temperature, salinity and velocities were collected from multiple vehicles. The extensive data set collected in the Serangoon Harbour provides an opportunity to study barotropic and baroclinic circulation in the harbour and to apply data assimilation methods in the estuarine area. In this study, a three-dimensional, primitive equation coastal ocean model (FVCOM) with a number of vertical layers is used to simulate barotropic and baroclinic flows and reconstruct the vertical velocity structures. The model results are validated with in situ ADCP observations to assess the realism of the model simulations. EnKF data assimilation method is successively implemented to assimilate all the available ADCP data, and thus correct for the model forecast deficiencies.Singapore. National Research FoundationSingapore-MIT AllianceSingapore-MIT Alliance. Center for Environmental Sensing and Monitorin

Comparison of CMS measurements with predictions at NLO applying the Parton Branching Method and PYTHIA

In August 2023, more than 30 students joined the Special Remote DESY summer-school to work on projects of importance for LHC experiments. In a dedicated initiative, analyses that had not been incorporated into the RIVET package were implemented and verified. Here, a brief description of the accomplished work is given, and a comparison of the measurements with predictions obtained from matched standard parton shower Monte Carlo event generators as well as with those obtained from Parton-Branching TMDs with corresponding parton showers are presented

Development of Lysine-Targeted Probes for Protein Kinases

Thesis (Master's)--University of Washington, 2022Lysine is one of the most common amino acids in the proteome, but relatively few probes have been designed to label specific lysine. Properties of lysine such as its low intrinsic nucleophilicity and its ubiquity has made it a challenge to develop probes that label active site lysine in protein kinases. In this thesis, I describe the design, synthesis, and testing of three different lysine-targeted type I kinases probes based on different scaffolds. Two of these probes are fluorosulfates (Probe 1 and Probe 2) displayed from either a quinazoline or pyridine-pyrimidine scaffold. The third (Probe 3) is a sulfonyl fluoride probe with a trans- cyclooctyne (TCO) click handle, which is based on the previously developed probe XO44 probe. Based on lysate labeling experiments and sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis, neither alkyne-containing nor TCO-containing versions of Probe 1 and Probe 2 are able to specifically label protein kinases. Lysate labelingexperiments followed by liquid chromatography tandem mass spectrometry (LC/MS/MS) demonstrate that Probe 3 can specifically label at least 7 protein kinases. Together, these results represent a comprehensive analysis of lysine-targeted type I kinases probes. The supplementary spreadsheets include the whole proteomic data for Probe 3 LC/MS/MS pull-down experiment (‘Proteomic data for Probe 3’); the protein kinases with non-significant label free intensities difference between the ‘Probe 3’ group and the ‘Probe 3 + Competitor 2’ group (‘Non-significant difference PKs’); the protein kinases only contain one label free intensity in the ‘Probe 3’ group (‘Non-representative PKs’); the protein kinases labeled by Probe 3 (‘Labeled PKs’)

Dynamical Behavior of Pure Spin Current in Organic Materials

Abstract Growing concentration on the novel information processing technology and low‐cost, flexible materials make the spintronics and organic materials appealing for the future interdisciplinary investigations. Organic spintronics, in this context, has arisen and witnessed great advances during the past two decades owing to the continuous innovative exploitation of the charge‐contained spin polarized current. Albeit with such inspiring facts, charge‐absent spin angular momentum flow, namely pure spin currents (PSCs) are less probed in organic functional solids. In this review, the past exploring journey of PSC phenomenon in organic materials are retrospected, including non‐magnetic semiconductors and molecular magnets. Starting with the basic concepts and the generation mechanism for PSC, the representative experimental observations of PSC in the organic‐based networks are subsequently demonstrated and summarized, by accompanying explicit discussion over the propagating mechanism of net spin itself in the organic media. Finally, future perspectives on PSC in organic materials are illustrated mainly from the material point of view, including single molecule magnets, complexes for the organic ligands framework as well as the lanthanide metal complexes, organic radicals, and the emerging 2D organic magnets

An Intelligent Inspection Robot for Underground Cable Trenches Based on Adaptive 2D-SLAM

With the rapid growth of underground cable trenches, the corresponding inspections become a heavy burden, and an intelligent inspection robot for automatic examinations in underground cable trenches would be a suitable solution. To achieve this, this paper establishes one new navigation methodology for intelligent inspection robots, especially when applied in complex scenarios and the corresponding hardware. Firstly, to map the underground trenches with higher precision, an improved graph optimization cartographer-SLAM algorithm is proposed, which is based on the combination of depth camera and LIDAR. The depth image is converted into pseudo laser data, and fused with LIDAR data for calibration. Secondly, to overcome the low precision of the Laser odometer due to the uneven ground, an adaptive keyframe selection method is designed. Thirdly, the forward A* model is presented, which has been adjusted in three aspects, including the convergence of node searching, the cost function, and the path smoothness, to adapt to the narrow underground environment for global path planning. Fourthly, to realize dynamic obstacle avoidance, an improved fusion scheme is built to integrate the proposed global path planning algorithm and the dynamic window approach (DWA). In the case study, the simulation experiments showed the advantage of the forward A* algorithm over the state-of-the-art algorithm in both time consumption and the number of inflection points generated, the field tests illustrated the effect of the fusion of depth camera images and LIDAR. Hence, the feasibility of this navigation methodology can be verified, and the average length of path and time consumption decreased by 6.5% and 17.8%, respectively, compared with the traditional methods

An Intelligent Inspection Robot for Underground Cable Trenches Based on Adaptive 2D-SLAM

With the rapid growth of underground cable trenches, the corresponding inspections become a heavy burden, and an intelligent inspection robot for automatic examinations in underground cable trenches would be a suitable solution. To achieve this, this paper establishes one new navigation methodology for intelligent inspection robots, especially when applied in complex scenarios and the corresponding hardware. Firstly, to map the underground trenches with higher precision, an improved graph optimization cartographer-SLAM algorithm is proposed, which is based on the combination of depth camera and LIDAR. The depth image is converted into pseudo laser data, and fused with LIDAR data for calibration. Secondly, to overcome the low precision of the Laser odometer due to the uneven ground, an adaptive keyframe selection method is designed. Thirdly, the forward A* model is presented, which has been adjusted in three aspects, including the convergence of node searching, the cost function, and the path smoothness, to adapt to the narrow underground environment for global path planning. Fourthly, to realize dynamic obstacle avoidance, an improved fusion scheme is built to integrate the proposed global path planning algorithm and the dynamic window approach (DWA). In the case study, the simulation experiments showed the advantage of the forward A* algorithm over the state-of-the-art algorithm in both time consumption and the number of inflection points generated, the field tests illustrated the effect of the fusion of depth camera images and LIDAR. Hence, the feasibility of this navigation methodology can be verified, and the average length of path and time consumption decreased by 6.5% and 17.8%, respectively, compared with the traditional methods