Norovirus GII.17: The Emergence and Global Prevalence of a Novel Variant

A rare norovirus (NoV) genotype GII.17 has recently emerged and rapidly became predominant in most East Asian countries in the winters of 2014–2015. In this study, we report the diversity of NoV GII.17 in detail; a total of 646 GII.17 sequences obtained during 1978–2015 were analyzed and subjected to meta-analysis. At least five major recombinant GII.17 clusters were identified. Each recombinant variant group appeared to have emerged following the time order: GII.P4-GII.17 (1978–1990), GII.P16-GII.17 (2001–2004), GII.P13-GII.17 (2004–2010), GII.Pe-GII.17 (2012–2015) and GII.P3-GII.17 (2011–2015). The newly emerged GII.P3-GII.17 variant, which exhibited significant sequence and structure variations, is evolving toward a unique lineage. Our results indicate that circulation of GII.17 appears to change every 3–5 years due to replacement by a newly emerged variant and that the evolution of GII.17 is sequentially promoted by inter-genotype recombination, which contributes to the exchange between non-GII.17 and GII.17 RdRp genes and drives the evolution of GII.17 capsid genes

Analysis on Alighting and Boarding Movement Laws in Subway Using Modified Social Force Model

This paper presents a multi-agent simulator based on social force model to simulate each passenger’s boarding and alighting behavior both in a train and on a platform seamlessly. Passengers can be divided into three types: to board, alight and stay in train. They have different individual attributes and follow different walking rules. Due to the characteristics of subway environment and passengers' behavior in boarding and alighting, some adjustment and improvement were made to the basic social force model: (1) In some cases during the process of boarding and alighting, the driving force targeting to destination needs to be doubled, and the repulsion force between two agents needs to be reduced. (2) Passengers who stay in the train show quite different movement from the usual pedestrian. They usually want to remain still, unless they are in front of the door. To describe their behaviors, we introduced a tangent detour force. The scope of the interaction between agents is extended and some passengers out of the visual field also should be counted. (3) Divide the repulsive force between an agent and an obstacle into the frontal force and convex corner force. These two forces have different spheres of influence and calculation methods. The agents could exhibit reasonable intelligence and diversity during alighting and boarding

MS23D: A 3D Object Detection Method Using Multi-Scale Semantic Feature Points to Construct 3D Feature Layer

Lidar point clouds, as a type of data with accurate distance perception, can effectively represent the motion and posture of objects in three-dimensional space. However, the sparsity and disorderliness of point clouds make it challenging to extract features directly from them. Many studies have addressed this issue by transforming point clouds into regular voxel representations. However, these methods often lead to the loss of fine-grained local feature information due to downsampling. Moreover, the sparsity of point clouds poses difficulties in efficiently aggregating features in 3D feature layer using voxel-based two-stage methods. To address these issues, this paper proposes a two-stage 3D detection framework called MS$^{2}$3D. In MS$^{2}$3D, we utilize small-sized voxels to extract fine-grained local features and large-sized voxels to capture long-range local features. Additionally, we propose a method for constructing 3D feature layer using multi-scale semantic feature points, enabling the transformation of sparse 3D feature layer into more compact representations. Furthermore, we compute the offset between feature points in the 3D feature layer and the centroid of objects, aiming to bring them as close as possible to the object's center. It significantly enhances the efficiency of feature aggregation. To validate the effectiveness of our method, we evaluated our method on the KITTI dataset and ONCE dataset together

PV-SSD: A Projection and Voxel-based Double Branch Single-Stage 3D Object Detector

LIDAR-based 3D object detection and classification is crucial for autonomous driving. However, inference in real-time from extremely sparse 3D data poses a formidable challenge. To address this issue, a common approach is to project point clouds onto a bird's-eye or perspective view, effectively converting them into an image-like data format. However, this excessive compression of point cloud data often leads to the loss of information. This paper proposes a 3D object detector based on voxel and projection double branch feature extraction (PV-SSD) to address the problem of information loss. We add voxel features input containing rich local semantic information, which is fully fused with the projected features in the feature extraction stage to reduce the local information loss caused by projection. A good performance is achieved compared to the previous work. In addition, this paper makes the following contributions: 1) a voxel feature extraction method with variable receptive fields is proposed; 2) a feature point sampling method by weight sampling is used to filter out the feature points that are more conducive to the detection task; 3) the MSSFA module is proposed based on the SSFA module. To verify the effectiveness of our method, we designed comparison experiments

SecureBoost Hyperparameter Tuning via Multi-Objective Federated Learning

SecureBoost is a tree-boosting algorithm leveraging homomorphic encryption to protect data privacy in vertical federated learning setting. It is widely used in fields such as finance and healthcare due to its interpretability, effectiveness, and privacy-preserving capability. However, SecureBoost suffers from high computational complexity and risk of label leakage. To harness the full potential of SecureBoost, hyperparameters of SecureBoost should be carefully chosen to strike an optimal balance between utility, efficiency, and privacy. Existing methods either set hyperparameters empirically or heuristically, which are far from optimal. To fill this gap, we propose a Constrained Multi-Objective SecureBoost (CMOSB) algorithm to find Pareto optimal solutions that each solution is a set of hyperparameters achieving optimal tradeoff between utility loss, training cost, and privacy leakage. We design measurements of the three objectives. In particular, the privacy leakage is measured using our proposed instance clustering attack. Experimental results demonstrate that the CMOSB yields not only hyperparameters superior to the baseline but also optimal sets of hyperparameters that can support the flexible requirements of FL participants.Comment: FL-ICAI'2

Classification of a Complexly Mixed Magnetic Mineral Assemblage in Pacific Ocean Surface Sediment by Electron Microscopy and Supervised Magnetic Unmixing

Unambiguous magnetic mineral identification in sediments is a prerequisite for reconstructing paleomagnetic and paleoenvironmental information from environmental magnetic parameters. We studied a deep-sea surface sediment sample from the Clarion Fracture Zone region, central Pacific Ocean, by combining magnetic measurements and scanning and transmission electron microscopic analyses. Eight titanomagnetite and magnetite particle types are recognized based on comprehensive documentation of crystal morphology, size, spatial arrangements, and compositions, which are indicative of their corresponding origins. Type-1 particles are detrital titanomagnetites with micron- and submicron sizes and irregular and angular shapes. Type-2 and -3 particles are well-defined octahedral titanomagnetites with submicron and nanometer sizes, respectively, which are likely related to local hydrothermal and volcanic activity. Type-4 particles are nanometer-sized titanomagnetites hosted within silicates, while type-5 particles are typical dendrite-like titanomagnetites that likely resulted from exsolution within host silicates. Type-6 particles are single domain magnetite magnetofossils related to local magnetotactic bacterial activity. Type-7 particles are superparamagnetic magnetite aggregates, while Type-8 particles are defect-rich single crystals composed of many small regions. Electron microscopy and supervised magnetic unmixing reveal that type-1 to -5 titanomagnetite and magnetite particles are the dominant magnetic minerals. In contrast, the magnetic contribution of magnetite magnetofossils appears to be small. Our work demonstrates that incorporating electron microscopic data removes much of the ambiguity associated with magnetic mineralogical interpretations in traditional rock magnetic measurements.This study was supported financially by the National Natural Science Foundation of China (Grant Nos. 41920104009, 41890843, and 41621004), The Senior User Project of RVKEXUE2019GZ06 (Center for Ocean Mega-Science, Chinese Academy of Sciences)

Experimental study and application of hydraulic fracturing in underlying coal seam

The coalbed methane resource under goaf is rich, but has not been effectively developed for a long time. Hydraulic fracturing technology stands as an effective means to augment coalbed methane recovery. The extraction and re-compaction of overlying coal seam will directly affect the expansion behavior of hydraulic fractures in the underlying coal seam. Though the large-scale (300 mm×300 mm×300 mm) true triaxial hydraulic fracturing experiments, the mechanical and acoustic emission response characteristics of coal were analyzed under different levels of loading and unloading stress perturbations. The damage variable T was proposed to characterize the degree of coal damage, and the relationship between damage and the initiation and expansion patterns of hydraulic fractures was elucidated. The results revealed that, the damage induced by vertical stress loading in the underlying coal significantly exceeded that in the unloading stage. When the vertical loading stress was below 11 MPa, the coal remained in an elastic stage with minimal damage. Loading between 11~15 MPa corresponded to the yielding stage, witnessing a substantial increase in damage. Loading between 15~18 MPa led to the strengthening stage, the pores and fractures of coal were gradually compacted. Damage variables T can effectively characterize the degree of internal damage of coal. When T=Tc, the internal damage of coal was comparable to that of a coal that has not disturbed by loading and unloading stress.Tc is the damage variable of coal without loading and unloading stress disturbance. When T＞Tc , the coal exhibited a stress-damaged state, with higher values of T corresponding to increasing damage levels. Conversely, when T＜Tc, the coal demonstrated a stress-compacted state, with smaller values of T indicating higher compaction degrees. The degree of stress damage in coal was negatively correlated with the fracture pressure, a high degree of damage made coal more prone to fracture, and it was favor to form the primary hydraulic fractures near the wellbore, which was conducive to hydraulic fracturing. The degree of compaction of coal was positively correlated with fracture pressure. The high degree of compaction weakened the effect of horizontal stress difference on hydraulic fracture expansion, and the hydraulic fracture near the wellbore was more developed, which hindered the formation of primary hydraulic fractures. Based on the research results, the principle of hydraulic fracturing construction scheme optimization for underlying coal seam in goaf was formulated and applied in the field. The hydraulic fracturing ability of the optimized scheme was significantly improved

Genistein Inhibition of Topoisomerase IIα Expression Participated by Sp1 and Sp3 in HeLa Cell

Genistein (4′, 5, 7-trihydroxyisoflavone) is an isoflavone compound obtained from plants that has potential applications in cancer therapy. However, the molecular mechanism of the action of genistein on cancer cell apoptosis is not well known. In this study, we investigated the effect of genistein on topoisomerase II-α (Topo IIα), an important protein involved in the processes of DNA replication and cell proliferation. The results revealed that inhibition of Topo IIα expression through the regulation of Specificity protein 1 and Specificity protein 3 may be one of the reasons for genistein’s induction of HeLa cell apoptosis

Ultrafast Control of Excitonic Rashba Fine Structure by Phonon Coherence in the Metal Halide Perovskite CH3NH3PbI3

We discover hidden Rashba fine structure in CH3NH3PbI3 and demonstrate its quantum control by vibrational coherence through symmetry-selective vibronic (electron-phonon) coupling. Above a critical threshold of a single-cycle terahertz pump field, a Raman phonon mode distinctly modulates the middle excitonic states with persistent coherence for more than ten times longer than the ones on two sides that predominately couple to infrared phonons. These vibronic quantum beats, together with first-principles modeling of phonon periodically modulated Rashba parameters, identify a threefold excitonic fine structure splitting, i.e., optically forbidden, degenerate dark states in between two bright ones with a narrow, similar to 3 nm splitting. Harnessing of vibronic quantum coherence and symmetry inspires light-perovskite quantum control and sub-THz-cycle Rashba engineering of spin-split bands for ultimate multifunction device