Modelling the Influence of Geological Structures in Paleo Rock Avalanche Failures Using Field and Remote Sensing Data

This paper focuses on the back analysis of an ancient, catastrophic rock avalanche located in the small city of Lettopalena (Chieti, Italy). The integrated use of various investigation methods was employed for landslide analysis, including the use of traditional manual surveys and remote sensing (RS) mapping for the identification of geological structures. The outputs of the manual and RS surveys were then utilised to numerically model the landslide using a 2D distinct element method. A series of numerical simulations were undertaken to perform a sensitivity analysis to investigate the uncertainty of discontinuity properties on the slope stability analysis and provide further insight into the landslide failure mechanism. Both numerical modelling and field investigations indicate that the landslide was controlled by translational sliding along a folded bedding plane, with toe removal because of river erosion. This generated daylighting of the bedding plane, creating kinematic freedom for the landslide. The formation of lateral and rear release surfaces was influenced by the orientation of the discrete fracture network. Due to the presence of an anticline, the landslide region was constrained in the middle-lower section of the slope, where the higher inclination of the bedding plane was detected. The landslide is characterized by a step-path slip surface at the toe of the slope, which was observed both in the modelling and the field. This paper highlights the combined use of a geological model and numerical modelling to provide an improved understanding of the origin and development of rock avalanches under the influence of river erosion, anticline structures, and related faults and fractures

Unsupervised Visible-Infrared Person ReID by Collaborative Learning with Neighbor-Guided Label Refinement

Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) aims at learning modality-invariant features from unlabeled cross-modality dataset, which is crucial for practical applications in video surveillance systems. The key to essentially address the USL-VI-ReID task is to solve the cross-modality data association problem for further heterogeneous joint learning. To address this issue, we propose a Dual Optimal Transport Label Assignment (DOTLA) framework to simultaneously assign the generated labels from one modality to its counterpart modality. The proposed DOTLA mechanism formulates a mutual reinforcement and efficient solution to cross-modality data association, which could effectively reduce the side-effects of some insufficient and noisy label associations. Besides, we further propose a cross-modality neighbor consistency guided label refinement and regularization module, to eliminate the negative effects brought by the inaccurate supervised signals, under the assumption that the prediction or label distribution of each example should be similar to its nearest neighbors. Extensive experimental results on the public SYSU-MM01 and RegDB datasets demonstrate the effectiveness of the proposed method, surpassing existing state-of-the-art approach by a large margin of 7.76% mAP on average, which even surpasses some supervised VI-ReID methods

Efficient Bilateral Cross-Modality Cluster Matching for Unsupervised Visible-Infrared Person ReID

Unsupervised visible-infrared person re-identification (USL-VI-ReID) aims to match pedestrian images of the same identity from different modalities without annotations. Existing works mainly focus on alleviating the modality gap by aligning instance-level features of the unlabeled samples. However, the relationships between cross-modality clusters are not well explored. To this end, we propose a novel bilateral cluster matching-based learning framework to reduce the modality gap by matching cross-modality clusters. Specifically, we design a Many-to-many Bilateral Cross-Modality Cluster Matching (MBCCM) algorithm through optimizing the maximum matching problem in a bipartite graph. Then, the matched pairwise clusters utilize shared visible and infrared pseudo-labels during the model training. Under such a supervisory signal, a Modality-Specific and Modality-Agnostic (MSMA) contrastive learning framework is proposed to align features jointly at a cluster-level. Meanwhile, the cross-modality Consistency Constraint (CC) is proposed to explicitly reduce the large modality discrepancy. Extensive experiments on the public SYSU-MM01 and RegDB datasets demonstrate the effectiveness of the proposed method, surpassing state-of-the-art approaches by a large margin of 8.76% mAP on average

Comprehensive characterization of irradiation induced defects in ceria: Impact of point defects on vibrational and optical properties

Validation of multiscale microstructure evolution models can be improved when standard microstructure characterization tools are coupled with methods sensitive to individual point defects. We demonstrate how electronic and vibrational properties of defects revealed by optical absorption and Raman spectroscopies can be used to compliment transmission electron microscopy (TEM) and x-ray diffraction (XRD) in the characterization of microstructure evolution in ceria under non-equilibrium conditions. Experimental manifestation of non-equilibrium conditions was realized by exposing cerium dioxide (CeO2) to energetic protons at elevated temperature. Two sintered polycrystalline CeO2 samples were bombarded with protons accelerated to a few MeVs. These irradiation conditions produced a microstructure with resolvable extended defects and a significant concentration of point defects. A rate theory (RT) model was parametrized using the results of TEM, XRD, and thermal conductivity measurements to infer point defect concentrations. An abundance of cerium sublattice defects suggested by the RT model is supported by Raman spectroscopy measurements, which show peak shift and broadening of the intrinsic T2g peak and emergence of new defect peaks. Additionally, spectroscopic ellipsometry measurements performed in lieu of optical absorption reveals the presence of Ce3+ ions associated with oxygen vacancies. This work lays the foundation for a coupled approach that considers a multimodal characterization of microstructures to guide and validate complex defect evolution models

SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation

Existing watermarking algorithms are vulnerable to paraphrase attacks because of their token-level design. To address this issue, we propose SemStamp, a robust sentence-level semantic watermarking algorithm based on locality-sensitive hashing (LSH), which partitions the semantic space of sentences. The algorithm encodes and LSH-hashes a candidate sentence generated by an LLM, and conducts sentence-level rejection sampling until the sampled sentence falls in watermarked partitions in the semantic embedding space. A margin-based constraint is used to enhance its robustness. To show the advantages of our algorithm, we propose a "bigram" paraphrase attack using the paraphrase that has the fewest bigram overlaps with the original sentence. This attack is shown to be effective against the existing token-level watermarking method. Experimental results show that our novel semantic watermark algorithm is not only more robust than the previous state-of-the-art method on both common and bigram paraphrase attacks, but also is better at preserving the quality of generation

Analysis of solids with different matrices by buffer-gas-assisted laser ionization orthogonal time-of-flight mass spectrometry

A laser ionization orthogonal time-of-flight mass spectrometer with a low-pressure source and high laser irradiance was used to analyze 27 solid samples with 9 different matrices, including aluminium, soil, copper sulfide, zinc sulfide, iron, nickel, copper, zinc, and tungsten. The influence of laser energy on non-stoichiometric effects, such as matrix effects and elemental fractionation, has been investigated. The results indicate that matrix effects can be alleviated to a great extent at high laser irradiance. Additionally, with the irradiance of 10(10)-10(11) Wcm(-2), most elements presented relatively stable relative sensitivity coefficients (RSC), while W, Pb, and Bi demonstrated unusual characteristics that their RSCs increased along with increasing laser energy.National 863 program ; Natural Science Foundation of China ; Fujian Province Department of Science Technolog

A novel 25-ferroptosis-related gene signature for the prognosis of gliomas

BackgroundFerroptosis is closely associated with cancer and is of great importance in the immune evasion of cancer. However, the relationship between ferroptosis and glioma is unclear.MethodsWe downloaded the expression profiles and clinical data of glioma from the GlioVis database and obtained the expression profiles of ferroptosis genes. A ferroptosis-related gene signature was developed for the prognosis of gliomas.ResultsWe screened out prognostic ferroptosis genes, named ferroptosis-related genes, by the Cox regression method. Based on these genes, we used unsupervised clustering to obtain two different clusters; the principal component analysis algorithm was applied to determine the gene score of each patient, and then all the patients were classified into two subgroups. Results showed that there exist obvious differences in survival between different clusters and different gene score subgroups. The prognostic model constructed by the 25 ferroptosis-related genes was then evaluated to predict the clinicopathological features of immune activity in gliomas.ConclusionThe ferroptosis-related genes play an important role in the malignant process of gliomas, potentially contributing to the development of prognostic stratification and treatment strategies

Kinetic energy and spatial distribution of ions in high irradiance laser ionization source

Characteristics of laser ionization in vacuum and low pressure background gas (He) have been investigated through the measurement of kinetic energy and spatial distributions of copper and tungsten ions. A Q-switched Nd:YAG laser with 532 nm wavelength was utilized and the laser irradiance was fixed at 9 x 10(9) W cm(-2). A plume splitting was observed in the low pressure regime investigated (from 100 Pa to 2000 Pa). The plume propagation translates from a free expansion in vacuum to shockwave-like expansion at relative low pressure and finally diffusion into background gas at relative high pressure environment. A measurement of ion spatial distribution in the ion source has also been carried out for characterizing ions at different pressures and the behaviors of doubly charged, singly charged, and polyatomic ions to reveal the effect of plume-background gas interaction.Natural Science Foundation of China Financial[20775063, 21027011]; National 863 program[2009AA06Z109]; NFFTBS[J1030415