Relative camera pose estimation method using optimization on the manifold

To solve the problem of relative camera pose estimation, a method using optimization with respect to the manifold is proposed. Firstly from maximum-a-posteriori (MAP) model to nonlinear least squares (NLS) model, the general state estimation model using optimization is derived. Then the camera pose estimation model is applied to the general state estimation model, while the parameterization of rigid body transformation is represented by Lie group/algebra. The jacobian of point-pose model with respect to Lie group/algebra is derived in detail and thus the optimization model of rigid body transformation is established. Experimental results show that compared with the original algorithms, the approaches with optimization can obtain higher accuracy both in rotation and translation, while avoiding the singularity of Euler angle parameterization of rotation. Thus the proposed method can estimate relative camera pose with high accuracy and robustness

Different Amyloid-β Self-Assemblies Have Distinct Effects on Intracellular Tau Aggregation.

Alzheimer's disease (AD) pathology is characterized by the aggregation of beta-amyloid (Aβ) and tau in the form of amyloid plaques and neurofibrillary tangles in the brain. It has been found that a synergistic relationship between these two proteins may contribute to their roles in disease progression. However, how Aβ and tau interact has not been fully characterized. Here, we analyze how tau seeding or aggregation is influenced by different Aβ self-assemblies (fibrils and oligomers). Our cellular assays utilizing tau biosensor cells show that transduction of Aβ oligomers into the cells greatly enhances seeded tau aggregation in a concentration-dependent manner. In contrast, transduced Aβ fibrils slightly reduce tau seeding while untransduced Aβ fibrils promote it. We also observe that the transduction of α-synuclein fibrils, another amyloid protein, has no effect on tau seeding. The enhancement of tau seeding by Aβ oligomers was confirmed using tau fibril seeds derived from both recombinant tau and PS19 mouse brain extracts containing human tau. Our findings highlight the importance of considering the specific form and cellular location of Aβ self-assembly when studying the relationship between Aβ and tau in future AD therapeutic development

Structures of fibrils formed by α-synuclein hereditary disease mutant H50Q reveal new polymorphs.

Deposits of amyloid fibrils of α-synuclein are the histological hallmarks of Parkinson's disease, dementia with Lewy bodies and multiple system atrophy, with hereditary mutations in α-synuclein linked to the first two of these conditions. Seeing the changes to the structures of amyloid fibrils bearing these mutations may help to understand these diseases. To this end, we determined the cryo-EM structures of α-synuclein fibrils containing the H50Q hereditary mutation. We find that the H50Q mutation results in two previously unobserved polymorphs of α-synuclein: narrow and wide fibrils, formed from either one or two protofilaments, respectively. These structures recapitulate conserved features of the wild-type fold but reveal new structural elements, including a previously unobserved hydrogen-bond network and surprising new protofilament arrangements. The structures of the H50Q polymorphs help to rationalize the faster aggregation kinetics, higher seeding capacity in biosensor cells and greater cytotoxicity that we observe for H50Q compared to wild-type α-synuclein

On linear-algebraic notions of expansion

A fundamental fact about bounded-degree graph expanders is that three notions of expansion -- vertex expansion, edge expansion, and spectral expansion -- are all equivalent. In this paper, we study to what extent such a statement is true for linear-algebraic notions of expansion. There are two well-studied notions of linear-algebraic expansion, namely dimension expansion (defined in analogy to graph vertex expansion) and quantum expansion (defined in analogy to graph spectral expansion). Lubotzky and Zelmanov proved that the latter implies the former. We prove that the converse is false: there are dimension expanders which are not quantum expanders. Moreover, this asymmetry is explained by the fact that there are two distinct linear-algebraic analogues of graph edge expansion. The first of these is quantum edge expansion, which was introduced by Hastings, and which he proved to be equivalent to quantum expansion. We introduce a new notion, termed dimension edge expansion, which we prove is equivalent to dimension expansion and which is implied by quantum edge expansion. Thus, the separation above is implied by a finer one: dimension edge expansion is strictly weaker than quantum edge expansion. This new notion also leads to a new, more modular proof of the Lubotzky--Zelmanov result that quantum expanders are dimension expanders.Comment: 23 pages, 1 figur

Synthesis and Characterization of Cobalt-Doped WS2 Nanorods for Lithium Battery Applications

Cobalt-doped tungsten disulfide nanorods were synthesized by an approach involving exfoliation, intercalation, and the hydrothermal process, using commercial WS2 powder as the precursor and n-butyllithium as the exfoliating reagent. XRD results indicate that the crystal phase of the sample is 2H-WS2. TEM images show that the sample consists of bamboo-like nanorods with a diameter of around 20 nm and a length of about 200 nm. The Co-doped WS2 nanorods exhibit the reversible capacity of 568 mAh g−1 in a voltage range of 0.01–3.0 V versus Li/Li+. As an electrode material for the lithium battery, the Co-doped WS2 nanorods show enhanced charge capacity and cycling stability compared with the raw WS2 powder

FractalAD: A simple industrial anomaly detection method using fractal anomaly generation and backbone knowledge distillation

Although industrial anomaly detection (AD) technology has made significant progress in recent years, generating realistic anomalies and learning priors of normal remain challenging tasks. In this study, we propose an end-to-end industrial anomaly detection method called FractalAD. Training samples are obtained by synthesizing fractal images and patches from normal samples. This fractal anomaly generation method is designed to sample the full morphology of anomalies. Moreover, we designed a backbone knowledge distillation structure to extract prior knowledge contained in normal samples. The differences between a teacher and a student model are converted into anomaly attention using a cosine similarity attention module. The proposed method enables an end-to-end semantic segmentation network to be used for anomaly detection without adding any trainable parameters to the backbone and segmentation head, and has obvious advantages over other methods in training and inference speed.. The results of ablation studies confirmed the effectiveness of fractal anomaly generation and backbone knowledge distillation. The results of performance experiments showed that FractalAD achieved competitive results on the MVTec AD dataset and MVTec 3D-AD dataset compared with other state-of-the-art anomaly detection methods.Comment: 12 pages, 5 figure

PRIMARY JOURNALS AND THEIR COUNTRIES IN THE FIELD OF DENGUE LITERATURE: AN ANALYSIS

Presents a bibliometric analysis of the literature in the field of Dengue as indexed the MEDLINE data which covered in the Pubmed for the period 2008 to 2017. It is noticed that total of 11826 records on literature of Dengue are covered for a period of ten years from 2008 to 2017. It is also noticed that the maximum number of records (1810) was published during year 2016, followed by 1540 in 2017 and 1520 in 2015. It was found that Journal Article (41.4%), Research Support, Non-U.S. Gov’t (33.81%), Review (10.69%), Letter (3.61%), and Research Support, U.S. Gov\u27t Non-P.H.S. (2.86%). 37 primary journals grouped in zone 1 published 1675 articles accounting for one third of the total output. Similarly the second zone comprises of 143 journals and 904 journals grouped in third zone. Of the 37 titles in zone-1, 12 are associated with United States and followed by England (9), Netherlands (5), India (4), Brazil (2), China (1), Germany (1), Japan (1), Sweden (1) and Thailand (1). In zone-1 & 2 ; out of 180 journals, 51 frequently cited journals are United States, this is followed by the countries i.e. England (33), India (19), Netherlands (11), Brazil (9), Switzerland (9), France (6), Japan (4), China (3), Egypt (3), Germany (3), Pakistan (3), Singapore (3), Colombia (2), Italy (2), Malaysia (2), Thailand (2), Argentina (1), Australia(1), Austria (1), Canada (1), Chile (1), Cuba (1), Indonesia (1), Iran (1), Jamaica (1), Mexico (1), Peru (1), Philippines (1), Poland (1), Sri Lanka (1) and Sweden (1)

Optimizing Closed Month Accounting by Utilizing Leases on Data Access and Editing

The present disclosure describes computer-implemented systems and methods for improved efficiency of closed month accounting procedures. More particularly, systems and methods can reduce system queries pertaining to a closed month by utilizing time-based locks, hereinafter “leases,” when preparing entries for the closed month. When a month begins to close, it is provided with a lease and an expiration time of the lease. During the lease, a user can commit entries to the closing month without creating data errors

CharacterChat: Learning towards Conversational AI with Personalized Social Support

In our modern, fast-paced, and interconnected world, the importance of mental well-being has grown into a matter of great urgency. However, traditional methods such as Emotional Support Conversations (ESC) face challenges in effectively addressing a diverse range of individual personalities. In response, we introduce the Social Support Conversation (S2Conv) framework. It comprises a series of support agents and the interpersonal matching mechanism, linking individuals with persona-compatible virtual supporters. Utilizing persona decomposition based on the MBTI (Myers-Briggs Type Indicator), we have created the MBTI-1024 Bank, a group that of virtual characters with distinct profiles. Through improved role-playing prompts with behavior preset and dynamic memory, we facilitate the development of the MBTI-S2Conv dataset, which contains conversations between the characters in the MBTI-1024 Bank. Building upon these foundations, we present CharacterChat, a comprehensive S2Conv system, which includes a conversational model driven by personas and memories, along with an interpersonal matching plugin model that dispatches the optimal supporters from the MBTI-1024 Bank for individuals with specific personas. Empirical results indicate the remarkable efficacy of CharacterChat in providing personalized social support and highlight the substantial advantages derived from interpersonal matching. The source code is available in \url{https://github.com/morecry/CharacterChat}.Comment: 10 pages, 6 figures, 5 table