A study of energy correction for the electron beam data in the BGO ECAL of the DAMPE

The DArk Matter Particle Explorer (DAMPE) is an orbital experiment aiming at searching for dark matter indirectly by measuring the spectra of photons, electrons and positrons originating from deep space. The BGO electromagnetic calorimeter is one of the key sub-detectors of the DAMPE, which is designed for high energy measurement with a large dynamic range from 5 GeV to 10 TeV. In this paper, some methods for energy correction are discussed and tried, in order to reconstruct the primary energy of the incident electrons. Different methods are chosen for the appropriate energy ranges. The results of Geant4 simulation and beam test data (at CERN) are presented

iPUNet:Iterative Cross Field Guided Point Cloud Upsampling

Point clouds acquired by 3D scanning devices are often sparse, noisy, and non-uniform, causing a loss of geometric features. To facilitate the usability of point clouds in downstream applications, given such input, we present a learning-based point upsampling method, i.e., iPUNet, which generates dense and uniform points at arbitrary ratios and better captures sharp features. To generate feature-aware points, we introduce cross fields that are aligned to sharp geometric features by self-supervision to guide point generation. Given cross field defined frames, we enable arbitrary ratio upsampling by learning at each input point a local parameterized surface. The learned surface consumes the neighboring points and 2D tangent plane coordinates as input, and maps onto a continuous surface in 3D where arbitrary ratios of output points can be sampled. To solve the non-uniformity of input points, on top of the cross field guided upsampling, we further introduce an iterative strategy that refines the point distribution by moving sparse points onto the desired continuous 3D surface in each iteration. Within only a few iterations, the sparse points are evenly distributed and their corresponding dense samples are more uniform and better capture geometric features. Through extensive evaluations on diverse scans of objects and scenes, we demonstrate that iPUNet is robust to handle noisy and non-uniformly distributed inputs, and outperforms state-of-the-art point cloud upsampling methods

A Review of the Engineering Role of Burrowing Animals: Implication of Chinese Pangolin as an Ecosystem Engineer

Ecosystem engineers are organisms that alter the distribution of resources in the environment by creating, modifying, maintaining and/or destroying the habitat. They can affect the structure and function of the whole ecosystem furthermore. Burrowing engineers are an important group in ecosystem engineers as they play a critical role in soil translocation and habitat creation in various types of environment.However, few researchers have systematically summarized and analyzed the studies of burrowing engineers. We reviewing the existing ecological studies of burrowing engineer about their interaction with habitat through five directions: (1) soil turnover; (2)changing soil physicochemical properties; (3) changing plant community structure; (4) providing limited resources for commensal animals;and/or (5) affecting animal communities. The Chinese pangolin (Manis pentadactyla) is a typical example of burrowing mammals, in part (5), we focus on the interspecific relationships among burrow commensal species of Chinese pangolin. The engineering effects vary with environmental gradient, literature indicates that burrowing engineer play a stronger role in habitat transformation in the tropical and subtropical areas.The most common experiment method is comparative measurements (include different spatial and temporal scale),manipulative experiment is relatively few. We found that most of the engineering effects had positive feedback to the local ecosystem, increased plant abundance and resilience, increased biodiversity and consequently improved ecosystem functioning. With the global background of dramatic climate change and biodiversity loss in recent decades, we recommend future studies should improving knowledge of long-term engineering effects on population scale and landscape scale, exploring ecological cascades through trophic and engineering pathways, to better understand the attribute of the burrowing behavior of engineers to restore ecosystems and habitat creation. The review is presented as an aid to systematically expound the engineering effect of burrowing animals in the ecosystem, and provided new ideas and advice for planning and implementing conservation management

3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge

Teeth localization, segmentation, and labeling from intra-oral 3D scans are essential tasks in modern dentistry to enhance dental diagnostics, treatment planning, and population-based studies on oral health. However, developing automated algorithms for teeth analysis presents significant challenges due to variations in dental anatomy, imaging protocols, and limited availability of publicly accessible data. To address these challenges, the 3DTeethSeg'22 challenge was organized in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2022, with a call for algorithms tackling teeth localization, segmentation, and labeling from intraoral 3D scans. A dataset comprising a total of 1800 scans from 900 patients was prepared, and each tooth was individually annotated by a human-machine hybrid algorithm. A total of 6 algorithms were evaluated on this dataset. In this study, we present the evaluation results of the 3DTeethSeg'22 challenge. The 3DTeethSeg'22 challenge code can be accessed at: https://github.com/abenhamadou/3DTeethSeg22_challengeComment: 29 pages, MICCAI 2022 Singapore, Satellite Event, Challeng

The survival benefit of adjuvant radiotherapy for pathological T4N2M0 colon cancer in the Modern Chemotherapy Era: evidence from the SEER database 2004–2015

AbstractNeoadjuvant chemoradiotherapy has been established as the standard treatment for patients with locally advanced rectal cancer. However, the role of radiotherapy (RT) has not been fully confirmed in advanced colon cancer (LACC). We postulated that patients with pathological T4N2 locally advanced colon cancer would benefit more from RT. 6715 pT4N2M0 colon cancer patients were included in the Surveillance, Epidemiology, and End Results (SEER) database. The primary endpoints were 5-year overall survival (OS) and cancer-specific survival (CSS). Propensity score matching (PSM) with Kaplan–Meier and Cox proportional hazards’ models was performed to estimate prognosis. Before PSM, patients underwent RT had better OS and CSS as compared to patients did not receive RT (OS: 40.1% vs 27.6%, p < .001; CSS: 49.6% vs 41.1%, p = .002). After PSM, 239 matched pairs were formed for further analysis. RT group also presented significantly improved prognosis (OS: 40.1% vs 25.7%, p = .008; CSS: 49.6% vs 38.2%, p = .042). Multivariable Cox regression analysis showed that RT was a protective factor [OS：Hazard ratio (HR) =0.677, 95% Confidence interval (CI): 0.532–0.862, p = .002; CSS: HR = 0.708, 95% CI: 0.533–0.941, p = .018]. For pT4N2M0 colon cancer patients, the addition of RT seems to confer survival benefit as compared to patients who did not receive RT

Field-aligned quadrangulation for image vectorization

Image vectorization is an important yet challenging problem, especially when the input image has rich content. In this paper, we develop a novel method for automatically vectorizing natural images with feature-aligned quad-dominant meshes. Inspired by the quadrangulation methods in 3D geometry processing, we propose a new directional field optimization technique by encoding the color gradients, sidestepping the explicit computing of salient image features. We further compute the anisotropic scales of the directional field by accommodating the distance among image features. Our method is fully automatic and efficient, which takes only a few seconds for a 400×400 image on a normal laptop. We demonstrate the effectiveness of the proposed method on various image editing applications.Ministry of Education (MOE)The research of Yuanfeng Zhou was supported by the NSFC Fund (No.61772312), the key research and development project of Shandong province (2017GGX10110), the fundamental research funds of Shandong University (2018JC030). The research of Shiqing Xin was supported by the NSFC Fund (No.61772016).The research of Ying He was supported by the Singapore Ministry of Education Grant RG26/17