Statistical modelling of local features of three-dimensional shapes

The rapid development of 3D imaging technology allows data to be collected directly in three-dimensional space. The high accuracy of the images requires further investigations on digitised objects, especially of local features. In the last decade, 3D Local features have played an important role in recognising and modelling real-world 3D objects. This thesis introduces a series of methods for 3D local features, including automatic keypoints detection, 3D model construction with curves, local region detection and statistical analysis of local features. Those methods are not only to build 3D local feature descriptors but also have a wide range of applications, such as shape comparison in medical facial treatments and evolutionary researches in biology. Conventional shape analysis, limited by the data-collection technology, project 3D objects into 2D space to analyse or focus on 3D discrete points which are not close to each other. Those points of anatomical meanings are called landmarks. Researchers used to manually place the landmarks on 2D or 3D images by eyes, but it generates the operator error which is not of interest but has a large influence on shape analysis. This thesis introduces a novel method to automatically estimate the landmarks on 3D models using Bayesian statistics. The Procrustes matching of the landmark sets shows that the variation of Bayesian placements is much smaller than the manual placements. Local shapes like $``$ridges$"$ and $``$valleys$"$, which are considered to contain rich geometric information, can be estimated based on landmarks. Existing methods rely heavily on landmarks, but in most cases, the number of landmarks is not enough and adding extra ones are time-and-labour consuming. A flexible and user-customisable method is introduced in this thesis to deal with complex surfaces marked with as few landmarks as possible. A simulation study is conducted, and the result shows that the method is stable and efficient in terms of local feature description. After the 3D curve is estimated, methods to analyse the local features using the curves are discussed. An algorithm to flexibly dissect the surface along the estimated curve is developed for extracting local pieces or divide the surface into pieces. The novelty of this method is that it applies directly on 3D shapes and dissects the shape along any 3D curves, such as the lip edge on a human facial model. Besides the novel method for 3D shapes, curvatures, which reflect the bending amount along the curves, are calculated. The curvatures of the same local feature on different individuals are aligned to analyse the average shape difference of groups, such as gender and age. A reconstruction procedure from the curvatures is discussed and the effect of noise on choosing the degree of freedom in smoothing is investigated. Another application of the estimated curves is in benchmarking the performance of different 3D camera systems. A new camera system developed by NCTech\textsuperscript{\textregistered}, Edinburgh, is assessed using the evaluation outcome of facial deformity surgeries in Brazil. It is designed to be child-friendly, portable and low-cost. Validation studies are carried out at three stages of the development, and both landmarks and curves are used to evaluate the performance of the new camera system on estimating local features in comparison with mature products from DI4D\textsuperscript{\textregistered} and Artec\textsuperscript{\textregistered}

RAFT based wireless blockchain networks in the presence of malicious jamming

Blockchain shows great potential to be applied in wireless IoT ecosystems for establishing the trust and consensus mechanisms without central authority’s involvement. Based on RAFT consensus mechanism, this paper investigates the security performance of wireless blockchain networks in the presence of malicious jamming. We first map and model the blockchain transaction as a wireless network composed of uplink and downlink transmissions by assuming the follower nodes’ position as a Poisson Point Process (PPP) with selected leader location. The probability of achieving successful blockchain transactions is derived and verified by extensive simulations. The results provide analytical guidance for the practical deployment of wireless blockchain networks

Improving Learning Engagement Among Ethnic Minority High School Students in China Through School-Based Social Support: An Intervention Study

The study aimed to examine the effect of school-based social support, specifically the integrated peer and teacher support on the learning engagement of ethnic minority high school students in China. Researchers designed a customized reading program to incorporate peer and teacher support through collaborative learning and dual-teacher classroom mechanisms. The intervention groups involve 192 first year high school students in an underdeveloped area in Yunnan province. Learning engagement was measured using a self-report interview and observation field note during the intervention. Results showed that the school-based social support has effectively promoted the student’s self-confidence, learning motivation, self-identity, and develop a positive learning environment. These findings suggest that school-based social support can be a productive way to improve learning engagement among ethnic minority high school students in China. Implications for education practice and future research are discussed

Future directions in ventilator-induced lung injury associated cognitive impairment: a new sight

Mechanical ventilation is a widely used short-term life support technique, but an accompanying adverse consequence can be pulmonary damage which is called ventilator-induced lung injury (VILI). Mechanical ventilation can potentially affect the central nervous system and lead to long-term cognitive impairment. In recent years, many studies revealed that VILI, as a common lung injury, may be involved in the central pathogenesis of cognitive impairment by inducing hypoxia, inflammation, and changes in neural pathways. In addition, VILI has received attention in affecting the treatment of cognitive impairment and provides new insights into individualized therapy. The combination of lung protective ventilation and drug therapy can overcome the inevitable problems of poor prognosis from a new perspective. In this review, we summarized VILI and non-VILI factors as risk factors for cognitive impairment and concluded the latest mechanisms. Moreover, we retrospectively explored the role of improving VILI in cognitive impairment treatment. This work contributes to a better understanding of the pathogenesis of VILI-induced cognitive impairment and may provide future direction for the treatment and prognosis of cognitive impairment

An Efficient Generalizable Framework for Visuomotor Policies via Control-aware Augmentation and Privilege-guided Distillation

Visuomotor policies, which learn control mechanisms directly from high-dimensional visual observations, confront challenges in adapting to new environments with intricate visual variations. Data augmentation emerges as a promising method for bridging these generalization gaps by enriching data variety. However, straightforwardly augmenting the entire observation shall impose excessive burdens on policy learning and may even result in performance degradation. In this paper, we propose to improve the generalization ability of visuomotor policies as well as preserve training stability from two aspects: 1) We learn a control-aware mask through a self-supervised reconstruction task with three auxiliary losses and then apply strong augmentation only to those control-irrelevant regions based on the mask to reduce the generalization gaps. 2) To address training instability issues prevalent in visual reinforcement learning (RL), we distill the knowledge from a pretrained RL expert processing low-level environment states, to the student visuomotor policy. The policy is subsequently deployed to unseen environments without any further finetuning. We conducted comparison and ablation studies across various benchmarks: the DMControl Generalization Benchmark (DMC-GB), the enhanced Robot Manipulation Distraction Benchmark (RMDB), and a specialized long-horizontal drawer-opening robotic task. The extensive experimental results well demonstrate the effectiveness of our method, e.g., showing a 17\% improvement over previous methods in the video-hard setting of DMC-GB

Kronos: A Secure and Generic Sharding Blockchain Consensus with Optimized Overhead

Sharding enhances blockchain scalability by dividing the network into shards, each managing specific unspent transaction outputs or accounts. As an introduced new transaction type, cross-shard transactions pose a critical challenge to the security and efficiency of sharding blockchains. Currently, there is a lack of a generic sharding consensus pattern that achieves both security and low overhead. In this paper, we present Kronos, a secure sharding blockchain consensus achieving optimized overhead. In particular, we propose a new secure sharding consensus pattern, based on a buffer managed jointly by shard members. Valid transactions are transferred to the payee via the buffer, while invalid ones are rejected through happy or unhappy paths. Kronos is proved to achieve security with atomicity under malicious clients with optimal intra-shard overhead $k\mathcal{B}$ ($k$ for involved shard number and $\mathcal{B}$ for a Byzantine fault tolerance (BFT) cost). Efficient rejection even requires no BFT execution in happy paths, and the cost in unhappy paths is still lower than a two-phase commit. Besides, we propose secure cross-shard certification methods based on batch certification and reliable cross-shard transfer. The former combines hybrid trees or vector commitments, while the latter integrates erasure coding. Handling $b$ transactions, Kronos is proved to achieve reliability with low cross-shard overhead $\mathcal{O}(n b \lambda)$ ($n$ for shard size and $\lambda$ for the security parameter). Notably, Kronos imposes no restrictions on BFT and does not rely on time assumptions, offering optional constructions in various modules. Kronos could serve as a universal framework for enhancing the performance and scalability of existing BFT protocols, supporting generic models, including asynchronous networks, increasing the throughput by several orders of magnitude. We implement Kronos using two prominent BFT protocols: asynchronous Speeding Dumbo (NDSS\u2722) and partial synchronous Hotstuff (PODC\u2719). Extensive experiments (over up to 1000 AWS EC2 nodes across 4 AWS regions) demonstrate Kronos scales the consensus nodes to thousands, achieving a substantial throughput of 320 ktx/sec with 2.0 sec latency. Compared with the past solutions, Kronos outperforms, achieving up to a 12$\times$ improvement in throughput and a 50% reduction in latency when cross-shard transactions dominate the workload

Doubly Efficient Interactive Proofs for General Arithmetic Circuits with Linear Prover Time

We propose a new doubly efficient interactive proof protocol for general arithmetic circuits. The protocol generalizes the doubly efficient interactive proof for layered circuits proposed by Goldwasser, Kalai and Rothblum to arbitrary circuits while preserving the optimal prover complexity that is strictly linear to the size of the circuits. The proof size remains succinct for low depth circuits and the verifier time is sublinear for structured circuits. We then construct a new zero knowledge argument scheme for general arithmetic circuits using our new interactive proof protocol together with polynomial commitments. Not only does our new protocol achieve optimal prover complexity asymptotically, but it is also efficient in practice. Our experiments show that it only takes 1 second to generate the proof for a circuit with 600,000 gates, which is 7 times faster than the original interactive proof protocol on the corresponding layered circuit. The proof size is 229 kilobytes and the verifier time is 0.56 second. Our implementation can take general arithmetic circuits generated by existing tools directly, without transforming them to layered circuits with high overhead on the size of the circuits

Impacts of climate change and human activities on vegetation coverage variation in mountainous and hilly areas in Central South of Shandong Province based on tree-ring

IntroductionIt is of great significance to understand the characteristics and influencing factors of vegetation coverage variation in the warm temperate zone. As a typical region of the warm temperate zone in eastern China, the mountainous and hilly region in central-south Shandong Province has fragile ecological environment and soil erosion problem. Studying on vegetation dynamics and its influencing factors in this region will help to better understand the relationship between climate change and vegetation cover change in the warm temperate zone of eastern China, and the influence of human activities on vegetation cover dynamics.MethodsBased on dendrochronology, a standard tree-ring width chronology was established in the mountainous and hilly region of central-south Shandong Province, and the vegetation coverage from 1905 to 2020 was reconstructed to reveal the dynamic change characteristics of vegetation cover in this region. Secondly, the influence of climate factors and human activities on the dynamic change of vegetation cover was discussed through correlation analysis and residual analysis.Results and discussionIn the reconstructed sequence, 23 years had high vegetation coverage and 15 years had low vegetation coverage. After low-pass filtering, the vegetation coverage of 1911–1913, 1945–1951, 1958–1962, 1994–1996, and 2007–2011 was relatively high, while the vegetation coverage of 1925–1927, 1936–1942, 2001–2003, and 2019–2020 was relatively low. Although precipitation determined the variation of vegetation coverage in this study area, the impacts of human activities on the change of vegetation coverage in the past decades cannot be ignored. With the development of social economy and the acceleration of urbanization, the vegetation coverage declined. Since the beginning of the 21st century, ecological projects such as Grain-for-Green have increased the vegetation coverage

Protection of Human Umbilical Vein Endothelial Cells against Oxidative Stress by MicroRNA-210

Oxidative stress induces endothelial cell apoptosis and promotes atherosclerosis development. MicroRNA-210 (miR-210) is linked with apoptosis in different cell types. This study aimed to investigate the role of miR-210 in human umbilical vein endothelial cells (HUVECs) under oxidative stress and to determine the underlying mechanism. HUVECs were treated with different concentrations of hydrogen peroxide (H2O2), and cell viability was evaluated using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay and ATP assay. To evaluate the role of miR-210 in H2O2-mediated apoptosis, gain-and-loss-of-function approaches were used, and the effects on apoptosis and reactive oxygen species (ROS) level were assayed using flow cytometry. Moreover, miR-210 expression was detected by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), and expression of the following apoptosis-related genes was assessed by qRT-PCR and Western blot at the RNA and protein level, respectively: caspase-8-associated protein 2 (CASP8AP2), caspase-8, and caspase-3. The results showed that H2O2 induced apoptosis in HUVECs in a dose-dependent manner and increased miR-210 expression. Overexpression of miR-210 inhibited apoptosis and reduced ROS level in HUVECs treated with H2O2. Furthermore, miR-210 downregulated CASP8AP2 and related downstream caspases at protein level. Thus, under oxidative stress, miR-210 has a prosurvival and antiapoptotic effect on HUVECs by reducing ROS generation and downregulating the CASP8AP2 pathway

Rare microbial taxa as the major drivers of nutrient acquisition under moss biocrusts in karst area

Karst rocky desertification refers to the process of land degradation caused by various factors such as climate change and human activities including deforestation and agriculture on a fragile karst substrate. Nutrient limitation is common in karst areas. Moss crust grows widely in karst areas. The microorganisms associated with bryophytes are vital to maintaining ecological functions, including climate regulation and nutrient circulation. The synergistic effect of moss crusts and microorganisms may hold great potential for restoring degraded karst ecosystems. However, our understanding of the responses of microbial communities, especially abundant and rare taxa, to nutrient limitations and acquisition in the presence of moss crusts is limited. Different moss habitats exhibit varying patterns of nutrient availability, which also affect microbial diversity and composition. Therefore, in this study, we investigated three habitats of mosses: autochthonal bryophytes under forest, lithophytic bryophytes under forest and on cliff rock. We measured soil physicochemical properties and enzymatic activities. We conducted high-throughput sequencing and analysis of soil microorganisms. Our finding revealed that autochthonal moss crusts under forest had higher nutrient availability and a higher proportion of copiotrophic microbial communities compared to lithophytic moss crusts under forest or on cliff rock. However, enzyme activities were lower in autochthonal moss crusts under forest. Additionally, rare taxa exhibited distinct structures in all three habitats. Analysis of co-occurrence network showed that rare taxa had a relatively high proportion in the main modules. Furthermore, we found that both abundant and rare taxa were primarily assembled by stochastic processes. Soil properties significantly affected the community assembly of the rare taxa, indirectly affecting microbial diversity and complexity and finally nutrient acquisition. These findings highlight the importance of rare taxa under moss crusts for nutrient acquisition. Addressing this knowledge gap is essential for guiding ongoing ecological restoration projects in karst rocky desertification regions