Study on Application of Solar Water Heat Pump for Building in China

AbstractIn order to solve the issue of applicability of solar water source heat pump for building, this article analyzes the load characteristics in different climate regions based on the three typical cities which are Harbin, Beijing, Shanghai, then sets up system mathematical models, uses the eQUEST set up the building model and puts the model into TRNSYS to do the optimization calculation. According to the theory of Life Cycle Assessment, this article analyzes the applicability of solar water source heat pump for building by taking feasibility, energy saving property, economy and environmental protection property as technical index and get the conclusion that the applicability of solar water source heat pump for building in severe cold region and cold region is well and the environmental benefit is obvious

Influence of polymorphisms of three TRP genes on pain sensitivity in neuropathic pain patients

Neuropathic pain is a chronic pain syndrome that has been associated with drug-, disease-, or injury-induced damage or destruction of the sensory afferent fibers of the peripheral nervous system (PNS). The type of pain could be manifested not only with positive sensory phenomena, such as pain, dysesthesia, and different types of hyperalgesia, but also with negative sensory phenomena and negative and positive motor symptoms and signs. The pharmacological treatment of the symptoms of painful neuropathy, however, is still considered to be difficult. Nowadays, much attention is focused on the genetic polymorphisms, some of the single nucleotide polymorphisms can be speculated to be associated with the pain sensitivity as a result of amino acid substitution in crucial position. But the detailed knowledge of individual variability on pain perception under neuropathic pain is still poorly understood. Candidate gene studies on the basis of biological hypothesis have been a practical approach to identify relevant genetic variation in complex traits. There is growing evidence showed that single nucleotide polymorphisms in related genes, including TRPV1, TRPA1 and TRPM8, may influence pain sensitivity in animal model of neuropathic pain. In our study, we selected 2 of the SNPs fromTRPV1, 3 of the SNPs from TRPA1 and 6 SNPs from TRPM8 to examine the effect of these variations on clinical neuropathic pain responses, to investigate the contribution of genetic factors on pain sensitivity in humans. There were a total of 296 Germany patients and 253 healthy volunteers recruited in our study for investigation. Owing to the failed collection of clinical data in some cases, finally only 237 patients were enrolled to carry out the association analysis. The results show that patients exhibited markedly gain of sensory function along with the application of cold detection (CDT), thermal sensitivity limen (TSL) on control side. The hypoesthesia, however, was occurred on test side when patients were giving mechanical pain threshold (MPT) and mechanical pain sensitivity (MPS) measure. The comparison of seven subgroups between test and control side showed that there are different pain patterns based on the subgroups. Besides the trigeminal pain and other neuropathy patients, the five other subgroups exhibiting either the loss of sensory function in CDT, WDT, TSL and VDT on central pain, or the gain of sensory function in pressure pain threshold (PPT) in CPRS patient. Referring to the genotype and allele frequencies on patients and controls, there are no significant differences between the two groups, except the TRPV1 polymorphism A1911G. With regard to the association between SNPs and 13 QST parameters, there were some significant correlations related to TRPV1 polymorphisms 1103 C>G and 1911A>G, as well as to TRPA1 polymorphism 710G>A and 3228A>G with several QST parameters in two neuropathic pain subgroups. The CRPS patients carrying homozygote G in TRPA1 3228A>G were more sensitive to pain perception than those patients carrying the heterozygote genotype in the TSL and CDT test, conversely, in some subgroups homozygote TRPV1 1911G carriers were more likely to be insensitive to sensory pain than homozygote 1911A carriers; Similarly, further comparison of the data indicated that patients carrying homozygote TRPA1 710A or 3228G were less sensitive to pain perception than heterozygote and homozygote G710 or 3228A carriers. The results suggest that at least some of these genetic polymorphisms may exert major effects on pain perception possibly by influencing the level of expression of the gene product, depending on its function. Finally, polymorphisms alone or interaction between SNPs may alter transcription, mRNA stability, or the protein half-life, leading to a specific clinical status. For those polymorphisms which do not involve amino acid substitution, the observed association with pain perception could be caused by other functional polymorphisms in the neighbouring genes that posses high LDs with tested SNPs

Learning from Few Demonstrations with Frame-Weighted Motion Generation

Learning from Demonstration (LfD) enables robots to acquire versatile skills by learning motion policies from human demonstrations. It endows users with an intuitive interface to transfer new skills to robots without the need for time-consuming robot programming and inefficient solution exploration. During task executions, the robot motion is usually influenced by constraints imposed by environments. In light of this, task-parameterized LfD (TP-LfD) encodes relevant contextual information into reference frames, enabling better skill generalization to new situations. However, most TP-LfD algorithms typically require multiple demonstrations across various environmental conditions to ensure sufficient statistics for a meaningful model. It is not a trivial task for robot users to create different situations and perform demonstrations under all of them. Therefore, this paper presents a novel algorithm to learn skills from few demonstrations. By leveraging the reference frame weights that capture the frame importance or relevance during task executions, our method demonstrates excellent skill acquisition performance, which is validated in real robotic environments.Comment: Accepted by ISER. For the experiment video, see https://youtu.be/JpGjk4eKC3

Vision-based Manipulation of Deformable and Rigid Objects Using Subspace Projections of 2D Contours

This paper proposes a unified vision-based manipulation framework using image contours of deformable/rigid objects. Instead of using human-defined cues, the robot automatically learns the features from processed vision data. Our method simultaneously generates---from the same data---both, visual features and the interaction matrix that relates them to the robot control inputs. Extraction of the feature vector and control commands is done online and adaptively, with little data for initialization. The method allows the robot to manipulate an object without knowing whether it is rigid or deformable. To validate our approach, we conduct numerical simulations and experiments with both deformable and rigid objects

Improving transferability of 3D adversarial attacks with scale and shear transformations

Previous work has shown that 3D point cloud classifiers can be vulnerable to adversarial examples. However, most of the existing methods are aimed at white-box attacks, where the parameters and other information of the classifiers are known in the attack, which is unrealistic for real-world applications. In order to improve the attack performance of the black-box classifiers, the research community generally uses the transfer-based black-box attack. However, the transferability of current 3D attacks is still relatively low. To this end, this paper proposes Scale and Shear (SS) Attack to generate 3D adversarial examples with strong transferability. Specifically, we randomly scale or shear the input point cloud, so that the attack will not overfit the white-box model, thereby improving the transferability of the attack. Extensive experiments show that the SS attack proposed in this paper can be seamlessly combined with the existing state-of-the-art (SOTA) 3D point cloud attack methods to form more powerful attack methods, and the SS attack improves the transferability over 3.6 times compare to the baseline. Moreover, while substantially outperforming the baseline methods, the SS attack achieves SOTA transferability under various defenses. Our code will be available online at https://github.com/cuge1995/SS-attackComment: 10 page

DASTSiam: Spatio-Temporal Fusion and Discriminative Augmentation for Improved Siamese Tracking

Tracking tasks based on deep neural networks have greatly improved with the emergence of Siamese trackers. However, the appearance of targets often changes during tracking, which can reduce the robustness of the tracker when facing challenges such as aspect ratio change, occlusion, and scale variation. In addition, cluttered backgrounds can lead to multiple high response points in the response map, leading to incorrect target positioning. In this paper, we introduce two transformer-based modules to improve Siamese tracking called DASTSiam: the spatio-temporal (ST) fusion module and the Discriminative Augmentation (DA) module. The ST module uses cross-attention based accumulation of historical cues to improve robustness against object appearance changes, while the DA module associates semantic information between the template and search region to improve target discrimination. Moreover, Modifying the label assignment of anchors also improves the reliability of the object location. Our modules can be used with all Siamese trackers and show improved performance on several public datasets through comparative and ablation experiments