1,793 research outputs found
Bolt Detection Signal Analysis Method Based on ICEEMD
The construction quality of the bolt is directly related to the safety of the
project, and as such, it must be tested. In this paper, the improved complete
ensemble empirical mode decomposition (ICEEMD) method is introduced to the bolt
detection signal analysis. The ICEEMD is used in order to decompose the anchor
detection signal according to the approximate entropy of each intrinsic mode
function (IMF). The noise of the IMFs is eliminated by the wavelet soft
threshold de-noising technique. Based on the approximate entropy, and the
wavelet de-noising principle, the ICEEMD-De anchor signal analysis method is
proposed. From the analysis of the vibration analog signal, as well as the bolt
detection signal, the result shows that the ICEEMD-De method is capable of
correctly separating the different IMFs under noisy conditions, and also that
the IMF can effectively identify the reflection signal of the end of the bolt
Graphene Helicoid: The Distinct Properties Promote Application of Graphene Related Materials in Thermal Management
The extremely high thermal conductivity of graphene has received great
attention both in experiments and calculations. Obviously, new feature in
thermal properties is of primary importance for application of graphene-based
materials in thermal management in nanoscale. Here, we studied the thermal
conductivity of graphene helicoid, a newly reported graphene-related
nanostructure, using molecular dynamics simulation. Interestingly, in contrast
to the converged cross-plane thermal conductivity in multi-layer graphene,
axial thermal conductivity of graphene helicoid keeps increasing with thickness
with a power law scaling relationship, which is a consequence of the divergent
in-plane thermal conductivity of two-dimensional graphene. Moreover, the large
overlap between adjacent layers in graphene helicoid also promotes higher
thermal conductivity than multi-layer graphene. Furthermore, in the small
strain regime (< 10%), compressive strain can effectively increase the thermal
conductivity of graphene helicoid, while in the ultra large strain regime
(~100% to 500%), tensile strain does not decrease the heat current, unlike that
in generic solid-state materials. Our results reveal that the divergence in
thermal conductivity, associated with the anomalous strain dependence and the
unique structural flexibility, make graphene helicoid a new platform for
studying fascinating phenomena of key relevance to the scientific understanding
and technological applications of graphene-related materials.Comment: 7 figure
Model and Integrate Medical Resource Available Times and Relationships in Verifiably Correct Executable Medical Best Practice Guideline Models (Extended Version)
Improving patient care safety is an ultimate objective for medical
cyber-physical systems. A recent study shows that the patients' death rate is
significantly reduced by computerizing medical best practice guidelines. Recent
data also show that some morbidity and mortality in emergency care are directly
caused by delayed or interrupted treatment due to lack of medical resources.
However, medical guidelines usually do not provide guidance on medical resource
demands and how to manage potential unexpected delays in resource availability.
If medical resources are temporarily unavailable, safety properties in existing
executable medical guideline models may fail which may cause increased risk to
patients under care. The paper presents a separately model and jointly verify
(SMJV) architecture to separately model medical resource available times and
relationships and jointly verify safety properties of existing medical best
practice guideline models with resource models being integrated in. The SMJV
architecture allows medical staff to effectively manage medical resource
demands and unexpected resource availability delays during emergency care. The
separated modeling approach also allows different domain professionals to make
independent model modifications, facilitates the management of frequent
resource availability changes, and enables resource statechart reuse in
multiple medical guideline models. A simplified stroke scenario is used as a
case study to investigate the effectiveness and validity of the SMJV
architecture. The case study indicates that the SMJV architecture is able to
identify unsafe properties caused by unexpected resource delays.Comment: full version, 12 page
Cross-Video Contextual Knowledge Exploration and Exploitation for Ambiguity Reduction in Weakly Supervised Temporal Action Localization
Weakly supervised temporal action localization (WSTAL) aims to localize
actions in untrimmed videos using video-level labels. Despite recent advances,
existing approaches mainly follow a localization-by-classification pipeline,
generally processing each segment individually, thereby exploiting only limited
contextual information. As a result, the model will lack a comprehensive
understanding (e.g. appearance and temporal structure) of various action
patterns, leading to ambiguity in classification learning and temporal
localization. Our work addresses this from a novel perspective, by exploring
and exploiting the cross-video contextual knowledge within the dataset to
recover the dataset-level semantic structure of action instances via weak
labels only, thereby indirectly improving the holistic understanding of
fine-grained action patterns and alleviating the aforementioned ambiguities.
Specifically, an end-to-end framework is proposed, including a Robust
Memory-Guided Contrastive Learning (RMGCL) module and a Global Knowledge
Summarization and Aggregation (GKSA) module. First, the RMGCL module explores
the contrast and consistency of cross-video action features, assisting in
learning more structured and compact embedding space, thus reducing ambiguity
in classification learning. Further, the GKSA module is used to efficiently
summarize and propagate the cross-video representative action knowledge in a
learnable manner to promote holistic action patterns understanding, which in
turn allows the generation of high-confidence pseudo-labels for self-learning,
thus alleviating ambiguity in temporal localization. Extensive experiments on
THUMOS14, ActivityNet1.3, and FineAction demonstrate that our method
outperforms the state-of-the-art methods, and can be easily plugged into other
WSTAL methods.Comment: Submitted to TCSVT. 14 pages and 7 figure
Liver regeneration: Influence-factors and mechanism of mesenchymal stem cell transplantation
Mesenchymal stem cells (MSCs) are considered the most promising candidate for therapeutic repair of liver disease due to their effect on immune privilege, self-renewal and multidifferential potency. Recently, there have been a number of advances in the area of the factors that influence liver regeneration as well as the impact of MSCs transplantation on liver regeneration. Moreover, there is important new data on the several factors affect the transplantation efficiency of MSC such as therapeutic pretreatment before MSCs transplantation, the impact of cell number and repeated administration on success, and the implications on the outcome for the various approaches used to transplant the cells. Furthermore, other elements the can influence transplantation success also include transdifferentiation of stem cells, improving the microenvironment for implantation, antioxidant treatments, improving hepatocyte viability and immunomodulation strategies. Similarly, there are a number of important pathways that play a vital role, such as IL-6/STAT3 and Wnt/β-catenin signaling, that can also be modified to improve outcomes. MSCs can effectively contribute to liver regeneration and offer an effective alternative therapy to organ transplantation for the treatment of liver diseases. By developing a better understanding of the factors associated with beneficial outcomes, new strategies for the treatment of liver disease can be developed.Keywords: Mesenchymal stem cells, Liver regeneration, Liver disease, Transplantation, Antioxidan
Performance Optimization of Variable Speed Room Air-Conditioner Under Intermediate Speed Working Condition
Through the method of experiment and simulation, some optimized designs have been carried out to improve the performance in intermediate working conditions during the process of performance matching for APF of R32 variable speed room air-conditioner. In this paper the main reason for the poor performance in intermediate conditions of R32 air conditioning system is clarified by the analysis of the heat exchange between the refrigerant side and the air side, and some optimized designs of the indoor unit heat exchanger\u27s pipeline layout and pipe diameter have been carried out. The optimization results show the performance of the intermediate condition has been improved by about 4%, and the performance of APF of the R32 room air conditioning system has been increased by 3.8% compared with the original unit
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