Substructuring Method in Structural Health Monitoring

In sensitivity-based finite element model updating, the eigensolutions and eigensensitivities are calculated repeatedly, which is a time-consuming process for large-scale structures. In this chapter, a forward substructuring method and an inverse substructuring method are proposed to fulfill the model updating of large-scale structures. In the forward substructuring method, the analytical FE model of the global structure is divided into several independent substructures. The eigensolutions of each independent substructure are used to recover the eigensolutions and eigensensitivities of the global structure. Consequently, only some specific substructures are reanalyzed in model updating and assembled with other untouched substructures to recover the eigensolutions and eigensensitivities of the global structure. In the inverse substructuring method, the experimental modal data of the global structure are disassembled into substructural flexibility. Afterwards, each substructure is treated as an independent structure to reproduce its flexibility through a model-updating process. Employing the substructuring method, the model updating of a substructure can be conducted by measuring the local area of the concerned substructure solely. Finally, application of the proposed methods to a laboratory tested frame structure reveals that the forward and inverse substructuring methods are effective in model updating and damage identification

Learning Second Order Local Anomaly for General Face Forgery Detection

In this work, we propose a novel method to improve the generalization ability of CNN-based face forgery detectors. Our method considers the feature anomalies of forged faces caused by the prevalent blending operations in face forgery algorithms. Specifically, we propose a weakly supervised Second Order Local Anomaly (SOLA) learning module to mine anomalies in local regions using deep feature maps. SOLA first decomposes the neighborhood of local features by different directions and distances and then calculates the first and second order local anomaly maps which provide more general forgery traces for the classifier. We also propose a Local Enhancement Module (LEM) to improve the discrimination between local features of real and forged regions, so as to ensure accuracy in calculating anomalies. Besides, an improved Adaptive Spatial Rich Model (ASRM) is introduced to help mine subtle noise features via learnable high pass filters. With neither pixel level annotations nor external synthetic data, our method using a simple ResNet18 backbone achieves competitive performances compared with state-of-the-art works when evaluated on unseen forgeries

Inclusions properties at 1673 K and room temperature with Ce addition in SS400 steel

Inclusion species formed in SS400 steel with Ce-addition was predicted by thermodynamic calculation. The analysis of the inclusion morphology and size distribution was carried out by applying Scanning Electron Microscopy (SEM) and Transmission Electron Microscope (TEM). Nano-Fe3O4 particles were also found in cerium-deoxidized and -desulfurized steel and their shapes were nearly spherical. The complex Ce2O3 inclusions covering a layer of 218 nm composed by several MnS particles with similar diffraction pattern. Most importantly, the complex Ce2O3 characterized by using TEM diffraction is amorphous in the steel, indicating that Ce2O3 formed in the liquid iron and then MnS segregated cling to it

Large Language Models are reasoners with Self-Verification

When a large language model (LLM) performs complex reasoning by chain of thought (CoT), it can be highly sensitive to individual mistakes. We have had to train verifiers to address this issue. As we all know, after human inferring a conclusion, they often check it by re-verifying it, which can avoid some mistakes. We propose a new method called self-verification that uses the conclusion of the CoT as a condition to build a new sample and asks the LLM to re-predict the original conditions which be masked. We calculate an explainable verification score based on the accuracy. This method can improve the accuracy of multiple arithmetics and logical reasoning datasets when using few-shot learning. we have demonstrated that LLMs can conduct explainable self-verification of their own conclusions and achieve competitive reasoning performance. Extensive experimentals have demonstrated that our method can help multiple large language models with self-verification can avoid interference from incorrect CoT. Code is available at \url{https://github.com/WENGSYX/Self-Verification

Community Involvement in Urban Water Management: The N Park Resort Condominium Rainfall Harvesting and Water Saving Project in Penang, Malaysia

Community engagement and involvement is vital for the success of urban water management. However, poor public engagement, cheap water tariffs, apathetic attitude and lack of public interest are identified as the main reasons for high water wastage in Penang State, Malaysia. The N Park Resort Condominium rainfall harvesting and water saving project in Penang, Malaysia is a prime example of successful urban water management involving government, private sector, non-governmental organisations (NGOs) and local communities. The N-Park condominium consisting of 965 units is the first condominium in the country to initiate a community water- saving project. Started in August 2009 and completed in December 2010, the project is jointly implemented by the Drainage and Irrigation Department (DID) Malaysia (Government), Water Watch Penang (WWP) (NGO), N-Park Management Corporation (NPMC)(Community) and the Penang Water Supply Corporation (PWSC). The methodology involved installation of a rainwater harvesting system, installation of water-saving devices and a water-saving campaign. Results of the project showed that the rainwater harvesting system was most successful as the rainwater harvested was used for gardening, washing common areas and toilets, flushing toilets, and washing vehicles. The installation of water-saving devices was also successful as it resulted in substantial water savings. Results showed reduced total water usage from 8 to 25 % between September 2009 to March 2010. The greatest reduction by 50 % was between May and July 2011, followed by 47.5 % in January 2011. During the time of the project, the amount of water saved was equivalent to RM1,3971 in monetary savings per month. Over a year, this is translated to a savings of 16,818 m3 of water or the equivalent of RM 16,782. More recently, between February 2020 and April 2021, the average water saved was 5852 m3 per month or averaging 48.77 % per month, equivalent to about RM34,255. Results also showed enhanced water awareness and better relationships between neighbours. Overall, this project proved that collaboration between government-private sector-NGOs is workable, and the project can be replicated nation-wide in apartments, hotels, factories, universities, and schools

Laser pulse compression towards collapse and beyond in plasma

The dynamics of three-dimensional (3D) compression of ultrashort intense laser pulses in plasma is investigated theoretically and numerically. Starting from the slowly-varying envelope model, we derive equations describing the spatiotemporal evolution of a short laser pulse towards the singularity, or collapse, based on the variational method. In particular, the laser and plasma conditions leading to spherical compression are obtained. 3D particle-in-cell simulations are carried out to verify these conditions, which also enable one to examine the physical processes both towards and beyond the pulse collapse. Simulations suggest that the laser pulse can be spherically compressed down to a minimum size of the order of the laser wavelength, the so called lambda-cubic regime. The compression process develops over twice as fast in simulation than is predicted by the envelope model, due to the simplified nature of the latter. The final result of this process is pulse collapse, which is accompanied with strong plasma density modulation and spectrum broadening. The collapse can occur multiple times during the laser pulse propagation, until a significant part of the pulse energy is dissipated to electron acceleration by the laser ponderomitve force. It is also shown that a strong external DC magnetic field applied along the laser propagation direction can enhance the rate of compression for circularly-polarised laser pulses, when compared to an unmagnetised plasma, allowing access to strong compression and focusing in the low-density and low-amplitude regime

Pheophorbide b ethyl ester from a chlorella vulgaris dietary supplement

In the title compound, C37H38N4O6, four five-membered nitro­gen-bearing rings are nearly coplanar. Two N atoms in two these five-membered rings have attached H atoms, which contribute to the formation of intra­molecular N—H⋯N hydrogen bonds [N⋯N = 2.713 (5)–3.033 (6) Å]