Mid-frequency prediction of transmission loss using a novel hybrid deterministic and statistical method

A novel hybrid deterministic-statistical approach named ES-FE-SEA method specially used to predict the sound Transmission loss of panels in mid-frequency is proposed in this paper. The proposed hybrid methods takes the best advantages of edged-based smoothing FEM (ES-FEM) and statistical energy analysis (SEA) to further improve the accuracy of mid-frequency transmission loss predictions. The application of ES-FEM will “soften” the well-known “overly-stiff” behavior in the standard FEM solution and reduce the inherent numerical dispersion error. While the SEA approach will deal with the physical uncertainty in the relatively higher frequency range. Two different types of subsystems will be coupled based on “reciprocity relationship” theorem. The proposed was firstly applied to a standard simple numerical example, and excellent agreement with reference results was achieved. Thus the method is then applied to a more complicated model-a 2D dash panel in a car. The proposed ES-FE-SEA is verified by various numerical examples

Longquan celadon: a quantified archaeological analysis of a pan-Indian Ocean industry of the 12th to 15th centuries

This paper examines the Longquan celadon industry, located in Zhejiang province in China, which flourished mainly between the Southern Song and early Ming dynasties (12th to 15th century). The products of this industry are found on archaeological sites from across China and the Indian Ocean. This paper attempts a quantified analysis of the development of the industry based on archaeological data, focussing on four aspects: production, domestic consumption, overseas consumption and, to a lesser degree, workshop organisation. Although much of the data is still, in many ways, problematic, and many of the conclusions drawn are necessarily tentative, it is possible to demonstrate the value and timeliness of the approach by charting the overall development of this industry and by arguing that the close integration of the four aspects examined indicates that the Longquan celadon industry was an industry of considerable economic significance across much of the Indian Ocean

Surface roughness of thin wood veneers sliced from laminated green wood lumber

Freshly-felled Chinese fir (Cunninghamia lanceolate), Masson Pine (Pinus massoniana) and Camphor Tree (Cinnamomum camphora) logs were reconstituted to form laminated lumber with moisture content above fiber saturation point by slicing, finger-jointing, gluing, and cold-pressing processes. The laminated lumber was then sliced into wood veneers, which were air-dried to about 15% moisture content. The surface roughness of the veneer was tested in comparison with two commercial engineered wood veneers using a stylus tracing method. The influence of  the wood surface roughness was relatively  small  for  the  wood  species chosen due  to  their  similar densities. All roughness parameter values were consistently larger along the transverse direction compared with these along longitudinal direction. The values of surface roughness at the finger-joint region were higher than these that at the non-finger-joint region along both longitudinal direction and transverse direction. The two engineered wood veneers had surface roughness values noticeably smaller in the longitudinal direction, but their values in transverse direction were comparable and even larger compared with these of the prepared wood veneers including both non-finger-joint and finger-joint regions.  Overall, the process of laminating finger-jointed green wood planks and subsequently slicing can be used to yield acceptable wood veneers with sufficient surface quality

The lithospheric S-wave velocity structure beneath the NE Tibetan Plateau and its surrounding craton basins

It is essential to investigate the spatial distribution of the lithosphere and asthenosphere in detail, to further obtain the understanding of the effect of plate collision and the process of orogenic movement. From the joint inversion of receiver functions and surface waves, the three-dimensional S-wave velocity structure results down to 200 km depth in the study area were obtained at 1,843 seismic stations. Analysis was performed on the sedimentary thickness, crustal thickness, lower crustal wave velocity, and lithospheric thickness. According to the crustal thickness, we evaluated the distribution of low-velocity zones in the lower crust. The results show that there are low-velocity bodies in the lower crust in the Qinling tectonic belt, but they are not connected, indicating that they may not be able to be used as a channel for material extrusion from the NE Tibetan Plateau at the crustal scale. According to the section results and the depth distribution of the lithosphere-astenosphere boundary, a relatively thick lithosphere exists below the Sichuan Basin and Ordos Basin, and the lithosphere in the east of the study area is relatively thin with a thickness of about 60–80 km, indicating that the lithosphere in the east of the study area has been severely destructed and restructured. The delamination has been observed in the lithosphere under the Songpan-Ganzi Block, showing characteristics of vertical movement of asthenosphere materials. There is a relatively thick low-velocity zone at the top of the mantle lithosphere of the NE plateau; however, it does not exist under the relatively stable Sichuan Basin and the Ordos Block. Compared with the Sichuan Basin and the Ordos Basin at both sides, the Qinling tectonic belt has a low-velocity zone at the depth of 100–160 km, which may be asthenosphere material. In combination with the polarization direction characteristics of the SKS wave, it is clearly observed that asthenospheric material movement exists in an approximate east-west direction beneath the Qinling tectonic belt. Therefore, the asthenosphere beneath the Qinling tectonic belt may serve as an important channel for material extrusion in the NE Tibetan Plateau

CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs

Controllable scene synthesis aims to create interactive environments for various industrial use cases. Scene graphs provide a highly suitable interface to facilitate these applications by abstracting the scene context in a compact manner. Existing methods, reliant on retrieval from extensive databases or pre-trained shape embeddings, often overlook scene-object and object-object relationships, leading to inconsistent results due to their limited generation capacity. To address this issue, we present CommonScenes, a fully generative model that converts scene graphs into corresponding controllable 3D scenes, which are semantically realistic and conform to commonsense. Our pipeline consists of two branches, one predicting the overall scene layout via a variational auto-encoder and the other generating compatible shapes via latent diffusion, capturing global scene-object and local inter-object relationships while preserving shape diversity. The generated scenes can be manipulated by editing the input scene graph and sampling the noise in the diffusion model. Due to lacking a scene graph dataset offering high-quality object-level meshes with relations, we also construct SG-FRONT, enriching the off-the-shelf indoor dataset 3D-FRONT with additional scene graph labels. Extensive experiments are conducted on SG-FRONT where CommonScenes shows clear advantages over other methods regarding generation consistency, quality, and diversity. Codes and the dataset will be released upon acceptance

Fractional creep model and experimental study of unsaturated silty clay in Fuyang

Due to the long-term overdraft of groundwater in Fuyang, silty clay in this area has been in an unsaturated state for a long time, which caused ground subsidence and threatened the safety of engineering construction. Creep is an important part of ground subsidence, but it is easily ignored in ground subsidence caused by groundwater overdraft. Therefore, in order to explore the creep behavior in this environment, a series of triaxial creep tests of unsaturated soil were conducted to research the effects of deviator stress, matrix suction and net confining pressure on creep. Then, based on analysis results of the geometric characteristics of the test creep curves, an improved fractional order Nishihara model of unsaturated soil under triaxial stress conditions was constructed by using fractional calculus theory. Finally, the effectiveness of improved fractional order Nishihara model was verified based on cooperation search algorithm and minimum mean square error principle. The simulation results show that the fitting curves of improved fractional order Nishihara model are in good agreement with the test curves, and it is feasible and effective to describe the creep characteristics of unsaturated silty clay in Fuyang

Deep Learning Approach for Large-Scale, Real-Time Quantification of Green Fluorescent Protein-Labeled Biological Samples in Microreactors

Absolute quantification of biological samples entails determining expression levels in precise numerical copies, offering enhanced accuracy and superior performance for rare templates. However, existing methodologies suffer from significant limitations: flow cytometers are both costly and intricate, while fluorescence imaging relying on software tools or manual counting is time-consuming and prone to inaccuracies. In this study, we have devised a comprehensive deep-learning-enabled pipeline that enables the automated segmentation and classification of GFP (green fluorescent protein)-labeled microreactors, facilitating real-time absolute quantification. Our findings demonstrate the efficacy of this technique in accurately predicting the sizes and occupancy status of microreactors using standard laboratory fluorescence microscopes, thereby providing precise measurements of template concentrations. Notably, our approach exhibits an analysis speed of quantifying over 2,000 microreactors (across 10 images) within remarkably 2.5 seconds, and a dynamic range spanning from 56.52 to 1569.43 copies per micron-liter. Furthermore, our Deep-dGFP algorithm showcases remarkable generalization capabilities, as it can be directly applied to various GFP-labeling scenarios, including droplet-based, microwell-based, and agarose-based biological applications. To the best of our knowledge, this represents the first successful implementation of an all-in-one image analysis algorithm in droplet digital PCR (polymerase chain reaction), microwell digital PCR, droplet single-cell sequencing, agarose digital PCR, and bacterial quantification, without necessitating any transfer learning steps, modifications, or retraining procedures. We firmly believe that our Deep-dGFP technique will be readily embraced by biomedical laboratories and holds potential for further development in related clinical applications.Comment: 23 pages, 6 figures, 1 tabl

HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Pose Dataset with Household Objects in Realistic Scenarios

Estimating the 6D pose of objects is a major 3D computer vision problem. Since the promising outcomes from instance-level approaches, research heads also move towards category-level pose estimation for more practical application scenarios. However, unlike well-established instance-level pose datasets, available category-level datasets lack annotation quality and provided pose quantity. We propose the new category-level 6D pose dataset HouseCat6D featuring 1) Multi-modality of Polarimetric RGB and Depth (RGBD+P), 2) Highly diverse 194 objects of 10 household object categories including 2 photometrically challenging categories, 3) High-quality pose annotation with an error range of only 1.35 mm to 1.74 mm, 4) 41 large-scale scenes with extensive viewpoint coverage and occlusions, 5) Checkerboard-free environment throughout the entire scene, and 6) Additionally annotated dense 6D parallel-jaw grasps. Furthermore, we also provide benchmark results of state-of-the-art category-level pose estimation networks

Stevioside Prevents Wear Particle-Induced Osteolysis by Inhibiting Osteoclastogenesis and Inflammatory Response via the Suppression of TAK1 Activation

Aseptic loosening and periprosthetic osteolysis are the leading causes of total joint arthroplasty failure, which occurs as a result of chronic inflammatory response and enhanced osteoclast activity. Here we showed that stevioside, a natural compound isolated from Stevia rebaudiana, exhibited preventative effects on titanium particle-induced osteolysis in a mouse calvarial model. Further histological assessment and real-time PCR analysis indicated that stevioside prevented titanium particle-induced osteolysis by inhibiting osteoclast formation and inflammatory cytokine expression in vivo. In vitro, we found that stevioside could suppress RANKL-induced osteoclastogenesis and titanium particle-induced inflammatory response in a dose-dependent manner. Mechanistically, stevioside achieved these effects by disrupting the phosphorylation of TAK1 and subsequent activation of NF-κB/MAPKs signaling pathways. Collectively, our data suggest that stevioside effectively suppresses osteoclastogenesis and inflammatory response both in vitro and in vivo, and it might be a potential therapy for particle-induced osteolysis and other osteolytic diseases