DROP: Dynamics Responses from Human Motion Prior and Projective Dynamics

Synthesizing realistic human movements, dynamically responsive to the environment, is a long-standing objective in character animation, with applications in computer vision, sports, and healthcare, for motion prediction and data augmentation. Recent kinematics-based generative motion models offer impressive scalability in modeling extensive motion data, albeit without an interface to reason about and interact with physics. While simulator-in-the-loop learning approaches enable highly physically realistic behaviors, the challenges in training often affect scalability and adoption. We introduce DROP, a novel framework for modeling Dynamics Responses of humans using generative mOtion prior and Projective dynamics. DROP can be viewed as a highly stable, minimalist physics-based human simulator that interfaces with a kinematics-based generative motion prior. Utilizing projective dynamics, DROP allows flexible and simple integration of the learned motion prior as one of the projective energies, seamlessly incorporating control provided by the motion prior with Newtonian dynamics. Serving as a model-agnostic plug-in, DROP enables us to fully leverage recent advances in generative motion models for physics-based motion synthesis. We conduct extensive evaluations of our model across different motion tasks and various physical perturbations, demonstrating the scalability and diversity of responses.Comment: SIGGRAPH Asia 2023, Video https://youtu.be/tF5WW7qNMLI, Website: https://stanford-tml.github.io/drop

Degradation of Carbon Nanotube Array Thermal Interface Materials through Thermal Aging: Effects of Bonding, Array Height, and Catalyst Oxidation

Carbon nanotube (CNT) array thermal interface materials (TIMs) are promising candidates for high-performance applications in terms of thermal performance. However, in order to be useful in commercial applications, the reliability of the interfaces is an equally important parameter, which so far has not been thoroughly investigated. In this study, the reliability of CNT array TIMs is investigated through accelerated aging. The roles of CNT array height and substrate configuration are studied for their relative impact on thermal resistance degradation. After aging, the CNT catalyst is analyzed using X-ray photoelectron spectroscopy to evaluate chemical changes. The CNT-catalyst bond appears to degrade during aging but not to the extent that the TIM performance is compromised. On the other hand, coefficient of thermal expansion mismatch between surfaces creates strain that needs to be absorbed, which requires CNT arrays with sufficient height. Transfer and bonding of both CNT roots and tips also create more reliable interfaces. Crucially, we find that the CNT array height of most previously reported CNT array TIMs is not enough to prevent significant reliability problems

Chinese herb medicine in augmented reality

Augmented reality becomes popular in education gradually, which provides a contextual and adaptive learning experience. Here, we develop a Chinese herb medicine AR platform based the 3dsMax and the Unity that allows users to visualize and interact with the herb model and learn the related information. The users use their mobile camera to scan the 2D herb picture to trigger the presentation of 3D AR model and corresponding text information on the screen in real-time. The system shows good performance and has high accuracy for the identification of herbal medicine after interference test and occlusion test. Users can interact with the herb AR model by rotating, scaling, and viewing transformation, which effectively enhances learners' interest in Chinese herb medicine

Multiple growth of graphene from a pre-dissolved carbon source

Mono- to few-layer graphene materials are successfully synthesized multiple times using Cu-Ni alloy as a catalyst after a single-chemical vapor deposition (CVD) process. The multiple synthesis is realized by extracting carbon source pre-dissolved in the catalyst substrate. Firstly, graphene is grown by the CVD method on Cu-Ni catalyst substrates. Secondly, the same Cu-Nicatalyst foils are annealed, in absence of any external carbon precursor, to grow graphene using the carbon atoms pre-dissolved in the catalyst during the CVD process. This annealing process is repeated to synthesize graphene successfully until carbon is exhausted in the Cu-Ni foils. After the CVD growth and each annealing growth process, the as-grown graphene is removed using a bubbling transfer method. A wide range of characterizations are performed to examine the quality of the obtained graphene material and to monitor the carbon concentration in the catalyst substrates. Results show that graphene from each annealing growth process possesses a similar quality, which confirmed the good reproducibility of the method. This technique brings great freedom to graphene growth and applications, and it could be also used for other 2D material synthesis

Fault diagnosis of motorized spindle via modified empirical wavelet transform-kernel PCA and optimized support vector machine

The fault diagnosis of motorized spindle contributes to the improvement of the reliability of computer numerical control machine tools. Presently, numerous mechanical fault diagnosis technologies suffer from the drawbacks of mode mixing, non-adaptive analysis, and low efficiency. Therefore, adopting an effective signal processing method for fault diagnosis of motorized spindle is essential. A method based on modified empirical wavelet transform (EWT) and kernel principal component analysis (Kernel PCA) is proposed. A new method, which determines the proper number of the Fourier spectrum segments, is applied when using EWT. To improve computational efficiency, Kernel PCA is adopted to reduce dimension. The support vector machine optimized by genetic algorithm is introduced to accomplish fault identification. The performance of the proposed method is validated through single and compound fault experiments. Results show that the recognition rate using the proposed method reached 98.8095 % and 98.4375 % in terms of single and compound fault diagnoses, respectively. Moreover, compared with empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), local mean decomposition (LMD) and EWT, the proposed method can save much computing time. The proposed method can be generalized to other mechanical fault diagnoses as well

High porosity and light weight graphene foam heat sink and phase change material container for thermal management

During the last decade, graphene foam emerged as a promising high porosity 3-dimensional (3D) structure for various applications. More specifically, it has attracted significant interest as a solution for thermal management in electronics. In this study, we investigate the possibility to use such porous materials as a heat sink and a container for a phase change material (PCM). Graphene foam (GF) was produced using chemical vapor deposition (CVD) process and attached to a thermal test chip using sintered silver nanoparticles (Ag NPs). The thermal conductivity of the graphene foam reached 1.3 W m(-1)K(-1), while the addition of Ag as a graphene foam silver composite (GF/Ag) enhanced further its effective thermal conductivity by 54%. Comparatively to nickel foam, GF and GF/Ag showed lower junction temperatures thanks to higher effective thermal conductivity and a better contact. A finite element model was developed to simulate the fluid flow through the foam structure model and showed a positive and a non-negligible contributions of the secondary microchannel within the graphene foam. A ratio of 15 times was found between the convective heat flux within the primary and secondary microchannel. Our paper successfully demonstrates the possibility of using such 3D porous material as a PCM container and heat sink and highlight the advantage of using the carbon-based high porosity material to take advantage of its additional secondary porosity

Upregulation of Glutamic-Oxaloacetic Transaminase 1 Predicts Poor Prognosis in Acute Myeloid Leukemia

One of the key features of acute myeloid leukemia (AML), a group of very aggressive myeloid malignancies, is their strikingly heterogenous outcomes. Accurate biomarkers are needed to improve prognostic assessment. Glutamate oxaloacetate transaminase 1 (GOT1) is essential for cell proliferation and apoptosis by regulating cell's metabolic dependency on glucose. It is unclear whether the expression level of GOT1 has clinical implications in AML. Therefore, we analyzed the data of 155 AML patients with GOT1 expression information from The Cancer Genome Atlas (TCGA) database. Among them, 84 patients were treated with chemotherapy alone, while 71 received allogeneic hematopoietic stem cell transplantation (allo-HSCT). In both treatment groups, high GOT1 expression was associated with shorter event-free survival (EFS) and overall survival (OS) (all P = 60 years, white blood cell count >= 15 x 10(9)/L, bone marrow blasts >= 70%, and DNMT3A, RUNX1 or TP53 mutations (all P <0.05); but in the allo-HSCT group, the only independent risk factor for survival was high GOT1 expression (P <0.05 for both EFS and OS). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the genes related to GOT1 expression were mainly concentrated in "hematopoietic cell lineage" and "leukocyte transendothelial migration" signaling pathways. Collectively, GOT1 expression may be a useful prognostic indicator in AML, especially in patients who have undergone allo-HSCT

A rolling bearing fault diagnosis method based on VMD – multiscale fractal dimension/energy and optimized support vector machine

To achieve the goal of automated rolling bearing fault diagnosis, a variational mode decomposition (VMD) based diagnosis scheme was proposed. VMD was firstly used to decompose the vibration signals into a series of band-limited intrinsic mode functions (BLIMFs). Subsequently, the multiscale fractal dimension (MSFD) and multiscale energy (MSEN) of each BLIMF were calculated and combined together as features of the original vibration signals. In an attempt to accelerate the classification speed, one-way analysis of variance (ANOVA) test was adopted to extract significant features from the redundant features. Finally, those significant features were fed into the optimized support vector machine (SVM), which was optimized by the genetic algorithm (GA), for classification. Experimental results on the international public Case Western Reserve University bearing data indicate the effectiveness of the proposed method with a classification accuracy of 99.75 % for seven classes. Moreover, our approach also shows good anti-noise performance in different signal-to-noise ratios (SNRs)

Integrative proteomics and metabolomics approach to identify the key roles of icariin-mediated protective effects against cyclophosphamide-induced spermatogenesis dysfunction in mice

The alkylating antineoplastic agent cyclophosphamide (CP) is known to be toxic to the male reproductive system, but there are no effective prevention or treatment options. The flavonoid icariin (ICA), which is used in Chinese medicine, has been shown to have a number of biological functions, including testicular protection. The current study looked into the protective effects of ICA in preventing CP-induced spermatogenesis dysfunction. The current study looked into the role of ICA in preventing testicular dysfunction caused by CP. For 5 days, healthy adult mice were given saline or a single dose of CP (50 mg/kg) intraperitoneally (i.p). For the next 30 days, mice were given ICA (80 mg/kg) by gavage. Animals were euthanized 12 h after receiving ICA, and testes were removed for biochemical, histopathological, sperm evaluation, and transmission electron microscope analysis (TEM). We also investigated the potential biological effects of ICA on CP-induced spermatogenesis dysfunction in mice using an integrated proteomic and metabolomic approach. The levels of 8309 proteins and 600 metabolites were measured. The majority of the differential proteins and metabolites were found to be enriched in a variety of metabolic pathways, including the PI3K-Akt signaling pathway, necroptosis, the mTOR signaling pathway, glycerophospholipid metabolism, and ABC transporters, implying that ICA may have molecular mechanisms that contribute to CP-induced spermatogenesis dysfunction in the testis. Taken together, these findings show that ICA effectively reduces testis injury, implying that ICA may have a role in male infertility preservation