TENT: Connect Language Models with IoT Sensors for Zero-Shot Activity Recognition

Recent achievements in language models have showcased their extraordinary capabilities in bridging visual information with semantic language understanding. This leads us to a novel question: can language models connect textual semantics with IoT sensory signals to perform recognition tasks, e.g., Human Activity Recognition (HAR)? If so, an intelligent HAR system with human-like cognition can be built, capable of adapting to new environments and unseen categories. This paper explores its feasibility with an innovative approach, IoT-sEnsors-language alignmEnt pre-Training (TENT), which jointly aligns textual embeddings with IoT sensor signals, including camera video, LiDAR, and mmWave. Through the IoT-language contrastive learning, we derive a unified semantic feature space that aligns multi-modal features with language embeddings, so that the IoT data corresponds to specific words that describe the IoT data. To enhance the connection between textual categories and their IoT data, we propose supplementary descriptions and learnable prompts that bring more semantic information into the joint feature space. TENT can not only recognize actions that have been seen but also ``guess'' the unseen action by the closest textual words from the feature space. We demonstrate TENT achieves state-of-the-art performance on zero-shot HAR tasks using different modalities, improving the best vision-language models by over 12%.Comment: Preprint manuscript in submissio

MM-Fi: Multi-Modal Non-Intrusive 4D Human Dataset for Versatile Wireless Sensing

4D human perception plays an essential role in a myriad of applications, such as home automation and metaverse avatar simulation. However, existing solutions which mainly rely on cameras and wearable devices are either privacy intrusive or inconvenient to use. To address these issues, wireless sensing has emerged as a promising alternative, leveraging LiDAR, mmWave radar, and WiFi signals for device-free human sensing. In this paper, we propose MM-Fi, the first multi-modal non-intrusive 4D human dataset with 27 daily or rehabilitation action categories, to bridge the gap between wireless sensing and high-level human perception tasks. MM-Fi consists of over 320k synchronized frames of five modalities from 40 human subjects. Various annotations are provided to support potential sensing tasks, e.g., human pose estimation and action recognition. Extensive experiments have been conducted to compare the sensing capacity of each or several modalities in terms of multiple tasks. We envision that MM-Fi can contribute to wireless sensing research with respect to action recognition, human pose estimation, multi-modal learning, cross-modal supervision, and interdisciplinary healthcare research.Comment: The paper has been accepted by NeurIPS 2023 Datasets and Benchmarks Track. Project page: https://ntu-aiot-lab.github.io/mm-f

High Concentration of Aspirin Induces Apoptosis in Rat Tendon Stem Cells via Inhibition of the Wnt/β-Catenin Pathway

Background/Aims: Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used in clinical practice to relieve fever and pain. Aspirin, as a representative NSAID, has been widely used in the treatment of tendinopathy. Some reports have demonstrated that aspirin can induce apoptosis in cancer cells. However, evidence regarding aspirin treatment for tendinopathy, especially the effect of this treatment on tendon stem cells (TSCs), is lacking. Understanding the effect of aspirin on tendinopathy may provide a basis for the rational use of NSAIDs in clinical practice. The aim of our study was to determine whether aspirin induces apoptosis in rat TSCs via the Wnt/β-catenin pathway. Methods: First, we used flow cytometry and fluorescence to detect TSC apoptosis. Protein expression of the apoptosis-related caspase-3 pathway was investigated via western blot analysis. Next, we used western blotting to determine the effect of aspirin on the Wnt/β-catenin pathway. We used immunostaining to detect the levels of Bcl2, cleaved caspase-3, and P-β-catenin in the Achilles tendon. Finally, we used flow cytometry, fluorescence, and western blotting to investigate the aspirin-induced apoptosis of TSCs via the Wnt/β-catenin pathway. Results: Aspirin induced morphological apoptosis in rat TSCs via the mitochondrial/caspase-3 pathway and induced cellular apoptosis in the Achilles tendon. Apoptosis was partly reversed after adding the Wnt signaling activator Wnt3a and lithium chloride (LiCl, a GSK-3β inhibitor). Aspirin administration led to a dose-dependent increase in COX-2 expression. Apoptosis was promoted after adding the COX-2 inhibitor NS398. Conclusion: The Wnt/β-catenin pathway plays a vital role in aspirin-induced apoptosis by regulating mitochondrial/caspase-3 function. Elevating COX-2 levels may protect cells against apoptosis. More importantly, the results remind us to consider the apoptotic effect of aspirin on TSCs and tendon cells when aspirin is administered to treat tendinopathy. The relationship between the positive and negative effects of aspirin remains a subject for future study

Induction of cyto-protective autophagy by paramontroseite VO2 nanocrystals

Chinese Ministry of Sciences 973 Program [2013CB933900]; Natural Science Foundation of China [30830036, 31170966, 31071211]; Fundamental Research Funds for the Central Universities [WK2070000008]A variety of inorganic nanomaterials have been shown to induce autophagy, a cellular degradation process critical for the maintenance of cellular homeostasis. The overwhelming majority of autophagic responses elicited by nanomaterials were detrimental to cell fate and contributed to increased cell death. A widely held view is that the inorganic nanoparticles, when encapsulated and trapped by autophagosomes, may compromise the normal autophagic process due to the inability of the cells to degrade these materials and thus they manifest a detrimental effect on the well-being of a cell. Here we show that, contrary to this notion, nano-sized paramontroseite VO2 nanocrystals (P-VO2) induced cyto-protective, rather than death-promoting, autophagy in cultured HeLa cells. P-VO2 also caused up-regulation of heme oxygenase-1 (HO-1), a cellular protein with a demonstrated role in protecting cells against death under stress situations. The autophagy inhibitor 3-methyladenine significantly inhibited HO-1 up-regulation and increased the rate of cell death in cells treated with P-VO2, while the HO-1 inhibitor protoporphyrin IX zinc (II) (ZnPP) enhanced the occurrence of cell death in the P-VO2-treated cells while having no effect on the autophagic response induced by P-VO2. On the other hand, Y2O3 nanocrystals, a control nanomaterial, induced death-promoting autophagy without affecting the level of expression of HO-1, and the pro-death effect of the autophagy induced by Y2O3. Our results represent the first report on a novel nanomaterial-induced cyto-protective autophagy, probably through up-regulation of HO-1, and may point to new possibilities for exploiting nanomaterial-induced autophagy for therapeutic applications

Learning multi-modal scale-aware attentions for efficient and robust road segmentation

Multi-modal fusion has proven to be beneficial to road segmentation in autonomous driving, where depth is commonly used as complementary data for RGB images to provide robust 3D geometry information. Existing methods adopt an encoder-decoder structure to fuse two modalities for segmentation through encoding and concatenating high-level and low-level features. However, this leads to increasing semantic gaps not only among modalities, but also different scales, which are detrimental to road segmentation. To overcome this challenge and obtain robust features, we propose a Multi-modal Scale-aware Attention Network (MSAN), to fuse RGB and depth data effectively via a novel transformer-based cross-attention module, namely Multi-modal Scare-aware Transformer (MST), which fuses RGB-D features across multiple scales at the encoder stage. To better consolidate different scales of feature, we further propose a Scale-aware Attention Module (SAM) that captures channel-wise attention for cross-scale fusion. The two attention-based modules focus on exploring the complementarity of modalities and the different importance of scales to narrow the gaps for road segmentation. Extensive experiments demonstrate that our method achieves competitive segmentation performance at a low computational cost.Master of Science (Computer Control and Automation

Characteristics and Source Analysis of High-Arsenic Groundwater in Typical Watershed Areas of Tibet, China

High-arsenic water limits the utilization and development of water resources in Tibet, and high-arsenic groundwater is one of the major sources of arsenic input to surface water in the area. In this work, the characteristics of groundwater and the source and formation of arsenic in a typical watershed in Tibet (the lower tributaries of the Angqu River) were investigated using systematic surveys, ionic ratios, Gibbs diagrams, in combination with isotopic and heat storage calculation methods. The studies show that the chemical composition of the water in the study area is mainly determined by the rock weathering of carbonate and silicate rocks. The average recharge elevation levels of hot spring water are 4874.1 m, 4058.1 m, and 4745.0 m, respectively. Deep hot water is the main source of arsenic in the spring water, and its arsenic flux accounts for 98.44–99.77% of the measured flux in the spring water

Rap1A Regulates Osteoblastic Differentiation via the ERK and p38 Mediated Signaling.

Rap1A is a member of small G proteins belonging to the Ras family. Recently, an integration of human genome-wide association studies (GWAS) and gene expression profiling study revealed that single-nucleotide polymorphisms (SNPs) within human Rap1A were strongly associated with narrow neck width in women. However, the regulatory role of Rap1A in osteoblasts remains to be elucidated. Here we report that Rap1A is a key regulator in osteoblast differentiation. Rap1A expression and activity were gradually enhanced during the induced differentiation of multipotent mesenchymal progenitor cells (C2C12) and preosteoblastic cells (MC3T3-E1). Knockdown of endogenous Rap1A significantly inhibited the osteogenic marker gene expression and matrix mineralization in cells with osteogenesis. In addition, knockdown of endogenous Rap1A suppressed the activation of extracellular signal-regulated kinase (ERK) and p38 mitogen-activated protein kinase (MAPK), while overexpression of Rap1A accelerated osteoblast differentiation and enhanced the phosphorylation of ERK and p38. Taken together, our study suggests that Rap1A regulates osteoblast differentiation through modulating the ERK/p38 signaling

Suppress voltage decay of lithium-rich materials by coating layers with different crystalline states

Li-rich oxides are considered as the most commercial potential cathode materials due to the high theoretical specific discharge capacity. Here, ZrO2 in different crystalline states are applied as the coating layers to enhance the electrochemical performance of hollow Li[Li0.2Mn0.54Ni0.13Co0.13]O2 materials. Meanwhile, a series of characterizations (XRD, SEM, TEM, EDX etc.) are conducted to compare the effects of ZrO2 coating layer with different crystalline states on the host material. The results elucidate that the Li-rich Mn-based material with the polycrystal ZrO2 coating layer has a slight advantage in rate performance, while the host material with the single crystal ZrO2-coating layer has a better cycling performance and effectively suppresses voltage decay with the effect of excellently inhibiting layered to spinel-like phase transition and metal dissolution during charging and discharging process.</p