Exploiting Spatial-Temporal Context for Interacting Hand Reconstruction on Monocular RGB Video

Reconstructing interacting hands from monocular RGB data is a challenging task, as it involves many interfering factors, e.g. self- and mutual occlusion and similar textures. Previous works only leverage information from a single RGB image without modeling their physically plausible relation, which leads to inferior reconstruction results. In this work, we are dedicated to explicitly exploiting spatial-temporal information to achieve better interacting hand reconstruction. On one hand, we leverage temporal context to complement insufficient information provided by the single frame, and design a novel temporal framework with a temporal constraint for interacting hand motion smoothness. On the other hand, we further propose an interpenetration detection module to produce kinetically plausible interacting hands without physical collisions. Extensive experiments are performed to validate the effectiveness of our proposed framework, which achieves new state-of-the-art performance on public benchmarks.Comment: 16 page

BEST: BERT Pre-Training for Sign Language Recognition with Coupling Tokenization

In this work, we are dedicated to leveraging the BERT pre-training success and modeling the domain-specific statistics to fertilize the sign language recognition~(SLR) model. Considering the dominance of hand and body in sign language expression, we organize them as pose triplet units and feed them into the Transformer backbone in a frame-wise manner. Pre-training is performed via reconstructing the masked triplet unit from the corrupted input sequence, which learns the hierarchical correlation context cues among internal and external triplet units. Notably, different from the highly semantic word token in BERT, the pose unit is a low-level signal originally located in continuous space, which prevents the direct adoption of the BERT cross-entropy objective. To this end, we bridge this semantic gap via coupling tokenization of the triplet unit. It adaptively extracts the discrete pseudo label from the pose triplet unit, which represents the semantic gesture/body state. After pre-training, we fine-tune the pre-trained encoder on the downstream SLR task, jointly with the newly added task-specific layer. Extensive experiments are conducted to validate the effectiveness of our proposed method, achieving new state-of-the-art performance on all four benchmarks with a notable gain.Comment: Accepted by AAAI 2023 (Oral

Feature Fusion from Head to Tail for Long-Tailed Visual Recognition

The imbalanced distribution of long-tailed data presents a considerable challenge for deep learning models, as it causes them to prioritize the accurate classification of head classes but largely disregard tail classes. The biased decision boundary caused by inadequate semantic information in tail classes is one of the key factors contributing to their low recognition accuracy. To rectify this issue, we propose to augment tail classes by grafting the diverse semantic information from head classes, referred to as head-to-tail fusion (H2T). We replace a portion of feature maps from tail classes with those belonging to head classes. These fused features substantially enhance the diversity of tail classes. Both theoretical analysis and practical experimentation demonstrate that H2T can contribute to a more optimized solution for the decision boundary. We seamlessly integrate H2T in the classifier adjustment stage, making it a plug-and-play module. Its simplicity and ease of implementation allow for smooth integration with existing long-tailed recognition methods, facilitating a further performance boost. Extensive experiments on various long-tailed benchmarks demonstrate the effectiveness of the proposed H2T. The source code is available at https://github.com/Keke921/H2T.Comment: Accepted to AAAI24, similar to the conference version. Add the supplementr

Challenges and Opportunities for Second-life Batteries: A Review of Key Technologies and Economy

Due to the increasing volume of Electric Vehicles in automotive markets and the limited lifetime of onboard lithium-ion batteries (LIBs), the large-scale retirement of LIBs is imminent. The battery packs retired from Electric Vehicles still own 70%-80% of the initial capacity, thus having the potential to be utilized in scenarios with lower energy and power requirements to maximize the value of LIBs. However, spent batteries are commonly less reliable than fresh batteries due to their degraded performance, thereby necessitating a comprehensive assessment from safety and economic perspectives before further utilization. To this end, this paper reviews the key technological and economic aspects of second-life batteries (SLBs). Firstly, we introduce various degradation models for first-life batteries and identify an opportunity to combine physics-based theories with data-driven methods to establish explainable models with physical laws that can be generalized. However, degradation models specifically tailored to SLBs are currently absent. Therefore, we analyze the applicability of existing battery degradation models developed for first-life batteries in SLB applications. Secondly, we investigate fast screening and regrouping techniques and discuss the regrouping standards for the first time to guide the classification procedure and enhance the performance and safety of SLBs. Thirdly, we scrutinize the economic analysis of SLBs and summarize the potentially profitable applications. Finally, we comprehensively examine and compare power electronics technologies that can substantially improve the performance of SLBs, including high-efficiency energy transformation technologies, active equalization technologies, and technologies to improve reliability and safety

Free chlorine loss during spraying of membraneless acidic electrolyzed water and its antimicrobial effect on airborne bacteria from poultry house

Spray-application of membraneless acidic electrolyzed water (MLAEW) is a novel technique for disinfection in livestock houses. This study investigated the loss of free chlorine (FC – the major germicidal component in MLAEW) over distance during spraying, as affected by air temperature and initial FC concentration. The anti-microbial effect of MLAEW on airborne bacteria from an aviary laying-hen house was examined. materials and methods. MLAEW was prepared at two FC concentrations: app. 15 and 60 mg L -1 , and sprayed at three air temperatures (18, 25, 32 °C). The original MLAEW solution and MLAEW aerosols collected at 0, 25, and 50 cm from the spray nozzle were analyzed for FC concentrations. Bacteria were immersed into these MLAEW samples and numerated for viable count after 0.5, 2 and 5-min treatments. results. MLAEW aerosols collected at 0 cm lost 11.7–13.2% FC, compared with the original MLAEW solution. This initial loss was affected neither by the initial FC concentration (P = 0.13) nor by air temperature (P = 0.57). The rate of FC loss during travelling was 0.79–0.87 % per cm of aerosol travel distance (% cm -1 ) at 18 °C, 1.08–1.15 % cm -1 at 25 °C, and 1.35–1.49% cm -1 at 32 °C. This travelling loss was affected by air temperature (P = 0.02), but not by initial FC concentration (P = 0.38). Bacteria were completely inactivated at 0.5 min when treated with MLAEW samples with FC \u3e 16.8 mg L -1 , in 2 min when FC \u3e 13.8 mg L -1 , and in 5 min when FC \u3e 7.2 mg L -1 . conclusion. Airborne bacteria from aviary hen house can be effectively inactivated by MLAEW with adequate FC concentration and contact time. During spraying, the anti-microbial efficacy of MLAEW aerosols decreased over distance due to FC loss which exacerbated at higher air temperatures

Large Language Models as Source Planner for Personalized Knowledge-grounded Dialogue

Open-domain dialogue system usually requires different sources of knowledge to generate more informative and evidential responses. However, existing knowledge-grounded dialogue systems either focus on a single knowledge source or overlook the dependency between multiple sources of knowledge, which may result in generating inconsistent or even paradoxical responses. To incorporate multiple knowledge sources and dependencies between them, we propose SAFARI, a novel framework that leverages the exceptional capabilities of large language models (LLMs) in planning, understanding, and incorporating under both supervised and unsupervised settings. Specifically, SAFARI decouples the knowledge grounding into multiple sources and response generation, which allows easy extension to various knowledge sources including the possibility of not using any sources. To study the problem, we construct a personalized knowledge-grounded dialogue dataset \textit{\textbf{K}nowledge \textbf{B}ehind \textbf{P}ersona}~(\textbf{KBP}), which is the first to consider the dependency between persona and implicit knowledge. Experimental results on the KBP dataset demonstrate that the SAFARI framework can effectively produce persona-consistent and knowledge-enhanced responses

Free chlorine loss during spray of membrane-less acidic electrolyzed water (MLAEW) and its antimicrobial effect on airborne bacteria from poultry house

Spray-application of membrane-less acidic electrolyzed water (MLAEW) is a novel technique for disinfection in livestock houses. This study investigated the loss of free chlorine (FC, the major germicidal component in MLAEW) over distance during spray, as affected by air temperature and initial FC concentration. The antimicrobial effect of MLAEW on airborne bacteria from an aviary laying-hen house was examined. MLAEW was prepared with two FC concentrations (app. 15 and 60 mg L-1), and was sprayed at three air temperatures (18, 25, 32°C). The original MLAEW solution and MLAEW aerosols collected at 0, 25, and 50 cm from the spray nozzle were analyzed for FC concentrations. Bacteria were immersed into these MLAEW samples and numerated for viable count after 0.5-, 2-, and 5-min treatments. MLAEW aerosols collected at 0 cm lost 11.7 – 13.2% FC as compared to the original MLAEW solution. This initial loss was affected neither by the initial FC concentration (P = 0.13) nor by air temperature (P = 0.57). The rate of FC loss during travelling was 0.79 – 0.87 % per centimeter of aerosol travel distance (% cm-1) at 18°C, 1.08 – 1.15 % cm-1 at 25°C, and 1.35 – 1.49 % cm-1 at 32°C. This travelling loss was affected by air temperature (P = 0.02), but not by initial FC concentration (P = 0.38). Bacteria were completely inactivated in 0.5 min when treated with MLAEW samples with FC \u3e 16.8 mg L-1, in 2 min when FC \u3e 13.8 mg L-1, and in 5 min when FC \u3e 7.2 mg L-1. Airborne bacteria from aviary hen house can be effectively inactivated by MLAEW with adequate FC concentration and contact time. During spray, antimicrobial efficacy of MLAEW aerosols decreased over distance due to FC loss which exacerbates at higher air temperature

Structure and Digestive Qualities of Cooked Black Beans after Soaked in NaCl with the Assistance of Ultrasound

To investigate the effect of ultrasound assisted NaCl soaking on the structure and digestive characteristics of black beans, the scanning electron microscopy, infrared spectroscopy analysis, X-ray diffraction and other methods were used to analyze the mechanism of NaCl on the structure of black beans. And the thermal properties, water absorption, and swelling rate were used to clarify the changes in the properties of the black beans during the ripening process, and the in vitro digestive properties of starch were analyzed. The results showed that ultrasound-assisted NaCl soaking decreased the densification of black bean powder particles and made the gap between particles larger while reducing the damage to the starch crystallization region. With the increase of NaCl concentration, the swelling rate of black bean particles increased by 28%, 48%, and 56% compared to water soaking, and the hardness significantly decreased. The gelatinization degree increased to 40%, 43%, and 45%, and the hydrolysis rate of black bean starch decreased to 19.05%, 17.93%, and 17.48%, respectively. This indicated that sodium ions could inhibit starch digestion, the NaCl soaking treatment in this study would provide a theoretical basis for the development of low GI functional foods

β-blockades and the risk of atrial fibrillation in patients with cardiovascular diseases

Backgroundβ-blockers have been widely used in patients with extensive cardiovascular disease (CVD) and have provided benefits. However, they are more likely to cause symptomatic bradycardia, hypotension, or glucose metabolism disorders, which may lead to an increased risk of atrial fibrillation (AF), but evidence is lacking.AimsThis study was to analyze the association between the use of β-blockers and the risk of developing AF.MethodsThis nationwide, prospective cohort study utilized data from the 2013–2020 National Health and Nutrition Examination Survey (NHANES). The patients were stratified into a β-blocker treatment group (n = 2585) and a non-β-blocker treatment group (n = 8525). Univariate and multivariate logistic regression analyses were performed to identify the relationship between β-blockades and the risk of AF. Propensity matching analysis was used to balance patient baseline characteristics and to control for confounders.ResultsA total of 11,110 subjects were included in this study (mean [SD] age, 59.89 [15.07] years; 5657 [49.7%] males). A total of 111/2585 subjects developed AF in the β-blocker treatment group, and 75/8525 developed AF in the non-β-blocker treatment group (incidence rate, 4.2% vs. 0.8%). Compared with the non-β-blocker group, the β-blocker group had an increased risk of incident AF (aOR, 2.339; 95% CI, 1.614–3.410). Some sensitivity analyses also revealed consistent findings of increased AF risk associated with β-blocker treatment.ConclusionThe findings from this study suggest that β-blocker treatment is associated with an increased risk of incident AF and may help physicians select a modest medication for patients while also assessing the risk of AF

Bioinformatics and systems biology approach to identify the pathogenetic link of neurological pain and major depressive disorder

Neurological pain (NP) is always accompanied by symptoms of depression, which seriously affects physical and mental health. In this study, we identified the common hub genes (Co-hub genes) and related immune cells of NP and major depressive disorder (MDD) to determine whether they have common pathological and molecular mechanisms. NP and MDD expression data was downloaded from the Gene Expression Omnibus (GEO) database. Common differentially expressed genes (Co-DEGs) for NP and MDD were extracted and the hub genes and hub nodes were mined. Co-DEGs, hub genes, and hub nodes were analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Finally, the hub nodes, and genes were analyzed to obtain Co-hub genes. We plotted Receiver operating characteristic (ROC) curves to evaluate the diagnostic impact of the Co-hub genes on MDD and NP. We also identified the immune-infiltrating cell component by ssGSEA and analyzed the relationship. For the GO and KEGG enrichment analyses, 93 Co-DEGs were associated with biological processes (BP), such as fibrinolysis, cell composition (CC), such as tertiary granules, and pathways, such as complement, and coagulation cascades. A differential gene expression analysis revealed significant differences between the Co-hub genes ANGPT2, MMP9, PLAU, and TIMP2. There was some accuracy in the diagnosis of NP based on the expression of ANGPT2 and MMP9. Analysis of differences in the immune cell components indicated an abundance of activated dendritic cells, effector memory CD8+ T cells, memory B cells, and regulatory T cells in both groups, which were statistically significant. In summary, we identified 6 Co-hub genes and 4 immune cell types related to NP and MDD. Further studies are needed to determine the role of these genes and immune cells as potential diagnostic markers or therapeutic targets in NP and MDD