Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?

The multimedia community has shown a significant interest in perceiving and representing the physical world with multimodal pretrained neural network models, and among them, the visual-language pertaining (VLP) is, currently, the most captivating topic. However, there have been few endeavors dedicated to the exploration of 1) whether essential linguistic knowledge (e.g., semantics and syntax) can be extracted during VLP, and 2) how such linguistic knowledge impact or enhance the multimodal alignment. In response, here we aim to elucidate the impact of comprehensive linguistic knowledge, including semantic expression and syntactic structure, on multimodal alignment. Specifically, we design and release the SNARE, the first large-scale multimodal alignment probing benchmark, to detect the vital linguistic components, e.g., lexical, semantic, and syntax knowledge, containing four tasks: Semantic structure, Negation logic, Attribute ownership, and Relationship composition. Based on our proposed probing benchmarks, our holistic analyses of five advanced VLP models illustrate that the VLP model: i) shows insensitivity towards complex syntax structures and relies on content words for sentence comprehension; ii) demonstrates limited comprehension of combinations between sentences and negations; iii) faces challenges in determining the presence of actions or spatial relationships within visual information and struggles with verifying the correctness of triple combinations. We make our benchmark and code available at \url{https://github.com/WangFei-2019/SNARE/}.Comment: [TL;DR] we design and release the SNARE, the first large-scale multimodal alignment probing benchmark for current vision-language pretrained model

Preparation of a nano emodin transfersome and study on its anti-obesity mechanism in adipose tissue of diet-induced obese rats

OBJECTIVE: To describe the preparation of nano emodin transfersome (NET) and investigate its effect on mRNA expression of adipose triglyceride lipase (ATGL) and G0/G1 switch gene 2 (G0S2) in adipose tissue of diet-induced obese rats. METHODS: NET was prepared by film-ultrasonic dispersion method. The effects of emodin components at different ratios on encapsulation efficiency were investigated.The NET envelopment rate was determined by ultraviolet spectrophotometry. The particle size and Zeta potential of NET were evaluated by Zetasizer analyzer. Sixty male SD rats were assigned to groups randomly. After 8-week treatment, body weight, wet weight of visceral fat and the percentage of body fat (PBF) were measured. Fasting blood glucose and serum lipid levels were determined. The adipose tissue section was HE stained, and the cellular diameter and quantity of adipocytes were evaluated by light microscopy. The mRNA expression of ATGL and G0S2 from the peri-renal fat tissue was assayed by RT-PCR. RESULTS: The appropriate formulation was deoxycholic acid sodium salt vs. phospholipids 1:8, cholesterol vs. phospholipids 1:3, vitamin Evs. phospholipids 1:20, and emodin vs. phospholipid 1:6. Zeta potential was −15.11 mV, and the particle size was 292.2 nm. The mean encapsulation efficiency was (69.35 ± 0.25)%. Compared with the obese model group, body weight, wet weight of visceral fat, PBF and mRNA expression of G0S2 from peri-renal fat tissue were decreased significantly after NET treatment (all P < 0.05), while high-density lipoprotein cholesterol (HDL-C), the diameter of adipocytes and mRNA expression of ATGL from peri-renal fat tissue were increased significantly (all P < 0.05). CONCLUSION: The preparation method is simple and reasonable. NET with negative electricity was small and uniform in particle size, with high encapsulation efficiency and stability. NET could reduce body weight and adipocyte size, and this effect was associated with the up-regulation of ATGL, down-regulation of G0S2 expression in the adipose tissue, and improved insulin sensitivity

α-Glucosidase Inhibitors From the Coral-Associated Fungus Aspergillus terreus

Nine novel butenolide derivatives, including four pairs of enantiomers, named (±)-asperteretones A–D (1a/1b–4a/4b), and a racemate, named asperteretone E (5), were isolated and identified from the coral-associated fungus Aspergillus terreus. All the structures were established based on extensive spectroscopic analyses, including HRESIMS and NMR data. The chiral chromatography analyses allowed the separation of (±)-asperteretones A–D, whose absolute configurations were further confirmed by experimental and calculated electronic circular dichroism (ECD) analysis. Structurally, compounds 2–5 represented the first examples of prenylated γ-butenolides bearing 2-phenyl-3-benzyl-4H-furan-1-one motifs, and their crucial biogenetically related metabolite, compound 1, was uniquely defined by an unexpected cleavage of oxygen bridge between C-1 and C-4. Importantly, (±)-asperteretal D and (4S)-4-decarboxylflavipesolide C were revised to (±)-asperteretones B (2a/2b) and D (4), respectively. Additionally, compounds 1a/1b–4a/4b and 5 were evaluated for the α-glucosidase inhibitory activity, and all these compounds exhibited potent inhibitory potency against α-glucosidase, with IC50 values ranging from 15.7 ± 1.1 to 53.1 ± 1.4 μM, which was much lower than that of the positive control acarbose (IC50 = 154.7 ± 8.1 μM), endowing them as promising leading molecules for the discovery of new α-glucosidase inhibitors for type-2 diabetes mellitus treatment

Particle conveying under microgravity in a vibrating vessel

This paper presents a numerical study on the conveying of particles in a vibrating vessel under microgravity. Such a vessel is composed of parallel plates with sawtooth wavy surfaces, which are specifically designed to convey particles using simple vibration. The numerical model was validated by good agreement between the simulated and experimental results. Then the effects of key variables, including the vessel geometry, vibration amplitude and frequency and gravity level, were systematically investigated by a series of controlled simulations. The results confirm the optimised design from the previous experiments, and numerically demonstrate that using such a system a steady conveying operation can be achieved under microgravity. The convey rate is positively affected by the vibration amplitude and frequency in a complicated way, which cannot be simply described by the commonly used vibration intensity or velocity amplitude. The gravity level also has a significant effect on the convey rate when it is over 0.001g. The convey rate can be estimated by the product of the average solid fraction and velocity. And the effects of the variables can be better understood through the analyses on these two parameters. Finally, a predictive model is proposed to estimate the convey rate under different operational conditions. The findings are useful for the design of particle conveying techniques for outer space applications

Design of removable vending machine and research on the key implementation technology

As a supplement to physical stores and online stores, vending machines are gradually becoming the third largest consumption mode. This article aims to design a removable vending machine, which can automatically move in front of the users to meet their demands, so as to realise a better shopping experience for people. The network structure for the vending machine was analysed and designed, and research on the wireless location technology and route planning of the vending machine is hoped to provide some reference value for the mobile technology of the vending machine

Neutrosophic Similarity Score Based Weighted Histogram for Robust Mean-Shift Tracking

Visual object tracking is a critical task in computer vision. Challenging things always exist when an object needs to be tracked. For instance, background clutter is one of the most challenging problems. The mean-shift tracker is quite popular because of its efficiency and performance in a range of conditions. However, the challenge of background clutter also disturbs its performance. In this article, we propose a novel weighted histogram based on neutrosophic similarity score to help the mean-shift tracker discriminate the target from the background. Neutrosophic set (NS) is a new branch of philosophy for dealing with incomplete, indeterminate, and inconsistent information. In this paper, we utilize the single valued neutrosophic set (SVNS), which is a subclass of NS to improve the mean-shift tracker. First, two kinds of criteria are considered as the object feature similarity and the background feature similarity, and each bin of the weight histogram is represented in the SVNS domain via three membership functions T(Truth), I(indeterminacy), and F(Falsity). Second, the neutrosophic similarity score function is introduced to fuse those two criteria and to build the final weight histogram. Finally, a novel neutrosophic weighted mean-shift tracker is proposed. The proposed tracker is compared with several mean-shift based trackers on a dataset of 61 public sequences. The results revealed that our method outperforms other trackers, especially when confronting background clutter

Thymalfasin therapy accelerates COVID-19 pneumonia rehabilitation through anti-inflammatory mechanisms

Abstract Introduction Thymosin drugs are commonly used for the treatment of viral infections due to their immunomodulatory effects. The comprehensive clinical efficacy of Thymalfasin therapy for COVID-19 associated pneumonia is not yet fully researched, another issue, whether the use of thymosin drugs can reduce the rate of COVID-19 progression to severe pneumonia has not been well documented. The aim of the present study was to multi-angle evaluate the clinical efficacy of Thymalfasin therapy for COVID-19 pneumonia by retrospective review of the clinical data of 338 inpatients with common COVID-19 infection who received treatment in our hospital. Methods The primary index of observation was whether progression to severe pneumonia occurred within a week after admission, and the secondary indexes were the length of hospital stay, time of negative conversion of COVID-19 antigen, the number of peripheral lymphocytes and white blood cells (WBC), and C-reactive protein (CRP) and procalcitonin (PCT) levels,and the control of pneumonia related symptoms, for example, fever, listlessness, inflammatory exudate area shown on lung CT (%). Results The length of hospital stay of patients in Thymalfasin group was significantly shorter than that of patients in the control group (p < 0.01). The proportion of relief of pneumonia related symptoms (fever, fatigue) in the Thymalfasin therapy group was significantly higher than that in the control group, and the inflammatory exudate area shown on CT was significantly lower than that in the control group (p < 0.05). Multivariate logistic regression analysis showed that the use of Thymalfasin was an independent protective factor affecting the progression to severe pneumonia. Multifactorial Cox model analysis indicated that negative conversion of COVID-19 antigen was significantly faster in patients using Thymalfasin and younger patients. Conclusion Thymalfasin therapy has shown excellent clinical efficacy in the treatment of COVID-19 pneumonia, it can reduce inflammatory reactions, promote the relief of COVID-19 pneumonia related symptoms such as fever and fatigue, facilitate effusion absorption, and accelerate COVID-19 pneumonia recovery. Thymalfasin can prevent progression of common COVID-19 infection to severe pneumonia via multiple immunity-enhancing and anti-inflammatory protective mechanisms

Study on Grid-Connected Strategy of Distribution Network with High Hydropower Penetration Rate in Isolated Operation

As the largest global renewable source, hydropower is a useful supplement to mountainous distribution networks with abundant water resources, and shoulders a large portion of the regulation duty in many power systems. In particular, in the form of decentralized energy sources located to their customers, small hydropower (SHP) improve grid stability by diversifying the electricity system and reducing power loss. The mountainous distribution networks supplied by small hydropower are closed-loop design but open-loop operation, which easily causes the tripping of tie line even further the off-grid operation of small hydropower system. Once the tie line trips, the current countermeasures&mdash;such as hydropower shutdown and load shedding&mdash;do not fully guarantee the reliability of power supply and the utilization efficiency of hydropower. This paper studies the amplitude-frequency characteristics of SHP off-grid, according to the typical integration of hydropower in South China, a SHP on-grid/off-grid model is established based on the Power Systems Computer Aided Design (PSCAD) platform. It is found that due to the inertia of SHP, the amplitude-frequency characteristics of SHP island system are relatively slow, and the process of non-synchronization with the main grid is gradually expanded. The characteristic of SHP has a certain degree of synchronization with the main grid in the initial island operates stage, which helps to find a novel grid connection method. This paper further proposes the strategy of using fast busbar automatic transfer switch (BATS), which quickly connect the trip-off SHP to the distribution network under the condition of permitting distributed energy grid-connected. The PSCAD simulation results show that proposed strategy has a limited impact on the power grid and prove the effectiveness of the method

Information Perception Method for Fruit Trees Based on 2D LiDAR Sensor

To solve the problem of orchard environmental perception, a 2D LiDAR sensor was used to scan fruit trees on both sides of a test platform to obtain their position. Firstly, the two-dimensional iterative closest point (2D-ICP) algorithm was used to obtain the complete point cloud data of fruit trees on both sides. Then, combining the lightning connection algorithm (LAPO) and the density-based clustering algorithm (DBSCAN), a fruit tree detection method based on density-based lightning connection clustering (LAPO-DBSCAN) was proposed. After obtaining the point cloud data of fruit trees on both sides of the test platform using the 2D-ICP algorithm, the LAPO-DBSCAN algorithm was used to obtain the position of fruit trees. The experimental results show that the positive detection rate was 96.69%, the false detection rate was 3.31%, and the average processing time was 1.14 s, verifying the reliability of the algorithm. Therefore, this algorithm can be used to accurately find the position of fruit trees, meaning that it can be applied to orchard navigation in a later stage