Dynamics of mass-spring-belt friction self-excited vibration system

In order to deeply study the non-smooth dynamic mechanism of self-excited vibration, the friction self-excited vibration system model containing the Stribeck friction model is established, which is a nonlinear dynamical mass-spring-belt model. For the established model, the critical instability speed is solved by the first approximate stability criterion of Lyapunov theory, and the stability of limit cycle is determined on the basis of curvature coefficient. Secondly, the bifurcation characteristics and system behaviors under different parameters are analyzed by using numerical simulation method. The results show that the theoretical analysis is feasible. Feed speed, damping coefficient and ratio of dynamic-static friction coefficient are the main factors that affect the system motion state. Thirdly, the Washout filter method is designed to control the bifurcation characteristics. By comparing the pre and post phase diagrams, results show that the amplitude of controlled system is reduced and the topology is improved after introducing the Washout filter. All the researches above prove that adding Washout filter into the system to control the bifurcation phenomenon is a more effective method

Pattern Recognition for Steam Flooding Field Applications based on Hierarchical Clustering and Principal Component Analysis

Steam flooding is a complex process that has been considered as an effective enhanced oil recovery technique in both heavy oil and light oil reservoirs. Many studies have been conducted on different sets of steam flooding projects using the conventional data analysis methods, while the implementation of machine learning algorithms to find the hidden patterns is rarely found. In this study, a hierarchical clustering algorithm (HCA) coupled with principal component analysis is used to analyze the steam flooding projects worldwide. The goal of this research is to group similar steam flooding projects into the same cluster so that valuable operational design experiences and production performance from the analogue cases can be referenced for decision-making. Besides, hidden patterns embedded in steam flooding applications can be revealed based on data characteristics of each cluster for different reservoir/fluid conditions. In this research, principal component analysis is applied to project original data to a new feature space, which finds two principal components to represent the eight reservoir/fluid parameters (8D) but still retain about 90% of the variance. HCA is implemented with the optimized design of five clusters, Euclidean distance, and Ward\u27s linkage method. The results of the hierarchical clustering depict that each cluster detects a unique range of each property, and the analogue cases present that fields under similar reservoir/fluid conditions could share similar operational design and production performance

MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansion

Query expansion is a commonly-used technique in many search systems to better represent users' information needs with additional query terms. Existing studies for this task usually propose to expand a query with retrieved or generated contextual documents. However, both types of methods have clear limitations. For retrieval-based methods, the documents retrieved with the original query might not be accurate enough to reveal the search intent, especially when the query is brief or ambiguous. For generation-based methods, existing models can hardly be trained or aligned on a particular corpus, due to the lack of corpus-specific labeled data. In this paper, we propose a novel Large Language Model (LLM) based mutual verification framework for query expansion, which alleviates the aforementioned limitations. Specifically, we first design a query-query-document generation pipeline, which can effectively leverage the contextual knowledge encoded in LLMs to generate sub-queries and corresponding documents from multiple perspectives. Next, we employ a mutual verification method for both generated and retrieved contextual documents, where 1) retrieved documents are filtered with the external contextual knowledge in generated documents, and 2) generated documents are filtered with the corpus-specific knowledge in retrieved documents. Overall, the proposed method allows retrieved and generated documents to complement each other to finalize a better query expansion. We conduct extensive experiments on three information retrieval datasets, i.e., TREC-DL-2020, TREC-COVID, and MSMARCO. The results demonstrate that our method outperforms other baselines significantly

Responses of human adipose-derived mesenchymal stem cells to chemical microenvironment of the intervertebral disc

<p>Abstract</p> <p>Background</p> <p>Human adipose-derived mesenchymal stem cells (ADMSCs) may be ideal source of cells for intervertebral disc (IVD) regeneration, but the harsh chemical microenvironment of IVD may significantly influence the biological and metabolic vitality of ADMSCs and impair their repair potential. This study aimed to investigate the viability, proliferation and the expression of main matrix proteins of ADMSCs in the chemical microenvironment of IVD under normal and degeneration conditions.</p> <p>Methods</p> <p>ADMSCs were harvested from young (aged 8-12 years, n = 6) and mature (aged 33-42 years, n = 6) male donors and cultured under standard condition and IVD-like conditions (low glucose, acidity, high osmolarity, and combined conditions) for 2 weeks. Cell viability was measured by annexin V-FITC and PI staining and cell proliferation was measured by MTT assay. The expression of aggrecan and collagen-I was detected by real-time quantitative polymerase chain reaction and Western blot analysis.</p> <p>Results</p> <p>IVD-like glucose condition slightly inhibited cell viability, but increased the expression of aggrecan. In contrast, IVD-like osmolarity, acidity and the combined conditions inhibited cell viability and proliferation and the expression of aggrecan and collagen-I. ADMSCs from young and mature donors exhibited similar responses to the chemical microenvironments of IVD.</p> <p>Conclusion</p> <p>IVD-like low glucose is a positive factor but IVD-like high osmolarity and low pH are deleterious factors that affect the survival and biological behaviors of ADMSCs. These findings may promote the translational research of ADMSCs in IVD regeneration for the treatment of low back pain.</p

Oxygen-Vacancy Abundant Ultrafine Co_3O_4/Graphene Composites for High-Rate Supercapacitor Electrodes

The metal oxides/graphene composites are one of the most promising supercapacitors (SCs) electrode materials. However, rational synthesis of such electrode materials with controllable conductivity and electrochemical activity is the topical challenge for high-performance SCs. Here, the Co_3O_4/graphene composite is taken as a typical example and develops a novel/universal one-step laser irradiation method that overcomes all these challenges and obtains the oxygen-vacancy abundant ultrafine Co_3O_4 nanoparticles/graphene (UCNG) composites with high SCs performance. First-principles calculations show that the surface oxygen vacancies can facilitate the electrochemical charge transfer by creating midgap electronic states. The specific capacitance of the UCNG electrode reaches 978.1 F g^(−1) (135.8 mA h g^(−1)) at the current densities of 1 A g^(−1) and retains a high capacitance retention of 916.5 F g^(−1) (127.3 mA h g^(−1)) even at current density up to 10 A g^(−1), showing remarkable rate capability (more than 93.7% capacitance retention). Additionally, 99.3% of the initial capacitance is maintained after consecutive 20 000 cycles, demonstrating enhanced cycling stability. Moreover, this proposed laser-assisted growth strategy is demonstrated to be universal for other metal oxide/graphene composites with tuned electrical conductivity and electrochemical activity

Robust Stereoscopic Crosstalk Prediction

We propose a new metric to predict perceived crosstalk using the original images rather than both the original and ghosted images. The proposed metrics are based on color information. First, we extract a disparity map, a color difference map, and a color contrast map from original image pairs. Then, we use those maps to construct two new metrics (Vdispc and Vdlogc). Metric Vdispc considers the effect of the disparity map and the color difference map, while Vdlogc addresses the influence of the color contrast map. The prediction performance is evaluated using various types of stereoscopic crosstalk images. By incorporating Vdispc and Vdlogc, the new metric Vpdlc is proposed to achieve a higher correlation with the perceived subject crosstalk scores. Experimental results show that the new metrics achieve better performance than previous methods, which indicate that color information is one key factor for crosstalk visible prediction. Furthermore, we construct a new data set to evaluate our new metrics

Construction of a Cross-layer Linked G-octamer via Conformational Control: A Stable G-quadruplex in H-bond Competitive Solvents

Methanol soluble and stable guanosine octamers were successfully achieved via H-bond self-assembly. Through structural conformational design, we developed a new class of guanosine derivatives with modification on guanine (8-aryl) and ribose (20 ,30 -isopropylidene). This unique design led to the formation of the first discrete G8-octamer with its structure characterized by single crystal X-ray diffraction, MS and NMR spectroscopy. The G8-octamer showed unique cation recognition properties, including the formation of a stable Rb+ templated G-quadruplex. Based on this observation, further modification on the 8-aryl moiety was performed to incorporate a cross-layer H-bond or covalent linkage. Similar G-octamers were obtained in both cases with structures confirmed by single crystal X-ray diffraction. Furthermore, the covalently linked G-quadruplex exhibited excellent stability even in MeOH and DMSO, suggesting a promising future for this new H-bond self-assembly system in biological and material applications