Theoretical and experimental verifications of intermolecular σ-hole⋯n and π-hole⋯n interactions between bromopentafluorobenzene and triethylenediamine

Mechanical lightweight structures often tend to unwanted vibrations due to disturbances. Passive methods for increasing the structural damping are often inadequate for the vibration suppression, since they include additional mass in the form of damping materials, additional stiffening designs or mass damper. In this paper the concept of an active vibration control for piezoelectric light weight structures is introduced and presented through several subsequent steps: model identification, controller design, simulation, experimental verification and implementation on a particular object—piezoelectric smart cantilever beam. Special attention is paid to experimental testing and verification of the results obtained through simulations. The efficiency of the modeling procedure through the subspace-based system identification along with the efficiency of the designed optimal controller are proven based on the experimental verification, which results in vibration suppression to a very high extent not only in comparison with the uncontrolled case, but also in comparison with previously achieved results. The experimental work demonstrates a very good agreement between simulations and experimental results.

Colorectal cancer (CRC) is a kind of malignant cancer with high morbidity and mortality. The purpose of this study was to explore potential regulated key genes involved in CRC through bioinformatics analysis and experimental verification. The gene expression profile data were downloaded from the Gene Expression Omnibus, and the differential expression genes were detected in cancerous and paracancerous samples of CRC patients, respectively. Then functional enrichment analysis, such as the Kyoto Encyclopedia of Genes and Genomes pathway analysis as well as the protein-protein interaction network were constructed, and the highly related genes were clustered by Molecular COmplex DEtection algorithm to find out the core interaction in different genes' crosstalk. The genes affecting CRC prognosis were screened by the Human Protein Atlas database. In addition, the expression level of core genes was detected by GEPIA database, and the core genes' changes in large-scale cancer genome data set were directly analyzed by cBioPortal database. The expression of the predicted hub genes DSN1, AHCY, and ERCC6L was verified by reverse-transcription quantitative polymerase chain reaction in CRC cells. The gene function of DSN1 was analyzed by wound healing and colony formation assays. The results showed that silencing of DSN1 could significantly reduce the migration and proliferation of CRC cells. Further, BUB1B, the potential interacting protein of DSN1, was also predicted via bioinformatics analysis. Above all, this study shows that bioinformatics analysis combined with experimental method verification provide more potential vital genes for the prevention and therapy of CRC.

This paper, the second part of two companion papers, reports experimental methodology and verification results based on the prototype device of the proposed passive MEMS dc current sensor in Part I. The relationship between output voltages and crucial factors, such as the relative position of the sensor to the two-wire appliance cord, different connection modes of the PZT partition plates, as well as the applied dc current has been characterized. The experimental methodology mainly includes those of how to position the sensor device, how to determine the measurement range for sensitivity characterization, and how to electrically connect the PZT partition plates in different modes. Sensitivity characteristics were studied in ac current from 8 to 400 mA and in dc current from 0.5 to 3 A, respectively. Two typical connection modes, i.e., in series and parallel, were investigated with ten PZT partition plates. In the case of dc current, the waveforms of the output voltage in the individual PZT plate were studied in detail. First, the initial peak voltages corresponding to ON–OFF switching of dc current can be clearly characterized with a higher amplitude (relatively lower frequency) for turning ON and a lower one (relatively higher frequency) for turning OFF. Second, the measured peak voltages are smaller than the analytical ones, but showing similar increasing tendency with the increasing of the dc current. In light of the above-mentioned experimental verifications, the proposed passive MEMS dc current sensor was proved to be applicable to direct measurements of the two-wire appliance cords without using cord separator. The proposed sensor devices are, therefore, more convenient than Hall-effect-based sensors in electricity end-use measuring and monitoring of dc power supply.

To explore hub genes for glaucoma based on bioinformatics analysis and an experimental model verification. In the Gene Expression Omnibus (GEO) database, the GSE25812 and GSE26299 datasets were selected to analyze differentially expressed genes (DEGs) by the GEO2R tool. Through bioinformatics analysis, 9 hub genes were identified. Receiver operating characteristic (ROC) curves and principal component analysis (PCA) were performed to verify whether the hub gene can distinguish glaucoma from normal eyes. The mouse model of glaucoma was constructed, and the real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) assay was performed to detect the expression levels of hub genes in glaucoma. There were 128 overlapping DEGs in the GSE25812 and GSE26299 datasets, mainly involved in intracellular signalling, cell adhesion molecules and the Ras signalling pathway. A total of 9 hub genes were screened out, including GNAL, BGN, ETS2, FCGP4, MAPK10, MMP15, STAT1, TSPAN8, and VCAM1. The area under the curve (AUC) values of 9 hub genes were greater than 0.8. The PC1 axle could provide a 70.5% interpretation rate to distinguish glaucoma from normal eyes. In the ocular tissues of glaucoma in the mice model, the expression of BGN, ETS2, FCGR4, STAT1, TSPAN8, and VCAM1 was increased, while the expression of GNAL, MAPK10, and MMP15 was decreased. Nine hub genes in glaucoma are identified, which may provide new biomarkers and therapeutic targets for glaucoma.

The effect of using curvilinear element blades (CEBs) on a low-solidity cascade diffuser (LSD) in a centrifugal compressor was investigated both experimentally and numerically. Centrifugal compressors require a higher efficiency and wider operating range to reduce the lifecycle costs of plants in which they are used and the effects their users have on the environment. A LSD has a wider operating range than a common vaned diffuser that has high solidity, but worse efficiency at the design point. For this reason, this research aims to improve the efficiency of the LSD and keep its operating range wide without changing the blade setting angle or two-dimensional geometry. As a first step, LSDs with three different curvilinear element profiles were compared with a conventional LSD, and the mechanism of the performance improvement was investigated by using a numerical simulation. These diffusers have the same two-dimensional geometry, blade setting angle, and number of blades but different blade stacking geometry in the span-wise direction. Unsteady Reynolds Averaged Navier-Stokes (RANS) simulations were conducted using a one-blade path model with an inlet, impeller, and LSD diffuser passages. The LSD using the CEBs improved the efficiency by 1.9% over that of the conventional LSD at the design point while maintaining the same operating range. The calculation results reveal that the recirculation region decreased at the suction surface of the diffuser vane in the CEB case and the diffuser efficiency improved. The concaved suction surface increased the blade loading and induced higher velocity on the suction surface. The higher velocity prevented reverse flow on the suction surface at the hub side, and the secondary flow removed the thick boundary layer at the trailing edge to the downstream of the diffuser. Experimental verification was also conducted using a single-stage compressor with an impeller, diffuser, and scroll casing to verify the prediction. The experimental results showed the LSD using the CEB has a higher pressure rise at the stator region than the conventional LSD and verified the performance improvement due to using the CEBs.

Application of the network alteration theory for modeling the time-dependent constitutive behaviour of rubbers. Part I. General theory

This low profile load cells are referred to the current injection molding machine manufacturers commonly used specifications. This study is about the low-profile load cell design by the finite element analysis and experimental strain measurement verification. In the study, two low-profile load cell were designed and analyzed. The A-type cross-section of the sensor is a generally designed cross-section and has sufficient reliability for commercial use. The B-type curve cross-section load cell from the previous study found that can carry a more significant load. In the study, compare the finite element analysis results with the actual strain measurements to verify the correctness of the analysis. In the experimental verification, the two type sections loadcells were calibrated. The load cells were loading from 0kN to 60kN to measure strain values. The strain values were recorded in experiment processes. When the two types of load cell under loading, the loading force, and strain values regression linearity was 99.99 %. The measured values of the A-type and B-type load cells at 60 kN were 298 με and 170 με, and the results matched finite element analysis strain values. It was shown that the setup of boundary conditions and loading method in finite element analysis were acceptable.

Study on the molecular mechanisms of tetrandrine against pulmonary fibrosis based on network pharmacology, molecular docking and experimental verification

Intelligent protein design is a frontier topic in the cross field of modern biotechnology and AI. Through the combination of algorithm innovation and experimental verification, it breaks through the limitations of traditional protein design. In this paper, the progress of algorithm innovation in intelligent protein design is summarized, especially the application of advanced algorithms such as deep learning, generative model and reinforcement learning in protein structure prediction, function optimization and interaction analysis. Taking DeepThermoNet, a deep learning algorithm, as an example, the effect of protein mutant designed by DeepThermonet in improving the thermal stability of β -glucosidase was verified by experiments. The results showed that the mutant designed by the algorithm group was significantly better than the mutant designed by the traditional method in melting temperature (Tm) and enzyme activity retention rate. The experimental verification not only proves the effectiveness of the algorithm design, but also optimizes the algorithm model through feedback, forming a closed loop of "algorithm design-experimental verification-model optimization". This paper further discusses the interactive relationship between algorithm innovation and experimental verification, looks forward to the future development direction of intelligent protein design, including interdisciplinary integration, new algorithm development and data resource expansion, and points out the limitations of current research and the key direction of future work. Intelligent protein design is expected to provide new theoretical and technical support for drug research and development, biocatalyst development and biomaterial design, and promote innovation and development in related fields.

Millable polyurethane (MPU) is widely used in the field of sealing and wear-resistant components due to its excellent solvent resistance and dimen-sional stability. However, its inherent drawbacks of high rigidity and low elas-ticity limit its application in complex working conditions. Carboxylated nitrile butadiene rubber (XNBR) contains reactive carboxyl groups (-COOH) in its mo-lecular chain, which can chemically interact with the isocyanate groups (-NCO) of MPU, providing a new approach to improve the mechanical properties of MPU. At present, research on the blending of XNBR with thermoplastic polyu-rethane (TPU) has been reported, but studies on the interfacial reaction mecha-nism, process regulation, and mechanical property synergy rules of the XNBR/MPU system are rarely conducted. In this study, an integrated technical route of "molecular simulation - experimental verification - performance char-acterization" was adopted, focusing on the correlation between the interfacial reaction and mechanical properties of the XNBR/MPU system: 1) Molecular dy-namics simulations were used to confirm that the amidation reaction between XNBR and MPU proceeds spontaneously at 80°C, and the interfacial cross-linking mechanism of amide bonds was revealed; 2) The optimal formula was determined through orthogonal experiments, and mechanical property tests were carried out. This study provides theoretical support for the development of high-performance XNBR/MPU blended materials and has application value in the fields of automotive sealing and shock absorption.

Discussions on Experiment Teaching of Mechanical System Dynamics

Reduction of threading dislocation density (TDD) in epitaxial germanium (Ge) on silicon (Si) has been one of the most important challenges for the realization of monolithically integrated photonics circuits. The present paper describes methods of theoretical calculation and experimental verification of a novel model for the reduction of TDD. The method of theoretical calculation describes the bending of threading dislocations (TDs) based on the interaction of TDs and non-planar growth surfaces of selective epitaxial growth (SEG) in terms of dislocation image force. The calculation reveals that the presence of voids on SiO2 masks help to reduce TDD. Experimental verification is described by germanium (Ge) SEG, using an ultra-high vacuum chemical vapor deposition method and TD observations of the grown Ge via etching and cross-sectional transmission electron microscope (TEM). It is strongly suggested that the TDD reduction would be due to the presence of semicylindrical voids over the SiO2 SEG masks and growth temperature. For experimental verification, epitaxial Ge layers with semicylindrical voids are formed as the result of SEG of Ge layers and their coalescence. The experimentally obtained TDDs reproduce the calculated TDDs based on the theoretical model. Cross-sectional TEM observations reveal that both the termination and generation of TDs occur at semicylindrical voids. Plan-view TEM observations reveal a unique behavior of TDs in Ge with semicylindrical voids (i.e., TDs are bent to be parallel to the SEG masks and the Si substrate).

Background: Due to the recognition and further promotion of green and low-carbon concepts worldwide, Stirling refrigeration technology has gained people's attention for its significant advantages, such as high cooling capacity, high efficiency, and strong reliability. In recent years, related products have gradually entered the field of civilian low-temperature refrigeration. One of the key research directions is to achieve better refrigeration performance at lower costs. Purpose: Through simulative analysis and experimental verification, Free piston Stirling refrigerators (FPSCs) have better economic and performance advantages using non-metallic materials. Methods: This paper analyzes an FPSC using Polyethylene naphthalate (PEN) material. The main losses and performance of the regenerator are analyzed about the impact of packing porosity and regenerator length. The actual performance obtained through experimental verification is compared with an FPSC with metal packing. Conclusion: Experimental verification was conducted, and it was found that FPSC using non-metallic materials with a porosity of 52.4% had better performance. Some details of the patent are shown in the article. The COP of 25w@-76℃ is 0.16, which is close to the performance of the PFSC using 200 mesh wound wire.

Currently, there is still no clear treatment for polycystic ovary syndrome (PCOS). YJKL has better therapeutic effects and lower toxic side effects for PCOS type infertility. This study aims to clarify the potential mechanism of YJKL Decoction in the treatment of PCOS based on network pharmacology and experiments verification. Network pharmacology and experimental validation approach were used to investigate the bioactive ingredients, critical targets and potential mechanisms of YJKL Decoction against PCOS. Firstly, we use network pharmacology methods to collect core targets, and then validate their effects on diseases through experiments. Five core targets were screened, Threonine kinase 1 (AKT1), Cellular tumor antigen p53 (TP53), Tumor necrosis factor (TNF), Albumin (ALB) and Vascular endothelial growthfactor A (VEGFA). KEGG analysis showed that YJKL treatment for PCOS mainly include AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway and HIF-1 signaling pathway. The molecular docking results showed that compounds have higher affinity with targets. Finally, experimental results had shown that YJKL Decoction had an better therapeutic effects in the treatment of PCOS. Based on a systematic network pharmacology approach and experimental verification, our results comprehensively illustrated the active ingredients, potential targets, and molecular mechanism of YJKL for application to PCOS and helps to illustrate mechanism of action on a comprehensive level.

Ferroptosis is an underlying mechanism for various degenerative diseases, but its role in intervertebral disc degeneration remains elusive. This study aims to explore the key ferroptosis-related genes and its role in nucleus pulposus (NP) and annulus fibrosus (AF) degeneration. We analyzed the gene expression profiles of NP and AF from the Gene Expression Omnibus database. The ferroptosis-related differentially expressed genes (FRDEGs) in degenerated NP and AF were filtered, followed by GO and KEGG analysis. Feature FRDEGs were identified by the LASSO and SVM-RFE algorithms, and then Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were conducted. Immune infiltration analysis was conducted by CIBERSORT algorithm. We established drug networks via the Drug-Gene Interaction Database and competitive endogenous RNA (ceRNA) networks via miRanda, miRDB, and TargetScan database. The expression levels of the feature FRDEGs were assessed by the validation sets, single-cell RNA-seq, and experimental verification. A total of 15 and 18 FRDEGs were obtained for NP and AF, respectively. GO and KEGG analysis revealed their implication in oxidative stress. Four (AKR1C1, AKR1C3, MUC1, ENPP2) and five (SCP2, ABCC1, KLF2, IDO1, CREB3) feature genes were identified for NP and AF, respectively. The GSEA and GSVA analysis showed that these feature genes were enriched in lots of biological functions, including immune response. CREB3 in degenerated AF was negatively correlated with Eosinophils via CIBERSORT algorithm. The drugs and ceRNAs targeting CREB3 and MUC1 were identified. Experimental verification and single-cell RNA-seq analysis revealed that MUC1 and CREB3 were downregulated in degenerated NP and AF, respectively. MUC1 and CREB3 were considered novel biomarkers for NP and AF ferroptosis, respectively. Drug and ceRNA networks were constructed for future drug development and investigation of new mechanisms of ferroptosis.