Study on AADDS Plunger Pump Driving Bearing Properties

The Auto Anti-Deviation Drilling System (AADDS) is a high-performance, highly automated vertical drilling hydraulic guide control system. This article takes its power extraction device - driving bearing for the study object, analyzed the single-plunger pump's principle, established the mathematical model of hydraulic guide system, applied Matlab/Simulink to simulate the pump outlet flow under different contour curve of the driving bearing. The results show the oval-shaped bearing is of high efficiency under lower drilling speed, and its performance is better than that of original eccentric-shaped and clover-shaped

Measurement-Based Small-Scale Channel Model for Sub-6 GHz RIS-Assisted Communications

Reconfigurable intelligent surfaces (RISs) have attracted increasing interest from both academia and industry, thanks to their unique features on controlling electromagnetic (EM) waves. Although theoretical models for RIS-empowered communications have covered a variety of applications, yet, very few papers have investigated the modeling of real propagation characteristics. In this paper, we fill this gap by providing an empirical statistical channel model to describe the small-scale channel variations for an RIS-assisted broadband system at 2.6 GHz. Based on real channel measurements in outdoor, indoor and outdoor-to-indoor (O2I) environments, we compare and analyze the global, inter-cluster and intra-cluster parameters. Measurement results indicate that the deployment of an RIS with proper phase configurations can significantly improve the channel quality by enhancing the $K$-factor and reducing the time dispersion. The small-scale fading is well characterized by the proposed statistical model and the empirical channel parameters. These results are essential for the design of emerging RIS-assisted wireless systems for future applications

Self-Assembled Monolayers of Alkanethiols on Nickel Insert: Characterization of Friction and Analysis on Demolding Quality in Microinjection Molding

When the part geometry scaling down from macro to microscale level, the size-induced surface effect becomes significant in the injection molding process. The adhesion between polymer and nickel (Ni) mold insert during the process can lead to defects in necking, warping and deformation of microstructure. In this study, the self-assembled monolayers (SAMs) with low surface energy were deposited on the Ni surface to reduce the adhesion and further improve the demolding quality of the microstructure. Results show that the alkyl mercaptan SAMs with chemical bonds and close alignment can be successfully deposited on the surface of Ni by the solution deposition method. The contact angle, surface free energy, and friction coefficient before and after anti-adhesion treatment on the surface of mold insert were measured. In addition, the anti-adhesion properties of different alkyl mercaptan materials and the correspondingly replication quality of microstructure parts after injection molding were analyzed. It is found that the Ni mold insert treated by the perfluorodecanethiol has the best wear resistance and still shows good reproducibility at the 100th demolding cycle

Artificial intelligence in breast MRI radiogenomics: towards accurate prediction of neoadjuvant chemotherapy responses

Neoadjuvant Chemotherapy (NAC) in breast cancer patients has considerable prognostic and treatment potential and can be tailored to individual patients as part of precision medicine protocols. This work reviews recent advances in artificial intelligence so as to enable the use of radiogeomics for the accurate NAC analysis and prediction. The work addresses a new problem in radiogenomics mining: How to combine structural radiomics information and non-structural genomics information for accurate NAC prediction. This requires the automated extraction of parameters from structural breast radiomics data, and finding non-structural feature vectors with diagnostic value, which then are combined with genomics data acquired from exocrine bodies in blood samples from a cohort of cancer patients to enable accurate NAC prediction. A self-attention-based deep learning approach along with an effective multi-channel tumour image reconstruction algorithm of high dimensionality is proposed. The aim is to generate non-structural feature vectors for accurate prediction of the NAC responses by combining imaging datasets with exocrine body related genomics analysis

Experimental Investigation and Molecular Dynamics Simulation on the Anti-Adhesion Behavior of Alkanethiols on Nickel Insert in Micro Injection Molding

Due to the adhesion between the polymer melt and nickel (Ni) mold insert in the micro injection molding process, deformation defects frequently occur when the microstructures are demolded from the insert. In this study, self-assembled alkanethiols were applied to modify the surface of Ni mold insert to reduce its surface energy. Experimental trials were undertaken to explore the effect of alkanethiols coating on the replication quality. After that, molecular dynamics (MD) simulation was then used to investigate the adhesion behavior between the self-assembled coating and polypropylene (PP) by establishing three different types of alkanethiol material. The interaction energy, the potential energy change and radial distribution function were calculated to study the anti-adhesion mechanism. Experimental results show that all the three coatings can effectively decrease the adhesion and therefore promote the replication fidelity. It is demonstrated in MD simulation that the adhesion mainly comes from the van der Waals (vdW) force at the interface. The arrangement of sulfur atom on the Ni surface results in different absorbing behaviors. Compared with that of the PP–Ni interface, the interfacial energy and adhesion work after surface treatment is significantly reduced

Vision-Based a Seedling Selective Planting Control System for Vegetable Transplanter

Seedling transplanting is an important part of vegetable mechanized production in modern agriculture. After the seedlings are cultivated on a large scale by the nursery tray, they are planted into the field by the transplanter. However, unlike manual transplanting, transplanter is unable to judge the status of seedlings in the hole during seedling planting, which leads to problems such as damaged seedlings and empty holes being picked in the same order and planted into the field, resulting in yield reduction and missed planting. Aiming at this problem, we designed a seedling selective planting control system for vegetable transplanter which includes vision unit, seedling picking mechanism, seedling feeding mechanism, planting mechanism, pneumatic push rod unit, limit sensor, industrial computer and logic controller. We used asymmetrical light to construct visual identification scenes for planting conditions, which suppresses environmental disturbances. Based on the intersection operation of mask and image, a fast framework of tray hole location and seedling identification (FHLSI) was proposed combined with FCM segmentation algorithm. The vision unit provides the transplanting system with information on the status of the holes to be transplanted. Based on the information, planting system chooses the healthy seedlings for transplanting, improving the survival rate and quality of transplanting. The results show that the proposed visual method has an average accuracy of 92.35% for identification with the selective planting control system of seedlings and improves the transplanting quality by 15.4%

Hierarchical oxygen-implanted MoS2 nanoparticle decorated graphene for the non-enzymatic electrochemical sensing of hydrogen peroxide in alkaline media

Owing to the extensive applications of hydrogen peroxide (H2O2) in biological, environmental and chemical engineering, it is of great importance to investigate sensitive and selective sensing platform towards the detection of H2O2. Herein, oxygen-implanted MoS2 nanoparticles decorated graphene nanocomposite is synthesized via a facile one-pot solvothermal method for the sensitive detection of H2O2 in alkaline media. The structure and morphology of the MoS2/graphene nanocomposites were systematically characterized, showing that Mo-O bonds are formed and oxygen is implanted into the crystal structure in the nanocomposite. As a result, the MoS2/graphene composite exhibited enhanced electron transfer kinetics and excellent electro-reduction performance towards 11202 in alkaline media. Under optimum conditions, the fabricated sensor demonstrated a wide linear response towards H2O2 in the range of 0.25-16 mM with a low detection limit of 0.12 mu M and high sensitivity of 269.7 mu A mM(-1) cm(-2). Besides, the constructed sensor presented a good selectivity to H2O2 with the presence of other interfering species. Therefore, the proposed sensor was successfully applied for the detection and determination of H2O2 in real sample, indicating great potential for the practical applications.</p

Development of automatic conveying system for vegetable seedlings

Abstract In order to improve the automation and reliability of the mechanized transplanting, a vegetable seedling automatic conveying system was designed. The functional execution component of the system consists of a tank-wheel storage seedling mechanism, a seedling tray conveyor, and a hanging cup circulating conveying mechanism. Combined with the communication technology between host computer and programmable logic controller (PLC), the user interface software of automatic conveying system for potted vegetable was developed by using Visual Studio to control and monitor the transmission progress. The PVDF pressure sensor was used to detect the pressure change of the seedling storage disk to obtain the information of the loading seedling tray. The limit switch and stroke switch were combined to obtain the information of the push rod and feed plate. The timing of each component is controlled by the PLC controller combined with the feedback information of each sensor. The test results show the effect of taking an individual seedling is excellent, the error rate of the pushing mechanism is about 2.08%, and the success rate was 97.91%

Time-domain channel measurements and small-scale fading characterization for RIS-assisted wireless communication systems

Reconfigurable intelligent surfaces (RISs) have attracted extensive attention from industry and academia. In RIS-assisted wireless communication systems, practical channel measurements and modeling serve as the foundation for system design, network optimization, and performance evaluation. In this paper, a RIS time-domain channel measurement system, based on a software defined radio platform, is developed for the first time to investigate the small-scale fading characteristics of RIS-assisted channels. We present RIS channel measurements in corridor and laboratory scenarios and compare the power delay profile of the channel without RIS, with RIS specular reflection, and with RIS intelligent reflection. The multipath component parameters and cluster parameters based on the Saleh–Valenzuela model are extracted. We find that the power delay profiles(PDPs)of the RIS-assisted channel fit the power-law decay model better than the common exponential decay model and approximate the law of square decay. Through intelligent reflection, the RIS can decrease the delay and concentrate the energy of the virtual line-of-sight (VLoS) path, thereby reducing the delay spread and mitigating multipath fading. Furthermore, the cluster characteristics of RIS-assisted channels are highly dependent on the measurement environment. In the laboratory scenario, a single cluster dominated by the VLoS path with smooth envelope is observed. On the other hand, in the corridor scenario, some additional clusters introduced by the RIS reflection are created.<br/