Composite rock-breaking of high-pressure CO2 jet & polycrystallinediamond-compact (PDC) cutter using a coupled SPH/FEM Model

Acknowledgments This work was supported by the National Natural Science Foundation of China (Grant No. 52004236), Sichuan Science and Technology Program (Grant No. 2021JDRC0114), the Starting Project of SWPU (Grant No.2019QHZ009), the China Postdoctoral Science Foundation (Grant No.2020M673285), the Open Project Program of Key Laboratory of Groundwater Resources and Environment (Jilin University), Ministry of Education (Grant No.202005009KF), and the Chinese Scholarship Council (CSC) funding (CSC NO.202008515107) for the financial support of this work.Peer reviewedPublisher PD

Association of age-related hearing loss with cognitive impairment and dementia: an umbrella review

BackgroundHearing loss, cognitive impairment and dementia have become common problems for older adults. Currently, systematic reviews and meta-analyses of the association between age-related hearing loss (ARHL) with cognitive impairment and dementia may have inconsistent results. To explore and validate the association between ARHL with cognitive impairment and dementia through summarizing and evaluating existing evidence.MethodsFrom inception to February 01, 2023, PubMed, Web of Science, Embase, and Cochrane Library databases were systematically searched. AMSTAR 2 was used to evaluate methodological quality and GRADE system was used to evaluate evidence quality. We summarized the basic characteristics of the included studies and extracted effect data for ARHL with cognitive impairment and dementia. Forest plots were used to describe the relative risk associated with ARHL and cognitive impairment, and the relative risk associated with ARHL and dementia, respectively.ResultsA total of 11 systematic reviews and meta-analyses met the inclusion criteria. Overall, the methodological quality of the included SRs/MAs was moderate and the quality of the evidence was low. The combined results found that the pooled risk ratio of ARHL and cognitive impairment was 1.30 (random-effects; 95% CI 1.16 to 1.45), and the pooled risk ratio of ARHL and dementia was 1.59 (random-effects; 95% CI 1.34 to 1.90).ConclusionBased on the evidence reported in this umbrella review, age-related hearing loss is significantly associated with cognitive impairment and dementia. Hearing loss may be a high risk factor for cognitive impairment and dementia in older adults

Injectable kartogenin and apocynin loaded micelle enhances the alleviation of intervertebral disc degeneration by adipose-derived stem cell.

Cell transplantation has been proved the promising therapeutic effects on intervertebral disc degeneration (IVDD). However, the increased levels of reactive oxygen species (ROS) in the degenerated region will impede the efficiency of human adipose-derived stem cells (human ADSCs) transplantation therapy. It inhibits human ADSCs proliferation, and increases human ADSCs apoptosis. Herein, we firstly devised a novel amphiphilic copolymer PEG-PAPO, which could self-assemble into a nanosized micelle and load lipophilic kartogenin (KGN), as a single complex (PAKM). It was an injectable esterase-responsive micelle, and showed controlled release ability of KGN and apocynin (APO). Oxidative stimulation promoted the esterase activity in human ADSCs, which accelerate degradation of esterase-responsive micelle. Compared its monomer, the PAKM micelle possessed better bioactivities, which were attributed to their synergistic effect. It enhanced the viability, autophagic activation (P62, LC3 II), ECM-related transcription factor (SOX9), and ECM (Collagen II, Aggrecan) maintenance in human ADSCs. Furthermore, it is demonstrated that the injection of PAKM with human ADSCs yielded higher disc height and water content in rats. Therefore, PAKM micelles perform promoting cell survival and differentiation effects, and may be a potential therapeutic agent for IVDD

ETO Meets Scheduling: Learning Key Knowledge from Single-Objective Problems to Multi-Objective Problem

Evolutionary transfer optimization(ETO) serves as "a new frontier in evolutionary computation research", which will avoid zero reuse of experience and knowledge from solved problems in traditional evolutionary computation. In scheduling applications via ETO, a highly competitive "meeting" framework between them could be constituted towards both intelligent scheduling and green scheduling, especially for carbon neutrality within the context of China. To the best of our knowledge, our study on scheduling here, is the 1st work of ETO for complex optimization when multiobjective problem "meets" single-objective problems in combinatorial case (not multitasking optimization). More specifically, key knowledge like positional building blocks clustered, could be learned and transferred for permutation flow shop scheduling problem (PFSP). Empirical studies on well-studied benchmarks validate relatively firm effectiveness and great potential of our proposed ETO-PFSP framework.Comment: For improvemen

Outage Probability Performance Prediction for Mobile Cooperative Communication Networks Based on Artificial Neural Network

This paper investigates outage probability (OP) performance predictions using transmit antenna selection (TAS) and derives exact closed-form OP expressions for a TAS scheme. It uses Monte-Carlo simulations to evaluate OP performance and verify the analysis. A back-propagation (BP) neural network-based OP performance prediction algorithm is proposed and compared with extreme learning machine (ELM), locally weighted linear regression (LWLR), support vector machine (SVM), and BP neural network methods. The proposed method was found to have higher OP performance prediction results than the other prediction methods

Prediction Model of Ammonia Nitrogen Concentration in Aquaculture Based on Improved AdaBoost and LSTM

The concentration of ammonia nitrogen is significant for intensive aquaculture, and if the concentration of ammonia nitrogen is too high, it will seriously affect the survival state of aquaculture. Therefore, prediction and control of the ammonia nitrogen concentration in advance is essential. This paper proposed a combined model based on X Adaptive Boosting (XAdaBoost) and the Long Short-Term Memory neural network (LSTM) to predict ammonia nitrogen concentration in mariculture. Firstly, the weight assignment strategy was improved, and the number of correction iterations was introduced to retard the shortcomings of data error accumulation caused by the AdaBoost basic algorithm. Then, the XAdaBoost algorithm generated and combined several LSTM su-models to predict the ammonia nitrogen concentration. Finally, there were two experiments conducted to verify the effectiveness of the proposed prediction model. In the ammonia nitrogen concentration prediction experiment, compared with the LSTM and other comparison models, the RMSE of the XAdaBoost–LSTM model was reduced by about 0.89–2.82%, the MAE was reduced by about 0.72–2.47%, and the MAPE was reduced by about 8.69–18.39%. In the model stability experiment, the RMSE, MAE, and MAPE of the XAdaBoost–LSTM model decreased by about 1–1.5%, 0.7–1.7%, and 7–14%. From these two experiments, the evaluation indexes of the XAdaBoost–LSTM model were superior to the comparison models, which proves that the model has good prediction accuracy and stability and lays a foundation for monitoring and regulating the change of ammonia nitrogen concentration in the future

Robust angle estimation for MIMO radar with the coexistence of mutual coupling and colored noise

This paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. Then taking advantage of the temporal uncorrelated characteristic of colored noise and the banded complex symmetric Toeplitz structure of the mutual coupling matrices, a novel fourth-order covariance tensor is constructed for eliminating the influence of both spatial colored noise and mutual coupling. After a robust signal subspace estimation is obtained by using the higher-order singular value decomposition (HOSVD) technique, the rotational invariance technique is applied to achieve the DODs and DOAs. Compared with the existing HOSVD-based subspace methods, the proposed method can provide superior angle estimation performance and automatically jointly perform the DODs and DOAs. Results from numerical experiments are presented to verify the effectiveness of the proposed method.Published versio

Blind Channel Estimation for FBMC/OQAM Systems Based on Subspace Approach

The conventional channel estimation schemes for filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems are mainly based on preamble methods. However, the utilization of preamble for channel estimation decreases the system’s spectrum efficiency. In this paper, we propose a modified subspace blind channel estimation method for FBMC/OQAM systems. The proposed method distinguishes itself from previously preamble based methods by utilizing spatial diversity technique to introduce data redundancy for blind channel estimation, which leads to high spectral utilization. Thus, the proposed method can provide significant root mean square error (RMSE) performance improvement compared to conventional preamble based methods at high SNRs. Simulation results verify the validity of the proposed method in FBMC/OQAM systems