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Uncovering the reason why some poorly conductive MOFs can be electrocatalysts with decent current density.

The machining accuracy is mainly indicated by the contour error especially in high-precision processing. Previously, scholars have proposed many controllers to reduce contour errors in real-time machining, such as the cross coupling controller and sliding mode controller. In this paper, we propose a controller based on model predictive control (MPC), and the contour error caused during path tracking can be effectively reduced by this controller. First of all, for two-dimensional (2D) and three-dimensional (3D) tool paths, their contour errors are deduced based on coordinate system transform. Second, the MPC-based controller is designed with the state-space discrete model of a machine tool. The contour error is regarded as a constraint during receding optimization. These are reasons why the presented control scheme is adapted with both bi-axis and three-axis machine tools. Furthermore, in order to improve the efficiency of receding optimization, the contour error of a 3D curve is simplified. Subsequently, the optimization problem is transformed into the standard form of quadratic programming. Finally, a 2D tool path and a 3D tool path are machined to test the proposed controller. Simulations and experiments show satisfactory results which indicate effectiveness of the proposed method.

Chunyu Lin,1,2,&ast; Yuan He,3,&ast; Mengnan Liu,1,4 Aihua Wu,1 Jing Zhang,4 Shurong Li,5 Shuqi Li,6 Qinghua Cao,6 Fang Liu1,2 1State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Department of Liver Tumor Center, Nanfang Hospital, Southern Medical University, Guangzhou, 51051, People’s Republic of China; 2Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, 51051, People’s Republic of China; 3Department of Radiotherapy, The First Affiliated Hospital of University of Science and Technology of China, Hefei, 23000, People’s Republic of China; 4Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, 51051, People’s Republic of China; 5Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 51008, People’s Republic of China; 6Department of Pathology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 51008, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Qinghua Cao, Department of Pathology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 51008, People’s Republic of China, Email caoqhua@mail.sysu.edu.cn Fang Liu, Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, 51051, People’s Republic of China, Email liufang7250@163.comBackground: To investigate the correlation between hepatocellular carcinoma (HCC) pathological types and conventional transarterial chemoembolization (cTACE), and to evaluate the predictive value of the pathological types for efficacy of cTACE.Methods: We investigated 186 naive HCC patients from 2 hospitals, including 63 patients with recurrence after surgical resection, and 123 unresectable cases, who underwent at least one cTACE procedure as the first treatment. All patients were histologically diagnosed with HCC by surgical resection and/or liver biopsy. Lipiodol deposition rate, ORR (objective response rate), PFS (progression-free survival), OS (overall survival) were compared among different HCC pathological types.Results: This study evaluated 186 naive HCC patients and 189 tumor nodules. Vessels that encapsulate tumor clusters (VETC), macrotrabecular-massive (MTM), CK19-positive types were identified in 38% (72/189), 40% (76/189), and 28% (53/189) of the whole cohort, respectively. VETC, MTM and CK19-negative HCCs derived significantly better lipiodol deposition rate and ORR. cTACE prolonged the PFS of VETC and CK19-negative HCCs compared with non-VETC and CK19-positive HCCs in the recurrence, liver biopsy and combining whole cohorts, whereas the OSs of different pathological types were not significantly different. Multivariate analysis showed that VETC (OR, 4.671, 95% CI [1.954, 11.166], P< 0.001) and CK19-positive type (OR, 0.127, 95% CI [0.044, 0.362], P< 0.001) were independent predictive factors for the first cTACE response. However, only VETC type was significantly associated with the second cTACE response in multivariate analysis (OR, 3.31, 95% CI [1.24, 8.83], P=0.017), suggesting that VETC might be a more useful predictor of cTACE response.Conclusion: Our study suggests that VETC is an effective predictor of cTACE response in patients with HCC.Keywords: hepatocellular carcinoma, vessels that encapsulate tumor clusters, CK19-positive, conventional transarterial chemoembolization

An injectable adhesive hydrogel based on N-hydroxysuccinimide γ-poly(glutamic acid) and 4-armed poly(ethylene glycol) amine showed rapid gelation time, strong mechanical strength, satisfactory burst pressure and excellent hemostatic performance.

We demonstrate that S-scheme photocatalysis of a hybrid system can promote the performance of photo-Fenton reaction under sunlight. Highly efficient charge-carrier separation can be achieved owing to a dispersion of TOC-PDI-POSS on the g-C3N4 surface.

Introduction: Isoflurane (ISO) may cause neuronal apoptosis and synaptic disorder during development, and damage long-term learning and memory function. This observation aimed to study the function of H19 in vitro and in vivo tests and the further mechanism was identified. Methods: ISO cell models and rat models were established and reactive oxygen species (ROS) identified. The viability and apoptosis of HT22 cells were detected by the MTT and flow cytometer. Morris water maze test was conducted to analyze the neurotoxicity of ISO on spatial learning and memory ability. Quantitative PCR was the method to verify the expression of H19. The concentration of inflammatory indicators was identified by enzyme-linked immunosorbent assay. Results: 1.5% and 2% ISO led to the neurotoxicity of HT22 cells and increased expression of H19. Silenced H19 meliorated these adverse impacts of ISO. Interference of H19 exerted neuroprotective roles by repressing modified neurological severity score, inhibiting escape latency, elevating distance and time of target area, and controlling ROS and inflammation. MiR-17-5p might be a promising competing endogenous RNA of H19. The expression of miR-17-5p was reduced in the ISO group and reversed by the absence of H19. Conclusion: Our results of in vitro and in vivo assay indicated that the absence of HT22 is a neuroprotective regulator of cognition and inflammation by accumulating miR-17-5p.

Improving the stability of aminated metal-free catalysts is a big challenge in Fenton-like reactions. Herein, trinuclear iron cluster (Fe3 cluster)-protected aminated graphene (Fe3-NH2-GR) is designed by a protective strategy. By protecting with the Fe3 cluster, the lone pair electrons of amino groups are protected and the N content of Fe3-NH2-GR can be fixed steadily. In peroxymonosulfate (PMS)-based Fenton-like reactions with a fixed-bed reactor, the lifetime of Fe3-NH2-GR is two times longer than that of aminated graphene (NH2-GR) under the same conditions. The deactivation kinetics shows that both Fe3-NH2-GR and NH2-GR follow zero-order kinetics and the deactivation rate constants of Fe3-NH2-GR are lower than that of NH2-GR at every period. Moreover, Fe3-NH2-GR still maintains 50% phenol degradation after 40 h rather than being constantly deactivated as NH2-GR. This stable activity is attributed to the formation of -O-NO2, while the N content will be lost in NH2-GR. This protective strategy by the Fe3 cluster provides a reliable method to enhance the efficiency and stability of carbon catalysts in Fenton-like reactions.

Human herpesvirus (HHV)-6 and HHV-7 have been detected in central nervous system and glioma tissue, while their exact role in glioma remains uncertain. Omics profiles and clinical information were downloaded from public databases, including The Cancer Genome Atlas cohort for training set and the Chinese Glioma Genome Atlas cohorts for validation sets. Differentially expressed genes between HHV-6 and HHV-7 infected or noninfected glioma patients were screened for establishing the HHV-6 and HHV-7 infection (HI) model through Lasso regression analysis. Bioinformatics methods were used to analyze the correlation between HI scores and prognosis, metastasis in glioma patients. Predictable efficacy of HI in temozolomide-resistance and HI-related genetic signatures were also explored. The HI model was constructed as: Risk score = (0.014709*DIRAS3) + (0.029787*TEX26) + (0.223492*FBXO39) + (0.074951*MYBL1) + (0.060202*HILS1). The five gene signature showed good performance in predicting survival time for glioma patients, while higher HI score is correlated with malignant features. Moreover, DNA mismatch repair genes were augmented in glioma patients with higher HI score as well as nonresponse to temozolomide treatment, which was in parallel with the transcriptomic result of temozolomide-resistant glioma cell. Targeting the five gene signature is beneficial for prognosis of glioma patients, especially in glioma patients underwent temozolomide treatment.

Alkali–surfactant–polymer (ASP) flooding holds a critical position in oil development. This paper is concerned with the distributed parameter system (DPS) modeling and development scheme optimization of ASP flooding. Owing to the neglect of coupling among three-dimensional (3-D) spatial information, most of the existing data-driven modeling methods fail to provide a high-precision model for this type of strongly nonlinear and spatiotemporal coupling 3-D DPS. To overcome this shortcoming, an integrated spatiotemporal modeling method (ISM) is proposed, which reconstructs temporal–spatial relationship to avoid spatial mapping distortion based on canonical polyadic decomposition (CPD), and a spatiotemporal MSSO-LS-SVM algorithm is presented to compensate the nonlinear dynamics and decrease truncation error. Moreover, the synchronous optimization of ASP injection strategy and oil wells switching scheduling is an urgent industry requirement of intelligent oilfield decision system, which can be described a mixed-integer optimal control/dynamic programming problem. This paper first puts forward a mixed-integer approximate dynamic programming (MIADP) algorithm, dedicated for solving this class of optimal control problem with integer control subset requirements. In the MIADP, a parallel mixed-integer policy improvement framework is developed, where (i) the continuous control weight updates by the temporal difference (TD) error, (ii) the quantum evolution mechanism is designed to learn the integer control, and (iii) the two parts share information interactively and iterate to approach the optimal mixed-integer policy. At last, a case study on ASP flooding is taken, and the superior performance metrics illustrate the effectiveness of the proposed ISM method and MIADP algorithm.

During T lymphocyte development, immature T lymphocyte undergoes V(D)J rearrangement of T-cell receptor (TCR) genes to further develop to functional T cells. Upon this situation, additional DNA damage coming from the mutation of DNA replication genes sensitively makes immature T cells undergo apoptosis. While the mechanisms how immature T lymphocytes undergo fast cell death upon genomic instability have not been resolved. In our current study, we showed that in zebrafish mcm5 mutants, the immature T cells specifically and cell-autonomously undergo rapid apoptosis during T lymphocytes maturation. In mechanism, mcm5 loss of function results in DNA damage and up-regulation of tp53 signaling, sequentially gives rise to immature T lymphocytes apoptosis. Meanwhile upon mcm5 mutant, the absence of MCM5 decreases MCM5-Stat1 complex and disrupts phosphorylation of Stat1, which sequentially inhibits bcl2a transcription and accelerates the apoptosis of immature T lymphocytes. As the evidence, after blocking DNA synthesizing using chemical DNA synthesis inhibitors, MCM5 facilitates the up-regulation of bcl2a transcription to avoid rapid death of immature T lymphocytes. Our study first provides a mechanism as to how immature T cells with DNA damage coming from endogenous DNA replication stress are rapidly cleared off during early development, as well explains the extra biological role of MCM5 beside the role in DNA duplication regulation.

With the rapid development of renewable energy resources, harmonics in modern distribution systems have become more serious owing to the wide adoption of power electronic devices. Today, distribution-level phasor measurement units (D-PMUs), which can provide synchronized harmonic data with high-time resolution, are being rapidly developed. To utilize the D-PMUs, a hierarchical harmonic contribution (HC) determination method is proposed in this paper for systems with multiple harmonic sources. The HCs were determined using a widely linear complex partial least squares (WL-CPLS) method, which is both accurate and efficient. In an actual power system, the D-PMUs are not fully installed at all buses and the harmonics monitored by each D-PMU are actually the aggregate effects of multiple harmonic sources in the subarea. Based on the above consideration, a hierarchical HC strategy is proposed to locate the main harmonic contributors, layer by layer. The proposed method can be applied to a radial distribution system with any number of D-PMU placements. The methodologies are explained and verified using the IEEE 37-bus system. The real case study results based on the demonstration project are also analyzed in this paper.

This article is concerned with the numerical solution for a class of interval multi-objective mixed-integer optimal control problems (IMOMIOCPs). The IMOMIOCPs under investigation are typical NP-hard problems involve unknown-but-bounded interval parameters, multiple objectives, and mixed-integer dynamic controls. Accordingly, a new numerical method based on quantum heuristic algorithm is designed, which has the following modules: (i) Control vector parameterization and the fourth order Runge–Kutta method for model discretization, (ii) interval programming based on interval credibility for addressing interval parameters, (iii) coevolution of Quantum Annealing and Quantum Krill Herd for searching the optimal mixed-integer decisions, and (iv) the multiple populations for multi-objective technology for establishing the Pareto optimal front. The analyses on convergence and computational complexity of the proposed optimization mechanism are given. Moreover, simulation results on benchmark functions and a practical engineering IMOMIOCP verify that the proposed numerical method is more excel at achieving promising results than some classic algorithms and state-of-the-art algorithms.

Mixed-integer optimal control problems (MIOCPs) usually play important roles in many real-world engineering applications. However, the MIOCP is a typical NP-hard problem with considerable computational complexity, resulting in slow convergence or premature convergence by most current heuristic optimization algorithms. Accordingly, this study proposes a new and effective hybrid algorithm based on quantum computing theory to solve the MIOCP. The algorithm consists of two parts: (i) Quantum Annealing (QA) specializes in solving integer optimization with high efficiency owing to the unique annealing process based on quantum tunneling, and (ii) Double-Elite Quantum Ant Colony Algorithm (DEQACA) which adopts double-elite coevolutionary mechanism to enhance global searching is developed for the optimization of continuous decisions. The hybrid QA/DEQACA algorithm integrates the strengths of such algorithms to better balance the exploration and exploitation abilities. The overall evolution performs to seek out the optimal mixed-integer decisions by interactive parallel computing of the QA and the DEQACA. Simulation results on benchmark functions and practical engineering optimization problems verify that the proposed numerical method is more excel at achieving promising results than other two state-of-the-art heuristics.

In recent decades, studies on short-term traffic speed forecasting of the large-scale road are a new challenge for researchers and engineers. Especially based on deep learning neural networks, studies on short-term traffic forecasting have achieved mush-room growth. This study proposes a stacked Bidirectional Gated Recurrent Unit neural network model to predict the traffic speed of the expressway over different estimation time intervals in an effective manner. By building a multiscale-grid model, it can take less time to derive a set of key traffic parameters of different scales to predict traffic speed of the various-scale road. The speed prediction of small-scale sections can cover more detailed road spatial features preparing for Vehicle Navigation System, and the speed prediction of large-scale sections can establish the real-time traffic control strategies. In order to validate the effectiveness of the proposed model, we use the floating car data, with an updating frequency of 1 minute from the urban freeway of Beijing, for model training and testing. The experimental results show that the stacked BiGRU network with the multiscale-grid model enables to capture the spatial-temporal characteristics of traffic speed efficiently. Furthermore, the BiGRU with two layers (BiGRU-2L) outperforms benchmark models in the prediction of the traffic speed, which presents a significant advantage in reducing the overfitting problem, decreasing the excessive time-consuming and improving the effective use of limited computation resources.

Minichromosome maintenance protein 5 (MCM5), a member of the microchromosomal maintenance protein family, plays an important role in the initiation and extension of DNA replication. However, its role in neural development in zebrafish remains unclear. Here, we used morpholino (MO) and CRISPR/Cas9 to knock down mcm5 and investigated the developmental features of facial motor neurons (FMNs) in the hindbrain of zebrafish. We found that knockdown of mcm5 using mcm5 MO resulted in a small head, small eyes, and a blurred midbrain-hindbrain boundary, while MO injection of mcm5 led to decrease in FMNs and their migration disorder. However, the mutant of mcm5 only resulted in the migration defect of FMNs rather than quantity change. We further investigated the underlying mechanism of mcm5 in the development of hindbrain using in situ hybridization (ISH) and fgfr1a mRNA co-injected with mcm5 MO. Results from ISH showed that the fibroblast growth factor (FGF) signaling pathway was changed when the MCM5 function was lost, with the decrease in fgfr1a and the increase in fgf8, while that of pea3 had opposite trend. FMN development defects were rescued by fgfr1a mRNA co-injected with mcm5 MO. Our results demonstrated that FGF signaling pathway is required for FMN development in zebrafish. Specifically, mcm5 regulates FMN development during zebrafish growing.

Nowadays, proteins separation has attracted great attention in proteomics research. Because the proteins separation is helpful for making an early diagnosis of many diseases. Magnetic nanoparticles are an interesting and useful functional material, and have attracted extensive research interest during the past decades. Because of the excellent properties such as easy surface functionalization, tunable biocompatibility, high saturation magnetization etc, magnetic microspheres have been widely used in isolation of proteins/peptides. Notably, with the rapid development of surface decoration strategies, more and more functional magnetic adsorbents have been designed and fabricated to meet the growing demands of biological separation. In this review, we have collected recent information about magnetic adsorbents applications in selective separation of proteins/peptides. Furthermore, we present a comprehensive prospects and challenges in the field of protein separation relying on magnetic nanoparticles.

Many engineering optimisation problems can be summarised as mixed-integer optimal control problems (MIOCPs) owing to the needs for mixed-integer dynamic control decisions. However, the convergence ...

To develop a multisequence MRI-based radiomics signature for the preoperative prediction of the muscle-invasive status of bladder cancer (BCa). This retrospective study involved 106 eligible patients from two independent clinical centers. All patients underwent a preoperative 3.0 T MRI scan with T2-weighted image (T2WI) and multi-b-value diffusion-weighted image (DWI) sequences. In total, 1404 radiomics features were extracted from the largest region of the reported tumor locations on the T2WI, DWI, and corresponding apparent diffusion coefficient map (ADC) of each patient. A radiomics signature, namely the Radscore, was then generated using the recursive feature elimination approach and a logistic regression algorithm in a training cohort (n = 64). Its performance was then validated in an independent validation cohort (n = 42). The primary imaging and clinical factors in conjunction with the Radscore were used to determine whether the performance could be further improved. The Radscore, generated by 36 selected radiomics features, demonstrated a favorable ability to predict muscle-invasive BCa status in both the training (AUC 0.880) and validation (AUC 0.813) cohorts. Subsequently, integrating the two independent predictors (including the Radscore and MRI-determined tumor stalk) into a nomogram exhibited more favorable discriminatory performance, with the AUC improved to 0.924 and 0.877 in both cohorts, respectively. The proposed multisequence MRI-based radiomics signature alone could be an effective tool for quantitative prediction of muscle-invasive status of BCa. Integrating the Radscore with MRI-determined tumor stalk could further improve the discriminatory power, realizing more accurate prediction of nonmuscle-invasive and muscle-invasive BCa. • DWI is superior to T2WI sequence in reflecting the heterogeneous differences between NMIBC and MIBC, and multisequence MRI helps in the preoperative prediction of muscle-invasive status of BCa. • Co-occurrence (CM), run-length matrix (RLM), and gray-level size zone matrix (GLSZM) features were the favorable feature categories for the prediction of muscle-invasive status of BCa. • The Radscore (proposed multisequence MRI-based radiomics signature) helps predict preoperatively muscle invasion. Combination with the MRI-determined tumor stalk further improves prediction.

This article presents a numerical method based on quantum computing to solve two unresolved key issues for alkali–surfactant–polymer (ASP) flooding in oil exploitation: uncertainties affecting deve...

This study proposes a lane-changing trajectory planning method for automated vehicles under various road line-types. The method uses the polynomial regression model to describe the road line-types, and then a non-linear optimisation model is constructed to generate the lane-changing trajectory based on the road polynomial functions. The process of connecting the lane-changing manoeuvre with the car-following manoeuvre is discussed in this study, which ensures the ride comfort of the ego vehicle after the lane-changing manoeuvre. Moreover, considering that the lag vehicle on the target lane may be affected by the lane-changing manoeuvre, the situation that the lag vehicle maintains the car-following manoeuvre with the ego vehicle is taken into account in the authors' model. Another small innovation is that they have designed a simple and effective method to find the suitable initial guess for the proposed non-linear optimisation model. The simulation results show that the lane-changing trajectory generated by the proposed model is smooth and continuous, and the automated vehicle can avoid potential collisions efficiently during the lane-changing process. In emergent conditions, the proposed model can also plan the corrected trajectory to ensure safety.