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Abstract Under the framework of event‐triggered transmission mechanism, the problem of attack detection and state estimation of multi‐sensor linear time‐invariant systems under static attacks is considered. First, for each transmission channel, the sensor collects measurement information according to an event‐triggered mechanism to reduce unnecessary energy consumption. Then, inspired by the clustering algorithm in machine learning, a detection mechanism based on Gaussian mixture model, which can set a confidence level for the measurement of each sensor is proposed. Finally, centralised data fusion is performed according to the results of attack detection and event‐triggered judgement to realise remote state estimation. A numerical example proves that the proposed algorithm can locate the damaged sensor, save the network transmission bandwidth under the premise of ensuring accuracy and efficiency of sensor estimation.

Labral tear of the hip joint is an important factor causing joint pain and locking, as well as mobility disturbance. Although femoroacetabular impingement syndrome often results in anterior labral tears, posterior labral tears are present in a subset of patients, especially those with a history of posterior hip dislocation. Posterior labral repair under arthroscopy usually requires switching between the viewing approach and the operating approach, but this undoubtedly increases the operative time and the destruction of soft tissue. This article introduces a technique for rapid posterior labral suture by rotating the arthroscopic camera without switching the surgical approach.

Hepatocellular carcinoma(HCC) has a high mortality and morbidity rate and seriously jeopardizes human life. Chemicals and chemotherapeutic agents have been experiencing problems such as side effects and drug resistance in the treatment of HCC, which cannot meet the needs of clinical treatment. Therefore, finding novel low-toxicity and high-efficiency anti-hepatocellular carcinoma drugs and exploring their mechanisms of action have become the current problems to be solved in the treatment of HCC. Several studies have reported anticancer effects of inotodiol. This study focuses on the anticancer effect of inotodiol in HCC cells and its molecular mechanism, aiming to explore its anticancer effect in depth. The CCK8 assay was utilized to assess cell viability, the scratch assay was utilized to detect migration ability, the clone formation assay was utilized to detect clonogenic ability, and flow cytometry was utilized to analyze apoptosis and cell cycle. Animal experiments was utilized to verify the inhibitory effect of inotodiol on HCC. Meanwhile, western blotting was utilized to detect proteins associated with apoptosis, cell cycle and MAPK/ERK pathway. These results showed that inotodiol has the ability to promote apoptosis, as well as inhibit the ability of cell proliferation, migration, and clonogenic ability. The cell cycle was arrested in G1 phase, when the expression of CDK2, CDK4, CDK6 and Cyclin D were inhibited. In addition, inotodiol showed to induce apoptosis, characterized by an increase in Bax expression, a decrease in Bcl-2, Bcl-XL and MCL1 expression, the initiation of cleaved PARP1 and cleaved caspase 3, and inhibition of the MAPK/ERK pathway. Animal studies demonstrated that inotodiol possessed the ability to suppress tumor growth in nude mice models, at the same time, there was no significant impact on the body weight and organs of the mice. In conclusion, the findings presented herein compellingly suggest that inotodiol may serve as a promising candidate for the treatment of hepatocellular carcinoma (HCC).

Abstract Hydrogel composites in an aqueous media with viscoelastic properties and elastic modulus that can be precisely tailored are desirable to mimic many biological tissues ranging from mucus, vitreous humor, and nucleus pulposus as well as build up biosensors. Without altering the chemistry, tuning the physical interactions and structures to govern the viscoelastic properties of the hydrogels is indispensable for their applications but quite limited. Here we design a complexation gel composite and utilize the physical principle of topologically frustrated dynamical state to tune the correlated structures between the guest polycation chains and negatively charged host gels. We precisely quantify the mesh size of the host gel and guest chain size. By designing various topologically correlated structures, a viscoelastic moduli map can be built up, ranging from tough to ultrasoft, and from elastic-like with low damping properties to viscous-like with high damping properties. We also tune the swelling ratio by using entropy effect and discover an Entropy-driven Topologically Isovolumetric Point. Our findings provide essential physics to understand the relationship between entropy-driven correlated structures and their viscoelastic properties of the complexation hydrogel composites and will have diverse applications in tissue engineering and soft biomaterials.

Entangled porous metallic wire material (EPMWM) has the potential as a thermal insulation material in defence and engineering. In order to optimize its thermophysical properties at the design stage, it is of great significance to reveal the thermal response mechanism of EPMWM based on its complex structural effects. In the present work, virtual manufacturing technology (VMT) was developed to restore the physics-based 3D model of EPMWM. On this basis, the transient thermal analysis is carried out to explore the contact-relevant thermal behavior of EPMWM, and then the spiral unit containing unique structural information are further extracted and counted. In particular, the thermal resistance network is numerically constructed based on the spiral unit through the thermoelectric analogy method to accurately predict the effective thermal conductivity (ETC) of EPMWM. Finally, the thermal diffusivity and specific heat of the samples were obtained by the laser thermal analyzer to calculate the ETC and thermal insulation factor of interest. The results show that the ETC of EPMWM increases with increasing temperature or reducing density under the experimental conditions. The numerical prediction is consistent with the experimental result and the average error is less than 4%.

ObjectiveThis paper aims to evaluate the impact of flow-induced vibration on the receiver performance of low-frequency magnetic antenna in an underwater environment, investigating the electromagnetic-induced noise of antenna under different vibration conditions. MethodsFirst, a fluid excitation antenna vibration model is established using COMSOL software, then an antenna vibration-induced noise model is constructed to simulate electromagnetic-induced noise. Finally, outdoor experiments to measure the antenna vibration-induced noise are carried out. Results The results show that the stronger the antenna vibration is, the greater the electromagnetic-induced noise is. When the antenna vibration acceleration reaches 0.029 4 m/s², the electromagnetic-induced noise above the pT level will be caused, and the normal communication signal will be submerged. ConclusionThe results show that the proposed model in this paper can be used to evaluate the vibration-induced noise of low frequency magnetic antenna.

The emergence and application of conjugate materials provide a broader space for the performance of sound and presentation effects on the modern music stage. This article compared and analyzed the application of conjugated materials and traditional methods in modern dance sound effects and stage presentation effects through experiments, found that the application of conjugated materials on modern stages had the effect of enhancing visual effects. Its overall reflectivity, color saturation, brightness, transparency, etc. remain in the range of 78%–97%, which is better than traditional methods. In addition, the use of conjugated materials can also improve auditory performance, have greater penetration and durability, and reduce the impact of external noise; in terms of audience experience and dancer experience, the average proportions also reached 87.8893% and 89.3867% respectively. In addition, it also has high temperature resistance and antibacterial effects, with a maximum temperature resistance value of 314.28°C and an antibacterial effect of 95.86%, indicating that it can still maintain stability under high temperature conditions and has a good inhibitory effect on the proliferation of bacteria and viruses. These findings will lay the foundation for further expanding the application of conjugated materials on the modern dance stage.

Abstract Background Varieties of animals were used to study osteoarthritis pathogenesis. The Diannan small-ear pig, which is native to Yunnan, China, is thought to have an articular anatomy similar to that of humans and is more likely to be a source of pathological tissues than other animals. The aim of this study was to determine whether this animal can serve as a more effective osteoarthritis model and explore the role of SDF-1/CXCR4 signaling pathway in the development of Osteoarthritis in animals. Methods Twenty-seven adult pigs were randomly divided into three groups and underwent the Hulth procedure, papain articular injection, and conventional breeding. After 4, 8, and 12 weeks, cartilage tissues from knee joint were extracted for general and histological observation, immunofluorescence, and biochemical analysis. Synovium was taken out for stromal cell-derived factor-1 analysis. Results Histopathological observation showed obvious cartilage loss in two experimental groups, this cartilage loss was more severe in the chemical groups. Synovial stromal cell-derived factor1 levels increased over time in all groups. mRNA and protein levels of matrix metalloproteinase-3 were much higher in the chemical groups than in the other groups, whereas levels of collagen type II and aggrecan were significantly lower in the chemical groups than in the other groups. Immunofluorescence assays of collagen type II revealed an apparent reduction in this marker in the chemical groups compared with the other groups. Conclusions These results indicated that the Diannan small-ear pig can be used as an effective osteoarthritis model. In addition, it is much more convenient and much faster to induce osteoarthritis by intra-articular injection of papain, which is a method worthy of being promoted.

Internal waves induced by an underwater self-propelled body expose its existence by changing the sea surface roughness. This study employs short-time Fourier transform to perform the time–frequency analysis on the internal wave signal captured in the experiments. Some key characteristics of the underwater self-propelled body are obtained through the spectrum analysis of the internal wave wake signal. Moreover, the influence of the interaction between the momentums induced by the propulsion and drag force is discussed. The results show that the action of the self-propelled body has varying degrees of influence on the symmetry and spatial distribution of the spectrum characteristics of the signal.

Gels are polymer networks swollen in various solvents [...]

Objectives To conduct a systematic review and meta-analysis of the efficacy and safety of abdominal paracentesis drainage (APD) in patients with acute pancreatitis (AP) when compared with conventional ‘step-up’ strategy based on percutaneous catheter drainage (PCD).Design Systematic review and meta-analysis.Methods PubMed, EMBASE, Cochrane Library, MEDLINE (OVID), China National Knowledge Infrastructure and Wanfang Database were electronically searched to collect cohort studies and randomised controlled trials (RCTs) from inception to 25 July 2020. Studies related to comparing APD with conventional ‘step-up’ strategy based on PCD were included.Outcomes The primary outcome was all-cause mortality. The secondary outcomes were the rate of organ dysfunction, infectious complications, hospitalisation expenses and length of hospital stay.Results Five cohort studies and three RCTs were included in the analysis. Compared with the conventional ‘step-up’ method, pooled results suggested APD significantly decreased all-cause mortality during hospitalisation (cohort studies: OR 0.48, 95% CI 0.26 to 0.89 and p=0.02), length of hospital stay (cohort studies: standard mean difference (SMD) −0.31, 95% CI −0.53 to –0.10 and p=0.005; RCTs: SMD −0.45, 95% CI −0.64 to –0.26 and p

To reduce the vibration of a cantilever steel plate in high-temperature environments (25°C–500°C), a new composite structure with entangled metallic wire material (EMWM) core was proposed. The damping performance of the EMWM under different temperatures was investigated. The results show that when the temperature does not exceed 260°C, the damping property of the EMWM is not affected by temperature. When the temperature exceeds 260°C, the damping property of the EMWM decreases with the increase of temperature. A thermal-vibration joint test system was set up to verify the energy dissipation mechanism of the composite structure with EMWM core and to research the effect of vibration reduction under different temperatures. The displacement deviation between the baseplate (steel plate) and constraining plate was sufficient to cause frictional energy dissipation of the EMWM core. The thermal-vibration joint test results indicated that the EMWM core had a positive impact on the damping properties of the cantilever structure. Adding EMWM core and constraining plate can significantly increase the damping ratio and reduces the vibration of the cantilever structures under different temperatures. This research is helpful to control the structural vibrations of cantilever structures in high-temperature environments.

Pavement crack detection and characterization is a fundamental part of road intelligent maintenance systems. Due to the high non-uniformity of cracks, topological complexity, and similar noise from crack texture, the challenge arises in this domain with automated crack detection and classification in a complex environment. In this work, an overarching framework for a universal and robust automatic method that simultaneously characterizes the type of crack and its severity level was developed. For crack detection, we propose a novel and efficient crack detection network that captures the crack context information by establishing a multiscale dilated convolution module. On this foundation, an attention mechanism is introduced to further refine the high-level features. Moreover, the rich features at different levels are fused in an upsampling module to generate more detailed crack detection results. For crack classification, a novel characterization algorithm is developed to classify the type of crack after detection. The crack segment branches are then merged and classified into four types: transversal, longitudinal, block, and alligator; the severity levels of cracks are assessed by calculating the average width and distance between the crack branches. The proposed crack detection method effectively detects crack information in a complex environment, and achieves the current state-of-the-art accuracy. Compared to manual classification results, the classification accuracy of transversal and longitudinal cracks is higher than 95%, and the classification accuracy of block and alligator is above 86%.

Anthracyline (ANT) has been demonstrated as a useful treatment for leukemia and solid tumors. However, ANT has previously reported cardiotoxic effects, which can reduce the therapeutic index for cancer treatment. This study aimed to investigate the associations of glycogen phosphorylase isoenzyme BB (GPBB), myoglobin (Mb), and brain natriuretic peptide (BNP) with anthracycline (ANT-induced cardiotoxicity (AIC)) amongst the Chinese population. Patients suffering from leukemia were recruited. Electrocardiogram and echocardiography were used along with chemotherapy to determine left ventricular ejection fraction (LVEF), mitral ratio of peak early to late diastolic filling velocity (E/A), E-wave deceleration time (EDT), and isovolumic relaxation time (IVRT). Double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) was employed to examine and compare serum GPBB, Mb, and BNP levels. Following chemotherapy, the patients presented higher levels of serum GPBB, Mb, and BNP than before chemotherapy treatment. The levels of LVEF (%), E/A, and IVRT were significantly decreased after chemotherapy, while EDT was markedly increased. The cumulative ANT dose was positively corelated to serum GPBB, Mb, and BNP levels while it was negatively corelated to LVEF levels. In conclusion, serum GPBB, Mb, and BNP levels in combination might provide higher diagnostic accuracy in the early detection of AIC compared with other single indicators.

Diffusion of molecules in crowded environment is important for various living systems, but the dynamics of charged molecules in charged matrices remains still unexplored. Here the authors report a dynamics of DNA and polyelectrolytes in a charged hydrogel where the guest molecules do not diffuse but experience topologically frustrated dynamics.

Osteoarthritis (OA) is a chronic joint function disorder with characteristics of chondrocytes reduction and extracellular matrix (ECM) components destruction. MicroRNAs (miRNAs) and the SDF-1/CXCR4 axis are essential factors of chondrocyte apoptosis and ECM degeneration. However, very few studies have investigated the correlation between miRNAs and the SDF-1/CXCR4 axis in osteoarthritis so far. Here, through miRNAs microarray and bioinformatics analyses, we identified miR-142-5p as a CXCR4-targeted and dramatically downregulated miRNA in cartilage from OA patients, as well as in SDF-1-induced OA chondrocytes in vitro. In SDF-1-treated primary human OA chondrocytes that were transfected with a miR-142-5p mimic or inhibitor, the expression of CXCR4 was found to be inversely correlated with the expression of miR-142-5p. The dual luciferase reporter assay further verified the target relationship between miR-142-5p and CXCR4. Overexpression of miR-142-5p alleviated OA pathology by suppressing chondrocyte apoptosis, even in CXCR4 overexpressed OA chondrocytes. This was associated with decreased cartilage matrix degradation, reduced cartilage inflammation, and inactivated MAPK signaling pathway. Our study suggests that upregulated expression of CXCR4-targeted miR-142-5p can inhibit apoptosis, inflammation, and matrix catabolism and inactivate the MAPK signaling pathway in OA chondrocytes. Our work provides important insight into targeting miR-142-5p and the SDF-1/CXCR4 axis in OA therapy.

Road pavement cracks automated detection is one of the key factors to evaluate the road distress quality, and it is a difficult issue for the construction of intelligent maintenance systems. However, pavement cracks automated detection has been a challenging task, including strong nonuniformity, complex topology, and strong noise-like problems in the crack images, and so on. To address these challenges, we propose the CrackSeg—an end-to-end trainable deep convolutional neural network for pavement crack detection, which is effective in achieving pixel-level, and automated detection via high-level features. In this work, we introduce a novel multiscale dilated convolutional module that can learn rich deep convolutional features, making the crack features acquired under a complex background more discriminant. Moreover, in the upsampling module process, the high spatial resolution features of the shallow network are fused to obtain more refined pixel-level pavement crack detection results. We train and evaluate the CrackSeg net on our CrackDataset, the experimental results prove that the CrackSeg achieves high performance with a precision of 98.00%, recall of 97.85%, F-score of 97.92%, and a mIoU of 73.53%. Compared with other state-of-the-art methods, the CrackSeg performs more efficiently, and robustly for automated pavement crack detection.

The fundamental attributes of charged hydrogels containing predominantly water and controllable amounts of low molar mass electrolytes are of tremendous significance in biological context and applications in healthcare. However, a rigorous theoretical formulation of gel behavior continues to be a challenge due to the presence of multiple length and time scales in the system which operate simultaneously. Furthermore, chain connectivity, the electrostatic interaction, and the hydrodynamic interaction all lead to long-range interactions. In spite of these complications, considerable progress has been achieved over the past several decades in generating theories of variable complexity. The present review presents an analytically tractable theory by accounting for correlations emerging from topological, electrostatic, and hydrodynamic interactions. Closed-form formulas are derived for charged hydrogels to describe their swelling equilibrium, elastic moduli, and the relationship between microscopic properties such as gel diffusion and macroscopic properties such as elasticity. In addition, electrostatic coupling between charged moieties and their ion clouds, which significantly modifies the elastic diffusion coefficient of gels, and various scaling laws are presented. The theoretical formulas summarized here are useful to adequately capture the essentials of the physics of charged gels and to design new hydrogels with specified elastic and dynamical properties.

This work presents the experimental characterization and theoretical modeling of composite elastic-porous metal materials (C-EPMM). C-EPMM is a novel porous metallic damping material made of wire mesh and wire helix. A series of quasi-static compressive experiments were carried out to investigate the stiffness and energy absorption ability of the C-EPMM with different mass ratios. The experimental results show that the mass ratios can significantly affect the stiffness and loss factor of C-EPMM. To efficiently predict the nonlinear mechanical properties of the C-EPMM a theoretical model of C-EPMM was proposed for the first time, the model was based on the manufacturing process. A comparison between the predicted data and the experimental data was conducted. The results show that the theoretical model can accurately predict the mechanical performance of C-EPMM. The conclusions derived from this work can provide a new method for adjusting the mechanical performance of EPMM in applications.

The accuracy of remote-sensing reflectance ( R r s ) estimated from ocean color imagery through the atmospheric correction step is essential in conducting quantitative estimates of the inherent optical properties and biogeochemical parameters of seawater. Therefore, finding the main source of error is the first step toward improving the accuracy of R r s . However, the classic validation exercises provide only the total error of the retrieved R r s . They do not reveal the error sources. Moreover, how to effectively improve this satellite algorithm remains unknown. To better understand and improve various aspects of the satellite atmospheric correction algorithm, the error budget in the validation is required. Here, to find the primary error source from the OLCI R r s , we evaluated the OLCI R r s product with in-situ data around the China Sea from open ocean to coastal waters and compared them with the MODIS-AQUA and VIIRS products. The results show that the performances of OLCI are comparable to those MODIS-AQUA. The average percentage difference (APD) in R r s is lowest at 490 nm (18%), and highest at 754 nm (79%). A more detailed analysis reveals that open ocean and coastal waters show opposite results: compared to coastal waters the satellite R r s in open seas are higher than the in-situ measured values. An error budget for the three satellite-derived R r s products is presented, showing that the primary error source in the China Sea was the aerosol estimation and the error on the Rayleigh-corrected radiance for OLCI, as well as for MODIS and VIIRS. This work suggests that to improve the accuracy of Sentinel-3A in the coastal waters of China, the accuracy of aerosol estimation in atmospheric correction must be improved.

Osteoarthritis (OA) is one of the most common diseases affecting older people; however, there remains no effective targeted drug to combat OA. The aims of this study were (1) to explore the effect of T140 in regulating degeneration of articular cartilage in vivo by targeted blocking of the SDF-1/CXCR4 signaling pathway, and (2) to provide experimental evidence for the development of a novel OA-targeted pharmacotherapy. Thirty-six healthy Hartley guinea pigs were randomly divided into three groups: a T140-treated group (n = 12), a phosphate buffer saline control group (n = 12) and an untreated control group (n = 12). At 2, 4, 6, 8, 10 and 12 weeks of treatment, SDF-1 in serum was quantified by enzyme-linked immunosorbent assay. At 12 weeks of treatment, the cartilage from knee tibial plateau in the knee joint was collected for H&E, Safranin-O staining and Mankin grading; measurement for mRNA levels of matrix metalloproteinases (MMP-3, MMP-9 and MMP-13), aggrecan (ACAN) and collagen II (Col II) using RT-PCR; and measurement for Col II protein levels by western blot. Results showed that SDF-1 in serum increased in the T140 group and increased in the control groups. H&E and Safranin-O staining revealed less cartilage loss in T140-treated animals compared to controls. The mRNA levels of MMP-3, MMP-9 and MMP-13 in cartilage were much lower in the T140 group than other groups, but mRNA levels of ACAN and Col II in cartilage were higher in the T140-treated group. Col II protein levels in the T140 group and control groups were different. T140 can downregulate the expression of matrix-degrading enzyme and lessen the degeneration of cartilage by blocking the SDF-1/CRCR4 signaling pathway in vivo. This mechanism may present a pharmacological target for the treatment of OA.

An efficient modified Fourier series-based sampling surface approach is proposed for the analytical evaluation of the vibration characteristics of thick curved beams subjected to general restraints. The theoretical models of the beams are formulated by the theory of elasticity in two dimensions, which allows arbitrary thickness configurations to be tackled. As an innovation of this work, the approach is based upon the sampling surface method combined with the use of modified Fourier series approximation. In particular, the transverse beam domain is discretized by a set of sampling surfaces with unequal spaces, and the displacement components in beam domain coinciding with these surfaces are mathematically described as a set of modified Fourier series in which certain supplementary functions are included to remove all the relevant discontinuities with the displacements and their derivatives at the boundaries to form a mathematically complete set and guarantee the results convergent to the exact solutions. The final results are numerically solved using a modified variational principle by means of Lagrange multipliers and penalty method for the sake of arbitrary boundary conditions. The influences of transverse normal and shear deformation on the vibration characteristics with respect to the geometrical dimension and boundary conditions are systematically evaluated.

Vivid main structure and rich texture detail are important factors with which to determine the quality of high-resolution images after super-resolution (SR) reconstruction. Owing to the loss of high-frequency information in the process of SR reconstruction and the limitation of the accurate estimation of the unknown information in the inversion process, a gap still exists between the high-resolution image and the real image. The main structure can better preserve the edge structure of the image, and detail boosting can compensate for the missing high-frequency information in the reconstruction process. Therefore, a novel single remote-sensing image SR reconstruction method based on multilevel main structure and detail boosting (MMSDB-SR) is put forward in this paper. First, the multilevel main structure was obtained based on the decomposition of the remote-sensing image through use of the relative total variation model. Subsequently, multilevel texture detail information was obtained by a difference process. Second, the multilevel main structure and texture detail were reconstructed separately. The detail-boosting function was used to compensate for the missing high-frequency details in the reconstruction process. Finally, the high-resolution remote-sensing image with clear edge and rich texture detail can be obtained by fusing the multilevel main structure and texture-detail information. The experimental results show that the reconstructed high-resolution image has high clarity, high fidelity, and multi-detail visual effects, and the objective evaluation index exhibits significant improvement. Actual results show an average gain in entropy of up to 0.34 dB for an up-scaling of 2. Real results show an average gain in enhancement measure evaluation of up to 2.42 for an up-scaling of 2. The robustness and universality of the proposed SR method are verified.

The close replication of synaptic function is critically important for achieving cognitive computing based on neuromorphic devices. Among the advanced neural learning rules, Bienenstock–Cooper–Munro (BCM) learning rules have been attracting great attention in neuromorphic electronics. Owing to their rich ion dynamic processes, ionic/electronic hybrid devices show great potential in hardware-based neuromorphic systems. Herein, a sodium alginate/graphene oxide hybrid-based electrolyte-gated indium tin oxide (ITO) hetero-dendritic neuron with multi-gate configuration was fabricated. Owing to its unique interfacial protonic hybrid effect, this device exhibited basic synaptic functions. With its proton-related temporal facilitation, this device demonstrated high-pass filter activities, showing potential in image sharpening. It also exhibited an ultra-low power consumption of ∼93.4 aJ for a single synaptic response. Paired-pulse facilitation behavior was mimicked on such a low power consumption. Subsequently, symmetrical Hebbian spike-timing-dependent plasticity and BCM learning rules with regulatory frequency threshold were simulated. Interestingly, a heterosynaptic model was constructed by integrating coplanar gates. Due to the protonic lateral coupling effects, the BCM learning rules could be modulated via the heterosynaptic mechanism. These results indicate the great potential of the present oxide hetero-dendritic neuron in neuromorphic electronics and brain-inspired cognitive platforms. [ABSTRACT FROM AUTHOR]

Electrolyte-gating poses a unique strategy to modulate physical characteristics and electronic transport properties of condensed materials. Here, solution-processed chitosan-based electrolyte-gated oxide ionotronic neuromorphic transistors are fabricated. Benefitting from unique protonic interfacial coupling processes, the ionotronic transistors can mimic different kinds of spike-timing-dependent plasticity (STDP), including the classical pair-STDP rule, triplet-STDP, and quadruplet-STDP. The triplet-STDP activities could be well explained with Froemke's triplet-STDP model, which proved to be effective in the biological nerve system. The oxide ionotronic neuromorphic transistors could act as fundamental building blocks in neuromorphic platforms. [ABSTRACT FROM AUTHOR]

To explore independent influencing factors for clinical efficacy of roxadustat in hemodialysis patients. Hemodialysis patients treated with roxadustat were enrolled. The plasma trough concentrations of roxadustat were measured using liquid chromatography–tandem mass spectrometry (LC–MS/MS). A multiple logistic regression model was established to determine the factors that affect clinical efficacy of roxadustat in patients undergoing hemodialysis. A total of 67 hemodialysis patients were enrolled in the study. The results showed that age, blood trough concentration of roxadustat, and baseline hemoglobin (Hb) level were independent factors of clinical efficacy of roxadustat (OR = 1.06, p =.025 for age; OR = 1.001, p =.037 for plasma concentration; and OR = 0.941, p =.003 for baseline Hb), with an AUC score of 0.859. Age, blood trough concentration of roxadustat, and baseline Hb level were independent influencing factors of the response to roxadustat in hemodialysis patients. [ABSTRACT FROM AUTHOR]

Nanoporous adsorbents are a diverse category of solid-state materials that hold considerable promise for vehicular hydrogen storage. Although impressive storage capacities have been demonstrated for several materials, particularly at cryogenic temperatures, materials meeting all of the targets established by the U.S. Department of Energy have yet to be identified. In this Perspective, we provide an overview of the major known and proposed strategies for hydrogen adsorbents, with the aim of guiding ongoing research as well as future new storage concepts. The discussion of each strategy includes current relevant literature, strengths and weaknesses, and outstanding challenges that preclude implementation. We consider in particular metal-organic frameworks (MOFs), including surface area/volume tailoring, open metal sites, and the binding of multiple H2 molecules to a single metal site. Two related classes of porous framework materials, covalent organic frameworks (COFs) and porous aromatic frameworks (PAFs), are also discussed, as are graphene and graphene oxide and doped porous carbons. We additionally introduce criteria for evaluating the merits of a particular materials design strategy. Computation has become an important tool in the discovery of new storage materials, and a brief introduction to the benefits and limitations of computational predictions of H2 physisorption is therefore presented. Finally, considerations for the synthesis and characterization of hydrogen storage adsorbents are discussed.