Search

By introducing bilinear operators of trigonometric type, we propose several novel integrable variants of the famous Toda lattice, two of which can be regarded as integrable discretizations of the Kadomtsev–Petviashvili equation—a universal model describing weakly nonlinear waves in media with dispersion of velocity. We also demonstrate that two one-dimensional reductions of these variants can approximate the nonlinear Schrödinger equation and a generalized nonlinear Schrödinger equation well. It turns out that these equations admit meaningful solutions including solitons, breathers, lumps and rogue waves, which are expressed in terms of explicit and closed forms. In particular, it seems to be the first time that rogue wave solutions have been obtained for Toda-type equations. Furthermore, g-periodic wave solutions are also produced in terms of Riemann theta function. An approximation solution of the three-periodic wave is successfully carried out by using a deep neural network. The introduction of trigonometric-type bilinear operators is also efficient in generating new variants together with rich properties for some other integrable equations. [ABSTRACT FROM AUTHOR]

The ocean world is full of Unknown Marine Objects (UMOs), making it difficult to deal with unknown ocean targets using the traditional instance segmentation model. This is because the traditional instance segmentation networks are trained on a closed dataset, assuming that all detected objects are Known Marine Objects (KMOs). Consequently, traditional closed-set networks often misclassify UMOs as KMOs. To address this problem, this paper proposes a new open-set instance segmentation model for object instance segmentation in marine environments with UMOs. Specifically, we integrate two learning modules in the model, namely a prototype module and an unknown learning module. Through the learnable prototype, the prototype module improves the class's compactness and boundary detection capabilities while also increasing the classification accuracy. Through the uncertainty of low probability samples, the unknown learning module forecasts the unknown probability. Experimental results illustrate that the proposed method has competitive known class recognition accuracy compared to existing instance segmentation models, and can accurately distinguish unknown targets. [ABSTRACT FROM AUTHOR]

Detecting roads in automatic driving environments poses a challenge due to issues such as boundary fuzziness, occlusion, and glare from light. We believe that two factors are instrumental in addressing these challenges and enhancing detection performance: global context dependency and effective feature representation that prioritizes important feature channels. To tackle these issues, we introduce DTRoadseg, a novel duplex Transformer-based heterogeneous feature fusion network designed for road segmentation. DTRoadseg leverages a duplex encoder architecture to extract heterogeneous features from both RGB images and point-cloud depth images. Subsequently, we introduce a multi-source Heterogeneous Feature Reinforcement Block (HFRB) for fusion of the encoded features, comprising a Heterogeneous Feature Fusion Module (HFFM) and a Reinforcement Fusion Module (RFM). The HFFM leverages the self-attention mechanisms of Transformers to achieve effective fusion through token interactions, while the RFM focuses on emphasizing informative features while downplaying less important ones, thereby reinforcing feature fusion. Finally, a Transformer decoder is utilized to produce the final semantic prediction. Furthermore, we employ a boundary loss function to optimize the segmentation structure area, reduce false detection areas, and improve model accuracy. Extensive experiments are carried out on the KITTI road dataset. The results demonstrate that, compared with state-of-the-art methods, DTRoadseg exhibits superior performance, achieving an average accuracy of 97.01%, a Recall of 96.35%, and runs at a speed of 0.09 s per picture. [ABSTRACT FROM AUTHOR]

Lentiviral vectors have markedly enhanced gene therapy efficiency in treating congenital diseases, but their long-term safety remains controversial. Most gene therapies for congenital eye diseases need to be carried out at early ages, yet the assessment of related risks to ocular development posed by lentiviral vectors is challenging. Utilizing single-cell transcriptomic profiling on human retinal organoids, this study explored the impact of lentiviral vectors on the retinal development and found that lentiviral vectors can cause retinal precursor cells to shift toward photoreceptor fate through the up-regulation of key fate-determining genes such as PRDM1. Further investigation demonstrated that the intron and intergenic region of PRDM1 was bound by PHLDA1, which was also up-regulated by lentiviral vectors exposure. Importantly, knockdown of PHLDA1 successfully suppressed the lentivirus-induced differentiation bias of photoreceptor cells. The findings also suggest that while lentiviral vectors may disrupt the fate determination of retinal precursor cells, posing risks in early-stage retinal gene therapy, these risks could potentially be reduced by inhibiting the PHLDA1-PRDM1 axis. [ABSTRACT FROM AUTHOR]

Microsized bismuth (Bi) with in-situ constructed three-dimensional (3D) porous network has been considered as a promising anode for high-performance potassium-ion batteries (PIBs). However, the mechanism of the in-situ porous evolution of microsized Bi during the charge/discharge process is still mysterious. Herein, various electrolytes are employed to disclose the origin of porous evolution of microsized Bi in PIBs. Experimentally and theoretically, the 3D porous network originates from the uniform interfacial charge distribution on the Bi surface in the linear ether-based electrolyte. In addition, the universality of the interfacial charge distribution mechanism was verified by microsized Sn and Sb. The in-situ constructed 3D porous network of Bi enables a superior potassium storage performance in a wide temperature range from −40 to 40 °C. More importantly, the K0.9Mn0.7Ni0.3O2∥Bi full cell delivers excellent cycling stability (a high capacity retention of 88.44% even after 2,000 cycles) and good temperature tolerance. This work gives a distinct clarification of the origin of the porous evolution of microsized Bi during cycling, which is critical for developing high-performance PIBs. [ABSTRACT FROM AUTHOR]

The implementation of registers from (potentially) weaker registers is a classical problem in the theory of distributed computing. Since Lamport's pioneering work (Lamport in Distrib Comput 1(2):77–101, 1986), this problem has been extensively studied in the context of asynchronous processes with crash failures. In this paper, we investigate this problem in the context of Byzantine process failures, with and without process signatures. We first prove that, without signatures, there is no wait-free linearizable implementation of a 1-writer n-reader register from atomic 1-writer 1-reader registers. In fact, we show a stronger result, namely, even under the assumption that the writer can only crash and at most one reader can be malicious, there is no linearizable implementation of a 1-writer n-reader register from atomic 1-writer (n - 1) -reader registers that ensures that every correct process eventually completes its operations. In light of this impossibility result, we give two implementations of a 1-writer n-reader register from atomic 1-writer 1-reader registers that work under different assumptions. The first implementation is linearizable (under any combination of Byzantine process failures), but it guarantees that every correct process eventually completes its operations only under the assumption that the writer is correct or no reader is Byzantine—thus matching the impossibility result. The second implementation assumes process signatures; it is wait-free and linearizable under any number and combination of Byzantine process failures. [ABSTRACT FROM AUTHOR]

Dipterocarpoideae species form the emergent layer of Asian rainforests. They are the indicator species for Asian rainforest distribution, but they are severely threatened. Here, to understand their adaptation and population decline, we assemble high-quality genomes of seven Dipterocarpoideae species including two autotetraploid species. We estimate the divergence time between Dipterocarpoideae and Malvaceae and within Dipterocarpoideae to be 108.2 (97.8‒118.2) and 88.4 (77.7‒102.9) million years ago, and we identify a whole genome duplication event preceding dipterocarp lineage diversification. We find several genes that showed a signature of selection, likely associated with the adaptation to Asian rainforests. By resequencing of two endangered species, we detect an expansion of effective population size after the last glacial period and a recent sharp decline coinciding with the history of local human activities. Our findings contribute to understanding the diversification and adaptation of dipterocarps and highlight anthropogenic disturbances as a major factor in their endangered status. Dipterocarp trees are iconic but severely threatened species in Asian rainforests. This study assembles high-quality genomes of seven dipterocarp species to reveal the molecular basis of key adaptations and identifies a recent sharp population decline coinciding with local human activity. [ABSTRACT FROM AUTHOR]

Objective: To analyze the diagnostic efficacy of the periportal hypoechoic band (PHB) in the histological stage of patients with primary biliary cholangitis (PBC). Methods: We prospectively included 77 cases of PBC pathologically or clinically confirmed, and high-frequency ultrasound (HFUS) measurements of the PHB were performed in all included patients. Ludwig staging system of histopathology was used as the gold standard. Results: The width of the PHB was positively correlated with histological staging (r = 0.844, p < 0.001). By area under the receiving operating characteristic curve (AUROC), the best cutoff value for PHB for advanced stage (≥ stage 3) was 2.4 mm (AUROC: 0.934; 95%CI: 0.841–0.981) and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The correct rate for early-stage PBC was 87.9% and for the progressive stage was 93.1%. After multi-factor regression analysis, the PHB (OR = 1.331, CI = 1.105–1.603, p = 0.003) and total bilirubin (OR = 1.156, CI = 1.041–1.285, p = 0.007) were independent influencing factors for progressive PBC. Conclusions: Measurement of the PHB to assess advanced PBC is a simple and effective method. This method may complement current methods for the histological staging assessment of patients with PBC. Registration: Clinical trial registration: ChiCTR 2000032053, 2020/04/19. Clinical relevance statement: The measurement of periportal hypoechoic band (PHB) provides a simple and easy assessment of the degree of disease progression in patients with PBC and provides an important clinical reference in predicting the histological staging of PBC from an ultrasound perspective. Key Points: • The PHB is correlated with histological staging in the patient with PBC. • The area under the ROC curves of PHB for detecting advanced stage (≥ stage 3) were 0.934 and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The application of PHB can better assess the advanced PBC. • Measurement of the PHB to assess advanced PBC is a simple and effective method that can significantly reduce the need for liver biopsy. [ABSTRACT FROM AUTHOR]

Differential evolution (DE) is one of the most efficient evolution algorithms (ES) for dealing with nonlinear, complicated and difficult global optimization problems. The main contribution of this paper can be summarized in three directions: Firstly, a novel crossover rate (CR) generation scheme based on the zscore value of fitness, named fcr, is introduced. For a minimization problem, the proposed CR generation strategy always assigns a smaller CR value to individual with smaller fitness value. Therefore, the parameters of individuals with better fitness are inherited by their offspring with high probability. In the second direction, the control parameters are adjusted by unused bimodal settings in which each parameter setting is selected according to the evolution status of individual. The third direction of our work is introducing the L1 norm distance as the weights for updating the mean value of crossover rate and scale factor. Theoretically, compared with L2 norm, L1-norm is more efficient to suppress outliers in the difference vector. These modifications are first integrated with the mutation strategy of JADE, then a modified version, named JADEfcr, is proposed. In addition, to improve the optimization ability further, another variant LJADEfcr by using a linear population reduction mechanism is considered. So as to confirm and examine the performance of JADEfcr and LJADEfcr, numerical experiments are conducted on 29 optimization problems defined by CEC2017 benchmark. For JADEfcr, its experimental results are made a comparison with twelve state-of-the-art algorithms. The comparative study demonstrates that in terms of robustness, stability and solution quality, JADEfcr are better and highly competitive with these well-known algorithms. For LJADEfcr, its results are compared with JADEfcr and other nine powerful algorithms including four recent algorithms and five top algorithms on CEC2017 competition. Experimental results indicate that LJADEfcr is superior and statistically competitive with these excellent algorithms in terms of robustness, stability and the quality of the obtained solutions. [ABSTRACT FROM AUTHOR]

Formaldehyde (FA), as the simplest endogenous carbonyl molecule, participates in many biosynthesis and metabolism in living organisms, such as nucleotides and adenosine triphosphate (ATP). FA concentrations are sub-millimolar in the normal healthy body, but can rise significantly in a number of disease pathologies. As a result, detecting endogenous FA is critical for illness diagnosis and rehabilitation therapy monitoring. Recent studies have focused on the FA-responsive turn-on fluorescence probe, which has huge promise in the detection and visualization of FA in living cells and organisms, as well as exceptional use in disease diagnosis and therapeutic monitoring. This review summarizes the fluorescence luminescence mechanism and design concepts of FA fluorescent probes, as well as their recent applications in bioimaging and illness diagnostics. Additionally, this article indicates the present dilemma of FA-responsive fluorescent probe, including selectivity, specificity, and detection mode, which may provide references for the development of FA-responsive fluorescent probes. [ABSTRACT FROM AUTHOR]

Dynamic neural network (NN) techniques are increasingly important because they facilitate deep learning techniques with more complex network architectures. However, existing studies, which predominantly optimize the static computational graphs by static scheduling methods, usually focus on optimizing static neural networks in deep neural network (DNN) accelerators. We analyze the execution process of dynamic neural networks and observe that dynamic features introduce challenges for efficient scheduling and pipelining in existing DNN accelerators. We propose DyPipe, a holistic approach to optimizing dynamic neural network inferences in enhanced DNN accelerators. DyPipe achieves significant performance improvements for dynamic neural networks while it introduces negligible overhead for static neural networks. Our evaluation demonstrates that DyPipe achieves 1.7x speedup on dynamic neural networks and maintains more than 96% performance for static neural networks. [ABSTRACT FROM AUTHOR]

Sidon spaces initially were introduced by Bachoc, Serra, and Zémor as a tool to characterize multiplicative properties of subspaces and systematically were designed by Roth, Raviv, and Tamo utilizing some roots of irreducible polynomials over the finite fields. Roth, Raviv, and Tamo have also shown the relation between Sidon spaces and cyclic constant dimension codes and constructed several such codes with one or more orbits. In this paper, we survey the constructions of Sidon spaces with new parameters. Furthermore, we present a family of large cyclic subspace codes in which the code size exceeds the previous works. [ABSTRACT FROM AUTHOR]

Vision-based sign language translation technology (SLT) has brought the communication distance between deaf and ordinary people closer to a certain extent. The obstacle of SLT is mainly in two aspects: firstly, when capturing sign language action features, it is impossible to effectively overcome the shortcomings such as redundant information of sign language gesture features and motion ambiguity; secondly, it is difficult to define the alignment between action sequences and lexical sequences when processing sentence-level sign language videos. To overcome these problems, this paper proposes a sign language translation method based on residual spatial graph convolution network (Res-SGCN) and temporal attention model. Where, the Res-SGCN module is used to capture the spatial interaction feature information between the sign language skeleton nodes, and subsequently the temporal attention network is used to capture the temporal dimensional information fusion of the sign language spatial feature sequence and align it with the predicted vocabulary for translation. Experiments on public datasets show that the word error rate(WER) output by the proposed model reaches 4.17%, which is superior to other advanced sign language translation methods. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa (PA) is a leading cause of hospital-acquired and ventilator-associated pneumonia. The multidrug-resistance (MDR) rate of PA is increasing making the management of PA a global challenge. Messenger RNA (mRNA) vaccines represent the most promising alternative to conventional vaccines and are widely studied for viral infection and cancer immunotherapy while rarely studied for bacterial infections. In this study, two mRNA vaccines encoding PcrV– the key component of the type III secretion system in Pseudomonas and the fusion protein OprF-I comprising outer membrane proteins OprF and OprI were constructed. The mice were immunized with either one of these mRNA vaccines or with the combination of both. Additionally, mice were vaccinated with PcrV, OprF, or the combination of these two proteins. Immunization with either mRNA-PcrV or mRNA-OprF-I elicited a Th1/Th2 mixed or slighted Th1-biased immune response, conferred broad protection, and reduced bacterial burden and inflammation in burn and systemic infection models. mRNA-PcrV induced significantly stronger antigen-specific humoral and cellular immune responses and higher survival rate compared with the OprF-I after challenging with all the PA strains tested. The combined mRNA vaccine demonstrated the best survival rate. Moreover, the mRNA vaccines showed the superiority over protein vaccines. These results suggest that mRNA-PcrV as well as the mixture of mRNA-PcrV and mRNA-OprF-I are promising vaccine candidates for the prevention of PA infection. [ABSTRACT FROM AUTHOR]

During the actual operation of subways, high-speed railway, and other infrastructure, subgrade soil will be subjected to periodic vibration and intermittent loading, i.e., intermittent cyclic load. To study the deformation characteristics of subgrade soil under intermittent cyclic loading, the Newtonian dashpot in the generalized Kelvin model is replaced by the fractional Abel dashpot, a fractional generalized Kelvin model is established. Then, a nonlinear viscoplastic body model considering damage is proposed, which is connected in series with the improved fractional generalized Kelvin model, and the deformation constitutive model of soil under intermittent cyclic loading is obtained. Finally, the effectiveness and applicability of the model are analyzed, and the model is compared with other constitutive models. The results show that the constitutive model established in the paper can reflect the combined effect of confining pressure, frequency, dynamic stress amplitude and other factors on the cumulative plastic strain of soil, and can well characterize the development law of three types of cumulative plastic strain curves of soil: stable, critical, and failure. The fitting parameters α and η tend to decay and rise, respectively, with the increase in loading stage N, which reflects the rationality and accuracy of the model. [ABSTRACT FROM AUTHOR]

In this paper, we propose a generalized discrete Lotka-Volterra equation and explore its connections with symmetric orthogonal polynomials, Hankel determinants and convergence acceleration algorithms. Firstly, we extend the fully discrete Lotka-Volterra equation to a generalized one with a sequence of given constants { u 0 (n) } and derive its solution in terms of Hankel determinants. Then, it is shown that the discrete equation of motion is transformed into a discrete Riccati system for a discrete Stieltjes function, hence leading to a complete linearization. Besides, we obtain its Lax pair in terms of symmetric orthogonal polynomials by generalizing the Christoffel transformation for the symmetric orthogonal polynomials. Moreover, a generalization of the famous Wynn's ε-algorithm is also derived via a Miura transformation to the generalized discrete Lotka-Volterra equation. Finally, the numerical effects of this generalized ε-algorithm are discussed by applying to some linearly, logarithmically convergent sequences and some divergent series. [ABSTRACT FROM AUTHOR]

Background: Acute liver injury is liver cell injury that occurs rapidly in a short period of time. Caffeine has been shown to maintain hepatoprotective effect with an unclear mechanism. Endoplasmic reticulum stress (ERS) has significant effects in acute liver injury. Induction of GRP78 is a hallmark of ERS. Whether or not caffeine's function is related to GRP78 remains to be explored. Methods: Acute liver injury model was established by LPS-treated L02 cells and in vivo administration of LPS/D-Gal in mice. Caffeine was pre-treated in L02 cells or mice. Gene levels was determined by real-time PCR and western blot. Cell viability was tested by CCK-8 assay and cell apoptosis was tested by flow cytometry. The interaction of GRP78 and NEDD4L was determined by Pull-down and co-immunoprecipitation (Co-IP) assay. The ubiquitination by NEDD4L on GRP78 was validated by in vitro ubiquitination assay. Results: Caffeine protected liver cells against acute injury induced cell apoptosis and ERS both in vitro and in vivo. Suppression of GRP78 could block the LPS-induced cell apoptosis and ERS. NEDD4L was found to interact with GRP78 and ubiquitinate its lysine of 324 site directly. Caffeine treatment induced the expression of NEDD4L, resulting in the ubiquitination and inhibition of GRP78. Conclusion: Caffeine mitigated the acute liver injury by stimulating NEDD4L expression, which inhibited GRP78 expression via ubiquitination at its K324 site. Low dose of caffeine could be a promising therapeutic treatment for acute liver injury. [ABSTRACT FROM AUTHOR]

Video anomaly detection plays a critical role in public safety and security. However, it is hard to perform supervised due to its characteristics such as definition ambiguity, scene dependency, and sample scarcity. This paper proposes an unsupervised video anomaly detection model, called Spatio-Temporal 3D Convolutional Auto-Encoder model (ST-3DCAE) based on the input of the fused features of both motion and appearance. First, to utilize both motion and appearance information in the scene, the optical flow feature map of the scene is extracted with PWCNet and fused with the original video frame as the model input. Then, the 3DConv module and the Convolution Long Short-Term Memory(ConvLSTM) module are then used for extracting the spatio-temporal features, and the 3DSEblock module is used to screen important features. Finally, the reconstruction error between the input and output of the auto-encoder is used to determine whether the video frames are related to abnormal behavior. The proposed model has been validated on publicly available datasets such as UCSD Pedestrian and Avenue datasets. Experimental results analysis, both qualitative and quantitative, demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this work, a Carrier Waveform Inter-Displacement (CWID) modulation, based on Linear Frequency Modulation-Phase Shift Keying (LFM-PSK), is proposed to achieve high Bit Transmission Rate (BTR) in wireless radio communications system. The novel modulation scheme introduces position modulation by re-ordering inter-displacement in different symbol carriers, which improves the BTR as compared with the LFM-PSK system. Moreover, a Graphical User Interface (GUI) based on Wireless open-Access Research Platform (WARP) is designed and the CWID system is implemented and validated on the Software Defined Electronics platform. Results of simulations and experiments show the effectiveness and the superiority of the CWID over its competitors. [ABSTRACT FROM AUTHOR]

The microstructural, textural, and hardness evolution of a cold-rolled high-purity Ti sheet (50 pct reduction in thickness) during isochronal annealing at 350 °C to 550 °C was investigated by jointly using electron backscatter diffraction, electron channel contrast imaging, X-ray diffraction, and hardness test, with a dedicated correlation analysis between them performed. Results show that recrystallization nucleation starts at 400 °C with prior grain boundaries as preferential sites while fully recrystallized structures were obtained after annealing at 550 °C for 1 hours. During the primary recrystallization, contrary to earlier reports, considerable textural changes occur: the prior bimodal basal texture characteristic is essentially replaced by a ring-like basal texture. Such a textural change is attributed to the orientation-gradient-related subgrain coalescence mechanism that dominates the recrystallization nucleation of the high-purity Ti sheet. Specimen hardness always decreases with increasing the annealing temperature (from 234.3 ± 5.8 to 135.9 ± 2.9 HV), which is closely related to continuous variations of grain sizes and dislocation densities (mainly stored in low-angle boundaries). Quantitative analyses reveal that both grain sizes and dislocation densities have mild effects on the hardness change when annealed below 450 °C. However, the decrease in dislocation density leads to more significant softening than grain coarsening when the annealing temperature exceeds 450 °C. [ABSTRACT FROM AUTHOR]

In this paper, we give the different topological types of phase portrait for Liénard system x ̇ = y , y ̇ = − g (x) in the case that deg g (x) = 7 and the system have six and seven singular points, respectively. For its perturbed system, the expansion of the Melnikov function near any of the above closed orbits, except that the closed orbit is a compound loop passing through a nilpotent cusp and two hyperbolic saddles or passing through three hyperbolic saddles, has been studied. In this paper, as one of main results, for a near-Hamiltonian system, we give the expansion of the Melnikov function near a compound loop with a nilpotent cusp and two hyperbolic saddles. Based on this, we present the conditions to obtain limit cycles. [ABSTRACT FROM AUTHOR]

Cirrhotic cardiomyopathy (CCM) is a recognized complication of cirrhosis and is associated with poor outcomes, especially under challenges such as surgery/liver transplantation. However, the mechanism is not clear, and the treatment is not specific. The present study aimed to evaluate the role of anti-β1-adrenergic receptor antibodies (anti-β1-AR) in CCM. We enrolled 3 groups: healthy controls, cirrhotic patients without CCM, and patients with CCM. We found that the anti-β1-AR levels in the CCM group were significantly higher than that in the non-CCM group; anti-β1-AR was positively correlated to NT-proBNP, negatively correlated to left ventricular ejection fraction, fractional shortening ((r = − 0.466, P < 0.05), and the ratio of peak early (E wave) and atrial (A wave) flow velocities (E/A (r = − 0.475, P < 0.05) in CCM patients. Anti-β1-AR is a useful predictive biomarker for the presence of CCM and eventually may also have therapeutic implications. Clinical Trials Registration: Chinese Clinical Trials No. ChiCTR 2,000,037,730 [ABSTRACT FROM AUTHOR]

Motivated by recent distributed systems technology, Aguilera et al. introduced a hybrid model of distributed computing, called the message-and-memory model or m&m model for short. In this model, processes can communicate by message passing and also by accessing some shared memory (e.g., through some RDMA connections). We first consider the basic problem of implementing an atomic single-writer multi-reader (SWMR) register shared by all the processes in m&m systems. Specifically, we give an algorithm that implements such a register in m&m systems and show that it is optimal in the number of process crashes that it tolerates. This generalizes the well-known ABD implementation of an atomic SWMR register in a pure message-passing system. We then combine our register implementation for m&m systems with a randomized consensus algorithm of Aspnes and Herlihy, and obtain a randomized consensus algorithm for m&m systems that is also optimal in the number of process crashes that it can tolerate. Finally, we determine the minimum number of RDMA connections that is sufficient to implement a SWMR register, or solve randomized consensus, in an m&m system with t process crashes, for any given t. [ABSTRACT FROM AUTHOR]

Firstly, a new sequence transformation that can be expressed in terms of a ratio of two pfaffians is derived based on a special kernel. It can be regarded as a direct generalization of Aitken's Δ2 process from the point of view of pfaffians and then the corresponding convergence acceleration algorithm is constructed. Numerical examples with applications of this algorithm are also presented. Secondly, we find a way to generalize the Shanks transformation via pfaffians so that a larger class of new sequence transformations are derived. The corresponding recursive algorithms are also proposed. [ABSTRACT FROM AUTHOR]

The fabrication of alkaline phosphatase (ALP)-responsive coordination polymer (CP) composite is demonstrated for establishing a fluorescent immunoassay. The CP composite (ThT@GMP/Eu) was synthesized by encapsulating thioflavin T (ThT) into the CP host that was composed of europium ion (Eu3+) and guanine monophosphate (GMP). The ThT@GMP/Eu composite shows a strong fluorescence in aqueous solution due to the confinement effect of GMP/Eu CPs, which restricts the conformational rotation of ThT. However, upon the addition of ALP, the structure of GMP/Eu CPs was disrupted to release ThT into solution. This results in the quenching of the fluorescence of ThT@GMP/Eu. The fluorescence of ThT@GMP/Eu has a linear response that covers 0.8 to 120 mU/mL ALP with a detection limit of 0.26 mU/mL and exhibits excellent specificity towards ALP against other enzymes. On this basis, inspired by the wide application of ALP as an enzyme label in enzyme-linked immunosorbent assay (ELISA), an ALP-based fluorescent immunoassay was further developed for the detection of mouse immunoglobulin G (mIgG). The developed immunoassay displays a linear fluorescent response towards mIgG from 0.8 to 100 ng/mL, and the detection limit is 0.16 ng/mL. The fluorescent immunoassay was successfully applied to the determination of mIgG in serum samples. [ABSTRACT FROM AUTHOR]

The original version of this article, published on 24 September 2020, unfortunately contained a mistake. [ABSTRACT FROM AUTHOR]

In order to improve the accuracy of human abnormal behavior recognition, a two-stream convolution neural network model was proposed. This model includes two main parts, VMHI and FRGB. Firstly, the motion history images are extracted and input into VGG-16 convolutional neural network for training. Then, the RGB image is input into Faster R-CNN algorithm for training using Kalman filter-assisted data annotation. Finally, the two stream VMHI and FRGB results are fused. The algorithm can recognize not only single person behavior, but also two person interaction behavior and improve the recognition accuracy of similar actions. Experimental results on KTH, Weizmann, UT-interaction, and TenthLab dataset showed that the proposed algorithm has higher accuracy than the other literature. [ABSTRACT FROM AUTHOR]

Objectives: To systematically review studies on the diagnostic accuracy of spleen stiffness measurement (SSM) for the detection of clinical significant portal hypertension (CSPH), severe portal hypertension (SPH), esophageal varices (EV), and high-risk esophageal varices (HREV) in patients with chronic liver diseases (CLD). Methods: Through a systematic search, we identified 32 studies reporting the accuracy of SSM for the diagnosis of portal hypertension (PH) and/or EV in adults with CLD. A bivariate random-effects model was performed to estimate pooled sensitivity, specificity, likelihood ratio, positive predictive value (PPV), negative predictive value (NPV), and diagnostic odds ratios (DOR). The clinical utility of SSM was evaluated by Fagan plot. Results: A total of 32 studies assessing 3952 patients were included in this meta-analysis. The pooled sensitivities of SSM were 0.85 (95% confidence interval (CI), 0.69–0.93) for CSPH; 0.84 (95% CI, 0.75–0.90) for SPH; 0.90 (95% CI, 0.83–0.94) for any EV; and 0.87 (95% CI, 0.77–0.93) for HREV. The pooled specificities of SSM were 0.86 (95% CI, 0.74–0.93) for CSPH; 0.84 (95% CI, 0.72–0.91) for SPH; 0.73 (95% CI, 0.66–0.79) for EV; and 0.66 (95% CI, 0.53–0.77) for HREV. Summary PPV and NPV of SSM for detecting HREV were 0.54 (95% CI, 0.47–0.62) and 0.88 (95% CI, 0.81–0.95), respectively. Conclusions: Our meta-analysis suggests that SSM could be used as a helpful surveillance tool in management of CLD patients and was quite useful for ruling out the presence of HREV thereby avoiding unnecessary endoscopy. Key Points: • SSM could be used to rule out the presence of HREV in patients with CLD thereby avoiding unnecessary endoscopy. • SSM has significant diagnostic value for CSPH and SPH with high sensitivity and specificity in patients with CLD. • SSM could be used as a helpful surveillance tool for clinicians managing CLD patients. [ABSTRACT FROM AUTHOR]

The cavity buffeting noise is related to the free shear layer oscillation and the periodic vortex shedding, where weak vortices coexist with strong vortices and the strong shear phenomenon also exists at the opening of the cavity. Therefore, it is of great significance to accurately capture vortices at the opening for the control of the cavity buffeting noise. This paper first compares the Omega vortex identification method with the Q and λ2 criteria based on the large eddy simulation (LES) of the backward-facing step flow, and it is found that the Omega method enjoys the following advantages: it is not sensitive to a moderate threshold change and Ω = 0.52 can be used as a fixed threshold, it can capture both the strong and weak vortices at the same time; and it will not be contaminated by the shear. Then the Omega (Ω) method is applied to the LES of the cavity buffeting noise: the mechanism of the cavity buffeting noise is studied based on a simple cavity model firstly, and then the effects of the incoming boundary layer thicknesses and the incoming boundary layer shapes on the cavity buffeting noise are analyzed. The results show that: the Ω method clearly captures the processes of the vortex generation, development, collision and fragmentation, verifying that the generation of the cavity buffeting noise is related to the free shear layer oscillation and the periodic vortex shedding; as the thickness of the incoming boundary layer increases, the free shear layer becomes more stable and the Helmholtz resonance is avoided effectively, thereby the cavity buffeting noise is reduced effectively, adding a convexity upstream of the cavity opening to interfere the shape of the incoming boundary layer to reduce the acoustic feedback effect can reduce the cavity buffeting noise effectively. [ABSTRACT FROM AUTHOR]

A photothermal immunoassay using a thermometer as readout based on polyaniline@Au organic-inorganic nanohybrids was built. Temperature output is acquired due to the photothermal effect of the photothermal nanomaterial. Polyaniline@Au organic-inorganic nanohybrids were synthesized by interfacial reactions with high photothermal conversion efficiency. A sandwich structure of the immunocomplex was prepared on a microplate for determination of carcinoembryonic antigen (CEA) by polyaniline@Au organic-inorganic nanohybrids as nanolabel. The released heat based on light-to-heat conversion from the photothermal nanolabel under NIR irradiation is detectable using the thermometer. The increased temperature is directly proportional to CEA concentration. The linear range of the photothermal immunoassay is 0.20 to 25 ng mL−1 with determination limit of 0.17 ng mL−1. [ABSTRACT FROM AUTHOR]

The water contamination on the side windows of moving vehicles is a crucial issue in improving the driving safety and the comfort. In this paper, an effective optimization method is proposed to reduce the water contamination on the side windows of automobiles. The accuracy and the efficiency of the numerical simulation are improved by using the lattice Boltzmann method, and the Lagrangian particle tracking method. Optimized parameters are constructed on the basis of the occurrence of the water deposition on a vehicle's side window. The water contamination area of the side window and the aerodynamic drag are considered simultaneously in the design process; these two factors are used to form the multi- objective optimization function in the genetic algorithm (GA) method. The approximate model, the boundary-seeded domain method, and the GA method are combined in this study to enhance the optimization efficiency. After optimization, the optimal parameters for the A-pillar section are determined by setting the boundary to an area of W = 7.77 mm, L = 1.27 mm and H = 11.22 mm. The side window's soiling area in the optimized model is reduced by 66.93%, and the aerodynamic drag is increased by 0.41% only, as compared with the original model. It is shown that the optimization method can effectively solve the water contamination problem of side windows. [ABSTRACT FROM AUTHOR]

Circulating current exists among phases or between the DC link and the three phases in a modular multilevel converter (MMC). Suppression control of the alternating components in circulating current is a critical issue for the stable and efficient operation of an MMC. Due to the redundancy and symmetry of MMCs, some of the self-redundant states of MMCs can be used to suppress the alternating components in circulating current without affecting the output performance of the converter. In this paper, a theoretical derivation of the boundary of redundant states is given. Then a suppression strategy for circulating current is proposed based on prediction control and the boundary of redundant states. The selection range of the redundant states is narrowed in this case, which reduces the computation burden when compared to the original method and ensures excellent performance in the suppression of circulating current. Simulations and experiments are carried out to verify the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

The isospectral deformations of the Frobenius–Stickelberger–Thiele (FST) polynomials introduced in Spiridonov et al. (Commun Math Phys 272:139–165, 2007) are studied. For a specific choice of the deformation of the spectral measure, one is led to an integrable lattice (FST lattice), which is indeed an isospectral flow connected with a generalized eigenvalue problem. In the second part of the paper the spectral problem used previously in the study of the modified Camassa–Holm (mCH) peakon lattice is interpreted in terms of the FST polynomials together with the associated FST polynomials, resulting in a map from the mCH peakon lattice to a negative flow of the finite FST lattice. Furthermore, it is pointed out that the degenerate case of the finite FST lattice unexpectedly maps to the interlacing peakon ODE system associated with the two-component mCH equation studied in Chang et al. (Adv Math 299:1–35, 2016). [ABSTRACT FROM AUTHOR]

During software maintenance, developers spend a lot of time understanding the source code. Existing studies show that code comments help developers comprehend programs and reduce additional time spent on reading and navigating source code. Unfortunately, these comments are often mismatched, missing or outdated in software projects. Developers have to infer the functionality from the source code. This paper proposes a new approach named Hybrid-DeepCom to automatically generate code comments for the functional units of Java language, namely, Java methods. The generated comments aim to help developers understand the functionality of Java methods. Hybrid-DeepCom applies Natural Language Processing (NLP) techniques to learn from a large code corpus and generates comments from learned features. It formulates the comment generation task as the machine translation problem. Hybrid-DeepCom exploits a deep neural network that combines the lexical and structure information of Java methods for better comments generation. We conduct experiments on a large-scale Java corpus built from 9,714 open source projects on GitHub. We evaluate the experimental results on both machine translation metrics and information retrieval metrics. Experimental results demonstrate that our method Hybrid-DeepCom outperforms the state-of-the-art by a substantial margin. In addition, we evaluate the influence of out-of-vocabulary tokens on comment generation. The results show that reducing the out-of-vocabulary tokens improves the accuracy effectively. [ABSTRACT FROM AUTHOR]

The function of natural killer (NK) cells after allogeneic hematopoietic stem cell transplantation (allo-HSCT) is regulated by the balance between inhibitory KIRs (iKIRs) and activating KIRs (aKIRs). However, few studies have examined the subsequent expression of KIR genes unique to the donor. We defined the set of KIR genes expressed only in the donor and designed a method for measuring the expression of these KIR genes by quantitative real-time polymerase chain reaction (RT-qPCR) based on genetic cloning techniques. In this study, we evaluated the recovery pattern of KIR genes in 252 donor-recipient pairs. The expression of each KIR unique to the donor was in line with that of KIR genes shared by the donor and recipient, such as KIR2DS1, KIR3DS1, KIR2DS4, or KIR2DS3. The timing of the peak mRNA expression of aKIRs unique to the donor was inconsistent but occurred within the first 3 months posttransplantation, whereas the peak mRNA expression of iKIRs was consistently observed in the third month after transplantation. The expression of KIR2DL2 in the third month posttransplantation was significantly higher in the transplant recipients than in the donors (p = 0.01). The KIR2DL1 and KIR3DL1 levels in the transplant recipients in the second and third months posttransplantation were also obviously higher than the donor levels (p < 0.0001). Thus, these observations should be considered when attempting to predict the correlation between mRNA expression and prognosis after allo-HSCT. [ABSTRACT FROM AUTHOR]

We construct new sequence transformations based on Wynn's epsilon and rho algorithms. The recursions of the new algorithms include the recursions of Wynn's epsilon and rho algorithm and of Osada's generalized rho algorithm as special cases. We demonstrate the performance of our algorithms numerically by applying them to some linearly and logarithmically convergent sequences as well as some divergent series. [ABSTRACT FROM AUTHOR]

Interactive image segmentation has been an active research topic in image processing and computer graphics. One of its appealing advantage is the optimization of human feedback and interactions to generate user-desired results. Segmentation results of most previous methods usually depend on the quality and quantity of the user input. In this paper, we propose an algorithm to solve one important challenge arising from inputs with bad or limited quality. Our work is notably different from previous methods. First, the weakly interactive image segmentation is formulated and deduced in theory, then we propose to reconstruct enough samples via sparse reconstruction to enhance the robustness to weakly interactive labels. More importantly, we leverage interactive labels to extract a latent subspace which jointly optimizes multiclass classification and binary classification based on fisher rules. Numerous experiments are conducted on MSRC (Ning et al. in Interact Imaging Vis Pattern Recognit 43(2):445–456, 2010) and KIM (Kim et al. in: 2010 IEEE computer society conference on computer vision and pattern recognition, 2010) database. The results demonstrate effectiveness and efficiency of our method. [ABSTRACT FROM AUTHOR]

Earthquake precursor data have been used as an important basis for earthquake prediction. In this study, a recurrent neural network (RNN) architecture with long short-term memory (LSTM) units is utilized to develop a predictive model for normal data. Furthermore, the prediction errors from the predictive models are used to indicate normal or abnormal behavior. An additional advantage of using the LSTM networks is that the earthquake precursor data can be directly fed into the network without any elaborate preprocessing as required by other approaches. Furthermore, no prior information on abnormal data is needed by these networks as they are trained only using normal data. Experiments using three groups of real data were conducted to compare the anomaly detection results of the proposed method with those of manual recognition. The comparison results indicated that the proposed LSTM network achieves promising results and is viable for detecting anomalies in earthquake precursor data. [ABSTRACT FROM AUTHOR]

Summary: Background This phase I trial was primarily conducted to determine the maximum tolerated dose (MTD) of apatinib combined with docetaxel in advanced lung adenocarcinoma patients with wild-type EGFR who have failed to first-line platinum-based chemotherapy, and to evaluate the safety and tolerability of apatinib plus docetaxel. Methods This was a single-center, open-label, dose-escalating phase I trial. The study used a standard 3 + 3 dose escalation design with the primary aim of determining the MTD. Twelve patients with advanced lung adenocarcinoma were enrolled, the primary endpoint was safety. Two doses of apatinib, 250 mg/day (level 1) and 500 mg/day (level 2), were evaluated in combination with 60 mg/m2 doxetacel every 3 weeks. Six patients have been treated at levels 1 and 2, respectively. Optimal dose of apatinib was determined by dose-limiting toxicity (DLT). Results Six patients have been treated at levels 1 and 2. At level 1, one of six patients experienced grade 3 acneiform rash as DLTs. At level 2, two patients experienced grade 3 hypertension and one experienced grade 3 nasal bleeding. MTD and recommended dose for phase II study was 250 mg/day. Most frequent adverse events of any grade were bilirubin elevation, hypertension, alanine aminotransferase elevation, transglutaminase elevation, hand foot syndrome and fatigue. The median progression-free survival was 2.76 month. Moreover, three patients had developed progressive disease and the mean duration of response was 2.79 months. Conclusion Apatinib plus docetaxel was well tolerated and showed promising efficacy in advanced lung adenocarcinoma. This combination therapy may represent a potent therapeutic option for advanced lung adenocarcinoma patients with wild-type EGFR. [ABSTRACT FROM AUTHOR]

Storing the large-scale data on the cloud server side becomes nowadays an alternative for the data owner with the popularity and maturity of the cloud computing technique, where the data owner can manage the data with limited resources, and the user issues the query request to the cloud server instead of the data owner. As the server is not completely trusted, it is necessary for the user to perform results authentication to check whether or not the returned results from the cloud server are correct. We investigate in this paper how to perform efficient data update for the result authentication of the outsourced univariate linear function query. We seek to outsource almost all the data and computing to the server, and as few data and computations as possible are stored and performed on the data owner side, respectively. We present a novel scheme to achieve the security goal, which is divided into two parts. The first part is a verification algorithm for the outsourced computing of line intersections, which enables the data owner to store most of the data on the server side, and to execute less of the computing of the line intersections. The second part is an authentication data structure Two Level Merkle B Tree for the outsourced univariate linear function query, where the top level is used to index the user input and authenticate the query results, and the bottom level is used to index the query condition and authenticate the query results. The authentication data structure enables the data owner to update the data efficiently, and to implement the query on the server side. The theoretic analysis shows that our proposed scheme works with higher efficiency. [ABSTRACT FROM AUTHOR]

Skew-orthogonal polynomials (SOPs) arise in the study of the n-point distribution function for orthogonal and symplectic random matrix ensembles. Motivated by the average of characteristic polynomials of the Bures random matrix ensemble studied in Forrester and Kieburg (Commun Math Phys 342(1):151-187, 2016), we propose the concept of partial-skew-orthogonal polynomials (PSOPs) as a modification of the SOPs, and then the PSOPs with a variety of special skew-symmetric kernels and weight functions are addressed. By considering appropriate deformations of the weight functions, we derive nine integrable lattices in different dimensions. As a consequence, the tau-functions for these systems are shown to be expressed in terms of Pfaffians and the wave vectors PSOPs. In fact, the tau-functions also admit the multiple integral representations. Among these integrable lattices, some of them are known, while the others are novel to the best of our knowledge. In particular, one integrable lattice is related to the partition function of the Bures ensemble. Besides, we derive a discrete integrable lattice which can be used to compute certain vector Padé approximants. This yields the first example regarding the connection between integrable lattices and generalised inverse vector-valued Padé approximants, about which Hietarinta, Joshi, and Nijhoff pointed out that, “This field remains largely to be explored”, in the recent monograph (Hietarinta et al. in Discrete systems and integrability, vol 54. Cambridge University Press, Cambridge, 2016, [Section 4.4]). [ABSTRACT FROM AUTHOR]

Electrochemiluminescence (ECL) is a very sensitive method for trace analysis because of its background interference and high signal-to-noise ratio. In the past decade, the determination of Cu2+ in environment has attracted considerable attention since it plays an essential role in many physiological processes. Herein, a novel ECL sensor based on C,N quantum dots embedded g-C3N4 nanosheets (C,N-QDs@NSs) was constructed for the detection of Cu2+. The nanocomposite was rapidly obtained via the oxidation of normal g-C3N4 in H2O2 solution using sonochemical synthesizing method. Due to the abundant surface defects on C,N-QDs@NSs, the ECL intensity was magnified 2.5 times for using a C,N-QDs@NSs electrode in comparision to a g-C3N4 modified electrode. Besides, C,N-QDs@NSs could accelerate the rate of electron transfer in ECL reaction and thus resulted in the lower cathodic peak potential. Significantly, Cu2+ could effectively quench the ECL of C,N-QD@NSs, which endowed C,N-QD@NSs with a great advantage in the ECL detection of Cu2+. under optimum conditions, C,N-QDs@NSs modified electrode exhibited a linear detection range from 5 × 10−4 to 10 µM with a detection limit of 2 × 10−4 µM (S/N = 3) for Cu2+, and was finally applied to detect Cu2+ in real samples with satisfactory results. [ABSTRACT FROM AUTHOR]

Numerous feature descriptors have been proposed for holistic facial analysis with satisfactory performances. However, few studies have been conducted on how to model the concept of facial beauty for face-related tasks. In addition, existing learning-based face recognition methods suffer from efficiency problems and rely heavily on a sufficient database. In this paper, we develop an efficient method which leverages the perception of human facial beauty for face recognition. Our work is notably different from previous face recognition works in several aspects: (1) we derive a set of facial features based on the fruits of facial attractiveness and beauty analysis research; (2) compared with traditional optimization-based learning methods, we propose simple yet effective C4.5 decision tree as classification model; (3) proposed method is invariant to both gesture variations and facial occlusions, which achieves good performance compared with a series of state-of-the-art methods. More importantly, we propose visualization experiments to verify the discriminative attributes of extracted features. In this paper, we start by preprocessing images in order to enhance image quality. Then, inspired by the facial beauty research, we design a set of new feature descriptors defined as natural feature. The extracted natural feature is embedded into C4.5 decision tree for supervised learning and classification. Extensive experiments are conducted on the AR database, FRGC database and Extended Yale B database. Comprehensive experiments and in-depth analysis verify the effectiveness and competitiveness of the proposed method. [ABSTRACT FROM AUTHOR]

When the subterranean termite Reticulitermes flavipes is fed heat-killed methicillin resistant Staphylococcus aureus (MRSA) or Pseudomonas aeruginosa, the termite produces proteins with antibacterial activity against the inducer pathogen in its hemolymph. We used a proteomic approach to characterize the alterations in protein profiles caused by the inducer bacterium in the hemolymph of the termite. Nano-liquid chromatography-tandem mass spectrometry analysis identified a total of 221 proteins and approximately 70% of these proteins could be associated with biological processes and molecular functions. Challenges with these human pathogens induced a total of 57 proteins (35 in MRSA-challenged, 16 in P. aeruginosa-challenged, and 6 shared by both treatments) and suppressed 13 proteins by both pathogens. Quasi-Poisson likelihood modeling with false discovery rate adjustment identified a total of 18 and 40 proteins that were differentially expressed at least 2.5-fold in response to MRSA and P. aeruginosa-challenge, respectively. We selected 7 differentially expressed proteins and verified their gene expression levels via quantitative real-time RT-PCR. Our findings provide an initial insight into a putative termite immune response against MRSA and P. aeruginosa-challenge. [ABSTRACT FROM AUTHOR]

Nowadays, Internet of things (IoT) become more and more popular. At the same time, the requirements of security mechanism for multimedia in IoT received a huge concern. Multimedia data is easily shared by devises, applications and social networks set by IoT. Therefore, it is indispensable to guarantee the privacy and security of shared multimedia data. In this paper, we address the secure multimedia data sharing problem in cloud computing by designing proxy re-encryption (PRE) scheme. Our schemes cope with the issues of data validity, data confidentiality and authentication during encrypted multimedia data sharing. Unlike as usually done in the literature, we present a CCA-secure PRE scheme which removes pairings firstly. Then we design a refined CCA-secure PRE scheme called publicly verifiable PRE without parings. It is demonstrated that our schemes meet not only the security and high efficiency requirements of multimedia data sharing, but also the public verifiability. The validity of ciphertext, both the original and re-encrypted ciphertext, can be publicly verified which brings additional efficiency due to offloading the validity check of ciphertexts from the power-limited clients to any semi-honest public cloud. [ABSTRACT FROM AUTHOR]