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Integrated microwave photonics (MWP) is an intriguing technology for the generation, transmission and manipulation of microwave signals in chip-scale optical systems1,2. In particular, ultrafast processing of analogue signals in the optical domain with high fidelity and low latency could enable a variety of applications such as MWP filters3–5, microwave signal processing6–9 and image recognition10,11. An ideal integrated MWP processing platform should have both an efficient and high-speed electro-optic modulation block to faithfully perform microwave–optic conversion at low power and also a low-loss functional photonic network to implement various signal-processing tasks. Moreover, large-scale, low-cost manufacturability is required to monolithically integrate the two building blocks on the same chip. Here we demonstrate such an integrated MWP processing engine based on a 4 inch wafer-scale thin-film lithium niobate platform. It can perform multipurpose tasks with processing bandwidths of up to 67 GHz at complementary metal–oxide–semiconductor (CMOS)-compatible voltages. We achieve ultrafast analogue computation, namely temporal integration and differentiation, at sampling rates of up to 256 giga samples per second, and deploy these functions to showcase three proof-of-concept applications: solving ordinary differential equations, generating ultra-wideband signals and detecting edges in images. We further leverage the image edge detector to realize a photonic-assisted image segmentation model that can effectively outline the boundaries of melanoma lesion in medical diagnostic images. Our ultrafast lithium niobate MWP engine could provide compact, low-latency and cost-effective solutions for future wireless communications, high-resolution radar and photonic artificial intelligence.An integrated lithium niobate photonic processing engine performs integration and differentiation of analogue signals, solves ordinary differential equations, generates ultra-wideband microwave signals and detects edges in images. [ABSTRACT FROM AUTHOR]

C1q, the initiator of the classical pathway of the complement system, is activated during Alzheimer's disease (AD) development and progression and is especially associated with the production and deposition of β-amyloid protein (Aβ) and phosphorylated tau in β-amyloid plaques (APs) and neurofibrillary tangles (NFTs). Activation of C1q is responsible for induction of synapse loss, leading to neurodegeneration in AD. Mechanistically, C1q could activate glial cells, which results in the loss of synapses via regulation of synapse pruning and phagocytosis in AD. In addition, C1q induces neuroinflammation by inducing proinflammatory cytokine secretion, which is partially mediated by inflammasome activation. Activation of inflammasomes might mediate the effects of C1q on induction of synapse apoptosis. On the other hand, activation of C1q impairs mitochondria, which hinders the renovation and regeneration of synapses. All these actions of C1q contribute to the loss of synapses during neurodegeneration in AD. Therefore, pharmacological, or genetic interventions targeting C1q may provide potential therapeutic strategies for combating AD. [ABSTRACT FROM AUTHOR]

Background: Acute myeloid leukemia (AML) treatment remains challenging. CD70 was reported as a promising AML-specific antigen. Preclinically, CAR T-cell with single-chain-variable fragment (scFv) or truncated CD27 targeting CD70 has been reported to treat AML. However, various disadvantages including spontaneous exhaustion, proteinase-mediated loss of functional receptors, and high immunogenicity, limited its further application to clinical settings. Alternatively, the single-variable domain on heavy chain (VHH), also known as nanobodies, with comparable binding ability and specificity, provides an optional solution. Method: We generated CD70 knocked-out novel nanobody-based anti-CD70-CAR T-cells (nb70CAR-T) with two different VHHs for antigen detection. Next, we detected the CD70 expression on primary AML blasts by flow cytometry and associated the efficacy of nb70CAR-T with the target antigen density. Finally, epigenetic modulators were investigated to regulate the CD70 expression on AML cells to promote the functionality of nb70CAR-T. Results: Our nb70CAR-T exhibited expected tumoricidal functionality against CD70-expressed cell lines and primary AML blasts. However, CD70 expression in primary AML blasts was not consistently high and nb70CAR-T potently respond to an estimated 40.4% of AML patients when the CD70 expression level was over a threshold of 1.6 (MFI ratio). Epigenetic modulators, Decitabine and Chidamide can up-regulate CD70 expression on AML cells, enhancing the treatment efficacy of nb70CAR-T. Conclusion: CD70 expression in AML blasts was not fully supportive of its role in AML targeted therapy as reported. The combinational use of Chidamide and Decitabine with nb70CAR-T could provide a new potential for the treatment of AML. [ABSTRACT FROM AUTHOR]

Searching for text in a document is a day-to-day task supported by a variety of visual interface techniques. Since the target searching word may be scattered across the document, manually checking each word is exhaustive and time-consuming, which calls for effective visualization of the search results to enable efficient visual document analysis. In this paper, we revisit the problem of visualizing word search results and formulate two design goals: minimizing the number of user interactions and optimizing the on-screen information of search results. Two visualization techniques are introduced accordingly: a structured list that integrates search results with the hierarchical document structure and full sentence snippets to provide more complete local context for each matched result. We then conduct a user study to compare these techniques with some most commonly used visual interfaces. The results show that the structured list is preferred by most participants and leads to more efficient search, whereas the full sentence snippet results in a slight improvement in accuracy and efficiency, but is still appreciated by the participants. [ABSTRACT FROM AUTHOR]

The treatment of refractory Burkitt's lymphoma (BL) is still a challenge. Although CAR-T cell therapy has achieved good responses in diffuse large B cell lymphoma, there is no case series report about the efficacy of CAR-T cell therapy in adult Burkitt's lymphoma. In this study, we evaluate the efficacy and safety of CAR19/22 T cell therapy in six refractory Burkitt's lymphoma cases with poor genetic prognostic factors. After CAR-T cell therapy, five cases had grade 1 and one had grade 3 cytokine release syndrome. Three patients achieved an objective response (3/6 50%), including two partial remission and one complete remission. One CR patient received allogeneic hematopoietic stem cell transplantation (HSCT) and one PR patient received CAR22/19-T cells following auto-HSCT, and they were still in remission at 37 and 22 months of follow-up, respectively. Interestingly, patients with bulky disease (case 2, 4 and 5) had higher levels of serum IL-2R, which was secreted by regulatory T cells, lower CAR lentiviral amplification and poorer prognosis with shorter survival time than cases with non-bulky disease. It is suggested that high tumor burden, more immune suppressive cells and limited CAR-T cell expansion might affect the efficacy of CAR-T cell therapy. CAR-T cell therapy in adult BL patients whose best response cannot achieve CR may need to bridge to other treatments (such as HSCT) early. [ABSTRACT FROM AUTHOR]

In the field of evolutionary genome analysis, biologists seek to identify important genes or chromosome regions by comparing phylogenetic trees and analyzing the mutation at which locus might affect phenotypic traits. Unfortunately, the tree comparison and accompanying analysis are often performed manually. In this paper, we characterize the workflow of evolutionary genome analysis and present a task analysis for the fundamental questions asked by biologists during the analysis procedure. We propose two algorithms to enable quantitative tree comparison. One is to measure the differences between corresponding leaf nodes on two trees, and the other is to compute the classification inconsistency of each leaf node by comparing tree structure with a given biological classification. Configuring with the obtained difference and inconsistency, we present a visual analysis system, visual comparison of phylogenetic trees for evolutionary genome analysis, which not only enables biologists to intuitively explore trees but also identify locus which affects their traits by comparing SNP variants of selected leaf nodes. We conclude with case studies from two biologists who used our system to augment their previous manual analysis workflow and demonstrate that our system can reveal more insight. [ABSTRACT FROM AUTHOR]

Models for underwater vehicle explaining its relationship between movement and the force exerting on the robot permit a wide range of development to be used in control and navigation. Yet currently no general method arrives a better model with structure and parameters for vehicles automatically. Based on the empirical data, symbolic regression method inspired by natural selection is conducted to automatically detect realistic structure and parameters of vehicle model. The proposed method is completely general and does not assume any pre-existing models before identification, it can be applied 'out of the box' to any given vehicle experiment data. To validate and compare our approach with parameter identification methods like Levenberg-Marquardt Algorithm and Genetic Algorithm, we systematically rediscover the laws underlying underwater vehicle models and neglected laws for reflect the environments. Predicted results for datasets show that we are able to find programs that are simple enough to lead to an actual accurate model for describing the mechanisms of the vehicle. [ABSTRACT FROM AUTHOR]

As ocean resources received considerable attention, the autonomous underwater vehicle (AUV) has been more widely applied due to its excellent flexibility and adaptability, and the optimization design of AUV has becoming a more important issue. The heavier-than-water underwater vehicle (HUV) is a new conceptual AUV, and its design is a typical multidisciplinary problem, but heavily dependent on the experience with naval architects at the present engineering design. To realize the optimization design of HUV, the multidisciplinary design optimization (MDO) method is applied to the multiple objective MDO design of an HUV. In this paper, a system synthesis model of the HUV has been set up. To predict the hydrodynamic characteristics accurately, the computational fluid dynamics (CFD) method is used. In the MDO process, the all-in-one (AIO) method has been adopted with non-dominated sorting genetic algorithms (NSGA)-II and a Kriging model for constructing global approximations to reduce the cost of the CFD numerical simulation. According to the multiple objective MDO design, the Pareto-optimal solutions are analyzed and verified by the numerical simulation, and it is found that the optimal design of HUV has better performance than that of prototype. [ABSTRACT FROM AUTHOR]

One of the shortcomings of a number of Class D amplifiers (CDAs) designs is their susceptibility to supply noise, quantified by Power Supply Rejection Ratio (PSRR). Reported investigations thereto to-date remain incomplete/over-simplified, particularly the assumption that the AC ground is noise-less and a simplified fully-differential integrator model. In this paper, the effect of supply noise in the AC ground to PSRR is analytically investigated, and the associated analytical expressions derived. Of specific interest, the analysis is applied to the ubiquitous 3-state Bridge-tied-load (BTL) closed-loop PWM CDA, taking into consideration not only the effect of the non-ideal AC ground, but also the effect of the resistor and capacitor mismatch based on a realistic fully-differential integrator model. Further, the PSRR analysis of 3-state BTL closed-loop CDAs has to date been limited to the single-feedback topology and in this paper, extended to the double-feedback topology. These analyses and derived equations herein are useful as they provide valuable insights to CDA designers into the PSRR mechanisms-for example, the counter-intuitive observation that the CDA with 1st-order integrators provides similar or better PSRR than the CDA with 2nd-order integrators if both CDAs are designed to the same carrier attenuation-including the effect of various circuit parameters, and ensuing trade-offs. The derived analytical expressions are verified by means of HSPICE simulations and on the basis of practical measurements on discretely-realized CDAs. [ABSTRACT FROM AUTHOR]

One way to solve topology optimization of continuum structures under design-dependent pressure loads is to recover the loading surface at each step of the minimization process. During the topology evolution, the intermediate topologies obtained by using the SIMP (Solid Isotropic Material with Penalization) method actually can be regarded as gray scale images, for which the paper proposes a new material boundary identification scheme based on image segmentation technique. The Distance Regularized Level Set Evolution (DRLSE) method proposed by Li et al., IEEE Trans Image Process 19(12):3243-3254 (2010) is utilized to detect the image edge. Then the pressure boundary is represented as the zero level contour of a level set function (LSF). Inheriting the merits of the level set method, the current scheme can handle the topological change of the pressure boundary efficiently and be easily extended to the three-dimensional problems. In addition, the scheme is more stable compared with the conventional loading surface searching methods since it works well for the intermediate topologies with local scattered densities. A new optimization framework is also proposed to avoid the load sensitivity analysis. Four numerical examples are presented to show the validity and advantages of the proposed scheme. [ABSTRACT FROM AUTHOR]

A systematic method for swimming control of the underwater snake-like robot is still lacking. We construct a simulation platform of the underwater snake-like robot swimming based on Kane's dynamic model and central pattern generator (CPG). The partial velocity is deduced. The forces which contribute to dynamics are determined by Kane's approach. Hydrodynamic coefficients are determined by experiments. Then, we design a CPG-based control architecture implemented as the system of coupled nonlinear oscillators. The CPG, like its biological counterpart, can produce coordinated patterns of rhythmic activity while being modulated by simple control parameters. The relations between the CPG parameters and the speed of the underwater snake-like robot swimming are investigated. Swimming in a straight line, turning, and switching between swimming modes are implemented in our simulation platform to prove the feasibility of the proposed simulation platform. The results show that the simulation platform can imitate different swimming modes of the underwater snake-like robot. [ABSTRACT FROM AUTHOR]

In this paper, a dynamic model for an underwater snake-like robot is developed based on Kane's dynamic equations. This methodology allows construction of the dynamic model simply and incrementally. The partial velocity is deduced. The forces which contribute to dynamics are determined by Kane's approach. The generalized active forces and the generalized inertia forces are deduced. The model developed in this paper includes inertia force, inertia moment, gravity, control torques, and three major hydrodynamic forces: added mass, profile drag and buoyancy. The equations of hydrodynamic forces are deduced. Kane's method provides a direct approach for incorporating external environmental forces into the model. The dynamic model developed in this paper is obtained in a closed form which is well suited for control purposes. It is also computationally efficient and has physical insight into what forces really influence the system dynamics. The simulation result shows that the proposed method is feasible. [ABSTRACT FROM AUTHOR]

In this paper, the kinematics and dynamics of an underwater quadruped walking robot were derived based on Kane dynamic equations. This methodology allows construction of the dynamic model simply and incrementally. The velocity and angular velocity components of an underwater quadruped walking robot were served as the generalized velocities. The forces which contribute to dynamics of an underwater quadruped walking robot were determined by Kane's approach. The equations of hydrodynamic forces of an underwater quadruped walking robot were deduced. Hydrodynamic coefficients were determined by experiments. The dynamic model was established by obtaining the generalized active forces and the generalized inertia forces. Numerical simulations of the walking behavior on underwater flat ground were implemented to verify the dynamic model of an underwater quadruped walking robot. Simulation results show that the dynamic model is correct. [ABSTRACT FROM AUTHOR]

This article describes a novel underwater robot, which is called underwater self-reconfigurable system (USS). USS is studied and developed by Shanghai Jiao Tong University. It is formed by a quantity of the same modules and works in group. Based on that, USS can change its form while working in the complicated underwater structures according to different tasks. New multi-jaw underwater docking system, piston style regulator and clamshell-like sampling module are designed for USS, these developments address the problems of underwater docking, floating condition adjusting and sampling. Besides, the gaits like wriggle, creeping, swimming and four-legged moving have been successfully implemented in tank and lake test, which verifies the validity of the concept. [ABSTRACT FROM AUTHOR]

In this paper, a gait control scheme is presented for planar quadruped robots based on a biologic concept, namely central pattern generator (CPG). A CPG is modeled as a group of the coupled nonlinear oscillators with an interaction weighting matrix which determines the gait patterns. The CPG model, mapping functions and a proportional-differential (PD) joint controller compose the basic gait generator. By using the duty factor of gait patterns as a tonic signal, the activity of the CPG model can be modulated, and as a result, a smooth transition between different gait patterns is achieved. Moreover, by tuning the parameters of the CPG model and mapping functions, the proposed basic gait generator can realize adaptive workspace trajectories for the robot to suit different terrains. Simulation results illustrate and validate the effectiveness of the proposed gait controllers. [ABSTRACT FROM AUTHOR]

Underwater self-reconfigurable system (USS), an underwater self-reconfigurable robot consisting of two types of modules, can reform various configurations in real time. Compared with normal underwater robots, its diverse configurations bring forward good adaptability and more abundant gaits. For the tree-like configurations, we propose a technique for dynamic modeling and configuration description. The eel-like configuration and the octopus-like one are chosen as examples to verify the technique, and some gaits are designed. For the eel-like configuration with the serpentine gait, the technique gives the same simulation results as existing eel-like models. For other cases, simulation results are consistent well with what happens in nature. [ABSTRACT FROM AUTHOR]

Aircraft icing accident happens frequently. Researchers try to find new ways to solve this problem. The study is facing the direction of intelligent inspection and control system. Previous studies focused on the principle of aircraft icing and its effects on flight performance. The onboard icing detection equipment can only give the qualitative icing information, but cannot effectively describe how serious the consequences would be. If the icing detection equipment fails, it will cause a serious threat to flight safety. This paper reviews the smart icing system and its fundamental principle. Then based on H theory, an aircraft icing parameter identification method is introduced, and its feasibility is verified by simulation results. Moreover, this method can work normally under noise interference and measurement error. Icing parameter identification method can also test part of aircraft's stability or control derivatives which would be changed obviously after aircraft icing. Classified by neural networks, the stability or control derivatives' variation can be mapped to ice parameters' variation that reflects the severity of aircraft icing. Then H state feedback control is designed originally to suppress the impact of noise interference, so aircraft can keep steady after it is iced. Seeing from simulation result of the whole system, it is clear that the system can effectively detect icing parameters and by using feedback control system, it can ensure the safety of aircraft in the flight envelope. [ABSTRACT FROM AUTHOR]

Active heave compensation systems are usually employed in offshore and deep-sea operations to reduce the adverse impact of unexpected vessel's vertical motion on the response of underwater instruments. This paper presents a control strategy for an active heave compensation system consisting of an electro-hydraulic system driven by a double rod actuator, which is subjected to parametric uncertainties and unmeasured environmental disturbances. Adaptive observer and discontinuous projection type updating law with bounded adaption rate are presented firstly to estimate the uncertain system parameters. Then a similar estimation algorithm is designed by using a multiple delayed version of the system to enhance the performance of parameter observation. A reduced order observer is also introduced to estimate unknown wave disturbances. Using the obtained uncertainty information, the resulting control development and stability analysis are implemented based on the Lyapunov's direct method and back-stepping technique. The proposed controller guarantees the heave compensation error convergent to a bounded neighborhood around the origin. Simulations illustrate the effectiveness of the proposed control system. [ABSTRACT FROM AUTHOR]

In this paper, robust adaptive control strategies are designed for Underwater Remotely Operated Vehicles (ROVs) with velocity constraints. First, robust control strategies are investigated for under-water ROVs, and then adaptive robust control strategies are further developed with online parameter estimation. To prevent the velocity constraint violation, the Barrier Lyapunov Function (BLF) is employed in Lyapunov synthesis. By ensuring the boundedness of the BLF, we also guarantee that the velocity constraints are not transgressed. The stability analysis of the closed-loop system is provided and all closed-loop signals are ensured to be bounded. Simulation results for 5 degree-of-freedom (DOF) underwater ROV demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This article describes an experimental prototype flying fish II and builds a dynamic model that is a novel type of autonomous underwater vehicle (AUV) under the condition of negative buoyancy vehicle (NBV) without large buoyancy mechanism. Compared with the AUV Remus100, the flying fish II can cruise with double speeds within the same range and dimensions. The static stability and motion modes of flying fish II in the longitudinal plane are analyzed through the linear system theory. The flying fish II has static stability in the longitudinal plane and the motion mode is related to metacentric height. [ABSTRACT FROM AUTHOR]

Mutations of the p53 tumor-suppressor gene are the most frequent genetic abnormality in soft tissue sarcomas. Because these rare tumors also respond poorly to standard chemotherapy and bear a 50% 5-year mortality rate, we investigated the possible therapeutic benefits of p53 gene restoration in sarcomas. We constructed Ad5p53, which is an E1A-deleted, replication-deficient adenovirus expressing a cytomegalovirus promoter-driven wild-type p53 cDNA with a Flag sequence tag. SKLMS-1 human leiomyosarcoma cells containing a mis-sense p53 point mutation were effectively transduced with Ad5p53. Increasing levels of Flag-p53 protein, as well as dose-dependent p21Cip1 induction, were observed through a dose range of 10–500 plaque-forming units (PFU)/cell. In vitro administration of Ad5p53 as a single 100 PFU/cell dose caused 40–60% growth inhibition of SKLMS-1 cells at posttreatment days 4, 6, and 8 compared with untreated or viral control treated-cells (P < .05, Student’s t test). Relative to these same controls, in vivo treatment of SKLMS-1-bearing severe combined immunodeficient mice with 6 × 109 PFU of Ad5p53 by intratumoral injection resulted in a 35-day tumor growth delay and complete tumor regression in 40% of mice (P < .05, Student’s t test). The expression of virally derived p53 mRNA in Ad5p53-treated tumor tissues was detected in treated tumor specimens by reverse transcriptase polymerase chain reaction. Reduced intratumoral cellularity and the presence of p53 staining in adjacent normal tissue, consistent with delivery of exogenous p53 to the tumor target, were evident only in Ad5p53-treated tumors after immunohistochemical staining for p53. These results indicate that wild-type p53 gene restoration in sarcomas retards tumor growth and may come to be usefully applied to the clinical treatment of this disease as a single regimen or in combination with conventional therapies. [ABSTRACT FROM AUTHOR]