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Beam profile measurement via wire scanner is a semi-invasive method, which has advantage of less beam influence compared with a profile target, and is widely used in particle accelerator all over the world. Wire scanner is adopted to be applied to Shanghai High Repetition Rate X-ray Free Electron Laser aNd Extreme Light Facility (SHINE). For this purpose, a prototype of wire scanner composed of a wire target, a set of mechanical mechanism, a beam loss monitor and a set of electronics was designed and developed. A tungsten wire with an outer diameter of 20 μm was used as the wire target, and the safety of this tungsten wire was proved by thermal simulation. The beam loss monitor in the wire scanner prototype consists of a quartz fiber that generates Cherenkov light, and a photomultiplier tube. The data acquisition module was developed based on the ADQ14AC-4C data acquisition platform from Teledyne SP Devices, which is equipped with ADC chip with nominal bit of 14 bit, effective bit of about 9 bit, and analog 3 dB bandwidth of 1.2 GHz. The principle and specific design of the prototype were introduced in this paper. The optimization scheme of installing a cavity beam position monitor (CBPM) upstream of the wire target to accurately compensate the beam center position and the beam charge was also mentioned. In order to accurately evaluate performance of the prototype, we measured the beam profile simultaneously by arranging wire scanner system and a YAG target adjacent to each other in Shanghai Soft X-ray Free Electron Laser (SXFEL). The comparison of the experimental results show that the wire scanner can be used for the online semi-invasive beam profile measurement of the 0.84 GeV electron beam with a bunch charge of 500 pC. The resolustion of the prototype wire scanner is better than 30 μm, and especially less than 10 μm in the direction of low beam jitter. When the beam position changes greatly, the measurement accuracy of the prototype wire scanner is sharply improved by the CBPM system. Furthermore, the relative charge quantity calculated by the CBPM reference cavity signal is used to compensate the beam loss signal, and the measurement result of the prototype wire scanner is slightly improved. The results of the profile target agree with those of the prototype wire scanner well which verify the function of the device applied to SXFEL. The prototype of wire scanner system has laid a good technical foundation for SHINE construction, and at the same time, wire scanner system with CBPM can be used as a supplement for beam profile measurement in SXFEL.

Stem cells play critical roles in cell therapies and tissue engineering for nerve repair. However, achieving effective delivery of high cell density remains a challenge. Here, a novel cell delivery platform termed the hyper expansion scaffold (HES) is developed to enable high cell loading. HES facilitated self‐promoted and efficient cell absorption via a dual driving force model. In vitro tests revealed that the HES rapidly expanded 80‐fold in size upon absorbing 2.6 million human amniotic epithelial stem cells (hAESCs) within 2 min, representing over a 400% increase in loading capacity versus controls. This enhanced uptake benefited from macroscopic swelling forces as well as microscale capillary action. In spinal cord injury (SCI) rats, HES–hAESCs promoted functional recovery and axonal projection by reducing neuroinflammation and improving the neurotrophic microenvironment surrounding the lesions. In summary, the dual driving forces model provides a new rationale for engineering hydrogel scaffolds to facilitate self‐promoted cell absorption. The HES platform demonstrates great potential as a powerful and efficient vehicle for delivering high densities of hAESCs to promote clinical treatment and repair of SCI. [ABSTRACT FROM AUTHOR]

This paper studies the optimal consumption, life insurance and investment problem for an income earner with uncertain lifetime under smooth ambiguity model. We assume that risky assets have unknown market prices that result in ambiguity. The individual forms his belief, that is, the distribution of market prices, according to available information. His ambiguity attitude, which is similar to the risk attitude described by utility function $ U $, is represented by an ambiguity preference function $ \phi $. Under the smooth ambiguity model, the problem becomes time-inconsistent. We derive the extended Hamilton-Jacobi-Bellman (HJB) equation for the equilibrium value function and equilibrium strategy. Then, we obtain the explicit solution for the equilibrium strategy when both $ U $ and $ \phi $ are power functions. We find that a more risk- or ambiguity-averse individual will consume less, buy more life insurance and invest less. Moreover, we find that the Tobin-Markowitz separation theorem is no longer applicable when ambiguity attitude is taken into consideration. The investment strategy will change with the characteristics of the decision maker, such as risk attitude, ambiguity attitude and age. [ABSTRACT FROM AUTHOR]

In order to better reduce the cost of e-commerce operations and save resources for marketing promotion, e-commerce merchants must adopt a reasonable and effective way to screen customers and improve the competitiveness of their own products. This paper takes the measurement of latent variable customer loyalty as the starting point, collects data through the design of questionnaires as the research basis, and uses Analysis of Moment Structure (AMOS) to construct structural equation model to conduct a validating factor analysis. It was found that the hypotheses proposed from the three subjects of business, customers themselves and logistics are all basically valid, and all three have a positive impact on loyalty. Ecommerce businesses should improve the service quality of their stores, ensure that their products can meet the needs of most customers, and build a good brand image, and should also carefully choose logistics companies that are reliable and new to customers to cooperate with.

This paper focuses on the state estimation problem for a class of switching complex dynamical networks (CDNs) with unknown nonlinear dynamics. A novel neural network based (NN-based) state estimator with non-fragility is constructed to fulfill the state estimation task. In order to improve the efficiency of communication resource utilization, an event-triggered mechanism is applied in designing the estimator. By employing the Lyapunov stability theory and inequality technique, sufficient criteria are derived for the existence of the desired exponentially ultimately bounded NN-based state estimator for CDNs. It is also proven that the proposed event-triggered mechanism can avoid Zeno phenomenon. In addition, the gains of the desired estimators are characterized by the explicit expressions. Finally, the effectiveness of the proposed NN-based state estimator is verified by a simulation example. [ABSTRACT FROM AUTHOR]

This paper mainly investigates the exponential stability of switched neural networks (SNNs) with partial state reset and time-varying delays, in which partial state reset means that only a fraction of the states can be reset at each switching instant. Moreover, both stable and unstable subsystems are also taken into account and therefore, switched systems under consideration can take several switched systems as special cases. The comparison principle, the Halanay-like inequality, and the time-dependent switched Lyapunov function approach are used to obtain sufficient conditions to ensure that the considered SNNs with delays and partial state reset are exponentially stable. Numerical examples are provided to demonstrate the reliability of the developed results. [ABSTRACT FROM AUTHOR]

In underground engineering, shear failure is a common failure type in coal-rock mass under medium and low strain-rate disturbance loads. Analyzing the shear failure mechanical properties of coal-rock mass under dynamic normal load is significant. In order to reveal the influence of disturbance load on the shear mechanical properties of coal rock, a dynamic and static load coupling electro-hydraulic servo testing machine was used to conduct the shear tests of coal-like rock materials under dynamic and constant normal load. The amplitude of dynamic load is 10 kN and the frequency is 5 Hz. The damage process of the specimens was detected by the acoustic emission (AE) detection system. The results imply that the shear failure process of coal-like rock materials under constant normal load can be divided into four stages. The normal disturbance decreased the shear strength of the specimens and increased the shear modulus of the specimens. With the increase in normal load, the influence of disturbance on the shear strength of the specimen decreased. By analyzing the AE parameters, it was found that the dynamic load made the internal damage of the specimen more severe during the shear failure process. The damage variable was calculated by AE cumulative energy, and the damage evolution was divided into three stages. The shear failure mechanism of the specimen was judged by RA (rise time/amplitude) and AF (average frequency). It was found that from the elastic deformation stage to the unstable development fracture stage, the proportion of shear fracture increased. When the dynamic normal load was 10 kN and 30 kN, the fracture was mainly shear fracture; When the dynamic normal load was 50 kN, the fracture was mainly tensile or mixed fracture. The dynamic normal load affects the shear strength and failure mechanism. Therefore, the influence of disturbance load on coal-rock mass strength cannot be ignored in underground engineering. [ABSTRACT FROM AUTHOR]

Spinal cord injury (SCI) results in devastating consequences for the motor and sensory function of patients due to neuronal loss and disrupted neural circuits, confronting poor prognosis and lack of effective therapies. A new therapeutic strategy is urgently required. Here, human amniotic epithelial cells (hAEC), featured with immunocompatibility, non-tumorgenicity and no ethical issues, were induced into neural-like cells by a compound cocktail, as evidenced with morphological change and the expression of neural cell markers. Interestingly, the hAEC-neural-like cells maintain the characteristic of low immunogenicity as hAEC. Aiming at SCI treatment in vivo, we constructed a 3D-printed GelMA hydrogel biomimetic spinal cord scaffold with micro-channels, in which hAEC-neural-like cells were well-induced and grown. In a rat full transection SCI model, hAEC-neural-like cell scaffolds that were implanted in the lesion demonstrated significant therapeutic effects; the neural circuit and hindlimb locomotion were partly recovered compared to little affection in the SCI rats receiving an empty scaffold or a sham implantation operation. Thus, the establishment of hAEC-neural-like cell biomimetic scaffolds may provide a safe and effective treatment strategy for SCI. [ABSTRACT FROM AUTHOR]

In order to study the weakening mechanism and mechanical behaviors of hard lamprophyre of Carboniferous Permian coal-bearing strata in China's mining area, lamprophyre samples were subjected to static rock dissolution experiments with pH values of 0, 2, and 4. The acid corrosion mechanism of lamprophyre was revealed from the weight changes of samples, characteristics of solution ion concentration, and macro-mechanical properties. The experimental results show that reaction occurred between lamprophyre and acid solution. With the increasing concentration of H+, the reaction was more intense, the degree of acid etching was higher, and the weight loss was greater. The internal damage induced by acid etching results in the slow extension of the compaction stage of stress–strain curve of uniaxial compression, and the obvious deterioration of mechanical properties of the lamprophyre. The uniaxial compressive strength of the lamprophyre in the dry state is 132 MPa, which decreased to 39 MPa under the acid etching condition, showing significant mudding characteristics. Dolomite (CaMg(CO3)2 with 19.63%) and orthoclase (KAlSi3O8 with 31.4%) in lamprophyre are the major minerals constituents involved in acidification reaction. Photomicrograph recorded from SEM studies reveals that the dissolution effect was directly related to the concentration of H+ in the solution. The dissolution effect was from the surface to the inside. The small dissolution pores became larger and continuously expanded, then finally formed a skeleton structure dominated by quartz. The content of K+, Ca2+, and Mg2+ in the solution after acid etching reaction indicates that the acidified product of orthoclase is colloidal H2SiO3, which adhered to the surface of samples during acid etching and hinders the further acidification of minerals. The dissolution of dolomite and orthoclase under acidic conditions directly leads to the damage of their structure and further promotes the water–rock interaction, which is the fundamental reason for the weakening of the mechanical properties of lamprophyre. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with the sampled-based consensus problem of multi-agent systems with bounded distributed time-delays and quantisation effects. A dynamic quantisation scheme is introduced to save the constrained communication resources, where some adjustable parameters are introduced to exclude the phenomena of quantiser saturation. In addition, to reduce the actuation burden of controller and quantiser cost, a sampled-data control strategy is employed to investigate the consensus problem. Several sufficient criteria are derived to achieve consensus of multi-agent systems based on the matrix theory and Lyapunov control techniques. Finally, two numerical examples are provided to demonstrate the effectiveness of the derived results. [ABSTRACT FROM AUTHOR]

The loss of photoreceptors is a major event of retinal degeneration that accounts for most cases of untreatable blindness globally. To date, there are no efficient therapeutic approaches to treat this condition. In the present study, we aimed to investigate whether human amniotic epithelial stem cells (hAESCs) could serve as a novel seed cell source of photoreceptors for therapy. Here, a two–step treatment with combined Wnt, Nodal, and BMP inhibitors, followed by another cocktail of retinoic acid, taurine, and noggin induced photoreceptor–like cell differentiation of hAESCs. The differentiated cells demonstrated the morphology and signature marker expression of native photoreceptor cells and, intriguingly, bore very low levels of major histocompatibility complex (MHC) class II molecules and a high level of non–classical MHC class I molecule HLA–G. Importantly, subretinal transplantation of the hAESCs–derived PR–like cells leads to partial restoration of visual function and retinal structure in Royal College of Surgeon (RCS) rats, the classic preclinical model of retinal degeneration. Together, our results reveal hAESCs as a potential source of functional photoreceptor cells; the hAESCs–derived photoreceptor–like cells could be a promising cell–replacement candidate for therapy of retinal degeneration diseases. [ABSTRACT FROM AUTHOR]

This article investigates the optimal control problem via reinforcement learning for a class of nonlinear discrete‐time systems. The nonlinear system under consideration is assumed to be partially unknown. A new learning‐based algorithm, T‐step heuristic dynamic programming with eligibility traces (T‐sHDP(λ)), is proposed to tackle the optimal control problem for such partially unknown system. First, the concerned optimal control problem is turned into its equivalence problem, that is, solving a Bellman equation. Then, the T‐sHDP(λ) is utilized to get an approximate solution of Bellman equation, and a rigorous convergence analysis is also conducted as well. Instead of the commonly used single step update approach, the T‐sHDP(λ) stores finite step past returns by introducing a parameter, and then utilizes these knowledge to update the value function (VF) of multiple moments synchronously, so as to achieve higher convergence speed. For implementation of T‐sHDP(λ), a neural network‐based actor‐critic architecture is applied to approximate VF and optimal control scheme. Finally, the feasibility of the algorithm is demonstrated by two illustrative simulation examples. [ABSTRACT FROM AUTHOR]

Summary: Synthetic biology offers new tools and capabilities of engineering cells with desired functions for example as new biosensing platforms leveraging engineered microbes. In the last two decades, bacterial cells have been programmed to sense and respond to various input cues for versatile purposes including environmental monitoring, disease diagnosis and adaptive biomanufacturing. Despite demonstrated proof‐of‐concept success in the laboratory, the real‐world applications of microbial sensors have been restricted due to certain technical and societal limitations. Yet, most limitations can be addressed by new technological developments in synthetic biology such as circuit design, biocontainment and machine learning. Here, we summarize the latest advances in synthetic biology and discuss how they could accelerate the development, enhance the performance and address the present limitations of microbial sensors to facilitate their use in the field. We view that programmable living sensors are promising sensing platforms to achieve sustainable, affordable and easy‐to‐use on‐site detection in diverse settings. [ABSTRACT FROM AUTHOR]