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Background: Feeding and eating disorders related to cognitive and psycho-behavioral symptoms are strongly associated with health status in persons with dementia (PWD). Non-pharmacological interventions have been the priority selection to address this significant issue. However, the direct targets of non-pharmacological interventions are unclear and there is no consistent evidence of recommendations on the intervention of different dementia stages and the settings of intervention practice. Objective: To provide caregivers with a set of self-help non-pharmacological interventions for feeding and eating disorders in PWD. Methods: Based on the process of evidence summary, a systematic literature search was performed on dementia websites and seven databases. Two researchers screened the studies independently and appraise the quality. The evidence was graded by Joanna Briggs Institute Grades of Recommendation. Results: Twenty-eight articles were included. Twenty-three non-pharmacological intervention recommendations were categorized into six themes containing oral nutritional supplementation, assistance with eating and drinking, person-centered mealtime care, environmental modification, education or training, and multi-component intervention. These interventions corresponded to three direct targets including improving engagement, making up for loss ability, and increasing food intake directly. They were applied to different stages of dementia and most interventions were targeted at PWD in long-term care institutions. Conclusion: This article summarized the direct targets and the specific implementation of recommendations at different stages of dementia to provide caregivers with self-help non-pharmacological interventions. The practice of recommendations was more applicable to institutionalized PWD. When applied to PWD at home, caregivers need to identify the specific feeding and eating conditions at different stages and adopted the interventions in conjunction with the wishes of the PWD and professional advice.

Since the matrix converter (MC) has no intermediate DC energy storage link, any disturbance at the input will affect the output. To guarantee the safe and stable operation of MC system, a feed-forward compensation (FFC) strategy for MC operation in abnormal input voltage conditions, including voltage unbalanced, non-sinusoidal and instantaneous drop, is presented in this paper. The drive performance on the Space Vector Modulation (SVM) Strategy of MC under abnormal input voltage conditions is deeply analyzed. It is proved that the unbalance, non-sinusoidal and instantaneous drop of the input voltage can be compensated by real-time adjusting the SVM coefficient of the control system. The output voltage of MC is kept at normal value by compensating the change of virtual DC voltage. Finally, the control strategy is verified by simulation and experiment.

Structural safety evaluation is a critical issue in the realm of civil engineering. It involves factors such as uncertainties, external loads, and structural damage after long-term service. Presently, real-time safety evaluation of structural resistance remains challenging for real-world structures. This study proposes a resistance updating model for reinforced concrete beams based on Bayesian inference. The measured static loads of six experimental beams were taken as the proof loads for assessing real-time safety, and a stiffness degradation coefficient (SDC) was developed to embody resistance reduction. The SDC was continuously updated based on the deflection monitoring data of the beams under the proof loads. Specifically, the beam resistances were defined as the random distributions, and their initial distributions were calculated according to the material properties of the beams. Then, the corresponding SDCs of each proof load were estimated. Based on the initial resistance distributions and the real-time SDCs, the iterative updating of the resistance distributions was carried out using Bayesian inference. Subsequently, the future reliability indices of these beams were inferred using the JC method, which utilized the updated resistance distributions and the assumed future load distributions. Finally, a reliability index evolution model was established to evaluate the safety of the experimental beams. The analysis results showed that the proposed method can effectively estimate the resistance to provide an upper limit of future loading. The proposed method is sensitive to the proposed SDC but insensitive to the initial distributions of the resistance.

Long noncoding RNA colon cancer-associated transcript 1 (LncRNA CCAT1) is highly expressed in gastric cancer tissues and plays a role in autophagy. However, the underlying mechanism still needs to be further clarified. To study the role of LncRNA CCAT1 in regulating autophagy of gastric cancer cells, analyze its downstream targets, and elucidate the mechanism. qPCR detected the expression of LncRNA CCAT1 in gastric cancer cells. The proliferation, migration, and invasion ability of LncRNA CCAT1 and the expression level of autophagy-related proteins in gastric cancer cells were detected. Bioinformatics method predicted the downstream targets of LncRNA CCAT1, and they were verified by dual-luciferase assay. The relationship between LncRNA CCAT1, miR-140, and ATG5 was verified by co-transfection, and the expression levels of ATG5 and ATG5–ATG12 complex proteins were detected. Finally, the role of LncRNA CCAT1 in vivo was confirmed by gastric cancer transplantation model. LncRNA CCAT1 was highly expressed in gastric cancer cells. LncRNA CCAT1 can promote the proliferation, migration, invasion, and autophagy activity of gastric cancer cells. LncRNA CCAT1 can bind to miR-140-3p and regulate its expression, while miR-140-3p further regulates the expression of ATG5. Overexpression of LncRNA CCAT1 can promote tumor growth in nude mice. After LncRNA CCAT1 silencing, the positive expression rate of ATG5 in nude mice was low. LncRNA CCAT1 may inhibit the expression of miR-140-3p by sponge adsorption, thus weakening its inhibitory effect on ATG5. Eventually, gastric cancer cells were more prone to autophagy under the pressure of stress.

Background Sepsis is a life-threatening disease with a limited effectiveness and the potential mechanism remains unclear. LncRNA NEAT-2 plays an important role in tumor proliferation, invasion and metastasis, and also involved in the regulation of cardiovascular disease. This study aimed to investigate the function of NEAT-2 in sepsis. Methods We built sepsis animal model with Male Balb/C mice induced by cecal ligation and puncture (CLP). A total of 54 mice were randomly assigned into eight groups: sham operation group (n = 18), CLP group (n = 18), CLP plus si-control group (n = 3), CLP plus si-NEAT2 group (n = 3), CLP plus mimic control group (n = 3), CLP plus miR-320 group (n = 3), CLP plus normal saline group (n = 3), and normal control group (n = 3). The number of peripheral endothelial progenitor cells (EPCs), the expression level of NEAT-2 and miR-320 were detected during progression of sepsis, as well as the number of peripheral EPCs and level of TNF-α, IL-6, VEGF, ALT, AST and Cr. In addition, the function of EPCs was evaluated after NEAT-2 knockdown and miR-320 overexpression in vitro. Results The number of circulating EPCs increased significantly in sepsis. NEAT-2 expression was significantly increased in the progress of sepsis, accompanied with miR-320 downregulated. NEAT-2 knockdown and miR-320 overexpression attenuated hepatorenal function and increased cytokines in sepsis. Moreover, NEAT-2 knockdown and miR-320 overexpression decreased the proliferation, migration and angiogenesis of endothelial progenitor cells in vitro. Conclusions LncRNA-NEAT2 regulated the number and function of endothelial progenitor cells via miR-320 in sepsis.

With the continuous development of new energy power generation and smart grid, Power Electronic Transformer (PET) has a good prospect for development because of its remarkable advantages. Based on the topology of AC/DC/AC, the modulation strategy with dual-PWM (Pulse Width Modulation) is adopted to control the operation of power electronic transformers in this paper. The PET structure consists of three units: importation portion, isolation portion and output portion. Model building and analyzing both at the input and output terminals are achieved step by step. And the simulation of the whole PET system with dual-PWM is accomplished with MATLAB/ Simulink. The simulation results show the control system stability and output voltage regulation precision are improved with feed-forward voltage decoupling vector control system. The correctness and effectiveness of the control strategy are demonstrated through the simulation. PETs play an important role in enhancing power supply reliability for Power Grid and promoting the new energy power generation development.

Truss structures have been widely adopted for civil structures such as long-span buildings and bridges. An actual truss system is usually statically indeterminate having numerous members and high redundancy. It is practically difficult to evaluate the truss safety through traditional reliability-based approaches in view of complex failure modes and uncertainties. Moreover, monitoring data are generally insufficient in reality due to limited sensors under cost consideration. Therefore, a nested discrete Bayesian network has been developed for safety evaluation of truss structures. A concept of member risk coefficient is first proposed based on the mechanical relationship between load effects and member resistance. According to the coefficients of all members, member risk sequences are found as the basis for establishing the topology of a member-level Bayesian network. Each network node represents a truss member and a nodal variable having three states: elasticity, plasticity, and failure. Two relevant member nodes are connected by a directed edge whose causality strength is expressed by a conditional probability table. Meanwhile, a system-level network topology is established to reflect the effects of member states on the truss system. The system is assigned with a node having two states: safety and failure. The directed edge of each member node directly points to the system node. Then, the two networks are combined to form a nested network topology. By this means, direct topology learning is avoided in order to find rational and concise topologies satisfying the mechanical characteristics of civil structures. After that, the conditional probability tables for the nested network are obtained through parameter learning on complete numerical observation data. The data acquirement procedure takes into account uncertainties by defining the randomness of cross-sectional areas and external loads. With the conditional probability tables, the nested network is ready for use. When new evidence from limited monitored members is input into the nested network, the state probabilities of the other members, as well as the system, are simultaneously updated using exact inference algorithms. The inference ability using insufficient information well accords with the demand of engineering practice. Finally, the proposed method has been successfully verified against both numerical and experimental truss structures. It was found that the network estimations could be further confirmed with more evidence.

Background: Neuropathic pain (NP), a severe and disruptive symptom following many diseases, normally restricts patients' physical functions and leads to anxiety and depression. As an economical and effective therapy, exercise may be helpful in NP management. However, few guidelines and reviews focused on exercise therapy for NP associated with specific diseases. The study aimed to summarize the effectiveness and efficacy of exercise for various diseases with NP supported by evidence, describe expert recommendations for NP from different causes, and inform policymakers of the guidelines.Design: A systematic review and expert consensus.Methods: A systematic search was conducted in PubMed. We included systematic review and meta-analysis, randomized controlled trials (RCTs), which assessed patients with NP. Studies involved exercise intervention and outcome included pain intensity at least. Physiotherapy Evidence Database and the Assessment of Multiple Systematic reviews tool were used to grade the quality assessment of the included RCTs and systematic reviews, respectively. The final grades of recommendation were based on strength of evidence and a consensus discussion of results of Delphi rounds by the Delphi consensus panel including 21 experts from the Chinese Association of Rehabilitation Medicine.Results: Eight systematic reviews and 21 RCTs fulfilled all of the inclusion criteria and were included, which were used to create the 10 evidence-based consensus statements. The 10 expert recommendations regarding exercise for NP symptoms were relevant to the following 10 different diseases: spinal cord injury, stroke, multiple sclerosis, Parkinson's disease, cervical radiculopathy, sciatica, diabetic neuropathy, chemotherapy-induced peripheral neuropathy, HIV/AIDS, and surgery, respectively. The exercise recommended in the expert consensus involved but was not limited to muscle stretching, strengthening/resistance exercise, aerobic exercise, motor control/stabilization training and mind-body exercise (Tai Chi and yoga).Conclusions: Based on the available evidence, exercise is helpful to alleviate NP intensity. Therefore, these expert consensuses recommend that proper exercise programs can be considered as an effective alternative treatment or complementary therapy for most patients with NP. The expert consensus provided medical staff and policymakers with applicable recommendations for the formulation of exercise prescription for NP. This consensus statement will require regular updates after five–ten years.

Background Brood pollination mutualism is a special type of plant-pollinator interaction in which adult insects pollinate plants, and the plants provide breeding sites for the insects as a reward. To manifest such a mutualism between Stellera chamaejasme and flower thrips of Frankliniella intonsa, the study tested the mutualistic association of the thrips life cycle with the plant flowering phenology and determined the pollination effectiveness of adult thrips and their relative contribution to the host’s fitness by experimental pollinator manipulation. Results The adult thrips of F. intonsa, along with some long-tongue Lepidoptera, could serve as efficient pollinators of the host S. chamaejasme. The thrips preferentially foraged half-flowering inflorescences of the plants and oviposited in floral tubes. The floral longevity was 11.8 ± 0.55 (mean ± se) days, which might precisely accommodate the thrips life cycle from spawning to prepupation. The exclusion of adult thrips from foraging flowers led to a significant decrease in the fitness (i.e., seed set) of host plants, with a corresponding reduction in thrips fecundity (i.e., larva no.) in the flowers. Conclusions The thrips of F. intonsa and the host S. chamaejasme mutualistically interact to contribute to each other’s fitness such that the thrips pollinate host plants and, as a reward, the plants provide the insects with brooding sites and food, indicating the coevolution of the thrips life cycle and the reproductive traits (e.g., floral longevity and morphology) of S. chamaejasme.

Theoretical or numerical progressive collapse analysis is necessary for important civil structures in case of unforeseen accidents. However, currently, most analytical research is carried out under the assumption of material elasticity for problem simplification, leading to the deviation of analysis results from actual situations. On this account, a progressive collapse analysis procedure for truss structures is proposed, based on the assumption of elastoplastic materials. A plastic importance coefficient was defined to express the importance of truss members in the entire system. The plastic deformations of members were involved in the construction of local and global stiffness matrices. The conceptual removal of a member was adopted, and the impact of the member loss on the truss system was quantified by bearing capacity coefficients, which were subsequently used to calculate the plastic importance coefficients. The member failure occurred when its bearing capacity arrived at the ultimate value, instead of the elastic limit. The extra bearing capacity was embodied by additional virtual loads. The progressive collapse analysis was performed by iterations until the truss became a geometrically unstable system. After that, the critical progressive collapse path inside the truss system was found according to the failure sequence of the members. Lastly, the proposed method was verified against both analytical and experimental truss structures. The critical progressive collapse path of the experimental truss was found by the failure sequence of damaged members. The experimental observation agreed well with the corresponding analytical scenario, proving the method feasibility.

Compared with classic probability or statistical theories, Bayesian inference could be a better option for real-world damage identification problems since it can simultaneously utilize both prior knowledge and current measurements of a structure. However for a complex problem, a Bayesian identification procedure should face the challenge of unknown likelihood functions and unacceptable computational expenses. Due to it, approximate Bayesian computation (ABC) is adopted and incorporated with the Metropolis Hastings sampling (MHS) algorithm and stochastic response surface (SRS). Likelihood functions are no longer required during the inference. A stable Markov chain is obtained containing qualified parameter samples, whose random responses are then fast computed by SRSs. Additionally, a nested Bayesian updating procedure with a dynamic tolerance is proposed for fast estimation convergence of posterior probability distributions. After that a probabilistic damage index is defined based on the statistical features of the estimated posterior probability distributions. Lastly, the feasibility of the proposed method has been validated using both numerical and experimental beams. Their damage was indicated by the magnitude variations of the damage index.

Poly(ethylene oxide) (PEO)-based polymers are common hosts in solid polymer electrolytes (SPEs) for high-power energy devices. Molecular simulations have provided valuable molecular insights into structures and ion transport mechanisms of PEO-based SPEs. The calculation of thermodynamic and kinetic properties rely crucially on the dependability of the molecular force fields describing inter- and intra-molecular interactions with the target system. In this work, we reparametrized atomic partial charges for the widely applied optimized potentials for liquid simulations (OPLS) force field of PEO. The revised OPLS force field, OPLSR, improves the calculations of density, thermal expansion coefficient, and the phase transition of the PEO system. In particular, OPLSR greatly enhances the accuracy of the calculated dielectric constant of PEO, which is critical for simulating polymer electrolytes. The reparameterization method was further applied to SPE system of PEO/LiTFSI with O:Li ratio of 16:1. Based on the reparametrized partial charges, we applied separate charge-scaling factors for PEO and Li salts. The charge-rescaled OPLSR model significantly improves the resulting kinetics of Li+ transport while maintaining the accurate description of coordination structures within PEO-based SPE. The proposed OPLSR force field can benefit the future simulation studies of SPE systems.

Two types of ion-conducting polyimides with sulfonate or ether functional groups were synthesized as ion-type or coordination-type cathode binders for lithium-ion batteries (LIBs), respectively. Although superior ion transport abilities have been reported for both types of ion-conducting polymers, their electrochemical performances are significantly different and the corresponding transport mechanisms at the electrolyte/electrode interface remain elusive. Here, we combine experimental and computational techniques to investigate the cathode interface in the presence of both functional polymer binders in comparison with the poly(vinylidene fluoride) (PVDF) binder as reference. A broad shoulder in the cyclic voltammogram accompanied by a poor rate performance of battery tests was observed for a LiFePO4 cathode with coordination-type ether-based polyimide (EPI) binder. In contrast, a LiFePO4 cathode with ion-type sulfonated polyimide (SPI) binder exhibits smaller concentration polarization, achieving satisfactory capacity at high current density. Simulations show that the ether-based binder strongly coordinates Li ions and thus slows the diffusion of Li ions. This leads to the reduction of the LIB electrochemical performance at a high C-rate. In contrast, the negative moiety of the SPI binder leads to less localization of Li ions, allowing a slightly higher Li-ion mobility. Conventional PVDF shows no affinity to Li ions, leading to less Li-ion accumulation at the electrode/electrolyte interface. Yet, the cathode surface covered with PVDF shows the lowest Li-ion diffusivity compared to those with the two types of Li-ion-conducting binders. Therefore, cathodes with SPI and PVDF binders show less polarization at the electrode interface and allow higher C-rate performance of LIBs. The combined results provide a comprehensive understanding of the mechanism of ion conduction in ion- and coordination-type Li-ion-conducting polymer binders. This gives valuable insight into the design of next-generation polymer materials for high-power LIBs.