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Nickel chloride hexahydrate (NiCl2·6H2O) was introduced into the SnO2 ETL, which significantly increased open-circuit voltage (VOC) and power conversion efficiency (PCE)

Elicitins are microbe-associated molecular patterns produced by oomycetes to elicit plant defense. It is still unclear whether elicitins derived from non-pathogenic oomycetes can be used as bioactive molecules for disease control. Here, for the first time we identify and characterize an elicitin named PpEli2 from the soil-borne oomycete Pythium periplocum, which is a non-pathogenic mycoparasite colonizing the root ecosystem of diverse plant species. Perceived by a novel cell surface receptor-like protein, REli, that is conserved in various plants (e.g. tomato, pepper, soybean), PpEli2 can induce hypersensitive response cell death and an immunity response in Nicotiana benthamiana. Meanwhile, PpEli2 enhances the interaction between REli and its co-receptor BAK1. The receptor-dependent immune response triggered by PpEli2 is able to protect various plant species against Phytophthora and fungal infections. Collectively, our work reveals the potential agricultural application of non-pathogenic elicitins and their receptors in conferring broad-spectrum resistance for plant protection.

From the end of 2019 to now, coronavirus disease 2019 (COVID-19) has put enormous strain on the world's health systems. As a characteristic sign of COVID-19 patient, olfactory dysfunction (OD) poses considerable problems for patients. In China, acupuncture has been widely used to treat OD caused by COVID-19, but there is still a lack of evidence-based medical evaluation. This study was designed to evaluate the effectiveness and safety of acupuncture for the treatment of COVID-19 OD.According to the retrieval strategies, randomized controlled trials on the acupuncture for COVID-19 OD were obtained from Cochrane Central Register of Controlled Trials, Embase, PubMed, Web of Science, the Chinese National Knowledge Infrastructure, the Chinese Biomedical Literature Database, the Chinese Scientific Journal Database and the Wanfang Database, regardless of publication date, or language. Studies were screened based on inclusion and exclusion criteria, and the Cochrane risk bias assessment tool was used to evaluate the quality of the studies. The meta-analysis was performed using Review Manager (RevMan 5.3) and STATA 14.2 software. Ultimately, the evidentiary grade for the results will be evaluated.The results of this meta-analysis will be submitted to a peer-reviewed journal for publication.This study will provide up-to-date summary proof for evaluating the effectiveness and safety of acupuncture for COVID-19 OD.

RXLR effectors, a class of secreted proteins that are transferred into host cells to manipulate host immunity, have been reported to widely exist in oomycetes, including those from genera Phytophthora, Hyaloperonospora, Albugo, and Saprolegnia. However, in Pythium species, no RXLR effector has yet been characterized, and the origin and evolution of such virulent effectors are still unknown. Here, we developed a modified regular expression method for de novo identification of RXLRs and characterized 359 putative RXLR effectors in nine Pythium species. Phylogenetic analysis revealed that all oomycetous RXLRs formed a single superfamily, suggesting that they might have a common ancestor. RXLR effectors from Pythium and Phytophthora species exhibited similar sequence features, protein structures, and genome locations. In particular, there were significantly more RXLR proteins in the mosquito biological control agent P. guiyangense than in the other eight Pythium species, and P. guiyangense RXLRs might be the result of gene duplication and genome rearrangement events, as indicated by synteny analysis. Expression pattern analysis of RXLR-encoding genes in the plant pathogen P. ultimum detected transcripts of the majority of the predicted RXLR genes, with some RXLR effectors induced in infection stages and one RXLR showing necrosis-inducing activity. Furthermore, all predicted RXLR genes were cloned from two biocontrol agents, P. oligandrum and P. periplocum, and three of the RXLR genes were found to induce a defense response in Nicotiana benthamiana. Taken together, our findings represent the first evidence of RXLR effectors in Pythium species, providing valuable information on their evolutionary patterns and the mechanisms of their interactions with diverse hosts.

Generalized pustular psoriasis (GPP) is a rare, severe, and sometimes fatal form of childhood psoriasis. The first line therapies include acitretin, cyclosporin A, and methotrexate which take effect slowly and have varying long-term side effects for children. Recently, the anti-tumor necrosis factor-alpha (TNF-α), adalimumab has shown efficacy in adult patients with pustular psoriasis; however, there is lack of evidence of its usage in the pediatric population.Data on efficacy of adalimumab in treating pediatric GPP along with a literature review are presented.A total of seven patients had marked clearance and reduction in PGA and systemic/laboratory score within the first week of first injection and achieved almost complete clearance of skin lesions by 1-month follow up. In literature, adalimumab treating pustular psoriasis in pediatric has been described in six children who failed in prior treatment. All six patients showed a satisfactory therapeutic effect.Subcutaneous injection of adalimumab every other week in the treatment of children with GPP has significant clinical efficacy with rapid clearance of skin lesions, providing a novel alternative for children with pustular psoriasis who responded poorly to traditional treatment or are not suitable for traditional treatment.

To synergistically treat glioma with a combination chemotherapy, we design and prepare novel cascade-targeted liposomes (Lip-TPGS) using glucose and triphenylphosphonium (TPP) as targeting moieties, which could intelligently deliver redox-sensitive doxorubicin (DOX) prodrugs (SDOX) and chemotherapeutic sensitizer lonidamine (LND). The pH-responsive ligand Chol-TPG modified by PEGylated glucose can overcome the blood-brain barrier and reach tumor cells. Combined with the modification of mitochondria targeting ligand (Chol-TPP), Lip-TPGS are endowed with pH-responsive charge regulation function and multi-stage targeting abilities. After triggered by the excessive glutathione in tumor cells, Lip-TPGS could sufficiently release the parent drugs DOX, which would significantly reduce side effects without compromising anti-glioma efficacy. Therefore, Lip-TPGS possess these characteristics: good pharmacokinetic behavior, superior brain targeting ability, specific tumor recognition and internalization capability, and strong endo/lysosome escaping and mitochondria targeting potential. Furthermore, Lip-TPGS exhibit significant advantages on anti-glioma by inhibiting proliferation, promoting apoptosis, inducing mitochondria dysfunction, inhibiting migration and invasion, prolonging the survival time, narrowing tumor areas, limiting lung metastasis, and reducing toxicity to normal organs. In summary, Lip-TPGS, with cascade targeting abilities from tissue/cell to organelle levels and highly controlled drug release properties, would become a promising drug delivery system for glioma treatment.

In order to have an accurate knowledge of system-wide operation states, it is necessary to perform state estimation for the integrated energy system (IES) as the basis of energy management and control. Centralized state estimation is practically infeasible for IES due to the unreliability of communication, the barrier on privacy, and the large scale of integrated systems. This paper proposes a distributed state estimation algorithm based on the alternating direction method of multipliers (ADMM) for IES containing electricity, heat, and natural gas. Various coupling units are taken into full consideration in modeling of IES state estimation to reflect the harmonization of multi energy. On the basis of bilinear measurement model, the state estimation considering nonlinear measurements can be replaced by an equivalent three-stage problem containing two linear state estimations and an intermediate transformation to avoid non-convex optimization. The three-stage procedure for IES state estimation can be further decoupled over three sub-systems with coordination on coupling units, yielding a fully distributed scheme based on ADMM. A modified ADMM with the self-adjusting penalty parameter is also adopted to enhance the convergence. Simulation results demonstrate the validity and superiority of the proposed algorithm.

Perovskite crystal quality plays an important role in perovskite solar cells, given that multiple grain boundaries and trap states in the perovskite films hamper further enhancement of solar cell efficiency. Using the solution method to prepare perovskite films with large grains and high coverage requires further improvements. Herein, we introduce Lewis base urea as an additive into the precursor of perovskite to control the crystallization dynamics, allowing for large-grain crystal growth. As a result, MAPbI

In view of the current inability to meet the requirements of fast speed and strong stability in feature extraction, and the slow speed in feature point elimination, this paper proposes an UAV remote sensing image mosaic algorithm based on FAST-Tomasi features and Delaunay triangulation. Firstly, FAST feature detection algorithm is used to accelerate Shi-Tomasi algorithm to obtain fast and accurate feature points, the feature points are described by BRIEF operator, and the phase is conducted by hamming distance. Then, Delaunay triangulation network is constructed according to the initial matching points, and the similarity between the triangles in the two images to be stitched is calculated. The triangle pair with large similarity is the matching triangle pair, so the corresponding accurate matching points are obtained. Then, the improved SPHP algorithm is used for registration. Finally, the weighted algorithm is used to fuse the image. Experimental results indicate that the algorithm retains more correct matching points, the accuracy of eliminating false matching points is higher, and the matching speed is significantly improved.

Phytophthora comprises a group of filamentous plant pathogens that cause serious crop diseases worldwide. It is widely known that a complex effector repertoire was secreted by Phytophthora pathogens to manipulate plant immunity and determine resistance and susceptibility. It is also recognized that Phytophthora pathogens may inhabit natural niches within complex environmental microbes, including bacteria. However, how Phytophthora pathogens interact with their cohabited microbes remains poorly understood. Here, we present such an intriguing case by using Phytophthora–bacteria interaction as a working system. We found that under co-culture laboratory conditions, several Phytophthora pathogens appeared to block the contact of an ecologically relevant bacterium, including Pseudomonas fluorescence and a model bacterium, Escherichia coli. We further observed that Phytophthora sojae utilizes a conserved Crinkler (CRN) effector protein, PsCRN63, to impair bacterial growth. Phytophthora capsici deploys another CRN effector, PcCRN173, to interfere with bacterial flagellum- and/or type IV pilus-mediated motility whereas a P. capsici-derived RxLR effector, PcAvh540, inhibits bacterial swimming motility, but not twitching motility and biofilm formation, suggesting functional diversification of effector-mediated Phytophthora–bacteria interactions. Thus, our studies provide a first case showing that the filamentous Phytophthora pathogens could deploy effectors to interfere with bacterial growth and motility, revealing an unprecedented effector-mediated inter-kingdom interaction between Phytophthora pathogens and bacterial species and thereby uncovering ecological significance of effector proteins in filamentous plant pathogens besides their canonical roles involving pathogen–plant interaction.

In the integrated energy system (IES), multi-energy coordination can provide power supply for distribution networks under extreme disturbances, yielding a positive impact on the resilience. This paper proposes a resilience assessment index system and its corresponding comprehensive assessment method for distribution networks considering multi-energy coordination. Firstly, a set of multi-dimensional resilience assessment indexes is selected based on the analysis of the resilience influence factors, in which multi-energy indexes are introduced to quantify the influence of multi-energy coordination. Secondly, a resilience assessment index system is established as the network hierarchical structure based on the analytic network process (ANP). The assessment index system can reflect the correlations among indexes, making it applicable for the resilience assessment. Then, an optimal weighting model is built to combine the subjective and objective factors, yielding more scientific comprehensive weights of indexes. Finally, the assessment results of distribution network resilience are obtained based on the fuzzy comprehensive assessment method, making the most of each index information. Case study shows the effectiveness of the proposed assessment index system and method in resilience assessment for distribution networks considering multi-energy coordination.

Being widely existed in oomycetes, the RXLR effector features conserved RXLR-dEER motifs in its N terminal. Every known Phytophthora or Hyaloperonospora pathogen harbors hundreds of RXLRs. In Pythium species, however, none of the RXLR effectors has been characterized yet. Here, we developed a stringent method for de novo identification of RXLRs and characterized 359 putative RXLR effectors from nine tested Pythium species. Phylogenetic analysis revealed a single superfamily formed by all oomycetous RXLRs, suggesting they descent from a common ancestor. RXLR effectors from Pythium and Phytophthora species exhibited similar sequence features, protein structures and genome locations. In particular, the mosquito biological agent P. guiyangense contains a significantly larger RXLR repertoire than the other eight Pythium species examined, which may result from gene duplication and genome rearrangement events as indicated by synteny analysis. Expression pattern analysis of RXLR-encoding genes in the plant pathogen P. ultimum detected transcripts from the vast majority of predicted RXLRs with some of them being induced at infection stages. One such RXLRs showed necrosis-inducing activity. Furthermore, all predicted RXLRs were cloned from two biocontrol agents P. oligandrum and P. periplocum. Three of them were found to encode effectors inducing defense response in Nicotiana benthamiana. Taken together, our findings represent the first complete synopsis of Pythium RXLR effectors, which provides critical clues on their evolutionary patterns as well as the mechanisms of their interactions with diverse hosts.Author summaryPathogens from the Pythium genus are widespread across multiple ecological niches. Most of them are soilborne plant pathogens whereas others cause infectious diseases in mammals. Some Pythium species can be used as biocontrol agents for plant diseases or mosquito management. Despite that phylogenetically close oomycete pathogens secrete RXLR effectors to enable infection, no RXLR protein was previously characterized in any Pythium species. Here we developed a stringent method to predict Pythium RXLR effectors and compared them with known RXLRs from other species. All oomycetous RXLRs form a huge superfamily, which indicates they may share a common ancestor. Our sequence analysis results suggest that the expansion of RXLR repertoire results from gene duplication and genome recombination events. We further demonstrated that most predicted Pythium RXLRs can be transcribed and some of them encode effectors exhibiting pathogenic or defense-inducing activities. This work expands our understanding of RXLR evolution in oomycetes in general, and provides novel insights into the molecular interactions between Pythium pathogens and their diverse hosts.

Owing to the climate change, it is expected that the frequency and severity of extreme weather will increase in the future. In order to avoid large-scale blackouts resulting from such events, it is important to take measures to enhance the distribution system resilience. This paper proposes an approach for enhancing the distribution system resilience to extreme weather using multi-energy coordination. First, a four-part resilience analysis framework is constructed as the basis for assessing the distribution system resilience and the effectiveness of resilience enhancement measures. Then, the distribution system resilience enhancement is achieved through conversion of gas to electricity and coordination of multi-energy demands. An optimal load-shedding model is employed during the response process to minimize the load losses in distribution system after fault, where the dynamic characteristic of gas system is considered. Simulation results show the validity of the proposed approach in resilience enhancement.

DC distribution systems, which can improve the accommodation of renewable energy sources and DC loads, have developed rapidly, leading to the appearance of hybrid AC/DC distribution systems. This paper proposes an optimal day-ahead scheduling model to increase the economy of the system operation considering the high penetration and uncertainty of the distributed generations. The proposed model aims to minimize the active power loss and electricity purchasing cost by coordinating active or reactive power outputs of voltage source converter (VSC), energy storage system (ESS) and static var compensation (SVC), as well as the voltage regulation capability of OLTC. Besides, the load model has been carefully analysed to implement conservation voltage reduction (CVR). In addition, VSC is detailed modelled to capture the coupling between active power and reactive power. Moreover, the second-order cone programming (SOCP) is used in this paper to transform the mixed integer nonlinear programming problem to a convex optimization one, which shortens the solving time. The IEEE 33-bus test system is employed to demonstrate the effectiveness and efficiency of the proposed method.

With the rapid development of integrated energy system (IES), there is an urgent need to implement state estimation to obtain accurate system-wide states for online analysis and optimal dispatch. Moreover, compared with the centralized scheme, distributed state estimation is more practical for IES due to the preservation of privacy, low communication burden, and high efficiency. This paper proposes a distributed bilinear state estimation algorithm based on the alternating direction method of multipliers (ADMM), which is applicable to IES combining electricity, heat, and gas. Based on the bilinear state estimation model, the conventional state estimation for IES is converted to a three-stage convex problem, including two linear estimation stages and an intermediate nonlinear transformation stage. Each of the three stages is further decoupled over the three sub-systems to perform a fully distributed state estimation via ADMM. A modified ADMM with self-adjusting penalty parameter is adopted to accelerate the convergence of ADMM iterations. Simulation results demonstrate the validity of the proposed algorithm.

Perovskite crystal quality plays an important role in perovskite solar cells, given that multiple grain boundaries and trap states in the perovskite films hamper further enhancement of solar cell efficiency. Using the solution method to prepare perovskite films with large grains and high coverage requires further improvements. Herein, we introduce Lewis base urea as an additive into the precursor of perovskite to control the crystallization dynamics, allowing for large-grain crystal growth. As a result, MAPbI3 films with urea as an additive are well crystallized with large crystal grains of sizes >3 μm. The large-grain perovskite is found to simultaneously improve the power-conversion efficiency (PCE) and device stability. With an optimal urea additive of 20 mol%, the PCE is significantly increased from 15.47% for the reference MAPbI3 solar cell to 18.53% for the device with MAPbI3 with urea as an additive. Finally, the optimized device demonstrates excellent stability and maintains 80% of the initial PCE after 60 days.

Increasingly frequent extreme weather events cause power outages in active distribution systems. Islanding and fault reconfiguration are effective approaches to service restoration and resilience enhancement. This paper proposes a multi-stage switch strategy based on dynamic programming (DP), considering both islanding and fault reconfiguration. First, numerous expected fault scenarios are constructed based on meteorological forecast and vulnerability analysis of system components, from which typical ones are selected by their information entropy. Second, for each typical scenario, a multi-stage switch strategy considering both islanding and fault reconfiguration is developed through DP. The objective is to make a tradeoff between minimizing total power shortage and minimizing the number of switching operations over the whole event's duration. The constraints comprise power flow limits, nodal voltage limits, and distributed generators’ capabilities. Finally, a risk-based resilience assessment is performed and the resilience improvement is presented. Tests on the IEEE 33-bus distribution system demonstrate the effectiveness of the proposed method.

Due to the large scale and three-phase unbalance problem of active distribution networks (ADNs), traditional centralized state estimation (CSE) cannot meet the requirements on estimation accuracy and efficiency for real-time analysis and control of distribution systems. This paper presents a novel consensus-based coordination distributed state estimation (CC-DSE) approach considering communication failures in ADNs. A network partition approach coupled with placement of phasor measurement units (PMUs), which is based on topology analysis, is firstly executed to divide the large-scale distribution network into several sub-regions. Then, the local state estimation (SE) of each sub-region is executed in parallel by improved weighted least squares (WLS) method with revising weights adaptive to residuals without changing the initial objective function, which can mitigate the negative effect of inner-region communication failures. The data coordination is embedded in the iteration of improved WLS of each sub-region estimation by consensus algorithm, which is robust to data missing and bad data caused by inter-region communication failures. The CC-DSE has better performance in accuracy, efficiency and robustness compared with CSE and distributed state estimation (DSE), which is demonstrated by the simulation results of the unbalanced IEEE 123 bus distribution network.

The early phase of extremity rehabilitation training has high potential impact for stroke patients. However, most of the lower limb rehabilitation robots in hospitals are proposed just suitable for patients at the middle or later recovery stage. This article investigates a new sitting/lying multi-joint lower limb rehabilitation robot. It can be used at all recovery stages, including the initial stage. Based on man–machine engineering and the innovative design for mechanism, the leg length of the lower limb rehabilitation robot is automatically adjusted to fit patients with different heights. The lower limb rehabilitation robot is a typical human–machine system, and the limb safety of the patient is the most important principle to be considered in its design. The hip joint rotation ranges are different in people’s sitting and lying postures. Different training postures cannot make the training workspace unique. Besides the leg lengths and joint rotation angles varied with different patients, the idea of variable workspace of the lower limb rehabilitation robot is first proposed. Based on the variable workspace, three trajectory planning methods are developed. In order to verify the trajectory planning methods, an experimental study has been conducted. Theoretical and actual curves of the hip rotation, knee rotation, and leg mechanism end point motion trajectories are obtained for three unimpaired subjects. Most importantly, a clinical trial demonstrated the safety and feasibility of the proposed lower limb rehabilitation robot.

The purpose of poverty declaration and evaluation of university students is to help the poor students to overcome economic difficulties, and to provide security for their normal life and learning. In this paper, we use the fuzzy comprehensive evaluation method to build a poverty evaluation model of university students. We combine the actual situation and questionnaire of a real university firstly, and divide the evaluation system into a number of indicators according to real need, and then establish the factor set, evaluation set and weights set. We also use analytic hierarchy process (AHP) to calculate the weights set. The applied experiment in SPSS indicates our method in the research is feasible and effective, and it can be used widely in poverty evaluation of university students.