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AbstractHigh-belite sulfoaluminate cement (HBSC), with low carbon dioxide emissions, can be used to repair old concrete. Calcium sulfate plays a significant role in hydration of ye’elimite, but a comprehensive study of the effects of the four different types and dosages of calcium sulfate on the hydration of HBSC is lacking. This study investigates the influence of different types (dihydrate, anhydrite, α-hemihydrate, and β-hemihydrate) and doses (2%, 4%, 6%, and 8%) of calcium sulfate on the hydration process and mechanical properties of HBSC. The findings indicate that the addition of calcium sulfate, specifically β-hemihydrate, had a significant impact on the reduction of setting times. The compressive strength of HBSC, particularly early strength, can be significantly increased by varying calcium sulfate dose and type, enhancing the performance of repair materials. The microstructure of ettringite is altered by different types of calcium sulfate, leading to varying pore structures and volume expansions.

This paper presents a human-like motion decision-making method for unmanned aerial vehicles (UAVs) navigating in trap environments. We proposed a space partitioning method based on sampling and consistency control to conduct a preliminary analysis of the indoor environment based on architectural blueprints. This method reduces the dimensionality of the path planning problem, thereby enhancing the efficiency. Then, we designed a target-switching logic for the dynamic window approach. This improvement endows the UAV with the capability of both real-time obstacle avoidance and global navigation, enhancing the efficiency of the UAV in flying to task spots indoors. Additionally, by applying human-like methods of batch distance perception and obstacle perception to this scheme, we have further enhanced the robustness and efficiency of path decisions. Finally, considering the scenario of high-rise fire rescue, we conducted simulation verification. It demonstrates that our scheme enhances the efficiency and robustness of path planning.

High-rate batteries will play a vital role in future energy storage systems, yet while good progress is being made in the development of high-rate lithium-ion batteries, there is less progress with post-lithium-ion chemistry. In this study, we demonstrate that pseudohexagonal Nb2O5(TT-Nb2O5) can offer a high specific capacity (179 mAh g–1∼ 0.3C), good lifetime, and an excellent rate performance (72 mAh g–1at ∼15C) in potassium-ion batteries (KIBs), when it is composited with a highly conductive carbon framework; this is the first reported investigation of TT-Nb2O5for KIBs. Specifically, multiwalled carbon nanotubes are strongly tethered to Nb2O5via glucose-derived carbon (Nb2O5@CNT) by a one-step hydrothermal method, which results in highly conductive and porous needle-like structures. This work therefore offers a route for the scalable production of a viable KIB anode material and hence improves the feasibility of fast-charging KIBs for future applications.

Thermophotovoltaic (TPV) generators provide continuous and high-efficiency power output by utilizing local thermal emitters to convert energy from various sources to thermal radiation matching the bandgaps of photovoltaic cells. Lack of effective guidelines for thermal emission control at high temperatures, poor thermal stability, and limited fabrication scalability are the three key challenges for the practical deployment of TPV devices. Here we develop a hierarchical sequential-learning optimization framework and experimentally realize a 6″ module-scale polaritonic thermal emitter with bandwidth-controlled thermal emission as well as excellent thermal stability at 1473 K. The 300 nm bandwidth thermal emission is realized by a complex photon polariton based on the superposition of Tamm plasmon polariton and surface plasmon polariton. We experimentally achieve a spectral efficiency of 65.6% (wavelength range of 0.4–8 μm) with statistical deviation less than 4% over the 6″ emitter, demonstrating industrial-level reliability for module-scale TPV applications.

The development and application scope of the Internet of Things is also becoming more and more extensive. Especially in the application of power testing improved systems, great progress has been made. This article aims to study how to analyze the system detection equipment based on the Internet of Things. This article describes the basic theoretical knowledge of the Internet of Things and power detection improved systems. A clustering analysis algorithm and a support vector machine algorithm based on the Internet of Things are proposed. In the experiment of this article, the scoring items of the expert’s traditional detection system include complex technology, inconvenient use, and incomplete intelligence. Among them, the highest score for complex technology is 8.6 points, the lowest score is 7 points; the highest score for inconvenience is 8.6 points, and the lowest is 8.3 points. It can be seen that related experts believe that the traditional power detection improved system is not only very complicated in technology, very inconvenient to use but also incompletely intelligent. Therefore, it is very necessary to study the system detection equipment based on the Internet of Things.

Long-distance measurement of lidar is a critical problem in various fields, such as airborne lidar detection, surveying, and mapping. Attenuation characteristic is the key factor affecting the lidar detection capability. However, some long-distance measurement methods based on the widely used and validated theoretical models are usually inefficient, while others relying on empirical models have limited applications due to experimental difficulties. This study proposes a semi-empirical model of long-distance measurement based on the Beer–Lambert–Bouguer law adopting mathematical methods. Compared to the theoretical model, the calculation efficiency of the semi-empirical model we constructed has been improved by more than two orders of magnitude, and the accuracy can reach more than 98% of the theoretical model. Compared to other empirical models, its accuracy is closer to the theoretical model, and the computational efficiency is similar. It can be more effectively applied to the actual long-distance detection scene.

The energy storage or management system is becoming more important as electrical energy demand globally grows. In the first step of the energy management plan, energy forecasting is an essential element. Software-defined network (SDN) seeks to change network architecture and processes to be agile and effectively enhance the functionality of fundamental system components such as switches and routers. Predicting electric energy is crucial to support demand-side management in the building business. The total power load of the individual building services systems management is becoming a challenging process to be predicted for buildings with electricity metering systems. Conventional model energy prediction focuses on predictive accuracy, and energy consumption must be predicted according to different conditions to build an efficient system. Novel deep learning-based smart energy metering prediction (DL-SEMP) technique is considered to overthrow such accuracy lack in prediction. Blockchain-based SDN has emerged a new architect for obtaining a distributed network in blockchain technology.

Mosquitoes are the most important vectors carrying significant numbers of human pathogens. Recent studies implicated that mosquitoes play an important role in circulation and transmission of multiple Rickettsiaspecies. In this study, Rickettsia belliiwas identified in four mosquito species (Culex pipiens, C. tritaeniorhynchus, Aedes albopictus, and Anopheles sinensis) collected from three Eastern China provinces during 2019–2020. Rickettsia belliiwas detected in 37.50 and 26.32% of the C. pipienspools from Beijing and Jiangsu province, respectively. In C. tritaeniorhynchusand An. sinensisfrom Shandong, the infection rate is 20.00 and 6.25%, respectively. Additionally, three Ae. albopictuspools (3/42, 7.14%) from Beijing were also detected positive for R. bellii. Genetic and phylogenetic analysis on 16S, gltA, and groELgenes indicates that sequences from all these strains are highly homologous and closely related to other R. belliistrains. This is the first report that Ae. albopictusand C. tritaeniorhynchusharbor R. bellii. The wide host range and high infection rate in certain areas may dramatically increase the exposure of R. belliito human and other vertebrates. The role of mosquitoes in transmission of rickettsiosis and its potential risk to public health should be further considered.

The laminar premixed n-propylamine (NPA) flame with equivalence ratio of 1.70 has been investigated at 4666.28 Pa using tunable synchrotron photoionization and molecular-beam mass spectrometry techniques. Chemical structures and mole fractions of 40 species were determined. Ethenol, allylamine, butadiyne, vinylacetylene, 1,3-butadiene, 1-butene, 2-butene, n-butyl radical, 1,3-cyclopentadiene, cyclopentene, 2-pentene, benzene, toluene, ethylbenzene, 2-propen-1-imine, cyclopropanimine, pyrrole, 2-butenenitrile and n-butylamine were newly identified in the amine flames. Mole fraction profiles of some species including reactants, intermediates and products in the NPA flame were given. HCN and N2were observed as the primary N-containing products in the NPA flame, which was different from the result that NO was the major N-containing products in previous studies of nitrogen flames. The bond energies of NPA were calculated through quantum chemistry calculations on the basis of density functional theory at the CBS-QB3 level. It showed that the CH3CH2-CH2NH2bond was the weakest and NPA mainly decomposed to CH2NH2and C2H5radicals. The H-abstractions at Cαby OH/O (NPA+OH=CH3CH2CHNH2+H2O and NPA+O=CH3CH2CHNH2+OH) had significant promoting effects on NPA consumption. The N conversion chain of NPA under flame conditions was proposed and detailed analysis with respect to intermediates especially the nitrogen-containing species were provided. The results will enrich the understanding of NPA flame and are essential to further establish the kinetic mechanism.

The poor clinical prognosis and microvascular patterns of glioblastoma (GBM) are of serious concern to many clinicians and researchers. However, very few studies have examined the correlation between microvascular niche patterns (MVNPs) and proteomic distribution. In this study, CD34 immunofluorescence staining and matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-IMS) technology were used to investigate the protein distributions in MVNPs. CD34+ microvascular phenotype could be divided into four types: microvascular sprouting (MS), vascular cluster (VC), vascular garland (VG), and glomeruloid vascular proliferation (GVP). Based on such characteristics, MVNPs were divided into two types by cluster analysis, namely, type I, comprising primarily MS and VC, and type II, comprising many VGs and GVPs. Survival analysis indicated the type of MVNPs to be an independent prognostic factor for progression-free and overall survival in GBM. MALDI-IMS results showed the peaks at m/z 1037 and 8960 to exhibit stronger ion signals in type II, while those at m/z 3240 and 3265 exhibited stronger ion signals in type I. The findings may assist future research on therapy and help predict prognosis in GBM. However, due to the limited number of studies, more well-designed studies are warranted to further verify our results.

A service ecosystem is an increasingly popular service organization form, where participants, services, data, resources, and capital of different domains are integrated. It can empower business systems to consider the exchanged values and creations in a certain context. How to manage the participants’ cooperation and arrange the elements in the service ecosystem, namely service pattern, have become an important factor to influence the competitiveness of enterprises. However, at present, most of the relevant researches stay in the description of business model and qualitative analysis stage. The design and application of service pattern is still blind and risky. In this article, a service pattern-oriented computing architecture is proposed. It can systematically design and innovate new service patterns and comprehensively assess and simulate them.

Organic–inorganic hybrid metal halide perovskite solar cells have been considered as one of the most promising next-generation photovoltaic technologies. Nevertheless, perovskite defects and Li+ionic migration will seriously affect the power conversion efficiency and stability of the formal device. Herein, we designed two crown ether derivatives (PC12 and PC15) with different cavity diameters, which selectively bind to different metal cations. It is found that PC15 in perovskite precursor solution can actively regulate the nucleation and crystallization processes and passivate the uncoordinated Pb2+ions, while PC12 at the interface between the perovskite layer and hole-transporting layer can effectively inhibit the migration of Li+ions and reduce nonradiative recombination losses. Therefore, PC12 and PC15 can act as “lubricant” and defect passivators, as well as inhibitors of ion migration, when they are synergistically applied at the surface and bulk of perovskite layer. Consequently, the optimized device achieved a champion efficiency of 24.8% with significantly improved humidity, thermal, and light stability.

To address the situation that the degraded system cannot be repaired as new and the degradation is accelerated after repair in engineering practice, an imperfect condition-based maintenance model is proposed based on the Gamma process by introducing the maintenance improvement factor and the accelerated degradation factor. The maintenance improvement factor describes the recovery degree of the degradation amount after imperfect maintenance, then gives a quantitative representation method of the system maintenance improvement effect and the determination method of the maximum number of imperfect maintenance. The accelerated degradation factor is combined with the geometric process to describe the accelerated degradation process of the system after imperfect maintenance. The Monte Carlo method is used to determine the optimal number of imperfect preventive maintenance decisions. Through the demonstration of calculation examples, the influence of accelerated degradation factor and maintenance improvement factor on the long-term operation maintenance rate and the optimal number of imperfect maintenance is analyzed. The results show that the model can more comprehensively describe the degradation and maintenance process of degraded systems, and it can effectively reduce maintenance cost ratio under long-term operation. It provides a certain theoretical support for formulating an economical and reasonable maintenance strategy that is more in line with the actual degradation and maintenance process in engineering practice.

As inorganic rigid waterproof materials with excellent substrate compatibility, non-toxicity, harmless, and deep penetration depth, cementitious capillary crystalline waterproof materials (CCCW) hold great potential for application in concrete structures. However, the formulations of commercially available CCCW are currently undisclosed, hindering the mechanism study of CCCW, which is not conducive to the development of more efficient and cost-effective CCCW materials. In this study, a new formulation of CCCW active chemicals was developed, consisting of calcium carbonate, sodium silicate, glycine, EDTA-4Na, and sodium acetate. The effectiveness of sodium acetate as a high-quality impermeable admixture to CCCW was explored to enhance the impermeability of the substrate. Subsequently, the fundamental performance of the coatings was subjected to further examination. After application of the coating, the impermeability and strength of the substrate were enhanced, and the fist impermeability strength reached 1.5MPa. Micro characteristics testing indicated that the coated sample had a denser microstructure, resulting in an increase of calcium carbonate crystals and hydrated calcium silicate in the pores. The harmful pores (100-3000nm) were transformed into less harmful or harmless pores (< 100nm). The durability tests indicated a 12.37% drop in carbonation area over 14 days, with an approximately 30% drop in the Coulomb electric flux of chloride ions.

Aqueous zinc-ion batteries (AZIBs) have the potential to be utilized in a grid-scale energy storage system owing to their high energy density and cost-effective properties. However, the dissolution of cathode materials and the irreversible extraction of preintercalated metal ions in the electrode materials restrict the stability of AZIBs. Herein, a cathode-stabilized ZIB strategy is reported based on a natural biomass polymer sodium alginate as the electrolyte coupling with a Na+preintercalated δ-Na0.65Mn2O4·1.31H2O cathode. The dissociated Na+in alginate after gelation directly stabilizes the cathodes by preventing the collapse of layered structures during charge processes. The as-fabricated ZIBs deliver a high capacity of 305 mA h g–1at 0.1 A g–1, 10% higher than the ZIBs with an aqueous electrolyte. Further, the hybrid polymer electrolyte possessed an excellent Coulombic efficiency above 99% and a capacity retention of 96% within 1000 cycles at 2 A g–1. A detailed investigation combining ex situexperiments uncovers the charge storage mechanism and the stability of assembled batteries, confirming the reversible diffusions of both Zn2+and preintercalated Na+. A flexible device of ZIBs fabricated based on vacuum-assisted resin transfer molding possesses an outstanding performance of 160 mA h g–1at 1 A g–1, which illustrates their potential for wearable electronics in mass production.

Ovonic threshold switching in chalcogenide glasses is a crucial physical phenomenon behind state-of-the-art memory chip technologies. Binary tellurides are one of the emerging candidates that deliver excellent properties, notably the large driving current and fast accessing speed, for volatile selector applications; however, the underlying switching mechanism remains poorly understood. To tackle this issue, we targeted the prototypical boron tellurides, further elevating the selector performances. Via ab initio simulating the electronic excitation process in the amorphous boron tellurides, we observed reversible semiconductor-metal transitions that can reflect the switching principles of the selectors. The transient switching in conductance originates from fine structural tunings, namely, the changes of constraint surrounding the big boron clusters and conversions between covalent and hypervalent bonding schemes throughout the entire tellurium network. Our work provides much-needed atomistic insight into the ovonic threshold switching mechanisms that may enlighten the material design to enable superior selector devices.

The chemical kinetics of hydrogen atom (H-atom) abstraction reactions from norbornadiene (NBD) by five radicals (H, O(3P), OH, CH3, and HO2), and the unimolecular reactions of three NBD derived radicals, were studied through high-level ab-initio calculations. The geometries optimization and vibrational frequencies calculation for all the reactants, transition states, products were obtained at the M06-2X/6-311++G(d,p) level of theory. The zero-point energy (ZPE) corrected potential energy surfaces (PESs) were determined at the QCISD(T)/cc-pVDZ, TZ level of theory with basis set corrections from MP2/cc-pVDZ, TZ, QZ methods for single point energy calculations. Conventional transition state theory (TST) was used for the rate constants calculations of H-atom abstraction reactions by five radicals (H, O(3P), OH, CH3, and HO2) at temperatures from 298.15 to 2000 K, while the α-site H-atom abstraction reaction rate constant of NBD by OH radical has been obtained through variational transition state theory (VTST). The results show that the H-atom abstraction reaction from the α-carbon atom of NBD are the most critical channels at low temperatures. Total rate constants for H-atom abstraction reactions by OH radical are also the fastest among all of the reaction channels investigated at the temperature range from 298.15 to 2000 K. Rice-Ramsperger-Kassel-Marcus/Master Equation (RRKM/ME) has been used to calculate the pressure- and temperature-dependent rate constants for the unimolecular reactions of three related C7H7product radicals which generated from H-atom abstraction reaction within temperature ranges of 300 to 2000 K and pressures of 0.01 to 100 atm. A combination of composite methods has been used to calculate the temperature-dependent thermochemical properties for NBD and related radicals. All the calculated kinetics and thermochemistry data can be utilized in the model development for NBD oxidation.

Rhipicephalus microplusis considered to be the most important tick infesting cattle, buffalo, horse, goats as well as other animals. They transmit diseases between domestic animals and act as vectors of a variety of zoonotic pathogens. Although pathogens harbored by R. microplushave been extensively studied, the Rickettsiales pathogens vectored by R. microplusin some areas of China remained largely unexplored. From August to October 2020, a total of 291 R. microplusticks were collected from goats and cattle in three Southern China provinces, Guangxi (n = 138), Sichuan (n = 120) and Hubei (n = 33) provinces. Phylogenetic analysis based on COI gene sequences shows that these ticks are divided into three distinct clades, indicating the remarkable genetic diversity of R. microplusticks in China. These samples were subsequently screened for the presence of Rickettsia, Anaplasmaand Ehrlichiausing conventional PCR and sequencing. Subsequently, five bacterial species were identified. Out of the 120 tick DNA samples from Sichuan province, 35.83% (43/120) were positive for Rickettsiasp. belonging to spotted fever group (SFG), 12.50% (15/120) were positive for Anaplasma marginaleand 0.83% (1/120) was identified as A. platys. From the 138 DNA samples from Guangxi province, an Ehrlichia canis-like and Rickettsiasp. were detected, with a positive rate of 11.59% (16/138) and 2.17% (3/138), respectively. A. capraDNA was detected in 4 out of 33 (12.12%) samples from Hubei province. Notably, the 16S, gltAand groELsequences of the E. canis-like are closely related to the E. canisstrain previously identified from China, and form a distinct cluster in the phylogenetic trees. Collectively, our results expand the knowledge on tick-borne Rickettsiales pathogens in China. Because the state of engorgement of ticks was not recorded, it is not clear at this stage whether these pathogens are infecting the ticks or are simply present in the blood meal. Given the public health significance of SFG Rickettsia, A. capra, A. platysand E. canis, a thorough investigation of the diversity and presence of pathogens in R. microplusin areas with tick-associated diseases are needed.

•A BTMS with PCM coupled cooling plate arrayed in honeycomb manner is proposed.•The temperature distribution of the battery pack has good uniformity.•The coupling of PCM and cooling plate greatly improve the heat dissipation effect.•Influence of cooling plate channel number on heat dissipation efficiency is low.

Proteins from U1 and U2 small nuclear ribonucleoprotein (snRNP) particles, which are common targets of autoantibodies found in some rheumatic diseases, were analysed for the presence of glycans. A glycan detection assay revealed that the U1-specific proteins 68K and A and the U2-specific protein B" are glycosylated. However, none of the Sm proteins, which are common to all the major snRNP particles, showed a detectable level of glycosylation. With the use of specific lectins, an analysis of the particular carbohydrate(s) attached to the U1 snRNP 68K protein demonstrated the presence of at least one N-linked oligosaccharide chain. Lectin detection of galactose, glucose, mannose and N-acetylglucosamine on 68K was confirmed by chemical analysis of the carbohydrates. The glycopeptide nature of these antigens may be important for understanding the role of autoantigens in the pathogenesis of autoimmune disorder.

Cross reactivity of patient lupus autoantibodies to the small nuclear ribonucleoprotein particles of many different types of animals is well documented. The aim of our research was to determine if any level of cross reactivity existed between proteins of common dietary plants and anti-Sm autoantibodies of lupus patient's sera, as has been found for scleroderma patient sera (Agris et al., Exptl. Cell Res. 189, 276-279, 1990). Protein extracts from soy bean, corn, spinach, and carrot were analyzed. At least one protein (molecular weight approximately 28,000 daltons) common to all the above protein extracts was recognized by most of the anti-Sm sera tested. Affinity purified antibody eluted from the 28 kilodalton plant protein specifically recognized the Sm proteins of a HeLa cell protein extract. Recognition of the 28 kilodalton dietary plant protein was found to be unique to anti-Sm lupus sera.

The spatial organization of two rheumatic disease-associated epitopes and the RNA "cap" structure of the U1 small nuclear ribonucleoprotein (snRNP2) was analyzed both in situ and in vitro by two independent interference immuno-assays. Sm and RNP autoantibodies, associated with systemic lupus erythematosus and mixed connective tissue disease, respectively, were used to probe the epitope locations. The Sm epitope on the U1 snRNP structure was localized proximal to the RNP. Experiments with an anti-m7G (mRNA "cap") monoclonal antibody revealed that an in situ association of the Sm and RNP epitopes with the mRNA "cap" structure may exist. Our findings, together with previous observations by others, suggest a model for the spatial arrangement of these rheumatic disease-associated protein epitopes, and the U1 RNA within the U1 snRNP particle.

In order to enable the smart energy meter to conduct trade settlement work in a normal and stable manner, in order to ensure the interests of both power users and power companies, the impact of power carrier communication on smart energy meters is studied. Through the carrier communication impact test of various bandwidth, frequency and intensity, it analyzes whether it has influence on the metering function, timing function, storage function and carrier communication function of the intelligent electric energy meter. The test analysis of the system provides data support for the in-depth study of the energy meter detection method and the operating environment.