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Traditional virtual simulated interaction systems experience data fragmentation during the process of converting from two-dimensional to three-dimensional information, resulting in reduced realism and an inability to meet the teaching requirements of computer courses. Therefore, the integration of augmented reality (AR) technology into the educational environment remains an urgent and unresolved issue. To address the aforementioned issues, this paper investigates the data throughput limitations present in virtual simulation interaction systems. In response to this problem, an application solution utilizing AR technology is proposed, specifically a design concept for a virtual simulation interactive system tailored to computer-related courses. This system achieves its objectives through the collaborative interaction of AR hardware and supplementary software algorithms. The AR hardware is subdivided into framework design and functional hardware design, while the software components encompass AR models, virtual interaction models, and fusion methods. Through testing and comparison of the data throughput of this system with two other virtual simulation interaction systems, it was found that the virtual simulation interactive system optimized using AR technology can effectively enhance data throughput and address the issue of reduced realism in virtual interaction scenes caused by data fragmentation. This design system provides a more realistic and efficient mode of interaction for teaching computer-related courses. [ABSTRACT FROM AUTHOR]

In order to improve the application of teaching resources and reduce delays in the integration process of multimedia network, a rational resource allocation method for multimedia network teaching reform based on Bayesian partition data mining is proposed. Bayesian partition is used to preprocess the multimedia network teaching resources (MNTR), adjusting the recognition probability of MNTR in each partition based on its attributes. By performing Bayesian quantitative classification using samples of MNTR, the prior probability is adjusted through maximization analysis. The partitioned resources undergo sample data mining to obtain the data category collection of all MNTR. A prediction model is then built to forecast the demand for teaching resources at specific times in the future. MNTR can be rationally allocated based on the prediction results. Experimental results demonstrate that this method reduces delays in MNTR application and improves the accuracy and utilization of teaching resources. [ABSTRACT FROM AUTHOR]

Alumina supported Pt nanoclusters under a hydrogen environment play a crucial role in many heterogeneous catalysis applications. We conducted grand canonical genetic algorithm simulations for supported Pt8 clusters in a hydrogen gas environment to study the intracluster, cluster-support, and cluster-adsorbate interactions. Two alumina surfaces, α-Al2O3(0001) and γ-Al2O3(100), and two conditions, T = 600 °C, p H 2 = 0.1 bar and T = 25 °C, p H 2 = 1.0 bar, were considered corresponding to low and high hydrogen chemical potential μH, respectively. The low free energy ensemble of Pt8 is decorated by a medium (2–12 H), respectively, high (20–30 H), number of hydrogen atoms under equilibrium at low μH, respectively, high μH, and undergoes different morphological transformations on the two surfaces. On α-Al2O3(0001), Pt8 is mostly 3D but very fluxional in structure at low μH and converts to open one-layer 2D structures with minimal fluxionality at high μH, whereas on γ-Al2O3(100), the exact opposite occurs: Pt8 clusters present one-layer 2D shapes at low μH and switch to compact 3D shapes under high μH, during which the Pt8 cluster preserves moderate fluxionality. Further analysis reveals a similar Pt–Pt bond length increase when switching from low μH to high μH on both surfaces although morphological transformations are different. Electronic structure analysis shows the existence of bonding interactions between Pt and Lewis acidic Al3+ sites along with the Pt–O interaction, which implies the necessity to include Al neighbors to discuss the electronic structure of small Pt clusters. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) is a promising communication platform to assist terrestrial networks. In this work, we aim to provide relay communication to the blocked or low-quality terrestrial networks via an aerial relay. Nevertheless, major issues of the considered system are the worrying security and limited service time. Thus, we study a novel aerial relay system via collaborative beamforming (CB) by exploiting a UAV-enabled virtual antenna array (UVAA) to achieve a secure and energy-efficient communication for remote ground users (GUs). Specifically, we formulate a secure and energy-efficient communication multi-objective optimization problem (SECMOP) to circumvent the effects of the known and unknown eavesdroppers and minimize the propulsion energy consumption of UAVs, by optimizing the hovering positions and excitation current weights of UAVs and the scheduling for communicating with the remote GUs. The formulated SECMOP is challenging and proven to be NP-hard. Thus, we propose an improved evolutionary computation method with several enhanced designs to solve this problem. Simulation results demonstrate the benefits of the proposed IMODAOM against various benchmark algorithms. Moreover, we find that the UVAA-based relay can achieve substantial energy consumption reduction as compared to the multi-hop relay scheme. [ABSTRACT FROM AUTHOR]

Single‐atom catalysts (SACs) have become a prominent theme in heterogeneous catalysis, not least because of the potential fundamental insight into active sites. The desired level of understanding, however, is prohibited due to the inhomogeneity of most supported SACs and the lack of suitable tools for structure–activity correlation studies with atomic resolution. Herein, we describe the potency of electrospray ionization mass spectrometry (ESI‐MS) to study molecularly defined SACs supported on polyoxometalates in catalytic reactions. We identified the exact composition of active sites and their evolution in the catalytic cycle during CO and alcohol oxidation reactions performed in the liquid phase. Critical information on metal‐dependent reaction mechanisms, the key intermediates, the dynamics of active sites and even the stepwise activation barriers were obtained, which would be challenging to gather via prevailingly adopted techniques in SAC research. DFT calculations revealed intricate details of the reaction mechanisms, and strong synergies between ESI‐MS defined SAC sites and electronic structure theory calculations become apparent. [ABSTRACT FROM AUTHOR]

Single‐atom catalysts (SACs) have become a prominent theme in heterogeneous catalysis, not least because of the potential fundamental insight into active sites. The desired level of understanding, however, is prohibited due to the inhomogeneity of most supported SACs and the lack of suitable tools for structure–activity correlation studies with atomic resolution. Herein, we describe the potency of electrospray ionization mass spectrometry (ESI‐MS) to study molecularly defined SACs supported on polyoxometalates in catalytic reactions. We identified the exact composition of active sites and their evolution in the catalytic cycle during CO and alcohol oxidation reactions performed in the liquid phase. Critical information on metal‐dependent reaction mechanisms, the key intermediates, the dynamics of active sites and even the stepwise activation barriers were obtained, which would be challenging to gather via prevailingly adopted techniques in SAC research. DFT calculations revealed intricate details of the reaction mechanisms, and strong synergies between ESI‐MS defined SAC sites and electronic structure theory calculations become apparent. [ABSTRACT FROM AUTHOR]

Improving both the quantity and quality of existing data are placed at the center of research for adaptive micro open learning. To cover this research gap, our work targets on the current scarcity of both data and rules that represent open learning activities. An evolutionary rule generator is constructed, which consists of an outer loop and an inner loop. The outer loop runs a genetic algorithm (GA) to produce association rules that can be effective in the micro open learning scenario from a small amount of available data sources; while the inner loop optimizes generated candidates by taking into account both rare and negative association rules (NARs). These optimized rules are further applied in refining and augmenting data denoting learners' behaviors in open learning into a low‐dimensional, descriptive and interpretable form. The performance of rule discovery and data processing have been empirically evaluated using genuine open learning data. [ABSTRACT FROM AUTHOR]

The soaring development of Web technologies and mobile devices has blurred time-space boundaries of people's daily activities. Such development together with the life-long learning requirement give birth to a new learning style, micro learning. Micro learning aims to effectively utilize learners' fragmented time to carry out personalized learning activities through online education resources. The whole workflow of a micro learning system can be separated into three processing stages: micro learning material generation, learning materials annotation and personalized learning materials delivery. Our micro learning framework is firstly introduced in this paper from a higher perspective. Then we will review representative segmentation and annotation strategies in the e-learning domain. As the core part of the micro learning service, we further investigate several the state-of-the-art recommendation strategies, such as soft computing, transfer learning, reinforcement learning, and context-aware techniques. From a research contribution perspective, this paper serves as a basis to depict and understand the challenges in the data sources and data mining for the research of micro learning. [ABSTRACT FROM AUTHOR]

Dispersing liquid metal droplets in a soft elastomer matrix yields a composite, called liquid metal embedded elastomer (LMEE), with less modified stiffness but noticeably increased relative permittivity. Stretching and applying voltage through the thickness of the elastomer composite directly, it is vulnerable to the loss of being an insulator due to the conductive pathway formed during prestretching. Here, we describe a very simple sandwich structure that enables electromechanical actuation of LMEE. It consists of two very high bonding tapes as skins and a layer of LMEE as the core, making the sandwich all polymeric and thus stretchable. The electromechanical performance of a LMEE made of Ecoflex and Galinstan at various mass ratios was systematically measured. For a typical circular actuation made of the sandwich structure, a 90% areal actuation strain was achieved. Our efforts pave the way for various applications of LMEE. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of different long-term (36 years) fertilizer treatments on soil pH, exchangeable acids, exchangeable base cation and cation exchange capacity (CEC) at 0–10 cm and 10–20 cm soil layers in a double-cropping rice field. The following fertilizer treatments were included: chemical fertilizer (MF), rice straw and chemical fertilizer (RF), 30% organic manure and 70% chemical fertilizer (OM), and without any fertilizer input as a control (CK). This result indicated that soil pH at 0–10 cm layer with RF and OM treatments was higher than that of MF and CK treatments. Soil exchangeable acidity content at 0–10 cm and 10–20 cm layers with RF and OM treatments were decreased by 48.4%, 51.6% and 49.2%, 54.2%, compared with CK treatment, respectively. Soil exchangeable calcium (Ca2+), magnesium (Mg2+) and potassium (K+) contents at 0–10 cm and 10–20 cm layers in paddy field with OM and RF treatments were higher than that of CK treatment. Moreover, compared with CK treatment, soil exchangeable base ion content at 0–10 cm and 10–20 cm layers in paddy field with OM treatment were increased by 54.1% and 42.6%, respectively. Soil CEC and effective cation exchange capacity (ECEC) at 0–10 cm and 10–20 cm layers with OM and RF treatments were significantly higher than that of MF and CK treatments. In conclusion, our results indicated that long-term application of crop residue or organic manure can improve soil exchangeable base ion and exchangeable capacity contents, alleviate soil acidity in a double-cropping paddy field. [ABSTRACT FROM AUTHOR]

Sparse synthesis can reduce the maximum sidelobe level (SLL) and overhead of the concentric circular antenna array (CCAA) by switching off partial array elements. However, previous works have not considered finding a balance between the number of switched-on elements of CCAA and reducing the maximum SLL, or jointly optimizing the excitation current weights of array elements to further suppress the maximum SLL. In this work, we address these challenges by formulating a hybrid multi-objective optimization problem (MOP) with discrete and continuous solutions. To solve this hybrid NP-hard problem, we consider two approaches: the two-step and one-step methods. In the two-step method, we convert the original MOP into two subproblems and propose an enhanced non-dominated sorting genetic algorithm-II (ENSGA-II) and an improved genetic algorithm with new mutation and attraction (IGAnMA) to solve these two subproblems. ENSGA-II and IGAnMA involve the hierarchy mechanism and attraction operator to enhance the solving abilities, respectively. In the one-step method, we propose an improved hybrid non-dominated sorting genetic algorithm-II (IHNSGA-II) with global search and hybrid solution update methods to solve the MOP in one step. Numerical simulation results show that the proposed methods are effective and stable for the sparse synthesis of CCAA. Additionally, electromagnetic simulation results demonstrate the validity of the proposed approaches in a more practical environment. • A practical, mixed-variable, and NP-hard problem from antenna optimization. • Two-step optimization methods based on enhanced evolutionary computation. • One-step optimization methods based on improved evolutionary computation. • Extensive numerical and electromagnetic simulations for verifications. [ABSTRACT FROM AUTHOR]

This paper proposed a power-pattern optimization method for suppressing the maximum side lobe level outside of the collection region (CSL) of energy beamforming for wireless power transmission based on the biogeography-based optimization with local search (BBOLS). Two improved components, local search operator and selection operator, are introduced into the normal biogeography-based optimization to improve the performance of the algorithm. These two introduced factors can significantly help the algorithm to improve the convergence rate, prevent the candidate solutions from being trapped into the local optimum. Simulation results show that the CSL of the planar antenna array obtained by BBOLS can be depressed effectively while the beam collection efficiency can be enhanced. Moreover, the accuracy and the convergence rate of BBOLS are better than other algorithms. In addition, the power-pattern performance obtained by BBOLS is also verified by the electromagnetic simulations. [ABSTRACT FROM AUTHOR]

Abstract A novel shortest path connectivity and coverage algorithm (SPCCA) for wireless sensor networks is proposed to reduce the energy consumption and to extend the network lifetime. The main procedure of SPCCA is as follows: first, each node determines whether it is the redundant node. Then, the redundant nodes enter into the ready-to-sleep mode through the node selection method and the sleepless nodes enter into the active mode. In this way, the blind spot can be avoided and the energy balance can be guaranteed. Finally, the redundant nodes on the shortest path are woken up in order to guarantee the connectivity of the network. Simulation results show that the number of working nodes of SPCCA is stable and they do not increase with the number of the deployed nodes. Moreover, SPCCA has better performance than most homogeneous algorithms in terms of the network coverage, connectivity, connection cost and network lifetime. [ABSTRACT FROM AUTHOR]

Feature selection is a complicated multi-objective optimization problem with aims at reaching to the best subset of features while remaining a high accuracy in the field of machine learning, which is considered to be a difficult task. In this paper, we design a fitness function to jointly optimize the classification accuracy and the selected features in the linear weighting manner. Then, we propose two hybrid meta-heuristic methods which are the hybrid basic bald eagle search-particle swarm optimization (HBBP) and hybrid chaos-based bald eagle search-particle swarm optimization (HCBP) that alleviate the drawbacks of bald eagle search (BES) by utilizing the advantages of particle swarm optimization (PSO) to efficiently optimize the designed fitness function. Specifically, HBBP is proposed to overcome the disadvantages of the originals (i.e., BES and PSO) and HCBP is proposed to further improve the performance of HBBP. Moreover, a binary optimization is utilized to effectively transfer the solution space from continuous to binary. To evaluate the effectiveness, 17 well-known data sets from the UCI repository are employed as well as a set of well-established algorithms from the literature are adopted to jointly confirm the effectiveness of the proposed methods in terms of fitness value, classification accuracy, computational time and selected features. The results support the superiority of the proposed hybrid methods against the basic optimizers and the comparative algorithms on the most tested data sets. [ABSTRACT FROM AUTHOR]

In this study, Complex I inhibitor R419 was firstly revealed to have significant anticancer activity against HepG2 cells (IC 50  = 5.2 ± 0.9 μM). Based on this finding, a series of R419 derivatives were synthesized and biologically evaluated. As results, 9 derivatives were found to have obvious anticancer activity. Among them, H20 exhibited the most potent activity (IC 50  = 2.8 ± 0.4 μM). Mechanism study revealed that H20 caused severe depletion of cellular ATP, dose-dependently activated AMPK, decreased Bcl-2/Bax ratio and induced necrotic cell death. Most importantly, H20 displayed definite inhibitory activity against Complex I. [ABSTRACT FROM AUTHOR]

A novel hybrid approach to suppress the maximum sidelobe level (SLL) of large scale concentric circular antenna array (CCAA) is proposed. The approach includes an improved discrete cuckoo search algorithm (IDCSA) for thinning the CCAA and a cuckoo search-invasive weed algorithm (CSIWA) for further optimizing the thinned CCAA. IDCSA introduces the nest location coding discretization, the mapping method based on jumping path, and an improved egg elimination mechanism for optimizing the discrete sparse array synthesis problem. Moreover, CSIWA introduces the chaotic initialization and the invasive weed-based Lévy flight method to solve the continuous excitation current optimization problem. Simulation results show that the thinning rate of CCAA obtained by IDCSA can reach more than 50%, resulting in significant cost savings. Moreover, both IDCSA and CSIWA can obtain a lower maximum SLL compared with other algorithms while achieving faster convergence rates. The stabilities of the proposed IDCSA and CSIWA are demonstrated by using multiple independent tests. In addition, the performance of the optimized designs obtained by the hybrid approach is also verified by electromagnetic simulations. [ABSTRACT FROM AUTHOR]

To support real-time power management of the supercapacitor-powered embedded systems, an online model parameter identification method is proposed for predicting the supercapacitor behavior. In the proposed method, an optimization problem is formulated based on our previously developed supercapacitor model, and a weighting bat algorithm (WBA) with the weighting solution update method is proposed for solving this problem in each model parameter updating time window. Simulation and experimental results show that the proposed online model parameter identification method can accurately capture the terminal behavior of a supercapacitor, and the proposed WBA-based optimization method has better performance for the supercapacitor model parameter identification compared with other benchmark algorithms. [ABSTRACT FROM AUTHOR]

The alpine meadows in Qinghai-Tibetan Plateau is an ecosystem sensitive to environmental changes. As part of a study on global climate change and the effects of N precipitation on soil microbiota, we fingerprinted ammonium oxidizing archaea (AOA) and bacteria (AOB) in relation to the N supplement in an alpine meadow in Qinghai-Tibetan Plateau. The results showed that nutrient content in the studied soil was significantly varied in different months (sampling period) but not influenced by the N supplement rate. Long-term nitrogen input dramatically changed the abundance and community composition of the AOB but exerted no obvious effect on the AOA community in the tested soil. Significant differences in the abundance and composition of AOA were recorded in different months. Our findings implied that 1) the soil fertility and physicochemical features of the studied alpine meadows in Qinghai-Tibetan Plateau were stable even under the long-term high N supply; 2) AOB might be the active nitrifiers responding to the high N supply, while the AOA were the abundant and stable nitrifiers despite the N supply; 3) sampling periods mainly affected the abundance and community composition of the nitrifiers in the tested alpine meadow; and 4) the AOB in the studied area are psychrotrophs. Therefore, despite the enhancement of plant growth, high N supplements in the tested alpine meadow ecosystems might cause more pollution to water and air, which in turn contributes to global climate change. [ABSTRACT FROM AUTHOR]

Reactivity studies on catalytic transition metal clusters are usually performed on a single global minimum structure. With the example of a Pt13 cluster under a pressure of hydrogen, we show from first-principle calculations that low energy metastable structures of the cluster can play a major role for catalytic reactivity and that hence consideration of the global minimum structure alone can severely underestimate the activity. The catalyst is fluxional with an ensemble of metastable structures energetically accessible at reaction conditions. A modified genetic algorithm is proposed to comprehensively search for the low energy metastable ensemble (LEME) structures instead of merely the global minimum structure. In order to reduce the computational cost of density functional calculations, a high dimensional neural network potential is employed to accelerate the exploration. The presence and influence of LEME structures during catalysis is discussed by the example of H covered Pt13 clusters for two reactions of major importance: hydrogen evolution reaction and methane activation. The results demonstrate that although the number of accessible metastable structures is reduced under reaction condition for Pt13 clusters, these metastable structures can exhibit high activity and dominate the observed activity due to their unique electronic or structural properties. This underlines the necessity of thoroughly exploring the LEME structures in catalysis simulations. The approach enables one to systematically address the impact of isomers in catalysis studies, taking into account the high adsorbate coverage induced by reaction conditions. [ABSTRACT FROM AUTHOR]

In this paper, an efficient biogeography-based optimization (EBBO) method is proposed to synthesize the circular antenna arrays (CAA) for specific radiation beam pattern properties and null controls. The proposed method achieves the desired beam patterns by jointly optimizing the excitation currents as well as the spaces between the array elements. Three improved components, including chaotic search theory, model learning method and a new random perturbation operator, are introduced into the standard biogeography-based optimization (BBO) to improve the performance of the algorithm. Simulation results show that the maximum sidelobe level obtained by EBBO can be suppressed effectively compared with other algorithms. Moreover, the null controlling performance of EBBO is the best among the algorithms. [ABSTRACT FROM AUTHOR]

Background and aims: The rhizosphere priming effect is caused by root carbon (C) exudation into the rhizosphere; the role of this effect in nutrient cycling and ecosystem recovery of natural grasslands as affected by different grazing intensities is still unknown. The objective of the present study was to investigate the relationships among root C exudation, rhizospheric microbial activity, and their influences on plant nutrient uptake during grazing and recovery periods . Methods: Field experiments were conducted in the Hongyuan Alpine Meadow to measure root exudation rate and nutrient cycling processes of the dominant species Elymus nutans. Three grazing intensities (an ungrazed control, moderate grazing and heavy grazing) were introduced for two months, following which all treatments received a recovery practice (no grazing for 21 days). Results: Heavy grazing significantly decreased root exudation rate, soil nitrogen (N) mineralization rate, β-1,4-glucosidase (BG) activity, and foliar C concentration, while moderate grazing had no influence on these parameters compared to the control. After the 21 days of recovery, all these parameters, except N mineralization rate and foliar C concentrations in the heavy grazing treatment, returned to similar levels as in the control, whereas root exudation rate and BG activity rose to even higher levels. Meanwhile, moderate grazing significantly promoted root exudation rate, soil inorganic N concentration, net soil N mineralization rate, and β- N-acetylglucosaminidase (NAG) activity during the recovery stage as compared to the control. Foliar quality was also improved by the recovery practice, indicating that the high availability of N and P is a consequence of the positive root-microbe feedback and will ultimately benefit grazers. Conclusions: The flush of labile C released to the rhizosphere by grazed plants stimulated extracellular enzyme activities, enhanced soil N mineralization, and increased plant nutrient uptake. These results imply that reasonable (i.e. moderate) grazing followed by a recovery practice can effectively restore and strengthen grassland vegetation, and contribute to the sustainable use of alpine meadows such as Hongyuan. [ABSTRACT FROM AUTHOR]

Medicinal secondary metabolites (salvianolic acids and tanshinones) are valuable natural bioactive compounds in Salvia miltiorrhiza and have widespread applications. Improvement of medicinal secondary metabolite accumulation through biotechnology is necessary and urgent to satisfy their increasing demand. Herein, it was demonstrated that the overexpression of the transcription factor Arabidopsis thaliana-enhanced drought tolerance 1 ( AtEDT1) could affect medicinal secondary metabolite accumulation. In this study, we observed that the transgenic lines significantly conferred drought tolerance phenotype. Meanwhile, we found that the overexpression of AtEDT1 promoted root elongation in S. miltiorrhiza. Interestingly, we also found that the overexpression of AtEDT1 determined the accumulation of salvianolic acids, such as rosmarinic acid, lithospermic acid, salvianolic acid B, and total salvianolic acids due to the induction of the expression levels of salvianolic acid biosynthetic genes. Conversely, S. miltiorrhiza plants overexpressing the AtEDT1 transgene showed a decrease in tanshinone synthesis. Our results demonstrated that the overexpression of AtEDT1 significantly increased the accumulation of salvianolic acids in S. miltiorrhiza. Further studies are required to better elucidate the functional role of AtEDT1 in the regulation of phytochemical compound synthesis. [ABSTRACT FROM AUTHOR]

Lipophilic shellfish toxins (LSTs) produced by diverse microalgae have become a potential threat to the marine aquaculture industry in coastal regions throughout the world. In this study, phytoplankton, scallop, and seawater samples were collected and monitored in the aquaculture zone of Liuqing Bay located in the coast of Qingdao, Yellow Sea, in 2014 and 2015. Dissolved LSTs in seawater were adsorbed by solid phase adsorption toxin tracking (SPATT) bags and solid phase extraction (SPE) cartridges, respectively. PTX2 was found to be the predominant LSTs, while OA and DTX1 were detected at trace levels in the three species of Dinophysis and Phalacroma genera picked from the investigation zone. The highest quota of PTX2 occurred in D. fortii (0.28 pg cell −1 ), followed by D. acuminata complex (0.08 pg cell −1 ) and P. rotundatum (= D. rotundata ) (0.02 pg cell −1 ). PTX2 (nd∼5.7 μg kg −1 ), OA (nd∼2.8 μg kg −1 ) and DTX1 (nd∼1.6 μg kg −1 ) were also observed in cultivated scallops, but in addition to the former, PTX2sa, 7- epi -PTX2sa and an isobaric form of DTX1 suspected as DTX1b were also found in the SPATT bags. The isobaric compound of DTX1 only appeared in the SPATT bags deployed in field samples of seawater. A significant higher quantity of OA was adsorbed by SPATT bags compared to DTX1, although similar concentrations of both toxins were adsorbed by SPE cartridges from the aquaculture zone. AZA2 was also found in the concentrated phytoplankton cells, which demonstrated that AZA-producing microalgae were present in this investigated area. The variation in concentrations of PTX2 adsorbed by SPATT bags could reflect the change of Dinophysis density in seawater, but there was a time lag behind the peaks of Dinophysis density. Comparative results did not support the SPATT technology as a useful warning tool for toxic algal blooms and toxin accumulation in bivalves. The data suggest that the contamination of LSTs was prevalent in the coast of Qingdao and the environmental behavior of LSTs should be explored further. [ABSTRACT FROM AUTHOR]

As a result of global climate change, frequent and intensive extreme climate events are observed and predicted. These extreme climate events can change ecosystem functions through driving plant growth and mortality, as well as ecological and evolutionary processes into different directions. We simulated a 1-in-100-year extreme precipitation event in different plant growth seasons (i.e. spring, summer, or autumn) to investigate the functional responses of a mesophytic alpine grassland ecosystem to climate change in the Tibetan plateau. The results demonstrated that the seasonal distribution of extreme precipitation is a critical factor in determining soil microbial- and plant-productivity. The response of vegetation net primary productivity (NPP) to extreme precipitation depends on the growth seasons and plant types. Total NPP in the treatments experienced extreme precipitation in the early (spring), mid- (summer) and late- (autumn) plant growth seasons were significant lower, higher, and no difference, respectively, compared with the control. Soil temperature and moisture were the key abiotic factors that affected ecosystem functions. For example, in the early plant growth season, no changes of soil moisture and the decreased temperature in response to the extreme precipitation resulted in a substantial decline in NPP. By contrast, in the mid-plant growth season, higher temperature and soil moisture elicited positive synergistic effects on plant growth and soil microbial processes. The increased sensitivity of above-ground NPP and the shift of dominant species from sedges to less palatable forbs might inevitably exaggerate the degradation of this grassland. Nevertheless, a high resilience index in the related ecological processes could potentially contribute to the grassland acclimation and stability, as most parameters returned to the similar levels as in the control after the extreme events ceased. Therefore, several synergistic or antagonistic mechanisms are hypothesized to operate in parallel or at different levels of organization and timescales. Further studies involving a range of different potential scenarios and longer periods are needed to predict the future climate change impacts on mesophytic grassland. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) have attracted growing attention in enhancing the performance of mobile wireless sensor networks (MWSNs) since they can act as aerial servers (ASs) and have the autonomous nature to collect data for edge computing. In this paper, we consider to construct a virtual antenna array (VAA) consists of mobile sensor nodes (MSNs) and adopt collaborative beamforming (CB) to achieve long-distance and efficient uplink data transmissions with the ASs. First, we formulate a low interference and high-performance uplink transmission multi-objective optimization problem (UTMOP) of the CB-based UAV-assisted MWSN to simultaneously improve the total transmission rates, suppress the total maximum sidelobe levels (SLLs) and reduce the total propulsion energy consumptions of MSNs by jointly optimizing the positions and excitation current weights of MSN-enabled VAA and the order of communicating with different ASs. Then, we propose an improved non-dominated sorting genetic algorithm-III (INSGA-III) with chaos initialization, average grade mechanism and hybrid-solution generate strategy to solve the problem. Simulation results verify that the proposed algorithm can effectively solve the formulated UTMOP, and it has better performance than some other benchmark methods and peer algorithms. [ABSTRACT FROM AUTHOR]

In the present study, okadaic acid (OA) and dinophysistoxin-1 (DTX1) were spiked into artificial seawater at low, medium and high estuarine salinities (9‰, 13.5‰ and 27‰). Passive samplers (HP20 resin) used for solid phase adsorption toxin tracking (SPATT) technology were exposed in these seawaters for 12-h periods. Adsorption curves well fitted a pseudo-secondary kinetics model. The highest initial sorption rates of both toxins occurred in the seawater of medium salinity, followed by seawater of low and high estuarine salinity. Pore volumes of micropores (<2 nm) and small mesopores (2 nm < diameter < 10 nm) of HP20 resin decreased after adsorption of toxins in seawater at high and low salinity but not in seawater at medium salinity, which demonstrated that the toxin molecules entered into micropores and mesopores (below 10 nm in size) in seawaters of high and low salinity. More toxin or other matrix agglomerates were displayed on the surface of resin deployed in the seawater of medium salinity. Taking into consideration the pore-size distribution and surface images, it appears that intra-particle diffusion governs toxin adsorption in seawater at high salinity while film diffusion mainly controls the adsorption process in seawater at medium salinity. This is the first study to confirm that molecules of OA and DTX1 are able to enter into micropores (<2 nm) and small mesopores (2–10 nm) of HP20 resin in estuarine seawater with high salinity (∼27‰). [ABSTRACT FROM AUTHOR]

Large‐scale antenna array (LSAA) is one of the key factors as well as a fundamental technology in fifth generation wireless communication systems. Beampattern sidelobe (SL) suppressing is a complex nonlinear optimisation problem, especially for LSAAs, because of the high‐dimensional solution space. A SL reduction method for LSAA based on a hierarchical cuckoo search (HCS) algorithm is proposed. HCS divides the candidate solutions into different levels to improve population utilisation, so that it is suitable for dealing with large‐scale elements. The effectiveness of the proposed method for synthesis of the beampattern of LSAA is verified by theoretical and EM simulations. [ABSTRACT FROM AUTHOR]

Plant senescence is a critical life history process accompanied by chlorophyll degradation and has large implications for nutrient resorption and carbohydrate storage. Although photoperiod governs much of seasonal leaf senescence in many plant species, temperature has also been shown to modulate this process. Therefore, we hypothesized that climate warming would significantly impact the length of the plant growing season and ultimate productivity. To test this assumption, we measured the effects of simulated autumn climate warming paradigms on four native herbaceous species that represent distinct life forms of alpine meadow plants on the Tibetan Plateau. Conditions were simulated in open-top chambers (OTCs) and the effects on the degradation of chlorophyll, nitrogen (N) concentration in leaves and culms, total non-structural carbohydrate (TNC) in roots, growth and phenology were assessed during one year following treatment. The results showed that climate warming in autumn changed the senescence process only for perennials by slowing chlorophyll degradation at the beginning of senescence and accelerating it in the following phases. Warming also increased root TNC storage as a result of higher N concentrations retained in leaves; however, this effect was species dependent and did not alter the growing and flowering phenology in the following seasons. Our results indicated that autumn warming increases carbohydrate accumulation, not only by enhancing activities of photosynthetic enzymes (a mechanism proposed in previous studies), but also by affecting chlorophyll degradation and preferential allocation of resources to different plant compartments. The different responses to warming can be explained by inherently different growth and phenology patterns observed among the studied species. The results implied that warming leads to changes in the competitive balance among life forms, an effect that can subsequently shift vegetation distribution and species composition in communities. [ABSTRACT FROM AUTHOR]

Heteronuclear Au-Pd nanoparticles were prepared and immobilized in the functionalized ionic liquid [C2OHmim][NTf2]. The structural and electronic properties of the nanoparticles were characterized by a range of techniques and the surface of the nanoparticles was found to be enriched in Pd. Moreover, the extent of Pd enrichment is easily controlled by varying the ratio of Au and Pd salts used in the synthesis. The heteronuclear nanoparticles were found to be effective catalysts in dehalogenation reactions with no activity observed for the pure Au nanoparticles and only limited activity for the pure Pd nanoparticles. The activity of the heteronuclear nanoparticles may be attributed to charge transfer from Pd to Au and consequently to more efficient reductive elimination. [ABSTRACT FROM AUTHOR]

Abstract: Aqueous phase Fischer–Tropsch synthesis catalyzed by Ru nanoparticles was studied in a continuous flow reactor for the first time. A 60ml autoclave was used for catalyst screening and a 1000ml reactor was used to test the scale-up stability of the catalysts. Ru nanoparticles reduced by hydrogen in the presence of poly(N-vinyl-2-pyrrolidone) (PVP) showed the highest activity compared with those of the particles reduced by other reductants. PVP/Ru molar ratio and reaction temperature were two key factors responsible for the stability and activity of the catalysts. With a PVP/Ru molar ratio of 40, Ru nanoparticles kept an almost steady space-time yield (STY) of C5+ hydrocarbons 0.51g-C5+ g-cat−1 h−1 throughout 240h running at 150°C. The size of Ru nanoparticles grew very slightly from 2.0nm before the reaction to 2.2nm after the reaction. X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, and Gel Permeation Chromatography were used to reveal the structural information of the catalysts before and after reaction, and the characterization results were correlated with the catalytic performances. [Copyright &y& Elsevier]

Objective: The aim of the study was to investigate the role of src-suppressed C kinase substrate (SSeCKS) in the modulation of rat pulmonary microvascular endothelial cells (RPMVEC) permeability elicited by interleukin (IL)-1β and tumor necrosis factor (TNF)-α. Methods: The gene expression of SSeCKS was analyzed by reverse transcription-polymerase chain reaction. Immunoblotting was used to determine the SSeCKS protein expression and the activation of the protein kinase C (PKC) signaling pathway. A RPMVEC monolayer was constructed to determine changes of transendothelial electrical resistance (TER) and FITC-dextran flux ( P) across the monolayer. SSeCKS-specific small interfering RNA was transfected into RPMVEC. Results: IL-1β and TNF-α activated the PKC signaling pathway in RPMVEC, and up-regulated the gene and protein expression of SSeCKS. Depletion of endogenous SSeCKS in RPMVEC significantly attenuated cytokine-induced decrease in TER and increase in P, but not to the basal levels. PKC inhibitors also significantly decreased cytokine-induced hyperpermeability and SSeCKS expression. Conclusions: SSeCKS is involved in the endothelial hyperpermeability induced by IL-1β and TNF-α in inflammatory process. [ABSTRACT FROM AUTHOR]

Background: Interleukin (IL)-17F is involved in lung inflammation, but the effect of IL-17F on endothelial permeability and its signaling pathway remain ill-defined. The current study sought to investigate the effect of IL-17F on endothelium and assess the role of protein kinase C (PKC) and src-suppressed C kinase substrate (SSeCKS) in this process. Methods: Rat pulmonary microvascular endothelial monolayers were constructed to determine changes of permeability as measured by means of FITC-dextran and Hank''s solution flux across monolayers and transendothelial electrical resistance with or without IL-17F and PKC inhibitors. Additional monolayers were stained using FITC-phalloidin for filamentous actin (F-actin). The gene expression of SSeCKS was analyzed by the reverse transcription-polymerase chains. Alterations of SSeCKS protein were investigated by immunoblotting and immunoprecipitation. Results: IL-17F increased endothelial monolayer permeability in a dose- and time-dependent manner. F-actin staining revealed that permeability changes were accompanied by reorganization of cytoskeleton. In the presence of PKC inhibitors, the IL-17F-induced hyperpermeability and reorganization of F-actin were attenuated. The gene and protein expression of SSeCKS were conspicuously elevated after IL-17F challenge. The process of SSeCKS phosphorylation followed a time course that mirrored the time course of hyperpermeability induced by IL-17F. IL-17F-induced SSeCKS phosphorylation was abrogated after PKC inhibitors pretreatment. The translocation of SSeCKS from the cytosol to the membrane and a significant increase in the SSeCKS association with the cytoskeleton were found after IL-17F treatment. Conclusions: IL-17F is an important mediator of increased endothelial permeability. PKC and SSeCKS are integral signaling components essential for IL-17F-induced hyperpermeability. [Copyright &y& Elsevier]

Abstract: Background: Detection of human telomerase reverse transcriptase (hTERT) mRNA by in situ hybridization (ISH) may be valuable in the diagnosis of cancer. We assessed the diagnostic performance of hTERT mRNA in cells from pleural fluid in malignant pleural effusions (PEs). Methods: We used a 2-step ISH with digoxin-labelled oligonucleotide probes to detect hTERT mRNA in a blinded prospective study of cells from 103 unselected pleural fluid specimens. The reference standard for malignant PEs was clinical evaluation and pleural fluid cytology, combined with pleural biopsy, other examination and follow-up as needed. Results: According to the final diagnoses, there were 41 malignant PEs, 55 benign PEs and 7 cases with uncertain etiology. When the 7 cryptogenic cases were excluded, the sensitivity and specificity of detectable hTERT mRNA for malignancy were 80% and 95%, respectively. When detection of hTERT mRNA was combined with clinical repeated pleural fluid cytology, the sensitivity and specificity were 90% and 95%, respectively. Conclusions: Detection of hTERT mRNA in cells from pleural fluid by ISH could potentially be used in diagnosing malignant PEs as an aid. Further investigations with stricter controls and cross-validation tests will be warranted. [Copyright &y& Elsevier]

Background: The renin-angiotensin system is thought to be involved in the development and progression of vascular endothelium inflammation, thereby contributing to vascular endothelium injury. To clarify the role of angiotensin II (Ang II) in rat pulmonary microvascular endothelial cells (RPMVECs), we examined the expression and functional significance of angiotensin II (AngII) receptors in normal and lipopolysacchride (LPS) treated RPMVECs. Methods: The expressions of Ang II type1(AT1) and Ang II type 2 (AT2) receptors in cultured RPMVECs were identified by the reverse transcription-polymerase chain reaction (RT-PCR) technique, Western blot and 125I-labeled [Sar1,Ile8] Ang II binding assays. The RPMVECs were treated with LPS (0.1–100 μg/ml) and Ang II (10−8–10−5 M) for 24 h, respectively. Next, RPMVECs were treated with 10 μg/ml LPS or 10−7 M AngII for various times (3, 6, 12, and 24 h). The mRNA and protein levels of, AT1 and AT2 receptors, were evaluated at 3, 6, 12, and 24 h, respectively. Results: The presence of specific Ang II binding sites in RPMVECs was found by Ang II saturated assays. RT-PCR revealed that only the AT1 receptor mRNA is presented in RPMVECs. Western blot analysis of the RPMVECs protein extracts showed only one prominent band of the protein at approximately 41 KDa when probed with anti-AT1 antibody and anti-AT2 antibody. No AT2 receptor mRNA and protein was detected. LPS treated cells resulted in an increase in the mRNA and protein levels of AT1 receptor, whereas, AngII treated cells showed a decrease in the mRNA and protein levels of AT1 receptor. Conclusions: We found that primary cultured RPMVECs expressed only AT1 receptor, but not AT2 receptor. LPS up-regulated the transcriptional and post-transcriptional expression of AT1 receptor in RPMVECS; in contrast, Ang II treatment caused a reduction in the mRNA and protein of AT1 receptor in a time-dependant manner. [Copyright &y& Elsevier]

Abstract: Lipopolysaccharide (LPS) is known to stimulate the circulation and local production of angiotensin II (Ang II). To assess whether Ang II plays a role in LPS-induced acute lung injury, rats were injected with LPS, the microvascular endothelial permeability injury was evaluated by histological changes, increased pulmonary wet/dry weight ratio, and pulmonary microvascular protein leak. Besides, increased rat pulmonary microvascular endothelial cell monolayer permeability coefficient (K f) was measured after treatment with LPS and/or Ang II, respectively. LPS/Ang II, treatment resulted in a significant increase in K f. Ang II cooperates with LPS to further increase K f. Hence, LPS increases pulmonary microvascular endothelial permeability both in vitro and in vivo. Local lung Ang II was increased in response to LPS challenge, and elevated Ang II ulteriorly exacerbates LPS-induced endothelium injury. [Sar1,Ile8]Ang II, a selective block of Ang II type 1 (AT1) receptors, eliminated these changes significantly. Our conclusion is that the LPS-induced lung injury may be mediated by the AT1 receptor. [Copyright &y& Elsevier]

Using W -transformation of Hairre and Wanner, high-order implicit Runge-Kutta (RK) methods based on Lobatto quadrature are studied. Methods constructed and presented include and extend the existing Lobatto III type RK methods. Two to four stages general Lobatto III methods with three parameters α, β, γ are constructed, and a particular one-parameter family Lobatto III C(γ) method is also presented. [ABSTRACT FROM AUTHOR]

In functional differential equations (FDEs), there is a class of infinite delay-differential equations (IDDEs) with proportional delays, which aries in many scientific fields such as electric mechanics, quantum mechanics, and optics. Ones have found that there exist very different mathematical challenges between FDEs with proportional delays and those with constant delays. Some research on the numerical solutions and the corresponding analysis for the linear FDEs with proportional delays have been presented by several authors. However, up to now, the research for nonlinear case still remains to be done. For this, in the present paper, we deal with nonlinear stability of the Runge-Kutta (RK) methods for a class of IDDEs with proportional delays. It is shown under the suitable conditions that a (k, l)-algebraically stable RK method for this kind of nonlinear IDDE is globally and asymptotically stable. [Copyright &y& Elsevier]

Presents a study which examined the structure-preserving algorithms to phase space volume for linear dynamical systems. Preservation of phase space volume for source-free dynamical systems; Description of a volume-preserving scheme for linear system with canonical form; Information on structure-preserving schemes for linear dynamical systems.

This paper is concerned with the error analysis of linear multistep methods and Runge-Kutta methods applied to some classes of one-parameter stiff singularly perturbed problems with delays. We derive the global error estimates of A(α)-stable linear multistep methods and algebraically and diagonally stable Runge-Kutta methods with Lagrange interpolation procedure. Numerical experiments confirm our theoretical analysis. [Copyright &y& Elsevier]

Building extraction using deep learning techniques has advantages but relies on a large number of clean labeled samples to train the model. Complex appearance and tilt shots often cause many offsets between building labels and true locations, and these noises have a considerable impact on building extraction. This paper proposes a new knowledge distillation-based building extraction method to reduce the impact of noise on the model and maintain the generalization of the model. The method can maximize the generalizable knowledge of large-scale noisy samples and the accurate supervision of small-scale clean samples. The proposed method comprises two similar teacher and student networks, where the teacher network is trained by large-scale noisy samples and the student network is trained by small-scale clean samples and guided by the knowledge of the teacher network. Experimental results show that the student network can not only alleviate the influence of noise labels but also obtain the capability of building extraction without incorrect labels in the teacher network and improve the performance of building extraction. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are usually resource constrained, and have the limited communication and energy storage capacity. Collaborative beamforming (CB) in UAV networks based on a virtual node antenna array (VNAA) can enhance the signal-to-noise-ratio (SNR) and energy efficiency of a single UAV node. The UAV nodes can move to better locations for constructing the VNAA to achieve a maximum SNR of CB. However, this will result in an extra motion energy consumption. In this paper, we formulate a joint optimization problem to simultaneously optimize the received SNR and motion energy consumption for UAV-enabled CB. Then, a mended particle swarm optimization with weed optimization mechanism algorithm is proposed to solve the formulated joint optimization problem. Simulation results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Activation of AMPK emerges as a potential therapeutic approach to metabolic diseases. AdipoRon is claimed to be an adiponectin receptor agonist that activates AMPK through adiponectin receptor 1 (AdipoR1). However, AdipoRon also exhibits moderate inhibition of mitochondrial complex I, leading to increased risk of lactic acidosis. In order to find novel AdipoRon analogues that activate AMPK without inhibition of complex I, 27 analogues of AdipoRon were designed, synthesized and biologically evaluated. As results, benzyloxy arylamide B10 was identified as a potent AMPK activator without inhibition of complex I. B10 dose-dependently improved glucose tolerance in normal mice, and significantly lowered fasting blood glucose level and ameliorated insulin resistance in db/db diabetic mice. More importantly, unlike the pan-AMPK activator MK-8722, B10 did not cause cardiac hypertrophy, probably owing to its selective activation of AMPK in the muscle tissue but not in the heart tissue. Together, B10 represents a novel class of AMPK activators with promising therapeutic potential against metabolic disease. Image 1 • A series of novel AdipoRon analogues were designed and synthesized. • Six analogues exhibited much more potency of AMPK activation than AdipoRon. • B10 exhibited significant in vitro and in vivo hypoglycemic effects in mice. • B10 did not inhibit mitochondrial complex I. • B10 did not cause cardiac hypertrophy in mice. [ABSTRACT FROM AUTHOR]

Antenna array makes an increasingly valuable contribution to various fields of communications. The beam pattern synthesis is one of the significant properties of antenna array. In this article, suppressing the maximum sidelobe levels (SLLs) of different antenna arrays is our main objective. Specifically, we first formulate the beam pattern optimization problems of the linear antenna array (LAA) and circular antenna array (CAA), respectively, and propose an improved biogeography‐based optimization (IBBO) approach to tackle the issue. IBBO introduces the hybrid migration and hybrid mutation operators by adopting several improved factors to strengthen the effect of conventional biogeography‐based optimization (BBO) algorithm. Emulate experiments are built to evaluate the performance of the IBBO for dealing with the formulated antenna array beam pattern optimization problems comprehensively. [ABSTRACT FROM AUTHOR]

Soil extracellular enzymes play an important role in regulating nitrogen (N) mineralization processes in paddy fields. Therefore, in this work, we determine the influence of a long-term fertilizer regime on rhizosphere soil N fertilization rates, soil enzymes, soil microbial community (bacterial ureolytic community (ureC), bacterial chitinolytic community (chiA)) under the double-cropping rice field in southern of China. The field experiment included the following fertilizer regimes: inorganic fertilizer alone (IF), rice straw and inorganic fertilizer (RF), 30% organic manure and 70% inorganic fertilizer (OM), without any fertilizer input as a control (CK). The results showed that rhizosphere soil N transformation rates in the paddy fields with OM and RF treatments were increased, compared with IF and CK treatments. Soil urease, β-glucosaminidase and arginase activities were significantly increased under OM and RF treatments. This result indicated that functional gene abundances of sub, npr and chiA were significantly greater under RF and OM treatments compared to IF and CK treatments. Soil bacterial ureolytic and chitinolytic communities were significantly changed by the different fertilization strategies. The practice of applying rice straw and organic manure seems beneficial for increasing rhizosphere soil N mineralization rates and microbial community diversity in the double-cropping rice fields. [ABSTRACT FROM AUTHOR]

Virtual antenna array (VAA) formed by unmanned aerial vehicle (UAV) antenna units using collaborative beamforming (CB) technology plays an important role in the air communication system, and can be used in radar, military, disaster rescue and other places. However, there are still some issues with the beam pattern formed by this method, such as high sidelobe level (SLL), high cost and low efficiency. In this article, each UAV carries an omnidirectional antenna unit, and a large number of UAVs form a UAV virtual rectangular antenna array (UVRAA) to communicate with the ground base station (BS). We formulate an overhead minimization and efficient communication multi‐objective optimization problem (OMECMOP) which jointly optimize the excitation current weights of the UVRAA and reduce the number of UAVs in operation to improve the beam pattern, enhance the communication efficiency and decrease the overhead of UVRAA. In addition, we also propose an improved multi‐objective multi‐verse optimization algorithm based on the inverse S$$ S $$ decline curve type (ISDT‐MOMVO) which introduces a strategy optimization initialization solution with quasi‐opposition based learning (QBL) and a hybrid solution updating operators to solve the OMECMOP. The simulation results show that compared with other traditional swarm intelligence (SI) optimization algorithms the ISDT‐MOMVO algorithm produces better beam pattern and the thinning rate can reach 50%. [ABSTRACT FROM AUTHOR]

Large‐scale antenna arrays (LSAAs) are used to achieve satisfactory performance in 5G communications and radar systems. However, sidelobe suppression and nulls control of LSAAs are high‐dimensional nonlinear optimization problems owing to the large number of antenna elements. In this study, we formulate an optimization problem for joint sidelobe suppression and nulls control of large‐scale linear antenna arrays and propose particle swarm optimization with global search and population mutation (PSOGP) to solve this problem. PSOGP introduces global search and population mutation operators into conventional particle swarm optimization to improve performance in terms of convergence rate and accuracy in large solution spaces. Simulation results demonstrate that compared with other methods, the proposed PSOGP has better overall performance in joint sidelobe suppression and nulls control. [ABSTRACT FROM AUTHOR]

The electrochemical performance of room-temperature sodium-sulfur batteries (SSBs) is limited by slow reaction kinetics and sulfur loss in the form of sodium polysulfides (SPSs). Here, it is demonstrated that through electron spin polarization, at no additional energy cost, an external magnetic field (M on) generated by a permanent magnet can significantly improve the SPSs adsorption capacity and reaction dynamics of a ferrimagnetic sulfur host. More specifically, the preparation of a carbon nanofiber/CoFe2O4/S (CNF/CoFe2O4/S) cathode with unprecedented performance and stability at ambient temperature is detailed when M on. It is experimentally and theoretically demonstrated that the magnetic field polarizes the electrons of Co ions, enhancing the adsorption of SPSs and their catalytic conversion. CNF/CoFe2O4/S cathodes with spin polarization provide unprecedented decay rates down to 0.0039% per cycle at 1.0 C for 2700 cycles. The performance of SSBs is further tested, which has 248 mAh g-1 under 1.0 C after 100 cycles when M on. Furthermore, it is evidenced that even when removing the external magnetic field, the magnetic polarization effect persists, opening the door for practical applications. This study not only demonstrates an effective strategy to improve electrochemical performance in SSBs, but also contributes to the enrichments of spin effects in the fields of electrocatalysis. [ABSTRACT FROM AUTHOR]

Conventional TiO2/N719 photoanodes often suffer from the limited visible light absorption (450–500 nm) and the serous recombination of photo-generated carries (e−/h+)/electrolyte ions (I3−), accordingly outputting a low photoelectronic conversion efficiency (PCE). In this work, a type of strawberry-like TiO2/NiTiO3 (NTO) nanospheres was designed via a simple hydrothermal method. In this design, the NTO quantum dots (QDs) with size of several nanometers were decorated on the surface of TiO2 nanospheres. This TiO2/NTO nanostructure can not only enhance the visible light absorption of the TiO2/N179 photoanodes but also improve the separation of photo-generated carriers and depress the recombination of e−/h+ and I3−. Thus, the optimal TiO2/NTO/N719 dye-sensitized solar cells (DSSCs) achieved greatly improved Jsc and Voc, both of which result into a 32.8%-improved PCE compared to the TiO2/N719 ones. These improvements could be due to the decreased charge transfer resistance at the photoanode/electrolyte interface (Rct2) and the increased electron lifetime (τn) caused by TiO2/NTO hetero-interface. In addition, the optimization on NTO QDs indicates that the density of QDs main affects the τn, and the size of QDs affects with Rct2. Moderate density and size (ca. 5 nm) of QDs can optimize the photoelectronic performances of DSSCs. [ABSTRACT FROM AUTHOR]

Abstract A wireless rechargeable sensor network (WRSN) consists of sensor nodes that can harvest energy from the wireless charging nodes (WCNs) for prolonging the network lifetime. This study deals with the WCN deployment optimization problem in WRSNs. We propose an optimization framework that simultaneously maximizes the coverage and the charging efficiency. Moreover, an improved firefly algorithm (IFA) is proposed for solving the WCN deployment optimization problem. IFA adopts a novel adaptive attractiveness factor and introduces a dynamic location update mechanism to enhance the performance of the conventional firefly algorithm (FA). We compare the proposed IFA with several benchmark algorithms in two different scenarios. Simulation results show that the proposed algorithm outperforms other comparative algorithms in both accuracy and convergence rate. [ABSTRACT FROM AUTHOR]