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Understanding the mechanisms driving parasite distributions is not only important for understanding ecosystem functioning, but also crucial for disease control. Previous studies have documented the important roles of host sex, host body size, host behavioral trait (such as boldness and trappability), and seasonality in shaping parasite load. However, few studies have simultaneously assessed the roles of these factors, as well as their interactions. In spring and summer of 2021, we conducted live trapping in Hohhot, China, to collect ectoparasites on Daurian ground squirrel (Spermophilus dauricus), a small rodent widely distributed in East Asian grassland. We then used generalized linear models to explore the effects of several biological factors (sex, body weight, trappability, and reproductive status) and seasonality on the abundance of ticks and fleas in S. dauricus. Significant but inconsistent seasonal effects were observed: tick load was significantly greater in summer than in spring, while flea load was greater in spring than in summer. Seasons also significantly interacted with host trappability and body weight to affect tick abundance. Our results highlight the importance of considering seasonal changes in parasitism, as well as interactions between season and host biological traits in shaping parasite distributions. [Display omitted] • Both fleas and ticks show seasonal changes in abundance but in different directions. • Relationship between host body weight and tick load changes between seasons. • Effect of trappability on tick abundance depends on season. [ABSTRACT FROM AUTHOR]

While extensive experimental activities have been carried out to study the phase transitions and ferroelectric properties of BaZr x Ti 1- x O 3 solid solutions, the corresponding theoretical understanding is largely lacking due to the unavailability of thermodynamic potentials for this system. In this work, an eighth-order polynomial of thermodynamic potential for BaZr x Ti 1- x O 3 (x ≤0.3) solid solutions is established based on the existing potential coefficients of BaTiO 3 and theexperimentally measured phase diagram of BaZr x Ti 1- x O 3 solid solutions. It is then employed to predict and understand the domain structures and switching for BaZr x Ti 1- x O 3 (x ≤0.3) single crystals using phase-field simulations. The simulated domain structures and switching are consistent with thermodynamic analysis and available experimental measurements, validating the established thermodynamic potential. It is expected that this thermodynamic potential will find wide applications to studying the phase transitions and ferroelectric properties of BaZr x Ti 1- x O 3 (x ≤0.3) bulk and nanoscale materials. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Recently, a robust least squares support vector machine (R-LSSVM) was proposed, but its computational complexity is very high compared with the traditional least squares support vector machine (LSSVM). To reduce R-LSSVM's computational complexity, an improved version, i.e., extended LSSVM (E-LSSVM), is developed in this paper. E-LSSVM and R-LSSVM are equivalent in terms of the generalization performance, but the former needs lower computational complexity than the latter. It is proved that the traditional LSSVM is a special case of E-LSSVM, and based on this fact, we know that the bias in the traditional LSSVM owns manifest physical meaning, i.e., the mean of the modeling error. To solve the mathematical model of E-LSSVM, two algorithms, DE-LSSVM (dual E-LSSVM) and PE-LSSVM (primal E-LSSVM), are proposed from dual and primal spaces, respectively. Even competing against the traditional LSSVM, DE-LSSVM takes the edge in term of the training time. In addition, the sparse problem and cross validation of DE-LSSVM are discussed as well. To verify the effectiveness and soundness of the proposed DE-LSSVM and PE-LSSVM, experiments on regression and classification problems are investigated. To be more important, DE-LSSM and PE-LSSVM are successfully applied to the fault diagnosis of aircraft engine, showing that they are eligible for potential techniques of the fault diagnosis of aircraft engine. [ABSTRACT FROM AUTHOR]

Understanding magnetic domain structures and their responses to electric fields in multiferroic heterostructures is critical to the design of electric-field-driven spintronic devices. High-throughput finite-element and phase-field simulations are performed to probe the piezoelectric strain anisotropy and its relaxation, magnetic domain structures and their responses to applied voltages as function of the in-plane dimensions and thickness of the magnetic Ni nanoislands grown on a Pb(Mg 1/3 Nb 2/3)O 3 –PbTiO 3 (PMN-PT) membrane. The piezoelectric strain anisotropy is found to increase with the in-plane aspect ratio, but it can be significantly relaxed, as large as >80%, in nanoislands of thickness larger than >15 nm. Magnetic domain diagrams are established to identify the domain structures for Ni nanoislands of different lengths of in-plane major and minor axis, as well as thickness. When a voltage is applied to the multiferroic heterostructure, the single-domain magnetic domain can be switched by the piezoelectric strain, whereas the vortex domain is not switched. However, for a multiferroic heterostructure with a thick nanoisland wherein most of the piezoelectric strain is relaxed, the single-domain magnetic domain shows a weak response to the voltage and cannot be switched. The effect of thickness variation in real magnets on the switching is also discussed. The present results are expected to provide guidance to the understanding and design of multiferroic nanostructures for achieving electric-field-modulated magnetic properties. Image 1 [ABSTRACT FROM AUTHOR]

We analyzed the data obtained from field observations on a gas hydrate drilling area in Dongsha of northern South China Sea (SCS) in middle May (before drilling) and early October (after drilling) in 2013. The variation in the phytoplankton communities and biomass as well as the impacts of environmental factors including dissolved methane was studied. Results indicated that the gas hydrate drilling area in Dongsha, SCS exhibited a typical low-nutrients low-chlorophyll a (LNLC) environment accompanied with low phytoplankton abundance. A total of 103 taxa belonging to 52 genera of 5 classes were identified, with diatoms and dinoflagellates dominating the community. Both phytoplankton abundance and chlorophyll a (Chl a ) were highest at the subsurface maximum layer. The subsurface chlorophyll maximum (SCM) before and after drilling were stabilized at 75 m (0.30 ± 0.06 mg/m 3 and 0.51 ± 0.29 mg/m 3 , respectively), while the subsurface maximum of abundance after drilling went deeper to 75 m (604.17 ± 313.22 cells/L) from the surface (707.14 ± 243.98 cells/L) before drilling. After drilling, phosphate and Chl a increased significantly, but no significant differences were observed on abundance. Dominant species of diatoms were basically constant with dinoflagellates becoming more apparent in higher occurrence and abundance, while Cyanophyta was diverse after drilling. Redundancy analysis (RDA) and Spearman's correlation analysis both indicated that temperature, pH and phosphates were major factors causing fluctuation in phytoplankton community structure, while dissolved methane had non-significant impact directly. We clearly found both abundance and Chl a increased in particular water layers (between 50 and 75 m) and at stations (DS06, DS08 and DS15) where dissolved methane concentrations were also abnormally high. This study appeared to partly coincide with the findings of natural oil seeps in the Gulf of Mexico, which assumed that the turbulence from the natural oil and gas leaking zone could raise the bottom water through the rising bubbles and bring cold nutrient rich waters to the thermocline from the deep seeps. This plume-generated upwelling could then fuel a bottom-up effect on the photosynthetic species in the upper pelagic waters within the euphotic zone. [ABSTRACT FROM AUTHOR]

Nanogenerator has caused extensive attraction to convert/collect dispersive energy as electric energy. Solar thermoelectric generator (STEG), based on Seebeck effect of semiconductors, is one of the most promising approaches for solar energy conversion because of its simple structure, high stability and long lifetime. The light absorbers are of paramount importance for high-efficient STEG. In this work, high performance carbon nanoparticles for light harvesting have been synthesized via a facile and efficient method. By the in-situ coating of the nanoparticles on a commercial thermoelectric generator, a high-efficient STEG was constructed. The performance of the designed STEG device can be further improved with the integration of heat preservation and heat sink components. There is 34 times higher efficiency than that of the bare commercial thermoelectric generator, which enables an electrochemical process to generate hydrogen gas by water splitting. Be a kind of nanogenerator, this designed STEG devices provide a cheap and facile strategy for the portable power supply. [ABSTRACT FROM AUTHOR]

• The optimum operation point is tracked by matching the virtual load impedance. • No microcontroller is used in the MPPT circuit. • The MPPT method can handle the intermittent and fast-changing voltage. • The energy efficiency of the generator was improved by 0.8 to 1.7 times. • The larger temporal storage capacitor helps to improve the energy efficiency. An innovative maximum power point tracking method based on impedance matching is proposed and applied in a micro hydropower generator. The micro hydropower generator exploits the water head which is derived from the repeated diving of the marine animal to power the marine telemetry tag. The output voltage of the micro generator is intermittent and changes very fast. The present maximum power point tracking methods can't deal with this type of intermittent and fast changing voltage of the generator. Hence, to track the optimum operation point and improve the energy efficiency, a new MPPT method which tracks the optimum operation point by directly matching the virtual load impedance of the generator to its internal resistance is proposed. The impedance matching law is developed based on the mathematical model. The experiment of the MPPT hardware is conducted, and the experiment result is used to validate the simulation model. Based on the validated model, the analysis results show that under the fluid pressure from 2 MPa to 8 MPa, the energy efficiency of the generator that uses the MPPT method increase to 1.8 to 2.7 times the one with the direct charging method. The results indicates the effectiveness and advantage of the MPPT method in tracking the optimum operation point and improving the energy efficiency in the context of intermittent and fast changing voltage. [ABSTRACT FROM AUTHOR]

Resistance degradation in perovskites is characterized by an increase in current over time with applied electric field. This behavior can be simulated and spatially resolved conductivity profiles can be measured, but some inconsistencies remain. A new approach to address these problems is presented that utilizes time-resolved impedance spectroscopy with an applied DC voltage to provide new insight into the resistance degradation phenomenon. In particular, this method allows the in-situ acquisition of spatio-temporal variations in conductivity. In SrTiO 3 a single bulk-dominated maximum of the imaginary part of the modulus M″ transitions to two maxima during degradation, reflecting the hole conductivity in the anode region and the electron conductivity in the cathode region. To clarify the influence of conductivity profiles on impedance data, the reversed route is presented by using simulated conductivity profiles to calculate impedance data. It will be emphasized that this methodology is not limited to the perovskite system considered here, but can be adapted to any kind of system characterized by a spatially varying conductivity. [ABSTRACT FROM AUTHOR]

Effective thermal conductivity as a function of domain structure is studied by solving the heat conduction equation using a spectral iterative perturbation algorithm in materials with inhomogeneous thermal conductivity distribution. Using this proposed algorithm, the experimentally measured effective thermal conductivities of domain-engineered {001} p -BiFeO 3 thin films are quantitatively reproduced. In conjunction with two other testing examples, this proposed algorithm is proven to be an efficient tool for interpreting the relationship between the effective thermal conductivity and micro-/domain-structures. By combining this algorithm with the phase-field model of ferroelectric thin films, the effective thermal conductivity for PbZr 1- x Ti x O 3 films under different composition, thickness, strain, and working conditions is predicted. It is shown that the chemical composition, misfit strain, film thickness, film orientation, and a Piezoresponse Force Microscopy tip can be used to engineer the domain structures and tune the effective thermal conductivity. Therefore, we expect our findings will stimulate future theoretical, experimental and engineering efforts on developing devices based on the tunable effective thermal conductivity in ferroelectric nanostructures. [ABSTRACT FROM AUTHOR]

Defect chemistry and transport in Fe-doped SrTiO 3 single crystal are studied to understand its resistance degradation mechanism. The temporal evolution of electric conductivity under a voltage stress was obtained computationally by solving the transport equations for ionic and electronic defects coupled with the defect reaction equilibrium equations. The computational results are compared to the corresponding experimental measurement under similar conditions. It is shown that the local electron and hole concentrations are controlled by the local electronic defect equilibria rather than by their quasi-steady state diffusional transport. It is the electric field-induced migration of oxygen vacancies and the subsequent instantaneous reestablishment of the local defect equilibria that lead to the resistance degradation. The resistance degradation behavior and the defect distributions under a long-term voltage stress are strongly influenced by the sample-annealing oxygen partial pressure, degrading electric field, and temperature. The present study contributes to the understanding of resistance degradation mechanism and provides guidance to improve the lifetime and reliability of wide band-gap semiconducting capacitors. [ABSTRACT FROM AUTHOR]

Many original equipment manufacturers (OEMs) allow third-party remanufacturers (3PRs) to perform remanufacturing operations of branded or patented products – through either outsourcing or authorization. This study compares these two modes by modeling the game between the OEM and the 3PR on equilibrium quantities, prices, and profits. The results suggest that when consumers perceive the remanufactured products with a low value, the 3PR prefers the authorization approach; otherwise the 3PR prefers the outsourcing approach. However, in both scenarios, the OEM obtains higher profit through outsourcing than through authorization. Our further analysis compares two modes’ impacts on consumer surplus, social welfare, and environment. [ABSTRACT FROM AUTHOR]

Robustness is an important characteristic of a classifier. With higher robustness, a classifier can resist much more against the noise of a contaminated dataset which is usually occurred in the real-world applications. With its excellence in robustness, a fuzzy support vector machine (fuzzy SVM) developed by Lin and Wang deserves the most attention among varieties of support vector machines. The main goal of this paper is to gain the Joachims’ ξ – α bound of the fuzzy SVM. Based on the decoupled α and ξ terms in its expression, the ξ – α based estimation is particularly suitable for robustness analysis of the fuzzy SVM. The study re-examines the theory of the fuzzy SVM having an additional fuzzy input s i in details with the ξ – α estimation, and conducts a relatively contracted condition for upper bounding the corresponding performance. The bound confirms the crucial robustness which the fuzzy SVM can achieve analytically, and would be helpful for the works such as model selection or model adaption for further applications. [ABSTRACT FROM AUTHOR]

The paper is devoted to some single-machine scheduling problems with variable job processing times. The objectives are to minimize the makespan (i.e., the maximum completion time of all jobs), and to minimize the total completion time. For some special cases, we show that these problems can be solved in polynomial time. For some another special cases of the makespan and the total completion time minimization problems, we prove that an optimal schedule has an V-shape property in terms of processing times. We also propose a heuristic algorithm by utilizing the V-shape property. [ABSTRACT FROM AUTHOR]

In this study, we propose a new scheduling model with position-dependent deterioration, in which the processing time of a job is defined by an increasing function of total weighted normal processing time of jobs prior to it in the sequence, where the weight is position dependent. We show that some single machine scheduling problems remain polynomially solvable under the proposed model, respectively. In addition, we show that some special cases of the flow shop scheduling problems can be optimally solved by polynomial time algorithm, respectively. [ABSTRACT FROM AUTHOR]

This paper deals with single machine scheduling problems with simple linear deterioration in which the processing time of a job is a simple linear function of its execution starting time. The objective is to determine the optimal schedule to minimize the weighted sum of the θ th ( θ is a positive integer number) power of waiting times. It is proved that the general problem can be solved in polynomial time. In addition, for the jobs with weak (strong) parallel chains and a series–parallel digraph precedence constraints, it is also proved that these problems can be solved in polynomial time, respectively. [ABSTRACT FROM AUTHOR]

In this study we consider unrelated parallel machines scheduling problems with learning effect and deteriorating jobs, in which the actual processing time of a job is a function of joint time-dependent deterioration and position-dependent learning. The objective is to determine the jobs assigned to corresponding each machine and the corresponding optimal schedule to minimize a cost function containing total completion (waiting) time, total absolute differences in completion (waiting) times and total machine load. If the number of machines is a given constant, we show that the problems can be solved in polynomial time under the time-dependent deterioration and position-dependent learning model. [ABSTRACT FROM AUTHOR]

This paper considers a group scheduling problem with two ordered criteria where both setup times and job-processing times are increasing functions of their starting times. It is assumed that the jobs be classified into several groups and the jobs of the same group have to be processed contiguously. We consider two objectives where the primary criterion is the total weighted completion time and the secondary criterion is the maximum cost. A polynomial time algorithm is presented to solve this bicriterion group scheduling problem with deteriorating setup times and job-processing times. This algorithm can also solve single-machine group scheduling problems with deteriorating setup times and job-processing times in several ordered maximum cost and arbitrary precedence. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we investigate a single machine scheduling problem with decreasing time-dependent processing times and group technology assumption. By the decreasing time-dependent processing times and group technology assumption, we mean that the group setup times and job processing times are both decreasing linear functions of their starting times. We want to minimize the makespan subject to release dates. We show that the problem can be solved in polynomial time. [Copyright &y& Elsevier]