Offset quantum-well method for tunable distributed Bragg reflector lasers and electro-absorption modulated distributed feedback lasers

A two-section offset quantum-well structure tunable laser with a tuning range of 7 nm was fabricated using offset quantum-well method. The distributed Bragg reflector (DBR) was realized just by selectively wet etching the multiquantum-well (MQW) layer above the quaternary lower waveguide. A threshold current of 32 mA and an output power of 9 mW at 100 mA were achieved. Furthermore, with this offset structure method, a distributed feedback (DFB) laser was integrated with an electro-absorption modulator (EAM), which was capable of producing 20 dB of optical extinction

Multi-Agent Consensus Seeking via Large Language Models

Multi-agent systems driven by large language models (LLMs) have shown promising abilities for solving complex tasks in a collaborative manner. This work considers a fundamental problem in multi-agent collaboration: consensus seeking. When multiple agents work together, we are interested in how they can reach a consensus through inter-agent negotiation. To that end, this work studies a consensus-seeking task where the state of each agent is a numerical value and they negotiate with each other to reach a consensus value. It is revealed that when not explicitly directed on which strategy should be adopted, the LLM-driven agents primarily use the average strategy for consensus seeking although they may occasionally use some other strategies. Moreover, this work analyzes the impact of the agent number, agent personality, and network topology on the negotiation process. The findings reported in this work can potentially lay the foundations for understanding the behaviors of LLM-driven multi-agent systems for solving more complex tasks. Furthermore, LLM-driven consensus seeking is applied to a multi-robot aggregation task. This application demonstrates the potential of LLM-driven agents to achieve zero-shot autonomous planning for multi-robot collaboration tasks. Project website: westlakeintelligentrobotics.github.io/ConsensusLLM/

The characteristics analysis and cogging torque optimization of a surface-interior permanent magnet synchronous motor

This paper proposes optimal stator skewed slot analytical method for cogging torque reduction in surface-interior permanent magnet synchronous motor(SIPMSM) and analyzes the characteristics of SIPMSM. The series-parallel equivalent magnetic circuit models(EMCMs) of SIPMSM is built based on the characteristics of magnetic circuits, which is used to design the basic electromagnetic parameters of SIPMSM. Analytical expressions of cogging torque are derived from applying analytical techniques. Stator skewed slot for cogging torque minimum is adopted, and the stator skewed slot pitch is confirmed based on the analytical expressions of the resultant cogging torque. The cogging torque, torque ripple, back electromotive force(back-EMF), power-angle characteristics, efficiency and power factor of SIPMSM are analyzed by establishing 3-dimensional finite element model(3-D-FED) of SIPMSM with stator skewed slot and straight slot. It is shown that the comprehensive performance of optimized SIPMSM is improved as confirmed by finite element analysis and analytical calculation results

Using aquatic animals as partners to increase yield and maintain soil nitrogen in the paddy ecosystems

Whether species coculture can overcome the shortcomings of crop monoculture requires additional study. Here, we show how aquatic animals (i.e. carp, crabs, and softshell turtles) benefit paddy ecosystems when cocultured with rice. Three separate field experiments and three separate mesocosm experiments were conducted. Each experiment included a rice monoculture (RM) treatment and a rice-aquatic animal (RA) coculture treatment; RA included feed addition for aquatic animals. In the field experiments, rice yield was higher with RA than with RM, and RA also produced aquatic animal yields that averaged 0.52–2.57 t ha-1. Compared to their corresponding RMs, the three RAs had significantly higher apparent nitrogen (N)-use efficiency and lower weed infestation, while soil N contents were stable over time. Dietary reconstruction analysis based on 13C and 15N showed that 16.0–50.2% of aquatic animal foods were from naturally occurring organisms in the rice fields. Stable-isotope-labeling (13C) in the field experiments indicated that the organic matter decomposition rate was greater with RA than with RM. Isotope 15N labeling in the mesocosm experiments indicated that rice used 13.0–35.1% of the aquatic animal feed-N. All these results suggest that rice-aquatic animal coculture increases food production, increases N-use efficiency, and maintains soil N content by reducing weeds and promoting decomposition and complementary N use. Our study supports the view that adding species to monocultures may enhance agroecosystem functions

A simple LC-ESI-MS method for the determination of norvancomycin in rat plasma and application to pharmacokinetic study

A simple and sensitive LC-ESI-MS method for determination of norvancomycin in plasma was developed and validated over the concentration range of 20-2,000 ng/mL. After addition of vancomycin as internal standard (IS), protein precipitation with 5 % trichloroacetic acid was employed for the sample preparation. Chromatographic separation was performed on a Zorbax SB-C18 (100 mm×2.1 mm, 3.5 μm) column with 10:90 (v/v) acetonitrile-0.1 % formic acid as mobile phase. The MS data acquisition was accomplished by selective ions monitoring (SIM) mode with positive electrospray ionization (ESI) interface. The limit of quantification (LOQ) was 20 ng/mL. For inter-day and intra-day tests, the precision (RSD) for the entire validation was less than 12 %. The developed method was successfully applied to pharmacokinetic studies of norvancomycin in rats following single intravenous administration dose of 10 mg/Kg.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Multiple positive solutions for singular higher-order semipositone fractional differential equations with p-Laplacian

In this article, together with Leggett–Williams and Guo–Krasnosel’skii fixed point theorems, height functions on special bounded sets are constructed to obtain the existence of at least three positive solutions for some higher-order fractional differential equations with p-Laplacian. The nonlinearity permits singularities both on the time and the space variables, and it also may change its sign

Target tracking in sensor networks using statistical graphical models

Recent advancement in sensor networks provides a platform for applications that requires in-network data fusion and parallel algorithms. However, processing data in parallel while propagating at low latency is very challenging. Also, implementation of these algorithms is limited by various constraints including energy, computation costs and complex network topology. In this paper, a statistical graphical model based algorithm is developed for in-network processing, which can be applied to tracking problems in the sensor networks. This algorithm represents the complex topology of a sensor network with a simple clique tree. It further utilizes the message passing algorithms to effectively make accurate inferences about the target location. The simulation shows that the algorithm can accurately track the target in a large scale random distributed sensor field with low complexity and low cost. The algorithm is also proved to be robust, as the simulation random disabled some sensors during the tracking phase. © 2008 IEEE

Near optimal two-tier target tracking in sensor networks

A distributed two-tier near optimal algorithm is proposed for target tracking in sensor networks. Tier one is a multiple hypothesis tracking (MHT) algorithm where the Viterbi algorithm is used. In this tier, only binary data is used to obtain a rough region around the target. Tier two improves the accuracy of the MHT decision by localized maximum likelihood. This reduces the computational complexity and the communication costs between sensors over the global maximum likelihood approach. It also results in higher sensor power efficiency, hence longer service time of the tracking network. This two-tier system is a distributed near optimal tracking algorithm. The localized maximum likelihood tracking can tolerate errors made by the Viterbi algorithm in tier one, hence the overall algorithm is robust. ©2007 IEEE