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Focusing on the problems of uncertainty and carbon emissions in the manufacturing process, this paper studies the low-carbon-emission scheduling optimization problem. Firstly, the variations in workpiece processing time and delivery date are selected as the uncertainty factors. A low-carbon-emission scheduling model for uncertain job shops is constructed with the optimization objectives of the time index, carbon emission index, and robustness index. Secondly, an improved third-generation non-dominated sorting genetic algorithm (NSGA-III) is proposed. Based on the original NSGA-III algorithm, this algorithm introduces the state transition algorithm to perform state transformation, neighborhood sampling, selection update, and alternate rotation operations on the parent population, generating new candidate solutions. Finally, the scheduling model and the improved algorithm are applied to a workshop example. Through case study computation and result analysis, the feasibility and effectiveness of the model and algorithm in addressing the low-carbon-emission job shop scheduling problem under uncertainty are further verified.

ABSTRACT Microbial symbiosis drives physiological processes of higher-order systems, including the acquisition and consumption of nutrients that support symbiotic partner reproduction. Metabolic analytics provide new avenues to examine how chemical ecology, or the conversion of existing biomass to new forms, changes over a symbiotic life cycle. We applied these approaches to the nematode Steinernema carpocapsae, its mutualist bacterium, Xenorhabdus nematophila, and the insects they infect. The nematode-bacterium pair infects, kills, and reproduces in an insect until nutrients are depleted. To understand the conversion of insect biomass over time into either nematode or bacterium biomass, we integrated information from trophic, metabolomic, and gene regulation analyses. Trophic analysis established bacteria as meso-predators and primary insect consumers. Nematodes hold a trophic position of 4.6, indicative of an apex predator, consuming bacteria and likely other nematodes. Metabolic changes associated with Galleria mellonella insect bioconversion were assessed using multivariate statistical analyses of metabolomics data sets derived from sampling over an infection time course. Statistically significant, discrete phases were detected, indicating the insect chemical environment changes reproducibly during bioconversion. A novel hierarchical clustering method was designed to probe molecular abundance fluctuation patterns over time, revealing distinct metabolite clusters that exhibit similar abundance shifts across the time course. Composite data suggest bacterial tryptophan and nematode kynurenine pathways are coordinated for reciprocal exchange of tryptophan and NAD+ and for synthesis of intermediates that can have complex effects on bacterial phenotypes and nematode behaviors. Our analysis of pathways and metabolites reveals the chemistry underlying the recycling of organic material during carnivory. IMPORTANCE The processes by which organic life is consumed and reborn in a complex ecosystem were investigated through a multiomics approach applied to the tripartite Xenorhabdus bacterium-Steinernema nematode-Galleria insect symbiosis. Trophic analyses demonstrate the primary consumers of the insect are the bacteria, and the nematode in turn consumes the bacteria. This suggests the Steinernema-Xenorhabdus mutualism is a form of agriculture in which the nematode cultivates the bacterial food sources by inoculating them into insect hosts. Metabolomics analysis revealed a shift in biological material throughout progression of the life cycle: active infection, insect death, and conversion of cadaver tissues into bacterial biomass and nematode tissue. We show that each phase of the life cycle is metabolically distinct, with significant differences including those in the tricarboxylic acid cycle and amino acid pathways. Our findings demonstrate that symbiotic life cycles can be defined by reproducible stage-specific chemical signatures, enhancing our broad understanding of metabolic processes that underpin a three-way symbiosis.

The rotation error is the most important quality characteristic index of a rotate vector (RV) reducer, and it is difficult to accurately optimize the design of a RV reducer, such as the Taguchi type, due to the many factors affecting the rotation error and the serious coupling effect among the factors. This paper analyzes the RV reducer rotation error and each factor based on the deep Gaussian processes (DeepGP) model and Sobol sensitivity analysis(SA) method. Firstly, using the optimal Latin hypercube sampling (OLHS) approach and the DeepGP model, a high-precision regression prediction model of the rotation error and each affecting factor was created. On the basis of the prediction model, the Sobol method was used to conduct a global SA of the factors influencing the rotation error and to compare the coupling relationship between the factors. The results show that the OLHS method and the DeepGP model are suitable for predicting the rotation error in this paper, and the accuracy of the prediction model constructed based on both of them is as high as 95%. The rotation error mainly depends on the influencing factors in the second stage cycloidal pinwheel drive part. The primary involute planetary part and planetary output carrier’s rotation error factors have little effect. The coupling effects between the matching clearance between the pin gear and needle gear hole (δJ) and the circular position error of the needle gear hole (δt) is noticeably stronger.

This paper proposes a new method for predicting rotation error based on improved grey wolf–optimized support vector regression (IGWO-SVR), because the existing rotation error research methods cannot meet the production beat and product quality requirements of enterprises, because of the disadvantages of its being time-consuming and having poor calculation accuracy. First, the grey wolf algorithm is improved based on the optimal Latin hypercube sampling initialization, nonlinear convergence factor, and dynamic weights to improve its accuracy in optimizing the parameters of the support vector regression (SVR) model. Then, the IGWO-SVR prediction model between the manufacturing error of critical parts and the rotation error is established with the RV-40E reducer as a case. The results show that the improved grey wolf algorithm shows better parameter optimization performance, and the IGWO-SVR method shows better prediction performance than the existing back propagation (BP) neural network and BP neural network optimized by the sparrow search algorithm rotation error prediction methods, as well as the SVR models optimized by particle swarm algorithm and grey wolf algorithm. The mean squared error of IGWO-SVR model is 0.026, the running time is 7.843 s, and the maximum relative error is 13.5%, which can meet the requirements of production beat and product quality. Therefore, the IGWO-SVR method can be well applied to the rotate vector (RV) reducer parts-matching model to improve product quality and reduce rework rate and cost.

ABSTRACT Animal-microbe symbioses are ubiquitous in nature and scientifically important in diverse areas, including ecology, medicine, and agriculture. Steinernema nematodes and Xenorhabdus bacteria compose an established, successful model system for investigating microbial pathogenesis and mutualism. The bacterium Xenorhabdus nematophila is a species-specific mutualist of insect-infecting Steinernema carpocapsae nematodes. The bacterium colonizes a specialized intestinal pocket within the infective stage of the nematode, which transports the bacteria between insects that are killed and consumed by the pair for reproduction. Current understanding of the interaction between the infective-stage nematode and its bacterial colonizers is based largely on population-level, snapshot time point studies on these organisms. This limitation arises because investigating temporal dynamics of the bacterium within the nematode is impeded by the difficulty of isolating and maintaining individual living nematodes and tracking colonizing bacterial cells over time. To overcome this challenge, we developed a microfluidic system that enables us to spatially isolate and microscopically observe individual, living Steinernema nematodes and monitor the growth and development of the associated X. nematophila bacterial communities—starting from a single cell or a few cells—over weeks. Our data demonstrate, to our knowledge, the first direct, temporal, in vivo visual analysis of a symbiosis system and the application of this system to reveal continuous dynamics of the symbiont population in the living host animal. IMPORTANCE This paper describes an experimental system for directly investigating population dynamics of a symbiotic bacterium, Xenorhabdus nematophila, in its host—the infective stage of the entomopathogenic nematode Steinernema carpocapsae. Tracking individual and groups of bacteria in individual host nematodes over days and weeks yielded insight into dynamic growth and topology changes of symbiotic bacterial populations within infective juvenile nematodes. Our approach for studying symbioses between bacteria and nematodes provides a system to investigate long-term host-microbe interactions in individual nematodes and extrapolate the lessons learned to other bacterium-animal interactions.

Entomopathogenic nematodes (EPNs), including Heterorhabditis and Steinernema, are parasitic to insects and contain mutualistically symbiotic bacteria in their intestines (Photorhabdus and Xenorhabdus, respectively) and therefore offer opportunities to study both mutualistic and parasitic symbiosis. The establishment of genetic tools in EPNs has been impeded by limited genetic tractability, inconsistent growth in vitro, variable cryopreservation, and low mating efficiency. We obtained the recently described Steinernema hermaphroditum strain CS34 and optimized its in vitro growth, with a rapid generation time on a lawn of its native symbiotic bacteria Xenorhabdus griffiniae. We developed a simple and efficient cryopreservation method. Previously, S. hermaphroditum isolated from insect hosts was described as producing hermaphrodites in the first generation. We discovered that CS34, when grown in vitro, produced consecutive generations of autonomously reproducing hermaphrodites accompanied by rare males. We performed mutagenesis screens in S. hermaphroditum that produced mutant lines with visible and heritable phenotypes. Genetic analysis of the mutants demonstrated that this species reproduces by self-fertilization rather than parthenogenesis and that its sex is determined chromosomally. Genetic mapping has thus far identified markers on the X chromosome and three of four autosomes. We report that S. hermaphroditum CS34 is the first consistently hermaphroditic EPN and is suitable for genetic model development to study naturally occurring mutualistic symbiosis and insect parasitism. [ABSTRACT FROM AUTHOR]

Xenorhabdus nematophila bacteria are mutualistic symbionts of Steinernema carpocapsae nematodes and pathogens of insects. The X. nematophila global regulator Lrp controls the expression of many genes involved in both mutualism and pathogenic activities, suggesting a role in the transition between the two host organisms. We previously reported that natural populations of X. nematophila exhibit various levels of Lrp expression and that cells expressing relatively low levels of Lrp are optimized for virulence in the insect Manduca sexta. The adaptive advantage of the high-Lrp-expressing state was not established. Here we used strains engineered to express constitutively high or low levels of Lrp to test the model in which high-Lrp-expressing cells are adapted for mutualistic activities with the nematode host. We demonstrate that high-Lrp cells form more robust biofilms in laboratory media than do low-Lrp cells, which may reflect adherence to host tissues. Also, our data showed that nematodes cultivated with high-Lrp strains are more frequently colonized than are those associated with low-Lrp strains. Taken together, these data support the idea that high-Lrp cells have an advantage in tissue adherence and colonization initiation. Furthermore, our data show that high-Lrp-expressing strains better support nematode reproduction than do their low-Lrp counterparts under both in vitro and in vivo conditions. Our data indicate that heterogeneity of Lrp expression in X. nematophila populations provides diverse cell populations adapted to both pathogenic (low-Lrp) and mutualistic (high-Lrp) states. IMPORTANCE Host-associated bacteria experience fluctuating conditions during both residence within an individual host and transmission between hosts. For bacteria that engage in evolutionarily stable, long-term relationships with particular hosts, these fluctuations provide selective pressure for the emergence of adaptive regulatory mechanisms. Here we present evidence that the bacterium Xenorhabdus nematophila uses various levels of the transcription factor Lrp to optimize its association with its two animal hosts, nematodes and insects, with which it behaves as a mutualist and a pathogen, respectively. Building on our previous finding that relatively low cellular levels of Lrp are optimal for pathogenesis, we demonstrate that, conversely, high levels of Lrp promote mutualistic activities with the Steinernema carpocapsae nematode host. These data suggest that X. nematophila has evolved to utilize phenotypic variation between high- and low-Lrp-expression states to optimize its alternating behaviors as a mutualist and a pathogen. [ABSTRACT FROM AUTHOR]

Temperature-dependent surface current measurements were performed to analyze the mechanism of surface conductance of AlGaN/GaN channel high-electron-mobility transistors by utilizing process-optimized double gate structures. Different temperatures and electric field dependence have been found in surface current measurements. At low electric field, the mechanism of surface conductance is considered to be two-dimensional variable range hopping. At elevated electric field, the Frenkel-Poole trap assisted emission governs the main surface electrons transportation. The extracted energy barrier height of electrons emitting from trapped state near Fermi energy level into a threading dislocations-related continuum state is 0.38 eV. SiN passivation reduces the surface leakage current by two order of magnitude and nearly 4 orders of magnitude at low and high electric fields, respectively. SiN also suppresses the Frenkel-Poole conductance at high temperature by improving the surface states of AlGaN/GaN. A surface treatment process has been introduced to further suppress the surface leakage current at high temperature and high field, which results in a decrease in surface current of almost 3 orders of magnitude at 476 K. [ABSTRACT FROM AUTHOR]

In mutually beneficial and pathogenic symbiotic associations, microbes must adapt to the host environment for optimal fitness. Both within an individual host and during transmission between hosts, microbes are exposed to temporal and spatial variation in environmental conditions. The phenomenon of phenotypic variation, in which different subpopulations of cells express distinctive and potentially adaptive characteristics, can contribute to microbial adaptation to a lifestyle that includes rapidly changing environments. The environments experienced by a symbiotic microbe during its life history can be erratic or predictable, and each can impact the evolution of adaptive responses. In particular, the predictability of a rhythmic or cyclical series of environments may promote the evolution of signal transduction cascades that allow preadaptive responses to environments that are likely to be encountered in the future, a phenomenon known as adaptive prediction. In this review, we summarize environmental variations known to occur in some well-studied models of symbiosis and how these may contribute to the evolution of microbial population heterogeneity and anticipatory behavior. We provide details about the symbiosis between Xenorhabdus bacteria and Steinernema nematodes as a model to investigate the concept of environmental adaptation and adaptive prediction in a microbial symbiosis. [ABSTRACT FROM AUTHOR]

A high-efficiency C-band internally matched power amplifier, developed with 12 mm AlGaN/GaN high-electron mobility transistors is described. The second-harmonic frequency (2f0) tuning network is applied to confine the impedance at 2f0 in safe efficiency regions. The packaged power amplifier achieves 71% power-added efficiency (PAE) and 102 W output power, associated with 17 dB power gain. The PAE is believed to be the highest of the C-band GaN power amplifiers reported to date. [ABSTRACT FROM AUTHOR]