Biosynthesis and PBAN-Regulated Transport of Pheromone Polyenes in the Winter Moth, Operophtera brumata

The trienoic and tetraenoic polyenes, (3Z,6Z,9Z)-3,6,9-nonadecatriene, (3Z,6Z,9Z)-3,6,9-henicosatriene, and (3Z,6Z,9Z)-1,3,6,9-henicosatetraene were found in the abdominal cuticle and pheromone gland of the winter moth Operophtera brumata L. (Lepidoptera: Geometridae), in addition to the previously identified single component sex pheromone (3Z,6Z,9Z)-1,3,6,9-nonadecatetraene. The pheromone biosynthesis activating neuropeptide (PBAN) is involved in the regulation of polyene transport from abdominal cuticle to the pheromone gland. In vivo deuterium labeling experiments showed that (11Z,14Z,17Z)-11,14,17-icosatrienoic acid, the malonate elongation product of linolenic acid, (9Z,12Z,15Z)-9,12,15-octadecatrienoic acid, is used to produce (3Z,6Z,9Z)-3,6,9-nonadecatriene and (3Z,6Z,9Z)-1,3,6,9-nonadecatetraene.     

Integration of machine learning and first principles models

Model building and parameter estimation are traditional concepts widely used in chemical, biological, metallurgical, and manufacturing industries. Early modeling methodologies focused on mathematically capturing the process knowledge and domain expertise of the modeler. The models thus developed are termed first principles models (or white-box models). Over time, computational power became cheaper, and massive amounts of data became available for modeling. This led to the development of cutting edge machine learning models (black-box models) and artificial intelligence (AI) techniques. Hybrid models (gray-box models) are a combination of first principles and machine learning models. The development of hybrid models has captured the attention of researchers as this combines the best of both modeling paradigms. Recent attention to this field stems from the interest in explainable AI (XAI), a critical requirement as AI systems become more pervasive. This work aims at identifying and categorizing various hybrid models available in the literature that integrate machine-learning models with different forms of domain knowledge. Benefits such as enhanced predictive power, extrapolation capabilities, and other advantages of combining the two approaches are summarized. The goal of this article is to consolidate the published corpus in the area of hybrid modeling and develop a comprehensive framework to understand the various techniques presented. This framework can further be used as the foundation to explore rational associations between several models.     

Adaptive optimal control without weight transport

Many neural control systems are at least roughly optimized, but how is optimal control learned? There are algorithms for this purpose, but in their current forms, they are not suited for biological neural networks because they rely on a type of communication that is not available in the brain, namely, weight transport-transmitting the strengths, or "weights," of individual synapses to other synapses and neurons. Here we show how optimal control can be learned without weight transport. Our method involves a set of simple mechanisms that can compensate for the absence of weight transport in the brain and so may be useful for neural computation generally.     

CO oxidation over Au/TiO2 prepared from metal-organic gold complexes

A series of Au/TiO₂ catalysts has been prepared from precursors of various metal-organic gold complexes (Au _n , n = 2–4) and their catalytic activity for CO oxidation studied. The Au/TiO₂ catalyst synthesized from a tetranuclear gold complex shows the best performance for CO oxidation with transmission electron microscopy of this catalyst indicating an average gold particle size of 3.1 nm.     

Olfactory reception of potential pheromones and plant odors by tarnished plant bug,Lygus lineolaris (Hemiptera: Miridae)

Olfactory reception of potential pheromones and host-plant odors by male and female tarnished plant bugs (TPBs),Lygus lineolaris (Hemiptera: Miridae), was investigated by utilizing electroantennogram (EAG) techniques. In general, EAGs were similar between the sexes. Among 31 compounds of seven chemical groups tested, insect-produced butyrates and host-plant-containing green leaf volatiles (GLVs) were the most active. Hexyl butyrate and (E)-2-hexenyl butyrate elicited greater EAGs in males than in females. Females responded with significantly greater EAGs to alcohol and aldehyde GLVs than to their acetate derivatives. Among GLVs, sexual dimorphism was also observed in response to (E)-2-hexenol and (E)-2-hexenal. Females were more sensitive to the monoterpene geraniol than were males. While nonanal was the most stimulatory compound tested, no sexual differences in EAGs to this compound were observed. These studies reveal olfactory receptors on TPB antennae responsive to insect and host-plant volatiles that are likely to play a role in host finding and sexual attraction.     

Business-to-business e-commerce adoption: An empirical investigation of business factors

We develop an overarching model to explain the adoption of business-to-business e-commerce using five business factors: external environment, organizational context, decision-maker’s characteristics, technology context, and organizational learning. Data collected from IS executives was analyzed using logistic regression. Our model has a good fit with over 77 % variance explained. Findings indicate that the existence of informal interest groups, and the tolerant attitude of decision makers towards negative information about business-to-business e-commerce have significant influence on the adoption decision. In addition, our results indicate that price intensity and perceived barriers negatively affect the adoption decision.     

Influence of Rolling Path on Microstructure and Mechanical Properties in EB Refined Tantalum

This work reports the effectiveness of multidirectional forging in breaking up the as-cast microstructure, and also discusses the influence of variation in rolling path on the homogeneity and grain size in heavily deformed tantalum (Ta) plates that are subjected to static recrystallization annealing. Ingots of electron-beam-refined, Ta were multi-directionally forged and subsequently cold rolled to a strain of 250?%. Cold rolling was performed in three distinct modes and the effect of the change in the rolling path on the microstructure and mechanical properties in as-rolled and annealed condition were investigated. The influence of such rolling path was found to be significantly strong. Results show that the kinetics of static recrystallization in differently rolled products are equal. Microstructural evaluation has revealed a high degree of homogeneity and elimination of orientation effects in cross rolled products. Discussion on the hardness and tensile properties in various conditions is also presented.     

High Na‐ion conducting Na1+x[SnxGe2−x(PO4)3] glass‐ceramic electrolytes: Structural and electrochemical impedance studies

Na‐ion conducting Na_1+x[Sn_xGe_2?x(PO₄)₃] (x = 0, 0.25, 0.5, and 0.75 mol%) glass samples with NASICON‐type phase were synthesized by the melt quenching method and glass‐ceramics were formed by heat treating the precursor glasses at their crystallization temperatures. XRD traces exhibit formation of most stable crystalline phase NaGe₂(PO₄)₃ (ICSD‐164019) with trigonal structure. Structural illustration of sodium germanium phosphate [NaGe₂(PO₄)₃] displays that each germanium is surrounded by 6 oxygen atom showing octahedral symmetry (GeO₆) and phosphorous with 4 oxygen atoms showing tetrahedral symmetry (PO₄). The highest bulk Na⁺ ion conductivities and lowest activation energy for conduction were achieved to be 8.39 × 10^?05 S/cm and 0.52 eV for the optimum substitution levels (x = 0.5 mol%, Na_1.5[Sn_0.5Ge_1.5(PO₄)₃]) of tetrahedral Ge⁴⁺ ions by Sn⁴⁺ on Na–Ge–P network. CV studies of the best conducting Na_1.5[Sn_0.5Ge_1.5(PO₄)₃] glass‐ceramic electrolyte possesses a wide electrochemical window of 6 V. The structural and EIS studies of these glass‐ceramic electrolyte samples were monitored in light of the substitution of Ge by its larger homologue Sn.