Predicting Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae) populations and associated grain damage in smallholder farmers’ maize stores: A machine learning approach

Prostephanus truncatus is a notorious pest of stored-maize grain and its spread throughout sub-Saharan Africa has led to increased levels of grain storage losses. The current study developed models to predict the level of P. truncatus infestation and associated damage of maize grain in smallholder farmer stores. Data were gathered from grain storage trials conducted in Hwedza and Mbire districts of Zimbabwe and correlated with weather data for each site. Insect counts of P. truncatus and other common stored grain insect pests had a strong correlation with time of year with highest recorded numbers from January to May. Correlation analysis showed insect-generated grain dust from boring and feeding activity to be the best indicator of P. truncatus presence in stores (r = 0.70), while a moderate correlation (r = 0.48) was found between P. truncatus numbers and storage insect parasitic wasps, and grain damage levels significantly correlated with the presence of Tribolium castaneum (r = 0.60). Models were developed for predicting P. truncatus infestation and grain damage using parameter selection algorithms and decision-tree machine learning algorithms with 10-fold cross-validation. The P. truncatus population size prediction model performance was weak (r = 0.43) due to the complicated sampling and detection of the pest and eight-week long period between sampling events. The grain damage prediction model had a stronger correlation coefficient (r = 0.93) and is a good estimator for in situ stored grain insect damage. The models were developed for use under southern African climatic conditions and can be improved with more input data to create more precise models for building decision-support tools for smallholder maize-based production systems.     

The effect of synthesis conditions on the physicochemical properties of magnesium aluminate materials

Magnesium aluminate-based materials were prepared by applying different methods: (i) mechanochemical milling of the initial mixture of magnesium and aluminium nitrate powders (in appropriate stoichiometric amounts) followed by heat treatment at temperatures of 650 °C and 850 °C and (ii) melting of the mixture of nitrate precursors at 240 °C followed by thermal treatment at 650 °C, 750 °C and 850 °C. The effect of synthesis method on the structure and morphology of the obtained solids was studied by using various techniques such as: nitrogen adsorption-desorption isotherms, powder XRD, IR spectroscopy and SEM. It was shown that the mechanochemical milling performed before calcination procedure leads to obtaining of nanocrystalline magnesium aluminate spinel phase at lower temperature of 650 °C in comparison with the method using thermal treatment only (at 750 °C). The obtained nanomaterials exhibit mesoporous structure.     

Bioinformatic characterization of the extracellular lipases from Kluyveromyces marxianus

Lipases are hydrolytic enzymes that break the ester bonds of triglycerides, generating free fatty acids and glycerol. Extracellular lipase activity has been reported for the nonconventional yeast Kluyveromyces marxianus, grown in olive oil as a substrate, and the presence of at least eight putative lipases has been detected in its genome. However, to date, there is no experimental evidence on the physiological role of the putative lipases nor their structural and catalytic properties. In this study, a bioinformatic analysis of the genes of the putative lipases from K. marxianus L-2029 was performed, particularly identifying and characterizing the extracellular expected enzymes, due to their biotechnological relevance. The amino acid sequence of 10 putative lipases, obtained by in silico translation, ranged between 389 and 773 amino acids. Two of the analysed putative proteins showed a signal peptide, 25 and 33 amino acids long for KmYJR107Wp and KmLIP3p, and a molecular weight of 44.53 and 58.23 kDa, respectively. The amino acid alignment of KmLIP3p and KmYJR107Wp with the crystallized lipases from a patatin and the YlLip2 lipase from Yarrowia lipolytica, respectively, revealed the presence of the hydrolase characteristic motifs. From the 3D models of putative extracellular K. marxianus L-2029 lipases, the conserved pentapeptide of each was determined, being GTSMG for KmLIP3p and GHSLG for KmYJR107Wp; besides, the genes of these two enzymes (LIP3 and YJR107W) are apparently regulated by oleate response elements. The phylogenetic analysis of all K. marxianus lipases revealed evolutionary affinities with lipases from abH15.03, abH23.01, and abH23.02 families.     

数控机床逐点比较法插补直线分析

通过分析四方向逐点比较法的基本原理及基本特点说明其插补精度比较低的原因,提出提高插补精度的方法——八方向逐点比较插补法。     

CD++: a toolkit to develop DEVS models

The features of a toolkit for modeling and simulation based on the DEVS formalism are presented. The tool is built as a set of independent software pieces running on different platforms. Not only are the main characteristics of the environment presented, a focus on its use is also considered by inclusion of application examples for a variety of problems. Many models can be defined in an automated fashion, simplifying the construction of new models and easing their verification. The use of this formal approach has allowed the development of safe and cost‐effective simulations, significantly reducing development time. Copyright © 2002 John Wiley & Sons, Ltd.     

Life cycle of hydroprocessing catalysts and total catalyst management

Hydroprocessing catalysts based on Ni, Co, Mo and W are used in various refinery processing applications where several deactivation mechanisms become of importance (coke formation, active phase sintering, metals deposition, poisoning) in the catalyst's life cycle. The life cycle of commercial hydroprocessing catalysts is very complex and includes the catalyst production, sulfidation, use, oxidative regeneration followed by re-sulfidation and reuse or, if reuse is not possible, recycling or disposal. To understand the changes in catalyst properties taking place during a life cycle, the catalyst quality in the different stages can be best monitored by using advanced analytical techniques. The catalyst's life cycle is further complicated by numerous technical, environmental and organizational issues involved. In principle, different companies can be involved in each of the life cycle steps. Leading catalyst manufacturers, together with specialized firms, offer refineries a total catalyst management concept, starting with the purchase of the fresh catalyst and ending with its final recycling or disposal. Total catalyst management includes a broad range of services, ensuring optimal timing during the change-out process, reliable, smooth and safe operations, minimal downtime and maximum catalyst and unit performance.     

Method to Characterize the Air Flow and Water Removal Characteristics During Vacuum Dewatering. Part II—Analysis and Characterization

This is part II of a study reported earlier on a method to characterize the air flow and water removal characteristics during vacuum dewatering. This article presents experimental data and analysis of results from the use of a cyclically actuated vacuum dewatering device for removing moisture from wetted porous materials such as paper with the intermittent application of vacuum and accompanying air flow though the material. Results presented include sheet moisture content as a function of residence time and hence water removal rate under a variety of process conditions. Also, experimental results on air flow through the wet porous structure and hence the role and importance of air flow during vacuum dewatering are presented. Vacuum dewatering process conditions include exit solids content between 11 and 20% solid under applied vacuum conditions of 13.5 to 67.7 kPa (4 to 20 in. Hg). Regression analysis indicated that the exit sheet moisture content exhibited a nonlinear relationship with residence time with exit solids reaching a plateau after a certain residence time. Final moisture content correlated linearly with the average overall flow rate of air through the paper sample and the basis weight of the material.     

An investigation into physicochemical characteristics of ash produced from combustion of oil palm biomass wastein a boiler

Ash derived from combustion of Malaysian oil palm biomass (empty fruit bunches consisting of fibers) was physically and chemically characterized in order to provide a comprehensive understanding of its specific properties in terms of toxicity, compositions and reusability. Principal analyses conducted include particle size distribution, scanning electron microscopy, elemental dispersive X-ray, elemental analysis, toxicity characteristic leaching procedure (TCLP) as well as thermogravimetric, X-ray diffractometry and Fourier-transform infrared analyses. TCLP result indicated that the oil palm ash (OPA) should not be classified as toxic wastes in terms of heavy metal leachability since leachable copper, cadmium, lead and nickel concentrations were detected below the stipulated leachability limits. It was determined that the OPA contained high amount of potassium as well as presence of silica which implied its suitability to be reused as crude fertilizer or cement replacement material.     

A place for Bobo in play therapy.

Some therapists hold that the Bobo and other aggressive toys should be excluded from the playroom as they elicit acting-out behavior that is transferred to the world outside the playroom. However, many therapists view the inclusion of these items as imperative elements that facilitate positive growth and maturation in the child. Interviews with authorities in the field of play therapy support the position that the inclusion of the Bobo is not only useful, but a therapeutic necessity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Issues in nonlinear stochastic grey box identification

Grey box identification refers to the practice of identifying dynamical systems in model structures exploiting partial prior information. This contribution reviews a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes. Issues to be addressed include advantages and costs of introducing stochastics into the model, the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.