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.     

Finite element optimization of sample geometry for measuring the torsional shear strength of glass/metal joints

Assessment of mechanical properties of glass/metal joints is a challenging process, especially when the application relevant conditions of the joints have to be considered in the test design. In this study, a finite element method (FEM) is implemented to analyze a torsional shear strength test designed for glass-ceramic/steel joints aiming towards solid oxide fuel/electrolysis cells application. Deviations from axial symmetry of the square flanges (ends) of respective hourglass-shaped specimens and also supporting and loading sockets of the test set-up are included in the model to simulate conditions close to reality. Undesirable tensile stress and also shear stress concentration appear at the outer edge of glass-ceramic layers, which are less for the hollow-full specimen. The simulation results show that for a specimen with either 9 mm thick square- or 6 mm thick triangular-flanges, locally enhanced tensile stresses almost disappear, resulting in a symmetric shear stress distribution. The difference between the analytically derived nominal shear strength and the real critical shear stress derived via simulation reduces with decreasing the fracture torque.     

A GIS plug-in for Bayesian belief networks: Towards a transparent software framework to assess and visualise uncertainties in ecosystem service mapping

The complexity and spatial heterogeneity of ecosystem processes driving ecosystem service delivery require spatially explicit models that take into account the different parameters affecting those processes. Current attempts to model ecosystem service delivery on a broad, regional scale often depend on indicator-based approaches that are generally not able to fully capture the complexity of ecosystem processes. Moreover, they do not allow quantification of uncertainty on their predictions. In this paper, we discuss a QGIS plug-in which promotes the use of Bayesian belief networks for regional modelling and mapping of ecosystem service delivery and associated uncertainties. Different types of specific Bayesian belief network output maps, delivered by the plug-in, are discussed and their decision support capacities are evaluated. This plug-in, used in combination with firmly developed Bayesian belief networks, has the potential to add value to current spatial ecosystem service accounting methods. The plug-in can also be used in other research domains dealing with spatial data and uncertainty.     

蓝藻基生物降解共混膜的力学性能

以聚乙烯醇(PVA)和水华蓝藻为主要原料,通过溶液铺膜法制备了蓝藻/PVA共混膜,采用万能试验机,研究了不同助剂对蓝藻/PVA共混膜力学性能的影响。结果表明,蓝藻的添加显著降低了共混膜的力学性能。当添加比例为PVA的1/2时,膜的拉伸强度和断裂伸长率分别比无藻处理下降了65.89%和79.57%。甘油、尿素显著提升了蓝藻/PVA共混膜的断裂伸长率,当添加比例为蓝藻的1/2时,分别能使共混膜的断裂伸长率提高73.20倍和62.02倍。虽然柠檬酸、硅烷偶联剂能够提升蓝藻/PVA共混膜的拉伸强度,但只能在低剂量时促进断裂伸长率的小幅提高,当柠檬酸添加比例为蓝藻的1/40时,膜的断裂伸长率能提高4.41倍,而当硅烷偶联剂添加比例为蓝藻的1/20时,膜的断裂伸长率能提高1.49倍。尿素与甘油复合增塑,更有利于提升共混膜的断裂伸长率。硅烷偶联剂与甘油复合增塑,更有利于提升共混膜的拉伸强度。     

Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.     

Electrochemically deposited Fe2O3 nanorods on carbon nanofibers for free-standing anodes of lithium-ion batteries

Fe₂O₃ nanorod/carbon nanofiber (CNF) composites were prepared by the electrochemical deposition of Fe₂O₃ on a web of CNFs, which was then used as a free-standing anode. The conductive, three-dimensional structure of the CNF web allowed for the electrodeposition of the Fe₂O₃ nanorods, while its high conductivity made it possible to use the composite as a free-standing electrode in lithium-ion batteries. In addition, it was easy and cheap to fabricate by a simplification of a process of cell preparation. The nanorod-like Fe₂O₃ structures could only be electrodeposited on the CNFs; flake-like Fe₂O₃ was formed on flat conductive glass substrates. It can be attributed to the different growth mechanism of Fe₂O₃ on the CNFs because of the large number of reaction sites on the CNFs, differences in the precursor concentration and diffusivity within the CNF web. The formation of aggregates of the Fe₂O₃ particles on thicker CNFs also indicated that the CNFs had determined the Fe₂O₃ growth mechanism. The synthesised Fe₂O₃/CNF composite electrode exhibited stable rate capacities at different current densities. This suggested that CNF-based composite did not exhibit the intrinsic disadvantages of Fe₂O₃. Finally, carbon coatings were deposited on the Fe₂O₃/CNF composites to further improve their electronic conductivity and rate capability.     

基于力测量法研究滑石的晶面各向异性

层状硅酸盐矿物滑石在解离时会形成具有明显性质差异的2种表面，滑石的晶面各向异性会导致矿物不同表面表现出不同的润湿性以及不同的电荷密度。通过原子力显微镜力（AFM）曲线测量以及经典DLVO理论计算，对滑石的非极性面和极性面进行深入研究，首先利用AFM力曲线测量和计算，得到不同pH值时氮化硅的电位值，利用AFM直接力测量法对符合粗糙度要求的滑石非极性面和极性面样品在10 mmol/L的KCl溶液中进行测量，得到不同pH值环境下的力曲线，通过DLVO理论拟合计算得到滑石非极性面和极性面的表面电位值。滑石的非极性面电位值在研究的pH范围内一直为负，且恒定，极性面电位值随pH升高而降低，零电点出现在pH=7.6左右。将计算得到的滑石表面电位与氮化硅之间的作用力拟合曲线与实际测得的作用力进行对比发现，计算值与测量值基本一致，拟合度较高。     

Model checking temporal knowledge and commitments in multi-agent systems using reduction

Though modeling and verifying Multi-Agent Systems (MASs) have long been under study, there are still challenges when many different aspects need to be considered simultaneously. In fact, various frameworks have been carried out for modeling and verifying MASs with respect to knowledge and social commitments independently. However, considering them under the same framework still needs further investigation, particularly from the verification perspective. In this article, we present a new technique for model checking the logic of knowledge and commitments (CTLKC⁺). The proposed technique is fully-automatic and reduction-based in which we transform the problem of model checking CTLKC⁺ into the problem of model checking an existing logic of action called ARCTL. Concretely, we construct a set of transformation rules to formally reduce the CTLKC⁺ model into an ARCTL model and CTLKC⁺ formulae into ARCTL formulae to get benefit from the extended version of NuSMV symbolic model checker of ARCTL. Compared to a recent approach that reduces the problem of model checking CTLKC⁺ to another logic of action called GCTL¹, our technique has better scalability and efficiency. We also analyze the complexity of the proposed model checking technique. The results of this analysis reveal that the complexity of our reduction-based procedure is PSPACE-complete for local concurrent programs with respect to the size of these programs and the length of the formula being checked. From the time perspective, we prove that the complexity of the proposed approach is P-complete with regard to the size of the model and length of the formula, which makes it efficient. Finally, we implement our model checking approach on top of extended NuSMV and report verification results for the verification of the NetBill protocol, taken from business domain, against some desirable properties. The obtained results show the effectiveness of our model checking approach when the system scales up.     

非连续采空区矿柱力学分析的数值模拟

为探讨非连续采空区矿柱力学原理，通过FLAC3D数值模拟技术，对下向水平分层进路式胶结充填采矿法开采形成的非连续采空区中矿柱的受力状态进行了分析。研究表明，非连续采空区中矿柱所受的力主要为覆岩的自重应力，水平应力对其影响不大；随着埋深的增加矿柱承受的垂直方向的力近似呈直线增加；随着非连续采空区跨度的增加（进路数量增加），非连续采空区受垂直方向的应力逐渐由围岩两侧向矿柱中间过渡。     

Enhanced properties for visible-light-driven photocatalysis of Ag nanoparticle modified Bi2MoO6 nanoplates

The visible light driven Bi₂MoO₆ photocatalyst doped with different contents of Ag nanoparticles was successfully synthesized by a combination of hydrothermal and sonochemical methods. The as-synthesized samples were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning and transmission electron microscopy (SEM and TEM) and UV–visible spectroscopy to investigate crystalline structure, morphology, composition and photocatalytic properties. XRD patterns and TEM images of the samples revealed pure phase orthorhombic Bi₂MoO₆ nanoplates without any detection of Ag dopant due to its low concentration and very tiny particle size. TEM images showed that Ag nanoparticles with the size of 10–15 nm were dispersed randomly on the surface of Bi₂MoO₆. The XPS analysis of Ag/Bi₂MoO₆ nanocomposites revealed the presence of additional metallic Ag. Photocatalytic activities of the Ag/Bi₂MoO₆ nanocomposites were evaluated by determining the degradation of rhodamine B (RhB) under visible light radiation. In this research, the 10 wt% Ag/Bi₂MoO₆ nanocomposites showed the best photocatalytic activity. The results suggest that the dispersion of Ag nanoparticles on the surface of Bi₂MoO₆ significantly enhances its photocatalytic activity.