Investigating the membrane morphology of water/solvent/nylon 6 systems

In this study, nylon 6 membranes were prepared in a water coagulation bath with two types of solvents, CaCl₂–methanol (CaClMe) and formic acid (FA). The morphology of the membranes, which was controlled by the phase behavior of their solutions, were connected to the mechanism of demixing, including liquid–liquid and liquid‐crystallization. Ternary phase diagrams showed that the CaClMe system coagulated significantly faster than the FA system. As observed by scanning electron microscopy, the CaClMe membrane had a porous, interconnected pore structure with macrovoids, whereas the FA membrane had a dense, spherulitic surface with a closed cell morphology. The high reaction surface of the CaClMe membrane with dye molecules provided outstanding dye rejection. Also, thermal analysis by differential scanning calorimetry showed that the slow coagulation of the FA system facilitated the formation of stable α‐form crystals rather than a metastable γ‐form structure. The results show that the phase‐separation mechanism was switched from liquid–liquid to liquid‐crystallization through a change in the solvent type from CaClMe to FA. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Application of ANFIS to predict crop yield based on different energy inputs

In this paper, adaptive neuro-fuzzy inference system (ANFIS) was used to predict the grain yield of irrigated wheat in Abyek town of Ghazvin province, Iran. Due to large number of inputs (eight inputs) for ANFIS, the input vector was clustered into two groups and two networks were trained. Inputs for ANFIS 1 were diesel fuel, fertilizer and electricity energies and for ANFIS 2 were human labor, machinery, chemicals, water for irrigation and seed energies. The RMSE and R² values were found 0.013 and 0.996 for ANFIS 1 and 0.018 and 0.992 for ANFIS 2, respectively. These results showed that ANFIS 1 and ANFIS 2 could well predict the yield. Finally, the predicted values of the two networks were used as inputs to the third ANFIS. The results indicated that the energy inputs in ANFIS 1 have a greater impact on the final yield production than other energy inputs. Also, the RMSE and R² values for ANFIS 3 were 0.013 and 0.996, respectively. These results showed that ANFIS 1 and the combined network (ANFIS 3) could both predict the grain yield with good accuracy.     

Machine-Learning-Based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and Its Components

A genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering marker-trait associations (MTAs) for complex traits in plant species. Insufficient statistical power is a limiting factor, especially in narrow genetic basis species, that conventional GWAS methods are suffering from. Using sophisticated mathematical methods such as machine learning (ML) algorithms may address this issue and advance the implication of this valuable genetic method in applied plant-breeding programs. In this study, we evaluated the potential use of two ML algorithms, support-vector machine (SVR) and random forest (RF), in a GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying MTAs for soybean-yield components. In this study, important soybean-yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and maturity, were assessed using a panel of 227 soybean genotypes evaluated at two locations over two years (four environments). Using the SVR-mediated GWAS method, we were able to discover MTAs colocalized with previously reported quantitative trait loci (QTL) with potential causal effects on the target traits, supported by the functional annotation of candidate gene analyses. This study demonstrated the potential benefit of using sophisticated mathematical approaches, such as SVR, in a GWAS to complement conventional GWAS methods for identifying MTAs that can improve the efficiency of genomic-based soybean-breeding programs.     

Texture‐based parametric active contour for target detection and tracking

In recent years, active contour models (ACM) have been considered as powerful tools for image segmentation and object tracking in computer vision and image processing applications. This article presents a new tracking method based on parametric active contour models. In the proposed method, a new pressure energy called “texture pressure energy” is added to the energy function of the parametric active contour model to detect and track a texture target object in a texture background. In this scheme, the texture features of the contour are calculated by a moment‐based method. Then, by comparing these features with texture features of the target object, the contour curve is expanded or contracted to be adapted to the object boundaries. Experimental results show that the proposed method is more efficient and accurate in the tracking of objects compare to the traditional ones, when both object and background are textures in nature. © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 187–198, 2009     

LTL is closed under topological closure

We constructively prove that for every LTL formula φ, the smallest safety property containing the property expressed by φ is also expressible in LTL. It immediately follows that LTL admits the safety-liveness decomposition: any property expressed by an LTL formula is equivalent to the intersection of a safety property and a liveness property, both of them expressible in LTL. Our proof is based on constructing a minimal deterministic counter-free Büchi automaton that recognizes the smallest safety property containing the property expressed by φ.     

Enhanced joint pricing and lotsizing problem in a two-echelon supply chain with logit demand function

In retail supply chains, ordering and pricing policies for the retailer and shipment plan for the supplier are the most important decisions. These policies are often conducted either individually or sequentially with poor overall performance for the whole supply chain resulting to extra inventory and other deficiencies. In this paper, an integrated marketing-inventory model in a two-echelon supply chain model is developed involving discount promotion, customer behaviour more realistically and operations aspects to determine optimal ordering, shipping and pricing quantities simultaneously. An efficient analytical solution procedure and a Particle Swarm Optimisation solution algorithm are also developed. Finally, a number of numerical tests are conducted to approve the interesting theoretical results of the analytical approach.     

Thermal performance and efficiency of convective–radiative T-shaped fins with temperature dependent thermal conductivity,heat transfer coefficient and surface emissivity

This paper analytically investigates the thermal performance of convective–radiative T-shape fin with simultaneous variation of thermal conductivity, heat transfer coefficient and surface emissivity with temperature. Unlike some other fin studies, the sink temperatures for convection and radiation are assumed to be non-zero. This model is a more realistic representation of fins in actual engineering practice. The collection of graphs provided should facilitate design and performance evaluation of T-shaped fins.     

Experimental Verification of the Averaged Strain Energy Density Criterion for Brittle Fracture in Blunt V-Notches under Pure Compression

Strength of Materials - The goal of the present study is to verify experimentally the Averaged Strain Energy Density (ASED) criterion for brittle fracture in blunt V-notches under pure compression....     

Novel Metamaterial Compact Planar MIMO Antenna Systems with Improved Isolation for WLAN Application

In this paper, two element multiple input–multiple output (MIMO) meander line antenna systems with improved isolation performance and compact size are proposed and fabricated in WLAN frequency band. To increase isolation among antenna elements, a novel metamaterial spiral S-shaped resonator is embedded between two radiating elements. The proposed resonator has planar configuration and miniaturized size and is capable of blocking electromagnetic propagation between antenna elements by exhibiting negative effective permeability in the desired frequency band. To illustrate and evaluate the design process, two design samples are fabricated and tested in WLAN frequency band and the agreement among measurement and simulation results approves the design method. In the frequency range of 2.38–2.48 GHz, some MIMO communication system requirements like total active reflection coefficient, envelope correlation coefficient and capacity loss are tested on design samples which show satisfactory results, so this method can be employed in designing array antennas for small mobile communication systems. The designed MIMO antenna systems separated by 13.8 mm (less than λ/9), has better than ??40 dB isolation coefficient and near zero correlation coefficient and capacity loss at the operating frequency (2.4 GHz).