Ultralow Voltage Nanoelectronics Powered Directly, and Solely, From a Tree

Complex patterns of electrical potential differences exist across the structure of a tree. We have characterized these voltages, and measured values ranging from a few millivolts to a few hundred millivolts for Bigleaf maple trees. These potential differences provide a unique opportunity to power nanoelectronic circuits directly from a tree. We have designed, constructed, and successfully tested two ICs, powered solely through a connection to Bigleaf maple trees. The first circuit, built in a 130-nm technology, creates a stable 1.1 V supply from input voltages as low as 20 mV, and can be deployed to generate a usable voltage level for standard circuits. The second circuit, fabricated in 90-nm technology is a timer, operating at 0.045 Hz and can be used for time keeping in stand-alone sensor network nodes. The boost circuit and timer consume 10 and 2.5 nW of power during operation, respectively.      

A hybrid FRTOC-SA algorithm for product mix problems with fuzzy processing time and capacity

Identification and determination of products and their quantities according to available resources is called product mix problem in manufacturing plants. One of the efficient and easy to use algorithms for solving product mix problems in uncertainty conditions is Fuzzy Revised Theory of Constraints (FRTOC) that was proposed by Azadegan et al. (2011). Their algorithm had a complete neighborhood search. So, it needed a long process to calculate the best result when demands of products were too much. Therefore, according to abilities of simulated annealing (SA) algorithm, we proposed a hybrid algorithm based on FRTOC and SA. In other words, the SA method is used instead of searching all neighbors in FRTOC. Also, a numerical example is used to show the capabilities of the proposed algorithm in comparison with the FRTOC.     

Skin regeneration stimulation: the role of PCL‐platelet gel nanofibrous scaffold

Skin is the largest organ of the human body. Thus far, tissue engineering of skin has developed rapidly and has used many types of growth factors and nanofibrous scaffolds. In this study, we differentiated neonate keratinocytes for epithelialization on the polycaprolactone‐Platelet gel (PCL‐PG) scaffold. Fabricated PCL nanofibers prepared by electrospinning technology and coated by platelet gel. Subsequently, the structure of the scaffold was evaluated by SEM, FTIR‐ATR, contact angle and tensile test assays. After seeding the neonate keratinocytes on neat PCL and PCL‐PG scaffolds, the epidermal maturation was tested by detecting cytokeratin 10 and loricrin determinants by immunocytochemistry; moreover, keratinocyte genes such as keratin 14, keratin 10, and Involucrin were investigated by real‐time PCR. The results of MTT assay indicated an increase in cell viability and cell proliferation of neonate keratinocytes on PCL‐PG nanofiber scaffolds compared with PCL. RT‐PCR and immunocytochemical analysis showed better cell differentiation on the PCL‐PG scaffolds than neat PCL. Furthermore, SEM microscopy images demonstrated that neo‐keratinocytes enhance adhesion and proliferation on PCL‐PG nanofiber scaffolds. We found that PG increases biocompatibility and wettability of scaffold, cell adhesion, and expression of keratinocyte markers. Overall, this procedure is recommended to be employed in skin tissue engineering and wounds healing.     

Kinetics studies on copolymerization of acrylonitrile vinyl acids by solvent–water suspension polymerization

Polyacrylonitrile is an important polymer that is widely used in the manufacture of synthetic fibers, particularly for applications in apparel. Although a vast amount of literature is available on the polymerization process of acrylonitrile (AN) with other monomers, there are few reports of studies on polymerization in a mixed solvent of water with an organic solvent. It is conceivable that this method could combine the advantages of the solution and suspension polymerization methods. Synthesis of AN copolymers with two vinyl acids, methacrylic acid (MAA) and itaconic acid (IA), is carried out by solvent–water suspension polymerization. The polymerizations are performed with an equal ratio mixture of dimethylformamide as a solvent and water as a nonsolvent at 60°C using α,α‐azobisisobutyronitrile as an initiator. The kinetics of polymerization are studied by plotting the conversion versus reaction time for different mole ratios of AN with vinyl acids. Copolymers are characterized by FTIR and capillary viscometery. The results show that IA depresses the rate of polymerization more than MAA in this reaction medium, and this effect becomes more significant at higher vinyl acid mole ratios. High conversion in a short reaction time is obtainable for copolymers with a low vinyl acid mole fraction. However, for mole ratios of more than 93:7, the rate of the reaction is drastically reduced and low conversion (<60%) results, even after 8 h. The intrinsic viscosities of all cases are surprisingly high. Although they are reduced with increasing acidic comonomer mole fraction, this reduction is more significant for IA compared to MAA. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1284–1291, 2005     

Hybrid credit ranking intelligent system using expert system and artificial neural networks

The main goal of all commercial banks is to collect the savings of legal and real persons and allocate them as credit to industrial, services and production companies. Non repayment of such credits cause many problems to the banks such as incapability to repay the central bank’s loans, increasing the amount of credit allocations comparing to credit repayment and incapability to allocate more credits to customers. The importance of credit allocation in banking industry and it’s important role in economic growth and employment creation leads the development of many models to evaluate the credit risk of applicants. But many of these models are classic and are incapable to do credit evaluation completely and efficiently. Therefore the demand to use artificial intelligence in this field has grown up. In this paper after providing appropriate credit ranking model and collecting expert’s knowledge, we design a hybrid intelligent system for credit ranking using reasoning-transformational models. Expert system as symbolic module and artificial neural network as non-symbolic module are components of this hybrid system. Such models provide the unique features of each components, the reasoning and explanation of expert system and the generalization and adaptability of artificial neural networks. The results of this system demonstrate hybrid intelligence system is more accurate and powerful in credit ranking comparing to expert systems and traditional banking models.     

Photoresist-based integration of enzyme functionality into MEMS

We demonstrate the direct immobilization of glucose oxidase and lactate oxidase onto photoresists commonly used in microfabrication. The method allows for a cost-effective, facile inclusion of enzyme functionality into novel MEMS devices because it does not require any chemical or physical pre-treatment of surfaces, and it is largely compatible with existing fabrication technologies. We used fluorescence imaging and absorbance spectrometry to confirm attachment of the enzymes onto the photoresists and to determine their activity. In addition, the procedure was used to successfully integrate enzyme functionality into a photoresist-based biosensor. This further demonstrates the effectiveness of the approach, and opens a path towards other novel applications in MEMS research.     

An immune algorithm for hybrid flow shop scheduling problem with time lags and sequence-dependent setup times

This paper deals with hybrid flow shop scheduling problems considering time lags and sequence-dependent setup times which have wide application in real-world problems. Most of the researches on operations scheduling problems have ignored time lags. A mathematical model is presented which is capable of solving the small size of the considered problem in a reasonable time. Since these problems are strongly NP-hard, a meta-heuristic algorithm based on the immune algorithm is developed. The optimization criterion considered in this paper is the minimization of the makespan. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. The results of the proposed algorithm are compared with the presented mathematical programming model and a benchmark algorithm. Computational results indicate that the proposed algorithm can produce near-optimal solutions in a short computational time. Moreover, it can be applied easily in real factory conditions and for large-sized problems.     

Guided local buckling (GLB) theory for short braces

According to recent earthquake experiences and experimental results, the local buckling is the most important parameter for limiting the ductility of short braces and prevents earthquake energy absorption in larger drifts. A new theory is introduced to prevent harmful effects of local buckling and use it as an energy absorption device in braced frames. According to this theory oblique stiffeners are provided inside braces section and it is expected to divide lateral drift of the system to smaller deflections inside stiffeners intervals. As much as number of local buckling along braces increases, more energy will be absorbed and the fracture life of the sections increases considerably. This theory is supported by half-scale experimental results and numerical modeling. The obtained results represent uniform and stable energy absorption and reasonable system ductility.