Herbage accumulation, growth and structural characteristics of Mombasa grass (Panicum maximum Jacq.) harvested at different cutting intervals

The objective of the present study was to evaluate herbage accumulation, morphological composition, growth rate and structural characteristics in Mombasa grass swards subject to different cutting intervals (3, 5 and 7 wk) during the rainy and dry seasons of the year. Treatments were assigned to experimental units (17.5 m(2)) according to a complete randomised block design, with four replicates. Herbage accumulation was greater in the rainy than in the dry season (83 and 17%, respectively). Herbage accumulation (24,300 kg DM ha(-1)), average growth rate (140 kg DM ha(-1) d(-1)) and sward height (111 cm) were highest in the 7 wk cutting interval, but leaf proportion (56%), leaf:stem (1.6) and leaf:non leaf (1.3) ratios decreased. Herbage accumulation, morphological composition and sward structure of Mombasa grass sward may be manipulated through defoliation frequency. The highest leaf proportion was recorded in the 3-wk cutting interval. Longer cutting intervals affected negatively sward structure, with potential negative effects on utilization efficiency, animal intake and performance.

A state-space modeling approach for active structural acoustic control

The demands for improvement in sound quality and reduction of noise generated by vehicles are constantly increasing, as well as the penalties for space and weight of the control solutions. A promising approach to cope with this challenge is the use of active structural-acoustic control. Usually, the low frequency noise is transmitted into the vehicle`s cabin through structural paths, which raises the necessity of dealing with vibro-acoustic models. This kind of models should allow the inclusion of sensors and actuators models, if accurate performance indexes are to be accessed. The challenge thus resides in deriving reasonable sized models that integrate structural, acoustic, electrical components and the controller algorithm. The advantages of adequate active control simulation strategies relies on the cost and time reduction in the development phase. Therefore, the aim of this paper is to present a methodology for simulating vibro-acoustic systems including this coupled model in a closed loop control simulation framework that also takes into account the interaction between the system and the control sensors/actuators. It is shown that neglecting the sensor/actuator dynamics can lead to inaccurate performance predictions.

Adaptable Strut-and-Tie Model for Design and Verification of Four-Pile Caps

A large percentage of pile caps support only one column, and the pile caps in turn are supported by only a few piles. These are typically short and deep members with overall span-depth ratios of less than 1.5. Codes of practice do not provide uniform treatment for the design of these types of pile caps. These members have traditionally been designed as beams spanning between piles with the depth selected to avoid shear failures and the amount of longitudinal reinforcement selected to provide sufficient flexural capacity as calculated by the engineering beam theory. More recently, the strut-and-tie method has been used for the design of pile caps (disturbed or D-region) in which the load path is envisaged to be a three-dimensional truss, with compressive forces being supported by concrete compressive struts between the column and piles and tensile forces being carried by reinforcing steel located between piles. Both of these models have not provided uniform factors of safety against failure or been able to predict whether failure will occur by flexure (ductile mode) or shear (fragile mode). In this paper, an analytical model based on the strut-and-tie approach is presented. The proposed model has been calibrated using an extensive experimental database of pile caps subjected to compression and evaluated analytically for more complex loading conditions. It has been proven to be applicable across a broad range of test data and can predict the failures modes, cracking, yielding, and failure loads of four-pile caps with reasonable accuracy.

Design and Characterization of a Biomimetic Piezoelectric Pump Inspired on Group Fish Swimming Effect

Flow pumps are important tools in several engineering areas, such as in the fields of bioengineering and thermal management solutions for electronic devices. Nowadays, many of the new flow pump principles are based on the use of piezoelectric actuators, which present some advantages such as miniaturization potential and lower noise generation. In previous work, authors presented a study of a novel pump configuration based on placing an oscillating bimorph piezoelectric actuator in water to generate flow. It was concluded that this oscillatory behavior (such as fish swimming) yields vortex interaction, generating flow rate due to the action and reaction principle. Thus, following this idea the objective of this work is to explore this oscillatory principle by studying the interaction among generated vortex from two bimorph piezoelectric actuators oscillating inside the same pump channel, which is similar to the interaction of vortex generated by frontal fish and posterior ones when they swim together in a group formation. It is shown that parallel-series configurations of bimorph piezoelectric actuators inside the same pump channel provide higher flow rates and pressure for liquid pumping than simple parallel-series arrangements of corresponding single piezoelectric pumps, respectively. The scope of this work includes structural simulations of bimorph piezoelectric actuators, fluid flow simulations, and prototype construction for result validation.

Toward Optimal Design of Piezoelectric Transducers Based on Multifunctional and Smoothly Graded Hybrid Material Systems

This work explores the design of piezoelectric transducers based on functional material gradation, here named functionally graded piezoelectric transducer (FGPT). Depending on the applications, FGPTs must achieve several goals, which are essentially related to the transducer resonance frequency, vibration modes, and excitation strength at specific resonance frequencies. Several approaches can be used to achieve these goals; however, this work focuses on finding the optimal material gradation of FGPTs by means of topology optimization. Three objective functions are proposed: (i) to obtain the FGPT optimal material gradation for maximizing specified resonance frequencies; (ii) to design piezoelectric resonators, thus, the optimal material gradation is found for achieving desirable eigenvalues and eigenmodes; and (iii) to find the optimal material distribution of FGPTs, which maximizes specified excitation strength. To track the desirable vibration mode, a mode-tracking method utilizing the `modal assurance criterion` is applied. The continuous change of piezoelectric, dielectric, and elastic properties is achieved by using the graded finite element concept. The optimization algorithm is constructed based on sequential linear programming, and the concept of continuum approximation of material distribution. To illustrate the method, 2D FGPTs are designed for each objective function. In addition, the FGPT performance is compared with the non-FGPT one.

Optimal design of periodic functionally graded composites with prescribed properties

The computational design of a composite where the properties of its constituents change gradually within a unit cell can be successfully achieved by means of a material design method that combines topology optimization with homogenization. This is an iterative numerical method, which leads to changes in the composite material unit cell until desired properties (or performance) are obtained. Such method has been applied to several types of materials in the last few years. In this work, the objective is to extend the material design method to obtain functionally graded material architectures, i.e. materials that are graded at the local level (e.g. microstructural level). Consistent with this goal, a continuum distribution of the design variable inside the finite element domain is considered to represent a fully continuous material variation during the design process. Thus the topology optimization naturally leads to a smoothly graded material system. To illustrate the theoretical and numerical approaches, numerical examples are provided. The homogenization method is verified by considering one-dimensional material gradation profiles for which analytical solutions for the effective elastic properties are available. The verification of the homogenization method is extended to two dimensions considering a trigonometric material gradation, and a material variation with discontinuous derivatives. These are also used as benchmark examples to verify the optimization method for functionally graded material cell design. Finally the influence of material gradation on extreme materials is investigated, which includes materials with near-zero shear modulus, and materials with negative Poisson`s ratio.

Piezoresistive sensor design using topology optimization

Piezoresistive materials, materials whose resistivity properties change when subjected to mechanical stresses, are widely utilized in many industries as sensors, including pressure sensors, accelerometers, inclinometers, and load cells. Basic piezoresistive sensors consist of piezoresistive devices bonded to a flexible structure, such as a cantilever or a membrane, where the flexible structure transmits pressure, force, or inertial force due to acceleration, thereby causing a stress that changes the resistivity of the piezoresistive devices. By applying a voltage to a piezoresistive device, its resistivity can be measured and correlated with the amplitude of an applied pressure or force. The performance of a piezoresistive sensor is closely related to the design of its flexible structure. In this research, we propose a generic topology optimization formulation for the design of piezoresistive sensors where the primary aim is high response. First, the concept of topology optimization is briefly discussed. Next, design requirements are clarified, and corresponding objective functions and the optimization problem are formulated. An optimization algorithm is constructed based on these formulations. Finally, several design examples of piezoresistive sensors are presented to confirm the usefulness of the proposed method.

Structural complexes of human adenine phosphoribosyltransferase reveal novel features of the APRT catalytic mechanism

Adenine phosphoribosyltransferase (APRT) is an important enzyme component of the purine recycling pathway. Parasitic protozoa of the order Kinetoplastida are unable to synthesize purines de novo and use the salvage pathway for the synthesis of purine bases rendering this biosynthetic pathway an attractive target for antiparasitic drug design. The recombinant human adenine phosphoribosyltransferase (hAPRT) structure was resolved in the presence of AMP in the active site to 1.76 angstrom resolution and with the substrates PRPP and adenine simultaneously bound to the catalytic site to 1.83 angstrom resolution. An additional structure was solved containing one subunit of the dimer in the apo-form to 2.10 angstrom resolution. Comparisons of these three hAPRT structures with other `type I` PRTases revealed several important features of this class of enzymes. Our data indicate that the flexible loop structure adopts an open conformation before and after binding of both substrates adenine and PRPR Comparative analyses presented here provide structural evidence to propose the role of Glu 104 as the residue that abstracts the proton of adenine N9 atom before its nucleophilic attack on the PRPP anomeric carbon. This work leads to new insights to the understanding of the APRT catalytic mechanism.

Using Computer-aided Drug Design and Medicinal Chemistry Strategies in the Fight Against Diabetes

The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics. ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.

The determination of the design strength of granite used as external cladding for buildings

This chapter is concerned with acquisition and analysis of test data for determining whether or not the flexural strength of granite cladding under extreme conditions is adequate to assure that reliability requirements are satisfied.

Applications of NMR in drug design: Sructure-activity relationships in disulfide-rich peptides

NMR is a powerful technique for determining structures of biologically active molecules in solution. In recent years. our laboratory has focussed on the structure determination of small disulfide-rich proteins from both plants and animals which are valuable targets in drug design applications. This article will review these structural studies and their implications in drug design.

Conformational selection of inhibitors and substrates by proteolytic enzymes: Implications for drug design and polypeptide processing

Inhibitors of proteolytic enzymes (proteases) are emerging as prospective treatments for diseases such as AIDS and viral infections, cancers, inflammatory disorders, and Alzheimer's disease. Generic approaches to the design of protease inhibitors are limited by the unpredictability of interactions between, and structural changes to, inhibitor and protease during binding. A computer analysis of superimposed crystal structures for 266 small molecule inhibitors bound to 48 proteases (16 aspartic, 17 serine, 8 cysteine, and 7 metallo) provides the first conclusive proof that inhibitors, including substrate analogues, commonly bind in an extended beta-strand conformation at the active sites of all these proteases. Representative superimposed structures are shown for (a) multiple inhibitors bound to a protease of each class, (b) single inhibitors each bound to multiple proteases, and (c) conformationally constrained inhibitors bound to proteases. Thus inhibitor/substrate conformation, rather than sequence/composition alone, influences protease recognition, and this has profound implications for inhibitor design. This conclusion is supported by NMR, CD, and binding studies for HIV-1 protease inhibitors/ substrates which, when preorganized in an extended conformation, have significantly higher protease affinity. Recognition is dependent upon conformational equilibria since helical and turn peptide conformations are not processed by proteases. Conformational selection explains the resistance of folded/structured regions of proteins to proteolytic degradation, the susceptibility of denatured proteins to processing, and the higher affinity of conformationally constrained 'extended' inhibitors/substrates for proteases. Other approaches to extended inhibitor conformations should similarly lead to high-affinity binding to a protease.

Molecular adaptability of nucleoside diphosphate kinase b from trypanosomatid parasites: stability, oligomerization and structural determinants of nucleotide binding

Nucleoside diphosphate kinases play a crucial role in the purine-salvage pathway of trypanosomatid protozoa and have been found in the secretome of Leishmania sp., suggesting a function related to host-cell integrity for the benefit of the parasite. Due to their importance for housekeeping functions in the parasite and by prolonging the life of host cells in infection, they become an attractive target for drug discovery and design. In this work, we describe the first structural characterization of nucleoside diphosphate kinases b from trypanosomatid parasites (tNDKbs) providing insights into their oligomerization, stability and structural determinants for nucleotide binding. Crystallographic studies of LmNDKb when complexed with phosphate, AMP and ADP showed that the crucial hydrogen-bonding residues involved in the nucleotide interaction are fully conserved in tNDKbs. Depending on the nature of the ligand, the nucleotide-binding pocket undergoes conformational changes, which leads to different cavity volumes. SAXS experiments showed that tNDKbs, like other eukaryotic NDKs, form a hexamer in solution and their oligomeric state does not rely on the presence of nucleotides or mimetics. Fluorescence-based thermal-shift assays demonstrated slightly higher stability of tNDKbs compared to human NDKb (HsNDKb), which is in agreement with the fact that tNDKbs are secreted and subjected to variations of temperature in the host cells during infection and disease development. Moreover, tNDKbs were stabilized upon nucleotide binding, whereas HsNDKb was not influenced. Contrasts on the surface electrostatic potential around the nucleotide-binding pocket might be a determinant for nucleotide affinity and protein stability differentiation. All these together demonstrated the molecular adaptation of parasite NDKbs in order to exert their biological functions intra-parasite and when secreted by regulating ATP levels of host cells.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd