MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing

Determining the modulus of elasticity of wood by applying an artificial neural network using the physical properties and non-destructive testing can be a useful method in assessments of the timber structure in old constructions. The modulus of elasticity of Abies pinsapo Boiss. timber was predicted in this study through the parameters of density, width, thickness, moisture content, ultrasonic wave propagation velocity and visual grading of the test pieces. A feedforward multilayer perceptron network was designed for this purpose, achieving 75.0% success in the testing or unknown group.     

Common coupling and pointer variables,with application to a Linux case study

Both common coupling and pointer variables can exert a deleterious effect on the quality of software. The situation is exacerbated when global variables are assigned to pointer variables, that is, when an alias to a global variable is created. When this occurs, the number of global variables increases, and it becomes considerably harder to compute quality metrics correctly. However, unless aliasing is taken into account, variables may incorrectly appear to be unreferenced (neither defined nor used), or to be used without being defined. These ideas are illustrated by means of a case study of common coupling in the Linux kernel.

Logical Representation of a Conceptual Model for Spatial Data Warehouses

The MultiDimER model is a conceptual model used for representing a multidimensional view of data for Data Warehouse (DW) and On-Line Analytical Processing (OLAP) applications. This model includes a spatial extension allowing spatiality in levels, hierarchies, fact relationships, and measures. In this way decision-making users can represent in an abstract manner their analysis needs without considering complex implementation issues and spatial OLAP tools developers can have a common vision for representing spatial data in a multidimensional model. In this paper we propose the transformation of a conceptual schema based on the MultiDimER constructs to an object-relational schema. We based our mapping on the SQL:2003 and SQL/MM standards giving examples of commercial implementation using Oracle 10g with its spatial extension. Further we use spatial integrity constraints to ensure the semantic equivalence of the conceptual and logical schemas. We also show some examples of Oracle spatial functions, including aggregation functions required for the manipulation of spatial data. The described mappings to the object-relational model along with the examples using a commercial system show the feasibility of implementing spatial DWs in current commercial DBMSs. Further, using integrated architectures, where spatial and thematic data is defined within the same DBMS, facilitates the system management simplifying data definition and manipulation.

Nonlinear inverse optimization approach for determining the weights of objective function in standing reach tasks

This paper presents a nonlinear inverse optimization approach to determine the weights for the joint displacement function in standing reach tasks. This inverse optimization problem can be formulated as a bi-level highly nonlinear optimization problem. The design variables are the weights of a cost function. The cost function is the weighted summation of the differences between two sets of joint angles (predicted posture and the actual standing reach posture). Constraints include the normalized weights within limits and an inner optimization problem to solve for joint angles (predicted standing reach posture). The weight linear equality constraints, obtained through observations, are also implemented in the formulation to test the method. A 52 degree-of-freedom (DOF) human whole body model is used to study the formulation and visualize the prediction. An in-house motion capture system is used to obtain the actual standing reach posture. A total of 12 subjects (three subjects for each percentile in stature of 5th percentile female, 50th percentile female, 50th percentile male and 95th percentile male) are selected to run the experiment for 30 tasks. Among these subjects one is Turkish, two are Chinese, and the rest subjects are Americans. Three sets of weights for the general standing reach tasks are obtained for the three zones by averaging all weights in each zone for all subjects and all tasks. Based on the obtained sets of weights, the predicted standing reach postures found using the direct optimization-based approach have good correlation with the experimental results. Sensitivity of the formulation has also been investigated in this study. The presented formulation can be used to determine the weights of cost function within any multi-objective optimization (MOO) problems such as any types of posture prediction and motion prediction.     

Theoretical method for the study of plasmon generation in hybrid multilayer-optical fiber structures

A theoretical method is presented for the determination of the behavior of devices based on the deposition of multilayer structures on polished optical fibers. Plasmon generation in metallic layers is modeled. The method is based on the Rayleigh expansion of the electric fields and permits us to determine their distribution over the whole structure by an application of boundary conditions. Once the distribution is known, the power transmitted by the fiber can be computed as a function of the geometrical and refractive parameters of the device. The method is versatile and can be used as a theoretical tool for the design of devices of that type used for many different purposes. We present real experimental results obtained with an operative sensor that agree with the theoretical predictions of our technique and prove its suitability.     

Inhibition of hIAPP Amyloid Aggregation and Pancreatic β‐Cell Toxicity by OH‐Terminated PAMAM Dendrimer

Human islet amyloid polypeptide (hIAPP, or amylin) forms amyloid deposits in the islets of Langerhans, a phenomenon that is associated with type‐2 diabetes impacting millions of people worldwide. Accordingly, strategies against hIAPP aggregation are essential for the prevention and eventual treatment of the disease. Here, it is shown that generation‐3 OH‐terminated poly(amidoamine) dendrimer, a polymeric nanoparticle, can effectively halt the aggregation of hIAPP and shut down hIAPP toxicity in pancreatic MIN6 and NIT‐1 cells as well as in mouse islets. This finding is supported by high‐throughput dynamic light scattering experiment and thioflavin T assay, where the rapid evolution of hIAPP nucleation and elongation processes is halted by the addition of the dendrimer up to 8 h. Discrete molecular dynamics simulations further reveal that hIAPP residues bound strongly with the dendrimer near the c‐terminal portion of the peptide, where the amyloidogenic sequence (residues 22–29) locates. Furthermore, simulations of hIAPP dimerization reveal that binding with the dendrimer significantly reduces formation of interpeptide contacts and hydrogen bonds, thereby prohibiting peptide self‐association and amyloidosis. This study points to a promising nanomedicinal strategy for combating type‐2 diabetes and may have broader implications for targeting neurological disorders whose distinct hallmark is also amyloid fibrillation.     

Identification of Structural and Molecular Signatures Mediating Adaptive Changes in the Mouse Kidney in Response to Pregnancy

Pregnancy is characterized by adaptations in the function of several maternal body systems that ensure the development of the fetus whilst maintaining health of the mother. The renal system is responsible for water and electrolyte balance, as well as waste removal. Thus, it is imperative that structural and functional changes occur in the kidney during pregnancy. However, our knowledge of the precise morphological and molecular mechanisms occurring in the kidney during pregnancy is still very limited. Here, we investigated the changes occurring in the mouse kidney during pregnancy by performing an integrated analysis involving histology, gene and protein expression assays, mass spectrometry profiling and bioinformatics. Data from non-pregnant and pregnant mice were used to identify critical signalling pathways mediating changes in the maternal kidneys. We observed an expansion of renal medulla due to proliferation and infiltration of interstitial cellular constituents, as well as alterations in the activity of key cellular signalling pathways (e.g., AKT, AMPK and MAPKs) and genes involved in cell growth/metabolism (e.g., Cdc6, Foxm1 and Rb1) in the kidneys during pregnancy. We also generated plasma and urine proteomic profiles, identifying unique proteins in pregnancy. These proteins could be used to monitor and study potential mechanisms of renal adaptations during pregnancy and disease.     

Parastrephia quadrangularis: A Possible Alternative to Inhibit the Microbial Effect on the Generation of Acid Mine Drainage

Mine Water and the Environment - The role of iron- and sulfur- oxidizing microorganisms in the generation of acid mine drainage (AMD) from sulfide ores and tailings is widely recognized. The...