Human computer-interaction in Latin America

Personal and Ubiquitous Computing -     

Investigating the Superoxide Formation and Stability in Mesoporous Carbon Perovskite Solar Cells with an Aminovaleric Acid Additive

Perovskite solar cells have attracted a great deal of attention thanks to their high efficiency, ease of manufacturing, and potential low cost. However, the stability of these devices is considered their main drawback and needs to be addressed. Mesoporous carbon perovskite solar cells (m‐CPSC), consisting of three mesoporous layers (TiO₂/ZrO₂/C) infiltrated with CH₃NH₃PbI₃ (MAPI) perovskite, have presented excellent lifetimes of more than 10 000 h when the additive NH₂(CH₂)₄CO₂HI (5‐ aminovaleric acid iodide; 5‐AVAI) is used to modify the perovskite structure. Yet, the role of 5‐AVAI in enhancing the stability has yet to be determined. Here, superoxide‐mediated degradation of MAPI m‐CPSC with and without the 5‐AVAI additive is studied using the fluorescence probe dihydroethidium for superoxide detection. In situ X‐ray diffractometry shows that aminovaleric acid methylammonium lead iodide (AVA‐MAPI) perovskite infiltrated in mesoporous layers presents higher stability in an ambient environment under illumination, evidenced by a slower decrease of the MAPI/PbI₂ peak ratio. Superoxide yield measurements demonstrate that AVA‐MAPI generates more superoxide than regular MAPI when deposited on glass but generates significantly less when infiltrated in mesoporous layers. It is believed that superoxide formation in m‐CPSC is dependent on a combination of competitive factors including oxygen diffusion, sample morphology, grain size, and defect concentration.     

Bacterial colonies as complex adaptive systems

The present work explores bacterial colonies and their individual and social behaviours under the lens of complex adaptive systems. We initially provide a background on the biology of bacteria to describe important phenomena, such as quorum-sensing, individual and collective behaviours, adaptation, evolution and self-organization over the influence of mechanical effects on bacterial systems and connecting scales. We then explore some associations between bacterial colonies and complex adaptive systems by considering components and ownerships of self-organization. The main contribution of this paper places emphasis on individual decision-making and behaviour as a cause of bacterial colonies’ actions, i.e., how self-organization and collective behaviours impact the ability of a bacterial colony to address an environmental stimulus and maintain itself as an open biological and fault-tolerant system. Finally, we conclude the work and provide some comments regarding future research.     

A low-cost decision-aided channel estimation method for Alamouti OSTBC

In wireless communication systems, channel state information (CSI) acquisition is typically performed at the receiver side every time a new frame is received, without taking into account whether it is really necessary or not. Considering the special case of the 2 × 1 Alamouti orthogonal space-time block code, this work proposes to reduce computational complexity associated with the CSI acquisition by including a decision rule to automatically determine the time instants when CSI must be again updated. Otherwise, a previous channel estimate is reused. The decision criterion has a very low computational complexity since it consists in computing the cross-correlation between preambles sent by the two transmit antennas. This allows us to obtain a considerable reduction on the complexity demanded by both supervised and unsupervised (blind) channel estimation algorithms. Such preambles do not penalize the spectral efficiency in the sense they are mandatory for frame detection as well as for time and frequency synchronization in current wireless communication systems.     

A uniform object-oriented solution to the eigenvalue problem for real symmetric and Hermitian matrices

We present a system of classes, SHMatrix, to deal in a unified way with the computation of eigenvalues and eigenvectors in real symmetric and Hermitian matrices. Thus, two descendant classes, one for the real symmetric and other for the Hermitian cases, override the abstract methods defined in a base class. The use of the inheritance relationship and polymorphism allows handling objects of any descendant class using a single reference of the base class. The system of classes is intended to be the core element of more sophisticated methods to deal with large eigenvalue problems, as those arising in the variational treatment of realistic quantum mechanical problems. The present system of classes allows computing a subset of all the possible eigenvalues and, optionally, the corresponding eigenvectors. Comparison with well established solutions for analogous eigenvalue problems, as those included in LAPACK, shows that the present solution is competitive against them.

Program summary

Program title: SHMatrixCatalogue identifier: AEHZ_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHZ_v1_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 2616No. of bytes in distributed program, including test data, etc.: 127 312Distribution format: tar.gzProgramming language: Standard ANSI C++.Computer: PCs and workstations.Operating system: Linux, Windows.Classification: 4.8.Nature of problem: The treatment of problems involving eigensystems is a central topic in the quantum mechanical field. Here, the use of the variational approach leads to the computation of eigenvalues and eigenvectors of real symmetric and Hermitian Hamiltonian matrices. Realistic models with several degrees of freedom leads to large (sometimes very large) matrices. Different techniques, such as divide and conquer, can be used to factorize the matrices in order to apply a parallel computing approach. However, it is still interesting to have a core procedure able to tackle the computation of eigenvalues and eigenvectors once the matrix has been factorized to pieces of enough small size. Several available software packages, such as LAPACK, tackled this problem under the traditional imperative programming paradigm. In order to ease the modelling of complex quantum mechanical models it could be interesting to apply an object-oriented approach to the treatment of the eigenproblem. This approach offers the advantage of a single, uniform treatment for the real symmetric and Hermitian cases.Solution method: To reach the above goals, we have developed a system of classes: SHMatrix. SHMatrix is composed by an abstract base class and two descendant classes, one for real symmetric matrices and the other for the Hermitian case. The object-oriented characteristics of inheritance and polymorphism allows handling both cases using a single reference of the base class. The basic computing strategy applied in SHMatrix allows computing subsets of eigenvalues and (optionally) eigenvectors. The tests performed show that SHMatrix is competitive, and more efficient for large matrices, than the equivalent routines of the LAPACK package.Running time: The examples included in the distribution take only a couple of seconds to run.     

Stack filter: Reducing L1 data cache power consumption

The L1 data cache is one of the most frequently accessed structures in the processor. Because of this and its moderate size it is a major consumer of power. In order to reduce its power consumption, in this paper a small filter structure that exploits the special features of the references to the stack region is proposed. This filter, which acts as a top – non-inclusive – level of the data memory hierarchy, consists of a register set that keeps the data stored in the neighborhood of the top of the stack. Our simulation results show that using a small Stack Filter (SF) of just a few registers, 10–25% data cache power savings can be achieved on average, with a negligible performance penalty.     

Query expansion using an immune-inspired biclustering algorithm

Query expansion is a technique utilized to improve the performance of information retrieval systems by automatically adding related terms to the initial query. These additional terms can be obtained from documents stored in a database. Usually, this task is performed by clustering the documents and then extracting representative terms from the clusters. Afterwards, a new search is performed in the whole database using the expanded set of terms. Recently, the authors have proposed an immune-inspired algorithm, namely BIC-aiNet, to perform biclustering of texts. Biclustering differs from standard clustering algorithms in the sense that the former can detect partial similarities in the attributes. The preliminary results indicated that our proposal is able to group similar texts effectively and the generated biclusters consistently presented relevant words to represent a category of texts. Motivated by this promising scenario, this paper better formalizes the proposal and investigates the usefulness of the whole methodology on larger datasets. The BIC-aiNet was applied to a set of documents aiming at identifying the set of relevant terms associated with each bicluster, giving rise to a query expansion tool. The obtained results were compared with those produced by two alternative proposals in the literature, and they indicate that these techniques tend to generate complementary results, as a consequence of the use of distinct similarity metrics.     

Gmat. A software tool for the computation of the rovibrational G matrix

Gmat is a C++ program able to compute the rovibrational G matrix in molecules of arbitrary size. This allows the building of arbitrary rovibrational Hamiltonians. In particular, the program is designed to work with the structural results of potential energy hypersurface mappings computed in computer clusters or computational Grid environments. In the present version, 1.0, the program uses internal coordinates as vibrational coordinates, with the principal axes of inertia as body-fixed system. The main design implements a complete separation of the interface and functional parts of the program. The interface part permits the automatic reading of the molecular structures from the output files of different electronic structure codes. At present, Gamess and Gaussian output files are allowed. To such an end, use is made of the object orientation polymorphism characteristic. The functional part computes numerically the derivatives of the nuclear positions respect to the vibrational coordinates. Very accurate derivatives are obtained by using central differences embedded in a nine levels Richardson extrapolation procedure.

Program summary

Program title: GmatCatalogue identifier: AECZ_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECZ_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 17 023No. of bytes in distributed program, including test data, etc.: 274 714Distribution format: tar.gzProgramming language: Standard C++Computer: All running Linux/WindowsOperating system: Linux, WindowsClassification: 16.2Nature of problem: Computation of the rovibrational G matrix in molecules of any size. This allows the building of arbitrary rovibrational Hamiltonians. It must be possible to obtain the input data from the output files of standard electronic structure codes. In addition, the program should handle the large number of files generated in massive explorations of molecular potential energy hypersurfaces. In these cases, Gmat will provide the G matrix as a function of the molecular structure.Solution method: To reach its objectives, Gmat has been organized in two components: an interface and a functional part. This organization allows for separating the input/output tasks, which are dependent on the human-machine interaction model selected, from the functional requirements, which are not. An object-oriented approach has been used in both parts. In the interface, polymorphism is used to allow the data acquisition from output files of different electronic structure codes. In the functional part, Gmat computes numerically the derivatives of the Cartesian coordinates respect to the vibrational coordinates needed to build the G matrix. Extremely accurate numerical derivatives are obtained in a double procedure. First, the truncation plus roundoff errors are minimized in the central differences expression. Second, the result is embedding in a nine levels Richardson extrapolation process. In the present version, the program allows the use of internal coordinates as vibrational coordinates, with the principal axes of inertia as body-fixed system.Running time: Sample test runs provided with the distribution take a few seconds to execute.