Select-divide-and-conquer method for large-scale configuration interaction

A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,...,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0={T0egy, T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates KS with attributes above T1≤T0. An eigenproblem of dimension d0+d1 for S0+S 1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j≥2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson's eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0, 1, 2,...,R} regulate accuracy; for large-dimensional S, high accuracy requires S 0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24 × 106, involving 1.2 × 1012 nonzero matrix elements, and 8.4×109 Slater determinants

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Compositional analysis of bivariate discrete probabilities

A joint distribution of two discrete random variables with finite support can be displayed as a two way table of probabilities adding to one. Assume that this table has n rows and m columns and all probabilities are non-null. This kind of table can be seen as an element in the simplex of n · m parts. In this context, the marginals are identified as compositional amalgams, conditionals (rows or columns) as subcompositions. Also, simplicial perturbation appears as Bayes theorem. However, the Euclidean elements of the Aitchison geometry of the simplex can also be translated into the table of probabilities: subspaces, orthogonal projections, distances. Two important questions are addressed: a) given a table of probabilities, which is the nearest independent table to the initial one? b) which is the largest orthogonal projection of a row onto a column? or, equivalently, which is the information in a row explained by a column, thus explaining the interaction? To answer these questions three orthogonal decompositions are presented: (1) by columns and a row-wise geometric marginal, (2) by rows and a columnwise geometric marginal, (3) by independent two-way tables and fully dependent tables representing row-column interaction. An important result is that the nearest independent table is the product of the two (row and column)-wise geometric marginal tables. A corollary is that, in an independent table, the geometric marginals conform with the traditional (arithmetic) marginals. These decompositions can be compared with standard log-linear models. Key words: balance, compositional data, simplex, Aitchison geometry, composition, orthonormal basis, arithmetic and geometric marginals, amalgam, dependence measure, contingency table

A unified approach for representing rows and columns in contingency tables

By using suitable parameters, we present a uni¯ed aproach for describing four methods for representing categorical data in a contingency table. These methods include: correspondence analysis (CA), the alternative approach using Hellinger distance (HD), the log-ratio (LR) alternative, which is appropriate for compositional data, and the so-called non-symmetrical correspondence analysis (NSCA). We then make an appropriate comparison among these four methods and some illustrative examples are given. Some approaches based on cumulative frequencies are also linked and studied using matrices. Key words: Correspondence analysis, Hellinger distance, Non-symmetrical correspondence analysis, log-ratio analysis, Taguchi inertia

Simultaneous estimation of indirect and interaction effects using structural equation models

Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting for measurement error. From the various specifications, Jöreskog and Yang's (1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Selected configuration interaction with truncation energy error and application to the Ne atom

Selected configuration interaction (SCI) for atomic and molecular electronic structure calculations is reformulated in a general framework encompassing all CI methods. The linked cluster expansion is used as an intermediate device to approximate CI coefficients BK of disconnected configurations (those that can be expressed as products of combinations of singly and doubly excited ones) in terms of CI coefficients of lower-excited configurations where each K is a linear combination of configuration-state-functions (CSFs) over all degenerate elements of K. Disconnected configurations up to sextuply excited ones are selected by Brown's energy formula, ΔEK=(E-HKK)BK2/(1-BK2), with BK determined from coefficients of singly and doubly excited configurations. The truncation energy error from disconnected configurations, Δdis, is approximated by the sum of ΔEKS of all discarded Ks. The remaining (connected) configurations are selected by thresholds based on natural orbital concepts. Given a model CI space M, a usual upper bound ES is computed by CI in a selected space S, and EM=E S+ΔEdis+δE, where δE is a residual error which can be calculated by well-defined sensitivity analyses. An SCI calculation on Ne ground state featuring 1077 orbitals is presented. Convergence to within near spectroscopic accuracy (0.5 cm-1) is achieved in a model space M of 1.4× 109 CSFs (1.1 × 1012 determinants) containing up to quadruply excited CSFs. Accurate energy contributions of quintuples and sextuples in a model space of 6.5 × 1012 CSFs are obtained. The impact of SCI on various orbital methods is discussed. Since ΔEdis can readily be calculated for very large basis sets without the need of a CI calculation, it can be used to estimate the orbital basis incompleteness error. A method for precise and efficient evaluation of ES is taken up in a companion paper

Linear response functions for a vibrational configuration interaction state

Linear response functions are implemented for a vibrational configuration interaction state allowing accurate analytical calculations of pure vibrational contributions to dynamical polarizabilities. Sample calculations are presented for the pure vibrational contributions to the polarizabilities of water and formaldehyde. We discuss the convergence of the results with respect to various details of the vibrational wave function description as well as the potential and property surfaces. We also analyze the frequency dependence of the linear response function and the effect of accounting phenomenologically for the finite lifetime of the excited vibrational states. Finally, we compare the analytical response approach to a sum-over-states approach

Desenvolupament de mètodes de preconcentració emprant membranes líquides suportades i extracció en fase sòlida per a la determinació de l'herbicida glifosat i el seu metabòlit AMPA en aigües naturals

El glifosat, N-(fosfonometil) glicina, és un dels herbicides més utilitzats arreu del món a causa de la seva baixa toxicitat i al seu ampli espectre d'aplicació. A conseqüència del gran ús que se'n fa, és necessari monitoritzar aquest compost i el seu principal metabòlit, l'àcid aminometilfosfònic (AMPA), en el medi ambient. S'han descrit diversos mètodes instrumentals basats en cromatografia de gasos (GC) i de líquids (HPLC), sent aquesta darrera l'opció més favorable a causa del caràcter polar dels anàlits. Per assolir nivells de concentració baixos cal, però, la preconcentració dels anàlits. En aquest treball s'estudien diferents alternatives amb aquest objectiu. S'ha avaluat la tècnica de membrana líquida suportada (SLM) on la membrana consisteix en una dissolució orgànica, que conté un transportador (en el nostre cas, un bescanviador d'anions comercial, Aliquat 336), que impregna un suport polimèric microporós que se situa entre dues solucions aquoses: la de càrrega, que conté els anàlits inicialment, i la receptora, on es retenen els anàlits després del seu transport a través de la membrana. Les condicions d'extracció més adequades s'obtenen treballant en medi bàsic amb NaOH on els anàlits estan en forma aniònica i les majors recuperacions s'obtenen amb HCl 0,1 M o NaCl 0,5 M, la qual cosa indica que l'ió clorur és la força impulsora del transport. Un cop dissenyat el sistema, es duen a terme experiments de preconcentració amb dues geometries diferents: un sistema de membrana laminar (LSLM) on recircula la fase receptora i un sistema de fibra buida (HFSLM). Els millors resultats s'obtenen amb el mòdul de fibra buida, amb factors de concentració de 25 i 3 per a glifosat i AMPA, respectivament, fent recircular durant 24 hores 100 ml de solució de càrrega i 4 ml de solució receptora. També s'aplica una tècnica més selectiva, la cromatografia d'afinitat amb ió metàl·lic immobilitzat (IMAC), basada en la interacció entre els anàlits i un metall immobilitzat en una resina a través d'un grup funcional d'aquesta. En aquest estudi s'immobilitza pal·ladi al grup funcional 8-hidroxiquinoleïna de la resina amb matriu acrílica Spheron Oxine 1000 i s'avalua per a l'extracció i preconcentració de glifosat i AMPA. Per a ambdós anàlits l'adsorció és del 100 % i les recuperacions són superiors al 80 % i al 60 % per a glifosat i AMPA, respectivament, utilitzant HCl 0,1 M + NaCl 1 M com a eluent. Aquests resultats es comparen amb els obtinguts amb dues resines més, també carregades amb pal·ladi: Iontosorb Oxin 100, que té el mateix grup funcional però matriu de cel·lulosa, i Spheron Thiol 1000, on el grup funcional és un tiol i la matriu també és acrílica. Per al glifosat els resultats són similars amb totes les resines, però per a l'AMPA la resina Spheron Thiol és la única que proporciona recuperacions superiors al 93 %. Finalment, una altra opció estudiada és l'acoblament de dues columnes de cromatografia líquida (LC-LC). En l'estudi l'objectiu és millorar el mètode existent per a glifosat i AMPA en aigües naturals on el LOD era de 0,25 ug/l. El mètode consisteix en la derivatització precolumna amb el reactiu fluorescent FMOC i l'anàlisi amb l'acoblament LC-LC-fluorescència. Variant lleugerament les condicions de derivatització s'aconsegueix quantificar 0,1 ug/l de glifosat i AMPA. Es fortifiquen aigües naturals amb 0,1, 1 i 10 ug/l dels anàlits per validar el mètode. S'obtenen recuperacions d'entre el 85 % i el 100 %, amb desviacions estàndard relatives inferiors al 8 %. Aplicant una tècnica de preconcentració prèvia a la derivatització i anàlisi utilitzant una resina de bescanvi aniònic, Amberlite IRA-900, es millora la sensibilitat del mètode i s'assoleix un LOD per al glifosat de 0,02 ug/l.

The role of fungi and bacteria on the organic matter decomposition process in streams: interaction and relevance in biofilms

L'objectiu d'aquest estudi és el d'investigar sobre l'ús de matèria orgànica per part dels fongs i bacteris que colonitzen diferents substrats bentònics en rius Mediterranis i analitzar l'efecte dels factors ambientals i antròpics sobre l'estabilitat estructural i funcional de les comunitats del biofilm. La metodologia emprada en aquest estudi consisteix en: i) anàlisi de la biomassa bacteriana i fúngica, ii) anàlisi de la composició de les comunitats bentòniques (identificació d'hifomicets aquàtics i anàlisi del 16S rDNA bacterià), i iii) anàlisi de l'activitat enzimàtica extracel·lular relacionada amb el reciclatge de matèria orgànica en rius.