Intramolecular basis set superposition error effects on the planarity of benzene and other aromatic molecules: A solution to the problem

Recently, the surprising result that ab initio calculations on benzene and other planar arenes at correlated MP2, MP3, configuration interaction with singles and doubles (CISD), and coupled cluster with singles and doubles levels of theory using standard Pople’s basis sets yield nonplanar minima has been reported. The planar optimized structures turn out to be transition states presenting one or more large imaginary frequencies, whereas single-determinant-based methods lead to the expected planar minima and no imaginary frequencies. It has been suggested that such anomalous behavior can be originated by two-electron basis set incompleteness error. In this work, we show that the reported pitfalls can be interpreted in terms of intramolecular basis set superposition error (BSSE) effects, mostly between the C–H moieties constituting the arenes. We have carried out counterpoise-corrected optimizations and frequency calculations at the Hartree–Fock, B3LYP, MP2, and CISD levels of theory with several basis sets for a number of arenes. In all cases, correcting for intramolecular BSSE fixes the anomalous behavior of the correlated methods, whereas no significant differences are observed in the single-determinant case. Consequently, all systems studied are planar at all levels of theory. The effect of different intramolecular fragment definitions and the particular case of charged species, namely, cyclopentadienyl and indenyl anions, respectively, are also discussed

Heritage Sporting Event : An Old Recipe for a New Problem

In the last decades, the globalized competition among cities and regions made them develop new strategies for branding and promoting their territory to attract tourists, investors, companies and residents. Major sports events - such as the Olympic Games, the FIFA World Cup or World and Continental Championships - have played an integral part in these strategies. Believing, with or without evidence, in the capacity of those events to improve the visibility and the economy of the host destination, many cities, regions and even countries have engaged in establishing sports events hosting strategies. The problem of the globalized competition in the sports events "market" is that many cities and regions do not have the resources - either financial, human or in terms of infrastructure - to compete in hosting major sports events. Consequently, many cities or regions have to turn to second-tier sports events. To organise those smaller events means less media coverage and more difficulty in finding sponsors, while the costs - both financial and in terms of services - stay high for the community. This paper analyses how Heritage Sporting Events (HSE) might be an opportunity for cities and regions engaged in sports events hosting strategies. HSE is an emerging concept that to date has been under-researched in the academic literature. Therefore, this paper aims to define the concept of HSE through an exploratory research study. A multidisciplinary literature review reveals two major characteristics of HSEs: the sustainability in the territory and the authenticity of the event constructed through a differentiation process. These characteristics, defined through multiple variables, give us the opportunity to observe the construction process of a sports event into a heritage object. This paper argues that HSEs can be seen as territorial resources that can represent a competitive advantage for host destinations. In conclusion, academics are invited to further research HSEs to better understand their construction process and their impacts on the territory, while local authorities are invited to consider HSEs for the branding and the promotion of their territory.

Feasibility of replacing multiple ADSL connections with Multi-Dwelling Access

This final project was made for the Broadband/Implementation department of TeliaSonera Finland. The question to be examined is if the operator should replace multiple ADSL connections implemented over a leased line with Multi-Dwelling access based on an Ethernet/Optical Fibre access network. The project starts with describing the technology related to these access network solu-tions and presents the technology that is used in TeliaSonera Finland's access network. It continues from the technology to describe the problem with some of the ADSL implemen-tations of TeliaSonera. The problem is the implementations done over a leased line that can cost TeliaSonera over years as much as a possible investment to extend network when there is several lines leased to the same building. The project proposes a Multi-Dwelling access as a solution to this problem and defines the circumstances when to use it. After a satisfactory solution has found the project takes a view how implementation of the solution might alter the network and a new problem is found. When used commonly to replace need of ADSL implementation Multi-Dwelling access would significantly increase optical cable congestion near operators POP. As a final deed this project also proposes a technical change to existing way to implement multi-dwelling access with EPON technology.

Measures of fit in multiple correspondence analysis of crisp and fuzzy coded data

When continuous data are coded to categorical variables, two types of coding are possible: crisp coding in the form of indicator, or dummy, variables with values either 0 or 1; or fuzzy coding where each observation is transformed to a set of "degrees of membership" between 0 and 1, using co-called membership functions. It is well known that the correspondence analysis of crisp coded data, namely multiple correspondence analysis, yields principal inertias (eigenvalues) that considerably underestimate the quality of the solution in a low-dimensional space. Since the crisp data only code the categories to which each individual case belongs, an alternative measure of fit is simply to count how well these categories are predicted by the solution. Another approach is to consider multiple correspondence analysis equivalently as the analysis of the Burt matrix (i.e., the matrix of all two-way cross-tabulations of the categorical variables), and then perform a joint correspondence analysis to fit just the off-diagonal tables of the Burt matrix - the measure of fit is then computed as the quality of explaining these tables only. The correspondence analysis of fuzzy coded data, called "fuzzy multiple correspondence analysis", suffers from the same problem, albeit attenuated. Again, one can count how many correct predictions are made of the categories which have highest degree of membership. But here one can also defuzzify the results of the analysis to obtain estimated values of the original data, and then calculate a measure of fit in the familiar percentage form, thanks to the resultant orthogonal decomposition of variance. Furthermore, if one thinks of fuzzy multiple correspondence analysis as explaining the two-way associations between variables, a fuzzy Burt matrix can be computed and the same strategy as in the crisp case can be applied to analyse the off-diagonal part of this matrix. In this paper these alternative measures of fit are defined and applied to a data set of continuous meteorological variables, which are coded crisply and fuzzily into three categories. Measuring the fit is further discussed when the data set consists of a mixture of discrete and continuous variables.

A multi-objective model for a multi-period distribution management problem

The problems arising in commercial distribution are complex and involve several players and decision levels. One important decision is relatedwith the design of the routes to distribute the products, in an efficient and inexpensive way.This article deals with a complex vehicle routing problem that can beseen as a new extension of the basic vehicle routing problem. The proposed model is a multi-objective combinatorial optimization problemthat considers three objectives and multiple periods, which models in a closer way the real distribution problems. The first objective is costminimization, the second is balancing work levels and the third is amarketing objective. An application of the model on a small example, with5 clients and 3 days, is presented. The results of the model show the complexity of solving multi-objective combinatorial optimization problems and the contradiction between the several distribution management objective.

Stepwise multiple testing as formalized data snooping

It is common in econometric applications that several hypothesis tests arecarried out at the same time. The problem then becomes how to decide whichhypotheses to reject, accounting for the multitude of tests. In this paper,we suggest a stepwise multiple testing procedure which asymptoticallycontrols the familywise error rate at a desired level. Compared to relatedsingle-step methods, our procedure is more powerful in the sense that itoften will reject more false hypotheses. In addition, we advocate the useof studentization when it is feasible. Unlike some stepwise methods, ourmethod implicitly captures the joint dependence structure of the teststatistics, which results in increased ability to detect alternativehypotheses. We prove our method asymptotically controls the familywise errorrate under minimal assumptions. We present our methodology in the context ofcomparing several strategies to a common benchmark and deciding whichstrategies actually beat the benchmark. However, our ideas can easily beextended and/or modied to other contexts, such as making inference for theindividual regression coecients in a multiple regression framework. Somesimulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data.

Exact and approximate stepdown methods for multiple hypothesis testing

Consider the problem of testing k hypotheses simultaneously. In this paper,we discuss finite and large sample theory of stepdown methods that providecontrol of the familywise error rate (FWE). In order to improve upon theBonferroni method or Holm's (1979) stepdown method, Westfall and Young(1993) make eective use of resampling to construct stepdown methods thatimplicitly estimate the dependence structure of the test statistics. However,their methods depend on an assumption called subset pivotality. The goalof this paper is to construct general stepdown methods that do not requiresuch an assumption. In order to accomplish this, we take a close look atwhat makes stepdown procedures work, and a key component is a monotonicityrequirement of critical values. By imposing such monotonicity on estimatedcritical values (which is not an assumption on the model but an assumptionon the method), it is demonstrated that the problem of constructing a validmultiple test procedure which controls the FWE can be reduced to the problemof contructing a single test which controls the usual probability of a Type 1error. This reduction allows us to draw upon an enormous resamplingliterature as a general means of test contruction.

Simultaneous Optical Recording in Multiple Cells by Digital Holographic Microscopy of Chloride Current Associated to Activation of the Ligand-Gated Chloride Channel GABA(A) Receptor.

Chloride channels represent a group of targets for major clinical indications. However, molecular screening for chloride channel modulators has proven to be difficult and time-consuming as approaches essentially rely on the use of fluorescent dyes or invasive patch-clamp techniques which do not lend themselves to the screening of large sets of compounds. To address this problem, we have developed a non-invasive optical method, based on digital holographic microcopy (DHM), allowing monitoring of ion channel activity without using any electrode or fluorescent dye. To illustrate this approach, GABA(A) mediated chloride currents have been monitored with DHM. Practically, we show that DHM can non-invasively provide the quantitative determination of transmembrane chloride fluxes mediated by the activation of chloride channels associated with GABA(A) receptors. Indeed through an original algorithm, chloride currents elicited by application of appropriate agonists of the GABA(A) receptor can be derived from the quantitative phase signal recorded with DHM. Finally, chloride currents can be determined and pharmacologically characterized non-invasively simultaneously on a large cellular sampling by DHM.

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

Meta-analysis identifies multiple loci associated with kidney function-related traits in east Asian populations.

Chronic kidney disease (CKD), impairment of kidney function, is a serious public health problem, and the assessment of genetic factors influencing kidney function has substantial clinical relevance. Here, we report a meta-analysis of genome-wide association studies for kidney function-related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN). Our meta-analysis identified 17 loci newly associated with kidney function-related traits, including the concentrations of blood urea nitrogen, uric acid and serum creatinine and estimated glomerular filtration rate based on serum creatinine levels (eGFRcrea) (P < 5.0 × 10(-8)). We further examined these loci with in silico replication in individuals of European ancestry from the KidneyGen, CKDGen and GUGC consortia, including a combined total of ∼110,347 individuals. We identify pleiotropic associations among these loci with kidney function-related traits and risk of CKD. These findings provide new insights into the genetics of kidney function.

Inversion of multiple intersecting high-resolution crosshole GPR profiles for hydrological characterization at the Boise Hydrogeophysical Research Site

The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. In particular, crosshole ground-penetrating radar (GPR) tomography has shown much promise in hydrology because of its ability to provide highly detailed images of subsurface radar wave velocity, which is strongly linked to soil water content. Here, we develop and demonstrate a procedure for inverting together multiple crosshole GPR data sets in order to characterize the spatial distribution of radar wave velocity below the water table at the Boise Hydrogeophysical Research Site (BHRS) near Boise, Idaho, USA. Specifically, we jointly invert 31 intersecting crosshole GPR profiles to obtain a highly resolved and consistent radar velocity model along the various profile directions. The model is found to be strongly correlated with complementary neutron porosity-log data and is further corroborated by larger-scale structural information at the BHRS. This work is an important prerequisite to using crosshole GPR data together with existing hydrological measurements for improved groundwater flow and contaminant transport modeling.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

The number of planar central configurations for the 4-body problem is finite when 3 mass positions are fixed

In the n{body problem a central con guration is formed when the position vector of each particle with respect to the center of mass is a common scalar multiple of its acceleration vector. Lindstrom showed for n = 3 and for n > 4 that if n ? 1 masses are located at xed points in the plane, then there are only a nite number of ways to position the remaining nth mass in such a way that they de ne a central con guration. Lindstrom leaves open the case n = 4. In this paper we prove the case n = 4 using as variables the mutual distances between the particles.

Reduced left hemisphere dominance for multiple versus single anagram solutions and its modulation by individuals' schizotypy

Problem solving (including insight, divergent thinking) seems to rely on the right hemisphere (RH). These functions are difficult to assess behaviorally. We propose anagram resolution as a suitable paradigm. University students (n=32) performed three tachistoscopic lateralized visual half-field experiments (stimulus presentation 150ms). In Experiment 1, participants recalled four-letter strings. Subsequently, participants provided solutions for four-letter anagrams (one solution in Experiment 2; two solutions in Experiment 3). Additionally, participants completed a schizotypy questionnaire (O-LIFE). Results showed a right visual field advantage in Experiment 1 and 2, but no visual field advantage in Experiment 3. In Experiment 1, increasing positive schizotypy associated with a RH performance shift. Problem solving seems to require increasingly the RH when facing several rather than one solution. This result supports previous studies on the RH's role in remote associative, metaphor and discourse processing. The more complex language requirements, the less personality traits seem to matter.

Transcatheter coil embolization of multiple bilateral congenital coronary artery fistulae.

Coronary artery fistulae represent the most frequent congenital anomalies of the coronary arteries, but remain a relatively uncommon clinical problem. Moreover, multiple fistulae originating from both the left and the right coronary arteries and draining into the left ventricular chamber are a rare condition. Due to the low prevalence of these anomalies, the appropriate management of patients with symptomatic coronary artery fistulae is controversial. Transcatheter closure approaches have emerged as a less invasive strategy and are nowadays considered a valuable alternative to surgical correction with similar effectiveness, morbidity and mortality. The percutaneous management, however, is mainly limited by the individual anatomic features of the fistula and an appropriate patient's selection is considered as a key determining factor to achieve complete occlusion. Thus, success rates of transcatheter closure techniques reported in the literature are extremely variable and highly dependent upon the nature of the follow up, which, at present, is not standardized. The optimal management of symptomatic patients with multiple coronary artery fistulae still remains a challenging problem and has been traditionally considered as an indication for cardiac surgery. We report here the case of a patient with double bilateral congenital coronary artery fistulae arising from both the left and right coronary arteries and draining individually into the left ventricular chamber. This patient underwent successful transcatheter anterograde closure of both fistulae using a microcoil embolization technique.