The psychometric properties of the Kessler Psychological Distress Scale (K6) in a general population sample of adolescents

The 6-item Kessler Psychological Distress Scale (K6; Kessler et al., 2002) is a screener for psychological distress that has robust psychometric properties among adults. Given that a significant proportion of adolescents experience mental illness, there is a need for measures that accurately and reliably screen for mental disorders in this age group. This study examined the psychometric properties of the K6 in a large general population sample of adolescents (N = 4,434; mean age = 13.5 years; 44.6% male). Factor analyses were conducted to examine the dimensionality of the K6 in adolescents and to investigate sex-based measurement invariance. This study also evaluated the K6 as a predictor of scores on the Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997). The K6 demonstrated high levels of internal consistency, with the 6 items loading primarily on 1 factor. Consistent with previous research, females reported higher mean levels of psychological distress when compared with males. The identification of sex-based measurement noninvariance in the item thresholds indicated that these mean differences most likely represented reporting bias in the K6 items rather than true differences in the underlying psychological distress construct. The K6 was a fair to good predictor of abnormal scores on the SDQ, but predictive utility was relatively low among males. Future research needs to focus on refining and augmenting the K6 scale to maximize its utility in adolescents. (PsycINFO Database Record (c) 2015 APA, all rights reserved)

The Use of Liquid-Liquid Interface (Biphasic) for the Preparation of Benzenetricarboxylate Complexes of Cobalt and Nickel

New metal-organic frameworks (MOFs) [Ni(C12N2H10)(H2O)][C6H3(COO)2(COOH)] (I), [Co2(H2O)6][C6H3(COO)3]2·(C4N2H12)(H2O)2 (II), [Ni2(H2O)6][C6H3(COO)3]2·(C4N2H12)(H2O)2 (III), [Ni(C13N2H14)(H2O)][C6H3(COO)2(COOH)] (IV), [Ni3(H2O)8][C6H3(COO)3] (V) and [Co(C4N2H4)(H2O)][C6H3(COO)3] (VI) {C6H3(COOH)3 = trimesic acid, C12N2H10 = 1,10-phenanthroline, C4N2H12 = piperazine dication, C13N2H14 = 1,3-bis(4-pyridyl)propane and C4N2H4 = pyrazine} have been synthesized by using an interface between two immiscible solvents, water and cyclohexanol. The compounds are constructed from the connectivity between the octahedral M2+ (M = Ni, Co) ions coordinated by oxygen atoms of carboxylate groups and water molecules and/or by nitrogen atoms of the ligand amines and the carboxylate units to form a variety of structures of different dimensionality. Strong hydrogen bonds of the type O-H···O are present in all the compounds, which give rise to supramolecularly organized higher-dimensional structures. In some cases ··· interactions are also observed. Magnetic studies indicate weak ferromagnetic interactions in I, IV and V and weak antiferromagnetic interactions in the other compounds (II, III and VI). All the compounds have been characterized by a variety of techniques.

Elastic properties of fast ion conducting lithium based borate glasses

Elastic properties of Li2O-PbO-B2O3 glasses have been investigated using sound velocity measurements at 10 MHz. Four series of glasses have been investigated with different concentrations of Li2O, PbO and B2O3. The variations of molar volume have been examined for the influences of Li2O and PbO. The elastic moduli reveal trends in their compositional dependence. The bulk and shear modulus increases monotonically with increase in the concentration of tetrahedral boron which increases network dimensionality. The variation of bulk moduli has also been correlated to the variation in energy densities. The Poisson's ratio found to be insensitive to the concentration of tetrahedral boron in the structure. The experimental Debye temperatures are in good agreement with the expected theoretical values. Experimental observations have been examined in view, the presence of borate network and the possibility of non-negligible participation of lead in network formation. (c) 2005 Elsevier B.V. All rights reserved.

Semi-supervised learning of WLAN radio maps

In this thesis a manifold learning method is applied to the problem of WLAN positioning and automatic radio map creation. Due to the nature of WLAN signal strength measurements, a signal map created from raw measurements results in non-linear distance relations between measurement points. These signal strength vectors reside in a high-dimensioned coordinate system. With the help of the so called Isomap-algorithm the dimensionality of this map can be reduced, and thus more easily processed. By embedding position-labeled strategic key points, we can automatically adjust the mapping to match the surveyed environment. The environment is thus learned in a semi-supervised way; gathering training points and embedding them in a two-dimensional manifold gives us a rough mapping of the measured environment. After a calibration phase, where the labeled key points in the training data are used to associate coordinates in the manifold representation with geographical locations, we can perform positioning using the adjusted map. This can be achieved through a traditional supervised learning process, which in our case is a simple nearest neighbors matching of a sampled signal strength vector. We deployed this system in two locations in the Kumpula campus in Helsinki, Finland. Results indicate that positioning based on the learned radio map can achieve good accuracy, especially in hallways or other areas in the environment where the WLAN signal is constrained by obstacles such as walls.

Flow Generated By Pitched Blade Turbines Ii: Simulation Using Κ-Ε Model

Experimental data on average velocity and turbulence intensity generated by pitched blade downflow turbines (PTD) were presented in Part I of this paper. Part II presents the results of the simulation of flow generated by PTD The standard κ-ε model along with the boundary conditions developed in the Part 1 have been employed to predict the flow generated by PTD in cylindrical baffled vessel. This part describes the new software FIAT (Flow In Agitated Tanks) for the prediction of three dimensional flow in stirred tanks. The basis of this software has been described adequately. The influence of grid size, impeller boundary conditions and values of model parameters on the predicted flow have been analysed. The model predictions successfully reproduce the three dimensionality and the other essential characteristics of the flow. The model can be used to improve the overall understanding about the relative distribution of turbulence by PTD in the agitated tank

Ordering near the percolation threshold in models of two-dimensional interacting bosons with quenched dilution

Randomly diluted quantum boson and spin models in two dimensions combine the physics of classical percolation with the well-known dimensionality dependence of ordering in quantum lattice models. This combination is rather subtle for models that order in two dimensions but have no true order in one dimension, as the percolation cluster near threshold is a fractal of dimension between 1 and 2: two experimentally relevant examples are the O(2) quantum rotor and the Heisenberg antiferromagnet. We study two analytic descriptions of the O(2) quantum rotor near the percolation threshold. First a spin-wave expansion is shown to predict long-ranged order, but there are statistically rare points on the cluster that violate the standard assumptions of spin-wave theory. A real-space renormalization group (RSRG) approach is then used to understand how these rare points modify ordering of the O(2) rotor. A new class of fixed points of the RSRG equations for disordered one-dimensional bosons is identified and shown to support the existence of long-range order on the percolation backbone in two dimensions. These results are relevant to experiments on bosons in optical lattices and superconducting arrays, and also (qualitatively) for the diluted Heisenberg antiferromagnet La-2(Zn,Mg)(x)Cu1-xO4.

FTIR-spektroskopia kasviuutteiden analysoinnissa

FTIR-spektroskopia (Fourier-muunnosinfrapunaspektroskopia) on nopea analyysimenetelmä. Fourier-laitteissa interferometrin käyttäminen mahdollistaa koko infrapunataajuusalueen mittaamisen muutamassa sekunnissa. ATR-liitännäisellä varustetun FTIR-spektrometrin käyttö ei edellytä juuri näytteen valmistusta ja siksi menetelmä on käytössä myös helppo. ATR-liitännäinen mahdollistaa myös monien erilaisten näytteiden analysoinnin. Infrapunaspektrin mittaaminen onnistuu myös sellaisista näytteistä, joille perinteisiä näytteenvalmistusmenetelmiä ei voida käyttää. FTIR-spektroskopian avulla saatu tieto yhdistetään usein tilastollisiin monimuuttuja-analyyseihin. Klusterianalyysin avulla voidaan spektreistä saatu tieto ryhmitellä samanlaisuuteen perustuen. Hierarkkisessa klusterianalyysissa objektien välinen samanlaisuus määritetään laskemalla niiden välinen etäisyys. Pääkomponenttianalyysin avulla vähennetään datan ulotteisuutta ja luodaan uusia korreloimattomia pääkomponentteja. Pääkomponenttien tulee säilyttää mahdollisimman suuri määrä alkuperäisen datan variaatiosta. FTIR-spektroskopian ja monimuuttujamenetelmien sovellusmahdollisuuksia on tutkittu paljon. Elintarviketeollisuudessa sen soveltuvuutta esimerkiksi laadun valvontaan on tutkittu. Menetelmää on käytetty myös haihtuvien öljyjen kemiallisten koostumusten tunnistukseen sekä öljykasvien kemotyyppien havaitsemiseen. Tässä tutkimuksessa arvioitiin menetelmän käyttöä suoputken uutenäytteiden luokittelussa. Tutkimuksessa suoputken eri kasvinosien uutenäytteiden FTIR-spektrejä vertailtiin valikoiduista puhdasaineista mitattuihin FTIR-spektreihin. Puhdasaineiden FTIR-spektreistä tunnistettiin niiden tyypilliset absorptiovyöhykkeet. Furanokumariinien spektrien intensiivisten vyöhykkeiden aaltolukualueet valittiin monimuuttuja-analyyseihin. Monimuuttuja-analyysit tehtiin myös IR-spektrin sormenjälkialueelta aaltolukualueelta 1785-725 cm-1. Uutenäytteitä pyrittiin luokittelemaan niiden keräyspaikan ja kumariinipitoisuuden mukaan. Keräyspaikan mukaan ryhmittymistä oli havaittavissa, mikä selittyi vyöhykkeiden aaltolukualueiden mukaan tehdyissä analyyseissa pääosin kumariinipitoisuuksilla. Näissä analyyseissa uutenäytteet pääosin ryhmittyivät ja erottuivat kokonaiskumariinipitoisuuksien mukaan. Myös aaltolukualueen 1785-725 cm-1 analyyseissa havaittiin keräyspaikan mukaan ryhmittymistä, mitä kumariinipitoisuudet eivät kuitenkaan selittäneet. Näihin ryhmittymisiin vaikuttivat mahdollisesti muiden yhdisteiden samanlaiset pitoisuudet näytteissä. Analyyseissa käytettiin myös muita aaltolukualueita, mutta tulokset eivät juuri poikenneet aiemmista. 2. kertaluvun derivaattaspektrien monimuuttuja-analyysit sormenjälkialueelta eivät myöskään muuttaneet tuloksia havaittavasti. Jatkotutkimuksissa nyt käytettyä menetelmää on mahdollista edelleen kehittää esimerkiksi tutkimalla monimuuttuja-analyyseissa 2. kertaluvun derivaattaspektreistä suppeampia, tarkkaan valittuja aaltolukualueita.

Agglomerative clustering using the concept of mutual nearest neighbourhood

A method for determining the mutual nearest neighbours (MNN) and mutual neighbourhood value (mnv) of a sample point, using the conventional nearest neighbours, is suggested. A nonparametric, hierarchical, agglomerative clustering algorithm is developed using the above concepts. The algorithm is simple, deterministic, noniterative, requires low storage and is able to discern spherical and nonspherical clusters. The method is applicable to a wide class of data of arbitrary shape, large size and high dimensionality. The algorithm can discern mutually homogenous clusters. Strong or weak patterns can be discerned by properly choosing the neighbourhood width.

Vision based indoor positioning in a retail environment

Modern smart phones often come with a significant amount of computational power and an integrated digital camera making them an ideal platform for intelligents assistants. This work is restricted to retail environments, where users could be provided with for example navigational in- structions to desired products or information about special offers within their close proximity. This kind of applications usually require information about the user's current location in the domain environment, which in our case corresponds to a retail store. We propose a vision based positioning approach that recognizes products the user's mobile phone's camera is currently pointing at. The products are related to locations within the store, which enables us to locate the user by pointing the mobile phone's camera to a group of products. The first step of our method is to extract meaningful features from digital images. We use the Scale- Invariant Feature Transform SIFT algorithm, which extracts features that are highly distinctive in the sense that they can be correctly matched against a large database of features from many images. We collect a comprehensive set of images from all meaningful locations within our domain and extract the SIFT features from each of these images. As the SIFT features are of high dimensionality and thus comparing individual features is infeasible, we apply the Bags of Keypoints method which creates a generic representation, visual category, from all features extracted from images taken from a specific location. A category for an unseen image can be deduced by extracting the corresponding SIFT features and by choosing the category that best fits the extracted features. We have applied the proposed method within a Finnish supermarket. We consider grocery shelves as categories which is a sufficient level of accuracy to help users navigate or to provide useful information about nearby products. We achieve a 40% accuracy which is quite low for commercial applications while significantly outperforming the random guess baseline. Our results suggest that the accuracy of the classification could be increased with a deeper analysis on the domain and by combining existing positioning methods with ours.

Mechanical Anisotropy in Crystalline Saccharin: Nanoindentation Studies

The nanoindentation technique has been employed to relate the mechanical properties of saccharin single crystals with their internal structure. Indentations were performed on (100) and (011) faces to assess the mechanical anisotropy. The load-displacement (P-h) curves indicate significant differences in the nature of the plastic deformation on the two faces. The P-h curves obtained on the (011) plane are smooth, reflecting homogeneous plasticity. However, displacement bursts (pop-ins) are observed in the P-h curves obtained on the (100) plane suggesting a discrete deformation mechanism. Marginal differences exist in the hardness and modulus on the two faces that may, in part, be rationalized, although one notes that saccharin has a largely three-dimensional close-packed structure. The structural origins of the fundamentally different deformation mechanisms on (100) and (011) are discussed in terms of the dimensionality of the hydrogen bonding networks. Down the (100) planes, the saccharin dimers are stacked and are stabilized by nonspecific van der Wants interactions mostly between aromatic rings. However, down the (011) planes, the molecules are stabilized by more directional and cross-linked C-H ... O hydrogen bonds. This anisotropy in crystal packing and interactions is reflected in the mechanical behavior on these faces. The displacements associated with the pop-ins were found to he integral multiples oldie molecule separation distances. Nanoindentation offers an opportunity to compare experimentally, and in a quantitative way, the various intermolecular interactions that fire present in a molecular crystal.

Operationalizing Supply Chain vs. Supply Chain Competion

Competition is an immensely important area of study in economic theory, business and strategy. It is known to be vital in meeting consumers’ growing expectations, stimulating increase in the size of the market, pushing innovation, reducing cost and consequently generating better value for end users, among other things. Having said that, it is important to recognize that supply chains, as we know it, has changed the way companies deal with each other both in confrontational or conciliatory terms. As such, with the rise of global markets and outsourcing destinations, increased technological development in transportation, communication and telecommunications has meant that geographical barriers of distance with regards to competition are a thing of the past in an increasingly flat world. Even though the dominant articulation of competition within management and business literature rests mostly within economic competition theory, this thesis draws attention to the implicit shift in the recognition of other forms of competition in today’s business environment, especially those involving supply chain structures. Thus, there is popular agreement within a broad business arena that competition between companies is set to take place along their supply chains. Hence, management’s attention has been focused on how supply chains could become more aggressive making each firm in its supply chain more efficient. However, there is much disagreement on the mechanism through which such competition pitching supply chain against supply chain will take place. The purpose of this thesis therefore, is to develop and conceptualize the notion of supply chain vs. supply chain competition, within the discipline of supply chain management. The thesis proposes that competition between supply chains may be carried forward via the use of competition theories that emphasize interaction and dimensionality, hence, encountering friction from a number of sources in their search for critical resources and services. The thesis demonstrates how supply chain vs. supply chain competition may be carried out theoretically, using generated data for illustration, and practically using logistics centers as a way to provide a link between theory and corresponding practice of this evolving competition mode. The thesis concludes that supply chain vs. supply chain competition, no matter the conceptualization taken, is complex, novel and can be very easily distorted and abused. It therefore calls for the joint development of regulatory measures by practitioners and policymakers alike, to guide this developing mode of competition.

Temperature-Sensitive Src-Transformed Mdck Cells nn 3d Cultures as a Model of Malignant Transformation of Epithelial Cells

The equilibrium between cell proliferation, differentiation, and apoptosis is crucial for maintaining homeostasis in epithelial tissues. In order for the epithelium to function properly, individual cells must gain normal structural and functional polarity. The junctional proteins have an important role both in binding the cells together and in taking part in cell signaling. Cadherins form adherens junctions. Cadherins initiate the polarization process by first recognizing and binding the neighboring cells together, and then guiding the formation of tight junctions. Tight junctions form a barrier in dividing the plasma membranes to apical and basolateral membrane domains. In glandular tissues, single layered and polarized epithelium is folded into tubes or spheres, in which the basal side of the epithelial layer faces the outer basal membrane, and the apical side the lumen. In carcinogenesis, the differentiated architecture of an epithelial layer is disrupted. Filling of the luminal space is a hallmark of early epithelial tumors in tubular and glandular structures. In order for the transformed tumor cells to populate the lumen, enhanced proliferation as well as inhibition of apoptosis is required. Most advances in cancer biology have been achieved by using two-dimensional (2D) cell culture models, in which the cells are cultured on flat surfaces as monolayers. However, the 2D cultures are limited in their capacity to recapitulate the structural and functional features of tubular structures and to represent cell growth and differentiation in vivo. The development of three-dimensional (3D) cell culture methods enables the cells to grow and to be studied in a more natural environment. Despite the wide use of 2D cell culture models and the development of novel 3D culture methods, it is not clear how the change of the dimensionality of culture conditions alters the polarization and transformation process and the molecular mechanisms behind them. Src is a well-known oncogene. It is found in focal and adherens junctions of cultured cells. Active src disrupts cell-cell junctions and interferes with cell-matrix binding. It promotes cell motility and survival. Src transformation in 2D disrupts adherens junctions and the fibroblastic phenotype of the cells. In 3D, the adherens junctions are weakened, and in glandular structures, the lumen is filled with nonpolarized vital cells. Madin-Darby canine kidney (MDCK) cells are an epithelial cell type commonly used as a model for cell polarization. Its-src-transformed variants are useful model systems for analyzing the changes in cell morphology, and they play a role in src-induced malignant transformation. This study investigates src-transformed cells in 3D cell cultures as a model for malignant transformation. The following questions were posed. Firstly: What is the role of the composition and stiffness of the extracellular matrix (ECM) on the polarization and transformation of ts v-src MDCK cells in 3D cell cultures? Secondly: How do the culture conditions affect gene expression? What is the effect of v-src transformation in 2D and in 3D cell models? How does the shift from 2D to 3D affect cell polarity and gene expression? Thirdly: What is the role of survivin and its regulator phosphatase and tensin homolog protein (PTEN) in cell polarization and transformation, and in determining cell fate? How does their expression correlate with impaired mitochondrial function in transformed cells? In order to answer the above questions, novel methods of culturing and monitoring cells had to be created: novel 3D methods of culturing epithelial cells were engineered, enabling real time monitoring of a polarization and transformation process, and functional testing of 3D cell cultures. Novel 3D cell culture models and imaging techniques were created for the study. Attention was focused especially on confocal microscopy and live-cell imaging. Src-transformation disturbed the polarization of the epithelium by disrupting cell adhesion, and sensitized the cells to their environment. With active src, the morphology of the cell cluster depended on the composition and stiffness of the matrix. Gene expression studies revealed a broader impact of src transformation than mere continuous activity of src-kinase. In 2D cultures, src transformation altered the expression of immunological, actin cytoskeleton and extracellular matrix (ECM). In 3D, the genes regulating cell division, inhibition of apoptosis, cell metabolism, mitochondrial function, actin cytoskeleton and mechano-sensing proteins were altered. Surprisingly, changing the culture conditions from 2D to 3D affected also gene expression considerably. The microarray hit survivin, an inhibitor of apoptosis, played a crucial role in the survival and proliferation of src-transformed cells.

A Feature-Based Solution to Forward Problem in Electrical Capacitance Tomography of Conductive Materials

A new feature-based technique is introduced to solve the nonlinear forward problem (FP) of the electrical capacitance tomography with the target application of monitoring the metal fill profile in the lost foam casting process. The new technique is based on combining a linear solution to the FP and a correction factor (CF). The CF is estimated using an artificial neural network (ANN) trained using key features extracted from the metal distribution. The CF adjusts the linear solution of the FP to account for the nonlinear effects caused by the shielding effects of the metal. This approach shows promising results and avoids the curse of dimensionality through the use of features and not the actual metal distribution to train the ANN. The ANN is trained using nine features extracted from the metal distributions as input. The expected sensors readings are generated using ANSYS software. The performance of the ANN for the training and testing data was satisfactory, with an average root-mean-square error equal to 2.2%.

Can one electrochemically measure the statistical morphology of a rough electrode

We have developed a theory for an electrochemical way of measuring the statistical properties of a nonfractally rough electrode. We obtained the expression for the current transient on a rough electrode which shows three times regions: short and long time limits and the transition region between them. The expressions for these time ranges are exploited to extract morphological information about the surface roughness. In the short and long time regimes, we extract information regarding various morphological features like the roughness factor, average roughness, curvature, correlation length, dimensionality of roughness, and polynomial approximation for the correlation function. The formulas for the surface structure factors (the measure of surface roughness) of rough surfaces in terms of measured reversible and diffusion-limited current transients are also obtained. Finally, we explore the feasibility of making such measurements.

Decorrelation of broad band signals by toeplitz-block-toeplitz structuring

We propose F-norm of the cross-correlation part of the array covariance matrix as a measure of correlation between the impinging signals and study the performance of different decorrelation methods in the broadband case using this measure. We first show that dimensionality of the composite signal subspace, defined as the number of significant eigenvectors of the source sample covariance matrix, collapses in the presence of multipath and the spatial smoothing recovers this dimensionality. Using an upper bound on the proposed measure, we then study the decorrelation of the broadband signals with spatial smoothing and the effect of spacing and directions of the sources on the rate of decorrelation with progressive smoothing. Next, we introduce a weighted smoothing method based on Toeplitz-block-Toeplitz (TBT) structuring of the data covariance matrix which decorrelates the signals much faster than the spatial smoothing. Computer simulations are included to demonstrate the performance of the two methods.