Multidimensional Analysis Techniques Research Articles

Time Series Characteristics of Serum Branched-Chain Amino Acids for Early Diagnosis of Chronic Heart Failure.

Chronic heart failure (CHF) is an ongoing clinical syndrome with cardiac dysfunction that can be traced to alterations in cardiac metabolism. The identification of metabolic biomarkers in easily accessible fluids to improve the early diagnosis of CHF has been elusive to date. In this study, we took multidimensional analytical techniques to discover potentially new diagnostic biomarkers by focusing on the dynamic changes of metabolites in serum during the progression of CHF. Using mass-spectrometry-based untargeted metabolomics, we identified 23 cardiac metabolites that were altered in a rat model of myocardial infarction induced CHF. Among these differential metabolites, branched-chain amino acids (BCAAs) in serum, especially leucine and valine, showed a high capability to differentiate between CHF and sham-operated rats, of which area under the receiver operating characteristic curve was greater than 0.75. Combining with targeted analysis of the amino acids and related proteins and genes, we confirmed that BCAA metabolic pathway was significantly inhibited in rat failing hearts. On the basis of the time series data of serum samples, we characterized the fluctuation pattern of circulating BCAAs by the disease progression model. Finally, the time-resolved diagnostic potential of serum BCAAs was evaluated by the machine-learning-based classifier, and high diagnostic accuracy of 93.75% was achieved within 3 weeks after surgery. These findings provide a promising metabolic signature that can be further exploited for CHF early diagnostic development.

Revealing Disciplinary Variation in Pakistani Academic Writing: A Multidimensional Analysis

Pakistani English as a non-native variety exhibits variation at different levels of language. Early quantitative studies on Pakistani English have compared individual linguistic features of Pakistani English with their counterparts in British English and claimed about the distinctive identity of Pakistani English as an indigenous variety. Pakistani English need to be compared at the level of register to further highlight its unique features and strengthen its distinct identity. Based on a special purpose corpus, the present research paper endeavors to investigate linguistic variation across disciplines in Pakistani academic writing as a register. Disciplinary variation is explored along with five new textual dimensions identified and labeled through the technique of Multidimensional analysis (Azher & Mehmood, 2016). The ANOVA results reveal that statistically significant differences are found among disciplines on all the new dimensions of Pakistani Academic Writing. The findings underline the implications for discipline-specific and register-based pedagogies with special reference to Pakistani English.

Who Am I? The Social Identities of Muslim-American Adolescents

Muslim-American adolescents face unique developmental challenges, due to the national and global negative spotlight on Islam, as they navigate identity formation in the mainstream American setting. However, the intersection of various social identities (SI) in the navigation of these challenges has been ignored in much social-scientific literature. We examined the SI of Muslim-American adolescents using the multidimensional cluster analysis technique. Correlates of adolescents’ SI were also explored, specifically adolescents’ self-reported psychological well-being. One hundred and fifty Muslim adolescents were recruited from schools, mosques, and community organizations throughout Maryland. Follow-up analyses indicated that the High-Muslim/High-American adolescents reported the highest well-being and Moderate-Muslim/Undifferentiated-American cluster reported poorer well-being than the other clusters. Findings highlighted the importance of simultaneously assessing Muslim and American SIs, and the differential psychological benefits based on adolescents’ SI profiles. The article concludes by discussing implications for future research on Muslim adolescents’ successful adjustment.

Who Am I? The Social Identities of Muslim-American Adolescents

Muslim-American adolescents face unique developmental challenges, due to the national and global negative spotlight on Islam, as they navigate identity formation in the mainstream American setting. However, the intersection of various social identities (SI) in the navigation of these challenges has been ignored in much social-scientific literature. We examined the SI of Muslim-American adolescents using the multidimensional cluster analysis technique. Correlates of adolescents’ SI were also explored, specifically adolescents’ self-reported psychological well-being. One hundred and fifty Muslim adolescents were recruited from schools, mosques, and community organizations throughout Maryland. Follow-up analyses indicated that the High-Muslim/High-American adolescents reported the highest well-being and Moderate-Muslim/Undifferentiated-American cluster reported poorer well-being than the other clusters. Findings highlighted the importance of simultaneously assessing Muslim and American SIs, and the differential psychological benefits based on adolescents’ SI profiles. The article concludes by discussing implications for future research on Muslim adolescents’ successful adjustment.

Peculiarities of homogeneous areas distribution within the fields of hydrometeorological characteristics in the Northern Pacific during the cold season

In order to investigate horizontal distribution of hydro-meteorological characteristics, statistical analysis techniques, including multidimensional statistical analysis techniques (for example, factor, cluster analysis etc.) are usually applied. These techniques allow obtaining not only fields of particular characteristic by means of plotting appropriate isolines, but determining entire homogeneous areas with typical representative point which helps to compress information considerably and to reveal boundaries of distribution of certain characteristic within the entire spatial aggregation.
 Schemes of zoning of fields of difference for monthly average temperatures “underlying surface-air” at 2 m height, of surface flows of latent heat, of zonal aspects of wind speed in the Northern Pacific obtained by means of the Universal Iterative Method of Data Clusterization are offered. The obtained clusterization schemes underwent both physical and statistical analyses having good scientific justification. It is shown that distribution of zonal aspect of wind speed has latitudinal direction, and distribution of flows of latent heat and temperature differences has mainly a focal nature. Analysis of variability of boundaries of homogeneous areas, average values of representative vectors, dispersions, mean-square deviations during future time intervals will allow identifying the specific features of climate variability through the example of the fields of hydrometeorological characteristics under study.

Linguistic Variation across Research Sections of Pakistan Academic Writing: A Multidimensional Analysis

With the concept of language variation, it has become utmost important to analyze linguistic patterns across register. Pakistani academic writing like other registers in Pakistan is an area that still seeks the attention of the researchers and linguists. This target register needs to be fully described in terms of linguistic characteristics to strengthen the distinct identity of Pakistani academic writing as a register. The present research strives to explore linguistic variation across research sections of Pakistani academic writing as a register along with five new textual dimensions explored through the technique of Multidimensional analysis (Azher & Mehmood, 2016). The research is based on the corpus of 235 M. Phil and PhD research dissertations taken from different universities all over Pakistan. The corpus was further divided into five research sections and was tagged for 189 linguistic features. The ANOVA results on variation among research sections indicate that there lie statistically significant differences among research sections of Pakistani Academic Writing on all the new textual dimensions.

Novel spatiotemporal analysis of gait changes in body weight supported treadmill trained rats following cervical spinal cord injury

BackgroundCommon gait measures such as stride length, cycle time, and step height are not independent variables, but different aspects of the same multidimensional step. This complicates comparisons between experimental groups. Here we present a novel multidimensional gait analysis method and use this method to assess the ability of body weight supported treadmill training (BWSTT) to improve rodent stepping after spinal cord injury (SCI).MethodsIn lieu of reducing a step to a collection of gait measures and comparing the means of several of these, we developed a multidimensional analysis technique that compares the step as a whole. While in a passive robotic gait training device, the pre-injury hindlimb stepping of 108 rats was recorded while they walked in a quadrupedal posture at 8 cm/s. Following a C4/5 over-hemisection spinal cord injury the weekly changes in stepping were tracked for 17 untrained and 10 BWSTT animals for 7 weeks. The performance of trained rats was recorded during training with BWS, as well as at the end of the training week without BWS. An additional six uninjured rats were trained for 5 weeks.ResultsOur novel multidimensional analysis shows that stepping is asymmetrically altered 1 week after SCI. The differences in stepping change over the following weeks, with the less impaired left hindlimb deviating further away from pre-injury than the more impaired right hindlimb. Uninjured rats do not significantly alter their stepping over 5 weeks. BWSTT improves the stepping of the right hindlimb, but only when the BWS is active. If the BWS is not present, the performance of trained animals is worse than untrained rats. The left hindlimb performance of BWSTT rats is worse than untrained rats, during both training sessions and weekly assessments.ConclusionsWe feel that our novel multidimensional analysis is a more appropriate method to address the inter-dependencies of gait measures. Untrained rats exhibit both initial impairments as well as the development of compensatory techniques. BWSTT does not improve this spontaneous recovery, but exacerbates it, particularly in the less impaired left hindlimb.

Update on sound quality assessment with TWO!EARS

The paper summarizes the different test and modeling campaigns carried out in the EC-funded FET-Open project TWO!EARS (www.twoears.eu) for sound quality and Quality of Experience (QoE) evaluation of spatial audio reproduction technology like stereophony or Wave-field Synthesis (WFS). This work represents one of the two proof-of-concept application domains of the interactive listening model developed in TWO!EARS. One stream of our sound-quality-related work focused on listening tests and model development for the individual sound quality features localization and coloration. After briefly reviewing the modeling approaches for these individual features presented in more depth elsewhere, the paper presents data and modeling considerations for a set of pairwise preference listening tests, following a dedicated audio mixing and reproduction paradigm. For subsequent model development, the results are analyzed in different ways, for example in terms of the pairwise preference data directly, using the Bradley-Terry-Luce model and using multidimensional analysis techniques. Based on these analyses, different modeling approaches based on the TWO!EARS framework are presented. To conclude, considerations are provided on how multimodal interaction can affect preference selections, based on an additional test on the selection of the “sweet spot” in a spatial audio listening context.

A multi-dimensional functional principal components analysis of EEG data.

The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal, and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations.

The medical sociological evaluation of population health in ecological bio-climatic conditions of the Primorskii Kraii

The article presents the results of medical sociological evaluation of population health in ecological bio-climatic conditions of the Primorskii Kraii. The purpose of study is to establish patterns of formation of population health exemplified by three systems of organism (respiratory organs, urogenital system, skin). The questionnaire technique was applied to study impact of factors of life-style, diet behavior, skin and urogenital system according official statistics data F12 in 2007-2011. The technique of such multi-dimensional analysis as P.V. Terentiev correlation pleiades was applied. The medical sociological study established input of social factors in formation of population health in the ecological bio-climatic conditions of the Primorskii Kraii. The results of study permit determining main directions of medical activities and to develop address programs of prevention.

Non-monetary poverty in Togo: a multidimensional approach

The monetary approach is not sufficient to understand the multiple dimension of poverty. The purpose of this research is therefore to measure and analyze multidimensional poverty reduced to a single non-monetary dimension and according to the characteristics of household heads. Based on the non-monetary variables provided by the most recent country survey (QUIBB 2006), we use Multidimensional Correspondence Analysis techniques to construct a Composite Poverty Indicator. The results of the non-poverty index suggest that the poorest are large families and households in rural areas. The deprivation is also more serious in households whose heads are male, aged between 51 and 99 and less educated. The findings are the same for the monetary approach at the poverty line, leading to the conclusion that both types of poverty are quite strongly and positively correlated. Finally, we propose some recommendations for socioeconomic policies.

The diffusion of cholera in Egypt, 1947: a time-space analysis of one of the largest single outbreaks in the twentieth century

The epidemic of cholera that spread through Egypt in the latter months of 1947 was one of the largest single outbreaks of the disease in the twentieth century. Using a swash–backwash model, this paper examines the geographical wave-like spread and subsequent retreat of the epidemic from an apparent origin in the settlements and prisoner-of-war camps of the Nile Delta area to reach its maximum geographical extent some six weeks later at Aswan (850 km away). Our results demonstrate the very rapid spatial advance of the epidemic wave through the provinces and governorates of Egypt, with an approximately linear sequence of progression up the Nile. Superimposed on this national pattern are pronounced differences in the rate of epidemic advance in the traditional geographical divisions of Lower and Upper Egypt. Alternative visualisations of the cholera spaces of Egypt, using techniques of multidimensional scaling (MDS) and cluster analysis, underscore the differential patterns of cholera transmission in these areas of the country. The patterns are interpreted in relation to a vigorous control effort that included restrictions on public transport, patient isolation, contact tracing and mass vaccination of the entire population exposed to risk of infection.

Entrepreneurial Activities and Level of Development in Morocco: Empirical Investigation from Global Entrepreneurship Monitor Data

The purpose of this article, which exploits data gathered by Global Entrepreneurship Monitor (GEM, 2009), is to establish a typology of countries based on the intentions and the level of entrepreneurial activities while focusing on the position of Morocco. We then test the form of the relationship that links the level of development of the countries to the level of intentions and entrepreneurial activity by relying on the techniques of multidimensional analysis and ordinary least squares (OLS). Results show that unlike popular belief, high-income countries are weakly involved in entrepreneurial activities. They also show that Moroccans have very favourable perceptions and intentions of entrepreneurship. However, the level of entrepreneurial activity at an early stage remains lower than the one recorded in other countries such as Yemen and Uganda. Thus in Morocco, policymakers should seize the opportunity linked to the very high status of the entrepreneur to encourage enterprise creation, and therefore wealth creation.

Visual analysis method for cultural heritage site risk assessment

Many significant cultural heritage sites are at risk caused by natural environment. A unique type of natural risk to heritage sites is deterioration risk. Conservators and managers of heritage sites are attempting to develop a risk management approach to reduce this type of risk. Risk assessment is the essential component part of risk management process. However, it is hindered by several challenges resulting from the complexity of deterioration risk. We propose the use of visual analysis method for deterioration risk assessment focusing on matching the major needs and objectives of deterioration risk analysis. Our purpose is to facilitate risk analysis which consists of perceiving risk as basis, risk level estimate, and risk cause analysis. A spatial view of deterioration risk is designed for the discovery of distribution patterns. Based on clustering technique, we propose a visual analytics method for risk level analysis. Lastly, the proposed multidimensional data analysis technique is used to detect the causes of deterioration risks.

Evaluating Romanian Eco-Innovation Performances in European Context

The field of eco-innovation is included in the area of sustainable development being closely related with ecological planning. In this context, this paper aims to evaluate Romanian eco-innovation performance during the period 2003–2013 by constructing a composite index and to also identify the main eco-innovation poles at the European level using multidimensional analysis techniques based on the eco-innovation specific indicators for the year 2013. This approach used the methodology of constructing composite indices proposed by Organization for Economic Co-operation and Development (OECD) in 2008. The index measured the eco-innovation dimensions in 27 countries over the period 2003–2013. The empirical analysis revealed the conclusion that in Romania, the eco-innovation level is low compared with other countries, thus Romania cannot emphasize its eco-innovation performance. The empirical results of the study highlighted that eco-innovation represents a phenomenon leading to significant progress in achieving the objective of sustainable development in Romania, and also at the European level, only if the importance of this area is awarded and eco-innovation measures are enforced through adequate policies, leading to economic growth.

Multidimensional characteristics of annoyance perception to tonal building mechanical noises

Tones in noises from building mechanical systems can be a leading cause of complaints in an indoor environment. One of the greatest challenges to quantifying annoyance perception from these noises is the lack of information on how assorted acoustic characteristics relate to perceptual annoyance. Recent evidence suggests that annoyance perception by noises should be treated as a multidimensional rather than a unidimensional problem. Thus, the aim of this study is to explore multidimensional aspects of annoyance perception specific for building mechanical noises with tonal components. Tone frequency, tonal strength, presence of harmonics, and time fluctuation characteristics are investigated using actual noise recordings as well as artificially synthesized signals. Two subjective tests were implemented with the noise signals. Part A of the experiment is designed to identify prevailing acoustic characteristics for annoyance perception. The dominant acoustic characteristics were determined by multidimensional scaling analysis technique. A multidimensional annoyance model is subsequently proposed based on the test results. Part B is conducted to specifically investigate perceptual weighting of individual tones to overall contributions towards annoyance perceptions when complex tones are present in signals. The results of this test help to increase the accuracy of the developed annoyance model.

Optimizing a catalyst many ways at once

Organic Chemistry Optimization strategies are often likened to hikes in a hilly landscape. If your goal is to get to the top of the highest hill, and you only take steps toward higher ground, you might never find a peak on a route that requires a preliminary descent. So it is in chemistry, where optimizing each structural feature of a catalyst consecutively might gloss over subtle tradeoffs that in combination offer the best performance. Milo et al. use multidimensional analysis techniques to generate a predictive model of how selectivity depends on multiple characteristics of the catalyst and substrate in a C-N bond-forming reaction (see the Perspective by Lu). They then apply this model to improve the catalyst globally. Science , this issue p. [737][1]; see also p. [719][2] [1]: /lookup/doi/10.1126/science.1261043 [2]: /lookup/doi/10.1126/science.aaa5624

Organic chemistry. A data-intensive approach to mechanistic elucidation applied to chiral anion catalysis.

Knowledge of chemical reaction mechanisms can facilitate catalyst optimization, but extracting that knowledge from a complex system is often challenging. Here, we present a data-intensive method for deriving and then predictively applying a mechanistic model of an enantioselective organic reaction. As a validating case study, we selected an intramolecular dehydrogenative C-N coupling reaction, catalyzed by chiral phosphoric acid derivatives, in which catalyst-substrate association involves weak, noncovalent interactions. Little was previously understood regarding the structural origin of enantioselectivity in this system. Catalyst and substrate substituent effects were probed by means of systematic physical organic trend analysis. Plausible interactions between the substrate and catalyst that govern enantioselectivity were identified and supported experimentally, indicating that such an approach can afford an efficient means of leveraging mechanistic insight so as to optimize catalyst design.

"Heroes" and "villains" of world history across cultures.

Emergent properties of global political culture were examined using data from the World History Survey (WHS) involving 6,902 university students in 37 countries evaluating 40 figures from world history. Multidimensional scaling and factor analysis techniques found only limited forms of universality in evaluations across Western, Catholic/Orthodox, Muslim, and Asian country clusters. The highest consensus across cultures involved scientific innovators, with Einstein having the most positive evaluation overall. Peaceful humanitarians like Mother Theresa and Gandhi followed. There was much less cross-cultural consistency in the evaluation of negative figures, led by Hitler, Osama bin Laden, and Saddam Hussein. After more traditional empirical methods (e.g., factor analysis) failed to identify meaningful cross-cultural patterns, Latent Profile Analysis (LPA) was used to identify four global representational profiles: Secular and Religious Idealists were overwhelmingly prevalent in Christian countries, and Political Realists were common in Muslim and Asian countries. We discuss possible consequences and interpretations of these different representational profiles.

Measuring and Analyzing the Non-Monetary Approach of Multidimensional Poverty by the Basic Needs in Togo

This paper aims at measuring and analyzing the non-monetary aspect of multidimensional poverty by the basic needs according to the characteristics of household head. This is the first study in this matter in Togo and using the Multidimensional Correspondence Analysis (MCA) techniques to construct a Composite Poverty Indicator (CPI). Moreover, we use the most recent data from the country survey QUIBB 2006. The results of the incidence of multidimensional poverty by two approaches (MCA and FGT) suggest that the households with larger size, living in rural area, whose head is male, aged between 51 and 99, less educated are the poorest. The findings are the same as those found in the monetary approach at the poverty line, leading to a conclusion that there is a positive correlation between monetary and non-monetary poverty. Finally, we propose some recommendations in terms of socioeconomic policies for alleviating multidimensional poverty.