Correlation-informed ordered dictionary learning for imaging in complex media

We propose a method for imaging in scattering media when large and diverse datasets are available. It has two steps. Using a dictionary learning algorithm the first step estimates the true Green's function vectors as columns in an unordered sensing matrix. The array data comes from many sparse sets of sources whose location and strength are not known to us. In the second step, the columns of the estimated sensing matrix are ordered for imaging using the multidimensional scaling algorithm with connectivity information derived from cross-correlations of its columns, as in time reversal. For these two steps to work together, we need data from large arrays of receivers so the columns of the sensing matrix are incoherent for the first step, as well as from sub-arrays so that they are coherent enough to obtain connectivity needed in the second step. Through simulation experiments, we show that the proposed method is able to provide images in complex media whose resolution is that of a homogeneous medium.

Testing the bipolar assumption of Singer-Loomis Type Deployment Inventory for Korean adults using classification and multidimensional scaling

In this study, we explored whether the Korean version of Singer Loomis Type Deployment Inventory II (K-SLTDI) captures the opposing tendencies of Jung's theory of psychological type. The types are Extroverted Sensing, Extroverted Intuition, Extroverted Feeling, Extroverted Thinking, Introverted Sensing, Introverted Intuition, Introverted Feeling, and Introverted Thinking. A nationwide online survey was conducted in South Korea. We performed multidimensional scaling and classification analyses based on 521 Korean adult profiles with eight psychological types to test the bipolarity assumption. The results showed that the Procrustes-rotated four-dimensional space successfully represented four types of opposing tendencies. Moreover, the bipolarity assumption in the four dimensions of Jungian typology was tested and compared between lower and higher psychological distress populations via cluster analysis. Lastly, we explored patterns of responses in lower and higher psychological distress populations using intersubject correlation. Both similarity analyses and classification results consistently support the theoretical considerations on the conceptualization of Jung's type in independent order that the types could be derived without bipolar assumption as Singer and Loomis expected in their Type Development Inventory. Limitations in our study include the sample being randomly selected internet users during the COVID-19 pandemic, despite excellence in the use of the internet in the general Korean population.

The Geometry of Low- and High-Level Perceptual Spaces

Low-level features are typically continuous (e.g., the gamut between two colors), but semantic information is often categorical (there is no corresponding gradient between dog and turtle) and hierarchical (animals live in land, water, or air). To determine the impact of these differences on cognitive representations, we characterized the geometry of perceptual spaces of five domains: a domain dominated by semantic information (animal names presented as words), a domain dominated by low-level features (colored textures), and three intermediate domains (animal images, lightly texturized animal images that were easy to recognize, and heavily texturized animal images that were difficult to recognize). Each domain had 37 stimuli derived from the same animal names. From 13 participants (9F), we gathered similarity judgments in each domain via an efficient psychophysical ranking paradigm. We then built geometric models of each domain for each participant, in which distances between stimuli accounted for participants' similarity judgments and intrinsic uncertainty. Remarkably, the five domains had similar global properties: each required 5-7 dimensions, and a modest amount of spherical curvature provided the best fit. However, the arrangement of the stimuli within these embeddings depended on the level of semantic information: dendrograms derived from semantic domains (word, image, and lightly texturized images) were more "tree-like" than those from feature-dominated domains (heavily texturized images and textures). Thus, the perceptual spaces of domains along this feature-dominated to semantic-dominated gradient shift to a tree-like organization when semantic information dominates, while retaining a similar global geometry.

Ordinal Characterization of Similarity Judgments

Characterizing judgments of similarity within a perceptual or semantic domain, and making inferences about the underlying structure of this domain from these judgments, has an increasingly important role in cognitive and systems neuroscience. We present a new framework for this purpose that makes very limited assumptions about how perceptual distances are converted into similarity judgments. The approach starts from a dataset of empirical judgments of relative similarities: the fraction of times that a subject chooses one of two comparison stimuli to be more similar to a reference stimulus. These empirical judgments provide Bayesian estimates of underling choice probabilities. From these estimates, we derive three indices that characterize the set of judgments, measuring consistency with a symmetric dis-similarity, consistency with an ultrametric space, and consistency with an additive tree. We illustrate this approach with example psychophysical datasets of dis-similarity judgments in several visual domains and provide code that implements the analyses.

Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets

Conventional dimensionality reduction methods like Multidimensional Scaling (MDS) are sensitive to the presence of orthogonal outliers, leading to significant defects in the embedding. We introduce a robust MDS method, called DeCOr-MDS (Detection and Correction of Orthogonal outliers using MDS), based on the geometry and statistics of simplices formed by data points, that allows to detect orthogonal outliers and subsequently reduce dimensionality. We validate our methods using synthetic datasets, and further show how it can be applied to a variety of large real biological datasets, including cancer image cell data, human microbiome project data and single cell RNA sequencing data, to address the task of data cleaning and visualization.

The impact of bilinguality and language context on the understanding of epistemic adverbs in health communication: the case of English and Russian

Aim

To explore how English epistemic adverbs, as used in health communication, are understood by speakers depending on their first language (L1) and language context.

Methods

We used an online dissimilarity rating task with paired doctors' opinions which differed only with respect to the embedded epistemic adverbs (e.g., This treatment definitely has side effects vs. This treatment possibly has side effects). In order to evaluate the possible effect of one's L1, we compared the ratings of English-speaking monolinguals and Russian-English bilinguals in Australia (Study 1). To evaluate the impact of language context, we compared the ratings of Russian-English bilinguals in Australia and Russia (Study 2). The data were interpreted using classical multidimensional scaling (C-MDS) analysis, complemented by cultural consensus analysis and hierarchical cluster analysis.

Results

The C-MDS analyses returned statistically acceptable results. Intragroup consensus was evident for all speaker groups. They all clustered the high confidence adverbs (clearly, definitely, and obviously) and the hearsay adverbs (presumably and supposedly) similarly. Effects of L1 were seen: for example, unlike the monolinguals, the Russian bilinguals did not include evidently with the high confidence adverbs (Study 1). An effect of context was also evident: Russian-English bilinguals in Australia most resembled the monolinguals in their understanding of epistemic adverbs. The way Russian-based bilinguals clustered epistemic adverbs reflected a less nuanced understanding (Study 2).

Conclusion

The subtle differences in how adverbs of likelihood and doubt are understood in health communication suggest extra care is needed when conveying risk and uncertainty to patients from diverse linguistic and/or cultural backgrounds to ensure mutual understanding and mitigate against miscommunication. The impact of L1 and language context on one's understanding highlights the need to explore more widely how epistemic adverbs are understood by diverse populations and, in doing so, improve healthcare communication practices.

A three-dimensional Oral health-related quality of life framework for temporomandibular joint disorders: a structural analysis of the Oral Health Impact Profile-14

OBJECTIVES

the objective is to analyze the structure and relationship between the components of the Oral health-related quality of life using the Oral Health Impact Profile-14 (OHIP-14) for patients with temporomandibular joint disorders (TMJD).

METHODS

two studies were examinated by means of factor analysis, multidimensional scaling and their spatial display in a cross-sectional design (n=153).

RESULTS

three-dimensional solutions with an adequate fit were found: residual distribution, root mean square of residuals (RMSR) = 0.04, Goodness of Fit Index (GFI) = 0.96, and Adjusted Goodness of Fit Index (AGFI) = 0.93; and Stress I = 0.023, respectively. The overall ordinal alpha coefficient was 0.92 (CI=0.90 to 0.94). The ordinal alpha coefficients for functional impact, psychosocial impact and psychological impact factors were 0.87 (CI=0.84 to 0.90), 0.88 (CI=0.84 to 0.91) and 0.78 (CI= 0.72 to 0.83), respectively. Item 9 was the most central, followed by 7 and 11. Items 1 and 2 had minor associations. There was no evidence of differences between centers: edge weight differences (M = 0.226, p = 0.94), global strength invariance test (S = 1.88, p = 0.1), centrality invariance test (p >0.05), edge invariance test (p >0.05).

CONCLUSIONS

the links between the dimensions and the items seem to involve psychological components. Oral health-related quality of life emerged as a three-dimensional structure (Functional Impact, Psychosocial Impact and Psychological Impact) of functional and psychosocial elements in which physical, psychological, and social disability were essential, while theoretical functional limitation was least important.

CLINICAL SIGNIFICANCE

the three-dimensional OHRQoL system for temporomandibular disorders (TMD) is a worthwhile alternative to interpret psychological and psychosocial aspects.

Improved approximation and visualization of the correlation matrix

The graphical representation of the correlation matrix by means of different multivariate statistical methods is reviewed, a comparison of the different procedures is presented with the use of an example data set, and an improved representation with better fit is proposed. Principal component analysis is widely used for making pictures of correlation structure, though as shown a weighted alternating least squares approach that avoids the fitting of the diagonal of the correlation matrix outperforms both principal component analysis and principal factor analysis in approximating a correlation matrix. Weighted alternating least squares is a very strong competitor for principal component analysis, in particular if the correlation matrix is the focus of the study, because it improves the representation of the correlation matrix, often at the expense of only a minor percentage of explained variance for the original data matrix, if the latter is mapped onto the correlation biplot by regression. In this article, we propose to combine weighted alternating least squares with an additive adjustment of the correlation matrix, and this is seen to lead to further improved approximation of the correlation matrix.

A unified approach based on multidimensional scaling for calibration estimation in survey sampling with qualitative auxiliary information

Survey calibration is a widely used method to estimate the population mean or total score of a target variable, particularly in medical research. In this procedure, auxiliary information related to the variable of interest is used to recalibrate the estimation weights. However, when the auxiliary information includes qualitative variables, traditional calibration techniques may be not feasible or the optimisation procedure may fail. In this article, we propose the use of linear calibration in conjunction with a multidimensional scaling-based set of continuous, uncorrelated auxiliary variables along with a suitable metric in a distance-based regression framework. The calibration weights are estimated using a projection of the auxiliary information on a low-dimensional Euclidean space. The approach becomes one of the linear calibration with quantitative variables avoiding the usual computational problems in the presence of qualitative auxiliary information. The new variables preserve the underlying assumption in linear calibration of a linear relationship between the auxiliary and target variables, and therefore the optimal properties of the linear calibration method remain true. The behaviour of this approach is examined using a Monte Carlo procedure and its value is illustrated by analysing real data sets and by comparing its performance with that of traditional calibration procedures.

Potential Haptic Perceptual Dimensionality of Rendered Compliance

Studies have proven that humans perceive haptic textures through different perceptual dimensions, such as rough/smooth and soft/hard, which provide useful guidance in the design of haptic devices. However, few of these have focused on the perception of compliance, which is another important perceptual property in haptic interfaces. This research was conducted to investigate the potential basic perceptual dimensions of the rendered compliance and quantify the effects of the simulation parameters. Two perceptual experiments were designed based on 27 stimuli samples generated by a 3-DOF haptic feedback device. Subjects were asked to describe these stimuli using adjectives, classify the samples, and rate them according to corresponding adjective labels. Multi-dimensional scaling (MDS) methods were then used to project adjective ratings into 2D and 3D perception spaces. According to the results, hardness and viscosity are considered two basic perceptual dimensions of the rendered compliance, while crispness can be regarded as a subsidiary perceptual dimension. Then, the relations between simulation parameters and perceptual feelings were analyzed by the regression analysis. This paper may provide a better understanding of the compliance perception mechanism and useful guidance for the improvement of rendering algorithms and devices for haptic human-computer interaction.

Haplotypic polymorphisms and forensic applications in Chinese Hunan Han population based on a series of Y-STR loci: a perspective of paternal inheritance

BACKGROUND

Hunan, a multinational province in China, possesses more than fifty ethnic groups, such as the Han, Yao, Tujia, Miao, and so on.

AIMS

To evaluate the forensic efficiency of the novel panel and investigate the genetic relationships between Hunan Han population and 12 other reference populations from China.

SUBJECTS AND METHODS

Haplotypic data of 153 unrelated males of Hunan Han population were investigated using the AGCU Y SUPP Plus amplification system containing 27 Y-chromosomal short tandem repeat (STR) loci. Forensic parameters were calculated to evaluate the application efficiency of this panel in Hunan Han population.

RESULTS

Haplotype diversity, discrimination capability, and match probability values were 0.9999999977, 1.0000, and 0.0065, respectively. Pairwise fixation index values demonstrated that the minimal genetic differentiation (0.0073) was found between Hunan Han population and Hunan Yao group, while the maximal genetic differentiation (0.0651) was observed between Hunan Han and Guangxi Yao group from the perspective of the patrilineal DNA analysis.

CONCLUSIONS

The haplotype distributions of 27 Y-STR loci in Hunan Han population exhibited remarkable polymorphisms. Moreover, this panel has potential advantages for the forensic applications regarding family investigations, paternity testing of the paternal line, and population genetics.

Gauging response time distributions to examine the effect of facial expression inversion

Introduction

We used images of facial expressions (FEs) of emotion in a speeded Same/Different task to examine (i) distributional characteristics of response times (RTs) in relation to inter-stimulus similarity and (ii) the impact of inversion on FE processing.

Methods

Stimuli were seven emotion prototypes, posed by one male and one female, and eight intermediate morphs. Image pairs (N = 225) were presented for 500 ms, upright or inverted, in a block design, each 100 times.

Results

For both upright and inverted FEs, RTs were a non-monotonic function: median values were longest for stimulus pairs of intermediate similarity, decreasing for both more-dissimilar and more-similar pairs. RTs of "Same" and "Different" judgments followed ex-Gaussian distributions. The non-monotonicity is interpreted within a dual-process decision model framework as reflecting the infrequency of identical pairs, shifting the balance between the Same and Different processes. The effect of stimulus inversion was gauged by comparing RT-based multidimensional scaling solutions for the two presentation modes. Solutions for upright and inverted FEs showed little difference, with both displaying some evidence of categorical perception. The same features appeared in hierarchical clustering solutions.

Discussion

This outcome replicates and reinforces the solutions derived from accuracy of "Different" responses reported in our earlier companion paper. We attribute this lack of inversion effect to the brief exposure time, allowing low-level visual processing to dominate Same/Different decisions while elevating early featural analysis, which is insensitive to face orientation but enables initial positive/negative valence categorization of FEs.

Multidimensional Scaling of Cognitive Ability and Academic Achievement Scores

Multidimensional scaling (MDS) was used as an alternate multivariate procedure for investigating intelligence and academic achievement test score correlations. Correlation coefficients among Wechsler Intelligence Scale for Children, Fifth Edition (WISC-5) and Wechsler Individual Achievement Test, Third Edition (WIAT-III) validity sample scores and among Kaufman Assessment Battery for Children, Second Edition (KABC-II) and Kaufman Test of Educational Achievement, Second Edition (KTEA-2) co-norming sample scores were analyzed using multidimensional scaling (MDS). Three-dimensional MDS configurations were the best fit for interpretation in both datasets. Subtests were more clearly organized by CHC ability and academic domain instead of complexity. Auditory-linguistic, figural-visual, reading-writing, and quantitative-numeric regions were visible in all models. Results were mostly similar across different grade levels. Additional analysis with WISC-V and WIAT-III tests showed that content (verbal, numeric, figural) and response process facets (verbal, manual, paper-pencil) were also useful in explaining test locations. Two implications from this study are that caution may be needed when interpreting fluency scores across academic areas, and MDS provides more empirically based validity evidence regarding content and response mode processes.

Statistical Analysis of the Impact of COVID-19 on PM2.5 Concentrations in Downtown Quito during the Lockdowns in 2020

In this paper, a comparative analysis between the PM2.5 concentration in downtown Quito, Ecuador, during the COVID-19 pandemic in 2020 and the previous five years (from 2015 to 2019) was carried out. Here, in order to fill in the missing data and achieve homogeneity, eight datasets were constructed, and 35 different estimates were used together with six interpolation methods to put in the estimated value of the missing data. Additionally, the quality of the estimations was verified by using the sum of squared residuals and the following correlation coefficients: Pearson's r, Kendall's τ, and Spearman's ρ. Next, feature vectors were constructed from the data under study using the wavelet transform, and the differences between feature vectors were studied by using principal component analysis and multidimensional scaling. Finally, a robust method to impute missing data in time series and characterize objects is presented. This method was used to support the hypothesis that there were significant differences between the PM2.5 concentration in downtown Quito in 2020 and 2015-2019.

Generating semantic maps through multidimensional scaling: linguistic applications and theory

This paper reports on the state-of-the-art in application of multidimensional scaling (MDS) techniques to create semantic maps in linguistic research. MDS refers to a statistical technique that represents objects (lexical items, linguistic contexts, languages, etc.) as points in a space so that close similarity between the objects corresponds to close distances between the corresponding points in the representation. We focus on the use of MDS in combination with parallel corpus data as used in research on cross-linguistic variation. We first introduce the mathematical foundations of MDS and then give an exhaustive overview of past research that employs MDS techniques in combination with parallel corpus data. We propose a set of terminology to succinctly describe the key parameters of a particular MDS application. We then show that this computational methodology is theory-neutral, i.e. it can be employed to answer research questions in a variety of linguistic theoretical frameworks. Finally, we show how this leads to two lines of future developments for MDS research in linguistics.

Assessment of using a gamma index analysis for patient-specific quality assurance in Japan

PURPOSE

The Task Group 218 (TG-218) report was published by the American Association of Physicists in Medicine in 2018, recommending the appropriate use of gamma index analysis for patient-specific quality assurance (PSQA). The paper demonstrates that PSQA for radiotherapy in Japan appropriately applies the gamma index analysis considering TG-218.

MATERIALS/METHODS

This survey estimated the acceptance state of radiotherapeutic institutes or facilities in Japan for the guideline using a web-based questionnaire. To investigate an appropriate PSQA of the facility-specific conditions, we researched an optimal tolerance or action level for various clinical situations, including different treatment machines, clinical policies, measurement devices, staff or their skills, and patient conditions. The responded data were analyzed using principal component analysis (PCA) and multidimensional scaling (MDS). The PCA focused on factor loading values of the first contribution over 0.5, whereas the MDS focused on mapped distances among data.

RESULTS

Responses were obtained from 148 facilities that use intensity-modulated radiation therapy (IMRT), which accounted for 42.8% of the probable IMRT use in Japan. This survey revealed the appropriate application of the following universal criteria for gamma index analysis from the guideline recommendation despite the facility-specific variations (treatment machines/the number of IMRT cases/facility attributes/responded [representative] expertise or staff): (a) 95% pass rate, (b) 3% dose difference and 2-mm distance-to-agreement, and (c) 10% threshold dose. Conditions (a)-(c) were the principal components of the data by the PCA method and were mapped in a similar distance range, which was easily clustered from other gamma index analytic factors by the MDS method. Conditions (a)-(c) were the universally essential factors for the PSQA in Japan.

CONCLUSION

We found that the majority of facilities using IMRT in each region of Japan complied with the guideline and conducted PSQA with deliberation under the individual facility-specific conditions.

Geochemical Characteristics and Environmental Implications of Surface Sediments from Different Types of Sand Dunes in the Dinggye Area, Southern Tibet

Geochemical characteristics of aeolian sand are beneficial for understanding sand dune formation and evolution. Few studies in the Dinggye area, Southern Tibet, have focused on the geochemical characteristics of aeolian sand. Thus, we present new geochemical data that provide insights into the geochemical characteristics and environmental implications of aeolian sands in the Dinggye area. The results show that mobile dunes, climbing sand sheets, and nebkhas show heterogeneity in elemental concentrations and UCC-normalized distribution; MgO, TiO₂, Ni, Pb, and Nb are higher in mobile dunes; SiO₂, CaO, K₂O, Na₂O, P₂O₅, V, Cr, Co, Cu, Ba, and Ce are higher in climbing sand sheets; and Al₂O₃, Fe₂O₃, La, Zn, As, Sr, Y, Zr, Rb, and Ga are higher in nebkhas. Principal component analysis (PCA) and correlation analysis indicate that the main factor affecting elemental content is grain size sorting, followed by provenance, while chemical weathering and regional precipitation are less influential. The CIA and A-CN-K triangle indicate that the different dune types are at a lower chemical weathering stage, with plagioclase weathering and decomposition first. The combination of grain size characteristics, elemental ratios, multidimensional scale (MDS), PCA, and geomorphological conditions suggest that the flood plain and the lakeshore are the main sand sources of aeolian sands in the Dinggye area.

Stability and change in the organisation of collective memory representations

In this study, we investigated the impact of a highly consequential public event, the July 15 Coup Attempt, on the structure and organisation of events in Turkish collective memory. To do this, we followed up on our earlier work (Mutlutürk, Tekcan, & Boduroglu, 2021) that used the multidimensional scaling approach to identify critical dimensions in public event representational space. Participants rated the similarity of 15 key public events in a pairwise fashion, across three waves of data collection. They were also asked to report for which political party they had voted in the most recent election. We replicated our earlier results that public events were distinguished based on their political and nonpolitical characteristics; political events were clustered based on their specific attributes. Despite substantial stability in the organisation of collective memories across three time points, the post-coup representational space among voters of the ruling party changed, eliminating clusters within the political dimension and resulting in the ruling party achieving a central and anchor status. These findings suggest that, transformative events may have the potential to impact the structure and organisation of collective memory representations and sociopolitical identity may have to do with the stability of collective memories.

Measuring the Refined Theory of Individual Values in 49 Cultural Groups: Psychometrics of the Revised Portrait Value Questionnaire

Researchers around the world are applying the recently revised Portrait Value Questionnaire (PVQ-RR) to measure the 19 values in Schwartz's refined values theory. We assessed the internal reliability, circular structure, measurement model, and measurement invariance of values measured by this questionnaire across 49 cultural groups (N = 53,472) and 32 language versions. The PVQ-RR reliably measured 15 of the 19 values in the vast majority of groups and two others in most groups. The fit of the theory-based measurement models supported the differentiation of almost all values in every cultural group. Almost all values were measured invariantly across groups at the configural and metric level. A multidimensional scaling analysis revealed that the PVQ-RR perfectly reproduced the theorized order of the 19 values around the circle across groups. The current study established the PVQ-RR as a sound instrument to measure and to compare the hierarchies and correlates of values across cultures.

Animals in multidimensional space: Interpreting coordinates throughout lexical-semantic features in mild cognitive impairment and control subjects

INTRODUCTION

Semantic verbal fluency is a useful neuropsychological tool since it involves language and executive abilities that can be impaired in patients with neurodegenerative diseases in comparison to healthy controls. The present study explores retrieve and executive control processes using traditional quantitative and qualitative raw scores and examines the utility of multidimensional scaling combined with linear regression to provide new insights about the underlying semantic network in mild cognitive impairment and in healthy older adults.

METHOD

A total of 165 Spanish older adults, 81 patients and 84 controls, were assessed in different cognitive domains and evoked animal names in one minute. Group differences on fluency raw scores were first explored. Regressions using tests to predict groups' fluency scores were also performed. The 12 animals that had been produced more frequently were selected to perform a multidimensional scaling analysis for each group. Four features related to animal names were extracted from normative studies and then were used as predictors in linear regression to provide an interpretation of the resulting dimensions' coordinates.

RESULTS

Patients performed worse on memory and naming and produced a shorter list of animals than controls. In controls, naming and visual memory explained a small part of variance related to the total of animals produced and to the number of switches. Both groups exhibited similar semantic maps.

CONCLUSIONS

Results suggest that patients' map is influenced by words with a dense associative neighborhood that were acquired at an early age, whereas in controls none of the predictors explained dimensions.

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Similarity judgments are commonly used to study mental representations and their neural correlates. This approach has been used to characterize perceptual spaces in many domains: colors, objects, images, words, and sounds. Ideally, one might want to compare estimates of perceived similarity between all pairs of stimuli, but this is often impractical. For example, if one asks a subject to compare the similarity of two items with the similarity of two other items, the number of comparisons grows with the fourth power of the stimulus set size. An alternative strategy is to ask a subject to rate similarities of isolated pairs, e.g., on a Likert scale. This is much more efficient (the number of ratings grows quadratically with set size rather than quartically), but these ratings tend to be unstable and have limited resolution, and the approach also assumes that there are no context effects. Here, a novel ranking paradigm for efficient collection of similarity judgments is presented, along with an analysis pipeline (software provided) that tests whether Euclidean distance models account for the data. Typical trials consist of eight stimuli around a central reference stimulus: the subject ranks stimuli in order of their similarity to the reference. By judicious selection of combinations of stimuli used in each trial, the approach has internal controls for consistency and context effects. The approach was validated for stimuli drawn from Euclidean spaces of up to five dimensions. The approach is illustrated with an experiment measuring similarities among 37 words. Each trial yields the results of 28 pairwise comparisons of the form, "Was A more similar to the reference than B was to the reference?" While directly comparing all pairs of pairs of stimuli would have required 221445 trials, this design enables reconstruction of the perceptual space from 5994 such comparisons obtained from 222 trials.

Robust analysis of phylogenetic tree space

Phylogenetic analyses often produce large numbers of trees. Mapping trees' distribution in 'tree space' can illuminate the behaviour and performance of search strategies, reveal distinct clusters of optimal trees, and expose differences between different data sources or phylogenetic methods - but the high-dimensional spaces defined by metric distances are necessarily distorted when represented in fewer dimensions. Here, I explore the consequences of this transformation in phylogenetic search results from 128 morphological datasets, using stratigraphic congruence - a complementary aspect of tree similarity - to evaluate the utility of low-dimensional mappings. I find that phylogenetic similarities between cladograms are most accurately depicted in tree spaces derived from information-theoretic tree distances or the quartet distance. Robinson-Foulds tree spaces exhibit prominent distortions and often fail to group trees according to phylogenetic similarity, whereas the strong influence of tree shape on the Kendall-Colijn distance makes its tree space unsuitable for many purposes. Distances mapped into two or even three dimensions often display little correspondence with true distances, which can lead to profound misrepresentation of clustering structure. Without explicit testing, one cannot be confident that a tree space mapping faithfully represents the true distribution of trees, nor that visually evident structure is valid. My recommendations for tree space validation and visualization are implemented in a new graphical user interface in the 'TreeDist' R package.

ProcData: An R Package for Process Data Analysis

Process data refer to data recorded in log files of computer-based items. These data, represented as timestamped action sequences, keep track of respondents' response problem-solving behaviors. Process data analysis aims at enhancing educational assessment accuracy and serving other assessment purposes by utilizing the rich information contained in response processes. The R package ProcData presented in this article is designed to provide tools for inspecting, processing, and analyzing process data. We define an S3 class 'proc' for organizing process data and extend generic methods summary and print for 'proc'. Feature extraction methods for process data are implemented in the package for compressing information in the irregular response processes into regular numeric vectors. ProcData also provides functions for making predictions from neural-network-based sequence models. In addition, a real dataset of response processes from the climate control item in the 2012 Programme for International Student Assessment is included in the package.

Fractional-Order Sensing and Control: Embedding the Nonlinear Dynamics of Robot Manipulators into the Multidimensional Scaling Method

This paper studies the use of multidimensional scaling (MDS) to assess the performance of fractional-order variable structure controllers (VSCs). The test bed consisted of a revolute planar robotic manipulator. The fractional derivatives required by the VSC can be obtained either by adopting numerical real-time signal processing or by using adequate sensors exhibiting fractional dynamics. Integer (fractional) VCS and fractional (integer) sliding mode combinations with different design parameters were tested. Two performance indices based in the time and frequency domains were adopted to compare the system states. The MDS generated the loci of objects corresponding to the tested cases, and the patterns were interpreted as signatures of the system behavior. Numerical experiments illustrated the feasibility and effectiveness of the approach for assessing and visualizing VSC systems.

A map of desire: multidimensional scaling of men's sexual interest in male and female children and adults

BACKGROUND

Men sexually interested in children of a specific combination of maturity and sex tend to show some lesser interest in other categories of persons. Patterns of men's sexual interest across erotic targets' categories of maturity and sex have both clinical and basic scientific implications.

METHOD

We examined the structure of men's sexual interest in adult, pubescent, and prepubescent males and females using multidimensional scaling (MDS) across four datasets, using three large samples and three indicators of sexual interest: phallometric response to erotic stimuli, sexual offense history, and self-reported sexual attraction. The samples were highly enriched for men sexually interested in children and men accused of sexual offenses.

RESULTS

Results supported a two-dimensional MDS solution, with one dimension representing erotic targets' biological sex and the other dimension representing their sexual maturity. The dimension of sexual maturity placed adults and prepubescent children on opposite ends, and pubescent children intermediate. Differences between men's sexual interest in adults and prepubescent children of the same sex were similar in magnitude to the differences between their sexual interest in adult men and women. Sexual interest in adult men was no more associated with sexual interest in boys than sexual interest in adult women was associated with sexual interest in girls.

CONCLUSIONS

Erotic targets' sexual maturity and biological sex play important roles in men's preferences, which are predictive of sexual offending. The magnitude of men's preferences for prepubescent children v. adults of their preferred sex is large.

Identification of Enhancers and Promoters in the Genome by Multidimensional Scaling

The positions of enhancers and promoters on genomic DNA remain poorly understood. Chromosomes cannot be observed during the cell division cycle because the genome forms a chromatin structure and spreads within the nucleus. However, high-throughput chromosome conformation capture (Hi-C) measures the physical interactions of genomes. In previous studies, DNA extrusion loops were directly derived from Hi-C heat maps. Multidimensional Scaling (MDS) is used in this assessment to more precisely locate enhancers and promoters. MDS is a multivariate analysis method that reproduces the original coordinates from the distance matrix between elements. We used Hi-C data of cultured osteosarcoma cells and applied MDS as the distance matrix of the genome. In addition, we selected columns 2 and 3 of the orthogonal matrix U as the desired structure. Overall, the DNA loops from the reconstructed genome structure contained bioprocesses involved in transcription, such as the pre-transcriptional initiation complex and RNA polymerase II initiation complex, and transcription factors involved in cancer, such as Foxm1 and CREB3. Therefore, our results are consistent with the biological findings. Our method is suitable for identifying enhancers and promoters in the genome.

Object Positioning Algorithm Based on Multidimensional Scaling and Optimization for Synthetic Gesture Data Generation

This work studies the feasibility of a novel two-step algorithm for infrastructure and object positioning, using pairwise distances. The proposal is based on the optimization algorithms, Scaling-by-Majorizing-a-Complicated-Function and the Limited-Memory-Broyden-Fletcher-Goldfarb-Shannon. A qualitative evaluation of these algorithms is performed for 3D positioning. As the final stage, smoothing filtering techniques are applied to estimate the trajectory, from the previously obtained positions. This approach can also be used as a synthetic gesture data generator framework. This framework is independent from the hardware and can be used to simulate the estimation of trajectories from noisy distances gathered with a large range of sensors by modifying the noise properties of the initial distances. The framework is validated, using a system of ultrasound transceivers. The results show this framework to be an efficient and simple positioning and filtering approach, accurately reconstructing the real path followed by the mobile object while maintaining low latency. Furthermore, these capabilities can be exploited by using the proposed algorithms for synthetic data generation, as demonstrated in this work, where synthetic ultrasound gesture data are generated.

A Study on Consumers' Visual Image Evaluation of Wrist Wearables

This study aimed to investigate consumers’ visual image evaluation of wrist wearables based on Kansei engineering. A total of 8 representative samples were screened from 99 samples using the multidimensional scaling (MDS) method. Five groups of adjectives were identified to allow participants to express their visual impressions of wrist wearable devices through a questionnaire survey and factor analysis. The evaluation of eight samples using the five groups of adjectives was analyzed utilizing the triangle fuzzy theory. The results showed a relatively different evaluation of the eight samples in the groups of “fashionable and individual” and “rational and decent”, but little distinction in the groups of “practical and durable”, “modern and smart” and “convenient and multiple”. Furthermore, wrist wearables with a shape close to a traditional watch dial (round), with a bezel and mechanical buttons (moderate complexity) and asymmetric forms received a higher evaluation. The acceptance of square- and elliptical-shaped wrist wearables was relatively low. Among the square- and rectangular-shaped wrist wearables, the greater the curvature of the chamfer, the higher the acceptance. Apparent contrast between the color of the screen and the casing had good acceptance. The influence of display size on consumer evaluations was relatively small. Similar results were obtained in the evaluation of preferences and willingness to purchase. The results of this study objectively and effectively reflect consumers’ evaluation and potential demand for the visual images of wrist wearables and provide a reference for designers and industry professionals.

Investigating the Use of Telemedicine for Digitally Mediated Delegation in Team-Based Primary Care: Mixed Methods Study

Background

Owing to the shortage of medical professionals, as well as demographic and structural challenges, new care models have emerged to find innovative solutions to counter medical undersupply. Team-based primary care using medical delegation appears to be a promising approach to address these challenges; however, it demands efficient communication structures and mechanisms to reinsure patients and caregivers receive a delegated, treatment-related task. Digital health care technologies hold the potential to render these novel processes effective and demand driven.

Objective

The goal of this study is to recreate the daily work routines of general practitioners (GPs) and medical assistants (MAs) to explore promising approaches for the digital moderation of delegation processes and to deepen the understanding of subjective and perceptual factors that influence their technology assessment and use.

Methods

We conducted a combination of 19 individual and group interviews with 12 GPs and 14 MAs, seeking to identify relevant technologies for delegation purposes as well as stakeholders’ perceptions of their effectiveness. Furthermore, a web-based survey was conducted asking the interviewees to order identified technologies based on their assessed applicability in multi-actor patient care. Interview data were analyzed using a three-fold inductive coding procedure. Multidimensional scaling was applied to analyze and visualize the survey data, leading to a triangulation of the results.

Results

Our results suggest that digital mediation of delegation underlies complex, reciprocal processes and biases that need to be identified and analyzed to improve the development and distribution of innovative technologies and to improve our understanding of technology use in team-based primary care. Nevertheless, medical delegation enhanced by digital technologies, such as video consultations, portable electrocardiograms, or telemedical stethoscopes, can counteract current challenges in primary care because of its unique ability to ensure both personal, patient-centered care for patients and create efficient and needs-based treatment processes.

Conclusions

Technology-mediated delegation appears to be a promising approach to implement innovative, case-sensitive, and cost-effective ways to treat patients within the paradigm of primary care. The relevance of such innovative approaches increases with the tremendous need for differentiated and effective care, such as during the ongoing COVID-19 pandemic. For the successful and sustainable adoption of innovative technologies, MAs represent essential team members. In their role as mediators between GPs and patients, MAs are potentially able to counteract patients’ resistance toward using innovative technology and compensate for patients’ limited access to technology and care facilities.

On the Behaviour of K-Means Clustering of a Dissimilarity Matrix by Means of Full Multidimensional Scaling

In this article, we analyse the usefulness of multidimensional scaling in relation to performing K-means clustering on a dissimilarity matrix, when the dimensionality of the objects is unknown. In this situation, traditional algorithms cannot be used, and so K-means clustering procedures are being performed directly on the basis of the observed dissimilarity matrix. Furthermore, the application of criteria originally formulated for two-mode data sets to determine the number of clusters depends on their possible reformulation in a one-mode situation. The linear invariance property in K-means clustering for squared dissimilarities, together with the use of multidimensional scaling, is investigated to determine the cluster membership of the observations and to address the problem of selecting the number of clusters in K-means for a dissimilarity matrix. In particular, we analyse the performance of K-means clustering on the full dimensional scaling configuration and on the equivalently partitioned configuration related to a suitable translation of the squared dissimilarities. A Monte Carlo experiment is conducted in which the methodology examined is compared with the results obtained by procedures directly applicable to a dissimilarity matrix.

The Unfolding Method to Explore Health-Related Quality of Life Constructs in a Chinese General Population

OBJECTIVES

Health-related quality of life (HRQOL) is a complicated concept that can be measured using multiple health items. Although HRQOL is closely associated with people's subjective assessment of their own health, a limited number of studies have investigated which health items are considered most important and relevant by the general population. Even fewer empirical studies have investigated how HRQOL is understood in non-Western populations. This study used multidimensional unfolding analysis in a Chinese general population to explore the constructs of HRQOL.

METHODS

A scoping review of Chinese generic HRQOL measures and a series of qualitative interviews produced a list of 42 potentially important health items in a Chinese cultural setting; 110 Chinese participants in face-to-face interviews ranked the health items from most important to least important. Responses were coded into a rectangular 110 × 42 matrix, and multidimensional unfolding was conducted to analyze participants' preferences for health items.

RESULTS

It was found that demographic characteristics and one's health condition affected views of HRQOL. Meanwhile, 3 health items were considered to be most important across the whole sample: sleep quality, body constitution, and spiritual appearance.

CONCLUSION

This study used a novel approach to explore how people coming from a Chinese cultural setting may perceive HRQOL and which aspects of HRQOL are most important to them. The study shows that multidimensional unfolding is a feasible approach to assess preferences in a general population. Future studies using this approach are recommended to further explore the constructs of HRQOL in other general populations.

The Scientific Impact Derived From the Disciplinary Profiles

The disciplinary profiles of the mean citation rates across 22 research areas were analyzed for 107 countries/territories that published at least 3,000 papers that exceeded the entrance thresholds for the Essential Science Indicators (ESI; Clarivate Analytics) during the period from January 1, 2009 to December 31, 2019. The matrix of pairwise differences between any two profiles was analyzed with a non-metric multidimensional scaling (MDS) algorithm, which recovered a two-dimensional geometric space describing these differences. These two dimensions, Dim1 and Dim2, described 5,671 pairwise differences between countries' disciplinary profiles with a sufficient accuracy (stress = 0.098). A significant correlation (r = 0.81, N = 107, p < 0.0001) was found between Dim1 and the Indicator of a Nation's Scientific Impact (INSI), which was computed as a composite of the average and the top citation rates. The scientific impact ranking of countries derived from the pairwise differences between disciplinary profiles seems to be more accurate and realistic compared with more traditional citation indices.

Assessing Various Control Samples for Microarray Gene Expression Profiling of Laryngeal Squamous Cell Carcinoma

Selection of optimal control samples is crucial in expression profiling tumor samples. To address this issue, we performed microarray expression profiling of control samples routinely used in head and neck squamous cell carcinoma studies: human bronchial and tracheal epithelial cells, squamous cells obtained by laser uvulopalatoplasty and tumor surgical margins. We compared the results using multidimensional scaling and hierarchical clustering versus tumor samples and laryngeal squamous cell carcinoma cell lines. A general observation from our study is that the analyzed cohorts separated according to two dominant factors: “malignancy”, which separated controls from malignant samples and “cell culture-microenvironment” which reflected the differences between cultured and non-cultured samples. In conclusion, we advocate the use of cultured epithelial cells as controls for gene expression profiling of cancer cell lines. In contrast, comparisons of gene expression profiles of cancer cell lines versus surgical margin controls should be treated with caution, whereas fresh frozen surgical margins seem to be appropriate for gene expression profiling of tumor samples.

Cooperative Localization Using Distance Measurements for Mobile Nodes

This paper considers the two-dimensional (2D) anchorless localization problem for sensor networks in global positioning system (GPS)-denied environments. We present an efficient method, based on the multidimensional scaling (MDS) algorithm, in order to estimate the positions of the nodes in the network using measurements of the inter-node distances. The proposed method takes advantage of the mobility of the nodes to address the location ambiguity problem, i.e., rotation and flip ambiguity, which arises in the anchorless MDS algorithm. Knowledge of the displacement of the moving node is used to produce an analytical solution for the noise-free case. Subsequently, a least squares estimator is presented for the noisy scenario and the associated closed-form solution derived. The simulations show that the proposed algorithm accurately and efficiently estimates the locations of nodes, outperforming alternative methods.

Color Space Geometry Uncovered with Magnetoencephalography

The geometry that describes the relationship among colors, and the neural mechanisms that support color vision, are unsettled. Here, we use multivariate analyses of measurements of brain activity obtained with magnetoencephalography to reverse-engineer a geometry of the neural representation of color space. The analyses depend upon determining similarity relationships among the spatial patterns of neural responses to different colors and assessing how these relationships change in time. We evaluate the approach by relating the results to universal patterns in color naming. Two prominent patterns of color naming could be accounted for by the decoding results: the greater precision in naming warm colors compared to cool colors evident by an interaction of hue and lightness, and the preeminence among colors of reddish hues. Additional experiments showed that classifiers trained on responses to color words could decode color from data obtained using colored stimuli, but only at relatively long delays after stimulus onset. These results provide evidence that perceptual representations can give rise to semantic representations, but not the reverse. Taken together, the results uncover a dynamic geometry that provides neural correlates for color appearance and generates new hypotheses about the structure of color space.

Indicating Care Process Quality: A Multidimensional Scaling Analysis

BACKGROUND AND PURPOSE

Resident assessments are analyzed by multidimensional scaling.

METHODS

We analyzed observer-based real care and support time in four facilities with 209 residents during two working days; resident, organizational data and pairs of residents were assessed by registered and assistant nurses regarding the dissimilarity of resident pairs. Registered- and assistant nurses dissimilarity assessments are compared to criteriabased nursing management assessment.

RESULTS

The fits of management criteria matrices as external restrictions are higher in registered nurses' than in assistant nurses' assessments. These differences disappear with low staffing.

CONCLUSION

The influence of qualification levels on assessment is affected by staffing. Low complexity of Assistant Nurses assessments is connected to higher nursing care and support time in groups of demanding residents.

Similarity as a Window on the Dimensions of Object Representation

Hebart et al. recently analysed 1.5 million human similarity judgments and found that natural objects are described by a small set of interpretable dimensions. Such large-scale analyses offer new opportunities to characterise how people represent their knowledge, but also challenges, including scaling to even larger data sets and integrating accounts of semantic representation.

Fractal and Entropy Analysis of the Dow Jones Index Using Multidimensional Scaling

Financial time series have a fractal nature that poses challenges for their dynamical characterization. The Dow Jones Industrial Average (DJIA) is one of the most influential financial indices, and due to its importance, it is adopted as a test bed for this study. The paper explores an alternative strategy to the standard time analysis, by joining the multidimensional scaling (MDS) computational tool and the concepts of distance, entropy, fractal dimension, and fractional calculus. First, several distances are considered to measure the similarities between objects under study and to yield proper input information to the MDS. Then, the MDS constructs a representation based on the similarity of the objects, where time can be viewed as a parametric variable. The resulting plots show a complex structure that is further analyzed with the Shannon entropy and fractal dimension. In a final step, a deeper and more detailed assessment is achieved by associating the concepts of fractional calculus and entropy. Indeed, the fractional-order entropy highlights the results obtained by the other tools, namely that the DJIA fractal nature is visible at different time scales with a fractional order memory that permeates the time series.

Multivariate Statistical Analysis and Odor-Taste Network To Reveal Odor-Taste Associations

Odor-taste association has been successfully applied to enhance taste perception in foods with low sugar or low salt content. Nevertheless, selecting odor descriptors with a given associated taste remains a challenge. In the aim to look for odors able to enhance some specific taste, we tested different multivariate analyses to find links between taste descriptors and odor descriptors, starting from a set of data previously obtained using gas chromatography/olfactometry-associated taste: 68 odorant zones described with 41 odor descriptors and 4 taste-associated descriptors (sweetness, saltiness, bitterness, and sourness). A partial least square analysis allowed for identification of odors associated with a specific taste. For instance, odors described as either fruity, sweet, strawberry, candy, floral, or orange are associated with sweetness, while odors described as either toasted, potato, sulfur, or mushroom are associated with saltiness. A network representation allowed for visualization of the links between odor and taste descriptors. As an example, a positive association was found between butter odor and both saltiness and sweetness. Our approach provided a visualization tool of the links between odor and taste description and could be used to select odor-active molecules with a potential taste enhancement effect based on their odor descriptors.

The Action System Model: A Typology of Spanish Homicides

The Action System model offers a scientific foundation to the differentiation and classification of crimes, based on behavioral indicators, allowing the establishment of relationships between the actions carried out by the offender on the crime scene and their characteristics. Although it was originally developed for application to fires, its utility has been tested in distinct criminal typologies, with few studies having considered homicides. The objective of this study was to examine the effectiveness and validity of the Action System model to differentiate thematically between the structure of the homicides and to create a typology of simple homicides in Spain, based on the relationships between the modus operandi, characteristics of the victims and characteristics of the offenders. The sample consisted of 448 homicides. Four homicide typologies were identified: Expressive, Adaptive, Integrative and Conservative, which represent 87.5% of the studied cases. Expressive homicides are impulsive, with offenders having criminal records and previously knowing their victims. Adaptive homicides are linked to robberies and sexual aggressions, in which the victim and offender are strangers. Integrative homicides take place in the family environment, specifically female offenders and femicides. Conservative homicides are very well planned, highlighting the presence of post mortem actions. The findings of this work suggest that the Action System model is a useful theoretical framework for the identification of variations in criminal behavior and understanding of the psychological processes underlying the homicides. These results have practical implications in the academic setting, since they offer a global perspective as to how simple homicides in Spain may be differentiated, also within the framework of criminal profiling, specifically, suspect prioritization.

The Barts Explanatory Model Inventory for Dementia: An item reduction approach based on responses from South Asian communities

BACKGROUND

Cultural differences in how the symptoms, causes, consequences, and treatments of dementia are understood and interpreted by South Asian people are a commonly expressed reason for late- or nonuse of mental health and care services. However, systematic collection of information on South Asian perceptions of dementia is hindered by a lack of appropriate instrumentation.

OBJECTIVES

To produce a shortened version of the Barts Explanatory Model Inventory for Dementia (BEMI-D) schedule.

METHODS

A two stage item reduction approach was employed first using multidimensional scaling categorizing items as core, intermediate, or outlier. Then, item review was undertaken using three criteria: literature importance, clinical face validity, and sub-group prevalence. The analysis followed a nonmetric multidimensional scaling method based on a two-way proximity matrix.

RESULTS

The original BEMI-D had 197 items allocated to four checklists: symptoms, causes, consequences, and treatments. The two stage item reduction approach resulted in the removal of 75 items. These reductions were achieved across all four checklists in relatively equal proportions. There was no evidence of substantive content loss in the revised schedule. The reduced version of the schedule comprises 122 items.

CONCLUSIONS

A condensed version of the BEMI-D is more efficient as an assessment schedule that captures the culturally diverse perceptions of memory problems for South Asians offering a balanced trade-off between feasibility of use and content validity.

Combining Associations Between Emotional Intelligence, Work Motivation, and Organizational Justice With Counterproductive Work Behavior: A Profile Analysis via Multidimensional Scaling (PAMS) Approach

The need for better incorporation of the construct emotional intelligence (EI) into counterproductive work behavior (CWB) research may be achieved via a unified conceptual framework. Accordingly, the purpose of this paper is to use the Profile Analysis via Multidimensional Scaling (PAMS) approach, and a conceptual framework that unifies motivational process with antecedents and outcomes, to assess differences in EI concerning a variety of constructs: organizational justice, CWB, emotional exhaustion, job satisfaction, and intrinsic motivation. Employing established scales within a framework unifying CWB, intrinsic motivation, EI, organizational justice, and outcome constructs, two EI-based profiles displayed associations with CWB based on responses from 3,293 employees. Both the first core profile, high overall justice and low emotional intelligence, and the second core profile, high emotional intelligence and low work motivation, displayed associations with interpersonal deviance and organizational deviance, as well as emotional exhaustion and job satisfaction. The results are discussed with respect to possible underlying theory and an overarching unified motivation framework that incorporates goal choice, intrinsic motivation, antecedents, and outcomes. We also provide directions for future research and implications for managers in the workplace based on heuristic conceptual frameworks that combine multiple motivational perspectives into a unified model.

Latent Feature Extraction for Process Data via Multidimensional Scaling

Computer-based interactive items have become prevalent in recent educational assessments. In such items, detailed human-computer interactive process, known as response process, is recorded in a log file. The recorded response processes provide great opportunities to understand individuals' problem solving processes. However, difficulties exist in analyzing these data as they are high-dimensional sequences in a nonstandard format. This paper aims at extracting useful information from response processes. In particular, we consider an exploratory analysis that extracts latent variables from process data through a multidimensional scaling framework. A dissimilarity measure is described to quantify the discrepancy between two response processes. The proposed method is applied to both simulated data and real process data from 14 PSTRE items in PIAAC 2012. A prediction procedure is used to examine the information contained in the extracted latent variables. We find that the extracted latent variables preserve a substantial amount of information in the process and have reasonable interpretability. We also empirically prove that process data contains more information than classic binary item responses in terms of out-of-sample prediction of many variables.

Characterizing Y-STRs in the Evaluation of Population Differentiation Using the Mean of Allele Frequency Difference between Populations

Y-chromosomal short tandem repeats (Y-STRs) are widely used in human research for the evaluation of population substructure or population differentiation. Previous studies show that several haplotype sets can be used for the evaluation of population differentiation. However, little is known about whether each Y-STR in these sets performs well during this procedure. In this study, a total of 20,927 haplotypes of a Yfiler Plus set were collected from 41 global populations. Different configurations were observed in multidimensional scaling (MDS) plots based on pairwise genetic distances evaluated using a Yfiler set and a Yfiler Plus set, respectively. Subsequently, 23 single-copy Y-STRs were characterized in the evaluation of population differentiation using the mean of allele frequency difference (mAFD) between populations. Our results indicated that DYS392 had the largest mAFD value (0.3802) and YGATAH4 had the smallest value (0.1845). On the whole, larger pairwise genetic distances could be obtained using the set with the top fifteen markers from these 23 single-copy Y-STRs, and clear clustering or separation of populations could be observed in the MDS plot in comparison with those using the set with the minimum fifteen markers. In conclusion, the mAFD value is reliable to characterize Y-STRs for efficiency in the evaluation of population differentiation.

Multidimensional Timbre Spaces of Cochlear Implant Vocoded and Non-vocoded Synthetic Female Singing Voices

Many post-lingually deafened cochlear implant (CI) users report that they no longer enjoy listening to music, which could possibly contribute to a perceived reduction in quality of life. One aspect of music perception, vocal timbre perception, may be difficult for CI users because they may not be able to use the same timbral cues available to normal hearing listeners. Vocal tract resonance frequencies have been shown to provide perceptual cues to voice categories such as baritone, tenor, mezzo-soprano, and soprano, while changes in glottal source spectral slope are believed to be related to perception of vocal quality dimensions such as fluty vs. brassy. As a first step toward understanding vocal timbre perception in CI users, we employed an 8-channel noise-band vocoder to test how vocoding can alter the timbral perception of female synthetic sung vowels across pitches. Non-vocoded and vocoded stimuli were synthesized with vibrato using 3 excitation source spectral slopes and 3 vocal tract transfer functions (mezzo-soprano, intermediate, soprano) at the pitches C4, B4, and F5. Six multi-dimensional scaling experiments were conducted: C4 not vocoded, C4 vocoded, B4 not vocoded, B4 vocoded, F5 not vocoded, and F5 vocoded. At the pitch C4, for both non-vocoded and vocoded conditions, dimension 1 grouped stimuli according to voice category and was most strongly predicted by spectral centroid from 0 to 2 kHz. While dimension 2 grouped stimuli according to excitation source spectral slope, it was organized slightly differently and predicted by different acoustic parameters in the non-vocoded and vocoded conditions. For pitches B4 and F5 spectral centroid from 0 to 2 kHz most strongly predicted dimension 1. However, while dimension 1 separated all 3 voice categories in the vocoded condition, dimension 1 only separated the soprano stimuli from the intermediate and mezzo-soprano stimuli in the non-vocoded condition. While it is unclear how these results predict timbre perception in CI listeners, in general, these results suggest that perhaps some aspects of vocal timbre may remain.

Evaluating the implementation and use of the regional cancer plan in Western Sweden through concept mapping

QUALITY PROBLEM OR ISSUE

Within healthcare, policy documents are often used to strategically standardize, streamline or change how general health issues are managed for a specific patient group or treatment. Despite significant effort in developing policy and strategic planning documents, these may not have the intended impact and their value has long been questioned by practitioners.

CHOICE OF SOLUTION

To identify barriers and affordances for the implementation and use of a strategic plan for cancer care in the Western Sweden Healthcare Region, we used Concept Mapping; a participatory mixed method approach to inquiry consisting of both qualitative and quantitative tasks intended to elicit and integrate the diverse perspectives of multiple stakeholders.

IMPLEMENTATION

The study was carried out between April and October 2017 and consisted of several sequential data collection steps: idea generation, sorting and rating ideas for importance and feasibility. Stakeholders from different levels and professions in cancercare participated, but the number varied in the separate steps of data collection: idea generation (n = 112), sorting (n = 16) and rating (n = 38).

EVALUATION

A concept map visualized seven areas that stakeholders throughout the cancer-care process considered necessary to address in order to enable the implementation of the plan. Skills provision was considered the most important cluster but also rated as least feasible. A consistent theme emerged that information, or lack thereof, might be a barrier for the plan being put into action to a greater extent in the cancer-care units. Nine actionable ideas rated highly on both importance and feasibility were presented as a go-zone.

LESSONS LEARNED

Our results suggest that efforts might be better spent on ensuring information about and accessibility to strategic documents throughout the organization, rather than frequently updating them or producing new ones. Having sufficient skills provision seems to be the prerequisite for successful implementation.

Time frame, problem specificity, and framing: the implicit structures of questions about memory in older adults

Objective: Self-reported memory complaints in older adults are common and may be an early indicator of future cognitive decline or dementia. However, there is wide variety in self-reported memory items that lack consensus on what they intend to measure. This study explored the perspectives of older adults on items currently used to assess self-reported memory.Method: A convenience sample of community dwelling older adults (n = 51) completed a free card sorting task of 16 commonly used items assessing self-reports of memory problems. Multidimensional scaling (MDS) was used to extract dimensions that describe the similarities among the self-reported items. Visual maps were created to interpret the content of each dimension and validity of the dimensions was checked using the labels provided by the participants.Results: Three underlying dimensions describing the items were identified: time frame, problem specificity, and framing. These dimensions were supported by participant provided labels.Conclusion: The three identified dimensions suggest that the commonly used self-reported memory items assess substantively different aspects of the same broad concept. To avoid inconsistencies in assessing self-reported memory problems in older adults, we recommend researchers specify the aspects of memory problems that they are interested in and link their items to those aspects. In addition, they should develop items that are a good match to their research question rather than simply selecting items that are commonly used or appear to have high face validity.

Successful Suicide Screening in the Pediatric Emergency Department: Youth, Parent, Researcher, and Clinician Perspectives

The purpose of this study was to include youth, parents, researchers, and clinicians in the identification of feasible and acceptable strategies for teen suicide screening in the pediatric emergency department (ED). Concept mapping methodology was used to elicit stakeholder responses. Regarding the most important result of suicide screening for teens in the pediatric ED, suicide prevention and education for parents, friends, and community members was rated easiest to implement, while short- and long-term follow-up and treatment was rated most important. In terms of successful suicide screening for teens in the pediatric ED, provision of resources and information was rated most feasible, and a safe, friendly, private screening environment was rated most important. The concept maps can be used to align suicide risk screening with the priorities and recommendations of pediatric ED stakeholders.

A Typology of Familicide Perpetrators in Australia

The murder of family members is one of the most difficult crimes to understand. This study uses Shye's action systems framework combined with multivariate data analysis to test the hypothesis that different forms of familicide will reflect the four states an action system can take, namely: Integrative, Expressive, Conservative and Adaptive. A multidimensional scaling analysis (MDS) was performed on 54 crime scene variables describing 104 cases of intra-familial homicide. The analysis revealed four distinct modes of functioning, which provided tentative support for Shye's action system. Each of the four modes had distinct associations with perpetrator characteristics. The Expressive and Integrative modes were associated with Cluster B personality traits, and criminal and substance use histories. The Adaptive mode was associated with trauma histories, mood disorders, and personality disorder traits. The Conservative theme was associated with trauma histories and psychotic disorders. Implications of findings for risk assessment and intervention are discussed.