Matrix sketching for supervised classification with imbalanced classes

The presence of imbalanced classes is more and more common in practical applications and it is known to heavily compromise the learning process. In this paper we propose a new method aimed at addressing this issue in binary supervised classification. Re-balancing the class sizes has turned out to be a fruitful strategy to overcome this problem. Our proposal performs re-balancing through matrix sketching. Matrix sketching is a recently developed data compression technique that is characterized by the property of preserving most of the linear information that is present in the data. Such property is guaranteed by the Johnson-Lindenstrauss’ Lemma (1984) and allows to embed an n-dimensional space into a reduced one without distorting, within an ϵ-size interval, the distances between any pair of points. We propose to use matrix sketching as an alternative to the standard re-balancing strategies that are based on random under-sampling the majority class or random over-sampling the minority one. We assess the properties of our method when combined with linear discriminant analysis (LDA), classification trees (C4.5) and Support Vector Machines (SVM) on simulated and real data. Results show that sketching can represent a sound alternative to the most widely used rebalancing methods

Analysis of the trueness and precision of complete denture bases manufactured using digital and analog technologies

PURPOSE. Digital technology has enabled improvements in the fitting accuracy of denture bases via milling techniques. The aim of this study was to evaluate the trueness and precision of digital and analog techniques for manufacturing complete dentures (CDs). MATERIALS AND METHODS. Sixty identical CDs were manufactured using different production protocols. Digital and analog technologies were compared using the reference geometric approach, and the Delta-error values of eight areas of interest (AOI) were calculated. For each AOI, a precise number of measurement points was selected according to sensitivity analyses to compare the Delta-error of trueness and precision between the original model and manufactured prosthesis. Three types of statistical analysis were performed: to calculate the intergroup cumulative difference among the three protocols, the intergroup among the AOIs, and the intragroup difference among AOIs. RESULTS. There was a statistically significant difference between the dentures made using the oversize process and injection molding process (P < .001), but no significant difference between the other two manufacturing methods (P = .1227). There was also a statistically significant difference between the dentures made using the monolithic process and the other two processes for all AOIs (P = .0061), but there was no significant difference between the other two processes (P = 1). Within each group, significant differences among the AOIs were observed. CONCLUSION. The monolithic process yielded better results, in terms of accuracy (trueness and precision), than the other groups, although all three processes led to dentures with Delta-error values well within the clinical tolerance limit. [J Adv Prosthodont 2023;15:22-32

Evaluation of trueness and precision of removable partial denture metal frameworks manufactured with digital technology and different materials

PURPOSE. The aim of this study is to evaluate the accuracy of removable partial denture (RPD) frameworks produced using different digital protocols. MATERIALS AND METHODS. 80 frameworks for RPDs were produced using CAD-CAM technology and divided into four groups of twenty (n = 20): Group 1, Titanium frameworks manufactured by digital metal laser sintering (DMLS); Group 2, Co-Cr frameworks manufactured by DMLS; Group 3, Polyamide PA12 castable resin manufactured by multi-jet fusion (MJF); and Group 4, Metal (Co-Cr) casting by using lost-wax technique. After the digital acquisition, eight specific areas were selected in order to measure the Δ-error value at the intaglio surface of RPD. The minimum value required for point sampling density (0.4 mm) was derived from the sensitivity analysis. The obtained Δ-error mean value was used for comparisons: 1. between different manufacturing processes; 2. between different manufacturing techniques in the same area of interest (AOI); and 3. between different AOI of the same group. RESULTS. The Δ-error mean value of each group ranged between -0.002 (Ti) and 0.041 (Co-Cr) mm. The Pearson’s Chi-squared test revealed significant differences considering all groups paired two by two, except for group 3 and 4. The multiple comparison test documented a significant difference for each AOI among group 1, 3, and 4. The multiple comparison test showed significant differences among almost all different AOIs of each group. CONCLUSION. All Δ-mean error values of all digital protocols for manufacturing RPD frameworks optimally fit within the clinical tolerance limit of trueness and precision

The effects of cerebrospinal fluid tap-test on idiopathic normal pressure hydrocephalus: an inertial sensors based assessment

BACKGROUND: Gait disturbances are typical of persons with idiopathic normal pressure hydrocephalus (iNPH) without signs distinctive from other neurodegenerative and vascular conditions. Cerebrospinal fluid tap-test (CSF-TT) is expected to improve the motor performance of iNPH patients and is a prognostic indicator in their surgical management. This observational prospective study aims to determine which spatio-temporal gait parameter(s), measured during instrumented motor tests, and clinical scale(s) may provide a relevant contribution in the evaluation of motor performance pre vs. post CSF-TT on iNPH patients with and without important vascular encephalopathy. METHODS: Seventy-six patients (20 with an associated vascular encephalopathy) were assessed before, and 24 and 72\u2009h after the CSF-TT by a timed up and go test (TUG) and an 18\u2009m walking test (18\u2009mW) instrumented using inertial sensors. Tinetti Gait, Tinetti Balance, Gait Status Scale, and Grading Scale were fulfilled before and 72\u2009h after the CSF-TT. Stride length, cadence and total time were selected as the outcome measures. Statistical models with mixed effects were implemented to determine the relevant contribution to response variables of each quantitative gait parameter and clinical scales. RESULTS AND CONCLUSION: From baseline to 72\u2009h post CSF-TT patients improved significantly by increasing cadence in 18\u2009mW and TUG (on average of 1.7 and 2.4 strides/min respectively) and stride length in 18\u2009mW (on average of 3.1\u2009cm). A significant reduction of gait apraxia was reflected by modifications in double support duration and in coordination index. Tinetti Gait, Tinetti Balance and Gait Status Scale were able to explain part of the variability of response variables not covered by instrumental data, especially in TUG. Grading Scale revealed the highest affinity with TUG total time and cadence when considering clinical scales alone. Patients with iNPH and an associated vascular encephalopathy showed worst performances compared to pure iNPH but without statistical significance. Gait improvement following CSF-TT was comparable in the two groups. Overall these results suggest that, in order to augment CSF-TT accuracy, is key to assess the gait pattern by analyzing the main spatio-temporal parameters and set post evaluation at 72\u2009h. TRIAL REGISTRATION: Approved by ethics committee: CE 14131 23/02/2015

Modelling the covariance structure in marginal multivariate count models: Hunting in Bioko Island.

The main goal of this article is to present a flexible statistical modelling framework to deal with multivariate count data along with longitudinal and repeated measures structures. The covariance structure for each response variable is defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. In order to specify the joint covariance matrix for the multivariate response vector, the generalized Kronecker product is employed. We take into account the count nature of the data by means of the power dispersion function associated with the Poisson–Tweedie distribution. Furthermore, the score information criterion is extended for selecting the components of the matrix linear predictor. We analyse a data set consisting of prey animals (the main hunted species, the blue duiker Philantomba monticola and other taxa) shot or snared for bushmeat by 52 commercial hunters over a 33-month period in Pico Basilé, Bioko Island, Equatorial Guinea. By taking into account the severely unbalanced repeated measures and longitudinal structures induced by the hunters and a set of potential covariates (which in turn affect the mean and covariance structures), our method can be used to indicate whether there was statistical evidence of a decline in blue duikers and other species hunted during the study period. Determining whether observed drops in the number of animals hunted are indeed true is crucial to assess whether species depletion effects are taking place in exploited areas anywhere in the world. We suggest that our method can be used to more accurately understand the trajectories of animals hunted for commercial or subsistence purposes and establish clear policies to ensure sustainable hunting practices

Understanding similarities and differences in land use visions for Scotland

The successful transition towards a global society that can live within planetary boundaries is one of the greatest challenges for the twenty-first century. Sustainable land use and land management will be essential to ensure the continued delivery of the ecosystem goods and services needed to support a rapidly growing global population. To support the transition towards sustainable development, decision-makers need to better understand how land use change affects people and the environment. However, these insights are of limited use without societal agreement on future land uses. Understanding synergies and differences between land use visions forms a first step in assessing and comparing alternative pathways towards a sustainable future. This thesis uses a range of methods to understand visions of future land use amongst professional land use stakeholders, society at large, and young people in Scotland. Twenty semi-structured interviews were held with policy experts from the Scottish land use sectors. A nationwide statistically representative web-based survey provided insight into the visions of the Scottish population. And finally, a novel visual interview methodology was used to interview 26 pupils from two high schools in Perthshire. Inductive content analysis and descriptive statistics were used to analyse the results and understand and compare the land use visions of these different groups. As expected, different groups had different visions of future land use. There was, however, general agreement on certain themes, in particular the desire for a more sustainable lifestyle and the importance of a healthy environment. The sectoral stakeholders would like to see more partnerships, dialogue and collaboration; a society that is more engaged and aware about land use; resilient local economies; and short-, medium-, and long-term policies that help to achieve these goals. One of the key challenges for these groups will be how to translate abstract concepts such as ‘healthy ecosystem’ and ‘dialogue and partnerships’ into practice. This clearly requires a shared understanding of what a ‘healthy ecosystem’ means to different stakeholders, as well as appreciation of what true dialogue means and how this can be used to co-create solutions – potentially a radical change from the traditional top-down approaches. The research also identified divisions in Scottish society between those who want to continue a ‘status quo’ lifestyle, and those – in particular younger people (who spent time in the natural environment, through either school or home life) and those from a higher socio-economic background – who want a more sustainable lifestyle and to be more connected with the natural environment. These results are important, as policy makers need to be able to identify the factors that have successfully engaged certain groups and to promote these factors. Programmes that provide access to the natural environment (such as the Duke of Edinburgh’s Award) need to ensure equal opportunities by targeting disadvantaged groups. Simultaneously, it needs to be explored how to encourage those who would like to continue a ‘status quo’ lifestyle into a more sustainable one. Past research has shown how preferences can be influenced and how changes can be initiated by incentives and restrictions in order to promote desired behaviours. The power of the media should be leveraged: programmes such as BBC’s ‘Blue Planet’ highlight how our lifestyle choices impact on the natural environment and can provide the motivation for change. The current issues surrounding Brexit and Climate Change require a national conversation; using methods such as those presented in the thesis to elicit land use visions can help identify the commonalties and differences between stakeholders’ views. This can provide a starting point for dialogue and critical reflection on current instruments and objectives, and how they might be adapted to better reflect Scottish preferences and conditions

Estrogen mediated-activation of miR-191/425 cluster modulates tumorigenicity of breast cancer cells depending on estrogen receptor status.

MicroRNAs (miRNAs), single-stranded non-coding RNAs, influence myriad biological processes that can contribute to cancer. Although tumor-suppressive and oncogenic functions have been characterized for some miRNAs, the majority of microRNAs have not been investigated for their ability to promote and modulate tumorigenesis. Here, we established that the miR-191/425 cluster is transcriptionally dependent on the host gene, DALRD3, and that the hormone 17β-estradiol (estrogen or E2) controls expression of both miR-191/425 and DALRD3. MiR-191/425 locus characterization revealed that the recruitment of estrogen receptor α (ERα) to the regulatory region of the miR-191/425-DALRD3 unit resulted in the accumulation of miR-191 and miR-425 and subsequent decrease in DALRD3 expression levels. We demonstrated that miR-191 protects ERα positive breast cancer cells from hormone starvation-induced apoptosis through the suppression of tumor-suppressor EGR1. Furthermore, enforced expression of the miR-191/425 cluster in aggressive breast cancer cells altered global gene expression profiles and enabled us to identify important tumor promoting genes, including SATB1, CCND2, and FSCN1, as targets of miR-191 and miR-425. Finally, in vitro and in vivo experiments demonstrated that miR-191 and miR-425 reduced proliferation, impaired tumorigenesis and metastasis, and increased expression of epithelial markers in aggressive breast cancer cells. Our data provide compelling evidence for the transcriptional regulation of the miR-191/425 cluster and for its context-specific biological determinants in breast cancers. Importantly, we demonstrated that the miR-191/425 cluster, by reducing the expression of an extensive network of genes, has a fundamental impact on cancer initiation and progression of breast cancer cells

Deep mixtures of unigrams for uncovering topics in textual data

Mixtures of unigrams are one of the simplest and most efficient tools for clustering textual data, as they assume that documents related to the same topic have similar distributions of terms, naturally described by multinomials. When the classification task is particularly challenging, such as when the document-term matrix is high-dimensional and extremely sparse, a more composite representation can provide better insight into the grouping structure. In this work, we developed a deep version of mixtures of unigrams for the unsupervised classification of very short documents with a large number of terms, by allowing for models with further deeper latent layers; the proposal is derived in a Bayesian framework. The behavior of the deep mixtures of unigrams is empirically compared with that of other traditional and state-of-the-art methods, namely k-means with cosine distance, k-means with Euclidean distance on data transformed according to semantic analysis, partition around medoids, mixture of Gaussians on semantic-based transformed data, hierarchical clustering according to Ward\u2019s method with cosine dissimilarity, latent Dirichlet allocation, mixtures of unigrams estimated via the EM algorithm, spectral clustering and affinity propagation clustering. The performance is evaluated in terms of both correct classification rate and Adjusted Rand Index. Simulation studies and real data analysis prove that going deep in clustering such data highly improves the classification accuracy

One-class classification with application to forensic analysis

The analysis of broken glass is forensically important to reconstruct the events of a criminal act. In particular, the comparison between the glass fragments found on a suspect (recovered cases) and those collected at the crime scene (control cases) may help the police to identify the offender(s) correctly. The forensic issue can be framed as a one-class classification problem. One-class classification is a recently emerging and special classification task, where only one class is fully known (the so-called target class), whereas information on the others is completely missing. We propose to consider Gini's classical transvariation probability as a measure of typicality, i.e. a measure of resemblance between an observation and a set of well-known objects (the control cases). The aim of the proposed transvariation-based one-class classifier is to identify the best boundary around the target class, i.e. to recognize as many target objects as possible while rejecting all those deviating from this class