Miracle-dz/UniFAR-FTUs huggingface dataset:
Do frontal dysfunctions play a role in visual hallucinations in Alzheimer's disease as in Parkinson's disease?a comparative study

Recent studies have demonstrated that nondemented patients with Parkinson's disease with visual hallucinations had lower scores on frontal-executive tasks than parkinsonian patients without hallucinations, most likely due to defective cholinergic circuitry. The aim of the present study is to investigate whether development of visual hallucinations in patients with Alzheimer's disease may also be related to more severe frontal dysfunctions. In the present study, 36 patients were included who were affected by probable Alzheimer's disease (18 with visual hallucinations and 18 without) and 38 patients affected by idiopathic Parkinson's disease (19 with visual hallucinations and 19 without). Patients completed a neuropsychological test battery and a short questionnaire to collect information about hallucination types and features. Multivariate analysis showed that patients with Alzheimer's disease scored significantly lower than patients with Parkinson's disease and that patients with hallucinations scored significantly lower than patients without hallucinations. Within both the Alzheimer's disease group and the Parkinson's disease group, patients with visual hallucinations scored significantly lower than patients without visual hallucinations, particularly on tests evaluating frontal-executive functions. These results demonstrate that patients with visual hallucinations show a significant impairment on tests tapping frontal-executive functions in Alzheimer's disease, as previously demonstrated (and verified here) in Parkinson's disease. On this basis it seems likely that analogous cognitive mechanisms underlie development of visual hallucinations in both degenerative diseases. Moreover, we may speculate that a defective circuitry of the prefrontal cortex is crucial for the genesis of hallucinations.
Segmentation of Medical Image using Clustering and Watershed Algorithms

Problem statement: Segmentation plays an important role in medical imaging. Segmentation of an image is the division or separation of the im age into dissimilar regions of similar attribute. I n this study we proposed a methodology that integrates clustering algorithm and marker controlled watershed segmentation algorithm for medical image segmentation. The use of the conservative watershed algorithm for medical image analysis is pervasive b ecause of its advantages, such as always being able to construct an entire division of the image. On the o ther hand, its disadvantages include over segmentat ion and sensitivity to false edges. Approach: In this study we proposed a methodology that integr ates K- Means clustering with marker controlled watershed segmentation algorithm and integrates Fuzzy C- Means clustering with marker controlled watershed segmentation algorithm separately for medical image segmentation. The Clustering algorithms are unsupervised learning algorithms, while the marker controlled watershed segmentation algorithm makes use of automated thresholding on the gradient magnitude map and post-segmentation merging on the initial partitions to reduce the number of false edges and over-segmentation. Results: In this study, we compared K-means clustering and marker controlled watershed algorithm with Fuzzy C-means clustering and marker controlled watershed algorithm. And also we showed that our proposed method produced segmentation maps which gave fewer partitions than the segmentation maps produced by the conservative watershed algorithm. Conclusion: Integration of K-means clustering with marker contr olled watershed algorithm gave better segmentation than integration of Fuzzy C-means clustering with marker controlled watershed algorithm. By reducing the amount of over segmentation, we obtained a segmentation map which is more diplomats of the several anatomies in the medical images.
Basal and Ischemia-Induced Transcardiac Troponin Release into the Coronary Circulation in Patients with Suspected Coronary Artery Disease

Background Cardiac troponin is a specific biomarker for cardiomyocyte necrosis in acute coronary syndromes. Troponin release from the coronary circulation remains to be determined because of the lower sensitivity of the conventional assay. We sought to determine basal and angina-induced troponin release using a highly sensitive troponin assay. Methods and Results The cardiac troponin T levels in serum sampled from the peripheral vein (PV), the aortic root (AO), and the coronary sinus (CS) were measured in 105 consecutive stable patients with coronary risk factor(s) and suspected coronary artery disease (CAD) and in 33 patients without CAD who underwent an acetylcholine provocation test. At baseline, there was a significant increase in the troponin levels from AO [9.0 (6.4, 13.1) pg/mL for median (25th, 75th percentiles)] to CS [10.3 (7.3, 15.5) pg/mL, p<0.001] in 96 (91.4%) patients and the difference was 1.1 (0.4, 2.1) pg/mL, which reflected basal transcardiac troponin release (TTR). TTR was positively correlated with PV levels (r = 0.22, p = 0.03). Male sex, left ventricular hypertrophy determined by echocardiography, T-wave inversion, and CAD correlated with elevated TTR defined as above: median, 1.1 pg/mL. A significant increase in TTR was noted in 17 patients with coronary spasms [0.6 (0.2, 1.2) pg/mL, p<0.01] but not in 16 patients without spasms [0.0 (−0.5, 0.9) pg/mL, p = 0.73] after the acetylcholine provocation. Conclusion Basal TTR in the coronary circulation was observed in most of the patients with suspected CAD and risk factor(s). This sensitive assay detected myocardial ischemia-induced increases in TTR caused by coronary spasms.
GPU & CPU cooperative accelerated pedestrian and vehicle detection

This paper presents a fast pedestrian and vehicle detection framework that integrates GPU (graphics processing unit) and CPU implementations. We employ the Histograms of Oriented Gradients (HoG) and the Feature Interaction Descriptor (FIND) as object descriptors. FIND describes the high-level properties of an object's appearance by computing pair-wise interactions of adjacent region-level features. We also employ the cascade approach in a sliding-window manner with multi-classifiers specialized for both the direction of a pedestrian and the distance of the pedestrian to a camera installed on a vehicle. Although our detection framework can detect pedestrians and vehicles in images, it wastes computational cost on calculating high-dimensional FIND features. Therefore, to realize real-time processing, we utilize the NVIDIA CUDA framework for pedestrian and vehicle detection. Three parallelization techniques implemented on both a GPU and a CPU are incorporated in our detection framework. As a result, our proposed implementation can perform detection more than 30 times faster than can a conventional implementation running on a CPU. For a 640×480 image, our parallel techniques attain a processing speed of 23.8 fps (42 [ms]) and detects both pedestrians and vehicles.
Object recognition using boosted adaptive features

Most existing pattern recognition techniques are based on using a fixed set of features, hand-crafted or learned by non supervised methods, to classify the data samples. But in natural and uncontrolled environments, sometimes it can be useful to use more adaptive classifiers. We propose a learning algorithm based on a boosting scheme where features are adapted to the classification task, resulting in an incremental learning approach. As a boosting scheme, a new classifier is trained at every step, but also a new feature extraction process is performed. The features are computed taking into account the most difficult examples to classify at each step, and are not imposed heuristically. The experimental results achieved show a significative increase in the learning speed as well as in the classification performance with respect to the classic boosting algorithm.
Complexity pursuit for unifying time series

Complexity pursuit is a recently developed algorithm using the gradient descent for separating interesting components from time series. It is an extension of projection pursuit to time series data and the method is closely related to blind separation of time-dependent source signals and independent component analysis. The goal is to find projections of time series that have interesting structure, defined using criteria related to Kolmogoroff complexity or coding length. In this paper, we derived a simple approximation of coding length that takes into account the nongaussianity, the autocorrelations and the variance nonstationary of the time series. We give a simple algorithm for its approximative optimization.
The Tripartite Type III Secreton of Shigella flexneri Inserts Ipab and Ipac into Host Membranes

Bacterial type III secretion systems serve to translocate proteins into eukaryotic cells, requiring a secreton and a translocator for proteins to pass the bacterial and host membranes. We used the contact hemolytic activity of Shigella flexneri to investigate its putative translocator. Hemolysis was caused by formation of a 25-Å pore within the red blood cell (RBC) membrane. Of the five proteins secreted by Shigella upon activation of its type III secretion system, only the hydrophobic IpaB and IpaC were tightly associated with RBC membranes isolated after hemolysis. Ipa protein secretion and hemolysis were kinetically coupled processes. However, Ipa protein secretion in the immediate vicinity of RBCs was not sufficient to cause hemolysis in the absence of centrifugation. Centrifugation reduced the distance between bacterial and RBC membranes beyond a critical threshold. Electron microscopy analysis indicated that secretons were constitutively assembled at 37°C before any host contact. They were composed of three parts: (a) an external needle, (b) a neck domain, and (c) a large proximal bulb. Secreton morphology did not change upon activation of secretion. In mutants of some genes encoding the secretion machinery the organelle was absent, whereas ipaB and ipaC mutants displayed normal secretons.
Using Instance Texts to Improve Keyword-Based Class Retrieval

In this paper we investigate the keyword based class retrieval problem, which we define as how to identify ontological classes that best match a keyword based query. Most previous applications use simple syntactic matching approaches on the class labels and/or comments, or expand the keyword query by using lexicons such as Word Net, but fail to retrieve relevant resources in many scenarios. Instead of relying on external sources, we investigate this problem by using the annotations of instances associated with classes in the knowledge base. We propose a general framework of this approach, which consists of two phases: the keyword query is first used to locate relevant instances, then we induce the classes given this list of weighted matched instances. If we identify sufficient text for the instances, then the first phase can be solved by a traditional information retrieval (IR) query, however the second phase might be cast in different ways: as an additive value function, as an IR problem with instance as queries, or as an instance-based ontology alignment problem. With many applicable strategies initiated from different viewpoints, we find that some of them are mathematically equivalent or very similar. In the experiments we compare our proposed framework to simple syntactic approaches and evaluate different strategies.
Worse-off than others? Abusive supervision’s effects in teams

Purpose The purpose of this paper is to examine how relative abusive supervision (i.e. team member’s perceived abusive supervision as compared with the team mean) influences team member’s job attitudes through the mediating role of relative leader–member exchange. This study also explores the cross-level moderating roles of team-level abusive supervision and team-level leader–member exchange (LMX) in the process. Design/methodology/approach This study used two-wave data from 1,479 employees in 145 work teams, and tested a cross-level moderated mediation model using multilevel structural equation modeling. Findings Results demonstrate that the negative indirect effects of relative abusive supervision on job satisfaction and team affective commitment through relative LMX are stronger when team-level abusive supervision is low rather than high. Originality/value Integrating LMX theory with a relative deprivation perspective, this study conceptualizes and operationalizes relative abusive supervision, develops an individual-within-group model of abusive supervision’s consequences in teams and demonstrates a cross-level moderating effect of team-level abusive supervision in buffering relative abusive supervision’s negative consequences.
A Probabilistic Approach for Concurrent Map Acquisition and Localization for Mobile Robots

Abstract : This paper addresses the problem of building large scale geometric maps of indoor environments with mobile robots. It poses the map building problem as a constrained, probabilistic maximum likelihood estimation problem. It then devises a practical algorithm for generating the most likely map from data, along with the most likely path taken by the robot. Experimental results in cyclic environments of size up to 80 by 25 meter illustrate the appropriateness of the approach.
Spi2 gene polymorphism is not associated with recurrent airway obstruction and inflammatory airway disease in thoroughbred horses

The aim was to detect the presence of polymorphisms at exons 1, 2, 3 and 4 of the Spi2 gene, and evaluate a possible association between them and recurrent airway obstruction (RAO) or inflammatory airway disease (IAD) in thoroughbred horses, through single-strand conformational-polymorphism (SSCP) screening. Although polymorphism was not detected in exons 1, 2 and 3, three alleles and six genotypes were identified in exon 4. The frequencies of allele A (0.6388) and genotype AA (0.3888) were higher in horses affected by RAO, although no association was found between polymorphism and horses with either RAO or IAD.
Kinematics and Dynamics Are Not Represented Independently in Motor Working Memory: Evidence from an Interference Study

Our capacity to learn multiple dynamic and visuomotor tasks is limited by the time between the presentations of the tasks. When subjects are required to adapt to equal and opposite position-dependent visuomotor rotations (Krakauer et al., 1999) or velocity-dependent force fields (Brashers-Krug et al., 1996) in quick succession, interference occurs that prevents the first task from being consolidated in memory. In contrast, such interference is not observed between learning a position-dependent visuomotor rotation and an acceleration-dependent force field. On the basis of this finding, it has been argued that internal models of kinematic and dynamic sensorimotor transformations are learned independently (Krakauer et al., 1999). However, these findings are also consistent with the perturbations interfering only if they depend on the same kinematic variable. We evaluated this hypothesis using kinematic and dynamic transformations matched in terms of the kinematic variable on which they depend. Subjects adapted to a position-dependent visuomotor rotation followed 5 min later by a position-dependent rotary force field either with or without visual feedback of arm position. The force field tended to rotate the hand in the direction opposite to the visuomotor rotation. To assess learning, all subjects were retested 24 hr later on the visuomotor rotation, and their performance was compared with a control group exposed only to the visuomotor rotation on both days. Adapting to the position-dependent force field, both with and without visual feedback, impaired learning of the visuomotor rotation. Thus, interference between our kinematic and dynamic transformations was observed, suggesting that the key determinant of interference is the kinematic variable on which the transformation depends.
Mobile collaboration: collaboratively reading and creating children's stories on mobile devices

This paper discusses design iterations of Mobile Stories - a mobile technology that empowers children to collaboratively read and create stories. We present the design and discuss the impact of different collocated collaborative configurations for mobile devices including: content splitting and space sharing. We share design experiences that illustrate how Mobile Stories supports collaboration and mobility, and identify how the collocated collaborative configurations are best suited for reading and sharing tasks. We also identify how creative tasks foster more mobility and dynamic interactions between collaborators.
‘Hard-to-reach’ parents: immigrant families’ participation in schools and the views of parent association leaders in Spain and the United States

ABSTRACT While research about the significance of parent participation in school is expanding, research about the role of Parent Associations (PA)/Parent and Teacher Associations (PTA) in the integration and participation of immigrant families in schools is limited. This is still the case in Spain and the U.S. despite the continued growth of the immigrant population and that of a scholarship linking parental involvement in school with the improved educational outcomes of their children. This study explores the role of PA/PTAs leaders in the school integration and participation of immigrant families, many of whom are considered ‘hard-to-reach. ’ The objectives are twofold: to contribute new insights with a description of immigrant families’ participation in PA/PTAs in two different national contexts; and to bring new insights from the views of PA/PTAs leaders about how to engage and improve the participation of ‘hard-to-reach’, immigrant families in schools. We compare results derived from in-depth, semi-structured, face-to-face interviews with PA/PTAs leaders in 26 public schools in Granada and New York City. The study yields two main findings: the importance of immigrant families’ active participation in the enrichment of schools; and the strategies used by PA/PTAs leaders in the participation and integration of parents in their children’s schools.
A context-aware light source

We present a technique that combines the visual benefits of virtual enhancement with the intuitive interaction of the real world. We accomplish this by introducing the concept of a context-aware light source. This light source provides illumination based on scene context in real-time. This allows us to project feature enhancement in-place onto an object while it is being manipulated by the user. A separate proxy light source can be employed to enable freely programmable shading responses for interactive scene analysis. We created a prototype hardware setup and have implemented several applications that demonstrate the approach, such as a sharpening light, an edge highlighting light, an accumulation light, and a light with a programmable, nonlinear shading response.
Investigation of the Rao-Blackwellized particle filter for two jump-Markov inertia measurement models

In the importance sampling step, the Rao-Blackwellized particle filter makes use of the probability density functions (pdf) of the Kalman filter for the computation of likelihood functions and sample weights. Whether these pdf are separated or overlap each other has a significant effect on the estimation of the posterior distribution of the non-marginalized states. This papers presents simulation results demonstrating the above phenomenon; the models considered are two simple jump-Markov inertia navigation measurement models. It is revealed that when the Kalman filter pdf for different jumps states are separated despite measurement noise, tracking of the jump state is more effective.
Largest Silhouette-Equivalent Volume for 3D Shapes Modeling without Ghost Object

In this paper, we investigate a practical framework to compute a 3D shape estimation of multiple objects in real-time from silhouettes in multi-view environments. A popular method called Shape From Silhouette (SFS), computes a 3D shape estimation from binary silhouette masks. This method has several limitations: The acquisition space is limited to the intersection of the camera viewing frusta ; SFS methods reconstruct some ghost objects which do not contain real objects, especially when there are multiple real objects in the scene. In this paper we propose two contributions to overcome these limitations. First, using a new formulation of SFS approach, our system reconstructs objects with no constraints on camera placement and their visibility. Second, a new theoretical approach identifies and removes ghost objects. The reconstructed shapes are more accurate than current silhouette-based approaches. Reconstructed parts are guaranteed to contain real objects. Finally, we present a real-time system that captures multiple and complex objects moving through many camera frusta to demonstrate the application and robustness of our method.
Women’s experiences of depression in rural NSW

ABSTRACT Objectives: The aim of this study was to investigate the lived experiences of women living in rural NSW with depression, their beliefs about its causes, their treatment, and ways in which they sought to recover. Method: As the basis of a qualitative study, semi-structured interviews were conducted with 27 women who identified as living with depression. Data were collected and analysed from 2011 to 2013 and were coded using thematic data analysis. Results: Women had a multiplicity of points of view on living with depression, its causes, and on the assistance and support they required. A large number of participants described adverse life experiences, including adverse childhood experiences. Many women demonstrated an internal understanding of the interconnectedness of their various adverse life experiences and their depression (loss, childhood abuse, violence). Despite most of these women also suffering from low self-worth, few attributed their self-processes either to their adverse childhood experiences or to their experience of depression. Taking a feminist perspective, this paper discusses the women’s understandings and explanations of depression, issues of adverse childhood experiences and grief and loss, and the ways in which the women sought help and support. Discussion: The flow-on effects of negative life experiences are known to be contributing factors in depression, and the women themselves identified them as causal. However, these factors appeared to be muted in diagnosis and treatment owing to the biomedical focus of Australia’s preferred depression treatment strategy.
Mining periodic-frequent patterns with maximum items' support constraints

The single minimum support (minsup) based frequent pattern mining approaches like Apriori and FP-growth suffer from "rare item problem" while extracting frequent patterns. That is, at high minsup, frequent patterns consisting of rare items will be missed, and at low minsup, number of frequent patterns explode. In the literature, efforts have been made to extract rare frequent patterns under "multiple minimum support framework". In this framework, "rare frequent patterns" can be extracted by specifying minsup of the pattern using two models: minimum constraint model and maximum constraint model. In the literature, an approach has been proposed to extract only those frequent patterns which occur periodically. The basic model of periodic-frequent patterns is based on single minsup constraint. It was observed that the periodic-frequent pattern mining approach also suffers from the "rare item problem". An effort has been made to extract rare periodic-frequent patterns using minimum constraint model. In this paper, we have proposed a pattern-growth approach to extract rare periodic-frequent patterns by specifying minsup under maximum constraint model. Experiment results show that the proposed approach is efficient.