Miracle-dz/UniFAR-FTUs huggingface dataset:
Do People With Dementia Experience Stigma? A Cross Country Comparison Between Italy, Poland and the UK

Introduction: Until now little research has been done to answer the question of whether people with dementia experience stigma and if so how they experience this. Also, no previous studies were conducted into possible differences between countries and cultures regarding the experience of stigma in dementia. Objectives: The aims of this study were to compare the experience of stigma (with social isolation, social rejection and internalised shame as components) among people with dementia (n=180) in three European countries: Italy, Poland and the United Kingdom (UK); and to investigate possible determinants in background characteristics, quality of life aspects, social support, mood and cognitive functioning. Material and Methods: A one group multinational cross-sectional design was used. Stigma was measured with the Stigma Impact Scale (SIS). Results: The results showed that people in the UK experience a higher level of stigmatisation than people in Italy and Poland. The experienced stigmatisation negatively correlated with obtained social support (DSSI; rho=-0.42, p=0.000) and quality of life aspects (QOL-AD; rho=-0.39, p=0.000). Positive correlations were found between experiencing stigma and negative mood (rho=0.28, p=0.0002). There was no significant correlation between level of cognitive functioning and stigmatisation (GDS, rho=0.02;p=0.98) although people rating their own memory lower reported a higher level of stigmatisation (QoL-AD, memory item; rho=-0.29; p=0.001). Conclusion: There is a strong need for research into the individual experience of people with dementia across Europe and the world. This could help in providing support and care services that match their experience, needs, preferences; and designing well informed awareness campaigns based on their voice.
Automatic Spoken Affect Analysis and Classification

This paper reports results from early experiments on automatic classification of spoken affect. The task was to classify short spoken sentences into one of two affect classes: approving or disapproving. Using an optimal combination of six acoustic measurements our classifier achieved an accuracy of 65% to 88% for speaker dependent, text-independent classification. The results suggest that pitch and energy measurements may be used to automatically classify spoken affect but more research will be necessary to understand individual variations and how to broaden the range of affect classes which can be recognized. In a second experiment we compared human performance in classifying the same speech samples. We found similarities between human and automatic classification results.
Statistically significant length-scale of filaments as a robust measure of galaxy distribution

We have used a statistical technique "Shuffle" (Bhavsar & Ling 1988; Bharadwaj, Bhavsar & Sheth 2004) in seven nearly two dimensional strips from the Sloan Digital Sky Survey Data Release Six (SDSS DR6) to test if the statistically significant length scale of filaments depends on luminosity, colour and morphology of galaxies. We find that although the average filamentarity depends on these galaxy properties, the statistically significant length scale of filaments does not depend on them. We compare it's measured values in SDSS against the predictions ofCDM N-body simulations and find thatCDM model is consistent with observations. The average filamentarity is known to be very sensitive to the bias parameter. UsingCDM N-body simulations we simulate mock galaxy distributions for SDSS NGP equatorial strip for different biases and test if the statistically significant length scale of filaments depends on bias. We find that statistically significant length scale of filaments is nearly independent of bias. This result is possibly related to the fact that statistically signif- icant length scale of filaments is nearly the same for different class of galaxies which are differently biased with respect to underlying dark matter distribution. The average filamentarity is also known to be dependent on the galaxy number density and size of the samples. We useCDM dark matter N-body simulations to test if the statistically significant length scale of filaments depends on number density of galaxies and size of the samples. Our analysis shows that the statistically significant length scale of filaments very weakly depends on these factors. Finally we test the reliability of our method by applying it to controlled samples of segment Cox process and find that our method successfully recovers the length of the inputted segments. Summarizing these results we conclude that the statistically significant length scale of filaments is a robust measure of the galaxy distribution.
Research and development of an acoustic modem for underwater bio-mimetic fish robots

Acoustic communication is one of the essential technologies for many promising underwater systems. In this paper, we focus on the research and development of an acoustic modem for a real-time water quality monitoring system using bio-mimetic fish robots. Challengeable issues from the viewpoint of acoustic communication for the application are first classified and then the detailed study is conducted to meet each design criterion. Also, the implemented modem hardware is verified in terms of functionality and performance through experiments in a lake and a river.
Cortical Bone Width Measurement Based on Active Shape Models and Automatic Contrast Stretching on Dental Panoramic Radiograph

Information on the morphological changes of mandibular on dental panoramic image is needed to detect various diseases, especially osteoporosis. Measure automatically the width of cortical bone is one of the measurement problems due to uneven illumination and noise disturbance of the image.This paper proposes a new system that can automatically measure the width of cortical bone along the sampled mandibular bone images by using Active Shape Models (ASM) method. For image enhancement, we introduce an automatic contrast stretching algorithm by which cortical bone area seems clearly. Measurements were taken at the boundary between the results of fitting statistical models generated by the ASM method with the object in the image. Experimental results on several dental panoramic radiographs for measuring cortical bone on the left and right region shows the robustness of the proposed method.
Using Natural Language Processing to Analyze Tutorial Dialogue Corpora Across Domains Modalities

Our research goal is to investigate whether previous findings and methods in the area of tutorial dialogue can be generalized across dialogue corpora that differ in domain (mechanics versus electricity in physics), modality (spoken versus typed), and tutor type (computer versus human). We first present methods for unifying our prior coding and analysis methods. We then show that many of our prior findings regarding student dialogue behaviors and learning not only generalize across corpora, but that our methodology yields additional new findings. Finally, we show that natural language processing can be used to automate some of these analyses.
TFT-bootstrap: Resampling time series in the frequency domain to obtain replicates in the time domain

A new time series bootstrap scheme, the Time Frequency Toggle (TFT)-Bootstrap, is proposed. Its basic idea is to bootstrap the Fourier coecients of the observed time series, and then back-transforming them to obtain a bootstrap sample in the time domain. Related previous proposals, such as the ‘surrogate data’ approach, resampled only the phase of the Fourier coecients, and thus had only limited validity. By contrast, we show that the appropriate resampling of phase and magnitude in addition to some smoothing of Fourier coecients yields a bootstrap scheme that mimics the correct second-order moment structure for a large class of time series processes. As a main result we obtain a functional limit theorem for the TFT-Bootstrap under a variety of popular ways of frequency domain bootstrapping. Possible applications of the TFT-Bootstrap naturally arise in change-point analysis and unit-root testing where statistics are frequently based on functionals of partial sums. Finally, a small simulation study explores the potential of the TFT-Bootstrap for small samples showing that for the discussed tests in change-point analysis as well as unit-root testing it yields better results than the corresponding asymptotic tests if measured by size and power.
Identification of a 251 Gene Expression Signature That Can Accurately Detect M. tuberculosis in Patients with and without HIV Co-Infection

Background Co-infection with tuberculosis (TB) is the leading cause of death in HIV-infected individuals. However, diagnosis of TB, especially in the presence of an HIV co-infection, can be limiting due to the high inaccuracy associated with the use of conventional diagnostic methods. Here we report a gene signature that can identify a tuberculosis infection in patients co-infected with HIV as well as in the absence of HIV. Methods We analyzed global gene expression data from peripheral blood mononuclear cell (PBMC) samples of patients that were either mono-infected with HIV or co-infected with HIV/TB and used support vector machines to identify a gene signature that can distinguish between the two classes. We then validated our results using publically available gene expression data from patients mono-infected with TB. Results Our analysis successfully identified a 251-gene signature that accurately distinguishes patients co-infected with HIV/TB from those infected with HIV only, with an overall accuracy of 81.4% (sensitivity = 76.2%, specificity = 86.4%). Furthermore, we show that our 251-gene signature can also accurately distinguish patients with active TB in the absence of an HIV infection from both patients with a latent TB infection and healthy controls (88.9–94.7% accuracy; 69.2–90% sensitivity and 90.3–100% specificity). We also demonstrate that the expression levels of the 251-gene signature diminish as a correlate of the length of TB treatment. Conclusions A 251-gene signature is described to (a) detect TB in the presence or absence of an HIV co-infection, and (b) assess response to treatment following anti-TB therapy.
The Relation between a Framework for Collaborative Ontology Engineering and Nicola Guarino's Terminology and Ideas in "Formal Ontology and Information Systems"

In this paper, we investigate the relation between Guarino’s seminal paper “Formal Ontology and Information Systems” and the DOGMA ontology-engineering framework. As DOGMA is geared towards the development of ontologies for semantic interoperation between autonomously developed and maintained information systems, it follows that the stakeholders in this project form a community and adds a social dimension to the ontology project. The goal of this exercise is to examine how the different terminologies and ideas relate to one and another, thus providing a reference for clarifying DOGMA’s ideas and notation inside Guarino’s framework.
A R-tree-based Fine Directional Query Filtering

there have little work on processing joins with direction predicates, the research work on processing of spatial joins has primarily focused on topological and distance relations. The processing of direction relation queries is essentially a traversing process. A new fine query filtering method based on R-tree presented in this paper. A fine filtering step added in the middle of the traditional 2-stage query model. The improved method could decrease the size of candidate set in the filter step, and thus it can reduce the workload of the refine step. The validity of method is be proved by theoretical analysis. The improved methods only achieve the 40% calculation cost of original method. Results fully prove the validity of this method. Finally, it uses real world datasets to prove the validity. The experiment results show that performance evaluation of the proposed method performs well with respect to both I/O-and CPU-time.
Phosphorylation-Dependent and Phosphorylation-Independent Modes of Modulation of Shaker Family Voltage-Gated Potassium Channels by Src Family Protein Tyrosine Kinases

Modulation of voltage-gated potassium (Kv) channels by protein phosphorylation plays an essential role in the regulation of the membrane properties of cells. Protein–protein binding domains, such as Src homology 3 (SH3) domains, direct ion channel modulation by coupling the channels with intracellular signaling enzymes. The conventional view is that protein kinase binding to ion channels leads to modulation by bringing the channel substrate into physical proximity to the enzyme, thereby fostering covalent modification of the channel. The SH3 domain binding-dependent functional suppression of Kv1.5 currents by Src family protein tyrosine kinases (PTKs) is considered a canonical example of this type of mechanism. In the present study we address whether the SH3-dependent binding of Src family PTKs toShaker family Kvs mediates modulatory events that are independent of and/or dependent on Src-catalyzed tyrosine phosphorylation of the channel. We find that Src binding and tyrosine phosphorylation are each able to modulate Kv1 family macroscopic channel currents independently. SH3-dependent binding of Src leads to the suppression of both Kv1.5 and Kv1.4 (modified to contain proline-rich SH3 domain binding sites) macroscopic currents even in the absence of Src-catalyzed tyrosine phosphorylation, whereas binding-independent tyrosine phosphorylation by Src leads to the suppression of Kv1.5 macroscopic currents and the modulation of Kv1.4 inactivation kinetics.
Efficient Cache-Supported Path Planning on Roads

Owing to the wide availability of the global positioning system (GPS) and digital mapping of roads, road network navigation services have become a basic application on many mobile devices. Path planning, a fundamental function of road network navigation services, finds a route between the specified start location and destination. The efficiency of this path planning function is critical for mobile users on roads due to various dynamic scenarios, such as a sudden change in driving direction, unexpected traffic conditions, lost or unstable GPS signals, and so on. In these scenarios, the path planning service needs to be delivered in a timely fashion. In this paper, we propose a system, namely, Path Planning by Caching (PPC), to answer a new path planning query in real time by efficiently caching and reusing historical queried-paths. Unlike the conventional cache-based path planning systems, where a queried-path in cache is used only when it matches perfectly with the new query, PPC leverages the partially matched queries to answer part(s) of the new query. As a result, the server only needs to compute the unmatched path segments, thus significantly reducing the overall system workload. Comprehensive experimentation on a real road network database shows that our system outperforms the state-of-the-art path planning techniques by reducing 32 percent of the computation latency on average.
Code-Shifted Reference Ultra-Wideband (UWB) Radio

In this paper, a code-shifted reference ultra-wideband (CSR-UWB) transceiver, which separates the reference pulse sequence and the data pulse sequences with a set of shifting and detection codes selected from Walsh codes, has been proposed to remove the ultra wideband delay element required by the transmitted reference UWB transceiver. As compared to the frequency-shifted reference UWB transceiver, which also can remove the delay element through separating the reference pulse sequence and the data pulse sequences with a group of analog carriers, the CSR-UWB transceiver has lower complexity as well as much better bit-error rate performance.
Short Hairpin RNA (shRNA) Ether à go-go 1 (Eag1) Inhibition of Human Osteosarcoma Angiogenesis via VEGF/PI3K/AKT Signaling

Ether à go-go 1 (Eag1) channel is overexpressed in a variety of cancers but the therapeutic potential of Eag1 in osteosarcoma remains elusive. In this study, we constructed an Ad5-Eag1-shRNA vector and evaluated its efficiency for Eag1 knockdown and its effects on osteosarcoma. Our results showed that Ad5-Eag1-shRNA had high interference efficiency of Eag1 expression and suppressed osteosarcoma growth both in vitro and in vivo. To explore the molecular mechanism underlying tumor growth inhibition induced by Eag1 silencing, the intratumoral microvessel density (MVD) was assessed by CD31 staining and the expression of vascular endothelial growth factor (VEGF) was detected by Western blot analysis. We found that Eag1 silencing led to decreased angiogenesis and VEGF expression in the xenograft model of osteosarcoma. Finally, we detected a time-dependent decrease in VEGF expression and considerably reduced phosphoinositide 3-kinase (PI3K) and protein kinase B (AKT) activation in osteosarcoma cells treated by Eag1 shRNA. Taken together, our results suggest that Eag1 silencing inhibits tumor growth and angiogenesis in osteosarcoma via the down regulation of VEGF/PI3K/AKT signaling.
Task Versus Vehicle-Based Control Paradigms in Multiple Unmanned Vehicle Supervision by a Single Operator

There has recently been a significant amount of activity in developing supervisory control algorithms for multiple unmanned aerial vehicle operation by a single operator. While previous work has demonstrated the favorable impacts that arise in the introduction of increasingly sophisticated autonomy algorithms, little work has performed an explicit comparison of different types of multiple unmanned vehicle control architectures on operator performance and workload. This paper compares a vehicle-based paradigm (where a single operator individually assigns tasks to unmanned assets) to a task-based paradigm (where the operator generates a task list, which is then given to the group of vehicles that determine how to best divide the tasks among themselves.) The results demonstrate significant advantages in using a task-based paradigm for both overall performance and robustness to increased workload. This effort also demonstrated that while previous video gaming experience mattered for performance, the degree of experience that demonstrated benefit was minimal. Further work should focus on designing a flexible automated system that allows operators to focus on a primary goal, but also facilitate lower level control when needed without degradation in performance.
Triple Security Generator in Smart Authentication Using Data Mining Techniques

— The primary objective of this paper is to authenticate and work with playlists by using Triple Security Generator (TSG). It is used to evaluate with best suitable data mining functions, to explore and express features and grouping of music. Here we have three methods to authenticate playlists. The recommender systems are popular social web tools, as they address the information overload problem and provide personalization of results. Our intent is to select optimal features, to identify and develop the best suitable Data Mining functionality that could be applied to class of problem. The TSG technique can provide best secure of the list. This playlist authentication generation technique provides security among music files and user interested music file with flexible manner.
Security of Wireless Sensor Network

Wireless Sensor Networks (WSN) is an emerging technology and day by day it is attracting the attention of researchers with its challenging characteristics and diversified application domain. The more researchers try to develop further cost and energy efficient computing devices and algorithms for WSN, the more challenging it becomes to fit the security of WSN into that constrained environment. However, security is crucial to the success of applying WSN. So, familiarity with the security aspects of WSN is essential before designing WSN system. This paper studies the security problems of WSN based on its resource restricted design and deployment characteristics and the security requirements for designing a secure WSN. Also, this study documents the well known attacks at the different layers of WSN and some counter measures against those attacks. Finally, this paper discusses on some defensive measures of WSN giving focus on the key management, link layer and routing security.
Efficiency comparisons between k-centers and k-means algorithms

This paper proposes an under-sampling method with an algorithm which guarantees the sampling quality called k-centers algorithm. Then, the efficiency of the sampling using under-sampling method with k-means algorithm is compared with the proposed method. For the comparison purpose, four datasets obtained from UCI database were selected and the RIPPER classifier was used. From the experimental results, our under-sampling method with k-centers algorithm provided the Accuracy, Recall, and F-measure values higher than that obtained from the under-sampling with k-means algorithm in every dataset we used. The Precision value from our k-centers algorithm might be lower in some datasets, however, its average value computed out of all datasets is still higher than using the under-sampling method with k-means algorithm. Moreover, the experimental results showed that our under-sampling method with k-centers algorithm also decreases the Accuracy value obtained from the original data less than that using the under-sampling with k-means algorithm.
Prediction of characteristic points of hip and knee joint trajectories during overground walking using IMUs and Artificial Neural Networks

This paper presents a study on overground non-pathological gait, focusing on hip and knee joint trajectories in sagittal plane. The objects of study are some characteristic points of the joint curves (including the extrema) and their relation to gait parameters, namely normalized walking speed, cadence and normalized step length. The main objective is to predict the spatio-temporal values of these points depending on given gait parameters. To this end, a study with 18 healthy subjects was conducted, where they were asked to walk as comfortable as possible whilst following different tasks, namely walking with desired and given cadence, step length and speed. The data was processed and fed to artificial neural networks to obtain an algorithm able to predict the characteristic points. Specifics of the study protocol and data processing are presented, as well as the prediction results.
Aged Care: Old Policies, New Problems

Part I. What's the Problem? : 1. The issues 2. The Australian policy response Part II. What's the Practice? : 3. De-institutionalisation and the aged care reform strategy 4. The feminisation of ageing 5. Regulating the quality of care 6. Implementing user rights strategies Part III. Reconceptualising Problems, Reorienting Solutions: 7. The 'problem of old women' redefined 8. The Gordian knot: Defining outcomes 9. Whose rights? Whose responsibility? 10. The problem of dependency: Construction and reconstruction 11. New problems, old solutions.
The Ubiquitin Ligase TRAF6 Negatively Regulates the JAK-STAT Signaling Pathway by Binding to STAT3 and Mediating Its Ubiquitination

STAT3 is a key transcription factor that mediates various cellular and organismal processes, such as cell growth, apoptosis, immune response and cancer. However, the molecular mechanisms of STAT3 regulation remain poorly understood. Here, we identified TRAF6 as a new STAT3 interactor. TRAF6 augmented the ubiquitination of STAT3 and deactivated its transcriptional activity induced by IFNα stimulation or overexpressed with JAK2. Both the RING domain and the TRAF-type zinc finger domain of TRAF6 were indispensable for STAT3 deactivation. Accordingly, TRAF6 also down-regulated the expression of two known STAT3 target genes, CRP and ACT. Therefore, we showed that TRAF6 is a new regulator of JAK/STAT signaling and provide a new mechanistic explanation for the crosstalk between the NF-κB and the JAK-STAT pathways.