Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation and cultural adaptation of the Arabic versions of the Mini–Mental Status Examination – 2 and Mini-Cog test

Introduction The elderly population is increasing around the world, and the prevalence of dementia increases with age. Hence, it is expected that the number of people with dementia will increase significantly in the coming years. The Mini–Mental Status Examination – 2 (MMSE-2) and Mini-Cog are widely used tests to screen for dementia. These scales have good reliability and validity and are easy to administer in clinical and research settings. Aim The purpose of this study was to validate the Arabic versions of MMSE-2 and Mini-Cog. These scales were assessed against the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) criteria for dementia, as the gold standard. Methods The standard versions of the MMSE-2 and Mini-Cog were translated to Arabic following the back-translation method. Then, a trained rater administered these tests to 134 Arab elderly aged >60 years. A physician, blind to the results of these two tests, assessed the participants for vascular dementia or probable Alzheimer’s disease, based on the DSM-IV-TR criteria. Results The sample included 67.2% Qataris. The mean age was 74.86 years (standard deviation =7.71), and 61.9% did not attend school. The mean of the adjusted scores of MMSE-2 based on age and education level was 19.60 (standard deviation =6.58). According to DSM-IV-TR, 17.2% of the participants had dementia. Sensitivity and specificity of the MMSE-2 and the Mini-Cog together were 71.4% and 61.6%, respectively, which were better than those of each test alone. Conclusion Together, the Arabic versions of MMSE-2 and Mini-Cog are good screening tools for cognitive impairment in Arabs.
Risk management in cyberspace

This paper addresses the social aspects of the information systems security and risk agenda. It counterposes the prevailing focus on technical issues by reviewing research undertaken using a social science perspective. Underpinning this account is a belief that information systems are essentially social systems that rely on an important technical component, and that security is likewise dependent on social behaviour. End-users who are appropriately trained and predisposed towards securing information offer a direct solution to a great many security problems; on the other hand, systems that fail to take account of end-users and their behaviour inevitably contribute to the creation of more vulnerabilities.
Improved approximate QR-LS algorithms for adaptive filtering

This paper studies a class of O(N) approximate QR-based least squares (A-QR-LS) algorithm recently proposed by Liu in 1995. It is shown that the A-QR-LS algorithm is equivalent to a normalized LMS algorithm with time-varying stepsizes and element-wise normalization of the input signal vector. It reduces to the QR-LMS algorithm proposed by Liu et al. in 1998, when all the normalization constants are chosen as the Euclidean norm of the input signal vector. An improved transform-domain approximate QR-LS (TA-QR-LS) algorithm, where the input signal vector is first approximately decorrelated by some unitary transformations before the normalization, is proposed to improve its convergence for highly correlated signals. The mean weight vectors of the algorithms are shown to converge to the optimal Wiener solution if the weighting factor w of the algorithm is chosen between 0 and 1. New Givens rotations-based algorithms for the A-QR-LS, TA-QR-LS, and the QR-LMS algorithms are proposed to reduce their arithmetic complexities. This reduces the arithmetic complexity by a factor of 2, and allows square root-free versions of the algorithms be developed. The performances of the various algorithms are evaluated through computer simulation of a system identification problem and an acoustic echo canceller.
KVFTL: Optimization of storage space utilization for key-value-specific flash storage devices

The strong momentum of key-value store applications drives the commercialization of key-value-specific hard disk drives. To achieve higher degree of performance, the specific flash-based solid state drives would be also commercialized for key-value store applications in the foreseeable future. However, the existing fixed-sized management strategies of flash-based devices would potentially result in low storage space utilization on managing variable-sized key-value data. This problem inspires this paper to propose a key-value flash translation layer (KVFTL) design to improve the storage space utilization of the key-value-specific solid state drives (KVSSDs). A series of experiments was conducted to evaluated the proposed design, and the experimental results on space utilization and device performance are very encouraging.
Shared Content Addressing Protocol (SCAP): Optimizing multimedia content distribution at the transport layer

In recent years, the networking community has put a significant research effort in identifying new ways to distribute content to multiple users in a better-than-unicast manner. Scalable delivery is more important now video is the dominant traffic type and further growth is expected. To make content distribution scalable, in-network optimization functions are needed such as caches. The established transport layer protocols are end-to-end and do not allow optimizing transport below the application layer, hence the popularity of overlay application layer solutions located in the network. In this paper, we introduce a novel transport protocol, the Shared Content Addressing Protocol (SCAP) that allows in-network intermediate elements to participate in optimizing the delivery process, using only the transport layer. SCAP runs on top of standard IP networks, and SCAP optimization functions can be plugged-in the network transparently as needed. As such, only transport protocol based intermediate functions need to be deployed in the network, and the applications can stay at the topological end points. We define and evaluate a prototype version of the SCAP protocol using both simulation and a prototype implementation of a transparent SCAP-only intermediate optimization function.
Modeling brain circuitry over a wide range of scales

If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Electron Microscopes (EM) can now provide the nanometer resolution that is needed to image synapses, and therefore connections, while Light Microscopes (LM) see at the micrometer resolution required to model the 3D structure of the dendritic network. Since both the topology and the connection strength are integral parts of the brain's wiring diagram, being able to combine these two modalities is critically important. In fact, these microscopes now routinely produce high-resolution imagery in such large quantities that the bottleneck becomes automated processing and interpretation, which is needed for such data to be exploited to its full potential. In this paper, we briefly review the Computer Vision techniques we have developed at EPFL to address this need. They include delineating dendritic arbors from LM imagery, segmenting organelles from EM, and combining the two into a consistent representation.
Using spin images for hand gesture recognition in 3D point clouds

Depth information from a captured scene can provide a more complete description of objects which can be exploited for recognition purposes. In this paper we propose a new approach to static hand gesture recognition that explores only depth information acquired with a Microsoft Kinect camera. Firstly, the regions of interest are extracted from depth data and a 3D point cloud is created taking into consideration the capture device settings. Then, for each 3D point in the simplified point cloud the local spin image descriptor is computed. The performance of hand pose detection greatly depends on the 3D shape descriptor used. KPCA is used for dimensionality reduction and for noise elimination from obtained spin image histograms. The most relevant features in terms of principal components are served as input for a SVM classifier. Experimental results show a high level of accuracy in recognizing static hand gestures using spin images in 3D point clouds.
Fostering Higher Knowledge Construction Levels in Online Discussion Forums: An Exploratory Case Study

Prior research has suggested that higher levels of knowledge construction e.g., where opinions are argued, challenged, or negotiated have rarely been demonstrated in student online discussions. In this study, the authors replicate prior research on group size, discussion duration, and student facilitation techniques to examine the influence of these factors on the attainment of higher level knowledge construction. Data were collected from 12 online discussion forums involving undergraduate students and students' reflection logs. Analysis of the data confirms a significant positive correction between higher level knowledge construction occurrences and group size. No correlation is found between the discussion duration and the occurrences of higher level knowledge construction. Further analysis between the higher and lower performing forums suggests that a certain critical mass, which appears to be a group size of about 10 participants, may be required to direct the discussion to advanced levels of knowledge construction. In addition, results show that students in higher performing forums used the facilitation technique of pointing, highlighting unanswered or unresolved issues statistically significantly more than their counterparts in lower performing forums.
Functional regions of the N-terminal domain of the antiterminator RfaH

RfaH is a bacterial elongation factor that increases expression of distal genes in several long, horizontally acquired operons. RfaH is recruited to the transcription complex during RNA chain elongation through specific interactions with a DNA element called ops. Following recruitment, RfaH remains bound to RNA polymerase (RNAP) and acts as an antiterminator by reducing RNAP pausing and termination at some factor‐independent and Rho‐dependent signals. RfaH consists of two domains connected by a flexible linker. The N‐terminal RfaH domain (RfaHN) recognizes the ops element, binds to the RNAP and reduces pausing and termination in vitro. Functional analysis of single substitutions in this domain reported here suggests that three separate RfaHN regions mediate these functions. We propose that a polar patch on one side of RfaHN interacts with the non‐template DNA strand during recruitment, whereas a hydrophobic surface on the opposite side of RfaHN remains bound to the β′ subunit clamp helices domain throughout transcription of the entire operon. The third region is apparently dispensable for RfaH binding to the transcription complex but is required for the antitermination modification of RNAP.
Building an adaptive museum gallery in Second Life

We describe initial work on building a virtual gallery, within Second Life, which can automatically tailor itself to an individual visitor, responding to their abilities, interests, preferences or history of interaction. The description of an object in the virtual world can be personalised to suit the beginner or the expert, varying how it is said—via the choice of language (such as English or Greek), the words, or the complexity of sentences—as well as what is said—by taking into account what else has been seen or described already. The guide delivering the descriptions can remain disembodied, or be embodied as a robotic avatar.
Machine Learning Data Imputation and Classification in a Multicohort Hypertension Clinical Study

Health-care initiatives are pushing the development and utilization of clinical data for medical discovery and translational research studies. Machine learning tools implemented for Big Data have been applied to detect patterns in complex diseases. This study focuses on hypertension and examines phenotype data across a major clinical study called Minority Health Genomics and Translational Research Repository Database composed of self-reported African American (AA) participants combined with related cohorts. Prior genome-wide association studies for hypertension in AAs presumed that an increase of disease burden in susceptible populations is due to rare variants. But genomic analysis of hypertension, even those designed to focus on rare variants, has yielded marginal genome-wide results over many studies. Machine learning and other nonparametric statistical methods have recently been shown to uncover relationships in complex phenotypes, genotypes, and clinical data. We trained neural networks with phenotype data for missing-data imputation to increase the usable size of a clinical data set. Validity was established by showing performance effects using the expanded data set for the association of phenotype variables with case/control status of patients. Data mining classification tools were used to generate association rules.
The history of effective population size and genetic diversity in the Yellowstone grizzly (Ursus arctos): Implications for conservation

Protein, mtDNA, and nuclear microsatellite DNA analyses have demonstrated that the Yellowstone grizzly bear has low levels of genetic variability compared with other Ursus arctos populations. Researchers have attributed this difference to inbreeding during a century of anthropogenic isolation and population size reduction. We test this hypothesis and assess the seriousness of genetic threats by generating microsatellite data for 110 museum specimens collected between 1912 and 1981. A loss of variability is detected, but it is much less severe than hypothesized. Variance in allele frequencies over time is used to estimate an effective population size of ≈80 across the 20th century and >100 currently. The viability of the population is unlikely to be substantially reduced by genetic factors in the next several generations. However, gene flow from outside populations will be beneficial in avoiding inbreeding and the erosion of genetic diversity in the future.
Selective Cortical Mapping of Biological Motion Processing in Young Infants

How specialized is the infant brain for perceiving the facial and manual movements displayed by others? Although there is evidence for a network of regions that process biological motion in adults—including individuated responses to the perception of differing facial and manual movements—how this cortical specialization develops remains unknown. We used functional near-infrared spectroscopy [Lloyd-Fox, S. , Blasi, A. , & Elwell, C. Illuminating the developing brain: The past, present and future of functional near-infrared spectroscopy. Neuroscience and Biobehavioral Reviews, 34, 269–284, 2010] to investigate the ability of 5-month-old infants to process differing biological movements. Infants watched videos of adult actors moving their hands, their mouth, or their eyes, all in contrast to nonbiological mechanical movements, while hemodynamic responses were recorded over the their frontal and temporal cortices. We observed different regions of the frontal and temporal cortex that responded to these biological movements and different patterns of cortical activation according to the type of movement watched. From an early age, our brains selectively respond to biologically relevant movements, and further, selective patterns of regional specification to different cues occur within what may correspond to a developing “social brain” network. These findings illuminate hitherto undocumented maps of selective cortical activation to biological motion processing in the early postnatal development of the human brain.
Improvement of authorship invarianceness for individuality representation in writer identification

Writer Identification (WI) is one of the areas in pattern recognition that have created a center of attention for many researchers to work in. Recently, its main focus is in forensics and biometric application, e.g. writing style can be used as biometric features for authenticating individuality uniqueness. Existing works in WI concentrate on feature extraction and classi? cation task in order to identify the handwritten authorship. However, additional steps need to be per- formed in order to have a better representation of input prior to the classi? cation task. Features extracted from the feature extraction task for a writer are in vari- ous representations, which degrades the classi? cation performance. This paper will discuss this additional process that can transform the various representations into a better representation of individual features for Individuality of Handwriting, in order to improve the performance of identification in WI.
Extracting Precursor Rules from Time SeriesA Classical Statistical Viewpoint

In many applications of interest one is faced with the problem of identifying precursor events for extraordinary phenomena. We investigate this problem within the framework of Temporal Data Mining. The concept of Precursor Rule is defined in terms of events and sequences of events. Precursor Rules relate Precursor Events extracted from input time series with Phenomenon events extracted from output time series. A methodology is proposed for extracting Precursor Rules from databases containing time series related to different regimes of a system. Given a fixed output time series containing one or more Phenomenon events, a key contribution of this paper is to show that the Granger Causality Test (GCT) can be used for ranking candidate time series according to the likelihood that Precursor Rules exist. Time Series Quantization is performed for extracting Phenomenon events and Precursor events, but GCT is applied to the raw time series, before Quantization and the definition of Event Types. The paper presents an analytic investigation of the utilization of the GCT for time series pairs containing impulsive time-localized structure. Following a number of approximations, the Granger Causality Index is related with the confidence of the Precursor Rules extracted from these time series pairs. An example from Network Security illustrates the effectiveness of the methodology. Using MIB (Management Information Base) datasets collected from real experiments involving Distributed Denial of Service Attacks, it is shown that Precursor Rules relating activities at Attacking Machines with Traffic Floods at Target Machines can be extracted by the method.
Social issues in amazon waters: senses, perceptions and representations

With the main objective of observing as the senses are constituted in Amazonian communities, the perception of the subjects and their social representations about the importance, the use and preservation of water to know the logic of these communities, social and problematic phenomena that surround it, a qualitative research was conducted under the theoretical framework of the Cultural Geography. The spatial area of this study consists of six (06) communities inserted in two cities of the State of Rondonia: Porto Velho and Guajara-Mirim . With the help of Human Geography in its phenomenological perspective, whose interface permeated the Sociocultural Geography, it was observed that Amazonian communities exposed intimate senses in relation to waters that constitute their identities and, through these senses, identified the connections between social phenomena and problems surrounding their water, their world lived.
Sampled-data stability criterion for T-S fuzzy systems with time-varying delay

According to the existing researches, a new Takagi-Sugeno fuzzy systems under the time-varying delay were constructed. To reaching a superior sampled-data stability, the approach of input delay with free-weighting matrix is used. New criterion of stability is proposed. Lyapunov-Krasovskii function's derivative also included, it means a feasible condition. Fuzzy sampled-data controller is designed with asymptotically stability. Truck-trailer system as a simulation illustrated the superiority of fuzzy sampled-data control design.
Couverture : an Innovative Open Framework for Coverage Analysis of Safety Critical Applications

One key step in the development of safety-critical applications is the assessment of the quality of the verification strategy. In practice, structural coverage is the methodology used to ascertain the testing campaign well satisfy a given quality criteria. In this paper, we describe the possible strategies to measure structural coverage in a DO-178B context. After evaluating state-ofthe-art approaches to measure structural coverage, we introduce Couverture, an innovative framework for coverage analysis exploiting a virtualized execution environment.
Thermal-Aware Cloud Middleware to Reduce Cooling Needs

As we are living in a data-driven world and directed toward internet, the need for data enter is growing. The main limitation for building cloud infrastructures is their energy consumption. Moreover, their conception is not perfect because servers are not the ones consuming all the power, cooling systems are responsible for half of the consumption. Cooling costs can be reduced by intelligent scheduling, and in our case through virtual machines migrations. In this paper, we propose a dynamic reconfiguration based on evolution of temperatures and load of the servers. The idea is to share heat production to reduce cooling costs and consolidate the workload when possible to reduce servers costs. The challenge resides in satisfying these opposite objectives. We tested our algorithm on an experimental test bed, and achieve to cap the temperature of the data enter room while not forgetting to optimize the server use, and without impacting on applications performance.