Miracle-dz/UniFAR-FTUs huggingface dataset:
The tremor coherence analyzer (TCA): a portable tool to assess instantaneous inter-muscle coupling in tremor

This paper proposes a novel system for pathological tremor study and diagnosis. The system described called TCA (tremor coherence analyzer) is based on a electronic device developed for wireless monitoring of physiological variables. The device uses Bluetooth technology to communicate. The proposed technique for pathological tremor analysis uses surface EMG signals. The EMG sensors are located on forearm muscles to measure muscular activity due to pathological tremor. The coherence function between these signals is calculated. The application of the coherence function allows to determine linear dependencies between two signals.
Identification of Network Applications with Co-training

Recently, A new generation of network applications, such as P2P, has started to consume a large amount of network resources, thus produce several problems to network operators, which make the identification of network applications become a new and difficult challenge for both network operators and the network measurement community. Traditional identification techniques that rely on the well-known ports registered by the IANA are no longer valid because of the inaccuracy of its classification results. This situation has motivated us to study how to use statistical features of the flow or characteristics patterns in the payload of the packets to solve the problem of application identification in the network traffic. In this paper, we present an effective supervised machine learning technique based on the characteristics patterns and the behaviors pattern to accurately identify the network traffic. We evaluate our method with an existing passive network monitoring system in our campus network and achieve an overall accuracy greater than 89% with a little training samples.
Supporting Network Coordinates on PlanetLab

Large-scale distributed applications need latency information to make network-aware routing decisions. Collecting these measurements, however, can impose a high burden. Network coordinates are a scalable and efficient way to supply nodes with up-to-date latency estimates. We present our experience of maintaining network coordinates on PlanetLab. We present two different APIs for accessing coordinates: a per-application library, which takes advantage of application-level traffic, and a stand-alone service, which is shared across applications. Our results show that statistical filtering of latency samples improves accuracy and stability and that a small number of neighbors is sufficient when updating coordinates.
Nonlinear Balance and Potential‐Vorticity Thinking At Large Rossby Number

Two rational approximations are made to the divergence, potential-vorticity, and potential-temperature equations resulting in two different nonlinear balance models. Semi-balance is similar (but not identical to) the nonlinear balance model of Lorenz. Quasi-balance is a simpler model which is equivalent to quasi-geostrophy at low Rossby number and to the barotropic model at high Rossby number. Practical solutions involving methods that work for all Rossby numbers are outlined for both models. A variety of simple initial-value problems are then solved with the aim of fortifying our insight into the behaviour of flows at large Rossby numbers. the flows associated with a potential-vorticity anomaly at very large Rossby numbers differ in significant ways from the corresponding low Rossby number results. In particular, an isolated anomaly has zero vertical radius of influence at infinite Rossby number, while the induced tangential velocity in a horizontal plane containing the anomaly decreases inversely as, rather than inversely as the square of, the radius. the effects of heating and frictional forces are approached from a point of view somewhat different from that recently expressed by Haynes and McIntyre, though the physical content is the same.
An Image-Based Approach to Visual Feature Space Analysis

Methods for management and analysis of non-standard data often rely on the so-called feature vector approach. The technique describes complex data instances by vectors of characteristic numeric values which allow to index the data and to calculate similarity scores between the data elements. Thereby, feature vectors often are a key ingredient to intelligent data analysis algorithms including instances of clustering, classification, and similarity search algorithms. However, identification of appropriate feature vectors for a given database of a given data type is a challenging task. Determining good feature vector extractors usually involves benchmarks relying on supervised information, which makes it an expensive and data dependent process. In this paper, we address the feature selection problem by a novel approach based on analysis of certain feature space images. We develop two image-based analysis techniques for the automatic discrimination power analysis of feature spaces. We evaluate the techniques on a comprehensive feature selection benchmark, demonstrating the effectiveness of our analysis and its potential toward automatically addressing the feature selection problem.
Relationship of Alcohol Drinking Pattern to Risk of Hypertension: A Population-Based Study

Epidemiological studies have demonstrated a positive relationship between heavy alcohol use and hypertension, but few studies have directly addressed the role of drinking pattern. This study was designed to investigate the association of current alcohol consumption and aspects of drinking pattern with hypertension risk in a sample of 2609 white men and women from western New York, aged 35 to 80 years, and free from other cardiovascular diseases. Hypertension was defined by systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg or use of antihypertensive medication. Odds ratios (95% confidence intervals) were computed after adjustment for several covariates. Compared with lifetime abstainers, participants reporting drinking on a daily basis (1.75 [1.13 to 2.72]) or mostly without food (1.64 [1.08 to 2.51]) exhibited significantly higher risk of hypertension. When analyses were restricted to current drinkers, daily drinkers and participants consuming alcohol without food exhibited a significantly higher risk of hypertension compared with those drinking less than weekly (1.65 [1.18 to 2.30]) and those drinking mostly with food (1.49 [1.10 to 2.00]), respectively. After additional adjustment for the amount of alcohol consumed in the past 30 days, the results were follows: 0.90 (0.58 to 1.41) for daily drinkers and 1.41 (1.04 to 1.91) for drinkers without food. For predominant beverage preference, no consistent association with hypertension risk was found across the various types of beverages considered (beer, wine, and liquor). In conclusion, drinking outside meals appears to have a significant effect on hypertension risk independent of the amount of alcohol consumed.
Spatio-Temporal Traffic Scene Modeling for Object Motion Detection

Moving object detection is an important component of a traffic surveillance system. Usual background subtraction approaches often poorly perform on a long outdoor traffic video due to vehicles waiting at an intersection and gradual changes of illumination and background shadow position. We present a fast and robust background subtraction algorithm based on unified spatio-temporal background and foreground modeling. The correlation between neighboring pixels provides high levels of detection accuracy in the dynamic background scene. Our Bayesian fusion method, which establishes the traffic scene model, combines both background and foreground models and considers prior probabilities to adapt changes of background in each frame. We explicitly model both temporal and spatial information based on the kernel density estimation (KDE) formulation for background modeling. Then, we use a Gaussian formulation to describe the spatial correlation of moving objects for foreground modeling. In the updating step, a fusion background frame is generated, and reasonable updating rates are also proposed for the traffic scene. The experimental results show that the proposed method outperforms the previous work with less computation and is better suited for the traffic scenes.
Massive loss of Cajal-Retzius cells does not disrupt neocortical layer order

Cajal-Retzius (CR) cells, the predominant source of reelin in developing neocortex, are thought to be essential for the inside out formation of neocortical layers. Fate mapping revealed that a large population of neocortical CR cells arises from the cortical hem. To investigate the function of CR cells, we therefore genetically ablated the hem. Neocortical CR cells were distributed beneath the pial surface in control mice, but were virtually absent in hem-ablated mice from embryonic day (E) 10.5 until birth. CR cells derived from other sources did not invade the neocortical primordium to compensate for hem loss. We predicted that neocortical layers would be inverted in hem-ablated animals, as in reeler mice, deficient in reelin signaling. Against expectation, layers showed the standard order. Low levels of reelin in the cortical primordium, or diffusion of reelin from other sites, may have allowed lamination to proceed. Our findings indicate, however, that the sheet of reelin-rich CR cells that covers the neocortical primordium is not required to direct layer order.
Classifying Acute Abdominal Pain By Assuming Independence : A Study Using Two Models Constructed Directly From Data

Medical Expert Systems have been under development for several years, MYCIN [1] being a typical example of a major project. Many of these recent systems have been constructed through expert opinions. In this paper we focus our attention on the semi-automated construction of a classifier directly from the database itself. The methodology employed utilises a data set specifically concerning the domain of Acute Abdominal Pain (AAP), courtesy of St John’s Hospital, Livingston, Scotland. Our objective is : given a set of diseases the computer diagnostic system will use a certain procedure to classify patients in accordance with their symptoms. The classifying procedure we propose to use centers on the assumption of independence. More specifically, a model described by naive Bayes (some times referred to as simple Bayes) and a new proposed model derived from Mutual Information Measure (MIM). Both models are constructed from a 2/3 randomly selected subset of the AAP data set and then validated by the remaining 1/3 unseen test data sample. A total of 3705 patient record test samples were classified using the two models and compared to the results obtained by the Doctors at St John’s Hospital. The MIM classifier identified correctly 70.04% of the unseen test samples with the naive Bayes classifier achieving 73.17%. In comparison to the Doctors’ 70.77%, both models of independence performed with a similar level of expertise, naive Bayes being marginally higher.
Reply to "Comment on 'Separability of quantum states and the violation of Bell-type inequalities'"

It is stated by C. Simon, quant-ph/0410032, that the definition of "classicality" used in quant-ph/0310116 is "much narrower than Bell's concept of local hidden variables" and that, in the separable quantum case, the validity of the perfect correlation form of the original Bell inequality is necessarily linked with "the assumption of perfect correlations if the same (quantum) observable is measured on both sides". Here, I prove that these and other statements in quant-ph/0410032 are misleading.
Statistical evaluation of the persistence of acquired hypersensitivity by standardized patch tests

Numerous studies have focused attention on the influence of various biological and environmental factors on contact hypersensitivity. In order to evaluate the persistence and/or modification of allergic contact sensitivity 10 a number of common contact sensitizers, the same standardized patch tests were repeated on 174 subjects with contact sensitivity after a lime lapse of 5 years (1987–1992). In 18.4% of the cases, 1 or more sensitivities were lost: 28.7% of the patients had a higher number of positive patch tests after 5 years, while the remaining 52.9% of the patients showed no change in the number of positive patch tests. In 88%, the positive allergens were unchanged, whereas in the remaining 12% of the subjects, they showed 1 or more variations. The association between the allergens most often positive was calculated for both the 1st and the 2nd patch lest results. Moreover, to evaluate the frequency of an allergen's positivity. We studied the disappearance of old sensitivities and the appearance of new sensitivities by the McNemar test. Cobalt chloride was the only allergen with a significant frequency of new positivities over the period of observation (p < 0.01). Logistic regression analysis was performed to evaluate the possible influence of positive tests to other allergens, and of some clinical findings associated with contact dermatitis, on the sensitivity to cobalt chloride in 1987 and in 1992.
An Estimate of a Structural Hedonic Price Model of the Housing Market: An Application of Rosen's Theory of Implicit Markets

A simultaneous equations model of bid and offer functions for housing attributes (dwelling quality, dwelling size, and lot size) is estimated in order to account for the heterogeneity of the housing good. Estimation of a traditional, nonlinear hedonic price equation in the first stage provides a basis for calculating implicit prices for housing attributes which are used in the second stage simultaneous equations model. Empirical results confirm the theoretically expected negative coefficient for each attribute in its own bid function and the expected positive or zero coefficient for each attribute in its own offer function. Cross price relationships reveal a general pattern of complementarity in consumption of housing attributes.
Featureless vehicle-based visual SLAM with a consumer camera

The Simultaneous Localisation And Mapping (SLAM) problem is one of the major challenges in mobile robotics. Probabilistic techniques using high-end range finding devices are well established in the field, but recent work has investigated vision-only approaches. We present an alternative approach to the leading existing techniques, which extracts approximate rotational and translation velocity information from a vehicle-mounted consumer camera, without tracking landmarks. When coupled with an existing SLAM system, the vision module is able to map a 45 metre long indoor loop and a 1.6 km long outdoor road loop, without any parameter or system adjustment between tests. The work serves as a promising pilot study into ground-based vision-only SLAM, with minimal geometric interpretation of the environment.
Respecting the Heterogeneity of the Natives: Antecedents and Consequences of Individuals' Digital nativeness

The Internet and digital media have forced many individuals to change their attitudes and behaviours in nearly all aspects of life, including work and consumption. Other individuals, often younger, have grown up with digital media and seem not to have undergone changes in attitudes and behaviours. This research suggests, however, that age should not be used as the criterion to differentiate between individuals’ attitudes and behaviours towards digital media. Rather, we suggest utilizing a construct that we call “digital nativeness,” which we characterize as an individual‘s propensity to use and have a positive attitude towards digital media. Both a qualitative and a quantitative study investigate digital nativeness as well as its antecedents and consequences. Results show that digital nativeness consists of three dimensions: Expertise in digital media, sophisticated digital media use and sophisticated mobile media use. The studies suggest that early and ubiquitous access to digital media influence an individual’s level of digital nativeness, while, importantly, age does not have such an influence. A high level of digital nativeness positively affects individuals’ attitude towards online social network communication, preference for online advertising, learning by doing, and media multitasking. Important implications for scholars and managers can be derived from this research.
On the theory of average case complexity

Summary form only given, as follows. The authors take the next step in developing the theory of average case complexity initiated by L.A. Levin. Previous work has focused on the existence of complete problems. The present authors widen the scope to other basic questions in computational complexity. Their results include: (1) the equivalence of search and decision problems in the context of average case complexity; (2) an initial analysis of the structure of distributional-NP under reductions which preserve average polynomial-time; (3) a proof that if all distributional-NP is in average polynomial-time then nondeterministic exponential-time equals deterministic exponential time (i.e. a collapse in the worst-case hierarchy); and (4) definitions and basic theorems regarding other complexity classes such as average log space. <<ETX>>
A comparative study of STBC transmissions at 2.4 GHz over indoor channels using a 2 × 2 MIMO testbed

In this paper we employ a 2 × 2 Multiple-Input Multiple-Output (MIMO) hardware platform to evaluate, in realistic indoor scenarios, the performance of different space-time block coded (STBC) transmissions at 2.4 GHz. In particular, we focus on the Alamouti orthogonal scheme considering two types of channel state information (CSI) estimation: a conventional pilot-aided supervised technique and a recently proposed blind method based on second-order statistics (SOS). For comparison purposes, we also evaluate the performance of a Differential (non-coherent) space-time block coding (DSTBC). DSTBC schemes have the advantage of not requiring CSI estimation but they incur in a 3 dB loss in performance. The hardware MIMO platform is based on high-performance signal acquisition and generation boards, each one equipped with a 1 GB memory module that allows the transmission of extremely large data frames. Upconversion to RF is performed by two RF vector signal generators whereas downconversion is carried out with two custom circuits designed from commercial components. All the baseband signal processing is implemented off-line in MATLAB®, making the MIMO testbed very flexible and easily reconfigurable. Using this platform we compare the performance of the described methods in line-of-sight (LOS) and non-line-of-sight (NLOS) indoor scenarios. Copyright © 2007 John Wiley & Sons, Ltd.
Positive Psychological Interventions in Counseling

Counseling psychologists are in a prime position to claim preeminence in the field of applied positive psychology. A number of misunderstandings or misconceptions of positive psychology seem to interfere, however, with the focus (or lack thereof) that has been placed upon training counseling psychologists to utilize and contribute to positive psychological scholarship and applications. In this article, the most commonly reported misconceptions are addressed, and foundational information regarding positive psychological constructs, theories, and processes most relevant to the applied work of counseling psychologists is reviewed. Counseling psychologists are encouraged to claim positive psychology as the logical extension of our humanistic roots and to consider how to both utilize and contribute to the growing body of positive psychological scholarship.
Filtering of Distractors during Visual Search Studied by Positron Emission Tomography

We investigated the sensitivity of brain areas to the presence of filtering operations during overt visual search in crowded displays. Task conditions involved either visual search or predetermined simple eye movements for the detection of target digits. Furthermore, visual displays either contained letter foils that required filtering or contained only target digits. Brain imaging using positron emission tomography showed extensive overlap between areas involved in overt visual search and eye movements. Selective filtering of foils affected visual processing in ventral areas associated with object recognition and in primary visual cortex.
In vitro analysis with human bone marrow stem cells on Ti-15Mo alloy for dental and orthopedic implants application

Aim Nowadays, research on orthopedic and dental implants is focused on titanium alloys for their mechanical properties and corrosion resistance in the human body environment. Another important aspect to be investigated is their surface topography, which is very important to osseointegration. With laser beam irradiation for roughening the implants surface an easier control of the microtopography is achieved, and surface contamination is avoided. The aim of this study was to assess human bone marrow stem cells response to a newly developed titanium alloy, Ti-15Mo, with surface topography modified by laser beam irradiation. Materials and methods A total of 10 Ti machined disks (control), 10 Ti-15Mo machined disks and 10 Ti-15Mo disks treated by laser beam-irradiation were prepared. To study how Ti-15Mo surface topografy can induce osteoblast differentiation in mesenchymal stem cells, the expression levels of bone related genes and mesenchymal stem cells marker were analyzed, using real time Reverse Transcription-Polymerase Chain Reaction. Results In Test 1 (comparison between Ti-15Mo machined disks and Ti-machined disks) quantitative real-time RT–PCR showed a significant induction of ALPL, FOSL1 and SPP1, which increase 20% or more. In Test 2 (comparison between Ti-15Mo laser treated disks and Ti-machined disks) all investigated genes were up-regulated. By comparing Test 1 and Test 2 it was detected that COL1A1, COL3A1, FOSL1 and ENG sensibly increased their expression whereas RUNX2, ALPL and SPP1 expression remained substantially unchanged. Conclusion The present study demonstrated that laser treated Ti- 15Mo alloys are promising materials for implants application.
EGFR Signaling Pathway estimation using a RISE-based asymptotic observer

In this paper a RISE (Robust Integral of the Sign Error) observer approach is used for estimating the concentrations of the proteins that participate in the reactions of a biological system. The system under study is the Epidermal Growth Factor Receptor (EGFR) Signaling Pathway. The EGFR family is directly related with diseases such as multiple sclerosis or Alzheimer and its members are important in basic research and drug development. The RISE observer provides estimates that rapidly converge asymptotically to the system's states and their derivatives. Simulation studies verify the effectiveness of the proposed approach.
Hierarchical Document Clustering Using Fuzzy Association Rule Mining

In this paper, we will present an effective Fuzzy Frequent Itemset-Based Hierarchical Clustering (F2IHC) approach, which uses fuzzy frequent itemsets discovered by fuzzy association rule mining to improve the clustering accuracy of FIHC (Frequent Itemset-Based Hierarchical Clustering) method. Our approach can alleviate the deficiencies of most of the traditional document clustering methods in dealing with the problems of high dimensionality, large data size, and meaningful cluster labels. We have conducted experiments to evaluate our approach on Reuters 21578 dataset. The experimental results show that our approach not only absolutely retains the merits of FIHC, but also improves the document clustering accuracy quality as compared with the FIHC method.