Miracle-dz/UniFAR-FTUs huggingface dataset:
Responsiveness of respiratory function in Parkinson’s Disease to an integrative exercise programme: A prospective cohort study

Introduction Respiratory disorders are the most common cause of death in Parkinson’s Disease (PD). Conflicting data exist on the aetiology of respiratory dysfunction in PD and few studies examine the effects of exercise-based interventions on respiratory measures. This study was conducted to better understand respiratory dysfunction in PD and to identify measures of dysfunction responsive to an integrative exercise programme. Objectives The objectives were to compare baseline respiratory measures with matched, published population norms and to examine immediate and longer-term effects of a 12-week integrated exercise programme on these measures. Design Twenty-three people with mild PD (median Hoehn & Yahr = 2) self-selected to participate in this exploratory prospective cohort study. Evaluation of participants occurred at three time points: at baseline; following the 12-week exercise programme and at 4-month follow-up. Outcome measures Outcome measures included: Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 second (FEV1), FEV1/FVC ratio, Peak Expiratory Flow (PEF), Inspiratory Muscle Strength (MIP), Expiratory Muscle Strength (MEP), Peak Cough Flow (PCF), and Cardiovascular Fitness measures of estimated VO2 max and 6-Minute Walk Test (6MWT). Results Compared to published norms, participants had impaired cough, reduced respiratory muscle strength, FEV, FVC, PEF and cardiovascular fitness. Post exercise intervention, statistically significant improvements were noted in MEP, cardiovascular fitness, and PEF. However only gains in PEF were maintained at 4-month follow-up. Conclusions Significant respiratory dysfunction exists, even in the early stages of PD. Metrics of respiratory muscle strength, peak expiratory flow and cardiovascular fitness appear responsive to an integrative exercise programme.
Deformation and Force Characteristics of Laminated Piezoelectric Actuators

ii This research discusses the mechanical characteristics of laminated piezoelectric actuators that are manufactured at an elevated temperature, to cure the adhesive bonding the layers together, or to cure the layers made of polymeric composite material, and then cooled to a service temperature. Mainly discussed are actuators that are composed of layers of passive materials and a layer of piezoelectric material. THUNDER (THin layer UNimorph ferroelectric DrivER and sensor) and LIPCA (LIghtweight Piezo-composite Curved Actuator) actuators, which consist of layers of metal, adhesive and piezoelectric material, and carbon-epoxy, glass-epoxy and piezoelectric material, respectively, are studied and investigated in detail to understand the thermal effects due to the elevated manufacturing temperature. Owing to the large out-of-plane deformations of the THUNDER actuators as a result of cooling to the service temperature, inclusion of geometric nonlinearities in the kinematic relations is taken into consideration for prediction of the thermally-induced deformations and residual stresses. The deformations and residual stresses are predicted by using a 23-term Rayleigh-Ritz approach and more rigorous, time-consuming, finite-element analyses performed with ABAQUS. The thermally-induced deformations of THUNDER actuators can result in multiple room-temperature manufactured shapes, whereas those of LIPCA actuators (LIPCA-C1 and LIPCA-C2) exhibit single room-temperature manufactured shape. Actuation responses of these actuators caused by a quasi-static electric iii field applied to the piezoelectric layer are also studied with the Rayleigh-Ritz approach. It is shown that geometrical nonlinearities play an important role in the actuation responses, and these nonlinearities can be controlled by the choice of actuator geometry and the materials in the passive layers. In addition, blocking forces representing load-carrying capability of THUNDER and LIPCA actuators are determined. Support conditions and again geometrical nonlinearities are vital factor in load-resisting performances. Amongst the actuators considered, the actuated deflection and blocking forces are compared. Finally, based on the outcome of this study, new criteria for designing a new type of laminated piezoelectric actuators with improvement of performance characteristics are proposed.
Sparse imaging based on SAR complex image domain

In this paper, a novel synthetic aperture radar (SAR) imaging algorithm based on two-dimensional (2-D) compressed sensing (CS) is presented. First, a complex image is generated by applying a traditional imaging method to raw echoes. Then, the basis pursuit (BP) method is applied to a CS framework to obtain the scattering coefficients of target points from the complex image. Since CS is applied jointly in range and azimuth, this algorithm utilizes the sparsity of the target scene fully. Experimental results using the real field data demonstrate the effectiveness of our algorithm.
Diversification along environmental gradients in spatially structured populations

Questions: Does frequency-dependent and spatially localized competition in geographically structured populations generate phenotypic diversification in the form of multimodal phenotype distributions? Is such pattern formation an artifact of the boundary conditions assumed for numerical simulations? Do environmental gradients facilitate phenotypic diversification, and how does the slope of the environmental gradient influence this facilitation? Mathematical methods: We solve numerically partial differential equations models for the dynamics of density distributions of phenotypically varying populations that occupy a continuous geographical area. Key assumptions: We assume a linear spatial gradient in the optimal phenotype for the stabilizing component of selection (carrying capacity). To address the role of boundary conditions, we use two types of models. First, we use models in which the carrying capacity declines to 0 in both the phenotypic and the spatial dimensions as the corresponding coordinates become either large or small enough. Second, we use models with periodic boundary conditions in both the phenotypic and the geographical dimensions. For sexual populations, we assume assortative mating without Allee effects. Conclusions: Multimodal pattern formation in phenotype space – that is, phenotypic diversification and speciation – is a robust outcome of models incorporating frequencydependent and spatially localized competition in geographically structured populations. Also, spatial gradients in the optimal phenotype lead to a facilitation of diversification. Confirming earlier results from individual-based models, this facilitation appears to be most pronounced for gradients of intermediate slopes. The pattern formation observed in our models is not an artifact of boundary conditions.
Metric forensics: a multi-level approach for mining volatile graphs

Advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. Existing graph analysis techniques are not appropriate for such data, especially in cases where streaming or near-real-time results are required. An example that has drawn significant research interest is the cyber-security domain, where internet communication traces are collected and real-time discovery of events, behaviors, patterns, and anomalies is desired. We propose MetricForensics, a scalable framework for analysis of volatile graphs. MetricForensics combines a multi-level "drill down" approach, a collection of user-selected graph metrics, and a collection of analysis techniques. At each successive level, more sophisticated metrics are computed and the graph is viewed at finer temporal resolutions. In this way, MetricForensics scales to highly volatile graphs by only allocating resources for computationally expensive analysis when an interesting event is discovered at a coarser resolution first. We test MetricForensics on three real-world graphs: an enterprise IP trace, a trace of legitimate and malicious network traffic from a research institution, and the MIT Reality Mining proximity sensor data. Our largest graph has 3M vertices and 32M edges, spanning 4.5 days. The results demonstrate the scalability and capability of MetricForensics in analyzing volatile graphs; and highlight four novel phenomena in such graphs: elbows, broken correlations, prolonged spikes, and lightweight stars.
Measuring Depression of Elderly Chinese Americans: A Replication Study

ABSTRACT Research findings aimed at understanding depression in ethnic elderly Chinese are lacking. Using a revised version of the Chinese Geriatric Depression Scale, this replication study measures the prevalence of depression and its related explanatory factors in a community sample of elderly Chinese. One in five respondents was found to be depressed. Reliability and validity of the instrument support the applicability of the Chinese GDS in measuring depression in elderly Chinese. The practice implications of serving the elderly Chinese population are also discussed.
1,8-Bis[3-(triethoxysilyl)propyl]-1,8-diazoniatricyclo[9.3.1.14,8]hexadecane diiodide

The organic molecule of title compound, C30H66N4O6Si2 2+·2I−, is located around a centre of symmetry. The structure exhibits disorder of the triethoxy groups with the ratios 0.78 (1)/0.22 (1), 0.67 (1)/0.33 (1) and 0.58 (1)/0.42 (1).
Statistical noise margin estimation for sub-threshold combinational circuits

The increasingly popular sub-threshold design is strongly calling for EDA support to estimate noise margins, minimum functional supply voltage, as well as the functional yield. In this paper, we propose a fast, accurate and statistical approach to accomplish these goals. First, we derive close-form functions based on a new equivalent resistance model which enables the fast estimation of noise margins of individual cells at the gate-level. Second, we propose to calculate and propagate the noise margin information with an affine arithmetic model that takes into account process variations and correspondent inter-cell correlations. Experiments with ISCAS benchmarks have shown that the new approach has an accuracy of 98.5% w.r. t. transistor-level Monte Carlo simulations. The running time per input vector of the new approach only needs a few seconds, in contrast to the many hours required by transistor-level DC Monte-Carlo simulations. To the best of our knowledge, we are the first to provide a fast, accurate and statistical methodology other than Monte-Carlo simulation for the noise margin estimation of sub-threshold combinational circuits.
Preventing Unraveling in Social Networks Gets Harder

The behavior of users in social networks is often observed to be affected by the actions of their friends. Bhawalkar et al. (ICALP '12) introduced a formal mathematical model for user engagement in social networks where each individual derives a benefit proportional to the number of its friends which are engaged. Given a threshold degree k the equilibrium for this model is a maximal subgraph whose minimum degree is at least k. However the dropping out of individuals with degrees less than k might lead to a cascading effect of iterated withdrawals such that the size of equilibrium subgraph becomes very small. To overcome this some special vertices called "anchors" are introduced: these vertices need not have large degree. Bhawalkar et al. considered the Anchored k-Core problem: Given a graph G and integers b, k and p do there exist sets of vertices B, H such that B is a subset of H, size of B is at most b and size of H is at least p, and every vertex v which is in H but not in B has degree at least k in the induced subgraph G[H]. They showed that the problem is NP-hard for all k greater equal 2, and gave some inapproximability and fixed-parameter intractability results. In this paper we give improved hardness results for this problem. In particular we show that the Anchored k-Core problem is W[1]-hard parameterized by p, even for k=3. This improves the result of Bhawalkar et al. (who show W[2]-hardness parameterized by b) as our parameter is always bigger since p is greater equal than b. Then we answer a question of Bhawalkar et al. by showing that the Anchored k-Core problem remains NP-hard on planar graphs for all k greater equal 3, even if the maximum degree of the graph is k+2. Finally we show that the problem is FPT on planar graphs parameterized by b for all k greater equal 7.
Non-HDL cholesterol predicts coronary heart disease in primary prevention: findings from an Italian 40-69 year-old cohort in general practice.

OBJECTS Non-HDL cholesterol is now recommended as an index of risk associated with combined dyslipidemia, and it has also been found useful in predicting coronary heart disease (CHD) risk in patients with diabetes. We studied the association between known CHD risk factors, enclosed non-HDL cholesterol, and a "high CHD risk condition", i.e. a "5-years CHD risk >15%" in general practice. METHODS We studied 4,085 40-69 year-old diabetic (no. 489) and non-diabetic (no. 3,596) individuals from an opportunistic cohort. Cross-sectional descriptive statistics, and age- and gender-adjusted multiple logistic exponential betas have been calculated. RESULTS About 12% of the participants had diabetes. Age- and gender-adjusted comparison showed that all the study variables were significantly worse in diabetic vs. non-diabetic individuals (except cigarette smoking, total blood cholesterol and the ratio of total to HDL cholesterol). They had a mean "5-year CHD-risk" significantly higher than non-diabetic individuals (18.8+/-11.9% vs 7.5+/-6.9%, P<0.01), and a four-fold prevalence of "5-years CHD risk >15%" (55.4% vs 11.1%, P<0.01). As to diabetic individuals, the study variables associated to a "high CHD risk condition" were cigarette smoking, systolic blood pressure, and non-HDL blood cholesterol levels. As to non-diabetic individuals cigarette smoking, systolic blood pressure, and HDL (inversely) and non-HDL blood cholesterol levels were associated to a "high CHD risk condition". CONCLUSIONS Non-HDL cholesterol--and cigarette smoking and systolic blood pressure--strongly predicted a "high CHD risk condition" both in diabetic and non-diabetic individuals.
An improved current mode control of a three-phase rectifier based on positive-sequence detection

In this paper an improved current mode control for a three-phase rectifier is presented which is able to compensate the line currents under unbalanced operation of the supplied grid voltage. Instrumental for the controller design is the computation of the current reference, where, the key point is the use of the positive-sequence of the grid voltage to construct it. The control scheme is designed to guarantee current tracking of the positive-sequence of the grid voltage and the average voltage regulation at the output towards the desired voltage reference. The overall resulting controller is composed by two main control loops, namely, current (or inner), the voltage (or outer) control loops and additionally a positive-sequence estimator of the grid is used to compute the current reference. The current control loop is designed as a proportional controller with a couple of adaptive estimators which have been added to cope with parameter uncertainties of the filter. The voltage control loop consists of an Integral plus a Proportional controller whose output signal acts as a modulating signal of the current reference.
A fast simulation approach for inductive effects of VLSI interconnects

Modeling on-chip inductive effects for interconnects of multi-gigahertz microprocessors remains challenging. SPICE simulation of these effects is very slow because of the large number of mutual inductances. Meanwhile, ignoring the non-linear behavior of drivers in a fast linear circuit simulator results in large errors for the inductive effect. In this paper, a fast and accurate time-domain transient analysis approach is presented, which captures the non-linearity of circuit drivers, the effect of non-ideal ground and de-coupling capacitors in a bus structure. The proposed method models the non-linearity of drivers in conjunction with specific bus geometries. Linearized waveforms at each driver output are incorporated into an interconnect reduced-order simulator for fast transient simulation. In addition, non-ideal ground and de-coupling capacitor models enable accurate signal and ground bounce simulations. Results show that this simulation approach is up-to 68x faster than SPICE while maintaining 95% accuracy.
Predicting citations from mainstream news, weblogs and discussion forums

The growth in the alternative digital publishing is widening the breadth of scholarly impact beyond the conventional bibliometric community. Thus, research is becoming more reachable both inside and outside of academic institutions and are found to be shared, downloaded and discussed in social media. In this study, we linked the scientific articles found in mainstream news, weblogs and Stack Overflow to the citation database of peer-reviewed literature called Scopus. We then explored how standard graph-based influence metrics can be used to measure the social impact of scientific articles. We also proposed the variant of Katz centrality metrics called EgoMet score to measure the local importance of scientific articles in its ego network. Later we evaluated these computed graph-based influence metrics by predicting absolute citations. Our results of the prediction model describe 34% variance to predict citations from blogs and mainstream news and 44% variance to predict citations from Stack Overflow.
A Novel Method for the Characterization of Synchronization and Coupling in Multichannel EEG and ECoG

In this paper we introduce a novel method for the characterization of synchronziation and coupling effects in multivariate time series that can be used for the analysis of EEG or ECoG signals recorded during epileptic seizures. The method allows to visualize the spatio-temporal evolution of synchronization and coupling effects that are characteristic for epileptic seizures. Similar to other methods proposed for this purpose our method is based on a regression analysis. However, a more general definition of the regression together with an effective channel selection procedure allows to use the method even for time series that are highly correlated, which is commonly the case in EEG/ECoG recordings with large numbers of electrodes. The method was experimentally tested on ECoG recordings of epileptic seizures from patients with temporal lobe epilepsies. A comparision with the results from a independent visual inspection by clinical experts showed an excellent agreement with the patterns obtained with the proposed method. Keywords—EEG, epilepsy, regression analysis, seizure propagation.
ANOMALOUS TRANSMISSION OF X-RAYS IN GERMANIUM. PART II. EFFECTS DUE TO ELASTIC DEFORMATION

The effect of elastic deformation on the anomalous transmission of Cu Ka radiation in germanium is investigated. The elastic deformation of the specimens is achieved by means of a bending moment, or by means of a temperature gradient. The bending experiment does not give reproducible results. It is shown that the surface of the specimen plays a very important part. It is not necessary to postulate the presence of micro-strains in dislocation-free germanium crystals, as suggested by Hunter. The results obtained from specimens deformed by a temperature gradient are in very good agreement with the dynamical theory for deformed crystals, as put forward by Penning and Polder. The value of the adjustable parameter . pH obtained experimentally is in good agreement with the value calculated theoretically.
Discrete Personalized Ranking for Fast Collaborative Filtering from Implicit Feedback

Personalized ranking is usually considered as an ultimate goal of recommendation systems, but it suffers from efficiency issues when making recommendations. To this end, we propose a learning-based hashing framework called Discrete Personalized Ranking (DPR), to map users and items to a Hamming space, where user-item affinity can be efficiently calculated via Hamming distance. Due to the existence of discrete constraints, it is possible to exploit a two-stage learning procedure for learning binary codes according to most existing methods. This two-stage procedure consists of relaxed optimization by discarding discrete constraints and subsequent binary quantization. However, such a procedure has been shown resulting in a large quantization loss, so that longer binary codes would be required. To this end, DPR directly tackles the discrete optimization problem of personalized ranking. And the balance and un-correlation constraints of binary codes are imposed to derive compact but informatics binary codes. Based on the evaluation on several datasets, the proposed framework shows consistent superiority to the competing baselines even though only using shorter binary code.
Optimal Deterministic Sorting on Parallel Disks

We present an optimal deterministic algorithm called Balance Sort for external sorting on multiple disks. Our measure of performance is the number of input/output (I/O) operations. In each I/O, each disk can simultaneously transfer a block of data. Our algorithm improves upon the randomized optimal algorithm of Vitter and Shriver as well as the (non-optimal) commonly-used technique of disk striping. It also improves upon our earlier merge-based sorting algorithm in that it has smaller constants hidden in the big~oh notation, it is possible to implement using only striped writes (but independent reads), and it has application to parallel memory hierarchies.
GreMuTRRR: A novel genetic algorithm to solve distance geometry problem for protein structures

Nuclear Magnetic Resonance (NMR) Spectroscopy is a widely used technique to predict the native structure of proteins. However, NMR machines are only able to report approximate and partial distances between pair of atoms. To build the protein structure one has to solve the Euclidean distance geometry problem given the incomplete interval distance data produced by NMR machines. In this paper, we propose a new genetic algorithm for solving the Euclidean distance geometry problem for protein structure prediction given sparse NMR data. Our genetic algorithm uses a greedy mutation operator to intensify the search, a twin removal technique for diversification in the population and a random restart method to recover stagnation. On a standard set of benchmark dataset, our algorithm significantly outperforms standard genetic algorithms.
Five Day Attachment ECG Electrodes for Longitudinal Bio-Sensing Using Conformal Tattoo Substrates

State-of-the-art ECG (electrocardiography) uses wet Silver/Silver-Chloride (Ag/AgCl) electrodes, where a conductive gel is used to provide a resistive, low impedance, connection to the skin. These electrodes are very easy to apply, but have a significant number of limitations for personalized and preventative healthcare. In particular, that the gel dries out giving a limited connection time. This paper presents ECG electrodes manufactured using the inkjet printing of Silver nanoparticles onto a conformal tattoo substrate. The substrate maintains a high quality connection to the body for many days at a time allowing ECG monitoring over periods not previously possible without electrode re-attachment. The design and manufacture of the conformal electrodes is presented, together with detailed characterization of the electrode performance in terms of the signal to noise ratio and baseline wander. The signal to noise ratio is shown to still be over 30 dB five days after the initial electrode attachment.