Miracle-dz/UniFAR-FTUs huggingface dataset:
Natural occurrence of subjective aging experiences in community-dwelling older adults.

OBJECTIVES The subjective experience of aging is a relevant correlate of developmental outcomes. However, traditional approaches fall short of capturing the inherent multidimensionality of subjective aging experiences (SAEs). Based on the concept of Awareness of Age-Related Change (AARC; Diehl, M. K., & Wahl, H.-W. (2010). Awareness of age-related change: Examination of a (mostly) unexplored concept. Journals of Gerontology: Series B: Psychological Sciences and Social Sciences, 65, 340-350. doi:10.1093/geronb/gbp110), this study provides a description of SAEs that is facet rich, and based on their natural occurrence, analyzes interindividual differences and associations with well-being. METHOD Data came from 225 participants (70-88 years) of the ongoing BEWOHNT study. Open-ended diary entries about age-related experiences were collected for more than 14 days and coded according to AARC domains and subdomains. RESULTS Seventy percent of all participants had SAEs about physical functioning. About half of the sample reported experiences in the domains interpersonal relations, social-emotional and social-cognitive functioning (COGN-EMOT), and lifestyle. Thirty percent experienced aging in terms of changes in cognitive functioning. Contents of SAEs varied by gender, age group, and functional status. SAEs about COGN-EMOT were most consistently related to affective components of subjective well-being. DISCUSSION Our results demonstrate the benefits of an open-ended approach to a multidimensional understanding of SAEs. Content-related, social-cognitive and social-emotional changes more than functional age-related changes were most important for well-being.
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Multi-person action recognition requires models of structured interaction between people and objects in the world. This paper demonstrates how highly struc-tured, multi-person action can be recognized from noisy perceptual data using visually grounded goal-based primitives and low-order temporal relationships that are integrated in a probabilistic framework. The representation, which is motivated by work in model-based object recognition and probabilistic plan recognition, makes four principal assumptions: (1) the goals of individual agents are natural atomic representational units for specifying the temporal relationships between agents engaged in group activities, (2) a high-level description of temporal structure of the action using a small set of low-order temporal and logical constraints is adequate for representing the relationships between the agent goals for highly structured, multi-agent action recognition, (3) Bayesian networks provide a suitable mechanism for integrating multiple sources of uncertain visual perceptual feature evidence, and (4) an automatically generated Bayesian network can be used to combine uncertain temporal information and compute the likelihood that a set of object trajectory data is a particular multi-agent action. The recognition method is tested using a database of American football play descriptions and manually-acquired but noisy player trajectories. The strengths and limitations of the system are discussed and compared with other multi-agent recognition algorithms. ÃÃÝ ÏÓÖ× ÑÙÐØØ¹ÔÖ×ÓÒ ØØÓÒ ÖÖ BLOCKINÓÓÒÒØØÓÒÒ ÔÐÐÒ ÖÖ BLOCKINÓÓÒÒØØÓÒÒ ÓÑÔÙØØÖ ÚÚ××ÓÒÒ Ý×××Ò ÒÒØÛÓÖÖ× ½º ÁAEÌÊÇÇÍÍÌÁÇAE Computer systems that can reliably observe, recognize, and respond to action using visual sensors will enable new computational applications ranging from automatic video annotation and retrieval to interactive environments. Most computer vision research on the visual recognition of action, however, has focused on recognizing the action performed by a single person in isolation from other people and objects. Unfortunately, while these ½
De novo Fatty Acid Biosynthesis Contributes Significantly to Establishment of a Bioenergetically Favorable Environment for Vaccinia Virus Infection

The poxvirus life cycle, although physically autonomous from the host nucleus, is nevertheless dependent upon cellular functions. A requirement for de novo fatty acid biosynthesis was implied by our previous demonstration that cerulenin, a fatty acid synthase inhibitor, impaired vaccinia virus production. Here we show that additional inhibitors of this pathway, TOFA and C75, reduce viral yield significantly, with partial rescue provided by exogenous palmitate, the pathway's end-product. Palmitate's major role during infection is not for phospholipid synthesis or protein palmitoylation. Instead, the mitochondrial import and β-oxidation of palmitate are essential, as shown by the impact of etomoxir and trimetazidine, which target these two processes respectively. Moreover, the impact of these inhibitors is exacerbated in the absence of exogenous glucose, which is otherwise dispensable for infection. In contrast to glucose, glutamine is essential for productive viral infection, providing intermediates that sustain the TCA cycle (anaplerosis). Cumulatively, these data suggest that productive infection requires the mitochondrial β-oxidation of palmitate which drives the TCA cycle and energy production. Additionally, infection causes a significant rise in the cellular oxygen consumption rate (ATP synthesis) that is ablated by etomoxir. The biochemical progression of the vaccinia life cycle is not impaired in the presence of TOFA, C75, or etomoxir, although the levels of viral DNA and proteins synthesized are somewhat diminished. However, by reversibly arresting infections at the onset of morphogenesis, and then monitoring virus production after release of the block, we determined that virion assembly is highly sensitive to TOFA and C75. Electron microscopic analysis of cells released into C75 revealed fragmented aggregates of viroplasm which failed to be enclosed by developing virion membranes. Taken together, these data indicate that vaccinia infection, and in particular virion assembly, relies on the synthesis and mitochondrial import of fatty acids, where their β-oxidation drives robust ATP production.
A Comparison of Physiological Signal Analysis Techniques and Classifiers for Automatic Emotional Evaluation of Audiovisual Contents

This work focuses on finding the most discriminatory or representative features that allow to classify commercials according to negative, neutral and positive effectiveness based on the Ace Score index. For this purpose, an experiment involving forty-seven participants was carried out. In this experiment electroencephalography (EEG), electrocardiography (ECG), Galvanic Skin Response (GSR) and respiration data were acquired while subjects were watching a 30-min audiovisual content. This content was composed by a submarine documentary and nine commercials (one of them the ad under evaluation). After the signal pre-processing, four sets of features were extracted from the physiological signals using different state-of-the-art metrics. These features computed in time and frequency domains are the inputs to several basic and advanced classifiers. An average of 89.76% of the instances was correctly classified according to the Ace Score index. The best results were obtained by a classifier consisting of a combination between AdaBoost and Random Forest with automatic selection of features. The selected features were those extracted from GSR and HRV signals. These results are promising in the audiovisual content evaluation field by means of physiological signal processing.
Parameter prediction for RIU-LBP based on PSO-BP algorithm

Local Binary Pattern (LBP) is one of the most popular feature extraction algorithms in face recognition with good performance. However, setting proper parameters for this algorithm is still an open question in pattern recognition. In most previous research, this problem is solved with experienced comparison tests. However, such tests might be constrained by certain database and application and thus lack of generalization ability. In this paper, based on our previous research on factor analysis of the Rotation Invariant Uniform LBP (RIU-LBP) feature, we propose a parameter prediction and selection method based on the Particle Swarm Optimizer-Back Propagation neural network (PSO-BP) for setting the dominant factor, i.e. the blocking number for RIU-LBP feature. Experimental results show that the proposed prediction method could effectively save the computation time in parameter selection.
Mechanisms of Wave Fractionation at Boundaries of High-Frequency Excitation in the Posterior Left Atrium of the Isolated Sheep Heart During Atrial Fibrillation

Background— High-frequency fractionated electrograms recorded during atrial fibrillation (AF) in the posterior left atrium (PLA) and elsewhere are being used as target sites for catheter ablation. We tested the hypothesis that highly periodic electric waves emerging from AF sources at or near the PLA give rise to the most fractionated activity in adjacent locations. Methods and Results— Sustained AF was induced in 8 isolated sheep hearts (0.5 &mgr;mol/L acetylcholine). Endocardial videoimaging (DI-4-ANEPPS) and electric mapping of the PLA enabled spatial characterization of dominant frequencies (DFs) and a regularity index (ratio of DF to total power). Regularity index showed that fractionation was lowest within the area with the maximal DF (DFmax domain; 0.19±0.02) and highest within a band of ≈3 mm (0.16±0.02; P=0.047) at boundaries with lower-frequency domains. The numbers of spatiotemporal periodic episodes (25.9±2.3) and rotors per experiment (1.9±0.7) were also highest within the DFmax domain. Most commonly, breakthrough waves at the PLA traveled toward the rest of the atria (76.8±8.1% outward versus 23.2±8.1% inward; P<0.01). In both experiments and simulations with an atrial ionic model, fractionation at DFmax boundaries was associated with increased beat-to-beat variability of conduction velocity and directionality with wavebreak formation. Conclusions— During stable AF, the PLA harbors regular, fast, and highly organized activity; the outer limit of the DFmax domain is the area where the most propagation pattern variability and fractionated activity occur. These new concepts introduce a new perspective in the clinical use of high-frequency fractionated electrograms to localize sources of AF precisely at the PLA and elsewhere.
Comment on the Theoretical and Empirical Evidence of Fundamental Indexing

In a recent article in this journal, Arnott and Hsu [Journal of Investment Management 6(1), 2008] proposed an equity pricing model in which a security’s current market price can help predict its future return. Their basic framework assumed that current prices consist of an underlying “fair value” and a mean-reverting “pricing error” that are not observable to investors. Their main finding was that securities with a higher price will tend to have below normal returns, thus a cap-weighted index that places more weight on high-priced securities will also tend to have below normal returns. This note describes how this result hinges on one very strong implicit assumption. In order to derive this result, Arnott and Hsu have assumed that investors have some reference point in which they know the stock’s fair value. This directly contradicts the notion that fair values are unobservable. I show that if one relaxes this assumption the result does not necessarily follow. In addition, I provide some empirical evidence suggesting that on average cap-weighted indexes have not experienced lower returns due to the systematic over-pricing of large cap securities, as Arnott and Hsu predict.
Testing for a Deterministic Trend When There is Evidence of Unit Root

Whilst the existence of a unit root implies that current shocks have permanent effects, in the long run, the simultaneous presence of a deterministic trend obliterates that consequence. As such, the long-run level of macroeconomic series depends upon the existence of a deterministic trend. This paper proposes a formal statistical procedure to distinguish between the null hypothesis of unit root and that of unit root with drift. Our procedure is asymptotically robust with regard to autocorrelation and takes into account a potential single structural break. Empirical results show that most of the macroeconomic time series originally analyzed by Nelson and Plosser (1982) are characterized by their containing both a deterministic and a stochastic trend.
Comparing user interaction with low and high fidelity prototypes of tabletop surfaces

This paper describes a comparative study between the usage of low-fidelity and a high-fidelity prototyping for the creation of multi-user multi-touch interfaces. The multi-touch interface presented in this paper allows users to collaboratively search for existing multimedia content, create new compositions with this content, and finally integrate it in a layout for presenting it. The study we conducted consists of a series of parallel user tests using both low-fidelity and high-fidelity prototypes to inform the design of the multi-touch interface. Based on a comparison of the two test sessions, we found that one should be cautious in generalising high-level user interactions from a low towards a high-fidelity prototype. However, the low-fidelity prototype approach presented proved to be very valuable to generate design ideas concerning both high and low-level user interactions on a multi-touch tabletop.
Bridging Theory and Practice in Cache Replacement

Much prior work has studied processor cache replacement policies, but a large gap remains between theory and practice. The optimal policy (MIN) requires unobtainable knowledge of the future, and prior theoretically-grounded policies use reference models that do not match real programs. Meanwhile, practical policies are designed empirically. Lacking a strong theoretical foundation, they do not make the best use of the information available to them. This paper bridges theory and practice. We propose that practical policies should replace lines based on their economic value added (EVA), the difference of their expected hits from the average. We use Markov decision processes to show that EVA is optimal under some reasonable simplifications. We present an inexpensive, practical implementation of EVA and evaluate it exhaustively over many cache sizes. EVA outperforms prior practical policies and saves area at isoperformance. These results show that formalizing cache replacement yields practical benefits.
Robust Differential Received Signal Strength-Based Localization

Source localization based on signal strength measurements has become very popular due to its practical simplicity. However, the severe nonlinearity and non-convexity make the related optimization problem mathematically difficult to solve, especially when the transmit power or the path-loss exponent (PLE) is unknown. Moreover, even if the PLE is known but not perfectly estimated or the anchor location information is not accurate, the constructed data model will become uncertain, making the problem again hard to solve. This paper particularly focuses on differential received signal strength (DRSS)-based localization with model uncertainties in case of unknown transmit power and PLE. A new whitened model for DRSS-based localization with unknown transmit powers is first presented and investigated. When assuming the PLE is known, we introduce two estimators based on an exact data model, an advanced best linear unbiased estimator (A-BLUE) and a Lagrangian estimator (LE), and then we present a robust semidefinite programming (SDP)-based estimator (RSDPE), which can cope with model uncertainties (imperfect PLE and inaccurate anchor location information). The three proposed estimators have their own advantages from different perspectives: the A-BLUE has the lowest complexity; the LE holds the best accuracy for a small measurement noise; and the RSDPE yields the best performance under a large measurement noise and possesses a very good robustness against model uncertainties. Finally, we propose a robust SDP-based block coordinate descent estimator (RSDP-BCDE) to deal with a completely unknown PLE and its performance converges to that of the RSDPE using a perfectly known PLE.
Harpoon selection: efficient selections for ungrouped content on large pen-based surfaces

In this paper, we present the Harpoon selection tool, a novel selection technique specifically designed for interactive whiteboards. The tool combines area cursors and crossing to perform complex selections amongst a large number of unsorted, ungrouped items. It is optimized for large-scale pen-based surfaces and works well in both dense and sparse surroundings. We describe a list of key features relevant to the design of the tool and provide a detailed description of both the mechanics as well as the feedback of the tool. The results of a user study are described and analyzed to confirm our design. The study shows that the Harpoon tool performs significantly faster than Tapping and Lassoing.
Extended Kalman filter under maximum correntropy criterion

As a nonlinear extension of Kalman filter, the extended Kalman filter (EKF) is also based on the minimum mean square error (MMSE) criterion. In general, the EKF performs well in Gaussian noises. But its performance may deteriorate substantially when the system is disturbed by heavy-tailed impulsive noises. In order to improve the robustness of EKF against impulsive noises, a new filter for nonlinear systems is proposed in this paper, namely the maximum correntropy extended Kalman filter (MCEKF), which adopts the maximum correntropy criterion (MCC) as the optimization criterion instead of using the MMSE. In MCEKF, the state mean and covariance matrix propagation equation are used to obtain a prior estimation of the state and covariance matrix, and then a fixed-point algorithm is used to update the posterior estimates. The robustness of the new filter is confirmed by simulation results.
National-Scale Estimates of Ground-Level PM2.5 Concentration in China Using Geographically Weighted Regression Based on 3 km Resolution MODIS AOD

High spatial resolution estimating of exposure to particulate matter 2.5 (PM2.5) is currently very limited in China. This study uses the newly released nationwide, hourly PM2.5 concentrations to create a nationwide, geographically weighted regression (GWR) model to estimate ground-level PM2.5 concentrations in China. A3 km resolution aerosol optical depth (AOD) product from MODIS is used as the primary predictor. Fire emissions detected by MODIS fire count were considered in the model development process. Additionally, meteorological features were used as covariates in the model to improve the estimation of ground-level PM2.5 concentrations. The model performed well and explained 81% of the daily PM2.5 concentration variations in model predictions, and the cross validations R2 is 0.79. The cross-validated root mean squared error (RMSE) of the model was 18.6 μg/m3.Annual PM2.5 concentrations retrieved by the MODIS 3 km AOD product indicated that most of the residential community areas exceeded the new annual Chinese PM2.5 National Standard level 2. Estimated high-resolution national-scale daily PM2.5 maps are useful to identify severe air pollution episodes and determine health risk assessments. These results suggest that this approach is useful for estimating large-scale ground-level PM2.5 distributions, especially for regions without PM monitoring sites.
Thesis Proposal Summary: Key Management Authentication and Non Repudiation for Information Transaction in Vehicular Cloud Environments

Vehicular Cloud Computing (VCC) is the latest technology in intelligent transport system. Vehicular cloud (VC) facilitates the customers to share underutilized resources by renting it to other users over the Internet. It aims to improve travelling beyond the boundaries of traditional transport systems. VCC has many advanced applications which will help society with minimum cost of investment and less maintenance. Security and privacy is very important issue for every VCC application. Research proposal highlights a cost effective, hassle free and secure communication between the cloud and moving vehicles. Security of VANET cloud covers the challenges, requirements, threats and authentication mechanisms which are very specific to connected high speed vehicles. The complexity of short range communication and location identities are important aspects in VCC security. We have considered Storage as a Service (SaaS) for our work. The security challenges are addressed with the help of cryptographic algorithms like Elliptical Curve Cryptography (ECC). For sharing secured data, access controlled with the help of Attribute Based Encryption (ABE). Implementation methodologies and performance measures are discussed for the proposed scheme.
Eighty Twenty Thinking in Traditional and Cloud Environment

: In traditional IT environment, there is a constant pressure of cost reduction. Unpredictable demands, rapid changes in technologies, complex IT portfolios and acquisitions, increased business competition, and revenue demands are the main factors which have compelled organizations to look for better alternatives. There is little automation and considerable amount of effort goes into resource provisioning of business processes. Approximately 80 percent of the average CIO’s time is spent on non-technical tasks such as cost, quality, and agility of service. Emergence of cloud computing is a boon for not only large organizations but SMBs also, considering agility, automation, on demand resources, scalability, low capital expense, and utility based billing model. Most of the organizations are inclined towards the use of cloud environment to be more strategic and to gain greater insight into business. Eighty Twenty Thinking has been applied in a variety of fields ranging from Economics, and Business, to Project Management and Software engineering to fine tune the practices in that field towards improved efficacy. Adoption of cloud models allows leaders and managers to devote relatively more time and effort to business strategy challenges and decision making. In this study, comparison of traditional and cloud environment has been done from the perspective of Eighty Twenty Thinking.
CONSISTENT SETS YIELD CONTRARY INFERENCES IN QUANTUM THEORY

In the consistent histories formulation of quantum theory, the probabilistic predictions and retrodictions made from observed data depend on the choice of a consistent set. We show that this freedom allows the formalism to retrodict contrary propositions which correspond to orthogonal commuting projections and which each have probability one. We also show that the formalism makes contrary probability one predictions when applied to Gell-Mann and Hartle{close_quote}s generalized time-neutral quantum mechanics. {copyright} {ital 1997} {ital The American Physical Society}
A New Game Model of Nodes' Strategies in P2P Network

The heterogeneity of P2P nodes' strategies has serious affect on the service performance of P2P network. Many incentive mechanisms based on game models of nodes' strategies are proposed to limit node's malicious actions. However, most of them don't take the diversity of nodes' types and the complexity of nodes' strategies into account, as well as the asymmetry of nodes' information. So the game models wouldn't imitate actual behavior and the incentive mechanisms based on them are not effective. This paper presents a new game model of nodes' strategies in P2P network, referring to the perspective of human society. The model classifies nodes' strategies to several sets according to their types, and analyzes the transfer conditions of different strategies. Finally, this paper simulates the evolution of the game model and the evolutionary results show similarity with real P2P network environment.