Miracle-dz/UniFAR-FTUs huggingface dataset:
Cortical Thickness Changes Correlate with Cognition Changes after Cognitive Training: Evidence from a Chinese Community Study

The aim of this study was to investigate whether changes in cortical thickness correlated with cognitive function changes in healthy older adults after receiving cognitive training interventions. Moreover, it also aimed to examine the differential impacts of a multi-domain and a single-domain cognitive training interventions. Longitudinal magnetic resonance imaging (MRI) scanning was performed on participants 65–75 years of age using the Siemens 3.0 T Trio Tim with the Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequence. The cortical thickness was determined using FreeSurfer Software. Cognitive functioning was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). There were significant group × time interaction effects on the left supramarginal, the left frontal pole cortical regions; and a marginal significant group × time interaction effects on visuospatial/constructional and delayed memory scores. In a multi-domain cognitive training group, a number of cortical region changes were significantly positively correlated with changes in attention, delayed memory, and the total score, but significantly negatively correlated with changes in immediate memory and language scores. In the single-domain cognitive training group, some cortical region changes were significantly positively associated with changes in immediate memory, delayed memory, and the total score, while they were significantly negatively associated with changes in visuospatial/constructional, language, and attention scores. Overall, multi-domain cognitive training offered more advantages in visuospatial/constructional, attention, and delayed memory abilities, while single-domain cognitive training benefited immediate memory ability more effectively. These findings suggest that healthy older adults benefit more from the multi-domain cognitive training than single-domain cognitive training. Cognitive training has impacted on cortical thickness changes in healthy elderly.
Designing User Interfaces for Hidden Markets

Market-based intelligent systems are becoming increasingly important in our everyday lives. However, when the goal of these systems is not the sale or purchase of items, traditional interfaces allowing users to specify bid or ask prices are no longer appropriate. Thus, there is a need for different kinds of user interfaces to interact with these “hidden markets”. In this paper, we present a novel user interface for one particular market-based system: a P2P backup application. The primary goal of the UI is to hide the market from the user as much as possible. Thus, the two main design challenges are how to provide current market information to the user without using prices or account balances, and how to elicit the user’s preferences with as little interaction as possible. The UI described in this paper is already implemented as part of a Microsoft research project on P2P backup systems and an internal alpha version of the software has been released. We are currently designing a usability study to evaluate the UI empirically.
The Bayesian Lasso Trevor Park

The Lasso estimate for linear regression parameters can be interpreted as a Bayesian posterior mode estimate when the regression parameters have independent Laplace (double-exponential) priors. Gibbs sampling from this posterior is possible using an expanded hierarchy with conjugate normal priors for the regression parameters and independent exponential priors on their variances. A connection with the inverse Gaussian distribution provides tractable full conditional distributions. The Bayesian Lasso provides interval estimates (Bayesian credible intervals) that can guide variable selection. Moreover, the structure of the hierarchical model provides both Bayesian and likelihood methods for selecting the Lasso parameter. Slight modifications lead to Bayesian versions of other Lasso-related estimation methods like bridge regression and a robust variant.
Optimizing motion estimation with linear programming and detail-preserving variational method

We propose a novel linear programming based method to estimate arbitrary motion from two images. The proposed method always finds the global optimal solution of the linearized motion estimation energy function and thus is much more robust than traditional motion estimation schemes. As well, the method estimates the occlusion map and motion field at the same time. To further reduce the complexity of even a complexity-reduced pure linear programming method we present a two-phase scheme for estimating the dense motion field. In the first step, we estimate a relatively sparse motion field for the edge pixels using a non-regular sampling scheme, based on the proposed linear programming method In the second step, we set out a detail-preserving variational method to upgrade the result into a dense motion field. The proposed scheme is much faster than a purely linear programming based dense motion estimation scheme. And, since we use a global optimization method - linear programming - in the first estimation step, the proposed two-phase scheme is also significantly more robust than a pure variational scheme.
Online Context-Dependent Clustering in Recommendations based on Exploration-Exploitation Algorithms

We investigate two context-dependent clustering techniques for content recommendation based on exploration-exploitation strategies in contextual multi-armed bandit settings. Our algorithms dynamically group users based on the items under consideration and, possibly, group items based on the similarity of the clusterings induced over the users. The resulting algorithm thus takes advantage of preference patterns in the data in a way akin to collaborative filtering methods. We provide an empirical analysis on extensive real-world datasets, showing scalability and increased prediction performance over state-of-the-art methods for clustering bandits. For one of the two algorithms we also give a regret analysis within a standard linear stochastic noise setting.
Online speaker change detection by combining BIC with microphone array beamforming

In this paper we consider the problem of detecting speaker changes in audio signals recorded by distant microphones. It is shown that the possibility to exploit the spatial separation of speakers more than makes up the degradation in detection accuracy due to the increased source-to-sensor distance compared to close-talking microphones. Speaker direction information is derived from the filter coefficients of an adaptive Filter-and-Sum Beamformer and is combined with BIC analysis. The experimental results reveal significant improvements compared to BIC-only change detection, be it with the distant or close-talking microphone.
'On a shiny night' : the representation of the English poacher, c.1830-1920

This thesis examines the representation of the English poacher from around the time of the reform to the Game Laws in 1831 to the ending of the First World War. Although a considerable body of work exists on nineteenth-century poaching, its representational aspects have yet to be fully explored. Moreover, existing studies have had little to say on poaching in the early years of the twentieth century. Set against the backdrop of the Edwardian Land Question the poacher, or more properly the idea of him, carried a far greater resonance than has been allowed for. Drawing on a wide range of literary and visual material, the work in hand offers a number of fresh perspectives on a significant figure in English culture and society. Chapter One considers the evolution of poacher representations from c.1830 to the next round of Game Law reform in 1880. The poacher of these years was largely defined by what he was against and made victim of. By the end of this period, however, representations of the poacher were clearly starting to show more positive aspects. The next two chapters focus on the years between 1880 and 1900. Chapter Two provides context by examining the growingly heated politics of the land-game nexus and the reasons for poaching’s recorded decline. Chapter Three considers the implications of these developments by looking more specifically towards poacher representations. Here we see how the poacher was viewed increasingly in terms of what he did, and the skills and values he embodied, as much as for the laws he opposed. Chapter Four takes us through to the end of our period – a time when the shooting and preservation of game reached their historic peaks and when debates about the land were at also their height. Focused on the production and consumption of ideas and images relating to the poacher, the central argument to be made is that during these years of profound social and economic change two clearly discernible developments occurred. First, the poacher came to occupy a more prominent place in English culture than hitherto had been the case; and second, he came to be represented in a number of more positive ways even as he remained on the wrong side of the law. This broadening representational palette served a surprising number of emotional and ideological needs and is suggestive of two further points. One, that the politics of the Game Laws - and thus of the poacher - carried greater importance than has previously been understood. And two, that existing accounts of ruralism’s role in shaping ideas of national identity in late-Victorian and Edwardian England have if anything been underplayed.
Alternative Measures of the Federal Reserve Banks' Cost of Equity Capital

The Monetary Control Act of 1980 requires the Federal Reserve System to provide payment services to depository institutions through the twelve Federal Reserve Banks at prices that fully reflect the costs a private-sector provider would incur, including a cost of equity capital (COE). Although Fama and French (1997) conclude that COE estimates are “woefully” and “unavoidably” imprecise, the Reserve Banks require such an estimate every year. We examine several COE estimates based on the Capital Asset Pricing Model (CAPM) and compare them using econometric and materiality criteria. Our results suggest that the benchmark CAPM applied to a large peer group of competing firms provides a COE estimate that is not clearly improved upon by using a narrow peer group, introducing additional factors into the model, or taking account of additional firm-level data, such as leverage and line-of-business concentration. Thus, a standard implementation of the benchmark CAPM provides a reasonable COE estimate, which is needed to impute costs and set prices for the Reserve Banks’ payments business.
Is the Internet useful for clinical practice?

BACKGROUND Internet use in dentistry is increasing. The authors surveyed dentists to determine how they are using the Internet to support patient care and how useful they perceive the Internet to be. MATERIALS AND METHODS The authors sent a 25-question survey to 455 subscribers to the Internet Dental Forum, an Internet discussion list. Participants completed the survey through a Web page or by e-mail during an 18-day period in December 1998. The survey included questions about when they began using the Internet and their motivations for doing so, their positive and negative experiences, where they use the Internet and why, their use of information resources--including electronic information resources--and demographics. RESULTS The authors received 314 surveys from 438 participants, a 72 percent response rate. Participants reported demographic characteristics similar to national averages and were highly computer-literate. Most considered the Internet essential for their practice and had increased their Internet use for professional reasons over time. Ninety-seven percent of respondents used the Internet at home, and 68 percent used it in the office. Only 5 percent used the Internet in the treatment area. The primary reason cited by participants for using the Internet was to keep up in general, followed by to answer patient-specific questions and to provide patient education. Reduction of professional isolation was one of the most frequently cited advantages of using the Internet. CONCLUSIONS The authors found that some dentists use the Internet to support clinical practice and that it helped dentists adopt new techniques for patient treatment and obtain information on new materials or products. CLINICAL IMPLICATIONS The Internet appears to support clinical practice mostly indirectly, by helping users keep up in general, rather than by answering specific clinical questions.
A Strategy to enable Prefix of Multicast VoD through dynamic buffer allocation

In this paper we have proposed a dynamic buffer allocation algorithm for the prefix, based on the popularity of the videos. More cache blocks are allocated for most popular videos and a few cache blocks are allocated for less popular videos. Buffer utilization is also maximized irrespective of the load on the Video-on-Demand system. Overload can lead the server getting slowed down. By storing the first few seconds of popular video clips, a multimedia local server can shield the users from the delay, throughput, and loss properties of the path between the local server and the central server. The key idea of controlled multicast is used to allow clients to share a segment of a video stream even when the requests arrive at different times. This dynamic buffer allocation algorithm is simulated and its performance is evaluated based on the buffer utilization by multimedia servers and average buffer allocation for the most popular videos. Our simulation results shows efficient utilization of network bandwidth and reduced hard disk utilization hence resulting in increase in the number of requests being served.
Performing Surgery: Commonalities with Performers Outside Medicine

This paper argues for the inclusion of surgery within the canon of performance science. The world of medicine presents rich, complex but relatively under-researched sites of performance. Performative aspects of clinical practice are overshadowed by a focus on the processes and outcomes of medical care, such as diagnostic accuracy and the results of treatment. The primacy of this “clinical” viewpoint—framed by clinical professionals as the application of medical knowledge—hides resonances with performance in other domains. Yet the language of performance is embedded in the culture of surgery—surgeons “perform” operations, work in an operating “theater” and use “instruments. ” This paper asks what might come into view if we take this performative language at face value and interrogate surgery from the perspective of performance science.
Numerical Performance Evaluation for OFDM Systems Affected by Phase Noise and Channel Estimation Errors

In this paper we present a numerical approach to evaluate the bit error rate (BER) and mutual information of OFDM links subject to phase noise, channel estimation error and frequency selective fading channels. Based on the analytical modeling of the correlation between channel estimates and received signals affected by phase noise, the statistical properties of the received signal can be numerically evaluated by means of a probability density function. The results illustrate that our analysis can approximate the simulative performance very accurately if the power delay profile of the fading channels and the phase noise properties are known. Hence, we present a useful numerical tool for OFDM performance analysis under the presence of phase noise that can be used for planning and design of mobile device architectures, without running extensive simulations.
Fuel Consumption and Effectiveness of Elimination of Energy-crop Willow Plantation

Abstract The objective of the paper was to determine fuel consumption on elimination of the energy willow plantation with current mechanical methods with the use of the machine research model. The paper covers investigations of four machine units. The lowest fuel consumption (142.6 l∙ha−1) with the use of Meri Crusher MJS-2.0) did not ensure effectiveness of operation of this unit. Efficiency of elimination of the plantation in this case is only 36.4%. On the other hand, the highest consumption of diesel oil (776.4 l∙ha−1) was reported for FAO FAR model FV 4088, and the effectiveness of elimination was not satisfactory and it was 57.0%. The highest effectiveness of elimination of the plantation was reported for the model of a new machine. Fuel consumption in this case was 535.7 l∙ha−1 and the willow plantation elimination effectiveness was the highest and it amounted to 94.8%.
Learning stateful models for network honeypots

Attacks like call fraud and identity theft often involve sophisticated stateful attack patterns which, on top of normal communication, try to harm systems on a higher semantic level than usual attack scenarios. To detect these kind of threats via specially deployed honeypots, at least a minimal understanding of the inherent state machine of a specific service is needed to lure potential attackers and to keep a communication for a sufficiently large number of steps. To this end we propose PRISMA, a method for protocol inspection and state machine analysis, which infers a functional state machine and message format of a protocol from network traffic alone. We apply our method to three real-life network traces ranging from 10,000 up to 2 million messages of both binary and textual protocols. We show that PRISMA is capable of simulating complete and correct sessions based on the learned models. A case study on malware traffic reveals the different states of the execution, rendering PRISMA a valuable tool for malware analysis.
Nonsymbolic Text Representation

We introduce the first generic text representation model that is completely nonsymbolic, i.e., it does not require the availability of a segmentation or tokenization method that attempts to identify words or other symbolic units in text. This applies to training the parameters of the model on a training corpus as well as to applying it when computing the representation of a new text. We show that our model performs better than prior work on an information extraction and a text denoising task.
Learning Semantic Classes for Word Sense Disambiguation

Word Sense Disambiguation suffers from a long-standing problem of knowledge acquisition bottleneck. Although state of the art supervised systems report good accuracies for selected words, they have not been shown to be promising in terms of scalability. In this paper, we present an approach for learning coarser and more general set of concepts from a sense tagged corpus, in order to alleviate the knowledge acquisition bottleneck. We show that these general concepts can be transformed to fine grained word senses using simple heuristics, and applying the technique for recent SENSEVAL data sets shows that our approach can yield state of the art performance.
Distributed Proxy: A Design Pattern for Distributed Object Communication

This paper presents the Distributed Proxy pattern, a design pattern for distributed object communication. The Distributed Proxy pattern decouples distributed object communication from object specific functionalities. It further decouples logical communication from physical communication. The Distributed Proxy pattern enforces an incremental development process, encapsulates the underlying distribution mechanisms, and offers location transparency. 1 Intent The Distributed Proxy pattern decouples the communication between distributed objects by isolating distributionspecific issues from object functionality. Moreover, distributed communication is further decoupled into logical communication and physical communication parts. 2 Motivation An example motivates for the problems and respective forces involved in distributed object communication. 2.1 Example A distributed agenda application has several users which manipulate agenda items, either private (appointments) or shared (meetings). A meeting requires the participation of at least two users. When an agenda session starts, it receives an agenda manager reference from which the agenda user informationcan be accessed. It is simple to design a solution ignoring distribution issues. The Booch[1] class diagram in Figure 1 shows the functionalities design of the agenda application, where distribution issues are ignored. Enriching this design with distribution is complex. For example we must consider different address spaces. In terms of our agenda application this means, that operation getUser in Agenda Manager should return to the remote Agenda Session a User object across the network. Another source of complexity is need to implement distributed communication. For instance, the communication between Agenda Session andAgenda Manager is implemented using sockets. From a user’s perspective, however, all distribution issues should be hidden. They just want to manipulate agenda items. Item Meeting Appointment A 0+
Language modeling for multi-domain speech-driven text retrieval

We report experimental results associated with speech-driven text retrieval, which facilitates retrieving information in multiple domains with spoken queries. Since users speak contents related to a target collection, we produce language models used for speech recognition based on the target collection, so as to improve both the recognition and retrieval accuracy. Experiments using existing test collections combined with dictated queries showed the effectiveness of our method.
Predicting the Usage Intention of Social Network Games: An Intrinsic-Extrinsic Motivation Theory Perspective

Social network sites (SNSs) are new communication channels with which people can share information. The main functions of SNSs, such as MySpace, Facebook, and Orkut, consist of displaying a userâ€™s social contacts, enabling people to view each otherâ€™s social networks and search for common friends or interesting content. Social networks are also connected to gaming and it is quickly becoming one of the most popular categories of applications on SNSs. The goal of this project is to gain insight into the factors that affect user intention to use a social network game. The study uses an extended technology acceptance model and focuses on combining personal innovativeness, personal involvement, intrinsic motivation and extrinsic motivation to explain usage intentions for social network games. The proposed model was tested with data collected from potential users of a social network game. A multiple regression analysis and MANOVA analysis were then conducted to identify the key causal relationships. It is expected that personal innovativeness and personal involvement will have positive effects on intrinsic and extrinsic motivation and ultimately influence usage intentions with regard to social network games.
Finite element emulation-based solver for electromagnetic computations

Electromagnetic (EM) computations are the cornerstone in the design process of several real-world applications, such as radar systems, satellites, and cell-phones. Unfortunately, these computations are mainly based on numerical techniques that require solving millions of linear equations simultaneously. Software-based solvers do not scale well as the number of equations-to-solve increases. FPGA solver implementations were used to speed up the process. However, using emulation technology is more appealing as emulators overcome the FPGA memory and area constraints. In this paper, we present a scalable design to accelerate the finite element solver of an EM simulator on a hardware emulation platform. Experimental results show that our optimized solver achieves 101.05x speed-up over the same pure software implementation on MATLAB and 35.29x over the best iterative software solver from ALGLIB C++ package in case of solving 2,002,000 equations.