Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparisons of men with full or partial eating disorders, men without eating disorders, and women with eating disorders in the community.

OBJECTIVE The authors compared 62 men who met all or most of the DSM-III-R criteria for eating disorders with 212 women who had similar eating disorders and 3,769 men who had no eating disorders on a wide variety of clinical and historical variables. METHOD The groups of subjects were derived from a community epidemiologic survey performed in the province of Ontario that used the World Health Organization's Composite International Diagnostic Interview. RESULTS Men with eating disorders were very similar to women with eating disorders on most variables. Men with eating disorders showed higher rates of psychiatric comorbidity and more psychosocial morbidity than men without eating disorders. CONCLUSIONS These results confirm the clinical similarities between men with eating disorders and women with eating disorders. They also reveal that both groups suffer similar psychosocial morbidity. Men with eating disorders show a wide range of differences from men without eating disorders; the extent to which these differences are effects of the illness or possible risk factors for the occurrence of these illnesses in men is not clear.
The Effects of Knee Joint Pain and Disorders on Knee Extension Strength and Walking Ability in the Female Elderly

This study examines the differences in leg strength and walking ability among groups with different knee problems. The participants were 328 elderly females (60 - 94 years old; mean age 76.1 years; SD = 6.2) who were classified into three groups: those without knee pain or a knee disorder, those with knee pain, and those with a knee disorder. The subjects took knee extension strength and 12 meter maximum effort walk tests. Knee extension strength was significantly lower in the groups with knee pain and a knee disorder than in the group without pain or a knee disorder. Walking speed was significantly slower in the group with a knee disorder than in the other two groups. In conclusion, the female elderly with knee pain or a knee disorder are inferior in knee extension strength and walking ability. In addition, the elderly with a knee disorder are inferior in walking ability to the elderly with knee pain.
Connecting soil to the cloud: A wireless underground sensor network testbed

In this demo, a novel underground communication system and an online underground sensor network testbed is demonstrated. The underground communication system, developed in the Cyber-physical Networking (CPN) Laboratory at the University of Nebraska-Lincoln, includes an underground antenna that is tailored to mitigate the adverse effects of soil on underground communication. An online connection is established with the CPN underground sensor network testbed that is located at Clay Center, Nebraska. The underground sensor network testbed consists of a network of underground communication systems equipped with soil moisture sensors and a mobile data harvesting unit equipped with cellular communication capabilities. Real-time soil moisture data delivery from Nebraska to Korea is demonstrated.
Oceansense: monitoring the sea with wireless sensor networks

In this project, we explore the possibility of deploying networked sensors on the Ocean's surface, to monitor depth and temperature, as well as other valuable environmental parameters. Sea depth monitoring is a critical task to ensure the safe operation of harbors. Traditional schemes largely rely on labor-intensive work and expensive hardware. We present a new solution for measuring the sea depth with Restricted Floating Sensors. To address the problem of node localization on the changeable sea environment, we propose Perpendicular Intersection (PI), a novel mobile-assisted localization scheme. In the OceanSense project, we propose the concept of passive diagnosis as well as the PAD approach which is both lightweight and adaptive to network dynamics. The OceanSense system has been working for over 16 months and provides large amounts of valuable data about the sea.
An Improved Apriori-Based Personal Recommendation Algorithm for E-commerce

In order to improve the quality of the recommended result, the personalized recommendation system should identify the similarity degree of visitor's accessing behavior so as to predict customer's interests. The key technology is to calculate the similar distance among different objects over either all or only a subset of the dimensions. This paper, first of all, analyses the commonly-used methods and points out their shortages, and then proposes an improved apriori-based personal recommendation algorithm for e-commerce. This algorithm considers overall the minable data source, users' similarity metric and k-support bound to get the data of those access Web pages, construct a matrix model having relatively high purchasing power about customer behavior, get the similar access behavior over the all or partial property space with high efficiency, help the customer find out the merchandise he wishes to buy through the mine of the similar pattern character between latent buyer and high buyer, promote customer satisfaction and truly promote the sale achievements for the enterprise.
Location Privacy Pricing and Motivation

This paper examines the results of our European-wide study on the price of location privacy of individuals using mobile phones. There were 1200 active participants from five EU countries in our experiment. We used tools from experimental psychology and economics to assess the value that users attach to their location data. This paper extends the results that are provided in [D. Cvrcek et al., 2006]. Our main focus in this paper was the motivation of the participants to take part in the experiment and further investigation of their bids. This paper presents a more detailed view of the motivation and a correlations between the motivation and the bids.
Pertinence Generation in Radiological Diagnosis: Spreading Activation and the Nature of Expertise

An empirical study of human expert reasoning processes is presented. Its purpose is to test a model of how a human expert's cognitive system learns to detect, and does detect, pertinent data and hypotheses. This process is called pertinence generation. The model is based on the phenomenon of spreading activation within semantic networks. Twenty-two radiologists were asked to produce diagnoses from two very difficult X-ray films. As the model predicted, pertinence increased with experience and with semantic network integration. However, the experts whose daily work involved explicit reasoning were able, in addition, to go beyond and to generate more pertinence. The results suggest that two qualitatively different kinds of expertise, basic and super, should be distinguished. A reinterpretation of the results of Lesgold et al. (1988) is proposed, suggesting that apparent nonmonotonicities in performance are not representative of common radiological expertise acquisition but result from the inclusion of basic and super expertise on the same curve.
RF Isolated Real-Time Multipath Testbed for Performance Analysis of WLANs

Real-time performance evaluation of WLANs is an extremely challenging topic. The major drawback of real-time performance analysis in actual network installations is a lack of repeatability due to uncontrollable interference and propagation complexities, which are caused by unpredictable variations in the propagation channel. This stresses a need for an RF test system that provides isolation from interfering sources while simulating a real-time channel, thereby creating a realistic and controllable radio propagation test environment. In this paper we introduce a novel testbed for real-time laboratory performance evaluation of WLANs utilizing an RF isolated test system (Azimuthtrade Systems 801W) for isolation from interference and a real-time multipath channel simulator (Elektrobit PROPSimtradeC8) for channel emulation. A software protocol analyzer (WildPackets Airopeek NX) is used to capture data packets in the testbed. The relationship between the throughput and received power, under controlled propagation and interference conditions, is analyzed. We present practical models describing the throughput/power relationship for multirate IEEE 802.11b/g devices in different propagation conditions.
Performance evaluation of downlink MU-MIMO transmission based on mobile WiMAX system in computer simulations and field experiments

In this paper, transmission performance for downlink MU-MIMO (Multiuser Multiple-Input Multiple-Output) systems with computer simulation and field experiment are described. The downlink MU-MIMO system is constructed as a transmitter with 6 antennas and receivers with 2 antennas, and the maximum number of users(receivers) is 3. In computer simulation, MU-MIMO transmission system can be realized by using the BD (Block Diagonalization) algorithm, and each user can receive signals without any signal interferences between the other users. BER (Bit Error Rate) performance and channel capacity according to modulation schemes and the number of streams are simulated in spatially uncorrelated and correlated multipath fading environment. In field experiment, downlink throughput on UDP layer are measured on the mobile WiMAX system with Matrix A mode and Matrix B mode developed at Azumino City in Japan. Compared with the simulated and experimented results, the measured maximum throughput performance in downlink has almost the same performance with the simulated throughput. It is confirmed that the experimental mobile WiMAX system for MU-MIMO transmission is actually performed for increasing the total channel capacity of the system.
SELECTING APPROPRIATE FEATURES FOR DETECTING BUILDINGS AND BUILDING PARTS

The paper addresses the problem of feature selection during classification of image regions within the context of interpreting images showing highly structured objects such as buildings. We present a feature selection scheme that is connected with the classification framework Adaboost, cf. (Schapire and Singer, 1999). We constricted our weak learners on threshold classification on a single feature. Our experiments showed that the classification with Adaboost is based on relatively small subsets of features. Thus, we are able to find sets of appropriate features. We present our results on manually annotated and automatically segmented regions from facade images of the eTRIMS data base, where our focus were the object classes facade, roof, windows and window panes.
Distributed atomic polarizabilities from electron density. 1. Motivations and Theory

In this paper, the distributed atomic polarizabilities computed within the Quantum Theory of Atoms in Molecules are discussed. Methods are presented to calculate and visualize symmetric atomic polarizability tensors, with proved additivity to molecular polarizabilities. The analysis of QTAIM bond polarizabilities is also presented for some simple molecules and potential applications in material science are anticipated. Introduction The response of electron density to an electric field is fundamental to understand, among the others, the behavior of molecules in chemical reactions, the solvation properties, the recognition processes and spectroscopic properties. As a matter of facts, the (hyper)polarizabilities tensors determine the soft ("orbital controlled") assembly and reactivity of molecules, the intensities of Raman scattering and many other optical processes. For this reason, measuring or calculating the molecular (hyper)polarizabilities is of fundamental importance, especially when dealing with material science. If the material is a crystalline solid, the properties are regulated by the electric susceptibilities, which are related, for molecular based materials, to the molecular (hyper)polarizabilities tensors through lattice summation. Quantum chemistry allows to calculate (hyper)polarizabilities of molecules and crystals, by derivation of the electronic energy E with respect to the electric field F. For example, the first order polarizability tensor is defined as
A Unified Economic Model of Standard Diffusion: The Impact of Standardization Cost, Network Effects, and Network Topology

This paper is motivated by the following question: What drives the diffusion of a communication standard and what results can we expect? Past literature provides many instructive but mostly unrelated answers. Frequent findings are startup problems, penguin effects, and tendencies toward monopoly. But substantial problems in applying the models to concrete standardization problems reveal that the dynamics are probably more complex. Not all networks are ultimately conquered by a single standard once it has attracted a certain number of users. And not all diffusion results are either complete or no standardization. We address the question of the conditions of particular diffusion behaviors by developing a formal standardization model that captures all fragmented phenomena in a unified approach. Drawing from findings of other research, we incorporate the structure of the underlying user network as an important determinant for diffusion behaviors. The approach allows us to disclose varying conditions that generate frequently observed standardization behaviors as special parameter constellations of the model. Using equilibrium analysis and computer simulations we identify a standardization gap that reveals the magnitude of available standardization gains for individuals and the network as a whole. The analysis shows that network topology and density have a strong impact on standard diffusion and that the renowned tendency toward monopoly is far less common. We also report how the model can be used to solve corporate standardization problems.
Comparative study on performance assessment of hospitals in various regions of China through comprehensive variable DEA and traditional DEA

This article has employed herein comprehensive variable DEA and traditional DEA to conduct comparative study of performance assessment of hospitals in various regions of China in 2007 to reflect the validity of DEA for hospitals of various regions. Studies indicate that comprehensive variable DEA has integrated advantages of traditional DEA and also made up for intrinsic disadvantages and defects of DEA itself, and thus enhanced the precision of and differentiating capacity of efficiency.
Periodic Points of Holomorphic Maps via Lefschetz Numbers

In this paper we study the set of periods of holomorphic maps on compact manifolds, using the periodic Lefschetz numbers introduced in D] and Ll], which can be computed from the homology class of the map. We show that these numbers contain information about the existence of periodic points of a given period and, if we assume the map to be transversal then they give us the exact number of such periodic orbits. We apply this result to the complex projective space of dimension n and to some special type of Hopf surfaces, partially characterizing their set of periods. In the rst case we also show that any holomorphic map of C P (n) of degree greater than one has innnitely many distinct periodic orbits, hence generalizing a theorem of FS]. We then characterize the set of periods of a holomorphic map on the Riemann sphere, hence giving an alternative proof of Baker's theorem in Ba].
Generalized cross‐validation as a stopping rule for the Richardson‐Lucy algorithm

The Richardson‐Lucy (R‐L) algorithm has been widely used to restore degraded astronomical images. This algorithm is nothing more than the expectation‐maximization (EM) algorithm applied to Poisson data. The R‐L method is iterative in nature and converges to a (possibly local) maximum of the likelihood function. Unfortunately, because of the ill‐conditioned nature of the problem, this maximum likelihood estimate may actually be a very poor restoration. One way to prevent degradation of the restoration is to stop the iteration before it reaches convergence. A number of methods have been proposed for determining the optimal stopping point‐the point that provides the best trade‐off between restoring the image and amplifying the noise. Cross‐validation (CV) has recently been proposed as an advantageous method for determining the optimal stopping point. We propose a different form of CV based on generalized cross‐validation (GCV) that overcomes some of the difficulties of CV. We derive a GCV‐based criterion for the R‐L algorithm that can be efficiently evaluated at each iteration. We present examples displaying the power of the stopping rule and discuss the abilities and shortcomings of the method.
A High-Precision Approach to Detecting Hedges and their Scopes

We extend our prior work on speculative sentence recognition and speculation scope detection in biomedical text to the CoNLL-2010 Shared Task on Hedge Detection. In our participation, we sought to assess the extensibility and portability of our prior work, which relies on linguistic categorization and weighting of hedging cues and on syntactic patterns in which these cues play a role. For Task 1B, we tuned our categorization and weighting scheme to recognize hedging in biological text. By accommodating a small number of vagueness quantifiers, we were able to extend our methodology to detecting vague sentences in Wikipedia articles. We exploited constituent parse trees in addition to syntactic dependency relations in resolving hedging scope. Our results are competitive with those of closed-domain trained systems and demonstrate that our high-precision oriented methodology is extensible and portable.
Motion planning for the discretely actuated steerable cannula

Discretely actuated steerable cannula is a multi-degree-of-freedom probe that could potentially be used to deliver therapeutic and diagnostic tools to the appropriate location through its hollow inner core. The cannula is composed of straight segments connected by shape memory alloy actuators (SMA) that generate local bending at discrete locations along the probe length. We take advantage of the redundancy of the cannula and apply configuration control approach to develop motion planning algorithms to steer the cannula to a desired location while avoiding obstacles. The maximum bending angle that can be achieved by the SMA actuator depends on the physical and mechanical properties of the SMA actuator, the initial strain of the SMA before actuation and the mechanical properties of the soft-tissue. Hence, we also investigate the maximum bending angle that can be achieved in motion planning. We demonstrate that the planner can successfully find trajectories in the presence of moving obstacles while avoiding the joint limits. Therefore, the planner can be used to steer the cannula under image guidance.
On the numerical Continuation of Isolas of Equilibria

We present a numerical strategy to compute one-parameter families of isolas of equilibrium solutions in ODEs. Isolas are solution branches closed in parameter space. Numerical continuation is required to compute one single isola since it contains at least one unstable segment. We show how to use pseudo-arclength predictor-corrector schemes in order to follow an entire isola in parameter space, as an individual object, by posing a suitable algebraic problem. We continue isolas of equilibria in a two-dimensional dynamical system, the so-called continuous stirred tank reactor model, and also in a three-dimensional model related to plasma physics. We then construct a toy model and follow a family of isolas past a fold and illustrate how to initiate the computation close to a formation center, using approximate ellipses in a model inspired by the Van der Pol equation. We also show how to introduce node adaptivity in the discretization of the isola, so as to concentrate nodes in region with higher curvature. We conclude by commenting on the extension of the proposed numerical strategy to the case of isolas of periodic orbits.
Long-Term Changes of the Wildland-Urban Interface in the Polish Carpathians

The Wildland–Urban Interface (WUI) is the area where houses and wildland vegetation meet or intermingle, which causes many environmental problems. The current WUI is widespread in many regions, but it is unclear how the WUI evolved, especially in regions where both houses and forest cover have increased. Here we compared WUI change in the Polish Carpathians for 1860 and 2013 in two study areas with different land use history. Our western study area experienced gradual forest increase and housing growth over time, while the eastern study area was subject to a shock due to post-war resettlements, which triggered rapid reforestation. We found that in both study areas WUI extent increased from 1860 to 2013 (41.3 to 54.6%, and 12.2 to 33.3%, in the west and east, respectively). However the causes of WUI growth were very different. In the western study area new houses were the main cause for new WUI, while in the eastern study area forest cover increase was more important. Our results highlight that regions with similar current WUI cover have evolved very differently, and that the WUI has grown rapidly and is widespread in the Polish Carpathians.
Discovering Best Teams for Data Leak-Aware Crowdsourcing in Social Networks

Crowdsourcing is emerging as a powerful paradigm to help perform a wide range of tedious tasks in various enterprise applications. As such applications become more complex, crowdsourcing systems often require the collaboration of several experts connected through professional/social networks and organized in various teams. For instance, a well-known car manufacturer asked fans to contribute ideas for the kinds of technologies that should be incorporated into one of its cars. For that purpose, fans needed to collaborate and form teams competing with each others to come up with the best ideas. However, once teams are formed, each one would like to provide the best solution and treat that solution as a “trade secret,” hence preventing any data leak to its competitors (i.e., the other teams). In this article, we propose a data leak--aware crowdsourcing system called SocialCrowd. We introduce a clustering algorithm that uses social relationships between crowd workers to discover all possible teams while avoiding interteam data leakage. We also define a ranking mechanism to select the “best” team configurations. Our mechanism is based on the semiring approach defined in the area of soft constraints programming. Finally, we present experiments to assess the efficiency of the proposed approach.
USE OF MIXTURE OF DISTRIBUTIONS FOR THE ERROR IN REGRESSION MODELS FOR LIFETIME DATA

Summary In this paper we present a Bayesian analysis of location-scale regression models assuming standard lifetime distributions and an additional error term with a mixture of normal distributions. Considering a censored lifetime data set, we use Gibbs sampling with Metropolis-Hastings algorithm to get Bayesian quantities of interest. The proposed regression model gives a great flexibility to fit lifetime data as we see in an example.