Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward the conceptualization and measurement of caregiver burden among Pueblo Indian family caregivers.

PURPOSE The purpose of this study was to evaluate burden experienced by a group of American Indian primary family caregivers and to determine if caregiver burden is a multi-dimensional concept. DESIGN AND METHODS This analysis is based on the results of a survey questionnaire administered to 169 Pueblo primary family caregivers in New Mexico. RESULTS Analysis of the items composing the Caregiver Burden scale indicated that caregiver burden is multidimensional and consists of several types of burden. Caregiver burden, as identified in this sample, is composed of four dimensions: role conflict, negative feelings, lack of caregiver efficacy, and guilt. Investigations of caregiver burden should consider the multidimensionality of this experience and evaluate burden accordingly. IMPLICATIONS By identifying the specific type of burden that a caregiver experiences, interventions can be targeted more accurately to support family caregiving.
Spatial Separation of Speech Signals Using Continuously-Variable Masks Estimated From Comparisons of Zero Crossings

This paper describes an algorithm that achieves noise robustness in speech recognition by reconstructing the desired signal from a mixture of two signals using continuously-variable masks. In contrast to current methods which use binary masks, this approach estimates the relative contribution of the desired source in a mixture of sources and reconstructs the desired signal in proportion to its estimated contribution to each time-frequency segment. Estimation of the continuously-variable masks is based on the relationship between the relative intensity of each source and the interaural time difference (ITD). Estimation of the ITD is accomplished using zero-crossing-based methods. It is shown that the use of zero-crossing approaches to estimate ITDs and continuously-variable masks provide better speech recognition accuracy than cross-correlation-based approaches to ITD estimation and binary masks
Scale invariant line matching on the sphere

This paper proposes a novel approach of line matching across images captured by different types of cameras, from perspective to omnidirectional ones. Based on the spherical mapping, this method utilizes spherical SIFT point features to boost line matching and searches line correspondences using an affine invariant measure of similarity. It permits to unify the commonest cameras and to process heterogeneous images with the least distortion of visual information.
TrekWizard: a GIS interface that adds value to a small-screen GPS

We present a description and an evaluation of the interface for the TrekWizard, a tool that adds value to raw location information available to trekkers from the GPS system. The interface has a novel component for providing distance and time readouts, including ETA (Estimated Time of Arrival) and ETT (Estimated Time to Travel) information.
Engineering Solution of a CAC Mechanism for Voice Traffic over IP Networks

The paper deals with the admissibility of voice traffic flows with QoS requirement in terms of packet delay and packet loss. A two-stage CAC approach based on the rate envelope multiplexing principle along with a simplified reference model is proposed. One concrete realization of such a CAC mechanism that utilizes the Chernoff bound based effective bandwidth and the recently stated negligib le jitter conjecture is constructed and analyzed. The admission rule is discussed and explored by considering both, an analytical model as well as realistic simulation scenarios .
Visual Tracking Using High-Order Particle Filtering

In this letter, we extend the first-order Markov chain model commonly used in visual tracking and present a novel framework of visual tracking using high-order Monte Carlo Markov chain. By using graphical models to obtain conditional independence properties, we derive a general expression for the posterior density function of an m th-order hidden Markov model. We subsequently use Sequential Importance Sampling (SIS) to estimate the posterior density and obtain the high-order particle filtering algorithm for visual object tracking. Experimental results demonstrate that the performance of our proposed algorithm is superior to traditional first-order particle filtering (i.e., particle filtering derived based on first-order Markov chain).
Dynamic reconfiguration for management of radiation-induced faults in FPGAs

Summary form only given. We describe novel methods of exploiting the partial, dynamic reconfiguration capabilities of Xilinx Virtex 1000 FPGAs to manage transient faults due to radiation in space environments. The on-orbit fault detection scheme uses a radiation-hardened reconfiguration controller to continuously monitor the configuration bit streams of 9 Virtex FPGAs and to correct errors by partial, dynamic reconfiguration of the FPGAs while they continue to execute. To study single event upset (SEU) impact on our signal processing applications, we use a novel fault injection technique to corrupt configuration bits, thereby simulating SEU faults. By using dynamic reconfiguration, we can run the corrupted designs directly on the FPGA hardware, giving many orders of magnitude speed-up over purely software techniques. The fault injection method has been validated against proton beam testing, showing 97.6% agreement. Our work highlights the benefits of dynamic reconfiguration for space-based reconfigurable computing.
Neuropsychological Outcome following Cranio-spinal Radiation in Medulloblastoma Patients: A Longitudinal Analysis of Predictors

Medulloblastoma is the most common malignant central nervous system (CNS) tumor in childhood. The cranio-spinal radiation (CSR) required to treat this disease results in long-term cognitive and neurologic impairments. Medulloblastoma was recently categorized into four genetic subgroups (WNT, SHH, Group 3, and Group 4). This study examined neuropsychological and intellectual functioning in 91 medulloblastoma patients (41 Group 4; 20 Group 3; 18 SHH; 12 WNT) following treatment, and examined the impact of several medical, treatment and demographic factors on functioning over time. Longitudinal growth curve analyses revealed hydrocephalus most clearly predisposes to poor neuropsychological functioning. Results also indicate medulloblastoma subgroups have heterogeneous intellectual outcomes following treatment. All subgroups experience intellectual declines following treatment; however, comparing between subgroups revealed Group 4 performs most poorly, and Group 3 has the best overall intellectual outcome. Lastly, qualitative analyses suggest treatment with a larger CSR dose may contribute to poor intellectual functioning.
Semantic exploration of lecture videos

E-Learning is rapidly changing the way that universities and corporations offer education and training. In recent years, the acquisition and distribution of rich media content has been largely automated [1], However, existing applications are functionally and visually static and remain organized around the delivery media, rather than the knowledge representation and learning tasks of the student. The innovative approach of this system is the extraction of semantically meaningful structures in the lecture combined with text analysis to support task based queries. In this demonstration we will show this combination of pedagogical and content descriptions leads to novel forms of visualization and exploration of course lectures. System capabilities and semantic analysis technologies applied to lecture content obtained from a graduate level SMA (Singapore-MIT Alliance) distance education course will also be presented.
The impact of consumer acculturation on ethnic Turkish-Dutch consumers in the Netherlands

Non-Western immigrants are a growing segment in European societies and represent a huge potential to marketers. From a marketing perspective, understanding the similarities and differences between the culture of the host and immigrant communities is important. It is necessary information for targeting these audiences effectively and also for developing products and services that fit their needs and values. This study is particularly interested in the impact of acculturation on Domestic (Turkish) and Mainstream (Dutch) consumption of food and entertainment. This study seeks to address the impact of bidimensional acculturation on consumer behaviour by determining relevant acculturation life domains i.e. private and public life, ethnic identity, media usage and culture value priorities. Two stages of quantitative data analysis were designed. An Exploratory Factor Analysis (EFA) was applied to provide data reduction and simplification. EFA has reduced the variables considered in this study to a smaller set of factors in which the implied underlying data structure is identified and defined. Part two involved a Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM), based on 530 usable questionnaires. The proposed research model was assessed for validity and reliability and the associated relationship paths quantified. Turkish Language (TL) emerged as the most substantial predictor of Domestic Consumer Behaviour, followed by Attachment Turkish Culture and Family Ties (ATCFT) and Turkish Identification Social Interaction (TSI). Turkish Friends and Peers have a substantial impact on ATCFT. Dutch Acculturation Social Interactions (DSI) and Dutch Acculturation Family Ties (DFT) emerged as predictors of Dutch Consumer Behaviour. Furthermore, Dutch Acculturation Media & Language is mediated by DSI on Mainstream consumption. One key finding is that Turkish Social Interactions have a positive and significant impact on Mainstream consumption. Contrary, Attachment Turkish Culture & Family Ties has a negative impact. This study’s contribution to knowledge is the impact acculturation life domains by exploring the bidimensional effects on consumption of products aligned with heritage and host cultures. This research highlights the importance of considering the distinction between life domains.
Ergodic Capacity of Cognitive Radio Under Imperfect Channel-State Information

A spectrum-sharing communication system where the secondary user is aware of the instantaneous channel-state information (CSI) of the secondary link but knows only the statistics and an estimated version of the secondary transmitter-primary receiver link is investigated. The optimum power profile and the ergodic capacity of the secondary link are derived for general fading channels [with a continuous probability density function (pdf)] under the average and peak transmit power constraints and with respect to the following two different interference constraints: 1) an interference outage constraint and 2) a signal-to-interference outage constraint. When applied to Rayleigh fading channels, our results show, for example, that the interference constraint is harmful at the high-power regime, because the capacity does not increase with the power, whereas at the low-power regime, it has a marginal impact and no-interference performance, which corresponds to the ergodic capacity under average or peak transmit power constraint in the absence of the primary user, may be achieved.
CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments

UNLABELLED CompleteMOTIFs (cMOTIFs) is an integrated web tool developed to facilitate systematic discovery of overrepresented transcription factor binding motifs from high-throughput chromatin immunoprecipitation experiments. Comprehensive annotations and Boolean logic operations on multiple peak locations enable users to focus on genomic regions of interest for de novo motif discovery using tools such as MEME, Weeder and ChIPMunk. The pipeline incorporates a scanning tool for known motifs from TRANSFAC and JASPAR databases, and performs an enrichment test using local or precalculated background models that significantly improve the motif scanning result. Furthermore, using the cMOTIFs pipeline, we demonstrated that multiple transcription factors could cooperatively bind to the upstream of important stem cell differentiation regulators. AVAILABILITY http://cmotifs.tchlab. org.
Effects of oxygen availability on maximum aerobic performance in Mus musculus selected for basal metabolic rate or aerobic capacity

SUMMARY Maximum aerobic metabolism cannot increase indefinitely in response to demands for ATP production and, therefore, must be constrained by one (or many) of the steps of the oxygen transport and utilization pathways. To elucidate those constraints we compared peak metabolic rate elicited by running () in hypoxia (14% O2), normoxia (21% O2) and hyperoxia (30% O2) of laboratory mice divergently selected for low and high basal metabolic rate (L-BMR and H-BMR, respectively), mice selected for maximum metabolic rate elicited by swimming () and mice from unselected lines. In all line types was lowest in hypoxia, intermediate in normoxia and highest in hyperoxia, which suggests a ‘central’ limitation of oxygen uptake or delivery instead of a limit set by cellular oxidative capacity. However, the existence of a common central limitation is not in agreement with our earlier studies showing that selection on high (in contrast to selection on high BMR) resulted in considerably higher oxygen consumption during cold exposure in a He–O2 atmosphere than . Likewise, between-line-type differences in heart mass and blood parameters are inconsistent with the notion of central limitation. Although responses of to hypoxia were similar across different selection regimens, the selection lines showed contrasting responses under hyperoxic conditions. in the H-BMR line type was highest, suggesting that selection on high BMR led to increased cellular oxidative capacity. Overall, between-line-type differences in the effect of the oxygen partial pressure on and in the components of O2 flux pathways are incompatible with the notion of symmorphosis. Our results suggest that constraints on are context dependent and determined by interactions between the central and peripheral organs and tissues involved in O2 delivery.
New Frameworks for Offline and Streaming Coreset Constructions

Let $P$ be a set (called points), $Q$ be a set (called queries) and a function $ f:P\times Q\to [0,\infty)$ (called cost). For an error parameter $\epsilon>0$, a set $S\subseteq P$ with a \emph{weight function} $w:P \rightarrow [0,\infty)$ is an $\epsilon$-coreset if $\sum_{s\in S}w(s) f(s,q)$ approximates $\sum_{p\in P} f(p,q)$ up to a multiplicative factor of $1\pm\epsilon$ for every given query $q\in Q$. We construct coresets for the $k$-means clustering of $n$ input points, both in an arbitrary metric space and $d$-dimensional Euclidean space. For Euclidean space, we present the first coreset whose size is simultaneously independent of both $d$ and $n$. In particular, this is the first coreset of size $o(n)$ for a stream of $n$ sparse points in a $d \ge n$ dimensional space (e.g. adjacency matrices of graphs). We also provide the first generalizations of such coresets for handling outliers. For arbitrary metric spaces, we improve the dependence on $k$ to $k \log k$ and present a matching lower bound. For $M$-estimator clustering (special cases include the well-known $k$-median and $k$-means clustering), we introduce a new technique for converting an offline coreset construction to the streaming setting. Our method yields streaming coreset algorithms requiring the storage of $O(S + k \log n)$ points, where $S$ is the size of the offline coreset. In comparison, the previous state-of-the-art was the merge-and-reduce technique that required $O(S \log^{2a+1} n)$ points, where $a$ is the exponent in the offline construction's dependence on $\epsilon^{-1}$. For example, combining our offline and streaming results, we produce a streaming metric $k$-means coreset algorithm using $O(\epsilon^{-2} k \log k \log n)$ points of storage. The previous state-of-the-art required $O(\epsilon^{-4} k \log k \log^{6} n)$ points.
A survey on emotional semantic image retrieval

Emotional semantic image retrieval is a new and promising research direction in recent years. This paper attempts to introduce this emerging area to researchers, give them a brief overview of current research progress and framework. In this field three key issues, emotional semantic representation, image feature extraction, and emotion recognition, are discussed in detail with approaches and challenges. In addition, future research directions are suggested.
Applications of Static Slicing in Cost Analysis of Java Bytecode

Java bytecode [? ] is a low-level object-oriented language which is widely used in the context of mobile code due to its security features and the fact that it is platform independent. Recent works study advanced properties of Java bytecode like cost analysis [? ] or termination [? ]. Automatic cost analysis has interesting applications in the context of Java bytecode. For instance, the receiver of the code may want to infer cost information in order to decide whether to reject code which has too large cost requirements in terms of computing resources (in time and/or space), and to accept code which meets the established requirements [? ,? ,? ]. Also, in parallel systems, knowledge about the cost of different procedures in the object code can be used in order to guide the partitioning, allocation and scheduling of parallel processes. Given an input program, cost analysis aims at inferring Cost Equations Systems (CES) which define the cost of the program as a function of (some of) its data input size. CES are a general form of describing the resource consumption of programs and, in a particular application, they can be used to infer heap consumption [? ], number of executed bytecode instructions [? ], etc. Essentially, CES are generated by abstracting the structure of the program such that when the program contains an iteration the CES contains a corresponding recursion, which in addition includes information about how the sizes of the different variables change when the program goes through this recursion. The traditional approach is to infer upper bounds of the cost by solving the CES, for instance using Computer Algebra Systems (CAS) like Mathematica, Maple, etc.
Source separation as an exercise in logical induction

We examine the relationship between the Bayesian and information-theoretic formulations of source separation algorithms. This work makes use of the relationship between the work of Claude E. Shannon and the “Recent Contributions” by Warren Weaver (Shannon & Weaver 1949) as clarified by Richard T. Cox (1979) and expounded upon by Robert L. Fry (1996) as a duality between a logic of assertions and a logic of questions. Working with the logic of assertions requires the use of probability as a measure of degree of implication. This leads to a Bayesian formulation of the problem. Whereas, working with the logic of questions requires the use of entropy as a measure of the bearing of a question on an issue leading to an information-theoretic formulation of the problem.
Simple fuzzy solution for quadrotor attitude control

This paper presents new computationally efficient and easy to tune attitude control of a four rotor helicopter called quadrotor. Short description of quadrotor concept and control framework is given and the segment of inner attitude control of the aircraft is addressed. Proposed fuzzy proportional - differential (PD) control structure utilizes Sugeno fuzzy engine, with simple intuitive set of rules and set of physically meaningful parameters. The verification of proposed solution was done via simulation and comparison with existing backstepping based attitude control system.
The impact of financial leverage sharp increase on earnings management on the accepted firms in Tehran Stock Exchange

The aim of the current study is to see the changes in the amount of benefit management regarding the firms whose liabilities increase to a large extent. The managers of these kinds of firms normally have more motivations to satisfy credit providers through profit management. But it seems that auditors and financial providers' more attention to these firms' leads to having more regular managers and decreasing profit management performance. The tested sample includes 136 firms among the accepted ones in Iran Stock Exchange considering a period of eight years from the beginning of 2000 to the end of 2007. In order to estimate the rate of profit management performance by the use of Jones adjusted model, the optional committed items were calculated. The hypotheses were tested via regression method. The results demonstrated that the increase of most liabilities causes the decrease of profit management performance. In fact, liability makes managers have less access to free cash flows in order to pay the liability and its interest; therefore, they cannot take advantage of the opportunities such as non-optimization investment, extra cost tolerance and earning waste. In other words, the more the liabilities increase, the more regular the managers perform.
Cancer Invasion: Patterns and Mechanisms

Cancer invasion and the ability of malignant tumor cells for directed migration and metastasis have remained a focus of research for many years. Numerous studies have confirmed the existence of two main patterns of cancer cell invasion: collective cell migration and individual cell migration, by which tumor cells overcome barriers of the extracellular matrix and spread into surrounding tissues. Each pattern of cell migration displays specific morphological features and the biochemical/molecular genetic mechanisms underlying cell migration. Two types of migrating tumor cells, mesenchymal (fibroblast-like) and amoeboid, are observed in each pattern of cancer cell invasion. This review describes the key differences between the variants of cancer cell migration, the role of epithelial-mesenchymal, collective-amoeboid, mesenchymal-amoeboid, and amoeboid- mesenchymal transitions, as well as the significance of different tumor factors and stromal molecules in tumor invasion. The data and facts collected are essential to the understanding of how the patterns of cancer cell invasion are related to cancer progression and therapy efficacy. Convincing evidence is provided that morphological manifestations of the invasion patterns are characterized by a variety of tissue (tumor) structures. The results of our own studies are presented to show the association of breast cancer progression with intratumoral morphological heterogeneity, which most likely reflects the types of cancer cell migration and results from different activities of cell adhesion molecules in tumor cells of distinct morphological structures.