Miracle-dz/UniFAR-FTUs huggingface dataset:
Feasibility of Diffusion Tractography for the Reconstruction of Intra-Thalamic and Cerebello-Thalamic Targets for Functional Neurosurgery: A Multi-Vendor Pilot Study in Four Subjects

Functional stereotactic neurosurgery by means of deep brain stimulation or ablation provides an effective treatment for movement disorders, but the outcome of surgical interventions depends on the accuracy by which the target structures are reached. The purpose of this pilot study was to evaluate the feasibility of diffusion tensor imaging (DTI) based probabilistic tractography of deep brain structures that are commonly used for pre- and perioperative targeting for functional neurosurgery. Three targets were reconstructed based on their significance as intervention sites or as a no-go area to avoid adverse side effects: the connections propagating from the thalamus to (1) primary and supplementary motor areas, (2) to somatosensory areas and the cerebello-thalamic tract (CTT). We evaluated the overlap of the reconstructed connectivity based targets with corresponding atlas based data, and tested the inter-subject and inter-scanner variability by acquiring repeated DTI from four volunteers, and on three MRI scanners with similar sequence parameters. Compared to a 3D histological atlas of the human thalamus, moderate overlaps of 35-50% were measured between connectivity- and atlas based volumes, while the minimal distance between the centerpoints of atlas and connectivity targets was 2.5 mm. The variability caused by the MRI scanner was similar to the inter-subject variability, except for connections with the postcentral gyrus where it was higher. While CTT resolved the anatomically correct trajectory of the tract individually, high volumetric variability was found across subjects and between scanners. DTI can be applied in the clinical, preoperative setting to reconstruct the CTT and to localize subdivisions within the lateral thalamus. In our pilot study, such subdivisions moderately matched the borders of the ventrolateral-posteroventral (VLpv) nucleus and the ventral-posterolateral (VPL) nucleus. Limitations of the currently used standard DTI protocols were exacerbated by large scanner-to-scanner variability of the connectivity-based targets.
Molecular detection of algal prey in copepod guts and fecal pellets

The ability to obtain information about feeding selectivity and rates in situ for key organisms such as copepods and other zooplankton is vital for understanding the mechanisms structuring marine ecosystems. Copepods feed on a wide range of prey, and there are presently no methods available to directly quantify zooplankton feeding on all different prey types in situ. Therefore, the development of a new nonintrusive direct method is necessary to gain a better understanding of the trophic interactions in aquatic ecosystems. Molecular methods based on the polymerase chain reaction have recently become an important tool to study predation by arthropods, particularly insects. Here we present the first results of successful molecular detection of a specific prey consumed by calanoid copepods from gut and fecal material. Using the calanoid copepod species Calanus finmarchicus consuming the haptophyte alga Emiliania huxleyi as a model system, 18S ribosomal DNA originating from E. huxleyi was unambiguously detected in whole DNA extracts from copepods and from their fecal pellets. The results also suggest that prey DNA may be quantified for determination of prey‐specific zooplankton feeding rates. However, significantly more research under controlled laboratory and field conditions will be required to achieve these objectives. We hypothesize that molecular methods will become an important tool with the potential to quantify undisturbed trophic interactions between individual predators and all their prey in the complex natural plankton.
Population Growth in Rural Missouri Counties in the 1990s: Yet Another Turnaround

Nonmetropolitan counties in Missouri, similar to their national counterparts, have experienced alternating decades of rapid and slower growth since the 1970s. A simple reduced form model is used to identify the factors that explain population growth in rural Missouri counties. As found by earlier researchers, such factors as agricultural employment, income, city size, population density, race, retirement attraction and the existence of a state college continue to influence population growth in rural counties in Missouri. The variables identified are likely to contribute to continued growth in nonmetropolitan counties in the present decade.
Energy-Efficient Routing Algorithms in Wireless Sensor Networks : e 3 D Diffusion vs . Clustering

One of the limitations of wireless sensor nodes is their inherent limited energy resource. Besides maximizing the lifetime of the sensor node, it is preferable to distribute the energy dissipated throughout the wireless sensor network in order to minimize maintenance and maximize overall system performance. Any communication protocol that involves synchronization of peer nodes incurs some overhead for setting up the communication. We introduce a new algorithm, e3D*, and compare it to two other algorithms, namely directed, and random clustering communication. We take into account the setup costs and analyze the energy-efficiency and the useful lifetime of the system. In order to better understand the characteristics of each algorithm and how well e3D really performs, we also compare e3D with its optimum counterpart and an optimum clustering algorithm. The benefit of introducing these ideal algorithms is to show the upper bound on performance at the cost of an astronomical prohibitive synchronization costs. We compare the algorithms in terms of system lifetime, power dissipation distribution, cost of synchronization, and simplicity of the algorithm. Our simulation results show that e3D performs only slightly worse than its optimal counterpart while having much less overhead. Therefore, our contribution is a diffusion based routing protocol that prolongs the system lifetime, evenly distributes the power dissipation throughout the network, and incurs minimal overhead for synchronizing communication.
Marginalized particle PHD filters for multiple object Bayesian filtering

The Probability Hypothesis Density (PHD) filter is a recent solution to the multi-target filtering problem. Because the PHD filter is not computable, several implementations have been proposed including the Gaussian Mixture (GM) approximations and Sequential Monte Carlo (SMC) methods. In this paper, we propose a marginalized particle PHD filter which improves the classical solutions when used in stochastic systems with partially linear substructure.
Pay What You Want! A Pilot Study on Neural Correlates of Voluntary Payments for Music

Pay-what-you-want (PWYW) is an alternative pricing mechanism for consumer goods. It describes an exchange situation in which the price for a given good is not set by the seller but freely chosen by the buyer. In recent years, many enterprises have made use of PWYW auctions. The somewhat contra-intuitive success of PWYW has sparked a great deal of behavioral work on economical decision making in PWYW contexts in the past. Empirical studies on the neural basis of PWYW decisions, however, are scarce. In the present paper, we present an experimental protocol to study PWYW decision making while simultaneously acquiring functional magnetic resonance imaging data. Participants have the possibility to buy music either under a traditional “fixed-price” (FP) condition or in a condition that allows them to freely decide on the price. The behavioral data from our experiment replicate previous results on the general feasibility of the PWYW mechanism. On the neural level, we observe distinct differences between the two conditions: In the FP-condition, neural activity in frontal areas during decision-making correlates positively with the participants’ willingness to pay. No such relationship was observed under PWYW conditions in any neural structure. Directly comparing neural activity during PWYW and the FP-condition we observed stronger activity of the lingual gyrus during PWYW decisions. Results demonstrate the usability of our experimental paradigm for future investigations into PWYW decision-making and provides first insights into neural mechanisms during self-determined pricing decisions.
Around the world in 8 pages? A longitudinal analysis of international news coverage in Flemish newspapers (1986-2006)

For some time now, scholars and other critics have warned for a decline in the quantity and the quality of international news coverage in almost all Western societies. Investigating international news in three Flemish newspapers between 1986 and 2006 and interviewing journalists on the issue, this Working Paper tends to moderate these accusations of a fast and increasingly shrinking international news agenda. Despite a gradual decline in the 1990s, we observed a fairly steady percentage of 15.5% over a period of twenty years, notwithstanding occasional peaks and lows due to exceptional news events. The quality newspapers De Morgen and De Standaard devoted considerably more attention and space to international news as compared to the more popular Het Laatste Nieuws. Nonetheless, international news reporting in all Flemish newspapers displayed several biases in terms of geographic and thematic diversity. The data support the claim that the newspapers in the sample reproduce a certain world order, characterized by Eurocentrism. Although we observed a shift to more human interest and entertainment-oriented stories, international news coverage still mainly deals with hard and negative news.
Theoretische Informatik , Universität Ulm Oberer Eselsberg , 89069 Ulm , Germany

In many works in the fields of computational complexity, algorithmic number theory and mathematical cryptology as well as in related areas, claims on the running times of algorithms are made. However, often no computational model is given and the analysis is performed in a more or less ad hoc way, counting in an intuitive way “bit operations”. On the other hand, the computational model of a successor RAM with logarithmic cost function provides an adequate and formal basis for the analysis of the complexity of algorithms from a “bit oriented” point of view. This motivates the search for a result on the simulation of machines in a suitably defined general model by successor RAMs. In this work, a very general RAM model is defined, and then a “quasi-optimal” result on the simulation of such machines by successor RAMs is given.
Disinhibition Outside Receptive Fields in the Visual Cortex

By definition, the region outside the classical receptive field (CRF) of a neuron in the visual cortex does not directly activate the cell. However, the response of a neuron can be influenced by stimulation of the surrounding area. In previous work, we showed that this influence is mainly suppressive and that it is generally limited to a local region outside the CRF. In the experiments reported here, we investigate the mechanisms of the suppressive effect. Our approach is to find the position of a grating patch that is most effective in suppressing the response of a cell. We then use a masking stimulus at different contrasts over the grating patch in an attempt to disinhibit the response. We find that suppressive effects may be partially or completely reversed by use of the masking stimulus. This disinhibition suggests that effects from outside the CRF may be local. Although they do not necessarily underlie the perceptual analysis of a figure–ground visual scene, they may provide a substrate for this process.
Standards-based teaching and educational digital libraries as innovations: Undergraduate science faculty in the adoption process

ii Dedication . iv Acknowledgments. v Vita. vi List of Tables . xvi List of Figures . xix Chapters: Page 1 The Problem. 1 Background. 1 Nature of the Problem. 3 Statement of the Problem. 7 Significance of the Study . 7 Methodology. 8 Participants. 8 Data Collection . 9 Data Analyses . 11 Definition of Terms. 12
Distributed Event-driven Simulation - Scheduling Strategies and Resource Management

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Intron 3 Sixteen Base Pairs Duplication Polymorphism of P53 Contributes to Breast Cancer Susceptibility: Evidence from Meta-Analysis

Background P53 is a tumor suppressor gene and plays important role in the etiology of breast cancer. Intron 3 sixteen-bp duplication polymorphism of p53 has been reported to be associated with breast cancer risk. However, the reported results remain conflicting rather than conclusive. Methods A meta-analysis including 19 case-control studies was performed to address this issue. Odds ratios (ORs) with 95% confidence intervals (CIs) were adopted to evaluate the association. Results The overall results suggested that the variant genotypes were associated with a significantly increased breast cancer risk (Del/Ins vs Del/Del: OR = 1.18, 95% CI: 1.00–1.40; Ins/Ins vs Del/Del: OR = 1.42, 95% CI = 1.09–1.84; Ins/Ins+Del/Ins vs Del/Del: OR = 1.21, 95% CI = 1.03–1.41). When stratifying by sample size of studies, a significantly elevated risk was also observed among large sample studies (>500 subjects) but not among small sample studies (≤500 subjects). Conclusion These results suggested that the 16-bp duplication polymorphism of p53 may contribute to susceptibility to breast cancer. Additional well-designed large studies were required to validate this association in different populations.
Distribution-free multivariate process control based on log-linear modeling

This paper considers Statistical Process Control (SPC) when the process measurement is multivariate. In the literature, most existing multivariate SPC procedures assume that the in-control distribution of the multivariate process measurement is known and it is a Gaussian distribution. In applications, however, the measurement distribution is usually unknown and it needs to be estimated from data. Furthermore, multivariate measurements often do not follow a Gaussian distribution (e.g., cases when some measurement components are discrete). We demonstrate that results from conventional multivariate SPC procedures are usually unreliable when the data are non-Gaussian. Existing statistical tools for describing multivariate non-Gaussian data, or transforming the multivariate non-Gaussian data to multivariate Gaussian data, are limited, making appropriate multivariate SPC difficult in such cases. In this paper, we suggest a methodology for estimating the in-control multivariate measurement distribution when a set of in-control data is available, which is based on log-linear modeling and which takes into account the association structure among the measurement components. Based on this estimated in-control distribution, a multivariate CUSUM procedure for detecting shifts in the location parameter vector of the measurement distribution is also suggested for Phase II SPC. This procedure does not depend on the Gaussian distribution assumption; thus, it is appropriate to use for most multivariate SPC problems.
A multi-source cooperative scheme based on IDMA aided superposition modulation

In this work, we propose a novel superposition modulated cooperative scheme for the scenario with multiple source nodes. With the proposed scheme, multiple source nodes are divided into several subsets to cooperate in a Time Division Duplexing (TDD) manner. The transmission of each node is a superimposed signal consists of its own information and the estimated data of nodes in the previous subset. Interleave Division Multiple Access (IDMA) is employed to sperate different nodes. The subset partition is also analyzed and the ways to get a tradeoff between performance and system complexity is shown. Simulation results are finally provided to show the performance of the proposed scheme.
AN INTEGRAL UNIVALENT OPERATOR OF THE CLASS S (p) AND T2

Let A be a class of the analytic functions { f : f(z) = z + a2z + . } , z ∈ U , where U is the unit disk, U = {z : |z| < 1} . By S we denote the subclass of A consisting of function univalent in the unit disk. Let p be a real number with the property 0 < p ≤ 2. We define the class S (p) as the class of the functions f ∈ A that satisfy the conditions f (z) 6= 0 and ∣(z/f (z))′′ ∣∣ ≤ p, z ∈ U. Also, if f ∈ S (p) then the following property is true ∣∣ z2f ′(z) f2(z) − 1 ∣∣ ≤ p |z| , z ∈ U . This relation was proved in [4]. We denote by T2 a class of the univalent functions that satisfy the condition ∣∣ z2f ′(z) f2(z) − 1 ∣∣ < 1, z ∈ U , and also have the property f ′′ (0) = 0. These functions have the form f(z) = z+a3z+a4z+. For 0 < μ < 1 we define a subclass of T2 containing the functions that satisfy the property ∣∣ z2f ′(z) f2(z) − 1 ∣∣ < μ < 1, z ∈ U . We denote that class by Tμ,2.
S-shaped probability weighting and hyperbolic preference reversal - an intimate relationship

This paper 1 argues that intertemporal decision experiments have to take into account the unavoidable uncertainty surrounding the realization of gains and losses in the future. It is shown that an intertemporal state-dependent expected utility model (generating S-shaped probability weighting by considering anticipated emotional reactions to the resolution of uncertainty in addition to expected utility of wealth) is capable to explain various stylized facts. (1) S-shaped probability weighting induces
Evaluation of network equivalents for voltage optimization in multi-area power systems

The paper addresses the problem of decentralized optimization for a power system partitioned into several areas controlled by different transmission system operators (TSOs). The optimization variables are the settings for taps, generators' voltages and compensators', and the objective function is either based on the minimization of reactive power support, the minimization of active power losses, or a combination of both criteria. We suppose that each TSO assumes an external network equivalent for its neighboring areas and optimizes without concern for the neighboring systems' objectives its own optimization function. We study, in the context where every TSO adopts the same type of objective function, the performance of an iterative scheme, where every TSO refreshes at each iteration the parameters of its external network equivalents depending on its past internal observations, solves its local optimization problem, and then, applies its “optimal actions” to the power system. In the context of voltage optimization, we find out that this decentralized control scheme can converge to nearly optimal global performance for relatively simple equivalents and simple procedures for fitting their parameters.
Job satisfaction of adjunct faculty serving in the online environment at a private evangelical university

The purpose of this study was to describe levels of satisfaction of the adjunct faculty who teach in online modalities of instruction at a private evangelical university located in the southern United States. The three faculty groups included in the study were (a) online adjunct faculty (independent contractors), (b) adjunct faculty (university full time staff and administrators teaching part-time in the online program) and (c) full-time residential faculty who teach online courses in the distance format. The abridged Job Descriptive Index and the abridged Job in General index were chosen to survey respondents regarding satisfaction levels. The results of the study found that in general, all faculty groups who taught in the online environment were satisfied with the work itself, supervision, staff, and the job in general. Full-time faculty were neither satisfied nor dissatisfied with pay and opportunities for improvement. Part-time faculty and full-time staff and administration who taught in the online programs scored in the neutral area of satisfaction regarding opportunities for promotion. In general, none of the faculty groups was dissatisfied with any of the job facets examined during the study.
Measuring EGFR Separations on Cells with ∼10 nm Resolution via Fluorophore Localization Imaging with Photobleaching

Detecting receptor dimerisation and other forms of clustering on the cell surface depends on methods capable of determining protein-protein separations with high resolution in the ∼10–50 nm range. However, this distance range poses a significant challenge because it is too large for fluorescence resonance energy transfer and contains distances too small for all other techniques capable of high-resolution in cells. Here we have adapted the technique of fluorophore localisation imaging with photobleaching to measure inter-receptor separations in the cellular environment. Using the epidermal growth factor receptor, a key cancer target molecule, we demonstrate ∼10 nm resolution while continuously covering the range of ∼10–80 nm. By labelling the receptor on cells expressing low receptor numbers with a fluorescent antagonist we have found inter-receptor separations all the way up from 8 nm to 59 nm. Our data are consistent with epidermal growth factor receptors being able to form homo-polymers of at least 10 receptors in the absence of activating ligands.
Business survey forecasts and measurement of output trends in five European economies

A framework for modelling actual and expected output growth is described when direct measures of expectations are available, and alternative measures of trend output are suggested. The relative merits of the alternatives are discussed and an illustative stochastic growth model is described where the trends are interpreted as potential output measures. Direct measures of expectations are derived from survey data in five European economies over 1968-1998. No evidence is found to reject rationality in any of the derived series, and the bivariate models of actual and expected outputs, and the associated trends, are shown to outperform those based on actual data alone.
PREDICTION OF STUDENT ACADEMIC PERFORMANCE BY AN APPLICATION OF DATA MINING TECHNIQUES

One of the significant facts in higher learning institution is the explosive growth educational data. These data are increasing rapidly without any benefit to the management. The main objective of any higher educational institution is to improve the quality of managerial decisions and to impart quality education. Good prediction of student's success in higher learning institution is one way to reach the highest level of quality in higher education system. There are many prediction model available with difference approach in student performance was reported by researcher, but there is no certainty if there are any predictors that accurately determine whether a student will be an academic genius, a drop out, or an average performer. The aims of this study was to apply the kernel method as data mining techniques to analyze the relationships between students's behavioral and their success and to develop the model of student performance predictors . This is done by using Smooth Support Vector Machine (SSVM) classification and kernel k-means clustering techniques. The results of this study reported a model of student academic performance predictors by employing psychometric factors as variables predictors.