Miracle-dz/UniFAR-FTUs huggingface dataset:
Dense entropy decrease estimation for mobile robot exploration

We propose a method for the computation of entropy decrease in C-space. These estimates are then used to evaluate candidate exploratory trajectories in the context of autonomous mobile robot mapping. The method evaluates both map and path entropy reduction and uses such estimates to compute trajectories that maximize coverage whilst minimizing localization uncertainty, hence reducing map error. Very efficient kernel convolution mechanisms are used to evaluate entropy reduction at each sensor ray, and for each possible robot position and orientation, taking frontiers and obstacles into account. In contrast to most other exploration methods that evaluate entropy reduction at a small number of discrete robot configurations, we do it densely for the entire C-space. The computation of such dense entropy reduction maps opens the window to new exploratory strategies. In this paper we present two such strategies. In the first one we drive exploration through a gradient descent on the entropy decrease field. The second strategy chooses maximal entropy reduction configurations as candidate exploration goals, and plans paths to them using RRT*. Both methods use PoseSLAM as their estimation backbone, and are tested and compared with classical frontier-based exploration in simulations using common publicly available datasets.
From vulnerable to responsible youth? Indonesian youth resisting the dominant discourse of sexual health

ABSTRACT Contemporary critical studies have identified that the dominant discourse of sexual health has positioned youth as hormone-driven, vulnerable, uninformed, and in need to be ‘saved’ by sexuality educators. The current article aims to explore possibilities to destabilise such positioning by examining alternative sexual subjectivities among youth in an Indonesian context. As many as 22 participants were interviewed through the Internet (e.g. email and instant messenger interviews) and the data were analysed using a discourse analysis method. Their narratives demonstrate that youth are not simply hormone-driven, uninformed, and vulnerable. Instead, they are agentic subjects who – within their limited discursive access – actively, creatively, and subversively learn about sexuality in order to take care of their well-being. The implications are discussed in relation to how sexual health education may accommodate the complexity of youth’s sexual subjectivities.
Application of Minimum Statistics and Minima Controlled Recursive Averaging Methods to Estimate a Cepstral Noise Model for Robust ASR

Many compensation techniques, both in the model and feature domain, require an estimate of the noise statistics to compensate for the clean speech degradation in adverse environments. We explore how two spectral noise estimation approaches can be applied in the context of model-based feature enhancement. The minimum statistics method and the improved minima controlled recursive averaging method are used to estimate the noise power spectrum based only on the noisy speech. The noise mean and variance estimates are nonlinearly transformed to the cepstral domain and used in the Gaussian noise model of MBFE. We show that the resulting system achieves an accuracy on the Aurora2 task that is comparable to MBFE with prior knowledge on noise. Finally, this performance can be significantly improved when the MS or EMCRA noise mean is reestimated based on a clean speech model
A new radiation infrastructure for the Modular Earth Submodel System (MESSy, based on version 2.51)

Abstract. The Modular Earth Submodel System (MESSy) provides an interface to couple submodels to a base model via a highly flexible data management facility (Jockel et al., 2010). In the present paper we present the four new radiation related submodels RAD, AEROPT, CLOUDOPT, and ORBIT. The submodel RAD (including the shortwave radiation scheme RAD_FUBRAD) simulates the radiative transfer, the submodel AEROPT calculates the aerosol optical properties, the submodel CLOUDOPT calculates the cloud optical properties, and the submodel ORBIT is responsible for Earth orbit calculations. These submodels are coupled via the standard MESSy infrastructure and are largely based on the original radiation scheme of the general circulation model ECHAM5, however, expanded with additional features. These features comprise, among others, user-friendly and flexibly controllable (by namelists) online radiative forcing calculations by multiple diagnostic calls of the radiation routines. With this, it is now possible to calculate radiative forcing (instantaneous as well as stratosphere adjusted) of various greenhouse gases simultaneously in only one simulation, as well as the radiative forcing of cloud perturbations. Examples of online radiative forcing calculations in the ECHAM/MESSy Atmospheric Chemistry (EMAC) model are presented.
OPTIMAL PROJECT SEQUENCING WITH RECOURSE AT A SCARCE RESOURCE

We develop a dynamic prioritization policy to optimally allocate a scarce resource among K projects, only one of which can be worked on at a time. When the projects' delay costs differ, the problem (a “restless bandit”) has not been solved in general. We consider the policy of working on the project with the highest expected delay loss as if the other project was completely finished first (although recourse is allowed). This policy is optimal if: (1) the delay cost increases with the delay regardless of the performance state, (2) costs are not discounted (or, discounting is dominated by delay costs), (3) projects are not abandoned based on their performance state during processing at the scarce resource, and (4) there are no stochastic delays. These assumptions are often fulfilled for processing at specialized resources, such as tests or one‐off analyses.
Transcriptional Evidence for the Role of Chronic Venlafaxine Treatment in Neurotrophic Signaling and Neuroplasticity Including also Glutatmatergic- and Insulin-Mediated Neuronal Processes

Objectives Venlafaxine (VLX), a serotonine-noradrenaline reuptake inhibitor, is one of the most commonly used antidepressant drugs in clinical practice for the treatment of major depressive disorder (MDD). Despite being more potent than its predecessors, similarly to them, the therapeutical effect of VLX is visible only 3–4 weeks after the beginning of treatment. Furthermore, recent papers show that antidepressants, including also VLX, enhance the motor recovery after stroke even in non depressed persons. In the present, transcriptomic-based study we looked for changes in gene expressions after a long-term VLX administration. Methods Osmotic minipumps were implanted subcutaneously into Dark Agouti rats providing a continuous (40 mg/kg/day) VLX delivery for three weeks. Frontal regions of the cerebral cortex were isolated and analyzed using Illumina bead arrays to detect genes showing significant chances in expression. Gene set enrichment analysis was performed to identify specific regulatory networks significantly affected by long term VLX treatment. Results Chronic VLX administration may have an effect on neurotransmitter release via the regulation of genes involved in vesicular exocytosis and receptor endocytosis (such as Kif proteins, Myo5a, Sv2b, Syn2 or Synj2). Simultaneously, VLX activated the expression of genes involved in neurotrophic signaling (Ntrk2, Ntrk3), glutamatergic transmission (Gria3, Grin2b and Grin2a), neuroplasticity (Camk2g/b, Cd47), synaptogenesis (Epha5a, Gad2) and cognitive processes (Clstn2). Interestingly, VLX increased the expression of genes involved in mitochondrial antioxidant activity (Bcl2 and Prdx1). Additionally, VLX administration also modulated genes related to insulin signaling pathway (Negr1, Ppp3r1, Slc2a4 and Enpp1), a mechanism that has recently been linked to neuroprotection, learning and memory. Conclusions Our results strongly suggest that chronic VLX treatment improves functional reorganization and brain plasticity by influencing gene expression in regulatory networks of motor cortical areas. These results are consonant with the synaptic (network) hypothesis of depression and antidepressant-induced motor recovery after stroke.
Discussion on Hedging Predictions in Machine Learning by A. Gammerman and V. Vovk

Research Institute of Control Problems, Russian Academy of Science in Moscow, and Computer Learning Research Centre, Royal Holloway, University of London, London, UK. Email: chervnks@ipu.rssi. ru A large variety of machine-learning algorithms are now developed and applied in different areas of science and industry. This new technique has a typical drawback, that there is no confidence measure for the prediction of output value for particular new objects. The main idea of the article is to look over all possible labeling of a new object and evaluate strangeness of each labeling in comparison with labeling of objects presented in the training set. The problem is to find appropriate measure of strangeness. Initially, authors try to apply the ideas of Kolmogogov complexity to estimate the strangeness of labeling. But firstly this complexity is not computable, then it is defined up to a constant factor and finally it is applied to the total sequence of objects, but not to one particular object. So the authors came to another idea (still induced by Kolmogorov complexity). Based on particular machinelearning algorithm it is possible to find reasonable measure of an object (with its labeling) strangeness. For regression (or ridge regression) it could be absolute difference between regression result and real output value: the larger the difference, the more strange is the object. In SVM approach to pattern recognition it could be weights of support vector: the larger is the weight of a vector, the more doubtful seems its labeling, and similar measures of strangeness may be proposed for other algorithms. So the protocol is as follows: look through all possible labeling of a new object. For each labeling add the object to the training set. Apply the machine-learning algorithm and rank the objects by their measure of strangeness. Estimate credibility of this labeling as one minus the ratio of the number of objects in the set more strange than the new one to the total number of objects in the set. This approach seems to be new and powerful. Its main advantage is that it is non-parametric and based only on i.i. d. assumption. In comparison with Bayesian approach, no prior distribution is used. The main theoretical result is the proof of validity of proposed conformal predictors. It means that in average, conformal predictors never over-rate the accuracy and reliability of their predictions. The second result is that asymptotically the relative number of cases when the real output value is within confidence interval converges to the average value of conformal predictors. Software implementing the proposed technique is now applied to a large variety of practical problems. Still I can mention two drawbacks of the article.
Power-minimizing and rate-maximizing transceivers with integer bit allocation: A duality

In this paper, we consider the bit rate maximizing problem and power minimizing problem with integer bit allocation. We will derive the duality between these two problems. We will show that if a transceiver is optimal for the power-minimizing problem, it is also optimal for the rate maxi-mizing problem, and the converse is true. For the power minimization problem with integer bit allocation, the solution has been found in the literature. However, there is no solution yet for the rate maximization problem with integer bit allocation. The duality allows us to develop an algorithm for finding the rate-maximizing transceiver with integer bit allocation using the solution of power-minimizing system. In the simulations, we will compute the optimal solution for the rate-maximizing problem using the proposed algorithm.
Automatic generation of RF compact models from device simulation

We review a recently proposed methodology for automatic generation of equivalent circuits from physical device simulation. The method is based on the calibration on a simplified equivalent-circuit model on simulation results, and can achieve an optimum balance of model complexity, accuracy, and generality. We discuss some of the possible applications of the technique to the modeling of active devices, parasitic elements, and complex physical effects such as selfheating and hot-carrier transport.
Design and development of intelligent anomalous behaviour and event detection system

This paper discusses the preliminary design and development of an online anomalous behaviour and event detection system. Live video feeds from CCTV camera were obtained and processed. Important biomechanics features were then extracted and analyzed to discriminate and determine the dynamic objects in the current video scene. Human and nonhuman dynamic objects were then stored in the temporal memory of the system and tracked within the video scene. The tracked human's spatio-temporal activities were then tracked to establish their behaviour and subsequently the occurred event. Augmented with ambient information and a-priori normal condition rules, the system will then search for any anomalous behaviour and event from the set of occurring behaviour and events. The preliminary implementation and result of the system, the Intelligent Video Surveillance System (InViSS©) are presented in this paper.
Tabu Search: A Tutorial

Tabu search is a “higher level” heuristic procedure for solving optimization problems, designed to guide other methods (or their component processes) to escape the trap of local optimality. Tabu search has obtained optimal and near optimal solutions to a wide variety of classical and practical problems in applications ranging from scheduling to telecommunications and from character recognition to neural networks. It uses flexible structures memory (to permit search information to be exploited more thoroughly than by rigid memory systems or memoryless systems), conditions for strategically constraining and freeing the search process (embodied in tabu restrictions and aspiration criteria), and memory functions of varying time spans for intensifying and diversifying the search (reinforcing attributes historically found good and driving the search into new regions). Tabu search can be integrated with branch-and-bound and cutting plane procedures, and it has the ability to start with a simple implementation th.
The cosmic shear three-point functions

We investigate the three-point functions of the weak lensing cosmic shear, using both analytic methods and numerical results from N -body simulations. The analytic model, an isolated dark matter halo with a power-law profile chosen to fit the effective index at the scale probed, can be used to understand the basic properties of the eight three-point functions observed in simulations. We use this model to construct a single three-point function estimator that “optimally” combines the eight three-point functions. This new estimator is an alternative to M ap statistics and provides up to a factor of two improvement in signal to noise compared to previously used combinations of cosmic shear three-point functions.
Optimal scheduling of independent tasks on heterogeneous computing systems

In this paper, the problem of optimal scheduling of independent tasks on heterogeneous computing systems is considered. Optimal scheduling algorithms which produce preemptive schedules with minimal completion times and non-preemptive schedules with minimal mean flow times are described. A bound on mean flow times also provides us with information concerning the relative merit of different multiprocessor systems.
Multiple Kernel Learning : A Unifying Probabilistic Viewpoint Multiple Kernel Learning : A Unifying Probabilistic Viewpoint

We present a probabilistic viewpoint to multiple kernel learning unifying well-known regularised risk approaches and recent advances in approximate Bayesian inference relaxations. The framework proposes a general objective function suitable for regression, robust regression and classification that is lower bound of the marginal likelihood and contains many regularised risk approaches as special cases. Furthermore, we derive an efficient and provably convergent optimisation algorithm.
Integration of Simulation Based Performance Assessment in a Software Development Process

From the early design phase through the implementation performance assessment of software has been subject to a great variety of approaches in the past. Performance modeling artifacts have to be created and results have to be evaluated. I chose a simulation technique based on a configurable environment simulator and I will show how the development of software in a process can be influenced and improved by intermediate results. This proposal achieves a simple integration of the artifacts in a classical software development process. When performance requirements have to be met, I want to achieve improvement of response time or to save money by terminating the process early enough, if requirements can not be achieved. As the improvement of performance properties can often only be achieved by reimplementing the entire application, performance aspects have to be considered in time. Expenses in modeling can be returned, if results can be derived early in the process. I introduce methods to resolve dependencies and consider dependencies to performance aspects with priority.
Taking Stock of Self-Control

Given assertions of the theoretical, empirical, and practical importance of self-control, this meta-analytic study sought to review evidence concerning the relationship between dispositional self-control and behavior. The authors provide a brief overview over prominent theories of self-control, identifying implicit assumptions surrounding the effects of self-control that warrant empirical testing. They report the results of a meta-analysis of 102 studies (total N = 32,648) investigating the behavioral effects of self-control using the Self-Control Scale, the Barratt Impulsiveness Scale, and the Low Self-Control Scale. A small to medium positive effect of self-control on behavior was found for the three scales. Only the Self-Control Scale allowed for a fine-grained analysis of conceptual moderators of the self-control behavior relation. Specifically, self-control (measured by the Self-Control Scale) related similarly to the performance of desired behaviors and the inhibition of undesired behaviors, but its effects varied dramatically across life domains (e.g., achievement, adjustment). In addition, the associations between self-control and behavior were significantly stronger for automatic (as compared to controlled) behavior and for imagined (as compared to actual) behavior.
Relationship between Urinary 15-F2t-Isoprostane and 8-Oxodeoxyguanosine Levels and Breast Cancer Risk

To evaluate the role of oxidative stress in breast cancer, we measured urinary levels of 15-F2t-isoprostane (15-F2t-IsoP) and 8-oxodeoxyguanosine (8-oxodG) in 400 cases and 401 controls, participants of the Long Island Breast Cancer Study Project. We also analyzed the effect of different factors that are associated with oxidative stress and might influence 15-F2t-IsoP and 8-oxodG levels. We observed a statistically significant trend in breast cancer risk with increasing quartiles of 15-F2t-IsoP levels [odds ratio (OR), 1.25; 95% confidence interval (95% CI), 0.81-1.94; OR, 1.53; 95% CI, 0.99-2.35; OR, 1.88; 95% CI, 1.23-2.88, for the 2nd, 3rd, and 4th quartile relative to the lowest quartile, respectively; Ptrend = 0.002]. Although it is possible that increased levels may reflect the stress associated with recent treatment, the positive association was also observed when the analyses were restricted to case women for whom chemotherapy and radiation therapy had not yet been initiated at the time of the urine collection. The association with the highest quartile compared with lowest quartile of 15-F2t-IsoP was similar across strata of age, physical activity, fruit and vegetable intake, alcohol intake, cigarette smoking, body mass index, and menopausal status. We did not observe any association of breast cancer risk with 8-oxodG levels, but when cases with radiation treatment were removed from the analysis, a significant inverse trend (P = 0.04) was observed. Among controls, levels of 15-F2t-IsoP were higher among current cigarette smokers but did not differ by the amount of physical activity, fruit and vegetable intake, alcohol intake, body mass index, and menopausal status. Among controls, levels of 8-oxodG were higher among postmenopausal women and current and former cigarette smokers but did not differ by the other factors. In summary, our results suggest that urinary markers of lipid peroxidation and oxidative DNA damage may be associated with breast cancer risk. (Cancer Epidemiol Biomarkers Prev 2006;15(4):639-44)
Dynamic authentication: Need than a choice

The increasing number of reported security vulnerabilities exploiting the weaknesses of static password based authentication methods, and the significant financial/brand loss caused to the enterprises due to those vulnerabilities are only highlighting the fact that the traditional static password based authentication solutions are no longer an adequate protection mechanism for serious enterprise applications. This necessitates enterprises to seriously explore and embrace more robust, secure, multi-factor, dynamic one-time password based authentication technologies into their IT infrastructure. In this work we discuss the various authentication schemes with their pros and cons and present an implemented two factor dynamic onetime password scheme using a mobile device.
Quantitative Comparison of PET and Bremsstrahlung SPECT for Imaging the In Vivo Yttrium-90 Microsphere Distribution after Liver Radioembolization

Background After yttrium-90 (90Y) microsphere radioembolization (RE), evaluation of extrahepatic activity and liver dosimetry is typically performed on 90Y Bremsstrahlung SPECT images. Since these images demonstrate a low quantitative accuracy, 90Y PET has been suggested as an alternative. The aim of this study is to quantitatively compare SPECT and state-of-the-art PET on the ability to detect small accumulations of 90Y and on the accuracy of liver dosimetry. Methodology/Principal Findings SPECT/CT and PET/CT phantom data were acquired using several acquisition and reconstruction protocols, including resolution recovery and Time-Of-Flight (TOF) PET. Image contrast and noise were compared using a torso-shaped phantom containing six hot spheres of various sizes. The ability to detect extra- and intrahepatic accumulations of activity was tested by quantitative evaluation of the visibility and unique detectability of the phantom hot spheres. Image-based dose estimates of the phantom were compared to the true dose. For clinical illustration, the SPECT and PET-based estimated liver dose distributions of five RE patients were compared. At equal noise level, PET showed higher contrast recovery coefficients than SPECT. The highest contrast recovery coefficients were obtained with TOF PET reconstruction including resolution recovery. All six spheres were consistently visible on SPECT and PET images, but PET was able to uniquely detect smaller spheres than SPECT. TOF PET-based estimates of the dose in the phantom spheres were more accurate than SPECT-based dose estimates, with underestimations ranging from 45% (10-mm sphere) to 11% (37-mm sphere) for PET, and 75% to 58% for SPECT, respectively. The differences between TOF PET and SPECT dose-estimates were supported by the patient data. Conclusions/Significance In this study we quantitatively demonstrated that the image quality of state-of-the-art PET is superior over Bremsstrahlung SPECT for the assessment of the 90Y microsphere distribution after radioembolization.