Miracle-dz/UniFAR-FTUs huggingface dataset:
Galaxies with a Central Minimum in Stellar Luminosity Density

We used Hubble Space Telescope WFPC2 images to identify six early-type galaxies with surface brightness profiles that decrease inward over a limited range of radii near their centers. The inferred luminosity density profiles of these galaxies have local minima interior to their core break radii. NGC 3706 harbors a high surface brightness ring of starlight with radius ≈20 pc. Its central structure may be related to that in the double-nucleus galaxies M31 and NGC 4486B. NGC 4406 and NGC 6876 have nearly flat cores that, on close inspection, are centrally depressed. Colors for both galaxies imply that this is not due to dust absorption. The surface brightness distributions of both galaxies are consistent with stellar tori that are more diffuse than the sharply defined system in NGC 3706. The remaining three galaxies are the brightest cluster galaxies in A260, A347, and A3574. Color information is not available for these objects, but they strongly resemble NGC 4406 and NGC 6876 in their cores. The thin ring in NGC 3706 may have formed dissipatively. The five other galaxies resemble the endpoints of some simulations of the merging of two gas-free stellar systems, each harboring a massive nuclear black hole. In one version of this scenario, diffuse stellar tori are produced when stars initially bound to one black hole are tidally stripped away by the second black hole. Alternatively, some inward-decreasing surface brightness profiles may reflect the ejection of stars from a core during the hardening of the binary black hole created during the merger.
Speaker adaptation techniques for automatic speech recognition

Statistical speech recognition using continuousdensity hidden Markov models (CDHMMs) has yielded many practical applications. However, in general, mismatches between the training data and input data significantly degrade recognition accuracy. Various acoustic model adaptation techniques using a few input utterances have been employed to overcome this problem. In this article, we survey these adaptation techniques, including maximum a posteriori (MAP) estimation, maximum likelihood linear regression (MLLR), and eigenvoice.
Duty-cycle optimization for IEEE 802.15.4 wireless sensor networks

Most applications of wireless sensor networks require reliable and timely data communication with maximum possible network lifetime under low traffic regime. These requirements are very critical especially for the stability of wireless sensor and actuator networks. Designing a protocol that satisfies these requirements in a network consisting of sensor nodes with traffic pattern and location varying over time and space is a challenging task. We propose an adaptive optimal duty-cycle algorithm running on top of the IEEE 802.15. 4 medium access control to minimize power consumption while meeting the reliability and delay requirements. Such a problem is complicated because simple and accurate models of the effects of the duty cycle on reliability, delay, and power consumption are not available. Moreover, the scarce computational resources of the devices and the lack of prior information about the topology make it impossible to compute the optimal parameters of the protocols. Based on an experimental implementation, we propose simple experimental models to expose the dependency of reliability, delay, and power consumption on the duty cycle at the node and validate it through extensive experiments. The coefficients of the experimental-based models can be easily computed on existing IEEE 802.15. 4 hardware platforms by introducing a learning phase without any explicit information about data traffic, network topology, and medium access control parameters. The experimental-based model is then used to derive a distributed adaptive algorithm for minimizing the power consumption while meeting the reliability and delay requirements in the packet transmission. The algorithm is easily implementable on top of the IEEE 802.15. 4 medium access control without any modifications of the protocol. An experimental implementation of the distributed adaptive algorithm on a test bed with off-the-shelf wireless sensor devices is presented. The experimental performance of the algorithms is compared to the existing solutions from the literature. The experimental results show that the experimental-based model is accurate and that the proposed adaptive algorithm attains the optimal value of the duty cycle, maximizing the lifetime of the network while meeting the reliability and delay constraints under both stationary and transient conditions. Specifically, even if the number of devices and their traffic configuration change sharply, the proposed adaptive algorithm allows the network to operate close to its optimal value. Furthermore, for Poisson arrivals, the duty-cycle protocol is modeled as a finite capacity queuing system in a star network. This simple analytical model provides insights into the performance metrics, including the reliability, average delay, and average power consumption of the duty-cycle protocol.
A Framework for Exploring the Macroeconomic Determinants of Systematic Risk

We selectively survey, unify and extend the literature on realized volatility of financial asset returns. Rather than focusing exclusively on characterizing the properties of realized volatility, we progress by examining economically interesting functions of realized volatility, namely realized betas for equity portfolios, relating them both to their underlying realized variance and covariance parts and to underlying macroeconomic fundamentals.
Lateralisation of Parkinson symptoms and visuomotor control in gait

De ziekte van Parkinson is een veel voorkomende neurologische aandoening waarbij een tekort aan dopamine tot gevolg heeft dat patienten moeite hebben met beweging. Deze bewegingstoornis is het sterkst aan een lichaamzijde. De achtergrond van deze asymmetrie wordt nog niet begrepen. In dit proefschrift lieten wij zien dat de hersenhelft die de dominante hand aanstuurt vatbaarder is voor het ontstaan van de ziekte van Parkinson. Het aantonen van deze relatie geeft aanknopingspunten om verder onderzoek te doen naar de oorzaak van de kenmerkende asymmetrie bij de ziekte van Parkinson. Daarnaast hebben we onderzoek gedaan naar loopblokkades bij Parkinson patienten. Tijdens loopblokkades (‘bevriezen’) voelt het alsof de voeten vastgelijmd zijn aan de grond. Eerder onderzoek suggereerde dat loopblokkades mogelijk gerelateerd zijn aan disfunctie van de rechter hersenhelft. Daarom hadden we de verwachting dat patienten met een voornamelijk aangedane rechter hersenhelft, en dus de meeste klachten links, vaker loopblokkades zouden hebben. Onze retrospectieve database studie gaf geen steun aan deze gedachte, maar een prospectieve studie van anderen wel. Vervolgens hebben we het onderliggende mechanisme van loopblokkades verder onderzocht door een aangeboden visueel bewegingspatroon (optische flow) te manipuleren. Nabootsen van het naderen van een nauwe doorgang, wat loopblokkades kan uitlokken, maakt het nodig dat de geschakeld wordt tussen externe ondersteuning van beweging naar eigen aanzet tot beweging. Wij lieten zien dat dit omschakelen gestoord is bij patienten, wat bleek uit zowel een verslechtering van het lopen bij loopband onderzoek als gestoorde activatie van betrokken hersengebieden bij functionele MRI scans.
Learning Arbitrary Sum-Product Network Leaves with Expectation-Maximization

It has been shown in recent work that Expectation-Maximization (EM) is an attractive way to learn the parameters of Sum-Product Networks (SPNs). However, previous derivations of EM do not easily extend to SPNs with general leaf distributions and shared parameters. In this paper we obtain a new derivation of EM for SPNs allowing to derive EM updates for \emph{arbitrary leaf distributions} and for \emph{shared parameters} between SPN nodes. Here, EM translates in a set of independent weighted maximum likelihood problems for each leaf distribution, and therefore \emph{any} distribution that can be trained with maximum likelihood (even approximately) fits in this framework. The ability of learning complex leaf distributions in a principled way makes SPN parameter learning more flexible than learning SPN weights only. We demonstrate the potential of this approach with extensive experiments on twenty widely used benchmark datasets, using tree graphical models as leaf distributions.
Layered Multiplexing Considered Harmful

Traditionally, computer communication networks have been optimized with respect to throughput, robustness and absolute delay, with little or no concern for the variation in delay (jitter) induced by the network. It is now desirable that high speed networks support a greater range of telecommunication services by providing a multi-service environment. If the transmission of jitter-sensitive tra c is not to be arbitrarily precluded, then new protocol architectures must take account of, and provide support for, the constraint of jitter. The ATM approach to broadband networking is presently being pursued within the CCITT (and elsewhere) as the unifying mechanism for the support of service integration, rate adaption, and jitter control within the lower layers of the network architecture. This position paper is speci cally concerned with the jitter arising from the design of the middle and upper layers that operate within the end systems and relays of multi-service networks (MSNs). 1 What is Layered Multiplexing? Multiplexing can be viewed as a layer function that maps some number of upper layer tributary associations onto a single lower layer aggregate association. The principal e ect of multiplexing is the sharing of lower layer resources by upper layer clients. Clearly some degree of inter-system multiplexing is justi ed when a common transmission medium is shared by a number of independent systems. This style of multiplexing is normally accommodated within the media-dependent components (MAC) of the Data Link layer. In most environments, there is a further requirement for intra-system multiplexing to support the shared use of a system's points of attachment to its transmission media. In traditional layered architectures, intra-system multiplexing is not restricted to a single layer. Instead, the functionality is supported in a layered fashion at many points within the upper and middle layers of the protocol stack. Title suggested by Dr David Clark
Multicolor Super-Resolution Imaging with Photo-Switchable Fluorescent Probes

Recent advances in far-field optical nanoscopy have enabled fluorescence imaging with a spatial resolution of 20 to 50 nanometers. Multicolor super-resolution imaging, however, remains a challenging task. Here, we introduce a family of photo-switchable fluorescent probes and demonstrate multicolor stochastic optical reconstruction microscopy (STORM). Each probe consists of a photo-switchable “reporter” fluorophore that can be cycled between fluorescent and dark states, and an “activator” that facilitates photo-activation of the reporter. Combinatorial pairing of reporters and activators allows the creation of probes with many distinct colors. Iterative, color-specific activation of sparse subsets of these probes allows their localization with nanometer accuracy, enabling the construction of a super-resolution STORM image. Using this approach, we demonstrate multicolor imaging of DNA model samples and mammalian cells with 20- to 30-nanometer resolution. This technique will facilitate direct visualization of molecular interactions at the nanometer scale.
Localized Algorithm for Coverage in Wireless Sensor Networks

Wireless sensor networks have posed a number of challenging problems such as localization, deployment and tracking, etc. One of the interesting problems is the calculation of the coverage path for sensor networks. In this paper, we design a localized algorithm to solve the worst coverage problem first introduced by Meguerdichian et al. All nodes cooperate to construct the worst coverage path with their one-hop neighbors’ information. Also, the correctness of the algorithm is proved under the diminishing model formally.
The Implementation of a Distributed Framework to support ‘Follow Me’ Applications

Follow me applications support user mobility by adapting their behaviour to follow a user as he moves around a building. In order to adapt sensibly to their current environment, such applications need to know about the location and status of people and computing resources. This information needs to be readily accessible and must be up-to-date and accurate. As such a system involves human interaction, this presents some real-time constraints. This paper describes a framework for supporting such applications. It is based around a 3-tier architecture comprising a centralised database, a middle layer of parallel servers and a collectionof distributedclients. Some clients gather information from the environment, and are long running. Other clients are mobile applications, which must respond rapidly to environmental changes. As all these applications are in daily use, robustness and availability are key additional requirements. The framework uses on-demand loading of CORBA objects and is sufficiently flexible and scalable to be applied to a wide variety of other application areas. The paper also describes some experiences of deploying a substantial CORBA based system. In particular, it shows how a design evolves due to changing requirements and problems encountered, and illustrates the importance of being able to rapidly prototype systems prior to deployment in order to adapt to these changes and to explore alternative solutions.
Physicians' view of primary care-based case management for patients with heart failure: a qualitative study

Background As part of a trial aiming to improve care for patients with chronic (systolic) heart failure, a standardized, multifaceted case management approach was evaluated in German general practices. It consisted of regular telephone monitoring, home visits, health counselling, diagnostic screening and booklets for patients. Practice-based doctors' assistants (equivalent to a nursing role) adopted these new tasks and reported regularly to the employing general practitioner (GP). Objective To explore GPs' perceptions of case management, subsequent changes in relationships within the practice team and the potential future role. Method Twenty-four GPs participated in five moderated, semi-structured, audio-taped focus groups. Full transcription and thematic content analysis was undertaken. Results GPs rated all elements and instruments of case management conducted by doctors' assistants feasible, except for the geriatric assessment as patients had not been at risk. GPs perceived difficulties in their own role in delivering health behaviour counselling. Relationships between doctors' assistants and patients and between GPs and patients or doctors' assistants remained stable or improved. All GPs perceived a variety of role changes in doctors' assistants including more in-depth medical knowledge and higher responsibilities yielding more recognition by patients and GPs. Some GPs suggested transferring the case management programme to other chronic conditions and that it should form part of a further education curriculum for doctors' assistants. Conclusion This primary care-based case management model characterized by the orchestrated delegation of tasks to doctors' assistants offers a promising strategy of enhanced chronic illness care, but it needs further adaptation and evaluation.
Micro-computed tomography assessment of human femoral trabecular bone for two disease groups (fragility fracture and coxarthrosis): Age and gender related effects on the microstructure

The aim of this study was to identify three-dimensional microstructural changes of trabecular bone with age and gender, using micro-computed tomography. Human trabecular bone from two disease groups, osteoporosis and osteoarthritis was analyzed. A prior analysis of the effects of some procedure variables on the micro-CT results was performed. Preliminary micro-CT scans were performed with three voxel resolutions and two acquisition conditions. On the reconstruction step, the image segmentation was performed with three different threshold values. Samples were collected from patients, with coxarthrosis (osteoarthritis) or fragility fracture (osteoporosis). The specimens of the coxarthrosis group include twenty females and fifteen males, while the fragility fracture group was composed by twenty three females and seven males. The mean age of the population was 69 ± 11 (females) and 67 ± 10 years (males), in the coxarthrosis group, while in the fragility fracture group was 81 ± 6 (females) and 78 ± 6 (males) years. The 30 μm voxel size provided lower percentage difference for the microarchitecture parameters. Acquisition conditions with 160 μA and 60 kV permit the evaluation of all the volume’s sample, with low average values of the coefficients of variation of the microstructural parameters. No statistically significant differences were found between the two diseases groups, neither between genders. However, with aging, there is a decrease of bone volume fraction, trabecular number and fractal dimension, and an increase of structural model index and trabecular separation, for both disease groups and genders. The parameters bone specific surface, trabecular thickness and degree of anisotropy have different behaviors with age, depending on the type of disease. While in coxarthrosis patients, trabecular thickness increases with age, in the fragility fracture group, there is a decrease of trabecular thickness with increasing age. Our findings indicate that disease, age and gender do not provide significant differences in trabecular microstructure. With aging, some parameters exhibit different trends which are possibly related to different mechanisms for different diseases.
Scalable Privacy-Preserving Linking of Multiple Databases Using Counting Bloom Filters

The integration, mining, and analysis of person-specific data can provide enormous opportunities for organizations, governments, and researchers to leverage today's massive data collections. However, the use of personal or otherwise sensitive data also raises concerns about the privacy, confidentiality, and potential discrimination of people. Privacy-preserving record linkage (PPRL) is a growing research area that aims at integrating sensitive information from multiple disparate databases held by different organizations while preserving the privacy of the individuals in these databases by not revealing their identities and thereby preventing re-identification and discrimination. PPRL approaches are increasingly required in many real-world application areas ranging from healthcare to national security. Previous approaches to PPRL have mostly focused on linking only two databases. Scaling PPRL to several databases is an open challenge since privacy threats as well as the computation and communication costs increase significantly with the number of databases involved. We thus propose a new encoding method of sensitive data based on Counting Bloom Filters (CBF) to improve privacy for multi-party PPRL (MP-PPRL). We investigate optimizations to reduce computation and communication costs for CBF-based MP-PPRL. Our empirical evaluation with real datasets demonstrates the viability of our approach in terms of scalability, linkage quality, and privacy.
Stair detection and tracking from egocentric stereo vision

In this work we present a real-time approach to capture the properties of staircases from a free moving, head mounted stereo-camera. A variety of systems can profit from such ability, examples range from robots in multi-floor exploration scenarios to wearable assistance systems for the visually impaired. We introduce a light-weight method to measure the individual steps and use this information to update a minimal stair model while approaching and traversing the stair. Results are evaluated on an in- and outdoor scenario and show competitive accuracy to state of the art approaches working on precise lidar-sensors.
SYSTEMATIC SYNTHESIS OF PARALLEL ARCHITECTURES FOR THE REAL-TIME ESTIMATION OF HIGHER ORDER STATISTICAL MOMENTS

Abstract The Higher Order Statistics, such as the Higher Order Moments, Cumulants and Polyspectra, have been recognized as important tools in modem time series analysis since they overcome well-known limitations of the autocorrelation/power spectrum second order methods. The systematic synthesis of parallel algorithms and architectures for the real-time estimation of moments up to any desirable maximal order k > 3 is presented. First, a design methodology is developed which can take into account the desirable characteristics of the targeted parallel architecture and used to construct an optimal locally recursive form of the algorithm amenable to efficient parallelization. The design methodology is then used to synthesize a family of algorithms and minimum latency, low granularity, processor array architectures that can compute all lags of Higher Order Moments, from the samples of the incoming data sequence in real-time.
Safety of PEGylated recombinant human full‐length coagulation factor VIII (BAX 855) in the overall context of PEG and PEG conjugates

BAX 855 is a PEGylated human full‐length recombinant factor VIII (rFVIII) based on licensed rFVIII (ADVATE). The applied PEGylation technology has been optimized to retain functionality of the FVIII molecule, improve its pharmacokinetic properties and allow less frequent injections while maintaining efficacy.
Visual Objects Classification with Sliding Spatial Pyramid Matching

We present a method for visual object classification using only a single feature, transformed color SIFT with a variant of Spatial Pyramid Matching (SPM) that we called Sliding Spatial Pyramid Matching (SSPM), trained with an ensemble of linear regression (provided by LINEAR) to obtained state of the art result on Caltech-101 of 83.46%. SSPM is a special version of SPM where instead of dividing an image into K number of regions, a subwindow of fixed size is slide around the image with a fixed step size. For each subwindow, a histogram of visual words is generated. To obtained the visual vocabulary, instead of performing K-means clustering, we randomly pick N exemplars from the training set and encode them with a soft non-linear mapping method. We then trained 15 models, each with a different visual word size with linear regression. All 15 models are then averaged together to form a single strong model.
Energy-Efficient Pattern Recognition Approach for Wireless Sensor Networks

Event detection and monitoring is an important application class for wireless sensor networks. Traditionally, sensory data are collected and processed at the base-station. Conveying large amounts of multidimensional sensory data is however impractical in resource-constrained sensor networks. In this paper we propose to convert event detection into pattern recognition that is particularly suited for sensor networks. Individual sensory measurements of sensor nodes are integrated into high-level event pattern, and used for recovering the state of the monitored environment. The pattern storage and pattern recognition operations are performed in a distributed manner within the network. Furthermore, a sleep mode strategy is incorporated for improving performance and prolonging the lifetime of the sensor network.