Miracle-dz/UniFAR-FTUs huggingface dataset:
X-Ray versus Optical Observations of Active Galactic Nuclei: Evidence for Large Grains?

Recently, Maiolino et al. constructed a sample of active galactic nuclei for which both the reddening E(B-V) and the column density NH to the nucleus could be determined. For most of the galaxies in their sample, they found that E(B-V)/NH is substantially smaller than for the diffuse interstellar medium of our Galaxy. They asserted that either the dust-to-gas ratio is lower than in the Galaxy or the grains are so large that they do not extinct or redden efficiently in the optical. We show that there is no systematic increase in E(B-V) with NH for the Maiolino et al. galaxies, which suggests that the X-ray absorption and optical extinction occur in distinct media. In a later paper, Maiolino et al. suggested that the observed lines of sight for the previous Maiolino et al. galaxies pass through the "torus" that obscures the broad-line region and nuclear continuum in Seyfert 2 galaxies and argued that the torus grains are larger than Galactic grains. There is no reason to believe that the lines of sight for these galaxies pass through the torus, since the observed column densities are lower than those typically observed in Seyfert 2 galaxies. We suggest instead that the X-ray absorption occurs in material located off the torus and/or accretion disk, while the optical extinction occurs in material located beyond the torus. The X-ray absorbing material could either be dust-free or contain large grains that do not extinct efficiently in the optical. There is no conclusive evidence that the grains in active galactic nuclei are systematically larger than those in the diffuse interstellar medium of our Galaxy. We discuss an alternative way to probe the properties of dust in Seyfert tori but find that observations of Seyfert 2 nuclei with higher resolution than currently available will be needed in order to place stringent limits on the dust.
Dancing with horses: automated quality feedback for dressage riders

The sport of dressage has become very popular not only amongst professional athletes but increasingly also for private horse owners. In well-defined tests, rider and horse execute movements, which demonstrate the strength, endurance, and dexterity of the animal as well as the quality of the interaction between rider and horse. Whilst at a professional level intensive expert coaching to refine the skill set of horse and rider is standard, such an approach to progression is not usually viable for the large amateur population. In this paper we present a framework for automated generation of quality feedback in dressage tests. Using on-body sensing and automated measurement of key performance attributes we are able to monitor the quality of horse movements in an objective way. We validated the developed framework in a large-scale deployment study and report on the practical usefulness of automatically generated quality feedback in amateur dressage.
Labour Market Integration of Immigrants and Their Children in Germany: Does Personality Matter?

Educational attainment, length of stay, di¤erences in national background and language skills play an acknowledged important role for the integration of immigrants. But integration is also a social process, which suggests that psychological factors are relevant. This paper explores whether and to what extent immigrants and their children need to believe in their ability to control their own success, in other words their sense of control. To quantify this personal trait I use a measure of an individual's sense of control over outcomes in life-such as …nding a job. This measure is known in psychology as "the locus of control". I …rst estimate an exogenous measure. Then I address the problem that this measure is actually endogeneous in a labor market outcome equation by employing a model in which the sense of control is an endogenized latent factor in a simultaneous equation model. The determinants of this sense of control as well as its e¤ect on the probability of being employed are examined. The model is estimated using an implemented Bayesian Markov Chain Monte Carlo algorithm. Results with endogenized personality indicate that, on average, immigrants believe less than natives in being able to control outcomes in life, but children of immigrants have already a stronger sense of control than their parents. The paper also …nds that sense of control over life's outcomes positively contributes to the probability of being employed. This means that immigrants and their children face a double disadvantage on the labor market: they are disadvantaged because of their status as an immigrant and they have a lower sense of being able to control their situation, which is a personality trait that matters on the labour market.
A language and system for composing autonomous, heterogeneous and distributed megamodules

New levels of software composition become possible through advances in distributed communication services. We focus on the composition of megamodules, which are large distributed components or computation servers that are autonomously operated and maintained. The composition of megamodules offers various challenges. Megamodules are not necessarily all accessible by the same distribution protocol (such as CORBA, DCOM, RMI and DCE). Their concurrent nature and potentially long duration of service execution necessitates asynchronous invocation and collection of results. Novel needs and opportunities for optimization arise when composing megamodules. In order to meet these challenges, we have defined a purely compositional language called CHAIMS, and are now developing the architecture supporting this language. In this paper we describe CHAIMS and how it meets the challenges of composing megamodules.
Data collection requirements for mobile connected health: an end user development approach

The rise of smart mobile devices presents increasing opportunities for health monitoring outside the clinic. Through the use of sensors and wearables, innovative Connected Health applications can be developed. In particular, Digital Therapeutics (DT), a type of technology-enabled intervention, can be made possible through continuous data capture, aiding users through gaining feedback on their lifestyle choices and engagement with programs of recovery, and supplementing conventional treatments for chronic disease management such as in diabetes, epilepsy, and mental health. Unfortunately, patient-facing professionals capable of articulating appropriate sensor-enabled solutions, generally lack the full range of skills to develop such systems. A connected health application may involve mobile development, data services, visualisation, machine learning, and sensor signal processing, needing multidisciplinary teams, including professional software engineers. The cost of maintaining a software team across the research and development stages may prove prohibitive for many, hindering innovation. This paper focuses on gathering requirements for data collection in mHealth studies, and reports the initial findings after a round of interviews with researchers in areas such as psychology, physiotherapy, neurology, and health promotion education. Those requirements are framed within an existing End User Development (EUD) tool to create mobile apps for the Android platform, the open source project MIT App Inventor. The survey results highlight not only the development work needed for App Inventor to be used as a data collection tool in DT, but also a number of potential security and privacy issues, and the implementation of a layered feedback loop with a social aspect at the heart of it.
On K(1)-local SU-bordism

This paper is on an E∞ splitting of the bordism spectrum MSU. Going the chromatic way, we make use of the resolution of the K(1)-local sphere in terms of KO-theory. The construction of an SU-Artin-Schreier class results in an E∞ summand Tζ in SU-bordism. Working towards other free summands TS, we apply the theory of Bott’s cannibalistic classes to compute some spherical classes. At the end an alternative calculation of Adams operations in terms of Mahler series in p-adic analysis is given. This paper is a shortened version of the author’s thesis.
Rejuvenating Nanoclusters With 'Sleeping Anchors': Pre-Adaptation And Life Cycle

This article investigates how anchor firms sustain high tech clusters rejuvenation by means of technological pre-adaptation. Based on evidences are drawn from the comparison of the evolution of two nano-electronics clusters, i.e., Grenoble (France) and Catania (Italy) clusters which are sharing the same anchor tenant firm STMicroelectronics. Cluster rejuvenation comes from pre-adaptation of actors (scientific and technological diversity), competition amongst anchor tenant firms, competition and overlap amongst networks and the mobilization of sleeping anchors tenant organizations to renew actors and technologies. As soon as the process of specialization (asset specificity, network specificity, technology speciation) starts, it is important to stimulate pre-adaptation to avoid lock-in of the cluster on one technological trajectory
Finger Vein Recognition with Personalized Feature Selection

Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.
Performance Analysis of Chinese Webpage Categorizing Algorithm Based on Support Vector Machines (SVM)

Categorizing web automatically for users is a key technique of information society, and the key point of this technique is web training and categorization. This paper researches one of the important algorithm in this field—support vector machines (SVM). By analyzing and simulating 4 kinds of kernel function and 3 ways of feature selection, polynomial kernel function and document frequency is chosen for the best way in SVM algorithm. Meanwhile, pre-process algorithm is given in this paper in order to improve the efficiency of categorization. By simulation, importing pre-process method to SVM enhances the capability of the web categorization both in precision and time-consumption.
A note about the generalisation of the $C$-tests

In this exploratory note we ask the question of what a measure of performance for all tasks is like if we use a weighting of tasks based on a difficulty function. This difficulty function depends on the complexity of the (acceptable) solution for the task (instead of a universal distribution over tasks or an adaptive test). The resulting aggregations and decompositions are (now retrospectively) seen as the natural (and trivial) interactive generalisation of the C-tests.
OSGAR: a scene graph with uncertain transformations

An important problem for augmented reality is registration error. No system can be perfectly tracked, calibrated or modeled. As a result, the overlaid graphics are not aligned perfectly with objects in the physical world. This can be distracting, annoying or confusing. In this paper, we propose a method for mitigating the effects of registration errors that enables application developers to build dynamically adaptive AR displays. Our solution is implemented in a programming toolkit called OSGAR. Built upon OpenSceneGraph (OSG), OSGAR statistically characterizes registration errors, monitors those errors and, when a set of criteria are met, dynamically adapts the display to mitigate the effects of the errors. Because the architecture is based on a scene graph, it provides a simple, familiar and intuitive environment for application developers. We describe the components of OSGAR, discuss how several proposed methods for error registration can be implemented, and illustrate its use through a set of examples.
Local Path Planning of Mobile Robots in Dynamic Unknown Environment Based on Prediction of Collision

The velocity and its distribution of obstacles isobserved by an adaptive Unscented Kalman Filter, based onwhich the position of the dangerous region (potential collisionregion) is predicted. And based on its distribution, thedangerous region is expanded to ensure the security. Byfinding the best “Free Road” and estimate the “danger”, a datareduction technique is employed to compress all theinformation needed, with the help of which the efficiency isimproved significantly. Benefit from those the proposedalgorithm gets a better performance in dynamic environment.The results of simulations have proved that.
A Permanent-Magnet Tubular Linear Generator for Ocean Wave Energy Conversion

This paper presents a novel permanent-magnet tubular linear generator (PMTLG) buoy system designed to convert the linear motion of ocean waves into electrical energy. The design incorporates no working seals and a saltwater air-gap bearing surface integration between the PMTLG buoy components. The internal generator design will be discussed, in addition to the system integration with the buoy structure. The simulation and hardware results of the generator are presented.
A Novel Shape Feature for Fast Region-Based Pedestrian Recognition

A new class of shape features for region classification and high-level recognition is introduced. The novel Randomised Region Ray (RRR) features can be used to train binary decision trees for object category classification using an abstract representation of the scene. In particular we address the problem of human detection using an over segmented input image. We therefore do not rely on pixel values for training, instead we design and train specialised classifiers on the sparse set of semantic regions which compose the image. Thanks to the abstract nature of the input, the trained classifier has the potential to be fast and applicable to extreme imagery conditions. We demonstrate and evaluate its performance in people detection using a pedestrian dataset.
CakeML: a verified implementation of ML

We have developed and mechanically verified an ML system called CakeML, which supports a substantial subset of Standard ML. CakeML is implemented as an interactive read-eval-print loop (REPL) in x86-64 machine code. Our correctness theorem ensures that this REPL implementation prints only those results permitted by the semantics of CakeML. Our verification effort touches on a breadth of topics including lexing, parsing, type checking, incremental and dynamic compilation, garbage collection, arbitrary-precision arithmetic, and compiler bootstrapping. Our contributions are twofold. The first is simply in building a system that is end-to-end verified, demonstrating that each piece of such a verification effort can in practice be composed with the others, and ensuring that none of the pieces rely on any over-simplifying assumptions. The second is developing novel approaches to some of the more challenging aspects of the verification. In particular, our formally verified compiler can bootstrap itself: we apply the verified compiler to itself to produce a verified machine-code implementation of the compiler. Additionally, our compiler proof handles diverging input programs with a lightweight approach based on logical timeout exceptions. The entire development was carried out in the HOL4 theorem prover.
Power Spreading in Distributed Transmit Antennas

In distributed antenna system (DAS), delay spreads between the receiver and each transmit antenna are different due to the unequal propagation delays from distributed transmit antennas to mobile receivers. To exploit the merit of DAS, power spreading in distributed transmit antennas is proposed for OFDM-based MIMO systems over frequency-selective fading channel. In this scheme, partial power of the same symbol can be transmitted simultaneously in the distributed antennas after spatial power spreading. Then the multipath-faded symbol information from different transmitter can be resolved at the receiver. It can be considered that MTL duplicates of original symbol are obtained where L is the number of channel taps and MT is the number of transmit antennas, and hence higher multipath diversity could be achieved. Combined with frequency power spreading and ML detection, this scheme can achieve better performance than that without spatial power spreading. Simulation results are provided with 2 transmit and 2 receive antennas, demonstrating about 1.5 dB signal to noise ratio (SNR) gain is obtained at bit error rate (BER) of 1e-3.
Essays on Quantitative Analysis of Supply Chain Structures, Contracts and Coordination

This thesis consists of three separate, but related, essays that deal with the topic of how supply chain structure as well as the use of contracts impact performance of a supply chain. The main focus is the analysis of behavior of indirect-sale supply chains in terms of relative bargaining power and decision rights of the participants. Modeling as Stackelberg games, this thesis explores the existence of Nash equilibriums and the issues surrounding supply chain coordination. In Essay one, “The Role of Decision Structure in Supply Chain Coordination with Stochastic Demand”, the analysis focuses on how different supply chain structures affect the choice of contracts in coordination under a generalized setting in which more powerful agent does not necessarily assume the Stackelberg leadership. This study shows that an optimal coordinating contract is based not only upon the overstock liquidation advantage the supplier/retailer may have, but also upon the specific decision hierarchy in the supply chain. In Essay two, “Supply Chain Performance with Power Imbalanced Suppliers”, studies the effects of product substitution when suppliers and retailers have an imbalance of decision making power. In particular, we address the questions of structure dominance and why certain supply chain power structures are more stable.
Light propagation on quantum curved spacetime and back reaction effects

We study the electromagnetic field equations on an arbitrary quantum curved background in the semiclassical approximation of loop quantum gravity. The effective interaction Hamiltonian for the Maxwell and gravitational fields is obtained and the corresponding field equations, which can be expressed as a modified wave equation for the Maxwell potential, are derived. We use these results to analyze electromagnetic wave propagation on a quantum Robertson–Walker spacetime and show that Lorentz invariance is not preserved. The formalism developed can be applied to the case where back reaction effects on the metric due to the electromagnetic field are taken into account, leading to non-covariant field equations.
Traffic prediction for mobile network using Holt-Winter’s exponential smoothing

This paper presents a technique for evaluation of future radio traffic of circuit switched services in Erlang for near-term outlook using Holt-Winter's exponential smoothing. The proposed traffic prediction technique relies on analysis of traffic data on cells. We propose how to classify traffic data for prediction. The result from a trial in history data of commercial GSM/GPRS network is presented. It shows that predicted traffic is good fitted with original one within our classification. The technique should be used in automated overload warning and express estimation of future traffic for capacity planning.
Transcription Factor PU.1 Is Necessary for Development of Thymic and Myeloid Progenitor-Derived Dendritic Cells1

Dendritic cells (DCs) are a heterogeneous population of cells that are specialized for Ag processing and presentation. These cells are believed to derive from both myeloid- and lymphoid-committed precursors. Normal human PBMC-derived, human CD14+ cell (monocyte)-derived, and mouse hematopoietic progenitor-derived DCs were shown to express the hematopoietic cell-restricted, ets family transcription factor PU.1. These populations represent myeloid progenitor-derived DCs. Hematopoietic progenitor cells from PU.1 gene-disrupted (null) mice were unable to generate MHC class IIhigh, CD11c+ myeloid-derived DCs in vitro. Mouse thymic DCs are proposed to be derived from a committed lymphoid progenitor cell that can give rise to T cells as well as DCs. Previously, we showed that CD4 and CD8 T cells developed in PU.1 null mice in a delayed manner and in reduced number. We examined the thymus of 10- to 12-day-old PU.1 null mice and found no evidence of DEC-205+, MIDC-8+ DCs in this tissue. Our findings indicate that PU.1 regulates the development of both thymic and myeloid progenitor-derived populations of DCs, and expand its known role in hematopoietic development.
Untraceable VoIP Communication based on DC-nets

Untraceable communication is about hiding the identity of the sender or the recipient of a message. Currently most systems used in practice (e.g., TOR) rely on the principle that a message is routed via several relays to obfuscate its path through the network. However, as this increases the end-to-end latency it is not ideal for applications like Voice-over-IP (VoIP) communication, where participants will notice annoying delays if the data does not arrive fast enough. We propose an approach based on the paradigm of Dining Cryptographer networks (DC-nets) that can be used to realize untraceable communication within small groups. The main features of our approach are low latency and resilience to packet-loss and fault packets sent by malicious players. We consider the special case of VoIP communication and propose techniques for a P2P implementation. We expose existing problems and sketch possible future large-scale systems composed of multiple groups.
Automated Scoring of a Summary-Writing Task Designed to Measure Reading Comprehension

We introduce a cognitive framework for measuring reading comprehension that includes the use of novel summary writing tasks. We derive NLP features from the holistic rubric used to score the summaries written by students for such tasks and use them to design a preliminary, automated scoring system. Our results show that the automated approach performs well on summaries written by students for two different passages.