Miracle-dz/UniFAR-FTUs huggingface dataset:
The Disaster of Central Control An Impressive Example from Nature

I t is commonplace to say that central control of large complex entities is doomed to fail. We have numerous examples from economies and societies of the past and the present demonstrating inefficiency when the systems exceed a certain size. In the old days, wise emperors were well aware of the problem and answered appropriately by the principle of divide et impera. Nature seems to have an elegant solution the problem too: Modular structure and partial autonomy of modules. The best example is the multicellular organism where the individual cell retains as much autonomy in metabolism as can be tolerated without endangering the whole system: A little more independence of somatic cells, for example, leads to tumor formation. Efficient division of labor is observed in bacterial cells too. No wonder I have thought that we can always learn from biology how to manage successfully the most sophisticated situations and how to handle and control complexity. It was a shocking experience therefore when I read a recent preprint and previous articles by John Mattick and his colleagues [1–3]. They present a plausible interpretation of the limitation in bacterial genome sizes based on DNA sequences: The number of genes in prokaryotes is bounded by an unaffordable regulatory overhead in genomes that are too large. This view is supported by an empirical fit of a power law to the data derived from some 90 fully sequenced prokaryotic genomes. The number of regulatory genes grows approximately with the square of the total number of genes, nr 1.63 10 5 n 1.2 10 5 n, where nr and n are the numbers of regulatory genes and all genes, respectively. Thus, complete regulation of ribosomal protein synthesis—when centrally organized on the DNA level in the spirit of the elegant operon mechanism as discovered by Jaques Monod, François Jacob, and André Lwow—falls into an inefficiency trap when genomes become too large. The guess is that the critical genome size for prokaryotes is in the range of 10,000 genes and indeed, this appears to be the size limit of bacterial genomes. Eukaryotes—these are all higher organisms from yeast to man—make use of other control mechanism in addition to genetic control at the DNA level. Examples are alternative splicing of precursor messenger RNAs (for reviews see [4, 5]), small interfering RNAs [6], genomic imprinting [7, 8], and other forms of epigenetic regulation of gene expression and silencing. For the purpose of illustration we shall consider here an idealized—and perhaps not yet fully accepted—model view of alternative splicing: The translation product of the same DNA stretch yields slightly or substantially different proteins depending on the individual organism and the particular tissue in which it is expressed. Diverse proteins are obtained by cutting out different sections called introns from the precursor RNA sequence. A well-known example is the protein that controls sex PETER SCHUSTER
Proxy re-signatures: new definitions, algorithms, and applications

In 1998, Blaze, Bleumer, and Strauss (BBS) proposed proxy re-signatures, in which a semi-trusted proxy acts as a translator between Alice and Bob. To translate, the proxy converts a signature from Alice into a signature from Bob on the same message. The proxy, however, does not learn any signing key and cannot sign arbitrary messages on behalf of either Alice or Bob. Since the BBS proposal, the proxy re-signature primitive has been largely ignored, but we show that it is a very useful tool for sharing web certificates, forming weak group signatures, and authenticating a network path.We begin our results by formalizing the definition of security for a proxy re-signature. We next substantiate the need for improved schemes by pointing out certain weaknesses of the original BBS proxy re-signature scheme which make it unfit for most practical applications. We then present two secure proxy re-signature schemes based on bilinear maps. Our first scheme relies on the Computational Diffie-Hellman (CDH) assumption; here the proxy can translate from Alice to Bob and vice-versa. Our second scheme relies on the CDH and 2-Discrete Logarithm (2-DL) assumptions and achieves a stronger security guarantee -- the proxy is only able to translate in one direction. Constructing such a scheme has been an open problem since proposed by BBS in 1998. Furthermore in this second scheme, even if the delegator and the proxy collude, they cannot sign on behalf of the delegatee. Both schemes are efficient and secure in the random oracle model.
Dense Stellar Cores in Merger Remnants

We use numerical models which include star formation to analyze the mass profiles of remnants formed by mergers of disk galaxies. During a merger, dissipation in gas and ensuing star formation leave behind a dense stellar core in the remnant. Rather than joining smoothly onto a de Vaucouleurs profile, the starburst population leads to a sharp break in the surface density profile at a few percent of the effective radius. While our results are preliminary, the lack of such signatures in most elliptical galaxies suggests that mergers of gas-rich disk galaxies may not have contributed greatly to the populations of present-day ellipticals.
Hidden Dynamic Probabilistic Models for Labeling Sequence Data

We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external class dynamics to label sequence data. We introduce a small number of hidden state variables to model the sub-structure of a observation sequence and learn dynamics between different class labels. An HDCRF offers several advantages over previous discriminative models and is attractive both, conceptually and computationally. We performed experiments on three well-established sequence labeling tasks in natural language, including part-of-speech tagging, noun phrase chunking, and named entity recognition. The results demonstrate the validity and competitiveness of our model. In addition, our model compares favorably with current state-of-the-art sequence labeling approach, Conditional Random Fields (CRFs), which can only model the external dynamics.
Adaptive bots for real-time strategy games via map characterization

This paper presents a proposal for a fast on-line map analysis for the RTS game Planet Wars in order to define specialized strategies for an autonomous bot. This analysis is used to tackle two constraints of the game, as featured in the Google AI Challenge 2010: the players cannot store any information from turn to turn, and there is a limited action time of just one second. They imply that the bot must analyze the game map quickly, to adapt its strategy during the game. Based in our previous work, in this paper we have evolved bots for different types of maps. Then, all bots are combined in one, to choose the evolved strategy depending on the geographical configuration of the game in each turn. Several experiments have been conducted to test the new approach, which outperforms our previous version, based on an off-line general training.
Modeling and Simulation of 6-DOF Parallel Manipulator Based on PID Control with Gravity Compensation in Simulink/ADAMS

A novel model-based controller for six degree of freedom (dof) parallel manipulator-PID controller with gravity compensation is developed, in order to improve the control precision of six-dof hydraulic driven parallel manipulator with long stroke hydraulic actuator and heavy load. In this paper, six-dof parallel manipulator is described as a thirteen rigid-body systems. The mathematical model of gravity item including upper platform and hydraulic cylinders is built using Kane method in six dimensions generalized coordinates system, based on close-form solutions and Newton-Raphson method, forward kinematics and inverse kinematics of the six-dof parallel manipulator are established. The PID controller with gravity compensation is presented with the feedback of cylinder length of platform, desired trajectories and dynamics gravity as the input. The physical systems of 6dof parallel manipulator are modeled by ADAMS, and the PID controller with gravity compensation is built with Simulink. The whole control system of 6-dof parallel manipulator is obtained by connecting ADAMS plant with PID control system with gravity compensation in Simulink. The simulation of the whole systems is executed in Simulink, the simulation results indicate the PID controller with gravity compensation can eliminate steady state error of 6-dof hydraulic driven parallel manipulator and improve the control precision.
Poster Abstract: LocaLight - A Battery-Free Passive Localization System Using Visible Light

Most existing indoor localization systems are battery-powered and use the changes in Radio Frequency (RF) signals to localize objects. In this paper, we present LocaLight: a battery-free indoor localization system that localizes objects using visible light by tracking the shadow they cast. By sensing a drop in the intensity of ambient light caused by the presence of a shadow, LocaLight localizes the object. Since the position of the shadow can be predicted, it is possible to localize the object in a sensitive area by carefully positioning the light sensors and the overhead lights. Our initial results suggest that LocaLight achieves an accuracy comparable to many of the state-of-the art solutions that use RF.
The role of cognitive skills in economic development

The role of improved schooling, a central part of most development strategies, has become controversial because expansion of school attainment has not guaranteed improved economic conditions. This paper reviews the role of cognitive skills in promoting economic well-being, with a particular focus on the role of school quality and quantity. It concludes that there is strong evidence that the cognitive skills of the population - rather than mere school attainment - are powerfully related to individual earnings, to the distribution of income, and to economic growth. New empirical results show the importance of both minimal and high level skills, the complementarity of skills and the quality of economic institutions, and the robustness of the relationship between skills and growth. International comparisons incorporating expanded data on cognitive skills reveal much larger skill deficits in developing countries than generally derived from just school enrollment and attainment. The magnitude of change needed makes clear that closing the economic gap with developed countries will require major structural changes in schooling institutions.
A nonsense mutation of human XRCC4 is associated with adult-onset progressive encephalocardiomyopathy

We studied two monozygotic twins, born to first cousins, affected by a multisystem disease. At birth, they both presented with bilateral cryptorchidism and malformations. Since early adulthood, they developed a slowly progressive neurological syndrome, with cerebellar and pyramidal signs, cognitive impairment, and depression. Dilating cardiomyopathy is also present in both. By whole‐exome sequencing, we found a homozygous nucleotide change in XRCC4 (c.673C>T), predicted to introduce a premature stop codon (p.R225*). XRCC4 transcript levels were profoundly reduced, and the protein was undetectable in patients' skin fibroblasts. XRCC4 plays an important role in non‐homologous end joining of DNA double‐strand breaks (DSB), a system that is involved in repairing DNA damage from, for example, ionizing radiations. Gamma‐irradiated mutant cells demonstrated reduction, but not abolition, of DSB repair. In contrast with embryonic lethality of the Xrcc4 KO mouse, nonsense mutations in human XRCC4 have recently been associated with primordial dwarfism and, in our cases, with adult‐onset neurological impairment, suggesting an important role for DNA repair in the brain. Surprisingly, neither immunodeficiency nor predisposition to malignancy was reported in these patients.
Texture and Relief Estimation from Multiple Georeferenced Images

1-3 (a): hemispherical tiling used for node acquisition; (b): textured hemispher-1-4 (a): the sweep-plane algorithm; (b): the recovered model (not textured). 2-2 (a): the position of the camera (red) and of the facade (white) in the modeled environment. The building in the foreground is projected onto the facade; (b): a color image showing the warped image; (c): the binary corresponding 2-3 (a): the position of the camera (red) and of the facade (white) in the modeled environment; (b): a color image showing low effective resolution at the left of the image due to projective distortion; (c): the corresponding Obliqueness 2-8 (a): result with median algorithm (b): result with improved algorithm. 24 2-9 Warped images and result after the process of the algorithm for one facade. 26 2-10 Warped images and result after the process of the algorithm for another facade. 27
Animal Cognition: Theory and Evidence Review of Species of Mind: The Philosophy and Biology of Cognitive Ethology by Colin Allen and Marc Bekoff

Species of mind seeks primarily to establish the credentials of cognitive ethology as an exciting and above all respectable branch of scientific inquiry. Difficulties in achieving the aims of cognitive ethology are not downplayed, but it is argued that they can be overcome sufficiently to sustain an empirical research program. An important subgoal is the promotion of an interdisciplinary approach to the required research.
Classification based 3-D surface analysis : predicting springback in sheet metal forming

This paper describes an application of data mining, namely classification, with respect to 3-D surface analysis. More specifically in the context of sheet metal forming, especially Asymmetric Incremental Sheet Forming (AISF). The issue with sheet metal forming processes is that their application results in springback, which means that the resulting shape is not necessarily the desired shape. Errors are introduced in a non-linear manner for a variety of reasons, but the main contributor is the geometry of the desired shape. A Local Geometry Matrix (LGM) representation is thus proposed that allows the capture of local 3-D surface geometries in such a way that classifier generators can be effectively applied. The resulting classifier can then be used to predict errors with respect to new surfaces to be manufactured so that some correcting strategy can be applied. The reported evaluation of the proposed technique indicates that excellent results can be produced.
Analysis of Ocular Dominance Pattern Formation in a High-dimensional Self-organizing-map-model

Using a distortion measure for the states emerging in self-organizing maps (SOM) we mathematically analyze a recently proposed high-dimensional map formation model for ocular dominance patterns. We calculate critical values of parameters for ocular dominance states to occur, and we determine how the pattern layout depends on these parameters. The analysis reveals an increase of ocular dominance band width with decreasing correlation, consistent with a recently observed increase of band width in strabismic cats. In subsequent simulations these analytical results are corroborated, irrespective of the speciic normalization procedure (multiplicative or subtractive) employed in the simulations.
DIFFERENTIABILITY OF M-FUNCTIONALS OF LOCATION AND SCATTER BASED ON T LIKELIHOODS

† Department of Mathematics, Massachusetts Institute of Technology Abstract. The paper aims at finding widely and smoothly defined nonparametric location and scatter functionals. As a convenient vehicle, maximum likelihood estimation of the location vector µ and scatter matrixof an elliptically symmetric t distribution on R d with degrees of freedom � > 1 extends to an M-functional defined on all probability distributions P in a weakly open, weakly dense domain U. Here U consists of P putting not too much mass in hyperplanes of dimension < d, as shown for empirical measures by Kent and Tyler (Ann. Statist. 1991). It is shown here that (µ,�) is analytic on U, for the bounded Lipschitz norm, or for d = 1, for the sup norm on distribution functions. For k = 1,2,. , and other norms, depending on k and more directly adapted to t functionals, one has continuous differentiability of order k, allowing the delta-method to be applied to (µ,�) for any P in U, which can be arbitrarily heavy-tailed. These results imply asymptotic normality of the corresponding M-estimators (µn,�n). In dimension d = 1 only, the tfunctional (µ,�) extends to be defined and weakly continuous at all P.
A Reliable Transaction Processing Framework for Digital Business Ecosystems

A key indicator of today's global business system supported by service oriented architecture (SOA), is the reliability and uptime. This concern is crucial for e-commerce sites and mission-critical business applications. SOA modelling is used to implement the concept of digital business ecosystem (DBE). In computing environment of DBE a chain of components link business applications together, and the strength of this chain, in terms of reliability and performance, will determine the success or failure of the business. One way to make the chain stronger is to increase the reliability of all components involved, especially the critical components of the chain. In this paper, we address the reliability issue of digital ecosystem's transactions. The major contribution of this research is to propose a framework for reliable transactions in DE, via the analysis of the reliability for Web services computing.
APPROXIMATIONS FROM SUBSPACES FOR THE SINGULAR VALUE PROBLEM

The computation (or approximation) of some of the smallest or largest singular values of a large sparse matrix is a big challenge, having many important applications. In this talk we discuss approximations to singular triples that can be obtained from subspaces. One of the topics is the concept of harmonic singular triples, introduced in [1]. The word “harmonic” expresses the fact that we try to approximate the smallest singular value by approximating the largest singular value of the inverse of the matrix. We give a definition, some properties, and show how harmonic singular values can be used in subspace methods. Some applications are given.
Multi-Sensor Fusion for Enhanced Contextual Awareness of Everyday Activities with Ubiquitous Devices

In this paper, the authors investigate the role that smart devices, including smartphones and smartwatches, can play in identifying activities of daily living. A feasibility study involving N = 10 participants was carried out to evaluate the devices' ability to differentiate between nine everyday activities. The activities examined include walking, running, cycling, standing, sitting, elevator ascents, elevator descents, stair ascents and stair descents. The authors also evaluated the ability of these devices to differentiate indoors from outdoors, with the aim of enhancing contextual awareness. Data from this study was used to train and test five well known machine learning algorithms: C4.5, CART, Naïve Bayes, Multi-Layer Perceptrons and finally Support Vector Machines. Both single and multi-sensor approaches were examined to better understand the role each sensor in the device can play in unobtrusive activity recognition. The authors found overall results to be promising, with some models correctly classifying up to 100% of all instances.
Contextual Learning in the Selective Attention for Identification model (CL-SAIM): Modeling contextual cueing in visual search tasks

Visual search is a commonly-used paradigm in psychological studies of attention. It is well-known that search efficiency is influenced by a broad range of factors, e.g. the featural similarity between targets and distractors [4] or the featural configuration (see [16] for a review). Recently, a series of paper by Chun and colleagues (see [1] for a review) has established a new factor that influences search termed ’contextual cueing’: visual search is more efficient when targets and distractors are repeated in the same locations across trials, compared with when they fall in new locations. In order to simulate this effect we extended the Selective Attention for Identification model (SAIM [5, 7]) with a mechanism for contextual learning (CL-SAIM). The learning mechanism is based on a Hop field pattern memory with asymmetric weights. This memory module integrates two functions: On one hand it stores the spatial configuration of search displays, and on the other it improves target detection for already seen displays. In this paper we will demonstrate that this relatively simple extension of SAIM is cable of simulating the experimental findings by [2].
Neural Networks and the Time Neural Networks and the Time Neural Networks and the Time Neural Networks and the Time----Sliced Sliced Sliced Sliced Paradigm for Speech Recognition Paradigm for Speech Recognition Paradigm for Speech Recognition Paradigm for Speech Recognition

The Time-Slicing paradigm is a newly developed method for the training of neural networks for speech recognition. The neural net is trained to spot the syllables in a continuous stream of speech. It generates a transcription of the utterance, be it a word, a phrase, etc. Combined with a simple error recovery method the desired units (words or phrases) can be retrieved. This paradigm uses a recurrent neural network trained in a modular fashion with natural connectionist glue. It processes the input signal sequentially regardless of the input's length and immediately extracts the syllables spotted in the speech stream. As an example, this character string is then compared to a set of possible words, picking out the five closest candidates. In this paper we describe the time-slicing paradigm and the training of the recurrent neural network together with details about the training samples. It also introduces the concept of natural connectionist glue and the recurrent neural network's architecture used for this purpose. Additionally we explain the errors found in the output and the process to reduce them and recover the correct words. The recognition rates of the network and the recovery rates for the words are also shown. The presented examples and recognition rates demonstrate the potential of the
Templates for Misuse Case Description

Use cases have proven helpful for eliciting, communicating and documenting requirements. But whereas functional requirements are well supported, use cases provide less support for working with extra-functional requirements, such as security requirements. With the advent of e-commerce applications, security and other extra-functional requirements are growing in importance. In an earlier paper, the authors have introduced the concept of misuse cases – inverted use cases to denote functions that should not be possible to perform in a system. In this paper, security related misuse cases are elaborated in further detail through a discussion of templates for their textual description.
Auditory processing of speech signals for robust speech recognition in real-world noisy environments

This paper presents a new approach to an auditory model for robust speech recognition in noisy environments. The proposed model consists of cochlear bandpass filters and nonlinear operations in which frequency information of the signal is obtained by zero-crossing intervals. Intensity information is also incorporated by a peak detector and a compressive nonlinearity. The robustness of the zero-crossings in spectral estimation is verified by analyzing the variance of the level-crossing intervals as a function of the crossing level values. Compared with other auditory models, the proposed auditory model is computationally efficient, free from many unknown parameters, and able to serve as a robust front-end for speech recognition in noisy environments. Experimental results of speech recognition demonstrate the robustness of the proposed method in various types of noisy environments.