Miracle-dz/UniFAR-FTUs huggingface dataset:
Gauging kinematical and internal symmetry groups for extended systems: the Galilean one-time and two-times harmonic oscillators

The possible external couplings of an extended non-relativistic classical system are characterized by gauging its maximal dynamical symmetry group at the centre-of-mass. The Galilean one-time and two-times harmonic oscillators are exploited as models. The following remarkable results are then obtained: 1), a peculiar form of interaction of the system as a whole with the external gauge fields; 2), a modification of the dynamical part of the symmetry transformations, which is needed to take into account the alteration of the dynamics itself, induced by the gauge fields. In particular, the Yang - Mills fields associated to the internal rotations have the effect of modifying the time derivative of the internal variables in a scheme of minimal coupling (introduction of an internal covariant derivative); 3), given their dynamical effect, the Yang - Mills fields associated to the internal rotations apparently define a sort of Galilean spin connection, while the Yang - Mills fields associated to the quadrupole momentum and to the internal energy have the effect of introducing a sort of dynamically induced internal metric in the relative space.
Early Standard Model Measurement and Determination of Standard Model Background for Searches

The Large Hadron Collider (LHC) at CERN in Geneva (Switzerland) will go in operation in the coming months and will soon enable us to analyze the highest energy collisions ever produced at an accelerator. Beyond Standard Model searches at LHC require a detailed understanding of the detector performance, reconstruction algorithms and triggering. Precision measurements of Standard Model processes are also mandatory to acquire the necessary knowledge of Standard Model background. Both ATLAS and CMS efforts are hence addressed to determine the best calibration candles and to design a realistic plan for the initial period of data taking.
Multi-Pedestrian Detection from Effective Proposal in Crowd Scene

Pedestrian detection is a challenging issue, especially when multiple pedestrians are close in space. In this condition, the detection score generated by a single pedestrian (SP) may be too low to indicate those mutually occluded pedestrians. To address the above problem, multi-pedestrian (MP) detector is applied to detect group pedestrians through sliding windows search, which heavily increases the computation burden caused by tremendous amount of candidate windows. To well balance the effectiveness and efficiency, we present a novel MP detection method motivated by the effective proposals idea. In order to localize and segment high-quality candidate windows, we introduce bottom-up region proposals (which are called effective proposals) into the MP detection process. From which, high detection rate as well as low computation complexity can be simultaneously achieved. Experimental results on two standard datasets have validated the effectiveness and efficiency of the proposed method.
Mapping Smart Cities in the EU

This report was commissioned to provide background information and advice on Smart Cities in the European Union (EU) and to explain how existing mechanisms perform. In exploring this, a working definition of a Smart City is established and the cities fitting this definition across the Member States are mapped. An analysis of the objectives and Europe 2020 targets of Smart City initiatives finds that despite their early stage of development, Smart City objectives should be more explicit, well defined and clearly aligned to city development, innovation plans and Europe 2020 in order to be successful.
Tempo Modification of Mixed Music Signal by Nonlinear Time Scaling and Sinusoidal Modeling

Changing tempo of the music signal is one of the most basic signal processing applied to music signals. Traditional algorithms such as phase vocoder or Time-Domain Harmonic Scaling (TDHS) uniformly stretch and shrink the input signal. Therefore, those methods change not only the tempo but also the structure of the signal of the instrumental sound, such as attack and decay time, which changes the timbre of the instruments. To change the tempo of the music signal while keeping the Attack-Decay-Sustain-Release structure of the instruments, we need a non-linear modification of the time scale. To realize this, we propose a two-stage modeling of the music signal. The first stage represents the music signal using the sinusoidal model that expresses the harmonic part of the signal. Because non-harmonic component of the signal cannot be represented using the sinusoidal model, the residue of the sinusoidal model is analyzed using the linear prediction coding (LPC) in the second stage, which expresses the reverberation of the impulsive sound. Then we estimate the "stretchable parts" by observing the temporal smoothness of the spectrogram, and then only the stretchable parts are modified. We conducted experiments to modify the tempo of piano sounds, and compared the result with the conventional time stretch methods.
The breadth of semantics: reply to critics

Abstract In our 2015 book Imagination and Convention, we explore the scope and limits of linguistic knowledge in semantics and pragmatics for natural language. We draw heavily on the notion of coordination from David Lewis' book on conventions. To the extent that the account we develop is right, general principles like Grice's cooperative principle and the maxims of conversation have little to say about about interpretation. Three commentators—Anne Bezuidenhout, Laurence Horn, and Zoltan Gendler Szabo—discuss and evaluate our program in three essays in this issue. What follows is our response to their challenges.
Corrections to Unruh effect in tunneling formalism and mapping with Hawking effect

We consider coordinate systems adapted to accelerated observers, construct a generalised Rindler metric and then adopt a specific form of it to compute the semiclassical Unruh temperature, using a WKB approximation within a Hamilton Jacobi analysis in the tunneling picture. Corrections to this temperature are next computed by going beyond the usual WKB approximation. A connection of the corrected Unruh temperature with the Hawking temperature is established. This connection is also explained through the method of Global Embedding Minkowski Spacetime (GEMS).
AmphiBot II: An Amphibious Snake Robot that Crawls and Swims using a Central Pattern Generator

This article presents AmphiBot II, an am- phibious snake robot designed for both serpentine loco- motion (crawling) and swimming. It is controlled by an on-board central pattern generator (CPG) inspired by those found in vertebrates. The CPG is modelled as a chain of coupled nonlinear oscillators, and is designed to produce travelling waves. Its parameters can be modi- fled on the ∞y. We present the hardware of the robot and the structure of the CPG, then the systematic parameter tests done in simulation and with the real robot to char- acterize how the speed of locomotion depends on the parameters determining the frequency, amplitude and wavelength of the body undulation.
Visualizing Network Data

Networks are critical to modern society, and a thorough understanding of how they behave is crucial to their efficient operation. Fortunately, data on networks is plentiful; by visualizing this data, it is possible to greatly improve our understanding. Our focus is on visualizing the data associated with a network and not on simply visualizing the structure of the network itself. We begin with three static network displays; two of these use geographical relationships, while the third is a matrix arrangement that gives equal emphasis to all network links. Static displays can be swamped with large amounts of data; hence we introduce direct manipulation techniques that permit the graphs to continue to reveal relationships in the context of much more data. In effect, the static displays are parameterized so that interesting views may easily be discovered interactively. The software to carry out this network visualization is called SeeNet. >
Piecewise linear relaying: A low complexity parametric relaying

We investigate the Gaussian, three-nodes relay channel with orthogonal receive components, i.e., the transmitted signals from the source and the relay do not interfere with each other. We develop and analyze low-complexity symbol-wise (as opposed to block-wise) relaying strategies based on a one-dimensional, parametric piecewise linear (PL) mapping. We numerically compute and optimize the achievable rates obtained by the PL mapping for a certain number of design parameters. We conclude that optimized PL relaying always outperforms conventional instantaneous linear relaying (amplify-and-forward). We also illustrate that the proposed PL relaying can improve on sophisticated block Markov encoding (i.e., decode-and-forward) when the source-relay link is ill-conditioned (relative to other links). Furthermore, PL relaying can work at rates close to those achieved by side-information encoding (i.e., compress-and-forward), but at a much lower complexity.
Lightweight Management of Authorization Update on Cloud Data

While outsourcing data to cloud, security and efficiency issues should be taken into account. However, it is very challenging to design a secure and efficient mechanism supporting authorization updates. In this paper, we aim to provide a mechanism supporting authorization updates which only incurs a lightweight cost of authorization updates and meanwhile supports a high level of security. This mechanism is consisted of two encryption schemes performed in different layers. The inner-layer encryption scheme is performed on the original plaintext and the generated cipher text is called inner-layer cipher text, while a part of the inner-layer cipher text is encrypted by the outer-layer encryption scheme to generate cipher text, called out-layer cipher text. These two encryption schemes are both performed by data owner. The inner-layer encryption realizes the initial authorization policy, while the outer-layer encryption reflects the updated authorization policy. We implement the proposed mechanism and conduct extensive experiments. The experimental results demonstrate that the proposed mechanism outperforms previous existing approaches, e.g. single-layer encryption and double-layer encryption.
Extracting Information from the World-Wide Web: A Case Study of Fuel Cell Contracts

Partek, and Sonera. The contributions are gratefully acknowledged. Working in this very ambitious project has been challenging – but enjoyable – and I am pleased to be able to support the project with the work done for this thesis. I would like to thank my instructors Matti Keijola and Samuel Kaski as well as my supervisor professor Olli Simula for their guidance and valuable comments. I would especially like to thank my dear girlfriend Marjut for supporting and standing me during this thesis process.
A Textual Approach Based on Passages Using IR-n in WikipediaMM Task 2008

In this paper we have focused our efforts on comparing the behaviour of two relevance feedback methods in this task - LCA and PRF - and in checking if our passage based information rerieval (IR) system is useful in a competition with small sized documents. Furthermore we have added an adaptation to this domain based on decompound in single terms those file names which use a Camel Case notation. We base our decision on the belief that the most meaningful information of an image file appointed by a human is on the file name itself. Thus, it is important to make visible this terms when they are hidden in a compounded file name. Finally we have added a geographical query expansion and a visual concept expansion. We have obtained a 29th place within a total of 77 runs with our baseline run - which only used the passage IR system -, and a 3rd place obtained with our best run - which used the passage IR system with Camel Case decompounding -. It shows us on one hand the usefulness of our passage based IR system in this domain, and on the other hand it confirms our belief in the existence of specially meaningful information within the file names. In the the relevance feedback respect, we have obtained contradictory results about the suitability of LCA or PRF to the task, but we have found that LCA has a more robust behavior than PRF.
Balanced ensemble learning with adaptive bounds

Different to other re-sampling ensemble learning, negative correlation learning trains all individual models in an ensemble simultaneously and cooperatively. In negative correlation learning, each individual could see all training data, and adapt its target function based on what the rest of individuals in the ensemble have learned. In this paper, two error bounds are introduced in negative correlation learning. One is the upper bound of error output (UBEO) which divides the training data into two groups. The other is the lower bound of error rate (LBER) which is set as a switch. Before the error rate of the learned ensemble is higher than LBER, all training data is learned by negative correlation learning. As soon as the learned ensemble has a lower error rate than LBER, negative correlation learning will be applied to one group only specified by UBEO in which data points are near to the current decision boundary. This paper will examine the differences among the individual models in the ensemble by negative correlation learning with two bounds to determine how LBER and UBEO should be adapted in negative correlation learning.
Content networks: distributed routing decisions in presence of repeated queries

Content networks are overlay networks, enabling access to distributed contents on centralized servers or individual computers. Since the flooding-based routing scheme features poor scalability, we present a modification, which reduces the total network traffic while retaining the original efficiency. In choosy routing, each node, while passing an answer, remembers where it came from. Subsequently repeated queries about the same content are forwarded only to one neighbor. This way, the network learns effective routes. The simulations on several topology types have shown the expected behavior, with up to three-fold reduction in the overall query traffic.
Enhanced multivariable TS fuzzy modeling in neural network perspective

A new approach is presented to enhance fuzzy modeling using multidimensional fuzzy sets directly in the fuzzy model in place of decomposed fuzzy sets by projection. The antecedent fuzzy sets in the form of multivariable functions are represented in continuous form. This is accomplished by using a multi input and multi output neural network, which is in particular radial basis functions (RBF) network providing the required multivariable function approximation properties in a fuzzy model. The inputs of the network are fuzzy model inputs, outputs are the membership function values as to the multivariable fuzzy sets involved in the model. Thus, each output is restricted to one multivariable fuzzy set. The RBF network is trained according to the multidimensional fuzzy sets which are identified after fuzzy clustering of the data. Based on this, the linear model parameters are determined by the method of least squares in a straightforward manner. The transparency issues can be handled by means of projection process to have information about the shape and locations of the membership functions pertinent to each variable at the input. The accurate fuzzy modeling having been thus guaranteed the information on the linear model parameters are used to establish the multivariable fuzzy rules with their respective validity regions. The redundancy of the number of fuzzy sets can be circumvented by classical cluster merging algorithms available. In this approach, the fuzzy rules are determined from the local linear models, however in contrast with the conventional fuzzy modeling, the model outputs are determined by the multivariable fuzzy sets. To obtain regular sets, RBF network is trained by means of orthogonal least squares (OLS) method so that at the same time the convergence issues of general neural network training is eliminated.
MINI-COURSE: p-MODULAR REPRESENTATIONS OF p-ADIC GROUPS

1.1. The case ` 6= p. In this case, we are in the setting of the classical Local Langlands Correspondence, which can be stated (roughly) as follows: Let n ≥ 1. We then have an injective map (1)  continuous representations of Gal(Qp/Qp) on n-dimensional Q`-vector spaces, up to isomorphism  ↪−→  irreducible, admissible representations of GLn(Qp) on Q`-vector spaces, up to isomorphism 
Towards a model for determining the scope of ICT integration in the enterprise: the case of enterprise resource planning (ERP) systems

The question of integration of information systems (IS) into the planning and execution of operational activities has been the focus for researchers from different constituencies. Organisational theorists recognise the need for integrating mechanisms for co-ordinating the actions of sub-units within an organisation. Centralisation has been seen as a defensive reaction by organisations when placed under increasing external control , and also as a way to improve the efficiency of information processing, at least for routine tasks. In the meantime, researchers have been sceptical about the ability for structured information systems to deal with the complexity of the information flows within the organisation. Frameworks have also been identifying characteristics of the tasks themselves that have a bearing on the amount of information processing required. The real world is complex and moving, thus managers require flexibility in their interpretation of the mixed signals arising from this complexity. However, managers are working in environments where highly integrated information systems blur the distinction between what is real and what is virtual. There is a need for an integration approach allowing organisations to question which areas of activity are worth integrating, and conversely which areas are better left under local control. Where integrated, managers require processes for the maintenance of data integrity (people, tools, procedures). Based on field work involving two multi-national manufacturing companies, this paper proposes a framework for ERP integration, which describes the evolution of functionality gaps as an ongoing and inevitable process that requires management.
Mobile continuous nearest neighbor queries on air

In this paper, we propose new spatial query processing algorithms to support Mobile Continuous Nearest Neighbor Query (MCNNQ) in wireless broadcast environments. Each client (object) computes individually the function that best captures the locations of the moving objects, while a server is only responsible for delivering information gathered from the clients. Extensive experiments demonstrate that our location-based data dissemination algorithm significantly out-performs index-based solutions.
Low energy availability, not exercise stress, suppresses the diurnal rhythm of leptin in healthy young women.

Because the effect of exercise on leptin was not established, we controlled energy intake (I) and exercise energy expenditure (E) to distinguish the independent effects of energy availability (A = I - E) and exercise stress (everything associated with exercise except its energy cost) on the diurnal leptin rhythm in healthy young women. In random order, we set A = 45 and 10 kcal. kg lean body mass(-1) (LBM) x day(-1) for 4 days during the early follicular phase of separate menstrual cycles in sedentary (S, n = 7) and exercising (X, n = 9: E = 30 kcal x kg LBM(-1) x day(-1)) women. Low energy availability suppressed the 24-h mean (P < 10(-6)) and amplitude (P < 10(-5)), whereas exercise stress did not (both P > 0.2). Suppressions of the 24-h mean (-72 +/- 3 vs. -53 +/- 3%, P < 0.001) and amplitude (-85 +/- 3 vs. -58 +/- 6%, P < 0.001) were more extreme in S vs. X than previously reported effects on luteinizing hormone pulsatility and carbohydrate availability. Thus the diurnal rhythm of leptin depends on energy, or carbohydrate, availability, not intake, and exercise has no suppressive effect on the diurnal rhythm of leptin beyond the impact of its energy cost on energy availability.
Nonlinear Robust Regression Using Kernel Principal Component Analysis and R-Estimators

In recent years, many algorithms based on kernel principal component analysis (KPCA) have been proposed including kernel principal component regression (KPCR). KPCR can be viewed as a non-linearization of principal component regression (PCR) which uses the ordinary least squares (OLS) for estimating its regression coefficients. We use PCR to dispose the negative effects of multicollinearity in regression models. However, it is well known that the main disadvantage of OLS is its sensitiveness to the presence of outliers. Therefore, KPCR can be inappropriate to be used for data set containing outliers. In this paper, we propose a novel nonlinear robust technique using hybridization of KPCA and R-estimators. The proposed technique is compared to KPCR and gives better results than KPCR.
The Circular RNA Cdr1as Act as an Oncogene in Hepatocellular Carcinoma through Targeting miR-7 Expression

CircRNAs are a class of endogenous RNA that regulates gene expression at the post-transcriptional or transcriptionallevel through interacting with other molecules or microRNAs. Increasing studies have demonstrated that circRNAs play a crucial role in biology processes. CircRNAs are proved as potentialbiomarkers in many diseases including cancers. However, the role of Cdr1as in Hepatocellular carcinoma (HCC) remains to be elucidated. We demonstrated that Cdr1as expression was upregulated in HCC tissues compared with the adjacent non-tumor tissues. In addtion, miR-7 expression was downregulated in HCC tissues compared with the adjacent non-tumor tissues. Moreover, the expression level of miR-7 was inversely correlated with that in HCC tissues. Knockdown of Cdr1as suppressed the HCC cell proliferation and invasion. Overexpression of miR-7 inhibited the HCC cell proliferation and invasion. Overexpression of miR-7 could suppress the direct target gene CCNE1 and PIK3CD expression. Knockdown of Cdr1as suppressed the expression of miR-7 and also inhibited the CCNE1 and PIK3CD expression. Furthermore, knockdown of Cdr1as suppressed the HCC cell proliferation and invasion through targeting miR-7. These data suggested that Cdr1as acted as an oncogene partly through targeting miR-7 in HCC.
Myogenin expression, cell cycle withdrawal, and phenotypic differentiation are temporally separable events that precede cell fusion upon myogenesis

During terminal differentiation of skeletal myoblasts, cells fuse to form postmitotic multinucleated myotubes that cannot reinitiate DNA synthesis. Here we investigated the temporal relationships among these events during in vitro differentiation of C2C12 myoblasts. Cells expressing myogenin, a marker for the entry of myoblasts into the differentiation pathway, were detected first during myogenesis, followed by the appearance of mononucleated cells expressing both myogenin and the cell cycle inhibitor p21. Although expression of both proteins was sustained in mitogen-restimulated myocytes, 5- bromodeoxyuridine incorporation experiments in serum-starved cultures revealed that myogenin-positive cells remained capable of replicating DNA. In contrast, subsequent expression of p21 in differentiating myoblasts correlated with the establishment of the postmitotic state. Later during myogenesis, postmitotic (p21-positive) mononucleated myoblasts activated the expression of the muscle structural protein myosin heavy chain, and then fused to form multinucleated myotubes. Thus, despite the asynchrony in the commitment to differentiation, skeletal myogenesis is a highly ordered process of temporally separable events that begins with myogenin expression, followed by p21 induction and cell cycle arrest, then phenotypic differentiation, and finally, cell fusion.