Miracle-dz/UniFAR-FTUs huggingface dataset:
NeedleHaystack: a program for the rapid recognition of local structures in large sets of atomic coordinates

A program that computes molecular superpositions is presented. A possible large molecule (target = haystack) is scanned for the occurrence of a given molecular motif (model = needle) within tolerances. The advance over other methods is that it can handle very large atom sets, e.g. targets of up to 100000 atoms, and does not necessarily require any chemical information and connectivity between atoms: chemical constraints to restrict the solution space are not used to relate non-obvious superpositions based on a geometric fit. The specialization to a needle-in-a-haystack problem allows a very fast algorithm. Trade-offs between run time and tolerance levels are possible. The program is fast enough to screen large databases in an acceptable time. An executable for Linux on Pentium-compatible machines is available free of charge at http://www.charite. de/bioinf/haystack. It is a command-line executable well suited for scripts and distributed computing. A Web interface for immediate testing is also available at this address.
Five Questions on Prion Diseases

Prion diseases are characterized by deposition of PrPSc, a misfolded and aggregated isoform of the host-encoded cellular prion protein (PrPC), within the central nervous system (CNS) and other organs. Here we review the current knowledge on five issues relevant to prion diseases: (1) how do prions enter the body, (2) how do prions reach the central nervous system, (3) how do prions damage the CNS, (4) do mammals have an antiprion defense system, and (5) how can the prion problem be resolved for good.
Kangaroo: Workload-Aware Processing of Range Data and Range Queries in Hadoop

Despite the importance and widespread use of range data, e.g., time intervals, spatial ranges, etc., little attention has been devoted to study the processing and querying of range data in the context of big data. The main challenge relies in the nature of the traditional index structures e.g., B-Tree and R-Tree, being centralized by nature, and hence are almost crippled when deployed in a distributed environment. To address this challenge, this paper presents Kangaroo, a system built on top of Hadoop to optimize the execution of range queries over range data. The main idea behind Kangaroo is to split the data into non-overlapping partitions in a way that minimizes the query execution time. Kangaroo is query workload-aware, i.e., results in partitioning layouts that minimize the query processing time of given query patterns. In this paper, we study the design challenges Kangaroo addresses in order to be deployed on top of a distributed file system, i.e., HDFS. We also study four different partitioning schemes that Kangaroo can support. With extensive experiments using real range data of more than one billion records and real query workload of more than 30,000 queries, we show that the partitioning schemes of Kangaroo can significantly reduce the I/O of range queries on range data.
Weight Shifting Strategies and Discomfort during Prolonged Standing

Over half of the top ten occupations in the United States require prolonged standing, translating to nearly 3.2 million people who spend the majority of their workday standing (Occupational Employment Statistics, 2014). Continual exposure to muscle fatigue, blood pooling, and cartilage compression due to prolonged standing may lead to long term injuries and damage. Current interventions show limited effectiveness in situ and in laboratory settings. The goal of this study is to investigate how weight shifting strategies may be used to alleviate discomfort. Seven subjects stood for one hour and reported their discomfort while weight distribution data was collected. Strategy significantly affected discomfort for overall tiredness (p < 0.0001), leg tiredness (p < 0.002), upper legs (p < 0.005), and feet (p < 0.0024). Those who use a moderate to full strategy reported less overall discomfort than moderate and full (p < 0.001) shifters. Standing strategy may minimize discomfort during the workday.
The role of the free-response receiver operating characteristic method for dose and image quality optimisation

This thesis describes the value of the free-response receiver operating characteristic (FROC) paradigm for dose and image quality optimisation in a niche area of imaging. The empirical works discussed in this thesis focus on the diagnostic value of the low-resolution computed tomography (CT) images acquired for attenuation correction (AC) – a process primarily used to correct for photon attenuation with images produced merely as a consequence of the exposure. The potential discovery of incidental findings on these images was investigated. The observers taking part in the empirical studies were generally lacking in significant experience of interpreting CT images. As a consequence it was also deemed valuable to investigate the value of the novice observer in free-response studies. A further methodological consideration for studies of this kind is consistent and reliable image display and FROC data collection. Prototype software, ROCView, was designed and developed to make this an easy process and the key functionality and impact is analysed here. In addition to the empirical works, two review papers, aimed at the technologists and radiographers performing low-resolution CT for AC, are summarised. They explain the value of the FROC paradigm and the jackkinfe alternative FROC (JAFROC) analysis method to a wide audience in nuclear medicine.
A Simple Approach to Unknown Word Processing in Japanese Morphological Analysis

This paper presents a simple but effective approach to unknown word processing in Japanese morphological analysis, which handles 1) unknown words that are derived from words in a pre-defined lexicon and 2) unknown onomatopoeias. Our approach leverages derivation rules and onomatopoeia patterns, and correctly recognizes certain types of unknown words. Experiments revealed that our approach recognized about 4,500 unknown words in 100,000 Web sentences with only 80 harmful side effects and a 6% loss in speed.
A semiparametric Bayesian model for repeatedly repeated binary outcomes

Summary. We discuss the analysis of data from single‐nucleotide polymorphism arrays comparing tumour and normal tissues. The data consist of sequences of indicators for loss of heterozygosity (LOH) and involve three nested levels of repetition: chromosomes for a given patient, regions within chromosomes and single‐nucleotide polymorphisms nested within regions. We propose to analyse these data by using a semiparametric model for multilevel repeated binary data. At the top level of the hierarchy we assume a sampling model for the observed binary LOH sequences that arises from a partial exchangeability argument. This implies a mixture of Markov chains model. The mixture is defined with respect to the Markov transition probabilities. We assume a non‐parametric prior for the random‐mixing measure. The resulting model takes the form of a semiparametric random‐effects model with the matrix of transition probabilities being the random effects. The model includes appropriate dependence assumptions for the two remaining levels of the hierarchy, i.e. for regions within chromosomes and for chromosomes within patient. We use the model to identify regions of increased LOH in a data set coming from a study of treatment‐related leukaemia in children with an initial cancer diagnostic. The model successfully identifies the desired regions and performs well compared with other available alternatives.
Vita: A Crowdsensing-Oriented Mobile Cyber-Physical System

As a prominent subcategory of cyber-physical systems, mobile cyber-physical systems could take advantage of widely used mobile devices, such as smartphones, as a convenient and economical platform that facilitates sophisticated and ubiquitous mobile sensing applications between humans and the surrounding physical world. This paper presents Vita, a novel mobile cyber-physical system for crowdsensing applications, which enables mobile users to perform mobile crowdsensing tasks in an efficient manner through mobile devices. Vita provides a flexible and universal architecture across mobile devices and cloud computing platforms by integrating the service-oriented architecture with resource optimization mechanism for crowdsensing, with extensive supports to application developers and end users. The customized platform of Vita enables intelligent deployments of tasks between humans in the physical world, and dynamic collaborations of services between mobile devices and cloud computing platform during run-time of mobile devices with service failure handling support. Our practical experiments show that Vita performs its tasks efficiently with a low computation and communication overhead on mobile devices, and eases the development of multiple mobile crowdsensing applications and services. In addition, we present a mobile crowdsensing application, Smart City, developed on Vita to demonstrate the functionalities and practical usage of Vita.
SYSTEM DYNAMICS AND ITS IMPACT ON MANAGERIAL DECISION MAKING

System Dynamics (SD) is a widely used methodology to study complex feedback structures using computer simulation models. However much of its success is attributed to anecdotal evidence. This paper discusses the effect of various SD interventions on dynamic decision making. A series of controlled experiments to test the effect of system interventions is proposed. These effects are analysed by measuring the change in mental models of decision makers (1) as the level of decision aid is increased and (2) as the complexity of the model is increased. The aim of this research is to scientifically test systems-based decision aids thereby resulting in increased confidence of their use.
Focusing on Computation with Binding

Variable binding is a prevalent feature of the syntax and proof theory of many logical systems. In this paper, we define a programming language that provides intrinsic support for both representing and computing with binding. This language is extracted as the Curry-Howard interpretation of a focused sequent calculus with two kinds of implication, of opposite polarity. The representational arrow extends systems of definitional reflection with the notion of a scoped inference rule, which permits the adequate representation of binding via higher-order abstract syntax. On the other hand, the usual computational arrow classifies recursive functions over such higher-order data. Unlike many previous approaches, both binding and computation can mix freely. Following Zeilberger [POPL 2008], the computational function space admits a form of open-endedness, in that it is represented by an abstract map from patterns to expressions. As we demonstrate with Coq and Agda implementations, this has the important practical benefit that we can reuse the pattern coverage checking of these tools.
Introduction to quantum mechanics and the quantum-classical transition

In this paper we present a survey of the use of differential geometric formalisms to describe Quantum Mechanics. We analyze Schroedinger and Heisenberg frameworks from this perspective and discuss how the momentum map associated to the action of the unitary group on the Hilbert space allows to relate both approaches. We also study Weyl-Wigner approach to Quantum Mechanics and discuss the implications of bi-Hamiltonian structures at the quantum level.
Vocalizations produced in the second year of life in response to speaking and singing

We compared infants’ vocalizations produced both in singing and speaking conditions. In this study we collected the vocalizations of 12 infants aged between 12 and 24 months. Each 30-minute session integrated two stimulus conditions – speaking and singing. An acoustic analysis was developed in order to measure both segmental properties and melodic and rhythmic features. The results showed significant differences in the vocalizations to which the two stimulus conditions gave rise: in the duration of the vocalizations and the duration of the phonation, the number of nuclei and the duration of each nucleus present in the vocalizations. In particular, the greater extension of vowels in vocalizations in response to the singing condition seems to be distinctive from those produced in response to the speaking condition. This may reveal that there is a precocious distinction between the singing voice and the speaking voice. The acoustic analysis that we used shows promise in monitoring children’s sequential singing development from early infancy onwards.
Analysis and Design of an Active Integrated Mach-Zehnder Interferometer with Semiconductor Optical Amplifiers and External Feedback Loop for All-Optical Self-Switching

We investigate the spectral properties of an active integrated Mach-Zehnder Interferometer (MZI) with Semiconductor Optical Amplifiers (SOA) inserted in its arms and provided with an external feedback loop. The whole system is described in the frame of an original extended Scattering Matrix Formalism including internal sources, that takes into account the saturation of each active medium under the influence of both signal and Amplified Spontaneous Emission.
Simulation of negative permittivity and negative permeability by means of evanescent waveguide Modes-theory and experiment

In this paper, the theoretical foundations of the equivalence between waveguide propagation below cutoff and artificial plasmas are carefully analyzed through the derivation of the propagation constants of normal modes in waveguides filled with anisotropic plasmas. The equivalence between waveguide and dielectric plasma proposed by Marquees et al., which is valid for evanescent TE modes, has a dual counterpart for magnetic plasmas and evanescent TM modes. This new equivalence states that a negative magnetic permeability medium can be simulated by means of TM modes below their cutoff frequencies. The need of an anisotropic filling of the waveguide for the equivalence between plasmas and evanescent modes is also highlighted. To exemplify the applicability of this new equivalence, a structure that implements a double-negative medium has been proposed. Full-wave simulations of the proposed structure and measurements from an experimental setup are presented, both of which corroborate the new equivalence's validity.
REAL TIME FLOOD FORECASTING-INDIAN EXPERIENCES

The real time flood forecasting is one of the most effective nonstructural measures for flood management. For formulating the flood forecast in the real time, the observed meteorological and flow data are transmitted to the forecasting station through the different means of data communication which include telephone, wireless and network of telemetry stations etc. The collected meteorological and flow data in real time are then used into the calibrated & validated real time flood forecasting model to forecast the flood flow and corresponding water levels for different lead periods varying from few hours to few days depending on the size of catchment and purpose of the forecast. The structure of the model should be simple and it should not have excessive input requirements, but at the same time the forecasted flood must be as accurate as possible. Different types of real time flood forecasting techniques and models have been suggested and used by many investigators. These can be broadly classified into (i) deterministic models, (ii) stochastic and statistical models and more recently (iii) Artificial Neural Network (ANN) and fuzzy logic techniques. In India the various flood forecasting centers are using different forecasting models, based on the availability of hydrological and hydro-meteorological data, basin characteristic, computational facilities available at the forecasting stations, warning time required and purpose of forecast. Some of the commonly used methods by various forecasting stations include: (i) simple correlation based on stage-discharge data, (ii) co-axial correlation based on stage, discharge and rainfall data etc, (iii) net work model wherein the lateral flows from different sub-basins are calculated using unit hydrograph approach and successive routing through different sub-reaches is carried out using river flood routing techniques, and (iv) hydrologic models (at selected places). The recent techniques like ANN and fuzzy logic are being currently used by the academicians and researchers for the development and testing. In this lecture brief description of various real time flood forecasting models and techniques being used in India are presented. The limitations of the techniques are discussed. The status of the real time flood forecasting in India including those of the arid and semi-arid basins is presented. The present gaps in the application of real time flood forecasting techniques in India are highlighted. ________________________________________________________________________ * Scientist F, National Institute of Hydrology, Roorkee247 667, India
Adaptive communication in multi-robot systems using directionality of signal strength

We consider the problem of satisfying communication demands in a multi-agent system where several robots cooperate on a task and a fixed subset of the agents act as mobile routers. Our goal is to position the team of robotic routers to provide communication coverage to the remaining client robots. We allow for dynamic environments and variable client demands, thus necessitating an adaptive solution. We present an innovative method that calculates a mapping between a robot’s current position and the signal strength that it receives along each spatial direction, for its wireless links to every other robot. We show that this information can be used to design a simple positional controller that retains a quadratic structure, while adapting to wireless signals in real-world environments. Notably, our approach does not necessitate stochastic sampling along directions that are counter-productive to the overall coordination goal, nor does it require exact client positions, or a known map of the environment.
Ancestry Estimation and Correction for Population Stratification in Molecular Epidemiologic Association Studies

Historically, racial groups have been defined by common geographic origins and shared physical characteristics, such as skin color, facial features, and hair texture. Linnaeus's Systema Naturae ([1][1]) described four racial groups (Europeanus, Asiaticus, Americanus, and Africanus), which were
The LARES mission revisited: an alternative scenario

In the original LARES mission, the general relativistic Lense–Thirring effect was to be detected using as an observable the sum of the residuals of the nodes of the existing passive geodetic laser-ranged LAGEOS satellite and of its proposed twin LARES. The proposed nominal orbital configuration of the latter would reduce the systematic error due to the mismodelling in the even zonal harmonics of the geopotential, which is the main source of error (to 0.3%) according to the most recent Earth gravity model EGM96. This observable turns out to be sensitive to possible departures of the LARES orbital parameters from their nominal values due to the orbital injection errors. By adopting a suitable combination of the orbital residuals of the nodes of LAGEOS, LAGEOS II and LARES and the perigees of LAGEOS II and LARES, it should be possible to reduce the error due to the geopotential by one order of magnitude, according to the EGM96 model. Moreover, the sensitivity to the orbital injection errors should be greatly reduced. According to a preliminary estimate of the error budget, the total error of the experiment should be reduced to less than 1%. In the near future, when the new data on the terrestrial gravitational field from CHAMP and GRACE missions become available, a further increase in the accuracy should be obtained. The proposal to place LARES in a polar 2000 km altitude orbit and consider only its nodal rate would present the drawback that even small departures from the polar geometry would yield notable errors due to the mismodelled even zonal harmonics of the geopotential, according to the EGM96 model.
A Semantic Content Analysis Model for Sports Video Based on Perception Concepts and Finite State Machines

In automatic video content analysis domain, the key challenges are how to recognize important objects and how to model the spatiotemporal relationships between them. In this paper we propose a semantic content analysis model based on Perception Concepts (PCs) and Finite State Machines (FSMs) to automatically describe and detect significant semantic content within sports video. PCs are defined to represent important semantic patterns for sports videos based on identifiable feature elements. PC-FSM models are designed to describe spatiotemporal relationships between PCs. And graph matching method is used to detect high-level semantic automatically. A particular strength of this approach is that users are able to design their own highlights and transfer the detection problem into a graph matching problem. Experimental results are used to illustrate the potential of this approach.
Analysis and Evaluating Security of Component- Based Software Development: A Security Metrics Framework

Evaluating the security of software systems is a complex problem for the research communities due to the multifaceted and complex operational environment of the system involved. Many efforts towards the secure system development methodologies like secSDLC by Microsoft have been made but the measurement scale on which the security can be measured got least success. As with a shift in the nature of software development from standalone applications to distributed environment where there are a number of potential adversaries and threats present, security has been outlined and incorporated at the architectural level of the system and so is the need to evaluate and measure the level of security achieved . In this paper we present a framework for security evaluation at the design and architectural phase of the system development. We have outlined the security objectives based on the security requirements of the system and analyzed the behavior of various software architectures styles. As the component-based development (CBD) is an important and widely used model to develop new large scale software due to various benefits like increased reuse, reduce time to market and cost. Our emphasis is on CBD and we have proposed a framework for the security evaluation of Component based software design and derived the security metrics for the main three pillars of security, confidentiality, integrity and availability based on the component composition, dependency and inter component data/information flow. The proposed framework and derived metrics are flexible enough, in way that the system developer can modify the metrics according to the situation and are applicable both at the development phases and as well as after development.
Data Security & Privacy Protection : Primary Inhibitor for Adoption of Cloud Computing Services

In cloud computing, the data will be stored in storage provided by CSP.Service providers must have a viable way to protect their user’s data, especially to prevent the data from disclosure by Malicious Insiders. Storing the data in encrypted form is a popular and common method of protecting user’s data . If a cloud is responsible for storage and encryption/decryption of data, then Malicious Insiders may simultaneously obtain encrypted data and decryption keys. This allows them to access information without authorization and thus poses a risk to user’s data. This paper proposes a Solution for cloud computing based on the concept of separating the encryption and decryption service from the storage