Miracle-dz/UniFAR-FTUs huggingface dataset:
A General Methodology for Testing the Performance of Technical Analysis on Financial Markets

Our study provides a general methodology for testing the performance of technical analysis on any market. This methodology is very useful to evaluate whether or not a market is efficient (EMH) in its weak form. The main difficulties of this area of research are encountered when one wants to provide a general result on different tools of technical analysis taken separately or as a trading system. Performance of trading systems is complicated to evaluate. They need to be programmed in the same exact way, with a general methodology. Its objective is to be able to compare the results and estimate if they issued a significant performance which can cause a bias in efficient market hypothesis.
Imperial / TP / 06 / RAR / 04 Geometric and Non-Geometric Compactifications of IIB

Complimentary geometric and non-geometric consistent reductions of IIB supergravity are studied. The geometric reductions on the identified group manifold X = G/Γ are found to have a gauge symmetry with Lie algebroid structure, generalising that found in similar reductions of the Bosonic string theory and eleven-dimensional supergravity. Examples of such compactifications are considered and the symmetry breaking in each case is analysed. Complimentary to the reductions on X are the nine-dimensional S-duality twisted reductions considered in the second half of the paper. The general reduced theory is given and symmetry breaking is investigated. The non-geometric S-duality twisted reductions and their relation to geometric reductions of F-Theory on X is briefly discussed. Email: r.reid-edwards@imperial.ac. uk
Language-Guided Controller Synthesis for Linear Systems

This paper considers the problem of controlling discrete-time linear systems from specifications given as formulas of syntactically co-safe linear temporal logic over linear predicates in the state variables. A systematic procedure is developed for the automatic computation of sets of initial states and feedback controllers such that all the resulting trajectories of the closed-loop system satisfy the given specifications. The procedure is based on the iterative construction and refinement of an automaton that enforces the satisfaction of the formula. Linear programming based approaches are proposed to compute the polytope-to-polytope controllers that label the transitions of the automaton. Extensions to discrete-time piecewise affine systems and specifications given as formulas of full linear temporal logic are included. The algorithms developed in this paper were implemented as a software package that is available for download. Their application and effectiveness are demonstrated for several case studies.
Quality-adaptive Spoken Dialogue Initiative Selection And Implications On Reward Modelling

Adapting Spoken Dialogue Systems to the user is supposed to result in more efficient and successful dialogues. In this work, we present an evaluation of a quality-adaptive strategy with a user simulator adapting the dialogue initiative dynamically during the ongoing interaction and show that it outperforms conventional non-adaptive strategies and a random strategy. Furthermore, we indicate a correlation between Interaction Quality and dialogue completion rate, task success rate, and average dialogue length. Finally, we analyze the correlation between task success and interaction quality in more detail identifying the usefulness of interaction quality for modelling the reward of reinforcement learning strategy optimization.
Optogenetic Stimulation of Lateral Amygdala Input to Posterior Piriform Cortex Modulates Single-Unit and Ensemble Odor Processing

Olfactory information is synthesized within the olfactory cortex to provide not only an odor percept, but also a contextual significance that supports appropriate behavioral response to specific odor cues. The piriform cortex serves as a communication hub within this circuit by sharing reciprocal connectivity with higher processing regions, such as the lateral entorhinal cortex and amygdala. The functional significance of these descending inputs on piriform cortical processing of odorants is currently not well understood. We have employed optogenetic methods to selectively stimulate lateral and basolateral amygdala (BLA) afferent fibers innervating the posterior piriform cortex (pPCX) to quantify BLA modulation of pPCX odor-evoked activity. Single unit odor-evoked activity of anesthetized BLA-infected animals was significantly modulated compared with control animal recordings, with individual cells displaying either enhancement or suppression of odor-driven spiking. In addition, BLA activation induced a decorrelation of odor-evoked pPCX ensemble activity relative to odor alone. Together these results indicate a modulatory role in pPCX odor processing for the BLA complex. This interaction could contribute to learned changes in PCX activity following associative conditioning, as well as support alternate patterns of odor processing that are state-dependent.
Minimize the Percentage of Noise in Biomedical Images Using Neural Networks

The overall goal of the research is to improve the quality of biomedical image for telemedicine with minimum percentages of noise in the retrieved image and to take less computation time. The novelty of this technique lies in the implementation of spectral coding for biomedical images using neural networks in order to accomplish the above objectives. This work is in continuity of an ongoing research project aimed at developing a system for efficient image compression approach for telemedicine in Saudi Arabia. We compare the efficiency of this technique against existing image compression techniques, namely, JPEG2000, in terms of compression ratio, peak signal to noise ratio (PSNR), and computation time. To our knowledge, the research is the primary in providing a comparative study with other techniques used in the compression of biomedical images. This work explores and tests biomedical images such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET).
Personalized anticancer therapy selection using molecular landscape topology and thermodynamics

Personalized anticancer therapy requires continuous consolidation of emerging bioinformatics data into meaningful and accurate information streams. The use of novel mathematical and physical approaches, namely topology and thermodynamics can enable merging differing data types for improved accuracy in selecting therapeutic targets. We describe a method that uses chemical thermodynamics and two topology measures to link RNA-seq data from individual patients with academically curated protein-protein interaction networks to select clinically relevant targets for treatment of low-grade glioma (LGG). We show that while these three histologically distinct tumor types (astrocytoma, oligoastrocytoma, and oligodendroglioma) may share potential therapeutic targets, the majority of patients would benefit from more individualized therapies. The method involves computing Gibbs free energy of the protein-protein interaction network and applying a topological filtration on the energy landscape to produce a subnetwork known as persistent homology. We then determine the most likely best target for therapeutic intervention using a topological measure of the network known as Betti number. We describe the algorithm and discuss its application to several patients.
Liver enzymes and risk of all-cause mortality in general populations: a systematic review and meta-analysis.

BACKGROUND Gamma glutamyltransferase (GGT), alanine aminotransferase (ALT), aspartate aminotransferase (AST) and alkaline phosphatase (ALP), commonly used as markers of liver dysfunction, have been implicated with risk of all-cause mortality. The prospective evidence on the associations in general populations has not been reliably quantified. METHODS We conducted a systematic review and meta-analysis of published prospective cohort studies evaluating the associations of baseline levels of these enzymes with all-cause mortality in general populations. Relevant studies were identified in a literature search of MEDLINE, EMBASE and Web of Science up to March 2013. Authors of unpublished studies provided data on request. RESULTS Nineteen unique cohort studies with aggregate data on over 9.24 million participants and 242 953 all-cause mortality outcomes were included. In a comparison of extreme thirds of baseline GGT and ALP levels, relative risks (RRs) (95% confidence intervals) for all-cause mortality were 1.60 (1.42-1.80) and 1.38 (1.17-1.63), respectively. The corresponding RRs for ALT were 0.82 (0.78-0.86) and 1.43 (1.08-1.90) in North American and Asian populations, respectively. There was no strong evidence of an association of AST with all-cause mortality: RR 1.23 (0.80-1.88). The pooled RRs per 5 U/l increment in GGT and ALP levels were 1.07 (1.04-1.10) and 1.03 (1.01-1.06), respectively. CONCLUSIONS Available data indicate positive independent associations of baseline levels of GGT and ALP with all-cause mortality, consistent with linear dose-response relationships. There were geographical variations in the association of ALT with all-cause mortality which require further investigation. The potential incremental prognostic values of GGT and ALP in mortality risk assessment need evaluation.
Boundary relations: technological objects and the restructuring of workplace boundaries

These papers are produced by Judge Business School, University of Cambridge. They are circulated for discussion purposes only. Their contents should be considered preliminary and are not to be quoted without the authors' permission. ABSTRACT Recent research has highlighted the role and use of workplace artefacts by occupational communities in enacting jurisdictions within organizations. This article builds on these insights to understand how the use of a new technological object by community members has implications for the restructuring of workplace boundaries. Our study of hospital pharmacy automation examines how a newly introduced dispensing robot mediated the work of dispensing technicians and distribution assistants. We found that use of the robot, which was expected to improve patient safety and pharmacy productivity, also served to restructure spatial, temporal, task and role aspects of workplace boundaries, having important implications for the visibility and invisibility of different forms of work. We identified three boundary relations that emerged among different occupational groups and which served to enable and constrain their cross-boundary work: boundary strain between technicians and assistants; boundary cooperation between technicians and pharmacists; and boundary neglect between pharmacists and assistants. Our study goes beyond the predominant focus on boundary objects as bridging and coordinating work, and seeks to provide a richer conceptualization of the role of technological objects in shaping boundary relations within organizations. 12968 3 Organizational scholars have recently highlighted the inadequacy of viewing organizations as circumscribed by fixed and unambiguous boundaries. Instead, they argue that boundaries should be recognized as dynamic (Hernes 2004) and emergent, established through processes of boundary setting (Abbott 1995). With the advent of the Internet and the proliferation of digital technologies in the workplace, post-bureaucratic organizations have been characterized as dynamic, flexible, and " boundaryless " (Hirschhorn and Gilmore 1992), though other scholars (e.g., Heracleous 2004) have emphasized the 'subtle' proliferation of boundaries in modern organizations. Despite these noteworthy studies, there is little understanding as to how new digital technologies are restructuring workplace boundaries within organizations. Prior research on technological objects has focused on cross-boundary coordination of work between different occupational groups (Star and Greismer 1989; Carlile 2004). In these studies, boundary objects are used to deal with the differences in meanings, norms, and interests by allowing for common ground and forms of translation that facilitate shared understandings and transformation processes (Kellogg, Orlikowski, and Yates 2006). While the notion of boundary objects has provided important insights, the emphasis …
Inhibition of PDGF-B Induction and Cell Growth by Syndecan-1 Involves the Ubiquitin and SUMO-1 Ligase, Topors

Syndecans are receptors for soluble ligands, including heparin-binding growth factors, and matrix proteins. However, intracellular targets of syndecan-1 (Sdc-1)-mediated signaling are not fully understood. A yeast two-hybrid protein interaction screening of a mouse embryo library identified the ubiquitin and SUMO-1 E3 ligase, Topors, as a novel ligand of the Sdc-1 cytoplasmic domain (S1CD), a finding confirmed by ligand blotting and co-precipitation with Sdc-1 from cell lysates. Deletion mutagenesis identified an 18-amino acid sequence of Topors required for the interaction with the S1CD. By immunohistochemistry, Topors and Sdc-1 co-localized near the cell periphery in normal murine mammary gland (NMuMG) cells in vitro and in mouse embryonic epithelia in vivo. Finally, siRNA-mediated knockdown of Topors demonstrated that Topors is a growth promoter for murine arterial smooth muscle cells and is required for the inhibitory effect of Sdc-1 on cell growth and platelet-derived growth factor-B induction. These data suggest a novel mechanism for the inhibitory effects of Sdc-1 on cell growth that involves the interaction between the cytoplasmic domain of Sdc-1 and the SUMO-1 E3 ligase, Topors.
Secure Mediation: Requirements, Design, and Architecture

In mediated information systems clients and various autonomous sources are brought together by mediators. The mediation paradigm needs powerful and expressive security mechanisms considering the dynamics and conflicting interests of the mediation participants. Firstly, we discuss the security requirements for mediation with an emphasis on confidentiality and authenticity. We argue for basing the enforcement of these properties on certified personal authorization attributes rather than on identification. Using a public key infrastructure such personal authorization attributes can be bound to asymmetric encryption keys by credentials. Secondly, we propose a general design of secure mediation where credentials are roughly used as follows: clients show their eligibility for receiving requested information by the contained personal authorization attributes, and sources and the mediator guarantee confidentiality by using the contained encryption keys. Thirdly, we refine the general design for a specific approach to mediation, given by our prototype of a Multimedia Mediator, MMM. Among other contributions, we define the authorization model and the specification of query access authorizations within the framework of ODL, as well as the authorization and encryption policies for mediation, and we outline the resulting security architecture of the MMM. We also analyze the achievable security properties including support for anonymity, and we discuss the inevitable tradeoffs between security and mediation functionality.
Extracting Meaningful Entities from Police Narrative Reports

Valuable criminal-justice data in free texts such as police narrative reports are currently difficult to be accessed and used by intelligence investigators in crime analyses. It would be desirable to automatically identify from text reports meaningful entities, such as person names, addresses, narcotic drugs, or vehicle names to facilitate crime investigation. In this paper, we report our work on a neural network-based entity extractor, which applies named-entity extraction techniques to identify useful entities from police narrative reports. Preliminary evaluation results demonstrated that our approach is feasible and has some potential values for real-life applications. Our system achieved encouraging precision and recall rates for person names and narcotic drugs, but did not perform well for addresses and personal properties. Our future work includes conducting larger-scale evaluation studies and enhancing the system to capture human knowledge interactively.
Revealing of Mycobacterium marinum Transcriptome by RNA-seq

Transcriptome analysis has played an essential role for revealing gene expression and the complexity of regulations at transcriptional level. RNA-seq is a powerful tool for transcriptome profiling, which uses deep-sequencing technologies to directly determine the cDNA sequence. Here, we utilized RNA-seq to explore the transcriptome of Mycobacterium marinum (M. marinum), which is a useful model to study the pathogenesis of Mycobacterium tuberculosis (Mtb). Two profiles of exponential and early stationary phase cultures were generated after a physical ribosome RNA removal step. We systematically described the transcriptome and analyzed the functions for the differentiated expressed genes between the two phases. Furthermore, we predicted 360 operons throughout the whole genome, and 13 out of 17 randomly selected operons were validated by qRT-PCR. In general, our study has primarily uncovered M. marinum transcriptome, which could help to gain a better understanding of the regulation system in Mtb that underlines disease pathogenesis.
Properties of Calcium Phosphate Cements With Different Tetracalcium Phosphate and Dicalcium Phosphate Anhydrous Molar Ratios

Calcium phosphate cements (CPCs) were prepared using mixtures of tetracalcium phosphate (TTCP) and dicalcium phosphate anhydrous (DCPA), with TTCP/DCPA molar ratios of 1/1, 1/2, or 1/3, with the powder and water as the liquid. Diametral tensile strength (DTS), porosity, and phase composition (powder x-ray diffraction) were determined after the set specimens have been immersed in a physiological-like solution (PLS) for 1 d, 5 d, and 10 d. Cement dissolution rates in an acidified PLS were measured using a dual constant composition method. Setting times ((30 ± 1) min) were the same for all cements. DTS decreased with decreasing TTCP/DCPA ratio and, in some cases, also decreased with PLS immersion time. Porosity and hydroxyapatite (HA) formation increased with PLS immersion time. Cements with TTCP/DCPA ratios of 1/2 and 1/3, which formed calcium-deficient HA, dissolved more rapidly than the cement with a ratio of 1/1. In conclusion, cements may be prepared with a range of TTCP/DCPA ratios, and those with lower ratio had lower strengths but dissolved more rapidly in acidified PLS.
Easymeeting - Prototyping ubiquitous computing in offices

This paper presents an intuitive, easy-to-use prototype system that supports users in booking and managing meeting rooms based on Near Field Communication (NFC) technology. The prototype was designed to evaluate an NFC application for smart office solutions. We used our prototype to conduct a study with 37 participants in two organizations. The evaluation was based on structured interviews and included a qualitative and quantitative part. The overall impression of the users was positive and NFC regarded as easy to use. The system was also considered useful for unobtrusively fulfilling tasks that arise during meetings. Based on this early prototype we extract findings for smart office applications.
Machine learning methods for predictive proteomics

The search for predictive biomarkers of disease from high-throughput mass spectrometry (MS) data requires a complex analysis path. Preprocessing and machine-learning modules are pipelined, starting from raw spectra, to set up a predictive classifier based on a shortlist of candidate features. As a machine-learning problem, proteomic profiling on MS data needs caution like the microarray case. The risk of overfitting and of selection bias effects is pervasive: not only potential features easily outnumber samples by 10(3) times, but it is easy to neglect information-leakage effects during preprocessing from spectra to peaks. The aim of this review is to explain how to build a general purpose design analysis protocol (DAP) for predictive proteomic profiling: we show how to limit leakage due to parameter tuning and how to organize classification and ranking on large numbers of replicate versions of the original data to avoid selection bias. The DAP can be used with alternative components, i.e. with different preprocessing methods (peak clustering or wavelet based), classifiers e.g. Support Vector Machine (SVM) or feature ranking methods (recursive feature elimination or I-Relief). A procedure for assessing stability and predictive value of the resulting biomarkers' list is also provided. The approach is exemplified with experiments on synthetic datasets (from the Cromwell MS simulator) and with publicly available datasets from cancer studies.
Functions of matrices - theory and computation

The only book devoted exclusively to matrix functions, this research monograph gives a thorough treatment of the theory of matrix functions and numerical methods for computing them. The author s elegant presentation focuses on the equivalent definitions of f(A) via the Jordan canonical form, polynomial interpolation, and the Cauchy integral formula, and features an emphasis on results of practical interest and an extensive collection of problems and solutions. Functions of Matrices: Theory and Computation is more than just a monograph on matrix functions; its wide-ranging content including an overview of applications, historical references, and miscellaneous results, tricks, and techniques with an f(A) connection makes it useful as a general reference in numerical linear algebra. Other key features of the book include development of the theory of conditioning and properties of the Frchet derivative; an emphasis on the Schur decomposition, the block Parlett recurrence, and judicious use of Pad approximants; the inclusion of new, unpublished research results and improved algorithms; a chapter devoted to the f(A)b problem; and a MATLAB toolbox providing implementations of the key algorithms. Audience: This book is for specialists in numerical analysis and applied linear algebra as well as anyone wishing to learn about the theory of matrix functions and state of the art methods for computing them. It can be used for a graduate-level course on functions of matrices and is a suitable reference for an advanced course on applied or numerical linear algebra. It is also particularly well suited for self-study. Contents: List of Figures; List of Tables; Preface; Chapter 1: Theory of Matrix Functions; Chapter 2: Applications; Chapter 3: Conditioning; Chapter 4: Techniques for General Functions; Chapter 5: Matrix Sign Function; Chapter 6: Matrix Square Root; Chapter 7: Matrix pth Root; Chapter 8: The Polar Decomposition; Chapter 9: Schur-Parlett Algorithm; Chapter 10: Matrix Exponential; Chapter 11: Matrix Logarithm; Chapter 12: Matrix Cosine and Sine; Chapter 13: Function of Matrix Times Vector: f(A)b; Chapter 14: Miscellany; Appendix A: Notation; Appendix B: Background: Definitions and Useful Facts; Appendix C: Operation Counts; Appendix D: Matrix Function Toolbox; Appendix E: Solutions to Problems; Bibliography; Index.