Miracle-dz/UniFAR-FTUs huggingface dataset:
Operational risk: acceptability criteria

The English proverb 'one man's meat is another man's poison' may be an apt description of our approach to risk. Some will ski or bungee jump whilst others shun even the gentlest of fairground rides. Some organisations allow their staff unrestricted Internet access; for others access is constrained technically with monitoring and blocking tools, and psychologically with the threat of dismissal. In this paper we look at whether there is a way that organisations, whose appetite for risk may vary greatly, could find a way to share resources and data with assurance. Could we define a model of attitudes to risk which permits one organisation to plug into another and vice versa? We propose that where standards are employed either with the intentional or coincidental purpose of managing risk, there is a way to find common ground on which to build trust.
Natural Resources for Human Health

Plants have evolved several mechanisms to protect themselves from different biotic and abiotic challenges, including pest and pathogen attacks. One of the most important mechanisms is the secondary metabolites (SM) (terpenes, phenolics and nitrogen/sulphurcontaining compounds). The plants have synthesised diverse compounds in different concentrations (mostly in tiny quantities) and have essential roles in plant defence, survival, adaptation, and reproduction. Citrus crops are among the most essential cultivated fruit groups and are rich in terpenoids and phenolics. Besides the well-known benefits of these compounds on human health, they have a significant role in plant/fruit defence against biotic and abiotic challenges. This review highlights the importance of these compounds (such as limonene, citral, saponin, hesperidin, quercetin, tangeritine, caffeic acid, p-coumaric acid, scoparone, etc.) and discusses their roles in tree and fruit defence against pests and pathogens. In today’s world, where there is an essential human impact on nature, a need is raised to reduce pesticides against pests and pathogens. Therefore, understanding the roles of these SM and their induction is believed to have a significant positive impact on the production and/or storage of horticultural crops andmay help reduce the use of synthetic agrochemicals. In line with this information, the present review was aimed to provide background information for researchers, farmers, horticulturalists and technology developers about the potential benefits of SM on plant/fruit defence and a guideline about their induction.
Sous-différentiels de fonctions convexes composées

Dans cet article nous etudions le sous-differentiel de la composition d'une fonction convexe croissante avec une application a valeurs dans un espace vectoriel topologique ordonne (mais non necessairement completement ordonne). Les resultats obtenus nous permettent d'etablir des conditions necessaires et suffisantes d'optimalite pour les problemes generaux d'optimisation convexe
Leveraging the structure of the Semantic Web to enhance information retrieval for proteomics

MOTIVATION Proteomics researchers need to be able to quickly retrieve relevant information from the web and the biomedical literature. To improve information retrieval, we leverage the structure of the semantic web, developing an approach for joining it with the largely opposing paradigm of unsupervised web search. RESULTS Our approach uses a Resource-Description-Framework (RDF) graph that inter-relates documents through their associated biological identifiers (e.g., protein ID). A search begins with a simple query term (UniProt identifier), which is expanded with terms extracted from documents in the RDF graph surrounding the query ("the subgraph"). We re-rank documents in the full corpus (e.g. all PubMed) by their cosine-similarity scores against a composite word-weight vector created from the subgraph. This vector is a weighted sum of individual word-weight vectors for documents at each node of the subgraph, taking into account the types of relationships between the central query identifier and the nodes connected to it. The computation also uses inverse document frequency (IDF) in a novel way to rescale the local word frequencies in the query's subgraph relative to that in other subgraphs. Applying our procedure to PubMed, we optimize weights for various relationships in the subgraph and benchmark overall performance in detail. Using a subgraph containing family relationships (from PFAM) results in a significant improvement in accuracy (as compared to not considering the subgraph in the search) when assessed against known relationships in the yeast literature. Moreover, we achieve this accuracy using only relatively simple and computationally efficient methods.
Clustering by common friends finds locally significant proteins mediating modules

MOTIVATION Much research has been dedicated to large-scale protein interaction networks including the analysis of scale-free topologies, network modules and the relation of domain-domain to protein-protein interaction networks. Identifying locally significant proteins that mediate the function of modules is still an open problem. METHOD We use a layered clustering algorithm for interaction networks, which groups proteins by the similarity of their direct neighborhoods. We identify locally significant proteins, called mediators, which link different clusters. We apply the algorithm to a yeast network. RESULTS Clusters and mediators are organized in hierarchies, where clusters are mediated by and act as mediators for other clusters. We compare the clusters and mediators to known yeast complexes and find agreement with precision of 71% and recall of 61%. We analyzed the functions, processes and locations of mediators and clusters. We found that 55% of mediators to a cluster are enriched with a set of diverse processes and locations, often related to translocation of biomolecules. Additionally, 82% of clusters are enriched with one or more functions. The important role of mediators is further corroborated by a comparatively higher degree of conservation across genomes. We illustrate the above findings with an example of membrane protein translocation from the cytoplasm to the inner nuclear membrane. AVAILABILITY All software is freely available under Supplementary information.
Fast Normal Approximation of Point Clouds in Screen Space

The display of large point clouds of planar distributions yet comes with large restrictions regarding the normal and surface reconstruction. The point data needs to be clustered or traversed to extract a local neighborhood, which is necessary to retrieve surface information. We propose the usage of the rendering pipeline to circumvent a pre-computation of the neighborhood and to perform a fast approximation of the surface. We present and compare three different methods for surface reconstruction within a post-process. These methods range from simple approximations to the deﬁnition of a tensor surface. All these methods are designed to run at interactive frame-rates. We also present a correction method to increase reconstruction quality, while preserving interactive frame-rates. Our results indicate, that the on-the-ﬂy computation of surface normals is not a limiting factor on modern GPUs. Additionally, as the surface information is generated during the post-process, only the target display size is the limiting factor. The size of the input point cloud does not inﬂuence the performance.
Chaos, Solitons and Fractals

The pathogen diversity means that multiple strains coexist, and widely exist in the biology systems. The new mutation of SARS-CoV-2 leading to worldwide pathogen diversity is a typical example. What are the main factors of inducing the pathogen diversity? Previous studies indicated the pathogen mutation is the most important reason for inducing the pathogen diversity. The traffic network and gene network are crucial in shaping the dynamics of pathogen contagion, while their roles for the pathogen diversity still lacking a theoretical study. To this end, we propose a reaction–diffusion process of pathogens with mutations on meta-population networks, which includes population movement and strain mutation. We extend the Microscopic Markov Chain Approach (MMCA) to describe the model. Traffic networks make pathogen diversity more likely to occur in cities with lower infection densities. The likelihood of pathogen diversity is low in cities with short effective distances in the traffic network. Star-type gene network is more likely to lead to pathogen diversity than lattice-type and chain-type gene networks. When pathogen localization is present, infection is localized to strains that are at the endpoints of the gene network. Both the increased probability of movement and mutation promote pathogen diversity. The results also show that the population tends to move to cities with short effective distances, resulting in the infection density is high.
Systematic studies, calibration, and software development for event reconstruction and data analysis using the ANTARES deep-sea neutrino telescope

The Antares neutrino telescope has been constructed in the Mediterranean deep sea in a depth of about 2500 m, 40 km off-shore the city of Toulon at the French coast, in order to detect cosmic neutrino signals. Being the largest apparatus on the Northern hemisphere, with about 900 photo-sensors, in addition to its unique discovery potential, Antares represents a benchmark and possible prototype for future neutrino telescope projects. After an introduction into neutrino telescopy and a description of the Antares telescope, this dissertation will describe the charge calibration of the front-end electronics. A long-term study of the calibration constants is discussed. Contributions to the software framework will be detailed and systematic studies of the event reconstruction are presented. For a precise telescopy, the absolute orientation of the detector is of utmost importance. A possible verification of the detector pointing relies on the detection of the shadow which is casted by the Moon in cosmic rays. The significance of this effect is evaluated with the help of a detailed Monte Carlo simulation. A first analysis of Antares data is performed. Kurzfassung Mit dem Antares Neutrino-Teleskop, welches im Mittelmeer, 40 km vor der französischen Küste bei Toulon, in einer Tiefe von ca. 2500 m errichtet wurde, sollen kosmische Neutrinos detektiert werden. Mit rund 900 Photosensoren stellt Antares derzeit das sensitivste Experiment auf der Nordhalbkugel dar. Neben dem inhärenten Entdeckungspotential können aus Aufbau, Betrieb und Datenanalyse wichtige Erkenntnisse für die nächste Generation von Teleskopen gewonnen werden. Nach einer Einführung in die Neutrinoastronomie und in das Antares Experiment stellt diese Dissertation die erarbeiteten Kalibrationsverfahren für die Ausleseelektronik vor. Eine Langzeitstudie der Zeitentwicklung der Kalibrationskonstanten wird präsentiert. Beiträge zur Softwareinfrastruktur (Online-Monitoring, Datenverarbeitung und Rekonstruktion) werden erörtert. Für eine exakte Teleskopie ist die Verifikation der Detektorausrichtung von großer Bedeutung. Eine Kalibrationsmethode besteht in der Beobachtung des Schattens, den der Mond in der kosmischen Strahlung wirft. Die Größe dieses Effektes wird anhand einer detaillierten Simulation quantifiziert. Eine erste Analyse der Daten des komplettierten Teleskopes wird diskutiert. The image on the cover page shows an event display of a simulated 540 GeV muon-neutrino that interacts via the charged-current process in the vicinity of the Antares detector to produce a 130 GeV up-going muon track (red line). The muon traverses the detector and gives rise to Cherenkov light (green lines) which is measured by the optical sensors (enlarged spheres) of the telescope. The image was created with an event-display program developed for this thesis. See Chapter 5 and Appendix A for further information. This document was typeset using LTEX.
The mechanics of growth and residual stress in biological cylinders

Biological tissue differs from other materials in many ways. Perhaps the most crucial difference is its ability to grow. Growth processes may give rise to stresses that exist in a body in the absence of applied loads and these are known as residual stresses. Residual stress is present in many biological systems and can have important consequences on the mechanical response of a body. Mathematical models of biological structures must therefore be able to capture accurately the effects of differential growth and residual stress, since greater understanding of the roles of these phenomena may have applications in many fields. In addition to residual stresses, biological structures often have a complex morphology. The theory of 3-D elasticity is analytically tractable in modelling mechanical properties in simple geometries such as a cylinder. On the other hand, rod theory is well-suited for geometrically-complex deformations, but is unable to account for residual stress. In this thesis, we aim to develop a map between the two frameworks. Firstly, we use 3-D elasticity to determine effective mechanical properties of a growing cylinder and map them into an effective rod. Secondly, we consider a growing filament embedded in an elastic foundation. Here, we estimate the degree of transverse reinforcement the foundation confers on the filament in terms of its material properties. Finally, to gain a greater understanding of the role of residual stress in biological structures, we consider a case study: the chameleon's tongue. In particular we consider the role of residual stress and anisotropy in aiding the rapid projection of the tongue during prey capture. We construct a mechanical model of the tongue and use it to investigate a proposed mechanism of projection by means of an energy balance argument.
UvA-DARE (Digital Academic Repository) Unraveling the origins of musicality: Beyond music as an epiphenomenon of language

The two target articles address the origins of music in complementary ways. However, both proposals focus on overt musical behaviour, largely ignoring the role of perception and cognition, and they blur the boundaries between the potential origins of language and music. To resolve this, an alternative research strategy is proposed that focusses on the core cognitive components of musicality. target music musicality in complementary ways. Savage et al theory that proposes music to be a relatively recent cultural invention that then further evolved though gene-culture coevolution. In contrast, Mehr et al. issue) present a single hypothesis capturing the biological origins of musical behaviour, suggesting a long evolutionary history.
Psychophysiological responses to group cognitive- behavioral therapy in depressive patients

Yves Martins Varela Universidade Federal do Rio Grande do Norte Centro de Biociencias Raíssa Nóbrega De Almeida Universidade Federal do Rio Grande do Norte Centro de Biociencias Ana Cecília de Menezes Galvão Universidade Federal do Rio Grande do Norte Centro de Biociencias Geovan Menezes Sousa Junior Universidade Federal do Rio Grande do Norte Centro de Biociencias https://orcid.org/0000-0002-86745067 Ana Cecília Lopes de Lima Universidade Federal do Rio Grande do Norte Centro de Biociencias Neuciane Gomes da Silva Universidade Federal do Rio Grande do Norte Centro de Ciencias Humanas Letras e Artes Mário André Leocádio-Miguel Universidade Federal do Rio Grande do Norte Centro de Biociencias Bruno Lobão-Soares Universidade Federal do Rio Grande do Norte Centro de Biociencias Jaime Eduardo Cecílio Hallak Universidade Federal de Sao Paulo João Paulo Maia-de-Oliveira Universidade Federal de Sao Paulo Nicole Leite Galvão-Coelho (  nicolelgalvaocoelho@gmail.com ) Federal University of Rio Grande do Norte https://orcid.org/0000-0002-4887-8635
Formal aspects of mobile code security

We believe that formal methods of all kinds are critical to mobile code security, as one route to gaining the assurance level necessary for running potentially hostile code on a routine basis. We begin by examining Java, and understanding the weaknesses in its architecture, on both design and implementation levels. Identifying dynamic linking as a key problem, we produce a formal model of linking, and prove desirable properties about our model. This investigation leads to a deep understanding of the underlying problem. Finally, we turn our attention to cryptographic hash functions, and their analysis with binary decision diagrams (BDDs). We show that three commonly used hash functions (MD4, MD5, and SHA-1) do not offer ideal strength against second preimages. The ability of a cryptographic hash function to resist the finding of second preimages is critical for its use in digital signature schemes: a second preimage enables the forgery of digital signatures, which would undermine confidence in digitally signed mobile code. Our results show that modern theorem provers and BDD-based reasoning tools are effective for reasoning about some of the key problems facing mobile code security today.
Weakly-Supervised Optical Flow Estimation for Time-of-Flight Supplementary Material

As a consequence, the arctan2 function has multiple branches, corresponding to the sign of its arguments, as can be seen in Fig. 1. The figure also illustrates the difference of dmax/2 between the two branches in this case. As a result if the target (red point) is on the different branch than the current depth estimate (green point), the direction of the optimization needs to be inverted in order to move the estimate dmax d^
Visualisation and 'Diagnostic Classifiers' Reveal how Recurrent and Recursive Neural Networks Process Hierarchical Structure (Extended Abstract)

In this paper, we investigate how recurrent neural networks can learn and process languages with hierarchical, compositional semantics. To this end, we define the artificial task of processing nested arithmetic expressions, and study whether different types of neural networks can learn to compute their meaning. We find that simple recurrent networks cannot find a generalising solution to this task, but gated recurrent neural networks perform surprisingly well: networks learn to predict the outcome of the arithmetic expressions with high accuracy, although performance deteriorates somewhat with increasing length. We test multiple hypotheses on the information that is encoded and processed by the networks using a method called diagnostic classification. In this method, simple neural classifiers are used to test sequences of predictions about features of the hidden state representations at each time step. Our results indicate that the networks follow a strategy similar to our hypothesised ‘cumulative strategy’, which explains the high accuracy of the network on novel expressions, the generalisation to longer expressions than seen in training, and the mild deterioration with increasing length. This, in turn, shows that diagnostic classifiers can be a useful technique for opening up the black box of neural networks.
Efficient Robust Matrix Factorization with Nonconvex Penalties

Robust matrix factorization (RMF), which uses the `1-loss, often outperforms standard matrix factorization using the `2loss, particularly when outliers are present. The state-of-theart RMF solver is the RMF-MM algorithm, which, however, cannot utilize data sparsity. Moreover, sometimes even the (convex) `1-loss is not robust enough. In this paper, we propose the use of nonconvex loss to enhance robustness. To address the resultant difficult optimization problem, we use majorization-minimization (MM) optimization and propose a new MM surrogate. To improve scalability, we exploit data sparsity and optimize the surrogate via its dual with the accelerated proximal gradient algorithm. The resultant algorithm has low time and space complexities and is guaranteed to converge to a critical point. Extensive experiments demonstrate its superiority over the state-of-theart in terms of both accuracy and scalability.
Causal diagrams for epidemiologic research.

Causal diagrams have a long history of informal use and, more recently, have undergone formal development for applications in expert systems and robotics. We provide an introduction to these developments and their use in epidemiologic research. Causal diagrams can provide a starting point for identifying variables that must be measured and controlled to obtain unconfounded effect estimates. They also provide a method for critical evaluation of traditional epidemiologic criteria for confounding. In particular, they reveal certain heretofore unnoticed shortcomings of those criteria when used in considering multiple potential confounders. We show how to modify the traditional criteria to correct those shortcomings. (Epidemiology 1999;10:37–48)
Parallelism for Free : E cient and Optimal Bitvector Analyses for Parallel Programs

We consider parallel programs with shared memory and interleaving semantics, for which we show how to construct for unidirectional bitvector problems optimal analysis algorithms that are as ef-cient as their purely sequential counterparts and that can easily be implemented. Whereas the complexity result is rather obvious, our optimality result is a consequence of a new Kam/Ullman-style Coincidence Theorem. Thus using our method, the standard algorithms for sequential programs computing liveness, availability, very busyness, reaching deenitions, deenition-use chains, or the analyses for performing code motion, assignment motion, partial dead-code elimination or strength reduction, can straightforward be transferred to the parallel setting at almost no cost. 1. MOTIVATION Parallel implementations are of growing interest, as they are more and more supported by modern hardware environments. However, despite its importance Srini-vasan and Wolfe 1991; Srinivasan et al. 1993; Wolfe and Srinivasan 1991], there is currently very little work on classical data ow analysis for parallel languages. Permission to make digital/hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proot or direct commercial advantage and that copies show this notice on the rst page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works, requires prior speciic permission and/or a fee.
A Comparative Study on Feature Selection and Classication Methods Using Gene Expression Proles and Proteomic Patterns

Feature selection plays an important role in classication. We present a comparative study on six feature selection heuristics by applying them to two sets of data. The rst set of data are gene expression proles from Acute Lymphoblastic Leukemia (ALL) patients. The second set of data are proteomic patterns from ovarian cancer patients. Based on features chosen by these methods, error rates of several classication algorithms were obtained for analysis. Our results demonstrate the importance of feature selection in accurately classifying new samples.