Miracle-dz/UniFAR-FTUs huggingface dataset:
The Homerian carbon isotope excursion (Silurian) within graptolitic successions on the Midland Platform (Avalonia), UK: implications for regional and global comparisons and correlations

Abstract New δ13Ccarb data from the most stratigraphically extensive graptolitic sections of Homerian age in the study area are reported from Wenlock Edge and the Ludlow Anticline (UK). These sections, situated upon the Midland Platform (Avalonia), were key in establishing the Homerian graptolite biozonation used within the type Wenlock Series, and are consequently of international importance. Based upon 162 δ13Ccarb samples from four outcrops (Eaton Track, Longville–Stanway Road Cutting, Burrington Section and Mortimer Forest Stop 1), new graptolite collections and a re-evaluation of the original graptolite collections, the onset of both lower (older) and upper (younger) peaks of the Homerian Carbon Isotope Excursion have been calibrated to a revised graptolite biozonation (lundgreni – nassa – praedeubeli-deubeli – ludensis biozones). In addition, high-resolution correlation between the Ludlow Anticline and Wenlock Edge has been achieved by bio-, chemo- and sequence stratigraphic techniques. These correlations suggest a uniformity of depositional rates across the study area and indicate minor diachroneity at the base of the Much Wenlock Limestone Formation. Finally, correlations of the Midland Platform Homerian Carbon Isotope Excursion have allowed for better comparisons with other sections from which high-resolution graptolite and carbon isotope data are available. Such comparisons highlight the pan-regional synchronicity of the Homerian Carbon Isotope Excursion.
Performance Evaluation of AQM Algorithms for SRM based group communication in DVMRP Multicasting Network

over the last decade numerous active queue management (AQM) schemes have been proposed. Many of these studies have been directed towards improving congestion control in best-effort networks. However, there has been a notable lack of standardized performance evaluation of AQM schemes. A rigorous study of the influence of parameterisation on specific schemes and the establishment of common comparison criteria is essential for objective evaluation of the different approaches. A framework for the detailed evaluation of AQM schemes is described in this paper. This provides a deceptively simple user interface whilst maximally exploiting relevant features of the NS2 simulator. The credibility of the results obtained is enhanced by vigilant treatment of the simulation data. The impact of AQM schemes on global network performance is carefully assessed using selected metrics. These metrics are Throughput (Quantity of Service), Delay (Quality of Service) and Packet Drop. Index Terms — Congestion Control, AQM, SRR, RED, RIO, BLUE, SFB. ——————————  ——————————
The Software-Landscape in (Prote)Omic Research

(Bio)Informatics plays a major role in (prote)omic research experiments and applications. Analysis of an entire proteome including protein identification, protein quantification, detecting biological pathways, metabolite identification and others is not possible without software solutions for analyzing the resulting huge data sets. In the last decade plenty of software-tools, -platforms and databases have been developed by vendors of analytical hardware, as well as by freeware developers and the open source software community. Some of these software packages are very much specialized for one (omic) topic, as for example genomics, proteomics, interactomics or metabolomics. Other software tools and platforms can be applied in a more general manner, e.g. for generating workflows, or performing data conversion and data management, or statistics. Nowadays the main problem is not to find out a way, how to analyze the experimental data, but to identify the most suitable software for this purpose in the vast software-landscape. This review focuses on the following issue: How complex is the link between biology, analysis and (bio) informatics, and how complex is the variety of software tools to be used for scientific investigations, starting from microorganisms up to the detection of a proteome. Thereby the main emphasis is on the variety in software for (LC) MS(/MS) proteomics. In the World Wide Web sites like ExPASy show extensive lists of proteomics software, leaving it to the user to identify which software actually serves their purposes. First we consider the huge variability of software in the field of proteomics research. Then we take a closer look on the variability of MS data and the incompatibilities of software tools with respect to that. We give an overview over commonly used software technologies and finally end up with the question, whether open source software would not add more value to this field.
Computer-aided diagnosis of dysplasia in Barrett’s esophagus using endoscopic optical coherence tomography

Barrett's esophagus (BE) has become a major health care burden because of its association with adenocarcinoma of the esophagus. We have shown that endoscopic optical coherence tomography (EOCT) has a 70% accuracy in the diagnosis of dysplasia (Gastrointest Endosc 2003; 57:AB77). To demonstrate the feasiblity of computer aided diagnosis (CAD) of dysplasia in BE using EOCT digital images, to quantitate/standardize the diagnosis of dysplasia, and to develop algorithms suitable for EOCT surveillance of large areas of Barrett’s mucosa, 106 EOCT images were selected (13 patients from 28 cases) from the clinical study including 68 of non-dysplastic and 38 of dysplastic mucosa. From the digital image stream, the 3 frames immediately preceding impact of the forceps on the tissue were selected to insure close correlation between histology/EOCT image pairs. Computer aided diagnosis by center symmetric autocorrelation (CENS) and principal component analysis (PCA) were used for feature parameter extraction and analysis based on the segmented ROI. Leave-one-out cross-validation was used for classification and finally receiver operating characteristic (ROC) curve was used to evaluate the performance of CAD and the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated. The result shows that CAD is able to achieve a higher accuracy than humans for identification of dysplasia in EOCT images. CAD may be of assistance in the EOCT surveillance of large surface areas of Barrett’s mucosa for dysplasia.
PERCEPTIONS OF THE ENVIRONMENT AND OF TOURISM IN THE ALTAI REPUBLIC, THE RUSSIAN FEDERATION

Although only 210,000 people reside in the Altai Republic of Western Siberia, the area received 1.8 million tourists in 2015. The overwhelming majority of visitors arrive from other areas of Russia. While tourists appreciate the landscape of the Altai Mountains and bring increased seasonal economic activity, not all of tourism’s effects benefit the local culture, economy or environment. This paper presents survey data concerning perceptions of residents and visitors about the environment and tourism. During the summer of 2015, a survey was distributed in four locations across the Altai Republic. Resident respondents included Russians, local members of Altaian clans, and Kazakhs, and visitors included Russian citizens from across the Russian Federation. Analyzing the data contributes to understanding the complex interactions between tourists, residents, indigenous peoples, the environment and the cultural landscape.
Mathematics Of The Discrete Fourier Transform Dft With Audio Applications Second Edition

Mathematics of Multidimensional Fourier Transform AlgorithmsThe DFTThe Discrete Fourier TransformComputational Frameworks for the Fast Fourier TransformFourier Analysis on Finite Groups and ApplicationsSimpson's Discrete Fourier TransformThe DFTFoundations of Signal ProcessingThe Discrete Fourier TransformFast Fourier TransformsAn Introduction to Laplace Transforms and Fourier SeriesAlgorithms for Discrete Fourier Transform and ConvolutionFourier Series, Fourier Transform and Their Applications to Mathematical PhysicsFourier TransformsMusic Through Fourier SpaceFourier TransformsDiscrete and Continuous Fourier TransformsAnalysis of Boolean FunctionsDiscrete Fourier Analysis and WaveletsPrinciples of Fourier AnalysisDiscrete Fourier AnalysisDiscrete Harmonic AnalysisThe Scientist and Engineer's Guide to Digital Signal ProcessingDiscrete Fourier Analysis and WaveletsMastering the Discrete Fourier Transform in One, Two or Several DimensionsThe XFT Quadrature in Discrete Fourier AnalysisMathematics of the Discrete Fourier Transform (DFT)Signal ProcessingDiscrete Fourier Transforms and their Applications,Harmonic AnalysisLectures on the Fourier Transform and Its ApplicationsAn Introduction to Fourier AnalysisDiscrete Fourier AnalysisTheory of Discrete and Continuous Fourier AnalysisThe Fast Fourier Transform and Its ApplicationsDiscrete Fourier and Wavelet TransformsIntroduction to Digital FiltersFourier Analysis—A Signal Processing ApproachMathematics of the Discrete Fourier Transform (DFT) with Music and Audio ApplicationsMathematics of the Discrete Fourier Transform (DFT)
Adapting to climate change: a case study on riverine flood risks in the Netherlands

Climate change may lead to an increased risk of river floods in the Netherlands. However, the impacts of changes in water management are even larger, whether enhancing or reducing flood risks. Therefore, the abilities of water management authorities to learn that climate and river flows are changing, and to recognise and act upon the implications are of crucial importance. At the same time, water management authorities respond to other trends, such as the democratisation of decision making, which alter their ability to react to climate change. This complex of interactions is illustrated with changes in river flood risk management for the Rhine and the Meuse in the Netherlands over the last 50 years. A scenario study is used to seek insight into the question whether current water management institutions and their likely successors are capable of dealing with plausible future flood risks. Structural solutions to future flood risks are feasible, but require considerable political will and institutional reform.
Writer Identification Using Curvature-free Features

In this chapter, we propose two novel and curvature-free features: run-lengths of Local Binary Pattern (LBPruns) and Cloud Of Line Distribution (COLD) features for writer identification. The LBPruns is the joint distribution of the traditional run-length and local binary pattern (LBP) methods, which computes the run-lengths of local binary patterns on both binarized images and gray scale images. The COLD feature is the joint distribution of the relation between orientation and length of line segments obtained from writing contours in handwritten documents. Our proposed LBPruns and COLD are textural-based curvature-free features and capture the line information of handwritten texts instead of the curvature information. The combination of the LBPruns and COLD features provides a significant improvement on the CERUG data set, handwritten documents on which contain a large number of irregular-curvature strokes. The proposed features evaluated on other two widely used data sets (Firemaker and IAM) demonstrate promising results.
Thermal State, Slab Metamorphism, and Interface Seismicity in the Cascadia Subduction Zone Based On 3‐D Modeling

Giant earthquakes have repeatedly ruptured the Cascadia subduction zone, and similar earthquakes will likely also occur there in the near future. We employ a 3‐D time‐dependent thermomechanical model that incorporates an up‐to‐date description of the slab geometry to study the Cascadia subduction thrust. Results show a distinct band of 3‐D slab dehydration that extends from Vancouver Island to the Seattle Basin and farther southward to the Klamath Mountains in northern California, where episodic tremors cluster. This distribution appears to include a region of increased dehydration in northern Cascadia. The phenomenon of heterogeneous megathrust seismicity associated with oblique subduction suggests that the presence of fluid‐rich interfaces generated by slab dehydration favors megathrust seismogenesis in the northern part of this zone. The thin, relatively weakly metamorphosed Explorer, Juan de Fuca, and Gorda Plates are associated with an anomalous lack of thrust earthquakes, and metamorphism that occurs at temperatures of 500–700°C near the Moho discontinuity may represent a key factor in explaining the presence of the associated episodic tremor and slip (ETS), which requires a young oceanic plate to subduct at a small dip angle, as is the case in Cascadia and southwestern Japan. The 3‐D intraslab dehydration distribution suggests that the metamorphosed plate environment is more complex than had previously been believed, despite the existence of channeling vein networks. Slab amphibolization and eclogitization near the continental Moho depth is thus inferred to account for the resultant overpressurization at the interface, facilitating the generation of ETS and the occurrence of small to medium thrust earthquakes beneath Cascadia.
The RapiD and SecuRe AI enhAnced DiaGnosis, Precision Medicine and Patient EmpOwerment Centered Decision Support System for Coronavirus PaNdemics

Description of the deliverable; A knowledge graph produced by systematic review of existing knowledge and the landscape of new therapeutic development that can be used to support decision making and the explainability of the analysis. Searching through the COVID-19 research literature to gain actionable clinical insight is a formidable task, even for experts. The usefulness of this corpus in terms of improving patient care is tied to the ability to see the big picture that emerges when the studies are seen in conjunction rather than in isolation. When the answer to a search query requires linking together multiple pieces of information across documents, simple keyword searches are insufficient. To answer such complex information needs, an innovative AI technology called a knowledge graph (KG) could prove to be effective
Promises and challenges of positron emission tomography for assessment of sarcoma in daily clinical practice

Abstract A correct histological diagnosis, careful staging and detection of tumour response to treatment are all crucial in the management of sarcomas. Imaging is important in all of these stages. Sarcomas have distinct biological and treatment-related features posing challenges for imaging. For example, size measurements may not adequately reflect response rates. Techniques which can measure tissue function rather than generate merely anatomical data such as positron emission tomography (PET) are rapidly gaining interest. We discuss the importance of imaging in different stages of patient management, emphasising the unique characteristics of sarcoma. Furthermore, we discuss the potential of PET for the various indications, focussing on therapy evaluation.
Statistical and Combinatorial Analysis of the TOR Routing Protocol - Structural Weaknesses Identified in the TOR Network

In this paper, we present the results of a deep analysis of TOR routing protocol from a statistical and combinatorial point of view. We have modeled all possible routes of this famous anonymity network exhaustively while taking different parameters into account with the data provided by the TOR foundation only. We have then confronted our theoretical model with the reality on the ground. To do this, we have generated thousands of roads on the TOR network and compared the results obtained with those predicted by the theory. A last step of combinatorial analysis has enabled us to identify critical subsets of Onion routers (ORs) which 33%, 50%, 66% and 75% of the TOR trafic respectively depends on. We have also managed to extract most of the TOR relay bridges which are non public nodes managed by the TOR foundation. The same results as for the ORs
A Pattern Language for Workﬂow Engine Conformance and Performance Benchmarking

Workﬂow engines are frequently used in the domains of business process management, service orchestration, and cloud computing, where they serve as middleware platforms for integrated business applications. Engines have a signiﬁcant impact on the quality of service provided by hosted applications. Therefore, it is desirable to compare them and to select the most appropriate engine for a given task. To enable such a comparison, approaches for benchmarking workﬂow engines have emerged. Although these approaches deal with diﬀerent quality attributes, i.e., performance or standard conformance, they face many reoccurring design and implementation problems, which have been solved in similar ways. In this paper, we present a pattern language that captures such common solutions to reoccurring problems (e.g., from test identiﬁcation, benchmarking procedure validation, automatic engine interaction, and workﬂow execution observation) in the area of workﬂow engine conformance and performance benchmarking. Our aim is to help future benchmark authors with the pattern language presented in this paper to beneﬁt from our experience with the design and implementation of workﬂow engine benchmarks and benchmarking tools.
Project Adaptation for MT-Enhanced Computer Assisted Translation

The effective integration of MT technology into CAT tools is a challenging topic both for academic research and the translation industry. Particularly, professional translators feel crucial the ability of MT systems to adapt to their feedback. In this paper, we propose an adaptation scheme to tune a statistical MT system to a translation project using small amounts of postedited texts. By running field tests on two domains with 8 professional translators working with a CAT tool, productivity gains up to over 20% were measured after applying MT project adaptation.
Automatic identification of best answers in online enquiry communities Conference Item

Online communities are prime sources of information. The Web is rich with forums and Question Answering (Q&A) communities where people go to seek answers to all kinds of questions. Most systems employ manual answer-rating procedures to encourage people to provide quality answers and to help users locate the best answers in a given thread. However, in the datasets we collected from three online communities, we found that half their threads lacked best answer markings. This stresses the need for methods to assess the quality of available answers to: 1) provide automated ratings to fill in for, or support, manually assigned ones, and; 2) to assist users when browsing such answers by filtering in potential best answers. In this paper, we collected data from three online communities and converted it to RDF based on the SIOC ontology. We then explored an approach for predicting best answers using a combination of content, user, and thread features. We show how the influence of such features on predicting best answers differs across communities. Further we demonstrate how certain features unique to some of our community systems can boost predictability of best answers.
This is the post-print version of the following article: “Perceived discrimination amongst young people in socio‐economically disadvantaged communities: Parental support and community identity buffer (some) negative impacts of stigma”

There is increasing acceptance that children are not unaware of when they are targets of discrimination. However discrimination as a consequence of socio-economic disadvantage remains under studied. The aim of the present study is to examine the impact of perceived discrimination on well-being, perceptions of safety and school integration amongst children growing up within socioeconomically disadvantaged communities in Limerick, Ireland. Mediation analysis was used to explore these relationship and to examine the potential buffering role of parental support and community identity in young people in the 7 th to 9 th year of compulsory education (N=199). Results indicate perceived discrimination contributed to negative outcomes in terms of school integration, perceptions of safety and levels of wellbeing. All negative outcomes were buffered by parental support. Community identity also protected young people in terms of feelings of school integration and risk but not in terms of psychological well-being. Findings are discussed in terms of the different role of family and community supports for children negotiating negative social representations of their community.
Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network: Supplementary Material

Let us recall the notation introduced in the main paper. We use superscript (i) to refer to a weight matrix or vector related to layer i in a stacked network, e.g., W h , or h (i) t . For a single-layer d-RNN, we refer to weight matrices and related vectors with "hat", e.g., Ŵh or ĥt. Additionally, we define the block notation as subvector v̂ t refers to the i-th block of vector v̂t composed of k blocks. The blocks follow the definition in Equations (3)-(5).
Exploiting Variance Reduction Potential in Local Gaussian Process Search

Gaussian process models are commonly used as emulators for computer experiments. However, developing a Gaussian process emulator can be computationally prohibitive when the number of experimental samples is even moderately large. Local Gaussian process approximation (Gramacy and Apley, 2015) was proposed as an accurate and computationally feasible emulation alternative. However, constructing local sub-designs specific to predictions at a particular location of interest remains a substantial computational bottleneck to the technique. In this paper, two computationally efficient neighborhood search limiting techniques are proposed, a maximum distance method and a feature approximation method. Two examples demonstrate that the proposed methods indeed save substantial computation while retaining emulation accuracy.
Plagiarism Detection in C++ Programs

For certain courses in the bachelor program, students have to write C++ programs to solve problems. Unfortunately it sometimes happens that students copy code from their fellow classmates, which is not allowed. Currently Moss2 is used to detect this plagiarism, but it does not find all plagiarized files. Therefore we experiment with a few new methods to improve upon Moss2. These methods are based upon transforming a file into a numerical array, which can be compared to other array’s of other files. Based upon these array’s, some of the new methods can express a distance between two files that could indicate plagiarism. The other methods can indicate what parts of these files might be plagiarized. To nullify certain plagiarism techniques, such as variable renaming, a preprocessing option is included that is able to edit files before they are divided into the numerical array’s.