Miracle-dz/UniFAR-FTUs huggingface dataset:
Aspects of the Biogeochemistry of Magnesium 1. Calcareous Marine Organisms

A study was made of the factors controlling the distribution of magnesium in the calcareous skeletons of marine organisms. The mineralogy of the carbonate appears to be the most important influence, with large amounts of magnesium occurring in solid solution in the calcitic forms and generally lesser amounts in the aragonitic forms. The complexity of the organisms and the temperature of the water in which they lived are also controlling factors in the amount of magnesium present. A large part of the study, both mineralogical and chemical, was made with X-ray diffraction techniques.
Trade-winds during the glacial cycles

Two deep-sea cores (one north, the other south of the Cape Verde Islands) have been analysed for (i) size distribution of the quartz mineral grains, (ii) mineralogy and colour of carbonate-free clay, (iii) frequency of the Globorotalia menardii foraminifera, (iv) the total carbonate, and (v) the 18O/16O deviations. The size analyses establish a general law . The plot of the logarithm of the cumulative mass percentage for particles equal to or greater than diameter D against D2 is linear above a critical particle size, which in this case is about 7 μm. The linear form can be explained by a simple winnowing theory which expresses the slope of the line in terms involving the speed of bulk flow of the trade winds, the distance along a trajectory between the coast and the core site, and a characteristic height describing the vertical distribution of dust in the air. Variations of the slope of the size distributions down the core relate to trade wind conditions during the glacial cycles. Together with the mineralogical and biological data it seems that the trades have been more ‘vigorous’ during the glacial stages.
A taxonomy and survey of grid resource management systems for distributed computing

The resource management system is the central component of distributed network computing systems. There have been many projects focused on network computing that have designed and implemented resource management systems with a variety of architectures and services. In this paper, an abstract model and a comprehensive taxonomy for describing resource management architectures is developed. The taxonomy is used to identify approaches followed in the implementation of existing resource management systems for very large‐scale network computing systems known as Grids. The taxonomy and the survey results are used to identify architectural approaches and issues that have not been fully explored in the research. Copyright © 2001 John Wiley & Sons, Ltd.
A statistical approach using network structure in the prediction of protein characteristics

MOTIVATION The Majority Vote approach has demonstrated that protein-protein interactions can be used to predict the structure or function of a protein. In this article we propose a novel method for the prediction of such protein characteristics based on frequencies of pairwise interactions. In addition, we study a second new approach using the pattern frequencies of triplets of proteins, thus for the first time taking network structure explicitly into account. Both these methods are extended to jointly consider multiple organisms and multiple characteristics. RESULTS Compared to the standard non-network-based method, namely the Majority Vote method, in large networks our predictions tend to be more accurate. For structure prediction, the Frequency-based method reaches up to 71% accuracy, and the Triplet-based method reaches up to 72% accuracy, whereas for function prediction, both the Triplet-based method and the Frequency-based method reach up to 90% accuracy. Function prediction on proteins without homologues showed slightly less but comparable accuracies. Including partially annotated proteins substantially increases the number of proteins for which our methods predict their characteristics with reasonable accuracy. We find that the enhanced Triplet-based method does not currently yield significantly better results than the enhanced Frequency-based method, suggesting that triplets of interactions do not contain substantially more information about protein characteristics than interaction pairs. Our methods offer two main improvements over current approaches--first, multiple protein characteristics are considered simultaneously, and second, data is integrated from multiple species. In addition, the Triplet-based method includes network structure more explicitly than the Majority Vote and the Frequency-based method. AVAILABILITY The program is available upon request. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Effective asymmetric XML compression

The innate verbosity of the extensible markup language (XML) remains one of its main weaknesses, especially when large documents are concerned. This problem can be solved with the aid of dedicated XML compression algorithms. In this work, we describe XML word-replacing transform (XML-WRT), a fast and fully reversible XML transform, which, when combined with generally used LZ77-style compression algorithms, allows to attain high compression ratios, comparable to those achieved by the current state-of-the-art XML compressors. The resulting compression scheme is asymmetric in the sense that its decoder is much faster than the coder. This is a desirable practical property, as in many XML applications data are read much more often than written. The key features of the transform are dictionary-based encoding of both document structure and content, separation of different content types into multiple streams, and dedicated encoding of specific patterns, including numbers and dates. The test results show that the proposed transform improves the XML compression efficiency of general-purpose compressors on average by 35p in case of gzip, and 17p in case of LZMA. Compared with the current state-of-the-art SCMPPM algorithm, XML-WRT with LZMA attains over 2p better compression ratio, while being 55p faster. Copyright © 2007 John Wiley & Sons, Ltd.
Bled Electronic Commerce Conference e-Reality : Constructing the e-Economy Bled , Slovenia , June 17-19 , 2002 An e-Business Model Ontology for Modeling e-Business

After explaining why business executives and academics should consider thinking about a rigorous approach to e-business models, we introduce a new e-Business Model Ontology. Using the concept of business models can help companies understand, communicate and share, change, measure, simulate and learn more about the different aspects of e-business in their firm. The generic e-Business Model Ontology (a rigorous definition of the e-business issues and their interdependencies in a company’s business model), which we outline in this paper is the foundation for the development of various useful tools for e-business management and IS Requirements Engineering. The e-Business Model Ontology is based on an extensive literature review and describes the logic of a “business system” for creating value in the Internet era. It is composed of four main pillars, which are Product Innovation, Infrastructure Management, Customer Relationship and Financial Aspects. These elements are then further decomposed.
Reverse-link power control in CDMA distributed antenna systems

It is well known that transmit power control is an essential component of any CDMA system. In conventional cellular systems, the interface between the wired network and wireless medium is the base station antenna (or closely located antennas if there is microdiversity) placed at the geographic center of the cell area. With such a "centralized" antenna, however, it is often impossible to maintain perfect power control (even if the power levels are adjusted in a precise and instantaneous manner) due to the fact that the required transmit power levels would occasionally (or often) be beyond practical limits; this is especially true for environments that yield high path losses. We investigate the peak and median transmit power requirements in a CDMA system that employs power control with a distributed antenna architecture. Computer simulations show that by using such an antenna architecture with only 4 antenna elements, the median and peak transmit power levels can be reduced by 13 dB and 20 dB, respectively. This may yield a substantial increase in system capacity, as well as a prolonged subscriber battery usage that may be critical in high data rate applications.
The MediaEval 2012 Affect Task: Violent Scenes Detection

This paper provides a description of the MediaEval 2012 Affect Task: Violent Scenes Detection. This task derives directly from a Technicolor use case which aims at easing a user's selection process from a movie database. This task will therefore apply to movie content. We provide some insight into the Technicolor use case, before giving details on the task itself. Dataset, annotations, and evaluation criteria as well as the two required and optional runs are described.
Beyond Proof-of-compliance: Security Analysis in Trust Management beyond Proof-of-compliance: Security Analysis in Trust Management

Trust management is a form of distributed access control that allows one principal to delegate some access decisions to other principals. While this makes trust management more flexible than the access matrix model, it makes safety and security analysis more important. We show that in contrast to the undecidability of classical HRU safety properties, our primary security properties are decidable. In particular, most safety properties we study are decidable in polynomial time. The computational complexity of containment analysis, the most complicated security property we study, forms a complexity hierarchy based on the expressive power of the trust management language.
Detecting periodic patterns in unevenly spaced gene expression time series using Lomb-Scargle periodograms

MOTIVATION Periodic patterns in time series resulting from biological experiments are of great interest. The commonly used Fast Fourier Transform (FFT) algorithm is applicable only when data are evenly spaced and when no values are missing, which is not always the case in high-throughput measurements. The choice of statistic to evaluate the significance of the periodic patterns for unevenly spaced gene expression time series has not been well substantiated. METHODS The Lomb-Scargle periodogram approach is used to search time series of gene expression to quantify the periodic behavior of every gene represented on the DNA array. The Lomb-Scargle periodogram analysis provides a direct method to treat missing values and unevenly spaced time points. We propose the combination of a Lomb-Scargle test statistic for periodicity and a multiple hypothesis testing procedure with controlled false discovery rate to detect significant periodic gene expression patterns. RESULTS We analyzed the Plasmodium falciparum gene expression dataset. In the Quality Control Dataset of 5080 expression patterns, we found 4112 periodic probes. In addition, we identified 243 probes with periodic expression in the Complete Dataset, which could not be examined in the original study by the FFT analysis due to an excessive number of missing values. While most periodic genes had a period of 48 h, some had a period close to 24 h. Our approach should be applicable for detection and quantification of periodic patterns in any unevenly spaced gene expression time-series data.
Robust adaptive sliding mode controller for triaxial gyroscope

This paper presents an adaptive variable structure controller with on-line identification of the upper bounds of uncertainties and disturbance for MEMS triaxial angular sensors device that is able to detect rotation in three orthogonal axes, using a single vibrating mass. An adaptive robust sliding mode controller is developed and the stability of the closed-loop system can be guaranteed with the proposed adaptive robust sliding mode control strategy. The on-line identification of the upper bounds of uncertainties and disturbance can be incorporated into sliding mode controller to alleviate the chartering. The proposed adaptive sliding mode controller updates estimates of all stiffness, damping errors, and input rotation parameters, upper bound of uncertainties and disturbance in real time, removing the need for any offline calibration stages. The numerical simulation for MEMS gyroscope triaxial angular sensor is investigated to verify the effectiveness of the proposed adaptive robust sliding mode control scheme.
A Feedback Quantization Scheme Leveraging Fairness and Throughput for Heterogeneous Multi-User Diversity Systems

We propose a feedback quantization scheme for downlink multiuser diversity systems. The scheme is designed for heterogeneous users, i.e., users operating under different levels of mean signal-to-noise ratios (SNRs). The proposed scheme equally distributes the channel access time to user clusters and, at the same time, maximizes the sum-rate capacity under equal-channel-access-time constraint. The method is compared to a normalized SNR scheduler, full-feedback scheduler, and finite-rate feedback scheduler without fairness consideration to illustrate the performance gaps between different modes of operation.
Hardware-independent Proofs of Numerical Programs

On recent architectures, a numerical program may give different answers depending on the execution hardware and the compilation. Our goal is to formally prove properties about numerical programs that are true for multiple architectures and compilers. We propose an approach that states the rounding error of each floating-point computation whatever the environment. This approach is implemented in the Frama-C platform for static analysis of C code. Small case studies using this approach are entirely and automatically proved.
Big Little Transformer Decoder

The recent emergence of Large Language Models based on the Transformer architecture has enabled dramatic advancements in the field of Natural Language Processing. However, these models have long inference latency, which limits their deployment, and which makes them prohibitively expensive for various real-time applications. The inference latency is further exacerbated by autoregressive generative tasks, as models need to run iteratively to generate tokens sequentially without leveraging token-level parallelization. To address this, we propose Big Little Decoder (BiLD), a framework that can improve inference efficiency and latency for a wide range of text generation applications. The BiLD framework contains two models with different sizes that collaboratively generate text. The small model runs autoregressively to generate text with a low inference cost, and the large model is only invoked occasionally to refine the small model’s inaccurate predictions in a non-autoregressive manner. To coordinate the small and large models, BiLD introduces two simple yet effective policies: (1) the fallback policy that determines when to hand control over to the large model; and (2) the rollback policy that determines when the large model needs to correct the small model’s inaccurate predictions. To evaluate our framework across different tasks and models, we apply BiLD to various text generation scenarios encompassing machine translation on IWSLT 2017 De-En and WMT 2014 De-En, and summarization on XSUM and CNN/DailyMail. On an NVIDIA T4 GPU, our
Reading the Comments: Likers, Haters, and Manipulators at the Bottom of the Web

Online comment can be informative or misleading, entertaining or maddening. Haters and manipulators often seem to monopolize the conversation. Some comments are off-topic, or even topic-less. In this book, Joseph Reagle urges us to read the comments. Conversations "on the bottom half of the Internet," he argues, can tell us much about human nature and social behavior. Reagle visits communities of Amazon reviewers, fan fiction authors, online learners, scammers, freethinkers, and mean kids. He shows how comment can inform us (through reviews), improve us (through feedback), manipulate us (through fakery), alienate us (through hate), shape us (through social comparison), and perplex us. He finds pre-Internet historical antecedents of online comment in Michelin stars, professional criticism, and the wisdom of crowds. He discusses the techniques of online fakery (distinguishing makers, fakers, and takers), describes the emotional work of receiving and giving feedback, and examines the culture of trolls and haters, bullying, and misogyny. He considers the way comment -- a nonstop stream of social quantification and ranking -- affects our self-esteem and well-being. And he examines how comment is puzzling -- short and asynchronous, these messages can be slap-dash, confusing, amusing, revealing, and weird, shedding context in their passage through the Internet, prompting readers to comment in turn, "WTF? "
An Approach to Find Localization of Non-Existent Historical Buildings by Terrestrial Photogrammetry

Preservation of cultural and historical values located in Bosphorus Area in Turkey and protection of natural structure is guaranteed by Bosphorus Law. According to the law, land owners who want to raise a new building in Bosphorus area can only do exactly like the previously constructed building in that area. In the event that there is no construction whatsoever regarding the building in the area, information about the building that will be constructed can only be reached by historical photographs. The study that is presented is made with the purpose of identifying if the historical building that can only be reached by historical maps and photographs and is planned to be reconstructed in the Bosphorus area, is the building shown in photographs or not, and also if it is on the alleged area. Aerial photograph of 1937, actual 1/1000 scaled digital photogrammetric map and satellite image of the same area, historical perspective photograph that was taken between 1903-1907, actual photograph that was taken with around the same perspective and 3D Google Earth image which provides the same perspective are used for this process. Historical buildings that remain the same until today are confirmed by the historical aerial photograph which includes study area and these buildings are used as control point. In the same way, with the historical perspective photograph, buildings that reach until today are confirmed and used as control point. With the acquired results, that the building is totally in the alleged parcel is crosschecked with all methods and confirmed with the error of 1.8357 meters.
Semantic Image Manipulation with Background-guided Internal Learning

Image manipulation has attracted a lot of interest due to its wide range of applications. Prior work modifies images either from low-level manipulation, such as image inpainting or through manual edits via paintbrushes and scribbles, or from high-level manipulation, employing deep generative networks to output an image conditioned on high-level semantic input. In this study, we propose Semantic Image Manipulation with Background-guided Internal Learning (SIMBIL), which combines high-level and low-level manipulation. Specifically, users can edit an image at the semantic level by applying changes on a scene graph. Then our model manipulates the image at the pixel level according to the modified scene graph. There are two major advantages of our approach. First, high-level manipulation of scene graphs requires less manual effort from the user compared to manipulating raw image pixels. Second, our low-level internal learning approach is scalable to images of various sizes without reliance on external visual datasets for training. We outperform the state-of-the-art in a quantitative and qualitative evaluation on the CLEVR and Visual Genome datasets. Experiments show 8 points improvement on FID scores (CLEVR) and 27% improvement on user evaluation (Visual Genome), demonstrating the effectiveness of our approach.
Tensorizing Subgraph Search in the Supernet

Recently, a special kind of graph, i.e., supernet, which allows two nodes connected by multi-choice edges, has exhibited its power in neural architecture search (NAS) by searching better architectures for computer vision (CV) and natural language processing (NLP) tasks. In this paper, we discover that the design of such discrete architectures also appears in many other important learning tasks, e.g., logical chain inference in knowledge graphs (KGs) and meta-path discovery in heterogeneous information networks (HINs). Thus, we are motivated to generalize the supernet search problem on a broader horizon. However, none of the existing works are effective since the supernet’s topology is highly task-dependent and diverse. To address this issue, we propose to tensorize the supernet, i.e., unify the subgraph search problems by a tensor formulation and encode the topology inside the supernet by a tensor network. We further propose an efficient algorithm that admits both stochastic and deterministic objectives to solve the search problem. Finally, we perform extensive experiments on diverse learning tasks, i.e., architecture design for CV, logic inference for KG, and meta-path discovery for HIN. Empirical results demonstrate that our method leads to better performance and architectures.
Model-Integrated Computing

Computers now control many critical systems in our lives, from the brakes on our cars to the avionics control systems on planes. Such computers wed physical systems to software, tightly integrating the two and generating complex component interactions unknown in earlier systems. Thus, it is imperative that we construct software and its associated physical system so they can evolve together. The paper discusses one approach that accomplishes this called model-integrated computing. This works by extending the scope and use of models. It starts by defining the computational processes that a system must perform and develops models that become the backbone for the development of computer-based systems. In this approach, integrated, multiple-view models capture information relevant to the system under design. The paper considers the Multigraph Architecture framework for model-integrated computing developed at Vanderbilt's Measurement and Computing Systems Laboratory.
Static Members and Cycles in Java Software

The static modifier is a convenient way to make class members "global" in object-oriented software systems. Given this, we wondered if static members significantly contribute to the long dependency cycles among the classes that we observed in a previous empirical study of Java software. In this paper, we examine 81 open source Java applications. We find empirical evidence that classes that declare a non-private static field or method that is accessed from within another class are likely to be involved in dependency cycles.
On computably locally compact Hausdorff spaces

Locally compact Hausdorff spaces generalise Euclidean spaces and metric spaces from ‘metric’ to ‘topology’. But does the effectivity on the latter (Brattka and Weihrauch 1999; Weihrauch 2000) still hold for the former? In fact, some results will be totally changed. This paper provides a complete investigation of a specific kind of space – computably locally compact Hausdorff spaces. First we characterise this type of effective space, and then study computability on closed and compact subsets of them. We use the framework of the representation approach, TTE, where continuity and computability on finite and infinite sequences of symbols are defined canonically and transferred to abstract sets by means of notations and representations.