Miracle-dz/UniFAR-FTUs huggingface dataset:
Workshop on the Physics and Chemistry of Magma Oceans from 1 Bar to 4 Mbar

Evidence for the existence of magma oceans is discussed in great detail, and among the many new items introduced were high-pressure phase equilibrium experiments, calculations of depth of impact-produced melting, models incorporating crystal growth rates with degree of crystallinity and convection, and models of hard turbulent convection. It was agreed that before we can point to some present-day observable parameters and confidently establish the existence of magma oceans, we must learn much more about their phase equilibria and solidification dynamics.
Supporting Children with Reading Difficulties Across the Summer Learning Gap

Aims: This study describes the components, and tests the efficacy of a full-day summer learning program offered by the Learning Disabilities Association of Niagara Region. The program is aimed to support children with reading difficulties who are particularly susceptible to the summer learning gap. Study Design: The summer program described in this study was designed to support children with reading difficulties in their development of foundational literacy skills including sight word efficiency, phonemic decoding, letter-sound understanding, and reading fluency. To assess the efficacy of the program, participating children were assessed on the first and last day of the week-long intensive intervention program. Methodology: A total of 31 children participated in the full-day summer learning program, Sunshine Learning Achievement and More (S.L.A.M.) program and were assessed using a pre post-test design utilizing five measures of literacy achievement corresponding to the literacy skills taught within the program. Results: Statistically significant results emerged for all measures including sight word efficiency [t (28) = -6.30, p < . 001, d = -. 03], phonemic decoding efficiency [t (26) = -6.64, p < . 001, d = -0.36], letter names [t (30) = -3.70, p < . 005, d = -0.21], letter sounds [t (28) = 4.72, p < . 001, d = -0.65], and reading fluency [t (28) = -8.40, p < . 001, d = -1.46]. Original Research Article British Journal of Education, Society & Behavioural Science, 4(3): 375-382, 2014 376 Conclusion: The findings of the study show the importance providing ongoing support to vulnerable readers or children with reading difficulties throughout the weeks of summer where significant learning loss is particularly evident. The study holds implications for all stakeholders concerned about supporting children with reading difficulties.
Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach

Large-scale analysis of EEG and other physiological measures promises new insights into brain processes and more accurate and robust brain–computer interface models. However, the absence of standardized vocabularies for annotating events in a machine understandable manner, the welter of collection-specific data organizations, the difficulty in moving data across processing platforms, and the unavailability of agreed-upon standards for preprocessing have prevented large-scale analyses of EEG. Here we describe a “containerized” approach and freely available tools we have developed to facilitate the process of annotating, packaging, and preprocessing EEG data collections to enable data sharing, archiving, large-scale machine learning/data mining and (meta-)analysis. The EEG Study Schema (ESS) comprises three data “Levels,” each with its own XML-document schema and file/folder convention, plus a standardized (PREP) pipeline to move raw (Data Level 1) data to a basic preprocessed state (Data Level 2) suitable for application of a large class of EEG analysis methods. Researchers can ship a study as a single unit and operate on its data using a standardized interface. ESS does not require a central database and provides all the metadata data necessary to execute a wide variety of EEG processing pipelines. The primary focus of ESS is automated in-depth analysis and meta-analysis EEG studies. However, ESS can also encapsulate meta-information for the other modalities such as eye tracking, that are increasingly used in both laboratory and real-world neuroimaging. ESS schema and tools are freely available at www.eegstudy. org and a central catalog of over 850 GB of existing data in ESS format is available at studycatalog.org. These tools and resources are part of a larger effort to enable data sharing at sufficient scale for researchers to engage in truly large-scale EEG analysis and data mining (BigEEG.org).
Automatic Discovery of Preservation Alternatives Supported by Community Maintained Knowledge Bases

Preservation Planning, which deals with selecting the most appropriate preservation action to be applied to digital objects, is an important step in any digital preservation activity. Comprehensive Preservation Planning depends on the availability of identified alternatives of preservation actions, which are for example file format migrations to migrate data in an outdated format to one that has better support. Also emulation, e.g. of the behaviour of a specific software application (application emulation), can be a viable preservation action. The alternative identification step can either be performed manually by an expert, or (semi-)automatically, if appropriate knowledge bases are available. Building and maintaining such knowledge bases is however a tedious task, as the number of software applications and file formats, and especially their relation to each other, is very large. In this paper, we therefore present an approach to automatically build knowledge bases for Preservation Planing from already existing, open resources. One such source is the community maintained Freebase, which contains linked data on many topics, among them file formats, software applications, and most importantly, their relations, in a structured manner. We demonstrate the applicability of these knowledge bases by automatically identifying possible digital preservative actions on a uses case, an eScience experiment from the domain of data mining. This use case originates from the task of process preservation, where we look beyond single files, but regard complete chains of executions as the objects to be preserved.
Rule of Three for Superresolution of Still Images with Applications to Compression and Denoising

We describe a new method for superresolution of still images (in the wavelet domain) based on the reconstruction of missing details subbands pixels at a given ith level via Rule of Three (Ro3) between pixels of approximation subband of such level, and pixels of approximation and detail subbands of (i+1)th level. The histogramic profiles demonstrate that Ro3 is the appropriate mechanism to recover missing detail subband pixels in these cases. Besides, with the elimination of the details subbands pixels (in an eventual compression scheme), we obtain a bigger compression rate. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain. Our method does not compress, but facilitates the action of the real compressor, in our case, Joint Photographic Experts Group (JPEG) and JPEg2000, that is, Ro3 acts as a catalyst compression
Glucose meter inaccuracy and the impact on the care of patients

Blood glucose testing utilizing point‐of‐care (POC) glucose meters has become increasingly common – in hospital settings, in outpatient areas, and in the self‐care of patients. It is rightly considered an essential tool for the management of diabetes. But many who rely on these meters are unaware of the pitfalls in their use and do not realize that there are settings where misleading results obtained by POC glucose meters may alter clinical decisions in the care of persons with diabetes and in some cases have caused catastrophic errors in care, even deaths. Their use in critical care settings is of great concern because many of the factors that increase the risk of inaccuracy of the POC glucose meters exist in critical care settings. Unfortunately, many clinicians are still uncritically accepting data from the POC glucose meters, to the potential detriment of the care of the patients.
Increasing the Efficiency of Latency-Driven DVFS with a Smart NoC Congestion Management Strategy

Dynamic Voltage and Frequency Scaling (DVFS) can be a very effective power management strategy not only for on-chip processing elements but also for the network-on-chip (NoC). In this paper we propose a new approach to DVFS in NoC, which combines a congestion management strategy with a feedback-loop controller. The controller sets frequency and voltage to the lowest values that keep the NoC latency below a predetermined threshold. To cope with burstiness and hotspot patterns, which may lead the controller to overdrive the NoC with too high frequencies and voltages, leading to excessive power consumption, the congestion management strategy promptly identifies the flows that caused the abnormal traffic situation and eliminates them from the latency calculation, leading to a significantly higher power saving. Compared to a baseline DVFS strategy without congestion management, our results show that our proposal saves up to 53% more power when bursty or hotspot-based traffic patterns are detected. In addition, since we also apply power-gating to make an efficient use of the network buffers, we achieve an improvement of up to 38% in power savings when no bursts or hotspots are present.
The Mood of the (Financial) Markets: In a Corpus of Words and of Pictures

Corpora of texts are used typically to study the structure and function of language. The distribution of various linguistic units, comprising texts in a corpus are used to make and test hypotheses relevant to different linguistic levels of description. News reports and editorials have been used extensively to populate corpora for studying language, for making dictionaries and for writing grammar books. News reports of financial markets are generally accompanied by time-indexed series of values of shares, currencies and so on, reflecting the change in value over a period of time. A corpus linguistic method for extracting sentiment indicators, e.g. shares going up or a currency falling down, is presented together with a technique for correlating the quantitative time-series of values with a time series of sentiment indicators. The correlation may be used in the analysis of the movement of shares, currencies and other financial instruments.
Unions of Disjoint NP-Complete Sets

We study the following question: if <i>A</i> and <i>B</i> are disjoint NP-complete sets, then is <i>A</i> ∪ <i>B</i> NP-complete? We provide necessary and sufficient conditions under which the union of disjoint NP-complete sets remain complete.
Orthophoto feature extraction and clustering

In this article we use a combination of neural networks with other techniques for the analysis of orthophotos. Our goal is to obtain results that can serve as a useful groundwork for interactive exploration of the terrain in detail. In our approach we split an aerial photo into a regular grid of segments and for each segment we detect a set of features. These features depict the segment from the viewpoint of a general image analysis (color, tint, etc.) as well as from the viewpoint of the shapes in the segment. We perform clustering based on the Formal Concept Analysis (FCA) and Non-negative Matrix Factorization (NMF) methods and project the results using effective visualization techniques back to the aerial photo. The FCA as a tool allows users to be involved in the exploration of particular clusters by navigation in the space of clusters. In this article we also present two of our own computer systems that support the process of the validation of extracted features using a neural network and also the process of navigation in clusters. Despite the fact that in our approach we use only general properties of images, the results of our experiments demonstrate the usefulness of our approach and the potential for further development.
An ac-dc single-stage full-bridge PWM converter with bridgeless input

A new ac-dc single-stage full-bridge PWM converter is proposed in the paper. The converter can operate with an excellent input power factor, continuous input and output currents, and has a bridgeless input that helps reduce conduction losses. In the paper, the basics of bridgeless ac-dc converters are briefly reviewed, the operation of the proposed converter is discussed, and experimental results that were obtained from a prototype and that confirm its feasibility are presented.
A Mathematical Theory for Clustering in Metric Spaces

Clustering is one of the most fundamental problems in data analysis and it has been studied extensively in the literature. Though many clustering algorithms have been proposed, clustering theories that justify the use of these clustering algorithms are still unsatisfactory. In particular, one of the fundamental challenges is to address the following question: What is a cluster in a set of data points? In this paper, we make an attempt to address such a question by considering a set of data points associated with a distance measure (metric). We first propose a new <italic>cohesion</italic> measure in terms of the distance measure. Using the cohesion measure, we define a cluster as a set of points that are cohesive to themselves. For such a definition, we show there are various equivalent statements that have intuitive explanations. We then consider the second question: How do we find clusters and good partitions of clusters under such a definition? For such a question, we propose a hierarchical agglomerative algorithm and a partitional algorithm. Unlike standard hierarchical agglomerative algorithms, our hierarchical agglomerative algorithm has a specific stopping criterion and it stops with a partition of clusters. Our partitional algorithm, called the <inline-formula><tex-math notation="LaTeX">$K$</tex-math><alternatives> <inline-graphic xlink:type="simple" xlink:href="chang-ieq1-2516339.gif"/></alternatives></inline-formula>-sets algorithm in the paper, appears to be a new iterative algorithm. Unlike the Lloyd iteration that needs two-step minimization, our <inline-formula><tex-math notation="LaTeX">$K$</tex-math><alternatives> <inline-graphic xlink:type="simple" xlink:href="chang-ieq2-2516339.gif"/></alternatives></inline-formula>-sets algorithm only takes one-step minimization. One of the most interesting findings of our paper is the duality result between a distance measure and a cohesion measure. Such a duality result leads to a dual <inline-formula><tex-math notation="LaTeX">$K$ </tex-math><alternatives><inline-graphic xlink:type="simple" xlink:href="chang-ieq3-2516339.gif"/></alternatives></inline-formula>-sets algorithm for clustering a set of data points with a cohesion measure. The dual <inline-formula> <tex-math notation="LaTeX">$K$</tex-math><alternatives><inline-graphic xlink:type="simple" xlink:href="chang-ieq4-2516339.gif"/> </alternatives></inline-formula>-sets algorithm converges in the same way as a sequential version of the classical kernel <inline-formula><tex-math notation="LaTeX">$K$</tex-math><alternatives> <inline-graphic xlink:type="simple" xlink:href="chang-ieq5-2516339.gif"/></alternatives></inline-formula>-means algorithm. The key difference is that a cohesion measure does not need to be positive semi-definite.
Signal decomposition by multi-scale PCA and its applications to long-term EEG signal classification

Data coming from a real-world complex system are usually contaminated by certain levels of noise or some irrelevant components, which do not contribute to improve signal classification accuracy. Also in signal de-noising, the performance of any statistical method used to recover the original signals may be impacted by the noise. In this paper, we propose the multi-scale principal component analysis (PCA) method, which combines discrete wavelet transform and PCA for de-noising and decomposing complex biomedical signals in both spatial and temporal domains for signal classification. We also develop a new classification method, called Empirical Classification (EC), based on the characteristics of data we analyzed. These methods were applied to a publicly available EEG database for the purpose of epilepsy diagnosis and epileptic seizure detection. Our study shows that signal decomposition by the multi-scale PCA method coupled with the EC method, leads to a highly promising classification accuracy in classifying epileptic EEG signals. Our methods are also applicable for classifying biomedical images.
Tailoring e-commerce sites to ease recovery after disruptions

Developers of e-commerce applications are often unrealistic about how their Web site is going to be used, and about possible outcomes during site usage. The most commonly considered outcomes of a user's visit to a site are firstly that the visit culminates in a sale, and secondly that the user leaves the site without buying anything - perhaps to return later. In the second case, sites often "remember" any accumulated items so that a shopper can return at a later stage to resume shopping. In this paper, we consider certain disruptions, such as breakdowns, problems caused by human errors and interruptions, which could affect the outcome of the e-commerce shopping experience. These events have definite and possibly long-lasting effects on users, and applications should therefore be developed to cater for these eventualities so as to enhance the usability of the site and encourage further usage. We develop a model for analysing e-commerce application usage and, using this model, propose an evaluation strategy for determining whether an e-commerce site is resistant to such factors. The proposed evaluation mechanism is applied to three sites to arrive at what we call a "disruption-resistance score".
High-performance data structures for de novo assembly of genomes: cache oblivious generic programming

Reconstructing genomes of organisms from high-throughput sequencing experiments without a reference genome available (de novo assembly) is a challenging problem which has been approached in several ways in the past decade. Although numerous methods are available and many offer fair performance in reconstruction, there is a lack of generalized template libraries and interchangeable data structures/methods for serial, multithreaded and distributed processing. In this work we propose a novel set of cache oblivious generic data structures for serial, multithreaded and distributed processing of high-throughput sequencing data for the creation of de Bruijn or k-mer graphs towards their usage in de novo assembly and related HTS data analytics problems.
Performance analysis of a city smart grid communication network based on the IEEE 802.16e standard

A smart grid communication network will enable the electricity operators to connect various intelligent devices, smart meters and other sensors to different servers located within the electricity grid. Automated meter reading is a key feature of a smart grid which requires installation of a communication network that can access 100% of smart meters within its coverage area. Smart meter connectivity in inner cities is a challenging problem due to the location of meters inside high rise buildings as well as due to difficult propagation conditions. In this paper we analyze the connectivity pattern of smart meters in an inner city environment using an IEEE 802.16e based WiMAX network. The paper initially models the inner city propagation environment to study the connectivity pattern. Based on the propagation model the work developed a transmission power ramping algorithm to provide 100% meter connectivity. Simulation models were developed based on OPNET and MATLAB packages.
Indifferentiable Security Analysis of choppfMD, chopMD, a chopMDP, chopWPH, chopNI, chopEMD, chopCS, and chopESh Hash Domain Extensions

We provide simple and unified indifferentiable security analyses of choppfMD, chopMD, a chopMDP (where the permutation P is to be xored with any non-zero constant.), chopWPH (the chopped version of Wide-Pipe Hash proposed in [16]), chopEMD, chopNI, chopCS, chopESh hash domain extensions. Even though there are security analysis of them in the case of no-bit chopping (i.e., s = 0), there is no unified way to give security proofs. All our proofs in this paper follow the technique introduced in [3]. These proofs are simple and easy to follow.
A new technique for design CMOS LNA for multi-standard receivers

The paper presents the design of a novel low-noise amplifier (LNA), for GSM and UMTS receivers, in a 0.18-/spl mu/m CMOS technology using an HSPICE simulator. For receiving signals of lower frequency, higher value inductors are needed. We have employed a new technique for obtaining the equivalent higher inductance at lower frequency by paralleling an appropriate capacitor with the inductor. Therefore it is not required to use an additional inductor for receiving lower frequency bands. By only switching the appropriate capacitor in parallel with the inductor, we can use one LNA for receiving more than one band; therefore this approach is very useful in multi-standard receivers. We have used this technique for receiving the UMTS and GSM standards. Simulation results show that, voltage gain, NF, IIP3 and 1-dB compression point are, respectively, 23.34 dB, 3.96 dB -6.27 dBm and -15 dBm for UMTS and 24.9 dB, 2.6 dB, -21.55 dBm and -25.7 dBm for GSM. The supply voltage is 1 V and LNA consumes only 9.04 mW.
Dermatofibrosarcoma protuberans of the breast: A case report

Dermatofibrosarcoma protuberans (DFSP) is a rare malignant tumor of subcutaneous tissue characterized by slow infiltrative growth. The tumor occurs in patients of all ages, with the highest frequency occurring between the second and the fifth decades of age. Genetically, DFSP is characterized by a reciprocal translocation t(17;22)(q22;q13), or more often, as a supernumerary ring chromosome involving chromosomes 17 and 22. Standard treatment of a localized tumor is surgical excision with wide margins. In the present study, a case report of a 43-year-old woman with a growing tumor in the left breast is discussed. The patient underwent breast-conserving surgery. Histological and cytogenetic examinations of the tumor resulted in a diagnosis of DFSP. The clinical and morphological characteristics of the tumor, in addition to the treatment options, were also evaluated.