Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental Observation of Energetic Ions Accelerated by Three-dimensional Magnetic Reconnection in a Laboratory Plasma

Magnetic reconnection is widely believed responsible for heating the solar corona as well as for generating X-rays and energetic particles in solar flares. On astrophysical scales, reconnection in the intergalactic plasma is a prime candidate for a local source (<100 Mpc) of cosmic rays exceeding the Greisen-Zatsepin-Kúzmin cutoff (~1019 eV). In a laboratory astrophysics experiment, we have made the first observation of particles accelerated by magnetic reconnection events to energies significantly above both the thermal and the characteristic magnetohydrodynamic energies. These particles are correlated temporally and spatially with the formation of three-dimensional magnetic structures in the reconnection region.
University of Birmingham High throughput functional annotation and data mining with the Blast2GO suite

Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.
Variance maximization via noise injection for active sampling in learning to rank

Active learning for ranking, which is to selectively label the most informative examples, has been widely studied in recent years. In this paper, we propose a general active learning for ranking strategy called Variance Maximization (VM). The algorithm relies on noise injection to perturb the original unlabeled examples and generate the rank distribution of each example. Using a DCG-like gain function to measure each ranked list sampled from the rank distribution, Variance Maximization selects the unlabeled example with the largest variance in the gain. The VM strategy is applied at both the query level and the document level, and a two-stage active learning algorithm is further derived. Experimental results on both the LETOR 4.0 dataset and a real-world Web search ranking dataset have demonstrated the effectiveness of the proposed active learning approach.
A Family of Design Patterns for Applications-Level Gateways

Developers of communication software must confront recurring design challenges involving robustness, efficiency, and extensibility. Many of these challenges are independent of the application-specific requirements. Successful developers resolve these challenges by applying appropriate design patterns. However, these patterns have traditionallybeen locked in the minds of expert developers or buried within complex system source code. The primary contribution of this paper is to describe a family of design patterns that underly many object-oriented communication software systems. In addition to describing each pattern separately, the paper illustrates how knowledge of the relationships and trade-offs among patterns helps guide the construction of reusable communication software frameworks.
Multi-Phase Fault Detection and Analysis in FPGA Interconnects

With the increase in integration density in FPGA devices, the possibility of interconnect faults are increasing. Various fault diagnosis approach were observed for the detection of faults in FPGA, through the conventional ATE. These devices are designed for the detection of logical faults occurring in the operation of the FPGA. The ATE devices are currently designed to diagnosis the FPGA operation for faults and intern the fault detection is rectified by reprogramming the device. The localization of such faults will result in faster fault diagnosis. In this paper an approach for faults in FPGA interconnects is developed called forward tree coding. The approach is developed to isolate the fault region in a defined FPGA to reduce the time to market of digital devices. The designing and realization of the suggested approach on a targeted Xilinx device is also developed to evaluate its real time feasibility.
Territory-Based Interaction Techniques for Tabletop Collaboration

For over hundreds of years people have been gathering around tables for the purposes of eating, conversing, working, and entertaining. Co-located collaboration researchers exploring alternatives to traditional “desktop” computers are beginning to exploit the benefits that this familiar environment appears to have for facilitating social interactions. Studies of tabletop collaboration involving traditional media (e.g., paper and pens) show collaborators often partition the tabletop workspace into various areas (e.g., personal and group). Just as partitioning of our physical spaces helps to maintain social order, such territorial behaviour on a tabletop workspace appears to be an important mechanism for organizing collaborative activities. This research further investigates tabletop territoriality, through new observational studies, as well as development of territory-based interaction techniques for tabletop collaboration. Initial results from these observational studies are presented, along with a proposed test-bed environment for exploring territory-based interaction techniques.
Performance Analysis of a District Heating System

Lowering the exergy content of heat required for heating purposes decreases the primary energy consumption. District heating systems are often an important link between facilities that generate heat with low exergy content and consumers. Exergetic efficiency of heat distribution is an important performance criterion in heat supply to consumers. It can serve as a criterion for optimization, towards a more sustainable distribution-network design and operation. This paper presents a methodology for an exergy-based distribution-network analysis in a district heating system. Criteria for performance evaluations are defined. They can be used to evaluate heat supply to different points in the network, or individual system components. A case study is performed on an existing district heating system. Energetic and exergetic efficiencies of supply lines are analyzed. Exergy destructions and exergy losses are studied. Large differences in efficiency of heat supply to different points in the network are discovered. Over-dimensioned parameters of the distribution network are investigated.
Comprehensive Analysis of Delay in Transcriptional Regulation Using Expression Profiles

Regulation of gene expression is mainly conducted by transcription factors (TFs) binding to upstream regions of their target genes (Targets). Many algorithms have been developed to extract such regulatory relationships between TFs and Targets from time series expression profiles. Here we focus our attention on the time delay of TF expression and its Targets expression, which may not be uniform because of the fluctuation of regulatory interactions. We analyzed time series expression profiles in yeast cell cycles and observed such regulatory delays within known pairs of TFs and Targets, providing the evidence that the distribution of such delays is not uniform.
Weighing nanoparticles in solution at the attogram scale

Significance Naturally occurring and engineered nanoparticles (e.g., exosomes, viruses, protein aggregates, and self-assembled nanostructures) have size- and concentration-dependent functionality, yet existing characterization methods in solution are limited for diameters below ∼50 nm. In this study, we developed a nanomechanical resonator that can directly measure the mass of individual nanoparticles down to 10 nm with single-attogram (10−18 g) precision, enabling access to previously difficult-to-characterize natural and synthetic nanoparticles. Physical characterization of nanoparticles is required for a wide range of applications. Nanomechanical resonators can quantify the mass of individual particles with detection limits down to a single atom in vacuum. However, applications are limited because performance is severely degraded in solution. Suspended micro- and nanochannel resonators have opened up the possibility of achieving vacuum-level precision for samples in the aqueous environment and a noise equivalent mass resolution of 27 attograms in 1-kHz bandwidth was previously achieved by Lee et al. [(2010) Nano Lett 10(7):2537–2542]. Here, we report on a series of advancements that have improved the resolution by more than 30-fold, to 0.85 attograms in the same bandwidth, approaching the thermomechanical noise limit and enabling precise quantification of particles down to 10 nm with a throughput of more than 18,000 particles per hour. We demonstrate the potential of this capability by comparing the mass distributions of exosomes produced by different cell types and by characterizing the yield of self-assembled DNA nanoparticle structures.
Women and Sport: Interdisciplinary Perspectives

This provocative text--the product of more than 10 years of instruction and research--is the most comprehensive study to date on the past, present, and future of women and sport. An ideal textbook for upper division undergraduate and graduate students as well as a timely reference for scholars and researchers, "Women and Sport: Interdisciplinary Perspectives" sets the record straight about the women's sport experience. More than 20 expert contributors examine, analyze, and synthesize the issues surrounding women and sport from historical, biomedical, psychological, and sociological perspectives. Part I discusses the historical and cultural foundations of women's sport from ancient times to the modern era, as seen through the eyes of the participants and general public. Part II examines biomedical considerations, touching on such topics as body composition, cardiovascular fitness, gender differences in muscular strength, exercise-induced amenorrhea, and osteoporosis. Part III analyzes the psychosocial dimensions of women's sport, including sociocultural, political, and economic factors that have led to changes for women in sport and reviews the oppression historically experienced by women and men in sport. Although the book is designed primarily as a text for upper division undergraduate and graduate courses in women's sport studies, the comprehensive nature of "Women and Sport: Interdisciplinary Perspectives" makes it equally appropriate for sport sociology, sport history, general women's studies, and gender-oriented psychology, sociology, and anthropology classes. In addition, female sport participants who want to know more about how their own sporting heritage has been influenced by social, psychological, and biomedical factors will find the book valuable.
Preprocessed Consortium for Neuropsychiatric Phenomics dataset

Here we present preprocessed MRI data of 265 participants from the Consortium for Neuropsychiatric Phenomics (CNP) dataset. The preprocessed dataset includes minimally preprocessed data in the native, MNI and surface spaces accompanied with potential confound regressors, tissue probability masks, brain masks and transformations. In addition the preprocessed dataset includes unthresholded group level and single subject statistical maps from all tasks included in the original dataset. We hope that availability of this dataset will greatly accelerate research.
Evaluation of a Strand Displacement Amplification Assay (BD ProbeTec-SDA) for Detection of Neisseria gonorrhoeae in Urine Specimens

ABSTRACT The performance of a strand displacement amplification assay (the BDProbeTec-SDA assay) in detecting Neisseria gonorrhoeae in urine specimens was evaluated. When performed under stringent quality control conditions, the BDProbeTec-SDA assay is a sensitive, specific, and efficient method for the screening of large numbers of noninvasively obtained specimens. Because the predictive value of an assay is a function of the prevalence of the disease, culture confirmation is needed for samples with positive results from populations in which the prevalence of a disease is low or in situations in which false-positive results may have important medical, psychosocial, or medicolegal consequences.
Quantitation, networking, and function of protein phosphorylation in plant cell

Protein phosphorylation is one of the most important post-translational modifications (PTMs) as it participates in regulating various cellular processes and biological functions. It is therefore crucial to identify phosphorylated proteins to construct a phosphor-relay network, and eventually to understand the underlying molecular regulatory mechanism in response to both internal and external stimuli. The changes in phosphorylation status at these novel phosphosites can be accurately measured using a 15N-stable isotopic labeling in Arabidopsis (SILIA) quantitative proteomic approach in a high-throughput manner. One of the unique characteristics of the SILIA quantitative phosphoproteomic approach is the preservation of native PTM status on protein during the entire peptide preparation procedure. Evolved from SILIA is another quantitative PTM proteomic approach, AQUIP (absolute quantitation of isoforms of post-translationally modified proteins), which was developed by combining the advantages of targeted proteomics with SILIA. Bioinformatics-based phosphorylation site prediction coupled with an MS-based in vitro kinase assay is an additional way to extend the capability of phosphosite identification from the total cellular protein. The combined use of SILIA and AQUIP provides a novel strategy for molecular systems biological study and for investigation of in vivo biological functions of these phosphoprotein isoforms and combinatorial codes of PTMs.
The influence of age on the time course of word preparation in multiword utterances

Sentence production requires speakers to co-ordinate the preparation of words so that they are ready for articulation when they are needed. Ageing appears to influence both the speed and likelihood of successful word retrieval. We examine how age differences in word production might influence the production of larger units of speech such as sentences. Speakers described displays containing three objects of systematically varied naming difficulty. The latency, duration, content, and fluency of speech in addition to its co-ordination with eye movements indicated that both young and older adults prepared their words immediately before uttering them. As a consequence, older adults were also significantly less fluent in their utterances than were younger adults.
The effects of trend and fluctuation of climate change on ecosystem productivity

Climate change is closely related to trends and fluctuations. Assessing the consequences of these changes to terrestrial ecosystems requires an understanding of the action mechanism of these fractions, respectively. This study examined 11 years of remotely sensed-derived net primary productivity (NPP) to identify the impacts of the trends and fluctuations of temperature change on ecosystem productivity in Hunan province, China. A climatic signal decomposition and contribution assessment model was proposed to decompose temperature change into trend and fluctuation components. The results indicated that the mean contributions of the trend component of temperature change contributed 77% of the total NPP variation from 2001 to 2011 in Hunan province, whereas the fluctuation component explained the remaining 23% of the total NPP variation. The spatial variations of NPP in Hunan province indicated that the contributions of temperature fluctuation-driven NPP variation were higher in the north than in the south, and the contributions of temperature trend-driven NPP variation exhibited opposite characteristics. These results prove that the climatic trend change brought about great impacts on ecosystem productivity, and that climatic fluctuations can also alter the ecosystem succession process. Keyword——net primary productivity, remote sensing, signal decomposition, contribution assessment
Partial lazy forward checking

Partial forward checking (PFC) may perform more consistency checks than really needed to detect dead-ends in MAX-CSP. After analyzing PFC, we have identified four causes of redundant check computation: (a) unnecessary lookahead when detecting an empty domain, (b) not always using the better bounds for future value pruning, (c) computing in advance inconsistency counts, and (d) lookahead is performed on the whole set of future variables. We present the partial lazy forward checking (PLFC) algorithm, which follows a lazy approach delaying as much as possible inconsistency count computation, keeping updated the contribution of future variables to the lower bound. This algorithm avoids the causes of redundant checks identified for PFC. It can be easily combined with DACs, producing the PLFC-DAC algorithm. Empirical results on random problems show that PLFC-DAC outperforms previous algorithms in both consistency checks and CPU time.
Initial Public Debt Issues and Accompanying Corporate Behavior

We examine a company’s decision to issue public debt for the first time by analyzing its behavior around the time of obtaining its first debt rating. Contrary to our expectations, we find that firms are more likely to pay dividends in the years prior to the initial rating rather than at or after the announcement date, and that the amount of dividend payments actually appears to decline (rather than increase). We posit that this may be attributable to the fact that firms initiate and/or increase dividend payments in anticipation of accessing the public debt markets for the first time. This behavior leads us to consider other actions that firms might undertake in preparation for this event. We go on to find that firms’ stock prices fall in the period following their initial debt rating. Further, there is strong evidence that earnings drop afterwards. We argue that these observations are consistent with the fact that firms “time” their decision to access public debt markets to follow periods of strong share price and earnings performance. This leads us to consider the possibility that companies may actively “manage” their earnings to make them appear as attractive as possible in the pre-rating period, and we find evidence to support this assertion. JEL Classification Codes: G35, G32
Improved Holistic Analysis for Fork–Join Distributed Real-Time Tasks Supported by the FTT-SE Protocol

Modern distributed real-time embedded applications have high processing requirements associated with strict deadlines. For some applications, such constraints cannot be fulfilled by existing single-core embedded platforms. A solution is to parallelize the execution of the applications, by allowing networked nodes to distribute their workload to remote nodes with spare capacity. In that context, this paper presents a holistic timing analysis for fixed-priority fork-join parallel/distributed tasks. Furthermore, we extend the holistic approach to consider the interaction between parallel threads and messages interchanged through a flexible time triggered switched Ethernet network, and we show how the pessimism on the worst case response time computation of such tasks can be reduced by considering the pipeline effect that occurs in such distributed systems. To evaluate the performance and correctness of the holistic model, this paper includes a numerical evaluation based on a real automotive application. The obtained results show that the proposed method is effective in distributing the load by different nodes, allowing a significant reduction of the worst case response time of the tasks. Moreover, the paper also reports an implementation of the model on a Linux library, called parallel/distributed real-time, as well as the corresponding results obtained on a real testbed. The obtained results are in accordance with the predictions of the holistic timing analysis.
China's Energy Strategy

success of the price reform. The planned prices could continuously be adjusted to a level close to the market equilibrium prices. This made the liberalization of all prices less risky. A brief summary of the findings is presented in the concluding chapter. First, the heavy industry-oriented development strategy is said to have been the main cause of the slow economic growth in pre-reform China. Second, under economic reform, China’s comparative advantages were better exploited and hence rapid growth became possible. Finally, the go-bust cycles during the reform period were mainly due to the institutional reforms lagging behind microeconomic changes. Therefore, macroeconomic reform is the key to sustained growth in China. While the coverage of this book is extensive, there are several important topics which are either ignored or treated too briefly. In the first place, the township, village and private enterprises (TVPs) should have been given more attention (they are now only mentioned on pp. 179-181 and 264). as they have been an engine of China’s recent growth. In the second place, it is surprising that the book does not discuss regional development issues, as one of the main and controversial policy shifts in post-reform has been the rapid development of the coastal areas. Finally, the use of Chinese jargon makes the book difficult to read for those who do not read Chinese. These are minor quibbles, however. Overall, this is a well-documented, informative and useful reference book on the Chinese economy as well as an important addition to the growing literature on the East Asian Growth debate.
Dynamic tiling display: building an interactive display surface using multiple mobile devices

Table display surfaces, like Microsoft PixelSense, can display multimedia content to a group of users simultaneously, but it is expensive and lacks mobility. On the contrary, mobile devices are more easily available, but due to limited screen size and resolution, they are not suitable for sharing multimedia data interactively. In this paper we present a "Dynamic Tiling Display", an interactive display surface built from mobile devices. Our framework utilizes the integrated front facing camera of mobile devices to estimate the relative pose of multiple mobile screens arbitrarily placed on a table. Using this framework, users can create a large virtual display where multiple users can explore multimedia data interactively through separate windows (mobile screens). The major technical challenge is the calibration of individual displays, which is solved by visual object recognition using front facing camera inputs.