Miracle-dz/UniFAR-FTUs huggingface dataset:
HEAPO: Heap-Based Persistent Object Store

In this work, we developed a Heap-Based Persistent Object Store (HEAPO) to manage persistent objects in byte-addressable Nonvolatile RAM (NVRAM). HEAPO defines its own persistent heap layout, the persistent object format, name space organization, object sharing and protection mechanism, and undo-only log-based crash recovery, all of which are effectively tailored for NVRAM. We put our effort into developing a lightweight and flexible layer to exploit the DRAM-like access latency of NVRAM. To address this objective, we developed (i) a native management layer for NVRAM to eliminate redundancy between in-core and on-disk copies of the metadata, (ii) an expandable object format, (iii) a burst trie-based global name space with local name space caching, (iv) static address binding, and (v) minimal logging for undo-only crash recovery. We implemented HEAPO at commodity OS (Linux 2.6.32) and measured the performance. By eliminating metadata redundancy, HEAPO improved the speed of creating, attaching, and expanding an object by 1.3×, 4.5×, and 3.8×, respectively, compared to memory-mapped file-based persistent object store. Burst trie-based name space organization of HEAPO yielded 7.6× better lookup performance compared to hashed B-tree-based name space of EXT4. We modified memcachedb to use HEAPO in maintaining its search structure. For hash table update, HEAPO-based memcachedb yielded 3.4× performance improvement against original memcachedb implementation which uses mmap() over ramdisk approach to maintain the key-value store in memory.
Service-Oriented-Architecture based framework for multi-user virtual environments

Service-oriented architecture (SOA) is an application framework used for creating complex enterprise systems by integrating distributed services. The SOA standards are primarily focused on the service composability and data interoperability. Because of the featured capabilities of SOA, it is also used in distributed simulations. However, SOA has its limitations in terms of the performance of real-time message exchanging. In order to address the disadvantages and improve the application performance, we propose a framework that combines the streaming technology and SOA. The proposed framework is used for constructing multi-user virtual environment (VE) applications by integrating the application content from distributed services. The additional streaming channels applied to SOA enable the services to actively propagate the real-time messages. The VE applications constructed using the framework have better performance. However, due to the distributed architecture of SOA and the heavy payload of message exchange in the framework, the application performance needs to be evaluated. We describe the metrics used to evaluate the performance and present the evaluation results. Based on the interaction latency we collected from the experiments, we discuss the categories of applications that can fit well in our framework.
Impact of Seasonal and Pandemic Influenza on Emergency Department Visits, 2003–2010, Ontario, Canada

Objectives Weekly influenza-like illness (ILI) consultation rates are an integral part of influenza surveillance. However, in most health care settings, only a small proportion of true influenza cases are clinically diagnosed as influenza or ILI. The primary objective of this study was to estimate the number and rate of visits to the emergency department (ED) that are attributable to seasonal and pandemic influenza and to describe the effect of influenza on the ED by age, diagnostic categories, and visit disposition. A secondary objective was to assess the weekly “real-time” time series of ILI ED visits as an indicator of the full burden due to influenza. Methods The authors performed an ecologic analysis of ED records extracted from the National Ambulatory Care Reporting System (NARCS) database for the province of Ontario, Canada, from September 2003 to March 2010 and stratified by diagnostic characteristics (International Classification of Diseases, 10th Revision [ICD-10]), age, and visit disposition. A regression model was used to estimate the seasonal baseline. The weekly number of influenza-attributable ED visits was calculated as the difference between the weekly number of visits predicted by the statistical model and the estimated baseline. Results The estimated rate of ED visits attributable to influenza was elevated during the H1N1/2009 pandemic period at 1,000 per 100,000 (95% confidence interval [CI] = 920 to 1,100) population compared to an average annual rate of 500 per 100,000 (95% CI = 450 to 550) for seasonal influenza. ILI or influenza was clinically diagnosed in one of 2.6 (38%) and one of 14 (7%) of these visits, respectively. While the ILI or clinical influenza diagnosis was the diagnosis most specific to influenza, only 87% and 58% of the clinically diagnosed ILI or influenza visits for pandemic and seasonal influenza, respectively, were likely directly due to an influenza infection. Rates for ILI ED visits were highest for younger age groups, while the likelihood of admission to hospital was highest in older persons. During periods of seasonal influenza activity, there was a significant increase in the number of persons who registered with nonrespiratory complaints, but left without being seen. This effect was more pronounced during the 2009 pandemic. The ratio of influenza-attributed respiratory visits to influenza-attributed ILI visits varied from 2.4:1 for the fall H1N1/2009 wave to 9:1 for the 2003/04 influenza A(H3N2) season and 28:1 for the 2007/08 H1N1 season. Conclusions Influenza appears to have had a much larger effect on ED visits than was captured by clinical diagnoses of influenza or ILI. Throughout the study period, ILI ED visits were strongly associated with excess respiratory complaints. However, the relationship between ILI ED visits and the estimated effect of influenza on ED visits was not consistent enough from year to year to predict the effect of influenza on the ED or downstream in-hospital resource requirements.
The future of multiprocessor systems-on-chips

This paper surveys the state-of-the-art and pending challenges in MPSoC design. Standards in communications, multimedia, networking, and other areas encourage the development of high-performance platforms that can support a range of implementations of the standard. A multiprocessor system-onchip includes embedded processors, digital logic, and mixedsignal circuits combined into a heterogeneous multiprocessor. This mix of technologies creates a major challenge for MPSoC design teams. We will look at some existing MPSoC designs and then describe some hardware and software challenges for MPSoC designers.
Multiple Resonances in Fluid-Loaded Vibrating Structures

This study deals with vibroacoustics under heavy fluid loading conditions. Considerable attention has been and remains focused on this subject not only because industry is very concerned but also because of mathematical difficulties that make the numerical resolution of the problem very difficult. It was recently observed in a numerical study on a high order perturbation method under heavy fluid loading that a loaded vibrating plate results in a frequency shift of the in vacuo single resonance (in both the real part because of the fluid added mass and the imaginary part because of energy lost by radiation into the fluid) as well as increase in the number of the resonance frequencies : as a result of the loading, each single in vacuo resonance frequency of the structure is transformed into a multiple resonance frequency. Here we show that this phenomenon is said to be an extension to the heavy loading condition of the Sanchez's classical result that have established that in the case of a light loading conditions ``the scattering frequencies of a fluid loaded elastic structure (ie the resonance frequencies) are nearly the real eigenfrequencies of the elastic body alone and the complex scattering frequencies of the fluid with a rigid solid''. Using classical results in the framework of the theory of entire functions, it is established that a single resonance of a simply supported fluid loaded rectangular plate is transformed into an infinite number of resonances.
Complement-Induced Cell Death by Rituximab Depends on CD20 Expression Level and Acts Complementary to Antibody-Dependent Cellular Cytotoxicity

Purpose: The use of the CD20-specific antibody rituximab has greatly improved the response to treatment of CD20+ follicular lymphoma. Despite the success of rituximab, resistance has been reported and prognostic markers to predict individual response are lacking. The level of CD20 expression on tumors has been related to response, but results of several studies are contradictory and no clear relationship could be established. Complement-dependent cytotoxicity (CDC) and antibody-dependent cellular cytotoxicity (ADCC) are thought to be important effector mechanisms, but the exact mechanism of rituximab-mediated cell kill is still unknown. Importantly, no data have been reported on the combined contribution of CDC and ADCC. Experimental Design: We have developed a system of clonally related CEM-CD20 cells by retroviral transfer of the human CD20 cDNA (n = 90). This set of cells, with the CD20 molecule as the only variable, was used to study the importance of CD20 expression level on rituximab-mediated CDC, ADCC, and the combination. Results: We show a sigmoidal correlation of CD20 expression level and rituximab-mediated killing via CDC but not ADCC. On both high and low CD20-expressing cells, all CD20 molecules were translocated into lipid rafts after rituximab binding. Furthermore, CDC and ADCC act simultaneously and CDC-resistant cells are sensitive to ADCC and vice versa. Conclusions: These findings suggest that CDC depends on CD20 expression level and that both CDC and ADCC act complementary. These data give new insights into novel strategies to improve the efficacy of CD20-specific antibodies for the treatment of CD20+ tumors.
Bank Overleverage and Macroeconomic Fragility Bank Overleverage and Macroeconomic Fragility

We incorporate the banks, de…ned as maturity-mismatching …nancial intermediaries by Diamond and Rajan (2001a, 2012), into an overlapping-generations model where capital good is reproducible. We show that, in our model, the laissez-faire banks take on undue risks, compared to the social optimum, owing to the pecuniary externalities. Further, the model replicates " rare but severe crises " without assuming any large ex-ogenous shocks because systemic bank runs take place endogenously followed by sharp contractions in output. We also make policy assessments based on the model. The assessment favors some macro-prudential measures over pre-committed bank bailouts. Tsyvinski for comments and discussions. In addition, we received helpful comments from participants at numerous conferences and seminars. We are also indebted to Daisuke Oyama and other members of the Banking Theory Study Group for helpful discussion. Takayuki Tsuruga gratefully acknowledges the …nancial support of the Grant-in-aid for Scienti…c Research and the Japan Securities Scholarship Foundation. Views expressed in this paper are those of the authors and do not necessarily re ‡ect the o¢ cial views of the Bank of Japan.
The time course of within and between-language interference in bilinguals

Purpose: Recent research has provided support for linguistic coactivation, the view that the two languages of a bilingual are simultaneously active. Importantly, even if the system is fundamentally nonselective, the two languages of a bilingual can be activated to different degrees. The main contribution of the present paper is to empirically test what “different degrees of activation” really means. Differences could emerge in the timing or the magnitude of language activation. Methodology: Most of the research to date has been based on experiments using reaction times. In the present experiment participants responded to a bilingual Stroop task using a computer mouse. We argue that mouse tracking can provide new insights into the temporal dynamics of cognitive processes. Data and analysis: We used a series of t-tests to analyze participants’ mouse trajectories (n = 20). We compared the x-coordinates over time for each of the four experimental conditions (Congruent-Within, Congruent-Between, Incongruent-Within, Incongruent-Between) with the x-coordinates over time for the control trajectory. Findings: Differences in the timing, but not the magnitude, of interference are at the root of the differential effects within and between languages. Within-language interference emerged 80 ms earlier than between-language interference. Originality: To our knowledge, the current experiment is the first to use the dynamic mouse-tracking paradigm to compare the time course of the two languages of a bilingual participant. Implications: The mouse-tracking paradigm can help to distinguish between the timing and the magnitude of interference, informing current theories of the bilingual mind.
Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification

The structure classification of proteins plays a very important role in bioinformatics, since the relationships and characteristics among those known proteins can be exploited to predict the structure of new proteins. The success of a classification system depends heavily on two things: the tools being used and the features considered. For the bioinformatics applications, the role of appropriate features has not been paid adequate importance. In this investigation we use three novel ideas for multiclass protein fold classification. First, we use the gating neural network, where each input node is associated with a gate. This network can select important features in an online manner when the learning goes on. At the beginning of the training, all gates are almost closed, i.e., no feature is allowed to enter the network. Through the training, gates corresponding to good features are completely opened while gates corresponding to bad features are closed more tightly, and some gates may be partially open. The second novel idea is to use a hierarchical learning architecture (HLA). The classifier in the first level of HLA classifies the protein features into four major classes: all alpha, all beta, alpha + beta, and alpha/beta. And in the next level we have another set of classifiers, which further classifies the protein features into 27 folds. The third novel idea is to induce the indirect coding features from the amino-acid composition sequence of proteins based on the N-gram concept. This provides us with more representative and discriminative new local features of protein sequences for multiclass protein fold classification. The proposed HLA with new indirect coding features increases the protein fold classification accuracy by about 12%. Moreover, the gating neural network is found to reduce the number of features drastically. Using only half of the original features selected by the gating neural network can reach comparable test accuracy as that using all the original features. The gating mechanism also helps us to get a better insight into the folding process of proteins. For example, tracking the evolution of different gates we can find which characteristics (features) of the data are more important for the folding process. And, of course, it also reduces the computation time.
Multi-resolution Dynamic Mode Decomposition for Foreground/Background Separation and Object Tracking

We demonstrate that the integration of the recently developed dynamic mode decomposition with a multi-resolution analysis allows for a decomposition of video streams into multi-time scale features and objects. A one-level separation allows for background (low-rank) and foreground (sparse) separation of the video, or robust principal component analysis. Further iteration of the method allows a video data set to be separated into objects moving at different rates against the slowly varying background, thus allowing for multiple-target tracking and detection. The algorithm is computationally efficient and can be integrated with many further innovations including compressive sensing architectures and GPU algorithms.
Languages Of The Brain Experimental Paradoxes And Principles In Neuropsychology

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Isolation and Characterization of Salt-sensitive Mutants of the Moderately Halophilic Bacterium, Salinivibrio sp. DL6

Salinivibrio sp. DL6 is a moderately halophilic bacterium that can grow over a wide range of salinity, 0.5-20% Nad. In response to the external osmotic stress (1-3 M NaCl), strain DI6 can accumulate ectoine, glycine betaine and glutamate as compatible solutes. Transposon mutagenesis appears to be a potentially useful tool in the research on the synthesis of compatible solutes in response to the high osmotic stress. We used suicide plasmids pSUPl 01 to introduce the transposon Tnl732 into Salinivibrio sp. DI6 via Escherichia coli SM10 mediated conjugation. One Tnl732-induced mutant, MU1, which was severely affected in salt tolerance, was isolated. Mutant MU1 could not grow above 1.5 M NaCl and did not synthesize ectoine but accumulated ectoine precursor, N-gamma-acetyl-diaminobutyrate, which was shown by 1H-NMR analysis. From these data, we concluded that in the strain Salinivibrio sp. DI6 ectoine performs a key role for the adaptation high salinity environments, since glycine betaine and glutamate were accumulated regardless of the salinity.
A language modeling approach to information retrieval

Models of document indexing and document retrieval have been extensively studied. The integration of these two classes of models has been the goal of several researchers but it is a very difficult problem. We argue that much of the reason for this is the lack of an adequate indexing model. This suggests that perhaps a better indexing model would help solve the problem. However, we feel that making unwarranted parametric assumptions will not lead to better retrieval performance. Furthermore, making prior assumptions about the similarity of documents is not warranted either. Instead, we propose an approach to retrieval based on probabilistic language modeling. We estimate models for each document individually. Our approach to modeling is non-parametric and integrates document indexing and document retrieval into a single model. One advantage of our approach is that collection statistics which are used heuristically in many other retrieval models are an integral part of our model. We have implemented our model and tested it empirically. Our approach significantly outperforms standard tf.idf weighting on two different collections and query sets.
The next frontier: Fostering innovation by improving health data access and utilization

Beneath most lively policy debates sit dry-as-dust theoretical and methodological discussions. Current disputes over the EU Adaptive Pathways initiative 1,2 and the proposed US 21st Century Cures Act 3 may ultimately rest on addressing arcane issues of data curation, standardization, and utilization. Improved extraction of information on the safety and effectiveness of drugs-in-use must parallel adjustments in evidence requirements at the time of licensing. To do otherwise may compromise safety and efﬁcacy in the name of fostering innovation . To take stock of the current state of the art, this essay identiﬁes sources of demand for better utilization of real-world medical data, highlights the need for improved data quality, data access, and analytic methods, and evaluates the US Sentinel Initiative and Optum Labs as examples of distributed and centralized data initiatives. To engage with emerging needs, this essay offers an integrated research and policy agenda. Academic research topics focus on improving data quality and access and on developing hybrid observational and interventionist methods to enhance causal inference under less-than-ideal conditions. Policy agendas focus on the need for international coordination on data access, data standards, and evidentiary thresholds.
Are Performance Limitations in Visual Short-Term Memory Tasks Due to Capacity Limitations or Model Mismatch?

Performance limitations in visual short-term memory (VSTM) tasks have traditionally been explained in terms of resource or capacity limitations. It has been claimed, for example, that VSTM possesses a limited amount of cognitive or neural "resources" that can be used to remember a visual display. In this paper, we highlight the potential importance of a previously neglected factor that might contribute significantly to performance limitations in VSTM tasks: namely, a mismatch between the prior expectations and/or the internal noise properties of the visual system based primarily on its adaptation to the statistics of the natural environment and the statistics of the visual stimuli used in most VSTM experiments. We call this 'model mismatch'. Surprisingly, we show that model mismatch alone, without assuming a general resource or capacity limitation, can, in principle, account for some of the main qualitative characteristics of performance limitations observed in VSTM tasks, including: (i) monotonic decline in memory precision with increasing set size; (ii) variability in memory precision across items and trials; and (iii) different set-size dependencies for initial encoding rate and asymptotic precision when the duration of image presentation is varied. We also investigate the consequences of using experimental stimuli that more closely match the prior expectations and/or internal noise properties of the visual system. The results reveal qualitatively very different patterns of behavior for such stimuli, suggesting that researchers should be cautious about generalizing the results of experiments using ecologically unrealistic stimulus statistics to ecologically more realistic stimuli.
Learning by Matching

We study how a continuum of agents learn about disseminated information in a dynamic beauty contest model when they do not observe aggregate variables, such as prices or quantities, but randomly observe each other's actions. We solve for the market equilibrium and find that the average learning curve is S-shaped: learning is slow initially, intensifies rapidly and finally converges slowly to the truth. We show that increasing public information always slows down learning in the long run. Under some conditions, even if agents have no coordination motive, it also reduces welfare. Lastly, optimal diffusion of information requires that agents ``strive to be different'': agents need to be rewarded for choosing actions away from the population average