Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation and evaluation of the Complex Streamed Instruction set

An architectural paradigm designed to accelerate streaming operations on mixed-width data is presented and evaluated. The described Complex Streamed Instruction (CSI) set contains instructions that process data streams of arbitrary length. The number of bits or elements that will be processed in parallel is therefore not visible to the programmer, so no recompilation is needed in order to benefit from a wider datapath. CSI also eliminates many overhead instructions (such as instructions needed for data alignment and reorganization) often needed in applications utilizing media ISA extensions such as MMX and VIS by replacing them with a hardware mechanism. Simulation results using several multimedia kernels demonstrate that CSI provides a factor of up to 9.9 (4.0 on average) performance improvement when compared to Sun's VIS extension. For complete applications, the performance gain is 9% to 36% with an average of 20%.
Chinese College Student Internet Use and Its Impact on Their Health and Life

In this paper, a study about the detailed online activities of Chinese college students is presented to assess students’ internet use behaviors and to determine the extent that Chinese college students’ internet use impact on their health and study. In present paper, a survey of college students that examines the nature of their internet use is conducted. A statistic analysis about Chinese college students’ internet use behavior is presented. The statistic results indicate that f that many college students in China used the Internet frequently and spent long hours online. The college students using internet for entertainment has a large proportion in their internet activities. College students use sex or violence Web-sites maybe have a significant impact on their health and study. A significant fact is that some students use internet all-night, they are infatuatedly online so that forget to eat and sleep. Some students are accustomed to using internet by skip classes. These internet use behavior will seriously influence their study in campus. Therefore, to utilize online resources more sufficiently, college students should have appropriate guidance. Keywordsinternet use; college students; study; online; online information
Combining color-based invariant gradient detector with HoG descriptors for robust image detection in scenes under cast shadows

In this work we present a robust detection method in outdoor scenes under cast shadows using color based invariant gradients in combination with HoG local features. The method achieves good detection rates in urban scene classification and person detection outperforming traditional methods based on intensity gradient detectors which are sensible to illumination variations but not to cast shadows. The method uses color based invariant gradients that emphasize material changes and extract relevant and invariant features for detection while neglecting shadow contours. This method allows to train and detect objects and scenes independently of scene illumination, cast and self shadows. Moreover, it allows to do training in one shot, that is, when the robot visits the scene for the first time.
Stability and Biological Responses of Zinc Oxide Metalworking Nanofluids (ZnO MWnF™) using Dynamic Light Scattering and Zebrafish Assays

Zinc oxide nanoparticles (ZnO NPs) have demonstrated the ability to improve lubrication and thermal conductivity and are promising metalworking lubricant and coolant additives due to their low cost compared to other NPs. Though nanomaterials are a focus of research due to their potential to enable advanced technologies, little is known about their effects on the environment and human health. This research investigates two main characteristics of ZnO metalworking nanofluids (MWnF). First, the stability of ZnO NPs (20 nm) is investigated using dynamic light scattering (DLS) for mixtures of a microemulsion (TRIM MicroSol 585XT) and several dispersants, all of which are commercially available. Second, toxicological assessments using a zebrafish assay method are conducted to survey the effect of ZnO NPs on MWnF safety. The research revealed that none of the dispersants enhanced the stability of ZnO NPs more than the prepared microemulsion alone. The work also revealed that ZnO MWnF had a significantly higher toxicity than the prepared microemulsion. This demonstrates the need for precautionary development of metalworking nanofluids.
A novel rod-like MnO2@Fe loading on graphene giving excellent electromagnetic absorption properties

Impedance matching and the attenuation constant, α, are two key parameters in determining electromagnetic absorption properties. Although materials with single magnetic or dielectric loss properties have a high α value, they nonetheless suffer from poor impedance matching. The design of magnetic and dielectric composites might possibly be an effective method of solving this problem, but unfortunately the introduction of magnetic material may give a poor value of α. In order to obtain absorptive materials with high impedance matching and a high value of α, we have designed a novel ternary composite of MnO2@Fe–graphene. A 30 nm wide rod-like strip of MnO2 was first obtained by a simple liquid process. Liquid decomposition of Fe(CO)5 was then carried out to deposit iron on the surface of the rod-like structure, and the MnO2@Fe was finally loaded on graphene by a liquid deposition technique. The resulting ternary composite exhibited attractive electromagnetic absorption properties, in which the optimal reflection loss of up to −17.5 dB obtained with a thin coating thickness of 1.5 mm was able to satisfy the requirements of lightness of weight and a high degree of absorption. The effective bandwidth frequency of MnO2@Fe–GNS is broader than that of pure MnO2 or MnO2@Fe, possibly due to its moderate impedance matching and attenuation ability. The possible attenuation mechanism will also be discussed.
RUNX1 repression‐independent mechanisms of leukemogenesis by fusion genes CBFB–MYH11 and AML1–ETO (RUNX1–RUNX1T1)

The core binding factor (CBF) acute myeloid leukemias (AMLs) are a prognostically distinct subgroup that includes patients with the inv(16) and t(8:21) chromosomal rearrangements. Both of these rearrangements result in the formation of fusion proteins, CBFB–MYH11 and AML1–ETO, respectively, that involve members of the CBF family of transcription factors. It has been proposed that both of these fusion proteins function primarily by dominantly repressing normal CBF transcription. However, recent reports have indicted that additional, CBF‐repression independent activities may be equally important during leukemogenesis. This article will focus on these recent advances. J. Cell. Biochem. 110: 1039–1045, 2010. Published 2010 Wiley‐Liss, Inc.
Delay-Aware Optimization of Physical Layer Security in Multi-Hop Wireless Body Area Networks

Joint optimization of the physical layer security with end-to-end delay management is studied in the uniquely constrained context of wireless body area networks (WBANs). A game-theoretic framework is proposed wherein body-worn sensor devices interact in the presence of wiretappers and under fading channel conditions to find the most secure multi-hop path to the hub, while adhering to the end-to-end delay requirements imposed by the application. We model the problem as the search for a Nash network topology where no unilateral deviation in strategy by any single sensor node improves the secrecy of its transmissions, and provide a distributed algorithm guaranteed to converge to a Pareto-dominant Nash solution. The framework is evaluated through numerical simulations in conditions approximating actual deployment of WBANs for moving and stationary scenarios. Results validate the merits of the proposed framework to improve the security of transmissions compared with the star topology and IEEE 802.15. 6 two-hop topology extension with a best-channel algorithm, at the expense of an admissible increase in the end-to-end delay.
Long Read Alignment with Parallel MapReduce Cloud Platform

Genomic sequence alignment is an important technique to decode genome sequences in bioinformatics. Next-Generation Sequencing technologies produce genomic data of longer reads. Cloud platforms are adopted to address the problems arising from storage and analysis of large genomic data. Existing genes sequencing tools for cloud platforms predominantly consider short read gene sequences and adopt the Hadoop MapReduce framework for computation. However, serial execution of map and reduce phases is a problem in such systems. Therefore, in this paper, we introduce Burrows-Wheeler Aligner's Smith-Waterman Alignment on Parallel MapReduce (BWASW-PMR) cloud platform for long sequence alignment. The proposed cloud platform adopts a widely accepted and accurate BWA-SW algorithm for long sequence alignment. A custom MapReduce platform is developed to overcome the drawbacks of the Hadoop framework. A parallel execution strategy of the MapReduce phases and optimization of Smith-Waterman algorithm are considered. Performance evaluation results exhibit an average speed-up of 6.7 considering BWASW-PMR compared with the state-of-the-art Bwasw-Cloud. An average reduction of 30% in the map phase makespan is reported across all experiments comparing BWASW-PMR with Bwasw-Cloud. Optimization of Smith-Waterman results in reducing the execution time by 91.8%. The experimental study proves the efficiency of BWASW-PMR for aligning long genomic sequences on cloud platforms.
Tools to support exploratory programming with data

A diverse range of people, from students to engineers to designers, are interested in using programming to analyze, visualize, and build new intelligent systems from data. However, when working with data, a programmer must typically experiment heavily: writing out and running many different approaches in code to reach a desired result [1][2]. This form of exploratory programming presents extra challenges and pitfalls for programmers. For example, as a person iterates on a problem over a long period of time, it can become difficult to answer questions like: “Through what steps did I achieve this result? ” [3] or “What different analyses have I tried or not tried so far? ”. Currently there is a sparsity of tools for programmers to keep track of all their code experimentation, and intermediary data analysis steps are easily lost. Programmers also struggle with making many small highly exploratory code changes, such as trying 10 different values of a parameter [2]. Current code version tools are not designed for rapid iteration on small sections of code, thus these programmers often resort to informal ad-hoc methods of versioning such as leaving 10 different values of a parameter in comments in their code, or copying the 10 different values to a separate text file. As programmers work to make sense of challenging data questions, managing experiments in code adds an extra degree of overhead and confusion that can make this work all the more difficult.
Crowdsourced data analytics: A case study of a predictive modeling competition

Predictive modeling competitions provide a new data mining approach that leverages crowds of data scientists to examine a wide variety of predictive models and build the best performance model. Competition hosts, who provide their own dataset and specify the problem to be solved, are not only able to obtain the best model from among those submitted but also to aggregate the submitted models to obtain one that outperforms the rest. In this paper, we report the results of a study conducted on CrowdSolving, a platform for predictive modeling competitions in Japan. We hosted a competition on a link prediction task and observed that (i) the prediction performance of the winner significantly outperformed that of a state-of-the-art method, (ii) the aggregated model constructed from all submitted models further improved the final performance, and (iii) the performance of the aggregated model built only from early submissions nevertheless overtook the final performance of the winner. Our results show the power of crowds for predictive modeling, not only in the quality of the obtained model, but also in its speed to achieve it. Furthermore, they demonstrate the possibilities of combining human insights and machine learning in data analytics.
Differencing and Merging of Software Diagrams - State of the Art and Challenges

For long, fine-grained version control for software documents has been neglected severely. Typically, software configuration management systems support the management of text or binary files. Unfortunately, text-based tools for fine-grained version control are not adequate for software documents produced in earlier phases in the software life cycle. Frequently, these documents have a graphical syntax; therefore we will call them software diagrams. This paper discusses the current state of the art in fine-grained version control (differencing and merging) for software diagrams with an emphasis on UML diagrams.
Matching Raw GPS Measurements on a Navigable Map Without Computing a Global Position

Map matching means determining the location of a mobile with respect to a road network description stored in a digital map. This problem is usually addressed using Global Positioning System (GPS)-like fixes. Unfortunately, there are many situations in urban areas where few satellites are visible because of outages due to tall buildings. In this paper, map matching is solved using raw GPS measurements (pseudoranges and Doppler measurements), avoiding the necessity to compute a global position. The problem is formalized in a general Bayesian framework to handle noise, which can perform multihypothesis map matching when there is not enough information to make unambiguous decisions. This tightly coupled GPS-map fusion has to simultaneously cope with identifying the road and estimating the mobile's position on that road. A marginalized particle filter is proposed to efficiently solve this hybrid estimation problem. Real experimental results are reported to show that this approach can be initialized with fewer than four satellites. It can also track the location with only two satellites once the road selection has been solved.
Is a Picture worth a Thousand Words?: A Comparative Analysis of Using Textual and Graphical Approaches to Specify Use Cases

Use cases specifications are artifacts employed in all stages of software development, from the requirements elicitation to implementation. During this process, issues related to ambiguity, redundancy, inconsistency, and incompleteness can affect these specifications. These issues can harm software engineers' understanding and, consequently, affect the software quality. Given this context, this paper describes an empirical study to evaluate two different use cases specifications approaches (textual and graphical-based forms). We compared the approaches by assessing the degree of correctness and the time spent to generate the specifications. In addition, we performed an analysis focusing on evaluating the ease of use and usefulness of each approach. The quantitative results showed that textual form and graphical-based specifications presented similar levels of correctness and the time spent to generate them were also similar. The qualitative results indicated that the subjects had difficulties using both approaches; however, subjects stated that graphic-based specifications were easier and more useful to specify use cases.
Context Semantics, Linear Logic and Computational Complexity

We show that context semantics can be fruitfully applied to the quantitative analysis of proof normalization in linear logic. In particular, context semantics lets us define the weight of a proof-net as a measure of its inherent complexity: it is both an upper bound to normalization time (modulo a polynomial overhead, independently on the reduction strategy) and a lower bound to the number of steps to normal form (for certain reduction strategies). Weights are then exploited in proving strong soundness theorems for various subsystems of linear logic, namely elementary linear logic, soft linear logic and light linear logic
Collective Production of Public Goods in Online Travel Communities

This study examines the conditions under which the collective production of public goods would likely happen and be sustained in an online tourism community. This study develops a theoretic and empirical model to incorporate social capital and technological factors of success in order to promote the collective production of public goods. This research explored both organizational and technological aspects of two online travel communities producing freely available accommodation and travel information in a collective manner. The study finding argues that conditions that facilitate and increase the capacity of social capital in online travel communities permits better understanding of the mechanisms of creating and sustaining public goods through online travel communities. It should, thus, enable a more refined model to explain how online users are retained and actively engage in online travel communities. Collective action theory, social capital, grounded theory, exchange theory, and generalized reciprocity theory are examined in this research.
The Meta–Cognitive Model (MCM) of Attitudes: Implications for Attitude Measurement, Change, and Strength

We present a Meta–Cognitive Model (MCM) of attitudes. According to the MCM, an attitude object can be associated with both positive and negative evaluations that can be detected with modern implicit (automatic) measures of attitudes. These evaluative associations can be further associated with validity tags that are also consulted when completing deliberative attitude measures. We explain how the MCM accounts for existing findings in the attitudes literature and discuss recent studies and novel predictions derived from the MCM framework. Particular attention is devoted to factors that produce discrepancies between automatic and deliberative measures of attitudes and their consequences. Implications for attitude change, attitude strength, and the domain of prejudice are also considered.
Dynamics of hot-potato routing in IP networks

Despite the architectural separation between intradomain and interdomain routing in the Internet, intradomain protocols do influence the path-selection process in the Border Gateway Protocol (BGP). When choosing between multiple equally-good BGP routes, a router selects the one with the closest egress point, based on the intradomain path cost. Under such hot-potato routing, an intradomain event can trigger BGP routing changes. To characterize the influence of hot-potato routing, we conduct controlled experiments with a commercial router. Then, we propose a technique for associating BGP routing changes with events visible in the intradomain protocol, and apply our algorithm to AT&T's backbone network. We show that (i) hot-potato routing can be a significant source of BGP updates, (ii) BGP updates can lag 60 seconds or more behind the intradomain event, (iii) the number of BGP path changes triggered by hot-potato routing has a nearly uniform distribution across destination prefixes, and (iv) the fraction of BGP messages triggered by intradomain changes varies significantly across time and router locations. We show that hot-potato routing changes lead to longer delays in forwarding-plane convergence, shifts in the flow of traffic to neighboring domains, extra externally-visible BGP update messages, and inaccuracies in Internet performance measurements.
Determination of temperature distribution in tissue for interstitial cancer photothermal therapy

Abstract Background: Temperature increase in tumour tissue during photothermal therapy (PTT) is a significant factor in determining the outcomes of the treatment. Therefore, controlling and optimising temperature distribution in target tissue is crucial for PTT. In this study, we developed a unique ex vivo device to study the temperature distribution during PTT to be used as a guide for the desired photothermal effects for cancer treatment. Methods: Bovine liver tissue buried inside agarose gel served as a phantom tumour surrounded by normal tissue. A thermostatic incubator was used to simulate tissue environment in live animals. The temperature distributions were measured by thermocouples with needle probes at different locations inside the target tissue, during laser irradiation using an 805-nm laser. Results: The results obtained using the ex vivo device were verified by comparing the tissue temperature directly measured in animal tumours irradiated under the same conditions. With this model, the spatial distribution of temperature in target tissue can be monitored in real time. A two-dimensional temperature distribution in target tissue allows us to establish the correlations among laser parameters, temperature distribution and tumour size. In addition, the optimal temperature range for tumour destruction and immunological stimulation was determined using metastatic rat mammary tumour model. Conclusion: The device and method developed in this study can provide guidance for choosing the appropriate treatment parameters for optimal photothermal effects, particularly when combined with immunotherapy, for cancer treatment.
HEADACHE AND MULTIPLE SCLEROSIS

Migraine is a disease not seen in the general population and in particular when the migraine is comorbid with other neurological diseases. This condition ensures that patients give little importance to this disease without acknowledging that this is likely to induce alterations in the quality of life often worse in the same multiple sclerosis (MS). The relationship between migraine and MS is still unclear. It is important that the physician has to consider a number of elements which differentiate the two clinical pictures in the context of a global vision that involves primarily the clinical evaluation and medical history, and subsequently the aid of instrumental and laboratory investigations. The recent development of new treatment options for MS requires professionals to be aware of the treatments for migraine and possible side effects that could limit or contraindicate the use of specific drugs. Patients with this comorbidity are "crushed" by the weight of two chronic diseases.
Isolation and Characterization of Single Vascular Smooth Muscle Cells From Spontaneously Hypertensive Rats

To study the properties of vascular smooth muscle in hypertension without the influence of the nerves and endothelium, a procedure was developed to isolate single smooth muscle cells from tail arteries of spontaneously hypertensive rats (SHR) and Wistar-Kyoto (WKY) normotensive control rats. Perfusion of intact arteries with a solution of papain and collagenase produced dense populations of viable cells (more than 104 cells/ml) that remained relaxed in the presence of physiological levels of calcium. Contractile responses of smooth muscle cells from the SHR were significantly more sensitive to noradrenallne, potassium depolarization, and the calcium channel agonist Bay K 8644 compared with those from WKY rats. Enhanced sensitivity to calcium in the SHR was also observed on readdition of calcium to cells preincubated in noradrenaline or KC1 in a calcium-free medium. These results provide evidence for alterations in the properties of vascular smooth muscle in the SHR at the single cell level.
Beyond the BARRIERS Scale: Commonly Reported Barriers to Research Use

The evidence-based practice movement has highlighted the importance of translating research evidence into practice. However, the gap between research and practice points to the existence of significant barriers to research use. To identify the most commonly cited barriers to the use of research in practice, the findings arising from studies that used the Barriers to Research Utilization Scale are examined. Based on these findings, the authors discuss and make recommendations to assist nurse administrators in overcoming universally reported barriers to research use.