Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilistic Best-Fit Multi-dimensional Range Query in Self-Organizing Cloud

With virtual machine (VM) technology being increasingly mature, computing resources in modern Cloud systems can be partitioned in fine granularity and allocated on demand with "pay-as-you-go" model. In this work, we study the resource query and allocation problems in a Self-Organizing Cloud (SOC), where host machines are connected by a peer-to-peer (P2P) overlay network on the Internet. To run a user task in SOC, the requester needs to perform a multi-dimensional range search over the P2P network for locating host machines that satisfy its minimal demand on each type of resources. The multi-dimensional range search problem is known to be challenging as contentions along multiple dimensions could happen in the presence of the uncoordinated analogous queries. Moreover, low resource matching rate may happen while restricting query delay and network traffic. We design a novel resource discovery protocol, namely Proactive Index Diffusion CAN (PID-CAN), which can proactively diffuse resource indexes over the nodes and randomly route query messages among them. Such a protocol is especially suitable for the range query that needs to maximize its best-fit resource shares under possible competition along multiple resource dimensions. Via simulation, we show that PID-CAN could keep stable and optimized searching performance with low query delay and traffic overhead, for various test cases under different distributions of query ranges and competition degrees. It also performs satisfactorily in dynamic node-churning situation.
Isolation and Characterization of Paracoccus sp. GSM2 Capable of Degrading Textile Azo Dye Reactive Violet 5

A potential bacterial strain GSM2, capable of degrading an azo dye Reactive Violet 5 as a sole source of carbon, was isolated from textile mill effluent from Solapur, India. The 16S rDNA sequence and phenotypic characteristics indicated an isolated organism as Paracoccus sp. GSM2. This strain exhibited complete decolorization of Reactive Violet 5 (100 mg/L) within 16 h, while maximally it could decolorize 800 mg/L of dye within 38 h with 73% decolorization under static condition. For color removal, the most suitable pH and temperature were pH 6.0–9.0 and 25–40°C, respectively. The isolate was able to decolorize more than 70% of five structurally different azo dyes within 38 h. The isolate is salt tolerant as it can bring out more than 90% decolorization up to a salt concentration of 2% (w/v). UV-Visible absorption spectra before and after decolorization suggested that decolorization was due to biodegradation and was further confirmed by FT-IR spectroscopy. Overall results indicate the effectiveness of the strain GSM2 explored for the treatment of textile industry effluents containing various azo dyes. To our knowledge, this could be the first report on biodegradation of Reactive Violet 5 by Paracoccus sp. GSM2.
Data Annotation Models and Annotation Query Language

—This paper presents data annotation models at ﬁve levels of granularity (database, relation, column, tuple, and cell) of relational data to address the problem of unsuitability of most relational databases to express annotations . These models do not require any structural and schematic changes to the underlying database. These models are also ﬂexible, extensible, customizable, database-neutral, and platform-independent. This paper also presents an SQL-like query language, named Annotation Query Language (AnQL), to query annotation documents. AnQL is simple to understand and exploits the already-existent wide knowledge and skill set of SQL.
More than a Feeling: Affect as Radical Situatedness

Martin Heidegger’s perspective stands out among the many proposals for understanding affect in the phenomenological tradition. One reason for this is that Heidegger is the most thorough antiCartesian among the phenomenologists. He rigorously disbands affectivity from notions of psychological interiority, inner states, or other individualist allegiances, construing affect instead as a form of being open to the world in a radical sense. Another reason is that Heidegger places affect in the thick of everyday social and interpersonal commerce—within the warp and weft of all our days. With this orientation, he manages to combine a sense for ordinary comportment and experience—a phenomenological and cultural analysis of the everyday—with a profound sense for the ontological depths of human existence. Rarely have the mundane and the metaphysical been so thoroughly coarticulated; and yet Heidegger works from an acute sense of the massive discordance between these two distinct but interwoven layers of existence. Despite this promising outlook, there is much one should take issue with in Heidegger’s work, above all and most strikingly his dubious politics. My way of dealing with this problematic is not the usual one of trying to identify fascistic or protofascistic tendencies in Heidegger’s philosophy (I made a start at that elsewhere, see Slaby forthcoming). Rather, in the final section of this article, I will indicate how the perspective on affect and historicity developed here might help us turn Heidegger’s insights against his own putative political orientation. I will mainly focus on two aspects of Heidegger’s view, as these might help orient critical work on affect in philosophy and the humanities today.
Learning Strategies and Transfer in the Domain of Programming

We report two studies involving an intelligent tutoring system for Lisp (the Camegie Mellon University Lisp Tutor). In Experiment 1, we developed a model, based on production system theories of transfer and analogical problem solving, that accounts for effects of instructional examples, the transfer of cognitive skills across programming problems, and practice effects. In Experiment 2, we analyzed protocols collected from subjects as they processed instructional texts and examples before working with the Lisp Tutor and protocols collected after subjects solved each programming problem. The results suggest that the acquisition of cognitive skills is facilitated by high degrees of metacognition, which includes higher degrees of monitoring states of knowledge, more self-generated explanation goals and strategies, and greater attention to the instructional structure. Improvement in skill acquisition is also strongly related to the generation of explanations connecting the example material to the abstract term.
In situ structural analysis of BPDA-PPD polyimide thin film using two-dimensional grazing incidence X-ray diffraction

Structural development of BPDA-PPD polyimide thin film has been investigated by in situ grazing incidence X-ray diffraction at the BL24XU beamline of the SPring-8. Optimizing the sample shape, two-dimensional images were measured successfully without sacrificing angle resolution. It has been clearly shown that the crystallization first begins in the in-plane direction, at the curing temperature of 180 °C, in which the periodic structure of the molecular chain axis (c axis) is developed. The crystallization in the surface normal (out-of-plane) direction is observed later, at the curing temperature above 300 °C. A slight increase of the d spacing of the c axis during heating process has been observed, suggesting the stretching of the contracted molecular chain in accordance with the curing process. In the cooling process, the decrease of the d spacings for a and b axes was considerable, which indicates thermal expansion of the crystals at high temperatures. The increases in the peak intensities during the cooling process have been observed, which indicate the d spacing of each axis becomes close to the equilibrium value to produce higher periodicity.
An Event-Based Approach for Discovering Activities of Daily Living by Hidden Markov Models

Smart Home technologies may improve the comfort and the safety of frail people into their home. To achieve this goal, models of Activities of Daily Living (ADL) are often used to detect dangerous situations or behavioral changes in the habits of these persons. In this paper, an approach is proposed to build a model of ADLs, under the form of Hidden Markov Models (HMMs), from a training database of observed events emitted by binary sensors. The main advantage of our approach is that no knowledge of actions really performed during the learning period is required. Finally, we apply our approach to a real case study and we discuss the quality of the results obtained.
curlX: A middleware to enforce access control policies within a cloud environment

Today cloud security and privacy concerns pose significant challenges. One particular challenge consists in how to take into consideration the user's security policies while accessing the outsourced data. In fact, for a given application, we may have a set of rules, as high level security policy, which needs to hold prior to any query execution. Therefore, the main problem that we tackle in this ongoing project is how to enforce this high level security policy in the cloud storage layer without conflicts. To address this challenges, we propose a middleware denoted curlX which consists of two main processes: the security policy enforcement process and the verification process.
Heart Rate Turbulence modeling using Boosted Regression Trees

Heart Rate Turbulence (HRT) is a relevant cardiac risk stratification criterion. It is accepted the baroreflex hypothesis as a source of the HRT. However, several studies showed different results about the relationship between coupling interval (CI) and HRT turbulence slope (TS) parameter. Our aim was to propose a nonparametric model based on Boosted Regression Trees (BRT) of TS as a function of CI, heart rate (quantified by sinus cardiac length SCL in ms), Age and Sex. We used a set of 11 patients with normal heart undergoing electrophysiological study (EPS) and 61 holters from actue myocardial infarction (AMI) patients (Hospital Arrixaca de Murcia). The AMI set was split into: AMI low-risk, and AMI high-risk according to HRT. We propose to model TS using BRT, which is an ensemble approach to build a regression model using several trees. SCL was the explicative variable with the highest importance both in EPS and AMI low-risk. TS correlated nonlinearly with SCL, and negatively with CI both in EPS and AMI low-risk. The model was completely different for AMI-HR. R2 was higher for EPS (0.63) and AMI-LR (0.38) than for AMI-HR (0.28). The model was in agreement with the baroreflex hypothesis, and the role of age and sex agrees with previous results for EPS and AMI-LR. CI was the most important variable and positively correlated with TS in AMI-HR.
Boosting with Online Binary Learners for the Multiclass Bandit Problem

We consider the problem of online multiclass prediction in the bandit setting. Compared with the full-information setting, in which the learner can receive the true label as feedback after making each prediction, the bandit setting assumes that the learner can only know the correctness of the predicted label. Because the bandit setting is more restricted, it is difficult to design good bandit learners and currently there are not many bandit learners. In this paper, we propose an approach that systematically converts existing online binary classifiers to promising bandit learners with strong theoretical guarantee. The approach matches the idea of boosting, which has been shown to be powerful for batch learning as well as online learning. In particular, we establish the weak-learning condition on the online binary classifier, and show that the condition allows automatically constructing a bandit learner with arbitrary strength by combining several of those classifiers. Experimental results on several real-world data sets demonstrate the effectiveness of the proposed approach.
Distributional Similarity in the Varied Order of Syntactic Spaces

The single valued decomposition (SVD) has been used widely in information retrieval and other language engineering projects. Another less-widely used technique is independent component analysis (ICA), which postulates much stricter conditions than SVD and aims to represent the meaningful structure behind data. We compare distributional word similarity estimates using raw syntactic relationships frequencies extracted from a large corpus, as well as SVD-reduced and ICA-extracted attributes. The results show that ICA does not help SVD in the syntactic space
J.M.P. Kneepkens HAIT Master Thesis series nr. 09-002 THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS IN COMMUNICATION AND INFORMATION SCIENCES, MASTER TRACK HUMAN ASPECTS OF INFORMATION TECHNOLOGY,

This research presents an evaluation of a recommender system that automatically generates recommendations for articles from an online newspaper. A prototype of a recommender system was built in cooperation with a Dutch newspaper called “Trouw”. With the data retrieved from Trouw, the system was able to recommend articles for news articles that were daily published on the website of Trouw. Trouw Web editors have to judge each day, for every online article, the top 15 recommendations as correct or incorrect with an online application. During the research period, we looked at performance differences in combination with article growth, incorporating temporal information, and incorporating author and section metadata. The results show that article growth has an influence on the number of approved recommendations over time, and the MAP and P@n scores get better over time as well. Incorporating temporal information showed the best results for the MAP scores when only textual similarity was taken into account. The P@n scores had the best results when taking both textual similarity and recency in equal amounts into account. However, the differences in MAP and P@n score between these two variations were not significant. Finally, incorporating author and section metadata did not have influence on generating better recommendations. Looking at the MAP scores it even scored significantly worse than the baseline algorithm.
Handover reduction in virtualized cloud radio access networks using TWDM-PON fronthaul

To meet challenging 5G capacity requirements, operators are densifying their cellular networks by deploying additional small cells to cover hot spots, and such an increase in the number and density of cells may result in excessive numbers of handovers. In this study, we propose a handover reduction mechanism implemented in a cloud radio access network (CRAN) by exploiting the high capacity of an optical access network serving as a "fronthaul. " CRAN has been proposed as a 5G radio access network architecture, where the digital unit (DU) of a conventional base station (BS) is separated from the radio unit (RU) and moved to the "cloud" (DU-cloud) for better mobility management and cost saving. Separating RUs and DUs requires a low-latency and high-bandwidth 5G transport network to handle "fronthaul" traffic, for which optical access is an excellent choice. Here, we present a new 5G architecture, called virtualized-CRAN (V-CRAN), moving toward a cell-less 5G mobile network architecture. We leverage the concept of a "virtualized-BS" (V-BS) that can be formed by exploiting several enabling technologies such as software-defined radio and coordinated multipoint transmission/reception. A V-BS can be formed on a per-user basis by allocating virtualized resources on demand so that common signals can be jointly transmitted from multiple RUs to the user without triggering handover. We first model the handover reduction optimization problem for a scenario where future mobility information is known, and then propose a suite of algorithms for a scenario where future information is unknown. Simulation results show that V-CRAN can enhance the throughput of users at the cell-edge, as well as significantly reduce the number of handovers, handover delay, and failure rate.
Rapid Prototyping of Context-Aware Applications

Although numerous context-aware applications, those that implicitly take their context of use into account, have been developed, and advances have been made in technology to acquire contextual information, it is still difficult to develop and prototype interesting context-aware applications. This is largely due to the lack of programming support available to both programmers and end users. In this paper we focus on providing support to end users to open up the space of context-aware application design to a larger group of users. We present iCAP, the interactive Context-Aware Prototyper, a system that allows end users to visually design a wide variety of context-aware applications, including those based on if-then rules, temporal and spatial relationships and environment personalization. iCAP allows users to quickly prototype and test their applications without writing any code. We describe the system design and several applications that demonstrate iCAP’s richness and ease of use. We also describe results from a user study performed with 15 end users and 5 programmers that illustrates iCAP’s expressiveness and usability. Author
Fiscal Stimulus with Spending Reversals

Abstract The short-run effects of fiscal policy depend not only on current tax and spending choices, but also on expectations about future policy adjustment. While general equilibrium models typically restrict medium-term adjustment to taxation, we highlight the importance of government spending dynamics. First, we provide time series evidence for the United States suggesting that an exogenous increase in government spending prompts a rise in public debt, followed over time by a reduction in spending below trend. Second, we show how expected spending reversals alter the short-run impact of fiscal policy in a new Keynesian model, bringing it closer in line with the evidence.
Analysis of [Gossypium capitis-viridis × (G.hirsutum × G.australe)2] Trispecific Hybrid and Selected Characteristics

Speciation is always a contentious and challenging issue following with the presence of gene flow. In Gossypium, there are many valuable resources and wild diploid cotton especially C and B genome species possess some excellent traits which cultivated cotton always lacks. In order to explore character transferring rule from wild cotton to upland tetraploid cotton, the [G. capitis-viridis × (G. hirsutum × G. australe)2] triple hybrid was synthesized by interspecies hybridization and chromosome doubling. Morphology comparisons were measured among this hybrid and its parents. It showed that trispecific hybrid F1 had some intermediate morphological characters like leaf style between its parents and some different characters from its parents, like crawl growth characteristics and two kind flower color. It is highly resistant to insects comparing with other cotton species by four year field investigation. By cytogenetic analysis, triple hybrid was further confirmed by meiosis behavior of pollen mother cells. Comparing with regular meiosis of its three parents, it was distinguished by the occurrence of polyads with various numbers of unbalanced microspores and finally generating various abnormal pollen grains. All this phenomenon results in the sterility of this hybrid. This hybrid was further identified by SSR marker from DNA molecular level. It showed that 98 selected polymorphism primers amplified effective bands in this hybrids and its parents. The genetic proportion of three parents in this hybrid is 47.8% from G. hirsutum, 14.3% from G. australe, 7.0% from G. capitis-viridis, and 30.9% recombination bands respectively. It was testified that wild genetic material has been transferred into cultivated cotton and this new germplasm can be incorporated into cotton breeding program.
SmartCrawl: a new strategy for the exploration of the hidden web

The way current search engines work leaves a large amount of information available in the World Wide Web outside their catalogues. This is due to the fact that crawlers work by following hyperlinks and a few other references and ignore HTML forms. In this paper, we propose a search engine prototype that can retrieve information behind HTML forms by automatically generating queries for them. We describe the architecture, some implementation details and an experiment that proves that the information is not in fact indexed by current search engines.
Herbal Compound “Jiedu Huayu” Reduces Liver Injury in Rats via Regulation of IL-2, TLR4, and PCNA Expression Levels

Aim of the Study. To investigate the preventative effects of Jiedu Huayu (JDHY) on D-galactosamine (D-GalN) and lipopolysaccharide-induced acute liver failure (ALF) and to evaluate the possible mechanisms of action. Materials and Methods. ALF was induced in Wistar rats by administrating D-GalN (900 mg/kg) and lipopolysaccharide (10 μg/kg). After treatment with JDHY granules, the levels of blood alanine aminotransferase, aspartate aminotransferase, total bilirubin, and prothrombin time were determined. Proliferating cell nuclear antigen was detected by immunohistochemistry staining. The expression of interleukin-2 (IL-2) and toll-like receptor 4 (TLR4) was examined by fluorescence quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blot. Results. JDHY treatment dramatically improved liver function and increased survival rates in an ALF model in rats. We observed a decrease in IL-2 and TLR4 expression following treatment with JDHY in liver cells from ALF rats using qRT-PCR and Western blot analysis. Conclusion. We hypothesize that the therapeutic potential of JDHY for treating ALF is due to its modulatory effect on the suppression of inflammation and by promoting hepatocyte regeneration. Our results contribute towards validation of the traditional use of JDHY in the treatment of liver disease.
MicroRNA-124a Regulates Foxa2 Expression and Intracellular Signaling in Pancreatic β-Cell Lines*

MicroRNAs (miRNAs) are short non-coding RNAs that have been implicated in fine-tuning gene regulation, although the precise roles of many are still unknown. Pancreatic development is characterized by the complex sequential expression of a gamut of transcription factors. We have performed miRNA expression profiling at two key stages of mouse embryonic pancreas development, e14.5 and e18.5. miR-124a2 expression was strikingly increased at e18.5 compared with e14.5, suggesting a possible role in differentiated β-cells. Among the potential miR-124a gene targets identified by biocomputation, Foxa2 is known to play a role in β-cell differentiation. To evaluate the impact of miR-124a2 on gene expression, we overexpressed or down-regulated miR-124a2 in MIN6 β-cells. As predicted, miR-124a2 regulated Foxa2 gene expression, and that of its downstream target, pancreatic duodenum homeobox-1 (Pdx-1). Foxa2 has been described as a master regulator of pancreatic development and also of genes involved in glucose metabolism and insulin secretion, including the ATP-sensitive K+ (KATP) channel subunits, Kir6.2 and Sur-1. Correspondingly, miR-124a2 overexpression decreased, and anti-miR-124a2 increased Kir6.2 and Sur-1 mRNA levels. Moreover, miR-124a2 modified basal and glucose- or KCl-stimulated intracellular free Ca2+ concentrations in single MIN6 and INS-1 (832/13) β-cells, without affecting the secretion of insulin or co-transfected human growth hormone, consistent with an altered sensitivity of the β-cell exocytotic machinery to Ca2+. In conclusion, whereas the precise role of microRNA-124a2 in pancreatic development remains to be deciphered, we identify it as a regulator of a key transcriptional protein network in β-cells responsible for modulating intracellular signaling.