Miracle-dz/UniFAR-FTUs huggingface dataset:
ROSA: Resource-Oriented Service Management Schemes for Web of Things in a Smart Home

A Pervasive-computing-enriched smart home environment, which contains many embedded and tiny intelligent devices and sensors coordinated by service management mechanisms, is capable of anticipating intentions of occupants and providing appropriate services accordingly. Although there are a wealth of research achievements in recent years, the degree of market acceptance is still low. The main reason is that most of the devices and services in such environments depend on particular platform or technology, making it hard to develop an application by composing the devices or services. Meanwhile, the concept of Web of Things (WoT) is becoming popular recently. Based on WoT, the developers can build applications based on popular web tools or technologies. Consequently, the objective of this paper is to propose a set of novel WoT-driven plug-and-play service management schemes for a smart home called Resource-Oriented Service Administration (ROSA). We have implemented an application prototype, and experiments are performed to show the effectiveness of the proposed approach. The results of this research can be a foundation for realizing the vision of “end user programmable smart environments”.
Estimating Dynamic Discrete Choice Models with Hyperbolic Discounting, with an Application to Mammography Decisions

We extend the semi-parametric estimation method for dynamic discrete choice models using Hotz and Miller's (1993) conditional choice probability (CCP) approach to the setting where individuals may have hyperbolic discounting time preferences and may be naive about their time inconsistency. We illustrate the proposed estimation method with an empirical application of adult women's decisions to undertake mammography to evaluate the importance of present bias and naivety in the under-utilization of this preventive health care. Our results show evidence for both present bias and naivety.
Characteristic formulae for the verification of imperative programs

In previous work, we introduced an approach to program verification based on characteristic formulae. The approach consists of generating a higher-order logic formula from the source code of a program. This characteristic formula is constructed in such a way that it gives a sound and complete description of the semantics of that program. The formula can thus be exploited in an interactive proof assistant to formally verify that the program satisfies a particular specification. This previous work was, however, only concerned with purely-functional programs. In the present paper, we describe the generalization of characteristic formulae to an imperative programming language. In this setting, characteristic formulae involve specifications expressed in the style of Separation Logic. They also integrate the frame rule, which enables local reasoning. We have implemented a tool based on characteristic formulae. This tool, called CFML, supports the verification of imperative Caml programs using the Coq proof assistant. Using CFML, we have formally verified nontrivial imperative algorithms, as well as CPS functions, higher-order iterators, and programs involving higher-order stores.
Complement-dependent synergistic bactericidal activity of antibodies against factor H-binding protein, a sparsely distributed meningococcal vaccine antigen.

BACKGROUND Antibodies to factor H (fH)-binding protein (fHBP), a meningococcal vaccine antigen, activate classical complement pathway serum bactericidal activity (SBA) and block binding of the complement inhibitor fH. METHODS To understand these 2 functions in protection, we investigated the interactions of human complement and 2 anti-fHBP monoclonal antibodies (MAbs) with encapsulated Neisseria meningitidis. RESULTS JAR 3 (IgG3) blocks fH binding and elicits SBA against 2 strains with naturally high fHBP expression and a low-expressing strain genetically engineered to express high fHBP levels. JAR 4 (IgG2a) does not block fH binding or elicit SBA. Neither MAb alone elicits SBA against 2 other strains with low fHBP expression, but together the MAbs increase C4b binding and elicit SBA; JAR 3 alone also is bactericidal in whole blood. In nonimmune blood, fHBP knockout mutants from high-expressing stains do not survive, but mutants of low-expressing strains do. CONCLUSIONS Expression of fHBP is a prerequisite for bacterial survival in blood only by strains with naturally high fHBP expression. In low-expressing strains, combinations of 2 nonbactericidal anti-fHBP MAbs can bind to nonoverlapping epitopes, engage C1q, activate C4, and mediate classical complement pathway SBA. In the absence of sufficient C4b binding for SBA, an individual MAb can have opsonophagocytic bactericidal activity.
Follistatin: A Multifunctional Regulatory Protein

Follistatin was first described in 1987 as a follicle-stimulating hormone inhibiting substance present in ovarian follicular fluid. We now know that this effect of follistatin is only one of its many properties in a number of reproductive and nonreproductive systems. A majority of these functions are facilitated through the affinity of follistatin for activin, where activin's effects are neutralized through its binding to follistatin. As such, the interplay between follistatin and activin represents a powerful regulatory mechanism that impinges on a variety of cellular processes within the body. In this review we focus on the biochemical characteristics of follistatin and its interaction with activin and discuss the emerging role of these proteins as potent tissue regulators in the gonad, pituitary gland, pregnancy membranes, vasculature, and liver. Consideration is also given to the larger family of proteins that contain follistatin-like modules, in particular with regard to their functional and structural implications.
Influence of Steaming and Boiling at 180 °C Plus on the Injectability of Bamboo Powder

In this study, we investigated changes in the injectability of bamboo powder and the Vickers hardness of compacted products resulting from differences in heat-treatment conditions such as steaming and boiling. We conducted injection tests and test fabrications of compacted products using bamboo powder treated under various conditions. From the injection tests of heat-treated bamboo powder, we found that injectability was improved by heat treatment. While bamboo powder steamed at 200 °C showed good injectability, boiling at 200 °C yielded better injectability. Vickers hardness tests conducted on compacted products showed that hardness was increased by heat treatment under appropriate conditions. In addition, we found that the heat-treatment condition required to increase the hardness of product was different from that needed to improve injectability.
Manifold Reconstruction in Arbitrary Dimensions Using Witness Complexes

It is a well-established fact that the witness complex is closely related to the restricted Delaunay triangulation in low dimensions. Specifically, it has been proved that the witness complex coincides with the restricted Delaunay triangulation on curves, and is still a subset of it on surfaces, under mild sampling conditions. In this paper, we prove that these results do not extend to higher-dimensional manifolds, even under strong sampling conditions such as uniform point density. On the positive side, we show how the sets of witnesses and landmarks can be enriched, so that the nice relations that exist between restricted Delaunay triangulation and witness complex hold on higher-dimensional manifolds as well. We derive from our structural results an algorithm that reconstructs manifolds of any arbitrary dimension or co-dimension at different scales. The algorithm combines a farthest-point refinement scheme with a vertex pumping strategy. It is very simple conceptually, and it does not require the input point sample to be sparse. Its running time is bounded by c(d)n2, where n is the size of the input point cloud, and c(d) is a constant depending solely (yet exponentially) on the dimension d of the ambient space. Although this running time makes our reconstruction algorithm rather theoretical, recent work has shown that a variant of our approach can be made tractable in arbitrary dimensions, by building upon the results of this paper.
A SURVEY ON SPECTRUM SENSING TECHNIQUES FOR COGNITIVE RADIO

The paper refers to the increased demand for a new approach to efficiently use the available mobile communications spectrum resources. The current static assignment of spectrum often exceeds the available bandwidth. Cognitive Radios (CR), self-learning, adaptive and intelligent radios with the capacity to sense the radio environment and to adapt to the current conditions like available frequencies and channel properties, can use the spectrum in a more flexible way. The spectrum sensing capacities of the CR rely on advanced signal processing techniques and can be enhanced by using cooperative sensing.
A classification study of marine phytoplankton on the base of improved SVM

The SVM (Support Vector Machine) is superior to other artificial neural network (such as the BP network) in classification. And its rapid development and the wide application are due to the introduction of the concept of soft margin. However, the traditional soft margin SVM gives the same misclassification costs for the various sample data, thus the processing results of the real data are not satisfactory. In this paper, the traditional SVM soft margin algorithm is improved by paying different costs for different misclassification. So the correct classification rate is further increased. And the BP network, RBF (Radial Basis Function) network, SVM and the improved SVM are applied to classify marine phytoplankton (enteromorpha) and the classification results are analyzed comparatively.
Learning Execution Contexts from System Call Distributions for Intrusion Detection in Embedded Systems

Existing techniques used for intrusion detection do not fully utilize the intrinsic properties of embedded systems. In this paper, we propose a lightweight method for detecting anomalous executions using a distribution of system call frequencies. We use a cluster analysis to learn the legitimate execution contexts of embedded applications and then monitor them at run-time to capture abnormal executions. We also present an architectural framework with minor processor modifications to aid in this process. Our prototype shows that the proposed method can effectively detect anomalous executions without relying on sophisticated analyses or affecting the critical execution paths.
High-Fidelity Bilateral Teleoperation Systems and the Effect of Multimodal Haptics

In master-slave teleoperation applications that deal with a delicate and sensitive environment, it is important to provide haptic feedback of slave/environment interactions to the user's hand as it improves task performance and teleoperation transparency (fidelity), which is the extent of telepresence of the remote environment available to the user through the master-slave system. For haptic teleoperation, in addition to a haptics-capable master interface, often one or more force sensors are also used, which warrant new bilateral control architectures while increasing the cost and the complexity of the teleoperation system. In this paper, we investigate the added benefits of using force sensors that measure hand/master and slave/environment interactions and of utilizing local feedback loops on the teleoperation transparency. We compare the two-channel and the four-channel bilateral control systems in terms of stability and transparency, and study the stability and performance robustness of the four-channel method against nonidealities that arise during bilateral control implementation, which include master-slave communication latency and changes in the environment dynamics. The next issue addressed in the paper deals with the case where the master interface is not haptics capable, but the slave is equipped with a force sensor. In the context of robotics-assisted soft-tissue surgical applications, we explore through human factors experiments whether slave/environment force measurements can be of any help with regard to improving task performance. The last problem we study is whether slave/environment force information, with and without haptic capability in the master interface, can help improve outcomes under degraded visual conditions.
Identifiability of the Simplex Volume Minimization Criterion for Blind Hyperspectral Unmixing: The No-Pure-Pixel Case

In blind hyperspectral unmixing (HU), the pure-pixel assumption is well known to be powerful in enabling simple and effective blind HU solutions. However, the pure-pixel assumption is not always satisfied in an exact sense, especially for scenarios where pixels are heavily mixed. In the no-pure-pixel case, a good blind HU approach to consider is the minimum volume enclosing simplex (MVES). Empirical experience has suggested that MVES algorithms can perform well without pure pixels, although it was not totally clear why this is true from a theoretical viewpoint. This paper aims to address the latter issue. We develop an analysis framework wherein the perfect endmember identifiability of MVES is studied under the noiseless case. We prove that MVES is indeed robust against lack of pure pixels, as long as the pixels do not get too heavily mixed and too asymmetrically spread. The theoretical results are supported by numerical simulation results.
A novel feature based rapid eye state detection method

A rapid algorithm for eye state detection is proposed in this paper. It takes use of gray scale characteristics of the eye and upper eyelid bending direction to distinguish the open and closed eye states. Circle Similarity of region is proposed as an index to characterize the eye state. And a simple method based on the relation of curve and the straight line linking the two endpoints of curve is proposed to determine the upper eyelid bending direction. The Algorithm is evaluated on BioID Face Database, Yale Face Database, and part of CAS-PEAL Face Database. The experimental results show that it achieves more than 85% accuracy of eye state detection in less than 5ms runtime in average.
On the Performance of Range Based Bayesian Tracking

In this letter we analyze the performance of location tracking for mobile devices that do not have direct access to Global Positioning Systems (GPS). To estimate positions, measurements of the device's distance to reference beacons are combined with measurements of its velocity in a Bayesian framework. We derive an analytical closed form description of the RMS error of the Bayesian position estimates when the tracking is posed as either a filtering or smoothing problem. Our result is independent of any particular tracking algorithm or implementation.
RPC as the Core of Networking Protocols

Consider the statement that packet headers of a modern protocol should not have a version number field. Today, it is not immediately clear whether this is a good advice or a problematic guideline. In this technical report we argue that remote procedure calls (RPC) –usually classified as a higher level service– can operate anywhere in the protocol stack and replaces protocol version numbers. We observe an (often incomplete) RPC interaction pattern entangled in packet header formats today, which extends to issues of parameter representation with RPC. Moreover, a historical reconsideration of Internet protocols reveals an evolutionary shift towards RPC, at many places and occasions. We experiment with an RPC-style dialect for handling two ICN transports (CCNx and NDN) at the same time –as well as itself– inside the same communication channel, without resorting to lower-level protocol demultiplexing support. Thereby we identify RPC as a vantage point in the design of new communication protocols and as a reference mechanism for embracing different information centric networking protocols.
Extracellular electron transfer: wires, capacitors, iron lungs, and more

Terry Beveridge’s broad and insightful studies of microbe– metal interactions, powered in large part by amazing microscopy, have served as an inspiration and provided guidance for many of us working in this field. This perspective deals with just one of the aspects of microbe–metal interactions to which Terry significantly contributed, extracellular electron transfer. For purposes of this perspective extracellular electron transfer is defined as the process in which electrons derived from the oxidation of electron donors are transferred to the outer surface of the cell to reduce an extracellular terminal electron acceptor. Extracellular electron acceptors may be soluble, yet reduced outside the cell because they are too large to enter the cell, as is probably the case for humic substances (Lovley et al ., 1996, 1998). Some soluble metal species, such as U(VI) complexed with carbonate, or Fe(III) chelated with citrate, are often reduced extracellularly (Lovley et al ., 1991; Marshall et al ., 2006; Coppi et al ., 2007; Gralnick & Newman, 2007; Shelobolina et al ., 2007) as is dimethyl sulfoxide (Gralnick et al ., 2006). It has also been proposed that organisms involved in the syntrophic degradation of organic compounds may make the appropriate connections to directly exchange electrons (Stams et al ., 2006). However, extracellular electron transfer to minerals, such as Fe(III) and Mn(IV) oxides (Lovley, 1991; Lovley et al ., 2004; Gralnick & Newman, 2007; Shi et al. , 2007) and to electrodes (Lovley, 2006a,b), is probably of the greatest interest at present because of their environmental significance and practical applications. Oxidation of organic matter coupled to the reduction of Fe(III) and Mn(IV) oxides plays an important role in the carbon, iron, and manganese cycles in sedimentary environments, and also influences the fate of a diversity of trace metals and phosphate (Lovley, 1993; Thamdrup, 2000). Anaerobic oxidation of organic contaminants with the reduction of Fe(III) is important in groundwater bioremediation (Lovley et al ., 1989; Lovley, 1997), and stimulating dissimilatory metal reduction has shown promise as a method for immobilizing toxic metals in the subsurface (Anderson et al ., 2003; Lloyd et al ., 2003). Oxidation of organic matter coupled to electron transfer to electrodes is a potential strategy for harvesting electricity from the environment and waste organic matter (Lovley, 2006a). The primary goal for many investigators of extracellular electron transfer is to determine how electrons are transferred to the electron acceptors and the factors controlling the rate and extent of this process. With this information in hand, it may be possible to optimize practical applications and better model natural processes. Some of the potentially important questions still remaining in extracellular electron transfer are discussed below in relation to key publications of Terry’s that have led to the development of these questions and/or have provided the techniques that may lead to their answers.
Iris Recognition using Combined Statistical and Co-Occurrence Multi-Resolutional Features

Iris recognition is one of the most reliable personal identification methods. This paper presents a novel algorithm for iris recognition encompassing iris segmentation, fusion of statistical and co-occurrence features extracted from the curvelet and ridgelet transformed images. In this work, the pupil and iris boundaries are detected by using the equation of circle from three points on its circumference. Using Canny edge detection, the iris radius value is empirically chosen based on rigorous experimentation. Eyelash removal is done by using a horizontal 1-D rank filter. Iris normalization is done by mapping the detected iris region from the polar domain to the rectangular domain and the multi-resolution transforms such as curvelet and ridgelet transforms are applied for multi-resolutional feature extraction. The classification is done using Manhattan distance (Md) and multiclass classifier with logistic function and the two results are compared. Here, the benchmark database CASIA-IRIS-V3 (Interval) is used for identification and recognition. It is observed that the ridgelet transform increases the iris recognition rate.
Measurement-calibrated graph models for social network experiments

Access to realistic, complex graph datasets is critical to research on social networking systems and applications. Simulations on graph data provide critical evaluation of new systems and applications ranging from community detection to spam filtering and social web search. Due to the high time and resource costs of gathering real graph datasets through direct measurements, researchers are anonymizing and sharing a small number of valuable datasets with the community. However, performing experiments using shared real datasets faces three key disadvantages: concerns that graphs can be de-anonymized to reveal private information, increasing costs of distributing large datasets, and that a small number of available social graphs limits the statistical confidence in the results. The use of measurement-calibrated graph models is an attractive alternative to sharing datasets. Researchers can "fit" a graph model to a real social graph, extract a set of model parameters, and use them to generate multiple synthetic graphs statistically similar to the original graph. While numerous graph models have been proposed, it is unclear if they can produce synthetic graphs that accurately match the properties of the original graphs. In this paper, we explore the feasibility of measurement-calibrated synthetic graphs using six popular graph models and a variety of real social graphs gathered from the Facebook social network ranging from 30,000 to 3 million edges. We find that two models consistently produce synthetic graphs with common graph metric values similar to those of the original graphs. However, only one produces high fidelity results in our application-level benchmarks. While this shows that graph models can produce realistic synthetic graphs, it also highlights the fact that current graph metrics remain incomplete, and some applications expose graph properties that do not map to existing metrics.
Host Nuclear Factor-κB Activation Potentiates Lung Cancer Metastasis

Epidemiologic and experimental evidence suggests that a link exists between inflammation and cancer, although this relationship has only recently begun to be elucidated for lung cancer, the most frequently fatal human tumor. Nuclear factor-κB (NF-κB), a transcription factor that controls innate immune responses in the lungs, has been implicated as an important determinant of cancer cell proliferative and metastatic potential; however, its role in lung tumorigenesis is uncertain. Here, we specifically examine the role of NF-κB–induced airway inflammation in lung cancer metastasis using a model of intravenous injection of Lewis lung carcinoma cells into immunocompetent C57Bl/6 mice. Induction of lung inflammation by direct and specific NF-κB activation in airway epithelial cells potentiates lung adenocarcinoma metastasis. Moreover, we identify resident lung macrophages as crucial effectors of lung susceptibility to metastatic cancer growth. We conclude that NF-κB activity in host tissue is a significant factor in the development of lung metastasis. (Mol Cancer Res 2008;6(3):364–71)