Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Routing Performance by Using Neighbor Coverage Knowledge and Energy Aware Metric in Mobile Adhoc Networks

— A mobile adhoc network is an independent collection of mobile nodes without having the fixed infrastructure. In the mobile adhoc networks, because of the high mobility of the nodes there is frequent link breakage that causes frequent path failure and route discoveries. A mobile node instinctively rebroadcasts the route request packets and it causes the broadcast storm problem. Because of the high dynamic networks, there is routing overhead so that it consumes high network resource. So, in order to conquer this problem, a neighbor coverage-based probabilistic rebroadcast protocol is used to reduce routing overhead. Also a rebroadcast delay is used to determine rebroadcast order and then to attain additional coverage ratio by sensing neighbor coverage knowledge. By using this method, the numbers of retransmissions is decreased, reduction in routing overhead and to improve the routing performance. But the limitation is the link stability is not considered. To improve the performance the link stability and path stability is an important conception among the nodes. In addition to that energy is an important resource that needs to be preserved in order to extend the lifetime of the network. Actually, in the wireless sensor network different nodes take different amount of energy for transmitting the same data packets. Based on this energy metric the path has to be chosen. Due to the energy drain rate, improve the energy saving. So, in this manuscript to compute the link stability metric and energy metric. Based on this the path is to be chosen. An experimental result shows that when compared to the existing system in the proposed method to achieve high packet delivery ratio, low delay and less energy consumption.
Extraordinary Late-Time Infrared Emission of Type IIn Supernovae

Near-infrared observations are presented for five Type IIn supernovae (SN 1995N, SN 1997ab, SN 1998S, SN 1999Z, and SN 1999el) that exhibit strong infrared excesses at late times (t ≳ 100 days). H- and K-band emission from these objects is dominated by a continuum that rises toward longer wavelengths. The data are interpreted as thermal emission from dust, probably situated in a preexisting circumstellar nebula. The IR luminosities implied by single-temperature blackbody fits are quite large, ≳1041-1042 ergs s-1, and the emission evolves slowly, lasting for years after maximum light. For SN 1995N, the integrated energy release via IR dust emission was ≈0.5-1 × 1050 ergs. A number of dust heating scenarios are considered, the most likely being an infrared echo powered by X-ray and UV emissions from the shock interaction with a dense circumstellar medium.
Using geospatial metadata to boost collaborative filtering

In this paper, we present a method for boosting collaborative filtering by integrating spatial information about geo-referenced items (e.g., photos). In particular, we developed a method to estimate missing ratings by propagating an item's neighbor's ratings based on the similarity of geospatial information. An empirical evaluation shows that geospatial information significantly improves recommendation results, and its contribution grows with the ratings data's level of sparseness. We illustrate the usefulness of the method for a photo recommendation task using data obtained from two popular photo-sharing websites: Flickr and Panoramio. A comparison with state-of-the-art methods indicates the superiority of the proposed method, implying that geospatial information should be considered, when available.
Belief propagation for spatial spectrum access games

Consider a wireless network in which selfish users compete with each other for usage of spectrum. We view this competition as a spatial spectrum access game. There are two fundamental questions regarding this game: how to converge to the optimal Nash equilibrium, and how to converge fast. To answer these two questions, we apply a technique called Belief Propagation to design algorithms for users in this game, which can guarantee fast convergence to an optimal or nearly optimal pure strategy Nash equilibrium. Specifically, when the interference graph is an undirected tree or a directed acyclic graph, our algorithms can find the optimal Nash equilibrium in linear time. For general undirected interference graph, our algorithm converges fast as long as the game is potential (which is the case for many typical scenarios). For some other typical spatial spectrum access games, our algorithms can provide a good approximation to the optimal Nash equilibrium.
EMPIRICAL COMPARISON OF VARIOUS FORMS OF ECONOMIC TRAVEL DEMAND MODELS (ABRIDGMENT)

This study examines some of the popular demand equations available for assessing future conditions of intercity travel demands and in knowing the passenger's response to a fare hike. Planners need to be able to forecast correctly how a reduction in air fare would affect the passenger demand for airlines and other competing modes such as rails and buses. These demand equations are designed to satisfy three basic properties: homogeneity, summability, and symmetry. The five demand models discussed in this paper are: a double-log demand model, an inequality-constrained double-log demand model, a weighted Stone model, the Rotterdam system of demand equations, and a homogeneous translog demand model. The results of the study indicate that demand equations that are imposed by the homogeneity, summability, and symmetry conditions provide more stable results on the compensated cross elasticities than those equations that do not have such conditions imposed. In general, the market cross elasticities--the traditional means of assessing travel demand--are very unstable; and they vary depending on the choice of functional forms, even when we impose the three basic conditions on their demand equations.
Structured Observation to Support Interaction Design

The structured observation method combines elements of a controlled experiment to facilitate comparison, with a realistic composition task to enhance external validity. Rather than test hypotheses, per se, we observe behavior in a systematic way, which helps us identify and better understand the similarities and differences that obtain among users and thus better inform the design of interactive systems.
Using UML Protocol State Machines in Conformance Testing of Components

In previous works we designed a comprehensive approach for conformance testing based on UML behavioral state machines. In this paper we propose two extensions to this approach. First, we apply our approach in the context of a component-based development, and address the problem of checking the interoperability of two connected components. Second, we address the problem of selecting relevant input sequences. Therefore we use UML protocol state machines to specify restricted environment models. This means that we restrict the valid protocol at the provided interface of the component under test with respect to a specific test purpose. Based on these models we select relevant input sequences. We implemented both extensions presented here in our TEAGER tool suite to show their applicability. Both extensions address the behavior at the interfaces of components. We use UML state machines as a unified notation for behavioral and protocol conformance testing as well as for test input selection. This considerably eases the work of test engineers.
The Dutch Block of the Escb Multi-Country Model

The paper presents the Dutch country block of the ESCB Multi-Country Model (MCM) for the euro area. We show how a theoretical model is translated into an econometric specification and how this specification is in turn estimated and used in the projection exercises of the E(S)CB. The dynamic properties of the model are analyzed and the effects of six exogenous shocks to the economy discussed. The long run simulations performed deliver responses of the baseline economy in line with both macroeconomic theory and practice, from a quantitative and a qualitative point of view. JEL Classification: C3, C5, E1, E2
Nonparametric additive regression models for binary time series

I consider models for binary time series, starting with autoregression models and then developing generalizations of them which allow nonparametric additive covariates. I show that several apparently different binary AR(1) models are equivalent. Three possible nonparametric additive regression models which allow for autocorrelation are considered; one is a generalization of an ARX model, the other two are generalizations of a regression model with AR errors. One of the models is applied to two data sets: IBM stock transactions and Melbourne’s rainfall. The fitted models show that stock transaction occurrences are more likely if there have been large transactions in the previous time period. They also show that the Southern Oscillation Index does not provide a strong predictor of rainfall occurrence in Melbourne, contrary to current meteorological practice.
Prevalence and risk factors for pulmonary arterial hypertension in patients with lupus.

OBJECTIVES Pulmonary arterial hypertension (PAH) is associated with rapid deterioration and poor prognosis in SLE, especially during pregnancy. The prevalence of PAH in SLE in non-tertiary centres is uncertain. This study aims to estimate the point prevalence of PAH and identify risk factors for PAH in a large cohort of SLE patients. METHODS A prospective cross-sectional study of 288 patients with SLE were recruited from lupus clinics in Birmingham, UK. Resting transthoracic echocardiography was performed to estimate the pulmonary artery pressures and to assess cardiac morphology and function. PAH was defined as systolic pulmonary artery pressure (sPAP) >30 mmHg. We assessed potential risk factors such as the presence of lung disease, respiratory muscle weakness, autoantibodies, smoking, RP and APS. RESULTS Of 288 patients who consented for participation, 283 patients were suitable for analysis. Twelve patients were found to have PAH with sPAP >30 mmHg. The range of sPAP in our PAH patients was 31-59 mmHg and three patients had sPAP >40 mmHg. The only significant risk factor for PAH was LAC (P = 0.005). CONCLUSIONS The point prevalence of PAH was 4.2% in our cohort of patients with SLE. Most of the PAH cases were found to be of mild severity (<40 mmHg). The significant association of LAC and presence of APS in PAH cases suggests that thrombosis may play an important role in PAH with SLE. This is important, as it is treatable.
Minimal Text Structuring to Improve the Generation of Feedback in Intelligent Tutoring Systems

The goal of our work is to improv ethe Natural Language feedback provided by Intelligent Tutoring Systems. In this paper, we discuss how to make the content presented by one such system more fluentandcom prehensible, and we show how we accomplish this by using relatively inexpensive domain-independent text structuring techniques. W esho who wspecifi crhetoricalrelations can be introduced based on the data itself in a bottom-up fashion rather than being planned top-down by the discourse planner.
BGRP: A Tree-Based Aggregation Protocol for Inter-domain Reservations

Resource reservation needs to accommodate the rapidly growing size and increasing service diversity of the Internet. Recently, hierarchical architectures have been proposed that provide domain-level reservation. However, it is not clear that these proposals can set up and maintain reservations in an efficient and scalable fashion. In this paper, we describe a distributed architecture for inter-domain aggregated resource reservation for unicast traffic. We also present an associated protocol, called the Border Gateway Reservation Protocol (BGRP), that scales well, in terms of message processing load, state storage and bandwidth. Each stub or transit domain may use its own intra-domain resource reservation protocol. BGRP builds a sink tree for each of the stub domains. Each sink tree aggregates bandwidth reservations from all data sources in the network. Since backbone routers only maintain the sink tree information, the total number of reservations at each router scales linearly with the number of domains in the Internet. (Even aggregated versions of the current protocol RSVP have an overhead that grows like N.) BGRP relies on Differentiated Services for data forwarding. As a result, the number of packet classifier entries is extremely small. To reduce the protocol message traffic, routers may reserve domain bandwidth beyond the current load, so that sources can join or leave the tree or change their reservation without having to send messages all the way to the tree root for every such change. We use “soft state” to maintain reservations. In contrast to RSVP, refresh messages are delivered reliably, allowing us to reduce the refresh frequency. Columbia University Computer Science Technical Report No. CUCS-029-99
Fault Injection Scheme for Embedded Systems at Machine Code Level and Verification

In order to evaluate software from the third party whose source codes are not available, after a careful analysis of the statistic data sorted by Orthogonal Defect Classification, and the corresponding relation between patterns of high level language programs and machine codes, we propose a fault injection scheme at machine code level suitable respectively to the IA32 ARM and MIPS architecture, which takes advantage of mutating machine code. To prove the feasibility and validity of this scheme, two sets of programs are chosen as our experimental target: Set I consists of two different versions of triangle testing algorithms, and Set II is a subset of the Mibench which is a collection of performance benchmark programs designed for embedded systems; we inject both high level faults into the source code written in C language and the corresponding machine code level faults directly into the executables, and monitor their running on Linux. The results from experiments show that at least 96% of total similarity degree is obtained. Therefore, we conclude that the effect of injecting corresponding faults on both the source code level and machine code level are mostly the same. Therefore, our scheme is rather useful in analyzing system behavior under faults.
Real-time learning behavior mining for e-learning

Over the last years, we have witnessed an explosive growth of e-learning. More and more learning contents have been published and shared over the Internet. Therefore, how to progress an efficient learning process becomes a critical issue. This paper proposes a sequential mining algorithm to analyze learning behaviors for discovering frequent sequential patterns. By these patterns, we can provide suggestions for learners to select their interest learning contents. Different to other sequential mining algorithms, this study provides an incrementally method to analyze learning sequencing. More specifically, the mining algorithm in this paper can provide real-time analysis, and then report to learners for selecting learning contents more easily.
Deletion of KIBRA, protein expressed in kidney and brain, increases filopodial-like long dendritic spines in neocortical and hippocampal neurons in vivo and in vitro

Spines are small protrusions arising from dendrites that receive most excitatory synaptic input in the brain. Dendritic spines represent dynamic structures that undergo activity-dependent adaptations, for example, during synaptic plasticity. Alterations of spine morphology, changes of spine type ratios or density have consequently been found in paradigms of learning and memory, and accompany many neuropsychiatric disorders. Polymorphisms in the gene encoding KIBRA, a protein present in kidney and brain, are linked to memory performance and cognition in humans and mouse models. Deletion of KIBRA impairs long-term synaptic plasticity and postsynaptic receptor recycling but no information is available on the morphology of dendritic spines in null-mutant mice. Here, we directly examine the role of KIBRA in spinous synapses using knockout mice. Since KIBRA is normally highly expressed in neocortex and hippocampus at juvenile age, we analyze synapse morphology in intact tissue and in neuronal cultures from these brain regions. Quantification of different dendritic spine types in Golgi-impregnated sections and in transfected neurons coherently reveal a robust increase of filopodial-like long protrusions in the absence of KIBRA. While distribution of pre- and postsynaptic marker proteins, overall synapse ultrastructure and density of asymmetric contacts were remarkably normal, electron microscopy additionally uncovered less perforated synapses and spinules in knockout neurons. Thus, our results indicate that KIBRA is involved in the maintenance of normal ratios of spinous synapses, and may thus provide a structural correlate of altered cognitive functions when this memory-associated molecule is mutated.
Clinical Communication in a Trauma Intensive Care Unit (ICU): A Case Study

In 2006, JCAHO defined the second of its National Patient Safety goals as to “Improve the effectiveness of communication among caregivers”. The SBAR protocol gives practical guidelines for person-to-person communication but may not be appropriate in its current form for more complex contexts. This paper presents a case study showing communication processes in one ICU and illustrates important principles of complex clinical communication. The case study is based on observational and interview data from a bedside nurse, a charge nurse, a resident and a fellow over 12 hours each in a major trauma ICU. Artefacts were also collected and annotated. Five types of interconnected communication events are described in the sequence in which they occur. Each communication event is described in terms of its purpose, participants, process, and support tools. Four principles are defined.
Extractive Summarisation Based on Keyword Profile and Language Model

We present a statistical framework to extract information-rich citation sentences that summarise the main contributions of a scientific paper. In a first stage, we automatically discover salient keywords from a paper’s citation summary, keywords that characterise its main contributions. In asecond stage, exploitingthe results of the first stage, we identify citation sentences that best capture the paper’s main contributions. Experimental results show that our approach using methods rooted in quantitative statistics and information theory outperforms the current state-of-the-art systems in scientific paper summarisation.
Haptic contents of a movie dynamically engage the spectator's sensorimotor cortex

Observation of another person's actions and feelings activates brain areas that support similar functions in the observer, thereby facilitating inferences about the other's mental and bodily states. In real life, events eliciting this kind of vicarious brain activations are intermingled with other complex, ever‐changing stimuli in the environment. One practical approach to study the neural underpinnings of real‐life vicarious perception is to image brain activity during movie viewing. Here the goal was to find out how observed haptic events in a silent movie would affect the spectator's sensorimotor cortex. The functional state of the sensorimotor cortex was monitored by analyzing, in 16 healthy subjects, magnetoencephalographic (MEG) responses to tactile finger stimuli that were presented once per second throughout the session. Using canonical correlation analysis and spatial filtering, consistent single‐trial responses across subjects were uncovered, and their waveform changes throughout the movie were quantified. The long‐latency (85–175 ms) parts of the responses were modulated in concordance with the participants’ average moment‐by‐moment ratings of own engagement in the haptic content of the movie (correlation r = 0.49; ratings collected after the MEG session). The results, obtained by using novel signal‐analysis approaches, demonstrate that the functional state of the human sensorimotor cortex fluctuates in a fine‐grained manner even during passive observation of temporally varying haptic events. Hum Brain Mapp 37:4061–4068, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Induction of mouse CYP2J by pyrazole in the eye, kidney, liver, lung, olfactory mucosa, and small intestine, but not in the heart.

We have recently shown that rat CYP2J4 is inducible by pyrazole in liver, small intestine, and olfactory mucosa. The aim of the present study was to determine whether mouse CYP2Js are also inducible by pyrazole, which was known to induce CYP2A5 in mouse liver and kidney, but not in lung or olfactory mucosa. CYP2J proteins were detected in mouse liver, lung, kidney, heart, eye, olfactory mucosa, and small intestine by immunoblot analysis with an anti-CYP2J4 antibody. The microsomal level of the CYP2J4-related P450s in various mouse tissues ranked in the order of small intestine > olfactory mucosa > liver > kidney > or = heart > lung > eye. Induction of the CYP2J proteins was observed in the eye, liver, lung, kidney, olfactory mucosa, and small intestine, but not in the heart, after daily i.p. injection of pyrazole at 120 or 200 mg/kg for 3 days. CYP2J proteins were induced similarly in C57BL/6 and DBA/2 mice. CYP2A5 was detected in the small intestine in addition to liver and olfactory mucosa; however, treatment with pyrazole induced CYP2A5 in the liver, but not in the olfactory mucosa or the small intestine. Induction of CYP2J mRNAs was also observed by RNA blot analysis with a CYP2J4 cDNA probe. RNA-polymerase chain reaction analysis showed that, in both untreated and pyrazole-treated mice, CYP2J5 was expressed in the kidney and liver, but not in the other tissues examined, whereas CYP2J6 was detected in all tissues examined. The different tissue selectivities in CYP2A5 and CYP2J induction by pyrazole suggest involvement of different regulatory mechanisms.
Privacy Violations in Constrained Micro-Grids: Adversarial Cases

Smart micro-grid architectures are small scale electricity provision networks composed of individual electricity providers and consumers. Supporting micro-grids with computationally limited devices, is a cost-effective approach to service provisioning in resource-limited settings. However, the limited availability of real time measurements and the unreliable communication network makes the use of Advanced Metering Infrastructure (AMI) for monitoring and control a challenging problem. Grid operation and stability are therefore reliant on inaccurate and incomplete information. Consequently, data gathering and analytics raise privacy concerns for grid users, which is undesirable. In this paper, we study adversarial scenarios for the privacy violations on micro-grids. We consider two types of privacy threats in constrained micro-grids, namely inferential and aggregation attacks. The reason is that both attacks capture scenarios that can be used to provoke energy theft and destabilize the grid. Grid destabilzation leads to distrust between suppliers and consumers. This work provides a roadmap towards a secure and resilient smart micro-grid energy networks.