Miracle-dz/UniFAR-FTUs huggingface dataset:
Trehalose metabolism in Escherichia coli: stress protection and stress regulation of gene expression

Endogenously synthesized trehalose is a stress protectant in Escherichia coli. Externally supplied trehalose does not serve as a stress protectant, but it can be utilized as the sole source of carbon and energy. Mutants defective in trehalose synthesis display an impaired osmotic tolerance in minimal growth media without glycine betaine, and an impaired stationary‐phaseinduced heat tolerance. Mechanisms for stress protection by trehalose are discussed. The genes for trehalose‐6‐phosphate synthase (otsA) and anabolic trehalose‐6‐phosphate phosphatase (otsB) constitute an operon. Their expression is induced both by osmotic stress and by growth into the stationary phase and depend on the sigma factor encoded by rpoS (katF). rpoS is amber‐mutated in E. coli K‐12 and its DNA sequence varies among K‐12 strains. For trehalose catabolism under osmotic stress E. coli depends on the osmoticcally inducible periplasmic trehalase (TreA). In the absence of osmotic stress, trehalose induces the formation of an enzyme IITre (TreB) of the group translocation system, a catabolic trehalose‐6‐phosphate phosphatase (TreE), and an amylotrehalase (TreC) which converts trehalose to free glucose and a glucose polymer.
TRADE: Precise Dynamic Race Detection for Scalable Transactional Memory Systems

As other multithreaded programs, transactional memory (TM) programs are prone to race conditions. Previous work focuses on extending existing definitions of data race for lock-based applications to TM applications, which requires all transactions to be totally ordered “as if” serialized by a global lock. This approach poses implementation constraints on the STM that severely limits TM applications’ performance. This article shows that forcing total ordering among all running transactions, while sufficient, is not necessary. We introduce an alternative data race definition, relaxed transactional data race, that requires ordering of only conflicting transactions. The advantages of our relaxed definition are twofold: First, unlike the previous definition, this definition can be applied to a wide range of TMs, including those that do not enforce transaction total ordering. Second, within a single execution, it exposes a higher number of data races, which considerably reduces debugging time. Based on this definition, we propose a novel and precise race detection tool for C/C++ TM applications (TRADE), which detects data races by tracking happens-before edges among conflicting transactions. Our experiments reveal that TRADE precisely detects data races for STAMP applications running on modern STMs with overhead comparable to state-of-the-art race detectors for lock-based applications. Our experiments also show that in a single run, TRADE identifies several races not discovered by 10 separate runs of a race detection tool based on the previous data race definition.
A Stable Matching-Based Virtual Machine Allocation Mechanism for Cloud Data Centers

Virtualization is the enabling technology that makes resource provisioning in Cloud computing feasible. With virtualization, virtual machines (VMs) can be migrated across physical hosts to achieve better utilization of resource with a minimum impact on service quality. The VM allocation problem can be formulated as a stable matching problem. In this paper, we propose a VM allocation mechanism based on stable matching. A deferred acceptance procedure is adopted to handle conflicts among preferences of VMs and physical hosts. Unlike ordinary stable matching problems, both involving party groups in our matching process are having a mutual objective, that is to reduce the overall energy consumption of a Cloud data center while maintaining a high level of Quality of Service. The proposed mechanism is evaluated using CloudSim with real-world workload data. Simulation results show that Cloud data centers with the proposed mechanism can reduce energy consumption and avoid violations of Service-Level Agreement.
Localization of volcanic activity: Topographic effects on dike propagation, eruption and conduit formation

Magma flow in a dike rising in a crack whose strike runs from a highland or a ridge to an adjacent lowland has been modelled to determine the effect of topography on the flow. It is found that there is a distinct tendency for the flow to be diverted away from the highland end of the strike toward the lowland. Separation of the geometric effect of the topography from its effect on lateral confining stresses on the crack indicates that both contribute to the effect but that the effect of stress is less important. Although this analysis explains a tendency for volcanic eruptions to occur in low lands, it does not preclude eruptions on highlands. The particular configuration modelled mimics topography around the proposed nuclear waste repository at Yucca Mountain, Nevada, so that the results may indicate some reduction in the volcanic hazard to the site.
Energy-aware adaptive checkpointing in embedded real-time systems

We present an integrated approach that provides fault tolerance and dynamic power management for a real-time task executing in an embedded system. Fault tolerance is achieved through an adaptive checkpointing scheme that dynamically adjusts the checkpointing interval during task execution. Adaptive checkpointing is then combined with a dynamic voltage scaling scheme to achieve power reduction. The resulting energy-aware adaptive checkpointing scheme uses a dynamic voltage scaling criterion that is based not only on the slack in task execution but also on the occurrences of faults during task execution. Simulation results show that compared to previous methods, the proposed approach significantly reduces power consumption and increases the likelihood of timely task completion in the presence of faults.
Considering Human Memory in PIM

As the amount of information we create and use has increased, people rely less on their memory and more on tools to manage their information. Nevertheless, memory remains key to retrieving information with these tools[1]. Our work has focused on understanding the role that memory plays in PIM. What do people remember and forget about their information collections and objects within, and how are these memories used to solve information needs? Based on investigatory work tools have been developed to better support memory for information. These will now be evaluated to determine whether such an approach can assist PIM practices and to learn more about the role of memory in PIM. This paper briefly summarises the work done so far, describes one of the interfaces created, and overviews a novel methodology to evaluate this and similar interfaces.
Perfluoroctansäure [Biomonitoring Methods in German language, 2006]

Mit dem hier beschriebenen Verfahren kann die innere Exposition von Personen erfasst werden, die beruflich oder umweltbedingt gegen ber der Perfluoroctans ure oder ihren Salzen als Zwischenprodukt in der Synthese von Fluoracryls ureestern exponiert sind. Dabei wird die Perfluoroctans ure im Plasma mittels GC/MS-SIM im EIoder NCI-Modus oder mittels Tandem-MS im NCI-Modus erfasst. Die Perfluoroctans ure wird in gepufferter L sung bei pH 10 als Ionenpaar aus dem Plasma in tert.Butylmethylether extrahiert und anschließend mit Benzylbromid derivatisiert. Die derivatisierte Perfluoroctans ure wird nach kapillargaschromatographischer Trennung mittels Massenspektrometrie nach Elektronenstoßionisation (EI) im SIMModus quantifiziert. Zur Empfindlichkeitssteigerung kann auch die Negative Chemische Ionisierung (NCI) im SIM-Modus oder im MRM-Modus des Tandem-Massenspektrometers eingesetzt werden. Die Kalibrierung erfolgt mit Vergleichsstandards, die in Schweineplasma angesetzt werden und in der gleichen Weise behandelt werden wie die zu analysierenden Proben. Als Interner Standard wird den Plasmaproben Perfluornonans ure zugesetzt. Analytische Methoden Perfluoroctans ure Analysen in biol. Material Bd. 2, Seite D 1
Trust management for IPsec

IPsec is the standard suite of protocols for network-layer confidentiality and authentication of Internet traffic. The IPsec protocols, however, do not address the policies for how protected traffic should be handled at security end points. This article introduces an efficient policy management scheme for IPsec, based on the principles of trust management. A compliance check is added to the IPsec architecture that tests packet filters proposed when new security associations are created for conformance with the local security policy, based on credentials presented by the peer host. Security policies and credentials can be quite sophisticated (and specified in the trust-management language), while still allowing very efficient packet-filtering for the actual IPsec traffic. We present a practical portable implementation of this design, based on the KeyNote trust-management language, that works with a variety of UNIX-based IPsec implementations. Finally, we discuss some applications of the enhanced IPsec architecture.
Decentralized Adaptive Fuzzy Control of Robot Manipulators

This paper develops a decentralized adaptive fuzzy control scheme for robot manipulators via a combination of genetic algorithm and gradient method. The controller for each link consists of a feedforward fuzzy torque-computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line by an improved genetic algorithm, that is to say, not only the parameters but also the structure of the fuzzy system are self-organized. Because genetic algorithm can operate successfully without the system model, no exact inverse dynamics of the robot system are required. The feedback fuzzy PD system, on the other hand, is tuned on-line using gradient method. In this way, the proportional and derivative gains are adjusted properly to keep the closed-loop system stable. The proposed controller has the following merits: 1) it needs no exact dynamics of the robot systems and the computation is time-saving because of the simple structure of the fuzzy systems; and 2) the controller is insensitive to various dynamics and payload uncertainties in robot systems. These are demonstrated by analyses of the computational complexity and various computer simulations.
Venus: Crater distribution and plains resurfacing models

Detailed analysis of the distribution of craters on Venus using Mth nearest neighbor analysis, coupled with models based upon surface morphology constraints, indicates that the hypothesis of complete spatial randomness (CSR) cannot be rejected, but is not a unique model of the observed crater distribution. Based on morphologic mapping, the extensive volcanic plains can be divided into four units that have a spread in age of the order of 0.5T (the mean surface age of the planet). This four-unit plains model, along with its derivatives, produce test statistics that indicate such models also cannot be rejected. Further, the probability of obtaining a result at least as extreme as the observed test statistic given that the null hypothesis (model corresponds to Venus) is true is lowest for the CSR model. There is no particular reason to pick a CSR model (along with its implications for catastrophic resurfacing) as a constraint on the evolution of Venus, and there are geological reasons to choose the multiage models. We find that we cannot distinguish statistically among models that have two, three, or four distinct production ages within the plains. However, the hypothesis that the variation in crater density within all of the plains is due to a single random process can be rejected for two reasons. First, the binomial probability that such a process could exist within each of the plains units is ≤0.05 except the smallest and youngest unit, PL1. Second, using a chi-squared statistic to test the hypothesis that four plains units have the same age gives a p value of 10−4, indicating confident rejection of the hypothesis. Thus CSR cannot be used as a constraint on models of resurfacing or planetary evolution of Venus because of the non-uniqueness in matching such a model to the observed crater distribution and the strong indication of distinct ages within the plains with a significant spread in age. Geological and geophysical constraints provide our best clues for understanding Venus.
Série Scientifique Scientific Series Experiments on the Application of Iohmms to Model Financial Returns Series Experiments on the Application of Iohmms to Model Financial Returns Series

Reproduction partielle permise avec citation du document source, incluant la notice ©. Short sections may be quoted without explicit permission, if full credit, including © notice, is given to the source. Les cahiers de la série scientifique (CS) visent à rendre accessibles des résultats de recherche effectuée au CIRANO afin de susciter échanges et commentaires. Ces cahiers sont écrits dans le style des publications scientifiques. Les idées et les opinions émises sont sous l'unique responsabilité des auteurs et ne représentent pas nécessairement les positions du CIRANO ou de ses partenaires. This paper presents research carried out at CIRANO and aims at encouraging discussion and comment. The observations and viewpoints expressed are the sole responsibility of the authors. They do not necessarily represent positions of CIRANO or its partners. Résumé / Abstract: "Input/Output Hidden Markov Models" (IOHMMs) sont des modèles de Markov cachés pour lesquels les probabilités d'émission (et possiblement de transition) peuvent dépendre d'une séquence d'entrée. Par exemple, ces distributions conditionnelles peuvent être linéaires, logistiques, ou non-linéaires (utilisant, par exemple, une réseau de neurones multi-couches). Nous comparons les performances de généralisation de plusieurs modèles qui sont des cas particuliers de IOHMMs pour des problèmes de prédiction de séries financières : une gaussienne inconditionnelle, une gaussienne linéaire conditionnelle, une mixture de gaussiennes, une mixture de gaussiennes linéaires conditionnelles, un modèle de Markov caché, et divers IOHMMs. Les expériences comparent ces modèles sur leurs prédictions de la densité conditionnelle des rendements des indices sectoriels et du marché. Notons qu'une gaussienne inconditionnelle estime le premier moment avec une moyenne historique. Les résultats montrent que, même si la moyenne historique donne les meilleurs résultats pour le premier moment, pour les moments d'ordres supérieurs les IOHMMs performent significativement mieux, comme estimé par la vraisemblance hors-échantillon. Input/Output Hidden Markov Models (IOHMMs) are conditional hidden Markov models in which the emission (and possibly the transition) probabilities can be conditioned on an input sequence. For example, these conditional distributions can be linear, logistic, or non-linear (using for example multi-layer neural networks). We compare the generalization performance of several models which are special cases of Input/Output Hidden Markov Models on financial time-series prediction tasks: an unconditional Gaussian, a conditional linear Gaussian, a mixture of Gaussians, a mixture of conditional linear Gaussians, a hidden Markov model, and various IOHMMs. The experiments compare these models on predicting the conditional density of returns of market and sector indices. Note that the unconditional …
Using Biometric Authentication to Improve Fire Ground Accountability: An Assessment of Firefighter Privacy Concerns

Two persistent resource management issues that arise in coordinated emergency response efforts are the timely delivery of accurate resource data to decision makers and effective methods for maintaining personnel accountability. Most emergency response agencies rely on manual systems to address each of these issues separately. These manual systems are often inefficient and hinder the effectiveness of the emergency response effort. Biometric authentication of firefighters holds promise as a means of improving both accurate data delivery and personnel accountability. One potential obstacle, however, is acceptance of such biometric systems by the users. In this research, we develop and pilot test an instrument for capturing firefighter privacy concerns associated with using biometric systems. Pilot test results indicate the instrument is reliable and valid for the intended purpose. Preliminary analyses of the pilot test data indicate that firefighter privacy concerns impact system acceptance. Additionally, privacy concerns vary significantly based on ethnic group.
Functional and Symbolic Values of Cloud Terminals: A Study of User Acceptance and Purchasing Behaviors

The purchasing behavior of cloud terminals is increasingly shaped by the emerging cloud services. Rather than its hardware configuration, performance of cloud intelligent terminals such as the Chromebook is more and more dependent on the cloud service capability. However, it remains unknown what factors will drive user's acceptance and purchase of these cloud terminals. Using the Chromebook and MacBook as two representative products, this study models user's acceptance and purchasing behavior of cloud terminals and examines multiple factors driving the consumer's purchasing decision from the perspective of functional and symbolic values. The results emphasize the importance of symbolic values and cost, and propose that symbolic values of different cloud terminals have different effects on consumers' acceptance and purchase. It has important implications for companies to design and sell cloud terminals based on user's acceptance and purchase intentions.
Signal-based Bayesian Seismic Monitoring

Detecting weak seismic events from noisy sensors is a difficult perceptual task. We formulate this task as Bayesian inference and propose a generative model of seismic events and signals across a network of spatially distributed stations. Our system, SIGVISA, is the first to directly model seismic waveforms, allowing it to incorporate a rich representation of the physics underlying the signal generation process. We use Gaussian processes over wavelet parameters to predict detailed waveform fluctuations based on historical events, while degrading smoothly to simple parametric envelopes in regions with no historical seismicity. Evaluating on data from the western US, we recover three times as many events as previous work, and reduce mean location errors by a factor of four while greatly increasing sensitivity to low-magnitude events.
Computer-aided diagnosis of mammographic masses using vocabulary tree-based image retrieval

Computer-aided diagnosis of masses in mammograms is important to the prevention of breast cancer. Many approaches tackle this problem through content-based image retrieval (CBIR) techniques. However, most of them fall short of scalability in the retrieval stage, and their diagnostic accuracy is therefore restricted. To overcome this drawback, we propose a scalable method for retrieval and diagnosis of mam-mographic masses. Specifically, for a query mammographic region of interest (ROI), SIFT descriptors are extracted and searched in a vocabulary tree, which stores all the quantized descriptors of previously diagnosed mammographic ROIs. In addition, to fully exert the discriminative power of SIFT descriptors, contextual information in the vocabulary tree is employed to refine the weights of tree nodes. The retrieved ROIs are then used to determine whether the query ROI contains a mass. This method has excellent scalability due to the low spatial-temporal cost of vocabulary tree. Retrieval precision and diagnostic accuracy are evaluated on 5005 ROIs extracted from the digital database for screening mammography (DDSM), which demonstrate the efficacy of our approach.
Precipitation characteristics in Greenland‐Iceland‐Norwegian Seas determined by using satellite microwave data

Precipitation characteristics and their connection with atmospheric conditions are studied for the Greenland-Iceland-Norwegian (GIN) Seas during wintertime using satellite microwave (Special Sensor Microwave/Imager) and SSM/T2 data. A snowfall algorithm using SSM/T2 data is presented, which makes it possible to estimate the total precipitation and the relative contribution of each precipitation component (rain or snow) over open water. The monthly mean snowfall rate distribution compares well with the snowfall frequency derived from shipboard present weather reports although no data are available for direct snowfall rate validation. The retrieved results show that more than half of the precipitation falls as snow in the GIN Seas during winter and that the monthly mean horizontal distributions of rain and snow have different patterns. By examining the relationship between surface wind and precipitation and conducting case studies, it is found that rainfall and snowfall are associated with different weather types: rainfall occurs mainly in low pressure systems, while snowfall is more likely associated with cold air outbreaks.
What is the Reaction of ISPs to Active Probing ?

Active probing has increasingly been used to collect information about the topological and functional characteristics of the Internet. Given the need for active probing and the lack of a widely accepted mechanism to minimize the overhead of such probes, the traffic and processing overhead introduced on the routers are believed to become an important issue for network operators. In this paper, we conduct an experimental study to understand the reaction of network operators to active probing. In our work, we study the reaction of network operators both from a historical perspective and their current practices. One main finding is that network operators are increasingly configuring their devices not to respond to active direct probes. In addition, ICMP based probes seem to elicit more responses and UDP based probes elicit the least.
Web Search Result Personalization Using Web Mining

The information on the web is growing dramatically. The users have to spend lots of time on the web finding the information they are interested in. Today, he traditional search engines do not give users enough personalized help but provide the user with lots of irrelevant information, In this paper, we present a personalize Web search system, which can helps users to get the relevant web pages based on their selection from the domain list. Thus, users can obtain a set of interested domains and the web pages from the system. The system is based on features extracted from hyperlinks, such as anchor terms or URL tokens, user interest domains and past search results. Our methodology uses an innovative weighted URL Rank algorithm based on user interested domains and user query.