Miracle-dz/UniFAR-FTUs huggingface dataset:
A Role for TASK-1 (KCNK3) Channels in the Chemosensory Control of Breathing

Acid-sensitive K+ channels of the tandem P-domain K+-channel family (TASK-1 and TASK-3) have been implicated in peripheral and central respiratory chemosensitivity; however, because of the lack of decisive pharmacological agents, the final proof of the role of the TASK channel in the chemosensory control of breathing has been missing. In the mouse, TASK-1 and TASK-3 channels are dispensable for central respiratory chemosensitivity (Mulkey et al., 2007). Here, we have used knock-out animals to determine whether TASK-1 and TASK-3 channels play a role in the carotid body function and chemosensory control of breathing exerted by the carotid body chemoreceptors. Ventilatory responses to hypoxia (10% O2 in inspired air) and moderate normoxic hypercapnia (3–6% CO2 in inspired air) were significantly reduced in TASK-1 knock-out mice. In contrast, TASK-3-deficient mice showed responses to both stimuli that were similar to those developed by their wild-type counterparts. TASK-1 channel deficiency resulted in a marked reduction of the hypoxia (by 49%)- and CO2 (by 68%)-evoked increases in the carotid sinus nerve chemoafferent discharge recorded in the in vitro superfused carotid body/carotid sinus nerve preparations. Deficiency in both TASK-1 and TASK-3 channels increased baseline chemoafferent activity but did not cause a further reduction of the carotid body chemosensory responses. These observations provide direct evidence that TASK-1 channels contribute significantly to the increases in the carotid body chemoafferent discharge in response to a decrease in arterial PO2 or an increase in PCO2/[H+]. TASK-1 channels therefore play a key role in the control of ventilation by peripheral chemoreceptors.
Limit Cycle Occurrence During Reactive Power Generation by Interlinking Converter in Hybrid Microgrids

This paper is concerned with the analysis of an instability phenomenon, known as limit cycle, in hybrid microgrids (HMGs). The rapid growth of distributed energy resources and their integration into existing distribution networks has opened a new era for electricity generation and distribution markets. The appearance of microgrids, both in the form of ac and dc, is the result of this integration. When both ac and dc microgrids (AC-MGs and DC-MGs) are in the vicinity of each other, they can be interconnected via ac-dc converters, also known as interlinking converters (ICs). Such a structure allows more efficient use of all resources in the system by enabling energy exchange between DC- and AC-MGs. In this paper, it is shown how the reactive power compensation method in IC leads to unstable operation of the HMG. Detailed analysis of this instability reveals that it is caused by a phenomenon known as limit cycle. By knowing the roots of instability, it is possible to eliminate it. Then we studied how the limit cycle that occurred is avoided by nonlinear control techniques support. The analytical studies are backed up by the simulation of a sample HMG.
System/370 Extended Architecture: Design Considerations

This paper reviews the overall objectives and the design considerations that led to the System/370 Extended Architecture (370-XA). It presents an overview of the differences between the System/370 and 370-XA architectures and summarizes all architectural extensions, deletions, and changes. Then it describes in more detail the extensions for interpretive execution, 31-bit addressing, protection, tracing, inter-CPU communications, and extended-precision floating-point division.
Traffic relaying in multi-hop wireless networks

We analyze the achievable data rate of relaying strategies in a wireless network where nodes are equipped with half-duplex radios. The nodes need to deliver their data to a destination node, possibly at different rates, through multi-hop communications. In such a scenario, we first derive a cut-set upper bound to the achievable rate(s), then we take into account the interference among simultaneous transmissions and devise a communication strategy. Such a strategy ensures a high rate allocation to the nodes, which is also fair, i.e., it provides the desired proportion among the average data rates of the nodes. Our results show that the proposed strategy closely approximates the bound for any value of SNR.
Diatom growth and productivity in an oligo‐trophic midocean gyre: A 3‐yr record from the Sargasso Sea near Bermuda

We measured the rate of biogenic silica production in the upper 160 m at the Bermuda Atlantic Time‐series Study (BATS) site in the western Sargasso Sea on 12 cruises between August 1991 and May 1994 using a 30Si tracer method. Previously initiated time series of particulate silica concentrations and the gravitational flux of siliceous particles were extended to produce an October 1988–December 1994 time series for biogenic silica concentrations and August 1991–December 1994 time series for lithogenic silica concentrations and fluxes of biogenic and lithogenic silica. Specific rates of biogenic silica production during nonbloom periods indicate active diatom growth, with a mean doubling time of 4.5 d for biogenic silica. The annual silica production rate is conservatively estimated to be 240 mmol Si m−2, which corresponds to a diatom productivity of ∼20–45 g C m−2 yr−1, ∼15–25% of the mean annual primary productivity. Comparison of silica production rates with sinking fluxes from the upper 150 m (26–53 mmol Si m−2 yr−1) indicates that ∼80% of the silica produced in the euphotic zone dissolves in the upper 150 m. Sinking of diatoms and their remains can account for ∼30% of the particulate organic carbon export at the BATS site on an annual basis and nearly 100% during the annual winter/spring diatom bloom. Atmospheric dust inputs each summer, indicated by July–August maxima in the concentration and vertical flux of lithogenic silica, do not stimulate either biogenic silica production or primary productivity, implying that iron availability limits neither diatom growth nor total primary production in the western Sargasso Sea.
A Specialized Global Software Engineering Taxonomy for Effort Estimation

To facilitate the sharing and combination of knowledge by Global Software Engineering (GSE) researchers and practitioners, the need for a common terminology and knowledge classification scheme has been identified, and as a consequence, a taxonomy and an extension were proposed. In addition, one systematic literature review and a survey on respectively the state of the art and practice of effort estimation in GSE were conducted, showing that despite its importance in practice, the GSE effort estimation literature is rare and reported in an ad-hoc way. Therefore, this paper proposes a specialized GSE taxonomy for effort estimation, which was built on the recently proposed general GSE taxonomy (including the extension) and was also based on the findings from two empirical studies and expert knowledge. The specialized taxonomy was validated using data from eight finished GSE projects. Our effort estimation taxonomy for GSE can help both researchers and practitioners by supporting the reporting of new GSE effort estimation studies, i.e. new studies are to be easier to identify, compare, aggregate and synthesize. Further, it can also help practitioners by providing them with an initial set of factors that can be considered when estimating effort for GSE projects.
Metasearching using modified rough set based rank aggregation

A metasearch engine is a search engine, which uses the results of several search engines to produce a collated list of search results. The actual success of a meta-search engine directly depends on the aggregation technique underlying it. User satisfaction is obviously the most important factor in measuring the quality of search results. Therefore, we propose a metasearch system that models user feedback based metasearching. Our system uses the modified rough set based rank aggregation for metasearching. In the modified rough set based rank aggregation technique, we incorporate the confidence of the rules in predicting a class for a given set of data. We associate a score variable to the predicted class of the record, where the value of the variable is equal to the confidence measure of the rule. For each query in the training set, we mine the ranking rules using rough set theory and select the best rules-set by performing cross-validation test. Once the system is trained, we may use the best rule set to get the overall ranking for the results returned from different search systems in response to other queries. Previously modified rough set based rank aggregation technique has been already used for the performance evaluation of Web Search systems but here, we apply this method for meta searching. We also perform an evaluation of our proposed system by three independent evaluators. We compare our method with metasearching method based on rough set based rank aggregation and find that our method performs better than the metasearching method based on rough set based rank aggregation.
Impact of One-Timer/N-Timer Object Classification on the Performance of Web Cache Replacement Algorithms

Web cache replacement Algorithms proposed in the literature try to maximize the Hit Ratio (HR), the Byte Hit Ratio (BHR), and the Delay Saving Ratio (DSR). However, even with an infinite Web cache storage capacity, values of these metrics could not exceed 70% most of the time. This is due to the fact that, given a workload, the first reference to an object is always a miss. Moreover, a statistical analysis of the workload shows that as much as 76% of objects are One-Timers (OT), i.e. they are referenced only once. Caching OT objects usually degrade the performance of all Web cache replacement algorithms. In fact, it may cause the eviction of N-Timer (NT) objects and hence increases the number of misses. In this paper, we present a technique to classify whether a cached object is an OT or not. We show through simulation that classification may significantly enhance the performance of replacement algorithms with respect to the HR, the BHR and the DSR.
Geophysical inversion in an integrated mineral exploration program : examples from the San Nicolás deposit

The ability to produce three-dimensional physical property models of the subsurface from surface geophysical data, coupled with an increasing need to explore for minerals in concealed terranes, results in geophysical inversions providing more significant information to the exploration team. We examine the role that geophysical inversion can play in an integrated mineral exploration program, and the impact it can have on the results. As an example, geophysical data from the San Nicolás copper-zinc massive sulfide deposit in Mexico are inverted.
How do radical climate movements negotiate their environmental and their social agendas? A study of debates within the Camp for Climate Action (UK)

This is a case study of the Camp for Climate Action, which has held several high-profile protest events in the UK since its inception in 2006. It analyses the Camp as a contested space where different emphases on environmental and social priorities have to be negotiated by its activists. The article considers areas of contestation where concerns over climate change meet questions of social justice. These are structured around tangible issues of campaigning, such as opposition to new coal-fired power stations or to the third runway at Heathrow airport, some of which have put the Camp at odds with labour movement and class struggle activists. While some demand a drastic shift away from current levels of consumption, others question the discriminatory effects of self-imposed austerity politics. On a more abstract level, the article considers debates on the need for government solutions to the environmental crisis and their possible impacts on social equality. The article is structured around movement-internal debates and makes use of interviews, extensive fieldwork notes and continuous participant observation over the course of four years.
Scalable , High Performance Ethernet Forwarding Lookup

This poster will describe a new Ethernet forwarding lookup architecture that enables the simple construction of switches that can contain tens of millions of forwarding entries. The core design is based upon recent work on concurrent multi-reader cuckoo hashing [1] to create fast and memory-efficient lookup tables. This work has two primary benefits: First, it suggests that were a need for such scale to arise—whether for flat addressing or for more extreme uses such as content-based networking— such huge-scale tables could be practically constructed. Second, as a pragmatic byproduct, the technique allows storing several hundred thousand forwarding entries entirely in fast L3 CPU cache, facilitating the construction of high-throughput software-based switches.
A combined Bayesian network method for predicting drive failure times from SMART attributes

Statistical and machine learning methods have been proposed to predict hard drive failure based on SMART attributes, and many achieve good performance. However, these models do not give a good indication as to when a drive will fail, only predicting that it will fail. To this end, we propose a new notion of a drive's health degree based on the remaining working time of hard drive before actual failure occurs. An ensemble learning method is implemented to predict these health degrees: four popular individual classifiers are individually trained and used in a Combined Bayesian Network (CBN). Experiments show that the CBN model can give a health assessment under the proposed definition where drives are predicted to fail no later than their actual failure time 70% or more of the time, while maintaining prediction performance standards at least approximately as good as the individual classifiers.
Brain activation gradients in ventrolateral prefrontal cortex related to persistence of ADHD in adolescent boys.

OBJECTIVE To explore the possible role that functional abnormalities of the prefrontal cortex and basal ganglia play in the persistence of attention-deficit/hyperactivity disorder (ADHD) in adolescents aged 15 to 19 years. METHOD Ten male adolescents who were diagnosed with ADHD during childhood were grouped into those who continued to meet full diagnostic criteria for DSM-IV ADHD (persisters; n = 5) and those in whom symptoms had remitted sufficiently to warrant a diagnosis of ADHD in partial remission (remitters; n = 5). Persisters, remitters, and five carefully matched controls with no history of ADHD were scanned using functional magnetic resonance imaging while performing a go/no-go task. RESULTS Parallel linear trends were found in performance on the go/no-go task and activation of ventrolateral prefrontal cortex, such that persisters made the most commission errors (33%) and showed the greatest activation, remitters made fewer commission errors (24%) and had lower activity, and activation was lowest in controls who made the fewest errors (13%). CONCLUSIONS These preliminary results suggest that developmental changes in ADHD symptomatology are associated with functional changes in ventrolateral prefrontal cortex activity.
Real-Time Impulse-Based Simulation of Rigid Body Systems for Haptic Display

To date, haptic interfaces have rarely been used to display complex virtual environments such as those involving 3D mechanical assembly operations, or the use of hand tools. Of the limitations which have been encountered, one is the absence of suitable simulation techniques which provide a general, user-defined virtual environment. This paper discusses the use of an impulse-based simulation as a general purpose multibody simulator for haptic display. This technique uses Poisson’s hypothesis in conjunction with Coulomb friction as the basis of the contact model. Since haptic displays are required to run in real time with a constant step size and high update rate, changes to the algorithm are required. We identify the “impact state” as a critical feature of the contact model, and outline the various ways it can be chosen. Finally, we describe the implementation of a planar multibody simulator on one and two-axis haptic displays.
Molten-Alloy Driven Self-Assembly for Nano and Micro Scale System Integration

Self-assembly is emerging as one of the main methods for constructionof heterogeneous systems consisting of multiple component types in nano- and micro-scales. The engineered self-assemblyusedfor sys- tem integrationinvolves preparation ofparts that can rec- ognize and bind to each other or a template, and perfec- tion ofprocedures that allow for high yieldself-assembly of these parts into a system. Capillary forces resultant from molten alloys are attractive candidates for driving such self-assembly processes as they can simultaneously provideelectrical and mechanical connections. The basic self-assembly process is reviewed here. Selection of the appropriate alloy, a critical issue in development of the self-assembly mechanism, is discussed and various can- didates are identified. Examples are provided in which alloys are used to interconnect parts in nano- and micro- scales or produce three-dimensional structures. We con- clude with a brief discussion of opportunities and chal- lenges ahead in the development of system integration processes taking advantage of self-assembly.
A New Clustering Algorithm Based on Self-Updating Process

Many of the popular clustering methods, such as K-means and Self-Organizing Maps, require a set of initial values to begin the iterative process. In this paper we present a simple and novel method that does not require such an initial set and can avoid the problem of local minima. The clustering strategy we propose is motivated by intuition on clustering. The algorithm stands from the viewpoint of subjects to be clustered and simulates the process of how they perform self-clustering. At the end of the process subjects belonged to the same cluster would converge to the same point, which represents the cluster location in a p-dimensional space. Our simulation study showed promising results compared to other clustering methods. An example on image segmentation will also be presented.
Automating the Measurement of Linguistic Features to Help Classify Texts as Technical

Text classification plays a central role in software systems which perform automatic information classification and retrieval. Occurrences of linguistic feature values must be counted by any mechanism that classifies or characterizes natural language text by topic, style, genre or, in our case, by the degree to which a text is technical. We discuss the methodology and key details of the feature value extraction process, paying attention to fast and reliable implementation. Our results are mixed but support continued investigation— while a significant level of automation has been achieved, the successfully extracted feature counts do not always correlate with technicality as strongly as anticipated.
Self-Certified Proxy Blind Signcryption Scheme from Pairings

By integrating the thoughts of self-certified signcryption and proxy blind signature, we propose a new self certified proxy blind signcryption scheme from pairings and prove its security in the random oracle model. The proposed overcomes the certificate existence problem and the key escrow problem in public key cryptosystem. In the scheme, the original signcrypter can delegate the signcryption power to a proxy blind signcrypter, then the proxy blind signcryption can be generated by the proxy blind signcrypter and the message owner, the proxy blind signcrypter learns nothing about the signed message and can not trace the proxy blind signcryption. Analysis shows the new scheme has lower communication overheads and computation efforts, furthermore, its efficiency is better than the existing literatures, so it has more practical value in applications.
Research Teams’ Human Capital

Adopting a Bourdieusian perspective, human capital of research team in the paper is understood as the configuration of the active properties of individual team’s members and the distribution of differences of their active properties. The paper describes a research team as an ensemble of social distinctions determined by a distribution of “active properties” of the team members (educational, research, administrative and media characteristics) and analyses their empirical distribution. The study is based on the consideration of sociological factors of research teams’ performance. The paper discusses in depth the performance of research team (from a sociological point of view) and the relationship between the performance and the social management efficiency. It is prouved that the performance depends on the efficiency of human capital management research team. These distributions show how holistic properties of the field develop, how they relate to individual agents’ properties and how individual researchers “fit” into science.
Multi-scale vehicle logo recognition by directional dense SIFT flow parsing

This paper considers robust vehicle logo recognition (without aiming at accurate location) for intelligent transportation systems. We propose a recognition-before-location framework for multi-scale vehicle logos which exploits a directional SIFT flow parsing method. We extract dense SIFT descriptors of different standard vehicle logos. An improved matching method is proposed to obtain a directional SIFT flow from standard logo models for vehicle images. Our vehicle logo recognition algorithm is based on dense SIFT matching energy and SIFT flow consistency. We verify the accuracy of vehicle logo recognition and the robustness for multi-scale logo images on various real data.
MODELLING URBAN FREIGHT GENERATION

This paper reviews the application of regression-type models in analysing the generation of urban freight, and presents the results of an investigation of the use of such models using data for Melbourne, Australia. The equations which were developed for relating zonal truck trip attraction and production to zonal land-use variables explained a high proportion of the variance in trip-making between zones. However, similar equations relating zonal goods generation in tonnes by commodity to land-use variables were not as successful. /Author/TRRL/
Geometric Snakes for Triangular Meshes

Feature detection is important in various mesh processing techniques, such as mesh editing, mesh morphing, mesh compression, and mesh signal processing. In spite of much research in computer vision, automatic feature detection even for images still remains a difficult problem. To avoid this difficulty, semi‐automatic or interactive techniques for image feature detection have been investigated. In this paper, we propose a geometric snake as an interactive tool for feature detection on a 3D triangular mesh. A geometric snake is an extension of an image snake, which is an active contour model that slithers from its initial position specified by the user to a nearby feature while minimizing an energy functional. To constrain the movement of a geometric snake onto the surface of a mesh, we use the parameterization of the surrounding region of a geometric snake. Although the definition of a feature may vary among applications, we use the normal changes of faces to detect features on a mesh. Experimental results demonstrate that geometric snakes can successfully capture nearby features from user‐specified initial positions.