Miracle-dz/UniFAR-FTUs huggingface dataset:
The Midbrain Precommand Nucleus of the Mormyrid Electromotor Network

The functional role of the midbrain precommand nucleus (PCN) of the electromotor system was explored in the weakly electric mormyrid fishGnathonemus petersii, using extracellular recording of field potentials, single unit activity, and microstimulationin vivo. Electromotor-related field potentials in PCN are linked in a one-to-one manner and with a fixed time relationship to the electric organ discharge (EOD) command cycle, but occur later than EOD command activity in the medulla. It is suggested that PCN electromotor-related field potentials arise from two sources: (1) antidromically, by backpropagation across electrotonic synapses between PCN axons and command nucleus neurons, and (2) as corollary discharge-driven feedback arriving from the command nucleus indirectly, via multisynaptic pathways. PCN neurons can be activated by electrosensory input, but this does not necessarily activate the whole motor command chain. Microstimulation of PCN modulates the endogenous pattern of electromotor command in a way that can mimic the structure of certain stereotyped behavioral patterns. PCN activity is regulated, and to a certain extent synchronized, by corollary discharge feedback inhibition. However, PCN does not generally function as a synchronized pacemaker driving the electromotor command chain. We propose that PCN neurons integrate information of various origins and individually relay this to the command nucleus in the medulla. Some may also have intrinsic, although normally nonsynchronized, pacemaker properties. This descending activity, integrated in the electromotor command nucleus, will play an important modulatory role in the central pattern generator decision process.
Fuzzy decision trees for dynamic data

The fuzzy decision tree based approach is a very popular machine learning method that deals with imprecise and uncertain data. This approach offers a good way to handle static data. However, few works have been conducted on the use of this approach to deal with stream of data or temporal data when the training set is built incrementally time after time. To handle such kind of data brings out a number of problems for the algorithms used to construct such fuzzy decision trees. In this paper, a new approach is proposed to construct a fuzzy decision tree (FDT) when the training set is built incrementally and when training examples are provided temporally. A new measure of discrimination is defined in order to rank attributes during the process of construction of the FDT and to take into account aging of examples.
Multimedia access and retrieval (panel session): the state of the art and future directions

Several years have passed since the research topic of content based multimedia retrieval emerged. We have witnessed the burgeoning research activities into a plenitude of new indexing, retrieval, and filtering tools for images, video, audio, music, graphics, and their combinations with text-based information. Exciting research opportunities arise when integrating knowledge from multiple disciplines, such as media content processing, database, information retrieval, and machine user interface. In the commercial domain, we have also witnessed several impressive efforts moving technologies into practical arenas.
A multi-step curved lane detection algorithm based on hyperbola-pair model

In this paper, we propose a multi-step algorithm based on a hyperbola-pair model for lane detection. We represent the lane markings on the road by a modified hyperbola-pair model, which contains two parts. The first one is a parallel straight line model, which is achieved by Hough transform. The second one is a hyperbola-pair line model, which is achieved by a searching strategy with the parameters got in the first stage as initial parameters. Experiment results show a robust performance in a noise condition, such as part of the lane markings are occupied by other vehicles in the lanes. The algorithm can provide accurate information of location and curvature of the lane markings in real-time.
Catalyst-like modulation of transition states for CFTR channel opening and closing: New stimulation strategy exploits nonequilibrium gating

Cystic fibrosis transmembrane conductance regulator (CFTR) is the chloride ion channel mutated in cystic fibrosis (CF) patients. It is an ATP-binding cassette protein, and its resulting cyclic nonequilibrium gating mechanism sets it apart from most other ion channels. The most common CF mutation (ΔF508) impairs folding of CFTR but also channel gating, reducing open probability (Po). This gating defect must be addressed to effectively treat CF. Combining single-channel and macroscopic current measurements in inside-out patches, we show here that the two effects of 5-nitro-2-(3-phenylpropylamino)benzoate (NPPB) on CFTR, pore block and gating stimulation, are independent, suggesting action at distinct sites. Furthermore, detailed kinetic analysis revealed that NPPB potently increases Po, also of ΔF508 CFTR, by affecting the stability of gating transition states. This finding is unexpected, because for most ion channels, which gate at equilibrium, altering transition-state stabilities has no effect on Po; rather, agonists usually stimulate by stabilizing open states. Our results highlight how for CFTR, because of its unique cyclic mechanism, gating transition states determine Po and offer strategic targets for potentiator compounds to achieve maximal efficacy.
A Model for Web Workload Generation Based on Content Classification

Web server performance is tightly bound to the workload the server has to support. Therefore, understanding the nature of the server workload is particularly important in capacity planning and overload control of Web servers. Web performance analysis can be done, a priori, with a synthetic generation of Web system workload. However, performance analysis results depend on the accuracy of this workload. In this paper, we propose and describe a workload-generation model based on group classification of Web server les according to their contents. This model, henceforth referred to as SURGE-CC (SURGE Content Classification), is an extension of the SURGE (Scalable URL Reference Generator) model. SURGE-CC is simple, very easy to understand and, most important of all, can be readily customized for specific applications. The parameter settings in our model allows the influnce of Web server contents on output load to be investigated from both a qualitative and quantitative point of view. The results of a workload-generation tool based on our model implementation show the workload dependence on the nature of the server contents, the model ability to generate self-similar tra c and the accuracy of the synthetic workload. The model was validated by a careful statistical analysis of massive data from several servers, computational simulations and by comparison of results found in literature. We point some future application of the SURGE-CC model and discuss the new investigation branches derived from the novelty of our model approach.
Biogeographic barriers drive co-diversification within associated eukaryotes of the Sarracenia alata pitcher plant system

Understanding if the members of an ecological community have co-diversified is a central concern of evolutionary biology, as co-diversification suggests prolonged association and possible coevolution. By sampling associated species from an ecosystem, researchers can better understand how abiotic and biotic factors influence diversification in a region. In particular, studies of co-distributed species that interact ecologically can allow us to disentangle the effect of how historical processes have helped shape community level structure and interactions. Here we investigate the Sarracenia alata pitcher plant system, an ecological community where many species from disparate taxonomic groups live inside the fluid-filled pitcher leaves. Direct sequencing of the eukaryotes present in the pitcher plant fluid enables us to better understand how a host plant can shape and contribute to the genetic structure of its associated inquilines, and to ask whether genetic variation in the taxa are structured in a similar manner to the host plant. We used 454 amplicon-based metagenomics to demonstrate that the pattern of genetic diversity in many, but not all, of the eukaryotic community is similar to that of S. alata, providing evidence that associated eukaryotes share an evolutionary history with the host pitcher plant. Our work provides further evidence that a host plant can influence the evolution of its associated commensals.
Identifying acne treatment uncertainties via a James Lind Alliance Priority Setting Partnership

Objectives The Acne Priority Setting Partnership (PSP) was set up to identify and rank treatment uncertainties by bringing together people with acne, and professionals providing care within and beyond the National Health Service (NHS). Setting The UK with international participation. Participants Teenagers and adults with acne, parents, partners, nurses, clinicians, pharmacists, private practitioners. Methods Treatment uncertainties were collected via separate online harvesting surveys, embedded within the PSP website, for patients and professionals. A wide variety of approaches were used to promote the surveys to stakeholder groups with a particular emphasis on teenagers and young adults. Survey submissions were collated using keywords and verified as uncertainties by appraising existing evidence. The 30 most popular themes were ranked via weighted scores from an online vote. At a priority setting workshop, patients and professionals discussed the 18 highest-scoring questions from the vote, and reached consensus on the top 10. Results In the harvesting survey, 2310 people, including 652 professionals and 1456 patients (58% aged 24 y or younger), made submissions containing at least one research question. After checking for relevance and rephrasing, a total of 6255 questions were collated into themes. Valid votes ranking the 30 most common themes were obtained from 2807 participants. The top 10 uncertainties prioritised at the workshop were largely focused on management strategies, optimum use of common prescription medications and the role of non-drug based interventions. More female than male patients took part in the harvesting surveys and vote. A wider range of uncertainties were provided by patients compared to professionals. Conclusions Engaging teenagers and young adults in priority setting is achievable using a variety of promotional methods. The top 10 uncertainties reveal an extensive knowledge gap about widely used interventions and the relative merits of drug versus non-drug based treatments in acne management.
Optimal placement of charging stations for electric taxis in urban area with profit maximization

The deployment of charging infrastructures is a key factor for the operation of electric taxis in urban area. This paper focuses on the operational efficiency and the charging convenience of electric taxis, and introduces a two-step optimization process of the charging station location for electric taxis. We propose a modified k-means clustering method to divide the urban area into multiple service regions according to the market demand distribution. Then we utilize the optimal location model in the service region to calculate the optimal sites of the charging stations to maximize the operational efficiency and charging convenience. We collect GPS data of electric taxis in Shenzhen and examine the behavior of our proposed approach. Numerical results suggest that the proposed approach outperforms the traditional particle swarm optimization (PSO) method and has improved the operational efficiency by 14.03% and reduced the average distance for the charging service by 12.30% compared with the actual physical sites.
Group-Analytic Art Therapy

T H E technique I have developed in art therapy groups is a ‘non-directive, theme-centred’ approach, which I suggest amounts to ‘group-analytic art therapy’ (McNeilly, 1984). In my early years as an art therapist I used the ‘directive’ approach. My motivation was to provide a context for the experience of intense and ambivalent feelings. This directive, uncovering approach caused many conflicts for my groups and myself, with numerous consequences. They included catharsis of questionable long-term value; intolerance of the uncovered feelings, and withdrawal or flight from the group. What emerged was not all negative, but in retrospect I wonder about the validity of group responses resulting from such a strong controlling input from me. An over-idealized aspect of this from my position was to gain access to unconscious material on demand. I believe that the reverse of this actually happened, and that my current ‘groupanalytic’ approach is far more productive. I think that in many ways the directive approach served as a safety net for a beginning art therapist and did not deal adequately with transference and counter-transference issues. I now realize that this theme-giving, directive technique might be equated with thc conductor in a group-analytic group who sits down and says: ‘Today I want us t o talk of love and hate’. Murray Cox (1978) speaks of disclosure between patient and therapist. He looks at the total process of therapeutic movement a s one of: unconscious conscious withheld conscious disclosed. With the directive approach to art therapy the therapist establishes largely a
THE MULTI INPUT-MULTI OUTPUT STATE SPACE AVERAGE MODEL OF KY BUCK-BOOST CONVERTER INCLUDING ALL OF THE SYSTEM PARAMETERS

In this paper a complete multi input-multi output state-space average model for the KY buck-boost converter is presented. The introduced model includes the most of the regulator’s parameters and uncertainties. In modeling, the load current is assumed to be unknown, and it is assumed that the inductor, capacitor, diode and regulator active switches are non ideal and have a resistance in conduction condition. Some other non ideal effects look like voltage drop of conduction mode of the diode and active switches are also considered. After presenting the complete model, the KY buck-boost converter Benchmark circuit is simulated in PSpice and its results are compared with our model simulation results in MATLAB SIMULINK. The results show the merit of our model.
The Information Systems Artifact: A Conceptualization Based on General Systems Theory

Passionate debates regarding the defining characteristic of the “IT artifact” continue. Such debates, and also the lack of explicit consideration of the “information” element in the IT artifact, motivate us to propose a revised conception, drawing upon concepts from General Systems Theory (GST). Following a number of scholars [39], we name our reconceptualization as an IS artifact, which aims to provide a contemporary view of an IS that could accommodate the changing nature of both society and technology while at the same time maintain a clear definition of what we mean by an IS.
Modeling and Verification of Complex Network Attacks Using an Actor-Based Language *

Increasing use of networks and their complexity have complicated the task of security analysis. Accordingly, automatic verification approaches have received more attention recently. In this paper, we showed how an attacker might combine simple attacks to construct a complex multiphase attack. We use Rebeca language to model the network of hosts and its model checker to find counter-examples as violation of security policies. Some simple attacks have been modeled in previous works in this area. First, we show these simple attacks in our model and then verify the model to find more complex attacks. These complex attacks may include some simpler attacks as their steps. We choose Rebeca because of its powerful yet simple actor-based paradigm in modeling concurrent and distributed systems.
Designing Random Allocation Mechanisms: Theory and Applications

Randomization is commonplace in everyday resource allocation. We generalize the theory of randomized assignment to accommodate multi-unit allocations and various real-world constraints, such as group-specific quotas ("controlled choice") in school choice and house allocation, and scheduling and curriculum constraints in course allocation. We develop new mechanisms that are ex ante efficient and fair in these environments, and that incorporate certain non-additive substitutable preferences. We also develop a "utility guarantee" technique that limits ex post unfairness in random allocations, supplementing the ex ante fairness promoted by randomization. This can be applied to multi-unit assignment problems and certain two-sided matching problems. (JEL C78, D82)
An Adaptive Discontinuous Galerkin Technique with an Orthogonal Basis Applied to Compressible Flow Problems

We present a high-order formulation for solving hyperbolic conservation laws using the discontinuous Galerkin method (DGM). We introduce an orthogonal basis for the spatial discretization and use explicit Runge--Kutta time discretization. Some results of higher order adaptive refinement calculations are presented for inviscid Rayleigh--Taylor flow instability and shock reflection problems. The adaptive procedure uses an error indicator that concentrates the computational effort near discontinuities.
M4D4: a Logical Framework to Support Alert Correlation in Intrusion Detection

Managing and supervising security in large networks has become a challenging task, as new threats and aws are being discovered on a daily basis. This requires an in depth and up-to-date knowledge of the context in which security-related events occur. Several tools have been proposed to support security operators in this task, each of which focuses on some specic aspects of the monitoring. Many alarm fusion and correlation approaches have also been investigated. However, most of these approaches suer from two major drawbacks. First, they only take advantage of the information found in alerts, which is not sucient to achieve the goals of alert correlation, that is to say to reduce the overall amount of alerts, while enhancing their semantics. Second, these techniques have been designed on an ad-hoc basis and lack a shared data model that would allow them to reason about events in a cooperative way. In this paper, we propose a federative data model for security systems to query and assert knowledge about security incidents and the context in which they occur. This model constitutes a consistent and formal ground to represent information that is required to reason about complementary evidences, in order to conrm or invalidate alerts raised by intrusion detection systems.
Content Based Image Retrieval by Combining Features and Query-By-Sketch

This paper reports an approach to improve content-based image retrieval systems. Most current systems are based on a single technique for feature extraction and similarity search. Each technique has its advantages and drawbacks concerning the result quality. Usually they cover one or two certain features of the image, e.g. histograms or shape information. To overcome these restrictions a flexible framework is proposed, capable of combining several different features in a single retrieval system. This system allows an administrator to build a repository managing different feature vectors. A user searching through this repository defines and weights these features according to his needs in the query. It concludes that a combined retrieval can be used much more widely than a highly specialized one and the use of query-by-sketch or -example combined with semantic information (e.g. keywords) could enhance the result quality.
An Approach to Learning Research with a Wireless Sensor Network in an Outdoor Setting

Automated collection of environmental data may be accomplished with wireless sensor networks (WSNs). In this paper, a general discussion of WSNs is given for the gathering of data for educational research. WSNs have the capability to enhance the scope of a researcher to include multiple streams of data: environmental, location, cyberdata, video, and RFID. The location of data stored in a database can allow reconstruction of the learning activity for the evaluation of significance at a later time. A brief overview of the technology forms the basis of an exploration of a setting used for outdoor learning.
Recommendations Regarding Quantitation in M-Mode Echocardiography: Results of a Survey of Echocardiographic Measurements

SUMMARY Four hundred M-mode echocardiographic surveys were distributed to determine interobserver variability in M-mode echocardiographic measurements. This was done with a view toward examining the need and determining the criteria for standardization of measurement.Each survey consisted of five M-mode echocardiograms with a calibration marker, measured by the survey participants anonymously. The echoes were judged of adequate quality for measurement of structures. Seventy-six of the 400 (19%) were returned, allowing comparison of interobserver variability as well as examination of the measurement criteria which were used.Mean measurements and percent uncertainty were derived for each structure for each criterion of measurement. For example, for the aorta, 33% of examiners measured the aorta as an outer/inner or leading edge dimension, and 20% measured it as an outer/outer dimension. The percent uncertainty for the measurement (1.97 SD divided by the mean) showed a mean of 13.8% for the 25 packets of five echoes measured using the former criteria and 24.2% using the latter criteria.For ventricular chamber and cavity measurements, almost one-half of the examiners used the peak of the QRS and one-half of the examiners used the onset of the QRS for determining end-diastole. Estimates of the percent of measurement uncertainty for the septum, posterior wall and left ventricular cavity dimension in this study were 10-25%. They were much higher (40-70%) for the right ventricular cavity and right ventricular anterior wall. The survey shows significant interobserver and interlaboratory variation in measurement when examining the same echoes and indicates a need for ongoing education, quality control and standardization of measurement criteria. Recommendations for new criteria for measurement of M-mode echocardiograms are offered.
Effect of Device Layout on the Stability of RF MOSFETs

<? Pub Dtl? >In this paper, the stability of RF MOSFETs is investigated in terms of the stability-factor (<formula formulatype="inline"><tex Notation="TeX">$k$</tex> </formula>-factor) for various layout schemes and device dimensions based on two different RFCMOS technologies. To systematically analyze the effect of small-signal device model parameters on RF MOSFET stability, the expression for <formula formulatype="inline"><tex Notation="TeX">$k$</tex></formula>-factor is derived as a function of the small-signal model parameters of RF MOSFETs. Based on the expression, the effect of small-signal model parameters on the stability of RF MOSFETs is explored along with its bias dependence. In addition, the effect of wiring schemes, number of gate fingers, gate finger pitch, and gate length is examined based on various device structures. It is shown that the transconductance and capacitances are the dominant device parameters to determine the stability of RF MOSFETs. The result also indicates that the stability of RF MOSFETs is strongly affected by the details of layout scheme and lateral dimension. Additionally, it was found that there is a tradeoff between device stability and speed. This study is expected to serve a guideline for the device design and optimization for stable operation of RF MOSFETs and circuits based on them.