Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutating the Conserved Q-loop Glutamine 1291 Selectively Disrupts Adenylate Kinase-dependent Channel Gating of the ATP-binding Cassette (ABC) Adenylate Kinase Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) and Reduces Channel Function in Primary Human Airway Epithelia*

Background: Cystic fibrosis transmembrane conductance regulator (CFTR) channels have ATPase and adenylate kinase activity. Results: Mutating Gln-1291 disrupts adenylate kinase- but not ATPase-dependent gating, and it reduces channel activity in airway epithelia. Conclusion: Normal CFTR function in airway epithelia may depend on its adenylate kinase activity. Significance: Adenylate kinase activity is important for the function of an ATP-binding cassette transporter. The ATP-binding cassette (ABC) transporter cystic fibrosis transmembrane conductance regulator (CFTR) and two other non-membrane-bound ABC proteins, Rad50 and a structural maintenance of chromosome (SMC) protein, exhibit adenylate kinase activity in the presence of physiologic concentrations of ATP and AMP or ADP (ATP + AMP ⇆ 2 ADP). The crystal structure of the nucleotide-binding domain of an SMC protein in complex with the adenylate kinase bisubstrate inhibitor P1,P5-di(adenosine-5′) pentaphosphate (Ap5A) suggests that AMP binds to the conserved Q-loop glutamine during the adenylate kinase reaction. Therefore, we hypothesized that mutating the corresponding residue in CFTR, Gln-1291, selectively disrupts adenylate kinase-dependent channel gating at physiologic nucleotide concentrations. We found that substituting Gln-1291 with bulky side-chain amino acids abolished the effects of Ap5A, AMP, and adenosine 5′-monophosphoramidate on CFTR channel function. 8-Azidoadenosine 5′-monophosphate photolabeling of the AMP-binding site and adenylate kinase activity were disrupted in Q1291F CFTR. The Gln-1291 mutations did not alter the potency of ATP at stimulating current or ATP-dependent gating when ATP was the only nucleotide present. However, when physiologic concentrations of ADP and AMP were added, adenylate kinase-deficient Q1291F channels opened significantly less than wild type. Consistent with this result, we found that Q1291F CFTR displayed significantly reduced Cl− channel function in well differentiated primary human airway epithelia. These results indicate that a highly conserved residue of an ABC transporter plays an important role in adenylate kinase-dependent CFTR gating. Furthermore, the results suggest that adenylate kinase activity is important for normal CFTR channel function in airway epithelia.
Buon appetito: recommending personalized menus

This paper deals with the problem of menu recommendation, namely recommending menus that a person is likely to consume at a particular restaurant. We mine restaurant reviews to extract food words, we use sentiment analysis applied to each sentence in order to compute the individual food preferences. Then we extract frequent combination of dishes using a variation of the Apriori algorithm. Finally, we propose several recommender systems to provide suggestions of food items or entire menus, i.e. sets of dishes.
Distributed Global Output-Feedback Control for a Class of Euler–Lagrange Systems

This paper investigates the distributed tracking control problem for a class of Euler–Lagrange multiagent systems when the agents can only measure the positions. In this case, the lack of the separation principle and the strong nonlinearity in unmeasurable states pose severe technical challenges to global output-feedback control design. To overcome these difficulties, a global nonsingular coordinate transformation matrix in the upper triangular form is first proposed such that the nonlinear dynamic model can be partially linearized with respect to the unmeasurable states. And, a new type of velocity observers is designed to estimate the unmeasurable velocities for each system. Then, based on the outputs of the velocity observers, we propose distributed control laws that enable the coordinated tracking control system to achieve uniform global exponential stability. Both theoretical analysis and numerical simulations are presented to validate the effectiveness of the proposed control scheme.
Automatic Human Face Detection for a Distributed Video Security System

This paper∗ presents a home video security system architecture, which employs pseudo real-time human face detection and recognition techniques for automatic person identification. In this system architecture, the individual processing steps, e.g. face detection and recognition, take place at different locations in the home network. The facial information conveyed in the network is encoded using MPEG-4 coding techniques to enable low bit-rate transmission at low cost within a home environment. In this paper, we primarily focus on the face detection part of the system. We use a combination of coding and analyzing techniques giving direct facial properties to perform face detection. The processing is divided into the following steps: (1) skin-color segmentation, (2) histogram analysis for facial feature detection, and (3) probability-based confidence value evaluation of facial features. The experimental results show that our approach of face detection offers near real-time processing speed with good detection capability and sufficiently reduces the video transmission cost over the network. Keywords—Home network; distributed system; video security; surveillance; face detection; MPEG-4; facial feature.
Implicit dynamic frames

An important, challenging problem in the verification of imperative programs with shared, mutable state is the frame problem in the presence of data abstraction. That is, one must be able to specify and verify upper bounds on the set of memory locations a method can read and write without exposing that method's implementation. Separation logic is now widely considered the most promising solution to this problem. However, unlike conventional verification approaches, separation logic assertions cannot mention heap-dependent expressions from the host programming language, such as method calls familiar to many developers. Moreover, separation logic-based verifiers are often based on symbolic execution. These symbolic execution-based verifiers typically do not support non-separating conjunction, and some of them rely on the developer to explicitly fold and unfold predicate definitions. Furthermore, several researchers have wondered whether it is possible to use verification condition generation and standard first-order provers instead of symbolic execution to automatically verify conformance with a separation logic specification. In this article, we propose a variant of separation logic called implicit dynamic frames that supports heap-dependent expressions inside assertions. Conformance with an implicit dynamic frames specification can be checked by proving the validity of a number of first-order verification conditions. To show that these verification conditions can be discharged automatically by standard first-order provers, we have implemented our approach in a verifier prototype and have used this prototype to verify several challenging examples from related work. Our prototype automatically folds and unfolds predicate definitions, as required, during the proof and can reason about non-separating conjunction which is used in the specifications of some of these examples. Finally, we prove the soundness of the approach.
UNDERSTANDING HUMAN ERROR IN CONTEXT: APPROACHES TO SUPPORT INTERACTION DESIGN USING AIR ACCIDENT REPORTS

Producing a deeper understanding of the ways in which human operators and technical systems have failed to collaborate in the past is one of the main sources of insight for designing safer systems. Accident reports are a vital source of information for interaction designers – by providing detail about how design oversights may relate to human errors. Using such information requires a complex reasoning process to understand the accident sequence and interpret the facts available. This paper explores ways in which to gain a deeper understanding of the underlying reasons for human error from accident reports, in order to identify interaction breakdowns between operators and interfaces. It demonstrates an approach for examining contextual information of human error and deriving design ideas through an informal analysis. Having re-examined the Cali Air accident report in depth (Aeronautica Civil, 1996; Kaiser, 1996; Simmon, 1998), a more comprehensive understanding of the design problem space could be gained by relating a detailed understanding of the accident to design options. Moreover, the information available was captured in an accessible format to inform interaction design more effectively.
SiteFinding-PCR: a simple and efficient PCR method for chromosome walking

In this paper, we present a novel PCR method, termed SiteFinding-PCR, for gene or chromosome walking. The PCR was primed by a SiteFinder at a low temperature, and then the target molecules were amplified exponentially with gene-specific and SiteFinder primers, and screened out by another gene-specific primer and a vector primer. However, non-target molecules could not be amplified exponentially owing to the suppression effect of stem–loop structure and could not be screened out. This simple method proved to be efficient, reliable, inexpensive and time-saving, and may be suitable for the molecules for which gene-specific primers are available. More importantly, large DNA fragments can be obtained easily using this method. To demonstrate the feasibility and efficiency of SiteFinding-PCR, we employed this method to do chromosome walking and obtained 16 positive results from 17 samples.
Schizophrenia and theory of mind

We suspect that people have an everyday theory of mind because they explain and frequently talk about the behaviour of others and themselves in terms of beliefs and desires. Having a theory of mind means that we believe that other people have minds like ours and that we understand the behaviour of these others in terms of the contents of their minds: their knowledge, beliefs and desires. But how can we demonstrate experimentally that people are using their theory of mind to predict the behaviour of others. This problem is particularly acute in the case of animals or young human children when they do not have language. Dennett (1978) discussing Premack & Woodruff's (1978) seminal paper ‘Does the chimpanzee have a theory of mind? ’, suggested that the use of false beliefs to explain behaviour would provide convincing evidence. When their belief is true (i.e. corresponds to the actual state of the world) we can explain peoples' behaviour on the basis of the state of the world without needing to know about their beliefs. This ambiguity does not arise when the belief is false. The first experiment to use this approach was published by Wimmer & Perner (1983). They showed that at around 4 years of age a child knows that Maxi will look for his chocolates where Maxi believes them to be, even though the child knows that this belief is false because he has seen Maxi's mother moving the chocolates. In the English-speaking world the task involving Maxi and the chocolates has become the Sally-Anne task (see this issue, Lee et al. 2004).
High-performance priority queues for parallel crawlers

Large scale data centers for crawlers are able to maintain a very large number of active http connections in order to download as fast as possible the usually huge number of web pages from given sections of the WWW. This generates a continuous stream of new URLs of documents to be downloaded and it is clear that the associated work-load can only be served efficiently with proper parallel computing techniques. The incoming new URLs have to be organized by a priority measure in order to download the most relevant documents first. Efficiently managing them along with other synchronization issues such as URLs downloaded by different processing nodes forming a cluster of computers are the matters of this paper. We propose efficient and scalable strategies which consider intra-node multi-core multi-threading on an inter-nodes distributed memory environment, including efficient use of secondary memory.
Paracrine Molecules of Mesenchymal Stem Cells for Hematopoietic Stem Cell Niche

Hematopoietic stem cells (HSCs) and mesenchymal stem cells (MSCs) are both adult stem cells residing in the bone marrow. MSCs interact with HSCs, they stimulate and enhance the proliferation of HSCs by secreting regulatory molecules and cytokines, providing a specialized microenvironment for controlling the process of hematopoiesis. In this paper we discuss how MSCs contribute to HSC niche, maintain the stemness and proliferation of HSCs, and support HSC transplantation.
Draft Genome Sequence of Microbacterium sp. Strain CH12i, Isolated from Shallow Groundwater in Cape Hallett, Antarctica

ABSTRACT The Antarctic continent is largely covered by an expansive ice sheet, but it harbors diverse terrestrial and aquatic habitats in the coastal ice-free continental margins. Here we present the draft genome of Microbacterium sp. CH12i, which was isolated from hypersaline, alkaline, and nutrient-rich groundwater from Cape Hallett, northern Victoria Land, Antarctica.
Learning Reward Uncertainty in the Basal Ganglia

Learning the reliability of different sources of rewards is critical for making optimal choices. However, despite the existence of detailed theory describing how the expected reward is learned in the basal ganglia, it is not known how reward uncertainty is estimated in these circuits. This paper presents a class of models that encode both the mean reward and the spread of the rewards, the former in the difference between the synaptic weights of D1 and D2 neurons, and the latter in their sum. In the models, the tendency to seek (or avoid) options with variable reward can be controlled by increasing (or decreasing) the tonic level of dopamine. The models are consistent with the physiology of and synaptic plasticity in the basal ganglia, they explain the effects of dopaminergic manipulations on choices involving risks, and they make multiple experimental predictions.
LOCKSMITH: Practical static race detection for C

Locksmith is a static analysis tool for automatically detecting data races in C programs. In this article, we describe each of Locksmith's component analyses precisely, and present systematic measurements that isolate interesting trade-offs between precision and efficiency in each analysis. Using a benchmark suite comprising stand-alone applications and Linux device drivers totaling more than 200,000 lines of code, we found that a simple no-worklist strategy yielded the most efficient interprocedural dataflow analysis; that our sharing analysis was able to determine that most locations are thread-local, and therefore need not be protected by locks; that modeling C structs and void pointers precisely is key to both precision and efficiency; and that context sensitivity yields a much more precise analysis, though with decreased scalability. Put together, our results illuminate some of the key engineering challenges in building Locksmith and data race detection analyses in particular, and constraint-based program analyses in general.
Partnership dynamics and strain competition

Models of epidemic spread that include partnership dynamics within the host population have demonstrated that finite length partnerships can limit the spread of pathogens. Here the influence of partnerships on strain competition is investigated. A simple epidemic and partnership formation model is used to demonstrate that, in contrast to standard epidemiological models, the constraint introduced by partnerships can influence the success of pathogen strains. When partnership turnover is slow, strains must have a long infectious period in order to persist, a requirement of much less importance when partnership turnover is rapid. By introducing a tradeoff between transmission rate and infectious period it is shown that populations with different behaviours can favour different strains. Implications for control measures based on behavioural modifications are discussed, with such measures perhaps leading to the emergence of new strains. r 2006 Elsevier Ltd. All rights reserved.
Fundamental matrix for cameras with radial distortion

When deploying a heterogeneous camera network or when we use cheap zoom cameras like in cell-phones, it is not practical, if not impossible to off-line calibrate the radial distortion of each camera using reference objects. It is rather desirable to have an automatic procedure without strong assumptions about the scene. In this paper, we present a new algorithm for estimating the epipolar geometry of two views where the two views can be radially distorted with different distortion factors. It is the first algorithm in the literature solving the case of different distortion in the left and right view linearly and without assuming the existence of lines in the scene. Points in the projective plane are lifted to a quadric in three-dimensional projective space. A radial distortion of the projective plane results to a matrix transformation in the space of lifted coordinates. The new epipolar constraint depends linearly on a 4 /spl times/ 4 radial fundamental matrix which has 9 degrees of freedom. A complete algorithm is presented and tested on real imagery.
Texture Classification using Histogram Equalization and the Lempel-Ziv-Welch Algorithm

Resumo—Este trabalho apresenta um novo método de classi-ficação de texturas usando equalização de histograma e o algo-ritmo Lempel-Ziv-Welch (LZW). Após equalização, cada amos-tra de textura é codificada pelo LZW usando dicionários pré-construídos e atribuída à classe cujos dicionários minimizam a taxa de codificação. Na avaliação experimental, o método atingiu precisão de 100%. Abstract— This paper presents a new texture classification method using histogram equalization and the Lempel-Ziv-Welch (LZW) compression algorithm. After equalization, each texture sample is encoded by LZW using pre-constructed dictionaries and assigned to the class whose dictionaries minimize the coding rate. In the empirical evaluation, the classifier achieved 100% accuracy.
Feature-aligned shape texturing

The essence of a 3D shape can often be well captured by its salient feature curves. In this paper, we explore the use of salient curves in synthesizing intuitive, shape-revealing textures on surfaces. Our texture synthesis is guided by two principles: matching the direction of the texture patterns to those of the salient curves, and aligning the prominent feature lines in the texture to the salient curves exactly. We have observed that textures synthesized by these principles not only fit naturally to the surface geometry, but also visually reveal, even reinforce, the shape's essential characteristics. We call these feature-aligned shape texturing. Our technique is fully automatic, and introduces two novel technical components in vector-field-guided texture synthesis: an algorithm that orients the salient curves on a surface for constrained vector field generation, and a feature-to-feature texture optimization.
Social Big Data Analysis of Information Spread and Perceived Infection Risk During the 2015 Middle East Respiratory Syndrome Outbreak in South Korea

We investigated online diffusion of information, spread of fear, and perceived risk of infection to Middle East Respiratory Syndrome (MERS) as cases of MERS spread rapidly and dozens of fatalities occurred in South Korea in May-June of 2015. This study retrieved 8,671,695 MERS-related online documents from May 20 to June 18, 2015, from 171 Korean online channels and analyzed such documents by using multilevel models and data mining with Apriori algorithm association analysis. We used R software (version 3.2.1) for the association analysis data mining and visualization. Buzz with negative emotions (i.e., anxiety or fear) was more prevalent in online discussion boards, Twitter, and online cafes than news sites and blogs. News buzz (b = 0.21, p < 0.001), but not rumor buzz (b = 0.06, p = 0.308), was associated with positive MERS emotions (i.e., being calm or composed). The mention of eating immunity-boosting food in the news led to a 94 percent chance of a positive MERS emotion and that such a chance of showing a positive emotion was 4.75 times higher than that without such a mention (support of 0.001, confidence of 0.94, and lift of 4.75). Even with the same precautionary messages that were disseminated, they yielded the opposite emotional reactions to people depending on the channel through which the messages were communicated. In the face of a novel and highly contagious disease such as MERS, the government must deploy a response system that includes provision and dissemination of reliable information and inhibits online diffusion of false information.
Crowdsourcing Real World Human-Robot Dialog and Teamwork through Online Multiplayer Games

100 AI MAGAZINE We envision the need for robots to be not only functional, but adaptable, robust to the diversity of human behaviors and speech patterns, and capable of acting in a both task and socially appropriate manner. Natural and diverse human-robot interaction (HRI) of this kind has been a long-standing goal for robotics research, and a broad range of approaches have been proposed for the development of robots that support diverse interactions. Among proposed techniques, variants that are dependent on hand-coded rule sets and probabilistic single-task policy learning methods have proven to be too brittle for interactive applications, failing to generalize over the diversity of possible inputs. Such systems typically force the user to adapt their method of interaction to fit the coded requirements of the robot. A different approach to creating more humanlike robotic systems has focused on imitating human cognitive processes by developing large scale cognitive architectures that support many modalities and interaction styles. While such systems have been shown to successfully support a broad range of interactions, they rely heavily on precoded data. For example, dialogue responses are typically limited to only one or two dozen phrases, which pales in comparison to the diversity of human speech. We believe that in order for robotic systems to become a truly ubiquitous technology, robots must make sense of natural human behavior and engage with humans in a more humanlike way. Robots must become more like humans instead of forcing humans to be more like robots. Much of human knowledge about the appropriateness of behavior, in terms of both speech and actions, comes from our personal experiences and our observations of others. Common