Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Forward Error Correcting Algorithms to Positioning Systems

The indoor localisation of a mobile target is an important issue in many robotics, automation, virtual reality and pervasive computing environments. The most sophisticated method for indoor localisation is based on processing the images captured by cameras that are placed on the target in order to recognise familiar landmarks and their distance (Jin et al, 2004); (Porta & Krose, 2006); (Clerentin et al, 2005); (Tovar et al, 2006); (Se et al, 2002). Image processing in conjunction with other localisation approaches described below (Borenstein et al., 1996) is very popular in autonomous robotics applications making feasible the familiarisation of a robot with unknown areas. Stochastic processing is often applied in this case in order to evaluate an estimated position. Nevertheless, expensive sensors and processing units are required in order to support the high computational complexity of this approach. More popular lower cost approaches are based either on measuring the round trip time of a reflected wave or the strength of a signal. In the first case, the cost is higher if optical or laser scanning is employed since very short time intervals have to be measured with high precision (Miura et al, 2006); (Clerentin et al, 2005); (Victorino et al, 2003); (Arras et al, 2001). Ultrasonic signals can offer a lower cost alternative to this approach since the sonar waves travel with much lower speed than light but their main drawback is that this type of signal is not directional enough (Smith & Zografos, 2005); (Minami et al, 2004); (Tardos et al, 2002); (Bicho et al, 2000); (Baskent & Barshan, 1999). Moreover, it is more difficult to isolate the sonar transmitter from the receiver in order to reassure that only the reflected signal will be received. Measuring the signal strength of multiple transmitters (Ladd et al, 2005); (Flora et al, 2005) can also provide an indication about the target position. This technique has already been adopted in cellular phone, Wireless Local Access Network (WLAN) or Bluetooth applications. Although wide areas can be covered in these networks, the distance estimation error is usually higher than half a meter. Even magnetic fields have been used for the accurate non-contact control of tools and medical instruments (Schlageter et al, 2001); (Kosel et al, 2005). The distance measured in this approach cannot be longer than some tenths of centimetres although a distance estimation of up to 10m has been reported in (Prigge & How, 2004). O pe n A cc es s D at ab as e w w w . ite ch on lin e. co m
Exploring Antismoking Ads: Appeals, Themes, and Consequences

In this study we seek a descriptive understanding of antismoking television advertising in light of the problem cigarette consumption poses for society today. We establish relationships between ad characteristics and whether ads have a youth or adult orientation, based on a content analysis of 197 antismoking television advertisements produced between 1991 and 1999. The study finds that youth-oriented ads have youth characters, sociability, and humor as common appeals, and social and short-term consequences. In contrast, adult-oriented ads relied on fear appeals and long-term, health-related consequences.
GEOMETRIC APPLICATIONS OF WASSERSTEIN DISTANCE

The second lecture will present the notion of the lower curvature bound [3] for a metric measure spaces. Some basic concepts of metric geometry (length spaces, geodesics, geodesic spaces) will be recalled. A kind of a generalization of Wasserstein distance, namely the Wasserstein-Gromov distance of metric measure spaces and the relative entropy of measures will be the main definitions that will be presented.
Distributed dialogue management for smart terminal devices

Mobile devices, such as smartphones and personal digital assistants, can be used to implement efficient speech-based and multimodal interfaces. Most of the systems are serverbased, and there is a need to distribute the dialogue management tasks between the terminal devices and the server. Since the technologies are not mature and the platforms are constantly changing, approaches that support generic and reusable components are needed. We describe a model where the tasks of the dialogue management are divided into two parts. The server handles the overall coordination of the dialogue by generating dialogue task descriptions. Smart terminal devices realize the low-level decisions by executing individual dialogue tasks. A prototype of multimodal dialogue application using the model is presented. It has two different user interface realizations using standard telephony equipment and smartphones.
Maximum Margin Clustering Made Practical

Motivated by the success of large margin methods in supervised learning, maximum margin clustering (MMC) is a recent approach that aims at extending large margin methods to unsupervised learning. However, its optimization problem is nonconvex and existing MMC methods all rely on reformulating and relaxing the nonconvex optimization problem as semidefinite programs (SDP). Though SDP is convex and standard solvers are available, they are computationally very expensive and only small data sets can be handled. To make MMC more practical, we avoid SDP relaxations and propose in this paper an efficient approach that performs alternating optimization directly on the original nonconvex problem. A key step to avoid premature convergence in the resultant iterative procedure is to change the loss function from the hinge loss to the Laplacian/square loss so that overconfident predictions are penalized. Experiments on a number of synthetic and real-world data sets demonstrate that the proposed approach is more accurate, much faster (hundreds to tens of thousands of times faster), and can handle data sets that are hundreds of times larger than the largest data set reported in the MMC literature.
Structure and Mechanism of the Glycerol-3-Phosphate Transporter from Escherichia coli

The major facilitator superfamily represents the largest group of secondary membrane transporters in the cell. Here we report the 3.3 angstrom resolution structure of a member of this superfamily, GlpT, which transports glycerol-3-phosphate into the cytoplasm and inorganic phosphate into the periplasm. The amino- and carboxyl-terminal halves of the protein exhibit a pseudo two-fold symmetry. Closed off to the periplasm, a centrally located substrate-translocation pore contains two arginines at its closed end, which comprise the substrate-binding site. Upon substrate binding, the protein adopts a more compact conformation. We propose that GlpT operates by a single–binding site, alternating-access mechanism through a rocker-switch type of movement.
miR-363-3p inhibits tumor growth by targeting PCNA in lung adenocarcinoma

Increasing evidence suggests that microRNAs play key roles in lung cancer. Our previous study demonstrated that microRNA 363-3p (miR-363-3p) is downregulated in lung cancer tissues. In this study, we demonstrated that overexpression of miR-363-3p inhibits the proliferation and colony formation of A549 and H441 cells, while silencing of miR-363-3p has the converse effects. The anti-oncogenic function of miR-363-3p was verified in a mouse tumor xenograft model. Furthermore, cell cycle analysis showed miR-363-3p can induce S phase arrest by downregulating Cyclin-D1 and upregulating Cyclin-dependent kinase-2 in lung adenocarcinoma cells. Additionally, miR-363-3p enhances cell apoptosis, whereas miR-363-3p inhibitor prevents apoptosis and leads to downregulation of Bax and Bak expression. The anti-proliferative function of miR-363-3p toward lung cancer cells may be explained by its ability to inhibit the activation of the mTOR and ERK signaling pathways. Using target prediction software and luciferase reporter assays, we identified PCNA as a specific target of miR-363-3p. miR-363-3p can decreased the accumulation of endogenous PCNA in lung adenocarcinoma cells. Moreover, exogenous expression of PCNA relieve the inhibition of miR-363-3p on cell proliferation, colony formation and mTOR and ERK signaling pathways. Taken together, our data indicate that miR-363-3p suppresses tumor growth by targeting PCNA in lung adenocarcinoma.
A 2b Adenosine Receptors Regulate the Mucus Clearance Component of the Lung's Innate Defense System Materials and Methods

Adenosine (ADO) signaling is altered in both asthma and chronic obstructive pulmonary disease, and the A 2B adenosine receptor (A 2B-R) may drive pulmonary inflammation. Accordingly, it has been proposed that specific inhibition of the A 2B-R could treat inflamma-tory lung diseases. However, stimulation of the cystic fibrosis trans-membrane conductance regulator (CFTR) by ADO may be crucial in permitting the superficial epithelium to maintain airway surface liquid (ASL) volume, which is required to ensure hydrated and clearable mucus. Our goal was to determine which ADO receptor (ADO-R) underlies ASL volume regulation in bronchial epithelia. We used PCR techniques to determine ADO-R expression in bronchial epithelia and used nasal potential difference measurements, Ussing chambers studies, and XZ-confocal microscopy to look at Cl-secretion and ASL volume regulation. The A 2B-R was the most highly expressed ADO-R in donor specimens of human bronchial epithelia, and inhibition of ADO-R in vivo prevented activation of CFTR. A 2B-R was the only ADO-R detected in cultured human bronchial epithelial cells and inhibition of this receptor with specific A 2B-R antagonists resulted in ASL height collapse and a failure to effect ASL height homeostasis. Removal of ADO with ADO deaminase and replacement with 59N-ethylcarboxamide adenosine resulted in dose-dependent changes in ASL height, and suggested that the cell surface (ADO) may be in excess of 1 mM, which is sufficient to activate A 2B-R. A 2B-R are required for ASL volume homeostasis in human airways, and therapies directed at inhibiting A 2B-R may lead to a cystic fibrosis–like phenotype with depleted ASL volume and mucus stasis. Altered adenosine (ADO) signaling has been associated with both asthma and chronic obstructive pulmonary disease (COPD) (1, 2). For example, inhaled ADO causes bronchoconstriction in individuals with asthma despite having little effect on normal subjects (3), and adenosine receptor (ADO-R) expression is altered in COPD (4). ADO is formed in airway lumens as a breakdown product of ATP (5, 6), and can signal through specific ADO receptors before being broken down by adenosine deaminase (ADA) (7, 8). A 1 and A 3 receptors signal through G i/o proteins to inhibit adenylyl cyclase, and in some cases, to activate Ca 21 , while A 2A and A 2B receptors signal through G s to activate adenylyl cyclase and raise cAMP (7). ADO can stimulate A 2B receptors (A 2B-R) to induce cytokine release from mast cells, smooth muscle, and epithelia (9). Further, ADA-null …
HO2: A new feature for multi-agent event detection and recognition

In this paper, we present a new feature to model a class of events that consist of complex interactions among multiple entities captured by tracks and inter-object relationships over space and time. Existing approaches represent these events using features that measure only pairwise relationships between entities at a time, such as relative distance and relative speed. Due to the limitations of the pairwise entity relationship descriptors, this class of events is mainly defined and recognized using rule-based approach. The new feature, Histogram of Oriented Occurrences (HO2), captures the interactions of all entities of interests in terms of configurations over space and time. HO2 features encapsulate entity tracks, inter-object relationships and the context of the environment into a spatial distribution that characterizes the corresponding event. HO2 feature is a compact and structured descriptor for capturing multi-object relationships. We demonstrate its value in complex event detection and recognition using standard statistical clustering and classification techniques.
Semantics and the Metaphysics of Belief

Apertures through each face of a planetary rotor, volutes for low loss delivery and collection of fluid to and from the working volumes of a planetary rotary pump, compressor, or turbine, and zero clearance seals by using continuous carbon fiber reinforced polyetheretherketone (PEEK) or other self-lubricating materials significantly improve the volumetric flow rate of such rotary pumps compressors or turbines.By establishing a means to vent each working volume to an intake or exhaust port at arbitrary rotor positions, apertures linking working volumes to intake or exhaust ports allows each working volume of a multilobe planetary rotary pump to function independently near peak volumetric efficiency. An additional means to improve the performance of planetary rotary pumps has been established by using scroll-like volutes which collect and deliver the exhaust and intake flow for each working volume in a manner which reduces the fluid dynamic loss associated with conventional sudden expansions and contractions found at the inlet and exit of a plenum. To minimize leakage between the separate working volumes and improve performance, self lubricated continuous carbon fiber reinforced polyetheretherketone seals are employed for components in high speed sliding contact. The continuous carbon fiber reinforced PEEK can withstand high sliding speeds, high temperatures with low wear and excellent foreign object impact resistance.
A straight-line-based vanishing point detection method for railway environmental images

In this paper, we present a method of estimating the vanishing point from the railway environment images. Vanishing point plays a very important role in the machine vision based railway-environment surveillance methods, e.g. estimating the pose of the camera, video segmentation and panorama. In the application of railway-environment surveillance, we most care about the vanishing point corresponding to the lines parallel to the rails. Based on the prior, we design a fast and effective method-Selected Line Segment Detector (SLSD) to detect the line segments corresponding to the scene-lines parallel to the rails, and then use a cross-iteration method to find the vanishing point in the railway environment images. We give both theoretical analysis and algorithm implementation. Our experimental results show the validation of the proposed method.
Evidence for Class-Specific Factors in Immunoglobulin Isotype Switching

Immunoglobulin class switch recombination (SR) occurs by a B cell–specific, intrachromosomal deletional process between switch regions. We have developed a plasmid-based transient transfection assay for SR to test for the presence of transacting switch activities. The plasmids are novel in that they lack a eukaryotic origin of DNA replication. The recombination activity of these switch substrates is restricted to a subset of B cell lines that support isotype switching on their endogenous loci and to mitogen-activated normal splenic B cells. The factors required for extrachromosomal plasmid recombination are constitutively expressed in proliferating splenic B cells and in B cell lines capable of inducibly undergoing immunoglobulin SR on their chromosomal genes. These studies suggest that mitogens that induce switching on the chromosome induce accessibility rather than switch recombinase activity. Finally, we provide evidence for two distinct switching activities which independently mediate μ→α and μ→γ3 SR.
Cloud enabled air quality detection, analysis and prediction - A smart city application for smart health

The work proposes a cloud based air quality detection system that analyzes the data for providing atmospheric quality to the user in real time. The data, collected through various gas sensors deployed outdoors in strategic locations across the city of Manipal, Karnataka is sent to the cloud via an adaptive interface that supports 2G/3G/4G infrastructure. Also, a live feed of Closed-circuit Television (CCTV) footage of some strategic locations of Manipal's road traffic is sent to the cloud for analysing the density of pollutants in air with respect to the road traffic. In addition to this, the database from the Regional Transport Office (RTO) and the Computerized Pollution Check Centres of Manipal provide a basis for a comparative analysis of the variances in the spectrum of emissions from vehicles and sensor-based data coming from strategic locations. This combination along with the knowledge of the geographic and industrial properties of the area will help analyse the data for finding patterns in air quality in a particular time interval. The proposed model will then be able to predict the air quality for future days. A web and mobile application interface will help the users to check and understand the air quality at their current location. The mobile application will also notify the user about severe toxicity. People with respiratory problems will be able to get personalized notifications for poor conditions.
Predicting Response Times of Applications in Virtualized Environments

We propose simple queueing models for predicting response times of applications executed in a cloud computing platform under the SaaS model. We assume that each application instance is executed within a virtual machine running on a computing node of a data-center, and that VMs running concurrently on the same node share fairly its capacity. Our main contribution is to explicitly take into account the different behaviors of the different classes of applications (interactive, CPU-intensive or permanent applications). We show that simple expressions of the mean processing times of applications can be obtained using standard results from queueing theory. Experiments on a real virtualized platform show that the mathematical models allow to predict response times accurately.
Mechanism design over discrete domains

Often, we wish to design incentive-compatible algorithms for settings in which the players' private information is drawn from discrete domains (e.g., integer values). Our main result is identifying discrete settings in which an algorithm can be made incentive-compatible iff the function it computes upholds a simple monotonicity constraint, known as weak-monotonicity. To the best of our knowledge, this is the first such characterization of incentive-compatibility in discrete domains (such characterizations were previously known only for inherently non-discrete domains, e.g., convex domains). We demonstrate the usefulness of this result by showing an application to the TCP-inspired congestion-control problem presented in [20].
Adaptation to Visuomotor Transformations: Consolidation, Interference, and Forgetting

The paradigm task A→task B→task A, which varies the time interval between task A and task B, has been used extensively to investigate the consolidation of motor memory. Consolidation is defined as resistance to retrograde interference (interference by task B on initial learning of task A). Consolidation has been demonstrated for simple skills, motor sequencing, and learning of force fields. In contrast, evidence to date suggests that visuomotor learning does not consolidate. We have shown previously that adaptation to a 30° screen-cursor rotation is faster and more complete on relearning 24 hr later. This improvement is prevented if a 30° counter-rotation is learned 5 min after the original rotation. Here, we sought to identify conditions under which rotation learning becomes resistant to interference by a counter-rotation. In experiment 1, we found that interference persists even when the counter-rotation is learned 24 hr after the initial rotation. In experiment 2, we removed potential anterograde interference (interference by task B on relearning of task A) by introducing washout blocks before all of the learning blocks. In contrast to experiment 1, we found resistance to interference (i.e., consolidation) when the counter-rotation was learned after 24 hr but not after 5 min. In experiment 3, we doubled the amount of initial rotation learning and found resistance to interference even after 5 min. Our results suggest that persistent interference is attributable to anterograde effects on memory retrieval. When anterograde effects are removed, rotation learning consolidates both over time and with increased initial training.
Designing and Implementing an Ambulatory Oncology Nursing Peer Preceptorship Program: Using Grounded Theory Research to Guide Program Development

Having enough staff to provide high-quality care to cancer patients will become a growing issue across Canada over the next decades. Statistical predictions indicate that both the number of new diagnoses and the prevalence of cancer will increase dramatically in the next two decades. When combining these trends with the simultaneous trend toward health human resource shortage in Canada, the urgency of assuring we have adequate staff to deliver cancer care becomes clear. This research study focuses directly on oncology nurses. Guided by the grounded theory methodology, this research study aims to formulate a strategic, proactive peer preceptorship program through a four-phased research process. The goal of this research is to develop a program that will support experienced staff members to fully implement their role as a preceptor to new staff, to facilitate effective knowledge transfer between experienced staff to the new staff members, and to assure new staff members are carefully transitioned and integrated into the complex ambulatory cancer care workplaces. In this article, the data from the first phase of the research project will be explored specifically as it relates to establishing the foundation for the development of a provincial ambulatory oncology nursing peer preceptorship program.
An Automatic Pedestrian Detection and Tracking Method: Based on MACH and Particle Filter

This paper introduces a pedestrian detecting and tracking approach. Correlation filters present the composite properties which have been successively used in target detection. Particle filter are combined to locate the targets in real-time. Our contribution is proposing a general algorithm that is able to detect and track pedestrians in clutter environments. We also create a different view pedestrian dataset. Experiments show our algorithm is comparative when there is block and occlusion in tracking.
Automatic tuning of hyperparameters for NMF-based face recognition system

In the paper, the NMF-based (non-negative matrix factorization) face recognition system is considered. An error rate made by such a system depends on the hyperparameters (for example, sparsity, a number of NMF components) which are usually determined experimentally. Typically, a large number of combinations of the hyperparameters is evaluated. Each evaluation involves substantial computational time. Recently, automatic procedures for tuning the hyperparameters have achieved a considerable success. They give a possibility to reduce a number of the system evaluations. In our study, we applied this approach to the NMF-based face recognition system. The results show that such tools can substantially reduce an overall computational complexity in comparison to random grid searching. They can also provide reliable information about the importance of the hyperparameters and their interactions.
Consecutive Interpreting and "AA+EA" Strategy

Based upon the theory of Cognitive Psychology,the practices of teaching and the experiments of Consecutive Interpreting,this study found out the students' Anxiety Mode(AM) and Exciting Mode(EM),two psychological modes which strongly affect Consecutive Interpreting.This study applied Anxiety Attention and Anxiety Adjustment to the students' Anxiety Mode and tried Exciting Attention and Exciting Adjustment to their Exciting Mode,thereby suggested an "AA + EA" strategy to deal with students' AM and EM in Consecutive Interpreting.