Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-Smoking Male Adolescents' Reactions to Cigarette Warnings

Background The U.S. Food and Drug Administration (FDA) is working to introduce new graphic warning labels for cigarette packages, the first change in cigarette warnings in more than 25 years. We sought to examine whether warnings discouraged participants from wanting to smoke and altered perceived likelihood of harms among adolescent males and whether these warning effects varied by age. Methods A national sample of 386 non-smoking American males ages 11–17 participated in an online experiment during fall 2010. We randomly assigned participants to view warnings using a 2×2 between-subjects design. The warnings described a harm of smoking (addiction or lung cancer) using text only or text plus an image used on European cigarette package warnings. Analyses tested whether age moderated the warnings' impact on risk perceptions and smoking motivations. Results The warnings discouraged most adolescents from wanting to smoke, but lung cancer warnings discouraged them more than addiction warnings did (60% vs. 34% were “very much” discouraged, p<.001). Including an image had no effect on discouragement. The warnings affected several beliefs about the harms from smoking, and age moderated these effects. Adolescents said addiction was easier to imagine and more likely to happen to them than lung cancer. They also believed that their true likelihood of experiencing any harm was lower than what an expert would say. Conclusions Our findings suggest that warnings focusing on lung cancer, rather than addiction, are more likely to discourage wanting to smoke among adolescent males and enhance their ability to imagine the harmful consequences of smoking. Including images on warnings had little effect on non-smoking male adolescents' discouragement or beliefs, though additional research on the effects of pictorial warnings for this at-risk population is needed as the FDA moves forward with developing new graphic labels.
Hierarchical backoff locks for nonuniform communication architectures

This paper identifies node affinity as an important property for scalable general-purpose locks. Nonuniform communication architectures (NUCA), for example CC-NUMA built from a few large nodes or from chip multiprocessors (CMP), have a lower penalty for reading data from a neighbor's cache than from a remote cache. Lock implementations that encourages handing over locks to neighbors will improve the lock handover time, as well as the access to the critical data guarded by the lock, but will also be vulnerable to starvation. We propose a set of simple software-based hierarchical backoff locks (HBO) that create node affinity in NUCA. A solution for lowering the risk of starvation is also suggested. The HBO locks are compared with other software-based lock implementations using simple benchmarks, and are shown to be very competitive for uncontested locks while being more than twice as fast for contended locks. An application study also demonstrates superior performance for applications with high lock contention and competitive performance for other programs.
Hierarchical control of flexible robots

A hierarchical control for flexible manipulators is presented in this paper. The equations of motion are derived using the miltibody system method. Exploiting the structure of the dynamic model, the control concept allows to combine any given joint level control for the gross motion of the manipulator with a decentralized linear control of the elastic deformation of each flexible link. In order to verify the control strategy proposed, a SCARA robot with one flexible link is considered.
Dynamization of the trapezoid method for planar point location (extended abstract)

We present a fully dynamic data structure for point location in a monotone subdivision, based on the trapezoid method. The operations supported are insertion and deletion of vertices and edges, and horizontal translation of vertices. Let n be the current number of vertices of the subdivision. Point location queries take O(log n) time, while updates take 0(log2 n) time. The space requirement is O(n log n). This is the first fully dynamic point location data structure for monotone subdivisions that achieves optimal query time.
Phytoextraction potential of water fern (Azolla pinnata) in the removal of a hazardous dye, methyl violet 2B: Artificial neural network modelling

ABSTRACT This study investigated the potential of Azolla pinnata (AP) in the removal of toxic methyl violet 2B (MV) dye wastewater using the phytoextraction approach with the inclusion of an Artificial Neural Network (ANN) modelling. Parameters examined included the effects of dye concentration, pH and plant dosage. The highest removal efficiency was 93% which was achieved at a plant dosage of 0.8 g (dye volume = 200 mL, initial pH = 6.0, initial dye concentration = 10 mg L−1). A significant decrease in relative frond number (RFN), a growth rate estimator, observed at a dye concentration of 20 mg L−1 MV indicated some toxicity, which coincided with the plant pigments studies where the chlorophyll a content was lower than the control. There were little differences in the plant pigment contents between the control and those in the presence of dye (5 to 15 mg L−1) indicating the tolerance of AP to MV at lower concentrations. A three-layer ANN model was optimized (6 neurons in the hidden layer) and successfully predicted the phytoextraction of MV (R = 0.9989, RMSE = 0.0098). In conclusion, AP proved to be a suitable plant that could be used for the phytoextraction of MV while the ANN modelling has shown to be a reliable method for the modelling of phytoextraction of MV using AP.
Subexponential parameterized algorithm for minimum fill-in

The Minimum Fill-in problem is to decide if a graph can be triangulated by adding at most k edges. Kaplan, Shamir, and Tarjan [FOCS 1994] have shown that the problem is solvable in time O(2O(k) + k2nm) on graphs with n vertices and m edges and thus is fixed parameter tractable. Here, we give the first subexponential parameterizedv algorithm solving Minimum Fill-in in time [EQUATION]. This substantially lowers the complexity of the problem. Techniques developed for Minimum Fill-in can be used to obtain subexponential parameterized algorithms for several related problems including Minimum Chain Completion, Chordal Graph Sandwich, and Triangulating Colored Graph.
Modeling of the Competitive Growth ofListeria monocytogenes and Lactococcus lactis in Vegetable Broth

ABSTRACT Current mathematical models used by food microbiologists do not address the issue of competitive growth in mixed cultures of bacteria. We developed a mathematical model which consists of a system of nonlinear differential equations describing the growth of competing bacterial cell cultures. In this model, bacterial cell growth is limited by the accumulation of protonated lactic acid and decreasing pH. In our experimental system, pure and mixed cultures of Lactococcus lactis and Listeria monocytogenes were grown in a vegetable broth medium. Predictions of the model indicate that pH is the primary factor that limits the growth of L. monocytogenes in competition with a strain of L. lactis which does not produce the bacteriocin nisin. The model also predicts the values of parameters that affect the growth and death of the competing populations. Further development of this model will incorporate the effects of additional inhibitors, such as bacteriocins, and may aid in the selection of lactic acid bacterium cultures for use in competitive inhibition of pathogens in minimally processed foods.
A toolkit for peer-to-peer distributed user interfaces: concepts, implementation, and applications

In this paper we present a software toolkit for deploying peer-to-peer distributed graphical user interfaces across four dimensions: multiple displays, multiple platforms, multiple operating systems, and multiple users, either independently or concurrently. This toolkit is based on the concept of multi-purpose proxy connected to one or many rendering engines in order to render a graphical user interface in part or whole for any user, any operating system (Linux, Mac OS X and Windows XP or higher), any computing platform (ranging from a pocket PC to a wall screen), and/or any display (ranging from private to public displays). This toolkit is a genuine peer-to-peer solution in that no computing platform is used for a server or for a client: any user interface can be distributed across users, systems, and platforms independently of their location, system constraints, and platform constraints. After defining the toolkit concepts, its implementation is described, motivated, and exemplified on two non-form based user interfaces: a distributed office automation and a distributed interactive game.
Cooperative selection diversity with a single fixed gain amplify-and-forward relay in Nakagami-m fading channels

We present new exact closed-form expressions for the symbol error rate (SER) of cooperative selection diversity (CSD) with a single fixed gain amplify-and-forward (AF) relay. We consider the general fading condition of independent but not necessarily identically distributed (i.n.d.) Nakagami-m fading. We also present a closed-form expression for i.n. d. Rayleigh fading as a special case. We highlight the performance improvements provided by CSD with fixed gain relaying in unbalanced fading conditions. Numerical results substantiate the validity of our analysis.
Scene segmentation from depth and color data driven by surface fitting

Scene segmentation is a very challenging problem for which color information alone is often not sufficient. Recently the introduction of consumer depth cameras has opened the way to novel approaches exploiting depth data. This paper proposes a novel segmentation scheme that exploits the joint usage of color and depth data together with a 3D surface estimation scheme. Firstly a set of multi-dimensional vectors is built from color and geometry information and normalized cuts spectral clustering is applied to them in order to coarsely segment the scene. Then a NURBS model is fitted on each of the computed segments. The accuracy of the fitting is used as a measure of the plausibility that the segment represents a single surface or object. Segments that do not represent a single surface are split again into smaller regions and the process is iterated until the optimal segmentation is obtained. Experimental results show how the proposed method allows to obtain an accurate and reliable scene segmentation.
Mr&mr-Sum: Maximum Relevance and Minimum Redundancy Document Summarization Model

We have presented an approach to automatic document summarization. In the proposed approach, text summarization is modeled as a quadratic integer-programming problem. This model generally attempts to optimize three properties, namely, (1) relevance: summary should contain informative textual units that are relevant to the user; (2) redundancy: summaries should not contain multiple textual units that convey the same information; and (3) length: summary is bounded in length. To solve the optimization problem we have created a novel differential evolution algorithm. Experimental results on DUC2005 and DUC2007 data sets showed that the proposed approach outperforms the other methods.
Quantized global parametrization

Global surface parametrization often requires the use of cuts or charts due to non-trivial topology. In recent years a focus has been on so-called seamless parametrizations, where the transition functions across the cuts are rigid transformations with a rotation about some multiple of 90°. Of particular interest, e.g. for quadrilateral meshing, paneling, or texturing, are those instances where in addition the translational part of these transitions is integral (or more generally: quantized). We show that finding not even the optimal, but just an arbitrary valid quantization (one that does not imply parametric degeneracies), is a complex combinatorial problem. We present a novel method that allows us to solve it, i.e. to find valid as well as good quality quantizations. It is based on an original approach to quickly construct solutions to linear Diophantine equation systems, exploiting the specific geometric nature of the parametrization problem. We thereby largely outperform the state-of-the-art, sometimes by several orders of magnitude.
Effect of Carbohydrate and Caffeine Ingestion on Badminton Performance.

PURPOSE To investigate the effect of ingesting carbohydrate and caffeine solutions on measures that are central to success in badminton. METHODS Twelve male badminton players performed a badminton serve-accuracy test, coincidence-anticipation timing (CAT), and a choice reaction-time sprint test 60 min before exercise. Participants then consumed 7 mL/kg body mass of either water (PLA), 6.4% carbohydrate solution (CHO), a solution containing a caffeine dose of 4 mg/kg, or 6.4% carbohydrate and 4 mg/kg caffeine (C+C). All solutions were flavored with orange-flavored concentrate. During the 33-min fatigue protocol, participants were provided with an additional 3 mL/kg body mass of solution, which was ingested before the end of the protocol. As soon as the 33-min fatigue protocol was completed, all measures were recorded again. RESULTS Short-serve accuracy was improved after the ingestion of CHO and C+C compared with PLA (P = .001, η(p)(2) = . 50). Long-serve accuracy was improved after the ingestion of C+C compared with PLA (P < .001, η(p)(2) = . 53). Absolute error in CAT demonstrated smaller deteriorations after the ingestion of C+C compared with PLA (P < .05; slow, η(p)(2) = . 41; fast, η(p)(2) = . 31). Choice reaction time improved in all trials with the exception of PLA, which demonstrated a reduction (P < .001, η(p)(2) = . 85), although C+C was faster than all trials (P < .001, η(p)(2) = . 76). CONCLUSION These findings suggest that the ingestion of a caffeinated carbohydrate solution before and during a badminton match can maintain serve accuracy, anticipation timing, and sprinting actions around the court.
Stakeholder Involvement in Business Process Management Agenda-Setting and Implementation

Process management serves the design of IT and organizations, while multiple actors have stakes in setting the agenda and implementing process innovations. These stakeholders, from both inside and outside an organization‟s boundaries, constitute integral elements of a larger network of actors. The stimulation and utilization of such networks are critical success factors for process management and innovation initiatives. Without the inclusion of stakeholders, adaption of organizational processes to a dynamic environment can be expected to be less effective and less successful. Although the importance of process management networks and stakeholder inclusion is widely acknowledged in the literature, current research lacks a thorough empirically informed understanding of the phenomenon. Taking the public sector example, this paper sets out to study empirically the involvement of different stakeholders and to develop a theory for analysis of process management collaboration. We conduct a comprehensive quantitative survey of more than 350 organizations and apply principle component analysis to identify distinct sets of stakeholders. Empirical evidence is provided for collaborative patterns of internal actors, vertical collaboration partners, horizontal collaboration partners, political actors, commercial actors, and customers. These patterns can serve as generic theory constructs, building blocks, for future research on process management stakeholders and solving issue in research and practice regarding stakeholder involvement.
Integrating Task Allocation , Planning , Scheduling , and Adaptive Resource Management to Support Autonomy in a Global Sensor Web

NASA’s Earth Science Vision calls for a global sensor web comprised of heterogeneous platforms with on-board information processing, capable of orchestrating real-time collaborative operations with other platforms and ground stations. Such a global sensor web will be a system of systems, including many distributed real-time embedded (DRE) systems, such as multi-satellite formations. Individual systems of the sensor web must collect and analyze large quantities of data via sequences of heterogeneous data collection, manipulation, and coordination tasks to meet specified goals for earth science applications. In large DRE systems, such as those composing a global sensor web, the sheer number of available components often poses a combinatorial planning problem for identifying component sequences to achieve specified goals. Moreover, the dynamic nature of these systems requires runtime management and modification of deployed components. We present the design of the Multi-agent Architecture for Coordinated Responsive Observations which includes two novel services contributing to the design and deployment of autonomous, predictable, and high performance DRE systems that operate in dynamic and uncertain environments: (i) the Spreading Activation Partial Order Planner (SA-POP) that performs decision-theoretic planning and scheduling using a spreading activation network to capture the probabilistic functional relationships between tasks (implemented as components) and goals; and (ii) the Resource Allocation and Control Engine (RACE), which is an opensource adaptive resource management framework built atop standards-based QoS-enabled component middleware. We illustrate the effectiveness of our approach in the face of changing operational conditions, workloads, and resource availability, in the context of salient Earth science missions.
Efficiency loss in market mechanisms for resource allocation

This thesis addresses a problem at the nexus of engineering, computer science, and economics: in large scale, decentralized systems, how can we efficiently allocate scarce resources among competing interests? On one hand, constraints are imposed on the system designer by the inherent architecture of any large scale system. These constraints are counterbalanced by the need to design mechanisms that efficiently allocate resources, even when the system is being used by participants who have only their own best interests at stake. We consider the design of resource allocation mechanisms in such environments. The analytic approach we pursue is characterized by four salient features. First, the monetary value of resource allocation is measured by the aggregate surplus (aggregate utility less aggregate cost) achieved at a given allocation. An efficient allocation is one which maximizes aggregate surplus. Second, we focus on market-clearing mechanisms, which set a single price to ensure demand equals supply. Third, all the mechanisms we consider ensure a fully efficient allocation if market participants do not anticipate the effects of their actions on market-clearing prices. Finally, when market participants are price anticipating, full efficiency is generally not achieved, and we quantify the efficiency loss. We make two main contributions. First, for three economic environments, we consider specific market mechanisms and exactly quantify the efficiency loss in these environments when market participants are price anticipating. The first two environments address settings where multiple consumers compete to acquire a share of a resource in either fixed or elastic supply; these models are motivated by resource allocation in communication networks. The third environment addresses competition between multiple producers to satisfy an inelastic demand; this model is motivated by market design in power systems. Our second contribution is to establish that, under reasonable conditions, the mechanisms we consider minimize efficiency loss when market participants anticipate the effects of their actions on market-clearing prices. Formally, we show that in a class of market-clearing mechanisms satisfying certain simple mathematical assumptions and for which there exist fully efficient competitive equilibria, the mechanisms we consider uniquely minimize efficiency loss when market participants are price anticipating. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
The forkhead transcription factor FOXK2 acts as a chromatin targeting factor for the BAP1-containing histone deubiquitinase complex

There are numerous forkhead transcription factors in mammalian cells but we know little about the molecular functions of the majority of these. FOXK2 is a ubiquitously expressed family member suggesting an important function across multiple cell types. Here, we show that FOXK2 binds to the SIN3A and PR-DUB complexes. The PR-DUB complex contains the important tumour suppressor protein, the deubiquitinase BAP1. FOXK2 recruits BAP1 to DNA, promotes local histone deubiquitination and causes changes in target gene activity. Our results therefore provide an important link between BAP1 and the transcription factor FOXK2 and demonstrate how BAP1 can be recruited to specific regulatory loci.
Why Are There Tropical Warm Pools

Tropical warm pools appear as the primary mode in the distribution of tropical sea surface temperature (SST). Most previous studies have focused on the role of atmospheric processes in homogenizing temperatures in the warm pool and establishing the observed statistical SST distribution. In this paper, a hierarchy of models is used to illustrate both oceanic and atmospheric mechanisms that contribute to the establishment of tropical warm pools. It is found that individual atmospheric processes have competing effects on the SST distribution: atmospheric heat transport tends to homogenize SST, while the spatial structure of atmospheric humidity and surface wind speeds tends to remove homogeneity. The latter effects dominate, and under atmosphere-only processes there is no warm pool. Ocean dynamics counter this effect by homogenizing SST, and it is argued that ocean dynamics is fundamental to the existence of the warm pool. Under easterly wind stress, the thermocline is deep in the west and shallow in the east. Because of this, poleward Ekman transport of water at the surface, compensated by equatorward geostrophic flow below and linked by equatorial upwelling, creates a cold tongue in the east but homogenizes SST in the west, creating a warm pool. High clouds may also homogenize the SST by reducing the surface solar radiation over the warmest water, but the strength of this feedback is quite uncertain. Implications for the role of these processes in climate change are discussed.
First results of the tracking system calibration of the TAIGA-IACT telescope

In TAIGA Observatory (Tunka Advanced Instrument for cosmic ray physics and Gamma-ray Astronomy) we are commissioning the first Imaging Atmospheric Cherenkov Telescope (IACT). The telescope has an alt-azimuth mount and 17-bit shaft encoder for each axis, stepper motors are used for axis control. For the pointing calibration of the telescope a CCD-camera is installed on the dish of the telescope and its position allows to capture simultaneously both the Cherenkov camera with LEDs and the sky with observed source. Since October 2017, the telescope has been operating in tracking mode. In this work the TAIGAIACT telescope pointing calibration approach and first results of the tracking operations are described.
Joint 3D Beamforming and Resource Allocation for Small Cell Wireless Backhaul in HetNets

Network densification and 3D beamforming are two potential techniques to support the increasing data rate in the upcoming 5G cellular networks. This letter focuses on the joint optimization of 3D beamforming and resource allocation for the small cell (SC) backhaul in a heterogeneous network. After analyzing the achievable data rates of users and SCs based on Gamma distribution, we formulate a joint optimization problem to maximize the network throughput. We then convert it to an equivalent optimization problem and develop a low-complexity algorithm on joint 3D beamforming and resource allocation. Simulation results demonstrate the performance improvement of the proposed algorithm.