Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential effects of proteins and carbohydrates on postprandial blood pressure-related responses

Diet composition may affect blood pressure (BP), but the mechanisms are unclear. The aim of the present study was to compare postprandial BP-related responses to the ingestion of pea protein, milk protein and egg-white protein. In addition, postprandial BP-related responses to the ingestion of maltodextrin were compared with those to the ingestion of sucrose and a protein mix. We hypothesised that lower postprandial total peripheral resistance (TPR) and BP levels would be accompanied by higher plasma concentrations of nitric oxide, insulin, glucagon-like peptide 1 (GLP-1) and glucagon. On separate occasions, six meals were tested in a randomised order in forty-eight overweight or obese adults with untreated elevated BP. Postprandial responses of TPR, BP and plasma concentrations of insulin, glucagon, GLP-1 and nitrite, nitroso compounds (RXNO) and S-nitrosothiols (NO x ) were measured for 4 h. No differences were observed in TPR responses. Postprandial BP levels were higher after the ingestion of the egg-white-protein meal than after that of meals containing the other two proteins (P≤ 0·01). The ingestion of the pea-protein meal induced the highest NO x response (P≤ 0·006). Insulin and glucagon concentrations were lowest after the ingestion of the egg-white-protein meal (P≤ 0·009). Postprandial BP levels were lower after the ingestion of the maltodextrin meal than after that of the protein mix and sucrose meals (P≤ 0·004), while postprandial insulin concentrations were higher after the ingestion of the maltodextrin meal than after that of the sucrose and protein mix meals after 1–2 h (P≤ 0·0001). Postprandial NO x , GLP-1 and glucagon concentrations were lower after the ingestion of the maltodextrin meal than after that of the protein mix meal (P≤ 0·008). In conclusion, different protein and carbohydrate sources induce different postprandial BP-related responses, which may be important for BP management. Lower postprandial BP levels are not necessarily accompanied by higher NO x , insulin, glucagon or GLP-1 responses.
Semi-automatic Generation of Multiple-Choice Tests from Mentions of Semantic Relations

We propose a strategy for the semiautomatic generation of learning material for reading-comprehension tests, guided by semantic relations embedded in expository texts. Our approach combines methods from the areas of information extraction and paraphrasing in order to present a language teacher with a set of candidate multiple-choice questions and answers that can be used for verifying a language learners reading capabilities. We implemented a web-based prototype showing the feasibility of our approach and carried out a pilot user evaluation that resulted in encouraging feedback but also pointed out aspects of the strategy and prototype implementation which need improvements.
Automatic generation of system-level virtual prototypes from streaming application models

Virtual prototyping is a more and more accepted technology to enable early software development in the design flow of embedded systems. Since virtual prototypes are typically constructed manually, their value during design space exploration is limited. On the other hand, system synthesis approaches often start from abstract and executable models, allowing for fast design space exploration, considering only predefined design decisions. Usually, the output of these approaches is an "ad hoc" implementation, which is hard to reuse in further refinement steps. In this paper, we propose a methodology for automatic generation of heterogeneous MPSoC virtual prototypes starting with models for streaming applications. The advantage of the proposed approach lies in the fact that it is open to subsequent design steps. The applicability of the proposed approach to real-world applications is demonstrated using a Motion JPEG decoder application that is automatically refined into several virtual prototypes within seconds, which are correct by construction, instead of using error-prone manual refinement, which typically requires several days.
An Empirical Bayesian Framework for Brain–Computer Interfaces

Current brain-computer interface (BCI) systems suffer from high complex feature selectors in comparison to simple classifiers. Meanwhile, neurophysiological and experimental information are hard to be included in these two separate phases. In this paper, based on the hierarchical observation model, we proposed an empirical Bayesian linear discriminant analysis (BLDA), in which the neurophysiological and experimental priors are considered simultaneously; the feature selection, weighted differently, and classification are performed jointly, thus it provides a novel systematic algorithm framework which can utilize priors related to feature and trial in the classifier design in a BCI. BLDA was comparatively evaluated by two simulations of a two-class and a four-class problem, and then it was applied to two real four-class motor imagery BCI datasets. The results confirmed that BLDA is superior in accuracy and robustness to LDA, regularized LDA, and SVM.
Accelerated Gossip Algorithms for Distributed Computation

We introduce a technique for accelerating the gos- sip algorithm of Boyd et. al. (INFOCOM 2005) for distributed averaging in a network. By employing memory in the form of a small shift-register in the computation at each node, we can speed up the algorithm’s convergence by a factor of 10. Our accelerated algorithm is inspired by the observation that the original gossip algorithm is analogous to the power method in Numerical Analysis, which can be accelerated by a shift-register based recurrence.
Understanding the need for micro-gestural inflections in parameter-mapping sonification

Most of the software tools used for data sonification have been adopted or adapted from those designed to compose computer music, which in turn, adopted them from abstractly notated scores. Such adoptions are not value-free; by using them, the cultural paradigms underlying the music for which the tools were made have influenced the conceptualization and, it is argued, the effectiveness of data sonifications. Recent research in cognition supports studies in empirical musicology that suggest that listening is not a passive ingestion of organised sounds but is an embodied activity that invisibly enacts gestures of what is heard. This paper outlines an argument for why sonifiers using parametric-mapping sonification should consider incorporating micro-gestural inflections if they are to mitigate The Mapping Problem in enhancing the intelligibility of sonified data.
Physical layer security of MISO TAS wiretap channels with interference-limited eavesdropper

This paper investigates the secrecy performance of multiple-input single-output (MISO) wiretap channels with transmit antenna selection (TAS) and subject to an interference-limited eavesdropper. By considering NA antennas at the transmitter, a single antenna at the legitimate receiver and eavesdropper, and multiple arbitrary co-channel interferers M at the eavesdropper, an exact closed-form expression for the secrecy outage probability is derived. The exact expression is simplified for two, yet novel, special cases. Based on these analytical expressions, an asymptotic secrecy outage analysis is carried out and it shows that the diversity order of the considered system equals to min(NA, M). The proposed analysis is corroborated through Monte Carlo simulation results. Illustrative numerical examples are depicted and insightful discussions are drawn. It is shown that the secrecy outage performance is largely limited by the number of interference channels and the number of transmit antennas due to diversity gain.
Phylogenetic insights into Andean plant diversification

Andean orogeny is considered as one of the most important events for the developmentof current plant diversity in South America. We compare available phylogenetic studies anddivergence time estimates for plant lineages that may have diversified in response to Andeanorogeny. The influence of the Andes on plant diversification is separated into four major groups:The Andes as source of new high-elevation habitats, as a vicariant barrier, as a North-Southcorridor and as generator of new environmental conditions outside the Andes. Biogeographicalrelationships between the Andes and other regions are also considered. Divergence timeestimates indicate that high-elevation lineages originated and diversified during or after the majorphases of Andean uplift (Mid-Miocene to Pliocene), although there are some exceptions. Asexpected, Andean mid-elevation lineages tend to be older than high-elevation groups. Mostclades with disjunct distribution on both sides of the Andes diverged during Andean uplift.Inner-Andean clades also tend to have divergence time during or after Andean uplift. This isinterpreted as evidence of vicariance. Dispersal along the Andes has been shown to occur ineither direction, mostly dated after the Andean uplift. Divergence time estimates of plant groupsoutside the Andes encompass a wider range of ages, indicating that the Andes may not benecessarily the cause of these diversifications. The Andes are biogeographically related to allneighbouring areas, especially Central America, with floristic interchanges in both directionssince Early Miocene times. Direct biogeographical relationships between the Andes and otherdisjunct regions have also been shown in phylogenetic studies, especially with the easternBrazilian highlands and North America. The history of the Andean flora is complex and plantdiversification has been driven by a variety of processes, including environmental change,adaptation, and biotic interactions
A secure routing algorithm based on nodes behavior during spectrum sensing in cognitive radio networks

Routing in cognitive radio networks (CRNs) faces many limitations that make it challenging. First, traditional routing protocols cannot be directly applied in CRNs because they consider fixed frequency band. Second, cognitive radio enables dynamic spectrum access which causes adverse effects on network performance. Third, effective routing in CR Networks (CRNs) needs local and continual knowledge of its environment. Last, presence of malicious nodes and their misbehaving activities affect the route establishment and therefore reduce the network performance. In this paper, we address such limitations by combining spectrum sensing and routing to propose a novel routing algorithm that uses nodes' behavior during spectrum sensing phase as a routing metric. Through the spectrum sensing phase, nodes behavior is measured through a parameter called belief level (BL), which describes the node's reliability to correctly sense the spectrum and to use spectrum channels accordingly. Moreover, we secure the routing requests and reply messages by encrypting them utilizing the existing cryptography techniques. The proposed approach is designed to maximize security level of paths, minimize the effects of licensed users activity over spectrum channels, and reduce the total channels cost over the best path(s). Evaluation of the proposed approach shows that its performance outperforms many current state-of-the-art routing algorithms used in CRNs in terms of end-to-end delay, packet delivery ratio, and packet loss ratio.
Development of a novel haptic perception device using “Touch Blend”

A simple haptic perception device using "Touch Blend". Our former device had some problems of device specifications and the method of haptic perceptions. In this study, a new device was made, and it could compound "haptic perceptions" from five elements (pressure, vibration, warmth, cold, pain). An evaluation experiment was carried out on 30 volunteers of early 20s. They put their fingertip on the device, and they answered into a sheet of items. The results suggested that the device could present hardness, titillate and warmth. The device failed to present elasticity, which was speculated to be presented by combining pressure and warmth, and throb as also the result of combining vibration and pain, and the device was not able to present cold and prick, though these problems can be solved by improving the device. And the results reached by the experiment were successful enough to say that our new haptic perception device based on “Touch Blend” is capable of presenting haptic sensations. Consequently, our idea of providing haptic perceptions based on “Touch Blend” theory was proved to be feasible.
Recipe recommendation for a diet considering a user's schedule and the balance of nourishment

Today, there are a lot of Web sites and tools that introduce and propose cooking recipes for a diet. However, it is difficult to be on a diet by following those recipes because many of them do not consider user's circumstances. So, in this study, we propose a method to recommend cooking recipes for a diet considering user's schedule. Concretely, the evaluation value of either intake or consumption calorie is assigned to each event in the user's schedule, and then based on the calculation with the values, some candidates of recipes with calorie to make the user easily lost weight for the objective weight are selected considering the user's schedule during the period of a diet. In addition, to recommend more healthy recipes among the selected recipes, we use linear programming with the constraints of carbohydrate, lipid, protein, salt, and increasing the amount of vegetable intake.
The Kinect up close: Adaptations for short-range imaging

With proper calibration of its color and depth cameras, the Kinect can capture detailed color point clouds at up to 30 frames per second. This capability positions the Kinect for use in robotics as a low-cost navigation sensor. Thus, techniques for efficiently calibrating the Kinect depth camera and altering its optical system to improve suitability for imaging short-range obstacles are presented. To perform depth calibration, a calibration rig and software were developed to automatically map raw depth values to object depths. The calibration rig consisted of a traditional chessboard calibration target with easily locatable features in depth at its exterior corners that facilitated software extraction of corresponding object depths and raw depth values. To modify the Kinect's optics for improved short-range imaging, Nyko's Zoom adapter was used due to its simplicity and low cost. Although effective at reducing the Kinect's minimum range, these optics introduced pronounced distortion in depth. A method based on capturing depth images of planar objects at various depths produced an empirical depth distortion model for correcting such distortion in software. Together, the modified optics and the empirical depth undistortion procedure demonstrated the ability to improve the Kinect's resolution and decrease its minimum range by approximately 30%.
FCA and pattern structures for mining care trajectories

In this paper, we are interested in the analysis of sequential data and we propose an original framework based on Formal Concept Analysis (FCA). For that, we introduce sequential pattern structures, an original specification of pattern structures for dealing with sequential data. Pattern structures are used in FCA for dealing with complex data such as intervals or graphs. Here they are adapted to sequences. For that, we introduce a subsumption operation for sequence comparison, based on subsequence matching. Then, a projection, i.e. a kind of data reduction of sequential pattern structures, is suggested in order to increase the efficiency of the approach. Finally, we discuss an application to a dataset including patient trajectories (the motivation of this work), which is a sequential dataset and can be processed with the introduced framework. This research work provides a new and efficient extension of FCA to deal with complex (not binary) data, which can be an alternative to the analysis of sequential datasets.
Using magnetic forces to convey state information: an exploration of a haptic technology

Using magnetic forces to provide haptic information is an area that remains largely unexplored and provides exciting opportunities for interaction that may not otherwise be possible. We present several example applications that illustrate how this technology is well suited to remote site collaboration techniques, conveying state information and simulating flows and turbulence. Furthermore, we present the results of our preliminary user study which has indicated that magnetic forces can convey two states of information to the user with 100% accuracy, and can convey three states with 89% accuracy.
Learning Optimal Parameters for Coordinated Helicopter Turns

The aim of our work is to develop a motion planning architecture for a fully autonomous helicopter that is e ↵ ectively able to emulate a professional pilot’s behavior. In this report, we consider the problem of learning the pilot’s preferences for coordinated helicopter turns. Speciﬁcally, we aim to learn the optimal set of parameters for a motion planner developed in our earlier work such that the turns executed by our planner accurately represents the ones demonstrated by the pilot. We present a basic parameter tuning algorithm for the planner’s cost function which gives satisfactory results for both self-generated and actual demonstrations of the coordinated turns.
Analysis of gradient algorithms for TLS-based adaptive IIR filters

Steepest descent gradient algorithms for unbiased equation error adaptive infinite impulse response (IIR) filtering are analyzed collectively for both the total least squares and mixed least squares-total least squares framework. These algorithms have a monic normalization that allows for a direct filtering implementation. We show that the algorithms converge to the desired filter coefficient vector. We achieve the convergence result by analyzing the stability of the equilibrium points and demonstrate that only the desired solution is locally stable. Additionally, we describe a region of initialization under which the algorithm converges to the desired solution. We derive the results using interlacing relationships between the eigenvalues of the data correlation matrices and their respective Schur complements. Finally, we illustrate the performance of these new approaches through simulation.
TRANSWARM: A SUGARCANE TRANSPORT SIMULATION MODEL BASED ON BEHAVIOURAL LOGISTICS

Transport logistics systems typically evolve as net works over time, which may result in system rigidity and cause changes to become expensi ve and time consuming. In this study a logistics model, named TranSwarm, was developed to simulate sugarcane harvesting, transport and mill-yard activities for a mill suppl y area. The aim was to (i) simulate produce flow, and (ii) allow individual working entities to make decisions, driven by rules and protocols, and based on their micro-environments. N oodsberg mill was selected for the case study because of low current levels of synchronisat ion. Growers were assumed to operate independent harvesting and transport systems causin g inconsistent convergences at the mill. This diverse and fragmented system provided a suita ble environment for constructing a model that would consider interactions between individual growers and their respective transport systems. Ideally, by assessing the micro-decisions of individuals and how these decisions influence the holistic supply chain, TranSwarm quan tifies the impacts of different types of transport practices, such as changing vehicle speed s to reduce queuing at the mill. TranSwarm is visual, mechanistic and represents key entities such as roads, farm groupings and the mill. The system uses discrete events to create a dynamic and stochastic environment from which observations and conclusions can be drawn. This app roach potentially allows stakeholders to identify key components and interactions that may j eopardise overall efficiency and to use the system to test new working protocols and logistics rules for improving the supply chain.
Selective Predation and Productivity Jointly Drive Complex Behavior in Host‐Parasite Systems

Successful invasion of a parasite into a host population and resulting host‐parasite dynamics can depend crucially on other members of a host’s community such as predators. We do not fully understand how predation intensity and selectivity shape host‐parasite dynamics because the interplay between predator density, predator foraging behavior, and ecosystem productivity remains incompletely explored. By modifying a standard susceptible‐infected model, we show how productivity can modulate complex behavior induced by saturating and selective foraging behavior of predators in an otherwise stable host‐parasite system. When predators strongly prefer parasitized hosts, the host‐parasite system can oscillate, but predators can also create alternative stable states, Allee effects, and catastrophic extinction of parasites. In the latter three cases, parasites have difficulty invading and/or persisting in ecosystems. When predators are intermediately selective, these more complex behaviors become less important, but the host‐parasite system can switch from stable to oscillating and then back to stable states along a gradient of predator control. Surprisingly, at higher productivity, predators that neutrally select or avoid parasitized hosts can catalyze extinction of both hosts and parasites. Thus, synergy between two enemies can end disastrously for the host. Such diverse outcomes underscore the crucial importance of the community and ecosystem context in which host‐parasite interactions occur.
A flexible multi-model approach to psychosocial integration in non player characters in modern video games

This paper introduces a novel approach to integrating various psychosocial models to facilitate the construction of flexible, expressive, and believable non player characters for modern video games. Instead of forcing game designers and developers to choose from a multitude of possible models for personality, emotion, and so on, each with their own strengths and weaknesses, our approach enables the use of multiple models simultaneously, either partially or in their entirety. In doing so, we can provide considerable flexibility and customizability in character design, leading to richer and more varied characters in video games. Based on our approach, a prototype run-time system has been developed, using our earlier work in emergent characters as a foundation. To further support our approach in the creation of characters, tools have also been created to construct psychosocial models, as well as the characters based on these models. These prototypes have been evaluated and shown through experimentation to produce very positive results, and have great promise for continued work in the future.
Design of PI controllers by using bacterial foraging strategy to control frequency for distributed generation

In this paper a hybrid distributed generation (DG) system connected to isolated load is studied. The DG system consisting of photo voltaic (PV) system, fuel cells, aqua electrolyzer, diesel engine generator and a battery energy storage system. The ambient temperature value of PV is taken as constant to make the output power of PV is directly proportional to the radiation and output power of other DG sources and frequency of the system is controlled by simple proportional plus integral (PI) controllers. A maiden attempt is made to apply a more recent and powerful optimization technique named as bacterial foraging technique for optimization of PI controllers gains of the proposed hybrid DG system. The system responses with bacterial foraging based PI controller are compared with that of classical method. Investigations reveal that bacterial foraging based PI controller gives better responses than the classical method. Sensitivity analysis is carried out which demonstrates the robustness of the optimized gain values for system loading condition.