Miracle-dz/UniFAR-FTUs huggingface dataset:
of the Annual Meeting of the Cognitive Science Society Title Phonological Encoding in Word Naming and Word Typing

The process of phonological encoding was investigated in primed word naming and word typing with Chinese monosyllabic words. The target words shared or did not share the onset consonants with the prime words. The stimulus onset asynchrony (SOA) was 100 ms or 300 ms. Typing required the participants to enter the phonetic letters of the target word, which correspond roughly to the onset and the rhyme of the word’s syllable. Regardless of SOAs, response times were shorter in the related condition than in the unrelated condition (an onset priming effect) for word typing, but were similar for word naming. The results suggest that naming and typing in Chinese may involve somewhat different phonological encoding processes even though both tasks require accessing the phonological codes. It is hypothesized that phonological encoding in Chinese is syllable driven in word naming, but is segment driven in word typing.
0 Eulerian-Lagrangian Formulation for Compressible Navier-Stokes Equations

The Eulerian-Lagrangian formulation of the (inviscid) Euler dynamics in terms of advected Weber-Clebsch potentials (Lamb, 1932), was extended by Constantin to cover the viscous Navier-Stokes dynamics (Constantin, 2001). Numerical studies (Ohkitani & Constantin, 2003), of this formulation of the Navier-Stokes equations concluded that the diffusive Lagrangian map becomes non-invertible under time evolution and requires resetting for its calculation. They proposed the observed sharp increase of the frequency of resettings as a new diagnostic of vortex reconnection. In previous work we were able (Cartes et al., 2007; 2009) to complement these results, using an approach that is based on a generalised set of equations of motion for the Weber-Clebsch potentials, that turned out to depend on a parameter τ, which has the unit of time for the Navier-Stokes case. Also to extend our formulation to magnetohydrodynamics, and thereby obtain a new diagnostic for magnetic reconnection. In this work we present a generalisation of the Weber-Clebsch variables in order to describe the compressible Navier-Stokes dynamics. Our main result is a good agreement between the dynamics for the velocity and density fields that come from the dynamics of Weber-Clebsch variables and direct numerical simulations of the compressible Navier-Stokes equations. We first present the inviscid Eulerian-Lagrangian theory, then Constantin’s extension to viscous fluids and derive our equations of motion for the Weber-Clebsch potentials that describe the compressible Navier-Stokes dynamics. Then, performing direct numerical simulations of the Taylor-Green vortex, we check that our formulation reproduces the compressible dynamics.
Analysis and Design of a Novel Linear Generator for Harvesting Oceanic Wave Energy

In almost every permanent magnet linear generator (PMLG), demagnetization would greatly degrade the electricity generation capability over time. This paper proposes a novel PMLG which consists of a permanent magnet excitation generator (PMEG) to supply electrical excitation to the field winding of an electromagnetic linear generator (EMLG) which functions as the main power generator. The proposed generator can reduce the demagnetization problem of the conventional PMLG. The finite element Analysis is performed by using the commercial software package ANSYS/ANSOFT for designing the proposed PMLG, and the genetic algorithm has been used to find the optimal pole size, pole pitch, air gap length and load variation to maximize the output power. Special m-shaped stator core is designed for the PMEG to minimize the leakage flux and cogging force. The voltage, current, power, magnetic flux density, force components and applied force are also analyzed and discussed.
Gene Polymorphism of Angiotensin II Type 1 Receptor (Agtr1) As A Risk Factor of Diabetic Nephropathy In Indonesian Patients With Type 2 Diabetes Mellitus

There are many works reported that angiotensin II type 1 receptor (AGTR1) gene polymorphisms associated with diabetic nephropathy and has variable expression in different ethnic groups. However, the distribution data of AGTR1 gene polymorphism in patients with diabetic nephropathy in Indonesia is still lacking. This study aimed to determine the polymorphism of AGTR1 gene A1166C in patients with Type 2 diabetes mellitus in Yogyakarta, Indonesia. The subjects of the research were 60 patients with Type 2 diabetes, 30 diabetic nephropathy and 30 without nephropathy respectively. Gene polymorphisms were determined by PCR-RFLP method and the PCR products were digested with BsuRI restriction enzyme. The results showed the frequency distribution of genotypes of AGTR1 gene in patients with diabetic nephropathy were 86,7% for AA, 13,3% for AC, and 0% for CC respectively. It can be inferred that in Indonesian genotype AA is predominant compared to AC or CC.
A relationship between behavioral choice and the visual responses of neurons in macaque

We have previously documented the exquisite motion sensitivity of neurons in extrastriate area MT by studying the relationship between their responses and the direction and strength of visual motion signals delivered to their receptive fields. These results suggested that MT neurons might provide the signals supporting behavioral choice in visual discrimination tasks. To approach this question from another direction, we have now studied the relationship between the discharge of MT neurons and behavioral choice, independently of the effects of visual stimulation. We found that trial-to-trial variability in neuronal signals was correlated with the choices the monkey made. Therefore, when a directionally selective neuron in area MT fires more vigorously, the monkey is more likely to make a decision in favor of the preferred direction of the cell. The magnitude of the relationship was modest, on average, but was highly significant across a sample of 299 cells from four monkeys. The relationship was present for all stimuli (including those without a net motion signal), and for all but the weakest responses. The relationship was reduced or eliminated when the demands of the task were changed so that the directional signal carried by the cell was less informative. The relationship was evident within 50 ms of response onset, and persisted throughout the stimulus presentation. On average, neurons that were more sensitive to weak motion signals had a stronger relationship to behavior than those that were less sensitive. These observations are consistent with the idea that neuronal signals in MT are used by the monkey to determine the direction of stimulus motion. The modest relationship between behavioral choice and the discharge of any one neuron, and the prevalence of the relationship across the population, make it likely that signals from many neurons are pooled to form the data on which behavioral choices are based.
Family Firms and clean technologies

Background: Sustainability practices have become a crucial factor for firms since there are external and internal pressures that expect firms to act environmentally friendly. Especially within organizations that are owned by family, being sustainable enables them to pass their firm in a good condition to the next generation. One way firms can be sustainable is through adopting clean technology strategy as it can provide both environmental and economic benefits to firms. Being sustainable and having the ability to implement clean technology requires a long-term vision or long-term orientation (LTO); a characteristic often associated with family-controlled businesses (FCBs). Purpose: The purpose is to examine the adoption of clean technology within family-controlled firms (FCBs) and non-family-controlled firms (Non-FCBs). The aim is to explore if there are certain characteristics of FCBs that facilitate implementation of clean technologies. Method: This research is based on qualitative research method with an abductive approach and interpretivism philosophy. The primary data is collected through semi-structured interviews with four companies of which three are family-controlled businesses and one is a non-familycontrolled business. Conclusion: FCBs are more inclined to invest in clean technologies. The extent to which a company does or does not implement clean technologies depends not only on the institutional values of an organization but also how deeply one or more of the three LTO dimensions are implanted in those values.
A PPROXIMABILITY OF DISCRIMINATORS IMPLIES DIVERSITY IN GAN S

While Generative Adversarial Networks (GANs) have empirically produced impressive results on learning complex real-world distributions, recent works have shown that they suffer from lack of diversity or mode collapse. The theoretical work of Arora et al. (2017a) suggests a dilemma about GANs’ statistical properties: powerful discriminators cause overfitting, whereas weak discriminators cannot detect mode collapse. By contrast, we show in this paper that GANs can in principle learn distributions in Wasserstein distance (or KL-divergence in many cases) with polynomial sample complexity, if the discriminator class has strong distinguishing power against the particular generator class (instead of against all possible generators). For various generator classes such as mixture of Gaussians, exponential families, and invertible and injective neural networks generators, we design corresponding discriminators (which are often neural nets of specific architectures) such that the Integral Probability Metric (IPM) induced by the discriminators can provably approximate the Wasserstein distance and/or KL-divergence. This implies that if the training is successful, then the learned distribution is close to the true distribution in Wasserstein distance or KL divergence, and thus cannot drop modes. Our preliminary experiments show that on synthetic datasets the test IPM is well correlated with KL divergence or the Wasserstein distance, indicating that the lack of diversity in GANs may be caused by the sub-optimality in optimization instead of statistical inefficiency.
From statin efficacy to everyday effectiveness: Studying the gap in between.

Paivi Ruokoniemi From statin efficacy to everyday effectiveness: Studying the gap in between. Institute of Biomedicine, Department of Pharmacology, Drug Development and Therapeutics, University of Turku, Turku, Finland; The Department of Clinical Pharmacology, University of Helsinki, Helsinki, Finland Annales Universitatis Turkuensis, Medica-Odontologica, Turku, Finland, 2015 Statins are indicated for preventing cardiovascular disease events. Patients with diabetes have a risk of major cardiovascular events double the risk of their peers without diabetes. Thus, clinical treatment guidelines recommend statins for the management of diabetic dyslipidemia. The evidence base for statin use in cardiovascular disease derives from the randomised controlled statin trials designed to prove statin efficacy under ideal conditions, among a homogenous study population meeting strict trial eligibility criteria. This thesis was implemented as four pharmacoepidemiological statin studies using register data on realworld statin users. The overall purpose was to evaluate the trends, patterns and effectiveness of statin use in everyday life. More specifically, nationwide secular trends in statin use in Finland were analysed, especially among patient groups which had been underrepresented in the statin trials. Furthermore, the benchmarking statin trials in diabetes, the Heart Protection Study and the Collaborative Atorvastatin Diabetes Study, were evaluated for their representativeness for real-world diabetes care with the emphasis placed on adherence to statin use. The association between good adherence and the incidence of major cardiovascular events in the real-world was further investigated in diabetes. These studies demonstrate that statin initiations increased from 1995 to 2005 in Finland. The increase was most pronounced among those aged at least 75 years and was observed already before the publication of rigorous trial data conducted in elderly subjects. Thus, statins seem to have been initiated in clinical practice also going beyond the strict trial eligibility criteria. Nonetheless, low adherence to statin use among the real-world patients with diabetes was found not only to limit the representativeness of the trials for clinical care but also to attenuate in all likelihood their benefits in the real-world. In fact, good adherence to statin use was found to associate with a decreased risk for major cardiovascular events in patients with diabetes. In conclusion, these studies highlight the importance of good adherence to statin use in clinical practice in order to obtain the full therapeutic value demonstrated in the statin trials. Simply increasing the number of statin users will not alone suffice in sharing our common resources appropriately.
Biological Principles of Nanostructured Hydroxyapatite Associated With Metals: A Literature Review

The aim of this paper is to present, in the light of literature, a comprehensive review, by reviewing the literature related to bone grafts, biomaterials (BM) and nanotechnology containing five metals (Zn, Fe, Sr, Mg and Mn) with a view of an unprecedented experimental research support evaluation of the biocompatibility of these materials for human implantation. The BM market for graft indicates a trend of using synthetic materials, to the detriment of those of biological origin, ease of its large-scale production, reproducibility, doping structure and control of their physical, chemical and morphological characteristics, enabling the association with growth factors. Understanding the bone structure and its interaction with the human body are grounds factors for the development of new research. In this context, pure hydroxyapatite (main component of bone) lacks adequate biological properties because it shows high solubility and rapid incorporation of time while the materials are on the market have only osteoconductive properties, ie still not known any with ideal property. Was performed with a bibliographic levamento bone substituitos descriptor, biocompatibility and metals involved (Mg, Sr, Zn, Fe, Mn) in Bireme databases, Medline, and lilacs, which were initially selected and journals 135 on the subject. After further screening, they remained 69 that are part of this review. The international consensus pointing hidroxipatita as a base material for bone grafting biomaterials in humans, however, alone, possesses rapid incorporation requiring doped with one or more structures to achieve satisfactory results. The Bicompatibilidade, biodegradability and osteocondutibilidade are basic characteristics of BM as well, based on these principles, translational research in the implant area has evolved, seeking changes at the molecular level bringing new attributes to BM and consequently.
A Strongly Interacting Dynamic Particle Swarm

A novel dynamic interacting particle swarm optimization algorithm (DYN-PSO) is proposed. The algorithm can be considered to be the synthesis of two established trajectory methods for unconstrained minimization. In the new method, the minimization of a function is achieved through the dynamic motion of a strongly interacting particle swarm, where each particle in the swarm is simultaneously attracted by all other particles located at positions of lower function value. The force of attraction experienced by a particle at higher function value due to a particle at a lower function value is equal to the difference between the respective functionvalues divided by their stochastically perturbed position difference. The resultant motion of the particles under the influence of the attracting forces is computed by solving the associated equations of motion numerically. An energy dissipation strategy is applied to each particle. The specific chosen force law and the dissipation strategy result in the rapid collapse (convergence) of the swarm to a stationary point. Numerical results show that, in comparison to the standard particle swarm algorithm, the proposed DYN-PSO algorithm is promising.
A Real-Time Letter Recognition Model for Arabic Sign Language Using Kinect and Leap Motion Controller v2

The objective of this research is to develop a supervised machine learning hand-gesturing model to recognize Arabic Sign Language (ArSL), using two sensors: Microsoft's Kinect with a Leap Motion Controller. The proposed model relies on the concept of supervised learning to predict a hand pose from two depth images and defines a classifier algorithm to dynamically transform gestural interactions based on 3D positions of a hand-joint direction into their corresponding letters whereby live gesturing can be then compared and letters displayed in real time. This research is motivated by the need to increase the opportunity for the Arabic hearing-impaired to communicate with ease using ArSL and is the first step towards building a full communication system for the Arabic hearing impaired that can improve the interpretation of detected letters using fewer calculations. To evaluate the model, participants were asked to gesture the 28 letters of the Arabic alphabet multiple times each to create an ArSL letter data set of gestures built by the depth images retrieved by these devices. Then, participants were later asked to gesture letters to validate the classifier algorithm developed. The results indicated that using both devices for the ArSL model were essential in detecting and recognizing 22 of the 28 Arabic alphabet correctly 100 %.
UvA-DARE ( Digital Academic Repository ) Fingermarks , more than just a ridge pattern

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Continuum modelling of the granular flows in gaseous states using material point method

In a quick flow of granular material, the initially densely packed material often starts to separate and its behaviour changes to that characteristic of a liquid and, at low enough density, to the state where grains are disconnected from the other grains (gaseous states). Modelling such a flow requires acknowledging the changes in the granular material, in particular noting the changes in the constitutive behaviour as well as having the capability to model large displacements and deformations. This study employs the Material Point Method to model the behaviour of granular material flow in transition from the solid to the gaseous state and from the gaseous to the solid state. The paper introduces modifications into the method to represent the changes in the granular material and the constitutive behaviour required for modelling of the granular material in the disconnected regime. This is the first step in application of the Material Point Method in modelling of the flow behaviour of granular material through its various states.
XMRs : Uniform Semantic Representations for Intermodular Communication in Cognitive Robots

We present the purpose, format and content of internal signals exchanged among the processing modules of the OntoAgent HRI-oriented architecture. These signals represent the agent’s understanding of the situation at hand and motivate its potential response to it. Having been formulated in the same ontological framework, they support the use of interpreted input from multiple perception sources in the agent’s decision-making and provide input for translating the agent’s decisions into physical and verbal action.
Web Search From a Bus Aruna Balasubramanian

Opportunistic connections to the Internet from open wireless access points is now commonly possible in municipal areas. Vehicular networks can opportunistically connect to the internet for several seconds via open access points. In this paper, we adapt the interactive process of web search and retrieval to vehicular networks with intermittent Internet access. Our system, called Thedu has mobile nodes use an Internet proxy to collect search engine results and prefetch result pages. The mobiles nodes download the pre-fetched web pages from the proxy. Our contribution is a novel set of techniques to make aggressive but selective prefetching practical, resulting in a significantly greater number of relevant web results returned to mobile users. To evaluate our scheme, we deployed Thedu on DieselNet, our vehicular testbed of buses operating in a micro-urban area around Amherst, MA. Using a simulated workload, we find that users can expect four times as many useful responses to web search queries compared to not using Thedu. Moreover, the mean latency in receiving the first relevant response for a query is 2.7 minutes when deployed in a semi-urban region with a sparser distribution of APs compared to big cities.
ASSESSMENT OF THE IMPACT OF ECOLOGICAL FACTORS ON YIELD AND QUALITY PARAMETERS IN TRITICALE USING GGE BIPLOT AND AMMI ANALYSIS

We examined the effects of late spring frost on grain yield (GY) and quality of spring triticale (× Triticosecale) genotypes, based on genotype plus genotype × environment interaction (GGE) biplot analysis. The study included a total of 25 genotypes, including 20 advanced lines, 3 triticale varieties, and 2 candidate lines. The genotypes were evaluated for GY and quality traits during the 2012/2013 (normal season) and 2013/2014 (late spring frost) seasons. We observed significant differences between seasons for GY and quality traits, as affected by changing environmental conditions over the two seasons. Late spring frost caused a statistically significant 50% reduction in GY, 7.1% reduction in test weight (TW), and 26.1% reduction in thousand grain weight (TGW); however, it positively affected protein content (PC), and it increased by 42.6%. We observed that early heading genotypes were differently affected by late spring frost, compared to late maturing genotypes, in terms of GY, TW, and TGW. The GGE biplot analysis highlighted three and four distinct groups of traits in the 2012/2013 and 2013/2014 growing seasons, respectively. Results from the GGE biplot analysis revealed that G12 and G16 were stable and ideal genotypes for all of the traits in the 2012/2013 season, and G10 and G23 were stable and ideal for the 2013/2014 season. In addition, G10 was the best genotype averaged over the two growing seasons. The genotypes G9, G13, and G17 were more stable and higher yielding, based on Additive Main Effect and Multiplicative Interaction (AMMI) analysis, compared to the remaining genotypes.
Dynamic Programming Approach to Unit Commitment Problem for Kuwait Power Generations

Optimization techniques are becoming essential in the field of power systems. In this paper, two Dynamic Programming (DP) optimization methods were used to solve a large-scale problem which is known as the unit commitment problem (UCP). A sample of ten generating units that forms one power station in Kuwait was chosen to be tested. This paper aims to have a schedule with the least possible electricity production cost while meeting the hourly demand in addition to other system constraints and this is what is known as UCP. A MATLAB code was used to generate solutions for the ten-unit system. The results showed that the conventional DP method reduced the cost by 36.1% while priority DP method reduced the cost by 35%. Since the future NEWKUWAIT vision is introducing renewable energy resources to the power system, solving the UCP will be the first step towards reaching the vision.