Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Microstrip Antennas Using Differential Evolution Algorithm

Differential evolution (DE) algorithm is applied to the design of single-layer and multi-layer microstrip antennas. For the design of single-layer co-axial probe-fed microstrip antenna, fitness function is obtained from cavity model theory of microstrip antenna, whereas for the design of multi-layer aperture-coupled microstrip antenna, transmission line model is used to obtain fitness function for DE. In both the cases, results obtained using DE, are verified with the results, obtained using genetic algorithm (GA) and particle swarm optimization (PSO).
An assistive tele-operated anthropomorphic robot hand: Osaka City University Hand II

This paper presents an anthropomorphic robot hand called Osaka-City-University-Hand II, which is an improved version of Osaka-City-University-Hand I. The cosmetic and the function of our proposed hand allow us to use the hand as a prosthetic hand in addition to as an open platform of robot hands for robotics research. Distributed tactile and force sensors are appended to the OCU-Hand II as a feedback system in order to grasp an object firmly. A new control strategy is to be adopted, in which a master light-weight glove is to be used to drive the OCU-Hand II as a slave. In the tele-operating task, arithmetic operations are to be done to the outputs of the feedback sensors in order to increase the resolution of the master-slave driving technique as well as to overcome the hardware amplification defects. In order to use OCU-Hand II as a helper equipment, a novel and unique assistive mode is included within master-slave control strategy, where the OCU-Hand II is assisting and helping its operators in order to reduce the load on the operator and perform the usual operations in a better manner or even faster than the usual. During the assistive mode the operator is enabled to perform different tasks other than the master-slave driving while he is still putting on the master-glove.
A Quick Browsing System for Surveillance Videos

Surveillance cameras have been widely installed in large cities to monitor and record human activities for different applications. Since surveillance cameras often record all events 24 hours/day, it necessarily takes huge workforce watching surveillance videos to search for specific targets, thus a system that helps the user quickly look for targets of interest is highly demanded. To this end, we propose a quick surveillance video browsing system. Our basic idea is to collect all of moving objects which carry the most significant information in surveillance videos to construct a corresponding compact video by tuning positions of these moving objects. The compact video rearranges the spatiotemporal coordinates of moving objects to enhance the compression, but the temporal relationships among moving objects are still kept. The compact video can preserve the essential activities involved in the original surveillance video. This paper presents the details of our browsing system and the approach to producing the compact video from a source surveillance video.
Security of quantum key distributions with entangled qudits

We consider a generalization of Ekert's entanglement-based quantum cryptographic protocol where qubits are replaced by N- or d-dimensional systems (qudits). In order to study its robustness against optimal incoherent attacks, we derive the information gained by a potential eavesdropper during a cloning-based individual attack. In doing so, we generalize Cerf's formalism for cloning machines and establish the form of the most general cloning machine that respects all the symmetries of the problem. We obtain an upper bound on the error rate that guarantees the confidentiality of qudit generalizations of the Ekert's protocol for qubits.
Metabolomic and Proteomic Profiles Reveal the Dynamics of Primary Metabolism during Seed Development of Lotus (Nelumbo nucifera)

Sacred lotus (Nelumbo nucifera) belongs to the Nelumbonaceae family. Its seeds are widely consumed in Asian countries as snacks or even medicine. Besides the market value, lotus seed also plays a crucial role in the lotus life cycle. Consequently, it is essential to gain a comprehensive understanding of the development of lotus seed. During its development, lotus seed undergoes cell division, expansion, reserve accumulation, desiccation, and maturation phases. We observed morphological and biochemical changes from 10 to 25 days after pollination (DAP) which corresponded to the reserve synthesis and accumulation phase. The volume of the seed expanded until 20 DAP with the color of the seed coat changing from yellow-green to dark green and gradually fading again. Starch and protein rapidly accumulated from 15 to 20 DAP. To further reveal metabolic adaptation, primary metabolites and proteins profiles were obtained using mass spectrometry based platforms. Metabolites and enzymes involved in sugar metabolism, glycolysis, TCA cycle and amino acid metabolism showed sequential dynamics enabling the clear separation of the different metabolic states during lotus seed development. The integration of the data revealed a highly significant metabolic switch at 15 DAP going through a transition of metabolically highly active tissue to the preparation of storage tissue. The results provide a reference data set for the evaluation of primary metabolism during lotus seed development.
A Novel Point Based Non-rigid Registration Method and Its Application on Brain Shift

This paper presents a novel point based non-rigid registration (NRR) method. We overcome the limitations of the traditional point-based NRR methods by using a biomechanical model with a Robust Point Matching framework. Our new framework relies on robust regression technique to handle sparse point sets which are partially correlated. The non-rigid registration problem is formulated as a two variables (Correspondence and Mapping) functional minimization problem. The functional is decomposed into stress and similarity components. Linear Finite Element method using a patient-specific biomechanical model along with Expectation Maximization method are used for the simultaneous computation/approximation of both Correspondence and Mapping function. Gaussian distribution-based search range is used to improve the computational efficiency and robustness of the method. The combination of the search range with Least Trimmed Squared can effectively detect outliers in both source and target point sets. Preliminary performance data from an experimental evaluation for brain shift compensation shows the effectiveness of this method for sparse and even partially correlated source and target point sets.
Exploring the Symbolic Frames of HIV/AIDS-Related Stigma: From Powerlessness to Transformative Empowerment

ABSTRACT Extant research has explored the symbolic depiction of HIV/AIDS-related stigma. Often, the portrayals derive from monolithic constructions of dominant society. However, how People Living with HIV/AIDS (PLWHA) make meaning of these dominant symbolic representations is understudied. This study, drawing from the perspectives of Gamson and Modigliani's (1989) framing devices and Burke's (1950) notion of consubstantiation, explores how PLWHA make meaning of societal symbolic representation of their identity. The meaning making process constitutes entry points for interrogating social depictions that disempower their everydayness. A qualitative analysis of focus groups and in-depth interviews revealed how participants subliminally interrogated dominant symbolic frames of the stigma in ways that were empowering for PLWHA as well as precipitate communicative action for social change.
Capital Taxation with Entrepreneurial Risk

This paper studies the effects of capital taxation in a dynamic heterogeneous-agent economy with uninsurable entrepreneurial risk. Although it allows for rich general-equilibrium effects and a stationary distribution of wealth, the model is highly tractable. This permits a clear analysis, not only of the steady state, but also of the entire transitional dynamics following any change in tax policies. Unlike either the complete-markets paradigm or Bewley-type models where idiosyncratic risk impacts only labor income, here it is shown that capital taxation may actually stimulate capital accumulation. This possibility emerges because of the general-equilibrium effects of the insurance aspect of capital taxation. In particular, for the preferred calibrated version of the model, when the tax on capital is 25 percent, output per work-hour is 2.2 percent higher than it would have been had the tax rate been zero. Turning to the welfare effects of a reform in capital taxation, it is examined how these effects depend on whether one focuses on the steady state or also takes into account transitional dynamics, as well as how they vary in the cross-section of the population (rich versus poor, entrepreneurs versus non-entrepreneurs).
Bio-Inspired Meta-Heuristics for Emergency Transportation Problems

Emergency transportation plays a vital role in the success of disaster rescue and relief operations, but its planning and scheduling often involve complex objectives and search spaces. In this paper, we conduct a survey of recent advances in bio-inspired meta-heuristics, including genetic algorithms (GA), particle swarm optimization (PSO), ant colony optimization (ACO), etc., for solving emergency transportation problems. We then propose a new hybrid biogeography-based optimization (BBO) algorithm, which outperforms some state-of-the-art heuristics on a typical transportation planning problem.
Valuing Air Quality Using the Life Satisfaction Approach

I use the life satisfaction approach to value air quality, combining individual-level panel and high-resolution SO2 data. To avoid simultaneity problems, I construct a novel instrument exploiting the natural experiment created by the mandated scrubber installation at power plants, with wind directions dividing counties into treatment and control groups. I find a negative effect of pollution on well-being that is larger for instrumental variable than conventional estimates, robust to controls for local unemployment, particulate pollution, reunification effects and rural/urban trends, and larger for environmentalists and predicted risk groups. To calculate total willingness-to-pay, the estimates are supplemented by hedonic housing regressions.
Procedural monsters: rhetoric, commonplace and ‘heroic madness’ in video games

ABSTRACT This paper draws on Ian Bogost’s argument that video games constitute a form of ‘procedural rhetoric’, in order to re-examine the representation of heroic madness First-Person-Shooter games. Rejecting the idea that games attempt to recreate the experience of madness to the player through linear representation, the paper instead identifies two persistent commonplace figures which appear within the genre: the monstrous double, and the reaching tentacle. While Bogost’s notion of procedural rhetoric allows analysis to move away from the more facile interpretations of gameplay, the paper argues that these figures also demand an account of the commonplace itself – the rhetorical ‘topic’ – which links the technical structure of gaming procedures with the tropes and figures that enable them to make sense within their wider cultural context and tradition. While the figures of the double and the tentacle purposefully draw on existing tropes and processes associated with the cultural meanings of mental health, a rhetorical analysis of their use of commonplaces suggests that they are not simply recycling older clichés, but constitute a creative ‘reobjectification’ of madness.
Understanding and recommending play relationships in online social gaming

Online Social Networking (OSN) applications such as Facebook's communication and Zynga's gaming platforms service hundreds of millions of users. To understand and model such relationships, social network graphs are extracted from running OSN applications and subsequently processed using social and complex network analysis tools. In this paper, we focus on the application domain of Online Social Games (OSGs) and deploy a formalism for extracting graphs from large datasets. Our formalism covers notions such as game participation, adversarial relationships, match outcomes, and allows to filter out “weak” links based on one or more threshold values. Using two novel large-scale OSG datasets, we investigate a range of threshold values and their influence on the resulting OSG graph properties. We discuss how an analysis of multiple graphs - obtained through different extraction rules - could be used in an algorithm to improve matchmaking for players.
Near-Infrared Spectroscopy based Neurofeedback of Prefrontal Cortex Activity: A Proof-of-Concept Study

Neurofeedback is a promising tool for treatment and rehabilitation of several patient groups. In this proof of principle study, near-infrared spectroscopy (NIRS) based neurofeedback of frontal cortical areas was investigated in healthy adults. Main aims were the assessment of learning, the effects on performance in a working memory (n-back) task and the impact of applied strategies on regulation. 13 healthy participants underwent eight sessions of NIRS based neurofeedback within 2 weeks to learn to voluntarily up-regulate hemodynamic activity in prefrontal areas. An n-back task in pre-/post measurements was used to monitor neurocognitive changes. Mean oxygenated hemoglobin (O2Hb) amplitudes over the course of the sessions as well as during the n-back task were evaluated. 12 out of 13 participants were able to regulate their frontal hemodynamic response via NIRS neurofeedback. However, no systematic learning effects were observed in frontal O2Hb amplitudes over the training course in our healthy sample. We found an impact of applied strategies in only 5 out of 13 subjects. Regarding the n-back task, neurofeedback appeared to induce more focused and specific brain activation compared to pre-training measurement. NIRS based neurofeedback is a feasible and potentially effective method, with an impact on activation patterns in a working memory task. Ceiling effects might explain the lack of a systematic learning pattern in healthy subjects. Clinical studies are needed to show effects in patients exhibiting pathological deviations in prefrontal function.
A Feature Extraction Method for Cursive Character Recognition Using Higher-Order Singular Value Decomposition

The use of Higher-Order Singular Value Decomposition (HOSVD) and other tensor decomposition methods are popular in the face recognition domain, yet a direct application to handwritten character recognition has not shown promising results so far. Character recognition is commonly performed in two steps: feature extraction and classification. In this paper, we propose a feature extraction algorithm based on HOSVD which is then combined with standard statistical classification. The algorithm constructs a tensor from the training data and applies HOSVD in order to obtain a feature extractor matrix for arbitrary character images. We evaluate the proposed handwriting features in combination with SVM classification for character recognition on the CEDAR benchmark data set. The results indicate that our proposed approach significantly outperforms the standard HOSVD classification method.
Optimal method for the affine F-matrix and its uncertainty estimation in the sense of both noise and outliers

We propose, in maximum likelihood sense, an optimal method for the affine fundamental matrix estimation in the presence of both Gaussian noise and outliers. It is based on weighting the squared residuals by the iteratively completed, residual posterior probabilities to be relevant. The proposed principle is also used for the covariance matrix estimation of the affine F-matrix where the novelty is in the fact that all data is used rather than the (erroneously) relevant classified matching points. The experiments on both synthetic and real data verify the optimality of the method in the sense of both false matches and Gaussian noise in data.
Electronic Reprint Applied Crystallography in Situ Data Collection and Structure Refinement from Microcapillary Protein Crystallization Applied Crystallography in Situ Data Collection and Structure Refinement from Microcapillary Protein Crystallization

Author(s) of this paper may load this reprint on their own web site provided that this cover page is retained. Republication of this article or its storage in electronic databases or the like is not permitted without prior permission in writing from the IUCr. In situ X-ray data collection has the potential to eliminate the challenging task of mounting and cryocooling often fragile protein crystals, reducing a major bottleneck in the structure determination process. An apparatus used to grow protein crystals in capillaries and to compare the background X-ray scattering of the components, including thin-walled glass capillaries against Teflon, and various fluorocarbon oils against each other, is described. Using thaumatin as a test case at 1.8 A ˚ resolution, this study demonstrates that high-resolution electron density maps and refined models can be obtained from in situ diffraction of crystals grown in microcapillaries.
College Student Writers' Use and Modification of Planning and Evaluation Strategies After a Semester of Instruction

The purpose of this study was to investigate how students who were enrolled in a developmental writing course at a community college used and adapted cognitive writing strategies learned in the course. The students participated in a funded research project for the development and evaluation of a writing curriculum based on self-regulated strategy instruction. The current study investigated students’ application of the planning and revising strategies using think-aloud protocols. The results showed that students remembered the strategies but did not use them consistently. Also, they tended to use an outline but not always effectively. Finally, reading comprehension seemed to impact their use of revision strategies. Limitations and implications for future research are discussed.
Parallel chemical switches underlying pollinator isolation in Asian Mitella

Floral scents are among the key signals used by pollinators to navigate to specific flowers. Thus, evolutionary changes in scents should have strong impacts on plant diversification, although scent‐mediated plant speciation through pollinator shifts has rarely been demonstrated, despite being likely. To examine whether and how scent‐mediated plant speciation may have occurred, we investigated the Asimitellaria plant lineage using multidisciplinary approaches including pollinator observations, chemical analyses of the floral scents, electroantennographic analyses and behavioural bioassays with the pollinators. We also performed phylogenetically independent contrast analyses of the pollinator/floral scent associations. First, we confirmed that the pairs of the sympatric, cross‐fertile Asimitellaria species in three study sites consistently attract different pollinators, namely long‐tongued and short‐tongued fungus gnats. We also found that a stereoisomeric set of floral volatiles, the lilac aldehydes, could be responsible for the pollinator specificity. This is because the compounds consistently elicited responses in the antennae of the long‐tongued fungus gnats and had contrasting effects on the two pollinators, that is triggering the nectaring behaviour of long‐tongued fungus gnats while repelling short‐tongued fungus gnats in a laboratory experiment. Moreover, we discovered that volatile composition repeatedly switched in Asimitellaria between species adapted to long‐tongued and short‐tongued fungus gnats. Collectively, our results support the idea that recurrent scent‐mediated speciation has taken place in the Asimitellaria–fungus gnat system.
Comparison of the ASTM Comparative Chart Method and the Mean Line Intercept Method in Determining the Effect of Solidification Rate on the Yield Strength of AA5182

The purpose of this laboratory was to determine the effect of cooling rate on the yield strength of metals. The sample photomicrographs provided were of a single AA5182 sample cooled at various rates. Each photomicrograph was taken with polarized light at 50x magnification. First the photomicrographs were examined using the ASTM comparative chart method. Then each photomicrograph was examined using the mean line intercept method. The ASTM grain size was calculated for each photomicrograph using the results of both methods. The Hall-Petch Equation was then used to determine the yield strength of the metal at the points where the photomicrographs were taken. There were some slight discrepancies in the results using the different methods but both the ASTM comparative chart and the mean line intercept method show the same trends in the yield strength of the sample at the various cooling rates. Both methods show that as the cooling rate of the metal decreases the yield strength also decreases.
CD1d-restricted Recognition of Synthetic Glycolipid Antigens by Human Natural Killer T Cells

A conserved subset of mature circulating T cells in humans expresses an invariant Vα24-JαQ T cell receptor (TCR)-α chain rearrangement and several natural killer (NK) locus–encoded C-type lectins. These human T cells appear to be precise homologues of the subset of NK1.1+ TCR-α/β+ T cells, often referred to as NK T cells, which was initially identified in mice. Here we show that human NK T cell clones are strongly and specifically activated by the same synthetic glycolipid antigens as have been shown recently to stimulate murine NK T cells. Responses of human NK T cells to these synthetic glycolipids, consisting of certain α-anomeric sugars conjugated to an acylated phytosphingosine base, required presentation by antigen-presenting cells expressing the major histocompatibility complex class I–like CD1d protein. Presentation of synthetic glycolipid antigens to human NK T cells required internalization of the glycolipids by the antigen-presenting cell and normal endosomal targeting of CD1d. Recognition of these compounds by human NK T cells triggered proliferation, cytokine release, and cytotoxic activity. These results demonstrate a striking parallel in the specificity of NK T cells in humans and mice, thus providing further insight into the potential mechanisms of immune recognition by NK T cells and the immunological function of this unique T cell subset.
Efficient parameter training for hidden Markov models using posterior sampling training and Viterbi training

Hidden Markov models are widely employed by numerous Bioinformatics programs used today. Many existing Bioinformatics applications risk becoming obsolete unless they can be readily adapted to new data sets, for example by incorporating algorithms for automatic parameter training. We present a new method for training the parameters of hidden Markov models using sampled state paths. As these state paths are sampled from the posterior distribution, we call our new training algorithm posterior sampling training. We also introduce a computationally efficient, linear-memory algorithm for posterior sampling training. In addition, we introduce the first linear-memory algorithm for Viterbi training. We evaluate posterior sampling training by comparing it to Viterbi training and Baum-Welch training for a hidden Markov model and find that posterior sampling training outperforms Baum-Welch training in terms of performance and computationally efficiency and that it is significantly more robust than the commonly used method of Viterbi training.