Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of the Steady-State Suppression on Consonant Identification by Native and Non-Native Listeners in Reverberant Environments (国際ワークショップ Frontiers in Speech and Hearing Research)

This study investigated whether the steady-state suppression proposed by Arai et al. (Proc. Autumn Meet. Acoust. Soc. Jpn., 2001; Acoust. Sci. Tech., 2002) improved consonant identification for non-native listeners in reverberation. This study also compared the effect of steady-state suppression on consonant identification by native and non-native listeners in reverberant environments. We used steady-state suppression as a pre-processing technique which processes speech signals before they are radiated from loudspeakers in order to reduce the amount of overlap-masking. Participants were 24 native English (native listeners) and 24 Japanese speakers (non-native listeners), both with normal hearing. A diotic Modified Rhyme Test (MRT) was conducted under 2 processing conditions (with or without steady-state suppression) for 3 reverberant conditions (reverberation times of 0.4, 0.7 and 1.1 s) and a dry condition. The results showed that native listeners performed better than non-native listeners in all conditions used in this study. Although there were no significant differences between unprocessed and steady-state suppressed stimuli, and no significant interaction between the effect of the steady-state suppression and listener group under the reverberant conditions used in the current study, the effect of the steady-state suppression differed in consonant position, reverberation time and listener group. These findings imply that a pre-processing technique would be required which helps non-native listeners to identify consonants as well as native listeners do. Keyword Speech enhancement, Non-native listeners, Reverberation, Steady-state suppression, Speech intelligibility
Modeling of Mass and Heat Transport in Planar Substrate Type SOFCs

A mathematical model is presented that incorporates the mass transport by diffusion in the porous structure of thick substrate type solid oxide fuel cells ~SOFCs! On the basis of the mean transport pore model a multidimensional study allows for an optimization of the structural parameters of the substrates with respect to cell performance. Next to the mass transport in the porous substrates the electrochemical kinetics, methane/steam reforming and shift reaction, and energy equations are integrated in the model and boundary as well as operation conditions can be varied. Two-dimensional simulations for both anode as well as cathode substrate describe the extension of the existing model to two dimensions. The analysis emphasizes mass transport in porous electrodes, especially in the problematical zone below the interconnect ribs. Furthermore, the cathode substrate concept is considered as well, which has not been done before. Model The model was developed for a SOFC based on a planar sub- strate type concept. The fuel cell is considered to operate on either hydrogen or a ~prereformed! methane/steam mixture as fuel and oxygen from air as oxidant. Next to the description of the electro- chemical reactions, the methane/steam reforming and shift reactions, the heat-transfer and the mass-transfer processes are included in the model. Distinct from previous models, the fuel and oxidant flow, i.e., multicomponent transport, were developed for a realistic fuel cell comprising porous elements, based on a finite-volume-based computational fluid dynamics ~CFD! approach. For this purpose the model calculations were performed using the commercial CFD- package FLUENT. Model assumptions. —Ideal gas mixtures, incompressible and laminar flow due to small gas velocities, and pressure gradients are assumed. The electrodes have a homogeneous, isotropic structure and no gradients within mechanical properties. The electrolyte is regarded as an infinite thin layer between anode and cathode. In the model the mass and heat sources according to the electrochemical conversion arise in the boundary cells of the anode next to the elec- trolyte. The thickness of these boundary cells depends on the trun- cation grade of the anode.
Zhou, Yan and Zeng, Fan-Zhi and Zhao, Hui-min and Murray, Paul and Ren, Jinchang (2016) Hierarchical visual perception and two- dimensional compressive sensing for effective content-based color

Content-based image retrieval (CBIR) has been an active research theme in the computer vision community for over two decades. While the field is relatively mature, significant research is still required in this area to develop solutions for practical applications. One reason that practical solutions have not yet been realized could be due to a limited understanding of the cognitive aspects of the human vision system. Inspired by three cognitive properties of human vision, namely, hierarchical structuring, color perception and embedded compressive sensing, a new CBIR approach is proposed. In the proposed approach, the Hue, Saturation and Value (HSV) color model and the Similar Gray Level Co-occurrence Matrix (SGLCM) texture descriptors are used to generate elementary features. These features then form a hierarchical representation of the data to which a two-dimensional compressive sensing (2D CS) feature mining algorithm is applied. Finally, a weighted feature matching method is used to perform image retrieval. We present a comprehensive set of results of applying our proposed Hierarchical Visual Perception Enabled 2D CS approach using publicly available datasets and demonstrate the efficacy of our techniques when compared with other recently published, state-of-the-art approaches.
IN SILICO DETECTION OF SIGNATURES FOR ADAPTIVE EVOLUTION AT SELECT INNATE IMMUNE AND HEAT STRESS GENES IN INDIGENOUS POULTRY

Indigenous poultry such as chickens and ducks have unique embedded adaptive traits which have evolved hence allowed their survival under varied environmental conditions. They provide a cheap source of protein in developing countries especially those in Sub-Saharan Africa. However, indigenous poultry are threatened by emerging disease outbreaks that are virulent and often associated with climate change conditions such as drought. Therefore, the objective of this work was to identify genetic signatures of natural selection at Toll-like Receptor 3 (TLR3), Toll-like Receptor 7 (TLR7), Protein Kinase R (PKR), 2’ 5’ - Oligoadenylate Snynthetase 1, Heat Shock Protein 90 (HSP90), Heat Shock Protein 70 (HSP70) and Small Heat Shock Proteins (sHSPs). A reciprocal BlastP algorithm was used to search a non-redudant protein database with an expectation value cut off of 1e-10 so as to obtain homologs. MUSCLE was used to perform Multiple Sequence Alignment, sequences edited in Jalview and MEGA v6 used for evolutionary substitution model selection and rate heterogeneity testing. Phylogeny reconstruction was built using FastME software that implements Nearest Neighbor Interchange and Subtree Pruning and Regrafting (SPR) algorithms. The reliability of the phylogeny tree generated was evaluated using 1000 bootstrap replicates. Codon substitution models in PAML were used to compute the rate of nonsynonymous to synonymous substitutions in different amino acid sites and lineages through likelihood Ratio Tests (LRTs). Heat shock protein genes results revealed signatures of negative selection suggestive of high evolutionary conservation. The results from disease-resistant genes revealed signatures of positive selection at several amino acid sites that encode protein domains. This is a good primer towards genetic development of better adapted and highly productive poultry breeds. This will likely reduce disease and drought-related morbidity in poultry, hence alleviation of food insecurity and better economic growth. Key words: Signatures, toll-like receptor, heat shock proteins, p rotein kinaseR, dN/dS, oligoadenylate Synthase 1
Diminished reality using plane-sweep algorithm with weakly-calibrated cameras

We present a plane-sweep algorithm for removing occluding objects in front of the objective scene from multiple weakly-calibrated cameras. Projective grid space (PGS), a weak cameras calibration framework, is used to obtain geometrical relations between cameras. Plane-sweep algorithm works by implicitly reconstructing the depth maps of the targeted view. By excluding the occluding objects from the volume of the sweeping planes, we can generate new views without the occluding objects. The results show the effectiveness of the proposed method and it is fast enough to run in several frames per second on a consumer PC by implementing the proposed plane-sweep algorithm in graphics processing unit (GPU).
Linearization strategies for high sensitivity magnetoresistive sensors

Ultrasensitive magnetic field sensors envisaged for applications on biomedical imaging require the detection of low-intensity and low-frequency signals. Therefore linear magnetic sensors with enhanced sensitivity low noise levels and improved field detection at low operating frequencies are necessary. Suitable devices can be designed using magnetoresistive sensors, with room temperature operation, adjustable detected field range, CMOS compatibility and cost-effective production. The advent of spintronics set the path to the technological revolution boosted by the storage industry, in particular by the development of read heads using magnetoresistive devices. New multilayered structures were engineered to yield devices with linear output. We present a detailed study of the key factors influencing MR sensor performance (materials, geometries and layout strategies) with focus on different linearization strategies available. Furthermore strategies to improve sensor detection levels are also addressed with best reported values of ∼40 pT/√Hz at 30 Hz, representing a step forward the low field detection at room temperature.
Advanced nanocomposite membranes for fuel cell applications: a comprehensive review

Combination of inorganic fillers into organic polymer membranes (organic–inorganic hybrid membranes) has drawn a significant deal of attention over the last few decades. This is because of the incorporated influence of the organic and inorganic phases towards proton conductivity and membrane stability, in addition to cost decline, improved water retention property, and also suppressing fuel crossover by increasing the transport pathway tortuousness. The preparation methods of the composite membranes and the intrinsic characteristics of the used particles as filler, such as size, type, surface acidity, shape, and their interactions with the polymer matrix can significantly affect the properties of the resultant matrix. The membranes currently used in proton exchange membrane fuel cells (PEMFCs) are perfluorinated polymers containing sulfonic acid, such as Nafion®. Although these membranes possess superior properties, such as high proton conductivity and acceptable chemical, mechanical, and thermal stability, they suffer from several disadvantages such as water management, CO poisoning, and fuel crossover. Organic-inorganic nanocomposite PEMs offer excellent potentials for overcoming these shortcomings in order to achieve improved FC performance. Various inorganic fillers for the fabrication of composite membranes have been comprehensively reviewed in the present article. Moreover, the properties of polymer composites containing different nanoparticles have been thoroughly discussed.
An energy-efficient route to the rapid synthesis of organically-modified SBA-15 via ultrasonic template removal

A low energy route for the removal of Pluronic P123 surfactant template during the synthesis of SBA-15 mesoporous silicas is explored. The conventional reflux of the hybrid inorganic–organic intermediate formed during co-condensation routes to Pr-SO3H-SBA-15 is slow, utilises large solvent volumes, and requires 24 h to remove ∼90% of the organic template. In contrast, room temperature ultrasonication in a small methanol volume achieves the same degree of template extraction in only 5 min, with a 99.9% energy saving and 90% solvent reduction, without compromising the textural, acidic or catalytic properties of the resultant Pr-SO3H-SBA-15.
Chemically modified PTFE particles as solid lubricant additive for the fixation on substrate surfaces

During the irradiation of high molecular weight poly(tetrafluoroethylene) (PTFE) in presence of oxygen perfluoroalkyl(peroxy) radicals and functional groups are formed which allow chemical coupling reactions (cc = chemical compatibilized) with oils and plastics. Contrary to the well-known inert properties of perfluorinated organic compounds high-effective additives can be produced by radiation modification and subsequent chemical compatibilization of such substances with olefinically unsaturated groups of oils/lubricants. By the irradiation process high molecular weight PTFE degrades by C-C and C-F bond scission to lower molecular weight PTFE microparticles which possess perfluoroalkyl(peroxy) radicals. These radicals are used for the chemical compatibilization reaction with olefinically unsaturated groups base oils. The tribological properties and the dispersion stability of the resulting oil-PTFE-cc (cc = chemical compatibilized) dispersions are significantly enhanced in comparison to physical mixture of oil and PTFE micropowder. These oil-PTFE-cc-dispersions show primarily anti-wear (AW) properties. The use of reactive groups (e.g. phosphite groups) in the oil gives the dispersions extreme pressure (EP) properties additionally. This article demonstrates the usefulness of the oil-PTFE-cc-dispersions in rolling bearings using phosphite-modified PTFE products as additive in lubricants (FE-8 test). The investigations are completed by the examination of roller elements by SEM/EDX analysis. A model is shown to explain the effect of phosphite groups on oxidic/hydrolytic metal surfaces.
High-resolution quantification of atmospheric CO 2 mixing ratios in the Greater Toronto Area, Canada

Abstract. Many stakeholders are seeking methods to reduce carbon dioxide (CO2) emissions in urban areas, but reliable, high-resolution inventories are required to guide these efforts. We present the development of a high-resolution CO2 inventory available for the Greater Toronto Area and surrounding region in Southern Ontario, Canada (area of ∼ 2.8 × 105 km2, 26 % of the province of Ontario). The new SOCE (Southern Ontario CO2 Emissions) inventory is available at the 2.5 × 2.5 km spatial and hourly temporal resolution and characterizes emissions from seven sectors: area, residential natural-gas combustion, commercial natural-gas combustion, point, marine, on-road, and off-road. To assess the accuracy of the SOCE inventory, we developed an observation–model framework using the GEM-MACH chemistry–transport model run on a high-resolution grid with 2.5 km grid spacing coupled to the Fossil Fuel Data Assimilation System (FFDAS) v2 inventories for anthropogenic CO2 emissions and the European Centre for Medium-Range Weather Forecasts (ECMWF) land carbon model C-TESSEL for biogenic fluxes. A run using FFDAS for the Southern Ontario region was compared to a run in which its emissions were replaced by the SOCE inventory. Simulated CO2 mixing ratios were compared against in situ measurements made at four sites in Southern Ontario – Downsview, Hanlan's Point, Egbert and Turkey Point – in 3 winter months, January–March 2016. Model simulations had better agreement with measurements when using the SOCE inventory emissions versus other inventories, quantified using a variety of statistics such as correlation coefficient, root-mean-square error, and mean bias. Furthermore, when run with the SOCE inventory, the model had improved ability to capture the typical diurnal pattern of CO2 mixing ratios, particularly at the Downsview, Hanlan's Point, and Egbert sites. In addition to improved model–measurement agreement, the SOCE inventory offers a sectoral breakdown of emissions, allowing estimation of average time-of-day and day-of-week contributions of different sectors. Our results show that at night, emissions from residential and commercial natural-gas combustion and other area sources can contribute > 80 % of the CO2 enhancement, while during the day emissions from the on-road sector dominate, accounting for > 70 % of the enhancement.
Using Inferential Robustness to Establish the Security of an Evidence Claim

Evidence claims depend on fallible assumptions. This paper discusses inferential robustness as a strategy for justifying evidence claims in spite of this fallibility. I argue that robustness can be understood as a means of establishing the partial security of evidence claims. An evidence claim is secure relative to an epistemic situation if it remains true in all scenarios that are epistemically possible relative to that epistemic situation.
Selection of mild virus strains of fanleaf degeneration by comparative field performance of infected grapevines

Healthy clones of Vitis vinifera L. cultivars Klevener de Heiligenstein, Chardonnay and Pinot noir were graft-inoculated with one clone of the rootstock Kober 5BB infected with potential mild strains of arabis mosaic virus (ArMV-Ta) or grapevine fanleaf virus (GFLV-CB844 or -F13). Such infected vines were planted in a nematode-free replant site and screened for comparative field performance on pruning weight, crop yield, bunch weight, and sugar content over a 5-year period. ArMV-Ta had the mildest impact on both vigor and yield for all three V. vinifera cultivars tested. The impact of ArMV-Ta, along with the other two GFLV strains, was much less evident during the last two years of the trial. Based on these results, ArMV-Ta was selected as a potential mild strain for cross-protection to control fanleaf degeneration. Our field trial also showed that field performance of infected vines was not affected by the vein mosaic virus-like disease.
On The Modelling of Electrowetting in COMSOL MultiPhysics

Abst ract: Electrowetting is a popular tool for manipulating small amounts of liquid. In this paper, we take a closer look at the ‘mechanism’ of electrowetting displays. We describe the physics which drive the phenomenon (Section 2). The equations are rewritten such that they can be implemented in COMSOL Multiphysics (Section 3). And in the last section, results of the implementation using COMSOL’s two phase flow with level set and the electrostatic module are shown (both for 2D and for 3D). A comparison of the ‘break up’ of the oil layer in 2D and an analytical calculation of the forces are compared.
SeamScape A procedural generation system for accelerated creation of 3D landscapes

This bachelor thesis rose from the idea of speeding up game production by using procedural generation techniques. Procedural generation in the project’s scope involves the algorithmic production of data which represents a 3D environment. This bachelor thesis describes Seamscape, an application which procedurally generates landscapes in real-time consisting of terrain, water, vegetation, and rocks. The purpose of the thesis was to use procedural generation as a means to create 3D environments in real-time. Generating landscapes in real-time as opposed to beforehand allows the user to visualize a design quickly, especially for an interface with many design options. However, this project focused more on generating environments than providing freedom of design. Simultaneously, the software design takes user design possibilities into account for future development. The methods employed are heterogeneous, and apply to specific parts of the landscape. Vegetation was created using L-systems and the terrain was built with noise functions. Distribution of vegetation on the heightmap was done with a technique using ecosystems. The project invented a method to create rivers, based on a selection of studies. Additionally, the rock generation process was tailored to the project, using a low-polygonal style. The results show that procedural generation of low-polygonal environments consisting of terrain, water, vegetation, and rocks is possible in real-time. Seamscape generates environments with all these features. Future development ideas lay mainly within the domain of diversification and extending the design possibilities for the user. In conclusion, the chosen methods were suitable for procedural generation of landscapes in real-time.
BPGD-AG: A New Improvement Of Back-Propagation Neural Network Learning Algorithms With Adaptive Gain

The back propagation algorithm is one of the popular learning algorithms to train self learning feed forward neural networks. However, the convergence of this algorithm is slow mainly because the algorithm required the designers to arbitrarily select parameters such as network topology, initial weights and biases, learning rate value, the activation function, value for gain in activation function and momentum. An improper choice of theses parameters can result the training process comes to as standstill or get stuck at local minima. Previous research demonstrated that in a back propagation algorithm, the slope of the activation function is directly influenced by a parameter referred to as ‘gain’. In this paper, the influence of the variation of ‘gain’ on the learning ability of a back propagation neural network is analysed. Multi layer feed forward neural networks have been assessed. Physical interpretation of the relationship between the gain value and the learning rate and weight values is given. Instead of a constant ‘gain’ value, we propose an algorithm to change the gain value adaptively for each node. The efficiency of the proposed algorithm is verified by means of simulation on a function approximation problem using sequential as well as batch modes of training. The results show that the proposed algorithm significantly improves the learning speed of the general back-propagation algorithm.
A RELATIONAL PERSPECTIVE ON CULTURE IN LATE MODERNITY

The subject of this article deals with the manner in which emotions have so far been considered in sociological migration studies. Existing works focus primarily on emotions in a pathological or therapeutic way, so it has to be stated, that the often postulated emotional turn in social sciences has not yet fully reached the area of migration. So the valuable analytical potential of a perspective based on the sociology of emotions is not completely exploited because that would imply focusing on the general functions of emotions in contexts of migration. This article introduces interesting works which already deal with the carrying concepts of emotion work and emotional transnationality and suggests guidelines on how to broaden these analytical views in a non-pathological direction.
Comparing the Consumer Price Index with the Gross Domestic Product Price Index and Gross Domestic Product Implicit Price Deflator

The Consumer Price Index (CPI) and the gross domestic product (GDP) price index and implicit price deflator are measures of inflation in the U.S. economy. The CPI measures price changes in goods and services purchased out of pocket by urban consumers, whereas the GDP price index and implicit price deflator measure price changes in goods and services purchased by consumers, businesses, government, and foreigners, but not importers. Thus, which one to use in a given scenario depends on one’s purpose.