Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing the speech-in-noise abilities of school-age children with a history of middle-ear diseases

Proceedings of the International Symposium on Auditory and Audiological Research (Proc. ISAAR), Vol. 7: Auditory Learning in Biological and Artificial Systems, August 2019, Nyborg, Denmark. Edited by A. Kressner, J. Regev, J. C. -Dalsgaard, L. Tranebjærg, S. Santurette, and T. Dau. The Danavox Jubilee Foundation, 2019. © The Authors. ISSN: 2596-5522. Characterizing the speech-in-noise abilities of school-age children with a history of middle-ear diseases
ANALYSIS OF HIERARCHICAL CONTROL IN A DC MICROGRID WITH DROOP STRATEGY APPLIED TO A FRONT-END DC-AC CONVERTER TO REGULATE DC BUS VOLTAGE

 This work investigates the influence of a droop control approach implemented to a front-end DC-AC converter connected to a DC microgrid. Distributed energy systems operating in a DC microgrid structure have been gaining traction recently, mainly due to the simplification process in the integration of renewable generation and energy storage systems. One of the most common strategies to guarantee proper operation of these structures is the droop control, which presents relatively easy implementation, enables microgrid coordination and also DC bus voltage regulation. However, the droop method lacks robustness and can present errors when lines between the terminals have non negligible impedances. This drawback can be mitigated with hierarchical control topologies. In addition to the aforementioned strategies, front-end DC-AC converters are also capable of contributing with DC bus voltage regulation if provided with proper droop strategy. To the best of the authors knowledge, this type of control has not been thoroughly explored, though. To partially fill this gap, the authors implemented a DC microgrid model in software environment, considering line cable impedances between units. In the front-end converter, the droop strategy is employed using the synchronous reference frame technique. Simulation results are presented to illustrate the influence of the control developed for the front-end converter in the performance of the microgrid, focusing on the primary and secondary responses. A comparison with the operation regimen under the most common control approach found in literature is also reported. Keywords Hierarchical Control, Droop Control, DC microgrids, Smart Grids.
Habitat suitability of Proboscis monkey (Nasalis larvatus) in Berau Delta, East Kalimantan, Indonesia

The proboscis monkey (Nasalis larvatus) is an endemic species to Borneos’ island and is largely confined to mangrove, riverine, and swamp forest. Most of their habitat is outside the conservation due to degraded and habitat converted. Habitat loss is a significant threat to a decreased in the monkey's population. Berau Delta is an unprotected habitat of proboscis monkey, lacking in attention and experiencing a lot of disturbances. This study was conducted on April – August 2019; with aims of the study is to determine Species Distribution Modeling (SDM) for identifying proboscis monkey habitat suitability in Delta Berau, East Kalimantan. The MaxEnt algorithm was used to produce a habitat suitability map based on this species’ occurrence records and environmental predictors. We built the models using 208 points of proboscis monkey presence and 12 environment variables within the study area. Model performance was assessed by examining the area under the curve. The variables most influencing the habitat suitability model were the riverine habitat (60.9%), distance from the pond (16.0%), and distance from the coastline (5.2%). The proboscis monkey suitable habitat is only 9.32% (8,726.58 ha) from 93,631.41 ha total area. The appropriate habitat areas are Sapinang Island, Bungkung Island, Sambuayan Island, Saodang Kecil Island, Besing Island, Lati River, Bebanir Lama, Batu-Batu, and Semanting Bay. We provide some suggestions for the proboscis monkey conservation, which are local protection of uninhabited islands, participatory ecotourism management, and company involvement in protection and management efforts.
Human action recognition method based on conformal geometric algebra and recurrent neural network

Deep Learning (DL) plays an important role in machine learning and artificial intelligence. DL is widely applied in many fields with high dimensional data, including natural language processing, image recognition. High dimensional data can lead to problems in machine learning such as overfitting, degradation of accuracy. To address these issues, some methods, such as Principal Components Analysis (PCA), principal component regression (PCR), Multi-class Linear Discriminant Analysis (MLDA), were proposed to reduce dimensions of the data and computational complexity simultaneously. The drawback of these methods is that they only work well on data distributed on the plane. In the case of the data distributed on the hyper-sphere, such as objects moving in space, the processing results are not so good as expected. In this paper, we propose the use of Conformal Geometric Algebra (CGA) to extract features and simultaneously reduce the dimensionality of a dataset for human activity recognition using Recurrent Neural Network (RNN). First, human activity data in a 3-dimensional coordinate system is pre-processed and normalized by calculating deviations from the mean coordinate. Next, the data is transformed to vectors in CGA space and its dimensions are reduced to return the feature vectors. Finally, we use the RNN model to train feature vectors. Empirical results performed on the CMU eight actions dataset show that the CGA combined with RNN gave the best test results of 92.5%.
Assimilation of MERIS FAPAR into a Terrestrial Vegeitation Model and Mission Design

The current and future strength of the terrestrial carbon sink has a crucial influence on the expected degree of climate warming humanity is going to face. Usually, Earth Observation (EO) by its very nature focuses on diagnosing the current state of the planet. However, it is possible to use EO products in data assimilation systems to improve not only the diagnostics of the current state, but also the accuracy of future predictions. This contribution reports from an on-going ESA funded study (see http://rs.ccdas.org) in which the MERIS FAPAR product is assimilated into a terrestrial biosphere model within the global Carbon Cycle Data Assimilation System (see http://CCDAS.org). Using methods of variational data assimilation, CCDAS relies on first and second derivatives of the underlying model for estimating process parameters with uncertainty ranges. In a subsequent step these parameter uncertainties are mapped forward onto uncertainty ranges for predicted carbon fluxes. In this contribution, we quantify how MERIS data improve the accuracy of the current and future (net and gross) carbon flux estimates for a range of sites spanning the major biomes of the globe. We further present first assimilation experiments of MERIS FAPAR at the global scale together with in situ observations of atmospheric CO2 in a coarse-resolution setup of CCDAS and address the systematic application of CCDAS for the design of future space missions. As an example application we demonstrate that even with considerably higher accuracy MERIS-like products can only provide a weak constraint on long-term carbon fluxes.
Effect of In Silico Site-Directed Mutagenesis of Trp164 and Ser165 on the Predicted 3D structure of the C-Terminal Domain of Glutathione s-transferase from Acidovoras sp. KKS102

In silico site-directed mutagenesis of two evolutionarily conserved amino acids, Trp164 and Ser165 in the C-terminal domain of cytosolic glutathiones transferase from Acidovorax sp. KKS102, a biphenyl/polychlorobiphenyl degrading bacterium was carried out using a SWISS MODEL DeepView/Swiss-Pdb viewer molecular graphics program. Of all the proteinogenic amino acids used for the mutation, only substitutions for Gly, W164G and S165G were found to likely affect the stability of the C-terminal domain of the both protein models. However, S165P and S165W substitutions at position 165 were theoretically predicted to affect the 3D model of the GSTKKS102 by either introducing a sharp turn in the peptide as proposed for Pro substitution, or by replacing the predicted hydrogen bond interactions contributed by Ser side chain with proposed hydrophobic interactions by the nonpolar aromatic Trp side chain. This hydrophobic interaction may result in the formation of a hydrophobic region in the C-terminal domain of GSTKKS102 models and consequently changes the stability of the protein structure and perhaps, its function.
Investigation of Chlamydia psittaci in pet birds of Uberlândia, Minas Gerais, Brazil

Andressa Afonso Borges1 , Daniel Amaral Gontijo2 , Ana Carolina de Andrade Mello Cintra de Amorin3  & Karinne Spirandelli Carvalho Naves4*  1Veterinarian. Autonomous, Uberlândia, MG, Brasil 2Veterinarian. Autonomous, Moema, MG, Brasil 3Veterinarian, Resident in Medicina de Animais Selvagens. Clínica Veterinária Vida Silvestre, Uberlândia, MG, Brasil 4Dentist, Professor. Departamento de Microbiologia, Instituto de Ciências Biomédicas, Universidade Federal de Uberlândia – UFU, Campus Umuarama, Uberlândia, MG, Brasil
From experiencing sites of past to the future of the Demolition Man

This paper explores the possibilities graffiti can provide to research user experience, focusing in those that might emerge in urban environments. The concept of User Experience (UX) can be seen as a consciously experienced phenomenon entailing for example biological, psychological and cultural, spatial and temporal aspects. Graffiti can be used as a tool to study experiences and meanings in physical and social places and practices. This can be done by studying direct experiences while completing a task, but also for example by narratives and memories involving graffiti. As the technology develops, it is incorporated in our lives, becoming more adaptive and virtual. This might have a strong impact in our future experiences while engaging with urban systems.
Structured Vectors for Chinese Word Representations

 Abstract —The use of word representations has been a key reason for the success of many NLP tasks. A lot of work has focused on improving the learning of word representations, and most approaches treat word as atomic unit. However, in some languages, for example Chinese, some words cannot be recognized correctly. This leads to the corruption of word embeddings’ ability to capture semantic information. This paper addresses this shortcoming by proposing structured embeddings for word representations. Our method utilizes sub-word and atomic unit embeddings to represent word embeddings. We build structured vectors for Chinese word representations based on the method, and evaluateon SemEval-2012 Task 4: Measuring Chinese word similarity. The result shows that our method is remarkably effective in capturing semantic information and outperforms previous best performance by a large margin. Our method can be extended to the languages which do not have a trivial word segmentation process.
Neural Networks Based Modeling with Adaptive Selection of Hidden Layer's Node for Path Loss Model

The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.
Dynamic Modelling and Experimental Validation of a Solid State Fermentation Reactor

Abstract A mathematical model is presented that predicts the non-isothermal dynamical behavior of a pilot-plant Solid State Fermentation (SSF) fed-batch reactor, employed in the preparation of compost for the Agaricus bisporus mushroom cultivation. The 9-ODE first-principles lumped-parameter model describes microbial growth, substrate consumption, compost solid and liquid volumetric fractions as well as bulk temperature and air humidity. The biomass is divided into 3 broad families with different macro-kinetics: mesophilic bacteria and fungi that may inhibit the A. bisporus growth, thermophilic fungi associated to the growth selectivity of A. bisporus and thermophilic actinobacteria degrading lignocellulose. Free-convection and evaporative heat transfer are included in the energy balance. Kinetic parameters were adjusted using a sensitivity analysis. The resulting model reproduces accurately the temperature profiles of the pilot-plant SSF reactor for different initial conditions and predicted final microflora concentration ratios are within expected values.
The Effects of Transport Infrastructure on India’s Urban and Rural Development*

This paper uses a two-sector domestic trade model to study urban and rural development in India over the past decade. Based on a version of the market access approach proposed by Donaldson and Hornbeck (2016), we derive general equilibrium relationships between a sector’s income and it’s access to markets in both the urban and rural sectors. While the one-sector model that is often used in the literature predicts a constant elasticity of income with respect to market access, the two-sector version allows for heterogeneous effects. We use satellite data to measure urban and rural growth in 5,900 sub-districts where we assign areas to either urban or rural sectors based on a threshold for urban light intensity. In order to estimate the relationship between income and market access, we exploit changes in transportation infrastructure that have led to reductions in travel times on the computed shortest path. The implied reduction in trade costs generates variation in the market access measures. This time variation allows us to estimate the elasticity of income in each sector with respect to market access in the own and the other sector. The results suggest that both urban and rural market access are each individually strongly correlated with income, but they are empirically difficult to disentangle when estimating jointly. We then study the role of various complementary factors that potentially play different roles for urban and rural production and could imply heterogeneous effects of transport infrastructure. We consider natural resources like ground water, rainfall, temperature, and the availability of crop land, as well as measures for human capital. The evidence on interaction effects is mixed and mostly suggests that the effect of market access is relatively stable.
Comparing Word Affect and Tone Affect: Comment on Sun and Cuthbert 2017

In the article "Emotion Painting: Lyric, affect, and musical relationships in a large lead-sheet corpus", Sun and Cuthbert (2017) explored the correlations between affect-carrying lyrics and musical features such as beat strength, pitch height, consonance, and mode. Several musical features did indeed turn out to be highly correlated with the affect of the lyrics. However, correlations between other features, particularly mode-related musical features and lyric affect, were either insignificant or even contradicted previous research. In the current commentary, it is argued that the difference between the musical features that show significant correlations and those that do not is that the former have a local musical effect whereas the latter tend to affect the mood of a whole phrase or piece, and that the way Sun and Cuthbert estimate lyric affect for sentences or song may not be appropriate. Furthermore, a few remarks are made about the way Sun and Cuthbert treat multi-syllable words and about some basic assumptions concerning the relation between music and lyrics in a song. Nevertheless, the authors are praised for their innovative and interesting work, while several alternative and additional analyses (for example with scale-degree qualia and syncopations) are proposed.
10,000-M RACE WALKING COMPETITION

Vernillo, G, Agnello, L, Drake, A, Padulo, J, Piacentini, MF, and Torre, AL. An observational study on the perceptive and physiological variables during a 10,000-m race walking competition. J Strength Cond Res 26(10): 2741–2747, 2012—In this study, we observed the variations on physiological and perceptual variables during a self-paced 10,000-m race walking (RW) event with the aim to trace a preliminary performance profile of the distance. In 14 male athletes, the heart rate (HR) was monitored continuously throughout the event. The rating of perceived exertion (RPE) was collected using the Borg’s 6–20 RPE scale placed at each 1,000 m of an outdoor tartan track. Pacing data were retrieved from the official race results and presented as percent change compared with the first split time. The athletes spent 95.4% at 90–100% of the HRpeak, whereas the other work (4.6%) was negligible. During the race, a shift toward higher HR values was observed because % HRpeak increased by 3.6% in the last vs. the first 1,000-m sector (p = 0.002, effect size [ES] = 1.55 6 0.68, large). The mean RPE reported by the athletes in the last 1,000 m was significantly higher than in the first 5 sectors (p , 0.02, ES = 1.93–2.96, large to very large). The mean percent change increased between the first 6 sectors and the last 1,000-m sector (p , 0.01, ES = 1.02–2.1, moderate to very large). The analysis of walking velocity at each 1,000-m sector suggested the adoption of a negative pacing. In conclusion, the RPE may be a valid marker of exercise intensity even in real settings. Match physiological and perceptual data with work rate are required to understand race-related regulatory processes. Pacing should be considered as a conscious behavior decided by the athletes based on the internal feedback during the race.
The challenges of conducting qualitative research: Student perspectives from the United Arab Emirates

Research activity and output is increasingly seen as a mark of excellence. Emerging education sectors often struggle to compete on this stage due to lack of experience or awareness of the process. Student research is an oft under-explored area of this debate and one that requires further attention an analysis. This paper uses a mixed methods approach and an ethnographic case study of two private universities in Dubai, in order to explore the experiences and challenges university students face when conducting research. Set against the backdrop of research output and rankings, this paper addresses key questions and proposes institutional responses to support student engagement, understanding and output.
Design and Deployment of an IoT-Based Water Quality Monitoring System for Aquaculture in Mekong Delta

The Mekong River Delta is a key area for aquaculture production, providing over 66% of Vietnam’s aquaculture production annually. However, large-scale cultivation and intensive farming have resulted in deterioration of aquaculture water quality and higher rate of aquatic animal diseases. Therefore, water quality control is the key to succeed an aquaculture management. This work presents the design and deployment of an IoT-based water quality monitoring system for Pangasius fish farming in Mekong Delta. The designed system allows farmers to monitor in real time the most important physico-chemical variables of the pond water. Especially, this work introduces a simple and effective approach for automatic cleaning sensor probes that helps improve sensor readings reliability and reduce maintenance costs. 
SELECTION OF WOVEN FABRIC COMPOSITES USING A MULTI- CRITERIA DECISION MAKING TECHNIQUE AND MESO-LEVEL FINITE ELEMENT SIMULATION

Various types of woven fabrics have found considerable attention in modern industries. Although they have brought design flexibilities for composite manufacturers, often the selection of the most suitable fabric that can meet all design requirements for a given product may be challenging, especially due to the potential presence of conflicting criteria. As a result, the application of Multi-Criteria Decision Making (MCDM) techniques is deemed necessary. In this article, a well-established MCDM technique is incorporated into a woven composite material selection problem, along with the capabilities of meso-scale finite element modeling which eliminates the need for time-consuming or expensive experiments. In implementing the MCDM, a new combination of the modified digital logic weighting factors (defined by the designer) with entropy weights (defined based on material data) is introduced.
Time-resolved and Temperature-dependent Broadband Emission of Plasmon-coupled Quantum Dots

The broadband photoluminescence (PL) emissions from CdSe QDs and plasmon-coupled QDs were characterized with time-resolved and temperature-dependent spectroscopy for the application of solid-state white light. The origin of broad spectral emission includes the transitions from bandedge and surface-trapped states. The emission intensity enhancement of plasmon-coupled QDs with respect to that of bare QDs is attributable to the reduction of nonradiative decay and the local field enhancement with plasmon-exciton coupling through the Coulomb interaction. The temperature-dependent and time-resolved PL spectroscopy revealed the existence of selective contribution strength of both the local field enhancement and the reduction of nonradiative decay with plasmon-exciton coupling at different spectral regions.
EFFECT OF CHRONIC IMMOBILIZATION STRESS ON KIDNEY FUNCTION IN RENAL ISCHEMIA/REPERFUSION RAT MODEL

Background: Renal ischemia/reperfusion (I/R) injury, a common and important cause of acute kidney injury (AKI), is considered a major socioeconomic health problem. Stress, a state of disrupted normal homeostasis is known to trigger the progression of many illnesses. Objectives: This study was designed to determine changes in renal function and structure induced by renal I/R in rats subjected to chronic immobilization stress and to elucidate the possible underlying mechanism(s). Materials and Methods: Forty seven adult male albino rats were allocated into 3 groups: Group I: Sham-Operated Control, Group II: Renal I/R in which rats were subjected to 45 minutes ischemia followed by 24 hours of reperfusion, and Group III: Stressed Renal I/R in which rats were separately subjected to immobilization stress, 2 hours/day for 4 weeks, and then exposed to renal I/R procedure. All rats were subjected to determination of body weight (BW) and kidney weight (KW), plasma levels of creatinine, urea and tumor necrosis factor-α (TNF-α), as well as renal tissue levels of malondialdehyde (MDA), nitrite and catalase activity. Kidney tissues were also examined histopathologically. Results: Stressed renal I/R group showed significant decrease in final BW, BW % change, KW and KW/BW, and significant increase in plasma levels of creatinine, urea, TNF-α, renal tissue MDA, and nitrite levels as compared to both renal I/R and sham-operated groups. Renal catalase significantly increased as compared to renal I/R group, but significantly decreased compared to sham-operated group. Stress provoked significant augmentation in renal histomorphological damage scores compared to renal I/R and sham groups, evidenced in the form of glomerular capsular thickening and tuft retraction, tubular cells necrosis with loss of brush borders and cast formation, interstitial cell necrosis and hemorrhage, and endothelial cell disruption. Conclusion: Chronic immobilization stress aggravated renal dysfunction and morphological disturbance induced by renal I /R injury. Accentuation of oxidative stress, inflammation and nitric oxide may contribute to such effect.