Miracle-dz/UniFAR-FTUs huggingface dataset:
Unstructured mesh based models for incompressible turbulent flows

A development of high resolution NFT model for simulation of incompressible flows is presented. The model uses finite volume spatial discretisation with edge based data structure and operates on unstructured meshes with arbitrary shaped cells. The key features of the model include non-oscillatory advection scheme Multidimensional Positive Definite Advection Transport Algorithm (MPDATA) and non-symmetric Krylov-subspace elliptic solver. The NFT MPDATA model integrates the Reynolds Average Navier Stokes (RANS) equations. The implementation of the Spalart-Allmaras one equations turbulence model extends the development further to turbulent flows. An efficient non-staggered mesh arrangement for pressure and velocity is employed and provides smooth solutions without a need of artificial dissipation. In contrast to commonly used schemes, a collocated arrangement for flow variables is possible as the stabilisation of the NFT MPDATA scheme arises naturally from the design of MPDATA. Other benefits of MPDATA include: second order accuracy, strict sign-preserving and full multidimensionality. The flexibility and robustness of the new approach is studied and validated for laminar and turbulent flows. Theoretical developments are supported by numerical testing. Successful quantitative and qualitative comparisons with the numerical and experimental results available from literature confirm the validity and accuracy of the NFT MPDATA scheme and open the avenue for its exploitation for engineering problems with complex geometries requiring flexible representation using unstructured meshes.
Transcutaneous Vagus Nerve Stimulation Combined with Rehabilitation Training in the Intervention of Upper Limb Movement Disorders After Stroke: A Systematic Review

Introduction Stroke often leaves behind a wide range of functional impairments, of which limb movement disorders are more common. Approximately 85% of patients have varying degrees of upper limb motor impairment. In recent years, transcutaneous vagus nerve stimulation combined with rehabilitation training has been gradually used in the rehabilitation of upper limb motor dysfunction after stroke and appears to have some therapeutic benefits. Purpose We conducted the systematic review to evaluate the efficacy and safety of transcutaneous vagus nerve stimulation combined with rehabilitation training in the rehabilitation of upper limb motor dysfunction after stroke. Methods Six databases, including PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure Database (CNKI), Wanfang Database, and China Science and Technology Journal Database (VIP), were searched for January 1, 2016 to January 30, 2022. Randomized controlled trials using TVNS combined with rehabilitation training to intervene in upper limb motor dysfunction after stroke were included, and meta-analysis was performed using Review Manager 5.4. 1 software. Results Total of 101 participants from 4 studies were included in this systematic review. These studies were evaluated using the Cochrane Review’s Handbook 5.1 evaluation criteria and PEDro scores, and meta-analysis was performed on the collected data. The systematic review shows a significant effect of TVNS combined with rehabilitation training on the Upper Extremity Fugl-Meyer Score (MD=3.58, 95% CI [2.34, 4.82], P<0.00001, I2=0%), Function Independent Measure Score (MD=3.86, 95% CI [0.45, 7.27], P=0.03, I2=0%) and the Wolf Motor Function Test Score (MD=3.58, 95% CI [1.97, 5.18], P<0.0001, I2=0%). Conclusion Based on UE-FM, FIM, and WMFT scores, TVNS combined with rehabilitation training showed some improvement in upper limb motor dysfunction in post-stroke patients, but its long-term effects, stimulation sites, stimulation parameters, combined mode with rehabilitation training, and adverse effects still need further observation. Registration PROSPERO: CRD42022312453 (https://www.crd.york.ac.uk/prospero/display_record.php? ID=CRD42022312453).
Microphone Array Channel Combination Algorithms for Overlapped Speech Detection

Overlapped speech occurs when multiple speakers are simultaneously active. This may lead to severe performance degradation in automatic speech processing systems such as speaker diarization. Overlapped speech detection (OSD) aims at detect-ing time segments in which several speakers are simultaneously active. Recent deep neural network architectures have shown impressive results in the close-talk scenario. However, performance tends to deteriorate in the context of distant speech. Microphone arrays are often considered under these conditions to record signals including spatial information. This paper inves-tigates the use of the self-attention channel combinator (SACC) system as a feature extractor for OSD. This model is also extended in the complex space (cSACC) to improve the interpretability of the approach. Results show that distant OSD performance with self-attentive models gets closer to the near-field condition. A detailed analysis of the cSACC combination-weights is also conducted showing that the self-attention module focuses attention on the speakers’ direction.
COVID-19 detection based on respiratory sensing from speech

COVID-19 affects a person's respiratory health, which is manifested in the form of shortness of breath during speech. Recent work shows that it is possible to use deep learning techniques to sense the speaker's respiratory parameters from a speech signal directly. Thus respiratory parameters like speech breathing rate and tidal volume can be computed and compared using deep learning techniques to detect COVID-19 from speech recordings. In this paper, we compute respiratory parameters using our pre-trained deep learning-based speech breathing models and use them for detecting COVID-19 from speech. Apart from using speech breathing models, we perform acoustic features identification using a statistical approach and classification based on low-level descriptive features. Our analysis investigates the distinction of speech of a healthy person and COVID-19 affected person. Copyright © 2022 ISCA.
CF4-n (SO3) n (n = 1–4): a new series of organic superhalogens

Superhalogens are species having higher electron affinity (EA) or vertical detachment energy (VDE) than those of halogen atoms. CF4 is a molecule having no positive EA or VDE. In the quest for new organic superhalogens, we substitute SO3 in the place of F in CF4 successively and study the resulting CF4-n (SO3) n (n = 1–4) neutral molecules and their anions using density functional theory and quantum theory of atoms in molecule at the ωB97xD/6-311 + G(d) and B3LYP/6-311 + G(d) levels, respectively. The EA of CF4-n (SO3) n and VDE of their anions, being greater than 5 eV, suggest that all these molecules behave as superhalogens. There is significant structural relaxation in C(SO3)4 molecule, leading to the remarkably high VDE of corresponding anions. The superhalogen properties have been explained on the basis of the electronic charge delocalisation over SO3 moieties. We believe that these findings will add a new chapter in the exploration of organic superhalogens. GRAPHICAL ABSTRACT
On the Slow-Wave Helical Clad Elliptical Fibers

Lightwave propagation through dielectric helical clad elliptical fibers is presented under the slow-wave consideration. The helical clad is achieved by putting helical turns on the core-clad interface. While treating analytically, two extreme cases of helix pitch angle — i.e., 0° and 90° — are considered along with the use of slowwave approximation. E- and H-field components are determined in the different sections of the guide followed by the evolution of the eigenvalue relation. The effect of ellipse eccentricity is determined on the dispersion characteristics for different operating wavelengths and corresponding to different values of the length of core semi-major axis.
Multi-Objective Cluster Ensemble based on Filter Refinement Scheme

Cluster ensemble improves the robustness and stability of clustering performances by utilizing multiple solutions. Although traditional cluster ensemble methods have achieved promising performances, they are not adaptive enough to cope with data sets that have multiple levels of complexities. Besides, these methods may contain noisy and redundancy members which have negative effects. To mitigate the above issues, in this paper, we propose a multi-objective filter refinement scheme (MOFRS). First, we perform various clustering methods on different representations of data to generate diverse solutions. Second, we propose a solution filter to select a proper method and reduce the number of initial partitions for a given data set. Third, four stability indices are designed to split instances into stable and unstable groups. Fourth, objective functions based on diversity and quality are utilized to quantify the goodness of base clustering solutions. Finally, we design an improvement oriented multi-objective evolutionary algorithm to optimize these objective functions. Extensive experimental results conducted on 27 real-world data sets show that MOFRS outperforms most cluster ensemble selection methods, and achieves statistically significant improvements, compared with full ensemble methods.
Optimum-width upward drawings of trees I: Rooted pathwidth

An upward drawing of a rooted tree is a drawing such that no parents are below their children. It is ordered if the edges to children appear in prescribed order around each vertex. It is well-known that any tree has an upward (unordered) drawing with width $\log (n+1)$. For ordered drawings, the best-known bounds for the width for binary trees is $O(\log n)$, while for arbitrary trees it is $O(2^{O(\sqrt{\log n})})$. We present algorithms that compute upward drawings with instance-optimal width, i.e., the width is the minimum-possible for the input tree. In this first paper, we mostly study unordered drawings, where the algorithm is very simple and the drawings obtained are straight-line. We also give 2-approximation algorithms for the width of upward ordered drawings, and $O(\Delta)$-approximation where additionally the height is small. In particular any tree has an upward straight-line ordered drawing of area $O(\Delta n\log n)$.
Participatory Variety Testing to Replace Old Mega Rice Varieties with Newly Developed Superior Varieties in Bangladesh

The Bangladesh Rice Research Institute (BRRI) has released more than 100 inbred rice varieties. Still, an old mega variety BRRI dhan28 dominates the farmers’ fields during the dry winter (Boro season: November–June) season. This variety is very susceptible to different diseases and insects, causing lower yield performance than its potential. To replace this variety, current on-farm research was planned to evaluate the newly developed four superior rice varieties: BRRI dhan58, BRRI dhan63, BRRI dhan67, and BRRI dhan74 during Boro season in 2017 and 2018. The objective was to create data and popularize new varieties among farmers all over the country. We conducted 15 on-farm trials with farmers’ active participation at Senbag, Fulgazi, and Mirsarai Upazila of Noakhali, Feni, and Chattogram districts, respectively, in Bangladesh. The results demonstrate that BRRI dhan74 produced the highest grain yield among the tested varieties, followed by BRRI dhan67, BRRI dhan63, and BRRI dhan58, while BRRI dhan28 produced the lowest. However, BRRI dhan67 obtained the highest preference scores from the farmers and extension personnel due to its medium and slender grains, shorter growth duration, resistance to lodging, less disease, and less insect invasion. Moreover, stability indices for yield revealed that BRRI dhan67 was the most stable, adaptive, and appropriate variety, followed by BRRI dhan74, across the locations. Farmers showed keen interest to grow BRRI dhan67 by themselves instead of BRRI dhan28 all over the study locations. The neighboring farmers also expressed their curiosity about cultivating BRRI dhan67 over BRRI dhan28 by collecting seeds from the participating farmers. Thus, BRRI dhan67 could be a perfect replacement for BRRI dhan28. However, conducting participatory varietal evaluation trials across the agroecological zones of the country is recommended to validate the results of this study.
Gravoturbulent Star Cluster Formation

Stars form by gravoturbulent fragmentation of interstellar gas clouds. The supersonic turbulence ubiquitously observed in Galactic molecular gas generates strong density fluctuations with gravity taking over in the densest and most massive regions. Collapse sets in to build up stars and star clusters. Turbulence plays a dual role. On global scales it provides support, while at the same time it can promote local collapse. Stellar birth is thus intimately linked to the dynamical behavior of parental gas cloud, which determines when and where protostellar cores form, and how they contract and grow in mass via accretion from the surrounding cloud material to build up stars. Slow, inefficient, isolated star formation is a hallmark of turbulent support, whereas fast, efficient, clustered star formation occurs in its absence. The fact that Galactic molecular clouds are highly filamentary can be explained by a combination of compressional flows and shear. The dynamical evolution of nascent star clusters is very complex. This strongly influences the stellar mass spectrum. The equation of state (EOS) plays a pivotal role in the fragmentation process. Under typical cloud conditions, massive stars form as part of dense clusters. However, for gas with effective polytropic index greater than unity star formation becomes biased towards isolated massive stars, which may be of relevance for understanding Pop III stars.
AKU Giant Pituitary Adenoma Score: A Novel Scoring System to Predict the Outcomes of Surgery for Giant Pituitary Adenomas

Background No scoring system is available to predict the extent of resection of giant pituitary adenomas (GPAs) based on magnetic resonance imaging (MRI) parameters. We developed a novel AKU Giant Pituitary Adenoma (AGPA) score and assessed the predictive ability of the scoring system concerning the extent of resection of GPAs. Methodology We retrospectively collected data of patients presenting with GPAs and used our scoring system to assess the surgical resection of these tumors. The Lundin-Pederson (ABC/2) method was used to calculate the pre- and post-resection tumor volume. The relationship between the extent of resection and the AGPA score was assessed using linear regression. The AGPA score considered the tumor’s extension into various planes. The maximum total score was 9. Results The scoring system was applied to 45 patients with GPA who underwent surgical resection. The mean resected tumor volume (%) was 82.0 ± 16.7, and the overall mean AGPA score was 4.2 ± 0.8. The pairwise correlation between the resected tumor volume and the overall AGPA scores showed a strong inverse association (r = -0.633, p < 0.001). A significant difference was detected between the estimated scores of 3 and 5 and 4 and 5 (p < 0.001). Conclusions AGPA score is inversely related to the extent of the tumor to be resected, which would help surgeons predict the amount of tumor resection possible as well as predict the difficulty of surgery and plan optimal preoperative patient counseling. In addition, it can predict if staging and a transcranial approach are required.
SiD-WaveFlow: A Low-Resource Vocoder Independent of Prior Knowledge

Flow-based neural vocoders have demonstrated their effectiveness in generating high-fidelity speech in real-time. However, most flow-based vocoders are computationally heavy models which rely on large amounts of speech for model training. Witnessing the limitations of these vocoders, a new flow-based vocoder, namely Semi-inverse Dynamic WaveFlow (SiD-WaveFlow), for low-resource speech synthesis is proposed. SiD-WaveFlow can generate high-quality speech in real-time with the constraint of limited training data. Specifically, in SiD-WaveFlow, a module named Semi-inverse Dynamic Trans-formation (SiDT) is proposed to improve the synthesis quality as well as the computational efficiency by replacing the affine coupling layers (ACL) used in WaveGlow. In addition, a pre-emphasis operation is introduced to the training process of SiD-WaveFlow to further improve the quality of the synthesized speech. Experimental results have corroborated that SiD-WaveFlow can generate speech with better quality compared with its counterparts. Particularly, the TTS system integrating SiD-WaveFlow vocoder achieves 3.416 and 2.968 mean MOS on CSMSC and LJ speech dataset, respectively. Besides, SiD-WaveFlow converges much faster than WaveGlow at the training stage. Last but not least, SiD-WaveFlow is a lightweight model and can generate speech on edge devices with a much faster inference speed. The source code and demos are available at https://slptongji.github. io/.
PQ Event Detection After Noise Removal Using Fuzzy Transform and Hilbert Spectral Analysis on EMD

In this paper, a noise removal technique from Power Quality (PQ) signals is proposed which is based on a soft thresholding method. Thresholding is accomplished by using Fuzzy Membership Function (MF) and Empirical Mode Decomposition (EMD). To assess the denoising performance, the proposed technique is applied to detect PQ disturbances from the denoised power system signals. The EMD is applied to decompose the signal into different components. Next, the Intrinsic Mode Functions (IMFs) obtained from the EMD are utilized to determine the IMF dependent thresholding parameters, which are used into the modified fuzzy MF for the noise removal. For improved performance, several random versions of the first IMF are created, independently soft thresholded, and averaged to yield the final denoised version of the first IMF. A separate measurement is used to decide how many IMFs are required to be thresholded. For the evaluation of the noise removal performance, 1) the proposed method is compared with a wavelet-transform-based state of art technique, and 2) an application is presented on the denoised signal for the detection of PQ events from real and simulated power system disturbance data. The denoised and processed IMFs are subjected to Hilbert spectral analysis for the identification of the localized features, which are then utilized for the detection of PQ events in smart grid signal.
ORGANIZATIONAL CLIMATE AND PERFORMANCE: MEDIATING ROLE OF AFFECTIVE COMMITMENT, KNOWLEDGE SHARING PRACTICES AND PERCEIVED COST OF KNOWLEDGE SHARING

This research work examines the impact of organizational climate on performance and considering affective commitment, knowledge sharing practices (KSPS) and perceived cost of knowledge sharing (KScost) as potential mediators by recognizing the need and importance of knowledge sharing among pharmaceutics to enhance their ability to perform best at workplace. Data collection is carried through convenient sampling from pharmaceutics through survey questionnaire from (Lahore and Karachi) two big cities of Pakistan. Confirmatory factor analysis is applied to test the reliability and validity of the constructs and the outcomes confirm the establishment of both internal reliability and validity. Sample size consists of 350 pharmaceutics. The outcomes of this paper reveal that organizational climate significantly and positively impact the performance. The results indicate that affective commitment, KScost and KSPS intervene the link between organizational commitment and organizational performance
Articulatory Synthesis for Data Augmentation in Phoneme Recognition

While numerous studies on automatic speech recognition have been published in recent years describing data augmentation strategies based on time or frequency domain signal processing, few works exist on the artificial extensions of training data sets using purely synthetic speech data. In this work, the German K IEL corpus was augmented with synthetic data generated with the state-of-the-art articulatory synthesizer V OCAL T RACT L AB . It is shown that the additional synthetic data can lead to a significantly better performance in single-phoneme recognition in certain cases, while at the same time, the performance can also decrease in other cases, depending on the degree of acoustic naturalness of the synthetic phonemes. As a result, this work can potentially guide future studies to improve the quality of articulatory synthesis via the link between synthetic speech production and automatic speech recognition.
Decomposição modular de grafos não orientados

Um modulo de um grafo e um subconjunto de seus vertices que nao e diferenciado, em relacao a adjancencia pecos demais vertices do mesmo grafo. Dado um mpodulo M de um grafo G, se todo modulo de G que intercepta M esta contido nele ou o contem. M e denominado modulo forte.Observacao: O resumo, na integra podera ser visualizado no texto completo da tese digital Abstract
Audio-Visual Wake Word Spotting in MISP2021 Challenge: Dataset Release and Deep Analysis

In this paper, we describe and release publicly the audio-visual wake word spotting (WWS) database in the MISP2021 Challenge, which covers a range of scenarios of audio and video data collected by near-, mid-, and far-field microphone arrays, and cameras, to create a shared and publicly available database for WWS. The database 1 and the code 2 are released, which will be a valuable addition to the community for promoting WWS research using multi-modality information in realistic and complex conditions. Moreover, we investigated the different data augmentation methods for single modalities on an end-to-end WWS network. A set of audio-visual fusion experiments and analysis were conducted to observe the assistance from visual information to acoustic information based on different audio and video field configurations. The results showed that the fusion system generally improves over the single-modality (audio-or video-only) system, especially under complex noisy conditions.
Cortical auditory evoked potentials using the speech stimulus /ma/

Purpose: to compare cortical auditory evoked responses using two speech stimuli, /ma/ and /da/, in normally hearing young adults. Methods: a cross-sectional, observational and analytical study, with a sample composed of nineteen normally hearing young adults, recruited by convenience, ages between 18 and 25 years old, from both genders, participated in the study. Cortical auditory evoked potentials (CAEP) were monaurally recorded in two conditions: 1) with a pair of speech stimuli /ba/ and /da/, and 2), with a pair of speech stimuli /ba/ and /ma/. The order of the experiments was randomized in a proportion of 50% for each of the two stimuli, totaling 100 stimuli for each experiment. Speech sounds were presented at 70 dB SPL. Descriptive and analytical statistical tests were performed. Results: mean latency values of the complex P1, N1, P2, N2 and P3 were lower for the /ma/ when compared to those of /da/ (p <0,05). There was no difference in amplitude values between responses evoked using /ma/ and /da/. Conclusion: cortical auditory evoked potentials, elicited by the speech stimulus /ma/ had, on average, lower latency peaks of P1-N1-P2-N2 and P3, when compared to those of speech stimulus /da/.