Miracle-dz/UniFAR-FTUs huggingface dataset:
Acoustic and Prosodic Correlates of Emotions in Urdu Speech

Emotional speech corpora exhibit differences in duration, intensity and fundamental frequency. We investigated acoustic as well as prosodic correlates of emotional speech in Urdu. We recorded a corpus of 23 sentences from four speakers of Urdu covering four emotional states. Main results show that: a) sadness exhibits lowest utterance rate, lowest intensity and narrow pitch range, b) anger exhibits highest utterance rate, highest intensity and wider pitch range, and c) happiness exhibits higher utterance rate and wider pitch range as compared to neutral and sadness; but no significant differences are found between the intensity and pitch range of anger and happiness. The analysis also shows differences in terms of pitch or phrase accents and boundary tones.
Multi-Object Segmentation in Complex Urban Scenes from High-Resolution Remote Sensing Data

Terrestrial features extraction, such as roads and buildings from aerial images using an automatic system, has many usages in an extensive range of fields, including disaster management, change detection, land cover assessment, and urban planning. This task is commonly tough because of complex scenes, such as urban scenes, where buildings and road objects are surrounded by shadows, vehicles, trees, etc., which appear in heterogeneous forms with lower inter-class and higher intra-class contrasts. Moreover, such extraction is time-consuming and expensive to perform by human specialists manually. Deep convolutional models have displayed considerable performance for feature segmentation from remote sensing data in the recent years. However, for the large and continuous area of obstructions, most of these techniques still cannot detect road and building well. Hence, this work’s principal goal is to introduce two novel deep convolutional models based on UNet family for multi-object segmentation, such as roads and buildings from aerial imagery. We focused on buildings and road networks because these objects constitute a huge part of the urban areas. The presented models are called multi-level context gating UNet (MCG-UNet) and bi-directional ConvLSTM UNet model (BCL-UNet). The proposed methods have the same advantages as the UNet model, the mechanism of densely connected convolutions, bi-directional ConvLSTM, and squeeze and excitation module to produce the segmentation maps with a high resolution and maintain the boundary information even under complicated backgrounds. Additionally, we implemented a basic efficient loss function called boundary-aware loss (BAL) that allowed a network to concentrate on hard semantic segmentation regions, such as overlapping areas, small objects, sophisticated objects, and boundaries of objects, and produce high-quality segmentation maps. The presented networks were tested on the Massachusetts building and road datasets. The MCG-UNet improved the average F1 accuracy by 1.85%, and 1.19% and 6.67% and 5.11% compared with UNet and BCL-UNet for road and building extraction, respectively. Additionally, the presented MCG-UNet and BCL-UNet networks were compared with other state-of-the-art deep learning-based networks, and the results proved the superiority of the networks in multi-object segmentation tasks.
Deliverable D 6 . 8 : Final scientific highlights from EUROCHAMP-2020

EUROCHAMP-2020 – The European Distributed Infrastructure for Experimental Atmospheric Simulation CNRS-LISA – Faculté des Sciences – 61 avenue du Général De Gaulle F-94010 Créteil CEDEX http://www.eurochamp. org follow us on Twitter https://twitter.com/EUROCHAMP2020 Deliverable D6.8: Final scientific highlights from EUROCHAMP-2020 Authors: David Bell, Christian George, Gordon McFiggans, Amalia Muñoz, Bénédicte Picquet-Varrault, Harald Saathoff, Peter Wiesen.
Estimating Shape Parameters of Piecewise Linear-Quadratic Problems

Piecewise Linear-Quadratic (PLQ) penalties are widely used to develop models in statistical inference, signal processing, and machine learning. Common examples of PLQ penalties include least squares, Huber, Vapnik, 1-norm, and their asymmetric generalizations. Properties of these estimators depend on the choice of penalty and its shape parameters, such as degree of asymmetry for the quantile loss, and transition point between linear and quadratic pieces for the Huber function. In this paper, we develop a statistical framework that can help the modeler to automatically tune shape parameters once the shape of the penalty has been chosen. The choice of the parameter is informed by the basic notion that each PLQ penalty should correspond to a true statistical density. The normalization constant inherent in this requirement helps to inform the optimization over shape parameters, giving a joint optimization problem over these as well as primary parameters of interest. A second contribution is to consider optimization methods for these joint problems. We show that basic ﬁrst-order methods can be immediately brought to bear, and design specialized extensions of interior point (IP) methods for PLQ problems that can quickly and eﬃciently solve the joint problem. Synthetic problems and larger-scale practical examples illustrate the utility of the approach. Code for the new IP method is implemented using the Julia language ( https://github.com/UW-AMO/shape-parameters/tree/ojmo ). Digital Object Identiﬁer 10.5802/ojmo.10 Acknowledgments The authors acknowledge the Washington Research Foundation Data Science Professorship.
Review on the Battery Model and SOC Estimation Method

The accuracy of the power battery model and SOC estimation directly affects the vehicle energy management control strategy and the performance of the electric vehicle, which is of great significance to the efficient management of the battery and the improvement of the reliability of the vehicle. Based on the research of domestic and foreign battery models and the previous results of SOC estimation, this paper classifies power battery models into electrochemical mechanism models, equivalent circuit models and data-driven models. This paper analyzes the advantages and disadvantages of various battery models and current research progress. According to the choice of battery model, the previous research results of the power battery SOC estimation method are divided into three categories: the direct measurement method not based on battery model, the estimation method using black box battery model, and the battery model SOC estimation method based on state space. This paper will summarize and analyze the principles, applicable scenarios and research progress of the three categories of estimation algorithms aiming to provide references for future in-depth research. Finally, in view of the shortcomings of the battery model and estimation algorithm of the existing method, the future improvement direction is proposed.
Multifunctional Nanofibrous Dressing with Antimicrobial and Anti-Inflammatory Properties Prepared by Needle-Free Electrospinning

An active wound dressing should address the main goals in wound treatment, which are improved wound healing and reduced infection rates. We developed novel multifunctional nanofibrous wound dressings with three active ingredients: chloramphenicol (CAM), beta-glucan (βG) and chitosan (CHI), of which βG and CHI are active nanofiber-forming biopolymers isolated from the cell walls of Saccharomyces cerevisiae and from shrimp shells, respectively. To evaluate the effect of each active ingredient on the nanofibers’ morphological features and bioactivity, nanofibers with both βG and CHI, only βG, only CHI and only copolymers, polyethylene oxide (PEO) and hydroxypropylmethylcellulose (HPMC) were fabricated. All four nanofiber formulations were also prepared with 1% CAM. The needle-free NanospiderTM technique allowed for the successful production of defect-free nanofibers containing all three active ingredients. The CAM-containing nanofibers had a burst CAM-release and a high absorption capacity. Nanofibers with all active ingredients (βG, CHI and CAM) showed a concentration-dependent anti-inflammatory activity, while maintaining the antimicrobial activity of CAM. The promising anti-inflammatory properties, together with the high absorption capacity and antimicrobial effect, make these multifunctional nanofibers promising as dressings in local treatment of infected and exuding wounds, such as burn wounds.
Variations and Drivers of Methane Fluxes from Double-Cropping Paddy Fields in Southern China at Diurnal, Seasonal and Inter-Seasonal Timescales

Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG) after carbon dioxide (CO2), and paddy fields are among the largest sources of CH4 emissions. Owing to the scarcity of observational data, the characteristics and influencing factors of CH4 fluxes in paddy fields at different timescales need to be further investigated. Observations of CH4 fluxes via eddy covariance (EC) data were performed over four seasons in two paddy fields in Nanchang, Jiangxi Province, China. The pattern, magnitude and biophysical controls of CH4 emissions were explored by wavelet analysis and stepwise multiplicative modelling. The results revealed a distinct, single-peak diurnal pattern in CH4 fluxes during the vegetative stage in all four rice growing seasons and the reproductive stage of early rice. Large seasonal variations in daily CH4 emissions were observed in the two double-cropping paddy fields, and the soil temperature at a depth of 5 cm (Ts5) explained most of the seasonality of the CH4 fluxes. At the inter-seasonal scale, under local farms’ traditional field management method, reducing the amount and frequency of irrigation during the vegetative stage could decrease CH4 emissions in southern China. This study improves the understanding of CH4 emissions and helps in developing GHG management strategies for paddy fields.
Antimicrobial Resistance of Bacterial Isolates from Patients with Bloodstream Infection 2 in Butembo , Democratic Republic of the Congo

6 Background: Emergence of antimicrobial resistance has limited treatment options against 7 bloodstream infections. This study aimed to determine bacterial isolates from blood culture at 8 patients with bloodstream infection and their sensitivity to antimicrobials at patients attending 9 the Central Laboratory of Research of the “Université Catholique du Graben” (UCG) in 10 Butembo. 11 Methodology: This was a cross-sectional study adopting a descriptive approach, conducted 12 from January, 2015 to December, 2016. Blood was collected from a peripheral vein using an 13 aseptic technique. The culture and the antimicrobial susceptibility testing were done by using 14 standard methods according to the Clinical Laboratory Standard Institute guidelines. 15 Results: The most isolated bacteria from blood culture of patient with bloodstream infections 16 were Staphylococcus aureus (39.8%), Listeria spp. (17.4%), Moraxella spp. (14.3%), Bacillus 17 spp. (13.4%) and Klebsiella rhinoscleromatis (4.1%). All bacterial isolates tested for 18 sensitivity were resistant to the group of β-lactamine antibiotics except S. aureus which was 19 sensitive only to vancomycin. It was also observed that all the bacterial species have a 20 Multiple Antibiotic Resistance Index greater than 0.2. 21
Large steps in inverse rendering of geometry

Inverse reconstruction from images is a central problem in many scientific and engineering disciplines. Recent progress on differentiable rendering has led to methods that can efficiently differentiate the full process of image formation with respect to millions of parameters to solve such problems via gradient-based optimization. At the same time, the availability of cheap derivatives does not necessarily make an inverse problem easy to solve. Mesh-based representations remain a particular source of irritation: an adverse gradient step involving vertex positions could turn parts of the mesh inside-out, introduce numerous local self-intersections, or lead to inadequate usage of the vertex budget due to distortion. These types of issues are often irrecoverable in the sense that subsequent optimization steps will further exacerbate them. In other words, the optimization lacks robustness due to an objective function with substantial non-convexity. Such robustness issues are commonly mitigated by imposing additional regularization, typically in the form of Laplacian energies that quantify and improve the smoothness of the current iterate. However, regularization introduces its own set of problems: solutions must now compromise between solving the problem and being smooth. Furthermore, gradient steps involving a Laplacian energy resemble Jacobi's iterative method for solving linear equations that is known for its exceptionally slow convergence. We propose a simple and practical alternative that casts differentiable rendering into the framework of preconditioned gradient descent. Our pre-conditioner biases gradient steps towards smooth solutions without requiring the final solution to be smooth. In contrast to Jacobi-style iteration, each gradient step propagates information among all variables, enabling convergence using fewer and larger steps. Our method is not restricted to meshes and can also accelerate the reconstruction of other representations, where smooth solutions are generally expected. We demonstrate its superior performance in the context of geometric optimization and texture reconstruction.
COPD_A_224943 1415..1423

M Voorhaar 1 J Tiemensma GM Asijee AHM Slok JWM Muris 1 AA Kaptein 3 1Department of Family Medicine, Maastricht University, CAPHRI Care and Public Health Research Institute, Maastricht, the Netherlands; 2Department of Anesthesiology, Erasmus University Medical Center, Rotterdam, the Netherlands; 3Department of Medical Psychology, Leiden University Medical Centre, Leiden, the Netherlands Introduction: Self-management (SM) is a core component of well-being and perceived health for patients with chronic obstructive pulmonary disease (COPD). Most theories on SM share that self-efficacy, illness-perception and coping are determinants of SM behavior. Optimal support to improve SM should be tailored to the individual patient’s level of these determinants as SM abilities vary between patients. To tailor SM support, it is therefore necessary to assess the scores on these determinants. Unfortunately, no such instrument exists for clinical use. Therefore, the first goal of this study was to verify presumed correlations between SM and the determinants thereof. The second goal was to develop an instrument to assess the SM abilities. Methods: In this cross-sectional, observational study, COPD patients completed the General Self-Efficacy Scale (GSES), Brief Illness Perception Questionnaire (B-IPQ) and the Utrecht Proactive Coping Competence measure (UPCC) as well as the Self-Management Ability Scale (SMAS-30). Correlations between the questionnaires were assessed and a principal component analysis (PCA) was performed to identify the best-fitting items in the three independent variables related to SM. These items were used to create an instrument to assess SM abilities. Results: Hundred COPD patients (58 males, 41 females, 1 unknown) were included. The correlation between SM and self-efficacy, illness perception on concerns and proactive coping was moderate and significant (r=0.318, p<0.01; r=−.230, p<0.05; r=.426, p<0.01, respectively). PCA identified six UPCC items and nine GSES items that met the predefined criteria. These items were supplemented with the B-IPQ concerns item to establish the new instrument to assess SM abilities.
The March 2021 Tyrnavos, central Greece, doublet (Μw6.3 and Mw6.0): Aftershock relocation, faulting details, coseismic slip and deformation

On 3 March 2021, the Mw6.3 Tyrnavos earthquake shook much of the Thessalia region, leading to extensive damage in many small towns and villages in the activated area. The first main shock was followed in the next day, on 4th of March 2021, by an “equivalent” main shock with Mw6.0 in the adjacent fault segment. These are the largest earthquakes to strike the northeastern part of Thessalia since the M6.3, 1941 Larissa earthquake. The main shocks triggered extensive liquefaction mainly along the banks of the Titarisios tributary where alluvial flood deposits most probably amplified the ground motions. Our seismic monitoring efforts, with the use of recordings of the regional seismological network along with a dense local network that was installed three days after the seismic excitation initiation, led to the improved understanding the geometry and kinematics of the activated faults. The aftershocks form a north–northwest–trending, east–northeast–dipping, ~40 km long distribution, encompassing the two main ruptures along with minor activated structures, consistent with the rupture length estimated from analysis of regional waveform data and InSAR modeling. The first rupture was expanded bilaterally, the second main shock nucleated at its northern tip, where from this second rupture propagated unilaterally to the north–northwest. The focal mechanisms of the two main shocks support an almost pure normal faulting, similar to the aftershocks fault plane solution determined in this study. The strong ground motion of the March 3 main shock was computed with a stochastic simulation of finite fault model. Coseismic displacements that were detected using a dense GPS / GNSS network of five permanent stations located the Thessaly region, have shown an NNE–SSW extension as expected from the nature and location of the causative fault. Coulomb stress changes due to the coseismic slip of the first main shock, revealed that the hypocentral region of the second main shock was brought closer to failure by more than 10 bars.
The Relationship Between Flipped Learning And Pupils’ Performance: A Reflection On Alternative Philosophical Underpinnings

This research paper investigates the significance of the relationship between flipped learning and pupils’ academic performance in secondary schools in the Kurdistan Region of Iraq especially with a focus on alternative philosophical underpinnings. Undoubtedly, the significance of this study in the field of educational research bubbles over with controversies. Professional researchers/teachers’ disagreements about what happens in schools emanate from the difference in philosophical lenses employed in understanding phenomena, divergent visions regarding the purpose of schooling, and what constitutes an ideal society and cultural differences. This research attempts to understand teachers’ perception of reality in classrooms and fathoms the relationship between flipped learning and pupil’s academic performance, engagement and achievement. The research methodology employed has focused on mixed methods that allow the data analysis to adopt an interpretive approach and attempted to address the research questions by developing a structured observation and a questionnaire to facilitate the data collection procedure. The findings show that alternative philosophical underpinnings bear profound effects on pupils’ learning: teachers and the epistemologies and ontologies employed to understand reality in classrooms significantly impact flipped learning and pupils’ academic performance. The results suggest that these implications share common critical statements found in the related literature reviews that also indicate reflections on alternative philosophical underpinnings.
The Relationship between Resilience and Academic Burnout among Nursing and Midwifery Students in Kermanshah, Iran

Background. Nursing and midwifery students have relatively high levels of academic burnout. One of the mechanisms to combat this issue is resilience. The results related to the association between academic burnout and resilience indicate a negative association, but various studies have reported different correlation coefficients. Therefore, the current study was aimed to investigate the association between resilience and academic burnout among nursing and midwifery students. Methods. A total of 240 nursing and midwifery students were recruited in this cross-sectional study using stratified random sampling. Data were collected by a demographic information questionnaire, the Connor–Davidson Resilience Scale (CD-RISC), and the Maslach Burnout Inventory-Student Survey (MBI-SS). Data were analyzed by SPSS-16 using t-test, ANOVA, Spearman’s correlation coefficient, and linear regression analysis. Results. The mean scores of academic burnout for nursing and midwifery students were 41.4 ± 14.8 and 41.2 ± 12.3, respectively, but the difference was not statistically significant ( p = 0.368). The mean scores of resilience for nursing and midwifery students were 58.1 ± 13.3 and 52.9 ± 13.9, respectively, which showed a statistically significant difference ( p = 0.004). Resilience was significantly inversely correlated with academic burnout in nursing and midwifery students (r = −0.04, p < 0.001; r = −0.39, p < 0.001). Increased resilience in students decreased academic burnout ( p < 0.001). Conclusion. Academic burnout was moderate in nursing and midwifery students, but resilience was relatively high. Given the negative correlation between resilience and academic burnout, it is necessary to strengthen resilience skills and reduce factors that cause academic burnout.
Delimitation of the genus Schizachyrium (Poaceae, Andropogoneae) based on molecular and morphological data

Schizachyrium (Poaceae, Andropogoneae) includes about 60 species distributed in tropical and subtropical regions of the world. In all recent molecular phylogenies of Andropogoneae, representatives of Schizachyrium appear closely related to Andropogon species. The objective of this study was to contribute to the delimitation of Schizachyrium. We performed a phylogenetic study including 38 taxa (>63%) of Schizachyrium, along with representatives of related genera, mainly of Andropogon, yielding a total of 49 taxa. This is the first phylogenetic analysis to include the type species of Schizachyrium, S. condensatum. DNA sequences of two plastid markers (ndhF and trnL‐F) were analyzed under Bayesian methods. The results indicate that Schizachyrium is not monophyletic: 26 of the 38 Schizachyrium taxa analyzed are placed in a Schizachyrium s.s. clade that includes the type species of the genus, while 10 taxa are related to Andropogon species and two other species, S. delavayi (from China and India) and S. jeffreysii (from Africa), appear clearly separated. Additionally, 58 morphological characters (41 qualitative and 17 quantitative) were scored for the same 49 taxa and analyzed under the parsimony criterion. Character optimizations showed that (i) the reduced pedicellate spikelets, (ii) with lower glume less than or equal to 0.5 mm wide, (iii) awned, and (iv) without lemma and palea support the Schizachyrium s.s. clade. We propose these four characters as diagnostic features for the delimitation of Schizachyrium s.s.