Miracle-dz/UniFAR-FTUs huggingface dataset:
Intrinsic pitch in German - Examining the whole fundamental frequency contour of the vowel

It is very well known that close vowels tend to have a higher fundamental frequency (F0) than open vowels (known as intrinsic pitch differences, hereafter IF0). This phenomenon is very robust: Whalen and Levitt (1995) found these F0 differences for 31 different languages, independent of their vowel inventory and in Whalen et al. (1995) for vowel productions of French and English babbling infants. These observations suggest a biomechanical explanation for these F0 differences, related to the tongue height: an upward movement of the tongue could causes a rotation of the thyroid cartilage with respect to the cricoid cartilage and therefore raises the fundamental frequency. However, the results of Fischer- Jorgensen (1990) indicated that in German tense-lax vowel pairs are produced with a similar F0 at the vowel midpoint, although the tongue position is lower for lax vowels. She also found a better agreement between intrinsic pitch and jaw position. Mooshammer et al. (2001) replicated this study and found comparable F0 results for the midpoint of the tense-lax vowels. Examining intrinsic F0 differences under a bite-block condition (fixed jaw) they found that intrinsic pitch differences remain constant or even increase, therefore excluding the jaw as the main cause. The aim of the current study is first to examine intrinsic pitch differences for the German tense and lax vowels with a more accurate measurement of the fundamental frequency (EGG) and secondly to examine the complete F0 contour. This was motivated by a pilot study of Hoole (to be published) who found higher CT activity at the beginning of lax vowels for one speaker, therefore speaking for another control mechanism of IF0 in German.
International insights into the consequences of COVID-19 on consumption and attitudes towards savings

Research background: The coronavirus has impacted the global economy as many businesses had to close due to the restrictions, and people’s spending and saving behaviour have changed. According to the negative consequences of the COVID-19, people reconsider their expenditures and rearrange their savings. To avoid the spread of infection, several employers switched to a home office where it was possible. As a result of working from home in numerous cases, monthly housing expenditures have increased. To prevent the spread of the disease, a great number of people tried not to appear in crowded places. Therefore, online shopping came to the fore. Purpose of the article: The main purpose of the article is to give a comprehensive picture of the relationship between the respondents’ job losses and their attitudes towards savings. Furthermore, the association was analysed, and its strength and direction were measured between the increased monthly housing expenditures and the reconsideration of shopping intentions. Moreover, the association was examined between the decreased spendings on commuting and the frequency of online shopping. Methods: The research was conducted among residents in two neighbouring V4 countries, Slovakia and Hungary. To analyse the formulated hypotheses, a nonparametric Pearson's chi-square test and Somers’ delta tests were used. Findings & Value added: Thanks to the results, it can be declared for both countries that there is an association between job losses due to the pandemic and saving behaviour. Based on Somers‘d test, there is a positive correlation between spending less on commuting and online shopping frequency and increased housing expenditures and shopping reconsideration between the respondents.
Estimation of the spatial resolution influence on the retrieval error of ozone profiles at the Siberian lidar station

In the report we present a quasi-three-year seasonal model of ozone vertical profiles; the model is obtained using the differential absorption lidar complex at Siberian Lidar Station (SLS) and Aura and MetOp satellites in the upper troposphere – stratosphere. Ozone profiles were retrieved using temperature vertical distribution from meteorological satellites. We analyzed and estimated the effect of different spatial resolutions on the error of ozone profiles retrieved using lidar and satellite measurements in 2021.
Coupled stepped-impedance-resonator bandstop filter

This study presents a novel design of bandstop filter with cancellation of first spurious mode by using coupled three-section step impedance resonators (SIRs). This cancellation occurs when two transmission poles coincide with the first spurious mode (transmission zero) by properly choosing the step impedance ratio and the gap between the SIR and the main transmission line. A stripline design of the proposed bandstop filter exhibits an upper passband width of up to six times the fundamental bandstop centre frequency at 1.0 GHz with 3 dB fractional bandwidth of 60%.
Design of galloping robots with elastic spine: tracking relations between dynamic model parameters based on motion analysis of a real cheetah*

One way to create a quadruped galloping robot from scratch is to design a brick-shaped body and utilize relatively simple open-chain leg mechanisms controlled with relatively complex control algorithms. Alternatively, we can look at how nature solved the same task designing fast mammals such as cheetah, and by means of morphological computation, we can design a complex mechanical system that has much of the desired behavior within inherent dynamics and only a little control effort is needed to stabilize or augment the motion.In this paper, we have analyzed a real cheetah motion using video tracking and looked for a way to match the dynamic model parameters of the real cheetah with a galloping robot with an elastic spine. We believe the elastic spine is the essential feature for a fast-running energy-efficient galloping robot. Within this paper, we are focused on the flying stage when the elastic spine affects the motion of the robot’s front and rear bodies. We have found how to optimize mass distribution and elasticity in the spine in order to get the cheetah-like galloping motion of a quadruped robot.
Predicting Mortality of Korean Geriatric Trauma Patients: A Comparison between Geriatric Trauma Outcome Score and Trauma and Injury Severity Score

Purpose The Geriatric Trauma Outcome Score (GTOS) is a new prognostic tool used to predict mortality of geriatric trauma patients. We aimed to apply this model to Korean geriatric trauma patients and compare it with the Trauma and Injury Severity Score (TRISS) method. Materials and Methods Patients aged ≥65 years who were admitted to a level 1 trauma center from 2014 to 2018 were included in this study. Data on age, Injury Severity Score (ISS), packed red blood cell transfusion within 24 h, TRISS, admission disposition, mortality, and discharge disposition were collected. We analyzed the validity of GTOS and TRISS by comparing the area under the survival curve. Subgroup analysis for age, admission disposition, and ISS was performed. Results Among 2586 participants, the median age was 75 years (interquartile range: 70–81). The median ISS was 9 (interquartile range: 4–12), with a transfusion rate (within 24 h) of 15.9% and mortality rate of 6.1%. The areas under the curve (AUCs) were 0.832 [95% confidence interval (CI), 0.817–0.846] and 0.800 (95% CI, 0.784–0.815) for GTOS and TRISS, respectively. On subgroup analysis, patients with ISS ≥9 showed a higher AUC of GTOS compared to the AUC of TRISS (p<0.05). Other subgroup analyses showed equally good power of discrimination for mortality. Conclusion GTOS can be used to predict mortality of severely injured Korean geriatric patients, and also be helpful in deciding whether invasive or aggressive treatments should be administered to them.
What’s Best for My Mesh? Convex or Non-Convex Regularisation for Mesh Optimisation

A 3D mesh offers a rich yet lightweight representation of geometry and topology for the metric and semantic understanding of a robot’s scene. Noisy features are often used to generate the mesh which furthers the need for accurate regularisation. Current approaches tightly couple front-end optimisation with regularisation making it difficult to evaluate the choice of discretisation and regularisation on mesh accuracy. In this work, we aim to explicitly query the performance of a set of well-known convex and non-convex regularisers on the mesh optimisation problem. We then apply these norms to dense depth estimation from a mesh representation and evaluate their performance in indoor and outdoor environments.While we show that the use of exotic, non-convex regularisers such as logTV and logTGV can result in more faithful structural reconstruction under noise, this comes at the cost of stronger outlier persistence that limits their performance when compared to their convex equivalents. This represents a significant departure from results achieved when the same regularisers are applied in denser "every-pixel" scenarios and suggests that current discretisation techniques adopted for this problem are more sensitive to triangulation. This sensitivity is often obscured in many practical robotic applications by a rigorous front-end that removes artefacts from the mesh to be optimised. By decoupling the front and back-ends we therefore show that further consideration must be taken to align current mesh discretisations with the classical definitions of variational regularisers to allow the full benefit of their well-documented properties to be realised.
Inappropriate Patient Sexual Behavior in Physiotherapy: A Systematic Review

A behavior which is increasing in prevalence is sexual harassment initiated by a client and displayed towards the healthcare professionals and students of these healthcare-related professions. This is termed inappropriate patient sexual behaviour (IPSB). The consequences of IPSB can be significant, including decreased academic and work performance, decreased attention/concentration, reductions in work satisfaction, and a loss of confidence. The primary aim is to evaluate the literature on sexual harassment in physiotherapy. The secondary aim is to report on the incidence, situational factors, and suggested strategies. The databases Pubmed, Ovid MEDLINE, CINAHL Plus, Embase via OVID, ProQuest, and EBM Reviews were searched from inception up to 5 November 2021. Data on the incidence, situations, and strategies were extracted by at least two independent researchers. The quality of included articles was assessed. Nine studies of cohort and cross-sectional design were included. The incidence of IPSB was reported to be between 48–100% of the samples of physiotherapy students and/or therapists. The situational factors are reported, and the recommended educational strategies are discussed. Articles suggest that educating physiotherapists and/or students about sexual harassment would be beneficial. This will help predict potential issues and highlight strategies to empower therapists in the workplace and in training.
Evolutionary learning in the brain by heterosynaptic plasticity

How the brain modifies synapses to improve the performance of complicated networks remains one of the biggest mysteries in neuroscience. Canonical models suppose synaptic weights change according to pre- and post-synaptic activities (i.e., local plasticity rules), implementing gradient-descent algorithms. However, the lack of experimental evidence to confirm these models suggests that there may be important ingredients neglected by these models. For example, heterosynaptic plasticity, non-local rules mediated by inter-cellular signaling pathways, and the biological implementation of evolutionary algorithms (EA), another machine-learning paradigm that successfully trains large-scale neural networks, are seldom explored. Here we propose and systematically investigate an EA model of brain learning with non-local rules alone. Specifically, a population of agents are represented by different information routes in the brain, whose task performances are evaluated through gating on individual routes alternatively. The selection and reproduction of agents are realized by dopamine-guided heterosynaptic plasticity. Our EA model provides a framework to re-interpret the biological functions of dopamine, meta-plasticity of dendritic spines, memory replay, and the cooperative plasticity between the synapses within a dendritic neighborhood from a new and coherent aspect. Neural networks trained with the model exhibit analogous dynamics to the brain in cognitive tasks. Our EA model manifests broad competence to train spiking or analog neural networks with recurrent or feedforward architecture. Our EA model also demonstrates its powerful capability to train deep networks with biologically plausible binary weights in MNIST classification and Atari-game playing tasks with performance comparable with continuous-weight networks trained by gradient-based methods. Overall, our work leads to a fresh understanding of the brain learning mechanism unexplored by local rules and gradient-based algorithms.
A novel discriminant feature selection–based mutual information extraction from MR brain images for Alzheimer's stages detection and prediction

Alzheimer's disease (AD), a neurodegenerative disorder, is a form of dementia. Quick or early diagnosis of AD is essential, but most of the available studies have focused on clinical or survey‐based data, leading to data inconsistency as many people feel hesitant or hide information due to disease and societal stigma. Nowadays, current computer‐aided support and techniques are mainly based on feature extraction, but due to redundant or similarly extracted features, any specific model is not producing best performance. This paper proposes a novel mutual relationship–based feature selection model with high‐altitude acute response like features for the brain‐predefined feature areas using magnetic resonance imaging. The mutual relationship between features is used to avoid similar features or create discrimination between different features due to which accuracy gets affected. In this work, four machine learning classifiers, namely decision tree, support vector machine (SVM), k‐nearest neighbor, and Naive Bayes are used for developing predictive model and algorithms. To avoid overfitting in model selection, we have used a 10‐fold cross‐validation for model training and testing. We collected data set from Alzheimer's disease Neuroimaging Initiative repository. The performance of supervised classifiers was estimated with area under the receiver operating characteristic curve, accuracy, precision, recall, and F1 score assessment measures. The results indicate SVM to be the best performing classifier for prediction (SVM recording the highest average area under curve score of 0.936, accuracy of 94.1%, precision of 96.9%, recall of 96.6%, and F1‐score of 96.8%) with 37 discriminant features.
An operational dropping model towards efficient aerial firefighting.

Forest fires have multifaceted impacts on societies. When integrated in an effective firefighting strategy, the rapid access of aerial resources to remote areas can play a crucial role. However, the efficiency of an aerial drop, due to the erratic atmospheric conditions and reduced visibility, depends essentially on the pilot’s expertise since on-board systems for computer-assisted drops are unavailable. This work addresses the development of a numerical model for the real-time simulation of an aerial drop of firefighting products. The gas-phase is modelled through a vegetative canopy model coupled to a modified surface-layer model under diabatic conditions. For the particulate phase, the primary breakup of the retardant jet is obtained through the continuous stripping of droplets from the exposed surfaces by Rayleigh-Taylor and Kelvin-Helmholtz instabilities. The formed droplets are then subjected to distortion and secondary breakup due to aerodynamic forces mostly based on experimental correlations defined in terms of the Weber number. During the process, droplets are dispersed applying a Lagrangian approach. The code is linked to a GIS-based graphical interface, thus privileging the use by operational people. Computed ground pattern has been compared, with generally good results, with experimental data from a set of real scale dropping tests in which both conventional and constant flow-rate delivery systems were used. The model has potential to be used as a demonstrative application in firefighters training; as an operational tool during firefighting operations; or in the development of new products, as an alternative method to real scale dropping tests.
320 Gbit/s error-free demultiplexing using ultrafast optical gate monolithically integrating a photodiode and electroabsorption modulator

A 320 Gbit/s error-free demultiplexing operation with a receiver sensitivity of −18 dBm using a monolithic optical gate integrating a uni-travelling-carrier photodiode and a travelling-wave electroabsorption modulator has been demonstrated. High on/off ratios of 14 dB for adjacent channels and 28 dB for the others have also been achieved.
Novel wide‐stopband bandpass filter with good frequency selectivity based on composite right/left handed transmission line

A novel wide‐stopband bandpass filter (BPF) with quasi‐elliptic response based on composite right/left handed transmission line (CRLH‐TL) is presented in this letter. Two compact CRLH‐TL resonators are utilized in the proposed wide‐stopband BPF. A magnetic cross coupling between the input and output ports is also used, which can generate three additional transmission zeros near the passband. Then, the frequency selectivity of the bandpass filter is greatly improved. The equivalent circuit method is used to analyze the mechanism of the magnetic coupling. A wide‐stopband BPF operating at 2.42 GHz is designed, simulated, and fabricated to demonstrate the performance of the proposed filter structure. The measured results show good agreement with the simulated ones. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:2494–2497, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27104
Multitarget-Multisensor Tracking: Applications and Advances

Practical Aspects of Multisensor Tracking. Survey of Assignment Techniques for Multitarget Tracking. IMM Estimator with Nearest Neighbor Joint Probabilistic Data Association. Multiassignment for Tracking a Large Number of Overlapping Objects. Finite Difference Methods for Nonlinear Filtering and Automatic Target Recognition. Large Scale Ground Target Tracking with Single and Multiple MTI Sensors. Radar Systems Modeling for Tracking. ECM Modeling for Multitarget Tracking and Data Association. Waveform Detection/Tracking Performance at the System Level. Engineer's Guide to Variable-Structure Multiple-Model Estimation for Tracking.
Fast Generation of Obstacle-Avoiding Motion Primitives for Quadrotors*

This work considers the problem of generating computationally efficient quadrotor motion primitives between a given pose (position, velocity, and acceleration) and a goal plane in the presence of obstacles. A new motion primitive tool based on the logistic curve is proposed and a closed-form analytic approach is developed to satisfy constraints on starting pose, goal plane, velocity, acceleration, and jerk. The geometric obstacle avoidance problem is represented as a combinatorial set problem and a heuristic approach is proposed to accelerate the solution search. Numerical examples are presented to highlight the fast motion primitive generation in multi-obstacle pose-to-plane scenarios.
Ectopic Expression of a Salt-Inducible Gene, LcSAIN3, from Sheepgrass Improves Seed Germination and Seedling Growth under Salt Stress in Arabidopsis

Sheepgrass is a perennial native grass species in China, and it can tolerate high levels of salt stress with an aggressive and vigorous rhizome system. Many salt-stress-responsive genes have been identified in sheepgrass. In this study, we report the cloning and characterization of a novel salt-induced gene, LcSAIN3 (Leymus chinensis salt-induced 3), from sheepgrass. Expression analysis confirmed that LcSAIN3 was induced by PEG, ABA, and salt treatments, and the expression of LcSAIN3 was significantly increased in salt-tolerant germplasms under salt treatment. Subcellular localization analysis indicated that the GFP-LcSAIN3 protein was mainly localized in the chloroplasts. The heterologous expression of LcSAIN3 in Arabidopsis increased the seed germination rate of transgenic plants under salt, ABA, and mannitol treatments. The seedling survival rate, plant height, and fresh weight of the transgenic plants were higher than those of WT plants under salt stress. The overexpression of LcSAIN3 caused a relatively high accumulation of free proline, enhanced SOD activity, and led to the upregulation of several stress-responsive genes such as AtRD26, AtRD29B, AtSOS1, and AtP5CS1. These results suggest that LcSAIN3 could be a potential target for molecular breeding to improve plants’ salt tolerance.
Joint Multiple Visual Constraints for High Speed Video Stitching

A major concern in aerial video surveillance today is to improve the processing speed continuously. This work introduces a joint visual constraints method for high speed aerial video stitching. To obtain real-time and accurate performance, we first select the compact and efficient ORB (Oriented FAST and Rotated BRIEF) for fast local feature description and matching, and then adopt the dynamic key frame based video stitching framework to reduce the accumulation errors. To further achieve high speed performance, we improve the above framework by fusing spatial and temporal constraints of ORB keypoints during online stitching, and increase the processing speed to 150 fps successfully. The results with public available UAV datasets demonstrate the superiority of joint constraints.
Linear Policies are Sufficient to Enable Low-Cost Quadrupedal Robots to Traverse Rough Terrain

The availability of inexpensive 3D-printed quadrupedal robots motivates the development of learning-based methods compatible with low-cost embedded processors and position-controlled hobby servos. In this work, we show that a linear policy is sufficient to modulate an open-loop trajectory generator, enabling a quadruped to walk over rough, unknown terrain, with limited sensing. The policy is trained in simulation using randomized terrain and dynamics and directly deployed on the robot. We show that the resulting controller can be implemented on resource-constrained systems. We demonstrate the results by deploying the policy on the OpenQuadruped, an open-source 3D-printed robot equipped with hobby servos and an embedded microprocessor.
“Hotel – OTA” interaction and its influence on the optimization of urban hotels’ distribution channels

Research background: The interaction between hotels and the online travel agencies (OTAs) influences the hotel sales, creating dependencies, which the hotel managers are reluctant to accept. The indicators that evaluate urban hotel sales in Bulgaria in the scope of partnership with OTA are examined. The influence of the modern digital tools to enhance business performance results is reviewed. Purpose of the article: Focusing on Bulgarian urban hotels, the research measures the impact of diverse factors for shaping an adequate business model of an urban hotel. The effect of the share of the hotel sales via OTA platforms, the number of OTAs used, the occupancy rate, the RevPAR and the Booking.com rating score is considered. Finding an appropriate model for digital behavior of urban hotel enterprises is one of the aims of the survey. Methods: A questionnaire distributed among urban hotels situated in industrial towns of Bulgaria is conducted. Linear regression and logistic regression methods are applied for the purpose of the study. Findings & Value added: The importance of channel manager technology for business metrics in this sector is concerned. Three generalized hotel operating models are extracted. It is concluded that there is a necessity for constant management and review of the hotel - OTA relations.