Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of low-temperature fluoride routes to synthesize actinide nitrides and oxide solid solutions

Evaluation of Low-Temperature Fluoride Routes to Synthesize Actinide Nitrides and Oxide Solid Solutions by Gunanda Waduge Chinthaka Silva Dr. Kenneth R. Czerwinski, Examination Committee Chair Professor of Chemistry Head of the Department of Radiochemistry University of Nevada, Las Vegas Actinide mononitrides have been considered as a possible nuclear fuel for the Generation-IV nuclear reactor systems. In the process of evaluating these actinide mononitrides as nuclear fuel, it is important to study different chemical and physical characteristics of these compounds. Synthesis of the materials is thus important. Carbothermic reduction is one of the techniques that have been used to synthesize actinide mononitrides. In this method, a mixture of actinide oxide such as UO2 and excess carbon is heat treated at temperatures greater than 1700 °C under a nitrogen atmosphere. The technique is however not promising in synthesizing the actinide mononitrides due to a number of disadvantages the technique presents. Lack of phase purity due to secondary chemical phases with carbon and oxygen, need of high temperatures such as 2200 °C, and the low density of the final product compared to theoretical density are some of the drawbacks that the researches have been encountered. Most of all this method is tiresome and difficult to handle in ordinary laboratories where the experimental setups and
Ethnobotanical study of plants used by Thami community in Ilam District, eastern Nepal

An ethnobotanical survey was carried out on the utilization of plants by Thami communities in Gorkhe, Jogmai and Nayabazar areas of Ilam by interviewing traditional herbalists and different age groups of men and women in June 2016. A total of 30 plants belonging to 24 families and 29 genera have been documented. These plants were used for food, fodder, firewood, medicine and in rituals. The documented medicinal plants were used to treat various human ailments of 12 categories; with the highest number of species being used for gastro-intestinal disorders (15 spp.) followed by ENT problems (14 spp.). Most of the medicines were prepared from underground parts in the form of paste and used orally. Informant Consensus Factor (Fic) ranges from 0.6 to 0.9 with an average of 0.82. Dermatological disorders have the highest Fic (0.90) and other categories have the lowest (0.6). Aconitum palmatum, Begonia picta, Bergenia ciliata, Astilbe rivularis, Swertia chirayita, Drymaria cordata and Remusatia pumila have the highest fidelity level (100% each) and Galium asperifolium has the lowest FL (16%). According to the use value, Swertia chirayita (UV=2.83) was the most important with uses against 6 ailments and Hypericum cordifolium has the least (UV=0.08), used in only one ailment. A variation in ethnobotanical knowledge was found according to age, gender and occupation in this community.
Automatic Speech Recognition for ILSE-Interviews: Longitudinal Conversational Speech Recordings Covering Aging and Cognitive Decline

The Interdisciplinary Longitudinal Study on Adult Development and Aging (ILSE) was initiated with the aim to investigate satisfying and healthy aging. Over 20 years, about 4200 hours of biographic interviews from more than 1,000 participants were recorded. Spoken language is a strong indicator for declining cognitive resources, as it is affected in early stage. Hence, various research topics related to aging like dementia, could be analyzed based on data such as the ILSE interviews. The analysis of language capabilities requires transcribed speech. Since manual transcriptions are time and cost consuming, we aim to automatically transcribing the ILSE data using Automatic Speech Recognition (ASR). The recognition of ILSE interviews is very demanding due to the combination of various challenges: 20 year old analog two-speaker one-channel recordings of low signal quality, emotional and personal interviews between doctor and participant, and repeated recordings of aging, partly fragile individuals. In this study, we describe ongoing work to develop hybrid Hidden Markov Model (HMM)Deep Neural Network (DNN) based ASR system for the ILSE corpus. So far, the best ASR system is obtained by second-pass decoding of a hybrid HMM-DNN model using recurrent neural network based language models with a word error rate of 50.39%.
DurIAN: Duration Informed Attention Network for Speech Synthesis

In this paper, we present a robust and effective speech synthesis system that generates highly natural speech. The key component of proposed system is Duration Informed Attention Network (DurIAN), an autoregressive model in which the alignments between the input text and the output acoustic features are inferred from a duration model. This is different from the attention mechanism used in existing end-to-end speech synthesis systems that accounts for various unavoidable artifacts. To improve the audio generation efﬁciency of neural vocoders, we also propose a multi-band audio generation framework exploiting the sparseness characteristics of neural network. With proposed multi-band processing framework, the total computational complexity of WaveRNN model can be effectively reduced from 9.8 to 3.6 GFLOPS without any performance loss. Finally, we show that proposed DurIAN system could generate highly natural speech that is on par with current state of the art end-to-end systems, while being robust and stable at the same time.
Sound Event Localization and Detection Based on Multiple DOA Beamforming and Multi-Task Learning

The performance of sound event localization and detection (SELD) degrades in source-overlapping cases since features of different sources collapse with each other, and the network tends to fail to learn to separate these features effectively. In this paper, by leveraging the conventional microphone array signal processing to generate comprehensive representations for SELD, we propose a new SELD method based on multiple direction of arrival (DOA) beamforming and multi-task learning. By using multiple beamformers to extract the signals from different DOAs, the sound ﬁeld is more diversely described, and specialised representations of target source and noises can be obtained. With labelled training data, the steering vector is estimated based on the cross-power spectra (CPS) and the signal presence probability (SPP), which eliminates the need of knowing the array geometry. We design two networks for sound event localization (SED) and sound source localization (SSL) and use a multi-task learning scheme for SED, in which the SSL-related task act as a regularization. Experimental results using the database of DCASE2019 SELD task show that the proposed method achieves the state-of-art performance.
Regional Resonance of the Lower Vocal Tract and its Contribution to Speaker Characteristics

This study attempts to describe a plausible causal mechanism of generating individual vocal characteristics in higher spectra. The lower vocal tract has been suggested to be such a causal region, but a question remains as to how this region modulates vowels’ higher spectra. Based on existing data, this study predicts that resonance of the lower vocal tract modulates higher vowel spectra into a peak-dip-peak pattern. A preliminary acoustic simulation was made to confirm that complexity of lower vocal-tract cavities generates such a pattern with the second peak. This spectral modulation pattern was further examined to see to what extent it contributes to generating static speaker characteristics. To do so, a statistical analysis of male and female F-ratio curves was conducted based on a speech database. In the result, three frequency regions for the peak-dip-peak patterns correspond to three regions in the gender-specific F-ratio curves. Thus, this study suggests that, while the first peak may be the major determinant by the human ears, the whole frequency pattern facilitates speaker recognition by machines.
Cross Attention with Monotonic Alignment for Speech Transformer

Transformer, a state-of-the-art neural network architecture, has been used successfully for different sequence-to-sequence transformation tasks. This model architecture disperses the attention distribution over entire input to learn long-term dependencies, which is important for some sequence-to-sequence tasks, such as neural machine translation and text summarization. However, automatic speech recognition (ASR) has a characteristic to have monotonic alignment between text output and speech input. Techniques like Connectionist Temporal Classiﬁ-cation (CTC), RNN Transducer (RNN-T) and Recurrent Neural Aligner (RNA) build on top of this monotonic alignment and use local encoded speech representations for corresponding to-ken prediction. In this paper, we present an effective cross attention biasing technique in transformer that takes monotonic alignment between text output and speech input into consideration by making use of cross attention weights. Speciﬁcally, a Gaussian mask is applied on cross attention weights to limit the input speech context range locally given alignment information. We further introduce a regularizer for alignment regularization. Experiments on LibriSpeech dataset ﬁnd that our proposed model can obtain improved output-input alignment for ASR, and yields 14.5%-25.0% relative word error rate (WER) reductions.
Gated Multi-Head Attention Pooling for Weakly Labelled Audio Tagging

Multiple instance learning (MIL) has recently been used for weakly labelled audio tagging, where the spectrogram of an audio signal is divided into segments to form instances in a bag, and then the low-dimensional features of these segments are pooled for tagging. The choice of a pooling scheme is the key to exploiting the weakly labelled data. However, the traditional pooling schemes are usually ﬁxed and unable to distinguish the contributions, making it difﬁcult to adapt to the characteristics of the sound events. In this paper, a novel pooling algorithm is proposed for MIL, named gated multi-head attention pooling (GMAP), which is able to attend to the information of events from different heads at different positions. Each head allows the model to learn information from different representation subspaces. Furthermore, in order to avoid the redundancy of multi-head information, a gating mechanism is used to fuse individual head features. The proposed GMAP increases the modeling power of the single-head attention with no computational overhead. Experiments are carried out on Audioset, which is a large-scale weakly labelled dataset, and show superior results to the non-adaptive pooling and the vanilla attention pooling schemes.
On the Effect of Age on the Transmission of SARS-CoV-2 in Households, Schools, and the Community

Abstract Background There is limited information on the effect of age on the transmission of SARS-CoV-2 infection in different settings. Methods We reviewed published studies/data on detection of SARS-CoV-2 infection in contacts of COVID-19 cases, serological studies, and studies of infections in schools. Results Compared to younger/middle-aged adults, susceptibility to infection for children younger than 10 years is estimated to be significantly lower, while estimated susceptibility to infection in adults older than 60 years is higher. Serological studies suggest that younger adults (particularly those younger than 35 years) often have high cumulative incidence of SARS-CoV-2 infection in the community. There is some evidence that given limited control measures, SARS-CoV-2 may spread robustly in secondary/high schools, and to a lesser degree in primary schools, with class size possibly affecting that spread. There is also evidence of more limited spread in schools when some mitigation measures are implemented. Several potential biases that may affect these studies are discussed. Conclusions Mitigation measures should be implemented when opening schools, particularly secondary/high schools. Efforts should be undertaken to diminish mixing in younger adults, particularly individuals aged 18–35 years, to mitigate the spread of the epidemic in the community.
Frame-Level Signal-to-Noise Ratio Estimation Using Deep Learning

This study investigates deep learning based signal-to-noise ratio (SNR) estimation at the frame level. We propose to employ recurrent neural networks (RNNs) with long short-term memory (LSTM) in order to leverage contextual information for this task. As acoustic features are important for deep learning algorithms, we also examine a variety of monaural features and investigate feature combinations using Group Lasso and sequential ﬂoating forward selection. By replacing LSTM with bidirectional LSTM, the proposed algorithm naturally leads to a long-term SNR estimator. Systematical evaluations demonstrate that the proposed SNR estimators signiﬁcantly outperform other frame-level and long-term SNR estimators.
Psychological Variables Related to Developmental Changes during Adolescence—A Comparison between Alpine and Non-Alpine Sport Participants

Alpine sport is a popular form of exercise and provides several skills that are potentially relevant for positive development during adolescence. However, empirical data on differences between alpine and non-alpine sport participants in variables related to developmental changes are lacking. Therefore, the primary aim of the present study was to analyze differences in self-esteem and additional variables between adolescent alpine and non-alpine sport participants. A comparison to non-regular exercisers was conducted for self-esteem. In a cross-sectional design, information on self-esteem, sensation seeking, agency, and emotion regulation was collected in 183 adolescents [(mean age: 15.4 (SD: 2.3) years, 71.0% female)]. Alpine sport participants reported significantly higher self-esteem compared to non-regular exercisers, p = 0.003, d = 0.95, but not compared to non-alpine sport participants, p = 0.774, d = 0.06. When controlling for sex and high-risk sport engagement, alpine sport participants showed a significantly higher experience of agency compared to non-alpine sport participants, p = 0.016, d = 0.46. We conclude that alpine sport participation is less relevant with regard to self-esteem compared to regular exercise. However, the characteristics of alpine sport might provide a trigger for higher experience of agency during sport participation, potentially helping to satisfy the increased need for autonomy and independence in adolescence.
New Nanostructured Carbon Coating Inhibits Bacterial Growth, but Does Not Influence on Animal Cells

An electrospark technology has been developed for obtaining a colloidal solution containing nanosized amorphous carbon. The advantages of the technology are its low cost and high performance. The colloidal solution of nanosized carbon is highly stable. The coatings on its basis are nanostructured. They are characterized by high adhesion and hydrophobicity. It was found that the propagation of microorganisms on nanosized carbon coatings is significantly hindered. At the same time, eukaryotic animal cells grow and develop on nanosized carbon coatings, as well as on the nitinol medical alloy. The use of a colloidal solution as available, cheap and non-toxic nanomaterial for the creation of antibacterial coatings to prevent biofilm formation seems to be very promising for modern medicine, pharmaceutical and food industries.
Introgression of durable blast resistance gene Pi-54 into indica rice cv. samba mahsuri, through Marker Assisted Backcross Breeding

Blast disease is one of the most significant diseases of rice, where severe infection results in more than 80% reduction in yield. It is caused by Pyricularia oryzae. New breeding strategies are essential for developing durable blast resistant varieties. The present study aimed to introgress Pi-54 gene from highly blast resistant genotype i.e. Tetep into elite rice cultivar Samba Mahsuri (BPT 5204), high yielding rice variety with good cooking quality ,but susceptible to blast disease, through Marker-Assisted Backcross Breeding programme (MABB). For foreground selection tightly linked molecular marker specific to Pi-54 gene (i.e. Pi-54MAS) which is located on chromosome 11, and it is utilized at each backcrossed generation to identify plants carrying heterozygous alleles for the targeted resistant gene. A total of 56 background markers were used to estimate the recovery of recurrent parent genome in each backcrossed generations. At BC2F2, a single plant carrying the targeted resistant gene Pi-54 with maximum recovery of recurrent parent genome (~92.80%; plant BT-8-47-22) was selected and forwarded to next generations through the selfing. Ancestry based selection procedure was employed for phenotypic disease screening and agro-morphological traits. Results confirmed that, resistance gene (Pi-54) was successfully incorporated into Samba Mahsuri. Six lines viz., BT-8-47-22-6-36, BT-8-47-22-6-55, BT-8-47-22-6-117, BT-8-47-22-6-159, BT-8-47-22-6-203 and BT-8-47-22-6-267 were identified at BC2F4 which were possessing high level of resistance to blast and agro-morphological traits similar to Samba Mahsuri. One NIL line (BT-8-47-22-6-203) was found to be better than recurrent parent Samba Mahsuri (BPT 5204) regarding grain yield per plant. This finding will be helpful in developing a blast resistant variety with highest recurrent parent genome recovery in less number of generations through the application of MABB.
The Strengths and Difficulties Questionnaire: An examination of factorial, convergent, and discriminant validity using multitrait-multirater data.

This study examined the factorial, convergent, and discriminant validity of scores on the Strengths and Difficulties Questionnaire (SDQ), a tool for screening children's psychological adjustment. Data were collected from a community sample of 346 children (46% girls, M age = 54.07 months), using teacher, mother, and father reports. Results from confirmatory factor analyses indicated that the SDQ's hypothesized 5-factor structure fit the data well and partial strict measurement invariance was established across raters. Using teachers' reports as reference method, a correlated trait-correlated method minus 1 model (Eid et al., 2008) was fitted to investigate convergent and discriminant validity. The convergent validity of parents' ratings relative to teachers' ratings was modest. Mothers and fathers had a unique perspective on children's behavior above and beyond their partial overlap with teacher reports. Results indicated good discriminant validity between most of the traits measured by the SDQ. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Concordance among patients and physicians about their ideal of autonomy impacts the patient-doctor relationship: A cross-sectional study of Mexican patients with rheumatic diseases

Introduction In patient-doctor interaction both parties play a role. Primary objective was to determine if the concordance among rheumatologists and their patients of their ideal of autonomy was associated with a better patient-doctor relationship. Secondary objective was to describe factors associated to a patient paternalistic ideal of autonomy (PPIA). Materials and methods This cross-sectional study had 3 steps. Step-1 consisted in translation/cultural local adaption of Ideal Patient Autonomy Scale (IPAS), a 14-items Dutch questionnaire. Step-2 consisted of IPAS validity and reliability in 201 outpatients. Step-3 consisted of the application of IPAS and the patient-doctor relationship questionnaire (PDRQ) to 601 outpatients with a medical encounter, and of IPAS to the 21 attending rheumatologists. Each patient-physician encounter was classified into with/without concordance in the ideal of autonomy and PRDQ scores were compared (Man Whitney U test). Regression analysis was used for associations. Results Step-1 followed ISPOR task force recommendations. Patients from Step-2 and Step-3 were representative outpatients with rheumatic diseases. IPAS structure underwent a modification; the 14 items were redistributed into four subscales, further combined into PPIA vs. patient-centered autonomy ideal. IPAS was valid and reliable. There were 497 patients with a preferred ideal of autonomy, primarily (84.9%) PPIA. There were 363 patient-doctor encounters with concordance in the autonomy ideal and their PDRQ-9 scores were higher. Religious beliefs and higher PDRQ-9 item 8 score (“I feel pleased with my doctor´s treatment”) were associated to a PPIA. Conclusions Concordance of autonomy ideal among patients and their rheumatologists positively impacts on the patient-doctor relationship.
Magnetorheological Elastomer Stress Relaxation Behaviour during Compression: Experiment and Modelling

Materials characterized by magnetorheological properties are non-classic engineering materials. A significant increase in the interest of the scientific community about this group of materials could be observed over the recent years. The results of research presented in this article are oriented on the examination of the said materials’ mechanical properties. Stress relaxation tests were carried out on cylindrical samples of magnetorheological elastomers loaded with compressive stress, for various values of magnetic induction (B1 = 0 mT, B2 = 32 mT, B3 = 48 mT, and B4 = 64 mT) and temperature (T1 = 25 °C, T2 = 30 °C, and T3 = 40 °C). The results of these tests indicate that the stiffness of the examined samples increased along with the increase of magnetic field induction, and decreased along with the increase of temperature. On this basis, it has been determined that: the biggest stress amplitude change, caused by the influence of magnetic field, was σ0ΔB = 12.7%, and the biggest stress amplitude change, caused by the influence of temperature, was σ0ΔT = 11.3%. As a result of applying a mathematical model, it was indicated that the stress relaxation in the examined magnetorheological elastomer, for the adopted time range (t = 3600 s), had a hyperbolic decline nature. The collected test results point to the examined materials being characterized by extensive rheological properties, which leads to the conclusion that it is necessary to conduct further tests in this area.
Transient Improvement after Switch to Low Doses of RimabotulinumtoxinB in Patients Resistant to AbobotulinumtoxinA

Botulinum toxin type B (BoNT/B) has been recommended as an alternative for patients who have become resistant to botulinum toxin type A (BoNT/A). This study aimed to compare the clinical effect, within a patient, of four injections with low doses of rimabotulinumtoxinB with the effect of the preceding abobotulinumtoxinA (aboBoNT/A) injections. In 17 patients with cervical dystonia (CD) who had become resistant to aboBoNT/A, the clinical effect of the first four rimabotulinumtoxinB (rimaBoNT/B) injections was compared to the effect of the first four aboBoNT/A injections using a global assessment scale and the TSUI score. After the first two BoNT/B injections, all 17 patients responded well and to a similar extent as to the first two BoNT/A injections, but with more side effects such as dry mouth and constipation. After the next BoNT/B injection, the improvement started to decline. The response to the fourth BoNT/B injection was significant (p < 0.048) lower than the fourth BoNT/A injection. Only three patients developed a complete secondary treatment failure (CSTF) and five patients a partial secondary treatment failure (PSTF) after four BoNT/B injections. In nine patients, the usual response persisted. With the use of low rimaBoNT/B doses, the induction of CSTF and PSTF to BoNT/B could not be avoided but was delayed in comparison to the use of higher doses. In contrast to aboBoNT/A injections, PSTF and CSTF occurred much earlier, although low doses of rimaBoNT/B had been applied.