Miracle-dz/UniFAR-FTUs huggingface dataset:
Dysarthric Speech Recognition, Detection and Classification using Raw Phase and Magnitude Spectra

In this paper, we explore the effectiveness of deploying the raw phase and magnitude spectra for dysarthric speech recognition, detection and classification. In particular, we scrutinise the usefulness of various raw phase-based representations along with their combinations with the raw magnitude spectrum and fil-terbank features. We employed single and multi-stream architectures consisting of a cascade of convolutional, recurrent and fully-connected layers for acoustic modelling. Furthermore, we investigate various configurations and fusion schemes as well as their training dynamics. In addition, the accuracies of the raw phase and magnitude based systems in the detection and classification tasks are studied and discussed. We report the performance on the UASpeech and TORGO dysarthric speech databases and for different severity levels. Our best system achieved WERs of 31.2% and 9.1% for dysarthric and typical speech on TORGO and 30.2% on UASpeech, respectively.
Embedding Articulatory Constraints for Low-resource Speech Recognition Based on Large Pre-trained Model

Knowledge about phonemes and their articulatory attributes can help improve automatic speech recognition (ASR) of low-resource languages. In this study, we propose a simple and effective approach to embed prior knowledge about phonemes into end-to-end ASR based on a large pre-trained model. An articulatory attribute prediction layer is constructed by embedding articulatory constraints in layer initialization, which allows for predicting articulatory attributes without the need for explicit training. The final ASR transcript is inferred by combining the output of this layer with encoded speech features. We apply our method to finetune a pre-trained XLS-R model using Ainu and Mboshi corpora, and achieve a 12% relative improvement when target data of only 1 hour is available. This demonstrates that the approach of incorporating phonetic prior knowledge is useful when combined with a large pre-trained model.
A Study on Using Duration and Formant Features in Automatic Detection of Speech Sound Disorder in Children

Speech sound disorder (SSD) in children is manifested by persistent articulation and phonological errors on specific phonemes of a language. Automatic SSD detection can be done using features extracted from deep neural network models. Interpretability of such learned features is a major concern. Motivated by clinical knowledge, the use of duration and formant features for SSD detection is investigated in this research. Acoustical analysis is performed to identify the acoustic features that differentiate between the speech of typical and disordered children. On the task of SSD detection in Cantonese-speaking children, the duration features are found to outperform the formant feature, and surpass previous methods that use par-alinguistic feature set and speaker embeddings. Specifically, the duration features achieve a mean unweighted average recall of 71.0%. The results enhance the understanding of SSD, and motivate further use of temporal information of child speech in SSD detection.
Traffic Flow Prediction Based on Optimized LSTM Model

Intelligent transportation system (ITS) refers to comprehensive transport systems that uses advanced science and technology to ensure safety, enhance efficiency, improve environment, and save energy. Traffic flow prediction is a research focus of Intelligent Transportation Systems (ITS), which provides important basis for ITS planning and scheduling, and is crucial for ITS. As traffic flow changes are the result of multiple factors such as weather, accidents, road control, etc., fluctuations are large and irregular. Especially in the minute-level and hour-level traffic flow prediction, it is difficult to predict the trend of traffic flow accurately. To address this issue, this paper fully considers the temporal, periodic, and spatial features of traffic flow, and proposes a serial model of LSTM-LightGBM for hour-level traffic flow prediction, which uses the output of LSTM as the input of LightGBM. LightGBM can capture the spatial and periodic features of traffic flow, while LSTM is able to capture the temporal features of traffic flow. The LSTM-LightGBM model is tested on the Chicago traffic dataset. Results show that LSTM-LightGBM has the least RMSE and MAE among all tested models, and the RMSE of LSTM-LightGBM can be reduced by up to 50% compared to other base models, indicating that this model has great potential.
Shoulder, Trunk, and Hip Sagittal Plane Kinematics during Stand-Up Paddle Boarding

Stand-up paddle boarding (SUP) as both a competitive and recreational sport has grown in popularity over the last decade. Better understanding paddling kinematics is beneficial for both injury prevention and informing coaching practices in this growing sport. The purpose of this study was to analyze sagittal plane kinematics during both standing and kneeling paddling postures commonly adopted by injury-free, recreational SUP participants. Eighteen recreational SUP participants (seven males/eleven females) were asked to complete a series of paddling tasks on a SUP ergometer in two postures, during which kinematic data were acquired. Sagittal plane kinematic data were analyzed for joint excursion, or range of motion used, while paddling on both sides of the body in each posture. Analysis of variance was used to compare joint excursions across tasks. There were no significant differences in hip or trunk sagittal plant excursion between postures. However, there was significantly greater sagittal plane excursion at the shoulder in the kneeling as compared to the standing posture with the shoulder opposite the paddling side demonstrating the greatest total excursion. These results help establish the parameters of the paddling technique currently in use among injury-free SUP participants and may be used in the future to inform coaching practices.
Opioid Harm Reduction Strategies for Age-Friendly Rural Communities

Background: Over 10, 000 overdose deaths have been attributed to opioid misuse, with numbers increasing exponentially as the exposure to fentanyl increases. Urban centers and rural communities continue to feel the impact of the opioid crisis in our nation with these increases and community exposure to more lethal forms of synthetic opioids as well. The Rural Opioid Technical Assistance (ROTA) grants have been designed by the Substance (SAMHSA) to build upon the nation’s efforts to stem the tide of fatalities related to opioid misuse and overdosing. Purpose: Under the ROTA grant, administered by Florida Agricultural and Mechanical University (FAMU) Extension and Florida State University (FSU) between 2020-2022, ten age-friendly rural counties were identified to implement programming that assists with opioid use disorder (OUD) and provide high-quality training for the targeted communities [1]. Technical assistance trainings were conducted in these areas with county leaders, clergy, schools, and other child serving agencies. The trainings and workshops were designed to meet the needs of the participating residents and to encourage county leaders to advocate for more services and resources to help reduce the harm of opioid overdose fatalities. This review is designed to provide an overview of the parameters and dynamics of age-friendly rural communities and to summarize the resource, service, and harm reduction information shared in the ROTA trainings. Key words: Opioid use disorder (OUD); Rural Opioid Technical Assistance (ROTA) Grant
Monitoring and Multi-Messenger Astronomy with IceCube

IceCube currently is the largest neutrino observatory with an instrumented detection volume of 1 km3 buried in the ice-sheet close to the antarctic South Pole station. With a 4 π field of view and an up-time of >99%, it is continuously monitoring the full sky to detect astrophysical neutrinos. With the detection of an astrophysical neutrino flux in 2013, IceCube opened a new observation window to the non-thermal Universe. The IceCube collaboration has a large program to search for astrophysical neutrinos, including measurements of the energy spectrum of the diffuse astrophysical flux, auto- and cross-correlation studies with other multi-messenger particles, and a real-time alert and follow-up system. On 22 September 2017, the IceCube online system sent out an alert reporting a high-energy neutrino event. This alert triggered a series of multi-wavelength follow-up observations that revealed a spatially-coincident blazar TXS 0506+056, which was also in an active flaring state. This correlation was estimated at a 3 σ level. Further observations confirmed the flaring emission in the very-high-energy gamma-ray band. In addition, IceCube found an independent 3.5 σ excess of a time-variable neutrino flux in the direction of TXS 0506+056 two years prior to the alert by examining 9.5 years of archival neutrino data. These are the first multi-messenger observations of an extra-galactic astrophysical source including neutrinos since the observation of the supernova SN1987A. This review summarizes the different detection and analysis channels for astrophysical neutrinos in IceCube, focusing on the multi-messenger program of IceCube and its major scientific results.
Host immunity and HBV S gene mutation in HBsAg-negative HBV-infected patients

Background Clinically, some patients whose HBsAg becomes negative owing to antiviral therapy or spontaneously still show a low level of HBV DNA persistence in serum. T-lymphocyte subsets, cytokine levels and HBV S gene sequences were analyzed in this study. Methods A total of 52 HBsAg-negative and HBV DNA-positive patients(HBsAg-/HBV DNA+ patients), 52 persistently HBsAg-positive patients(HBsAg+/HBV DNA+ patients) and 16 healthy people were evaluated. T-lymphocyte subsets of these patients were detected by flow cytometry, serum cytokines and chemokines were detected by the Luminex technique, and the HBV S region was evaluated by Sanger sequencing. T%, T-lymphocyte, CD8+ and CD4+T lymphocyte were lower in the HBsAg-negative group than in the HC group. Compared with the HBsAg-positive group, the HBsAg-negative group had lower levels in T lymphocyte %, CD8+T lymphocyte %, CD8+T lymphocyte and CD4/CD8. These difference were statistically significant (P<0.05). Serum IFN-γ, IFN-α and FLT-3L levels were significantly higher in the HBsAg-negative group than in the HBsAg-positive group (P<0.05). However, levels of many cytokines related to inflammation (i.e., IL-6, IL-8, IL10, IL-12, IL-17A) were lower in the HBsAg-negative group. Fifty-two HBsAg-negative samples were sequenced, revealing high-frequency amino acid substitution sites in the HBV S protein, including immune escape mutations (i.e., Y100C, S114T, C124Y, P127L, G130R, T131N, M133T, C137S, G145A) and TMD region substitutions (i.e., E2K/R/D, G7D/R, G10D, A17R, F20L/S, L21V, L22V). Conclusions According to the results of T-lymphocyte subsets and serum cytokines, it can be deduced that the cellular immune function of HBsAg-negative patients is superior to that of HBsAg-positive patients, with attenuation of liver inflammation. HBsAg-negative patients may show a variety of mutations and amino acid replacement sites at high frequency in the HBV S region, and these mutations may lead to undetectable HBsAg, HBsAg antigenic changes or secretion inhibition.
The Integral Role of Chloride & With-No-Lysine Kinases in Cell Volume Regulation & Hypertension

Abstract Chloride anions are the most abundant in humans. For many years, it has been believed that chloride is simply a counterion of all other cations, ensuring the electroneutrality of the extracellular space. Recent data suggests that chloride anions possess a broad spectrum of important activities that regulate vital cellular functions. It is now evident that, apart from its contribution to the electroneutrality of the extracellular space, it acts as an osmole and contributes to extracellular and intracellular volume regulation. Its anionic charge also contributes to the generation of cell membrane potential. The most interesting action of chloride anions is their ability to regulate the activity of with-no-lysine kinases, which in turn regulate the activity of sodium chloride and potassium chloride cotransporters and govern the reabsorption of salt and excretion of potassium by nephron epithelia. Chloride anions seem to play a crucial role in cell functions, such as cell volume regulation, sodium reabsorption in the distal nephron, potassium balance, and sodium sensitivity, which lead to hypertension. All of these functions are accomplished on a molecular level via complicated metabolic pathways, many of which remain poorly defined. We attempted to elucidate some of these pathways in light of recent advances in our knowledge, obtained mainly from experimental studies.
Cetacean-watching in developing countries: a case study from the Mekong River

[Extract] Cetacean-watch tourism in developing countries remains poorly documented, and often poorly managed as a result of limited in-country capacity, ineffective governance, conflicting policy goals, and limited accountability. The dolphin-watch tourism that targets the population of Irrawaddy dolphins, Orcaella brevirostris, in the Mekong River in Cambodia and Laos is used as a case study to illustrate growing concerns associated with cetacean-watch tourism in developing countries. In the early 1990s, unregulated and unmanaged dolphin-watching tourism began in two of the most important habitats for this population, which now numbers less than 100 individuals. An Integrated Conservation Development Project, 'Dolphins for Development', was initiated in Kampi Village, Cambodia in 2004. This Project included an attempt to manage the existing dolphin-watch tourism through: (1) promoting the sharing of tourism revenue to the local community; (2) encouraging effective management of the industry to minimize threats to the dolphins; (3) promoting visitor satisfaction; and (4) raising community and visitor awareness of the status of the dolphins and the need for conservation. Although the initial results were encouraging, subsequent government intervention has resulted in: (1) a large increase in the number of boats operating in prime dolphin habitat and an increase in the harassment of dolphins; (2) reduction in the benefit to local communities; and (3) little or no information being provided to national or international tourists. Although management agencies are implementing significant conservation measures to reduce the threat to the dolphins from gillnet fishing by subsistence fishers, few efforts are being directed towards management of the dolphin-watch tourism industry. The urgent need to develop dolphin-watching tourism management initiatives in Cambodia was highlighted at the 2010 International Whaling Commission meeting, where a 'no vessel-based' dolphin tourism policy was recommended. A precautionary approach to management is needed to address the problem of unsustainable cetacean-watching currently occurring in numerous developing countries. This approach should be informed by location-specific and comprehensive studies on both the ecology of the dolphin-tourism interactions and the social, economic, managerial and political influences on cetacean-watch operations.
Markov chain Monte Carlo approach to the analysis of response patterns in data collection process

Abstract Survey research, such as telephone, mail, or online questionnaires, is one of the most widely used tools for collecting sample data. We are often interested in the total number of replies that would be received during a given time period. Many researchers have developed a wide variety of curve-fitting methods to predict the response rate of recipients over time. However, previous models are based on some assumptions that are hardly justified in practice. In this paper, a new response model is proposed that is based on meaningful parameters such as the ultimate response rate of questionnaire recipients, delay rate of respondents, and average delivery time of responses. To estimate those model parameters, we use the Markov chain Monte Carlo (MCMC) method, which is increasingly popular in the operational research community. With mail survey data in marketing research, we test our Bayesian response model and compare its performance with those of traditional curve-fitting models.
Unlocking the secrets of wheat production: Evaluating phosphorus levels and seeding rates in alluvial soil conditions

A research study was conducted to determine the effect of different P levels and seeding rates on the growth, phenology, and yield of wheat. The experiment used a randomized complete block design with split plot arrangement and four replications. The main plots consisted of six seeding rates, ranging from 50 to 175 kg/ha, while the sub-plots received six different P levels, ranging from 50 to 200 kg/ha. In consecutive years, the study revealed significant effects of phosphorus levels, seeding rates, and their interaction on various growth characteristics and yield parameters of wheat. These included days to 50% heading and 50% maturity, leaf area index (LAI), leaf area duration (LAD), crop growth rate (CGR), net assimilation rate (NAR), and grain yield (GY). Phosphorus (P) level of 140 kg/ha resulted in the highest CGR, NAR, and GY in both years of the study. At a seeding density of 125 kg/ha, similar findings were observed, with the maximum CGR, NAR, and GY recorded. The highest interaction values for CGR, NAR, and GY were achieved with the combination of 140 kg P/ha and a seeding rate of 125 kg/ha. By utilizing a seed rate of 175 kg/ha and a P level of 200 kg/ha, the study revealed the highest values for LAI and LAD. Additionally, the maximum protein content was observed in treatments where seeds and P were applied at 50 and 200 kg/ha, respectively. In summary, the study provided conclusive evidence that the application of suitable seeding rates and P levels can yield significant improvements in the growth, phenology, and yield of wheat. The findings could be beneficial for farmers and researchers in improving wheat production.
Characterization of SiO2 Plasma Etching with Perfluorocarbon (C4F8 and C6F6) and Hydrofluorocarbon (CHF3 and C4H2F6) Precursors for the Greenhouse Gas Emissions Reduction

This paper proposes the use of environmentally friendly alternatives, C6F6 and C4H2F6, as perfluorocarbon (PFC) and hydrofluorocarbon (HFC) precursors, respectively, for SiO2 plasma etching, instead of conventional precursors C4F8 and CHF3. The study employs scanning electron microscopy for etch profile analysis and quadrupole mass spectrometry for plasma diagnosis. Ion bombardment energy at the etching conditions is determined through self-bias voltage measurements, while densities of radical species are obtained using quadrupole mass spectroscopy. The obtained results compare the etch performance, including etch rate and selectivity, between C4F8 and C6F6, as well as between CHF3 and C4H2F6. Furthermore, greenhouse gas (GHG) emissions are evaluated using a million metric ton of carbon dioxide equivalent, indicating significantly lower emissions when replacing conventional precursors with the proposed alternatives. The results suggest that a significant GHG emissions reduction can be achieved from the investigated alternatives without a deterioration in SiO2 etching characteristics. This research contributes to the development of alternative precursors for reducing global warming impacts.
Mitigation of Salt Stress in Reaumuria soongarica Seedlings by Exogenous Ca2+ and NO Compound Treatment

Soil salinization is a common abiotic stress that severely limits the growth of Reaumuria soongarica and reduces its application value. To better understand the response of R. soongarica to salt stress and the physiological mechanisms of exogenous Ca2+ and NO compound treatment in alleviating salt stress, the growth parameters, antioxidant system, carbohydrate metabolism and nitrogen compound metabolism were compared on Days 0, 1, 3, 6, 9, 15 and 30. The results showed that salt stress could significantly reduce the plant height, root length, fresh and dry weights of aboveground and underground parts, as well as the relative water content, severely inhibiting the growth of R. soongarica seedlings. After Ca2+ and NO compound treatment, these growth parameters were significantly improved, and the harm caused by stress in R. soongarica was alleviated. Regarding the antioxidant system, the Ca2+ and NO compound treatment could significantly increase the activities of SOD, CAT, APX and GR, as well as the contents of ASA and GSH, which indicated that exogenous Ca2+ and NO could eliminate the accumulated active oxygen by increasing the activities of oxidoreductases and the content of nonenzymatic antioxidant substances, thereby improving the salt tolerance of R. soongarica. Regarding carbon metabolism, after Ca2+ and NO compound treatment, the soluble sugar and sucrose contents, as well as the activities of sucrose phosphate synthase and sucrose synthase, were significantly increased, which indicated that Ca2+ and NO compound treatment could maintain higher soluble sugar and sucrose contents in R. soongarica and reduce osmotic stress caused by salt treatment. Regarding nitrogen metabolism, the Ca2+ and NO compound treatment reduced the harm of salt stress by regulating the nitrogen compound contents and nitrogen compound-related enzyme activities, including increases in the NO3− content and NR, NiR, GS, GOGAT and GDH activities and a reduction in the NO2− content. The results of this study indicate that the inhibition of the growth and development of R. soongarica by salt stress can be alleviated by regulating the antioxidant system, carbohydrate metabolism and nitrogen compound metabolism, which provides a theoretical basis for Ca2+ and NO compound treatment to improve plant salt tolerance.
Anomalous Sound Detection Using Self-Attention-Based Frequency Pattern Analysis of Machine Sounds

Different machines can exhibit diverse frequency patterns in their emitted sound. This feature has been recently explored in anomaly sound detection and reached state-of-the-art performance. However, existing methods rely on the manual or empirical determination of the frequency filter by observing the effective frequency range in the training data, which may be impractical for general application. This paper proposes an anomalous sound detection method using self-attention-based frequency pattern analysis and spectral-temporal information fusion. Our experiments demonstrate that the self-attention module automatically and adaptively analyses the effective frequencies of a machine sound and enhances that information in the spectral feature representation. With spectral-temporal information fusion, the obtained audio feature eventually improves the anomaly detection performance on the DCASE 2020 Challenge Task 2 dataset.
Filling the population statistics gap: Swiss German reference data on F0 and speech tempo for forensic contexts

The increased focus on big data in phonetics, and Bayesian statistics in the forensic sciences, prompt a fundamental issue in common applications of forensic phonetics. Relevant population distributions for most features, a key element when evaluating the similarity and distinctiveness of voices, remain lacking for a substantial number of languages and dialects. This paper provides population statistics for two phonetic features in the Swiss German context, speech tempo and F0, and outlines a potential method for big data analysis. The speech data is taken from 1000 SwG speakers and include two different style conditions: spontaneous and read speech. Results indicate significant variation for both parameters: we contradict previous findings on gender differences in speech tempo and note discrepancies for both features between the two styles. These findings constitute an important contribution to the field of forensic phonetics, as well as the field of general phonetics more broadly.