Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Speech Recognition Using GAN-Based Speech Synthesis and Contrastive Unspoken Text Selection

Text-to-Speech synthesis (TTS) based data augmentation is a relatively new mechanism for utilizing text-only data to improve automatic speech recognition (ASR) training without parameter or inference architecture changes. However, efforts to train speech recognition systems on synthesized utterances suffer from limited acoustic diversity of TTS outputs. Additionally, the text-only corpus is always much larger than the transcribed speech corpus by several orders of magnitude, which makes speech synthesis of all the text data impractical. In this work, we propose to combine generative adversarial network (GAN) and multi-style training (MTR) to increase acoustic diversity in the synthesized data. We also present a contrastive language model-based data selection technique to improve the efﬁciency of learning from unspoken text. We demonstrate that our proposed method allows ASR models to learn from synthesis of large-scale unspoken text sources and achieves a 35% relative WER reduction on a voice-search task.
Minimally invasive esthetic management of dental fluorosis: a case report

Dental fluorosis is a dental condition caused by excessive intake of fluoride during enamel formation, which can lead to color abnormalities or defects on the tooth surface. The resultant abnormal appearance ranges in severity from mildly white and opaque to dark brown, which substantially affects patients’ esthetic characteristics and self-confidence. Treatment methods include tooth whitening or restoration. This clinical report describes the use of a minimally invasive esthetic technique in a 22-year-old woman with moderate dental fluorosis. The treatment plan included enamel microabrasion, at-home bleaching for 2 weeks, and subsequent resin infiltration for each tooth under a rubber dam. After 2 years of follow-up, evaluation of the patient’s esthetic appearance revealed that teeth affected by dental fluorosis could be successfully treated with a minimally invasive technique involving microabrasion, at-home bleaching, and resin infiltration.
Prevalence of Physical Frailty and Its Multidimensional Risk Factors in Korean Community-Dwelling Older Adults: Findings from Korean Frailty and Aging Cohort Study

Frailty is defined as a state of increased vulnerability to stressors, and it predicts disability and mortality in the older population. This study aimed to investigate the standardized prevalence and multidimensional risk factors associated with frailty among Korean community-dwelling older adults. We analyzed the baseline data of 2907 adults aged 70–84 years (mean age 75.8 ± 3.9 years, 57.8% women) in the Korean Frailty and Aging Cohort Study. The Fried frailty phenotype was used to define frailty. Analyzed data included sociodemographic, physical, physical function, biological, lifestyle, health condition, medical condition, psychological, and social domains. Data were standardized using the national standard population composition ratio based on the Korean Population and Housing Census. The standardized prevalence of frailty and prefrailty was 7.9% (95% confidence interval (CI) 6.8–8.9%) and 47.0% (95% CI, 45.1–48.8%), respectively. The following 14 risk factors were significantly associated with frailty: at risk of malnutrition, sarcopenia, severe mobility limitation, poor social capital, rural dwellers, depressive symptoms, poor self-perceived health, polypharmacy, elevated high-sensitivity C-reactive protein, elevated glycosylated hemoglobin, low 25-hydroxy vitamin D level, longer Timed Up and Go, and low Short Physical Performance Battery score (p < 0.05). Physiconutritional, psychological, sociodemographic, and medical factors are strongly associated with frailty.
Suitability of transbronchial brushing cytology specimens for next‐generation sequencing in peripheral lung cancer

Next‐generation sequencing (NGS) enables the diagnosis of large numbers of gene aberrations during one examination, and precision medicine has been developed for patients with advanced non–small cell lung cancer (NSCLC). However, peripheral lung lesions account for the majority of advanced lung cancers, especially lung adenocarcinoma. In these cases, it is difficult to obtain tissue samples which contain sufficient tumor cells by transbronchial biopsy (TBB) with forceps. Even when the target lesions are quite small, bronchial brushing can obtain enough tumor cells by endobronchial ultrasonography using guide sheath (EBUS‐GS). In this study, we investigate the suitability of bronchial brushing cytology specimens obtained by EBUS‐GS‐TBB to evaluate the correlation between the success rate of NGS and extracted DNA/RNA yields according to biopsy method. We prospectively collected 222 tumor samples obtained from patients with advanced lung cancer. All patients were enrolled in a prospective nationwide genomic screening project for lung cancer (LC‐SCRUM‐Japan/Asia). Genomic data were obtained from the clinico‐genomic database of LC‐SCRUM‐Japan/Asia. The extraction yields of DNA/RNA from samples obtained by EBUS‐GS‐TBB were relatively low compared with tissue samples. The success rate of DNA sequencing for EBUS‐GS‐TBB was 97.9%, with no significant differences between biopsy methods. The success rate of RNA sequencing for EBUS‐GS‐TBB was 80.4%, which was relatively low compared with surgical biopsy samples (P = 0.069). However, some rare oncogenic driver aberrations were detected from these specimens. This study demonstrated that cytology samples obtained by transbronchial brushing with EBUS‐GS‐TBB were suitable for NGS analysis.
Fast Response to Superspreading: Uncertainty and Complexity in the Context of COVID-19

Although the first coronavirus disease 2019 (COVID-19) wave has peaked with the second wave underway, the world is still struggling to manage potential systemic risks and unpredictability of the pandemic. A particular challenge is the “superspreading” of the virus, which starts abruptly, is difficult to predict, and can quickly escalate into medical and socio-economic emergencies that contribute to long-lasting crises challenging our current ways of life. In these uncertain times, organizations and societies worldwide are faced with the need to develop appropriate strategies and intervention portfolios that require fast understanding of the complex interdependencies in our world and rapid, flexible action to contain the spread of the virus as quickly as possible, thus preventing further disastrous consequences of the pandemic. We integrate perspectives from systems sciences, epidemiology, biology, social networks, and organizational research in the context of the superspreading phenomenon to understand the complex system of COVID-19 pandemic and develop suggestions for interventions aimed at rapid responses.
Rescore in a Flash: Compact, Cache Efficient Hashing Data Structures for n-Gram Language Models

We introduce DashHashLM, an efﬁcient data structure that stores an n -gram language model compactly while making minimal trade-offs on runtime lookup latency. The data structure implements a ﬁnite state transducer with a lossless structural compression and outperforms comparable implementations when considering lookup speed in the small-footprint setting. DashHashLM introduces several optimizations to language model compression which are designed to minimize expected memory accesses. We also present variations of Dash-HashLM appropriate for scenarios with different memory and latency constraints. We detail the algorithm and justify our de-sign choices with comparative experiments on a speech recognition task. Speciﬁcally, we show that with roughly a 10% increase in memory size, compared to a highly optimized, compressed baseline n -gram representation, our proposed data structure can achieve up to a 6x query speedup.
Development of Multilingual ASR Using GlobalPhone for Less-Resourced Languages: The Case of Ethiopian Languages

In this paper, we present the cross-lingual and multilingual experiments we have conducted using existing resources of other languages for the development of speech recognition system for less-resourced languages. In our experiments, we used the Globalphone corpus as source and considered four Ethiopian languages namely Amharic, Oromo, Tigrigna and Wolaytta as targets. We have developed multilingual (ML) Automatic Speech Recognition (ASR) systems and decoded speech of the four Ethiopian languages. A multilingual acoustic model (AM) trained with speech data of 22 Globalphone languages but the target languages, achieved a Word Error Rate (WER) of 15.79%. Moreover, including training speech of one closely related language (in terms of phonetic overlap) in ML AM training resulted in a relative WER reduction of 51.41%. Although adaptation of ML systems did not give signiﬁcant WER reduction over the monolingual ones, it enables us to rapidly adapt existing ML ASR systems to new languages. In sum, our experiments demonstrated that ASR systems can be developed rapidly with a pronunciation dictionary (PD) of low out of vocabulary (OOV) rate and a strong language model (LM).
Learning Better Speech Representations by Worsening Interference

Can better representations be learnt from worse interfering scenarios? To verify this seeming paradox, we propose a novel framework that performed compositional learning in traditionally independent tasks of speech separation and speaker iden-tiﬁcation. In this framework, generic pre-training and compositional ﬁne-tuning are proposed to mimic the bottom-up and top-down processes of a human’s cocktail party effect. More-over, we investigate schemes to prohibit the model from ending up learning an easier identity-prediction task. Substantially discriminative and generalizable representations can be learnt in severely interfering conditions. Experiment results on down-stream tasks show that our learnt representations have superior discriminative power than a standard speaker veriﬁcation method. Meanwhile, RISE achieves higher SI-SNRi consistently in different inference modes over DPRNN, a state-of-the-art speech separation system.
Single inhaler triple therapy (FF/UMEC/VI) versus FF/VI and UMEC/VI in patients with COPD: subgroup analysis of the China cohort in the IMPACT trial

Abstract Objectives Chronic obstructive pulmonary disease (COPD) is becoming a leading cause of morbidity and mortality in China. In the IMPACT trial, fluticasone furoate[FF]/umeclidinium[UMEC]/vilanterol[VI] single-inhaler triple therapy demonstrated lower rates of moderate/severe exacerbations than dual therapy with FF/VI or UMEC/VI in patients with symptomatic COPD and a history of exacerbations. This analysis investigates the China cohort and its consistency with the overall ITT population. Methods 10,355 patients were randomized 2:2:1 to once-daily FF/UMEC/VI 100/62.5/25 µg, FF/VI 100/25 µg, or UMEC/VI 62.5/25 µg for 52 weeks. Endpoints included: annual rates of exacerbations, time-to-first on-treatment moderate/severe exacerbation and change from baseline in trough forced expiratory volume in 1 s (FEV1) at Week-52. Clinical trial registration is NCT02164513 (CTT116855). Results 535 patients (5.2%) were from China. Annual on-treatment moderate/severe exacerbation rate was 0.81 with FF/UMEC/VI versus 0.96 with FF/VI (rate ratio: 0.84; 95% confidence interval [CI]: 0.64, 1.11; p = .227) and 0.80 with UMEC/VI (rate ratio: 1.02; 95% CI: 0.72, 1.44; p = .929). Hazard ratio for time-to-first moderate/severe exacerbation was 0.84 (95% CI: 0.63, 1.11; p = .218) for FF/UMEC/VI versus FF/VI and 0.89 (95% CI: 0.62, 1.27; p = .516) versus UMEC/VI. Significant improvements in mean change from baseline in trough FEV1 were observed for FF/UMEC/VI versus FF/VI (treatment difference 137 mL; 95% CI: 86, 188; p < .001) and UMEC/VI (63 mL; 0, 125; p = .050). Health status was improved with FF/UMEC/VI versus both dual therapies. Results were similar to the overall ITT population. No new safety signals were identified. Conclusions Single-inhaler triple therapy with FF/UMEC/VI versus FF/VI or UMEC/VI reduced the rate and risk of exacerbations, and improved lung function and health status in the China cohort similar to the overall ITT population. No new safety signals were identified.
Mapping Progressive Gray Matter Alterations in Early Childhood Autistic Brain.

Autism spectrum disorder is an early-onset neurodevelopmental condition. This study aimed to investigate the progressive structural alterations in the autistic brain during early childhood. Structural magnetic resonance imaging scans were examined in a cross-sectional sample of 67 autistic children and 63 demographically matched typically developing (TD) children, aged 2-7 years. Voxel-based morphometry and a general linear model were used to ascertain the effects of diagnosis, age, and a diagnosis-by-age interaction on the gray matter volume. Causal structural covariance network analysis was performed to map the interregional influences of brain structural alterations with increasing age. The autism group showed spatially distributed increases in gray matter volume when controlling for age-related effects, compared with TD children. A significant diagnosis-by-age interaction effect was observed in the fusiform face area (FFA, Fpeak = 13.57) and cerebellum/vermis (Fpeak = 12.73). Compared with TD children, the gray matter development of the FFA in autism displayed altered influences on that of the social brain network regions (false discovery rate corrected, P < 0.05). Our findings indicate the atypical neurodevelopment of the FFA in the autistic brain during early childhood and highlight altered developmental effects of this region on the social brain network.
Terminalia catappa fruit extract reverses streptozotocin- induced diabetic retinopathy in rats.

OBJECTIVE AND BACKGROUND Diabetic retinopathy is amongst the most common microvascular complication associated with diabetes. Controlling blood glucose level alone cannot manage diabetes associated complications. Thus, mechanism that additionally prevent diabetes associated complication are need of the hour, driving the researchers towards herbal therapies. Terminalia catappa is renowned for its anti-inflammatory, antioxidant, anti-hyperglycemic and anti-angiogenic activity. The current study explores the effect of Terminalia catappa fruit extract in streptozotocin-induced diabetic retinopathy in rats. METHODS Streptozotocin-induced chronic diabetic rat model was utilized in the study. Hydro-alcoholic fruit extract of T. catappa in 20mg/kg, 30mg/kg and 40mg/kg dose and standard anti-diabetic drug, glibenclamide (10mg/kg) was given orally. Retinopathy was evaluated by monitoring lenticular, fundus images and measuring arteriole and venule tortuosity index. Oxidative, angiogenic and inflammatory biomarkers were assessed at 12th week in retinal homogenate. Histopathological changes in retina were also examined. Data was analyzed using one-way Repeated Measure ANOVA followed by MannWhitney test. RESULTS Hydro-alcoholic fruit extract of T. catappa significantly decreased blood glucose (p<0.001) in dose-dependent manner in diabetic rats. Cataract lens was observed in all experimental groups and became clear (grade 0) with 40mg/kg and with 40mg/kg along with glibenclamide at eight and sixth week respectively. Hydro-alcoholic fruit extract in all three doses significantly reduced (p<0.01) arteriole and venule tortuosity in diabetic rats. T. catappa in all three doses in diabetic rats showed modulatory effect in oxidative, angiogenic and inflammatory biomarkers. CONCLUSION T. catappa reverses diabetes-induced retinopathy by anti-hyperglycemic, anti-oxidant, anti-angiogenic and anti-inflammatory actions, and thus has a potential to be used in diabetes-induced retinopathy.
Effects of Non-invasive Neurostimulation on Autism Spectrum Disorder: A Systematic Review

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by major impairments in social communication, stereotyped and ritualistic behaviors and deficits in sensory reactivity. Recently, noninvasive brain stimulation (NIBS) methods, namely transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), have been examined as possible new therapeutic options for modifying the pathological neuroplasticity involved in neuropsychiatric disorders including ASD. Therefore, we conducted a systematic review on the therapeutic uses of tDCS and repetitive TMS (rTMS) in ASD patients. A systematic search was performed on Scopus, Web of Science, PubMed, Cochrane and Embase. Original articles reporting the use of tDCS or rTMS to treat ASD were screened and studied by two researchers independently based on PRISMA guidelines. We found 32 eligible studies including 8 tDCS reports, 23 rTMS reports and one report with both tDCS and rTMS. These studies comprised 6 case-reports, 9 non-controlled trials and 17 controlled trials which assessed NIBS effects on the three cognitive, behavioral and biological dimensions in ASD. Existing evidence demonstrates that NIBS methods could be helpful for treating some dimensions of ASD such as repetitive behavior, sociability or some aspects of executive and cognitive functions. However, such evidence should be regarded with care because of the quality of original researches and serious publication bias as well as the heterogeneity of data. Further randomized, double-blind, sham-controlled trials with appropriate follow-up periods should be designed to assess the efficacy of NIBS methods for ASD treatment.
Principal Style Components: Expressive Style Control and Cross-Speaker Transfer in Neural TTS

We propose a novel semi-supervised technique that enables expressive style control and cross-speaker transfer in neural text to speech (TTS), when available training data contains a limited amount of labeled expressive speech from a single speaker. The technique is based on unsupervised learning of a style-related latent space, generated by a previously proposed reference audio encoding technique, and transforming it by means of Principal Component Analysis to another low-dimensional space. The latter space represents style information in a purified form, disentangled from text and speaker-related information. Encodings for expressive styles that are present in the training data are easily constructed in this space. Furthermore, this technique provides control over the speech rate, pitch level, and articulation type that can be used for TTS voice transformation. We present the results of subjective crowd evaluations confirming that the synthesized speech convincingly conveys the desired expressive styles and preserves a high level of quality.
CATOTRON - A Neural Text-to-Speech System in Catalan

We present Catotron, a neural network-based open-source speech synthesis system in Catalan. Catotron consists of a sequence-to-sequence model trained with two small open-source datasets based on semi-spontaneous and read speech. We demonstrate how a neural TTS can be built for languages with limited resources using found-data optimization and cross-lingual transfer learning. We make the datasets, initial models and source code publicly available for both commercial and research purposes.
Rifabutin-Loaded Nanostructured Lipid Carriers as a Tool in Oral Anti-Mycobacterial Treatment of Crohn’s Disease

Oral anti-mycobacterial treatment of Crohn’s disease (CD) is limited by the low aqueous solubility of drugs, along with the altered gut conditions of patients, making uncommon their clinical use. Hence, the aim of the present work is focused on the in vitro evaluation of rifabutin (RFB)-loaded Nanostructured lipid carriers (NLC), in order to solve limitations associated to this therapeutic approach. RFB-loaded NLC were prepared by hot homogenization and characterized in terms of size, polydispersity, surface charge, morphology, thermal stability, and drug payload and release. Permeability across Caco-2 cell monolayers and cytotoxicity and uptake in human macrophages was also determined. NLC obtained were nano-sized, monodisperse, negatively charged, and spheroidal-shaped, showing a suitable drug payload and thermal stability. Furthermore, the permeability profile, macrophage uptake and selective intracellular release of RFB-loaded NLC, guarantee an effective drug dose administration to cells. Outcomes suggest that rifabutin-loaded NLC constitute a promising strategy to improve oral anti-mycobacterial therapy in Crohn’s disease.
Detrimental effects of clothianidin on foraging and dance communication in honey bees

Ongoing losses of pollinators are of significant international concern because of the essential role they have in our ecosystem, agriculture, and economy. Both chemical and non-chemical stressors have been implicated as possible contributors to their decline, but the increasing use of neonicotinoid insecticides has recently emerged as particularly concerning. In this study, honey bees were exposed orally to sublethal doses of the neonicotinoid clothianidin in the field in order to assess its effects on the foraging behavior, homing success, and dance communication. The foraging span and foraging activity at the contaminated feeder decreased significantly due to chronic exposure at field-realistic concentrations. Electrostatic field of dancing bees was measured and it was revealed that the number of waggle runs, the fanning time and the number of stop signals were significantly lower in the exposed colony. No difference was found in the homing success and the flight duration between control and treated bees released at a novel location within the explored area. However, a negative effect of the ambient temperature, and an influence of the location of the trained feeder was found. Finally, the residues of clothianidin accumulated in the abdomens of exposed foraging bees over time. These results show the adverse effects of a chronic exposure to sublethal doses of clothianidin on foraging and dance communication in honey bees.
Copper Ionophores as Novel Antiobesity Therapeutics

The therapeutic utility of the copper ionophore disulfiram was investigated in a diet-induced obesity mouse model (C57BL/6J background), both through administration in feed (0.05 to 1% (w/w)) and via oral gavage (150 mg/kg) for up to eight weeks. Mice were monitored for body weight, fat deposition (perigonadal fat pads), metabolic changes (e.g., glucose dyshomeostasis) and pathologies (e.g., hepatic steatosis, hyperglycaemia and hypertriglyceridemia) associated with a high-fat diet. Metal-related pharmacological effects across major organs and serums were investigated using inductively coupled plasma mass spectrometry (ICP-MS). Disulfiram treatments (all modes) augmented hepatic copper in mice, markedly moderated body weight and abolished the deleterious systemic changes associated with a high-fat diet. Likewise, another chemically distinct copper ionophore H2(gtsm), administered daily (oral gavage), also augmented hepatic copper and moderated mouse body weight. Postmortem histological examinations of the liver and other major organs, together with serum aminotransferases, supported the reported therapeutic safety of disulfiram. Disulfiram specifically altered systemic copper in mice and altered hepatic copper metabolism, perturbing the incorporation of copper into ceruloplasmin (holo-ceruloplasmin biosynthesis) and subsequently reducing serum copper concentrations. Serum ceruloplasmin represents a biomarker for disulfiram activity. Our results establish copper ionophores as a potential class of antiobesity agents.