Miracle-dz/UniFAR-FTUs huggingface dataset:
Task-Oriented Dialog Generation with Enhanced Entity Representation

Recent advances in neural sequence-to-sequence models have led to promising results for end-to-end task-oriented dialog generation. Such frameworks enable a decoder to retrieve knowledge from the dialog history and the knowledge base during generation. However, these models usually rely on learned word embeddings as entity representation, which is difﬁcult to deal with the rare and unknown entities. In this work, we propose a novel enhanced entity representation (EER) to simultaneously obtain context-sensitive and structure-aware entity representation. Our proposed method enables the decoder to facilitate both the ability to fetch the relevant knowledge and the effectiveness of incorporating grounding knowledge into the dialog generation. Experimental results on two publicly available dialog datasets show that our model outperforms the state-of-the-art data-driven task-oriented dialog models. Moreover, we conduct an Out-of-Vocabulary (OOV) test to demonstrate the superiority of EER in handling common OOV problem.
The effectiveness and value of novel acute treatments for migraine

DISCLOSURES: Funding for this summary was contributed by Arnold Ventures, California Health Care Foundation, Harvard Pilgrim Health Care, and Kaiser Foundation Health Plan to the Institute for Clinical and Economic Review (ICER), an independent organization that evaluates the evidence on the value of health care interventions. ICER's annual policy summit is supported by dues from Aetna, America's Health Insurance Plans, Anthem, Allergan, Alnylam, AstraZeneca, Biogen, Blue Shield of CA, Boehringer-Ingelheim, Cambia Health Services, CVS, Editas, Express Scripts, Genentech/Roche, GlaxoSmithKline, Harvard Pilgrim, Health Care Service Corporation, HealthFirst, Health Partners, Johnson & Johnson (Janssen), Kaiser Permanente, LEO Pharma, Mallinckrodt, Merck, Novartis, National Pharmaceutical Council, Pfizer, Premera, Prime Therapeutics, Regeneron, Sanofi, Spark Therapeutics, and United Healthcare. Agboola, Borrelli, Rind, and Pearson are employed by ICER. Touchette, through the University of Illinois at Chicago, received funding from ICER for development of the economic model described in this publication. Atlas has nothing to disclose.
Integrating the Application and Realization of Mandarin 3rd Tone Sandhi in the Resolution of Sentence Ambiguity

Chinese third tone sandhi (T3S) covaries with the prosodic hierarchy both in the probability of application and in the realization of pitch slope. This paper evaluates whether Mandarinspeaking listeners integrate the covariation between T3S and prosody to resolute sentence ambiguity. Twenty-seven structurally ambiguous sentences were designed, each containing two consecutive T3 syllables situated across a word boundary, and the strength of the T3-intervening boundary crucially differentiates different interpretations of the sentence. The first T3 was manipulated to bear either a low, a shallow-rising, or a sharp-rising pitch. Sixty native Mandarin-speaking listeners heard each of these sentences and chose from two written interpretations the one that was consistent with what they heard. The results show that listeners are more likely to report a majorjuncture interpretation when T3S does not apply (low) than when it applies (rising), and in the latter case, when the T3S variant has a sharper rather than shallower slope. Post-hoc analyses show that the T3S application is a more robust parsing cue for short sentences (4-5 syllables long), whereas the pitch shape of T3S is a more efficient parsing cue for longer sentences, indicating that listeners make sophisticated use of tonal variation to facilitate sentence processing.
‘The Mould that Changed the World’: Quantitative and qualitative evaluation of children’s knowledge and motivation for behavioural change following participation in an antimicrobial resistance musical

Background A primary school musical (“The Mould that Changed the World”) was developed as a unique public engagement strategy to combat antimicrobial resistance (AMR) by engaging children in the story of the discovery of antibiotics, the risks of drug-resistant infections and the importance of prudent antibiotic use. Methods The musical intervention was implemented in two UK primary schools by music specialists through a series of workshops, associated learning resources and performances to relatives. Participating children (n = 182), aged 9 to 11 years, were given an online questionnaire in the classroom before rehearsals began and at two weeks post-performance with a six-month evaluation in one school. The impact of the musical was analysed using generalised linear models to control for confounding factors. For the qualitative evaluation, fifteen participating children were selected randomly from each school to take part in semi-structured focus groups (n = 5 per group) before rehearsals began and two weeks post-performance. Findings Knowledge gain was demonstrated with children being more likely to answer questions on key messages of the musical correctly at two weeks post- performance (response rate 88%, n = 161) compared with the pre-rehearsal questionnaire (response rate 99%, n = 180) (bacteria can become resistant to antibiotics OR 4.63, C.I. 2.46–9.31 p<0.0001, antibiotic resistant infections can be life threatening OR 3.26 C.I. 1.75–6.32 p = 0.0001, prudent use of antibiotics will slow the rise of antibiotic resistant infections OR 2.16, C.I. 1.39–3.38, p = 0.0006). Long term knowledge gain was demonstrated by a consistent level of correct answers on key messages between two weeks (response rate 95%, n = 89) and 6 months post musical (response rate 71%, n = 67). Following the musical children participating in the focus groups (n = 30) articulated a greater understanding of AMR and the risks of antibiotic overuse. They discussed motivation to minimise personal antibiotic use and influence attitudes to antibiotics in their family and friends. Interpretation This study demonstrates that musical theatre can improve both short and long-term knowledge. It demonstrates a hitherto infrequently reported change in attitude and motivation to change behaviour in children at an influential age for health beliefs. This unique public health tool has the potential for high impact particularly if rolled out within national education programmes for primary school aged children.
Domain Adaptation for Enhancing Speech-Based Depression Detection in Natural Environmental Conditions Using Dilated CNNs

Depression disorders are a major growing concern worldwide, especially given the unmet need for widely deployable depression screening for use in real-world environments. Speech-based depression screening technologies have shown promising results, but primarily in systems that are trained using laboratory-based recorded speech. They do not generalize well on data from more naturalistic settings. This paper addresses the generalizability issue by proposing multiple adaptation strategies that update pre-trained models based on a dilated convolutional neural network (CNN) framework, which improve depression detection performance in both clean and naturalistic environments. Experimental results on two depression corpora show that feature representations in CNN layers need to be adapted to accommodate environmental changes, and that increases in data quantity and quality are helpful for pre-training models for adaptation. The cross-corpus adapted systems produce relative improvements of 29.4% and 17.2% in unweighted average recall over non-adapted systems for both clean and naturalistic corpora, respectively.
Multi-Scale TCN: Exploring Better Temporal DNN Model for Causal Speech Enhancement

Capturing the temporal dependence of speech signals is of great importance for numerous speech related tasks. This paper proposes a more effective temporal modeling method for causal speech enhancement system. We design a forward stacked temporal convolutional network (TCN) model which exploits multi-scale temporal analysis in each residual block. This model incorporates a multi-scale dilated convolution to better track the target speech through its context information from past frames. Applying multi-target learning of log power spectrum (LPS) and ideal ratio mask (IRM) further improves model robustness, due to the complementarity among the tasks. Experimental results show that the proposed TCN model not only performs better speech reconstruction ability in terms of speech quality and speech intelligibility, but also has smaller model size than that of long short-term memory (LSTM) network and the gated recurrent units (GRU) network.
A 43 Language Multilingual Punctuation Prediction Neural Network Model

Punctuation prediction is a critical component for speech recognition readability and speech translation segmentation. When considering multiple language support, traditional monolingual neural network models used for punctuation prediction can be costly to manage and may not produce the best accuracy. In this paper, we investigate multilingual Long Short-Term Memory (LSTM) modeling using Byte Pair Encoding (BPE) for punctuation prediction to support 43 languages 1 across 69 countries. Our ﬁndings show a single multilingual BPE-based model can achieve similar or even better performance than separate mono-lingual word-based models by beneﬁting from shared information across different languages. On an in-domain news text test set, the multilingual model achieves on average 80.2% F1 -score while on out-of-domain speech recognition text, it achieves 73.5% F1 -score. We also show that the shared information can help in ﬁne-tuning for low-resource languages as well.
Multimodal Association for Speaker Verification

In this paper, we propose a multimodal association on a speaker veriﬁcation system for ﬁne-tuning using both voice and face. Inspired by neuroscientiﬁc ﬁndings, the proposed approach is to mimic the unimodal perception system beneﬁts from the multisensory association of stimulus pairs. To verify this, we use the SRE18 evaluation protocol for experiments and use out-of-domain data, Voxceleb, for the proposed multimodal ﬁne-tuning. Although the proposed approach relies on voice-face paired multimodal data during the training phase, the face is no more needed after training is done and only speech audio is used for the speaker veriﬁcation system. In the experiments, we observed that the unimodal model, i.e. speaker veriﬁcation model, beneﬁts from the multimodal association of voice and face and generalized better than before by learning channel invariant speaker representation.
Effectiveness and Tolerability of Korean Red Ginseng Augmentation in Major Depressive Disorder Patients with Difficult-to-treat in Routine Practice

Objective To test clinical effectiveness and tolerability of Korean Red Ginseng augmentation (RGA) in major depressive disorder (MDD) patients with difficult-to-treat. Methods Thirty six patients were enrolled in this 6 weeks, prospective, clinical trial. Rating scales were Montgomery-Åsberg Depression Rating Scale (MADRS), Patient Health Questionnaire-15, Clinical Global Impression-improvement (CGI-I), and Patient Satisfaction Score. The primary endpoint was a remission rate measured by MADRS score at the end of study (≤ 10). Clinical outcomes and tolerability were assessed at baseline, week 2, and week 6. Results Among 36 patients, 26 patients completed the study and 28 patients had post-baseline visit data. The remission rate by MADRS score was 39.3% (11/28) and 57.1% by CGI-I scores of 1 or 2 at the end of the study. The mean change of MADRS score was significantly decreased by 44.4% from baseline to the end of study. The most frequent adverse events were headache (7/28, 25.0%) during the study. Conclusion Our study indicates the putative effectiveness and tolerability of RGA for treating MDD with difficult-to-treat in clinical practice. However, adequately powered, randomized, controlled trials will be needed to confirm these results.
Audio-Visual Multi-Speaker Tracking Based on the GLMB Framework

Multi-speaker tracking using both audio and video modalities is a key task in human-robot interaction and video conferencing. The complementary nature of audio and video signals improves the tracking robustness against noise and outliers compared to the uni-modal approaches. However, the online tracking of multiple speakers via audio-video fusion, especially without the target number prior, is still an open challenge. In this paper, we propose a Generalized Labelled Multi-Bernoulli (GLMB)- based framework that jointly estimates the number of targets and their respective states online. Experimental results using the AV16.3 dataset demonstrate the effectiveness of the proposed method.
Clustering and rapid long-range motility behavior of bacteria by type IV pili

Many organisms coordinate to move and colonize over surfaces. Bacteria such as Pseudomonas aeruginosa exhibit such surface motility as a precursor step to forming biofilms. Here we show a group surface motility where small groups of P. aeruginosa use their type IV pili (TFP) appendages over long-distances. Small cell clusters employ their TFP to move multiple cell lengths in fractions of a second and form new multicellular groups. Given the length scale and speed of displacement, cells appear to “snap” to a new position and then resume their previous behavior. The same long range TFP action also leads to rapid community contraction of sparsely arranged cell clusters. Cluster development and snapping motility does not require exogenous DNA or extracellular polysaccharides.
Fusion Architectures for Word-Based Audiovisual Speech Recognition

In this study we investigate architectures for modality fusion in audiovisual speech recognition, where one aims to alleviate the adverse effect of acoustic noise on the speech recognition accuracy by using video images of the speaker’s face as an additional modality. Starting from an established neural network fusion system, we substantially improve the recognition accuracy by taking single-modality losses into account: late fusion (at the output logits level) is substantially more robust than the base-line, in particular for unseen acoustic noise, at the expense of having to determine the optimal weighting of the input streams. The latter requirement can be removed by making the fusion itself a trainable part of the network.
Microneedles: Characteristics, Materials, Production Methods and Commercial Development

Although transdermal drug delivery systems (DDS) offer numerous benefits for patients, including the avoidance of both gastric irritation and first-pass metabolism effect, as well as improved patient compliance, only a limited number of active pharmaceutical ingredients (APIs) can be delivered accordingly. Microneedles (MNs) represent one of the most promising concepts for effective transdermal drug delivery that penetrate the protective skin barrier in a minimally invasive and painless manner. The first MNs were produced in the 90s, and since then, this field has been continually evolving. Therefore, different manufacturing methods, not only for MNs but also MN molds, are introduced, which allows for the cost-effective production of MNs for drug and vaccine delivery and even diagnostic/monitoring purposes. The focus of this review is to give a brief overview of MN characteristics, material composition, as well as the production and commercial development of MN-based systems.
Transient activation of tumoral DNA damage tolerance pathway coupled with immune checkpoint blockade exerts durable tumor regression in mouse melanoma

Major advances in cancer therapy rely on engagement of the patient’s immune system and suppression of mechanisms that impede the antitumor immune response. Among the most notable is immune checkpoint blockade (ICB) therapy that releases immune cells from suppression. Although ICB has had significant success particularly in melanoma, it eradicates tumors in subsets of patients and sequencing data across different cancers suggest that tumors with high mutational loads are more likely to respond to ICB. This is consistent with the premise that greater tumoral mutational loads contribute to formation of neoantigens that spur the body’s antitumor immune response. Prompted by strong evidence supporting the therapeutic benefits of neoantigens in the context of ICB, we have developed a mouse melanoma combination treatment, where intratumoral administration of DNA‐damaging drug transiently activates intrinsic mutagenic DNA damage tolerance pathway and improves success rates of ICB. Using the YUMM1.7 cells melanoma model, we demonstrate that intratumoral delivery of cisplatin activates translesion synthesis DNA polymerases‐catalyzed DNA synthesis on damaged DNA, which when coupled with ICB regimen, elicits durable tumor regression. We expect that this new combination protocol affords insights with clinical relevance that will help expand the range of patients who benefit from ICB therapy.
Er-Suffixation in Southwestern Mandarin: An EMA and Ultrasound Study

This paper is an articulatory study of the er-suffixation (a.k.a. erhua) in Southwestern Mandarin (SWM), using co-registered EMA and ultrasound. Data from two female speakers in their twenties were analyzed and discussed. Our recording materials contain unsuffixed stems, er-suffixed forms and the rhotic schwa /ɚ/, a phonemic vowel in its own right. Results suggest that the er-suffixation in SWM involves suffixing a rhotic schwa [ɚ] to the stem, unlike its counterpart in Beijing and Northeastern Mandarin [5]. Specifically, an entire rime will be replaced with the er-suffix if the nucleus vowel is non-high; only high vocoids will be preserved after the er-suffixation. The “rhoticity” is primarily realized as a bunched tongue shape configuration (i.e. a domed tongue body), while the Tongue Tip gesture plays a more limited role in SWM. A phonological analysis is accordingly proposed for the er-suffixation in SWM.
On Synthesis for Supervised Monaural Speech Separation in Time Domain

Time-domain approaches for speech separation have achieved great success recently. However, the sources separated by these time-domain approaches usually contain some artifacts (broad-band noises), especially when separating mixture with noise. In this paper, we incorporate synthesis way into the time-domain speech separation approaches to deal with above broadband noises in separated sources, which can be seamlessly used in the speech separation system by a ‘plug-and-play’ way. By directly learning an estimation for each source in encoded domain, synthesis way can reduce artifacts in estimated speeches and improve the speech separation performance. Extensive experiments on different state-of-the-art models reveal that the synthesis way acquires the ability to handle with noisy mixture and is more suitable for noisy speech separation. On a new benchmark noisy dataset, the synthesis way obtains 0.97 dB (10.1%) SDR relative improvement and respective gains on various metrics without extra computation cost.
Neutralization of Voicing Distinction of Stops in Tohoku Dialects of Japanese: Field Work and Acoustic Measurements

Research on Tohoku dialects, which is a variety of Japanese, has found that the voiceless stops /k/ and /t/ in the intervocalic position are frequently realized as voiced stops. However, the phenomenon has mainly been judged aurally in the Japanese linguistics literature and has not been confirmed by acoustic measurements. We measured the VOT of data originally collected in the survey of Tohoku dialects by [1]. The data used in this study includes two age groups from eight sites. The results demonstrate that for word medial stops, the VOT distribution of voiced and voiceless stops largely overlapped, while, the laryngeal contrast was maintained for the word initial stops. Intervocalic voicing neutralization was confirmed by quantitative acoustic measurements. The effects of neighboring vowels were also investigated to show that height, but not duration, had a significant effect on voicing neutralization. Our results shed light on the phonetic nature of Tohoku dialects as well as on their phonological structure, such as the role of voicing contrast.
Effects of Quality Improvement Education in Diabetic Retinopathy on Routine Clinical Practice Patterns of Optometrists

SIGNIFICANCE Optometrists play a preventive role in diabetic care by detecting early signs of diabetic retinopathy (DR), a leading cause of blindness in adults. This study demonstrates that additional training can improve optometrists' ability to assess the presence and severity of DR in individuals with diabetes. PURPOSE This study aimed to determine the impact of a quality improvement intervention involving education, assessment, and feedback on improving the evaluation and referral patterns of optometrists with regard to their patients with diabetes. METHODS A pre-interventional and post-interventional analysis of optometrist practices was conducted through a retrospective chart review of diabetic patient encounters from July 2018 to March 2019. Dilated fundus examination (DFE) documentation, follow-up scheduling, referral practices, and usage of various imaging modalities were collected from patient records. Concordance of DR severity recordings between DFE findings, assessment and plan notes, and International Classification of Diseases codes was calculated. RESULTS After intervention, the proportion of optometrists who conducted a DFE significantly increased from 79.5 (95% confidence interval [CI], 77.3 to 81.7%) to 84.4% (95% CI, 82.4 to 86.4%). In addition, the rate of improper follow-up instructions decreased from 13.8 (95% CI, 12.0 to 15.7%) to 10.8% (95% CI, 9.2 to 12.6%), and the decrease was significant (P = .02). Although overall referrals decreased from 19.8 (95% CI, 17.6 to 21.9%) to 14.6% (95% CI, 12.6 to 16.5%), optometrists were as likely to refer to retinal specialists. Finally, concordance between documented DFE findings, assessment and plan notes, and International Classification of Diseases codes significantly increased from 78.8 (95% CI, 76.5 to 81.0%) to 88.7% (95% CI, 86.9 to 90.4%). CONCLUSIONS Providing optometrists education in screening and assessing DR is effective in improving diabetic patient care.
Method feasibility for cross-species testing, qualification, and validation of the Filovirus Animal Nonclinical Group anti-Ebola virus glycoprotein immunoglobulin G enzyme-linked immunosorbent assay for non-human primate serum samples

An anti-Zaire Ebola virus (EBOV) glycoprotein (GP) immunoglobulin G (IgG) enzyme linked immunosorbent assay (ELISA) was developed to quantify the serum levels of anti-EBOV IgG in human and non-human primate (NHP) serum following vaccination and/or exposure to EBOV. This method was validated for testing human serum samples as previously reported. However, for direct immunobridging comparability between humans and NHPs, additional testing was warranted. First, method feasibility experiments were performed to assess cross-species reactivity and parallelism between human and NHP serum samples. During these preliminary assessments, the goat anti-human IgG secondary antibody conjugate used in the previous human validation was found to be favorably cross-reactive with NHP samples when tested at the same concentrations previously used in the validated assay for human sample testing. Further, NHP serum samples diluted in parallel with human serum when tested side-by-side in the ELISA. A subsequent NHP matrix qualification and partial validation in the anti-GP IgG ELISA were performed based on ICH and FDA guidance, to characterize assay performance for NHP test samples and supplement the previous validation for human sample testing. Based on our assessments, the anti-EBOV GP IgG ELISA method is considered suitable for the intended use of testing with both human and NHP serum samples in the same assay for immunobridging purposes.