Perceptual contribution of vowels to Mandarin sentence intelligibility under conditions of spectral degradation

A recent study showed a vowel advantage over consonant to sentence intelligibility in Mandarin. Considering the fact that many important acoustic cues for sentence intelligibility are contained in the vowel segment, the present study investigated the effect of spectral degradation and its interaction effect with vowel duration on Mandarin vowel-only sentence intelligibility. Three types of spectrally degraded stimuli, including fundamental frequency flattened (F0F), sine-wave synthesized (SWS)and noise-vocoded(NV)vowel-only sentences, were generated. Different proportions of vowel centers were preserved by using a noise-replacement paradigm. Listening experiments showed that fundamental frequency contour only had a minimal effect to vowel-only sentence intelligibility, while harmonic cues had a more notable effect. Intelligibility of NV sentences was significantly lower than that of SWS sentences, suggesting other acoustic cues such as formant frequency information contribute to the vowel advantage when harmonic cues are discarded. Discarding vowel edges had a significantly negative effect on vowel-only sentence intelligibility under conditions of spectral degradation. The present study supports emphasis on the preservation of harmonic cues and vowel duration in speech processing strategies.published_or_final_versionSpeech and Hearing SciencesBachelorBachelor of Science in Speech and Hearing Science

Autophagy in Multidrug-Resistant Cancers

Multidrug resistance (MDR) in cancers is the major challenge in cancer therapy, thus the development of sensitizing agents or small molecules with new mechanisms of action to kill the resistant cancers is highly desired. Autophagy is a cellular process responsible for the turnover of misfolded proteins or damaged organelles and recycling of nutrients to maintain cellular homeostasis. Recently, autophagy has been shown to regulate MDR in cancers. In this chapter, both intrinsic and acquired drug resistance affecting the efficiency of chemotherapy, and the MDR mechanisms including nonclassical MDR phenotype and classical transport-based MDR phenotype were discussed. In addition, the development of apoptosis-resistant cancer by the deregulation of apoptotic gene machinery, such as BCL-2, BAX, BAK, and TRAILR, was also covered. We then further discussed the controversial role of autophagy by illustrating how induction of autophagy could work as a tumor suppressor or promote tumor survival. The modulation of MDR in cancer by either induction or inhibition of autophagy was also discussed. We have further summarized the current compounds or drugs for modulating MDR cancers and how autophagy modulators could circumvent the MDR phenotypes in cancers. Finally, the new mechanisms participating in MDR phenotypes were proposed for future MDR drugs discovery

Dialog Action-Aware Transformer for Dialog Policy Learning

Recent works usually address Dialog policy learning DPL by training a reinforcement learning (RL) agent to determine the best dialog action. However, existing works on deep RL require a large volume of agent-user interactions to achieve acceptable performance. In this paper, we propose to make full use of the plain text knowledge from the pre-trained language model to accelerate the RL agent's learning speed. Specifically, we design a dialog action-aware transformer encoder (DaTrans), which integrates a new fine-tuning procedure named masked last action task to encourage DaTrans to be dialog-aware and distils action-specific features. Then, DaTrans is further optimized in an RL setting with ongoing interactions and evolves through exploration in the dialog action space toward maximizing long-term accumulated rewards. The effectiveness and efficiency of the proposed model are demonstrated with both simulator evaluation and human evaluation.Comment: To be appeared in SIGdial 202

Applying Theories of Particle Packing and Rheology to Concrete for Sustainable Development

Concrete is one of the most important construction materials. However, it is not so compatible with the demands of sustainable development because manufacturing of cement generates a large amount of carbon dioxide and therefore cement consumption produces a huge carbon footprint. Currently, the cement consumption is generally lowered by adding supplementary cementitious materials to replace part of the cement. Nonetheless, in order to maintain performance, there is a limit to such cement replacement by supplementary cementitious materials. To further reduce the cement consumption, the total cementitious materials content has to be reduced. This requires the packing density of the aggregate particles to be maximized so that the amount of voids in the bulk volume of aggregate to be filled with cement paste could be minimized and the surface area of the aggregate particles to be minimized so that the amount of cement paste needed to form paste films coating the surfaces of aggregate particle for rheological performance could be minimized. Such optimization is not straightforward and modern concrete science based on particuology is needed. Herein, a number of new theories regarding particle packing and rheology of concrete, which are transforming conventional concrete technology into modern concrete science, are presented. These theories would help to develop a more scientific and systematic concrete mix design method for the production of high-performance concrete with minimum cement consumption

MCML: A Novel Memory-based Contrastive Meta-Learning Method for Few Shot Slot Tagging

Meta-learning is widely used for few-shot slot tagging in task of few-shot learning. The performance of existing methods is, however, seriously affected by \textit{sample forgetting issue}, where the model forgets the historically learned meta-training tasks while solely relying on support sets when adapting to new tasks. To overcome this predicament, we propose the \textbf{M}emory-based \textbf{C}ontrastive \textbf{M}eta-\textbf{L}earning (aka, MCML) method, including \textit{learn-from-the-memory} and \textit{adaption-from-the-memory} modules, which bridge the distribution gap between training episodes and between training and testing respectively. Specifically, the former uses an explicit memory bank to keep track of the label representations of previously trained episodes, with a contrastive constraint between the label representations in the current episode with the historical ones stored in the memory. In addition, the \emph{adaption-from-memory} mechanism is introduced to learn more accurate and robust representations based on the shift between the same labels embedded in the testing episodes and memory. Experimental results show that the MCML outperforms several state-of-the-art methods on both SNIPS and NER datasets and demonstrates strong scalability with consistent improvement when the number of shots gets greater

Graft Suturing for Lenticule Dislocation after Descemet Stripping Automated Endothelial Keratoplasty

Purpose: To report the mid-term outcomes of graft suturing in a patient with lenticule dislocation after Descemet stripping automated endothelial keratoplasty (DSAEK). Case Report: A 78-year old woman was found to have graft dislocation involving the nasal half of the cornea after uneventful DSAEK. Graft repositioning, refilling the anterior chamber with air, and placement of four full-thickness 10/0 nylon sutures over the detached area were performed two weeks after the initial surgery. The sutures were removed 6 weeks later. Serial specular microscopy and anterior segment optical coherence tomography were performed. At 18 months, there was good lenticule apposition and a clear graft. Conclusion: Anchoring sutures seem to be effective for management of graft detachment following DSAEK

Combining CD4 recovery and CD4: CD8 ratio restoration as an indicator for evaluating the outcome of continued antiretroviral therapy: an observational cohort study

Immune recovery following highly active antiretroviral therapy (HAART) is commonly assessed by the degree of CD4 reconstitution alone. In this study, we aimed to assess immune recovery by incorporating both CD4 count and CD4:CD8 ratio

Immunotherapeutic Approaches of Rheumatoid Arthritis and the Implication on Novel Interventions for Refractoriness

Rheumatoid arthritis is an autoimmune disorder involving the chronic inflammation of affected joints which lead to the distortion and eventually destruction of the articular tissues. Clinically, many therapeutic methods are being used for RA treatment. Non-steroidal anti-inflammatory drugs (NSAIDs), steroid, and disease-modifying anti-rheumatic drugs (DMARDs) are the three main categories of intervention approaches. Among which DMARDs, targeting mainly the release of pro-inflammatory cytokines, demonstrated high efficacy because of its direct drug action that alter the underlying disease mechanisms rather than simply to mediate symptoms relieve. However, the use of DMARDs also accompanying some unwanted adverse side effects, in particular, the development of refractoriness, which hampers the successful rate of treatment. In this chapter, the conventional RA drugs will be reviewed, focusing on the currently used and latest development of DMARDs. Novel methods that could improve RA pathogenesis will also be introduced. Because of the critical role of refractory RA, the progress of the disease to develop resistance to standard drug treatment will also be described. Finally, innovative RA therapeutic methods inspired by researches concerning the pathogenesis and contemporary treatments of RA will be discussed

An Unifying Replacement Approach for Caching Systems

A cache replacement algorithm called probability based replacement (PBR) is proposed in this paper. The algorithm makes replacement decision based on the byte access probabilities of documents. This concept can be applied to both small conventional web documents and large video documents. The performance of PBR algorithm is studied by both analysis and simulation. By comparing cache hit probability, hit rate and average time spent in three systems, it is shown that the proposed algorithm outperforms the commonly used LRU and LFU algorithms. Simulation results show that, when large video documents are considered, the PBR algorithm provides up to 120% improvement in cache hit rate when comparing to that of conventional algorithms. The uniqueness of this work is that, unlike previous studies that propose different solutions for different types of documents separately, the proposed PBR algorithm provides a simple and unified approach to serve different types of documents in a single system

Genome sequence and genetic linkage analysis of Shiitake mushroom _Lentinula edodes_

_Lentinula edodes_ (Shiitake/Xianggu) is an important cultivated mushroom. Understanding the genomics and functional genomics of _L. edodes_ allows us to improve its cultivation and quality. Genome sequence is a key to develop molecular genetic markers for breeding and genetic manipulation. We sequenced the genome of _L. edodes_ monokaryon L54A using Roche 454 and ABI SOLiD genome sequencing. Sequencing reads of about 1400Mb were de novo assembled into a 40.2 Mb genome sequence. We compiled the genome sequence into a searchable database with which we have been annotating the genes and analyzing the metabolic pathways. In addition, we have been using many molecular techniques to analyze genes differentially expressed during development. Gene ortholog groups of _L. edodes_ genome sequence compared across genomes of several fungi including mushrooms identified gene families unique to mushroom-forming fungi. We used a mapping population of haploid basidiospores of dikaryon L54 for genetic linkage analysis. High-quality variations such as single nucleotide polymorphisms, insertions, and deletions of the mapping population formed a high-density genetic linkage map. We compared the linkage map to the _L. edodes_ L54A genome sequence and located selected quantitative trait loci. The Shiitake community will benefit from these resources for genetic studies and breeding.
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