Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Glottis Detection and Segmentation in Stroboscopic Videos Using Convolutional Networks

Laryngeal videostroboscopy is widely used for the analysis of glottal vibration patterns. This analysis plays a crucial role in the diagnosis of voice disorders. It is essential to study these patterns using automatic glottis segmentation methods to avoid subjectiveness in diagnosis. Glottis detection is an essential step before glottis segmentation. This paper considers the problem of automatic glottis segmentation using U-Net based deep convolutional networks. For accurate glottis detection, we train a fully convolutional network with a large amount of glottal and non-glottal images. In glottis segmentation, we consider U-Net with three different weight initialization schemes: 1) Random weight Initialization (RI), 2) Detection Network weight Initialization (DNI) and 3) Detection Network encoder frozen weight Initialization (DNIFr), using two different architectures: 1) U-Net without skip connection (UWSC) 2) U-Net with skip connection (USC). Experiments with 22 subjects’ data reveal that the performance of glottis segmentation network can be increased by initializing its weights using those of the glottis detection network. Among all schemes, when DNI is used, the USC yields an average localization accuracy of 81.3% and a Dice score of 0.73, which are better than those from the base-line approach by 15.87% and 0.07 (absolute), respectively
Compressing LSTM Networks with Hierarchical Coarse-Grain Sparsity

The long short-term memory (LSTM) network is one of the most widely used recurrent neural networks (RNNs) for automatic speech recognition (ASR), but is parametrized by millions of parameters. This makes it prohibitive for memory-constrained hardware accelerators as the storage demand causes higher dependence on off-chip memory, which bottlenecks latency and power. In this paper, we propose a new LSTM training technique based on hierarchical coarse-grain sparsity (HCGS), which enforces hierarchical structured sparsity by randomly dropping static block-wise connections between layers. HCGS maintains the same hierarchical structured sparsity throughout training and inference; this reduces weight storage for both training and inference hardware systems. We also jointly optimize in-training quantization with HCGS on 2/3-layer LSTM networks for the TIMIT and TED-LIUM corpora. With 16 × structured compression and 6-bit weight precision, we achieved a phoneme error rate (PER) of 16.9% for TIMIT and a word error rate (WER) of 18.9% for TED-LIUM, showing the best trade-off between error rate and LSTM memory compression compared to prior works.
Language Modeling for Speech Analytics in Under-Resourced Languages

Different language modeling approaches are evaluated on two under-resourced, agglutinative, South African languages; Sesotho and isiZulu. The two languages present different challenges to language modeling based on their respective orthogra-phies; isiZulu is conjunctively written whereas Sotho is disjunc-tively written. Two subword modeling approaches are evaluated and shown to be useful to reduce the OOV rate for isiZulu, and for Sesotho, a multi-word approach is evaluated for improving ASR accuracy, with limited success. RNNs are also evaluated and shown to slightly improve ASR accuracy, despite relatively small text corpora.
WISE: Word-Level Interaction-Based Multimodal Fusion for Speech Emotion Recognition

While having numerous real-world applications, speech emotion recognition is still a technically challenging problem. How to effectively leverage the inherent multiple modalities in speech data (e.g., audio and text) is key to accurate classiﬁcation. Existing studies normally choose to fuse multimodal features at the utterance level and largely neglect the dynamic interplay of features from different modalities at a ﬁne-granular level over time. In this paper, we explicitly model dynamic interactions between audio and text at the word level via interaction units between two long short-term memory networks representing audio and text. We also devise a hierarchical representation of audio information from the frame, phoneme and word levels, which largely improves the expressiveness of re-sulting audio features. We ﬁnally propose WISE, a novel word-level interaction-based multimodal fusion framework for speech emotion recognition, to accommodate the aforementioned components. We evaluate WISE on the public benchmark IEMOCAP corpus and demonstrate that it outperforms state-of-the-art methods.
Effects of Communication Channels and Actor's Gender on Emotion Identification by Native Mandarin Speakers

Communication channels and actor’s gender have been increasingly reported to influence emotion perception, but past literature exploring these two factors has largely been disassociated. The present study examined how emotions expressed by actors of the two genders are perceived in three different sensory channels (i.e. face, prosody, and semantics). Eighty-eight native Mandarin participants (43 females and 45 males) were asked to identify the emotion displayed visually through face, or auditorily through prosody or semantics in a fixed-choice format, in which accuracy and reaction time were recorded. Results revealed that visual facial expressions were more accurately and rapidly identified, particularly when posed by female actors. Additionally, emotion perception in the auditory modality was modulated by actor’s gender to a greater extent: emotional prosody yielded more accurate and faster responses when expressed by female than male actors, while emotional semantics produced better performances when presented by males. To sum up, paralinguistic (i.e., visual and prosodic) dominance effects are more evident in emotions expressed by female than male actors.
Costs of providing HIV care and optimal allocation of HIV resources in Guyana

Introduction Great strides in responding to the HIV epidemic have led to improved access to and uptake of HIV services in Guyana, a lower-middle-income country with a generalized HIV epidemic. Despite efforts to scale up HIV treatment and adopt the test and start strategy, little is known about costs of HIV services across the care cascade. Methods We collected cost data from the national laboratory and nine selected treatment facilities in five of the country’s ten Regions, and estimated the costs associated with HIV testing and services (HTS) and antiretroviral therapy (ART) from a provider perspective from January 1, 2016 to December 31, 2016. We then used the unit costs to construct four resource allocation scenarios. In the first two scenarios, we calculated how close Guyana would currently be to its 2020 targets if the allocation of funding across programs and regions over 2017–2020 had (a) remained unchanged from latest-reported levels, or (b) been optimally distributed to minimize incidence and deaths. In the next two, we estimated the resources that would have been required to meet the 2020 targets if those resources had been distributed (a) according to latest-reported patterns, or (b) optimally to minimize incidence and deaths. Results The mean cost per test was US$15 and the mean cost per person tested positive was US$796. The mean annual cost per of maintaining established adult and pediatric patients on ART were US$428 and US$410, respectively. The mean annual cost of maintaining virally suppressed patients was US$648. Cost variation across sites may suggest opportunities for improvements in efficiency, or may reflect variation in facility type and patient volume. There may also be scope for improvements in allocative efficiency; we estimated a 28% reduction in the total resources required to meet Guyana’s 2020 targets if funds had been optimally distributed to minimize infections and deaths. Conclusions We provide the first estimates of costs along the HIV cascade in the Caribbean and assessed efficiencies using novel context-specific data on the costs associated with diagnostic, treatment, and viral suppression. The findings call for better targeting of services, and efficient service delivery models and resource allocation, while scaling up HIV services to maximize investment impact.
Lithiation Mechanism in High-Entropy Oxides as Anode Materials for Li-Ion Batteries: An Operando XAS Study

High-entropy oxides based on transition metals, such as Mg0.2Co0. 2Ni0.2Cu0. 2Zn0.2O (TM-HEO), have recently drawn special attention as potential anodes in lithium-ion batteries due to high specific capacity and cycling reversibility. However, the lithiation/delithiation mechanism of such systems is still controversial and not clearly addressed. Here, we report on an operando XAS investigation into TM-HEO-based anodes for lithium-ion cells during the first lithiation/delithiation cycle. This material showed a high specific capacity exceeding 600 mAh g–1 at 0.1 C and Coulombic efficiency very close to unity. The combination of functional and advanced spectroscopic studies revealed complex charging mechanisms, developing through the reduction of transition-metal (TM) cations, which triggers the conversion reaction below 1.0 V. The conversion is irreversible and incomplete, leading to the final collapse of the HEO rock-salt structure. Other redox processes are therefore discussed and called to account for the observed cycling behavior of the TM-HEO-based anode. Despite the irreversible phenomena, the HEO cubic structure remains intact for ∼60% of lithiation capacity, so proving the beneficial role of the configuration entropy in enhancing the stability of the HEO rock-salt structure during the redox phenomena.
Genetic Landscape of Papillary Thyroid Carcinoma and Nuclear Architecture: An Overview Comparing Pediatric and Adult Populations

Simple Summary Papillary thyroid carcinoma (PTC) represents 80–90% of all differentiated thyroid carcinomas. PTC has a high rate of gene fusions and mutations, which can influence clinical and biological behavior in both children and adults. In this review, we focus on the comparison between pediatric and adult PTC, highlighting genetic alterations, telomere-related genomic instability and changes in nuclear organization as novel biomarkers for thyroid cancers. Abstract Thyroid cancer is a rare malignancy in the pediatric population that is highly associated with disease aggressiveness and advanced disease stages when compared to adult population. The biological and molecular features underlying pediatric and adult thyroid cancer pathogenesis could be responsible for differences in the clinical presentation and prognosis. Despite this, the clinical assessment and treatments used in pediatric thyroid cancer are the same as those implemented for adults and specific personalized target treatments are not used in clinical practice. In this review, we focus on papillary thyroid carcinoma (PTC), which represents 80–90% of all differentiated thyroid carcinomas. PTC has a high rate of gene fusions and mutations, which can influence the histologic subtypes in both children and adults. This review also highlights telomere-related genomic instability and changes in nuclear organization as novel biomarkers for thyroid cancers.
Parental Investment After the Birth of a Sibling: The Effect of Family Size in Low-Fertility China

A large body of research has examined the relationship between family size and child well-being in developing countries, but most of this literature has focused on the consequences of high fertility. The impact of family size in a low-fertility developing country context remains unknown, even though more developing countries are expected to reach below-replacement fertility levels. Set in China between 2010 and 2016, this study examines whether an increase in family size reduces parental investment received by the firstborn child. Using data from the China Family Panel Studies (CFPS), this study improves on previous research by using direct measures of parental investment, including monetary and nonmonetary investment, and distinguishing household-level from child-specific resources. It also exploits the longitudinal nature of the CFPS to mediate the bias arising from the joint determination of family size and parental investment. Results show that having a younger sibling significantly reduces the average household expenditure per capita. It also directly reduces parental investment received by the firstborn child, with two exceptions: (1) for firstborn boys, having a younger sister does not pose any competition; and (2) for firstborn children whose mothers have completed primary education or more, having a younger brother does not reduce parental educational aspirations for them. Findings from this study provide the first glimpse into how children fare as China transitions to a universal two-child policy regime but have wider implications beyond the Chinese context.
Extended Study on the Use of Vocal Tract Variables to Quantify Neuromotor Coordination in Depression

Changes in speech production that occur as a result of psychomotor slowing, a key feature of Major Depressive Disorder (MDD), are used to non-invasively diagnose MDD. In previous work using data from seven subjects, we showed that using speech-inverted vocal tract variables (TVs) as a direct measure of articulation to quantify changes in the way speech is produced when depressed relative to being not depressed outperforms formant information as a proxy for articulatory information. In this paper, we made significant extensions by using more subjects, taking into account more eigenvalue features and incorporating TVs related to (1) place of articulation and (2) the glottal source. These additions result in a significant improvement in accuracy, particularly for free speech. As a baseline, we perform a similar analysis using higher-dimensional Mel Frequency Cepstral Coefficients (MFCCs).
Fantastic Four: Honest-Majority Four-Party Secure Computation With Malicious Security

This work introduces a novel four-party honest-majority MPC protocol with active security that achieves comparable efﬁciency to equivalent protocols in the same setting, while having a much simpler design and not relying on function-dependent preprocessing. Our initial protocol satisﬁes security with abort, but we present some extensions to achieve guaranteed output delivery. Unlike previous works, we do not achieve this by delegating the computation to one single party that is identiﬁed to be honest, which is likely to hinder the adoption of these technologies as it centralizes sensitive data. Instead, our novel approach guarantees termination of the protocol while ensuring that no single party (honest or corrupt) learns anything beyond the output. We implement our four-party protocol with abort in the MP-SPDZ framework for multi-party computation and benchmark multiple applications like MNIST classiﬁcation training and ImageNet inference. Our results show that our four-party protocol performs similarly to an efﬁcient honest-majority three-party protocol that only provides semi-honest/passive security, which suggests that adding a fourth party can be an effective method to achieve active security without harming performance. Changelog: This version improves accuracy ﬁgures, which were impacted by a bug in our software in a previous version. We have also improved Section 7.1. 2.
Black-capped chickadees (Poecile atricapillus) alter alarm call duration and peak frequency in response to traffic noise

Anthropogenic noise is an often-overlooked byproduct of urbanization and affects the soundscape in which birds communicate. Previous studies assessing the impact of traffic noise have focused on bird song, with many studies demonstrating the ability of birds to raise song frequency in the presence of low-frequency traffic noise to avoid masking. Less is known about the impact of traffic noise on avian alarm calls, which is surprising given the degree to which predator information within alarm calls may impact fitness. The objective of this study was to assess the impacts of traffic noise on the Black-capped Chickadees (Poecile atricapillus), a small non-migratory songbird with a well-studied and information-rich alarm call. We studied birds at eight locations in Stark County, Ohio, from 15 January to 7 March 2016, and used a taxidermic mount of an Eastern Screech-Owl to elicit alarm calls. In half of the trials, a pre-recorded traffic noise track was also broadcasted at 50 decibels. In noise trials, chickadee calls contained more introductory notes (P < 0.001), more total notes (P < 0.001), were of longer duration (P < 0.001), and had lower introductory and D-note peak frequencies (P = 0.032 and P = 0.041, respectively). No differences were noted in the number of D-notes per call between noise and control trials. Modifying alarm call duration and frequency, without changing the number of D-notes, may be a strategy that chickadees use to convey predator information and to coordinate a threat-appropriate mobbing response when it is not possible to change call type. Our results add to the small, but growing, literature documenting the effects of anthropogenic noise on avian alarm calls, demonstrate the flexibility and complexity of chickadee calls given in response to predators, and may partially explain why chickadees adapt well to urban areas.
Order Matters! Influences of Linear Order on Linguistic Category Learning

Abstract Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers (premarkers, e.g., gendered articles) or succeeding category markers (postmarkers, e.g., gendered suffixes). Given that numerous systems for marking grammatical categories exist in natural languages, it follows that a better understanding of these findings can shed light on the factors underlying this diversity. In two discriminative learning simulations and an artificial language learning experiment, we identify two factors that modulate linear order effects in linguistic category learning: category structure and the level of abstraction in a category hierarchy. Regarding category structure, we find that postmarking brings an advantage for learning category diagnostic stimulus dimensions, an effect not present when categories are non‐confusable. Regarding levels of abstraction, we find that premarking of super‐ordinate categories (e.g., noun class) facilitates learning of subordinate categories (e.g., nouns). We present detailed simulations using a plausible candidate mechanism for the observed effects, along with a comprehensive analysis of linear order effects within an expectation‐based account of learning. Our findings indicate that linguistic category learning is differentially guided by pre‐ and postmarking, and that the influence of each is modulated by the specific characteristics of a given category system.
The Achilles tendon: Management of acute and chronic conditions.

BACKGROUND The prevalence of acute and chronic conditions of the Achilles tendon is increasing among an ageing, active population. These conditions are a common cause of presentation to general practitioners and allied health practitioners. Achilles tendon injuries have a bimodal demographical presentation, with acute injuries commonly occurring in younger people and chronic conditions presenting in patients who are elderly. OBJECTIVE The aims of this article are to discuss management of acute Achilles tendon ruptures in the primary care setting, explain the risks associated with calcaneal tuberosity fracture and discuss non-operative and surgical management of acute and chronic overload conditions of the Achilles tendon. DISCUSSION Achilles tendon injuries can be divided into acute ruptures and chronic overuse injuries. Both can be debilitating, with significant morbidity for patients; fortunately, both types of injuries respond well to non-operative interventions, with only a small proportion requiring surgery. Management of acute Achilles tendon rupture has evolved, with increasing evidence that non-operative management is appropriate providing patients participate in a functional rehabilitation protocol. Chronic conditions such as the sequalae of an untreated rupture or Achilles tendinopathy can be debilitating but often respond well to non-operative management.
FLANNEL (Focal Loss bAsed Neural Network EnsembLe) for COVID-19 detection

Abstract Objective The study sought to test the possibility of differentiating chest x-ray images of coronavirus disease 2019 (COVID-19) against other pneumonia and healthy patients using deep neural networks. Materials and Methods We construct the radiography (x-ray) imaging data from 2 publicly available sources, which include 5508 chest x-ray images across 2874 patients with 4 classes: normal, bacterial pneumonia, non–COVID-19 viral pneumonia, and COVID-19. To identify COVID-19, we propose a FLANNEL (Focal Loss bAsed Neural Network EnsembLe) model, a flexible module to ensemble several convolutional neural network models and fuse with a focal loss for accurate COVID-19 detection on class imbalance data. Results FLANNEL consistently outperforms baseline models on COVID-19 identification task in all metrics. Compared with the best baseline, FLANNEL shows a higher macro-F1 score, with 6% relative increase on the COVID-19 identification task, in which it achieves precision of 0.7833 ± 0.07, recall of 0.8609 ± 0.03, and F1 score of 0.8168 ± 0.03. Discussion Ensemble learning that combines multiple independent basis classifiers can increase the robustness and accuracy. We propose a neural weighing module to learn the importance weight for each base model and combine them via weighted ensemble to get the final classification results. In order to handle the class imbalance challenge, we adapt focal loss to our multiple classification task as the loss function. Conclusion FLANNEL effectively combines state-of-the-art convolutional neural network classification models and tackles class imbalance with focal loss to achieve better performance on COVID-19 detection from x-rays.
Prolonged grief in refugees, parenting behaviour and children’s mental health

Background: Many refugees experience bereavement, and as a result they suffer elevated rates of prolonged grief disorder. Evidence also indicates that elevated rates of psychological disturbance in refugee children can be associated with parental mental health. This study examined the extent to which prolonged grief disorder in refugees is associated with their parenting behaviour and in turn with their children’s mental health. Methods: This study recruited participants from the Building a New Life in Australia prospective cohort study of refugees admitted to Australia between October 2013 and February 2014. The current data were collected in 2015–2016 and comprised 1799 adults, as well as 411 children of the adult respondents. Adult refugees were assessed for trauma history, post-migration difficulties, harsh and warm parenting, probable prolonged grief disorder and posttraumatic stress disorder. Children were administered the Strengths and Difficulties Questionnaire. The current analyses on bereaved refugees comprise 110 caregivers and 178 children. Results: In this cohort, 37% of bereaved refugees reported probable prolonged grief disorder. Path analysis indicated that caregivers’ grief was directly associated with children’s emotional difficulties. Caregiver warmth was associated with reduced emotional problems in children of refugees with minimal grief but associated with more emotional problems in caregivers with more severe grief. More harsh parenting was associated with children’s conduct problems, and this was more evident in those with less severe grief. Conclusion: Severity of prolonged grief disorder is directly linked to refugee children’s mental health. The association between parenting style, grief severity and children’s mental health highlights that managing grief reactions in refugees can benefit both refugees and their children.