Miracle-dz/UniFAR-FTUs huggingface dataset:
Training in Temporal Information Processing Ameliorates Phonetic Identification

Many studies revealed a link between temporal information processing (TIP) in a millisecond range and speech perception. Previous studies indicated a dysfunction in TIP accompanied by deficient phonemic hearing in children with specific language impairment (SLI). In this study we concentrate in SLI on phonetic identification, using the voice-onset-time (VOT) phenomenon in which TIP is built-in. VOT is crucial for speech perception, as stop consonants (like /t/ vs. /d/) may be distinguished by an acoustic difference in time between the onsets of the consonant (stop release burst) and the following vibration of vocal folds (voicing). In healthy subjects two categories (voiced and unvoiced) are determined using VOT task. The present study aimed at verifying whether children with SLI indicate a similar pattern of phonetic identification as their healthy peers and whether the intervention based on TIP results in improved performance on the VOT task. Children aged from 5 to 8 years (n = 47) were assigned into two groups: normal children without any language disability (NC, n = 20), and children with SLI (n = 27). In the latter group participants were randomly classified into two treatment subgroups, i.e., experimental temporal training (EG, n = 14) and control non-temporal training (CG, n = 13). The analyzed indicators of phonetic identification were: (1) the boundary location (α) determined as the VOT value corresponding to 50% voicing/unvoicing distinctions; (2) ranges of voiced/unvoiced categories; (3) the slope of identification curve (β) reflecting the identification correctness; (4) percent of voiced distinctions within the applied VOT spectrum. The results indicated similar α values and similar ranges of voiced/unvoiced categories between SLI and NC. However, β in SLI was significantly higher than that in NC. After the intervention, the significant improvement of β was observed only in EG. They achieved the level of performance comparable to that observed in NC. The training-related improvement in CG was non-significant. Furthermore, only in EG the β values in post-test correlated with measures of TIP as well as with phonemic hearing obtained in our previous studies. These findings provide another evidence that TIP is omnipresent in language communication and reflected not only in phonemic hearing but also in phonetic identification.
Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization

Asynchronous momentum stochastic gradient descent algorithms (Async-MSGD) is one of the most popular algorithms in distributed machine learning. However, its convergence properties for these complicated nonconvex problems is still largely unknown, because of the current technical limit. Therefore, in this paper, we propose to analyze the algorithm through a simpler but nontrivial nonconvex problem - streaming PCA, which helps us to understand Aync-MSGD better even for more general problems. Specifically, we establish the asymptotic rate of convergence of Async-MSGD for streaming PCA by diffusion approximation. Our results indicate a fundamental tradeoff between asynchrony and momentum: To ensure convergence and acceleration through asynchrony, we have to reduce the momentum (compared with Sync-MSGD). To the best of our knowledge, this is the first theoretical attempt on understanding Async-MSGD for distributed nonconvex stochastic optimization. Numerical experiments on both streaming PCA and training deep neural networks are provided to support our findings for Async-MSGD.
Is an SGLT 2 inhibitor right for your patient with type 2 diabetes ?

CASE 1 u Joe S is a 41-year-old African-American man who comes to your clinic after his employee health screening revealed elevated triglycerides. The patient has a 3-year history of type 2 diabetes mellitus (T2DM); he also has a history of hypertension, gastroesophageal reflux disease, and obstructive sleep apnea. Mr. S tells you he takes metformin 1000 mg twice daily, but stopped taking his glipizide because he didn’t think it was helping his blood sugar. His last hemoglobin (Hb) A1c result was 8.8%, and he is very resistant to starting insulin therapy. The patient’s other medications include enalapril 10 mg/d, atorvastatin 10 mg/d, and omeprazole 20 mg/d. Mr. S weighs 255.6 lbs (body mass index=34.7), his BP is 140/88 mm Hg, and his heart rate is 82 beats per minute. Laboratory values include: serum creatinine, 1.01 mg/dL; estimated glomerular filtration rate (eGFR) >100 mL/min/1.73 m2; potassium (K), 4.3 mmol/L; serum phosphorous (Phos), 2.8 mg/dL; magnesium (Mg), 1.9 mg/dL; total cholesterol, 167 mg/dL; low-density lipoprotein (LDL), 78 mg/dL; high-density lipoprotein (HDL), 38 mg/dL; and triglycerides, 256 mg/dL.
DETC 2018-85339 SYNTHESIZING DESIGNS WITH INTER-PART DEPENDENCIES USING HIERARCHICAL GENERATIVE ADVERSARIAL NETWORKS

Real-world designs usually consist of parts with hierarchical dependencies, i.e., the geometry of one component (a child shape) is dependent on another (a parent shape). We propose a method for synthesizing this type of design. It decomposes the problem of synthesizing the whole design into synthesizing each component separately but keeping the inter-component dependencies satisfied. This method constructs a two-level generative adversarial network to train two generative models for parent and child shapes, respectively. We then use the trained generative models to synthesize or explore parent and child shapes separately via a parent latent representation and infinite child latent representations, each conditioned on a parent shape. We evaluate and discuss the disentanglement and consistency of latent representations obtained by this method. We show that shapes change consistently along any direction in the latent space. This property is desirable for design exploration over the
Trees with Unique Least Central Subtrees

Abstract A subtree S of a tree T is a central subtree of T if S has the minimum eccentricity in the join-semilattice of all subtrees of T. Among all subtrees lying in the join-semilattice center, the subtree with minimal size is called the least central subtree. Hamina and Peltola asked what is the characterization of trees with unique least central subtree? In general, it is difficult to characterize completely the trees with unique least central subtree. Nieminen and Peltola [The subtree center of a tree, Networks 34 (1999) 272–278] characterized the trees with the least central subtree consisting just of a single vertex. This paper characterizes the trees having two adjacent vertices as a unique least central subtree.
Attention Based Fully Convolutional Network for Speech Emotion Recognition

Speech emotion recognition is a challenging task for three main reasons: 1) human emotion is abstract, which means it is hard to distinguish; 2) in general, human emotion can only be detected in some specific moments during a long utterance; 3) speech data with emotional labeling is usually limited. In this paper, we present a novel attention based fully convolutional network for speech emotion recognition. We employ fully convolutional network as it is able to handle variable-length speech, free of the demand of segmentation to keep critical information not lost. The proposed attention mechanism can make our model be aware of which time-frequency region of speech spectrogram is more emotion-relevant. Considering limited data, the transfer learning is also adapted to improve the accuracy. Especially, it's interesting to observe obvious improvement obtained with natural scene image based pre-trained model. Validated on the publicly available IEMOCAP corpus, the proposed model outperformed the state-of-the-art methods with a weighted accuracy of 70.4% and an unweighted accuracy of 63.9% respectively.
Huge Enhancement of Luminescence from a Coaxial-Like Heterostructure of Poly(3-methylthiophene) and Au

Recently, the light-matter interaction at nanoscale has attracted great interest from physicists, chemists and material scientists, as it gives peculiar optical properties that couldn’t be observed at the bulk scale. The synthesis and characterization of organic-inorganic heterostructures forming quantum dots, nanowires or nanotubes provide opportunities to understand their photophysical mechanism and to apply optoelecronic devices. Herein, we report a huge enhanced luminescence in a coaxial-like heterostructured poly (3-methylthiophene) (P3MT) with Au. We electrochemically synthesized P3MT nanowires (NWs) on a nanoporous template, and sequentially deposited Au on the surface of P3MT NWs. The diameter of heterostructured P3MT/Au NWs was about 200 nm, where the cladding-shape Au were about 10 nm. The visible range absorbance, with two new absorption peaks of P3MT/Au NWs, was significantly increased compared with that of P3MT NWs. Accordingly, the photoluminescence (PL) of a P3MT/Au NW was enormously increased; up to 170 times compared to that of P3MT NWs. More interestingly, an unexpected enhancement of PL was observed from cross-junction point of P3MT/Au NWs. The abnormal PL properties of P3MT/Au NWs were attributed to the charge transfer and the surface plasmon resonance between the cladding-shape Au and the core-shape P3MT, which resulted in the enhanced quantum yield. This incites us to reconsider the light-matter interaction in polymer-metal hybrid structures applicable for high-performance optoelectronic devices.
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms

Despite the recent successes of probabilistic programming languages (PPLs) in AI applications, PPLs offer only limited support for random variables whose distributions combine discrete and continuous elements. We develop the notion of measure-theoretic Bayesian networks (MTBNs) and use it to provide more general semantics for PPLs with arbitrarily many random variables defined over arbitrary measure spaces. We develop two new general sampling algorithms that are provably correct under the MTBN framework: the lexicographic likelihood weighting (LLW) for general MTBNs and the lexicographic particle filter (LPF), a specialized algorithm for state-space models. We further integrate MTBNs into a widely used PPL system, BLOG, and verify the effectiveness of the new inference algorithms through representative examples.
Current endovascular strategies for cerebral venous thrombosis: report of the SNIS Standards and Guidelines Committee

Cerebral venous thrombosis (CVT) is a rare condition accounting for <1% of all strokes, with highly variable clinical presentations ranging from a headache to coma.1–4 Although MRI and MR venography have significantly improved early diagnosis, clinical outcomes after treatment remain mixed.5 6 The aims of this document include: (1) to review existing knowledge about the natural history, diagnostic methodology, and treatment modalities/techniques for CVT, and (2) to provide recommendations on management strategies for CVT using the best available evidence, but out of necessity, frequently relying on expert opinion concerning this rare disease. Recommendations follow the American College of Cardiology/American Heart Association (ACC/AHA) classification of recommendation/level of evidence and definition of classes and levels of evidence used in AHA/American Stroke Association (ASA) recommendations.7 The Standards and Guidelines Committee of the Society of Neurointerventional Surgery (SNIS), a multidisciplinary society representing leaders in the field of endovascular therapy for neurovascular disease, prepared this document based on a comprehensive review of English language literature relating to the topic. A literature search using PubMed (US National Library of Medicine) and Ovid (Wolters Kluwer) databases was performed from January 1, 1980, through December 31, 2016. The following key words were used: [(sinus thrombosis) AND ((cerebral veins) OR (cranial sinuses) OR (heparin) OR (thrombectomy) OR (anticoagulation))]. A review of references provided in review articles and textbook chapters was also performed. Studies published in languages other than English were excluded. ### Incidence/prevalence The estimated incidence of adult CVT is 1.32 per 100 000 person-years. Among women aged between 31 and 50 years, the incidence is as high as 2.78 per 100 000 person-years.8 9 In children less than 18 years of age, the estimated incidence is 0.67 per 100 000 children per year, with neonates the most affected age group.10 Risk factors and conditions known to be associated with CVT are listed in …
Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex

Several recently proposed architectures of neural networks such as ResNeXt, Inception, Xception, SqueezeNet and Wide ResNet are based on the designing idea of having multiple branches and have demonstrated improved performance in many applications. We show that one cause for such success is due to the fact that the multi-branch architecture is less non-convex in terms of duality gap. The duality gap measures the degree of intrinsic non-convexity of an optimization problem: smaller gap in relative value implies lower degree of intrinsic non-convexity. The challenge is to quantitatively measure the duality gap of highly non-convex problems such as deep neural networks. In this work, we provide strong guarantees of this quantity for two classes of network architectures. For the neural networks with arbitrary activation functions, multi-branch architecture and a variant of hinge loss, we show that the duality gap of both population and empirical risks shrinks to zero as the number of branches increases. This result sheds light on better understanding the power of over-parametrization where increasing the network width tends to make the loss surface less non-convex. For the neural networks with linear activation function and $\ell_2$ loss, we show that the duality gap of empirical risk is zero. Our two results work for arbitrary depths and adversarial data, while the analytical techniques might be of independent interest to non-convex optimization more broadly. Experiments on both synthetic and real-world datasets validate our results.
Plasmodium falciparum subtilisin‐like ookinete protein SOPT plays an important and conserved role during ookinete infection of the Anopheles stephensi midgut

Transmission of the malaria parasite Plasmodium falciparum involves infection of Anopheles mosquitoes. Here we characterize SOPT, a protein expressed in P. falciparum ookinetes that facilitates infection of the mosquito midgut. SOPT was identified on the basis that it contains a signal peptide, a PEXEL‐like sequence and is expressed in asexual, ookinete and sporozoite stages, suggesting it is involved in infecting the human or mosquito host. SOPT is predicted to contain a subtilisin‐like fold with a non‐canonical catalytic triad and is orthologous to P. berghei PIMMS2. Localization studies reveal that SOPT is not exported to the erythrocyte but is expressed in ookinetes at the parasite periphery. SOPT‐deficient parasites develop normally through the asexual and sexual stages and produce equivalent numbers of ookinetes to NF54 controls, however, they form fewer oocysts and sporozoites in mosquitoes. SOPT‐deficient parasites were also unable to activate the immune‐responsive midgut invasion marker SRPN6 after mosquito ingestion, suggesting they are defective for entry into the midgut. Disruption of SOPT in P. berghei (PIMMS2) did not affect other lifecycle stages or ookinete development but again resulted in fewer oocysts and sporozoites in mosquitoes. Collectively, this study shows that SOPT/PIMMS2 plays a conserved role in ookinetes of different Plasmodium species.
Passive, Active, or Co-Active? The Link Between Synchronous User Participation and Willingness to Pay for Premium Options

Social media-enabled business models have transformed the content industry. To increase users’ willingness to pay (WTP), many of today’s content providers have changed from mere content provision towards offering social content experiences. Recent research has confirmed that users’ participation activities, e.g. commenting on content, increase the WTP for social content services’ premium options. So far, social content has been available predominantly ondemand, only allowing asynchronous user participation. Recently, social live content services emerged, which facilitate synchronous user participation and enable so-called co-active behavior. With this study, we conceptualize co-active behavior as the interplay between users while co-experiencing content together, and empirically show that co-active behavior has a stronger effect on WTP for premium options than the classic forms of passive and active behavior. Our work provides theoretical contributions on the WTP for social content as well as implications for the management of social content services.
Evaluating the Cost-Effectiveness of Proportional-Assist Ventilation Plus vs. Pressure Support Ventilation in the Intensive Care Unit in Two Countries

Background: Mechanical ventilation is an integral, but expensive, part of the intensive care unit (ICU). Optimal use of mechanical ventilation could save costs and improve patient outcomes. Here, the cost effectiveness of proportional assist ventilation (PAV™ ventilation by Medtronic) is estimated relative to pressure support ventilation (PSV). Methods: A cohort-level, clinical model was built using data from clinical trials. The model estimates patient-ventilator asynchrony >10%, tracheostomy, ventilator-associated pneumonia, other nosocomial infections, spontaneous breathing trial success, hypoxemia, and death. Cost and quality of life are associated with all events, with cost effectiveness defined as the cost per quality-adjusted life year (QALY) gained in the US and UK. Results: The mean cost of ICU care was lower with PAV™ than with PSV in the US and UK, but the total cost of care over 40 years was higher due to more patients surviving and incurring future care costs. Reduced time on mechanical ventilation, fewer nosocomial infections, and extended life expectancy with PAV™ drove QALY improvement. The cost per QALY gained with PAV™ was $8,628 and £2,985. Conclusion: PAV™ improves quality of life and reduces short-term costs. PAV™ is likely to be considered cost-effective over 40-years in the US and UK.
Optimization of Remote Core Locking Synchronization in Multithreaded Programs for Multicore Computer Systems

This paper proposes the algorithms for optimization of Remote Core Locking (RCL) synchronization method in multithreaded programs. The algorithm of initialization of RCL-locks and the algorithms for threads affinity optimization are developed. The algorithms consider the structures of hierarchical computer systems and non-uniform memory access (NUMA) to minimize execution time of RCLprograms. The experimental results on multi-core computer systems represented in the paper shows the reduction of RCLprograms execution time.
Co-creating an Open Government Data Driven Public Service: The Case of Chicago's Food Inspection Forecasting Model

Large amounts of Open Government Data (OGD) have become available and co-created public services have started to emerge, but there is only limited empirical material available on co-created OGD-driven public services. To address this shortcoming and explore the concept of co-created OGD-driven public services the authors conducted an exploratory case study. The case study explored Chicago’s use of OGD in the co-creation of a predictive analytics model that forecasts critical safety violations at food serving establishments. The results of this exploratory work allowed for new insights to be gained on co-created OGD-driven public services and led to the identification of six factors that seem to play a key role in allowing for a OGD-driven public service to be co-created. The results of the initial work also provide valuable new information that can be used to aid in the development and improvement of the authors’ conceptual model for understanding co-created OGD-driven public service.
Ethical Implications of Bias in Machine Learning

Biases in AI and machine learning algorithms are presented and analyzed through two issues management frameworks with the aim of showing how ethical problems and dilemmas can evolve. While “the singularity” concept in AI is presently more predictive than actual, both benefits and damage that can result by failure to consider biases in the design and development of AI. Inclusivity and stakeholder awareness regarding potential ethical risks and issues need to be identified during the design of AI algorithms to ensure that the most vulnerable in societies are protected from harm.
The relevance of irrelevant information

This paper experimentally investigates the effect of introducing unavailable alternatives and irrelevant information regarding the alternatives on the optimality of decisions in choice problems. We find that the presence of unavailable alternatives and irrelevant information generates suboptimal decisions with the interaction between the two amplifying this effect. Irrelevant information in any dimension increases the time costs of decisions. We also identify a “preference for simplicity” beyond the desire to make optimal decisions or minimize time spent on a decision problem.
Comparison of the Efficacy of Different Analgesia Treatments for Total Knee Arthroplasty: A Network Meta-Analysis

Background and Aim: The severe pain after total knee arthroplasty (TKA) brings many patients more suffering, longer hospital stay, and higher expenses. This study was designed to assess the relative efficacy of several clinical treatments for postoperative analgesia of TKA through network meta-analysis based on multiple published randomized controlled trials. Methods: Embase and PubMed were utilized to conduct this network meta-analysis from inception until 2016. Pain score, morphine consumption (milligrams), and length of hospitalization (day) were selected as the endpoints. Results: A total of 58 studies with 3501 patients were included in this network meta-analysis. Except for patient-controlled epidural analgesia+femoral nerve block (FNB) and sciatic nerve block, all treatments were significantly superior to placebo in pain score 6 to 8 hours. In terms of pain score 24 hours, only continuous femoral nerve block (cFNB), periarticular infiltration, periarticular infiltration+FNB, single-dose FNB, and sciatic nerve block+FNB exhibited better performance than control group. For pain score 48 hours after surgery, only cFNB and intra-articular infiltration yielded better results than control group [standard mean difference=−0.68, 95% credible intervals (CrIs)=−1.03 to −0.33; standard mean difference=−0.53, 95% CrIs=−1.07 to −0.01, respectively]. Only cFNB exhibited better results with respect to morphine consumption day 2 after surgery (mean difference=−12.95, 95% CrIs=−19.70 to −6.53). Conclusions: Considering both pain score and morphine consumption, cFNB was potentially the most efficacious postoperative treatment for patients undergoing TKA.