Order-Free RNN with Visual Attention for Multi-Label Classification

In this paper, we propose the joint learning attention and recurrent neural network (RNN) models for multi-label classification. While approaches based on the use of either model exist (e.g., for the task of image captioning), training such existing network architectures typically require pre-defined label sequences. For multi-label classification, it would be desirable to have a robust inference process, so that the prediction error would not propagate and thus affect the performance. Our proposed model uniquely integrates attention and Long Short Term Memory (LSTM) models, which not only addresses the above problem but also allows one to identify visual objects of interests with varying sizes without the prior knowledge of particular label ordering. More importantly, label co-occurrence information can be jointly exploited by our LSTM model. Finally, by advancing the technique of beam search, prediction of multiple labels can be efficiently achieved by our proposed network model.Comment: Accepted at 32nd AAAI Conference on Artificial Intelligence (AAAI-18

Non-autoregressive Transformer-based End-to-end ASR using BERT

Transformer-based models have led to a significant innovation in various classic and practical subjects, including speech processing, natural language processing, and computer vision. On top of the transformer, the attention-based end-to-end automatic speech recognition (ASR) models have become a popular fashion in recent years. Specifically, the non-autoregressive modeling, which can achieve fast inference speed and comparable performance when compared to conventional autoregressive methods, is an emergent research topic. In the context of natural language processing, the bidirectional encoder representations from transformers (BERT) model has received widespread attention, partially due to its ability to infer contextualized word representations and to obtain superior performances of downstream tasks by performing only simple fine-tuning. In order to not only inherit the advantages of non-autoregressive ASR modeling, but also receive benefits from a pre-trained language model (e.g., BERT), a non-autoregressive transformer-based end-to-end ASR model based on BERT is presented in this paper. A series of experiments conducted on the AISHELL-1 dataset demonstrates competitive or superior results of the proposed model when compared to state-of-the-art ASR systems

Development and validation of the newly developed Preschool Theory of Mind Assessment (ToMA-P)

IntroductionTheory of mind (ToM) refers to the ability to understand and attribute mental states to oneself and others. A ToM measure is warranted for preschool children to assess their ToM development from a multidimensional perspective (i.e., cognitive and affective dimensions). This study aimed to develop the Preschool Theory of Mind Assessment (ToMA-P) and to evaluate its construct validity and applicability.MethodsThe ToMA-P was developed based on comprehensive literature review and revised with expert panel feedback. Its psychometric properties were evaluated in 205 typically developing preschoolers with Rasch analysis for its dimensionality, item difficulties, and convergent validity.ResultsThe results indicated that all ToMA-P items, except for one, fit the hypothesized two-dimensional construct. The item difficulties in the cognitive and affective dimensions followed developmental sequences. The ToMA-P scores exhibited good convergent validity, as evidenced by its significant correlations with age, verbal comprehension, adaptive functions, and daily ToM performance (p < 0.05). Children’s responses and behaviors also showed that the ToMA-P has good applicability.DiscussionThis study provides empirical evidence that the ToMA-P measures cognitive and affective ToM following developmental sequences, and that it has potential as a clinical tool for assessing ToM in preschool children

Proizvodnja novog probiotičkog sira tipa Cheddar, veće ACE inhibicijske aktivnosti i većeg udjela γ-aminomaslačne kiseline, s pomoću Lactobacillus casei Zhang, izolirane iz fermentiranoga mliječnog napitka

Cheddar cheese has been manufactured with Lactobacillus casei Zhang as the dairy starter adjunct. L. casei Zhang had previously been isolated from koumiss collected from Xilin Guole in Inner Mongolia and characterized in detail with regard to their probiotic potential. The addition of L. casei Zhang to Cheddar cheese had no adverse effects on sensory criteria. The cheese made with 0.1, 1 and 2 % of the probiotic strain L. casei Zhang adjuncts contained high levels of the Lactobacillus after 6 months of ripening with final counts of 9.6·10^7, 7.7·10^7 and 1.02·10^8 CFU/g, respectively. In the ripe control cheese, without the addition of probiotic strain L. casei Zhang, the number of Lactobacillus reached 5.7·107 CFU/g. Enterobacterial repetitive intergenic consensus PCR (ERIC-PCR) analysis was used to distinguish the added L. casei Zhang from the natural flora of the cheese and to determine whether L. casei Zhang grew in the cheese. ACE-inhibitory activity and γ-aminobutyric acid (GABA) concentrations in the cheese were measured. Compared with control cheese, experimental cheese with 0.1, 1 and 2 % of probiotic strain L. casei Zhang revealed some increase in ACE-inhibitory activity and GABA mass fraction. In the present study, the production of both ACE-inhibitory activity and GABA in the probiotic cheese with the L. casei Zhang adjunct isolated from koumiss has been found for the first time. The results suggest that cheese with the probiotic strain L. casei Zhang showed good potential for application in the management of hypertension.Proizveden je sir tipa Cheddar s pomoću dodane kulture Lactobacillus casei Zhang, prethodno izolirane iz fermentiranoga mliječnog napitka „koumiss“ (Xilin Guole, središnja Mongolija, Kina). Iscrpno su ispitana probiotička svojstva izolirane kulture. Utvrđeno je da dodatak kulture nije bitno promijenio senzorička svojstva sira. Sir pripremljen s 0,1 % probiotičke kulture imao je nakon 6 mjeseci zrenja 9,6·107 CFU/g, sir s 1 % probiotičke kulture 7,7·107 CFU/g, a sir s 2 % probiotičke kulture 1,02·108 CFU/g bakterija roda Lactobacillus. U zrelom je kontrolnom uzorku sira (bez dodatka L. casei Zhang) broj bakterija Lactobacillus bio 5,7·107 CFU/g. Provedbom ERIC-PCR analize razlučena je dodana kultura L. casei Zhang od prirodne mikroflore sira, te utvrđen njezin rast. Također je izmjerena veća ACE inhibicijska aktivnost te veći udio γ-aminomaslačne kiseline u dobivenom siru, u usporedbi s kontrolnim uzorkom. Rezultati pokazuju da se dodatkom probiotičke kulture L. casei Zhang dobiva sir boljih svojstava, čija veća primjena pridonosi liječenju povišenog arterijskog tlaka

Antiviral Prescriptions to U.S. Ambulatory Care Visits with a Diagnosis of Influenza before and after High Level of Adamantane Resistance 2005–06 Season

Rapid emergence of influenza A viruses resistance to anti-influenza drugs has been observed in the past five years. Our objective was to compare antiviral prescription patterns of ambulatory care providers to patients with a diagnosis of influenza before and after the 2005-2006 influenza season, which was temporally concordant with the emergence of adamantane resistance. We also determined providers' adherence to Centers for Disease Control and Prevention (CDC) 2006 interim treatment guidelines for influenza after the dissemination of guidelines.We conducted a multi-year cross-sectional analysis using 2002-2006 data from the national representative ambulatory care surveys, National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey. Our main outcome measure was prescription of any anti-influenza pharmaceutical medication, including amantadine, rimantadine, oseltamivir, and zanamivir. Analyses were performed using procedures taking into account the multi-stage survey design and weighted sampling probabilities of the data source. Overall, there were 941 visits to U.S. ambulatory care providers for which the diagnosis of influenza was made, representing 12,140,727 visits nationally. Antiviral drugs were prescribed in 21.7% of visits. Even though prescription rates were not significantly different by influenza season (2001-02: 26.4%; 2002-03: 11.2%; 2003-04: 16.5%; 2004-05: 18.0%; 2005-06: 35.8%; 2006-07: 46.5%, p = 0.061), significantly higher prescription rates were observed in the high adamantane resistance period (18.7% versus 37.0%, p = 0.023), and after the announcement of the 2006 guidelines (18.5% versus 38.8%, p = 0.032). Use of adamantanes decreased over time, in that they were commonly used during influenza seasons 2001-03 (60.1%), but used much less frequently during seasons 2003-05 (31.9%), and used rarely after high adamantane resistance emerged (2.2%) (p<0.001). Adherence to 2006 guidelines was 97.7%. After March 2006, no prescriptions for adamantanes were given to patients with a diagnosis of influenza.In this nationally representative study of U.S. ambulatory care visits, we found a complete absence of the use of adamantanes in all ambulatory care settings after March 2006, closely corresponding to release of the 2006 CDC interim guidelines. Adherence to such practice is an essential element for control and prevention of influenza, especially during the era of emergence of resistance to anti-viral drugs

trans-Dichloridobis(2,4-dimethyl­aniline-κN)palladium(II)

In the title compound, [PdCl2(C8H11N)2], the PdII atom is located on a crystallographic inversion center and adopts a square-planar coordination geometry, with pairs of equivalent ligands in trans positions. In the crystal, adjacent mol­ecules are linked with each other through weak N—H⋯Cl hydrogen bonds and π–π stacking inter­actions between the phenyl rings [shortest centroid–centroid distance = 3.720 (2) Å], leading to the formation of layers parallel to the a-axis direction

Identification of patients with chronic migraine by using sensory-evoked oscillations from the electroencephalogram classifier

Background: To examine whether the modulating evoked cortical oscillations could be brain signatures among patients with chronic migraine, we investigated cortical modulation using an electroencephalogram with machine learning techniques. Methods: We directly record evoked electroencephalogram activity during nonpainful, painful, and repetitive painful electrical stimulation tasks. Cortical modulation for experimental pain and habituation processing was analyzed and used to differentiate patients with chronic migraine from healthy controls using a validated machine-learning model. Results: This study included 80 participants: 40 healthy controls and 40 patients with chronic migraine. Evoked somatosensory oscillations were dominant in the alpha band. Longer latency (nonpainful and repetitive painful) and augmented power (nonpainful and repetitive painful) were present among patients with chronic migraine. However, for painful tasks, alpha increases were observed among healthy controls. The oscillatory activity ratios between repetitive painful and painful tasks represented the frequency modulation and power habituation among healthy controls, respectively, but not among patients with chronic migraine. The classification models with oscillatory features exhibited high performance in differentiating patients with chronic migraine from healthy controls. Conclusion: Altered oscillatory characteristics of sensory processing and cortical modulation reflected the neuropathology of patients with chronic migraine. These characteristics can be reliably used to identify patients with chronic migraine using a machine-learning approach

(E)-1-(4-Chloro­phen­yl)-3-[4-(2,3,4,6-tetra-O-acetyl-β-d-allopyranos­yloxy)phen­yl]prop-2-en-1-one

The asymmetric unit of the title compound, C29H29ClO11, contains two independent mol­ecules of similar geometry, both adopting an E conformation about the C=C double bond. The dihedral angles formed by benzene rings are 10.73 (16) and 13.79 (18)°. The pyran­oside rings adopt a chair conformation. Intra­molecular C—H⋯O close contacts occur. The crystal packing is stabilized by inter­molecular C—H⋯O hydrogen bonds

Dopant Segregation Boosting High‐Voltage Cyclability of Layered Cathode for Sodium Ion Batteries

As a widely used approach to modify a material’s bulk properties, doping can effectively improve electrochemical properties and structural stability of various cathodes for rechargeable batteries, which usually empirically favors a uniform distribution of dopants. It is reported that dopant aggregation effectively boosts the cyclability of a Mg‐doped P2‐type layered cathode (Na0.67Ni0.33Mn0.67O2). Experimental characterization and calculation consistently reveal that randomly distributed Mg dopants tend to segregate into the Na‐layer during high‐voltage cycling, leading to the formation of high‐density precipitates. Intriguingly, such Mg‐enriched precipitates, acting as 3D network pillars, can further enhance a material’s mechanical strength, suppress cracking, and consequently benefit cyclability. This work not only deepens the understanding on dopant evolution but also offers a conceptually new approach by utilizing precipitation strengthening design to counter cracking related degradation and improve high‐voltage cyclability of layered cathodes.Improved cyclability of Mg‐doped P2‐NMM layered cathode is mainly due to suppression of cracking. Randomly distributed Mg dopants tend to segregate into precipitates during high‐voltage cycling, which can further strengthen the layered cathode and suppress cracking, leading to superior cycling stability at elevated voltage. Dopant precipitate is a new design concept to improve layered cathode cyclability.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153093/1/adma201904816.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153093/2/adma201904816-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153093/3/adma201904816_am.pd