Miracle-dz/UniFAR-FTUs huggingface dataset:
Iterative Pseudo-Labeling with Deep Feature Annotation and Confidence-Based Sampling

Training deep neural networks is challenging when large and annotated datasets are unavailable. Extensive manual annotation of data samples is time-consuming, expensive, and error-prone, notably when it needs to be done by experts. To address this issue, increased attention has been devoted to techniques that propagate uncertain labels (also called pseudo labels) to large amounts of unsupervised samples and use them for training the model. However, these techniques still need hundreds of supervised samples per class in the training set and a validation set with extra supervised samples to tune the model. We improve a recent iterative pseudo-labeling technique, Deep Feature Annotation (DeepFA), by selecting the most confident unsupervised samples to iteratively train a deep neural network. Our confidence-based sampling strategy relies on only dozens of annotated training samples per class with no validation set, considerably reducing user effort in data annotation. We first ascertain the best configuration for the baseline – a self-trained deep neural network – and then evaluate our confidence DeepFA for different confidence thresholds. Experiments on six datasets show that DeepFA already outperforms the self-trained baseline, but confidence DeepFA can considerably outperform the original DeepFA and the baseline.
Naturalness Evaluation of Natural Language Generation in Task-oriented Dialogues Using BERT

This paper presents an automatic method to evaluate the naturalness of natural language generation in dialogue systems. While this task was previously rendered through expensive and time-consuming human labor, we present this novel task of automatic naturalness evaluation of generated language. By fine-tuning the BERT model, our proposed naturalness evaluation method shows robust results and outperforms the baselines: support vector machines, bi-directional LSTMs, and BLEURT. In addition, the training speed and evaluation performance of naturalness model are improved by transfer learning from quality and informativeness linguistic knowledge.
P3FA: Unified Unicast/Multicast Forwarding with Low Egress Diversities

Multicast is an efficient way to realize one-to-many group communications in large-scale networks such as the Internet. However, the deployment of IP multicast services over the Internet has not been as rapid as expected and needed. Excepting the fatal defects in designing IPv4 address structure. Another main reason that contributes to this slow deployment is the lack of carrier-grade multicast-enabled switches and routers that can be as to scale as their unicast counterparts. Implementing a high-performance switch/router relies on a polynomial-time group membership query algorithm within the Packet Forwarding Engines (PFEs) to determine whether or not a packet is forwarded through an egress. Among these, Bloom filter (BF)-based and Residue Number System (RNS)-based are being considered as two representations of the membership query algorithms. However, both approaches suffer from some fatal weaknesses such as space and time inefficiencies, especially for a carrier-grade PFE with high port-density features. According to similar properties of the prime theorem, we propose a simplified forwarding scheme in this paper, named Per-Port Prime Filter Array (P3FA). The simulation results indicate that the P3FA can significantly improve space efficiencies under specific lower egress-diversities conditions. Under the same space constraints, compared with the SVRF, the multicast time efficiencies, the unicast time efficiency of the P3FA are respectively increased by 12x-17234x and 19x-2038x at a range of port-densities 16-1024, but at the expense of hardware cost, which increased by \r{ho}/2x. A PFE designer that attempts to adopt P3FA should trade-off between required performance and cost.
MicroRNA-301b-3p facilitates cell proliferation and migration in colorectal cancer by targeting HOXB1

ABSTRACT Previous studies revealed that miR-301b-3p was essential to the onset and development of several cancers, but the implied functions of miR-301b-3p in colorectal cancer (CRC) remained largely unclear. The current study is aimed to exploring the potential roles and possible mechanism of miR-301b-3p in CRC. The abundance of miR-301b-3p and HOXB1 in CRC clinical specimens and cell lines was verified using RT-qPCR. The CCK-8, colony formation, wound healing and transwell assays were adopted to evaluate cell proliferation and migration. The interactivity of miR-301b-3p and homeobox B1 (HOXB1) was identified using bioinformatics analysis and dual-luciferase reporter. The results of RT-qPCR indicated that miR-301b-3p was significantly upregulated in CRC clinical specimens and cell lines. Furthermore, overexpression of miR-301b-3p speeds up CRC cell proliferation and migration. Bioinformatics analysis and dual-luciferase reporter verified that HOXB1 acted as the downstream targeted mRNA. Furthermore, silencing of HOXB1 also obviously accelerated the proliferation and migration ability of CRC cells. miR-301b-3p facilitated cell proliferation and migration in CRC, which was partly reversed by overexpressing HOXB1. In conclusion, our findings demonstrated that miR-301b-3p facilitated CRC cell growth and migration via targeting HOXB1. Our results identified that miR-301b-3p served as a significant oncogene in CRC, which may provide a novel biomarker for diagnosis and therapeutic objective for CRC.
Barriers in access to services and information gaps by genders and key populations in the national Tuberculosis programme in Cambodia

ABSTRACT Approximately 34% of people with tuberculosis (TB) were undiagnosed in Cambodia in 2017. This study explored barriers in access to TB services and information gaps by genders and key populations in the Cambodian national TB programme. In 2017, we conducted a consensus and validation workshop, desk reviews, 19 in-depth interviews, and 30 focus group discussions with representatives of stakeholder groups, affected populations, and communities. Content analyses were performed for qualitative interviews. We employed the consensus development methods during the workshop to define and prioritise key populations. Key themes that inhibited access to TB services included the lack of knowledge, awareness, time and financial means, and gender-specific vulnerabilities. Systemic barriers included inconsistencies in policy and guideline implementation and lack of resources required for effective TB management. We did not find indications of coercive practices against women and key populations. However, stigma and discrimination did exist in healthcare institutions, the workplace, and the community. There were significant gaps in gender and key population-specific data and reporting systems at all levels. Data availability is vital for understanding gender and key population-specific gaps, and they should be duly utilised. Mechanisms to ensure equality and inclusivity are necessary to end TB in Cambodia.
Vision, challenges and opportunities for a Plant Cell Atlas

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.
A comparison of trans-fistula contrast-enhanced endoanal ultrasound and MRI in the diagnosis of anal fistula.

BACKGROUND Many hospitals favor magnetic resonance imaging (MRI) as the preferred diagnostic method to detect anal fistula, trans-fistula contrast-enhanced ultrasound (CEUS) for the diagnosis of anal fistula have attracted the attention of investigators worldwide. This study aimed to investigate the efficacy of trans-fistula contrast-enhanced endoanal ultrasound (CEUS) and magnetic resonance imaging (MRI) in the diagnosis of anal fistula. METHODS Ninety-eight patients undergoing trans-fistula CEUS and MRI were retrospectively analyzed. The fistulous trend and positional relation between the fistula, levator ani muscle, and sphincter (Parks classification), as well as the numbers of fistulous branches, number and position of the fistula, and distance between internal opening and anal edge were recorded. These parameters were compared with the postoperative results. RESULTS There were no significant statistical differences (P>0.05) in the accuracy rates of trans-fistula CEUS and MRI, respectively, in terms of Parks classification (90.82%, 92.86%), branches (89.19%, 81.08%), internal openings (92.68%, 89.43%), and internal openings ≥3 cm from the anal edge (85.71%, 92.86%). However, we observed a significant difference in terms of internal openings <3 cm from the anal edge (96.30%, 87.65%) (P=0.043). CONCLUSIONS Although both methods exhibited a perfect accuracy rate in diagnosing anal fistula, trans-fistula CEUS displayed superior diagnostic value for internal openings <3 cm from the anal edge, and could provide reliable pre-operative evidence.
Meningeal lymphatic endothelial cells fulfill scavenger endothelial cell function and cooperate with microglia in waste removal from the brain

Brain lymphatic endothelial cells (BLECs) constitute a group of loosely connected endothelial cells that reside within the meningeal layer of the zebrafish brain without forming a vascular tubular system. BLECs have been shown to readily endocytose extracellular cargo molecules from the brain parenchyma, however, their functional relevance in relation to microglia remains enigmatic. We here compare their functional uptake efficiency for several macromolecules and bacterial components with microglia in a qualitative and quantitative manner in 5‐day‐old zebrafish embryos. We find BLECs to be significantly more effective in the uptake of proteins, polysaccharides and virus particles as compared to microglia, while larger particles like bacteria are only ingested by microglia but not by BLECs, implying a clear distribution of tasks between the two cell types in the brain area. In addition, we compare BLECs to the recently discovered scavenger endothelial cells (SECs) of the cardinal vein and find them to accept an identical set of substrate molecules. Our data identifies BLECs as the first brain‐associated SEC population in vertebrates, and demonstrates that BLECs cooperate with microglia to remove particle waste from the brain.
SS-MLA: a semisupervised method for multi-label annotation of remotely sensed images

Abstract. Recent technological advancements in satellite imagery have increased the production of remotely sensed images. Therefore, developing efficient methods for annotating these images has gained popularity. Most of the current state-of-the-art methods are based on supervised machine learning techniques. We propose a method called semisupervised multi-label annotizer (SS-MLA) that adapts vector-quantized temporal associative memory to annotate remotely sensed images. One of the advantages of SS-MLA over the supervised methods is that it extracts features not only from the given sample but also from similar samples that are previously seen without using an explicit attention mechanism. Thus SS-MLA enhances the learning efficiency of the training process. We conduct extensive performance comparisons with five different methods in the literature over four datasets. The comparison results indicate the success of the proposed method over the existing ones: SS-MLA generates the best results in 7 out of 11 comparisons.
Evaluation of the effects of chlorhexidine digluconate with and without cBD103 or cCath against multidrug‐resistant clinical isolates of Staphylococcus pseudintermedius

Background Because of the increased incidence of multidrug‐resistant (MDR) bacteria, the use of disinfectants over antibiotics has been encouraged. However, the interactions between disinfectants and host local immunity are poorly understood. Objective To assess the effects of chlorhexidine digluconate (Chx), with and without selected host defence peptides (HDPs), against MDR Staphylococcus pseudintermedius (MDR‐SP). Methods and materials Ten clinical isolates of MDR‐SP were tested, using a modified microbroth dilution method. Four two‐fold dilutions of 2% Chx and 1 μg/mL the HDPs synthetic canine β‐defensin 103 (cBD103) or cathelicidin (cCath) were tested alone or in combination. Colony counts after 5, 15, 30 and 60 min, and a minimum inhibitory concentration (MIC) after 24 h were recorded. Friedman followed by Dunn’s multiple comparison tests with significance of P < 0.05 were used for statistical analysis. Synergy, additivity/neutrality or antagonism were calculated. Results Growth was not inhibited by either HDP alone. An MIC of 0.312 μg/mL Chx was achieved for nine of the isolates. One isolate had an MIC of 0.078 μg/mL Chx. A MIC90 (in nine of 10 isolates) of 0.312 µg/mL was seen for Chx in combination with either HDP. Synergy was seen in the combination Chx/cCath used at the highest concentrations of Chx (0.624 µg/mL and 0.312 µg/mL) after 30 and 60 min incubation. Additivity/neutrality was seen for most of the other concentrations and times of incubation. Conclusions and clinical importance These results suggest a synergistic/additive effect between Chx and HDPs in dogs. Further studies evaluating the mechanisms behind this effect are needed.
Trivalent Subunit Vaccine Candidates for COVID-19 and Their Delivery Devices

The COVID-19 pandemic highlights the need for platform technologies enabling rapid development of vaccines for emerging viral diseases. The current vaccines target the SARS-CoV-2 spike (S) protein and thus far have shown tremendous efficacy. However, the need for cold-chain distribution, a prime-boost administration schedule, and the emergence of variants of concern (VOCs) call for diligence in novel SARS-CoV-2 vaccine approaches. We studied 13 peptide epitopes from SARS-CoV-2 and identified three neutralizing epitopes that are highly conserved among the VOCs. Monovalent and trivalent COVID-19 vaccine candidates were formulated by chemical conjugation of the peptide epitopes to cowpea mosaic virus (CPMV) nanoparticles and virus-like particles (VLPs) derived from bacteriophage Qβ. Efficacy of this approach was validated first using soluble vaccine candidates as solo or trivalent mixtures and subcutaneous prime-boost injection. The high thermal stability of our vaccine candidates allowed for formulation into single-dose injectable slow-release polymer implants, manufactured by melt extrusion, as well as microneedle (MN) patches, obtained through casting into micromolds, for prime-boost self-administration. Immunization of mice yielded high titers of antibodies against the target epitope and S protein, and data confirms that antibodies block receptor binding and neutralize SARS-CoV and SARS-CoV-2 against infection of human cells. We present a nanotechnology vaccine platform that is stable outside the cold-chain and can be formulated into delivery devices enabling single administration or self-administration. CPMV or Qβ VLPs could be stockpiled, and epitopes exchanged to target new mutants or emergent diseases as the need arises.
Two novel alleles on Fucosyltransferase 2 from northern Thai para‐Bombay family and computational prediction on mutation effect

Major characteristics of the para‐Bombay phenotype are the absence of ABH antigens on red blood cells due to fucosyltransferase 1 (FUT1) gene mutation and the presence of these antigens in body secretions due to the active fucosyltransferase 2 (FUT2) gene. An ABO blood group discrepancy can be identified via serological testing, and additional tests can be performed for confirmation. This study aimed to resolve the ABO discrepancy and report two novel alleles on the FUT2 gene in northern Thai para‐Bombay families.
Optical properties of monolayer BeC under an external electric field: A DFT approach

Abstract BeC, a two-dimensional hypercoordinated nanostructure carbon compound, has been the focus of the nanoworld because of its high value of dynamical stability, in-plane stiffness, carrier mobility and the existence of band gap. In this work, we have explored the electronic and the optical properties of this material under the influence of static external perpendicular electric field within the framework of density functional theory. Under the influence of a uniform electric field, the band gap changes within the meV range. The electron energy loss function study reveals that this material has optical band gaps which remain constant irrespective of the applied electric field strength. The optical property also exhibits interesting features when the applied field strength is within 0.4–0.5 V/Å. We have also tried to explain the optical data from the respective band structures and thus paving the way to understand qualitatively the signature of the optical anisotropy from the birefringence study.
Validation of the Seattle Suprastomal Safety Score (5S): A Novel Measure in Pediatric Tracheostomy-Dependent Patients

Objective Suprastomal collapse and granulation are common sequelae of pediatric tracheostomy. We present the first measure of suprastomal obstructive pathology, the Seattle Suprastomal Safety Score (5S), an instrument with 2 domains: collapse and granulation. Study Design Cross-sectional repeated testing survey. Setting Electronic survey. Methods A library of images was assembled from still pictures of the suprastomal area in 50 patients who previously underwent trachea-bronchoscopy at a quaternary children’s hospital. Five pediatric otolaryngologists and 2 pediatric pulmonologists reviewed the images in random, blinded fashion and provided 5S scores. Participants repeated this process 2 to 4 weeks later. Interrater agreement was calculated with an intraclass correlation coefficient (ICC) with a 2-way random-effects model and Fleiss’s κ. Intrarater agreement was measured with an ICC using a 2-way mixed-effects model as well as with test-retest correlations using Spearman rank coefficient. All measures were performed separately on collapse and granulation domains. Results ICC for interrater agreement was 0.88 (95% CI, 0.82-0.93) for collapse and 0.97 (95% CI, 0.96-0.98) for granulation, indicating almost perfect agreement. Fleiss’s κ demonstrated moderate agreement for collapse and almost perfect agreement for granulation. ICC for intrarater agreement was 0.95 (95% CI, 0.93-0.97) and 0.99 (95% CI, 0.98-0.99) for collapse and granulation, respectively, indicating almost perfect agreement. Spearman rank correlation for test-retest demonstrated substantial agreement for collapse and almost perfect agreement for granulation. Conclusion The 5S demonstrates excellent interrater and intrarater agreement, making it highly reliable as a novel measure of suprastomal collapse and granulation in tracheostomy-dependent pediatric patients.
The genome sequence provides insights into salt tolerance of Achnatherum splendens (Gramineae), a constructive species of alkaline grassland

Summary Achnatherum splendens Trin. (Gramineae) is a constructive species of the arid grassland ecosystem in Northwest China and is a major forage grass. It has good tolerance of salt and drought stress in alkaline habitats. Here, we report its chromosome‐level genome, determined through a combination of Illumina HiSeq sequencing, PacBio sequencing and Hi‐C technology. The final assembly of the ~1.17 Gb genome sequence had a super‐scaffold N50 of 40.3 Mb. A total of 57 374 protein‐coding genes were annotated, of which 54 426 (94.5%) genes have functional protein annotations. Approximately 735 Mb (62.37%) of the assembly were identified as repetitive elements, and among these, LTRs (40.53%) constitute the highest proportion, having made a major contribution to the expansion of genome size in A. splendens. Phylogenetic analysis revealed that A. splendens diverged from the Brachypodium distachyon–Hordeum vulgare–Aegilops tauschii subclade around 37 million years ago (Ma) and that a clade comprising these four species diverged from the Phyllostachys edulis clade ~47 Ma. Genomic synteny indicates that A. splendens underwent an additional species‐specific whole‐genome duplication (WGD) 18–20 Ma, which further promoted an increase in copies of numerous saline–alkali‐related gene families in the A. splendens genome. By transcriptomic analysis, we further found that many of these duplicated genes from this extra WGD exhibited distinct functional divergence in response to salt stress. This WGD, therefore, contributed to the strong resistance to salt stress and widespread arid adaptation of A. splendens.
Explaining Compositional Semantics in Neural Networks via Neighborhood Sampling and Decomposition

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Deep Learning Predicts Interval and Screening-detected Cancer from Screening Mammograms: A Case-Case-Control Study in 6369 Women.

Background The ability of deep learning (DL) models to classify women as at risk for either screening mammography-detected or interval cancer (not detected at mammography) has not yet been explored in the literature. Purpose To examine the ability of DL models to estimate the risk of interval and screening-detected breast cancers with and without clinical risk factors. Materials and Methods This study was performed on 25 096 digital screening mammograms obtained from January 2006 to December 2013. The mammograms were obtained in 6369 women without breast cancer, 1609 of whom developed screening-detected breast cancer and 351 of whom developed interval invasive breast cancer. A DL model was trained on the negative mammograms to classify women into those who did not develop cancer and those who developed screening-detected cancer or interval invasive cancer. Model effectiveness was evaluated as a matched concordance statistic (C statistic) in a held-out 26% (1669 of 6369) test set of the mammograms. Results The C statistics and odds ratios for comparing patients with screening-detected cancer versus matched controls were 0.66 (95% CI: 0.63, 0.69) and 1.25 (95% CI: 1.17, 1.33), respectively, for the DL model, 0.62 (95% CI: 0.59, 0.65) and 2.14 (95% CI: 1.32, 3.45) for the clinical risk factors with the Breast Imaging Reporting and Data System (BI-RADS) density model, and 0.66 (95% CI: 0.63, 0.69) and 1.21 (95% CI: 1.13, 1.30) for the combined DL and clinical risk factors model. For comparing patients with interval cancer versus controls, the C statistics and odds ratios were 0.64 (95% CI: 0.58, 0.71) and 1.26 (95% CI: 1.10, 1.45), respectively, for the DL model, 0.71 (95% CI: 0.65, 0.77) and 7.25 (95% CI: 2.94, 17.9) for the risk factors with BI-RADS density (b rated vs non-b rated) model, and 0.72 (95% CI: 0.66, 0.78) and 1.10 (95% CI: 0.94, 1.29) for the combined DL and clinical risk factors model. The P values between the DL, BI-RADS, and combined model's ability to detect screen and interval cancer were . 99, . 002, and . 03, respectively. Conclusion The deep learning model outperformed in determining screening-detected cancer risk but underperformed for interval cancer risk when compared with clinical risk factors including breast density. © RSNA, 2021 See also the editorial by Bae and Kim in this issue.