LED-Induced Fluorescence System for Tea Classification and Quality Assessment

A fluorescence system is developed by using several light emitting diodes (LEDs) with different wavelengths as excitation light sources. The fluorescence detection head consists of multi LED light sources and a multimode fiber for fluorescence collection, where the LEDs and the corresponding filters can be easily chosen to get appropriate excitation wavelengths for different applications. By analyzing fluorescence spectra with the principal component analysis method, the system is utilized in the classification of four types of green tea beverages and two types of black tea beverages. Qualities of the Xihu Longjing tea leaves of different grades, as well as the corresponding liquid tea samples, are studied to further investigate the ability and application of the system in the evaluation of classification/quality of tea and other foods

Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering

Visual question answering (VQA) is challenging not only because the model has to handle multi-modal information, but also because it is just so hard to collect sufficient training examples -- there are too many questions one can ask about an image. As a result, a VQA model trained solely on human-annotated examples could easily over-fit specific question styles or image contents that are being asked, leaving the model largely ignorant about the sheer diversity of questions. Existing methods address this issue primarily by introducing an auxiliary task such as visual grounding, cycle consistency, or debiasing. In this paper, we take a drastically different approach. We found that many of the "unknowns" to the learned VQA model are indeed "known" in the dataset implicitly. For instance, questions asking about the same object in different images are likely paraphrases; the number of detected or annotated objects in an image already provides the answer to the "how many" question, even if the question has not been annotated for that image. Building upon these insights, we present a simple data augmentation pipeline SimpleAug to turn this "known" knowledge into training examples for VQA. We show that these augmented examples can notably improve the learned VQA models' performance, not only on the VQA-CP dataset with language prior shifts but also on the VQA v2 dataset without such shifts. Our method further opens up the door to leverage weakly-labeled or unlabeled images in a principled way to enhance VQA models. Our code and data are publicly available at https://github.com/heendung/simpleAUG.Comment: Accepted to EMNLP 202

The impact of metabolic overweight/obesity phenotypes on unplanned readmission risk in patients with COPD: a retrospective cohort study

Background: There is an inconsistent association between overweight/obesity and chronic obstructive pulmonary disease (COPD). Considering that different metabolic characteristics exist among individuals in the same body mass index (BMI) category, the classification of overweight/obesity based on metabolic status may facilitate the risk assessment of COPD. Our study aimed to explore the relationship between metabolic overweight/obesity phenotypes and unplanned readmission in patients with COPD.Methods: We conducted a retrospective cohort study using the Nationwide Readmissions Database (NRD). According to metabolic overweight/obesity phenotypes, patients were classified into four groups: metabolically healthy non-overweight/obesity (MHNO), metabolically unhealthy non-overweight/obesity (MUNO), metabolically healthy with overweight/obesity (MHO), and metabolically unhealthy with overweight/obesity (MUO). The primary outcome was unplanned readmission to hospital within 30 days of discharge from index hospitalization. Secondary outcomes included in-hospital mortality, length of stay (LOS) and total charges of readmission within 30 days.Results: Among 1,445,890 patients admitted with COPD, 167,156 individuals were unplanned readmitted within 30 days. Patients with the phenotype MUNO [hazard ratio (HR), 1.049; 95%CI, 1.038–1.061; p < 0.001] and MUO (HR, 1.061; 95%CI, 1.045–1.077; p < 0.001) had a higher readmission risk compared with patients with MHNO. But in elders (≥65yr), MHO also had a higher readmission risk (HR, 1.032; 95%CI, 1.002–1.063; p = 0.039). Besides, the readmission risk of COPD patients with hyperglycemia or hypertension regardless of overweight/obesity increased (p < 0.001).Conclusion: In patients with COPD, overweight/obesity alone had little effect on unplanned readmission, whereas metabolic abnormalities regardless of overweight/obesity were associated with an increased risk of unplanned readmission. Among the metabolic abnormalities, particular attention should be paid to hyperglycemia and hypertension. But in elders (≥65yr) overweight/obesity and metabolic abnormalities independently exacerbated the adverse outcomes

Survey and Visual Detection of Zaire ebolavirus in Clinical Samples Targeting the Nucleoprotein Gene in Sierra Leone

Ebola virus (EBOV) can lead to severe hemorrhagic fever with a high risk of death in humans and other primates. To guide treatment and prevent spread of the viral infection, a rapid and sensitive detection method is required for clinical samples. Here, we described and evaluated a reverse transcription loop-mediated isothermal amplification (RT-LAMP) method to detect Zaire ebolavirus using the nucleoprotein gene (NP) as a target sequence. Two different techniques were used, a calcein/Mn2+ complex chromogenic method and real-time turbidity monitoring. The RT-LAMP assay detected the NP target sequence with a limit of 4.56 copies/μL within 45 min under 61°C, a similar even or increase in sensitivity than that of real-time reverse transcription-polymerase chain reaction (RT-PCR). Additionally, all pseudoviral particles or non- Zaire EBOV genomes were negative for LAMP detection, indicating that the assay was highly specific for EBOV. To appraise the availability of the RT-LAMP method for use in clinical diagnosis of EBOV, of 417 blood or swab samples collected from patients with clinically suspected infections in Sierra Leone, 307 were identified for RT-LAMP-based surveillance of EBOV. Therefore, the highly specific and sensitive RT-LAMP method allows the rapid detection of EBOV, and is a suitable tool for clinical screening, diagnosis, and primary quarantine purposes

Time Series Gene Expression Profiling and Temporal Regulatory Pathway Analysis of Angiotensin II Induced Atrial Fibrillation in Mice

Background/Aim: Angiotensin II (Ang II) and hypertension play critical roles in the pathogenesis of the atrial remodeling that contributes to atrial fibrillation (AF). However, the gene expression profiles and signaling pathways in atria during the development of AF induced by Ang II remain unknown.Methods: Wild-type male mice (C57BL/6 background, 10 weeks old) were administered an infusion of Ang II (2000 ng/kg/min) using an osmotic pump for 1, 2, and 3 weeks. Blood pressure (BP) was measured by the tail-cuff method. AF was induced and recorded. Atrial enlargement and remodeling were examined by echocardiography and Masson’s trichrome staining. Time-series microarray analyses were conducted to examine gene expression profiles and pathways.Results: Ang II infusion resulted in marked elevation of systolic BP, increased AF incidence and duration, atrial enlargement, fibrosis, and atrial infiltration of myofibroblasts and F4/80-positive macrophages in a time-dependent manner. Microarray results showed that 1,719 genes were differentially expressed in the atrium at weeks 1, 2, and 3 after Ang II infusion. Gene ontology showed that these genes participate mainly in immune system processes, and regulation of cell migration, cell adhesion, complement activation, and the inflammatory response. Significant pathways included lysosomal and phagosomal pathways, which are involved in antigen processing and presentation, as well as chemokine signaling, and extracellular matrix–receptor interaction, which are known to play important roles in Ang II-induced AF. Moreover, these differentially expressed genes were classified into 50 profiles by hierarchical cluster analysis. Of these, eight profiles were significant and contained a total of 1,157 genes. Gene co-expression network analysis identified that Pik3cg (also known as phosphoinositide-3-kinase regulatory subunit 3) was localized in the core of the gene network, and was the most highly expressed among the Pik3 isoforms at different time points.Conclusion: The present findings revealed that many genes are involved in Ang II-induced AF, and highlighted that Pik3cg may play a central role in this disease