Nondestructive Near-infrared Identification of Hawthorn Fruit Cultivars Based on Natural Language Processing

Hawthorn fruits of different varieties have varied nutritional composition, sensory properties etc., thus required for different processing for product development. Due to the limitations of traditional analytical methods of time-consuming, destructive sample preparation, and high cost ect., non-destructive techniques for variety identification are needed which would benefit for large scale production of foods with hawthorn fruits. In this study, a total of 240 hawthorn fruit samples from four different varieties were subjected for near-infrared spectroscopy analysis and the collected spectral data were pre-processed by different algorithms. In order to achieve non-destructive identification of hawthorn varieties, natural language processing (NLP) model was applied for data analysis, including long short-term memory (LSTM), gated recurrent unit (GRU) neural network, logistic regression, native Bayes, decision trees, and k-nearest neighbors. The results showed that the two deep learning models both had the best discrimination effect on the spectral preprocessed by principal component analysis (PCA) with the accuracy of the validation set and test set reached 99.46%±0.00% and 100%±0.00%. While, the logistic regression model showed excellent discrimination ability for hawthorn fruit spectra but poor discrimination ability for the difference of second order (D2) pretreatment spectra (accuracy of 96.65% in the validation set and 89.58% in the test set). The naive Bayes model also showed excellent discrimination effect on the spectra processed by PCA, and the accuracy of the validation set was 95.65%, and the accuracy of the test set was 95.83%. Results gained in this study confirmed the feasibility of applying NLP to the near-infrared non-destructive identification of hawthorn fruits

Regulating the coordination mode of Ti atoms in the beta zeolite framework to enhance the 1-Hexene Epoxidation

Regulating the Ti active sites in titanosilicates with different coordination modes is of prime scientific and industrial significance to the rational design of efficient catalysts for olefin epoxidation. In this study, the Ti species in Ti-beta zeolite catalysts (open/closed tetra-coordinated Ti sites, hexa-coordinated Ti species, and TiO2) were keenly controlled via the dealumination-metallization approach. By multiple characterizations, kinetics study, and multivariate model analysis, it is found that the open tetra-coordinated framework Ti(OH)(OSi)3 species contribute more to the catalytic performance for 1-hexene epoxidation with H2O2. Moreover, the Ti-beta with rich open tetra-coordinated Ti(OH)(OSi)3 species showed significantly improved reaction performance (TON: 401, conversion: 64%, selectivity: 98%, H2O2 efficiency: 97%) with lower apparent activation energy. This study not only opens up new prospects for the design of efficient titanosilicates by modifying Ti microenvironments but also proposes the strategy to improve the content of open tetra-coordinated Ti sites

The Relationship Between Cognitive Dysfunction and Symptom Dimensions Across Schizophrenia, Bipolar Disorder, and Major Depressive Disorder

Background: Cognitive dysfunction is considered a core feature among schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Despite abundant literature comparing cognitive dysfunction among these disorders, the relationship between cognitive dysfunction and symptom dimensions remains unclear. The study aims are a) to identify the factor structure of the BPRS-18 and b) to examine the relationship between symptom domains and cognitive function across SZ, BD, and MDD.Methods: A total of 716 participants [262 with SZ, 104 with BD, 101 with MDD, and 249 healthy controls (HC)] were included in the study. One hundred eighty participants (59 with SZ, 23 with BD, 24 with MDD, and 74 HC) completed the MATRICS Consensus Cognitive Battery (MCCB), and 507 participants (85 with SZ, 89 with BD, 90 with MDD, and 243 HC) completed the Wisconsin Card Sorting Test (WCST). All patients completed the Brief Psychiatric Rating Scale (BPRS).Results: We identified five BPRS exploratory factor analysis (EFA) factors (“affective symptoms,” “psychosis,” “negative/disorganized symptoms,” “activation,” and “noncooperation”) and found cognitive dysfunction in all of the participant groups with psychiatric disorders. Negative/disorganized symptoms were the most strongly associated with cognitive dysfunctions across SZ, BD, and MDD.Conclusions: Our findings suggest that cognitive dysfunction severity relates to the negative/disorganized symptom domain across SZ, BD, and MDD, and negative/disorganized symptoms may be an important target for effective cognitive remediation in SZ, BD, and MDD

Precise Measurements of Branching Fractions for Ds+D_s^+ Meson Decays to Two Pseudoscalar Mesons

We measure the branching fractions for seven $D_{s}^{+}$ two-body decays to pseudo-scalar mesons, by analyzing data collected at $\sqrt{s}=4.178\sim4.226$ GeV with the BESIII detector at the BEPCII collider. The branching fractions are determined to be $\mathcal{B}(D_s^+\to K^+\eta^{\prime})=(2.68\pm0.17\pm0.17\pm0.08)\times10^{-3}$, $\mathcal{B}(D_s^+\to\eta^{\prime}\pi^+)=(37.8\pm0.4\pm2.1\pm1.2)\times10^{-3}$, $\mathcal{B}(D_s^+\to K^+\eta)=(1.62\pm0.10\pm0.03\pm0.05)\times10^{-3}$, $\mathcal{B}(D_s^+\to\eta\pi^+)=(17.41\pm0.18\pm0.27\pm0.54)\times10^{-3}$, $\mathcal{B}(D_s^+\to K^+K_S^0)=(15.02\pm0.10\pm0.27\pm0.47)\times10^{-3}$, $\mathcal{B}(D_s^+\to K_S^0\pi^+)=(1.109\pm0.034\pm0.023\pm0.035)\times10^{-3}$, $\mathcal{B}(D_s^+\to K^+\pi^0)=(0.748\pm0.049\pm0.018\pm0.023)\times10^{-3}$, where the first uncertainties are statistical, the second are systematic, and the third are from external input branching fraction of the normalization mode $D_s^+\to K^+K^-\pi^+$. Precision of our measurements is significantly improved compared with that of the current world average values

Serum MicroRNA Expression Profile Distinguishes Enterovirus 71 and Coxsackievirus 16 Infections in Patients with Hand-Foot-and-Mouth Disease

Altered circulating microRNA (miRNA) profiles have been noted in patients with microbial infections. We compared host serum miRNA levels in patients with hand-foot-and-mouth disease (HFMD) caused by enterovirus 71 (EV71) and coxsackievirus 16 (CVA16) as well as in other microbial infections and in healthy individuals. Among 664 different miRNAs analyzed using a miRNA array, 102 were up-regulated and 26 were down-regulated in sera of patients with enteroviral infections. Expression levels of ten candidate miRNAs were further evaluated by quantitative real-time PCR assays. A receiver operating characteristic (ROC) curve analysis revealed that six miRNAs (miR-148a, miR-143, miR-324-3p, miR-628-3p, miR-140-5p, and miR-362-3p) were able to discriminate patients with enterovirus infections from healthy controls with area under curve (AUC) values ranged from 0.828 to 0.934. The combined six miRNA using multiple logistic regression analysis provided not only a sensitivity of 97.1% and a specificity of 92.7% but also a unique profile that differentiated enterovirial infections from other microbial infections. Expression levels of five miRNAs (miR-148a, miR-143, miR-324-3p, miR-545, and miR-140-5p) were significantly increased in patients with CVA16 versus those with EV71 (p<0.05). Combination of miR-545, miR-324-3p, and miR-143 possessed a moderate ability to discrimination between CVA16 and EV71 with an AUC value of 0.761. These data indicate that sera from patients with different subtypes of enteroviral infection express unique miRNA profiles. Serum miRNA expression profiles may provide supplemental biomarkers for diagnosing and subtyping enteroviral HFMD infections

A Droplet-Based Microfluidic Electrical Lysis Device using 3D Gallium Electrodes

Most biological applications require access to the cell’s components and machinery and therefore a cell lysis step is required. Droplet-based microfluidics has the ability to perform millions of distinct biological assays on individual cells. Typically, droplet-based cell lysis is achieved in presence of chemicals, which is not compatible with most subsequent analysis. Electrical lysis is a rapid, simple, and compatible method to extract intracellular contents. However, very limited studies reported droplet-based electrical lysis. To fill the blank of this topic, we designed a droplet-based device with 3D liquid metal (gallium) electrodes configuration to achieve electrical lysis. This platform has been validated as a robust electrical lysis device with a lysis efficiency of ~ 99 %. The device is further examined for extracting plasmid DNA from E. coli cells. We propose that this system has the potential to be used for rapid cell lysis and extracting intracellular components on chip. In near future, CRISPR-based DNA assays will be performed to show the system can be utilized as a rapid detection device for specific biological application

Regulating the Expansion Characteristics of Cementitious Materials Using Blended MgO-Type Expansive Agent

To promote the application of MgO-type expansive agents (MEAs), the expansion stresses produced by compacted MEAs with different activities cured in water at 40 &#176;C were measured using a self-designed expansion stress test apparatus. Based on these, different MEAs were divided into the early-type MgO expansive agent and the late-type MgO expansive agent classifications according to the stress curves of compacted MEAs. The two types of MEAs were blended with each other at different ratios and added into cement pastes. Results indicated that the expansion of the cement pastes added with blended MEAs lasted from the beginning to 200 days later, and the expansion characteristics can be regulated by adjusting the blending ratio of MEAs and the choice of types of MEAs. The results suggest that the expansion of MEAs can be improved by using blended MEAs in practical applications