Characteristics of molecular changes in lespedeza plants after seeds been flown on satellite

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Boosting Multi-Modal E-commerce Attribute Value Extraction via Unified Learning Scheme and Dynamic Range Minimization

With the prosperity of e-commerce industry, various modalities, e.g., vision and language, are utilized to describe product items. It is an enormous challenge to understand such diversified data, especially via extracting the attribute-value pairs in text sequences with the aid of helpful image regions. Although a series of previous works have been dedicated to this task, there remain seldomly investigated obstacles that hinder further improvements: 1) Parameters from up-stream single-modal pretraining are inadequately applied, without proper jointly fine-tuning in a down-stream multi-modal task. 2) To select descriptive parts of images, a simple late fusion is widely applied, regardless of priori knowledge that language-related information should be encoded into a common linguistic embedding space by stronger encoders. 3) Due to diversity across products, their attribute sets tend to vary greatly, but current approaches predict with an unnecessary maximal range and lead to more potential false positives. To address these issues, we propose in this paper a novel approach to boost multi-modal e-commerce attribute value extraction via unified learning scheme and dynamic range minimization: 1) Firstly, a unified scheme is designed to jointly train a multi-modal task with pretrained single-modal parameters. 2) Secondly, a text-guided information range minimization method is proposed to adaptively encode descriptive parts of each modality into an identical space with a powerful pretrained linguistic model. 3) Moreover, a prototype-guided attribute range minimization method is proposed to first determine the proper attribute set of the current product, and then select prototypes to guide the prediction of the chosen attributes. Experiments on the popular multi-modal e-commerce benchmarks show that our approach achieves superior performance over the other state-of-the-art techniques

Chiral Phonons in Chiral Materials

The concept of chirality makes ubiquitous appearance in nature. Particularly, both a structure and its collective excitations may acquire well defined chiralities. In this work, we reveal an intrinsic connection between the chiralities of a crystal structure and its phonon excitations. We show that the phonon chirality and its propagation direction are strongly coupled with the lattice chirality, which will be reversed when a chiral lattice is switched to its enantiomorph. In addition, distinct from achiral lattices, propagating chiral phonons exist for chiral crystals also on the principal axis through the $\Gamma$ point, which strengthens its relevance to various physical processes. We demonstrate our theory with a 1D helix-chain model and with a concrete and important 3D material, the $\alpha$-quartz. We predict a chirality diode effect in these systems, namely, at certain frequency window, a chiral signal can only pass the system in one way but not the other, specified by the system chirality. Experimental setups to test our theory are proposed. Our work discovers fundamental physics of chirality coupling between different levels of a system, and the predicted effects will provide a new way to control thermal transport and design information devices.Comment: 5 pages, 5 figure

Electrochemical Investigation of Calcium Substituted Monoclinic Li3_3 V2_2(PO4_4)3_3 Negative Electrode Materials for Sodium‐ and Potassium‐Ion Batteries

Herein, the electrochemical properties and reaction mechanism of Li$_{3‒2x}$Ca$_x$V$_2$(PO$_4$)$_3$/C (x = 0, 0.5, 1, and 1.5) as negative electrode materials for sodium-ion/potassium-ion batteries (SIBs/PIBs) are investigated. All samples undergo a mixed contribution of diffusion-controlled and pseudocapacitive-type processes in SIBs and PIBs via Trasatti Differentiation Method, while the latter increases with Ca content increase. Among them, Li$_3$V$_2$(PO$_4$)$_3$/C exhibits the highest reversible capacity in SIBs and PIBs, while Ca$_{1.5}$V$_2$(PO$_4$)$_3$/C shows the best rate performance with a capacity retention of 46% at 20 C in SIBs and 47% at 10 C in PIBs. This study demonstrates that the specific capacity of this type of material in SIBs and PIBs does not increase with the Ca-content as previously observed in lithium-ion system, but the stability and performance at a high C-rate can be improved by replacing Li$^+$ with Ca$^{2+}$. This indicates that the insertion of different monovalent cations (Na$^+$/K$^+$) can strongly influence the redox reaction and structure evolution of the host materials, due to the larger ion size of Na$^+$ and K$^+$ and their different kinetic properties with respect to Li$^+$. Furthermore, the working mechanism of both LVP/C and Ca$_{1.5}$V$_2$(PO$_4$)$_3$/C in SIBs are elucidated via in operando synchrotron diffraction and in operando X-ray absorption spectroscopy

A method to prolong lithium-ion battery life during the full life cycle

Extended lifetime of lithium-ion batteries decreases economic costs and environmental burdens in achieving sustainable development. Cycle life tests are conducted on 18650-type commercial batteries, exhibiting nonlinear and inconsistent degradation. The accelerated fade dispersion is proposed to be triggered by the evolution of an additional potential of the anode during cycling as measured vs. Li$^+$/Li. A method to prolong the battery cycle lifetime is proposed, in which the lower cutoff voltage is raised to 3 V when the battery reaches a capacity degradation threshold. The results demonstrate a 38.1% increase in throughput at 70% of their beginning of life (BoL) capacity. The method is applied to two other types of lithium-ion batteries. A cycle lifetime extension of 16.7% and 33.7% is achieved at 70% of their BoL capacity, respectively. The proposed method enables lithium-ion batteries to provide long service time, cost savings, and environmental relief while facilitating suitable second-use applications

Bibliometric analysis of post-traumatic stress disorder in forensic medicine: Research trends, hot spots, and prospects

BackgroundPost-traumatic stress disorder (PTSD) has various risk factors, complex pathogenesis, and diverse symptoms, and is often comorbid with other injuries and diseases, making forensic diagnosis difficult.MethodsTo explore the current research status and trends of PTSD, we used the Web of Science Core Collection databases to screen PTSD-related literature published between 2010 and 2021 and CiteSpace to perform bibliometric analysis.ResultsIn recent years, PTSD-related research has grown steadily. The countries and institutions with the most research results were the United States and England, and King’s College London and Boston University, respectively. Publications were identified from 2,821 different journals, including 13 forensic-related journals, but the journal distribution was relatively scattered and there was a lack of professional core journals. Keyword co-occurrence and clustering identified many hot topics; “rat model,” “mental health,” and “satisfaction” were the topics most likely to have a clear effect on future research. Analysis extracted nine turning points from the literature that suggested that neural network centers, the hypothalamic–pituitary–adrenal axis, and biomarkers were new research directions. It was found that COVID-19 can cause severe psychological stress and induce PTSD, but the relationship needs further study. The literature on stress response areas and biomarkers has gradually increased over time, but specific systemic neural brain circuits and biomarkers remain to be determined.ConclusionThere is a need to expand the collection of different types of biological tissue samples from patients with different backgrounds, screen PTSD biomarkers and molecular targets using multi-omics and molecular biology techniques, and establish PTSD-related molecular networks. This may promote a systematic understanding of the abnormal activation of neural circuits in patients with PTSD and help to establish a personalized, accurate, and objective forensic diagnostic standard

Validation of the Oxford classification of IgA nephropathy for pediatric patients from China

BACKGROUND: The Oxford classification of IgA nephropathy (IgAN) provides a useful tool for prediction of renal prognosis. However, the application of this classification in children with IgAN needs validation in different patient populations. METHODS: A total of 218 children with IgAN from 7 renal centers in China were enrolled. The inclusion criteria was similar to the original Oxford study. RESULTS: There were 98 patients (45%) with mesangial proliferation (M1), 51 patients (23%) with endocapillary proliferation (E1), 136 patients (62%) with segmental sclerosis/adhesion lesion (S1), 13 patients (6%) with moderate tubulointerstitial fibrosis (T1 26-50% of cortex scarred), and only 2 patients (1%) with severe tubulointerstitial fibrosis (T2, >50% of cortex scarred). During a median follow-up duration of 56 months, 24 children (12.4%) developed ESRD or 50% decline in renal function. In univariate COX analysis, we found that tubular atrophy/interstitial fibrosis (HR 4.3, 95%CI 1.8-10.5, P < 0.001) and segmental glomerulosclerosis (HR 9.2 1.2-68.6, P = 0.03) were significant predictors of renal outcome. However, mesangial hypercellularity, endocapillary proliferation, crescents, and necrosis were not associated with renal prognosis. In the multivariate COX regression model, none of these pathologic lesions were shown to be independent risk factors of unfavorable renal outcome except for tubular atrophy/interstitial fibrosis (HR 2.9, 95%CI 1.0-7.9 P = 0.04). CONCLUSIONS: We confirmed tubular atrophy/interstitial fibrosis was the only feature independently associated with renal outcomes in Chinese children with IgAN

One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction

Magnetic resonance imaging (MRI) is a principal radiological modality that provides radiation-free, abundant, and diverse information about the whole human body for medical diagnosis, but suffers from prolonged scan time. The scan time can be significantly reduced through k-space undersampling but the introduced artifacts need to be removed in image reconstruction. Although deep learning (DL) has emerged as a powerful tool for image reconstruction in fast MRI, its potential in multiple imaging scenarios remains largely untapped. This is because not only collecting large-scale and diverse realistic training data is generally costly and privacy-restricted, but also existing DL methods are hard to handle the practically inevitable mismatch between training and target data. Here, we present a Physics-Informed Synthetic data learning framework for Fast MRI, called PISF, which is the first to enable generalizable DL for multi-scenario MRI reconstruction using solely one trained model. For a 2D image, the reconstruction is separated into many 1D basic problems and starts with the 1D data synthesis, to facilitate generalization. We demonstrate that training DL models on synthetic data, integrated with enhanced learning techniques, can achieve comparable or even better in vivo MRI reconstruction compared to models trained on a matched realistic dataset, reducing the demand for real-world MRI data by up to 96%. Moreover, our PISF shows impressive generalizability in multi-vendor multi-center imaging. Its excellent adaptability to patients has been verified through 10 experienced doctors' evaluations. PISF provides a feasible and cost-effective way to markedly boost the widespread usage of DL in various fast MRI applications, while freeing from the intractable ethical and practical considerations of in vivo human data acquisitions.Comment: 22 pages, 9 figures, 1 tabl

Antioxidant Properties of the Mung Bean Flavonoids on Alleviating Heat Stress

Background: It is a widespread belief in Asian countries that mung bean soup (MBS) may afford a protective effect against heat stress. Lack of evidence supports MBS conferring a benefit in addition to water. Results: Here we show that vitexin and isovitexin are the major antioxidant components in mungbean (more than 96 % of them existing in the bean seed coat), and both of them could be absorbed via gavage into rat plasma. In the plasma of rats fed with mungbean coat extract before or after exposure to heat stress, the levels of malonaldehyde and activities of lactate dehydrogenase and nitric oxide synthase were remarkably reduced; the levels of total antioxidant capacity and glutathione (a quantitative assessment of oxidative stress) were significantly enhanced. Conclusions: Our results demonstrate that MBS can play additional roles to prevent heat stress injury. Characterization of the mechanisms underlying mungbean beneficial effects should help in the design of diet therapy strategies to alleviate heat stress, as well as provide reference for searching natural medicines against oxidative stress induced diseases

Pre-anesthetic use of butorphanol for the prevention of emergence agitation in thoracic surgery: A multicenter, randomized controlled trial

BackgroundEmergence agitation (EA) is common in patients after general anesthesia (GA) and is associated with poor outcomes. Patients with thoracic surgery have a higher incidence of EA compared with other surgery. This study aimed to investigate the impact of pre-anesthetic butorphanol infusion on the incidence of EA in patients undergoing thoracic surgery with GA.Materials and methodsThis prospective randomized controlled trial (RCT) was conducted in 20 tertiary hospitals in China. A total of 668 patients undergoing elective video-assisted thoracoscopic lobectomy/segmentectomy for lung cancer were assessed for eligibility, and 620 patients were enrolled. In total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. Patients in the intervention group received butorphanol 0.02 mg/kg 15 min before induction of anesthesia. Patients in the control group received volume-matched normal saline in the same schedule. The primary outcome was the incidence of EA after 5 min of extubation, and EA was evaluated using the Riker Sedation-Agitation Scale (RSAS). The incidence of EA was determined by the chi-square test, with a significance of P &lt; 0.05.ResultsIn total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. The incidence of EA 5 min after extubation was lower with butorphanol treatment: 9.8% (29 of 296) vs. 24.5% (75 of 306) in the control group (P = 0.0001). Patients who received butorphanol had a lower incidence of drug-related complications (including injecting propofol pain and coughing with sufentanil): 112 of 296 vs. 199 of 306 in the control group (P = 0.001) and 3 of 296 vs. 35 of 306 in the control group (P = 0.0001).ConclusionThe pre-anesthetic administration of butorphanol reduced the incidence of EA after thoracic surgery under GA.Clinical trial registration[http://www.chictr.org.cn/showproj.aspx?proj=42684], identifier [ChiCTR1900025705]