Temporal Signature Modeling and Analysis

A vast amount of digital satellite and aerial images are collected over time, which calls for techniques to extract useful high-level information, such as recognizable events. One part of this thesis proposes a framework for streaming analysis of the time series, which can recognize events without supervision and memorize them by building the temporal contexts. The memorized historical data is then used to predict the future and detect anomalies. A new incremental clustering method is proposed to recognize the event without training. A memorization method of double localization, including relative and absolute localization, is proposed to model the temporal context. Finally, the predictive model is built based on the method of memorization. The Edinburgh Pedestrian Dataset , which offers about 1000 observed trajectories of pedestrians detected in camera images each working day for several months, is used as an example to illustrate the framework. Although there is a large amount of image data captured, most of them are not available to the public. The other part of this thesis developed a method of generating spatial-spectral-temporal synthetic images by enhancing the capacity of a current tool called DIRISG (Digital Imaging and Remote Sensing Image Generation). Currently, DIRSIG can only model limited temporal signatures. In order to observe general temporal changes in a process within the scene, a process model, which links the observable signatures of interest temporally, should be developed and incorporated into DIRSIG. The sub process models could be categorized into two types. One is that the process model drives the property of each facet of the object changing over time, and the other one is to drive the geometry location of the object in the scene changing as a function of time. Two example process models are used to show how process models can be incorporated into DIRSIG

Investigating the Hypolipidemic Mechanism of Anthocyanins Combined with Allicin in Rats Using Network Pharmacology

Objectives: Using network pharmacology methods, investigate the potential lipid-lowering mechanism of the combination of anthocyanins and allicin in hyperlipidemic rats. Methods: Apply databases such as Pubchem, SwissTargetPrediction, TCMSP, DrugBank and BATMAN-TCM to predict potential targets for anthocyanins and allicin. Additionally, targets connected to hyperlipidemia were found in multiple databases (GeneCards, OMIM, Drugbank, and TTD). Upload the discovered drug-disease intersection targets into the database of STRING in order to construct a common target protein-protein interactions network (PPI). To find important targets, a PPI network analysis was built using Cytoscape 3.9.1. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enriched and analyzed these common drug-disease targets. In order to further confirm the key targets of anthocyanins combined with allicin in hyperlipidemia, animal experiments were conducted. Results: There are 63 potential targets for the combined effect of anthocyanins and allicin on hyperlipidemia. The PPI topology analysis results found that TNF, IL-6, AKT1, PTGS2, GSK3B, EGFR, etc. are the main key targets. The main pathways included PI3K-Akt, JAK-STAT, Fluid shear stress and atherosclerosis, HIF-1and MAPK signaling pathway. The animal experiments results revealed that anthocyanins combined with allicin can improve blood lipid levels in hyperlipidemic rats and decrease the serum levels of inflammatory factors. Conclusion: Anthocyanins combined with allicin can intervene in hyperlipidemia through a variety of targets and pathways. This research offers a theoretical reference for the investigation of the pathogenesis of hyperlipidemia and the production of functional foods

A randomized controlled trial protocol comparing the feeds of fresh versus frozen mother’s own milk for preterm infants in the NICU

Abstract Background Necrotizing enterocolitis (NEC) is the leading cause of death among preterm infants born at < 30 weeks’ gestation. The incidence of NEC is reduced when infants are fed human milk. However, in many neonatal intensive care units (NICUs), it is standard practice to freeze and/or pasteurize human milk, which deactivates bioactive components that may offer additional protective benefits. Indeed, our pilot study showed that one feed of fresh mother’s own milk per day was safe, feasible, and can reduce morbidity in preterm infants. To further evaluate the benefits of fresh human milk in the NICU, a randomized controlled trial is needed. Methods Our prospective multicenter, double-blinded, randomized, controlled trial will include infants born at < 30 weeks’ gestation and admitted to one of 29 tertiary NICUs in China. Infants in the intervention (fresh human milk) group (n = 1549) will receive at least two feeds of fresh human milk (i.e., within 4 h of expression) per day from the time of enrollment until 32 weeks’ corrected age or discharge to home. Infants in the control group (n = 1549) will receive previously frozen human milk following the current standard protocols. Following informed consent, enrolled infants will be randomly allocated to the control or fresh human milk groups. The primary outcome is the composite outcome mortality or NEC ≥ stage 2 at 32 weeks’ corrected age, and the secondary outcomes are mortality, NEC ≥ stage 2, NEC needing surgery, late-onset sepsis, retinopathy of prematurity (ROP), bronchopulmonary dysplasia (BPD), weight gain, change in weight, increase in length, increase in head circumference, time to full enteral feeds, and finally, the number and type of critical incident reports, including feeding errors. Discussion Our double-blinded, randomized, controlled trial aims to examine whether fresh human milk can improve infant outcomes. The results of this study will impact both Chinese and international medical practice and feeding policy for preterm infants. In addition, data from our study will inform changes in health policy in NICUs across China, such that mothers are encouraged to enter the NICU and express fresh milk for their infants. Trial registration Chinese Clinical Trial Registry; #ChiCTR1900020577; registered January 1, 2019; http://www.chictr.org.cn/showprojen.aspx?proj=3427