200 research outputs found
Evaluation of Battery Storage to Provide Virtual Transmission Service
An immediate need in the transmission system is to find alternative solutions
that improve system operation and defer the need for new transmission lines.
This study comprehensively evaluates the performance and economic benefits of
using battery energy storage systems (BESS) as virtual transmission (VT) to
promote power transfer cross distant regions. Specifically, this work
implements various day-ahead energy scheduling models to analyze the impact of
VT on system operation cost, network congestion, model computational time, and
market performance. The performance of VT is compared with three alternative
network congestion mitigation methods, including building new high-voltage
physical transmission lines, cost-driven battery energy storage systems, and
network reconfiguration, as well as combinations of two of aforementioned
methods. The benchmark day-ahead scheduling model is a traditional
security-constrained unit commitment model without system upgrades or other
network congestion mitigation. Numerical simulations conducted on the IEEE
24-bus system demonstrate that among all the examined schemes, VT is the only
one comparable to physical transmission lines that can provide satisfying
congestion relief and operation cost reduction without sacrificing computing
time and load payment significantly
A Meta-Analysis of Enteral Nutrition and Total Parenteral Nutrition in Patients with Acute Pancreatitis
Objective. To analyze the effect of total parenteral nutrition (TPN) and enteral nutrition (EN) in patients with acute pancreatitis. Methods. Randomized controlled trials of TPN and EN in patients with acute pancreatitis were searched in NCBI and CBM databases and The Cochrane Controlled Trials Register. Six studies were enrolled into the analysis, and the details about the trial designs, characters of the subjects, results of the studies were reviewed by two independent authors and analyzed by STATA 11.0 software. Results. Compared with TPN, EN was associated with a significantly lower incidence of pancreatic infection complications (RR = 0.556, 95% CI 0.436∼0.709, P = .000), MOF (RR = 0.395, 95% CI 0.272∼0.573, P = .003), surgical interventions (RR = 0.556, 95% CI 0.436∼0.709, P = .000), and mortality (RR = 0.426, 95% CI 0.238∼0.764, P = .167). There was no statistic significance in non-pancreatitis-related complications (RR = 0.853, 95% CI 0.490∼1.483, P = .017). However, EN had a significantly higher incidence of non-infection-related complications (RR = 2.697, 95% CI 1.947∼3.735, P = .994). Conclusion. EN could be the preferred nutrition feeding method in patients with acute pancreatitis
Machine learning approaches for cyanobacteria bloom prediction using metagenomic sequence data, a case study
DAA: A Delta Age AdaIN operation for age estimation via binary code transformer
Naked eye recognition of age is usually based on comparison with the age of
others. However, this idea is ignored by computer tasks because it is difficult
to obtain representative contrast images of each age. Inspired by the transfer
learning, we designed the Delta Age AdaIN (DAA) operation to obtain the feature
difference with each age, which obtains the style map of each age through the
learned values representing the mean and standard deviation. We let the input
of transfer learning as the binary code of age natural number to obtain
continuous age feature information. The learned two groups of values in Binary
code mapping are corresponding to the mean and standard deviation of the
comparison ages. In summary, our method consists of four parts: FaceEncoder,
DAA operation, Binary code mapping, and AgeDecoder modules. After getting the
delta age via AgeDecoder, we take the average value of all comparison ages and
delta ages as the predicted age. Compared with state-of-the-art methods, our
method achieves better performance with fewer parameters on multiple facial age
datasets.Comment: Accepted by CVPR2023; 8 pages, 3 figure
Stereotactic radiotherapy: An alternative option for refractory ventricular tachycardia to drug and ablation therapy
Refractory ventricular tachycardia (VT) often occurs in the context of organic heart disease. It is associated with significantly high mortality and morbidity rates. Antiarrhythmic drugs and catheter ablation represent the two main treatment options for refractory VT, but their use can be associated with inadequate therapeutic responses and procedure-related complications. Stereotactic body radiotherapy (SBRT) is extensively applied in the precision treatment of solid tumors, with excellent therapeutic responses. Recently, this highly precise technology has been applied for radioablation of VT, and its early results demonstrate a favorable safety profile. This review presents the potential value of SBRT in refractory VT
Core Gut Bacteria Analysis of Healthy Mice
Previous studies revealed that there existed great individual variations of gut microbiota in mice, and the gut bacteria of mice were changed with the occurrence and development of diseases. To identify the core gut bacteria in healthy mice and explore their relationships with the host phenotypes would help to understand the underlying mechanisms. In this study, we identified 37 genus-level core bacteria from feces of 101 healthy mice with different ages, sexes, and mouse strains in three previous studies. They collectively represented nearly half of the total sequences, and predominantly included carbohydrate- and amino acids-metabolizing bacteria and immunomodulatory bacteria. Among them, Anaerostipes indwelt the gut of all healthy mice. Co-abundance analysis showed that these core genera were clustered into five groups (Group C1–C5), which were ecologically related. For example, the abundances of Group C2 including probiotics Bifidobacterium and Lactobacillus slightly positively correlated with those of Group C1. Principal component analysis (PCA) and multivariate analysis of variance test revealed that these core gut genera were distinguished with age and sex, and also associated with their health/disease state. Linear discriminant analysis effect size (LEfSe) method showed that bacteria in Group C1 and C2/C3 increased with the age in infancy and early adulthood, and were more abundant in female mice than in male ones. The metabolic syndrome (MS) induced by high fat diet (HFD) and accelerated postnatal growth would decrease Group C2 genera, whereas probiotics intervention would reverse HFD-induced reduction of Group C2. Spearman correlation analysis indicated that the principal components based on the abundance of the 37 core genera were significantly correlated with host characteristic parameters of MS. These results demonstrated that the 37 core genera in five co-abundance groups from healthy mice were related to host phenotypes. It was indicated that these prevalent gut bacterial genera could be representative of the healthy gut microbiome in gnotobiotic animal models, and might also be candidates of probiotics and fecal microbiota transplantation
Association between marijuana use and kidney stone: a cross-sectional study of NHANES 2009 to 2018
Objective: The purpose of this investigation is to determine whether regular marijuana use is related to history of kidney stones in the US population.Methods: Data were obtained from the National Health and Nutrition Examination Survey (NHANES) from 2009 to 2018. Kidney stone and marijuana use data were collected from self-report questionnaires. Multivariate logistic regression and multiple sensitivity analyses were applied to examine the relationship between marijuana usage and kidney stones.Results: There are approximately 26.04% of the US population have admitted to using marijuana in their lifetime. Compared with none regular users, those with a higher frequency of marijuana use were more males, more non-Hispanic races, lower than high school education, overweight, no recreational activity, without diabetes mellitus, and more coronary heart disease. After adjusting for potential confounders, multivariate regression analysis demonstrated that marijuana use was inversely correlated to kidney stones in males (Odds ratio [OR] = 0.72, 95% Confidence interval [CI] = 0.54–0.97). One to seven times/week regular consumption of marijuana was associated with kidney stones in males (OR = 0.62, 95% CI = 0.43–0.89). Sensitivity analyses validated the robustness of our outcomes.Conclusion: Our findings revealed that regular marijuana male users were inversely associated with kidney stones. Marijuana use one to six times/week was inversely related to the risk of kidney stones in males. Further studies are required to explore the dose and type associations of marijuana with kidney stones
Expression of DNMT1 and DNMT3a Are Regulated by GLI1 in Human Pancreatic Cancer
BACKGROUND AND AIMS: GLI1, as an indispensable transcriptional factor of Hedgehog signaling pathway, plays an important role in the development of pancreatic cancer (PC). DNA methyltransferases (DNMTs) mediate the methylation of quantity of tumor-related genes. Our study aimed to explore the relationship between GLI1 and DNMTs. METHODS: Expressions of GLI1 and DNMTs were detected in tumor and adjacent normal tissues of PC patients by immunohistochemistry (IHC). PANC-1 cells were treated by cyclopamine and GLI1-siRNA, while BxPC-3 cells were transfected with overexpression-GLI1 lentiviral vector. Then GLI1 and DNMTs expression were analyzed by qRT-PCR and western blot (WB). Then we took chromatin immunoprecipitation (ChIP) to demonstrate GLI1 bind to DNMT1. Finally, nested MSP was taken to valuate the methylation levels of APC and hMLH1, when GLI1 expression altered. RESULTS: IHC result suggested the expressions of GLI1, DNMT1 and DNMT3a in PC tissues were all higher than those in adjacent normal tissues (p<0.05). After GLI1 expression repressed by cyclopamine in mRNA and protein level (down-regulation 88.1±2.2%, 86.4±2.2%, respectively), DNMT1 and DNMT3a mRNA and protein level decreased by 91.6%±2.2% and 83.8±4.8%, 87.4±2.7% and 84.4±1.3%, respectively. When further knocked down the expression of GLI1 by siRNA (mRNA decreased by 88.6±2.1%, protein decreased by 63.5±4.5%), DNMT1 and DNMT3a mRNA decreased by 80.9±2.3% and 78.6±3.8% and protein decreased by 64.8±2.8% and 67.5±5.6%, respectively. Over-expression of GLI1 by GLI1 gene transfection (mRNA increased by 655.5±85.9%, and protein increased by 272.3±14.4%.), DNMT1 and DNMT3a mRNA and protein increased by 293.0±14.8% and 578.3±58.5%, 143.5±17.4% and 214.0±18.9%, respectively. ChIP assays showed GLI1 protein bound to DNMT1 but not to DNMT3a. Results of nested MSP demonstrated GLI1 expression affected the DNA methylation level of APC but not hMLH1 in PC. CONCLUSION: DNMT1 and DNMT3a are regulated by GLI1 in PC, and DNMT1 is its direct target gene
Multispectral Palmprint Recognition Using a Quaternion Matrix
Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%
Generation of phase-only holograms with high-diffraction-order reconstruction by a U-Net-based neural network: A phase grating perspective
Implicit periodic structure in phase-only holograms will result in many diffraction orders in the diffraction field. We analyzed the diffraction pattern from a phase gratings point of view and proved that the diffraction orders were jointly influenced by the phase factor, the single-beam diffraction factor, and the multibeam interference factor. According to the analysis, we proposed the high-diffraction-order angular spectrum method (HDO-ASM) for the numerical reconstruction of high diffraction orders. Different from the conventional methods of removing high diffraction orders, we chose to reconstruct target images in high diffraction orders with HDO-ASM and a U-Net-based neural network. Finally, the 4 K phase-only holograms with high-diffraction-order reconstruction were generated in 0.09s and had a mean reconstruction quality of 34.3 dB (PSNR) in the DIV2K valid dataset. Theoretical and experimental results demonstrated that there are few speckle noises and fringes in the reconstructed images of holograms generated by the proposed method
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