106 research outputs found
Lattice piecewise affine approximation of explicit nonlinear model predictive control with application to trajectory tracking of mobile robot
To promote the widespread use of mobile robots in diverse fields, the
performance of trajectory tracking must be ensured. To address the constraints
and nonlinear features associated with mobile robot systems, we apply nonlinear
model predictive control (MPC) to realize the trajectory tracking of mobile
robots. Specifically, to alleviate the online computational complexity of
nonlinear MPC, this paper devises a lattice piecewise affine (PWA)
approximation method that can approximate both the nonlinear system and control
law of explicit nonlinear MPC. The kinematic model of the mobile robot is
successively linearized along the trajectory to obtain a linear time-varying
description of the system, which is then expressed using a lattice PWA model.
Subsequently, the nonlinear MPC problem can be transformed into a series of
linear MPC problems. Furthermore, to reduce the complexity of online
calculation of multiple linear MPC problems, we approximate the optimal
solution of the linear MPC by using the lattice PWA model. That is, for
different sampling states, the optimal control inputs are obtained, and lattice
PWA approximations are constructed for the state control pairs. Simulations are
performed to evaluate the performance of our method in comparison with the
linear MPC and explicit linear MPC frameworks. The results show that compared
with the explicit linear MPC, our method has a higher online computing speed
and can decrease the offline computing time without significantly increasing
the tracking error
Plasma nitriding induced growth of Pt-nanowire arrays as high performance electrocatalysts for fuel cells
Smoking and coronary artery disease risk in patients with diabetes: A Mendelian randomization study
BackgroundPrevious observational studies have shown an association between smoking and coronary artery disease (CAD) in patients with diabetes. Whether this association reflects causality remains unestablished. This study aimed to explore the causal effect of smoking on CAD in patients with diabetes.MethodsGenetic signatures for smoking were extracted from a large genome-wide association study (GWAS), consisted of up to 1.2 million participants. Four smoking phenotypes were included: smoking initiation, cigarettes per day, age at initiation of regular smoking, and smoking cessation. Genetic associations with CAD in patients with diabetes were extracted from another GWAS, which included 15,666 participants (3,968 CAD cases and 11,696 controls). The analyses were performed using the univariable and multivariable Mendelian randomization (MR) method.ResultsMR analysis revealed that smoking initiation was positively related to CAD risk in patients with diabetes (OR = 1.322, 95% CI = 1.114 – 1.568, P = 0.001), but this association was attenuated when adjusted for cardiovascular risk factors (OR = 1.212, 95% CI = 1.008 – 1.457, P = 0.041). Age at initiation of regular smoking was negatively related to CAD in patients with diabetes (OR = 0.214, 95% CI = 0.070 – 0.656, P = 0.007), but this association became insignificant when adjusted for cardiovascular risk factors.ConclusionsThis study supported the effect of smoking initiation on the risk of CAD in patients with diabetes
Period2 is associated with immune cell infiltration and is a potential diagnostic and prognostic marker for hepatocellular carcinoma
Background: Hepatocellular carcinoma (HCC) health challenge worldwide. Many studies showed that circadian rhythms play a critical role in tumor development. This study aimed to investigate the role of the circadian gene period2 (PER2) in HCC development and explore the possible mechanisms involved.Methods: From fresh HCC tissues and paired paracancerous tissues, we measured PER2 mRNA and protein expression levels and calculated the correlations between PER2 expression and clinicopathological parameters in patients with HCC. We used transcriptome data from The Cancer Genome Atlas to mine the PER2 gene, including single gene difference analysis, single gene co-expression analysis, gene set enrichment analysis, immune infiltration analysis, and methylation analysis to explore its role and mechanism in HCC occurrence and development.Results: PER2 expression levels were significantly lower in HCC tissues than in the paired paracancerous tissues. PER2 expression in HCC significantly correlated with neural invasion, Child-Pugh classification, and China liver cancer staging stage in HCC patients. The differentially expressed genes associated with PER2 were significantly enriched in mitochondrial oxidative phosphorylation, transcriptional translation, amino acid metabolism, and other related pathways. PER2 expression levels significantly correlated with immune cell infiltration and immune checkpoint genes and positively correlated with TP53 expression in HCC tissues. The DNA methylation status in eight CpG islands of the PER2 gene was associated with HCC outcomes.Conclusion: PER2 is a potential diagnostic and prognostic biomarker and a promising therapeutic target in HCC
Genetic sources and loci for Fusarium head blight resistance in bread wheat
Fusarium head blight (FHB) of wheat is an important disease worldwide, affecting the yield, end-use quality and threatening food safety. Genetic resources or stable loci for FHB resistance are still limited in breeding programs. A panel of 265 bread wheat accessions from China, CIMMYT-Mexico and other countries was screened for FHB resistance under 5 field experiments in Mexico and China, and a genome-wide association analysis was performed to identify QTLs associated with FHB resistance. The major locus Fhb1 was significantly associated with FHB severity and Deoxynivalenol content in grains. FHB screening experiments in multiple environments showed that Fhb1-harbouring accessions Sumai3, Sumai5, Ningmai9, Yangmai18 and Tokai66 had low FHB index, disease severity and DON content in grains in response to different Fusarium species and ecological conditions in Mexico and China. Accessions Klein Don Enrique, Chuko and Yumai34 did not have Fhb1 but still showed good FHB resistance and low mycotoxin accumulation. Sixteen loci associated with FHB resistance or DON content in grains were identified on chromosomes 1A, 1B, 2B, 3A, 3D, 4B, 4D, 5A, 5B, 7A, and 7B in multiple environments, explaining phenotypic variation of 4.43–10.49%. The sources with good FHB resistance reported here could be used in breeding programs for resistance improvement in Mexico and China, and the significant loci could be further studied and introgressed for resistance improvement against FHB and mycotoxin accumulation in grains
Wheat Blast: A Disease Spreading by Intercontinental Jumps and Its Management Strategies
Wheat blast (WB) caused by Magnaporthe oryzae pathotype Triticum (MoT) is an important fungal disease in tropical and subtropical wheat production regions. The disease was initially identified in Brazil in 1985, and it subsequently spread to some major wheat-producing areas of the country as well as several South American countries such as Bolivia, Paraguay, and Argentina. In recent years, WB has been introduced to Bangladesh and Zambia via international wheat trade, threatening wheat production in South Asia and Southern Africa with the possible further spreading in these two continents. Resistance source is mostly limited to 2NS carriers, which are being eroded by newly emerged MoT isolates, demonstrating an urgent need for identification and utilization of non-2NS resistance sources. Fungicides are also being heavily relied on to manage WB that resulted in increasing fungal resistance, which should be addressed by utilization of new fungicides or rotating different fungicides. Additionally, quarantine measures, cultural practices, non-fungicidal chemical treatment, disease forecasting, biocontrol etc., are also effective components of integrated WB management, which could be used in combination with varietal resistance and fungicides to obtain reasonable management of this disease
A Survey on Evaluation of Large Language Models
Large language models (LLMs) are gaining increasing popularity in both
academia and industry, owing to their unprecedented performance in various
applications. As LLMs continue to play a vital role in both research and daily
use, their evaluation becomes increasingly critical, not only at the task
level, but also at the society level for better understanding of their
potential risks. Over the past years, significant efforts have been made to
examine LLMs from various perspectives. This paper presents a comprehensive
review of these evaluation methods for LLMs, focusing on three key dimensions:
what to evaluate, where to evaluate, and how to evaluate. Firstly, we provide
an overview from the perspective of evaluation tasks, encompassing general
natural language processing tasks, reasoning, medical usage, ethics,
educations, natural and social sciences, agent applications, and other areas.
Secondly, we answer the `where' and `how' questions by diving into the
evaluation methods and benchmarks, which serve as crucial components in
assessing performance of LLMs. Then, we summarize the success and failure cases
of LLMs in different tasks. Finally, we shed light on several future challenges
that lie ahead in LLMs evaluation. Our aim is to offer invaluable insights to
researchers in the realm of LLMs evaluation, thereby aiding the development of
more proficient LLMs. Our key point is that evaluation should be treated as an
essential discipline to better assist the development of LLMs. We consistently
maintain the related open-source materials at:
https://github.com/MLGroupJLU/LLM-eval-survey.Comment: 23 page
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