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result(s) for
"Peng, Yuwei"
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A Survey on Advancing the DBMS Query Optimizer: Cardinality Estimation, Cost Model, and Plan Enumeration
by
Peng, Yuwei
,
Lan, Hai
,
Bao, Zhifeng
in
Algorithm Analysis and Problem Complexity
,
Algorithms
,
Artificial Intelligence
2021
Query optimizer is at the heart of the database systems. Cost-based optimizer studied in this paper is adopted in almost all current database systems. A cost-based optimizer introduces a plan enumeration algorithm to find a (sub)plan, and then uses a cost model to obtain the cost of that plan, and selects the plan with the lowest cost. In the cost model, cardinality, the number of tuples through an operator, plays a crucial role. Due to the inaccuracy in cardinality estimation, errors in cost model, and the huge plan space, the optimizer cannot find the optimal execution plan for a complex query in a reasonable time. In this paper, we first deeply study the causes behind the limitations above. Next, we review the techniques used to improve the quality of the three key components in the cost-based optimizer, cardinality estimation, cost model, and plan enumeration. We also provide our insights on the future directions for each of the above aspects.
Journal Article
Preparation and Characterization of Natural Silk Fibroin Hydrogel for Protein Drug Delivery
2022
In recent years, hydrogels have been widely used as drug carriers, especially in the area of protein delivery. The natural silk fibroin produced from cocoons of the Bombyx mori silkworm possesses excellent biocompatibility, significant bioactivity, and biodegradability. Therefore, silk fibroin-based hydrogels are arousing widespread interest in biomedical research. In this study, a process for extracting natural silk fibroin from raw silk textile yarns was established, and three aqueous solutions of silk fibroin with different molecular weight distributions were successfully prepared by controlling the degumming time. Silk fibroin was dispersed in the aqueous solution as “spherical” aggregate particles, and the smaller particles continuously accumulated into large particles. Finally, a silk fibroin hydrogel network was formed. A rheological analysis showed that as the concentration of the silk fibroin hydrogel increased its storage modulus increased significantly. The degradation behavior of silk fibroin hydrogel in different media verified its excellent stability, and the prepared silk fibroin hydrogel had good biocompatibility and an excellent drug-loading capacity. After the protein model drug BSA was loaded, the cumulative drug release within 12 h reached 80%. We hope that these investigations will promote the potential utilities of silk fibroin hydrogels in clinical medicine.
Journal Article
A Clinically Interpretable Computer-Vision Based Method for Quantifying Gait in Parkinson’s Disease
by
Peng, Yuwei
,
Sibley, Krista
,
Morgante, Francesca
in
Bayes Theorem
,
Cameras
,
Clinical medicine
2021
Gait is a core motor function and is impaired in numerous neurological diseases, including Parkinson’s disease (PD). Treatment changes in PD are frequently driven by gait assessments in the clinic, commonly rated as part of the Movement Disorder Society (MDS) Unified PD Rating Scale (UPDRS) assessment (item 3.10). We proposed and evaluated a novel approach for estimating severity of gait impairment in Parkinson’s disease using a computer vision-based methodology. The system we developed can be used to obtain an estimate for a rating to catch potential errors, or to gain an initial rating in the absence of a trained clinician—for example, during remote home assessments. Videos (n=729) were collected as part of routine MDS-UPDRS gait assessments of Parkinson’s patients, and a deep learning library was used to extract body key-point coordinates for each frame. Data were recorded at five clinical sites using commercially available mobile phones or tablets, and had an associated severity rating from a trained clinician. Six features were calculated from time-series signals of the extracted key-points. These features characterized key aspects of the movement including speed (step frequency, estimated using a novel Gamma-Poisson Bayesian model), arm swing, postural control and smoothness (or roughness) of movement. An ordinal random forest classification model (with one class for each of the possible ratings) was trained and evaluated using 10-fold cross validation. Step frequency point estimates from the Bayesian model were highly correlated with manually labelled step frequencies of 606 video clips showing patients walking towards or away from the camera (Pearson’s r=0.80, p<0.001). Our classifier achieved a balanced accuracy of 50% (chance = 25%). Estimated UPDRS ratings were within one of the clinicians’ ratings in 95% of cases. There was a significant correlation between clinician labels and model estimates (Spearman’s ρ=0.52, p<0.001). We show how the interpretability of the feature values could be used by clinicians to support their decision-making and provide insight into the model’s objective UPDRS rating estimation. The severity of gait impairment in Parkinson’s disease can be estimated using a single patient video, recorded using a consumer mobile device and within standard clinical settings; i.e., videos were recorded in various hospital hallways and offices rather than gait laboratories. This approach can support clinicians during routine assessments by providing an objective rating (or second opinion), and has the potential to be used for remote home assessments, which would allow for more frequent monitoring.
Journal Article
Population structure and selective signature analysis of local sheep breeds in Xinjiang, China based on high-density SNP chip
2024
The frigid and droughty climate of Xinjiang in China has given rise to unique indigenous sheep breeds with robust adaptability and resistance. To investigate the genetic mechanism of adaptability of Xinjiang sheep to the local extreme environment, we conducted population genetic structure analyses for three native Xinjiang sheep breeds: Altay sheep (ALT), Bashbay Sheep (BSBC), and Duolang sheep (DLC), as well as two foreign sheep breeds: Suffolk and Dorset, using the Ovine Infinium HD SNP BeadChip(680 K). Our findings revealed distinct genetic and evolutionary histories between Xinjiang and foreign sheep breeds. Principal Component Analysis (PCA) and phylogenetic tree effectively differentiate these five sheep breeds based on their geographical origins, and the domestication level of Xinjiang sheep is comparatively lower than that of foreign sheep breeds. Furthermore, by utilizing three selective signature methods, namely Fixation Index (Fst), Cross Population Extended Haplotype Homozygosity Test (XP-EHH), and Nucleotide Diversity (π), we have successfully identified 22 potential candidate genes. Among these genes, there are
TBXT
,
PDGFD
, and
VEGFA
, which are closely related to tail type and lipid metabolism;
VIL1
,
SLC11A1
, and
ZBTB46
, which are associated with immune function; and candidate genes such as
BNC1
,
HDAC1
, and
BMP5
, which impact sheep reproductive traits. This study establishes a foundation for conserving and utilizing local sheep germplasm resources in Xinjiang and provides molecular insights into the genetic mechanisms governing sheep adaptation to extreme cold and arid environments.
Journal Article
A Fault Diagnosis Method of Rolling Bearings Based on Parameter Optimization and Adaptive Generalized S-Transform
2022
As for the fault diagnosis of rolling bearings under strong background noises, whether the fault feature extraction is comprehensive and accurate is critical, especially for the data-driven fault diagnosis methods. To improve the comprehensiveness and accuracy of the fault feature extraction, a fault diagnosis method of rolling bearings is proposed based on parameter optimization and Adaptive Generalized S-Transform (AGST). The AGST is used to solve the problem of incomplete feature extraction of bearing faults. The Particle Swarm Brain Storm Optimization algorithm based on the Discussion Mechanism (PSDMBSO) is used for the parameter optimization of VMD, which can better separate the complete fault components. The effectiveness of the fault diagnosis method proposed in this paper is verified by comparison with other methods.
Journal Article
Genome-based analysis of the genetic pattern of black sheep in Qira sheep
by
Zhang, Xuechen
,
Peng, Yuwei
,
Bai, Xinyu
in
Admixture mapping
,
Analysis
,
Animal Genetics and Genomics
2025
Objective
Black wool can effectively prevent sheep from DNA damage as well as fungal infection, and can improve reproductive performance. In order to explore the candidate genes related to black wool formation in Qira sheep.
Methods
We selected 123 adult healthy ewes with different coat colors in Qira sheep groups (black (B), brown (Y) and grey (G)) and extracted DNA from their venous blood to obtain Illumina Ovine SNP 50K chip data. Subsequently, our PCA, NJ-tree, and Admixture population structure analyses of the 3 wool color Qira sheep populations showed that the 3 middle wool color populations exhibited the same genetic traits. Fst, xp-EHH, iHS, and π were detected for selection signals, and the 5% SNPs loci positively selected from the analyses were annotated based on SheepOar_v4.0. The region of exon 1 of the
TYRP1
gene was further screened, amplified and sequenced through the DNA of the Qira sheep and associated with goodness-of-fit using the chi-square test.
Results
The results showed that 71 SNPs associated with black wool traits, among which
TYRP1, PARD3
and
CDH2
genes were strongly associated with black wool production. Three mutations were detected in the exon 1 region of the
TYRP1
gene that were significantly associated with coat color variation inQira sheep (2:81,183,168, 2:81,183,281 and 2:81,183,284).
Conclusion
In this paper, Qira sheep could not differentiate the genetic structure of this population by wool color, and obtained 71 SNPs related to black wool. Detection of mutation sites on the
TYRP1
gene affecting hair color change provides a basis for black sheep line selection as well as breed conservation.
Journal Article
Screening of molecular markers associated with hornless traits in Qira black sheep
by
Zhang, Xuechen
,
Peng, Yuwei
,
Gao, Qifeng
in
Animal genetics
,
Animal Genetics and Genomics
,
Animals
2025
Hornless trait in sheep is one of the important traits affecting their economic production efficiency. In order to screen the molecular markers related to hornless trait in Qira black sheep, we used Illumina Ovine 50 K SNP chip data of 189 Qira black sheep, which were divided into two groups based on their horned and hornless traits. GWAS analysis of individuals of interest. Used the horned trait group as the reference group, and performed xp-EHH analysis with the hornless group. The hornless group was subjected to iHS and Pi analyses. After annotating the relevant candidate regions based on the sheep 4.0 genome microarray data. 681 candidate genes were obtained from the xp-EHH analysis, 87 candidate genes from the iHS analysis, and 2,171 candidate genes from the Pi analysis. A total of 19 candidate genes were obtained from further analysis of the candidate regions. Candidate genes were analyzed by GO and KEGG, and
RXFP2
,
TNS3
,
EYA2
and
OCSTAMP
genes were found to be associated with horned traits in Qira black sheep. Further PCR validation of
RXFP2
revealed that loci 10: 29,501,280 (
P
= 0.002), 10: 29,501,431 (
P
= 0.003) and 10: 29,051,333 (
P
= 0.0001) were significantly associated with hornless trait in Qira black sheep.
Journal Article
Techno-Economic Analysis of a Novel Two-Stage Flashing Process for Acid Gas Removal from Natural Gas
2019
Excessive CO2 content will reduce the natural gas calorific value and increase the energy consumption of the regenerator in natural gas desulfurization and decarbonization. This paper uses Aspen HYSYS to model a novel two-stage flash process of acid gas removal process from natural gas. According to the results from the simulation, as well as running experiences in a natural gas processing plant in the middle east, it can be demonstrated that this new process, which has been used in the field of natural gas desulfurization and decarbonization, can meet the requirement of product specifications. Based on the steady state simulation, Aspen HYSYS sensitivity function is used to evaluate influence of key operating parameters, such as the second flash pressure and temperature, on the energy consumption. Compared to the traditional acid gas removal process and acid gas enrichment process, the new two-stage flash acid gas removal process has less energy consumption (2.2 × 109 kJ·h−1). In addition, two-stage flash acid gas removal process also improves the efficiency of acid gas enrichment, while the overall energy consumption is less than combination process of traditional process and acid gas enrichment process.
Journal Article
Computer vision quantification of whole-body Parkinsonian bradykinesia using a large multi-site population
by
Peng, Yuwei
,
Sibley, Krista
,
Morgante, Francesca
in
692/53/2423
,
692/617/375/1718
,
Agreements
2023
Parkinson’s disease (PD) is a common neurological disorder, with bradykinesia being one of its cardinal features. Objective quantification of bradykinesia using computer vision has the potential to standardise decision-making, for patient treatment and clinical trials, while facilitating remote assessment. We utilised a dataset of part-3 MDS-UPDRS motor assessments, collected at four independent clinical and one research sites on two continents, to build computer-vision-based models capable of inferring the correct severity rating robustly and consistently across all identifiable subgroups of patients. These results contrast with previous work limited by small sample sizes and small numbers of sites. Our bradykinesia estimation corresponded well with clinician ratings (interclass correlation 0.74). This agreement was consistent across four clinical sites. This result demonstrates how such technology can be successfully deployed into existing clinical workflows, with consumer-grade smartphone or tablet devices, adding minimal equipment cost and time.
Journal Article
A Coordinated Optimal Strategy for Voltage and Reactive Power Control with Adaptive Amplitude Limiter Based on Flexible Excitation System
by
Zhang, Tiantian
,
Peng, Yuwei
,
Xiong, Hongtao
in
adaptive amplitude limiter
,
Bridges
,
Controllers
2021
The flexible excitation system (FES) is a kind of novel excitation system with two channels for damping control. Besides the basic functions of traditional excitation systems, flexible excitation systems can provide reactive power support for the terminal voltage, and the large-capacity FES can improve the voltage stability and power-angle stability of synchronous generator units. However, with the increase in system capacity and the complication of control objectives, the difficulty of controller design will be increased. The randomness and fluctuation of new energy resources such as photovoltaic and wind turbines may cause disturbance and fault to the power system, which requires the coordinated control strategy for the FES to achieve stability in voltage and power angle. In this paper, the basic characteristics of FES are analyzed, and the mathematic model of the single machine infinite bus (SMIB) system based on FES is derived. The coordinated control strategy based on decoupling control of stator and rotor is proposed according to the optimal objectives of voltage stability and power-angle stability, and the linear optimal excitation control (LOEC) is adopted with the adaptive amplitude limiter (AAL) determined by fuzzy rules. The MATLAB/Simulink platform is established and the results verify the superiority of the proposed LOEC + AAL control strategy in large disturbance working conditions, which showed better robustness. The proposed coordinated control strategy provides an effective solution for industrial application and performance improvement of FES.
Journal Article