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From One Strand Dyed/Undyed Hair With/Without Root to Fast and Successful STR Profiling and Evaluation With principle component analysis

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ELECTROPHORESIS 2025年 2025 May 2页

作者： Rayimoglu, Gulten Yonar, Fatma Cavus Anilanmert, Beril Istanbul Univ Cerrahpasa Inst Forens Sci & Legal Med Istanbul Turkiye

Fallen/shed single hair shafts with/without roots can be encountered as evidence in crime scenes. Identification from hair exhibits serious difficulties, due to the low amount of DNA, PCR inhibitors, and the existence of DNA mostly in degraded forms. Exposure of hair to chemical oxidation, sunlight, etc. brings extra difficulties to DNA analysis. In single hair shafts, no satisfactory nuDNA test method that can be used both for dyed/undyed single hair shafts with/without root exists in the literature. Next-generation systems are expensive, have a labor-intensive workflow, and are not available in many forensic laboratories. Here an STR profiling method has been developed modifying an isolation kit method for an easy, successful DNA for (1) dyed/undyed single hairs with root and (2) without root from 36 individuals and compared with the unmodified method (total 432 analyzed samples). Modified silica-based isolation method, yielded 0.65-1.05 ng/mu L DNA. The success of STR typing after capillary electrophoresis was 96%-98% for dyed/undyed hair with roots and 89%-93% for rootless ones, while the results for the unmodified method were 67%-82%. The results were investigated using PCA, t-test, and F-test. This protocol is simple, inexpensive, does not require automation, and can be performed using kits/equipment available in every forensic laboratory for forensic genotyping.

关键词： degraded DNA in hair strand dyed/undyed hair hair with root principle component analysis rootless hair STR profiling

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A Novel DABU-Net Model Based On principle component analysis For Intelligent Collaborative Robot Design

JOURNAL OF APPLIED SCIENCE AND ENGINEERING

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JOURNAL OF APPLIED SCIENCE AND ENGINEERING 2024年第11期27卷 3463-3471页

作者： Jiang, Yu Shenyang Normal Univ 253 Huanghe North St Shenyang 110034 Peoples R China

In the traditional space art, the idea of the unity of heaven and man and the connection between heaven and man has been fully affirmed and developed in the long history. In the architectural space, it is often reflected in the geographical location because of the weather, and it should find its own appropriate posture in nature, rather than compete with him. In traditional architectural planning and design, it advocates the organic view of nature that emphasizes the integrity of nature and the internal relationship between things, and pays attention to the combination of Yin and Yang, so as to unify man and nature and self. In particular, image classification plays a very important role in art design, because images are part of art. As the depth of the network deepens, the detail information of the image is lost, which leads to poor segmentation of the edge semantics of objects and objects, and inaccurate prediction of pixel categories in intelligent collaborative robot design. Therefore, this paper proposes a novel DABU-Net model based on principle component analysis for intelligent collaborative robot design. First, we adopt DABU-Net model to extract region of interest in image. Second, the improved channel attention module and spatial attention module extract more important feature details from channel and space respectively. A new image dimensionality reduction algorithm is designed by using principal component analysis, and the algorithm is added to the spatial self -attention module to improve its computing power. Finally, experiments on open data sets show that the proposed method has better segmentation efficiency than other advanced methods.

关键词： DABU-Net model principle component analysis intelligent collaborative robot design self-attention module

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Online prediction of network-level public transport demand based on principle component analysis

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Communications in Transportation Research 2023年第1期3卷 62-71页

作者： Cheng Zhong Peiling Wu Qi Zhang Zhenliang Ma Department of Civil and Architectural Engineering KTH Royal Institute of TechnologyStockholm10044Sweden

Online demand prediction plays an important role in transport network services from operations,controls to management,and information ***,the online prediction models are impacted by streaming data quality issues with noise measurements and missing *** address these,we develop a robust prediction method for online network-level demand prediction in public *** consists of a PCA method to extract eigen demand images and an optimization-based pattern recognition model to predict the weights of eigen demand images by making use of the partially observed real-time data up to the prediction time in a *** prediction model is robust to data quality issues given that the eigen demand images are stable and the predicted weights of them are optimized using the network level data(less impacted by local data quality issues).In the case study,we validate the accuracy and transferability of the model by comparing it with benchmark models and evaluate the robustness in tolerating data quality issues of the proposed *** experimental results demonstrate that the proposed Pattern Recognition Prediction based on PCA(PRP-PCA)consistently outperforms other benchmark models in accuracy and ***,the model shows high robustness in accommodating data quality *** example,the PRP-PCA model is robust to missing data up to 50%regardless of the noise *** also discuss the hidden patterns behind the network level *** visualization analysis shows that eigen demand images are significantly connected to the network structure and station activity *** the demand changes dramatically before and after the pandemic,the eigen demand images are consistent over time in Stockholm.

关键词： Network-level demand prediction Data quality issues Eigen demand image Pattern recognition principle component analysis

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A Long-Term and Global Energy Security Performance Evaluation Model Integrating principle component analysis, Assurance Region Approach, and the Malmquist Technology

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Journal of the Knowledge Economy 2024年 1-32页

作者： Wu, Tai-Hsi Yu, Chi Department of Business Administration National Taipei University 115 University Rd San Shia District New Taipei City 23741 Taiwan Johnson Controls-Hitachi Air Conditioning Taiwan Co. Ltd Taoyuan Taiwan

A comprehensive literature review on energy security performance (ESP) highlighted a major gap in long-term, systematic global ESP studies. While some studies have assessed ESP changes in various countries over 20 years to identify progress or decline, their methods may not accurately reflect long-term ESP trends. Furthermore, the Malmquist productivity index (MPI), commonly used for calculating intertemporal performances and efficiencies, lacks flexibility in adjusting weights for inputs and outputs in assessments. Addressing this gap, this study proposes PCA/MPI-AR, an integrated approach merging principal component analysis (PCA), the assurance region (AR) technique, and MPI, to analyze ESP trends in 125 countries from 1997 to 2017. The results showed MPI-AR scores ranging from 0.3543 to 4.2800, indicating a general trend of ESP improvement over 21 years, with significant recent progress compared to earlier periods. Notably, 107 countries scored at least 1.0, and 3 scored below 0.5. A grouping analysis classified 12 countries as “highly efficient and improving,” with Switzerland, Ireland, Denmark, and Luxembourg as benchmarks. For the countries labeled “inefficient and regressing,” understanding and potentially emulating the strategies of these benchmarks is essential. Adopting this integrated PCA/MPI-AR approach incorporates flexible weighting capabilities and marks a significant advancement in the field of ESP evaluation. It is anticipated that our model will not only align more closely with the real-world conditions under which energy policies are formulated and implemented but also provide a more precise tool for evaluating and comparing the efficiency of different countries in enhancing their ESP. The research also suggests three potential policy directions for improvement in underperforming countries: renewable energy investment, energy efficiency enhancement, and energy taxation policy, as well as enhancing international cooperation through sharing best pr

关键词： Assurance region DEA Energy security performance Malmquist production index MPI-AR principle component analysis

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Risk assessment of chemical mixtures by benchmark dose-principle component analysis approach in occupational exposure

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2021年第41期28卷 58781-58786页

作者： Zendehdel, Rezvan Parsarad, Majid Gandomani, Elham Asgari Panjali, Zahra Rafieepour, Athena Mohammadi, Zahra Moradpour, Zahra Vahabi, Masoomeh Alipour, Maryam Mohammad Gholamiarjenaki, Reza Shahid Beheshti Univ Med Sci Environm & Occupat Hazards Control Res Ctr Tehran Iran Shahid Beheshti Univ Med Sci Sch Publ Hlth & Safety Dept Occupat Hlth Engn & Safety Tehran Iran Islamic Azad Univ Sch Hlth & Med Engn Dept Occupat Hlth & Safety Tehran Med Sci Tehran Iran Shahid Beheshti Univ Med Sci Dept Occupat Hlth Engn Hlth Tehran Iran Natl Iranian Oil Co Pars Oil & Gas Co Tehran Iran

Mixtures of organic solvents are widely used in industrial processes. Risk assessment for chemical co-exposure has always been a challenge in past years. The present study aims to employ principle component analysis (PCA) to produce an entry for benchmark dose approximation in shoemakers based on the color vision effect. A total of 134 subjects consisting of 67 shoemakers and 67 staff workers were employed for Benchmark Dose (BMD) evaluation. Occupational exposure to benzene, toluene, xylene, and n-hexane was evaluated using NIOSH 1501 and OSHA ID-07 methods. The color vision effect was quantified using Lanthony D-15 desaturated test (D-15d). PCA was run for cumulative exposure dose (CED) of the solvents by MATLAB 2018. Finally, the lowest 95% confidence limit of the benchmark dose (BMDL) was determined using US EPA benchmark dose software (BMDS) version 3.2.1. The color confusion index (CCI) level in shoemakers increased from 1 to 1.15 by a median of 1.07. There was a significant difference in the CCI level (p value<0.0001) between exposed and control subjects. The first score of PCA was used as intake dose level (IDL) in solvents co-exposure. Using BMD analysis, the log-logistics model was fitted with a p-value> 0.1 and the lowest BMDL level. BMDL level was evaluated at 1.63, 10.25, 2.21, and 3.35 ppm for benzene, toluene, xylene, and n-hexane, respectively. The results showed a risk of color vision effect with co-exposure to solvents at different levels in the occupational exposure standards. In conclusion BMDL-PCA approach has been suggested for the risk assessment of chemical co-exposure.

关键词： Benchmark dose Organic solvents Color vision impairment principle component analysis Shoemaker

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Dimensional synthesis method of parallel manipulators based on the principle component analysis

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MECHANISM AND MACHINE THEORY 2022年 176卷

作者： Yang, Chao Li, Qinchuan Ye, Wei Jiaxing Univ Coll Mech & Elect Engn Jiaxing 314001 Zhejiang Peoples R China Zhejiang Sci Tech Univ Fac Mech Engn & Automat Hangzhou 310018 Zhejiang Peoples R China

The results of dimensional synthesis have an important influence on the comprehensive performance of parallel manipulators (PMs). Usually, dimensional synthesis for PMs should take multiple performance indices such as kinematic index, stiffness index, etc., into consideration. It is difficult to establish a comprehensive performance index with clear explanation since the nonuniform dimensions of multiple indices. This paper presents a dimensional synthesis method for PMs based on the principle component analysis. For p performance indices that are concerned, m (m < p) principle components are identified to achieve dimensionally reduction. Then a reasonable explanation for the meaning of principle components is provided using factor analysis method. A comprehensive performance index is finally presented, and its weight factors are clearly explained. An intelligent algorithm is adopted for obtaining the optimal comprehensive performance. Meanwhile, a bisection method is employed to accelerate the detection of boundaries of the regular workspace to improve the computational cost of objective functions. A 6-DOFs 6PSS PM is taken as an example to verify the proposed method (where P is a prismatic joint and S is a spherical joint).

关键词： Parallel manipulator Dimensional synthesis principle component analysis Factor analysis Regular workspace Bisection method

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Modeling outdoor thermal comfort using satellite imagery: A principle component analysis-based approach

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ECOLOGICAL INDICATORS 2020年 117卷 106555-106555页

作者： Mijani, Naeim Alavipanah, Seyed Kazem Firozjaei, Mohammad Karimi Arsanjani, Jamal Jokar Hamzeh, Saeid Weng, Qihao Univ Tehran Fac Geog Dept Remote Sensing & GIS Tehran Iran Aalborg Univ Dept Planning & Dev Geoinformat Res Grp AC Meyers Vcenge 15 DK-2450 Copenhagen Denmark Indiana State Univ Ctr Urban & Environm Change Dept Earth & Environm Syst Terre Haute IN 47809 USA

A harmful effect of anthropogenic activities in urban environments is the increases of thermal discomfort and subsequently, a negative effect on humans' mental and physical performance. Therefore, it is of high importance to detect, monitor, and predict thermal discomfort, especially its temporal and spatial patterns in cities. The objective of this study is to propose a new method for modeling outdoor thermal comfort based on remote sensing and climatic datasets. To do so, several datasets were utilized, including those from Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS), Digital Elevation Model (DEM) from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and climatic datasets from local meteorological stations. The method was experimented in the city of Tehran, Iran. For modeling outdoor thermal comfort, the Least Squares Adjustment (LSA) model was presented based on the principle component analysis (PCA). In this model, the principle components (PCs) of the environmental and surface biophysical parameters were considered as independent variables and Discomfort Index (DI) as dependent variable. Finally, by determining the optimal values of the adjustment coefficients for each independent variable, maps of outdoor thermal comfort at different timestamps were produced and analyzed. The results of the modeling showed that correlation coefficient and Root Mean Square Error (RMSE) between the modeled and observed outdoor thermal comfort values at the meteorological stations for the training data sets were 0.86 and 1.80, for the testing data set were 0.89 and 2.04, respectively, while it was 0.85 and 1.15 for the self-deployed devices. The average values of DI in warm season of year was 8.5 degrees C higher than the cold season of the year. Further, in both warm and cold seasons of year the mean value of DI for bare land was found higher than other land covers, whereas that of water bodies lower than others. Our findings suggest tha

关键词： Outdoor thermal comfort Least squares adjustment principle component analysis Thermal remote sensing Urban areas

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Double-Attentive principle component analysis

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IEEE SIGNAL PROCESSING LETTERS 2020年 27卷 1814-1818页

作者： Wu, Danyang Zhang, Han Nie, Feiping Wang, Rong Yang, Chao Jia, Xiaoxue Li, Xuelong Northwestern Polytech Univ Sch Comp Sci Xian 710072 Peoples R China Northwestern Polytech Univ Ctr Opt IMagery Anal & Learning OPTIMAL Xian 710072 Peoples R China Aircraft Strength Res Inst Dept Composite Struct Strength Xian 710065 Peoples R China

This letter proposes a double-attentive principle component analysis (DA-PCA) model for image processing. Compared to the previous PCA-based works that cannot deal with normal images and outliers effectively, the proposed DA-PCA model performs a double-attentive mechanism to sever the connections with outliers and hold the effectiveness of normal images. To solve the proposed DA-PCA model, we propose an efficiently iterative algorithm and provide strict convergence analysis for it. Moreover, in the simulations, we conduct the reconstruction and classification experiments on several real datasets and the experimental results demonstrate the superb performance of our proposal.

关键词： Principal component analysis Analytical models Image reconstruction Signal processing algorithms Convergence Robustness principle component analysis robust learning attentive mechanism image reconstruction

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Evaluation of morphometric analysis of flash flood potential of Eastern Mediterranean Basin using principle component analysis

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2021年第3期36卷 1670-1685页

作者： Kocyigit, Musteyde Baduna Akay, Huseyin Babaiban, Egemen Gazi Univ Muhendisl Fak Insaat Muhendisligi Bolumu TR-06570 Maltepe Turkey Gazi Univ Fen Bilimleri Enstitusu Insaat Muhendisligi Anabilim Dali Yuksek Lisans Ogrencisi TR-06680 Ankara Turkey

In this study, the flash flood potential of the Eastern Mediterranean Basin was examined by using morphometric analysis. Basin was divided into 8 main, with 775 sub-basins in total, and twelve morphometric parameters were computed for each sub-basin. Drainage density, Ro coefficient and bifurcation, texture, elongation and circulatory ratios were determined to be used in classifying sub-basins according to their flash flood potential by using principal component analysis. The sub-basins are divided into five categories in terms of their flash flood potential as very high, high, medium, low and very low. The flash flood potential categories of the sub-basins determined from the analysis were then compared with the recorded flood events for each eight main sub-basin and the reliability and applicability of the approach was thus tested. It was noted that successful results were achieved in main sub-basins with large drainage areas whereas in main sub-basins with small drainage areas, floods were generally experienced in sub-basins with low flash flood potential, and no floods occurred in sub-basins that are in high risk category according to the records. The reason for these results is thought to be due to the determination of the components evaluated using all 775 sub-basins of the Eastern Mediterranean Basin in the principal component analysis and thus the effective parameters in the small sub-basins with structural differences might have lost their effect when evaluated throughout the whole basin. To improve the results obtained from the study, it is believed that besides morphometric parameters, factors which directly affect the rainfall-runoff relationship such as vegetation cover, land use, basin geology and water use in the basin should be taken into consideration.

关键词： Eastern Mediterranean Basin flash flood risk estimation basin prioritization morphometric analysis principle component analysis

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Anti-Staphylococcus aureus evaluation of gallic acid by isothermal microcalorimetry and principle component analysis

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JOURNAL OF THERMAL analysis AND CALORIMETRY 2019年第3期136卷 1425-1432页

作者： Pu, Shi-biao Ma, Zhi-jie Wang, Qi Beijing Univ Tradit Chinese Med Beijing 100029 Peoples R China Yunnan Univ Tradit Chinese Med Kunming 650500 Yunnan Peoples R China Capital Med Univ Beijing Friendship Hosp Pharm Dept Beijing 100050 Peoples R China

The emergence of antibiotic-resistant Staphylococcus aureus requires new antibacterial drugs. In this study, using a thermal activity monitor air isothermal microcalorimeter, the heat flow power-time curves of S. aureus growth at 37 degrees C in the presence of different concentrations of gallic acid were determined. By analyzing the metabolic curves and some quantitative thermo-kinetic parameters obtained from these curves with the help of principle component analysis (PCA), the antibacterial effects of gallic acid on S. aureus were rapidly and accurately evaluated. Growth rate constant k(2) of the second exponential phase and the maximum heat flow output power P-2 for S. aureus growth were selected as the two main parameters for the antibacterial evaluation. Results showed that 10 mu g mL(-1) of gallic acid began to inhibit the growth of S. aureus, and high concentrations (more than 20 mu g mL(-1)) of this compound exhibited strong anti-S. aureus effects. 63.51 mu g mL(-1) of gallic acid resulted in a 50% inhibitory ratio on S. aureus. All these illustrated that the anti-S. aureus effects were enhanced with increasing the concentration of this compound. Gallic acid can be used as a new natural and safe antibacterial drug for treating multidrug-resistant S. aureus. This work provided a useful idea of the combination of microcalorimetry and PCA for highly sensitive evaluation of the antibacterial effects of various compounds, providing reliable references for screening out new antibacterial drugs.

关键词： Isothermal microcalorimetry S. aureus Gallic acid principle component analysis Growth inhibitory ratio

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