Showing 3,101 - 3,120 results of 8,512 for search 'sequence evaluation', query time: 0.17s Refine Results
  1. 3101

    TECHNIQUE AND HARDWARE FOR THE FREE OSCILLATION FREQUENCY DETERMINATION OF MODERNIZED SAWING UNIT ARROW by M. G. Kiselyov, A. V. Drozdov, D. A. Yamnaya

    Published 2015-03-01
    “…On the basis of experimentally evaluated values of the free oscillation frequency of the arrow and coefficient of rigidity of its subweight parameters of excitement of oscillatory system are established. …”
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    Article
  2. 3102
  3. 3103

    Mesenchymal stromal cell isolation from pond slider (Trachemys scripta) adipose tissue obtained during routine neutering: a model for turtle species by Valentina Andreoli, Alessandro Vetere, Virna Conti, Martina Gavezzoli, Priscilla Berni, Roberto Ramoni, Giuseppina Basini, Giordano Nardini, Igor Pelizzone, Stefano Grolli, Francesco Di Ianni

    Published 2025-03-01
    “…RT–PCR revealed the expression of CD105, CD73, CD44, and CD90, whereas CD34 and HLA-DRA were not expressed. Sequence homology analysis demonstrated that the amplicons matched the sequences reported in the Trachemys scripta whole-genome shotgun sequence. …”
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    Article
  4. 3104

    The Quality of Randomized Controlled Trial in Cochrane Kidney and Transplant Group by Hanieh Salehi-Pourmehr, Ali Mostafaei, Amir Mehdizadeh, Sakineh Hajebrahimi, Leila Hosseini, Zahra Sheikhalipour, Nasrin Abolhasanpour

    Published 2021-12-01
    “…From 2008 to 2009, high random sequence generation bias has dramatically increased, and after decreasing, the gradual growth has been continuing over time. …”
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    Article
  5. 3105

    Rapid Detection of Feline Calicivirus Using Lateral Flow Dipsticks Based on CRISPR/Cas13a System by Zichuang Zhang, Jing Li, Chengqi Zhang, Xue Bai, Tie Zhang

    Published 2024-12-01
    “…To construct the Cas13a-RAA-LFD reaction system, this study specifically designed recombinase-aided amplification (RAA) primers added with a T7 promoter and CRISPR RNA (crRNA), which were both based on the FCV relatively conserved sequence. The Cas13a protein cleaved the reporting probes only when crRNA recognized the target sequence. …”
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    Article
  6. 3106

    Brain tumor segmentation using deep learning: high performance with minimized MRI data by Jacky Huang, Banu Yagmurlu, Powell Molleti, Richard Lee, Abigail VanderPloeg, Humaira Noor, Rohan Bareja, Yiheng Li, Michael Iv, Haruka Itakura

    Published 2025-07-01
    “…We compared the performances of models trained on four different combinations of MRI sequences: T1C-only, FLAIR-only, T1C + FLAIR and T1 + T2 + T1C + FLAIR to evaluate whether a smaller MRI data subset could achieve comparable performance. …”
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    Article
  7. 3107

    Identifying the confidence level of activity recognition via HMM by Chang-hai WANG, Jian-zhong ZHANG, Jing-dong XU, Yu-wei XU

    Published 2016-05-01
    “…A context-based method to identify the confidence level of activ recognition was proposed,referred to as S-HMM(sliding window hidden Markov model),which reduced the confusion rate and facilitated the transfer learning.With S-HMM,the activity recognition sequence was modeled as HMM(hidden Markov model)and the corresponding probability was adopted as the confidence level.This ,S-HMM removed the dependency of the confidence level on the sample distribution in the feature space.S-HMM is extensively evaluated based on real-life activity data,demonstrat-ing a reduced confusion rate of 37% when compared to the state-of-the-art methods.…”
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    Article
  8. 3108

    Identifying the confidence level of activity recognition via HMM by Chang-hai WANG, Jian-zhong ZHANG, Jing-dong XU, Yu-wei XU

    Published 2016-05-01
    “…A context-based method to identify the confidence level of activ recognition was proposed,referred to as S-HMM(sliding window hidden Markov model),which reduced the confusion rate and facilitated the transfer learning.With S-HMM,the activity recognition sequence was modeled as HMM(hidden Markov model)and the corresponding probability was adopted as the confidence level.This ,S-HMM removed the dependency of the confidence level on the sample distribution in the feature space.S-HMM is extensively evaluated based on real-life activity data,demonstrat-ing a reduced confusion rate of 37% when compared to the state-of-the-art methods.…”
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    Article
  9. 3109

    A New Sixth Order Method for Nonlinear Equations in R by Sukhjit Singh, D. K. Gupta

    Published 2014-01-01
    “…The number of iterations and the total number of function evaluations used to get a simple root are taken as performance measure of our method. …”
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    Article
  10. 3110

    Targeting intestinal inflammation using locked nucleic acids delivered via lipid nanoparticles by Shahd Qassem, Gonna Somu Naidu, Meir Goldsmith, Dor Breier, Riccardo Rampado, Srinivas Ramishetti, Michael Keller, Felix Schumacher, Kara G. Lassen, Leilah Otikovs, Roman Kamyshinsky, Inbal Hazan-Halevy, Dan Peer

    Published 2025-08-01
    “…The most potent formulation, encapsulating a sequence against Tumor necrosis factor alpha, was evaluated in a mouse model of colitis. …”
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    Article
  11. 3111
  12. 3112
  13. 3113

    Validation of genetic risk scores for hypertension in the Central Russian population by A. S. Limonova, A. I. Ershova, A. V. Kiseleva, V. A. Kutsenko, V. E. Ramensky, Yu. V. Vyatkin, E. A. Sotnikova, A. A. Zharikova, M. Zaichenoka, M. S. Pokrovskaya, S. А. Shalnova, A. N. Meshkov, O. M. Drapkina

    Published 2023-12-01
    “…Aim. To validate and evaluate the accuracy of 4 genetic risk scores (GRSs) for hypertension (HTN), previously created on European samples, on a population sample of the Ivanovo Oblast.Material and methods. …”
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    Article
  14. 3114

    Deciphering genetic relationships within and among banana (Musa spp.) genome groups using ISSR and SRAP markers by Roshida Soraisham, Punshi Tongbram, Surendrakumar Singh Thingnam, Boris Aheibam, John Zothanzama, Dinamani Singh Lourembam, Robert Thangjam

    Published 2025-09-01
    “…In the present study, the genetic relationship between and among 28 banana (Musa spp.) accessions representing 5 genome groups (AAA, BB, AAB, ABB and AB) were evaluated using sequence-related amplified polymorphism (SRAP) and inter simple sequence repeat (ISSR) markers. …”
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    Article
  15. 3115

    Radiotherapy and MVA-MUC1-IL-2 vaccine act synergistically for inducing specific immunity to MUC-1 tumor antigen by Philippe Slos, Gilda G. Hillman, Lyndsey A. Reich, Shoshana E. Rothstein, Lisa M. Abernathy, Matthew D. Fountain, Kali Hankerd, Christopher K. Yunker, Joseph T. Rakowski, Eric Quemeneur

    Published 2017-11-01
    “…To investigate whether tumor irradiation augments the immune response to MUC1 tumor antigen, we have tested the efficacy of tumor irradiation combined with an MVA-MUC1-IL2 cancer vaccine (Transgene TG4010) for murine renal adenocarcinoma (Renca) cells transfected with MUC1.Methods Established subcutaneous Renca-MUC1 tumors were treated with 8 Gy radiation on day 11 and peritumoral injections of MVA-MUC1-IL2 vector on day 12 and 17, or using a reverse sequence of vaccine followed by radiation. Growth delays were monitored by tumor measurements and histological responses were evaluated by immunohistochemistry. …”
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  16. 3116
  17. 3117

    Bridging One Health: Computational design of a multi-epitope messenger RNA vaccine for cross-species immunization against Nipah virus by Edward C. Banico, Ella Mae Joy S. Sira, Lauren Emily Fajardo, Fredmoore L. Orosco

    Published 2024-11-01
    “…Signal peptides were added to the construct, and mRNA sequences were generated using LinearDesign. The minimum free energies (MFEs) and codon adaptation indices (CAI) were used to select the final mRNA sequence of the vaccine construct. …”
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  18. 3118

    Cross-sectional and longitudinal Biomarker extraction and analysis for multicentre FLAIR brain MRI by J. DiGregorio, A. Gibicar, H. Khosravani, P. Jabehdar Maralani, J.-C. Tardif, P.N. Tyrrell, A.R. Moody, A. Khademi

    Published 2022-06-01
    “…In this work, automated tools were used to extract biomarkers from large, FLAIR-only datasets to evaluate the feasibility of this sequence to characterize healthy, AD, and CVD subjects in a similar manner to traditional approaches. …”
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    Article
  19. 3119

    Synergistic effect and mechanism of meropenem with ciprofloxacin against carbapenem-resistant Acinetobacter baumannii by Ying Feng, Xu Chen, Yu Sun, Tingting Guo, Feng Wu, Feng Jin, Jun Zhou

    Published 2025-05-01
    “…The antibacterial efficacy of meropenem combined with ciprofloxacin was evaluated using checkerboard and growth curve assays. …”
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    Article
  20. 3120

    NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides by Chengzhi Xie, Yijie Wei, Xinwei Luo, Huan Yang, Hongyan Lai, Fuying Dao, Juan Feng, Hao Lv

    Published 2025-07-01
    “…NeXtMD systematically extracts four functionally relevant sequence-derived descriptors—residue composition, inter-residue correlation, physicochemical properties, and sequence patterns—and utilizes a two-stage prediction strategy. …”
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    Article