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Journal articles on the topic 'Localized features'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 May 2022

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1

Liu, P., Y. Uziel, S. Chuang, E. Silverman, B. Krafchik, and R. Laxer. "Localized scleroderma: Imaging features." Pediatric Radiology 24, no. 3 (June 1994): 207–9. http://dx.doi.org/10.1007/bf02012193.

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2

Hong, Yong Tae, and Ki Hwan Hong. "Localized Laryngeal Myxoma: Laryngoscopic Features." Ear, Nose & Throat Journal 99, no. 5 (April 28, 2019): NP56—NP57. http://dx.doi.org/10.1177/0145561319840234.

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3

Versluis, P. J., and R. J. S. Lamers. "Localized pleural fibroma: radiological features." European Journal of Radiology 18, no. 2 (May 1994): 124–25. http://dx.doi.org/10.1016/0720-048x(94)90278-x.

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4

Higgins, Gary J. "Detecting and Correcting Localized Roughness Features." Transportation Research Record: Journal of the Transportation Research Board 2525, no. 1 (January 2015): 71–78. http://dx.doi.org/10.3141/2525-08.

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Data collected by inertial profilers on new asphalt pavements in Colorado in 2012 were used to analyze the effectiveness of the localized roughness specification in Colorado. For the analyzed projects, data were collected before any corrections were made as well as after diamond grinding had been performed to remove areas of localized roughness. The data indicated that localized roughness features having a half-car roughness index (HRI) lower than 175 in./mi were rarely addressed during correction. However, about half the localized roughness features that had an HRI of 175 to 200 in./mi were successfully addressed during correction. Localized roughness features having an HRI greater than 200 in./mi appeared to be successfully addressed during correction. The analysis indicated a significant difference in the localized roughness locations identified by AASHTO R 54 and the Colorado Department of Transportation (DOT) method of detecting localized roughness. The Colorado DOT procedure specifies a minimum length for a roughness feature that is to be corrected, but AASHTO R 54 does not. This paper shows that collecting accurate profile data and analyzing the data to determine localized roughness locations are not enough. The identified locations must be correctly marked on the pavement in the field so that the feature does not cause localized roughness. This paper presents a procedure not only for collecting accurate data but also for accurately marking the roughness features in the field. It is shown that it is possible to locate and correct localized roughness accurately to the current thresholds as set by AASHTO R 54.

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5

YUAN, Yuan, Sheng-nan REN, Xiao-yu GUO, Xiao-long MA, and Jian-ping LU. "CT features of localized tracheobronchial amyloidosis." Academic Journal of Second Military Medical University 36, no. 12 (2015): 1385. http://dx.doi.org/10.3724/sp.j.1008.2015.01385.

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6

Jogan, Matjaz, Benjamin Serbiak, and Laura Higgins. "Human perception of localized skin features." Journal of Vision 19, no. 10 (September 6, 2019): 228a. http://dx.doi.org/10.1167/19.10.228a.

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7

Arndt, Petra A., Hanspeter A. Mallot, and Heinrich H. B\"ulthoff. "Human stereovision without localized image features." Biological Cybernetics 72, no. 4 (March 1, 1995): 279–93. http://dx.doi.org/10.1007/s004220050130.

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8

Arndt, Petra A., Hanspeter A. Mallot, and Heinrich H. Bülthoff. "Human stereovision without localized image features." Biological Cybernetics 72, no. 4 (March 1995): 279–93. http://dx.doi.org/10.1007/bf00202784.

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9

Sulaiman, Dawlat Mustafa, Adnan Mohsin Abdulazeez, and Habibollah Haron. "Double stages of feature extarction-based GFPMI for colored finger vein identification." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 2 (May 1, 2020): 927. http://dx.doi.org/10.11591/ijeecs.v18.i2.pp927-937.

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Today, finger vein recognition has a lot of attention as a promising approach of biometric identification framework and still does not meet the challenges of the researchers on this filed. To solve this problem, we propose s double stage of feature extraction schemes based localized finger fine image detection. We propose Globalized Features Pattern Map Indication (GFPMI) to extract the globalized finger vein line features basede on using two generated vein image datasets: original gray level color, globalized finger vein line feature, original localized gray level image, and the colored localized finger vein images. Then, two kinds of features (gray scale and texture features) are extracted, which tell the structure information of the whole finger vein pattern in the whole dataset. The recurrent based residual neural network (RNN) is used to identify the finger vein images. The experimental show that the localized colored finger vein images based globalized feature extraction has achieved the higher accuracy (93.49%) while the original image dataset achieved less accuracy by (69.86%).

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10

Casalino, Gabriella, and Nicolas Gillis. "Sequential dimensionality reduction for extracting localized features." Pattern Recognition 63 (March 2017): 15–29. http://dx.doi.org/10.1016/j.patcog.2016.09.006.

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11

Diepgen, T. L., J. Tacke, and H. Schell. "Acral localized melanoma — clinical and prognostic features." Melanoma Research 3 (September 1993): 44. http://dx.doi.org/10.1097/00008390-199309002-00165.

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12

Schanz, Stefan, Gerhard Fierlbeck, Anja Ulmer, Marc Schmalzing, Jasmin Kümmerle-Deschner, Claus D. Claussen, and Marius Horger. "Localized Scleroderma: MR Findings and Clinical Features." Radiology 260, no. 3 (September 2011): 817–24. http://dx.doi.org/10.1148/radiol.11102136.

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13

Farhan, Erez. "Highly Accurate Matching of Weakly Localized Features." SIAM Journal on Imaging Sciences 12, no. 4 (January 2019): 1833–63. http://dx.doi.org/10.1137/18m1231626.

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14

Sudhakaran, Swathikiran, and Alex Pappachen James. "Sparse distributed localized gradient fused features of objects." Pattern Recognition 48, no. 4 (April 2015): 1538–46. http://dx.doi.org/10.1016/j.patcog.2014.10.002.

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15

SASAKI, Masahiro, and Shigehiko YAMAMOTO. "Localized and Delocalized Features of Microscopic Work Functions." Shinku 50, no. 5 (2007): 313–18. http://dx.doi.org/10.3131/jvsj.50.313.

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16

Kim, J. "US features of localized form of xanthogranulomatous pyelonephritis." Ultrasound in Medicine & Biology 29, no. 5 (May 2003): S16. http://dx.doi.org/10.1016/s0301-5629(03)00125-x.

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17

Fernandez-Flores, Angel, and David S. Cassarino. "Gottron Papules Show Histopathologic Features of Localized Lymphedema." American Journal of Dermatopathology 39, no. 7 (July 2017): 518–23. http://dx.doi.org/10.1097/dad.0000000000000701.

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18

Darbar, Dawood, Kenton Zehr, Jerome F. Breen, and Roger Click. "Localized Aortic Dissection: Unusual Features by Transesophageal Echocardiography." Journal of the American Society of Echocardiography 13, no. 12 (December 2000): 1130–34. http://dx.doi.org/10.1067/mje.2000.108467.

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19

Saito, Ryo, and Yu-ichi Takamizu. "Localized features in non-Gaussianity from heavy physics." Journal of Cosmology and Astroparticle Physics 2013, no. 06 (June 21, 2013): 031. http://dx.doi.org/10.1088/1475-7516/2013/06/031.

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20

Ludlam, J. J., S. N. Taraskin, S. R. Elliott, and D. A. Drabold. "Universal features of localized eigenstates in disordered systems." Journal of Physics: Condensed Matter 17, no. 30 (July 15, 2005): L321—L327. http://dx.doi.org/10.1088/0953-8984/17/30/l01.

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21

Kim, Hyae Young, Jung-Gi Im, Koun-Sik Song, Kyung Soo Lee, Sang Jin Kim, Joung Sook Kim, Jin Seong Lee, and Tae-Hwan Lim. "Localized Amyloidosis of the Respiratory System: CT Features." Journal of Computer Assisted Tomography 23, no. 4 (July 1999): 627–31. http://dx.doi.org/10.1097/00004728-199907000-00026.

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22

Giagkos, Alexandros, Daniel Lewkowicz, Patricia Shaw, Suresh Kumar, Mark Lee, and Qiang Shen. "Perception of Localized Features During Robotic Sensorimotor Development." IEEE Transactions on Cognitive and Developmental Systems 9, no. 2 (June 2017): 127–40. http://dx.doi.org/10.1109/tcds.2017.2652129.

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23

Jaiswal, Vilkesh R., Julie Baird, Jason Fleming, David Scott Miller, Suash Sharma, and Kyle Molberg. "Localized Retroperitoneal Lymphangioleiomyomatosis Mimicking Malignancy." Archives of Pathology & Laboratory Medicine 127, no. 7 (July 1, 2003): 879–82. http://dx.doi.org/10.5858/2003-127-879-lrlmm.

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Abstract Lymphangioleiomyomatosis (lymphangiomyomatosis [LAM]), a rare disease of unknown etiology that is seen only in women usually in the reproductive period, generally presents with features of pulmonary involvement. Extrapulmonary involvement, such as angiomyolipomas and retroperitoneal adenopathy, can occur in up to 75% of cases. It is very rare, however, for patients to present with features of extrapulmonary LAM. We present an unusual, localized case of LAM presenting with neurologic symptoms related to a retroperitoneal mass in a 51-year-old woman. Magnetic resonance imaging showed that the mass involved retroperitoneal lymph nodes, and a clinical diagnosis of atypical sarcoma (possibly from a uterine primary) was made. The mass was resected, and a total abdominal hysterectomy was performed. On pathologic examination, the mass showed classic histologic features of LAM with spread along lymphatic channels in the lymph nodes. Intralymphatic projections simulated lymphatic metastasis; however, the cytologic features were benign. Immunostains revealed the tumor to be positive for smooth muscle actin and desmin, but negative for HMB-45. The uterus was unremarkable, except for a subserosal leiomyoma. Although intratumoral variability for HMB-45 has recently been described, to the best of our knowledge, this is the first documented case of HMB-45–negative, histologically classic LAM. Because of the presence of several atypical features in this case, such as age, location, compressive neurologic presentation, radiologic impression of atypical sarcoma, and HMB-45 negativity, we feel that this case may represent a distinct, as yet uncharacterized variant of LAM.

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24

Jemilda, G., and S. Baulkani. "Moving Object Detection and Tracking using Genetic Algorithm Enabled Extreme Learning Machine." International Journal of Computers Communications & Control 13, no. 2 (April 13, 2018): 162–74. http://dx.doi.org/10.15837/ijccc.2018.2.3064.

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In this proposed work, the moving object is localized using curvelet transform, soft thresholding and frame differencing. The feature extraction techniques are applied on to the localized object and the texture, color and shape information of objects are considered. To extract the shape information, Speeded Up Robust Features (SURF) is used. To extract the texture features, the Enhanced Local Vector Pattern (ELVP) and to extract color features, Histogram of Gradient (HOG) are used and then reduced feature set obtained using genetic algorithm are fused to form a single feature vector and given into the Extreme Learning Machine (ELM) to classify the objects. The performance of the proposed work is compared with Naive Bayes, Support Vector Machine, Feed Forward Neural Network and Probabilistic Neural Network and inferred that the proposed method performs better.

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25

Farhan, Erez. "Matching of Weakly-Localized Features under Different Geometric Models." Image Processing On Line 10 (February 22, 2020): 1–23. http://dx.doi.org/10.5201/ipol.2020.247.

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26

Ata, Mohamed Abbas. "Features of biochemical changes in patients with localized scleroderмa." ScienceRise: Medical Science, no. 1 (28) (February 7, 2019): 20–24. http://dx.doi.org/10.15587/2519-4798.2019.156030.

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27

Cross, J., W. N. Nasser, and L. C. Carbone. "MAGNETIC RESONANCE IMAGING FEATURES OF LIMB-LOCALIZED POLYARTERITIS NODOSA." Journal of Investigative Medicine 55, no. 1 (January 2007): S253. http://dx.doi.org/10.1097/00042871-200701010-00554.

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28

Fenzi, F., A. Simonati, F. Crosato, L. Ghersini, and N. Rizzuto. "Clinical Features of Kleine-Levin Syndrome with Localized Encephalitis." Neuropediatrics 24, no. 05 (October 1993): 292–95. http://dx.doi.org/10.1055/s-2008-1071559.

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29

Yu, M. L., F. X. Giraldo, M. Peng, and Z. J. Wang. "Localized Artificial Viscosity Stabilization of Discontinuous Galerkin Methods for Nonhydrostatic Mesoscale Atmospheric Modeling." Monthly Weather Review 143, no. 12 (November 24, 2015): 4823–45. http://dx.doi.org/10.1175/mwr-d-15-0134.1.

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Abstract Gibbs oscillation can show up near flow regions with strong temperature gradients in the numerical simulation of nonhydrostatic mesoscale atmospheric flows when using the high-order discontinuous Galerkin (DG) method. The authors propose to incorporate flow-feature-based localized Laplacian artificial viscosity in the DG framework to suppress the spurious oscillation in the vicinity of sharp thermal fronts but not to contaminate the smooth flow features elsewhere. The parameters in the localized Laplacian artificial viscosity are modeled based on both physical criteria and numerical features of the DG discretization. The resulting numerical formulation is first validated on several shock-involved test cases, including a shock discontinuity problem with the one-dimensional Burger’s equation, shock–entropy wave interaction, and shock–vortex interaction. Then the efficacy of the developed numerical formulation on stabilizing thermal fronts in nonhydrostatic mesoscale atmospheric modeling is demonstrated by two benchmark test cases: the rising thermal bubble problem and the density current problem. The results indicate that the proposed flow-feature-based localized Laplacian artificial viscosity method can sharply detect the nonsmooth flow features, and stabilize the DG discretization nearby. Furthermore, the numerical stabilization method works robustly for a wide range of grid sizes and polynomial orders without parameter tuning in the localized Laplacian artificial viscosity.

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30

Guan, Chen-Ning, Chia-Feng Juang, and Guo-Cyuan Chen. "Face localization using fuzzy classifier with wavelet-localized focus color features and shape features." Digital Signal Processing 22, no. 6 (December 2012): 961–70. http://dx.doi.org/10.1016/j.dsp.2012.05.011.

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31

WALKER, ROSS F., PAUL T. JACKWAY, and DENNIS LONGSTAFF. "GENETIC ALGORITHM OPTIMIZATION OF ADAPTIVE MULTI-SCALE GLCM FEATURES." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 01 (February 2003): 17–39. http://dx.doi.org/10.1142/s0218001403002228.

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We introduce a new second-order method of texture analysis called Adaptive Multi-Scale Grey Level Co-occurrence Matrix (AMSGLCM), based on the well-known Grey Level Co-occurrence Matrix (GLCM) method. The method deviates significantly from GLCM in that features are extracted, not via a fixed 2D weighting function of co-occurrence matrix elements, but by a variable summation of matrix elements in 3D localized neighborhoods. We subsequently present a new methodology for extracting optimized, highly discriminant features from these localized areas using adaptive Gaussian weighting functions. Genetic Algorithm (GA) optimization is used to produce a set of features whose classification "worth" is evaluated by discriminatory power and feature correlation considerations. We critically appraised the performance of our method and GLCM in pairwise classification of images from visually similar texture classes, captured from Markov Random Field (MRF) synthesized, natural, and biological origins. In these cross-validated classification trials, our method demonstrated significant benefits over GLCM, including increased feature discriminatory power, automatic feature adaptability, and significantly improved classification performance.

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32

Grimes, David B., and Rajesh P. N. Rao. "Bilinear Sparse Coding for Invariant Vision." Neural Computation 17, no. 1 (January 1, 2005): 47–73. http://dx.doi.org/10.1162/0899766052530893.

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Recent algorithms for sparse coding and independent component analysis (ICA) have demonstrated how localized features can be learned from natural images. However, these approaches do not take image transformations into account. We describe an unsupervised algorithm for learning both localized features and their transformations directly from images using a sparse bilinear generative model. We show that from an arbitrary set of natural images, the algorithm produces oriented basis filters that can simultaneously represent features in an image and their transformations. The learned generative model can be used to translate features to different locations, thereby reducing the need to learn the same feature at multiple locations, a limitation of previous approaches to sparse coding and ICA. Our results suggest that by explicitly modeling the interaction between local image features and their transformations, the sparse bilinear approach can provide a basis for achieving transformation-invariant vision.

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33

Li, Suzanne C., Xiaohu Li, Elena Pope, Katie Stewart, Gloria C. Higgins, C. Egla Rabinovich, Kathleen M. O’Neil, et al. "New Features for Measuring Disease Activity in Pediatric Localized Scleroderma." Journal of Rheumatology 45, no. 12 (September 15, 2018): 1680–88. http://dx.doi.org/10.3899/jrheum.171381.

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Objective.To identify clinical features that define disease activity in pediatric localized scleroderma (LS), and determine their specificity and importance.Methods.We conducted a multicenter prospective study of patients with active and inactive LS skin lesions. A standardized evaluation of a single designated study lesion per subject was performed at 3 visits. We evaluated the pattern and correlation between assessed features and physician’s global assessments of activity (PGA-A).Results.Ninety of 103 subjects had evaluable data; 66 had active and 24 inactive disease. Subjects had similar age of onset, sex, and disease patterns. Linear scleroderma was the most common subtype. Features specific for active disease included erythema, violaceous color, tactile warmth, abnormal skin texture, and disease extension. Scores for these variables changed over time and correlated with PGA-A of the lesion. Active and inactive lesions could not be distinguished by the presence or level of skin thickening, either of lesion edge or center. However, in active lesions, skin thickening scores did correlate with PGA–A scores. Regression analysis identified the combination of erythema, disease extension, violaceous color, skin thickening, and abnormal texture as predictive of PGA-A at study entry. Damage features were common irrespective of activity status.Conclusion.We identified variables strongly associated with disease activity, expanding upon those used in current measures, and determined their relative importance in physician activity scoring. Skin thickening was found to lack specificity for disease activity. These results will help guide development of a sensitive, responsive activity tool to improve care of patients with LS.

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34

Gubin, M. Yu, A. V. Shesterikov, S. N. Karpov, and A. V. Prokhorov. "Features of localized plasmons formation in four-particle spaser systems." Journal of Physics: Conference Series 951 (January 2018): 012034. http://dx.doi.org/10.1088/1742-6596/951/1/012034.

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35

Escribano Paredes, J. Bernardo, Rodrigo Carrasco Moro, María López Gutiérrez, Héctor Pian Arias, Mónica García-Cosío, Sebastián García Madrona, Velina Nedkova Hristova, Javier Martínez Poles, and Javier Buisán Catevilla Francisco. "Radiologic and Histopathologic Features in an Intracranial Localized Castleman Disease." Neurologist 24, no. 1 (January 2019): 33–36. http://dx.doi.org/10.1097/nrl.0000000000000203.

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36

Herrick, A. L., H. Ennis, M. Bhushan, A. J. Silman, and E. M. Baildam. "Clinical features of childhood localized scleroderma in an incidence cohort." Rheumatology 50, no. 10 (July 5, 2011): 1865–68. http://dx.doi.org/10.1093/rheumatology/ker142.

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37

Kurzinski, Katherine, and Kathryn S. Torok. "Cytokine profiles in localized scleroderma and relationship to clinical features." Cytokine 55, no. 2 (August 2011): 157–64. http://dx.doi.org/10.1016/j.cyto.2011.04.001.

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38

Danilov, V. I., V. V. Gorbatenko, L. V. Danilova, and D. V. Orlova. "Features of switching autowaves of localized plasticity in FCC alloy." Izvestiya vysshikh uchebnykh zavedenii. Fizika, no. 3 (2021): 27–32. http://dx.doi.org/10.17223/00213411/64/3/27.

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The kinetics of deformation processes at the yield plateau in the aluminum alloy 1550 studied. It is established that in the general case, the motion of the Lüders band fronts occurs discretely and only in the phase of sample unloading. Continuous motion of the deformation fronts is possible if the rate of relaxation of the applied stresses due to the test machine is greater than or equal to the rate of their decline, controlled by internal processes at a lower scale level. The discrete motion of the Lüders fronts in the 1550 alloy suggests that they are not pure autowaves of switching.

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39

Yin, Hong, Nasir Alhasan, Alfonso Ciervo, and Louis Zinterhofer. "Soft Tissue Amyloidoma With Features of Plasmacytoma." Archives of Pathology & Laboratory Medicine 126, no. 8 (August 1, 2002): 969–71. http://dx.doi.org/10.5858/2002-126-0969-stawfo.

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Abstract Soft tissue amyloidoma is rare, and soft tissue amyloidoma associated with plasmacytoma and without evidence of systemic amyloidosis is even more rare. We report a case of soft tissue amyloidoma associated with an apparently localized monoclonal proliferation of plasma cells (plasmacytoma).

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40

Levitan, Alexander, Avihai Danon, and Thomas Lisowsky. "Unique Features of Plant Mitochondrial Sulfhydryl Oxidase." Journal of Biological Chemistry 279, no. 19 (March 2, 2004): 20002–8. http://dx.doi.org/10.1074/jbc.m312877200.

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The yeast and human mitochondrial sulfhydryl oxidases of the Erv1/Alr family have been shown to be essential for the biogenesis of mitochondria and the cytosolic iron sulfur cluster assembly. In this study we identified a likely candidate for the first mitochondrial flavin-linked sulfhydryl oxidase of the Erv1-type from a photosynthetic organism. The central core of the plant enzyme (AtErv1) exhibits all of the characteristic features of the Erv1/Alr protein family, including a redox-active YPCXXC motif, noncovalently bound FAD, and sulfhydryl oxidase activity. Transient expression of fusion proteins of AtErv1 and the green fluorescence protein in plant protoplasts showed that the plant enzyme preferentially localizes to the mitochondria. Yet AtErv1 has several unique features, such as the presence of a CXXXXC motif in its carboxyl-terminal domain and the absence of an amino-terminally localized cysteine pair common to yeast and human Erv1/Alr proteins. In addition, the dimerization of AtErv1 is not mediated by its amino terminus but by its unique CXXXXC motif.In vitroassays with purified protein and artificial substrates demonstrate a preference of AtErv1 for dithiols with a defined space between the thiol groups, suggesting a thioredoxin-like substrate.

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41

Le, Trang Thanh Quynh, Thuong-Khanh Tran, and Manjeet Rege. "Rank-Pooling-Based Features on Localized Regions for Automatic Micro-Expression Recognition." International Journal of Multimedia Data Engineering and Management 11, no. 4 (October 2020): 25–37. http://dx.doi.org/10.4018/ijmdem.2020100102.

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Facial micro-expression is a subtle and involuntary facial expression that exhibits short duration and low intensity where hidden feelings can be disclosed. The field of micro-expression analysis has been receiving substantial awareness due to its potential values in a wide variety of practical applications. A number of studies have proposed sophisticated hand-crafted feature representations in order to leverage the task of automatic micro-expression recognition. This paper employs a dynamic image computation method for feature extraction so that features can be learned on certain localized facial regions along with deep convolutional networks to identify micro-expressions presented in the extracted dynamic images. The proposed framework is simple as opposed to other existing frameworks which used complex hand-crafted feature descriptors. For performance evaluation, the framework is tested on three publicly available databases, as well as on the integrated database in which individual databases are merged into a data pool. Impressive results from the series of experimental work show that the technique is promising in recognizing micro-expressions.

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42

Compagnini, Giuseppe, Marcello Condorelli, Maria E. Fragalà, Vittorio Scardaci, Ilaria Tinnirello, Orazio Puglisi, Fortunato Neri, and Enza Fazio. "Growth Kinetics and Sensing Features of Colloidal Silver Nanoplates." Journal of Nanomaterials 2019 (January 15, 2019): 1–8. http://dx.doi.org/10.1155/2019/7084731.

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This paper presents the growth mechanisms and the plasmon sensing features for a large class of silver nanoplates obtained in the colloidal form. The synthesis is conducted by seed-mediated growth and leads to plates with aspect ratios as large as 20, having localized surface plasmon resonances extending deeply into the infrared spectral region (1000 nm and above). We measure plasmon sensitivity by varying the colloidal local refractive index, and Δλ/Δn sensitivity values up to 500 nm/RIU are obtained. Theoretical considerations regarding the correlation between the refractive index sensitivity and the position of the main localized plasmon resonance band demonstrate that plasmon sensitivity does not depend directly on the nanoparticle shape and aspect ratio.

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43

Jiang, M., C. Xiao, G. S. Xu, B. N. Wan, H. Q. Wang, L. Wang, D. S. Wang, et al. "Features of the repetition frequency of edge localized modes in EAST." Radiation Effects and Defects in Solids 167, no. 10 (October 2012): 743–51. http://dx.doi.org/10.1080/10420150.2012.690762.

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44

Majid, M. J., and S. S. Savinskii. "Features of the time evolution of localized quantum states in graphene." Semiconductors 47, no. 1 (January 2013): 141–45. http://dx.doi.org/10.1134/s1063782612120111.

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45

KAWANO, Hiroaki, Mitsuhrio KAWAGOE, Kou ARAKAWA, Masahiko AKANUMA, Masako HARA, Haruo NAKAMURA, and Yasuki MAMIYA. "Clinical, pathological and immunohistological features of case with localized nodular myopathy." Nihon Naika Gakkai Zasshi 78, no. 5 (1989): 661–65. http://dx.doi.org/10.2169/naika.78.661.

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46

Toki, Sayaka, Sei-ichiro Motegi, Kazuya Yamada, Akihiko Uchiyama, Sahori Kanai, Masayoshi Yamanaka, and Osamu Ishikawa. "Clinical and laboratory features of systemic sclerosis complicated with localized scleroderma." Journal of Dermatology 42, no. 3 (January 13, 2015): 283–87. http://dx.doi.org/10.1111/1346-8138.12775.

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47

Zhou, Haiyan, Liangping Li, and J. Jaime Gómez-Hernández. "Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter." Abstract and Applied Analysis 2012 (2012): 1–18. http://dx.doi.org/10.1155/2012/805707.

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The localized normal-score ensemble Kalman filter is shown to work for the characterization of non-multi-Gaussian distributed hydraulic conductivities by assimilating state observation data. The influence of type of flow regime, number of observation piezometers, and the prior model structure are evaluated in a synthetic aquifer. Steady-state observation data are not sufficient to identify the conductivity channels. Transient-state data are necessary for a good characterization of the hydraulic conductivity curvilinear patterns. Such characterization is very good with a dense network of observation data, and it deteriorates as the number of observation piezometers decreases. It is also remarkable that, even when the prior model structure is wrong, the localized normal-score ensemble Kalman filter can produce acceptable results for a sufficiently dense observation network.

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Shastri, Bhavin J., and Martin D. Levine. "Face recognition using localized features based on non-negative sparse coding." Machine Vision and Applications 18, no. 2 (December 19, 2006): 107–22. http://dx.doi.org/10.1007/s00138-006-0052-0.

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Nordemar, D., J. Öberg, O. Brosjö, and M. Skorpil. "Intra-Articular Synovial Sarcomas: Incidence and Differentiating Features from Localized Pigmented Villonodular Synovitis." Sarcoma 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/903873.

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Purpose.To determine the incidence of intra-articular synovial sarcomas and investigate if any radiological variables can differentiate them from localized (unifocal) pigmented villonodular synovitis (PVNS) and if multivariate data analysis could be used as a complementary clinical tool.Methods.Magnetic resonance images and radiographs of 7 cases of intra-articular synovial sarcomas and 14 cases of localized PVNS were blindedly reviewed. Variables analyzed were size, extra-articular growth, tumor border, blooming, calcification, contrast media enhancement, effusion, bowl of grapes sign, triple signal intensity sign, synovial low signal intensity, synovitis, age, and gender. Univariate and multivariate data analysis, the method of partial least squares-discriminant analysis (PLS-DA), were used. Register data on all synovial sarcomas were extracted for comparison.Results.The incidence of intra-articular synovial sarcomas was 3%. PLS-DA showed that age, effusion, size, and gender were the most important factors for discrimination between sarcomas and localized PVNS. No sarcomas were misclassified as PVNS with PLS-DA, while some PVNS were misclassified as sarcomas.Conclusions.The most important variables in differentiating intra-articular sarcomas from localized PVNS were age, effusion, size, and gender. Multivariate data analysis can be helpful as additive information to avoid a biopsy, if the tumor is classified as most likely being PVNS.

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Savotchenko, S. E. "The new features of generalized order parameter localization in multi-layered magnetic structures." Modern Physics Letters B 35, no. 12 (February 26, 2021): 2150201. http://dx.doi.org/10.1142/s0217984921502018.

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The new types of nonlinear localized state of generalized order parameter in the three-layered structure of band antiferromagnets with congruent sections of the Fermi surface are obtained. The nonlinear effects inside the narrow plane defects between the layers representing the local magnetization in the direction of polarization of the spin density wave are described by the nonlinear source function. The variation of the Ginsburg–Landau functional near the Lifshitz point leads to nonlinear Schrödinger equation (NSE) with cubic nonlinear terms and self-consistent nonlinear potential modeling the plane defects. The dispersion equations of two type stationary nonlinear localized states are derived. The solutions of dispersion equations in explicit analytical form in dependence on characteristics of plane defects and the distance between them are found and analyzed. The localized states of order parameter existing only near the plane defects with nonlinear response are obtained.

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