Journal articles on the topic 'STRESS IDENTIFICATION'

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1

Wheeler, Robert J., and Monica A. Frank. "Identification of Stress Buffers." Behavioral Medicine 14, no. 2 (June 1988): 78–89. http://dx.doi.org/10.1080/08964289.1988.9935128.

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2

Newton, Cameron, and Stephen Teo. "Identification and Occupational Stress: A Stress-Buffering Perspective." Human Resource Management 53, no. 1 (December 30, 2013): 89–113. http://dx.doi.org/10.1002/hrm.21598.

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3

Kunstmann, Antje, and Kerrin Christiansen. "Testosterone levels and stress in women: the role of stress coping strategies, anxiety and sex role identification." Anthropologischer Anzeiger 62, no. 3 (September 4, 2004): 311–21. http://dx.doi.org/10.1127/anthranz/62/2004/311.

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4

Sauerland, Melanie, Linsey H. C. Raymaekers, Henry Otgaar, Amina Memon, Thijs T. Waltjen, Maud Nivo, Chiel Slegers, Nick J. Broers, and Tom Smeets. "Stress, stress-induced cortisol responses, and eyewitness identification performance." Behavioral Sciences & the Law 34, no. 4 (July 2016): 580–94. http://dx.doi.org/10.1002/bsl.2249.

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5

Jovani, Théo, Hélène Chanal, Benoît Blaysat, and Michel Grédiac. "Direct Residual Stress Identification during Machining." Journal of Manufacturing Processes 82 (October 2022): 678–88. http://dx.doi.org/10.1016/j.jmapro.2022.08.015.

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6

Barac‐Cikoja, Dragana, and Sally Revoile. "Stress identification by hearing‐impaired listeners." Journal of the Acoustical Society of America 98, no. 5 (November 1995): 2983. http://dx.doi.org/10.1121/1.413908.

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7

Erkens, Valerie A., Urs M. Nater, Jürgen Hennig, and Jan A. Häusser. "Social identification and contagious stress reactions." Psychoneuroendocrinology 102 (April 2019): 58–62. http://dx.doi.org/10.1016/j.psyneuen.2018.11.034.

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8

Davis, Russell H. "Discordant identification in critical incident stress." Journal of Religion and Health 33, no. 1 (March 1994): 7–15. http://dx.doi.org/10.1007/bf02354494.

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9

Sinclair, GB. "Stress singularities in classical elasticity—II: Asymptotic identification." Applied Mechanics Reviews 57, no. 5 (September 1, 2004): 385–439. http://dx.doi.org/10.1115/1.1767846.

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This review article (Part II) is a sequel to an earlier one (Part I) that dealt with means of removal and interpretation of stress singularities in elasticity, as well as their asymptotic and numerical analysis. It reviews contributions to the literature that have actually effected asymptotic identifications of possible stress singularities for specific configurations. For the most part, attention is focused on 2D elastostatic configurations with constituent materials being homogeneous and isotropic. For such configurations, the following types of stress singularity are identified: power singularities with both real and complex exponents, logarithmic intensification of power singularities with real exponents, pure logarithmic singularities, and log-squared singularities. These identifications are reviewed for the in-plane loading of angular elastic plates comprised of a single material in Section 2, and for such plates comprised of multiple materials in Section 3. In Section 4, singularity identifications are examined for the out-of-plane shear of elastic wedges comprised of single and multiple materials, and for the out-of-plane bending of elastic plates within the context of classical and higher-order theory. A review of stress singularities identified for other geometries is given in Section 5, axisymmetric and 3D configurations being considered. A limited examination of the stress singularities identified for other field equations is given as well in Section 5. The paper closes with an overview of the status of singularity identification within elasticity. This Part II of the review has 227 references.
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10

Asaadi, Erfan, and P. Stephan Heyns. "Flow stress identification of tubular materials using the progressive inverse identification method." Engineering Computations 33, no. 5 (July 4, 2016): 1472–89. http://dx.doi.org/10.1108/ec-08-2015-0219.

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Purpose – The purpose of this paper is to propose a progressive inverse identification algorithm to characterize flow stress of tubular materials from the material response, independent of choosing an a priori hardening constitutive model. Design/methodology/approach – In contrast to the conventional forward flow stress identification methods, the flow stress is characterized by a multi-linear curve rather than a limited number of hardening model parameters. The proposed algorithm optimizes the slopes and lengths of the curve increments simultaneously. The objective of the optimization is that the finite element (FE) simulation response of the test estimates the material response within a predefined accuracy. Findings – The authors employ the algorithm to identify flow stress of a 304 stainless steel tube in a tube bulge test as an example to illustrate application of the algorithm. Comparing response of the FE simulation using the obtained flow stress with the material response shows that the method can accurately determine the flow stress of the tube. Practical implications – The obtained flow stress can be employed for more accurate FE simulation of the metal forming processes as the material behaviour can be characterized in a similar state of stress as the target metal forming process. Moreover, since there is no need for a priori choosing the hardening model, there is no risk for choosing an improper hardening model, which in turn facilitates solving the inverse problem. Originality/value – The proposed algorithm is more efficient than the conventional inverse flow stress identification methods. In the latter, each attempt to select a more accurate hardening model, if it is available, result in constructing an entirely new inverse problem. However, this problem is avoided in the proposed algorithm.
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11

McKimmie, Blake M., Tamara Butler, Edward Chan, Allira Rogers, and Nerina L. Jimmieson. "Reducing stress: Social support and group identification." Group Processes & Intergroup Relations 23, no. 2 (January 30, 2019): 241–61. http://dx.doi.org/10.1177/1368430218818733.

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Three studies systematically explored the relationship between social support and group identification in the context of how individuals cope with stress. In Study 1, 101 participants took part in a simulated group task where they either received social support or not under conditions of either high or low demand. Social support was associated with higher group identification, and this mediated the effect of social support on more positive appraisals and task satisfaction. In Study 2, 83 participants were either made aware of their group membership or worked as individuals on a group task under high or low demand. In this study, group membership salience was associated with greater perceived support, which was associated with greater group identification, and subsequently more positive primary and secondary appraisals, more problem-focused coping, and task satisfaction. Study 3 assessed the perceived social support and group identification reported by 71 volleyball team members before and after a game. Results were more consistent with the notion that support and identification were two concurrent perceptions associated with being in a group, rather than identification priming the recognition of support or support increasing identification.
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12

Dhole, N. P., and S. N. Kale. "Multilayer Perceptron Classification in Stress Speech Identification." International Journal of Computer Sciences and Engineering 6, no. 4 (April 30, 2018): 471–75. http://dx.doi.org/10.26438/ijcse/v6i4.471475.

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13

Saga, Milan, Milan Vasko, Peter Kopas, and Lenka Jakubovicova. "Numerical Algorithm for Beam Residual Stress Identification." Communications - Scientific letters of the University of Zilina 16, no. 3A (October 31, 2014): 13–18. http://dx.doi.org/10.26552/com.c.2014.3a.13-18.

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14

Tan, Jian, Yunliang Tan, Zihui Wang, and Yubao Zhang. "Identification for Abutment Stress by Drilling Cuttings." Applied Sciences 11, no. 20 (October 12, 2021): 9467. http://dx.doi.org/10.3390/app11209467.

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The concentration of abutment pressure acting on coal seams induced by mining is a key factor to trigger rock burst. Understanding of abutment pressure or stress concentration is fundamental in preventing and controlling rock burst. The influence on abutment pressure fluctuation caused by the inhomogeneity of coal seams needs to be considered, but it is difficult to obtain by the present usual ways such as acoustic transmission, electromagnetic wave transmission, etc. In this article, the relationship between the amount of cuttings drilled in a coal seam and stress level was analyzed by considering the effect of drilling cutting expansion, and the drilling cutting test was carried out in Xinglongzhuang Coal Mine, Shandong Energy Ltd. It is found that the amount of cuttings drilled is positively related to the degree of stress concentration in both the plastic fracture zone and elastic zone. The amount of drilling cuttings is closely related to the roof weighting. In addition, the irregular fluctuation of drilling cuttings is an approximate map of distribution of stress concentration because of the non-uniformity of cracks and other defects in the coal seam. In order to meet the need of rock burst prevention by accurate pressure relief in high-stress zones, enough boreholes are needed.
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15

Brown, Marie, and Sue Ralph. "Towards the identification of stress in teachers." Research in Education 48, no. 1 (November 1992): 103–10. http://dx.doi.org/10.1177/003452379204800110.

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16

Ballén-Taborda, Carolina, Germán Plata, Sarah Ayling, Fausto Rodríguez-Zapata, Luis Augusto Becerra Lopez-Lavalle, Jorge Duitama, and Joe Tohme. "Identification of Cassava MicroRNAs under Abiotic Stress." International Journal of Genomics 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/857986.

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The study of microRNAs (miRNAs) in plants has gained significant attention in recent years due to their regulatory role during development and in response to biotic and abiotic stresses. Although cassava (Manihot esculentaCrantz) is tolerant to drought and other adverse conditions, most cassava miRNAs have been predicted using bioinformatics alone or through sequencing of plants challenged by biotic stress. Here, we use high-throughput sequencing and different bioinformatics methods to identify potential cassava miRNAs expressed in different tissues subject to heat and drought conditions. We identified 60 miRNAs conserved in other plant species and 821 potential cassava-specific miRNAs. We also predicted 134 and 1002 potential target genes for these two sets of sequences. Using real time PCR, we verified the condition-specific expression of 5 cassava small RNAs relative to a non-stress control. We also found, using publicly available expression data, a significantly lower expression of the predicted target genes of conserved and nonconserved miRNAs under drought stress compared to other cassava genes. Gene Ontology enrichment analysis along with condition specific expression of predicted miRNA targets, allowed us to identify several interesting miRNAs which may play a role in stress-induced posttranscriptional regulation in cassava and other plants.
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17

Portig, Irene, Sabine Pankuweit, Friedrich Lottspeich, and Bernhard Maisch. "Identification of stress proteins in endothelial cells." Electrophoresis 17, no. 4 (1996): 803–8. http://dx.doi.org/10.1002/elps.1150170431.

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18

Hoenen, Matthias, Oliver T. Wolf, and Bettina M. Pause. "The Impact of Stress on Odor Perception." Perception 46, no. 3-4 (January 10, 2017): 366–76. http://dx.doi.org/10.1177/0301006616688707.

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The olfactory system and emotional systems are highly intervened and share common neuronal structures. The current study investigates whether emotional (e.g., anger and fear) and physiological (saliva cortisol) stress responses are associated with odor identification ability and hedonic odor judgments (intensity, pleasantness, and unpleasantness). Nineteen men participated in the modified Trier Social Stress Test (TSST) and a control session (cycling on a stationary bike). The physiological arousal was similar in both sessions. In each session, participants’ odor identification score was assessed using the University of Pennsylvania Smell Identification Test, and their transient mood was recorded on the dimensions of valence, arousal, anger, and anxiety. Multivariate regression analyses show that an increase of cortisol in the TSST session (as compared with the control session) is associated with better odor identification performance (β = .491) and higher odor intensity ratings (β = .562). However, increased anger in the TSST session (as compared with the control session) is associated with lower odor identification performance (β = −.482). The study shows divergent effects of the emotional and the physiological stress responses, indicating that an increase of cortisol is associated with better odor identification performance, whereas increased anger is associated with poorer odor identification performance.
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19

Han, Jae Hwan, Jung Suk Lee, Yun Hee Lee, Min Jae Choi, Gyu Jei Lee, Kwang Ho Kim, and Dong Il Kwon. "Residual Stress Estimation with Identification of Stress Directionality Using Instrumented Indentation Technique." Key Engineering Materials 345-346 (August 2007): 1125–28. http://dx.doi.org/10.4028/www.scientific.net/kem.345-346.1125.

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The instrumented indentation technique (IIT) has recently attracted significant research interest because it is nondestructive and easy to perform, and can characterize materials on local scales. Residual stress can be determined by analyzing the indentation load-depth curve from IIT. However, this technique using a symmetric indenter is limited to an equibiaxial residual stress state. In this study, we determine the directionality of the non-equibiaxial residual stress by using the Knoop indentation technique. Different indentation load-depth curves are obtained at nonequibiaxial residual stresses depending on the Knoop indentation direction. A model for Knoop indentation was developed through experiments and theoretical analysis.
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20

Roux, Stéphane, François Hild, and Stéphane Pagano. "A stress scale in full-field identification procedures: a diffuse stress gauge." European Journal of Mechanics - A/Solids 24, no. 3 (May 2005): 442–51. http://dx.doi.org/10.1016/j.euromechsol.2005.02.002.

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21

Neto, Perrin Smith, Luiz Claudio Oliveira, Adriana Costa, and Marco Antonio Quinam. "GSW0007 Identification of the physical characteristics of a stress distribution through qualitative three-dimensional photoelasticity." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2003.2 (2003): _GSW0007–1—_GSW0007–6. http://dx.doi.org/10.1299/jsmeatem.2003.2._gsw0007-1.

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22

Abdul Jalil, S., A. Anwar, SM Chou, and K. Tai. "Material yield strain identification using energy absorption." Journal of Strain Analysis for Engineering Design 53, no. 6 (July 18, 2018): 463–69. http://dx.doi.org/10.1177/0309324718774950.

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The current gold standard of identifying yield points from stress strain curves involves identifying a significant change in elastic modulus or using an arbitrary strain offset (0.1%, 0.2% or 2%) of the elastic modulus. The development of the offset method was due to the ambiguous definitions of yield point. The result is an arbitrary yield point which is prone to various human-related errors. This article presents a method to identify a unique yield point consistently using energy absorbed by the material up to first peak stress. This mathematical process idealises the stress strain curve for easy identification of the yield point. The method was tested on three possible types of stress strain curves with either a distinct yield point or without a distinct yield point (with peak stress closer to elastic region or closer to fracture). The yield points obtained by the proposed method are shown to be robust, consistent and unaffected by variations of the stress strain curves and data noises.
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23

Vítámvás, P., K. Kosová, and I. T. Prášil. "Proteome analysis in plant stress research: a review." Czech Journal of Genetics and Plant Breeding 43, No. 1 (January 7, 2008): 1–6. http://dx.doi.org/10.17221/1903-cjgpb.

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Proteomic techniques that allow the identification and quantification of stress-related proteins, mapping of dynamics of their expression and posttranslational modifications represent an important approach in the research of plant stresses. In this review, we show an outline of proteomics methods and their applications in the research of plant resistance to various types of stresses.
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24

Inagaki, Satoshi, Michinori Funato, Junko Seki, Chizuru Kawase, Kazuki Ohuchi, Shiori Ando, Shinsuke Nakamura, Masamitsu Shimazawa, Hideo Kaneko, and Hideaki Hara. "Identification of the Stress Which Causes Optineurin Aggregation." Neuroscience and Medicine 10, no. 02 (2019): 150–61. http://dx.doi.org/10.4236/nm.2019.102010.

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25

Taylor, Anna K., Christine Fothergill, Carolyn A. Chew-Graham, Serena Patel, and Anton Krige. "Identification of post-traumatic stress disorder following ICU." British Journal of General Practice 69, no. 680 (February 28, 2019): 154–55. http://dx.doi.org/10.3399/bjgp19x701765.

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26

Ursano, Robert J., Carol S. Fullerton, Kelley Vance, and Tzu-Cheg Kao. "Posttraumatic Stress Disorder and Identification in Disaster Workers." American Journal of Psychiatry 156, no. 3 (March 1, 1999): 353–59. http://dx.doi.org/10.1176/ajp.156.3.353.

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27

Gautam, Vinay, and Jyoti Rani. "Mango Leaf Stress Identification Using Deep Neural Network." Intelligent Automation & Soft Computing 34, no. 2 (2022): 849–64. http://dx.doi.org/10.32604/iasc.2022.025113.

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28

Pratiwi, Herdina, Novita Nugrahaeni, and Abdullah Taufiq. "Identification of Peanut Germplasm Tolerance to Salinity Stress." Buletin Palawija 19, no. 1 (May 31, 2021): 1. http://dx.doi.org/10.21082/bulpa.v19n1.2021.p1-9.

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Varietas toleran salinitas adalah kunci utama pengembangan kacang tanah di tanah salin, namun sampai saat ini belum ada perakitan varietas kacang tanah di Indonesia dengan spesifikasi toleran terhadap salinitas. Penelitian ini bertujuan untuk mengevaluasi toleransi 25 aksesi kacang tanah koleksi plasma nutfah Balai Penelitian Tanaman Aneka Kacang dan Umbi terhadap cekaman salinitas untuk menyediakan sumber gen persilangan tahan salinitas. Aksesi kacang tanah ditanam pada tiga level salinitas yaitu non salin, sedang (5-6 dS/m), dan tinggi (8-10 dS/m). Parameter yang diamati meliputi skor keracunan, kadar K dan Na pada akar dan tajuk, hasil polong dan biji, dan indeks toleransi cekaman (ITC). Hasil penelitian menunjukkan bahwa semua aksesi teridentifikasi peka pada salinitas tinggi. Salinitas sedang merupakan level salinitas tertinggi yang masih dapat ditoleransi oleh 23 aksesi kacang tanah. Pada tingkat salinitas sedang, empat aksesi kacang tanah (MLGA 0211, MLGA 0222, MLGA 0546, MLGA 0570) teridentifikasi toleran, dua aksesi (MLGA 0473 danMLGA 0605) peka, dan 19 aksesi lainnya tergolong sedang. Toleransi terhadap salinitas berhubungan dengan kemampuan aksesi untuk membatasi serapan Na dan translokasinya ke tajuk sehingga rasio K/Na di tajuk tetap tinggi dan dapat meningkatkan proses fotosintesis tanaman. Rasio Na-akar/Na-tajuk sama efektifnya dengan indikator rasio K/Na tajuk, oleh karena itu dapat dijadikan kriteria baru dalam seleksi toleransi kacang tanah terhadap cekaman salinitas. Aksesi yang toleran berdasarkan kemampuan untuk membentuk polong dan biji serta kemampuan menahan efek salinitas dapat dimanfaatkan dan diintegrasikan dalam pemuliaan kacang tanah untuk toleransi salinitas.
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29

Grelet, C., V. Vanden Dries, J. Leblois, J. Wavreille, L. Mirabito, H. Soyeurt, S. Franceschini, et al. "Identification of chronic stress biomarkers in dairy cows." Animal 16, no. 5 (May 2022): 100502. http://dx.doi.org/10.1016/j.animal.2022.100502.

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30

Caine, Randy M., and Levon Ter-Bagdasarian. "Early Identification and Management of Critical Incident Stress." Critical Care Nurse 23, no. 1 (February 1, 2003): 59–65. http://dx.doi.org/10.4037/ccn2003.23.1.59.

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31

Costin, Hariton, Cristian Rotariu, and Alexandru Pasarica. "IDENTIFICATION OF PSYCHOLOGICAL STRESS BY ANALYZING ELECTROCARDIOGRAPHIC SIGNAL." Environmental Engineering and Management Journal 12, no. 6 (2013): 1255–63. http://dx.doi.org/10.30638/eemj.2013.154.

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32

Rush, Elizabeth B., Jodi A. Quas, Ilona S. Yim, Mariya Nikolayev, Steven E. Clark, and Rakel P. Larson. "Stress, Interviewer Support, and Children's Eyewitness Identification Accuracy." Child Development 85, no. 3 (October 16, 2013): 1292–305. http://dx.doi.org/10.1111/cdev.12177.

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33

Grédiac, M. "Stress Analysis and Identification with Full-Field Measurements." Applied Mechanics and Materials 3-4 (August 2006): 9–16. http://dx.doi.org/10.4028/www.scientific.net/amm.3-4.9.

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The wealth of information provided by full-field measurement techniques is very useful in experimental mechanics. Among different possible applications, full-field measurements can be used to identify parameters governing constitutive equations from heterogeneous strain fields. This keynote lecture first describes the different possible uses of such measurements. It then focuses on the virtual fields method which has been proposed to extract constitutive parameters from full-field measurements. Finally, the method is compared with the finite element model updating technique which is usually used for solving such a problem.
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34

Quiles, Justin M., Madhusudhanan Narasimhan, Timothy Mosbruger, Gobinath Shanmugam, David Crossman, and Namakkal S. Rajasekaran. "Identification of transcriptome signature for myocardial reductive stress." Redox Biology 13 (October 2017): 568–80. http://dx.doi.org/10.1016/j.redox.2017.07.013.

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35

Rince, Alain, Sigrid Flahaut, and Yanick Auffray. "Identification of general stress genes in Enterococcus faecalis." International Journal of Food Microbiology 55, no. 1-3 (April 2000): 87–91. http://dx.doi.org/10.1016/s0168-1605(00)00180-x.

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36

Tahara, S., S. Kasai, M. Inoue, J. Kawabata, and J. Mizutani. "Identification of mucondialdehyde as a novel stress metabolite." Experientia 50, no. 2 (February 1994): 137–41. http://dx.doi.org/10.1007/bf01984952.

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37

Sorensen, Elaine Shaw. "Identification of Stress Buffers in School-Age Children." Journal of Community Health Nursing 8, no. 1 (March 1991): 15–24. http://dx.doi.org/10.1207/s15327655jchn0801_2.

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38

Vasterling, Jennifer J., Kevin Brailey, and Patricia B. Sutker. "Olfactory identification in combat-related posttraumatic stress disorder." Journal of Traumatic Stress 13, no. 2 (April 2000): 241–53. http://dx.doi.org/10.1023/a:1007754611030.

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39

Koslowsky, Meni. "Commuting Stress: Problems of Definition and Variable Identification." Applied Psychology 46, no. 2 (April 1997): 153–73. http://dx.doi.org/10.1111/j.1464-0597.1997.tb01222.x.

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40

Pokorska, I. "Experimental identification of yield stress for sintered materials." Powder Metallurgy and Metal Ceramics 47, no. 7-8 (July 2008): 393–97. http://dx.doi.org/10.1007/s11106-008-9032-4.

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41

Valentine, Tin, and Jan Mesout. "Eyewitness identification under stress in the London Dungeon." Applied Cognitive Psychology 23, no. 2 (February 2009): 151–61. http://dx.doi.org/10.1002/acp.1463.

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42

Lim, Eng Mong, S. Dusko Ehrlich, and Emmanuelle Maguin. "Identification of stress-inducible proteins inLactobacillus delbrueckii subsp.bulgaricus." Electrophoresis 21, no. 12 (July 1, 2000): 2557–61. http://dx.doi.org/10.1002/1522-2683(20000701)21:12<2557::aid-elps2557>3.0.co;2-b.

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43

Mash, PhD, Holly B. Herberman, Carol S. Fullerton, PhD, and Robert J. Ursano, MD. "Post-traumatic stress symptoms following sniper attacks: Effects of television viewing and identification with victims." American Journal of Disaster Medicine 13, no. 1 (January 1, 2018): 29–36. http://dx.doi.org/10.5055/ajdm.2018.0285.

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Objective: A series of sniper attacks in the Washington, DC, area left 10 people dead and three wounded. The authors examined the relationship of sniper-related television (TV) viewing, identification with victims, and peritraumatic dissociation to posttraumatic stress symptoms.Methods: Participants were 1,238 DC residents (ages 18-90, M = 41.7; 51 percent female; 68 percent White) who completed an online survey including items assessing identification, amount of TV, peritraumatic dissociation, and post-traumatic stress symptoms. Identification was measured by assessing to what extent participants identified victims as similar to themselves, a friend, or a family member. Peritraumatic dissociation and post-traumatic stress symptoms were assessed with the Peritraumatic Dissociative Experiences Questionnaire and Impact of Event Scale-Revised. Relationships of TV viewing, identification, and peritraumatic dissociation to post-traumatic stress symptoms were examined by univariable and multivariable regressions and variable interactions.Results: Female gender and higher levels of TV viewing, identification, and peritraumatic dissociation were each related to greater post-traumatic stress symptoms. After adjusting for gender and the predictor variables, higher TV viewing was associated with posttraumatic stress symptoms (B = 0.72, p 0.01, ΔR2 = 0.05). Participants with greater identification (B = 0.85, p 0.001, ΔR2 = 0.08) and peritraumatic dissociation (B = 1.58, p 0.001, ΔR2 = 0.39) reported more post-traumatic stress symptoms. Among those with both high (B = 1.19, p 0.001) and low TV viewing, identification was associated with post-traumatic stress symptoms. Among those reporting low TV viewing, this association was greater for those who experienced more peritraumatic dissociation (B = −0.09, p 0.001).Conclusions: Trauma-related TV viewing, which may stimulate identification and peritraumatic dissociation, is an important consideration in understanding development of post-traumatic stress symptoms.
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44

Brace, Nicola A., Graham E. Pike, Richard I. Kemp, and Jim Turner. "Eye-Witness Identification Procedures and Stress: A Comparison of Live and Video Identification Parades." International Journal of Police Science & Management 11, no. 2 (June 2009): 183–92. http://dx.doi.org/10.1350/ijps.2009.11.2.122.

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45

Koohestani, Kambiz. "Automated element grouping and self-stress identification of tensegrities." Engineering Computations 32, no. 6 (August 3, 2015): 1643–60. http://dx.doi.org/10.1108/ec-08-2014-0165.

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Purpose – The determination of feasible self-stress modes and grouping of elements for tensegrities with predefined geometry and multiple self-stress modes is very important, though difficult, in the design of these structures. The purpose of this paper is to present a novel approach to the automated element grouping and self-stress identification of tensegrities. Design/methodology/approach – A set of feasible solutions conforming to the unilateral behaviour of elements is obtained through an optimisation process, which is solved using a genetic algorithm. Each chromosome in the population having a negative fitness is a distinctive feasible solution with its own grouping characteristic, which is automatically determined throughout the evolution process. Findings – The self-stress identification is formulated through an unconstrained minimisation problem. The objective function of this minimisation problem is defined in such a way that takes into account both the feasibility of a solution and grouping of elements. The method generates a set of feasible self-stress modes rather than a single one and automatically and simultaneously suggests a grouping of elements for every feasible self-stress mode. A self-stress mode with a minimal/subminimal grouping of elements is also obtained. Originality/value – The method can efficiently generate sets of feasible solutions rather than a single one. The authors also address one of the challenging issues related to this identification, i.e., automated grouping of elements. These features makes the method very efficient since most of the state-of-the-art methods address the self-stress identification of tensegrities based on predefined groupings of elements whilst providing only a single corresponding solution.
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46

Kim, Dong Won, Nak Kyu Lee, Kyoung Hoan Na, and Dong Il Kwon. "Identification of Stress-Free State and Mapping of Residual Stress Fields by Laser Interferemetry." Key Engineering Materials 270-273 (August 2004): 1682–87. http://dx.doi.org/10.4028/www.scientific.net/kem.270-273.1682.

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MURATA, Masanobu, Takeshi NISHIWAKI, and Yoshinori YOSHIDA. "Stress Correction Method for Flow Stress Identification by Tensile Test using Notched Round Bar." Journal of the Japan Society for Technology of Plasticity 57, no. 669 (2016): 977–82. http://dx.doi.org/10.9773/sosei.57.977.

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48

Zhou, J. M., M. Andersson, and J. E. Ståhl†. "Cutting tool fracture prediction and strength evaluation by stress identification, part i: Stress model." International Journal of Machine Tools and Manufacture 37, no. 12 (December 1997): 1691–714. http://dx.doi.org/10.1016/s0890-6955(97)00031-x.

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49

Murata, Masanobu, Yoshinori Yoshida, and Takeshi Nishiwaki. "Stress correction method for flow stress identification by tensile test using notched round bar." Journal of Materials Processing Technology 251 (January 2018): 65–72. http://dx.doi.org/10.1016/j.jmatprotec.2017.08.008.

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OKIMURA, Tsutomu, Yoko SATOMI-SASAKI, and Shigenori OHKUMA. "Stress and Immune Responses II. Identification of Stress-Sensitive Cells in Murine Spleen Cells." Japanese Journal of Pharmacology 40, no. 4 (1986): 513–25. http://dx.doi.org/10.1254/jjp.40.513.

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