Influence of Fibre Reinforcement on the Long-Term Behaviour of Cracked Concrete

The influence of fibre reinforcement on the long-term behaviour of cracked concrete is analysed in this work by means of a creep test. Nine concrete mixes were prepared (7 SFRCs and 2 conventional RCs) based on two basic mix designs. Concretes type I were conceived for structural precast applications and concretes type II reproduce a general purpose. Fibre dosages and conventional reinforcements were varied to represent a wide spectrum of post-peak flexural responses. In all cases with fibre reinforcement steel fibres were used. Conventional RC specimens were reinforced with two steel rebars. In addition to the variables of mix design of concrete, there are two significant variables related to the creep test: the pre-crack opening level (CMODpn) and the stress level (Ic) sustained during the test. Creep tests were performed by applying a constant flexural load on notched pre-cracked specimens and controlling crack opening evolution. Some of the specimens developed a sudden increase of crack opening deformations during the creep test. Creep coefficients and Crack Opening Rates were calculated and analysed. Creep coefficients show significant dependence on the analysed variables. The results of this experimental campaign show that creep of SFRC specimens may be similar to a traditional RC

The Spheres & Shield Maze Task: A virtual reality serious game for the assessment of risk taking in decision making

[EN] Risk taking (RT) is an essential component in decision-making process that depicts the propensity to make risky decisions. RT assessment has traditionally focused on self-report questionnaires. These classical tools have shown clear distance from real-life responses. Behavioral tasks assess human behavior with more fidelity, but still show some limitations related to transferability. A way to overcome these constraints is to take advantage from virtual reality (VR), to recreate real-simulated situations that might arise from performance-based assessments, supporting RT research. This article presents results of a pilot study in which 41 individuals explored a gamified VR environment: the Spheres & Shield Maze Task (SSMT). By eliciting implicit behavioral measures, we found relationships between scores obtained in the SSMT and self-reported risk-related constructs, as engagement in risky behaviors and marijuana consumption. We conclude that decontextualized Virtual Reality Serious Games are appropriate to assess RT, since they could be used as a cross-disciplinary tool to assess individuals' capabilities under the stealth assessment paradigm.This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness funded projects "Advanced Therapeutic Tools for Mental Health'' (DPI2016-77396-R), and "Assessment and Training on Decision Making in Risk Environments'' (RTC-2017-6523-6) (MINECO/AEI/FEDER,UE) and by the Generalitat Valenciana funded project "Rebrand'' (PROMETEU/2019/105).Juan-Ripoll, CD.; Soler-Domínguez, JL.; Chicchi-Giglioli, IA.; Contero, M.; Alcañiz Raya, ML. (2020). The Spheres & Shield Maze Task: A virtual reality serious game for the assessment of risk taking in decision making. Cyberpsychology Behavior and Social Networking. 23(11):773-781. https://doi.org/10.1089/cyber.2019.0761S7737812311Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (2005). The Iowa Gambling Task and the somatic marker hypothesis: some questions and answers. Trends in Cognitive Sciences, 9(4), 159-162. doi:10.1016/j.tics.2005.02.002Krain, A. L., Wilson, A. M., Arbuckle, R., Castellanos, F. X., & Milham, M. P. (2006). Distinct neural mechanisms of risk and ambiguity: A meta-analysis of decision-making. NeuroImage, 32(1), 477-484. doi:10.1016/j.neuroimage.2006.02.047Einhorn, H. J. (1970). The use of nonlinear, noncompensatory models in decision making. Psychological Bulletin, 73(3), 221-230. doi:10.1037/h0028695Figner, B., & Weber, E. U. (2011). Who Takes Risks When and Why? Current Directions in Psychological Science, 20(4), 211-216. doi:10.1177/0963721411415790Endsley, M. R., & Garland, D. J. (Eds.). (2000). Situation Awareness Analysis and Measurement. doi:10.1201/b12461Lauriola, M., & Levin, I. P. (2001). Personality traits and risky decision-making in a controlled experimental task: an exploratory study. Personality and Individual Differences, 31(2), 215-226. doi:10.1016/s0191-8869(00)00130-6Rundmo, T. (1996). Associations between risk perception and safety. Safety Science, 24(3), 197-209. doi:10.1016/s0925-7535(97)00038-6Zuckerman, M., & Kuhlman, D. M. (2000). Personality and Risk‐Taking: Common Bisocial Factors. Journal of Personality, 68(6), 999-1029. doi:10.1111/1467-6494.00124Dahlen, E. R., Martin, R. C., Ragan, K., & Kuhlman, M. M. (2005). Driving anger, sensation seeking, impulsiveness, and boredom proneness in the prediction of unsafe driving. Accident Analysis & Prevention, 37(2), 341-348. doi:10.1016/j.aap.2004.10.006Donohew, L., Zimmerman, R., Cupp, P. S., Novak, S., Colon, S., & Abell, R. (2000). Sensation seeking, impulsive decision-making, and risky sex: implications for risk-taking and design of interventions. Personality and Individual Differences, 28(6), 1079-1091. doi:10.1016/s0191-8869(99)00158-0Moreno, M., Estevez, A. F., Zaldivar, F., Montes, J. M. G., Gutiérrez-Ferre, V. E., Esteban, L., … Flores, P. (2012). Impulsivity differences in recreational cannabis users and binge drinkers in a university population. Drug and Alcohol Dependence, 124(3), 355-362. doi:10.1016/j.drugalcdep.2012.02.011Dvorak, R. D., & Day, A. M. (2014). Marijuana and self-regulation: Examining likelihood and intensity of use and problems. Addictive Behaviors, 39(3), 709-712. doi:10.1016/j.addbeh.2013.11.001Trocki, K. F., Drabble, L. A., & Midanik, L. T. (2009). Tobacco, marijuana, and sensation seeking: Comparisons across gay, lesbian, bisexual, and heterosexual groups. Psychology of Addictive Behaviors, 23(4), 620-631. doi:10.1037/a0017334Ames, S. L., Zogg, J. B., & Stacy, A. W. (2002). Implicit cognition, sensation seeking, marijuana use and driving behavior among drug offenders. Personality and Individual Differences, 33(7), 1055-1072. doi:10.1016/s0191-8869(01)00212-4Highhouse, S., Nye, C. D., Zhang, D. C., & Rada, T. B. (2016). Structure of the Dospert: Is There Evidence for a General Risk Factor? Journal of Behavioral Decision Making, 30(2), 400-406. doi:10.1002/bdm.1953Jackson, D. N., Hourany, L., & Vidmar, N. J. (1972). A four-dimensional interpretation of risk taking1. Journal of Personality, 40(3), 483-501. doi:10.1111/j.1467-6494.1972.tb00075.xSkeel, R. L., Neudecker, J., Pilarski, C., & Pytlak, K. (2007). The utility of personality variables and behaviorally-based measures in the prediction of risk-taking behavior. Personality and Individual Differences, 43(1), 203-214. doi:10.1016/j.paid.2006.11.025Horvath, P., & Zuckerman, M. (1993). Sensation seeking, risk appraisal, and risky behavior. Personality and Individual Differences, 14(1), 41-52. doi:10.1016/0191-8869(93)90173-zLejuez, C. W., Aklin, W. M., Zvolensky, M. J., & Pedulla, C. M. (2003). Evaluation of the Balloon Analogue Risk Task (BART) as a predictor of adolescent real-world risk-taking behaviours. Journal of Adolescence, 26(4), 475-479. doi:10.1016/s0140-1971(03)00036-8Verhulst, N., De Keyser, A., Gustafsson, A., Shams, P., & Van Vaerenbergh, Y. (2019). Neuroscience in service research: an overview and discussion of its possibilities. Journal of Service Management, 30(5), 621-649. doi:10.1108/josm-05-2019-0135de-Juan-Ripoll, C., Soler-Domínguez, J. L., Guixeres, J., Contero, M., Álvarez Gutiérrez, N., & Alcañiz, M. (2018). Virtual Reality as a New Approach for Risk Taking Assessment. Frontiers in Psychology, 9. doi:10.3389/fpsyg.2018.02532Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50(1-3), 7-15. doi:10.1016/0010-0277(94)90018-3Bottari, C., Dassa, C., Rainville, C., & Dutil, É. (2009). The factorial validity and internal consistency of the Instrumental Activities of Daily Living Profile in individuals with a traumatic brain injury. Neuropsychological Rehabilitation, 19(2), 177-207. doi:10.1080/09602010802188435Verschoor, A., D’Exelle, B., & Perez-Viana, B. (2016). Lab and life: Does risky choice behaviour observed in experiments reflect that in the real world? Journal of Economic Behavior & Organization, 128, 134-148. doi:10.1016/j.jebo.2016.05.009Tarr, M. J., & Warren, W. H. (2002). Virtual reality in behavioral neuroscience and beyond. Nature Neuroscience, 5(S11), 1089-1092. doi:10.1038/nn948Alcañiz, M., Rey, B., Tembl, J., & Parkhutik, V. (2009). A Neuroscience Approach to Virtual Reality Experience Using Transcranial Doppler Monitoring. Presence: Teleoperators and Virtual Environments, 18(2), 97-111. doi:10.1162/pres.18.2.97Chittaro, L., & Ranon, R. (2009). Serious Games for Training Occupants of a Building in Personal Fire Safety Skills. 2009 Conference in Games and Virtual Worlds for Serious Applications. doi:10.1109/vs-games.2009.8Lovreglio, R., Gonzalez, V., Amor, R., Spearpoint, M., Thomas, J., Trotter, M., & Sacks, R. (2017). The Need for Enhancing Earthquake Evacuee Safety by Using Virtual Reality Serious Games. Lean and Computing in Construction Congress - Volume 1: Proceedings of the Joint Conference on Computing in Construction. doi:10.24928/jc3-2017/0058Rizzo, A. A., Bowerly, T., Buckwalter, J. G., Klimchuk, D., Mitura, R., & Parsons, T. D. (2009). A Virtual Reality Scenario for All Seasons:The Virtual Classroom. CNS Spectrums, 11(1), 35-44. doi:10.1017/s1092852900024196Chicchi Giglioli, I. A., de Juan Ripoll, C., Parra, E., & Alcañiz Raya, M. (2019). Are 3D virtual environments better than 2D interfaces in serious games performance? An explorative study for the assessment of executive functions. Applied Neuropsychology: Adult, 28(2), 148-157. doi:10.1080/23279095.2019.1607735Huang, H.-M., Rauch, U., & Liaw, S.-S. (2010). Investigating learners’ attitudes toward virtual reality learning environments: Based on a constructivist approach. Computers & Education, 55(3), 1171-1182. doi:10.1016/j.compedu.2010.05.014Dalgarno, B., & Lee, M. J. W. (2009). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10-32. doi:10.1111/j.1467-8535.2009.01038.xFowler, C. (2014). Virtual reality and learning: Where is the pedagogy? British Journal of Educational Technology, 46(2), 412-422. doi:10.1111/bjet.12135Zuckerman, M., Kolin, E. A., Price, L., & Zoob, I. (1964). Development of a sensation-seeking scale. Journal of Consulting Psychology, 28(6), 477-482. doi:10.1037/h0040995Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the barratt impulsiveness scale. Journal of Clinical Psychology, 51(6), 768-774. doi:10.1002/1097-4679(199511)51:63.0.co;2-1So, R. H. Y., Lo, W. T., & Ho, A. T. K. (2001). Effects of Navigation Speed on Motion Sickness Caused by an Immersive Virtual Environment. Human Factors: The Journal of the Human Factors and Ergonomics Society, 43(3), 452-461. doi:10.1518/001872001775898223Zuckerman, M. (2008). Sensation Seeking. The International Encyclopedia of Communication. doi:10.1002/9781405186407.wbiecs029Orlebeke, J. F., Van Der Molen, M. W., Dolan, C., & Stoffels, E. J. (1990). The additive factor logic applied to the personality trait disinhibition. Personality and Individual Differences, 11(6), 553-558. doi:10.1016/0191-8869(90)90037-rPopham, L. E., Kennison, S. M., & Bradley, K. I. (2011). Ageism, Sensation-Seeking, and Risk-Taking Behavior in Young Adults. Current Psychology, 30(2), 184-193. doi:10.1007/s12144-011-9107-0Roberti, J. W. (2004). A review of behavioral and biological correlates of sensation seeking. Journal of Research in Personality, 38(3), 256-279. doi:10.1016/s0092-6566(03)00067-9Zuckerman, M., Eysenck, S. B., & Eysenck, H. J. (1978). Sensation seeking in England and America: Cross-cultural, age, and sex comparisons. Journal of Consulting and Clinical Psychology, 46(1), 139-149. doi:10.1037/0022-006x.46.1.139Television campaigns and adolescent marijuana use: tests of sensation seeking targeting. (2001). American Journal of Public Health, 91(2), 292-296. doi:10.2105/ajph.91.2.292Barry, D., & Petry, N. M. (2008). Predictors of decision-making on the Iowa Gambling Task: Independent effects of lifetime history of substance use disorders and performance on the Trail Making Test. Brain and Cognition, 66(3), 243-252. doi:10.1016/j.bandc.2007.09.00

Decreasing trends in cardiovascular mortality in Turkey between 1988 and 2008.

BACKGROUND: Cardiovascular disease (CVD) mortality increased in developed countries until the 1970s then started to decline. Turkey is about to complete its demographic transition, which may also influence mortality trends. This study evaluated trends in coronary heart disease (CHD) and stroke mortality between 1988 and 2008. METHODS: The number of deaths by cause (ICD-8), age and sex were obtained from the Turkish Statistical Institute (TurkStat) annually between 1988 and 2008. Population statistics were based on census data (1990 and 2000) and Turkstat projections. European population standardised mortality rates for CHD and stroke were calculated for men and women over 35 years old. Joinpoint Regression was used to identify the points at which a statistically significant (p < 0.05) change of the trend occurred. RESULTS: The CHD mortality rate increased by 2.9% in men and 2.0% in women annually from 1988 to 1994, then started to decline. The annual rate of decline for men was 1.7% between 1994-2008, whilst in women it was 2.8% between 1994-2000 and 6.7% between 2005-2008 (p < 0.05 for all periods).Stroke mortality declined between 1990-1994 (annual fall of 3.8% in both sexes), followed by a slight increase between 1994-2004 (0.6% in men, 1.1% in women), then a further decline until 2008 (annual reduction of 4.4% in men, 7.9% in women) (p < 0.05 for all periods). CONCLUSIONS: A decrease in CVD mortality was observed from 1995 onwards in Turkey. The causes need to be explored in detail to inform future policy priorities in noncommunicable disease control

The health disparities cancer collaborative: a case study of practice registry measurement in a quality improvement collaborative

<p>Abstract</p> <p>Background</p> <p>Practice registry measurement provides a foundation for quality improvement, but experiences in practice are not widely reported. One setting where practice registry measurement has been implemented is the Health Resources and Services Administration's Health Disparities Cancer Collaborative (HDCC).</p> <p>Methods</p> <p>Using practice registry data from 16 community health centers participating in the HDCC, we determined the completeness of data for screening, follow-up, and treatment measures. We determined the size of the change in cancer care processes that an aggregation of practices has adequate power to detect. We modeled different ways of presenting before/after changes in cancer screening, including count and proportion data at both the individual health center and aggregate collaborative level.</p> <p>Results</p> <p>All participating health centers reported data for cancer screening, but less than a third reported data regarding timely follow-up. For individual cancers, the aggregate HDCC had adequate power to detect a 2 to 3% change in cancer screening, but only had the power to detect a change of 40% or more in the initiation of treatment. Almost every health center (98%) improved cancer screening based upon count data, while fewer (77%) improved cancer screening based upon proportion data. The aggregate collaborative appeared to increase breast, cervical, and colorectal cancer screening rates by 12%, 15%, and 4%, respectively (p < 0.001 for all before/after comparisons). In subgroup analyses, significant changes were detectable among individual health centers less than one-half of the time because of small numbers of events.</p> <p>Conclusions</p> <p>The aggregate HDCC registries had both adequate reporting rates and power to detect significant changes in cancer screening, but not follow-up care. Different measures provided different answers about improvements in cancer screening; more definitive evaluation would require validation of the registries. Limits to the implementation and interpretation of practice registry measurement in the HDCC highlight challenges and opportunities for local and aggregate quality improvement activities.</p

Sharing clinical research data in the United States under the health insurance portability and accountability act and the privacy rule

Sharing of final research data from clinical research is an essential part of the scientific method. The U.S. National Institutes of Health require some grant applications to include plans for sharing final research data, which it defines as the factual materials necessary to document, support, and validate research findings. In the U.S., however, the Privacy Rule adopted under the Health Insurance Portability and Accountability Act impedes the sharing of final research data. In most situations, final research data may be shared only where all information that could possibly be used to identify the subject has been deleted, or where the subject has given authorization for specific research, or an Institutional Review Board has granted a waiver

CT pulmonary angiography: an over-utilized imaging modality in hospitalized patients with suspected pulmonary embolism

Aims: To determine if computed tomographic pulmonary angiography (CTPA) was overemployed in the evaluation of hospitalized patients with suspected acute pulmonary embolism (PE). Methods: Data were gathered retrospectively on hospitalized patients (n=185) who had CTPA for suspected PE between June and August 2009 at our institution. Results: CTPA was done in 185 hospitalized patients to diagnose acute PE based on clinical suspicion. Of these, 30 (16.2%) patients were tested positive for acute PE on CTPA. The Well&#x0027;s pretest probability for PE was low, moderate, and high in 77 (41.6%), 83 (44.9%), and 25 (13.5%) patients, respectively. Out of the 30 PE-positive patients, pretest probability was low in 2 (6.6%), moderate in 20 (66.7%), and high in 8 (26.6%) (p=0.003). Modified Well&#x0027;s criteria applied to all patients in our study revealed 113 (61%) with low and 72 (39%) with high clinical pretest probability. When modified Well&#x0027;s criteria was applied to 30 PE-positive patients, 10 (33.3%) and 20 (66.6%) were found to have low and high pretest probability, respectively (p=0.006). D-dimer assay was done in 30 (16.2%) of the inpatients with suspected PE and all of them were found to have elevated levels. A lower extremity duplex ultrasound confirmed deep venous thrombosis in 17 (9.1%) of the patients with suspected PE, at least 1 week prior to having CTPA. Conclusion: Understanding the recommended guidelines, evidence-based literature, and current concepts in evaluation of patients with suspected acute PE will reduce unnecessary CTPA examinations

Computed CD4 percentage as a low-cost method for determining pediatric antiretroviral treatment eligibility

<p>Abstract</p> <p>Background</p> <p>The performance of the WHO recommendations for pediatric antiretroviral treatment (ART) in resource poor settings is insufficiently documented in routine care.</p> <p>Methods</p> <p>We compared clinical and immunological criteria in 366 children aged 0 to 12 years in Kinshasa and evaluated a simple computation to estimate CD4 percent, based on CD4 count, total white blood cell count and percentage lymphocytes. Kappa (κ) statistic was used to evaluate eligibility criteria and linear regression to determine trends of CD4 percent, count and total lymphocyte count (TLC).</p> <p>Results</p> <p>Agreement between clinical and immunological eligibility criteria was poor (κ = 0.26). One third of children clinically eligible for ART were ineligible using immunological criteria; one third of children immunologically eligible were ineligible using clinical criteria. Among children presenting in WHO stage I or II, 54 (32%) were eligible according to immunological criteria. Agreement with CD4 percent was poor for TLC (κ = 0.04), fair for total CD4 count (κ = 0.39) and substantial for CD4 percent computational estimate (κ = 0.71). Among 5 to 12 years old children, total CD4 count was higher in younger age groups (-32 cells/mm³per year older), CD4 percent was similar across age groups.</p> <p>Conclusion</p> <p>Age-specific thresholds for CD4 percent optimally determine pediatric ART eligibility. The use of CD4 percent computational estimate may increase ART access in settings with limited access to CD4 percent assays.</p