Literatura académica sobre el tema "National Center for Environmental Assessment (Washington, D.C.)"

School readiness during early childhood establishes the fundamental basis for prospective academic achievement, emphasizing the necessity for a comprehensive preparation that encompasses both mental and physical readiness. The current study examines the impact of child well-being and family support on school readiness among young learners. This Study used a correlational quantitative approach, the research involved 139 children between the ages of 4 and 7, along with their parents and 30 teachers selected through purposive sampling based on their socioeconomic status. The participants included 54.7% boys (n=76) and 45.3% girls (n=63) from families with varying income levels – low-income (25%), middle-income (29%), and upper-middle-income (46%). The results of the regression analysis indicated that both family support and child well-being have a significant influence on children's school readiness. Particularly, there is a notable positive association among all factors, a correlation between school readiness and child well-being at 42% (r = 0.420, p < 0.001), highlighting that higher levels of child well-being are linked to increased school readiness. Furthermore, family support exhibits a positive contribution to school readiness at 37% (r = 0.370, p < 0.001). The findings suggest that preparing children for school should extend beyond academic and motor skills development to include substantial psychological support, thus enhancing their ability to thrive in an academic environment. Keywords: early childhood, Emotion, Emotion regulation, parenting, happiness References: Atkins, R., Deatrick, J. A., Bocage, C., Huc, R., Aromolaran, D., Besseir, E., Hinckson, A., Joseph, M., Kim, D., Lagman, D., Gladsden, V. L., & Lipman, T. H. (2022). School Readiness and Social Determinants of Health: A Collaboration with Community Teachers and Parents. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4090268 Ayriza, Y., Setiawati, F. A., Nurhayati, S. R., Gumelar, S. R., & Sholeha, E. P. D. R. (2019). Does sleep quality serve as a mediator between well-being and academic achievement? Cakrawala Pendidikan, 38(1), 63–74. https://doi.org/10.21831/cp.v38i1.22181 Azra, A., Risnawati, E., Hermaini, B., Hendra, M., Kartikawati, E., Buana, U. M., & Terbuka, U. (2023). How family communication pattern affect a family ’ s capacity for resilience during covid-19 pandemic. 11(1), 117–137. Barnett, M. A., Paschall, K. W., Mastergeorge, A. M., Cutshaw, C. A., & Warren, S. M. (2020). Influences of Parent Engagement in Early Childhood Education Centers and the Home on Kindergarten School Readiness. Early Childhood Research Quarterly, 53, 260–273. https://doi.org/10.1016/j.ecresq.2020.05.005 Borualogo;, Ihsana Sabriani, F. C. (2020). Subjective Well-Being of Indonesian Children:A Perspective of Material Well-Being. ANIMA Indonesian Psychological Journal, 44–47. https://doi.org/10.1515/9783111634487-006 Borualogo, I. S., & Casas, F. (2022). The children’s worlds psychological well-being scale: Adaptation and fit in the Indonesian context. Cogent Psychology, 9(1), 1–17. https://doi.org/10.1080/23311908.2022.2053377 Cress, C. J., Synhorst, L., Epstein, M. H., & Allen, E. (2012). Confirmatory factor analysis of the preschool behavioral and emotional rating scale (PreBERS) with preschool children with disabilities. Assessment for Effective Intervention, 37(4), 203–211. https://doi.org/10.1177/1534508411433499 Cress, C., Lambert, M. C., & Epstein, M. H. (2016). Factor Analysis of the Preschool Behavioral and Emotional Rating Scale for Children in Head Start Programs. Journal of Psychoeducational Assessment, 34(5), 473–486. https://doi.org/10.1177/0734282915617630 Diener, E., & Ryan, K. (2009). Subjective Well-Being: A General Overview. South African Journal of Psychology, 39(4), 391–406. https://doi.org/10.1177/008124630903900402 El Zaatari, W., & Maalouf, I. (2022). How the Bronfenbrenner Bio-ecological System Theory Explains the Development of Students’ Sense of Belonging to School? SAGE Open, 12(4), 1–18. https://doi.org/10.1177/21582440221134089 Golshirazi, F., & Sadeghi, A. (2021). The Effect of Home-to-School Transition Program on Social-Emotional Readiness of Preschool Students. Journal of Counseling Research. https://doi.org/10.18502/qjcr.v20i77.6147 Gómez-Leal, R., Holzer, A. A., Bradley, C., Fernández-Berrocal, P., & Patti, J. (2022). The relationship between emotional intelligence and leadership in school leaders: a systematic review. Cambridge Journal of Education, 52(1), 1–21. https://doi.org/10.1080/0305764X.2021.1927987 Gregory, T., Dal Grande, E., Brushe, M., Engelhardt, D., Luddy, S., Guhn, M., Gadermann, A., Schonert-Reichl, K. A., & Brinkman, S. (2021). Associations between School Readiness and Student Wellbeing: A Six-Year Follow Up Study. Child Indicators Research, 14(1), 369–390. https://doi.org/10.1007/s12187-020-09760-6 Halimah, N., & Kawuryan, F. (2010). Kesiapan Memasuki Sekolah Dasar Pada Anak Yang Mengikuti Pendidikan Tk Dengan Yang Tidak Mengikuti Pendidikan Tk Di Kabupaten Kudus. Jurnal Psikologi Universitas Muria Kudus, I(1), 1–8. http://www.pustaka.unpad.ac.id Harrington, E. M., Trevino, S. D., Lopez, S., & Giuliani, N. R. (2020). Emotion regulation in early childhood: Implications for socioemotional and academic components of school readiness. Emotion (Washington, D.C.), 20(1), 48–53. https://doi.org/10.1037/emo0000667 Holzer, J., Bürger, S., Lüftenegger, M., & Schober, B. (2022). Revealing associations between students’ school-related well-being, achievement goals, and academic achievement. Learning and Individual Differences, 95(March), 102140. https://doi.org/10.1016/j.lindif.2022.102140 Hughes, C., White, N., Foley, S., & Devine, R. T. (2018). Family support and gains in school readiness: A longitudinal study. British Journal of Educational Psychology, 88(2), 284–299. https://doi.org/10.1111/bjep.12188 Jung, S., & Choi, N. (2020). Effect of Family Functioning on Preschoolers’ School Readiness: Mediating Effects of Mothers’ Affective Parenting and Preschoolers’ Self-regulation. Family and Environment Research, 58(1), 1–12. https://doi.org/10.6115/fer.2020.001 Kokkalia, G., Drigas, A., Economou, A., & Roussos, P. (2019). School readiness from kindergarten to primary school. International Journal of Emerging Technologies in Learning, 14(11), 4–18. https://doi.org/10.3991/IJET.V14I11.10090 Lazarus, R. S. (1991). Emotion and Adaptation. Oxford University Press. https://doi.org/10.2307/2075902 Lin, M. L., & Faldowski, R. A. (2023). The Relationship of Parent Support and Child Emotional Regulation to School Readiness. International Journal of Environmental Research and Public Health, 20(6). https://doi.org/10.3390/ijerph20064867 Lombardi, C. M. (2023). Early Maternal Employment And Children’s School Readiness: Changing Associations Over Time? Journal of Child and Family Studies, 32(4), 1032–1047. https://doi.org/10.1007/s10826-022-02357-3 Lombardi, C. M., & Dearing, E. (2021). Maternal Support of Children’s Math Learning in Associations Between Family Income and Math School Readiness. Child Development, 92(1). https://doi.org/10.1111/cdev.13436 Luby, J. L., Barch, D. M., Belden, A., Gaffrey, M. S., Tillman, R., Babb, C., Nishino, T., Suzuki, H., & Botteron, K. N. (2012). Maternal support in early childhood predicts larger hippocampal volumes at school age. Proceedings of the National Academy of Sciences of the United States of America, 109(8), 2854–2859. https://doi.org/10.1073/pnas.1118003109 Mariyati, L. I. (2017). Usia dan Jenis Kelamin dengan Kesiapan Masuk Sekolah Dasar. Prosiding Seminar Nasional Psikologi UMG, 095, 331–344. Mashar, R., & Pudji Astuti, F. (2022). Correlation between Parenting Skills, Children’s Emotional and Intelligence Quotient with School Readiness. JPUD - Jurnal Pendidikan Usia Dini, 16(2), 215–223. https://doi.org/10.21009/JPUD.162.02 Nurmaria, H., & Risnawati, E. (2022). The Relationship of Loneliness and Internet Addiction To Psychological Well-Being in Adolescents. Biopsikososial: Jurnal Ilmiah Psikologi Fakultas Psikologi Universitas Mercubuana Jakarta, 5(2), 509. https://doi.org/10.22441/biopsikososial.v5i2.14644 Rahmawati. (2018). Kesiapan sekolah merupakan kesiapan anak untuk memasuki sekolah . Di Indonesia istilah kesiapan sekolah lazim digunakan untuk merujuk kesiapan anak masuk Sekolah Dasar ( SD ), sebagai sekolah f. Jurnal Pendidikan Usia Dini,12(November), 201–210. http://journal.unj.ac.id/unj/index.php/jpud Risnawati, E., Meiliyandrie, L., Wardani, I., Saputra, A. H., Pramitasari, M., Mercu Buana, U., Pendidikan, J., & Dini, U. (2023). Theory of Mind, Roles, and the Development of Emotion Regulation in Early Childhood. 17(2), 1693–1602. https://doi.org/10.21009/JPUD.172.01 Risnawati Erna, Arisandi Alfida, D. R. (2019). Peran Religiusitas dan Psychological Well-Being terhadap Resiliensi Korban KDRT. Journal.Univpancasila.Ac.Id, 10(2), 67–77. http://journal.univpancasila.ac.id/index.php/mindset/article/view/836 Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology, 57(6), 1069–1081. https://doi.org/10.1037/0022-3514.57.6.1069 Ryff, C. D., & Keyes, C. L. M. (1995). The Structure of Psychological Well-Being Revisited. Journal of Personality and Social Psychology, 69(4), 719–727. https://doi.org/10.1037/0022-3514.69.4.719 Seran, T. N., Haryono, & Anni, C. T. (2017). School Readiness: Readiness Children Seen from The Whole Aspect of Early Childhood Development Article Info. Journel of Primary Education, 6(3), 224–232. http://journal.unnes.ac.id/sju/index.php/jpe St. Laurent, C. W., Burkart, S., Andre, C., & Spencer, R. M. C. (2021). Physical Activity, Fitness, School Readiness, and Cognition in Early Childhood: A Systematic Review. Journal of Physical Activity and Health, 18(8), 1004–1013. https://doi.org/10.1123/jpah.2020-0844 Turner, K. M. T., Dittman, C. K., Rusby, J. C., & Lee, S. (2017). Parenting Support in an Early Childhood Learning Context. In M. R. Sanders & T. G. Mazzucchelli (Eds.), The Power of Positive Parenting (pp. 242–251). Oxford University Press. https://doi.org/10.1093/med-psych/9780190629069.003.0021

Abstract The Environmental Modeling Center (EMC) at the National Centers for Environmental Prediction (NCEP) and the University of Washington (UW) run parallel drought monitoring systems over the continental United States based on the North American Land Data Assimilation System (NLDAS). The NCEP system uses four land surface models (LSMs): Variable Infiltration Capacity (VIC), Noah, Mosaic, and Sacramento (SAC). The UW system uses VIC, SAC, Noah, and the Community Land Model (CLM). An assessment of differences in drought characteristics using both systems for the period 1979–2008 was performed. For soil moisture (SM) percentiles and runoff indices, differences are relatively small among different LSMs in the same system. However, the ensemble mean differences between the two systems are large over the western United States—in some cases exceeding 20% for SM and runoff percentile differences. These differences are most apparent after 2002 when the NCEP system transitioned to use the real-time North American Regional Reanalysis (NARR) and its precipitation gauge station data. (The UW system went into real-time operation in 2005.) Experiments were performed to address the sources of uncertainties. Comparison of simulations using the two systems with different model forcings indicates that the precipitation forcing differences are the primary source of the SM and runoff differences. While temperature, shortwave and longwave radiation, and wind speed forcing differences are also large after 2002, their contributions to SM and runoff differences are much smaller than precipitation.

ABSTRACT The U.S. Coast Guard (USCG) hosted the 2002 SONS Gulf National Incident Commander (NIC) Exercise in New Orleans, Louisiana on 23–25 April 2002 and the 2002 SONS Gulf Executive Seminar in Washington, D. C. on 26 April 2002. This massive effort was accomplished through almost two years of planning by a government/industry workgroup representing the USCG, Texas General Land Office (TGLO), Louisiana Oil Spill Coordinator's Office, ExxonMobil, Stolt-Nielsen Transportation Group, and Environmental Protection Agency Region VI. The original SONS exercise was scheduled to exercise the Nation's ability to respond to a SONS in a two-part format. The terrorist attacks at the Pentagon and the World Trade Center in September 2001 required that the original SONS exercise plans be delayed and amended. The final SONS exercise format was a three-part series. The first part involved tabletop discussions with port-level responders to determine what actions and issues would result from the exercise scenarios. The second part was a multi-day NIC tabletop exercise to understand the roles and responsibilities of the NIC by exploring the NIC's reactions to the scenarios and the issues raised by the affected ports. The third part was an executive-level seminar attended by senior federal government and industry executives as well as elected officials to discuss reactions to national-level issues identified by the NIC and to enhance interagency communication at the headquarters level.

Abstract. The South China Sea Operational Oceanography Forecasting System (SCSOFS), constructed and operated by the National Marine Environmental Forecasting Center of China, has been providing daily updated hydrodynamic forecasting in the South China Sea (SCS) for the next 5 d since 2013. This paper presents recent comprehensive updates to the configurations of the physical model and data assimilation scheme in order to improve the forecasting skill of the SCSOFS. This paper highlights three of the most sensitive updates: the sea surface atmospheric forcing method, the discrete tracer advection scheme, and a modification of the data assimilation scheme. Intercomparison and accuracy assessment among the five sub-versions were performed during the entire upgrading process using the OceanPredict Intercomparison and Validation Task Team Class 4 metrics. The results indicate that remarkable improvements have been made to the SCSOFSv2 with respect to the original version (known as SCSOFSv1). The domain-averaged monthly mean root-mean-square errors of the sea surface temperature and sea level anomaly have decreased from 1.21 to 0.52 ∘C and from 21.6 to 8.5 cm, respectively.

A pesquisa estudou a saída de modelos de mudanças climáticas que melhor expressam a atuação dos Vórtices Ciclônicos em Altos Níveis (VCANs) no Nordeste Brasileiro (NEB). Os VCANs foram quantificados pela sua ocorrência diária durante 5 anos (1995-1999), no período de outubro a março. O objeto de estudo foram 13 modelos do CMIP5/IPCC/AR5 (Coupled Model Intercomparison Project Phase 5/Intergovernmental Panel on Climate Change/Fifth Assessment Report), comparados com os resultados do NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research), por meio de métodos estatísticos para escolha do modelo que melhor indica a presença dos VCANs no NEB. A primeira análise comparativa foi feita através das correlações de Pearson, Kendall e Spearman, Raiz quadrada do erro quadrático médio, Raiz quadrada do erro quadrático médio normalizada e os índices de Eficiência e desempenho, Nash-Sutcliffe (NSE), Kling-Gupta (KGE) e o Índice de Concordância de Willmott (d). Em seguida foram selecionados os modelos de melhor desempenho e com significância estatística para uma análise posterior de acertos e erros através dos índices: Índice de Proporção Correta (PC), Índice de Sucesso Crítico (ISC), Probabilidade de Detecção (POD), Taxa de alarme Falso (TAF) e Taxa de Tendência (VIÉS). Para os testes estatísticos aplicados na primeira avaliação realizada o modelo MIROC4h foi o que apresentou os melhores índices seguido pelo MIROC-ESM e inmCM4, respectivamente. Além destes, ainda apresentaram correlação estatística significante o MPI-ESM-LR,o MRI-CGCM3 e o CSIRO-MK3-6-0. A segunda análise também apresentou o MIROC4h com os melhores valores de PC, ISC e POD, excetuando-se o VIÉS que apresentou o segundo melhor resultado e o TAF com o pior resultado em relação aos outros 5 modelos. Dessa forma o MIROC4h apresentou-se como o mais indicado entre os modelos do CMIP5 para estudos de cenários presentes e futuros de VCANs no NEB. A B S T R A C T The research studied the output of climate change models that best express the actions of Upper Tropospheric Cyclonic Vortices (UTCV) in high levels in the Northeast Brazil (NEB). The UTCV were quantified by a daily occurrence for 5 years (1995-1999) in the period from October to March. The object of the study were 13 models from CMIP5/IPCC/AR5 (Coupled Model Intercomparison Project Phase 5 / Intergovernmental Panel on Climate Change / Fifth Assessment Report ), compared with results from the NCEP / NCAR (National Centers for Environmental Prediction / National Center for Atmospheric Research) by means of statistical methods for choosing the model which best indicates the presence of UTCV in the NEB. The first comparative analysis was performed using the Pearson, Spearman and Kendall correlations, mean square error, normalized mean square error and efficiency and performance indices, Nash-Sutcliff (NSE), Kling-Gupta (KGE) and Index of Agreement of the Willmott (d). Then models with better performance and statistical significance for further analysis of successes and mistakes through the indices were selected: Index Proportion Correct (PC), Critical Success Index (CSI), Probability of Detection (POD), False Alarm Rate (FAR) and Trend Rate (BIAS). For the statistical analyzes used in the first test performed MIROC4h model showed the best rates followed by MIROC-ESM and inmCM4 respectively. In addition, further significant statistical correlation MPI-ESM-LR, MRI-CGCM3 and CSIRO-MK3-6-0. The second analysis also showed the MIROC4h with the best values ​​of PC, CSI and POD, except the BIAS that had the second best result and the FAR with the worst result in relation to the other five models considered in this phase. Thus the MIROC4h introduced himself as the most suitable model of the CMIP5 for studies of the present and future scenarios of UTCV in the NEB

Over the past few years, energy security and sustainable development have moved up the global agenda. Energy is what makes an economy run. There is a strong correlation between economic development and energy consumption. Energy security plays an important role in all economic sectors in attaining the long-term vision of inclusive economic growth and development of the economy. The attainment of this vision is difficult as it is challenged by the need to build energy infrastructures that are not only responsive to the growing demand but can withstand the maximum credible natural disaster. One of the primary objectives of sustainable development is to make people without access to enough energy be able to meet their needs through the provision of stable, reliable, clean, safe, and affordable energy services. This research will use the Granger Causality test to analyze the causal relationship among the endogenous variables among (1) GNI per capita; (2) GHG Emissions; and (3) Herfindahl-Hirschman Index (HHI) between energy-economic development and the influencing factors of power supply security indicators. In the end, this paper expects to suggest that the paper electric power development plans in the country also have implications for the path that would lead the country to what is known as a green economy. It is in this background that energy security and economic growth development are intertwined by public policy. In a broader development sense, public policy draws in the active involvement of the community in identifying problems. Anchored deeply in the national development agenda, the local community develops its own sets of development goals and pushes itself towards realizing this long-range vision. Hence, the output of public policy supported by strategic planning will require effective monitoring and evaluation of programs. This remains to be both a challenge and priority for both the national and local governments.ReferencesAstana, K. (2011). Greening the economy: mainstreaming the environment into economic development. https://sustainabledevelopment .un.org/content/documents/796unece2.pdfAslan, T., Ayşe, A., & Fatma, Z. (2013). The Impact of Electricity Consumption on Economic Development in. Istanbul University School of Economics.Edomah, N. (2018). Economics of Energy Supply. DOI: 10.1016/B978-0-12-409548-9.11713-0..Elahee, K. (2004). Access to Energy: The Key to Poverty Alleviation. Retrieved March 06, 2015, from International Research Foundation for Development Research: http://irfd.org/events/wfsids/virtual/papers/sids_kelahee.pdfEnergy Policy and Planning Bureau - Department of Energy Philippines. (2014). Philippine Energy Plan 2012-2030. Department of Energy.Gradl, C., & Knobloch, C. (2011). Energize the BoP! Energy Business Model Generator for Low-Income Markets (A Practitioners Guide). Enterprise Solutions for Development (ENDEVA).Gujarati, D. (2003). Basic Econometrics (4th Ed.). McGraw-Hill.Hamilton, C., Kellett, J. & Moore, T. (2021). Resourcing A Low Carbon Future.Hossain, Mondal et al. (2018). The Philippines energy future and lowcarbon development strategies. https://www.sciencedirect.com/science/article/pii/S0360544218300458International Atomic Energy Agency. (2005). IAEA.( 2005). Energy Indicators for Sustainable Development: Guidelines and Methodologies. IAEA.International Energy Agency. (2013). World Energy Outlook 2010. Paris. IEA.Kanchana, K. & Unesaki, H. (2014). ASEAN Energy Security: An Indicator-based Assessment. Energy Procedia. 56. 163–171. DOI: 10.1016/j.egypro.2014.07.145.Leuschner, P. (2014). The Effect of GDP per capita on Renewable Energy Production in China. University of Colorado Boulder.Mendoza Jr, C. B., Cayonte, D. D. D., Leabres, M. S., & Manaligod, L. R. A. (2019). Understanding multidimensional energy poverty in the Philippines. Energy Policy, 133, 110886.Modi, V., McDade, S., Lallement, D., & Saghir, J. (2005). Energy Services for the Millennium Development Goals. The International Bank for Reconstruction and Development/TheWorld Bank/ESMAP.Modi, V., McDade, S., Lallement, D., & Saghir, J. (2005). Energy Services for the Millennium Development Goals. United Nations Development Programme.Navarro, A., Sambodo, M. T., & Todoc, J. L. (October 2013). Energy Market Integration and Energy Poverty in the ASEAN. PIDS Discussion Paper Series.Pasternak, A. D. (October 2000). Global Energy Futures and Human Development: A Framework for Analysis. Department of Energy.Phillips, M. (n.d.). Why electricity demand is linked to GDP.Söderholm, P. (2020). The green economy transition: the challenges of technological change for sustainability. https://sustainableearth.biomedcentral.com/articles/10.1186/s42055-020-00029-yStern, D.I. (2004). Environmental Kuznets Curve: Encyclopedia of Energy. https://www.sciencedirect.com/topics/earth-andplanetary-sciences/environmental-kuznets-curveStiglitz, J. E., Sen, A., & Fitoussi, J.-P. (2009). Report by the Commission on the Measurement of Economic Performance and Social Progress. Institut national de la statistique et des études économiques (INSEE).University Corporation for Atmospheric Research (UCAR), https://scied.ucar.edu/learning-zone/how-climateworks/greenhouse-effect.U.S. Energy Information Association. (2013, March 22). Today in Energy. Retrieved February 28, 2014, from U.S. Energy Information Association - Independent Statistics and Analysis: http://www.eia.gov/todayinenergy/detail.cfm?id=10491Wen Center for Social Research Method. (n.d.). Research Methods Knowledge Base. 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The present study assessed dairy cow welfare through the application of the Italian National Animal Welfare Reference Center (CReNBA) checklist in 36 dairy farms located in Ragusa (Italy) subjected to two different management conditions, housing with free access to pasture (Group 1, farms n = 17) and indoor housing (Group 2, farms n = 19). Five areas of investigation were considered: Area A, “Farm management and personnel”; Area B, “Facilities and equipment”; Area C, “Animal-based measures”; Area D, “Inspection of microclimatic environmental conditions and alarm systems”; and Area E, “Biosecurity”. Blood samples were collected by coccygeal venipuncture from all animals (4081 cows). The specific antibodies against Mycobacterium avium subsp. paratuberculosis, Chlamydiophila abortus, Neospora caninum, bovine viral diarrhea virus, and the bovine herpesvirus were assessed by enzyme linked immunosorbent assay (ELISA) serological test. Group 1 (access to pasture) showed a lower value of percentage score recorded in Area A (p = 0.02) and E (p = 0.01) than Group 2 (indoor housing). Herpesvirus (Infectious bovine rhinotracheitis - IBR - detection of gB antibodies/IBR-gB) blood concentrations were higher in the cows housed indoor versus those with access to pasture (p = 0.01). Farm management and personnel (score A) was correlated with the level of bovine viral diarrhea virus (τ = 0.3754) and bovine-herpesvirus-specific antibodies (IBR-gB) (τ = 0.4159). “Biosecurity” percentage score showed a significant correlation with Chlamydiophila abortus (τ = −0.4621) in the cows with access to pasture and IBR-gB (τ = 0.3435) in the cows housed fully indoors. Group 2 showed a significantly reduced level of antibodies against Neospora caninum. In conclusion, differences in the welfare assessment score were observed in the “Farm management and personnel” and “Biosecurity” between the two management conditions. It had an effect on the prevalence of herpesvirus, which occurred more in cattle with access to pasture. Therefore, an accurate application of the checklist could be an instrument to prevent and control the spread of infections in farms.

BackgroundThe ORAL-surveillance trial showed a higher risk of major adverse cardiovascular events (MACE) and cancer in patients with rheumatoid arthritis (RA) taking tofacitinib, a Janus kinase inhibitor (JAKi), compared to those taking tumor necrosis factor alpha inhibitors (TNFi’s). However, little is known regarding the comparative safety of these two drug classes relative to non-TNFi biologics.ObjectivesTo assess the comparative safety of TNFi’s, non-TNFi’s, and JAKi’s in RA patients for the risk of MACE (e.g., myocardial infarction, cardiac arrest, sudden death, stroke, percutaneous coronary intervention, and coronary artery bypass graft), cancer, deep vein thrombosis (DVT), and pulmonary embolism (PE).MethodsWe performed a retrospective cohort study using IBM Watson MarketScan databases (2012-2019) of RA patients 18-64 years of age who initiated treatment with TNFi’s, non-TNFi’s, or JAKi’s on or after January 2012. We used Cox Proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for developing MACE, cancer, DVT, and PE within 2 years of initiation in patients on non-TNFi’s or JAKi’s relative to TNFi’s, adjusting for multiple confounders, including age, gender, geographic region, year of initiating a biologic, Charlson Comorbidity Index, frailty status, healthcare utilization within 12 months prior to starting treatment (i.e., major infection requiring hospital admissions, general hospital admissions, outpatient visits, and emergency department visits), and RA severity (i.e. disease-modifying antirheumatic drug, nonsteroidal anti-inflammatory drug, glucocorticoid, and opioid fills 3 months prior to starting treatment).ResultsA total of 39,032 drug initiation events met eligibility criteria for our study (73.6% initiation of TNFi’s, 18.6% non-TNFi’s, and 7.80% JAKi’s). The mean age of the patients in each of the groups ranged from 47-49 years old; the majority were female. The mean follow-up time was 349 days for TNFi’s, 272 days for non-TNFi’s, and 266 days for JAKi’s. Non-TNFi’s were associated with an increased risk of MACE, cancer, and DVT, though the incidence of adverse health outcomes overall was still quite low (Table 1). In multivariable models, patients who started non-TNFi’s had a significantly higher risk of MACE (HR 1.75; 1.34-2.28), incident cancer (HR 2.06; 1.70-2.50), and DVT (HR 1.84; 1.45-2.32) compared to those who initiated TNFi’s. Patients who filled JAKi’s had a significantly higher risk of developing cancer compared to those who filled TNFi’s (HR 1.48; 1.09-2.03).ConclusionTNFi’s may be safer for RA treatment than non-TNFi’s and JAKi’s for RA in this generally younger and predominantly female population. However, since most RA patients initiate treatment with TNFi’s, results could be confounded by the possibility of more severe or prolonged disease in patients on non-TNFi’s and JAKi’s. These findings need to be replicated in other study populations. Future steps include looking at the risk conferred by individual non-TNFi’s towards these risks. Studies with longer follow-up are needed for better assessment of cancer risk among these drug classes.Table 1.Incidence per 10,000 person-years of each adverse health outcome* stratified by drug class in RA patients 18-64 years of age.Adverse Health OutcomeTNFi n = 28,716 (73.6%)**Non-TNFi n = 7,290 (18.6%)**JAKi n = 3,026 (7.80%)**MACE72.9162.694.8Cancer132.9296.4192.3DVT90.9216.5107.7PE22.143.924.6*Outcomes are not mutually exclusive; each patient could have experienced multiple outcomes.**Number and percentage of drug class initiation events.Reference[1] Ytterberg, S. R., Bhatt, D. L., Mikuls, T. R., Koch, G. G., Fleischmann, R., Rivas, J. L., Germino, R., Menon, S., Sun, Y., Wang, C., Shapiro, A. B., Kanik, K. S., Connell, C. A., & ORAL Surveillance Investigators (2022). Cardiovascular and Cancer Risk with Tofacitinib in Rheumatoid Arthritis.The New England journal of medicine,386(4), 316–326.AcknowledgementsResearch reported in this publication was supported by the National Institute of Arthritis And Musculoskeletal And Skin Diseases of the National Institutes of Health under Award Number K23AR079588 to Dr. Namrata Singh. This research was supported in part by the University of Washington Clinical Learning, Evidence, And Research (CLEAR) Center for Musculoskeletal Disorders, Administrative, Methodologic and Resource Cores and NIAMS/NIH grant P30AR072572.Disclosure of InterestsXavier Sendaydiego: None declared, Laura Gold: None declared, Jiha Lee: None declared, Radjiv Goulabchand Consultant of: NOVARTIS: involved in board concerning ITP management, Grant Hughes Employee of: Janssen Rheumatology Fellowship in Diagnostic and Therapeutic Disparities in Axial Spondyloarthritis: PI/Program Director, 7/1/2022 – 6/30/2023, Mathilde Pioro: None declared, James Andrews: None declared, Una Makris: None declared, Pradeep Suri: None declared, Jeffrey Jarvik: None declared, Jeffrey Sparks Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Gilead, Inova Diagnostics, Janssen, Optum, and Pfizer, Grant/research support from: Bristol Myers Squibb, Siddharth Singh: None declared, Namrata Singh: None declared.

Climate change induced sea-level rise (SLR) is on its increase globally. Regionally the lowlands of China, Vietnam, Bangladesh, and islands of the Malaysian, Indonesian and Philippine archipelagos are among the world’s most threatened regions. Sea-level rise has major impacts on the ecosystems and society. It threatens coastal populations, economic activities, and fragile ecosystems as mangroves, coastal salt-marches and wetlands. This paper provides a summary of the current state of knowledge of sea level-rise and its effects on both human and natural ecosystems. The focus is on coastal urban areas and low lying deltas in South-East Asia and Vietnam, as one of the most threatened areas in the world. About 3 mm per year reflects the growing consensus on the average SLR worldwide. The trend speeds up during recent decades. The figures are subject to local, temporal and methodological variation. In Vietnam the average values of 3.3 mm per year during the 1993-2014 period are above the worldwide average. Although a basic conceptual understanding exists that the increasing global frequency of the strongest tropical cyclones is related with the increasing temperature and SLR, this relationship is insufficiently understood. Moreover the precise, complex environmental, economic, social, and health impacts are currently unclear. SLR, storms and changing precipitation patterns increase flood risks, in particular in urban areas. Part of the current scientific debate is on how urban agglomeration can be made more resilient to flood risks. Where originally mainly technical interventions dominated this discussion, it becomes increasingly clear that proactive special planning, flood defense, flood risk mitigation, flood preparation, and flood recovery are important, but costly instruments. Next to the main focus on SLR and its effects on resilience, the paper reviews main SLR associated impacts: Floods and inundation, salinization, shoreline change, and effects on mangroves and wetlands. The hazards of SLR related floods increase fastest in urban areas. This is related with both the increasing surface major cities are expected to occupy during the decades to come and the increasing coastal population. In particular Asia and its megacities in the southern part of the continent are increasingly at risk. The discussion points to complexity, inter-disciplinarity, and the related uncertainty, as core characteristics. An integrated combination of mitigation, adaptation and resilience measures is currently considered as the most indicated way to resist SLR today and in the near future.References Aerts J.C.J.H., Hassan A., Savenije H.H.G., Khan M.F., 2000. Using GIS tools and rapid assessment techniques for determining salt intrusion: Stream a river basin management instrument. 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This study aim to attempt mapping out the Land Use or Land Cover (LULC) status of Regional Project Coordination Committee (RPCC) between 2009-2019 with a view of detecting the land consumption rate and the changes that has taken place using RS and GIS techniques; serving as a precursor to the further study on urban induced variations or change in weather pattern of the cityn Rangpur City Corporation(RCC) is the main administrative functional area for both of Rangpur City and Rangpur division and experiencing a rapid changes in the field of urban sprawl, cultural and physical landscape,city growth. These agents of Land use or Land cover (LULC) varieties are responsible for multi-dimensional problems such as traffic congestion, waterlogging, and solid waste disposal, loss of agricultural land. In this regard, this study fulfills LULC changes by using Geographical Information Systems (GIS) and Remote Sensing (RS) as well as field survey was conducted for the measurement of change detection. The sources of data were Landsat 7 ETM and landsat 8 OLI/TIRS of both C1 level 1. Then after correcting the data, geometrically and radiometrically change detection and combined classification (supervised & unsupervised) were used. The study finds LULC changes built-up area, water source, agricultural land, bare soil in a change of percentage is 17.23, 2.58, -9.94, -10.19 respectively between 2009 and 2019. Among these changes, bare soil is changed to a great extent, which indicates the expansion of urban areas is utilizing the land to a proper extent. Keywords: Urban expansion; land use; land cover; remote sensing; geographic information system (GIS); Rangpur City Corporation(RCC). References Al Rifat, S. A., & Liu, W. (2019). 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(2008). Impact of land use and land cover change on the water balance of a large agricultural watershed: Historical effects and future directions. Water Resources Research, 44(7). doi:10.1029/2007wr006644 Copyright (c) 2019 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License