cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19898029
title: Laboratory for innovation in Primary Health Care: implementation and results

description: Abstract This article presents and problematizes innovation actions aimed at improving the quality of Primary Health Care (PHC), describing an experience that can be adapted to different contexts, considering diverse sociodemographic, economic, cultural and epidemiological realities. We conducted an exploratory study using documentary sources referring to the implementation of the Campo Grande Laboratory for Innovation in Primary Health Care (INOVAAPS). The project proposes the reorientation of the care model adopted in the municipality’s public primary care services, redefining work processes and improving the quality of practice. We identified product, process and organizational innovations that have the potential to transform and tailor health care practices to the population’s health needs. It is concluded that the proposals implemented by the project focus on the consolidation and expansion of access to primary care, recruitment and training of adequately qualified health professionals, adoption of resolutive technologies, regulatory improvement, and strengthening the mediating role of primary health care.
DOI: 10.6084/m9.figshare.19898029.v1
title: Laboratory for innovation in Primary Health Care: implementation and results

description: Abstract This article presents and problematizes innovation actions aimed at improving the quality of Primary Health Care (PHC), describing an experience that can be adapted to different contexts, considering diverse sociodemographic, economic, cultural and epidemiological realities. We conducted an exploratory study using documentary sources referring to the implementation of the Campo Grande Laboratory for Innovation in Primary Health Care (INOVAAPS). The project proposes the reorientation of the care model adopted in the municipality’s public primary care services, redefining work processes and improving the quality of practice. We identified product, process and organizational innovations that have the potential to transform and tailor health care practices to the population’s health needs. It is concluded that the proposals implemented by the project focus on the consolidation and expansion of access to primary care, recruitment and training of adequately qualified health professionals, adoption of resolutive technologies, regulatory improvement, and strengthening the mediating role of primary health care.
DOI: 10.6084/m9.figshare.19898035.v1
title: Perception, Torsion, Event: links between body, discourse and art

description: ABSTRACT This study is based on the identification of the subject and his/her social place in the performance, in order to connect subject, body, and gesture in the performing act. This link becomes possible from the discursive analysis of the sixth dimension of the performing activity: an updating of Schechner’s theory of performance, in conjunction with the postulates of Merleau-Ponty on perception, and Pêcheux on discourse. Results indicate an opportunity for a materialistic analysis of the field of sensitive experimentation, emphasizing the theoretical unfolding of the notion of perception in the analytical act consolidated in the feeling and action of/by the subject’s body.
DOI: 10.6084/m9.figshare.19898035
title: Perception, Torsion, Event: links between body, discourse and art

description: ABSTRACT This study is based on the identification of the subject and his/her social place in the performance, in order to connect subject, body, and gesture in the performing act. This link becomes possible from the discursive analysis of the sixth dimension of the performing activity: an updating of Schechner’s theory of performance, in conjunction with the postulates of Merleau-Ponty on perception, and Pêcheux on discourse. Results indicate an opportunity for a materialistic analysis of the field of sensitive experimentation, emphasizing the theoretical unfolding of the notion of perception in the analytical act consolidated in the feeling and action of/by the subject’s body.
DOI: 10.5517/ccdc.csd.cc27fzc1
title: CCDC 2069013: Experimental Crystal Structure Determination

description: Related Article: Yue Wang, Na Xu, Jianxin Ma, Hui Li, Yue Zhang, Guocheng Liu, Xiuli Wang|2022|Inorg.Chem.|61|7780|doi:10.1021/acs.inorgchem.2c00164
DOI: 10.5517/ccdc.csd.cc28hxqf
title: CCDC 2100675: Experimental Crystal Structure Determination

description: Related Article: Bingbing Guo, Hongyan Liu, Jia Pang, Qiang Lyu, Yutong Wang, Weidong Fan, Xiaoqing Lu, Daofeng Sun|2022|J.Hazard.Mater.|436|129094|doi:10.1016/j.jhazmat.2022.129094
DOI: 10.5517/ccdc.csd.cc28wlf6
title: CCDC 2111888: Experimental Crystal Structure Determination

description: Related Article: Manasa Purushotham, Bishwajit Paul, Divya Maldepalli Govindachar, Ashutosh Kumar Singh, Ganga Periyasamy, Sebastian C. Peter|2022|J.Mol.Struct.|1264|133276|doi:10.1016/j.molstruc.2022.133276
DOI: 10.5517/ccdc.csd.cc28x3t4
title: CCDC 2112396: Experimental Crystal Structure Determination

description: Related Article: Manasa Purushotham, Bishwajit Paul, Divya Maldepalli Govindachar, Ashutosh Kumar Singh, Ganga Periyasamy, Sebastian C. Peter|2022|J.Mol.Struct.|1264|133276|doi:10.1016/j.molstruc.2022.133276
DOI: 10.5517/ccdc.csd.cc28x3v5
title: CCDC 2112397: Experimental Crystal Structure Determination

description: Related Article: Manasa Purushotham, Bishwajit Paul, Divya Maldepalli Govindachar, Ashutosh Kumar Singh, Ganga Periyasamy, Sebastian C. Peter|2022|J.Mol.Struct.|1264|133276|doi:10.1016/j.molstruc.2022.133276
DOI: 10.5517/ccdc.csd.cc28x3w6
title: CCDC 2112398: Experimental Crystal Structure Determination

description: Related Article: Manasa Purushotham, Bishwajit Paul, Divya Maldepalli Govindachar, Ashutosh Kumar Singh, Ganga Periyasamy, Sebastian C. Peter|2022|J.Mol.Struct.|1264|133276|doi:10.1016/j.molstruc.2022.133276
DOI: 10.5517/ccdc.csd.cc28xc9w
title: CCDC 2112628: Experimental Crystal Structure Determination

description: Related Article: Saul M. Cooper, Andrew J. P. White, Thomas R. Eykyn, Michelle T. Ma, Philip W. Miller, Nicholas J. Long|2022|Inorg.Chem.|61|8000|doi:10.1021/acs.inorgchem.2c00693
DOI: 10.5517/ccdc.csd.cc28xcbx
title: CCDC 2112629: Experimental Crystal Structure Determination

description: Related Article: Saul M. Cooper, Andrew J. P. White, Thomas R. Eykyn, Michelle T. Ma, Philip W. Miller, Nicholas J. Long|2022|Inorg.Chem.|61|8000|doi:10.1021/acs.inorgchem.2c00693
DOI: 10.5517/ccdc.csd.cc28xccy
title: CCDC 2112630: Experimental Crystal Structure Determination

description: Related Article: Saul M. Cooper, Andrew J. P. White, Thomas R. Eykyn, Michelle T. Ma, Philip W. Miller, Nicholas J. Long|2022|Inorg.Chem.|61|8000|doi:10.1021/acs.inorgchem.2c00693
DOI: 10.6084/m9.figshare.10305443.v2
title: Fields of Research (FoR) Classification

description: The 2008 ANZSRC FoR classification allows R&D activity to be categorised according to the field of research. In this respect, it is the methodology used in the R&D that is being considered.<br><br>The categories in the classification include major fields and related sub-fields of research and emerging areas of study investigated by businesses, universities, tertiary institutions, national research institutions and other organisations.
DOI: 10.5517/ccdc.csd.cc28xcdz
title: CCDC 2112631: Experimental Crystal Structure Determination

description: Related Article: Saul M. Cooper, Andrew J. P. White, Thomas R. Eykyn, Michelle T. Ma, Philip W. Miller, Nicholas J. Long|2022|Inorg.Chem.|61|8000|doi:10.1021/acs.inorgchem.2c00693
DOI: 10.5517/ccdc.csd.cc265ys4
title: CCDC 2031516: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc260m51
title: CCDC 2026382: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc265ygt
title: CCDC 2031506: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc265yhv
title: CCDC 2031507: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc2668h6
title: CCDC 2031817: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc2668c2
title: CCDC 2031813: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc2668d3
title: CCDC 2031814: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc260m40
title: CCDC 2026381: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc2668f4
title: CCDC 2031815: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc2668g5
title: CCDC 2031816: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc2668j7
title: CCDC 2031818: Experimental Crystal Structure Determination

description: Related Article: Yong Xu, Li He, Shouwen Jin, Xingjun Gao, Hui Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
description: Related Article: Jingxuan Zhou, Shouwen Jin, Li He, Yong Xu, Xingjun Gao, Bin Liu, Zhuoran Chen, Daqi Wang|2022|J.Mol.Struct.|1263|133042|doi:10.1016/j.molstruc.2022.133042
DOI: 10.5517/ccdc.csd.cc29h9ns
title: CCDC 2129875: Experimental Crystal Structure Determination

description: Related Article: Saul M. Cooper, Andrew J. P. White, Thomas R. Eykyn, Michelle T. Ma, Philip W. Miller, Nicholas J. Long|2022|Inorg.Chem.|61|8000|doi:10.1021/acs.inorgchem.2c00693
DOI: 10.5517/ccdc.csd.cc29hjx8
title: CCDC 2130100: Experimental Crystal Structure Determination

description: Related Article: Zhizhou Liu, Chao Li, Chen Chen, Tong Wang, Liang He, Xueyan Nan, Li Li, Qing Qian, Pengli Bai|2022|Dyes Pigm.|204|110404|doi:10.1016/j.dyepig.2022.110404
DOI: 10.5517/ccdc.csd.cc29w9m4
title: CCDC 2141406: Experimental Crystal Structure Determination

description: Related Article: Santosh J. Gharpure, Sanyog Kumari|2022|J.Org.Chem.|87|6781|doi:10.1021/acs.joc.2c00473
DOI: 10.5517/ccdc.csd.cc29wbdy
title: CCDC 2141430: Experimental Crystal Structure Determination

description: Related Article: Yan Zheng, Siqi Dong, Kai Xu, Delong Liu, Wanbin Zhang|2022|Org.Lett.|24|3440|doi:10.1021/acs.orglett.2c00937
DOI: 10.5517/ccdc.csd.cc2bn1gj
title: CCDC 2164217: Experimental Crystal Structure Determination

description: Related Article: Cornelius V. Gärtner, Christoph Schneider|2022|Org.Lett.|24|3560|doi:10.1021/acs.orglett.2c01265
DOI: 10.25430/researchdata.cab.unipd.it.00000645
title: Data related to article titled "A quantitative assay for Ca2+ uptake through normal and pathological hemichannels".

description: Hemichannels (HCs) are large pore hexameric structures composed of connexin (Cx) subunits that allow the exchange of ions, metabolites, and a variety of other molecules between cell cytoplasm and extracellular milieu. HC inhibitors are attracting growing interest as drug candidates because deregulated fluxes through HCs have been implicated in a plethora of genetic conditions and other diseases. HC activity has been mainly investigated by electrophysiological methods and/or using HC-permeable dye uptake measurements. Here, we present an all-optical assay based on fluo-rometric measurements of Ca2+ uptake with a Ca2+-selective genetically encoded indicator (GCaMP6s) that permits optical tracking of cytosolic Ca2+ concentration ([Ca2+]cyt) changes with high sensitivity. We exemplify use of the assay in stable pools of HaCaT cells overexpressing human Cx26, Cx46, or the pathological mutant Cx26G45E under control of a tetracycline (Tet) responsive element (TRE) promoter (Tet-on). We demonstrate its usefulness for the characteriza-tion of new monoclonal antibodies (mAb) targeting the extracellular domain of the HCs. Although we developed the assay on a spinning disk confocal fluorescence microscope, the same method-ology can be extended seamlessly to high-throughput high-content platforms to screen other kinds of inhibitors and/or to probe HCs expressed in primary cells and microtissues.
DOI: 10.34688/v9te-6y23
title: OpenSpecimen Samples
DOI: 10.17028/rd.lboro.14406644
title: Cultural-cognitive elements and BIM adoption

description: This is questionnaire data for the analysis of the construction industry's cultural-cognitive elements associated with BIM adoption. The dataset includes the name for each variable, the wording as in the questionnaire, and the measurement scale.
DOI: 10.17028/rd.lboro.14406644.v1
title: Cultural-cognitive elements and BIM adoption

description: This is questionnaire data for the analysis of the construction industry's cultural-cognitive elements associated with BIM adoption. The dataset includes the name for each variable, the wording as in the questionnaire, and the measurement scale.
DOI: 10.5281/zenodo.6574855
title: Soil sand content [%] for continental Europe at 30 m spatial resolution for period 2000-2020: Open Soil Data Cube for Europe

description: Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environment for statistical computing (Hengl & MacMillan, 2019; Hengl, et al., 2021). For each pixel we provide prediction errors as 1 standard deviation in either log or the original variable scale. The short description of currently available soil properties: sand.tot = sand content [percent]; Soil properties were predicted at fixed depths: Surface soil = s0..0cm,<br> Subsoil 1 = s30..30cm,<br> Subsoil 2 = s60..60cm,<br> Subsoil 3 = s100..100cm. To produce estimates for depth intervals e.g. 0–30 cm, 0–100 cm best use the trapezoidal rule formula. Periods: 2000 (2000–2003), 2004 (2004–2007), 2008 (2008–2011), 2012 (2012–2015), 2016 (2016–2019), 2020;
DOI: 10.5281/zenodo.6574844
title: Soil pH in H2O [-] for continental Europe at 30 m spatial resolution for period 2000-2020: Open Soil Data Cube for Europe

description: Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environment for statistical computing (Hengl & MacMillan, 2019; Hengl, et al., 2021). For each pixel we provide prediction errors as 1 standard deviation in either log or the original variable scale. The short description of currently available soil properties: soil pH in H2O; Soil properties were predicted at fixed depths: Surface soil = s0..0cm,<br> Subsoil 1 = s30..30cm,<br> Subsoil 2 = s60..60cm,<br> Subsoil 3 = s100..100cm. To produce estimates for depth intervals e.g. 0–30 cm, 0–100 cm best use the trapezoidal rule formula. Periods: 2000 (2000–2003), 2004 (2004–2007), 2008 (2008–2011), 2012 (2012–2015), 2016 (2016–2019), 2020;
DOI: 10.5281/zenodo.6574843
title: Soil pH in H2O [-] for continental Europe at 30 m spatial resolution for period 2000-2020: Open Soil Data Cube for Europe

description: Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environment for statistical computing (Hengl & MacMillan, 2019; Hengl, et al., 2021). For each pixel we provide prediction errors as 1 standard deviation in either log or the original variable scale. The short description of currently available soil properties: soil pH in H2O; Soil properties were predicted at fixed depths: Surface soil = s0..0cm,<br> Subsoil 1 = s30..30cm,<br> Subsoil 2 = s60..60cm,<br> Subsoil 3 = s100..100cm. To produce estimates for depth intervals e.g. 0–30 cm, 0–100 cm best use the trapezoidal rule formula. Periods: 2000 (2000–2003), 2004 (2004–2007), 2008 (2008–2011), 2012 (2012–2015), 2016 (2016–2019), 2020;
DOI: 10.5526/erdr-00000150
title: Stomata on the abaxial and adaxial leaf surface contribute differently to leaf gas exchange and photosynthesis in wheat
DOI: 10.5281/zenodo.6574829
title: Soil bulk density [10x kg/m3] for continental Europe at 30 m spatial resolution for period 2000-2020: Open Soil Data Cube for Europe

description: Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environment for statistical computing (Hengl & MacMillan, 2019; Hengl, et al., 2021). For each pixel we provide prediction errors as 1 standard deviation in either log or the original variable scale. The short description of currently available soil properties: db_od = bulk density over dry [kg/m3 ⨉ 10]; Soil properties were predicted at fixed depths: Surface soil = s0..0cm,<br> Subsoil 1 = s30..30cm,<br> Subsoil 2 = s60..60cm,<br> Subsoil 3 = s100..100cm. To produce estimates for depth intervals e.g. 0–30 cm, 0–100 cm best use the trapezoidal rule formula. Periods: 2000 (2000–2003), 2004 (2004–2007), 2008 (2008–2011), 2012 (2012–2015), 2016 (2016–2019), 2020; The bulk density maps are also provided in 10 kg / m-cubic to reduce total data size; to convert values to kg / m-cubic multiply by 10 e.g. 120 = 1200 kg / m-cubic = 1.2 t / m-cubic.
DOI: 10.5281/zenodo.6574828
title: Soil bulk density [10x kg/m3] for continental Europe at 30 m spatial resolution for period 2000-2020: Open Soil Data Cube for Europe

description: Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environment for statistical computing (Hengl & MacMillan, 2019; Hengl, et al., 2021). For each pixel we provide prediction errors as 1 standard deviation in either log or the original variable scale. The short description of currently available soil properties: db_od = bulk density over dry [kg/m3 ⨉ 10]; Soil properties were predicted at fixed depths: Surface soil = s0..0cm,<br> Subsoil 1 = s30..30cm,<br> Subsoil 2 = s60..60cm,<br> Subsoil 3 = s100..100cm. To produce estimates for depth intervals e.g. 0–30 cm, 0–100 cm best use the trapezoidal rule formula. Periods: 2000 (2000–2003), 2004 (2004–2007), 2008 (2008–2011), 2012 (2012–2015), 2016 (2016–2019), 2020; The bulk density maps are also provided in 10 kg / m-cubic to reduce total data size; to convert values to kg / m-cubic multiply by 10 e.g. 120 = 1200 kg / m-cubic = 1.2 t / m-cubic.
DOI: 10.48370/ofd/byluwf/onlchl
title: FMW Dacryobolus karstenii (Bres.) Oberw. ex Parmasto M-4793 (2).JPG

description: :unav
DOI: 10.48370/ofd/byluwf/zg1mhc
title: FMW Dacryobolus karstenii (Bres.) Oberw. ex Parmasto M-4793.JPG

description: :unav
DOI: 10.48370/ofd/byluwf/7tkn9u
title: FMW Dacryobolus karstenii (Bres.) Oberw. ex Parmasto M-4793 (3).JPG

description: :unav
DOI: 10.48370/ofd/byluwf
title: Dacryobolus karstenii (Bres.) Oberw. ex Parmasto, 4793

description: Fungarium Macromycetes
DOI: 10.48370/ofd/bszezy/fycbkb
title: FMW Dacryobolus karstenii (Bres.) Oberw. ex Parmasto M-4260 (3).JPG

description: :unav
DOI: 10.48370/ofd/bszezy/ib1xqk
title: FMW Dacryobolus karstenii (Bres.) Oberw. ex Parmasto M-4260.JPG

description: :unav
DOI: 10.48370/ofd/bszezy/hfuoer
title: FMW Dacryobolus karstenii (Bres.) Oberw. ex Parmasto M-4260 (2).JPG

description: :unav
DOI: 10.48370/ofd/bszezy
title: Dacryobolus karstenii (Bres.) Oberw. ex Parmasto, 4260

description: Fungarium Macromycetes
DOI: 10.48370/ofd/skhy39/fjhvri
title: FMW Dacryobolus karstenii (Bres.) Oberw. ex Parmasto M-1965 (2).JPG

description: :unav
DOI: 10.48370/ofd/skhy39/rnq5le
title: FMW Dacryobolus karstenii (Bres.) Oberw. ex Parmasto M-1965.JPG

description: :unav
DOI: 10.48370/ofd/skhy39/j7zqks
title: FMW Dacryobolus karstenii (Bres.) Oberw. ex Parmasto M-1965 (3).JPG

description: :unav
DOI: 10.48370/ofd/skhy39
title: Dacryobolus karstenii (Bres.) Oberw. ex Parmasto, 1965

description: Fungarium Macromycetes
DOI: 10.6084/m9.figshare.14304485
title: Lower back pain and level of disability amongst construction workers

description: Abstract Introduction: Lower back pain is a symptom that significantly affects people's lives, especially workers whose professional achievements can be limited by this pain. Objective: Estimate prevalence of lower back pain and describe the levels of disability amongst construction workers. Methods: 84 construction workers participated in this study. Each of them was given three questionnaires. The first questionnaire was aimed at identifying sociodemographic variables such as work and lifestyle habits. The second questionnaire was created by Monnerat and Pereira to measure the intensity of lower back pain. The last questionnaire was created by Roland-Morris to measure functional incapacity. The SPSS 18.0 program was used for data analysis. Lower back pain was described with the Mann Whitney U test using the variables of both labor and time. Furthermore, a correlation between lower back pain intensity and functional incapacity was found by Spearman. Results: A higher prevalence of lower back pain was found (71.4%) amongst the construction workers especially during laborious activity. Time worked did not affect the prevalence of lower back pain nor did it lead to functional incapacity in workers. Conclusion: Based on all observed data, it was concluded that strenuous labor activity amongst the populace drove lower back pain prevalence.