928 resultados para curriculum in Swedish as Second Language 1


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BACKGROUND In 2007, a first survey on undergraduate palliative care teaching in Switzerland has revealed major heterogeneity of palliative care content, allocation of hours and distribution throughout the 6 year curriculum in Swiss medical faculties. This second survey in 2012/13 has been initiated as part of the current Swiss national strategy in palliative care (2010 - 2015) to serve as a longitudinal monitoring instrument and as a basis for redefinition of palliative care learning objectives and curriculum planning in our country. METHODS As in 2007, a questionnaire was sent to the deans of all five medical faculties in Switzerland in 2012. It consisted of eight sections: basic background information, current content and hours in dedicated palliative care blocks, current palliative care content in other courses, topics related to palliative care presented in other courses, recent attempts at improving palliative care content, palliative care content in examinations, challenges, and overall summary. Content analysis was performed and the results matched with recommendations from the EAPC for undergraduate training in palliative medicine as well as with recommendations from overseas countries. RESULTS There is a considerable increase in palliative care content, academic teaching staff and hours in all medical faculties compared to 2007. No Swiss medical faculty reaches the range of 40 h dedicated specifically to palliative care as recommended by the EAPC. Topics, teaching methods, distribution throughout different years and compulsory attendance still differ widely. Based on these results, the official Swiss Catalogue of Learning Objectives (SCLO) was complemented with 12 new learning objectives for palliative and end of life care (2013), and a national basic script for palliative care was published (2015). CONCLUSION Performing periodic surveys of palliative care teaching at national medical faculties has proven to be a useful tool to adapt the national teaching framework and to improve the recognition of palliative medicine as an integral part of medical training.

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BACKGROUND The number of patients in need of second-line antiretroviral drugs is increasing in sub-Saharan Africa. We aimed to project the need of second-line antiretroviral therapy in adults in sub-Saharan Africa up to 2030. METHODS We developed a simulation model for HIV and applied it to each sub-Saharan African country. We used the WHO country intelligence database to estimate the number of adult patients receiving antiretroviral therapy from 2005 to 2014. We fitted the number of adult patients receiving antiretroviral therapy to observed estimates, and predicted first-line and second-line needs between 2015 and 2030. We present results for sub-Saharan Africa, and eight selected countries. We present 18 scenarios, combining the availability of viral load monitoring, speed of antiretroviral scale-up, and rates of retention and switching to second-line. HIV transmission was not included. FINDINGS Depending on the scenario, 8·7-25·6 million people are expected to receive antiretroviral therapy in 2020, of whom 0·5-3·0 million will be receiving second-line antiretroviral therapy. The proportion of patients on treatment receiving second-line therapy was highest (15·6%) in the scenario with perfect retention and immediate switching, no further scale-up, and universal routine viral load monitoring. In 2030, the estimated range of patients receiving antiretroviral therapy will remain constant, but the number of patients receiving second-line antiretroviral therapy will increase to 0·8-4·6 million (6·6-19·6%). The need for second-line antiretroviral therapy was two to three times higher if routine viral load monitoring was implemented throughout the region, compared with a scenario of no further viral load monitoring scale-up. For each monitoring strategy, the future proportion of patients receiving second-line antiretroviral therapy differed only minimally between countries. INTERPRETATION Donors and countries in sub-Saharan Africa should prepare for a substantial increase in the need for second-line drugs during the next few years as access to viral load monitoring improves. An urgent need exists to decrease the costs of second-line drugs. FUNDING World Health Organization, Swiss National Science Foundation, National Institutes of Health.

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The way media depict women and men can reinforce or diminish gender stereotyping. Which part does language play in this context? Are roles perceived as more gender-balanced when feminine role nouns are used in addition to masculine ones? Research on gender-inclusive language shows that the use of feminine-masculine word pairs tends to increase the visibility of women in various social roles. For example, when speakers of German were asked to name their favorite "heroine or hero in a novel," they listed more female characters than when asked to name their favorite "hero in a novel." The research reported in this article examines how the use of gender-inclusive language in news reports affects readers' own usage of such forms as well as their mental representation of women and men in the respective roles. In the main experiment, German participants (N = 256) read short reports about heroes or murderers which contained either masculine generics or gender-inclusive forms (feminine-masculine word pairs). Gender-inclusive forms enhanced participants' own usage of gender-inclusive language and this resulted in more gender-balanced mental representations of these roles. Reading about "heroines and heroes" made participants assume a higher percentage of women among persons performing heroic acts than reading about "heroes" only, but there was no such effect for murderers. A post-test suggested that this might be due to a higher accessibility of female exemplars in the category heroes than in the category murderers. Importantly, the influence of gender-inclusive language on the perceived percentage of women in a role was mediated by speakers' own usage of inclusive forms. This suggests that people who encounter gender-inclusive forms and are given an opportunity to use them, use them more themselves and in turn have more gender-balanced mental representations of social roles.

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A shortage of bilingual/bicultural speech language pathologists may reflect a problem with recruitment and retention of bilingual/bicultural students. The purpose of the present study was to survey graduate training programs in speech language pathology to determine typical policies and practices concerning students who apply and are admitted as ELLs. With a growing number of ELL children needing services from a bilingual SLP, it seems that little is being done to address the issue. The problem may be with the reluctance of programs to not only accept ELL students, but there also seems to be a disinclination for any sort of training program to be established for these ELL students. Clinic directors were asked to complete a survey about ELLs seeking clinical training in speech language pathology. In particular, we were interested in obtaining information about whether clinical training programs a) provided opportunities for ELL to participate in clinic, b) assessed the English skills of these students, and c) provided remediation if these students English skills were judged to be less than proficient.

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment at 9 stations in the North Atlantic, from the Iceland Basin in the East to the Labrador Sea in the West. The data were sampled along vertical profiles by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA) and a fluorescence sensor (F, ECO Puck chlorophyll a fluorometer, WET Labs Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10(body volume) increments, see Edvardsen et al. (2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). Fluorescence was roughly converted into chlorophyll based on filtered chlorophyll values obtained from station 10 in the Labrador Sea. Due to the low number of filtered samples that was used for the conversion the resulting chlorophyll values should be considered with care. CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column, see Herman et al., (2004, doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10 (body volume) increments (Edvardsen et al., 2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column (Herman et al., 2004; doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).