Ichthyoplankton density and zooplankton biomass in the Benguela upwelling system during AFR258 in December 2009

IIchthyoplankton density (fish eggs and larvae) and bulk zooplankton biomass in December 2009 were determined for 22 stations in the Benguela upwelling system, based on oblique Multinet hauls during the FRS Africana cruise AFR258. A HYDROBIOS Multinet, type Midi (0.25 m**2 mouth area) was equipped with five nets of 500 µm-mesh size, temperature and oxygen probes, and an inner and outer flow meter to monitor the net's trajectory (for volume filtered calculations) as well as net clogging. The Multinet was handled over the side, towed horizontally at 2 knots. Winch speed when fearing was 0.5 or 0.3 m/s, heaving velocity 0.2 - 0.3 m/s. The Multinet was towed obliquely at 22 stations sampling the upper 200 m of the water column, which were divided into five different depth strata after inspection of temperature and oxygen concentration depth profiles. Ichthyoplankton densities and zooplankton biomass were calculated for each depth stratum (=single net) from total abundance and the volume of water filtered [individuals per m**3 and g wet weight per m**3, respectively]. Densities and biomass were integrated over the area for each station [individuals per m**2], as sum of calculations for each net: Sum ([individuals per m**3]*Delta (depth bot[m]-depth top [m]).

Ichthyoplankton density and zooplankton biomass in the Benguela upwelling system during MSM07/3 in March 2008

Ichthyoplankton density (fish eggs and larvae) and bulk zooplankton biomass in March 2008 were determined for 32 stations in the northern Benguela upwelling system, based on oblique Multinet hauls during the FS Maria S. Merian MSM07/3 cruise. A HYDROBIOS Multinet, type Midi (0.25 m**2 mouth area) was equipped with five nets of 500 µm-mesh size, temperature and oxygen probes, and an inner and outer flow meter to monitor the net's trajectory (for volume filtered calculations) as well as net clogging. The Multinet was handled over the side, towed horizontally at 2 knots. Winch speed when fearing was 0.5 or 0.3 m/s, heaving velocity 0.2 - 0.3 m/s. The Multinet was towed obliquely at 32 stations sampling the upper 200 m of the water column, which were divided into five different depth strata after inspection of temperature and oxygen concentration depth profiles. Ichthyoplankton densities and zooplankton biomass were calculated for each depth stratum (=single net) from total abundance and the volume of water filtered [individuals per m**3 and g wet weight per m**3, respectively]. In addition, densities and biomass were integrated over the area for each station [individuals per m**2], as sum of calculations for each net: Sum ([individuals per m**3]*Delta (depth bot[m]-depth top [m]).

Ichthyoplankton density and zooplankton biomass in the Benguela upwelling system during MSM18/4 in July and August 2011

Ichthyoplankton density (fish eggs and larvae) and bulk zooplankton biomass in September 2010 were determined for 10 stations in the northern Benguela upwelling system, based on oblique Multinet hauls during the RRS Discovery D356 cruise. A HYDROBIOS Multinet, type Midi (0.25 m**2 mouth area) was equipped with five nets of 500 µm-mesh size, temperature and oxygen probes, and an inner and outer flow meter to monitor the net's trajectory (for volume filtered calculations) as well as net clogging. The Multinet was handled over the side, towed horizontally at 2 knots. Winch speed when fearing was 0.5 or 0.3 m/s, heaving velocity 0.2 - 0.3 m/s. The Multinet was towed obliquely at 10 stations sampling the upper 200 m of the water column, which were divided into five different depth strata after inspection of temperature and oxygen concentration depth profiles. Ichthyoplankton densities and zooplankton biomass were calculated for each depth stratum (=single net) from total abundance and the volume of water filtered [individuals per m**3 and g wet weight per m**3, respectively]. In addition, densities and biomass were integrated over the area for each station [individuals per m**2], as sum of calculations for each net: Sum ([individuals per m**3]*Delta(depth bot[m]-depth top [m]).

Coupling between protein folding and allostery in the GroE chaperonin system

GroEL is an allosteric protein that facilitates protein folding in an ATP-dependent manner. Herein, the relationship between cooperative ATP binding by GroEL and the kinetics of GroE-assisted folding of two substrates with different GroES dependence, mouse dihydrofolate reductase (mDHFR) and mitochondrial malate dehydrogenase, is examined by using cooperativity mutants of GroEL. Strong intra-ring positive cooperativity in ATP binding by GroEL decreases the rate of GroEL-assisted mDHFR folding owing to a slow rate of the ATP-induced transition from the protein-acceptor state to the protein-release state. Inter-ring negative cooperativity in ATP binding by GroEL is found to affect the kinetic partitioning of mDHFR, but not of mitochondrial malate dehydrogenase, between folding in solution and folding in the cavity underneath GroES. Our results show that protein folding by this “two-stroke motor” is coupled to cooperative ATP binding.

Evidence-Based Practice in the Juvenile Justice System: Balancing Clinical Expertise with Best Available Research and Client Variables

Each year, thousands of adolescents are processed through the juvenile justice system -- a system that is complicated, expensive, and inadequately addressing the needs of the youth in its care. While there is extensive literature available in support of interventions for youthful offenders that are clinically superior to current care and more cost-effective than the existing structure, there is a gap between research and practice that is preventing their implementation. The use of Evidence-Based Practice in Psychology (EBPP) as defined by the American Psychological Association is presented as one method to bridge this gap. This paper identifies and discusses each of five barriers to effective use of EBPP: cost, fragmentation of the mental health system, historical and systemic variables, research methodology, and clinician variables. These barriers are first defined and then illustrated using examples from the author's experience working in the juvenile justice field. Finally, recommendations for the field are presented.