Evaluation of the In Situ Ichthyoplankton Imaging System (ISIIS): comparison with the traditional (bongo net) sampler

Plankton and larval fish sampling programs often are limited by a balance between sampling frequency (for precision) and costs. Advancements in sampling techniques hold the potential to add considerable efficiency and, therefore, add sampling frequency to improve precision. We compare a newly developed plankton imaging system, In Situ Ichthyoplankton Imaging System (ISIIS), with a bongo sampler, which is a traditional plankton sampling gear developed in the 1960s. Comparative sampling was conducted along 2 transects ~30–40 km long. Over 2 days, we completed 36 ISIIS tow-yo undulations and 11 bongo oblique tows, each from the surface to within 10 m of the seafloor. Overall, the 2 gears detected comparable numbers of larval fishes, representing similar taxonomic compositions, although larvae captured with the bongo were capable of being identified to lower taxonomic levels, especially larvae in the small (<5 mm), preflexion stages. Size distributions of the sampled larval fishes differed considerably between these 2 sampling methods, with the size range and mean size of larval fishes larger with ISIIS than with the bongo sampler. The high frequency and fine spatial scale of ISIIS allow it to add considerable sampling precision (i.e., more vertical sections) to plankton surveys. Improvements in the ISIIS technology (including greater depth of field and image resolution) should also increase taxonomic resolution and decrease processing time. When coupled with appropriate net sampling (for the purpose of collecting and verifying the identification of biological samples), the use of ISIIS could improve overall survey design and simultaneously provide detailed, process-oriented information for fisheries scientists and oceanographers.

Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning.

Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

Biological evaluation of running waters in Korea, with special reference to bioassessment using the PFU system

A total of six stations in the Han River system were selected for establishing polyurethane foam units (PFUs) to collect protozoans, including phytomastigophorans, zoomastigophorans, amoebas and ciliates, in July 1993. In the bioassessment of microbial communities using the PFUs, the number of species decreased as pollution intensity increased. The diversity index values calculated at the main stations generally agreed with the pollution status of the stations. Anyang-Chon (Chon means stream) showed the lowest diversity value (1.89), and all stations, except Masok and Anyang-Chon, showed diversity index values ranging from 3.15 to 3.93. The highest heterotrophic index (HI) value was detected in Anyang-Chon followed by Masok-Chon. The number of species at the main stations reached a maximum on day 11 of being exposed to PFUs. The results of S-eq, G and T-90% all suggest that bioassessments using the PFU system were well matched with pollution status of the water. All microbial variables were significantly correlated with comprehensive chemical pollution indices, P-a and P-b, with correlation coefficients ranging from r=0.87 to r=0.96.

Evaluation and application of micro-sampling system for inductively coupled plasma mass spectrometry

Two Meinhard microconcentric nebulizers, model AR30-07-FM02 and AR 30-07-FM005, were employed as a self-installed micro-sampling system for inductively coupled plasma-mass spectrometry (ICP-MS). The FM02 nebulizer at 22 muL/min of solution uptake rate gave the relative standard deviations of 7.6%, 3.0%, 2.7%, 1.8% for determinations (n = 10) of 20 mug/L Be, Co, In and Bi, respectively, and the detection limits (3s) of 0.14, 0.10, 0.02 and 0.01 mug/L for Be, Co In and Bi, respectively. The mass intensity of In-115 obtained by this micro-sampling system was 60% of that by conventional pneumatic nebulizer system at 1.3 mL/min. The analytical results for La, Ce, Pr and Nd in 20 muL Wistar rat amniotic fluid obtained by the present micro-sampling system were precisely in good agreement with those obtained using conventional pneumatic nebulization system.

Evaluation of luminol-H2O2-KIO4 chemiluminescence system and its application to hydrogen peroxide, glucose and ascorbic acid assays

(A) novel chemiluminescence (CL) system was evaluated for the determination of hydrogen peroxide, glucose and ascorbic acid based on hydrogen peroxide, which has a catalytic-cooxidative effect on the oxidation of luminol by KIO4. Hydrogen peroxide can be directly determined by luminol-KIO4 -H2O2 CL system. The detection limit was 3.0 x 10(-8) mol l(-1) and the calibration graph was linear over the range of 2.0 x 10(-7)-6.0 x 10(-4) mol l(-1). The relative standard deviation of H2O2 was 1.1% for 2.0 x 10(-6) mol l(-1) (N = 11). Glucose was indirectly determined through measuring the H2O2 generated by the oxidation of glucose in the presence of glucose oxidase at pH 7.6. The present method provides a source for H2O2, which, in turn, coupled with the luminol-KIO4-H2O2 CL reaction system. The CL was linearly correlated with glucose concentration of 0.6-110 mu g ml(-1). The relative standard deviation was 2.1% for 10 mu g ml(-1) (N = 11). Detection limit of glucose was 0.08 mu g ml(-1). Ascorbic acid was also indirectly determined by the suppression of luminol-KIO4-H2O2 CL system. The calibration curve was linear over the range of 1.0 x 10(-7)-1.0 x 10(-5) mol l(-1) of ascorbic acid. The relative standard deviation was 1.0% for 8.0 x 10(-7) mol l(-1) (N = 11). Detection limit of ascorbic acid was 6.0 x 10(=8) mol l(-1). These proposed methods have been applied to determine glucose, ascorbic acid in tablets and injection. (C) 1999 Elsevier Science B.V. All rights reserved.

Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

Design and Evaluation of a Retrofittable Electric Snow Melting System for Pavements

Gemstone Team SnowMelt

Multiple Response System: Evaluation of Policy Change in North Carolina's Child Welfare System.

Systemic challenges within child welfare have prompted many states to explore new strategies aimed at protecting children while meeting the needs of families, but doing so within the confines of shrinking budgets. Differential Response has emerged as a promising practice for low or moderate risk cases of child maltreatment. This mixed methods evaluation explored various aspects of North Carolina's differential response system, known as the Multiple Response System (MRS), including: child safety, timeliness of response and case decision, frontloading of services, case distribution, implementation of Child and Family Teams, collaboration with community-based service providers and Shared Parenting. Utilizing Child Protective Services (CPS) administrative data, researchers found that compared to matched control counties, MRS: had a positive impact on child safety evidenced by a decline in the rates of substantiations and re-assessments; temporarily disrupted timeliness of response in pilot counties but had no effect on time to case decision; and increased the number of upfront services provided to families during assessment. Qualitative data collected through focus groups with providers and phone interviews with families provided important information on key MRS strategies, highlighting aspects that families and social workers like as well as identifying areas for improvement. This information is useful for continuous quality improvement efforts, particularly related to the development of training and technical assistance programs at the state and local level.

Evaluation of particle degradation due to high-speed impacts in a pneumatic handling system

Particle degradation can be a significant issue in particulate solids handling and processing, particularly in pneumatic conveying systems, in which high-speed impact is usually the main contributory factor leading to changes in particle size distribution (comparing the material to its virgin state). However, other factors may strongly influence particles breakage as well, such as particle concentrations, bend geometry,and hardness of pipe material. Because of such complex influences, it is often very difficult to predict particle degradation accurately and rapidly for industrial processes. In this article, a general method for evaluating particle degradation due to high-speed impacts is described, in which the breakage properties of particles are quantified using what are known as "breakage matrices". Rather than a pilot-size test facility, a bench-scale degradation tester has been used. Some advantages of using the bench-scale tester are briefly explored. Experimental determination of adipic acid has been carried out for a range of impact velocities in four particle size categories. Subsequently, particle breakage matrices of adipic acid have been established for these impact velocities. The experimental results show that the "breakage matrices" of particles is an effective and easy method for evaluation of particle degradation due to high-speed impacts. The possibility of the "breakage matrices" approach being applied to a pneumatic conveying system is also explored by a simulation example.

Communication system model for information rate evaluation of differential detection over time-varying channels

A communication system model for mutual information performance analysis of multiple-symbol differential M-phase shift keying over time-correlated, time-varying flat-fading communication channels is developed. This model is a finite-state Markov (FSM) equivalent channel representing the cascade of the differential encoder, FSM channel model and differential decoder. A state-space approach is used to model channel phase time correlations. The equivalent model falls in a class that facilitates the use of the forward backward algorithm, enabling the important information theoretic results to be evaluated. Using such a model, one is able to calculate mutual information for differential detection over time-varying fading channels with an essentially finite time set of correlations, including the Clarke fading channel. Using the equivalent channel, it is proved and corroborated by simulations that multiple-symbol differential detection preserves the channel information capacity when the observation interval approaches infinity.