Life history of the bay anchovy, Anchoa mitchilli, in Chesapeake Bay

In lower Chesapeake Bay, the spawning season of the bay anchovy Anchoa mitchilli in 1988 was from early May to mid-September. Spawning was temporally synchronized and lasted for about 1.5 h each night. Spawning frequency per individual was every 4 d in early June and 1.3-1.9 d in other months. Batch fecundity was a linear function of fork length and body weight; regression slopes on 6 July and 4 August were significantly higher than those on 6 June and 31 August. Estimated mean total spawnings per female in 1988 was 54. Total egg production for a fish of average size was 45,110, which is equivalent to 346% of body biomass energy. Age determination based on lagenar otoliths showed that some fish spawned when as young as 2.5-3 months. Transport of the adult bay anchovy in darkness was studied in laboratory and field experiments. In a hydraulic flume, 99% of all fish were transported to the end of the flume in darkness at a current speed of 30 cm s&\sp{lcub}-1{rcub}&. In field experiments, fish marked with neutral red dye and released in a creek at flood tide were recaptured 5.1 km upstream 4 h after release at night, and were recaptured within 200 m of the release site 3 h after release in daylight. This nocturnal transport phenomenon may help in understanding behavior and distribution of pelagic estuarine fishes. The standardized CPUE data show long-term population fluctuations on the order of ten fold. The bay anchovy population also has extensive seasonal variations. A Fourier analysis removed the seasonal (short-term) variation from the long-term data series. An autoregressive analysis of the residual series indicated that it contained a significant first-order autoregressive process component (r&\sp2& = 0.26, P &\le& 0.0066), which was interpreted as a spawner-recruit relationship. Cross-correlation analysis indicated that bay anchovy population abundance was positively correlated with winter water temperature (r = 0.663, P &\le& 0.0001) and river flow (r = 0.376, P &\le& 0.027), but negatively correlated with the abundances of white perch (r = &-&0.437, P &\le& 0.011), and the squared function of residual wind speed (r = &-&0.377, P &\le& 0.026). A multiple regression model indicated that temperature, white perch abundance and wind made significant contributions (accounting for 78% of the variation) to the model

Reference trajectory modification based on spatial iterative learning for contour control of 2-axis NC systems

Contour error is a main factor that affects the quality of products in numerical control (NC) machining. This paper presents a contour control strategy based on digital curves for high-precision control of computer numerical control (CNC) machines. A contour error estimation algorithm is presented for digital curves based on a geometrical method. The dynamic model of the motion control system is transformed from time domain to space domain because the contour error is dependent on space instead of time. Spatial iterative learning control (sILC) is developed to reduce the contour error, by modifying the reference trajectory in the form of G code. This allows system improvement without interference of low-level controllers so it is applicable to many commercial controllers where interpolators and feed-drive controllers cannot be altered. The effectiveness of this method is verified by experiments on a NC machine, which have shown good performance not only for smooth trajectories but also for large curvature trajectories

Mitochondrial nutrients improve immune dysfunction in the type 2 diabetic Goto-Kakizaki rats.

The development of type 2 diabetes is accompanied by decreased immune function and the mechanisms are unclear. We hypothesize that oxidative damage and mitochondrial dysfunction may play an important role in the immune dysfunction in diabetes. In the present study, we investigated this hypothesis in diabetic Goto-Kakizaki rats by treatment with a combination of four mitochondrial-targeting nutrients, namely, R-alpha-lipoic acid, acetyl-L-carnitine, nicotinamide and biotin. We first studied the effects of the combination of these four nutrients on immune function by examining cell proliferation in immune organs (spleen and thymus) and immunomodulating factors in the plasma. We then examined, in the plasma and thymus, oxidative damage biomarkers, including lipid peroxidation, protein oxidation, reactive oxygen species, calcium and antioxidant defence systems, mitochondrial potential and apoptosis-inducing factors (caspase 3, p53 and p21). We found that immune dysfunction in these animals is associated with increased oxidative damage and mitochondrial dysfunction and that the nutrient treatment effectively elevated immune function, decreased oxidative damage, enhanced mitochondrial function and inhibited the elevation of apoptosis factors. These effects are comparable to, or greater than, those of the anti-diabetic drug pioglitazone. These data suggest that a rational combination of mitochondrial-targeting nutrients may be effective in improving immune function in type 2 diabetes through enhancement of mitochondrial function, decreased oxidative damage, and delayed cell death in the immune organs and blood

Impacts of Sample Size on Calculation of Pavement Texture Indicators with 1mm 3D Surface Data

The emerging 1mm resolution 3D data collection technology is capable of covering the entire pavement surface, and provides more data sets than traditional line-of-sight data collection systems. As a result, quantifying the impact of sample size including sample width and sample length on the calculation of pavement texture indicators is becoming possible. In this study, 1mm 3D texture data are collected and processed at seven test sites using the PaveVision3D Ultra system. Analysis of Variance (ANOVA) test and linear regression models are developed to investigate various sample length and width on the calculation of three widely used texture indicators: Mean Profile Depth (MPD), Mean Texture Depth (MTD) and Power Spectra Density (PSD). Since the current ASTM standards and other procedures cannot be directly applied to 3D surface for production due to a lack of definitions, the results from this research are beneficial in the process to standardize texture indicators’ computations with 1mm 3D surface data of pavements

Expanding oxygen minimum zones, tropical pelagic predators, and Atlantic fisheries that exploit them

This paper links 50 years of ongoing ocean scale deoxygenation trends in the tropical Atlantic Ocean to changes in vertical habitat use of large pelagic predators, and the Atlantic fisheries that exploited them. Climate induced warming in this large ocean area (Oxygen Minimum Zones, OMZs) has compressed the volumes of surface mixed layer habitat by about 1 m y-1 over the last 5 decades, concentrating predators, preferred prey, and influencing Atlantic-wide fishing effort patterns into progressively shallower surface zones. This phenomenon increases the catchability of these predators and may contribute to overly optimistic abundance estimates derived from surface fishing gears. Overall, deoxygenation is estimated to have caused a 15% reduction in suitable habitat for tropical pelagic tunas and billfishes in the tropical Atlantic during this time period. To demonstrate ocean scale changes in available habitat we use Hydrobase 3 database to compute decadal matrices of OMZ size (volume and surface area), as well as the reciprocal decline in surface mixed layer from 1955 through 2004. Further, we tracked fishing effort and catch inside and outside of the Atlantic OMZ for 9 major ICCAT assessment species to examine potential compression impacts. We found that during the last decade analyzed (1995-2004), longline fishing effort has coalesced on-top of the Atlantic OMZ, while hooks from outside the OMZ have decreased by about the same proportion. During the initial decade (1955-1964), 3 longline fleets deployed about 500,000 hooks, while by the last decade (1995-2004) longline effort had expanded to 94 fleets and almost 4.2 billion hooks. We determined that at least 7 out of 9 major ICCAT stock assessment species examined here are severely impacted by the OMZ expansion and resulting loss of available habitat. We also point out some significant ecosystem interactions between predators and preferred prey that appear to fuel predator assemblages.in progressively shallow OMZ areas, including some predators that are not sensitive to low ambient DO levels. As deoxygenation is expected to continue during the current cycle of climate change and global warming, and has been observed in other oceans as well, this suggests it may have broad-scale impacts on the sustainability of pelagic fisheries and their management. In order to maintain sustainable fisheries for tropical pelagic fishes, we feel its incumbent upon the assessment community to incorporate hypoxia-based habitat compression impacts for species of concern (identified here) into the assessment process. One potential approach might be accomplished during the Catch-Per-Unit-Effort standardization process, by scaling catchability coefficients (by species and gear) using the progressive decadal decline in available surface mixed layer habitat (in volume) presented here

Transfer Learning Based Traffic Sign Recognition Using Inception-v3 Model

Traffic sign recognition is critical for advanced driver assistant system and road infrastructure survey. Traditional traffic sign recognition algorithms can't efficiently recognize traffic signs due to its limitation, yet deep learning-based technique requires huge amount of training data before its use, which is time consuming and labor intensive. In this study, transfer learning-based method is introduced for traffic sign recognition and classification, which significantly reduces the amount of training data and alleviates computation expense using Inception-v3 model. In our experiment, Belgium Traffic Sign Database is chosen and augmented by data pre-processing technique. Subsequently the layer-wise features extracted using different convolution and pooling operations are compared and analyzed. Finally transfer learning-based model is repetitively retrained several times with fine-tuning parameters at different learning rate, and excellent reliability and repeatability are observed based on statistical analysis. The results show that transfer learning model can achieve a high-level recognition performance in traffic sign recognition, which is up to 99.18 % of recognition accuracy at 0.05 learning rate (average accuracy of 99.09 %). This study would be beneficial in other traffic infrastructure recognition such as road lane marking and roadside protection facilities, and so on

Nonlinear Dynamics of a PI Hydroturbine Governing System with Double Delays

A PI hydroturbine governing system with saturation and double delays is generated in small perturbation. The nonlinear dynamic behavior of the system is investigated. More precisely, at first, we analyze the stability and Hopf bifurcation of the PI hydroturbine governing system with double delays under the four different cases. Corresponding stability theorem and Hopf bifurcation theorem of the system are obtained at equilibrium points. And then the stability of periodic solution and the direction of the Hopf bifurcation are illustrated by using the normal form method and center manifold theorem. We find out that the stability and direction of the Hopf bifurcation are determined by three parameters. The results have great realistic significance to guarantee the power system frequency stability and improve the stability of the hydropower system. At last, some numerical examples are given to verify the correctness of the theoretical results

A Synthetic Material to Simulate Soft Rocks and Its Applications for Model Studies of Socketed Piles

A detailed manufacturing procedure of a synthetic soft rock is presented, as well as its applications on the laboratory experiments of socketed piles. With the homogeneity and isotropy of the simulated soft rock, the influence of different variables on the bearing performance could be investigated independently. The constituents, cement, gypsum powder, river sand, concrete-hardening accelerator, and water, were mixed to form the specimens. Both uniaxial and triaxial compressive tests were conducted to investigate the stress-strain behavior of the simulated soft rock. Additionally, the simulated soft rock specimens were used in model pile tests and simple shear tests of the pile-rock interface. Results of the simulated soft rock in both the uniaxial and triaxial compressive tests are consistent with those of natural soft rocks. The concrete-hardening accelerator added to the mixtures improves the efficiency in laboratory investigations of soft rock specimens with a curing time of 7 days. The similarities between the laboratory tests and the field observations provide convincing evidence to support its suitability in modeling the behavior of soft rocks

Benthic Habitat Mapping in the Tortugas Region, Florida

Concern about declining trends in coral reef habitats and reef fish stocks in the Florida Keys contributed to the implementation of a network of no-take marine protected areas in 1997. In support of the efforts of the Dry Tortugas National Park and Florida Keys National Marine Sanctuary to implement additional no-take areas in the Tortugas region in 2001, we expanded the scale of our fisheries independent monitoring program for coral reef fishes in the region. To provide a foundation for the habitat-based, stratified random sampling design of the program, we created a digital benthic habitat map of coral reef and hard-bottom habitats in a geographic information system by synthesizing data from bathymetric surveys, side-scan sonar imagery, aerial photogrammetry, existing habitat maps, and in situ visual surveys. Existing habitat maps prior to 1999 were limited to shallow-water (\u3c 20 m depth) soft-sediment, coral reef, and hard-bottom habitats within Dry Tortugas National Park and did not include deeper areas such as the Tortugas Bank, now partially contained within no-take marine protected area boundaries. From diver observations made during the 1999 survey, we developed a classification scheme based on habitat relief and patchiness to describe nine hard-bottom and coral reef habitats encountered from 1-33 m depth. We provide estimates of area by habitat type for no-take marine protected areas in the Tortugas region. Updated information on the spatial distribution and characteristics of benthic habitats will be used to guide future monitoring, assessment, and management activities in the region. Significant data gaps still exist for the western area of the Florida Keys National Marine Sanctuary and are a priority for future research

Research Progress on the Application of Spectroscopy in Meat Spoilage Detection

The growth and metabolism of microorganisms is the main cause of meat spoilage. The rapid and nondestructive techniques for detecting microorganisms in meat have attracted more and more attentions. Spectroscopic techniques such as Raman spectroscopy, infrared spectroscopy and spectral imaging show great advantages in rapid and non-destructive detection, but their application in meat spoilage detection has not been timely summarized. Based on an overview of the dominant spoilage organisms and microbial metabolism in meat under different storage conditions, this paper briefly describes the material basis for spectroscopic prediction of meat spoilage. Then, the application of Raman spectroscopy, infrared spectroscopy and spectral imaging technology in predicting the shelf life of meat is summarized. The efficiency of predictive modeling of meat shelf life based on total bacterial count or total volatile basic nitrogen (TVB-N) content and problems existing in this field are highlighted. We anticipate that this review will provide new ideas and theoretical guidance for the development and application of rapid and nondestructive techniques for meat spoilage identification