食物蛋白质营养价值的化学评分法改进之一——氨基酸分直线回归法求化学法生物价

本文主要研究和探讨了50种食物蛋白质的氨基酸分与其生物学价值的相关性和偏离情况;求出了采用不同模式计算所得的氨基酸分与其生物学价值的相关系数和回归方法。利用所得的回归方程对相应的氨基酸分进行回归,求得化学法生物价。与氨基酸分相比,化学生物价能更准确地作为生物学价值的估计值,也解决了氨基酸分为零的生物学价值并不为零的矛盾。     

Genetic relationships between calving interval and body condition score conditional on milk yield

Body condition score (BCS) is a useful tool in assessing the energy status of dairy cattle. Previous research has shown that it is heritable and genetically correlated to reproductive performance. Currently, interest exists in developing selection indexes for fertility that include BCS information. Before such indexes are developed, it is important to assess the genetic covariance between BCS and fertility after fully accounting for the covariance of both traits with milk yield, as indices to predict selection responses require knowledge of these (co)variances. In the present study, calving interval (CI) was used as a measure of reproductive performance. The genetic correlations between BCS and CI before and after genetically adjusting for milk yield were -0.48 and -0.22, respectively. Thus, cows with low BCS have longer CI, which is exacerbated by high levels of milk production. Using selection index theory, we showed that selecting for milk yield alone will result in an increase of 768 kg of milk, an increase of 4.46 d in CI and a reduction of 0.41 BCS units for every standard deviation change in the index. Restricting BCS to no genetic change, whereas still selecting for milk yield will result in an increase of 653.1 kg of milk per standard deviation of the selection index. However, CI will still continue to increase at a rate of 3.20 d per standard deviation of the selection index. The selection indices used here are not optimum, in that they are not economically driven and do not consider all traits that contribute to profitability. However, they demonstrate that, even though restricting BCS may be seen as an attractive way of limiting reliance of body tissue mobilization to fuel milk production, this is unlikely to result in improvements in CI, although the rate of increase in CI will be reduced.     

Effect of fat level and partial replacement of pork backfat with olive oil on processing and quality characteristics of fermented sausages

Six formulations of dry fermented sausages were produced in three replications with three initial fat levels (30, 20 and 10%) and two levels (0 and 20%) of pork backfat replacing olive oil. After 4 weeks of fermentation and ripening the fat content of the treatments with 30, 20 and 10% fat level ranged from 38.86 to 43.60%, 25.56 to 26.86% and 19.01 to 20.14%, respectively. Fat level affected (P<0.05) the weight losses, the chemical composition, the Gram −ve bacterial count, the lightness, the texture and the appearance of fermented sausages. Replacing 20% of pork backfat by olive oil affected (P<0.05) the lightness and yellowness of sausages. Fat-reduced sausages without olive oil and low-fat sausages with olive oil had the highest score for odour and taste. However, the appearance of fat-reduced sausages was just acceptable while that of low-fat sausages was unacceptable, because the surface was intensively wrinkled and case hardening had developed. Further research is needed to improve the appearance of these sausages.     

Comparison of two-level and three-level classifications of moisture-damaged dwellings in relation to health effects

A total of 630 randomly selected dwellings were surveyed for visible signs of moisture damage by civil engineers, and questionnaire responses were collected from the occupants (a total of 1,017 adults) to analyse the association between moisture damage and occupant health. A three-level grading system was developed, which took into account the number of damage sites in buildings and estimated the severity of the damage. In the present study, this grading system was tested as an improved model of moisture damage-related exposure in comparison to a conventional two-category system: based on independent, technical criteria it also allowed dose-response to be estimated. The questionnaire probed 28 individual health symptoms, based on earlier reported associations with building moisture and mould-related exposure. Criteria in evaluating the goodness of the selected exposure model were (1) dose-responsiveness and (2) higher risk compared to a two-level classification. Dose-responsiveness was observed with the three-level classification in 7, higher risk in 10, and both criteria in 5 out of 28 health symptoms. Two-level classification had higher risk in 4 health symptoms. Dose-dependent risk increases for respiratory infections and lower respiratory symptoms, and recurrent irritative and skin symptoms were observed with the three-level classification using symptom score variables. Although the results did not unambiguously support the three-level model, they underline the importance of developing more accurate exposure models in assessing the severity of moisture damage.     

RHex: A Biologically Inspired Hexapod Runner

RHex is an untethered, compliant leg hexapod robot that travels at better than one body length per second over terrain few other robots can negotiate at all. Inspired by biomechanics insights into arthropod locomotion, RHex uses a clock excited alternating tripod gait to walk and run in a highly maneuverable and robust manner. We present empirical data establishing that RHex exhibits a dynamical (bouncing) gait—its mass center moves in a manner well approximated by trajectories from a Spring Loaded Inverted Pendulum (SLIP)—characteristic of a large and diverse group of running animals, when its central clock, body mass, and leg stiffnesses are appropriately tuned. The SLIP template can function as a useful control guide in developing more complex autonomous locomotion behaviors such as registration via visual servoing, local exploration via visual odometry, obstacle avoidance, and, eventually, global mapping and localization.     

Feedforward and Feedback Dynamic Trot Gait Control for Quadruped Walking Vehicle

To realize dynamically stable walking for a quadruped walking robot, the combination of the trajectory planning of the body and leg position (feedforward control) and the adaptive control using sensory information (feedback control) is indispensable. In this paper, we propose a new body trajectory, the 3D sway compensation trajectory, for a stable trot gait; we show that this trajectory has a lower energy consumption than the conventional sway trajectory that we have proposed. Then, for the adaptive attitude control method during the 2-leg supporting phase, we consider four methods, that is, a) rotation of body along the diagonal line between supporting feet, b) translation of body along the perpendicular line between supporting feet, c) vertical swing motion of recovering legs, and d) horizontal swing motion of recovering legs; we then describe how we verify the stabilization efficiency of each method through computer simulation, stabilization experimentation, and experimenting in walking on rough terrain using the quadruped walking robot, TITAN-VIII.     

Energy-optimal gait analysis of quadruped robots

It is important for walking robots such as quadruped robots to have an efficient gait. Since animals and insects are the basic models for most walking robots, their walking patterns are good examples. In this study, the walking energy consumption of a quadruped robot is analyzed and compared with natural animal gaits. Genetic algorithms have been applied to obtain the energy-optimal gait when the quadruped robot is walking with a set velocity. In this method, an individual in a population represents the walking pattern of the quadruped robot. The gait (individual) which consumes the least energy is considered to be the best gait (individual) in this study. The energy-optimal gait is analyzed at several walking velocities, since the amount of walking energy consumption changes if the walking velocity of the robot is changed. The results of this study can be used to decide what type of gait should be generated for a quadruped robot as its walking velocity changes. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001.     

Precision Evaluation of Search Engines

In this paper, we present a general approach for statistically evaluating precision of search engines on the Web. Search engines are evaluated in two steps based on a large number of sample queries: (a) computing relevance scores of hits from each search engine, and (b) ranking the search engines based on statistical comparison of the relevance scores. In computing relevance scores of hits, we study four relevance scoring algorithms. Three of them are variations of algorithms widely used in the traditional information retrieval field. They are cover density ranking, Okapi similarity measurement, and vector space model algorithms. In addition, we develop a new three-level scoring algorithm to mimic commonly used manual approaches. In ranking the search engines in terms of precision, we apply a statistical metric called probability of win. In our experiments, six popular search engines, AltaVista, Fast, Google, Go, iWon, and NorthernLight, were evaluated based on queries from two domains of interest: parallel and distributed processing, and knowledge and data engineering. The first query set contains 1726 queries collected from the index terms of papers published in the IEEE Transactions on Knowledge and Data Engineering. The second set contains 1383 queries collected from the index terms of papers published in the IEEE Transactions on Parallel and Distributed Systems. Search engines were queried and compared in two different search modes: the default search mode and the exact phrase search mode. Our experimental results show that these six search engines performed differently under different search modes and scoring methods. Overall, Google was the best. NorthernLight was mostly second in the default search mode, whereas iWon was mostly second in the exact phrase search mode.     

Genetic improvement of mastitis resistance: validation of somatic cell score and clinical mastitis as selection criteria

Mean daughter deviations for clinical mastitis among second-crop daughters were regressed on predicted transmitting abilities for clinical mastitis and lactation mean somatic cell score in first-crop daughters to validate the predictive ability of these traits as selection criteria for reduced incidence of clinical mastitis. A total of 321 sires had 684,897 second-crop daughters, while predicted transmitting abilities were calculated for 2159 sires, based on 495,681 records of first-crop daughters. Predictive ability, as a measure of efficiency of selection, was 23 to 43% higher for clinical mastitis than for lactation mean somatic cell score. Compared to single-trait selection, predictive ability improved 8 to 13% from utilizing information on both traits. The relative weight that should be assigned to standardized predicted transmitting abilities from univariate genetic analyses were 60 to 67% for clinical mastitis and 33 to 40% for lactation mean somatic cell score. No significant nonlinear genetic relationship between the two traits was found.     

Genetic relationship between body condition score, dairy character, mastitis, and diseases other than mastitis in first-parity Danish Holstein cows

The aim of this study was to explore the possibilities of using body condition score (BCS) or dairy character (DC) as indicators of mastitis and diseases other than mastitis in first-parity Danish Holsteins. The dataset included 28,948 observations on conformation scores and 365,136 disease observations. The analysis was performed using a multitrait linear sire model. Heritability estimates for BCS and DC were moderate (0.25 and 0.22), and heritability estimates for mastitis and diseases other than mastitis were low (0.038 and 0.022). Between BCS and diseases other than mastitis, the genetic correlation was -0.22, whereas the genetic correlation was -0.16 between BCS and mastitis. The genetic correlation between DC and diseases other than mastitis was 0.43, and between DC and mastitis it was 0.27. The genetic correlation between BCS and DC was -0.61. Residual correlations were close to 0, except between BCS and DC (-0.37). Including DC as an indicator of diseases other than mastitis will increase the accuracy of the predicted breeding value for diseases, especially when the progeny group is small. Using BCS as an additional indicator of diseases did not increase the accuracy. Breeding for less DC will increase resistance to diseases.