Effect of age and nutrient restriction pre partum on beef suckler cow serum immunoglobulin concentrations, colostrum yield, composition and immunoglobulin concentration and immune status of their progeny

peer-reviewedThe effect of cow age (multiparous (MP) v. primiparous (PP)) and nutritional restriction pre partum (grass silage ad libitum v. straw only ad libitum for the last 15 (s.d. 3.3) days of gestation) on cow serum immunoglobulin (Ig) concentration, on colostrum yield, composition and Ig concentration and on calf serum Ig concentrations (at ~8 and 48 h post partum) using spring-calving Limousin Holstein-Friesian cows and their progeny was studied over 3 years. The method of colostrum administration (stomach tube vs. assisted suckling within 1 h post partum) on calf immune status was also investigated. When feeding colostrum the target was to give each calf 50 mL per kg birthweight via stomach tube. Colostrum yield and Ig concentration were measured following administration of oxytocin and hand-milking of half (Experiments 1 and 2) or the complete udder (Experiment 3). Following an 8-h period after birth during which suckling was prevented a further colostrum sample was obtained. There was no significant difference in first milking colostrum Ig subclass concentrations between the within-quarter fractions or between the front and rear quarters of the udder in either MP or PP cows. Colostrum Ig subclass concentrations at second milking were 0.46 to 0.65 of that at first milking. Compared to MP cows offered silage, colostrum yield and the mass of colostrum IgG1, IgG2, IgM, IgA and total Ig produced was lower (P < 0.001) for PP cows and the mass of IgG1, IgM and total Ig produced was lower (P < 0.05) for MP cows offered straw. Calves from PP cows and MP cows offered straw had significantly lower serum IgG1 and total Ig concentrations at 48 h post partum than calves from MP cows offered silage but there was no difference (P > 0.05) between colostrum feeding methods. In conclusion, calves from PP cows and MP cows offered straw had a lower humoral immune status than those from MP cows offered grass silage

Effect of suckler cow genotype on cow serum immunoglobulin (Ig) levels, colostrum yield, composition and Ig concentration and subsequent immune status of their progeny

peer-reviewedSurvival of the neonatal calf is largely dependent on humoral immunity. The objective of three experiments reported here was to compare cow serum immunoglobulin (Ig) concentration, colostrum yield, composition and Ig concentration and calf serum Ig concentrations at ~8- and 48-h post partum of spring-calving Charolais (C) and Beef × Holstein-Friesian (BF) cows and their progeny. Cows were individually offered a restricted allowance of grass silage pre partum in Experiments 1 and 2 and silage ad libitum in Experiment 3. In Experiment 1 calves were assisted to suckle after parturition. In Experiments 2 and 3, colostrum yield and Ig concentration were measured following administration of oxytocin and hand milking of half or the complete udder, respectively. It was intended to feed each calf 50 ml (Experiment 2) or 40 ml (Experiment 3) of colostrum per 1 kg birth weight via stomach tube. Following an 8-h period, during which suckling was prevented, a further colostrum sample was obtained. The decrease in cow serum IgG1 concentration pre partum was greater (P < 0.05) in BF cows than C cows. In comparison to BF cows, C cows had a lower colostrum yield (P < 0.001) and the colostrum had lower concentrations of dry matter (P < 0.01), crude protein (P < 0.05), fat (P < 0.05), IgG1 (P = 0.06), IgG2 (P < 0.01), IgM (P < 0.01) and Ig total (P < 0.05). The mass of IgG1, IgG2, IgM, IgA and Ig total in the colostrum produced was significantly lower for C cows than BF cows. Calves from C cows had significantly lower serum Ig subclass concentration at 48-h post partum than calves from BF cows. In conclusion, due to a lower Ig mass produced by their dams, calves from C cows had a lower humoral immune status than those from BF cowsTeagasc Walsh Fellowship Programm

XinuPi3: Teaching Multicore Concepts Using Embedded Xinu

As computer platforms become more advanced, the need to teach advanced computing concepts grows accordingly. This paper addresses one such need by presenting XinuPi3, a port of the lightweight instructional operating system Embedded Xinu to the Raspberry Pi 3. The Raspberry Pi 3 improves upon previous generations of inexpensive, credit card-sized computers by including a quad-core, ARM-based processor, opening the door for educators to demonstrate essential aspects of modern computing like inter-core communication and genuine concurrency. Embedded Xinu has proven to be an effective teaching tool for demonstrating low-level concepts on single-core platforms, and it is currently used to teach a range of systems courses at multiple universities. As of this writing, no other bare metal educational operating system supports multicore computing. XinuPi3 provides a suitable learning environment for beginners on genuinely concurrent hardware. This paper provides an overview of the key features of the XinuPi3 system, as well as the novel embedded system education experiences it makes possible

Production and carcass traits of high dairy genetic merit Holstein, standard dairy genetic merit Friesian and Charolais × Holstein-Friesian male cattle

peer-reviewedThe increased proportion of Holstein genetic material in the dairy herd has consequences for beef production in Ireland. A total of 72 spring-born male calves (24 Holsteins (HO), 24 Friesian (FR) and 24 Charolais × Holstein-Friesians (CH)) were reared from calfhood to slaughter. Calves were artificially reared indoors and spent their first summer at pasture following which they were assigned, on a breed basis, to a factorial combination of two production systems (intensive 19-month bull beef and extensive 25-month steer beef) and two slaughter weights (560 and 650 kg). After slaughter the pistola hind quarter was separated into fat, bone and muscle. Live-weight gain, carcass gain, kill-out proportion, carcass conformation and carcass fat scores were 830, 811 and 859 (s.e. 14.9) g/day, 540, 533, 585 (s.e. 7.7) g/day, 526, 538 and 561 (s.e. 3.0) g/kg, 1.51, 2.18 and 2.96 (s.e. 0.085), and 3.40, 4.25 and 4.06 (s.e. 0.104) for HO, FR and CH, respectively. Corresponding values for pistola weight as a proportion of carcass weight, pistola muscle proportion and pistola fat proportion were 458, 459 and 461 (s.e. 2.6) g/kg, 657, 645 and 667 (s.e. 3.7) g/kg, and 132, 161 and 145 (s.e. 4.1) g/kg. Compared with the intensive system, animals on the extensive system had a lower (P < 0.001) daily live-weight gain, kill-out proportion and a lower muscle proportion in the pistola. Increasing slaughter weight increased (P < 0.001) carcass weight and carcass fat score and reduced the proportion of muscle in the pistola. Allometric regression coefficients for pistola weight on side weight, and total bone, muscle and fat weights on pistola weight were 0.898, 0.755, 0.900 and 1.910 respectively. It is concluded that HO grew at least as fast as FR but had a lower killout proportion. Carcass conformation and fat scores were greater for FR than for HO and muscle proportion in the pistola was lower and total fat proportion was higher. Compared with FR, CH had heavier carcasses, a higher kill-out proportion and less fat and more muscle in the pistola

Body and carcass measurements, carcass conformation and tissue distribution of high dairy genetic merit Holstein, standard dairy genetic merit Friesian and Charolais x Holstein-Friesian male cattle

peer-reviewedThe increased proportion of Holstein genes in the dairy herd may have undesirable consequences for beef production in Ireland. A total of 72 spring-born calves, (24 Holstein (HO), 24 Friesian (FR) and 24 Charolais X Holstein-Friesian (CH)) were reared from calfhood to slaughter. Calves were artificially reared indoors and spent their first summer at pasture following which they were assigned to a 3 breeds (HO, FR and CH) 2 production systems (intensive 19-month bull beef and extensive 25-month steer beef) 2 slaughter weights (560 and 650 kg) factorial experiment. Body measurements of all animals were recorded at the same time before the earliest slaughter date. After slaughter, carcasses were graded and measured and the pistola hind-quarter was separated into fat, bone and muscle. HO had significantly higher values for withers height, pelvic height and chest depth than FR, which in turn had higher values than CH. HO had a longer back and a narrower chest than either FR or CH, which were not significantly different. Carcass length and depth, pistola length, and leg length were 139.2, 134.4 and 132.0 (s.e. 0.81), 52.1, 51.3 and 47.7 (s.e. 0.38), 114.4, 109.0 and 107.0 (s.e. 0.65) and 76.7, 71.9 and 71.4 (s.e. 0.44) cm for HO, FR and CH, respectively. Breed differences in pistola tissue distribution between the joints were small and confined to the distal pelvic limb and ribs. There were relatively small breed differences in the distribution of pistola muscle weight between individual muscles. Body measurements were significantly greater for animals on the intensive system (bulls) than the extensive system (steers) in absolute terms, but the opposite was so when they were expressed relative to live weight. The only significant difference in relative carcass measurements between the production systems was for carcass depth, which was lower for the intensive compared with the extensive system. Increasing slaughter weight significantly increased all carcass measurements in absolute terms but reduced them relative to weight. It is concluded that there were large differences between the breed types in body and carcass measurements, and hence in carcass shape and compactness but differences in tissue distribution were small

Non-carcass parts and carcass composition of high dairy genetic merit Holstein, standard dairy genetic merit Friesian and Charolais × Holstein-Friesian steers

peer-reviewedThe increased use of Holstein genetic material in the dairy herd has consequences for beef production. A total of 24 spring-born calves comprising 8 Holsteins (HO), 8 Friesians (FR) and 8 Charolais × Holstein-Friesians (CH) were reared from calfhood to slaughter. At the end of the second grazing season they were assigned to a 3 (breeds; HO, FR and CH) × 2 (slaughter weights; 620 and 730 kg) factorial experiment and fin¬ished indoors. After slaughter carcasses were classified for conformation and fatness, all organs and non-carcass parts were weighed, and the right side of each carcass was dissected into fat, bone and muscle. Non-carcass parts, carcass weight, kill-out propor¬tion, carcass conformation score and m. longissimus area were 405, 398 and 368 (s.e. 8.31) g/kg empty body weight, 355, 344 and 383 (s.e. 9.4) kg, 509, 520 and 545 (s.e. 8.99) g/kg, 1.0, 2.0 and 3.1 (s.e. 0.16), 7616, 7096 and 9286 (s.e. 223.4) mm2 for HO, FR and CH, respectively. Corresponding proportions of carcass muscle and fat were 631, 614 and 656 (s.e. 8.4), and 165, 200 and 165 (s.e. 10.5) g/kg. Increasing slaughter weight increased the proportion of total non-carcass parts, carcass weight, carcass fat score and fat proportion, and reduced carcass muscle and bone proportions. It is concluded that differences in kill-out proportion between the two dairy breeds was primarily due to the lower proportion of gastrointestinal tract (GIT) in FR, and the higher kill-out proportion of CH was mainly due to lower proportions of GIT, internal organs and internal fat. In terms of beef production, HO and FR were broadly comparable for most traits except carcass conformation score and carcass fat proportion, which were lower for HO. CH was superior to the dairy breeds in all important production traits

Using Embedded Xinu and the Raspberry Pi 3 to Teach Operating Systems

Multicore processors have become the standard in modern computing platforms. Such complex hardware enables faster execution of the programs it runs, but this is only true if its programmer has the knowledge and ability to make it so. Thus, there is a great need to prepare computing students by establishing robust educational tools. Existing tools often include abstract learning environments such as a virtual machine. While such platforms are widely available and convenient, they are unable to expose students to concurrency on real hardware.This paper presents multicore Embedded Xinu, an educational operating system used to teach concurrency concepts at the university level. The latest port of Embedded Xinu to the four-core, ARM-based Raspberry Pi 3 B+ enabled an operating systems curriculum in which students build their own concurrency-oriented kernel and execute it on a real machine. Assignments that have been run in the course include concepts of synchronization, scheduling, and memory allocation on a multicore platform. Upon completing the course, students are capable of solving problems commonly found in the field of parallel computing

Charter School Funding Inequities: Rochester, New York

Public charter schools are increasingly becoming part of both the broader national conversation about education policy as well as the local urban scene in the United States. The latter is certainly true in Rochester, New York, where charter schools serve more than 18 percent of the students who attend school in the city. Given the important role that charter schools play in educating Rochester’s students, we sought to learn if students who attend the city’s charter schools are funded equitably when compared to students in Rochester City School District (RCSD) schools

Identification of quantitative trait loci controlling root and shoot traits associated with drought tolerance in a lentil (Lens culinaris Medik.) recombinant inbred line population

Drought is one of the major abiotic stresses limiting lentil productivity in rainfed production systems. Specific rooting patterns can be associated with drought avoidance mechanisms that can be used in lentil breeding programs. In all, 252 co-dominant and dominant markers were used for Quantitative Trait Loci (QTL) analysis on 132 lentil recombinant inbred lines based on greenhouse experiments for root and shoot traits during two seasons under progressive drought-stressed conditions. Eighteen QTLs controlling a total of 14 root and shoot traits were identified. A QTL-hotspot genomic region related to a number of root and shoot characteristics associated with drought tolerance such as dry root biomass, root surface area, lateral root number, dry shoot biomass and shoot length was identified. Interestingly, a QTL (QRSratioIX-2.30) related to root-shoot ratio, an important trait for drought avoidance, explaining the highest phenotypic variance of 27.6 and 28.9% for the two consecutive seasons, respectively, was detected. This QTL was closed to the co-dominant SNP marker TP6337 and also flanked by the two SNP TP518 and TP1280. An important QTL (QLRNIII-98.64) related to lateral root number was found close to TP3371 and flanked by TP5093 and TP6072 SNP markers. Also, a QTL (QSRLIV-61.63) associated with specific root length was identified close to TP1873 and flanked by F7XEM6b SRAP marker and TP1035 SNP marker. These two QTLs were detected in both seasons. Our results could be used for marker-assisted selection in lentil breeding programs targeting root and shoot characteristics conferring drought avoidance as an efficient alternative to slow and labor-intensive conventional breeding methods

A neural network simulation package in CLIPS

The intrinsic similarity between the firing of a rule and the firing of a neuron has been captured in this research to provide a neural network development system within an existing production system (CLIPS). A very important by-product of this research has been the emergence of an integrated technique of using rule based systems in conjunction with the neural networks to solve complex problems. The systems provides a tool kit for an integrated use of the two techniques and is also extendible to accommodate other AI techniques like the semantic networks, connectionist networks, and even the petri nets. This integrated technique can be very useful in solving complex AI problems