Effects of Nutrition and Time of Weaning on Dry Season Liveweight Loss of Breeder Cows

In the seasonally dry tropics of northern Australia, breeder cows may lose up to 30% liveweight during the dry season when pasture is of low nutritive value. This is a major cause of low reproductive rates and high mortality. Weaning early in the dry season is effective to reduce this liveweight loss of the breeder (Holroyd et al. 1988). An experiment examined the dry season liveweight loss of breeders for a range of weaning times and levels of nutrition. From April to October through the dry season, 209 Bos indicus x Shorthorn cross cows 4-6 years of age grazed speargrass pastures in north Queensland. The cows had been joined with bulls from late January until April. Twenty-nine breeders had not suckled a calf during the previous wet season (DRY cows). In addition 180 cows lactating in April were weaned in late April, mid July or early September. The cows were allocated by stratified randomisation based on lactational status, stage of pregnancy and body condition to 15 x 40 ha paddocks. Five paddocks with low fertility soils provided LOW nutrition, while 10 paddocks with medium fertility soils and no supplementation or with supplementation provided MEDIUM and HIGH nutrition, respectively. The supplement consisted of molasses containing 14% urea offered ad libitum. Liveweight was measured at intervals and conceptus-free liveweight (CF-LW) calculated. Data were analyses by AOV within groups of paddocks. Animal production for a consuming world : proceedings of 9th Congress of the Asian-Australasian Association of Animal Production Societies [AAAP] and 23rd Biennial Conference of the Australian Society of Animal Production [ASAP] and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, [DRF]. 2-7 July 2000, Sydney, Australia.

Classification and rating of strong-motion earthquake records

Ninety-two strong-motion earthquake records from the California region, U.S.A., have been statistically studied using principal component analysis in terms of twelve important standardized strong-motion characteristics. The first two principal components account for about 57 per cent of the total variance. Based on these two components the earthquake records are classified into nine groups in a two-dimensional principal component plane. Also a unidimensional engineering rating scale is proposed. The procedure can be used as an objective approach for classifying and rating future earthquakes.

Runoff, sediment loss and water quality from forest roads in a southeast Queensland coastal plain Pinus plantation

Runoff and sediment loss from forest roads were monitored for a two-year period in a Pinus plantation in southeast Queensland. Two classes of road were investigated: a gravelled road, which is used as a primary daily haulage route for the logging area, and an ungravelled road, which provides the main access route for individual logging compartments and is intensively used as a haulage route only during the harvest of these areas (approximately every 30 years). Both roads were subjected to routine traffic loads and maintenance during the study. Surface runoff in response to natural rainfall was measured and samples taken for the determination of sediment and nutrient (total nitrogen, total phosphorus, dissolved organic carbon and total iron) loads from each road. Results revealed that the mean runoff coefficient (runoff depth/rainfall depth) was consistently higher from the gravelled road plot with 0.57, as compared to the ungravelled road with 0.38. Total sediment loss over the two-year period was greatest from the gravelled road plot at 5.7 t km−1 compared to the ungravelled road plot with 3.9 t km−1. Suspended solids contributed 86% of the total sediment loss from the gravelled road, and 72% from the ungravelled road over the two years. Nitrogen loads from the two roads were both relatively constant throughout the study, and averaged 5.2 and 2.9 kg km−1 from the gravelled and ungravelled road, respectively. Mean annual phosphorus loads were 0.6 kg km−1 from the gravelled road and 0.2 kg km−1 from the ungravelled road. Organic carbon and total iron loads increased in the second year of the study, which was a much wetter year, and are thought to reflect the breakdown of organic matter in roadside drains and increased sediment generation, respectively. When road and drain maintenance (grading) was performed runoff and sediment loss were increased from both road types. Additionally, the breakdown of the gravel road base due to high traffic intensity during wet conditions resulted in the formation of deep (10 cm) ruts which increased erosion. The Water Erosion Prediction Project (WEPP):Road model was used to compare predicted to observed runoff and sediment loss from the two road classes investigated. For individual rainfall events, WEPP:Road predicted output showed strong agreement with observed values of runoff and sediment loss. WEPP:Road predictions for annual sediment loss from the entire forestry road network in the study area also showed reasonable agreement with the extrapolated observed values.

CBCT-guided radiotherapy for locally advanced head and cancer: dosimetric impact of weight loss on VMAT and IMRT plans for selected organs at risk structures (OARs)

Purpose: It is common for head and neck patients to be affected by time trend errors as a result of weight loss during a course of radiation treatment. The objective of this planning study was to investigate the impact of weight loss on Volumetric Modulated Arc Therapy (VMAT) as well as Intensity modulated radiation therapy (IMRT) for locally advanced head and neck cancer using automatic co-registration of the CBCT. Methods and Materials: A retrospective analysis of previously treated IMRT plans for 10 patients with locally advanced head and neck cancer patients was done. A VMAT plan was also produced for all patients. We calculated the dose–volume histograms (DVH) indices for spinal cord planning at risk volumes (PRVs), the brainstem PRVs (SC+0.5cm and BS+0.5cm, respectively) as well as mean dose to the parotid glands. Results: The results show that the mean difference in dose to the SC+0.5cm was 1.03% and 1.27% for the IMRT and VMAT plans, respectively. As for dose to the BS+0.5, the percentage difference was 0.63% for the IMRT plans and 0.61% for the VMAT plans. The analysis of the parotid gland doses shows that the percentage change in mean dose to left parotid was -8.0% whereas that of the right parotid was -6.4% for the IMRT treatment plans. In the VMAT plans, the percentages change for the left and the right parotid glands were -6.6% and -6.7% respectively. Conclusions: This study shows a clinically significant impact of weight loss on DVH indices analysed in head and neck organs at risk. It highlights the importance of adaptive radiotherapy in head and neck patients if organ at risk sparing is to be maintained.

Effect of fragmentation, habitat loss and within-patch habitat characteristics on ant assemblages in semi-arid woodlands of eastern Australia.

The reliability of ants as bioindicators of ecosystem condition is dependent on the consistency of their response to localised habitat characteristics, which may be modified by larger-scale effects of habitat fragmentation and loss. We assessed the relative contribution of habitat fragmentation, habitat loss and within-patch habitat characteristics in determining ant assemblages in semi-arid woodland in Queensland, Australia. Species and functional group abundance were recorded using pitfall traps across 20 woodland patches in landscapes that exhibited a range of fragmentation states. Of fragmentation measures, changes in patch area and patch edge contrast exerted the greatest influence on species assemblages, after accounting for differences in habitat loss. However, 35% of fragmentation effects on species were confounded by the effects of habitat characteristics and habitat loss. Within-patch habitat characteristics explained more than twice the amount of species variation attributable to fragmentation and four times the variation explained by habitat loss. The study indicates that within-patch habitat characteristics are the predominant drivers of ant composition. We suggest that caution should be exercised in interpreting the independent effects of habitat fragmentation and loss on ant assemblages without jointly considering localised habitat attributes and associated joint effects.

Limb-loss in pond-reared blue swimmer crabs Portunus pelagicus (L.): Effect on growth in an indoor shedding system

Limb-loss in crustaceans can reduce moult increment and delay or advance the timing of moulting, both aspects that are likely to impact upon soft-shell crab production. Pond-reared blue swimmer crabs Portunus pelagicus were harvested and maintained in a crab shedding system. The wet weight, carapace width (CW) and the occurrence of limb-loss were assessed before stocking in the shedding system and after each of the next three moults. Many of the crabs were initially missing one or two limbs and these did not grow as much as the crabs that were intact at the start of the trial. Despite its strong correlation with wet weight, CW changes proved to be misleading. Limb-loss reduced the %CW increment but not the per cent weight increment (where the later is calculated from the actual pre-moult weight). Pre-moult weight explained much of the variation in post-moult weight, with crabs moulting to approximately double their weight. Limb-loss reduced 'growth' and production from the pond because it reduced pre-moult weight but limb-loss did not alter the weight change on shedding a given weight of crabs, although some of that change now included regeneration of limbs. One can hypothesize that much of the size variation seen in pond-reared crabs may be due to accumulated effects of repeated limb-loss, rather than genetic variation.

Transmission loss analysis of rectangular expansion chamber with arbitrary location of inlet/outlet by means of Green's functions

Transmission loss of a rectangular expansion chamber, the inlet and outlet of which are situated at arbitrary locations of the chamber, i.e., the side wall or the face of the chamber, are analyzed here based on the Green's function of a rectangular cavity with homogeneous boundary conditions. The rectangular chamber Green's function is expressed in terms of a finite number of rigid rectangular cavity mode shapes. The inlet and outlet ports are modeled as uniform velocity pistons. If the size of the piston is small compared to wavelength, then the plane wave excitation is a valid assumption. The velocity potential inside the chamber is expressed by superimposing the velocity potentials of two different configurations. The first configuration is a piston source at the inlet port and a rigid termination at the outlet, and the second one is a piston at the outlet with a rigid termination at the inlet. Pressure inside the chamber is derived from velocity potentials using linear momentum equation. The average pressure acting on the pistons at the inlet and outlet locations is estimated by integrating the acoustic pressure over the piston area in the two constituent configurations. The transfer matrix is derived from the average pressure values and thence the transmission loss is calculated. The results are verified against those in the literature where use has been made of modal expansions and also numerical models (FEM fluid). The transfer matrix formulation for yielding wall rectangular chambers has been derived incorporating the structural–acoustic coupling. Parametric studies are conducted for different inlet and outlet configurations, and the various phenomena occurring in the TL curves that cannot be explained by the classical plane wave theory, are discussed.

Validation-Based Sparse Gaussian Process Classifier Design

Gaussian processes (GPs) are promising Bayesian methods for classification and regression problems. Design of a GP classifier and making predictions using it is, however, computationally demanding, especially when the training set size is large. Sparse GP classifiers are known to overcome this limitation. In this letter, we propose and study a validation-based method for sparse GP classifier design. The proposed method uses a negative log predictive (NLP) loss measure, which is easy to compute for GP models. We use this measure for both basis vector selection and hyperparameter adaptation. The experimental results on several real-world benchmark data sets show better orcomparable generalization performance over existing methods.

Site classification and estimation of surface level seismic hazard using geophysical data and probabilistic approach

This paper presents the site classification of Bangalore Mahanagar Palike (BMP) area using geophysical data and the evaluation of spectral acceleration at ground level using probabilistic approach. Site classification has been carried out using experimental data from the shallow geophysical method of Multichannel Analysis of Surface wave (MASW). One-dimensional (1-D) MASW survey has been carried out at 58 locations and respective velocity profiles are obtained. The average shear wave velocity for 30 m depth (Vs(30)) has been calculated and is used for the site classification of the BMP area as per NEHRP (National Earthquake Hazards Reduction Program). Based on the Vs(30) values major part of the BMP area can be classified as ``site class D'', and ``site class C'. A smaller portion of the study area, in and around Lalbagh Park, is classified as ``site class B''. Further, probabilistic seismic hazard analysis has been carried out to map the seismic hazard in terms spectral acceleration (S-a) at rock and the ground level considering the site classes and six seismogenic sources identified. The mean annual rate of exceedance and cumulative probability hazard curve for S. have been generated. The quantified hazard values in terms of spectral acceleration for short period and long period are mapped for rock, site class C and D with 10% probability of exceedance in 50 years on a grid size of 0.5 km. In addition to this, the Uniform Hazard Response Spectrum (UHRS) at surface level has been developed for the 5% damping and 10% probability of exceedance in 50 years for rock, site class C and D These spectral acceleration and uniform hazard spectrums can be used to assess the design force for important structures and also to develop the design spectrum.

Prospective decrease in progesterone concentrations in female lightweight rowers during the competition season compared with the off-season: A controlled study examining weight loss and intensive exercise

The purpose of this study was to monitor ovarian hormone function response to intense exercise and body weight changes in female athletes. Ovarian hormone function was evaluated in 12 female lightweight rowers and 10 age-height-weight matched sedentary controls. Ovarian hormone function was assessed during consecutive competition season and off season, by measurement of peak and average alternative day overnight urinary oestrone glucuronide (E1G) and pregnanediol glucuronide (PdG) excretion. Competition season was associated with a 5.8 kg (9.3%) body weight loss in the lightweight rowers. Significantly lower competition season peak and average urinary excretion of PdG were found in the lightweight rowers compared with the controls. Lower competition season peak and average urinary excretion of E1G were also found in the lightweight rowers compared with the controls, but the difference did not reach significance. The number of rowing training hours was a significant determinant of peak PdG excretion in the rowers (R2 = 0.40; p<0.02). The seasonal suppression of PdG excretion was associated with degree of weight loss (R2 = 0.46; p<0.01). The competition related decrease in E1G and PdG excretion for the lightweight rowers was predominantly restored during the off season when exercise intensity and duration were decreased and body weight increased. These results showed a significant (p<0.05) reduction in progesterone metabolite excretion and a non-significant decrease in oestrone metabolite excretion associated with intensive competition season training loads and body weight reduction in female lightweight rowers.

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Mortality and blood loss by blue swimmer crabs (Portunus pelagicus) after simulated capture and discarding from gillnets

Two laboratory experiments were carried out to quantify the mortality and physiological responses of juvenile blue swimmer crabs (Portunus pelagicus) after simulated gillnet entanglement, air exposure, disentanglement, and discarding. In both experiments, all but control blue swimmer crabs were entangled in 1-m(2) gillnet panels for 1 h, exposed to air for 2 min, subjected to various treatments of disentanglement ranging between the forceful removal of none, one, two, and four appendages, then "discarded" into individual experimental tanks and monitored for 10 d. In Experiment 1, mortalities were associated with the number of appendages removed and the occurrence of unsealed wounds. In Experiment 2, live blue swimmer crabs were sampled for blood at 2 min and 6, 24, and 72 h post-discarding to test for the effects of disentanglement and appendage removal on total haemocyte counts, clotting times, protein levels (by refractive index), and blood ion concentrations. Compared with blue swimmer crabs that had sealed or no wounds, those with unsealed wounds had lower total haemocyte counts, protein, and calcium concentrations and increased clotting ties and magnesium and sodium levels. Induced autotomy, as opposed to the arbitrary, forceful removal of a appendages has the potential to minimize the mortality and stress of discarded, juvenile blue swimmer crabs.

Automatic ICD-10 classification of cancers from free-text death certificates

Objective Death certificates provide an invaluable source for cancer mortality statistics; however, this value can only be realised if accurate, quantitative data can be extracted from certificates – an aim hampered by both the volume and variable nature of certificates written in natural language. This paper proposes an automatic classification system for identifying cancer related causes of death from death certificates. Methods Detailed features, including terms, n-grams and SNOMED CT concepts were extracted from a collection of 447,336 death certificates. These features were used to train Support Vector Machine classifiers (one classifier for each cancer type). The classifiers were deployed in a cascaded architecture: the first level identified the presence of cancer (i.e., binary cancer/nocancer) and the second level identified the type of cancer (according to the ICD-10 classification system). A held-out test set was used to evaluate the effectiveness of the classifiers according to precision, recall and F-measure. In addition, detailed feature analysis was performed to reveal the characteristics of a successful cancer classification model. Results The system was highly effective at identifying cancer as the underlying cause of death (F-measure 0.94). The system was also effective at determining the type of cancer for common cancers (F-measure 0.7). Rare cancers, for which there was little training data, were difficult to classify accurately (F-measure 0.12). Factors influencing performance were the amount of training data and certain ambiguous cancers (e.g., those in the stomach region). The feature analysis revealed a combination of features were important for cancer type classification, with SNOMED CT concept and oncology specific morphology features proving the most valuable. Conclusion The system proposed in this study provides automatic identification and characterisation of cancers from large collections of free-text death certificates. This allows organisations such as Cancer Registries to monitor and report on cancer mortality in a timely and accurate manner. In addition, the methods and findings are generally applicable beyond cancer classification and to other sources of medical text besides death certificates.

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis.

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images. PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.

Porn, censorship, classification and free speech: Global paradoxes in the governance of media content

In this presentation, I reflect upon the global landscape surrounding the governance and classification of media content, at a time of rapid change in media platforms and services for content production and distribution, and contested cultural and social norms. I discuss the tensions and contradictions arising in the relationship between national, regional and global dimensions of media content distribution, as well as the changing relationships between state and non-state actors. These issues will be explored through consideration of issues such as: recent debates over film censorship; the review of the National Classification Scheme conducted by the Australian Law Reform Commission; online controversies such as the future of the Reddit social media site; and videos posted online by the militant group ISIS.