scholarly journals Conditional Analysis for Mixed Covariates, with Application to Feed Intake of Lactating Sows

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
S. Y. Park ◽  
C. Li ◽  
S. M. Mendoza Benavides ◽  
E. van Heugten ◽  
A. M. Staicu
Keyword(s):  
Feed Intake ◽  
Dynamic Change ◽  
Estimation Algorithm ◽  
Joint Estimation ◽  
Efficient Estimation ◽  
Specific Information ◽  
Computationally Efficient ◽  
Modeling Framework ◽  
Lactating Sows ◽  
Information Vector

We propose a novel modeling framework to study the effect of covariates of various types on the conditional distribution of the response. The methodology accommodates flexible model structure, allows for joint estimation of the quantiles at all levels, and provides a computationally efficient estimation algorithm. Extensive numerical investigation confirms good performance of the proposed method. The methodology is motivated by and applied to a lactating sow study, where the primary interest is to understand how the dynamic change of minute-by-minute temperature in the farrowing rooms within a day (functional covariate) is associated with low quantiles of feed intake of lactating sows, while accounting for other sow-specific information (vector covariate).

An Energy Efficient Estimation Algorithm for Wireless Sensor Network

2011 ◽  
Vol 216 ◽  
pp. 176-180
Author(s):  
Yong Ding ◽  
Yue Mei Su
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Estimation Algorithm ◽  
Efficient Estimation ◽  
Wireless Sensor ◽  
Estimation Algorithms ◽  
Current Energy

Wireless Sensor Networks functionality is closely related to network lifetime which depends on the energy consumption, so require energy- efficient protocols to improve the network lifetime. According to the analysis and summary of the current energy efficient estimation algorithms in wireless sensor network An energy-efficient algorithm is proposed,. Then this optimization algorithm proposed in the paper is adopted to improve the traditional diffusion routing protocol. Simulation results show that this algorithm is to effectively balance the network energy consumption, improve the network life-cycle and ensure the communication quality.

PSIII-13 Effects of Saccharomyces Cerevisiae Fermentation Products on Lactating Sow Performance

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 172-172
Author(s):  
Ricardo M Garcia ◽  
Morgan T Thayer ◽  
Kayla M Mills ◽  
Jacob A Richert ◽  
Katharine G Sharp ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Water Intake ◽  
Feed Intake ◽  
Control Diet ◽  
Feed Additives ◽  
Intermediate Water ◽  
Lactation Period ◽  
Fermentation Products ◽  
Once Daily ◽  
Lactating Sows

Abstract Lactating sows (N=140, York x Landrace) were used to evaluate the effects of a liquid prototype (LIQP) and dry (XPC®; Diamond V) Saccharomyces cerevisiae feed additives on sow and litter performance. Sows were fed a common gestation diet (0.55% SID-Lysine) until d112 of pregnancy and then allotted to lactation treatments: 1) Control diet (CON; 1.00% SID-Lysine), 2) CON +15 mL of LIQP from d112 to weaning (LIQ), 3) CON +0.20% of XPC from d112 to weaning (DRY), and 4) DRY +15 mL of LIQP from d112 to d7 post-farrowing (D+L). The LIQP was given once daily using an oral dose gun and XPC was included in the feed. Immunoglobulin concentrations were estimated on colostrum samples using Brix refractometer and piglet d 1 serum immunocrit ratio and plasma IgA and IgG. Daily sow water intake and daily feed intake (DFI) from d112 of gestation to d7 post-farrowing and weekly feed intake (ADFI) were recorded. There were no treatment effects on sow BW, backfat, or loin depth (P >0.05) although sows from LIQ group had numerically smaller BW reductions compared to CON sows (4.9% vs 7.2%, P=0.19). LIQ sows had greater DFI and CON lower DFI during week 1 of lactation (P=0.04) as well as ADFI for weeks 2, 3, and overall lactation period (P< 0.01) with DRY and D+L sows being intermediate. Water intake, immunoglobulins, and litter performance did not differ among treatments (P >0.05) although pigs from LIQ sows, compared to CON, had numerically increased weaning (6.14 vs 5.82kg, P >0.05) and litter weights (63.2 vs 60.1kg, P >0.05). LIQ sows had 0.7 d reduced wean-to-estrus interval (P< 0.001) and tended to have greater conception rates (P=0.07). In conclusion, LIQ supplementation of lactating sows improves feed intake, allowing sows to keep body reserves, and have better subsequent rebreeding performance.

scholarly journals Research on Multiple States Joint Estimation Algorithm for Electric Vehicles Under Charge Mode

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 40143-40153 ◽  
Author(s):  
Liye Wang ◽  
Lifang Wang ◽  
Chenglin Liao ◽  
Wenjie Zhang
Keyword(s):  
Electric Vehicles ◽  
Estimation Algorithm ◽  
Joint Estimation ◽  
Charge Mode

scholarly journals Flexible expressed region analysis for RNA-seq with derfinder

2015 ◽  
Author(s):  
Leonardo Collado-Torres ◽  
Abhinav Nellore ◽  
Alyssa C. Frazee ◽  
Christopher Wilks ◽  
Michael I. Love ◽  
...  
Keyword(s):  
Differential Expression ◽  
Time Course ◽  
Differential Expression Analysis ◽  
Tissue Expression ◽  
Rna Seq ◽  
Computationally Efficient ◽  
Modeling Framework ◽  
Single Base ◽  
Region Analysis ◽  
Bump Hunting

AbstractBackgroundDifferential expression analysis of RNA sequencing (RNA-seq) data typically relies on reconstructing transcripts or counting reads that overlap known gene structures. We previously introduced an intermediate statistical approach called differentially expressed region (DER) finder that seeks to identify contiguous regions of the genome showing differential expression signal at single base resolution without relying on existing annotation or potentially inaccurate transcript assembly.ResultsWe present the derfinder software that improves our annotation-agnostic approach to RNA-seq analysis by: (1) implementing a computationally efficient bump-hunting approach to identify DERs which permits genome-scale analyses in a large number of samples, (2) introducing a flexible statistical modeling framework, including multi-group and time-course analyses and (3) introducing a new set of data visualizations for expressed region analysis. We apply this approach to public RNA-seq data from the Genotype-Tissue Expression (GTEx) project and BrainSpan project to show that derfinder permits the analysis of hundreds of samples at base resolution in R, identifies expression outside of known gene boundaries and can be used to visualize expressed regions at base-resolution. In simulations our base resolution approaches enable discovery in the presence of incomplete annotation and is nearly as powerful as feature-level methods when the annotation is complete.Conclusionsderfinder analysis using expressed region-level and single base-level approaches provides a compromise between full transcript reconstruction and feature-level analysis.The package is available from Bioconductor at www.bioconductor.org/packages/derfinder.

scholarly journals Vinasse in the diet of lactating sows and its effect on litter

2020 ◽  
Vol 42 ◽  
pp. e48152
Author(s):  
Dandara Silva Barros ◽  
Jean kaique Valentim ◽  
Silvana Lúcia dos Santos Medeiros ◽  
Sandra Regina Faria ◽  
Isabelli Dias Brito Pereira ◽  
...  
Keyword(s):  
Weight Gain ◽  
Experimental Design ◽  
Feed Intake ◽  
Liquid Diet ◽  
Feed Consumption ◽  
Experimental Facility ◽  
Lactating Sows ◽  
Randomized Experimental Design ◽  
Water Feed ◽  
The Impact

The aim of this study was to verify the impact of adding vinasse as an acidifier in sows diet during the lactating period and its effect on litter. A total of 14 agroceres females were used from the first day of lactation until weaning. The vinasse was obtained in a mill near the experimental facility and was stored in sterilized barrels. Animals were distributed in a completely randomized experimental design into two treatments: control liquid diet and liquid diet with the inclusion of vinasse in each feed supply of the day. The diets were supplied four times a day, containing a mixture of ½ L of vinasse and ½ L of water. Feed leftovers were weighted daily. Feed intake was used to evaluate sows’ performance. The piglets were weighted every week after birth until weaning in order to obtain weight gain. Vinasse inclusion showed an increase (p < 0.05) in feed intake of lactating sows, improving diet palatability. Inclusion of acidifier in the diet did not show (p > 0.05) difference in weight gain of piglets. Vinasse consumption by sows did not influence litter performance. The inclusion of vinasse in the diet of lactating sows is beneficial because increases feed consumption.

scholarly journals Variational Bayesian inversion of seismic attributes jointly for geologic facies and petrophysical rock properties

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. MR213-MR233 ◽  
Author(s):  
Muhammad Atif Nawaz ◽  
Andrew Curtis ◽  
Mohammad Sadegh Shahraeeni ◽  
Constantin Gerea
Keyword(s):  
Gaussian Mixture ◽  
Seismic Attributes ◽  
Joint Estimation ◽  
Training Data ◽  
P Wave ◽  
Rock Properties ◽  
Inversion Method ◽  
Computationally Efficient ◽  
S Wave ◽  
Well Data

Seismic attributes (derived quantities) such as P-wave and S-wave impedances and P-wave to S-wave velocity ratios may be used to classify subsurface volume of rock into geologic facies (distinct lithology-fluid classes) using pattern recognition methods. Seismic attributes may also be used to estimate subsurface petrophysical rock properties such as porosity, mineral composition, and pore-fluid saturations. Both of these estimation processes are conventionally carried out independent of each other and involve considerable uncertainties, which may be reduced significantly by a joint estimation process. We have developed an efficient probabilistic inversion method for joint estimation of geologic facies and petrophysical rock properties. Seismic attributes and petrophysical properties are jointly modeled using a Gaussian mixture distribution whose parameters are initialized by unsupervised learning using well-log data. Rock-physics models may be used in our method to augment the training data if the existing well data are limited; however, this is not required if sufficient well data are available. The inverse problem is solved using the Bayesian paradigm that models uncertainties in the form of probability distributions. Probabilistic inference is performed using variational optimization, which is a computationally efficient deterministic alternative to the commonly used sampling-based stochastic inference methods. With the help of a real data application from the North Sea, we find that our method is computationally efficient, honors expected spatial correlations of geologic facies, allows reliable detection of convergence, and provides full probabilistic results without stochastic sampling of the posterior distribution.

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