scholarly journals Analysis of agonistic interactions between sows with different rank position during mixing

2009 ◽  
Vol 52 (6) ◽  
pp. 603-612 ◽  
Author(s):  
C. Borberg ◽  
S. Hoy
Keyword(s):  
Low Rank ◽  
Agonistic Interactions ◽  
High Ranking ◽  
Rank Position ◽  
The Individual ◽  
Individual Rank

Abstract. Ninety-six sows in twelve groups of eight sows were continuously video-observed during 48 hours after weaning and mixing. The occurrence and the outcome of all agonistic interactions (AI) were recorded and data of wins and defeats were transformed into a 8 × 8 (winner-loser) matrix. Aggressor and receiver of the attacks and fights in the dyads have been determined and the rank index for each sow was calculated leading to the individual rank place RP (1 to 8) and to the classifying into high ranking (HRS: RP 1 to 4) and low ranking sows (LRS: RP 5 to 8). Based on a total number of 2 414 AI dominant sows with RP=1 initiated 94.3 % of the AI they were involved in and were the receiver in 5.7 % of the AI. In contrast, every fourth AI was orientated towards the subdominant sow with RP=8. The sows with RP 7 or 8 were the receivers in nearly half of all AI (44.9 %). Fights occurred more frequently between sows with a low rank place difference. More than 60 % of the attacks and more than 40 % of the fights were initiated from high ranking sows towards low ranking sows even though 28.6 % was the estimated value for those dyads. In only 2 % of the attacks and 18.8 % of the fights LRS engaged HRS which means that HRS usually react with a counter-attack when being attacked by a LRS.

scholarly journals Zu den Auswirkungen der Rangposition auf die Fruchtbarkeitsleistung von Sauen

2008 ◽  
Vol 51 (4) ◽  
pp. 351-358
Author(s):  
S. Hoy ◽  
J. Bauer ◽  
C. Borberg ◽  
C. Weirich
Keyword(s):  
Litter Size ◽  
Rank Order ◽  
Negative Influence ◽  
High Rank ◽  
Low Rank ◽  
Rank Position ◽  
Parity Number ◽  
The Difference ◽  
The Individual ◽  
Farrowing Rate

Abstract. Title of the paper: Impact of rank position on fertility of sows The investigations were carried out with 460 sows from two farms (farm A: housing the sows in small groups of 8 animals each, farm B with a large group of 100 sows) and a total number of 901 matings. The number of agonistic interactions was registered for each sow during 48 h after mixing soon after weaning the piglets. The individual rank place in the social hierarchy was calculated on the basis of wins and defeats and the sows were divided in high and low ranking sows. At farm B the rank position was estimated on the basis of the daily feeding order at two electronic feeding stations (first half = high ranking, second half of the sows in the feeding order = low ranking). Additionally, the following parameters were recorded for each sow: parity, farrowing rate and litter size (total and alive born piglets). The analysis showed that sows with a high rank position had a significantly higher farrowing rate (89.8 %) compared to pen-mates with low rank places (83.9 %, p<0.05)(farm A). Sows with a high rank position reached a significantly higher litter size of total born piglets (12.51, 16.14 piglets per litter respectively) than the low-ranking pen-mates (12.00, 14.83 piglets/litter respectively – farms A and B). In tendency the difference concerning the litter size between sows with high and low rank position was larger in sows with parity 2 than in sows with a higher parity number (farm A). When mixing sows, the time and the conditions (e.g. group size, space allowance per sow) have to be considered to prevent the negative influence of (low) rank order on fertility.

scholarly journals Supervised dimensionality reduction for big data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Joshua T. Vogelstein ◽  
Eric W. Bridgeford ◽  
Minh Tang ◽  
Da Zheng ◽  
Christopher Douville ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
Data Science ◽  
Real Data ◽  
Low Rank ◽  
Conditional Moment ◽  
Desktop Computer ◽  
Reduction Techniques ◽  
Reduction Methods ◽  
The Individual ◽  
Low Dimensional

AbstractTo solve key biomedical problems, experimentalists now routinely measure millions or billions of features (dimensions) per sample, with the hope that data science techniques will be able to build accurate data-driven inferences. Because sample sizes are typically orders of magnitude smaller than the dimensionality of these data, valid inferences require finding a low-dimensional representation that preserves the discriminating information (e.g., whether the individual suffers from a particular disease). There is a lack of interpretable supervised dimensionality reduction methods that scale to millions of dimensions with strong statistical theoretical guarantees. We introduce an approach to extending principal components analysis by incorporating class-conditional moment estimates into the low-dimensional projection. The simplest version, Linear Optimal Low-rank projection, incorporates the class-conditional means. We prove, and substantiate with both synthetic and real data benchmarks, that Linear Optimal Low-Rank Projection and its generalizations lead to improved data representations for subsequent classification, while maintaining computational efficiency and scalability. Using multiple brain imaging datasets consisting of more than 150 million features, and several genomics datasets with more than 500,000 features, Linear Optimal Low-Rank Projection outperforms other scalable linear dimensionality reduction techniques in terms of accuracy, while only requiring a few minutes on a standard desktop computer.

Environmental and geographical effects on fog occurrence

2021 ◽  
Author(s):  
Iva Hunova ◽  
Marek Brabec ◽  
Marek Malý ◽  
Alexandru Dumitrescu ◽  
Jan Geletič
Keyword(s):  
Air Pollution ◽  
Environmental Factors ◽  
Tensor Product ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Low Rank ◽  
Seasonal Component ◽  
Explanatory Variables ◽  
The Individual

&lt;p&gt;Fog is a very complex phenomenon (Gultepe et al., 2007). In some areas it can contribute substantially to hydrological and chemical inputs and is therefore of high environmental relevance (Blas et al., 2010). Fog formation is affected by numerous factors, such as meteorology, air pollution, terrain (geomorphology), and land-use.&lt;/p&gt;&lt;p&gt;In our earlier studies we addressed the role of meteorology and air pollution on fog occurrence (H&amp;#367;nov&amp;#225; et al., 2018) and long-term trends in fog occurrence in Central Europe (H&amp;#367;nov&amp;#225; et al., 2020). This study builds on earlier model identification of year-to-year and seasonal components in fog occurrence and brings an analysis of the deformation of the above components due to the individual explanatory variables. The aim of this study was to indicate the geographical and environmental factors affecting the fog occurrence.&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; We have examined the data on fog occurrence from 56 meteorological stations of various types from Romania reflecting different environments and geographical areas. We used long-term records from the 1981&amp;#8211;2017 period.&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; We considered both the individual explanatory variables and their interactions. With respect to geographical factors, we accounted for the altitude and landform. With respect to environmental factors,&amp;#160;&amp;#160; we accounted for proximity of large water bodies, and proximity of forests. Geographical data from Copernicus pan-European (e.g. CORINE land cover, high resolution layers) and local (e.g. Urban Atlas) projects were used. Elevation data from EU-DEM v1.1 were source for morphometric analysis (Copernicus, 2020).&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;We applied a generalized additive model, GAM (Wood, 2017; Hastie &amp; Tibshirani, 1990) to address nonlinear trend shapes in a formalized and unified way. In particular, we employed penalized spline approach with cross-validated penalty coefficient estimation. To explore possible deformations of annual and seasonal components with various covariates of interest, we used (penalized) tensor product splines to model (two-way) interactions parsimoniously, Wood (2006).&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; The fog occurrence showed significant decrease over the period under review. In general the selected explanatory variables significantly affected the fog occurrence and their effect was non-linear. Our results indicated that, the geographical and environmental variables affected primarily the seasonal component of the model. Of the factors which were accounted for, it was mainly the altitude showing the clear effect on seasonal component deformation (H&amp;#367;nov&amp;#225; et al., in press).&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References:&lt;/p&gt;&lt;p&gt;Blas, M, Polkowska, Z., Sobik, M., et al. (2010). Atmos. Res. 95, 455&amp;#8211;469.&lt;/p&gt;&lt;p&gt;Copernicus Land Monitoring Service (2020). Accessed online at: https://land.copernicus.eu/.&lt;/p&gt;&lt;p&gt;Gultepe, I., Tardif, R., Michaelidis, S.C., Cermak, J., Bott, A. et al. (2007). Pure Appl Geophys, 164, 1121-1159.&lt;/p&gt;&lt;p&gt;Hastie, T.J., Tibshirani, R.J. (1990). Generalized Additive Models. Boca Raton, Chapman &amp; Hall/CRC.&lt;/p&gt;&lt;p&gt;H&amp;#367;nov&amp;#225;, I., Brabec, M., Mal&amp;#253;, M., Dumitrescu, A., Geleti&amp;#269;, J. (in press) Sci. Total Environ. 144359.&lt;/p&gt;&lt;p&gt;H&amp;#367;nov&amp;#225;, I., Brabec, M., Mal&amp;#253;, M., Valeri&amp;#225;nov&amp;#225;, A. (2018) Sci. Total Environ. 636, 1490&amp;#8211;1499.&lt;/p&gt;&lt;p&gt;H&amp;#367;nov&amp;#225;, I., Brabec, M., Mal&amp;#253;, M., Valeri&amp;#225;nov&amp;#225;, A. (2020) Sci. Total Environ. 711, 135018.&lt;/p&gt;&lt;p&gt;Wood, S.N. (2006) Low rank scale invariant tensor product smooths for generalized additive mixed models. Biometrics 62(4):1025-1036&lt;/p&gt;&lt;p&gt;Wood, S.N. (2017). Generalized Additive Models: An Introduction with R (2nd ed). Boca Raton, Chapman &amp; Hall/CRC.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals On the Performance of Efficient Channel Estimation Strategies for Hybrid Millimeter Wave MIMO System

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1121
Author(s):  
Prateek Saurabh Srivastav ◽  
Lan Chen ◽  
Arfan Haider Wahla
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Optimization Problem ◽  
Mimo Systems ◽  
Mimo System ◽  
Low Rank ◽  
Potential Candidate ◽  
Alternating Direction ◽  
The Individual ◽  
Joint Channel

Millimeter wave (mmWave) relying upon the multiple output multiple input (MIMO) is a new potential candidate for fulfilling the huge emerging bandwidth requirements. Due to the short wavelength and the complicated hardware architecture of mmWave MIMO systems, the conventional estimation strategies based on the individual exploitation of sparsity or low rank properties are no longer efficient and hence more modern and advance estimation strategies are required to recapture the targeted channel matrix. Therefore, in this paper, we proposed a novel channel estimation strategy based on the symmetrical version of alternating direction methods of multipliers (S-ADMM), which exploits the sparsity and low rank property of channel altogether in a symmetrical manner. In S-ADMM, at each iteration, the Lagrange multipliers are updated twice which results symmetrical handling of all of the available variables in optimization problem. To validate the proposed algorithm, numerous computer simulations have been carried out which straightforwardly depicts that the S-ADMM performed well in terms of convergence as compared to other benchmark algorithms and also able to provide global optimal solutions for the strictly convex mmWave joint channel estimation optimization problem.

Relationships Between Social Dominance and Feeding Behaviour in Lactating Heifers During Periods of Heavy Competition

1993 ◽  
Vol 1993 ◽  
pp. 150-150
Author(s):  
A.D. Kenwright ◽  
J.M. Forbes
Keyword(s):  
Social Interaction ◽  
Social Dominance ◽  
Feeding Behaviour ◽  
Feeding Activity ◽  
Dairy Herds ◽  
Agonistic Interactions ◽  
High Ranking ◽  
The Way

Previous research has shown that social dominance in dairy herds can be measured using replacements of one cow by another at feed stations (Rutter et al,1987). When there is competition for feed or space, the motivation to engage in physical and non-physical agonistic interactions will be stronger than if resources are freely available. When resources are limited, social dominance becomes very important and high ranking animals have priority.This becomes especially important after cows are returned from milking and/or when fresh feed is added when the number of cows is far greater than the number of feeding spaces (Campling and Morgan, 1981). This experiment aimed to further investigate the way in which social interaction between cows affects the feeding behaviour, particularly at times of peak feeding activity.

scholarly journals Fusing website usability and search engine optimisation

2014 ◽  
Vol 16 (1) ◽  
Author(s):  
Eugene B. Visser ◽  
Melius Weideman
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Experimental Results ◽  
New Model ◽  
High Ranking ◽  
Website Usability ◽  
The Individual

Background: Most websites, especially those with a commercial orientation, need a high ranking on a search engine for one or more keywords or phrases. The search engine optimisation process attempts to achieve this. Furthermore, website users expect easy navigation, interaction and transactional ability. The application of website usability principles attempts to achieve this. Ideally, designers should achieve both goals when they design websites.Objectives: This research intended to establish a relationship between search engine optimisation and website usability in order to guide the industry. The authors found a discrepancy between the perceived roles of search engines and website usability.Method: The authors designed three test websites. Each had different combinations of usability, visibility and other attributes. They recorded and analysed the conversions and financial spending on these experimental websites. Finally, they designed a model that fuses search engine optimisation and website usability.Results: Initially, it seemed that website usability and search engine optimisation complemented each other. However, some contradictions between the two, based on content, keywords and their presentation, emerged. Industry experts do not acknowledge these contradictions, although they agree on the existence of the individual elements. The new model highlights the complementary and contradictory aspects.Conclusion: The authors found no evidence of any previous empirical experimental results that could confirm or refute the role of the model. In the fast-paced world of competition between commercial websites, this adds value and originality to the websites of organisations whose websites play important roles.

scholarly journals Predicting the effects of drug combinations using probabilistic matrix factorization

2021 ◽  
Author(s):  
Ron Nafshi ◽  
Timothy R Lezon
Keyword(s):  
Matrix Factorization ◽  
Partial Information ◽  
Matrix Completion ◽  
Drug Combinations ◽  
Training Data ◽  
Low Rank ◽  
Probabilistic Matrix Factorization ◽  
Low Rank Matrix Completion ◽  
The Individual ◽  
Synergistic Combinations

Drug development is costly and time-consuming, and developing novel practical strategies for creating more effective treatments is imperative. One possible solution is to prescribe drugs in combination. Synergistic drug combinations could allow lower doses of each constituent drug, reducing adverse reactions and drug resistance. However, it is not feasible to sufficiently test every combination of drugs for a given illness to determine promising synergistic combinations. Since there is a finite amount of time and resources available for finding synergistic combinations, a model that can identify synergistic combinations from a limited subset of all available combinations could accelerate development of therapeutics. By applying recommender algorithms, such as the low-rank matrix completion algorithm Probabilistic Matrix Factorization (PMF), it may be possible to identify synergistic combinations from partial information of the drug interactions. Here, we use PMF to predict the efficacy of two-drug combinations using the NCI ALMANAC, a robust collection of pairwise drug combinations of 104 FDA-approved anticancer drugs against 60 common cancer cell lines. We find that PMF is able predict drug combination efficacy with high accuracy from a limited set of combinations and is robust to changes in the individual training data. Moreover, we propose a new PMF-guided experimental design to detect all synergistic combinations without testing every combination.

Research on Background Modeling Based on Low-Rank Matrix Recovery

2014 ◽  
Vol 635-637 ◽  
pp. 1056-1059 ◽  
Author(s):  
Bao Yan Wang ◽  
Xin Gang Wang
Keyword(s):  
Sparse Matrix ◽  
Background Modeling ◽  
Low Rank ◽  
Complex Scene ◽  
Matrix Recovery ◽  
Rank Matrix ◽  
Training Samples ◽  
The Individual ◽  
Low Rank Matrix Recovery ◽  
Low Rank Matrix

Key and difficult points of background subtraction method lie in looking for an ideal background modeling under complex scene. Stacking the individual frames as columns of a big matrix, background parts can be viewed as a low-rank background matrix because of large similarity among individual frames, yet foreground parts can be viewed as a sparse matrix as foreground parts play a small role in individual frames. Thus the process of video background modeling is in fact a process of low-rank matrix recovery. Background modeling based on low-rank matrix recovery can separate foreground images from background at the same time without pre-training samples, besides, the approach is robust to illumination changes. However, there exist some shortcomings in background modeling based on low-rank matrix recovery by analyzing numerical experiments, which is developed from three aspects.

scholarly journals Rituali di segni e metamorfosi Ṭuqūs al-išārāt wa-l-taḥawwulāt

2020 ◽  
Author(s):  
Martina Censi
Keyword(s):  
Social Change ◽  
Point Of View ◽  
Individual Identity ◽  
Legal Authority ◽  
Political Commitment ◽  
High Ranking ◽  
Individual Point ◽  
The Individual ◽  
The City ◽  
Collective Dimension

Ṭuqūs al-išārāt wa-l-taḥawwulāt (Rituals of Signs and Transformations), published in 1994, is a play which can be attributed to the last phase of Saʿd Allāh Wannūs’s literary production. At this stage, the Syrian author’s political commitment is no longer expressed through the interest for the collective dimension, but it focuses on the individual, considered as a pivotal element for social change. In Ṭuqūs, Saʿd Allāh Wannūs revisits history from an individual point of view, fragmenting it into a multiplicity of micro-narratives. During the 1880s in Damascus, the muftī, the chief religious legal authority, and the leader of the ašrāf, the descendants of the Prophet, are involved in a feud that splits the city into factions and brings it on the verge of anarchy. When the chief of police arrests the leader of the ašrāf while he is engaged in lovemaking with his mistress in his semi-private garden, the muftī concocts a scheme to save his enemy’s reputation, but his real aim is to subdue him and get rid of him. This event triggers a series of transformations involving the identities of the characters. Thus, the leader of the ašrāf, a regular of prostitutes and assiduous drinker, suddenly becomes a mystic with ascetic ambitions, while the upright muftī loses his head for a high-ranking woman who leaves her respectable life to become a prostitute. The whole society is destabilized by the desires of the characters. Desire not only affects their individual identity, but it also exerts influence on their social position, undermining a system of norms based on hypocrisy and on the division between the ‘latent’ and the ‘manifest’.

Relationships Between Social Structure and Response To Novelty in Captive Jackdaws, Corvus Monedula L., I. Response To Novel Space

Behaviour ◽  
1982 ◽  
Vol 81 (2-4) ◽  
pp. 231-263 ◽  
Author(s):  
Gadi Katzir
Keyword(s):  
Social Structure ◽  
Entire Group ◽  
The Novel ◽  
High Ranking ◽  
The Social ◽  
Early Exploration ◽  
The Individual ◽  
Duration Measure ◽  
Corvus Monedula ◽  
Initial Delay

AbstractThe response of six groups of captive, handreared jackdaws, Corvus monedula L. (Aves), to a novel space was tested. Birds were tested in groups and were free to make contact with the novelty or remain in a familiar area. The individual manner of response was related to the social position of the individual. i) Exploratory behaviour occurred in bouts. Familiarization with the novelty was mostly gradual, but in some groups after an initial delay, the entire group began to explore and then to enter the novel space very rapidly ("avalanche"). ii) In each group one or two birds performed most of the early exploration, and termed "initiators". iii) The initiator in each group was distinguished from all others by duration and by frequency measures. Both for approach and for entering of the novel space (a) birds that scored high on the frequency measure, scored high also on the duration measure, (b) birds that scored high on either measure, for the approach, were the most likely to score high on that measure for the entering. iv) In all six groups the "initiators" were sociall mid or low ranking birds. v) Top ranking birds were distinguished from all others by the combination of two features; (a) they did not act as initiators, and (b) they were not the last to peak in their duration inside the novel space. It is argued that top ranking birds are more conservative, and that it benefits them as they have relatively more to lose and less to gain by being exploratory. The converse is true for mid or low ranking birds, which may benefit by exploiting resources outside the reach of the high ranking birds.

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