Statistical Inference for Valued-Edge Networks: Generalized Exponential Random Graph Models

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks, exponential random graph models are a ubiquitous means of analysis. However, they are limited by an inability to model networks with valued edges. We solve this problem by introducing a class of generalized exponential random graph models capable of modeling networks whose edges are valued, thus greatly expanding the scope of networks applied researchers can subject to statistical analysis

The interplay of microscopic and mesoscopic structure in complex networks

Not all nodes in a network are created equal. Differences and similarities exist at both individual node and group levels. Disentangling single node from group properties is crucial for network modeling and structural inference. Based on unbiased generative probabilistic exponential random graph models and employing distributive message passing techniques, we present an efficient algorithm that allows one to separate the contributions of individual nodes and groups of nodes to the network structure. This leads to improved detection accuracy of latent class structure in real world data sets compared to models that focus on group structure alone. Furthermore, the inclusion of hitherto neglected group specific effects in models used to assess the statistical significance of small subgraph (motif) distributions in networks may be sufficient to explain most of the observed statistics. We show the predictive power of such generative models in forecasting putative gene-disease associations in the Online Mendelian Inheritance in Man (OMIM) database. The approach is suitable for both directed and undirected uni-partite as well as for bipartite networks

H-reflex amplitude asymmetry is an earlier sign of nerve root involvement than latency in patients with S1 radiculopathy

Abstract Background Based on our clinical experience, the H-reflex amplitude asymmetry might be an earlier sign of nerve root involvement than latency in patients with S1 radiculopathy. However, no data to support this assumption are available. The purpose of this study was to review and report the electrophysiological changes in H-reflex amplitude and latency in patients with radiculopathy in order to determine if there is any evidence to support the assumption that H-reflex amplitude is an earlier sign of nerve root involvement than latency. Results Patients with radiculopathy showed significant amplitude asymmetry when compared with healthy controls. However, latency was not always significantly different between patients and healthy controls. These findings suggest nerve root axonal compromise that reduced reflex amplitude earlier than the latency parameter (demyelination) during the pathologic processes. Conclusion Contrary to current clinical thought, H-reflex amplitude asymmetry is an earlier sign/parameter of nerve root involvement in patients with radiculopathy compared with latency.</p

Increased yearling weight as a proportion of 21-month weight was associated with increased milk production in dairy heifers

Aims: To examine the relationship between liveweight (LWT) at 12 months as a proportion of LWT at 21 months of age (LWT(12/21)%) and first lactation and cumulative 3-year milk production in dairy heifers in New Zealand. Methods: Liveweight and milk production records were obtained for dairy heifers born from June to December (spring-calving season) between 2006–2007 and 2013–2014 dairy seasons; production records included first lactation (n = 140,113) and cumulative 3-year (n = 67,833) milksolids and energy-corrected milk (ECM) yields. Heifers were classified into five breed groups; Holstein-Friesian, Holstein-Friesian crossbred, Jersey, Jersey crossbred and Holstein-Friesian-Jersey crossbred. Within each breed group heifers were categorised into quintiles based on 21-month LWT. The LWT(12/21)% was calculated for each animal. Relationships between LWT(12/21)% and milk production within each breed group and LWT category were estimated using linear mixed effects models including the linear and quadratic effects of LWT(12/21)%. Results: The relationship between LWT(12/21)% and milk production was predominantly curvilinear, with lower milk production at lesser LWT(12/21)% compared with greater LWT(12/21)%. For all breed groups and most LWT categories, heifers that were 55 or 65% LWT(12/21)% produced greater ECM and milksolids yields compared with heifers that were 45% LWT(12/21)%. Holstein-Friesian, Holstein-Friesian crossbred and Holstein-Friesian-Jersey crossbred heifers that were 65% LWT(12/21)% produced greater cumulative 3-year ECM and milksolids yields compared with heifers of the same breed group that were 45% LWT(12/21)% Conclusions and clinical relevance: Heifers that were a greater proportion of their 21-month LWT at 12 months of age produced more first lactation and cumulative 3-year milk yields than heifers that were a lesser proportion of their 21-month LWT at 12 months of age. These results indicate that increased growth in early life of New Zealand dairy heifers is beneficial to future milk production

Body weight of dairy heifers is positively associated with reproduction and stayability

This study investigated the relationships between body weight (BW) and stayability, and BW and calving pattern, of 189,936 New Zealand dairy heifers. Heifers were classified into 5 breed groups: Holstein-Friesian (F), Holstein-Friesian crossbred (FX), Jersey (J), Jersey crossbred (JX), and Holstein-Friesian × Jersey crossbred (FJ). Body weight was predicted using Legendre polynomials at 6, 12, and 15 mo of age, and we analyzed their relationships with stayability, calving rate, and re-calving rate over the first 3 calvings. Approximately 92% of heifers calved for the first time at age 2 yr, 76% a second time at 3 yr, and 61% a third time at 4 yr. Heifers that were heavier were more likely to remain in the herd for first, second, and third calving compared with heifers that were lighter. Furthermore, we found positive curvilinear relationships between pre-breeding BW and reproductive performance of dairy heifers. Heifers that were heavier at 6, 12, and 15 mo were more likely to calve early for first calving compared with heifers that were lighter, regardless of breed group. In addition, we found a large range in BW where the probability of calving or re-calving early was high. For example, FJ heifers that were between 255 and 396 kg at 15 mo of age had 21-d calving and re-calving rates above 75 and 70%, respectively. For second and third lactations, however, heifer pre-breeding BW showed only small effects on the 21-d calving and re-calving rates. For heifers that were at the heaviest end of the BW range in the current study, slight declines in stayability and reproductive performance occurred, compared with heifers in the mid-range of BW. Consequently, for heifers that were above average in BW, the benefit of increasing BW before first breeding would be small and might even result in slight declines in stayability and reproductive performance. For heifers that were below average in BW, considerable beneficial effects on stayability and reproductive performance are predicted as a result of improving rearing practices to produce heavier heifers throughout the pre-breeding rearing phase

Live weight and growth of Holstein-Friesian, Jersey and crossbred dairy heifers in New Zealand

The objective of this study was to model the growth of dairy heifers to estimate the effects of breed and heterosis on live weight (LWT) and growth from three to 22 months of age. Data comprised of 1,653,214 LWT records obtained from 189,936 dairy heifers in 1547 herds. At all ages Holstein-Friesian (F) heifers were heavier than Holstein-Friesian–Jersey crossbred (F × J) which were heavier than Jersey (J) heifers. Heterosis effects for LWT were greatest at nine months of age (3.6%) and least at 22 months of age (2.0%). The growth pattern differed, as evidenced by the regression coefficients of the Legendre polynomial. Growth was non-linear and heterosis effects were different throughout the growth period. Friesian, J and F × J heifers exhibited different growth patterns. These differences in growth pattern should be considered when formulating target LWTs and growth rates for a pasture-based system