Language and Letters of the Bluestocking Network : Sociolinguistic Issues in Eighteenth Century Epistolary English

This study deals with language change and variation in the correspondence of the eighteenth-century Bluestocking circle, a social network which provided learned men and women with an informal environment for the pursuit of scholarly entertainment. Elizabeth Montagu (1718 1800), a notable social hostess and a Shakespearean scholar, was one of their key figures. The study presents the reconstruction of Elizabeth Montagu s social networks from her youth to her later years with a special focus on the Bluestocking circle, and linguistic research on private correspondence between Montagu and her Bluestocking friends and family members between the years 1738 1778. The epistolary language use is investigated using the methods and frameworks of corpus linguistics, historical sociolinguistics, and social network analysis. The approach is diachronic and concerns real-time language change. The research is based on a selection of manuscript letters which I have edited and compiled into an electronic corpus (Bluestocking Corpus). I have also devised a network strength scale in order to quantify the strength of network ties and to compare the results of the linguistic research with the network analysis. The studies range from the reconstruction and analysis of Elizabeth Montagu s most prominent social networks to the analysis of changing morphosyntactic features and spelling variation in Montagu s and her network members correspondence. The linguistic studies look at the use of the progressive construction, preposition stranding and pied piping, and spelling variation in terms of preterite and past participle endings in the regular paradigm (-ed, - d, -d, - t, -t) and full / contracted spellings of auxiliary verbs. The results are analysed in terms of social network membership, sociolinguistic variables of the correspondents, and, when relevant, aspects of eighteenth-century linguistic prescriptivism. The studies showed a slight diachronic increase in the use of the progressive, a significant decrease of the stigmatised preposition stranding and increase of pied piping, and relatively informal but socially controlled epistolary spelling. Certain significant changes in Elizabeth Montagu s language use over the years could be attributed to her increasingly prominent social standing and the changes in her social networks, and the strength of ties correlated strongly with the use of the progressive in the Bluestocking Corpus. Gender, social rank, and register in terms of kinship/friendship had a significant influence in language use, and an effect of prescriptivism could also be detected. Elizabeth Montagu s network ties resulted in language variation in terms of network membership, her own position in a given network, and the social factors that controlled eighteenth-century interaction. When all the network ties are strong, linguistic variation seems to be essentially linked to the social variables of the informants.

New insights from a fixed-point analysis of single cell IEEE 802.11 WLANs

We study a fixed-point formalization of the well-known analysis of Bianchi. We provide a significant simplification and generalization of the analysis. In this more general framework, the fixed-point solution and performance measures resulting from it are studied. Uniqueness of the fixed point is established. Simple and general throughput formulas are provided. It is shown that the throughput of any flow will be bounded by the one with the smallest transmission rate. The aggregate throughput is bounded by the reciprocal of the harmonic mean of the transmission rates. In an asymptotic regime with a large number of nodes, explicit formulas for the collision probability, the aggregate attempt rate, and the aggregate throughput are provided. The results from the analysis are compared with ns2 simulations and also with an exact Markov model of the backoff process. It is shown how the saturated network analysis can be used to obtain TCP transfer throughputs in some cases.

Topological analysis of general linear networks

A new method of network analysis, a generalization in several different senses of existing methods and applicable to all networks for which a branch-admittance (or impedance) matrix can be formed, is presented. The treatment of network determinants is very general and essentially four terminal rather than three terminal, and leads to simple expressions based on trees of a simple graph associated with the network and matrix, and involving products of low-order, usually(2 times 2)determinants of tree-branch admittances, in addition to tree-branch products as in existing methods. By comparison with existing methods, the total number of trees and of tree pairs is usually considerably reduced, and this fact, together with an easy method of tree-pair sign determination which is also presented, makes the new method simpler in general. The method can be very easily adapted, by the use of infinite parameters, to accommodate ideal transformers, operational amplifiers, and other forms of network constraint; in fact, is thought to be applicable to all linear networks.

Network properties of protein-decoy structures

Convergence of the vast sequence space of proteins into a highly restricted fold/conformational space suggests a simple yet unique underlying mechanism of protein folding that has been the subject of much debate in the last several decades. One of the major challenges related to the understanding of protein folding or in silico protein structure prediction is the discrimination of non-native structures/decoys from the native structure. Applications of knowledge-based potentials to attain this goal have been extensively reported in the literature. Also, scoring functions based on accessible surface area and amino acid neighbourhood considerations were used in discriminating the decoys from native structures. In this article, we have explored the potential of protein structure network (PSN) parameters to validate the native proteins against a large number of decoy structures generated by diverse methods. We are guided by two principles: (a) the PSNs capture the local properties from a global perspective and (b) inclusion of non-covalent interactions, at all-atom level, including the side-chain atoms, in the network construction accommodates the sequence dependent features. Several network parameters such as the size of the largest cluster, community size, clustering coefficient are evaluated and scored on the basis of the rank of the native structures and the Z-scores. The network analysis of decoy structures highlights the importance of the global properties contributing to the uniqueness of native structures. The analysis also exhibits that the network parameters can be used as metrics to identify the native structures and filter out non-native structures/decoys in a large number of data-sets; thus also has a potential to be used in the protein `structure prediction' problem.

An automated approach to network features of protein structure ensembles

Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of 2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.

Exploring Technology Evolution Using Patent Classification: A Case of Cochlear Implant Technology Patents

Understanding technology evolution through periodic landscaping is an important stage of strategic planning in R&D Management. In fields like that of healthcare, where the initial R&D investment is huge and good medical product serve patients better, these activities become crucial. Approximately five percentage of the world population has hearing disabilities. Current hearing aid products meet less than ten percent of the global needs. Patent data and classifications on cochlear implants from 1977-2010, show the landscapes and evolution in the area of such implant. We attempt to highlight emergence and disappearance of patent classes over period of time showing variations in cochlear implant technologies. A network analysis technique is used to explore and capture technology evolution in patent classes showing what emerged or disappeared over time. Dominant classes are identified. The sporadic influence of university research in cochlear implants is also discussed.

Complexity of planning in design

Planning in design processes is modeled in terms of connectivities between product developments. Each product development comprises a network of processes. Similarity between processes is analysed by a layered classification ranging from common components to shared design knowledge. The connectivities between products arising from similarities among products are represented by a multidimensional network. Design planning is described by flows or 'traffic' on this network which represents a structural model of complexity. Comparison is made with information based measures of the complexity of designs and processes.

Finite element analysis of compressor disc heat transfer using the transient conduction method with sparse boundary collocation points

Surface temperature measurements from two discs of a gas turbine compressor rig are used as boundary conditions for the transient conduction solution (inverse heat transfer analysis). The disc geometry is complex, and so the finite element method is used. There are often large radial temperature gradients on the discs, and the equations are therefore solved taking into account the dependence of thermal conductivity on temperature. The solution technique also makes use of a multigrid algorithm to reduce the solution time. This is particularly important since a large amount of data must be analyzed to obtain correlations of the heat transfer. The finite element grid is also used for a network analysis to calculate the radiant heat transfer in the cavity formed between the two compressor discs. The work discussed here proved particularly challenging as the disc temperatures were only measured at four different radial locations. Four methods of surface temperature interpolation are examined, together with their effect on the local heat fluxes. It is found that the choice of interpolation method depends on the available number of data points. Bessel interpolation gives the best results for four data points, whereas cubic splines are preferred when there are considerably more data points. The results from the analysis of the compressor rig data show that the heat transfer near the disc inner radius appears to be influenced by the central throughflow. However, for larger radii, the heat transfer from the discs and peripheral shroud is found to be consistent with that of a buoyancy-induced flow.

Ulva and Enteromorpha (Ulvaceae, Chlorophyta) from two sides of the Yellow Sea: analysis of nuclear rDNA ITS and plastid rbcL sequence data

Ulvacean green seaweeds are common worldwide; they formed massive green tides in the Yellow Sea in recent years, which caused marine ecological problems as well as a social issue. We investigated two major genera of the Ulvaceae, Ulva and Enteromorpha, and collected the plastid rbcL and nuclear ITS sequences of specimens of the genera in two sides of the Yellow Sea and analyzed them. Phylogenetic trees of rbcL data show the occurrence of five species of Enteromorpha (E. compressa, E. flexuosa, E. intestinalis, E. linza and E. prolifera) and three species of Ulva (U. pertusa, U. rigida and U. ohnoi). However, we found U. ohnoi, which is known as a subtropical to tropical species, at two sites on Jeju Island, Korea. Four ribotypes in partial sequences of 5.8S rDNA and ITS2 from E. compressa were also found. Ribotype network analysis revealed that the common ribotype, occurring in China, Korea and Europe, is connected with ribotypes from Europe and China/Japan. Although samples of the same species were collected from both sides of the Yellow Sea, intraspecific genetic polymorphism of each species was low among samples collected worldwide.

Safe Compositional Network Sketches: NetSketch Tool Implementation

Numerous problems exist that can be modeled as traffic through a network in which constraints exist to regulate flow. Vehicular road travel, computer networks, and cloud based resource distribution, among others all have natural representations in this manner. As these networks grow in size and/or complexity, analysis and certification of the safety invariants becomes increasingly costly. The NetSketch formalism introduces a lightweight verification framework that allows for greater scalability than traditional analysis methods. The NetSketch tool was developed to provide the power of this formalism in an easy to use and intuitive user interface.

Planning the deployment of fault-tolerant wireless sensor networks

Since Wireless Sensor Networks (WSNs) are subject to failures, fault-tolerance becomes an important requirement for many WSN applications. Fault-tolerance can be enabled in different areas of WSN design and operation, including the Medium Access Control (MAC) layer and the initial topology design. To be robust to failures, a MAC protocol must be able to adapt to traffic fluctuations and topology dynamics. We design ER-MAC that can switch from energy-efficient operation in normal monitoring to reliable and fast delivery for emergency monitoring, and vice versa. It also can prioritise high priority packets and guarantee fair packet deliveries from all sensor nodes. Topology design supports fault-tolerance by ensuring that there are alternative acceptable routes to data sinks when failures occur. We provide solutions for four topology planning problems: Additional Relay Placement (ARP), Additional Backup Placement (ABP), Multiple Sink Placement (MSP), and Multiple Sink and Relay Placement (MSRP). Our solutions use a local search technique based on Greedy Randomized Adaptive Search Procedures (GRASP). GRASP-ARP deploys relays for (k,l)-sink-connectivity, where each sensor node must have k vertex-disjoint paths of length ≤ l. To count how many disjoint paths a node has, we propose Counting-Paths. GRASP-ABP deploys fewer relays than GRASP-ARP by focusing only on the most important nodes – those whose failure has the worst effect. To identify such nodes, we define Length-constrained Connectivity and Rerouting Centrality (l-CRC). Greedy-MSP and GRASP-MSP place minimal cost sinks to ensure that each sensor node in the network is double-covered, i.e. has two length-bounded paths to two sinks. Greedy-MSRP and GRASP-MSRP deploy sinks and relays with minimal cost to make the network double-covered and non-critical, i.e. all sensor nodes must have length-bounded alternative paths to sinks when an arbitrary sensor node fails. We then evaluate the fault-tolerance of each topology in data gathering simulations using ER-MAC.

De la cooperativa agroalimentaria a la "learning netchain". Hacia un planteamiento teorico interorganizativo e interpersonal

Se propone un planteamiento teórico/conceptual para determinar si las relaciones interorganizativas e interpersonales de la netchain de las cooperativas agroalimentarias evolucionan hacia una learning netchain. Las propuestas del trabajo muestran que el mayor grado de asociacionismo y la mayor cooperación/colaboración vertical a lo largo de la cadena están positivamente relacionados con la posición horizontal de la empresa focal más cercana del consumidor final. Esto requiere una planificación y una resolución de problemas de manera conjunta, lo que está positivamente relacionado con el mayor flujo y diversidad de la información/conocimiento obtenido y diseminado a lo largo de la netchain. Al mismo tiempo se necesita desarrollar un contexto social en el que fluya la información/conocimiento y las nuevas ideas de manera informal y esto se logra con redes personales y, principalmente, profesionales y con redes internas y, principalmente, externas. Todo esto permitirá una mayor satisfacción de los socios de la cooperativa agroalimentaria y de sus distribuidores y una mayor intensidad en I+D, convirtiéndose la netchain de la cooperativa agroalimentaria, así, en una learning netchain.

Recent advances in the analysis of behavioural organization and interpretation as indicators of animal welfare

While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify 'hidden' aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.

The discursive turn in policy analysis and the validation of policy stories

This paper is concerned with the language of policy documents in the field of health care, and how ‘readings’ of such documents might be validated in the context of a narrative analysis. The substantive focus is on a comparative study of UK health policy documents (N=20) as produced by the various assemblies, governments and executives of England, Scotland, Wales and Northern Ireland during the period 2000-2009. Following an identification of some key characteristics of narrative structure the authors indicate how text-mining strategies allied with features of semantic and network analysis can be used to unravel the basic elements of policy stories and to facilitate the presentation of data in such a way that readers can verify the strengths (and weaknesses) of any given analysis – with regard to claims concerning, say, the presence, absence, or relative importance of key ideas and concepts. Readers can also ‘see’ how the different components of any one story might fit together, and to get a sense of what has been excluded from the narrative as well as what has been included, and thereby assess the reliability and validity of interpretations that have been placed upon the data.

Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses

BACKGROUND:

We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq.

13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03).

Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.