Boundary spanning in a for-profit research lab: An exploration of the interface between commerce and academe

In innovative industries, private-sector companies increasingly are participants in open communities of science and technology. To participate in the system of exchange in such communities, firms often publicly disclose what would otherwise remain private discoveries. In a quantitative case study of one firm in the biopharmaceutical sector, we explore the consequences of scientific publication-an instance of public disclosure-for a core set of activities within the firm. Specifically, we link publications to human capital management practices, showing that scientists' bonuses and the allocation of managerial attention are tied to individuals' publications. Using a unique electronic mail dataset, we find that researchers within the firm who author publications are much better connected to external (to the company) members of the scientific community. This result directly links publishing to current understandings of absorptive capacity. In an unanticipated finding, however, our analysis raises the possibility that the company's most prolific publishers begin to migrate to the periphery of the intra-firm social network, which may occur because these individuals' strong external relationships induce them to reorient their focus to a community of scientists beyond the firm's boundary.

Social Influence Given (Partially) Deliberate Matching: Career Imprints in the Creation of Academic Entrepreneurs

Actors often match with associates on a small set of dimensions that matter most for the particular relationship at hand. In so doing, they are exposed to unanticipated social influences because counterparts have more interests, attitudes, and preferences than would-be associates considered when they first chose to pair. This implies that some apparent social influences (those tied to the rationales for forming the relationship) are endogenous to the matching process, while others (those that are incidental to the formation of the relationship) may be conditionally exogenous, thus enabling causal estimation of peer effects. We illustrate this idea in a new dataset tracking the training and professional activities of academic biomedical scientists. In qualitative and quantitative analyses, we show that scientists match to their postdoctoral mentors based on two dominant factors, geography and scientific focus. They then adopt their advisers' orientations toward commercial science as evidenced by the transmission of patenting behavior, but they do not match on this dimension. We demonstrate this in two-stage models that adjust for the endogeneity of the matching process, using a modification of propensity score estimation and a sample selection correction with valid exclusion restrictions. Furthermore, we draw on qualitative accounts of the matching process recorded in oral histories of the career choices of the scientists in our data. All three methods-qualitative description, propensity score estimators, and those that tackle selection on unobservable factors-are potential approaches to establishing evidence of social influence in partially endogenous networks, and they may be especially persuasive in combination.

Exploiting Synergy Between Ontologies and Recommender Systems

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations. Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

Tracking Debris Shed by a Space-Shuttle Launch Vehicle

The DEBRIS software predicts the trajectories of debris particles shed by a space-shuttle launch vehicle during ascent, to aid in assessing potential harm to the space-shuttle orbiter and crew. The user specifies the location of release and other initial conditions for a debris particle. DEBRIS tracks the particle within an overset grid system by means of a computational fluid dynamics (CFD) simulation of the local flow field and a ballistic simulation that takes account of the mass of the particle and its aerodynamic properties in the flow field. The computed particle trajectory is stored in a file to be post-processed by other software for viewing and analyzing the trajectory. DEBRIS supplants a prior debris tracking code that took .15 minutes to calculate a single particle trajectory: DEBRIS can calculate 1,000 trajectories in .20 seconds on a desktop computer. Other improvements over the prior code include adaptive time-stepping to ensure accuracy, forcing at least one step per grid cell to ensure resolution of all CFD-resolved flow features, ability to simulate rebound of debris from surfaces, extensive error checking, a builtin suite of test cases, and dynamic allocation of memory

Exploiting synergy between ontologies and recommender systems

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations.Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

Acoustic characterization of crack damage evolution in sandstone deformed under conventional and true triaxial loading

We thank the Associate Editor, Michelle Cooke, and the reviewers, Ze'ev Reches and Yves Guéguen, for useful comments which helped to improve the manuscript. We thank J.G. Van Munster for providing access to the true triaxial apparatus at KSEPL and for technical support during the experimental program. We thank R. Pricci for assistance with technical drawings of the apparatus. This work was partly funded by NERC award NE/N002938/1 and by a NERC Doctoral Studentship, which we gratefully acknowledge. Supporting data are included in a supporting information file; any additional data may be obtained from J.B. (e-mail: [email protected]).Peer reviewedPublisher PD

System of farm cost accounting

The business farmer wishes to know how much he is making or losing on his business each year, how much he is making or losing on each crop or class of animals, and how he can improve his business so as to make more money. The function of farm cost accounting is to supply this information. Cost accounting for the farm is the same sort of work large manufacturing companies do to learn whether they are making a profit on their different products. The farmer wants to know whether his wheat pays, whether his cows pay, or his orchard. These are some of the questions a set of farm cost accounts will settle

Risk and protective factors for meningococcal disease in adolescents: matched cohort study

Objective: To examine biological and social risk factors for meningococcal disease in adolescents. Design: Prospective, population based, matched cohort study with controls matched for age and sex in 1:1 matching. Controls were sought from the general practitioner. Setting: Six contiguous regions of England, which represent some 65% of the country’s population. Participants: 15-19 year olds with meningococcal disease recruited at hospital admission in six regions (representing 65% of the population of England) from January 1999 to June 2000, and their matched controls. Methods: Blood samples and pernasal and throat swabs were taken from case patients at admission to hospital and from cases and matched controls at interview. Data on potential risk factors were gathered by confidential interview. Data were analysed by using univariate and multivariate conditional logistic regression. Results: 144 case control pairs were recruited (74 male (51%); median age 17.6). 114 cases (79%) were confirmed microbiologically. Significant independent risk factors for meningococcal disease were history of preceding illness (matched odds ratio 2.9, 95% confidence interval 1.4 to 5.9), intimate kissing with multiple partners (3.7, 1.7 to 8.1), being a university student (3.4, 1.2 to 10) and preterm birth (3.7, 1.0 to 13.5). Religious observance (0.09, 0.02 to 0.6) and meningococcal vaccination (0.12, 0.04 to 0.4) were associated with protection. Conclusions: Activities and events increasing risk for meningococcal disease in adolescence are different from in childhood. Students are at higher risk. Altering personal behaviours could moderate the risk. However, the development of further effective meningococcal vaccines remains a key public health priority

Overcoming the false-minima problem in direct methods: Structure determination of the packaging enzyme P4 from bacteriophage φ13

The problems encountered during the phasing and structure determination of the packaging enzyme P4 from bacteriophage φ13 using the anomalous signal from selenium in a single-wavelength anomalous dispersion experiment (SAD) are described. The oligomeric state of P4 in the virus is a hexamer (with sixfold rotational symmetry) and it crystallizes in space group C2, with four hexamers in the crystallographic asymmetric unit. Current state-of-the-art ab initio phasing software yielded solutions consisting of 96 atoms arranged as sixfold symmetric clusters of Se atoms. However, although these solutions showed high correlation coefficients indicative that the substructure had been solved, the resulting phases produced uninterpretable electron-density maps. Only after further analysis were correct solutions found (also of 96 atoms), leading to the eventual identification of the positions of 120 Se atoms. Here, it is demonstrated how the difficulties in finding a correct phase solution arise from an intricate false-minima problem. © 2005 International Union of Crystallography - all rights reserved