When sharing becomes a liability: An intellectual capital approach to describing the dichotomy of knowledge protection versus sharing in intra- and interorganizational relationships

The tension created when companies are collaborating with competitors – sometimes termed co-opetition - has been subject of research within the network approach. As companies are collaborating with competitors, they need to simultaneously share and protect knowledge. The opportunistic behavior and learning intent of the partner may be underestimated, and collaboration may involve significant risks of loss of competitive edge. Contrastingly, the central tenet within the Intellectual Capital approach is that knowledge grows as it flows. The person sharing does not lose the knowledge and therefore knowledge has doubled from a company’s point of view. Value is created through the interplay of knowledge flows between and within three forms of intellectual capital: human, structural and relational capital. These are the points of departure for the research conducted in this thesis. The thesis investigates the tension between collaboration and competition through an Intellectual Capital lens, by identifying the actions taken to share and protect knowledge in interorganizational collaborative relationships. More specifically, it explores the tension in knowledge flows aimed at protecting and sharing knowledge, and their effect on the value creation of a company. It is assumed, that as two companies work closely together, the collaborative relationship becomes intertwined between the two partners and the intellectual capital flows of both companies are affected. The research finds that companies commonly protect knowledge also in close and long-term collaborative relationships. The knowledge flows identified are both collaborative and protective, with the result that they sometimes are counteracting and neutralize each other. The thesis contributes to the intellectual capital approach by expanding the understanding of knowledge protection in interorganizational relationships in three ways. First, departing from the research on co-opetition it shifts the focus from the internal view of the company as a repository of intellectual capital onto the collaborative relationships between competing companies. Second, instead of the traditional collaborative and sharing point of departure, it takes a competitive and protective perspective. Third, it identifies the intellectual capital flows as assets or liabilities depending on their effect on the value creation of the company. The actions taken to protect knowledge in an interorganizational relationship may decrease the value created in the company, which would make them liabilities.

The Organisation of Policy Meets the Commercialisation of Sex - Global Linkages, Policies, Technologies

During recent years the commercialisation of sex has increased and intensified both locally and globally. This thesis explores the commercialisation of bodies, sex and sexualities, particularly the sex trade, and the impact of rapidly evolving information and communication technologies on this globalising trade. The main focus of this work is on the policies, discourses and policy developments in the area especially in the Finnish context. The study is based on multidisciplinary theoretical sources through which the framework of multiple linkages relevant to the commercialisation of sex is conceptualised. The sex trade functions through a web of intersecting linkages of a substantive, economic, organisational, temporal, spatial, cultural, technological, as well as of legislative and policy nature. This framework of linkages forms the basis for the analysis of the main empirical data, namely qualitative interviews with thirty key managers and professionals, who are responsible for the preparation and implementation of policies on commercial sex. In addition, the thesis addresses the policies and policy practices on the sex trade through the analysis of national and international policy instruments. In addition to analysing the processes of the commercialisation of sex and its effects, the study also discusses their further implications for organisational policy-making, research, and society more generally. The thesis thus seeks to contribute to practice, research and theory on gender, management and organisations.

The Impact of Readily Detected- and Underlying Attributes on Social Integration in Cross-Cultural Settings

The benefits and drawbacks of homogeneity and heterogeneity have been debated at length. Whereas some researchers assert that heterogeneity is beneficial for groups that are engaged in complex problem solving, the other researchers emphasize the potential costs associated with diversity. The inconsistency is a result of the incomplete measurement of diversity and focus one or two types of diversity. Most research concentrates on the readily detected/visible characteristics, making the assumption that such characteristics are related to underlying attributes (e.g., attitudes and values). In many cases, the demographic characteristics do not covary perfectly with the psychological attributes. Thus both types of attributes need to be utilized to fully understand the impact of diversity. The present research with four essays takes into account both types of attributes and tests their impact on social integration in cross-cultural settings. The results indicate that: (1) readily detectable- and underlying attributes are not related; (2) diversity has overall a negative impact on social integration; (3) socio-cultural context potentially influences the salience of diversity; and (4) diversity and social integration influences the formation of social cognition in form of transactive memory directories. The limits of research and managerial implications are discussed.

Generation of parabolic trajectories for current error space phasor similar to an SVPWM controller for control of switching frequency variation in current hysteresis PWM controlled IM drives

Switching frequency variation over a fundamental period is a major problem associated with hysteresis controller based VSI fed IM drives. This paper describes a novel concept of generating parabolic trajectories for current error space phasor for controlling the switching frequency variation in the hysteresis controller based two-level inverter fed IM drives. A generalized algorithm is developed to determine unique set of parabolic trajectories for different speeds of operation for any given IM load. Proposed hysteresis controller provides the switching frequency spectrum of inverter output voltage, similar to that of the constant switching frequency VC-SVPWM based IM drive. The scheme is extensively simulated and experimentally verified on a 3.7 kW IM drive for steady state and transient performance.

Purification and characterization of an alpha-D-glucuronidase from a thermophilic fungus, Thermoascus aurantiacus

An alpha-D-glucuronidase was purified from the culture filtrates of Thermoascus aurantiacus. A simple colorimetric method for its assay is reported. The enzyme is a single polypeptide chain with a molecular weight of 118,000. It acts optimally at pH 4.5. It shows maximum activity at 65 degrees C. The t 1/2 at 70 degrees C was 40 min. It specifically cleaved the alpha-(1----2) linkage between 4-O-methyl-alpha-D-glucuronic acid and the xylose residue in xylan and several glucurono-xylooligosaccharides.

Comparative study on damage identification from lso-Eigen-Value-Change contours and smeared damage model

The paper proposes two methodologies for damage identification from measured natural frequencies of a contiguously damaged reinforced concrete beam, idealised with distributed damage model. The first method identifies damage from Iso-Eigen-Value-Change contours, plotted between pairs of different frequencies. The performance of the method is checked for a wide variation of damage positions and extents. The method is also extended to a discrete structure in the form of a five-storied shear building and the simplicity of the method is demonstrated. The second method is through smeared damage model, where the damage is assumed constant for different segments of the beam and the lengths and centres of these segments are the known inputs. First-order perturbation method is used to derive the relevant expressions. Both these methods are based on distributed damage models and have been checked with experimental program on simply supported reinforced concrete beams, subjected to different stages of symmetric and un-symmetric damages. The results of the experiments are encouraging and show that both the methods can be adopted together in a damage identification scenario.

sRNAscanner: A Computational Tool for Intergenic Small RNA Detection in Bacterial Genomes

Background:Bacterial non-coding small RNAs (sRNAs) have attracted considerable attention due to their ubiquitous nature and contribution to numerous cellular processes including survival, adaptation and pathogenesis. Existing computational approaches for identifying bacterial sRNAs demonstrate varying levels of success and there remains considerable room for improvement. Methodology/Principal Findings: Here we have proposed a transcriptional signal-based computational method to identify intergenic sRNA transcriptional units (TUs) in completely sequenced bacterial genomes. Our sRNAscanner tool uses position weight matrices derived from experimentally defined E. coli K-12 MG1655 sRNA promoter and rho-independent terminator signals to identify intergenic sRNA TUs through sliding window based genome scans. Analysis of genomes representative of twelve species suggested that sRNAscanner demonstrated equivalent sensitivity to sRNAPredict2, the best performing bioinformatics tool available presently. However, each algorithm yielded substantial numbers of known and uncharacterized hits that were unique to one or the other tool only. sRNAscanner identified 118 novel putative intergenic sRNA genes in Salmonella enterica Typhimurium LT2, none of which were flagged by sRNAPredict2. Candidate sRNA locations were compared with available deep sequencing libraries derived from Hfq-co-immunoprecipitated RNA purified from a second Typhimurium strain (Sittka et al. (2008) PLoS Genetics 4: e1000163). Sixteen potential novel sRNAs computationally predicted and detected in deep sequencing libraries were selected for experimental validation by Northern analysis using total RNA isolated from bacteria grown under eleven different growth conditions. RNA bands of expected sizes were detected in Northern blots for six of the examined candidates. Furthermore, the 5'-ends of these six Northern-supported sRNA candidates were successfully mapped using 5'-RACE analysis. Conclusions/Significance: We have developed, computationally examined and experimentally validated the sRNAscanner algorithm. Data derived from this study has successfully identified six novel S. Typhimurium sRNA genes. In addition, the computational specificity analysis we have undertaken suggests that similar to 40% of sRNAscanner hits with high cumulative sum of scores represent genuine, undiscovered sRNA genes. Collectively, these data strongly support the utility of sRNAscanner and offer a glimpse of its potential to reveal large numbers of sRNA genes that have to date defied identification. sRNAscanner is available from: http://bicmku.in:8081/sRNAscanner or http://cluster.physics.iisc.ernet.in/sRNAscanner/.

Antibodies raised against denatured DNA bind to double-stranded DNA

Antibodies raised against denatured DNA complexed with methylated bovine serum albumin have been reported to react with ssDNA but not with dsDNA. Using a highly sensitive avidin-biotin microELISA, we report that such antibodies also bind to dsDNA. Antibodies which reacted with ssDNA and dsDNA were found to be IgG type. The antibodies did not react with tRNA and rRNA. The binding of antibodies to dsDNA was partially inhibited dy individual deoxyribonucleotides. ssDNA as well as dsDNA inhibited the binding of antibodies to dsDNA. The binding of these antibodies to supercoiled and relaxed forms of pBR322 DNA was demonstrated by gel retardation assay. The cross-reaction with ssDNA was observed even after affinity purification on native DNA-cellulose. The antibodies were also shown to bind to poly(dA-dT)·poly(dA-dT)

Reducing the babel in plant volatile communication: using the forest to see the trees

While plants of a single species emit a diversity of volatile organic compounds (VOCs) to attract or repel interacting organisms, these specific messages may be lost in the midst of the hundreds of VOCs produced by sympatric plants of different species, many of which may have no signal content. Receivers must be able to reduce the babel or noise in these VOCs in order to correctly identify the message. For chemical ecologists faced with vast amounts of data on volatile signatures of plants in different ecological contexts, it is imperative to employ accurate methods of classifying messages, so that suitable bioassays may then be designed to understand message content. We demonstrate the utility of `Random Forests' (RF), a machine-learning algorithm, for the task of classifying volatile signatures and choosing the minimum set of volatiles for accurate discrimination, using datam from sympatric Ficus species as a case study. We demonstrate the advantages of RF over conventional classification methods such as principal component analysis (PCA), as well as data-mining algorithms such as support vector machines (SVM), diagonal linear discriminant analysis (DLDA) and k-nearest neighbour (KNN) analysis. We show why a tree-building method such as RF, which is increasingly being used by the bioinformatics, food technology and medical community, is particularly advantageous for the study of plant communication using volatiles, dealing, as it must, with abundant noise.