In Search of Corporate Renewal: How to Benefit from Corporate Venturing?

Despite the rapid change in today's business environment there are relatively few studies about corporate renewal. This study aims for its part at filling that research gap by studying the concepts of strategy, corporate renewal, innovation and corporate venturing. Its purpose is to enhance our understanding of how established companies operating in dynamic and global environment can benefit from their corporate venturing activities. The theoretical part approaches the research problem in corporate and venture levels. Firstly, it focuses on mapping the determinants of strategy and suggests using industry, location, resources, knowledge, structure and culture, market, technology and business model to assess the environment and using these determinants to optimize speed and magnitude of change.Secondly, it concludes that the choice of innovation strategy is dependent on the type and dimensions of innovation and suggests assessing market, technology, business model as well as novelty and complexity related to each of them for choosing an optimal context for developing innovations further. Thirdly, it directsattention on processes through which corporate renewal takes place. On corporate level these processes are identified as strategy formulation, strategy formation and strategy implementation. On the venture level the renewal processes are identified as learning, leveraging and nesting. The theoretical contribution of this study, the framework of strategic corporate venturing, joins corporate and venture level management issues together and concludes that strategy processes and linking processes are the mechanism through which continuous corporate renewaltakes place. The framework of strategic corporate venturing proposed by this study is a new way to illustrate the role of corporate venturing as a purposefullybuilt, different view of a company's business environment. The empirical part extended the framework by enhancing our understanding of the link between corporate renewal and corporate venturing in its real life environment in three Finnish companies: Metso, Nokia and TeliaSonera. Characterizing companies' environmentwith the determinants of strategy identified in this study provided a structured way to analyze their competitive position and renewal challenges that they arefacing. More importantly the case studies confirmed that a link between corporate renewal and corporate venturing exists and found out that the link is not as straight forward as indicated by the theory. Furthermore, the case studies enhanced the framework by indicating a sequence according to which the processes work. Firstly, the induced strategy processes strategy formulation and strategy implementation set the scene for corporate venturing context and management processes and leave strategy formation for the venture. Only after that can strategies formed by ventures come back to the corporate level - and if found viable in the corporate level be formalized through formulation and implementation. With the help of the framework of strategic corporate venturing the link between corporaterenewal and corporate venturing can be found and managed. The suggested response to the continuous need for change is continuous renewal i.e. institutionalizing corporate renewal in the strategy processes of the company. As far as benefiting from venturing is concerned the answer lies in deliberately managing venturing in a context different to the mainstream businesses and establishing efficientlinking processes to exploit the renewal potential of individual ventures.

Reporting of methodologic information on trial registries for quality assessment: a study of trial records retrieved from the WHO search portal

Background: Although randomized clinical trials (RCTs) are considered the gold standard of evidence, their reporting is often suboptimal. Trial registries have the potential to contribute important methodologic information for critical appraisal of study results. Methods and Findings: The objective of the study was to evaluate the reporting of key methodologic study characteristics in trial registries. We identified a random sample (n = 265) of actively recruiting RCTs using the World Health Organization International Clinical Trials Registry Platform (ICTRP) search portal in 2008. We assessed the reporting of relevant domains from the Cochrane Collaboration’s ‘Risk of bias’ tool and other key methodological aspects. Our primary outcomes were the proportion of registry records with adequate reporting of random sequence generation, allocation concealment, blinding, and trial outcomes. Two reviewers independently assessed each record. Weighted overall proportions in the ICTRP search portal for adequate reporting of sequence generation, allocation concealment, blinding (including and excluding open label RCT) and primary outcomes were 5.7% (95% CI 3.0–8.4%), 1.4% (0–2.8%), 41% (35–47%), 8.4% (4.1–13%), and 66% (60–72%), respectively. The proportion of adequately reported RCTs was higher for registries that used specific methodological fields for describing methods of randomization and allocation concealment compared to registries that did not. Concerning other key methodological aspects, weighted overall proportions of RCTs with adequately reported items were as follows: eligibility criteria (81%), secondary outcomes (46%), harm (5%) follow-up duration (62%), description of the interventions (53%) and sample size calculation (1%). Conclusions: Trial registries currently contain limited methodologic information about registered RCTs. In order to permit adequate critical appraisal of trial results reported in journals and registries, trial registries should consider requesting details on key RCT methods to complement journal publications. Full protocols remain the most comprehensive source of methodologic information and should be made publicly available.

In search for better pharmacological prophylaxis for acute mountain sickness: looking in other directions.

Despite decades of research, the exact pathogenic mechanisms underlying acute mountain sickness (AMS) are still poorly understood. This fact frustrates the search for novel pharmacological prophylaxis for AMS. The prevailing view is that AMS results from an insufficient physiological response to hypoxia and that prophylaxis should aim at stimulating the response. Starting off from the opposite hypothesis that AMS may be caused by an initial excessive response to hypoxia, we suggest that directly or indirectly blunting-specific parts of the response might provide promising research alternatives. This reasoning is based on the observations that (i) humans, once acclimatized, can climb Mt Everest experiencing arterial partial oxygen pressures (PaO2 ) as low as 25 mmHg without AMS symptoms; (ii) paradoxically, AMS usually develops at much higher PaO2 levels; and (iii) several biomarkers, suggesting initial activation of specific pathways at such PaO2 , are correlated with AMS. Apart from looking for substances that stimulate certain hypoxia triggered effects, such as the ventilatory response to hypoxia, we suggest to also investigate pharmacological means aiming at blunting certain other specific hypoxia-activated pathways, or stimulating their agonists, in the quest for better pharmacological prophylaxis for AMS.

CD103 marks a subset of human CD34(+)-derived langerin(+) dendritic cells that induce T-regulatory cells via indoleamine 2,3-dioxygenase-1.

Indoleamine 2,3-dioxygenase 1 (IDO1) is an immunosuppressive molecule expressed in some subsets of normal and neoplastic cells. Mature human dendritic cells (DCs) have been shown to express IDO1, but little is known about its expression and function during DC differentiation from bone marrow hematopoietic stem/progenitor cells (HSPCs). Here, we show that during in vitro differentiation along the myeloid DC lineage, CD34(+) HSPCs acquire IDO1 expression, which acts in a tolerogenic manner by inducing a population of fully functional CD4(+)CD25(+) FOXP3(+) T-regulatory cells. Phenotypically, CD1a(+)CD14(-) HPSC-derived DCs expressed IDO1, langerin, CD11b, and CD1c. Cell-sorting experiments demonstrated that IDO1 expression is found in a subset of CD1a(+)CD14(-)langerin(+) cells, expressing CD103, which is capable of inducing T-regulatory cells in an IDO1-dependent manner. In conclusion, DC differentiation from CD34(+) HSPCs results in the expression of a functionally active IDO1 protein in CD1a(+)langerin(+), CD103-expressing DCs. These data point toward IDO1 expression as part of a tolerogenic signature during DC development.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

KLF2 mutation is the most frequent somatic change in splenic marginal zone lymphoma and identifies a subset with distinct genotype.

To characterise the genetics of splenic marginal zone lymphoma (SMZL), we performed whole exome sequencing of 16 cases and identified novel recurrent inactivating mutations in Kruppel-like factor 2 (KLF2), a gene whose deficiency was previously shown to cause splenic marginal zone hyperplasia in mice. KLF2 mutation was found in 40 (42%) of 96 SMZLs, but rarely in other B-cell lymphomas. The majority of KLF2 mutations were frameshift indels or nonsense changes, with missense mutations clustered in the C-terminal zinc finger domains. Functional assays showed that these mutations inactivated the ability of KLF2 to suppress NF-κB activation by TLR, BCR, BAFFR and TNFR signalling. Further extensive investigations revealed common and distinct genetic changes between SMZL with and without KLF2 mutation. IGHV1-2 rearrangement and 7q deletion were primarily seen in SMZL with KLF2 mutation, while MYD88 and TP53 mutations were nearly exclusively found in those without KLF2 mutation. NOTCH2, TRAF3, TNFAIP3 and CARD11 mutations were observed in SMZL both with and without KLF2 mutation. Taken together, KLF2 mutation is the most common genetic change in SMZL and identifies a subset with a distinct genotype characterised by multi-genetic changes. These different genetic changes may deregulate various signalling pathways and generate cooperative oncogenic properties, thereby contributing to lymphomagenesis.

Anther culture properties of oat x wild red oat progenies and a search for RAPD markers associated with anther culture ability

Selostus: Ponsiviljeltävyys ja siihen liittyvät geenimerkit peltokauran ja susikauran risteytysjälkeläisissä

All-sky search algorithms for monochromatic signals in bar gravitational wave detector data

In this paper we design and develop several filtering strategies for the analysis of data generated by a resonant bar gravitational wave (GW) antenna, with the goal of assessing the presence (or absence) therein of long-duration monochromatic GW signals, as well as the eventual amplitude and frequency of the signals, within the sensitivity band of the detector. Such signals are most likely generated in the fast rotation of slightly asymmetric spinning stars. We develop practical procedures, together with a study of their statistical properties, which will provide us with useful information on the performance of each technique. The selection of candidate events will then be established according to threshold-crossing probabilities, based on the Neyman-Pearson criterion. In particular, it will be shown that our approach, based on phase estimation, presents a better signal-to-noise ratio than does pure spectral analysis, the most common approach.

Evolutionary computing in search-based software engineering

This master’s thesis aims to study and represent from literature how evolutionary algorithms are used to solve different search and optimisation problems in the area of software engineering. Evolutionary algorithms are methods, which imitate the natural evolution process. An artificial evolution process evaluates fitness of each individual, which are solution candidates. The next population of candidate solutions is formed by using the good properties of the current population by applying different mutation and crossover operations. Different kinds of evolutionary algorithm applications related to software engineering were searched in the literature. Applications were classified and represented. Also the necessary basics about evolutionary algorithms were presented. It was concluded, that majority of evolutionary algorithm applications related to software engineering were about software design or testing. For example, there were applications about classifying software production data, project scheduling, static task scheduling related to parallel computing, allocating modules to subsystems, N-version programming, test data generation and generating an integration test order. Many applications were experimental testing rather than ready for real production use. There were also some Computer Aided Software Engineering tools based on evolutionary algorithms.

Quest for Orthologs Entails Quest for Tree of Life: In Search of the Gene Stream.

Quest for Orthologs (QfO) is a community effort with the goal to improve and benchmark orthology predictions. As quality assessment assumes prior knowledge on species phylogenies, we investigated the congruency between existing species trees by comparing the relationships of 147 QfO reference organisms from six Tree of Life (ToL)/species tree projects: The National Center for Biotechnology Information (NCBI) taxonomy, Opentree of Life, the sequenced species/species ToL, the 16S ribosomal RNA (rRNA) database, and trees published by Ciccarelli et al. (Ciccarelli FD, et al. 2006. Toward automatic reconstruction of a highly resolved tree of life. Science 311:1283-1287) and by Huerta-Cepas et al. (Huerta-Cepas J, Marcet-Houben M, Gabaldon T. 2014. A nested phylogenetic reconstruction approach provides scalable resolution in the eukaryotic Tree Of Life. PeerJ PrePrints 2:223) Our study reveals that each species tree suggests a different phylogeny: 87 of the 146 (60%) possible splits of a dichotomous and rooted tree are congruent, while all other splits are incongruent in at least one of the species trees. Topological differences are observed not only at deep speciation events, but also within younger clades, such as Hominidae, Rodentia, Laurasiatheria, or rosids. The evolutionary relationships of 27 archaea and bacteria are highly inconsistent. By assessing 458,108 gene trees from 65 genomes, we show that consistent species topologies are more often supported by gene phylogenies than contradicting ones. The largest concordant species tree includes 77 of the QfO reference organisms at the most. Results are summarized in the form of a consensus ToL (http://swisstree.vital-it.ch/species_tree) that can serve different benchmarking purposes.

Trust region versus line search for computing the optical flow

We consider the numerical treatment of the optical flow problem by evaluating the performance of the trust region method versus the line search method. To the best of our knowledge, the trust region method is studied here for the first time for variational optical flow computation. Four different optical flow models are used to test the performance of the proposed algorithm combining linear and nonlinear data terms with quadratic and TV regularization. We show that trust region often performs better than line search; especially in the presence of non-linearity and non-convexity in the model.

Direct tumor recognition by a human CD4(+) T-cell subset potently mediates tumor growth inhibition and orchestrates anti-tumor immune responses.

Tumor antigen-specific CD4(+) T cells generally orchestrate and regulate immune cells to provide immune surveillance against malignancy. However, activation of antigen-specific CD4(+) T cells is restricted at local tumor sites where antigen-presenting cells (APCs) are frequently dysfunctional, which can cause rapid exhaustion of anti-tumor immune responses. Herein, we characterize anti-tumor effects of a unique human CD4(+) helper T-cell subset that directly recognizes the cytoplasmic tumor antigen, NY-ESO-1, presented by MHC class II on cancer cells. Upon direct recognition of cancer cells, tumor-recognizing CD4(+) T cells (TR-CD4) potently induced IFN-γ-dependent growth arrest in cancer cells. In addition, direct recognition of cancer cells triggers TR-CD4 to provide help to NY-ESO-1-specific CD8(+) T cells by enhancing cytotoxic activity, and improving viability and proliferation in the absence of APCs. Notably, the TR-CD4 either alone or in collaboration with CD8(+) T cells significantly inhibited tumor growth in vivo in a xenograft model. Finally, retroviral gene-engineering with T cell receptor (TCR) derived from TR-CD4 produced large numbers of functional TR-CD4. These observations provide mechanistic insights into the role of TR-CD4 in tumor immunity, and suggest that approaches to utilize TR-CD4 will augment anti-tumor immune responses for durable therapeutic efficacy in cancer patients.

Search Interfaces on the Web: Querying and Characterizing

Current-day web search engines (e.g., Google) do not crawl and index a significant portion of theWeb and, hence, web users relying on search engines only are unable to discover and access a large amount of information from the non-indexable part of the Web. Specifically, dynamic pages generated based on parameters provided by a user via web search forms (or search interfaces) are not indexed by search engines and cannot be found in searchers’ results. Such search interfaces provide web users with an online access to myriads of databases on the Web. In order to obtain some information from a web database of interest, a user issues his/her query by specifying query terms in a search form and receives the query results, a set of dynamic pages that embed required information from a database. At the same time, issuing a query via an arbitrary search interface is an extremely complex task for any kind of automatic agents including web crawlers, which, at least up to the present day, do not even attempt to pass through web forms on a large scale. In this thesis, our primary and key object of study is a huge portion of the Web (hereafter referred as the deep Web) hidden behind web search interfaces. We concentrate on three classes of problems around the deep Web: characterization of deep Web, finding and classifying deep web resources, and querying web databases. Characterizing deep Web: Though the term deep Web was coined in 2000, which is sufficiently long ago for any web-related concept/technology, we still do not know many important characteristics of the deep Web. Another matter of concern is that surveys of the deep Web existing so far are predominantly based on study of deep web sites in English. One can then expect that findings from these surveys may be biased, especially owing to a steady increase in non-English web content. In this way, surveying of national segments of the deep Web is of interest not only to national communities but to the whole web community as well. In this thesis, we propose two new methods for estimating the main parameters of deep Web. We use the suggested methods to estimate the scale of one specific national segment of the Web and report our findings. We also build and make publicly available a dataset describing more than 200 web databases from the national segment of the Web. Finding deep web resources: The deep Web has been growing at a very fast pace. It has been estimated that there are hundred thousands of deep web sites. Due to the huge volume of information in the deep Web, there has been a significant interest to approaches that allow users and computer applications to leverage this information. Most approaches assumed that search interfaces to web databases of interest are already discovered and known to query systems. However, such assumptions do not hold true mostly because of the large scale of the deep Web – indeed, for any given domain of interest there are too many web databases with relevant content. Thus, the ability to locate search interfaces to web databases becomes a key requirement for any application accessing the deep Web. In this thesis, we describe the architecture of the I-Crawler, a system for finding and classifying search interfaces. Specifically, the I-Crawler is intentionally designed to be used in deepWeb characterization studies and for constructing directories of deep web resources. Unlike almost all other approaches to the deep Web existing so far, the I-Crawler is able to recognize and analyze JavaScript-rich and non-HTML searchable forms. Querying web databases: Retrieving information by filling out web search forms is a typical task for a web user. This is all the more so as interfaces of conventional search engines are also web forms. At present, a user needs to manually provide input values to search interfaces and then extract required data from the pages with results. The manual filling out forms is not feasible and cumbersome in cases of complex queries but such kind of queries are essential for many web searches especially in the area of e-commerce. In this way, the automation of querying and retrieving data behind search interfaces is desirable and essential for such tasks as building domain-independent deep web crawlers and automated web agents, searching for domain-specific information (vertical search engines), and for extraction and integration of information from various deep web resources. We present a data model for representing search interfaces and discuss techniques for extracting field labels, client-side scripts and structured data from HTML pages. We also describe a representation of result pages and discuss how to extract and store results of form queries. Besides, we present a user-friendly and expressive form query language that allows one to retrieve information behind search interfaces and extract useful data from the result pages based on specified conditions. We implement a prototype system for querying web databases and describe its architecture and components design.

Question Waves: A multicast query routing algorithm for social search

This paper describes Question Waves, an algorithm that can be applied to social search protocols, such as Asknext or Sixearch. In this model, the queries are propagated through the social network, with faster propagation through more trustable acquaintances. Question Waves uses local information to make decisions and obtain an answer ranking. With Question Waves, the answers that arrive first are the most likely to be relevant, and we computed the correlation of answer relevance with the order of arrival to demonstrate this result. We obtained correlations equivalent to the heuristics that use global knowledge, such as profile similarity among users or the expertise value of an agent. Because Question Waves is compatible with the social search protocol Asknext, it is possible to stop a search when enough relevant answers have been found; additionally, stopping the search early only introduces a minimal risk of not obtaining the best possible answer. Furthermore, Question Waves does not require a re-ranking algorithm because the results arrive sorted