Performance measurement: questions for tomorrow

Ever since Johnson and Kaplan (1987) published their seminal article performance measurement gained increasing popularity both in practice and research with over 3600 articles between 1994 and 1996. A précis of the literature on global and business trends predicts that the world is heading towards a networking era dominated by global autopoietic networks. A systematic review of the performance measurement literature concludes that although historically the performance measurement literature had tracked the global business trends our current state of knowledge on performance measurement is not complete and a number of fundamental questions remain unanswered, particularly in the context of future trends

From hard data to soft decision

It is impossible to create model of decision process, as we know nothing about the original decision process. Although it is possible to build models that can get us to the spaces where our fitness is strong enough. These models can contain hard data and soft information as well. In the background of the widely accepted solutions there are transformations of soft information into hard data. This leads us to the world of quantitative decision support. This step is very dangerous! The decision maker uses logic not arithmetic in his thinking process. DoctuS© Knowledge-Based System uses logic. The latest version is also capable of data mining. Using a clusteranalyzing algorithm it can transform the relations between hard data into soft information, which will be used for deduction in reasoning. The number of clusters is given by the user. The cluster-analyzing algorithm makes the clusters using learning example. When running the data mining the clusters remains unchanged and the new data will be transformed. The clusters can be handled using logic. For illustration we use an example of taking decision about location for a power plant

Learning capability : the effect of existing knowledge on learning

It has been observed that different people learn the same things in different ways - increasing their knowledge of the subject/domain uniquely. One plausible reason for this disparity in learning is the difference in the existing personal knowledge held in the particular area in which the knowledge increase happens. To understand this further, in this paper knowledge is modelled as a 'system of cognitive schemata', and knowledge increase as a process in this system; the effect of existing personal knowledge on knowledge increase is 'the Learning Capability'. Learning Capability is obtained in form of a function; although it is merely a representation making use of mathematical symbolism, not a calculable entity. The examination of the function tells us about the nature of learning capability. However, existing knowledge is only one factor affecting knowledge increase and thus one component of a more general model, which might additionally include talent, learning willingness, and attention

Cascade Failure in a Phase Model of Power Grids

We propose a phase model to study cascade failure in power grids composed of generators and loads. If the power demand is below a critical value, the model system of power grids maintains the standard frequency by feedback control. On the other hand, if the power demand exceeds the critical value, an electric failure occurs via step out (loss of synchronization) or voltage collapse. The two failures are incorporated as two removal rules of generator nodes and load nodes. We perform direct numerical simulation of the phase model on a scale-free network and compare the results with a mean-field approximation.Comment: 7 pages, 2 figure

Deep learning for brain metastasis detection and segmentation in longitudinal MRI data

Brain metastases occur frequently in patients with metastatic cancer. Early and accurate detection of brain metastases is very essential for treatment planning and prognosis in radiation therapy. To improve brain metastasis detection performance with deep learning, a custom detection loss called volume-level sensitivity-specificity (VSS) is proposed, which rates individual metastasis detection sensitivity and specificity in (sub-)volume levels. As sensitivity and precision are always a trade-off in a metastasis level, either a high sensitivity or a high precision can be achieved by adjusting the weights in the VSS loss without decline in dice score coefficient for segmented metastases. To reduce metastasis-like structures being detected as false positive metastases, a temporal prior volume is proposed as an additional input of DeepMedic. The modified network is called DeepMedic+ for distinction. Our proposed VSS loss improves the sensitivity of brain metastasis detection for DeepMedic, increasing the sensitivity from 85.3% to 97.5%. Alternatively, it improves the precision from 69.1% to 98.7%. Comparing DeepMedic+ with DeepMedic with the same VSS loss, 44.4% of the false positive metastases are reduced in the high sensitivity model and the precision reaches 99.6% for the high specificity model. The mean dice coefficient for all metastases is about 0.81. With the ensemble of the high sensitivity and high specificity models, on average only 1.5 false positive metastases per patient needs further check, while the majority of true positive metastases are confirmed. The ensemble learning is able to distinguish high confidence true positive metastases from metastases candidates that require special expert review or further follow-up, being particularly well-fit to the requirements of expert support in real clinical practice.Comment: Implementation is available to public at https://github.com/YixingHuang/DeepMedicPlu

Topochemical conversion of an imine-into a thiazole-linked covalent organic framework enabling real structure analysis

Stabilization of covalent organic frameworks (COFs) by post-synthetic locking strategies is a powerful tool to push the limits of COF utilization, which are imposed by the reversible COF linkage. Here we introduce a sulfur-assisted chemical conversion of a two-dimensional imine-linked COF into a thiazole-linked COF, with full retention of crystallinity and porosity. This post-synthetic modification entails significantly enhanced chemical and electron beam stability, enabling investigation of the real framework structure at a high level of detail. An in-depth study by electron diffraction and transmission electron microscopy reveals a myriad of previously unknown or unverified structural features such as grain boundaries and edge dislocations, which are likely generic to the in-plane structure of 2D COFs. The visualization of such real structural features is key to understand, design and control structure-property relationships in COFs, which can have major implications for adsorption, catalytic, and transport properties of such crystalline porous polymers

Paradoxes of creativity : examining the creative process through an antenarrative lens

Accounts of the creative process tend to be retrospective and implicitly ground the creative act within the person, the mind, the moment, the idea; in doing so, they often miss the larger sociomaterial qualities that can provide us with important insights about the social relationality and playfulness of the creative process. In this article, we examine the creative process through an antenarrative lens that we consider very useful for theorizing the creative process from a cultural and sociomaterial perspective. More specifically, we argue that ‘having an idea’ is a contextualized and embodied process that can be regarded as an antenarrative of the overall creative process. We also discuss how the paradoxical relation between the formative and sudden manifestations of the creative act can be understood through the notion of play

Functional Redundancy of Two Pax-Like Proteins in Transcriptional Activation of Cyst Wall Protein Genes in Giardia lamblia

The protozoan Giardia lamblia differentiates from a pathogenic trophozoite into an infectious cyst to survive outside of the host. During encystation, genes encoding cyst wall proteins (CWPs) are coordinately induced. Pax family transcription factors are involved in a variety of developmental processes in animals. Nine Pax proteins have been found to play an important role in tissue and organ development in humans. To understand the progression from primitive to more complex eukaryotic cells, we tried to identify putative pax genes in the G. lamblia genome and found two genes, pax1 and pax2, with limited similarity. We found that Pax1 may transactivate the encystation-induced cwp genes and interact with AT-rich initiatior elements that are essential for promoter activity and transcription start site selection. In this study, we further characterized Pax2 and found that, like Pax1, Pax2 was present in Giardia nuclei and it may specifically bind to the AT-rich initiator elements of the encystation-induced cwp1-3 and myb2 genes. Interestingly, overexpression of Pax2 increased the cwp1-3 and myb2 gene expression and cyst formation. Deletion of the C-terminal paired domain or mutation of the basic amino acids of the paired domain resulted in a decrease of nuclear localization, DNA-binding activity, and transactivation activity of Pax2. These results are similar to those found in the previous Pax1 study. In addition, the profiles of gene expression in the Pax2 and Pax1 overexpressing cells significantly overlap in the same direction and ERK1 associated complexes may phosphorylate Pax2 and Pax1, suggesting that Pax2 and Pax1 may be downstream components of a MAPK/ERK1 signaling pathway. Our results reveal functional redundancy between Pax2 and Pax1 in up-regulation of the key encystation-induced genes. These results illustrate functional redundancy of a gene family can occur in order to increase maintenance of important gene function in the protozoan organism G. lamblia