INCORPORATING KNOWLEDGE BUILDING IN REAL OPTIONS ANALYSIS OF TECHNOLOGY PROJECT INVESTMENT

Real options theory has provided a useful framework for technology investment decision making. Researchers in this area have emphasized the importance of considering the option-like characteristics of IT investment projects. However, unlike financial options, investment in IT projects is typically irreversible: such investment cannot be recovered for other purposes without very costly rework. The objective of our work is to study the effects of knowledge building on the valuation of real options by using a continuous-time stochastic model. To our knowledge, this is the first model that formally builds a linkage between proactive learning and investment cost and examines the consequences of this linkage on the management of real options. Our main finding is that knowledge building can expedite the adoption of new technology and significantly enhance the value of technology options

Real Options and Software Upgrades: An Economic Analysis

This work extends earlier work on software upgrades as well as research on real options and IT investment. We consider a two-period model with one software provider who develops and releases a software product to the market. The result shows that the profit from the upgrade policy increases when the market size uncertainty increases. The option value of upgrade is higher when there is more market uncertainty. Also, the value of investing in design effort is more when the development cost is low

Permeation Mechanism of Potassium Ions through the Large Conductance Ca2+-Activated Potassium Channel

The permeation of the potassium ion (K+) through the selectivity filter (SF) of the large conductance Ca2+-activated potassium (Slo1) channel remains an interesting question to study. Although the mode of K+ entering and leaving the SF has been revealed, the mechanism of K+ passing through the SF is still not clear. In the present study, the pattern of K+ permeation through the SF is investigated by chemical computation and data mining based on the molecular structure of Slo1 from Aplysia californica. Both bond configurations and the free energy of K+s inside the SF was studied using Discovery Studio software. The results suggested that, to accommodate increasing energy levels and to tolerate more K+s, 4-fold symmetric subunits of SF can only move at one direction that is perpendicular to the center axis. In addition, two configurations of chemical bonds between K+s and the SF are usually employed including the chelate configuration under low free energy and the complex configuration under high free energy conditions. Moreover, three patterns of bond configurations for multiple K+s within the SF are used to accommodate the energetic changes of the SF, and each pattern is composed of one or two subconformations. These findings likely resulted from the evolutionary optimization of the protein function of Slo1. The specific conductance and the voltage-gating of the Slo1 channel can be reinterpreted with the permeation mechanism of K+s found in the current study. The permeation mechanism of K+s through the SF can be used to understand the interaction between various toxins and the Slo1 channel, and can be employed to develop new drugs targeting relevant ion channels

Information Security Investment with Different Information Types: A Two-Firm Analysis

We analyze information security investment decisions by two firms that possess imperfectly substitutable information assets. Information assets are imperfectly substitutable if information at each firm is valuable and becomes more valuable when combined. When compared to optimal investment decisions made by a central planner, we find diametrically opposite results in the case where these decisions are made independently: substitutable assets lead to an “arms race” in which both firms over-invest whereas complementary assets lead to under-provision of “public goods” in which both firms under-invest. We also find that firms with highly substitutable information assets may not necessarily increase the amount of security investment in a centralized investment environment as the intensity of the deflected cross traffic increases

Mining the Virgin Land of Neurotoxicology: A Novel Paradigm of Neurotoxic Peptides Action on Glycosylated Voltage-Gated Sodium Channels

Voltage-gated sodium channels (VGSCs) are important membrane protein carrying on the molecular basis for action potentials (AP) in neuronal firings. Even though the structure-function studies were the most pursued spots, the posttranslation modification processes, such as glycosylation, phosphorylation, and alternative splicing associating with channel functions captured less eyesights. The accumulative research suggested an interaction between the sialic acids chains and ion-permeable pores, giving rise to subtle but significant impacts on channel gating. Sodium channel-specific neurotoxic toxins, a family of long-chain polypeptides originated from venomous animals, are found to potentially share the binding sites adjacent to glycosylated region on VGSCs. Thus, an interaction between toxin and glycosylated VGSC might hopefully join the campaign to approach the role of glycosylation in modulating VGSCs-involved neuronal network activity. This paper will cover the state-of-the-art advances of researches on glycosylation-mediated VGSCs function and the possible underlying mechanisms of interactions between toxin and glycosylated VGSCs, which may therefore, fulfill the knowledge in identifying the pharmacological targets and therapeutic values of VGSCs

Convolutional neural network application for supply–demand matching in Zhuang ethnic clothing image classification

Abstract This study aims to design a classification technique suitable for Zhuang ethnic clothing images by integrating the concept of supply–demand matching and convolutional neural networks. Firstly, addressing the complex structure and unique visual style of Zhuang ethnic clothing, this study proposes an image resolution model based on supply–demand matching and convolutional networks. By integrating visual style and label constraints, this model accurately extracts local features. Secondly, the model’s effectiveness and resolution performance are analyzed through various performance metrics in experiments. The results indicate a significant improvement in detection accuracy at different annotation points. The model outperforms other comparative methods in pixel accuracy (90.5%), average precision (83.7%), average recall (80.1%), and average F1 score (81.2%). Next, this study introduces a clothing image classification algorithm based on key points and channel attention. Through key point detection and channel attention mechanisms, image features are optimized, enabling accurate classification and attribute prediction of Zhuang ethnic clothing. Experimental results demonstrate a notable enhancement in category classification and attribute prediction, with classification accuracy and recall exceeding 90% in top-k tasks, showcasing outstanding performance. In conclusion, this study provides innovative approaches and effective solutions for deep learning classification of Zhuang ethnic clothing images

Evaluation of coal preparation plant separation effect based on multi-level fuzzy comprehensive evaluatio

In order to reflect situation that whether products meet index requirements in coal preparation plant, a multi-level fuzzy comprehensive evaluation method was proposed. Taking production data of seven months in one coal preparation plant as research object， the heavy medium separation product index, the coarse slime separation product index and flotation product index were concentrated to form a fuzzy relation matrix, the weight vector was constructed by expert scoring method. And the production data of seven months was calculated by the multi-level fuzzy comprehensive evaluation method. The evaluation results indicated that the optimal target was January and July, and separation effect of February to May was suboptimal. By contrast, separation effect of June was unfavorable. This conclusion is in conformity with field separation effect