A Suggestion on the Roadmapping Process to Make an Integration Roadmap between Service-Device-Technology–With a Focus on the Case of U-City

The Technology Roadmap(TRM) is a technical strategic decision support framework in order for the anticipation and projection of the changes of technologies in the future, which has higher uncertainty in general. While the importance of technology management is receiving more attention these days, the research works on the TRMs have been limited to project future technology trends yet diversely studied in different sector such as the service industry The aim of research is therefore to explored and proposed a integrated roadmapping process based on the service oriented business model which based on technology. Proposed methodology has been applied into smart city development project to validate its usefulness and benefit

Dip-Pen Nanolithography of Reactive Alkoxysilanes on Glass

The use of organofunctional silane chemistry is a flexible and general method for immobilizing biomolecules on silicon oxide surfaces, including fabricating DNA, small-molecule, and protein microarrays. The biggest hurdle in employing dip-pen nanolithography (DPN) for extending this general approach to the nanoscopic domain is the tendency of trialkoxy- and trichlorosilanes to rapidly polymerize due to hydrolysis reactions. The control of the local water concentration between the substrate surface and the scanning AFM tip is critical, both to the physical and chemical processes involved in DPN writing and to the ability to form well-defined thin layers of reactive silanes without extensive polymerization induced disorder. We found that we could control the degree of polymerization through careful choice of the alkoxysilane used as the “ink” for DPN and through control of the relative humidity during inking and writing with the coated AFM tip. As a proof-of-principle, we demonstrate that areas patterned with an alkoxysilane on glass with DPN are functional for subsequent immobilization of fluorescently labeled streptavidin via covalent attachment of biotin. This preliminary result sets the stage for the ability to capture proteins in their fully hydrated state from buffered solution, by molecular recognition onto previously written reactive nanoscopic regions on oxidized silicon and glass

Surfactant Activated Dip-Pen Nanolithography

Direct nanoscale patterning of maleimide-linked biotin on mercaptosilane-functionalized glass substrates using dip-pen nanolithography (DPN) was facilitated by the addition of a small amount of the biocompatible nonionic surfactant Tween-20. A correlation was found between activated biotin transfer from the AFM tip with surfactant included in the ink and an increase in the wettability of the partially hydrophobic silanized substrate. Surfactant concentration represents a new control variable for DPN that complements relative humidity, tip−substrate contact force, scan speed, and temperature. Using surfactants systematically as ink additives may expand the possible ink−substrate combinations that can be used for patterning biotin and other biomolecules, including proteins

Anomaly Detection in Multi-Host Environment Based on Federated Hypersphere Classifier

Detecting anomalous inputs is essential in many mission-critical systems in various domains, particularly cybersecurity. In particular, deep neural network-based anomaly detection methods have been successful for anomaly detection tasks with the recent advancements in deep learning technology. Nevertheless, the existing methods have considered somewhat idealized problems where it is enough to learn a single detector based on a single dataset. In this paper, we consider a more practical problem where multiple hosts in an organization collect their input data, while data sharing among the hosts is prohibitive due to security reasons, and only a few of them have experienced abnormal inputs. Furthermore, the data distribution of the hosts can be skewed; for example, a particular type of input can be observed by a limited subset of hosts. We propose the federated hypersphere classifier (FHC), which is a new anomaly detection method based on an improved hypersphere classifier suited for running in the federated learning framework to perform anomaly detection in such an environment. Our experiments with image and network intrusion detection datasets show that our method outperforms the state-of-the-art anomaly detection methods trained in a host-wise fashion by learning a consensus model as if we have accessed the input data from all hosts but without communicating such data

Solvent-Free Polycaprolactone Dissolving Microneedles Generated via the Thermal Melting Method for the Sustained Release of Capsaicin

(1) Background: Dissolving microneedles (DMNs), a transdermal drug delivery system, have been developed to treat various diseases in a minimally invasive, painless manner. However, the currently available DMNs are based on burst release systems due to their hydrophilic backbone polymer. Although hydrophobic biodegradable polymers have been employed on DMNs for sustained release, dissolution in an organic solvent is required for fabrication of such DMNs. (2) Method: To overcome the aforementioned limitation, novel separable polycaprolactone (PCL) DMNs (SPCL-DMNs) were developed to implant a PCL-encapsulated drug into the skin. PCL is highly hydrophobic, degrades over a long time, and has a low melting point. Under thermal melting, PCL encapsulated capsaicin and could be fabricated into a DMN without the risk of toxicity from an organic solvent. (3) Results: Optimized SPCL-DMNs, containing PCL (height 498.3 ± 5.8 µm) encapsulating 86.66 ± 1.13 µg capsaicin with a 10% (w/v) polyvinyl alcohol and 20% (w/v) polyvinylpyrrolidone mixture as a base polymer, were generated. Assessment of the drug release profile revealed that this system could sustainably release capsaicin for 15 days from PCL being implanted in porcine skin. (4) Conclusion: The implantable SPCL-DMN developed here has the potential for future development of toxicity-free, sustained release DMNs