Service Systems and Service Innovation: Toward the Theory of Service Systems

Services have been regarded as something intangible, perishable, and heterogeneous so that it is difficult to measure the quality and productivity of them. Services also have long been considered non-productive economic activities. However, considering the recent growth of service industry across the world, it is imperative to study the very nature of service and its systems in the knowledge-based economy from an integrated perspective to improve the quality of life and effective economic development. For this, we in this study will develop a systematic way of understanding the nature service in the knowledge-based economy from a systems’ perspective and build an integrated theory of service systems which facilitates service innovation and improves service productivity. The proposed theory will provide the foundation for designing, producing, delivering, operating, maintaining, monitoring, and improving service systems, which in turn leads to service innovation and thus a sustainable economic growth with providing greater employment opportunities. This study will also provide researchers and companies with the basis for future study and guidelines to further service innovation

Suppressed Superconductivity of the Surface Conduction Layer in Bi2_2Sr2_2CaCu2_2O8+x_{8+x} Single Crystals Probed by {\it c}-Axis Tunneling Measurements

We fabricated small-size stacks on the surface of Bi$_2$Sr$_2$CaCu$_2$O$_{8+x}$ (BSCCO-2212) single crystals with the bulk transition temperature $T_c$$\simeq$90 K, each containing a few intrinsic Josephson junctions. Below a critical temperature $T_c'$ ($\ll$ $T_c$), we have observed a weakened Josephson coupling between the CuO$_2$ superconducting double layer at the crystal surface and the adjacent one located deeper inside a stack. The quasiparticle branch in the $IV$ data of the weakened Josephson junction (WJJ) fits well to the tunneling characteristics of a d-wave superconductor($'$)/insulator/d-wave superconductor (D$'$ID) junction. Also, the tunneling resistance in the range $T_c'$$<$$T$$<$$T_c$ agrees well with the tunneling in a normal metal/insulator/d-wave superconductor (NID) junction. In spite of the suppressed superconductivity at the surface layer the symmetry of the order parameter appears to remain unaffected.Comment: 13 pages, 6 figure

In Vitro Chemosensitivity Using the Histoculture Drug Response Assay in Human Epithelial Ovarian Cancer

The choice of chemotherapeutic drugs to treat patients with epithelial ovarian cancer has not depended on individual patient characteristics. We have investigated the correlation between in vitro chemosensitivity, as determined by the histoculture drug response assay (HDRA), and clinical responses in epithelial ovarian cancer. Fresh tissue samples were obtained from 79 patients with epithelial ovarian cancer. The sensitivity of these samples to 11 chemotherapeutic agents was tested using the HDRA method according to established methods, and we analyzed the results retrospectively. HDRA showed that they were more chemosensitive to carboplatin, topotecan and belotecan, with inhibition rates of 49.2%, 44.7%, and 39.7%, respectively, than to cisplatin, the traditional drug of choice in epithelial ovarian cancer. Among the 37 patients with FIGO stage Ⅲ/Ⅳ serous adenocarcinoma who were receiving carboplatin combined with paclitaxel, those with carboplatin-sensitive samples on HDRA had a significantly longer median disease-free interval than patients with carboplatin- resistant samples (23.2 vs. 13.8 months, p＜0.05), but median overall survival did not differ significantly (60.4 vs. 37.3 months, p＝0.621). In conclusion, this study indicates that HDRA could provide useful information for designing individual treatment strategies in patients with epithelial ovarian cancer

Decomposed Temporal Dynamic CNN: Efficient Time-Adaptive Network for Text-Independent Speaker Verification Explained with Speaker Activation Map

Temporal dynamic models for text-independent speaker verification extract consistent speaker information regardless of phonemes by using temporal dynamic CNN (TDY-CNN) in which kernels adapt to each time bin. However, TDY-CNN shows limitations that the model is too large and does not guarantee the diversity of adaptive kernels. To address these limitations, we propose decomposed temporal dynamic CNN (DTDY-CNN) that makes adaptive kernel by combining static kernel and dynamic residual based on matrix decomposition. The baseline model using DTDY-CNN maintained speaker verification performance while reducing the number of model parameters by 35% compared to the model using TDY-CNN. In addition, detailed behaviors of temporal dynamic models on extraction of speaker information was explained using speaker activation maps (SAM) modified from gradient-weighted class activation mapping (Grad-CAM). In DTDY-CNN, the static kernel activates voiced features of utterances, and the dynamic residual activates unvoiced high-frequency features of phonemes. DTDY-CNN effectively extracts speaker information from not only formant frequencies and harmonics but also detailed unvoiced phonemes' information, thus explaining its outstanding performance on text-independent speaker verification.Comment: Submitted to InterSpeech 202