A Study of Effectiveness and Satisfaction Level of Cloud CRM Users in Taiwan\u27s Enterprises

Cloud computing in recent years has become a popular IT application. In Taiwan, enterprises currently using CRM (Customer Relationship Management) applications seek to take advantages of cloud computing features to enhance CRM effectiveness. However, despite international IT service providers’ investments in Taiwan’s market for establishing a cloud computing environment for CRM users, no statistics are available to reflect experience with actual use. Therefore, the purposes of this study are to understand the satisfaction levels of the current cloud CRM users (i.e., Taiwan’s enterprises) and to determine the key factors, which significantly affect enterprises’ managerial effectiveness and users’ satisfaction with cloud CRM. The basis for the research model is the Information System Success model and the characteristics of SaaS and CRM. This study has obtained contacts with Taiwan’s enterprises currently using cloud CRM, and the complete analyses of valid survey responses will occur shortly

General approach of causal mediation analysis with causally ordered multiple mediators and survival outcome

Causal mediation analysis with multiple mediators (causal multi-mediation analysis) is critical in understanding why an intervention works, especially in medical research. Deriving the path-specific effects (PSEs) of exposure on the outcome through a certain set of mediators can detail the causal mechanism of interest. However, the existing models of causal multi-mediation analysis are usually restricted to partial decomposition, which can only evaluate the cumulative effect of several paths. Moreover, the general form of PSEs for an arbitrary number of mediators has not been proposed. In this study, we provide a generalized definition of PSE for partial decomposition (partPSE) and for complete decomposition, which are extended to the survival outcome. We apply the interventional analogues of PSE (iPSE) for complete decomposition to address the difficulty of non-identifiability. Based on Aalen’s additive hazards model and Cox’s proportional hazards model, we derive the generalized analytic forms and illustrate asymptotic property for both iPSEs and partPSEs for survival outcome. The simulation is conducted to evaluate the performance of estimation in several scenarios. We apply the new methodology to investigate the mechanism of methylation signals on mortality mediated through the expression of three nested genes among lung cancer patients

Acute Fatty Liver of Pregnancy in a Taiwanese Tertiary Care Center: A Retrospective Review

SummaryObjectiveTo evaluate the demographics, clinical presentations, laboratory findings, and maternal and fetal outcomes in patients with acute fatty liver of pregnancy.Materials and MethodsA retrospective review was conducted of the records of pregnant patients with a diagnosis of acute fatty liver in a tertiary medical center over a 22-year period.ResultsEighteen patients with acute fatty liver of pregnancy were recruited, all of whom developed the disease in the third trimester. Eleven women (61%) were primigravid and four (22%) had twin pregnancies; six (33%) were diagnosed antepartum, and the other 12 (67%) were diagnosed postpartum. There were two maternal deaths (11%) and four fetal deaths (18%). The most common complications apart from severe liver dysfunction were acute renal failure (83%), hypoglycemia (61%), and disseminated intravascular coagulation (61%).ConclusionWomen who become acutely ill during the third trimester of pregnancy should undergo tests for acute fatty liver of pregnancy, including laboratory tests for assessing liver function and coagulation profile

Development of a deep learning-based tool to assist wound classification

This paper presents a deep learning-based wound classification tool that can assist medical personnel in non-wound care specialization to classify five key wound conditions, namely deep wound, infected wound, arterial wound, venous wound, and pressure wound, given color images captured using readily available cameras. The accuracy of the classification is vital for appropriate wound management. The proposed wound classification method adopts a multi-task deep learning framework that leverages the relationships among the five key wound conditions for a unified wound classification architecture. With differences in Cohen's kappa coefficients as the metrics to compare our proposed model with humans, the performance of our model was better or non-inferior to those of all human medical personnel. Our convolutional neural network-based model is the first to classify five tasks of deep, infected, arterial, venous, and pressure wounds simultaneously with good accuracy. The proposed model is compact and matches or exceeds the performance of human doctors and nurses. Medical personnel who do not specialize in wound care can potentially benefit from an app equipped with the proposed deep learning model

Realization of Polarization Control in High-Order Harmonic Generation

The nature of high-order harmonic generation process limits the harmonics emission to linear polarization. In this paper, we review the recent progress to generate elliptically or circularly polarized high-harmonic EUV pulses. We further demonstrate how complete control of polarization state of isolated high-harmonic pulse can be realized today by noncollinear focusing of two driving pulses with identical ellipticity but counter-rotating helicity. This paper opens a path towards the study of the fastest dynamics--down to attosecond time scales--in circular dichroism of magnetic materials, chiral molecules, and electronic spin motion.Taiwan Ministry of Science and Technology; Academia Sinica; Junta de Castilla y León; Ministerio de Economía y Competitividad; Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation; Ministerio de Ciencia, Innovación y Universidades for a Ramón y Cajal; European Social Fund; Ministerio de Educación, Cultura y Deporte

The Relationship between Brown Adipose Tissue Activity and Neoplastic Status: an 18F-FDG PET/CT Study in the Tropics

<p>Abstract</p> <p>Background</p> <p>Brown adipose tissue (BAT) has thermogenic potential. For its activation, cold exposure is considered a critical factor though other determinants have also been reported. The purpose of this study was to assess the relationship between neoplastic status and BAT activity by 2-deoxy-2-[18F]fluoro-D-glucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) in people living in the tropics, where the influence of outdoor temperature was low.</p> <p>Methods</p> <p>¹⁸F-FDG PET/CT scans were reviewed and the total metabolic activity (TMA) of identified activated BAT quantified. The distribution and TMA of activated BAT were compared between patients with and without a cancer history. The neoplastic status of patients was scored according to their cancer history and ¹⁸F-FDG PET/CT findings. We evaluated the relationships between the TMA of BAT and neoplastic status along with other factors: age, body mass index, fasting blood sugar, gender, and outdoor temperature.</p> <p>Results</p> <p>Thirty of 1740 patients had activated BAT. Those with a cancer history had wider BAT distribution (<it>p </it>= 0.043) and a higher TMA (<it>p </it>= 0.028) than those without. A higher neoplastic status score was associated with a higher average TMA. Multivariate analyses showed that neoplastic status was the only factor significantly associated with the TMA of activated BAT (<it>p </it>= 0.016).</p> <p>Conclusions</p> <p>Neoplastic status is a critical determinant of BAT activity in patients living in the tropics. More active neoplastic status was associated with more vigorous TMA of BAT.</p