Search

Publications in Renal Failure in Science Citation Index Expanded (SCI-EXPANDED) between 1992 and 2021 were analyzed. Six publication indicators: total, independent, collaborative, first author, corresponding author, and single author publications as well as their related citation indicators, were used to compare performances of countries, institutes, and authors. Comparison of the highly cited papers and journal's impact factor (IF) contributors was discussed. In addition, the main research topics in the journal were presented. Results show that China published the most total articles and reviews, as well as the first-author papers and corresponding-author papers in the journal. The Chang Gung Memorial Hospital in Taiwan ranked the top in five publication indicators: total, single-institution, inter-institutionally collaborative, first author, and corresponding-author papers. A low percentage of productive authors emerged as a journal IF contributor. Similarly, only a limited relationship between highly cited papers and IF contributing papers was found. Publications related to hemodialysis, chronic kidney disease, and acute kidney injury were the most popular topic, while meta-analysis was new focus in the last decade in the journal. [ABSTRACT FROM AUTHOR]

Background: The overlapping symptoms of schizophrenia and dissociation have been increasingly recognized. This paper explains why it is reasonable to expect that there would be a substantial subgroup of patients diagnosed with schizophrenia spectrum disorders (SSDs) who suffer from pathological dissociation. Objective: As little is known about the prevalence of dissociative disorders and symptoms among patients with SSDs, we investigated the prevalence of dissociative disorders and symptoms among patients with SSDs. Method: We used both self-report measures and structured interviews to examine dissociative disorders and symptoms in a randomly recruited sample of inpatients with a clinical diagnosis of SSDs in Taiwan (N = 100). Results: Over 60% of participants exhibited pathological dissociation, and 54% had a dissociative disorder according to structured interview data; three participants met the DSM-5 diagnostic criteria for dissociative identity disorder. The concurrent validity of pathological dissociation in this sample was similar to that of depression among patients with schizophrenia reported in the literature. Participants with a dissociative disorder were more likely to report high-betrayal traumas and meet DSM-5 criteria for post-traumatic stress disorder; they also reported more psychotic symptoms than those without a dissociative disorder. Conclusions: This was one of very few studies that used structured interviews to examine pathological dissociation in patients with SSDs. The results indicate that pathological dissociation in SSDs is not uncommon. Clinical assessment should include measures of dissociation to facilitate early identification. Patients with dissociative disorders are often diagnosed with a psychotic disorder. Our study found that unrecognized dissociation is common in a sample of Taiwan inpatients with schizophrenia. Patients with schizophrenia spectrum disorders should be screened for dissociation. Trauma and dissociation are not rare among inpatients diagnosed with schizophrenia spectrum disorders in Taiwan. [ABSTRACT FROM AUTHOR]

The use of information technology during the COVID-19 pandemic raises significant questions around the protection of personal data in a disaster. This paper considers how the clear benefits of using and sharing such data in disaster scenarios can be achieved while recognising an individual's right to privacy through examining the experiences of Taiwan and New Zealand. These states represent two successful COVID-19 response strategies which utilised different approaches to the use of technology. In Taiwan, the response made significant use of personal data and information technology. New Zealand, by contrast, has relied upon stringent lockdowns and extreme limits upon personal freedoms. The paper considers the different approaches to data and privacy that underpinned these responses and considers whether New Zealand can learn from the Taiwanese experience in future disaster planning. In doing so, the paper concludes by examining the wider question of when and if the community's expectation of a safe environment should trump the rights of individuals to retain personal data both in the context of pandemics and in other emergency or disaster scenarios. It also raises deeper questions, exposed by the COVID-19 response, about whether our current approach to privacy is sustainable in the digital age. [ABSTRACT FROM AUTHOR]

In this paper, we suggest a technique to quantify model risk, particularly model misspecification for binary response regression problems found in financial risk management, such as in credit risk modelling. We choose the probability of default model as one instance of many other credit risk models that may be misspecified in a financial institution. By way of illustrating the model misspecification for probability of default, we carry out quantification of two specific statistical predictive response techniques, namely the binary logistic regression and complementary log–log. The maximum likelihood estimation technique is employed for parameter estimation. The statistical inference, precisely the goodness of fit and model performance measurements, are assessed. Using the simulation dataset and Taiwan credit card default dataset, our finding reveals that with the same sample size and very small simulation iterations, the two techniques produce similar goodness-of-fit results but completely different performance measures. However, when the iterations increase, the binary logistic regression technique for balanced dataset reveals prominent goodness of fit and performance measures as opposed to the complementary log–log technique for both simulated and real datasets. [ABSTRACT FROM AUTHOR]

Short-term hourly reliable prediction of significant wave height is an important research topic in coastal engineering. Many researchers have carried out in-depth studies in many ocean regions. Generally, most of this work is implemented through numerical models. However, as for numerical models, with the increase of hourly prediction duration, the accumulation of wave randomness leads to the poor prediction effect. In this paper, four buoy stations in the Taiwan Strait are taken as the research objects. We propose a significant wave height prediction algorithm, which combines numerical weather prediction model WRF and deep-learning model, called WRF-CLSF(Convolution-LSTM-FC). WRF can forecast 24-h wind speed in real-time, based on a variety of interpretable physical mechanisms. CLSF aims to extract the information of historical wind-wave interaction scale and the trend of wind-wave coherence, with the help of convolution operation and the time series model(LSTM), respectively. In the experiment, the proposed model was compared with the state-of-the-art prediction model. The results show that WRF-CLSF has an outstanding prediction effect at four buoy observation stations along with the Taiwan Strait. [ABSTRACT FROM AUTHOR]

This study focuses on the impact of the unexpected events of the marine casualties in Taiwan international ports and aims to develop an undesirable-output Data Envelopment Analysis (DEA) model to evaluate navigation safety and acquires the improvement in marine casualties that affect the performance of port safety. Moreover, the major difficulties in this study are the data collection and classification for each marine casualties, the selection of key parameters and weighted value for assessment model. Then, the undesirable-output DEA can conquer the dilemma and render marine casualties be negative factor. This paper searches the main cause about marine casualties adopted by R.O.C. Ministry of Transportation and Communications (MOTC). Based upon 899 sets of marine casualties collected from 2010 to 2019 in Taiwan international ports water, an assessment model comprising four international ports is built, each of which is composed of an input variable and eleven undesirable-output variables. Finally, the results show that: (1) The method which was demonstrated on Taiwan international ports indicates navigation safety ordering is Hualien port, Keelung port, Taichung port and Kaohsiung port. (2) All of the marine casualties, collision and structural damage/ship sinking are the severest casualty that should be improved. Furthermore, the findings of this study correspond to reality so it can help the port authority to take effective risk control actions to increase the navigation safety of international ports. [ABSTRACT FROM AUTHOR]