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Rice-paper plant, Tetrapanax papyrifer is a woody plant native to Taiwan and widely distributed in western Japan. Due to its low commercial value, little is known about its interactions with microorganisms. Here, we isolated Neofusicoccum parvum, a known causal agent of grape stem rot and mango stem-end rot, from leaf blight on T. papyrifer. Compared to mango isolate, N. parvum from rice-paper plant showed comparable virulence on grape stem and mango fruit. N. parvum strains exhibited pathogenicity on a variety of common weeds, which may act as disease reservoirs and boost N. parvum prevalence in commercially grown mango and grape. [ABSTRACT FROM AUTHOR]

Paper cultural relics such as double-sided printed newspapers and periodicals represent modern cultural heritage. Severe damage such as embrittlement, decay, and dreg generally occur to paper; hence, it urgently needs conservation and restoration. Therefore, herein, a new reinforcement method for the fragile double-sided printed paper cultural relics is proposed with cotton mesh and adhesive PVA217 as reinforcement materials. Using a computer measured and controlled folding endurance tester, a pendulum tensile strength tester, pH meter, pulp viscosimeter, and other instruments, the physical properties of newspaper samples before and after aging were evaluated. In addition, the mechanical properties, chromatic aberration and surface morphology of simulated samples before and after the cotton mesh reinforcement and Japanese washi paper reinforcement were assessed. The experimental results indicate that this new reinforcement method could effectively improve the physical strength, chromatic aberration and durability of the simulated samples. Widespread applications of this cotton mesh reinforcement method for the reinforcement and protection of the red revolutionary cultural relics such as double-sided printed newspaper and periodicals during the Republic of China era are foreseeable. [ABSTRACT FROM AUTHOR]

Mudstone soils (MS) are widely distributed in southern Taiwan and have an inherent proclivity to geological damages and failures. However, the use of traditional and non-traditional techniques to treat MS remains a challenge and is an area relatively unexplored due to the soils' distinct and sophisticated features. This study examined the hydromechanical performance of reconstituted MS treated with colloidal nanosilica (CN), fiber (f), and combinations thereof (CN-f) via a series of laboratory tests, including the unconfined compressive strength tests, 3D volumetric shrinkage tests, free swell tests, 1D consolidation tests, and filter paper tests. Fourier-transform infrared spectroscopy (FTIR) and Scanning electron microscopy (SEM) were also used to inspect the geochemical composition and microstructure of the untreated and treated MS. Results suggest that CN-f treatment can significantly improve the peak and postpeak strengths and ductility of MS while achieving satisfactory improvements in swelling control, shrinkage limits, and volumetric strains. Following treatment with 15% CN and 1% f for 28 days, the MS showed an optimal 527% improvement in Unconfined compressive strength (UCS) and satisfactory residual strain. Finally, the FTIR and SEM images revealed enhanced interlocking between the MS particles and the formation of marginal C–S–H and viscous gels, supporting the improved performance in MS. This study provides comprehensive analyses that offer insights into the synergistic effects of CN-f on the hydromechanical performance of MS. The findings will be valuable to engineers exploring innovative and ecofriendly alternatives for treating MS with a robust design. [ABSTRACT FROM AUTHOR]

This paper complicates the classic security dilemma by considering the notions of ontological security and relational deterrence. It studies how the ontological security dilemma has emerged between the US, China, and Taiwan from the relational perspective and how these spiral chains will further develop in the future. The paper incurs the literature on relational analysis to expound on how different ontological security concerns allude to relational deterrence between the three actors. Taiwan's separatism is more of a threat to China's relational self than to physical security because the separatist does not belong to any already agreed relationship. A geometric model and a few simulations yield three unconventional findings. 1) The less advantaged the US military is over China, the less likely armed unification will occur. 2) The US anti-Chinese tendency is irrelevant in determining the probability of armed unification. 3) What may escalate the spiral are China's anti-Taiwan independence and Taiwan's anti-unification. Case sensitivity indicates the ontological sensibilities of a security dilemma. [ABSTRACT FROM AUTHOR]

Oyster Farming is one of important fisheries and aquaculture industries in Taiwan. Each year, approximately 4000–5000 tons of discarded bamboo scaffolding (BS) used in oyster farming, are generated, so the treatment and utilization of BS should be taken seriously. This study evaluates the suitability of BS for pulp and papermaking by assessing the chemical compositions, microstructural, and fiber morphology. The pulping properties is investigated by soda pulping. The chemical composition of BS shows the potential for application in pulping. The BS microstructure shows that can enhance pulping reactions, while the fiber morphology indicates the possibility of producing high-strength paper. Through the pulping experiment, it demonstrated that BS is suitable for pulping with lower NaOH dosage and longer digestion time. The condition at 170 °C with 14% NaOH dosage for 90 min digestion has the highest yield. After refining the highest pulping yield BS pulp, it can improve the handsheet strength and bulk of the OCC-BS mixed pulp, which can achieve the strength property required for industrial paper. In summary, BS exhibits the potential for pulping application and produces a better paper strength than OCC pulp, exhibiting the feasibility of enhancing the circular utilization value of BS in Taiwan. [ABSTRACT FROM AUTHOR]

Climate change induced partly by emissions of carbon dioxide (CO2) is an urgent issue worldwide, calling for advanced methods of carbon sequestration. Since CO2-emitting industries often generate alkaline waste, sequestrating CO2 by mineral carbonation of alkaline waste is promising both for carbon capture and utilization, and for preventing waste disposal. Here we review the principles of mineral carbonation and we discuss mineral carbonation of alkaline waste and byproducts in Taiwan. We focus on wastes such as iron and steel slag, cement and concrete waste, incineration ash, coal combustion ash, and paper waste. We evaluate the CO2 reduction potential to reveal promising materials and industries. We found that 4.2 Mt CO2 can be directly sequestered annually. Moreover, the use of alternative materials in the cement and concrete industries can indirectly facilitate CO2 sequestration. [ABSTRACT FROM AUTHOR]

Pineapples are an important agricultural economic crop in Taiwan. Considerable human resources are required to protect pineapples from excessive solar radiation, which could otherwise lead to overheating and subsequent deterioration. Note that simple covering all of the fruit with a paper bag is not a viable solution, due to the fact that it makes it impossible to determine whether the fruit is ripe. This paper proposes a system by which to automate the detection of ripe pineapples. The proposed deep learning architecture enables detection regardless of lighting conditions, achieving accuracy of more than 99.27% with error of less than 2% at distances of 300 ~ 800 mm. This proposed system using an Nvidia TX2 is capable of 15 frames per second, thereby making it possible to mount the device on machines that move at walking speed. [ABSTRACT FROM AUTHOR]

Dengue is one of the world's most rapidly spreading mosquito-borne viral diseases. As it is found mostly in urban and semi-urban areas, urbanization and associated human activities that affect the environment and larval habitats could become risk factors (e.g., lane width, conditions of street ditches) for the spread of dengue. However, there are currently no systematic studies of micro-scale urbanization-based risk factors for the spread of dengue epidemics. We describe the study area, two micro-scale environmental risk factors associated with urbanization, and meteorological data. Since the observations involve spatial and temporal correlations, we also use some statistical methods for the analysis of spatial and spatial-temporal data for the relationship between urbanization and dengue. In this study, we analyzed data from Kaohsiung, a densely populated city in southern Taiwan, and found a positive correlation between environmental risk factors associated with urbanization (ditches positive for mosquito larvae and closely packed streets termed "dengue lanes") and clustering effects in dengue cases. The statistical analysis also revealed that the occurrence of positive ditches was significantly associated with that of dengue lanes in the study area. The relationship between climate variables and positive ditches was also analyzed in this paper, indicating a relationship between dengue and both rainfall and temperature, with temperature having a greater effect. Overall, this work is immediately relevant and applicable for policymakers in government, who will need to reduce these favorable habitats for vector-born disease spreaders and implement regulations for new urban constructions to thus reduce dengue spread in future outbreaks. [ABSTRACT FROM AUTHOR]

Why do some movement parties successfully institutionalize into a functioning party organization while others struggle? This paper argues that not all movement parties institutionalize in the same way. Movement parties that emanate out of a long-term social movement organization face a qualitatively different set of challenges than those that form out of a short-term movement. Routinization—the process of parties developing rules, regulation, and predictable behavior—is a particularly crucial component for short-term movement party institutionalization. When parties emanate out of long-standing social movement organizations, they are advantaged because they already have existing formal rules and regulations. Short-term parties however, are disadvantaged because they lack these organizational structures. Further, short-term movement parties not only need routinization, but must make it a priority; the sequencing of their institutionalization matters. I demonstrate the importance of routinization with the case of Taiwan's New Power Party, a movement party formed out of the 2014 Sunflower Movement. This case shows how struggles to routinize early for short-term movement parties leads to crucial causal mechanisms hindering party institutionalization instead of helping it. [ABSTRACT FROM AUTHOR]

With the Internet becoming indispensable in our lives, social media has become an integral part of our lives. However, with this has come the phenomenon of a single user registering multiple accounts (sockpuppets) to advertise, spam, or cause controversy on social media sites, where the user is called the puppetmaster. This phenomenon is even more evident on forum-oriented social media sites. Identifying sockpuppets is a critical step in stopping the above-mentioned malicious acts. The identification of sockpuppets on a single forum-oriented social media site has seldom been addressed. This paper proposes a Single-site Multiple Accounts Identification Model (SiMAIM) framework to address this research gap. We used Mobile01, Taiwan's most popular forum-oriented social media site, to validate SiMAIM's performance. SiMAIM achieved F1 scores between 0.6 and 0.9 on identifying sockpuppets and puppetmasters under different datasets and settings. SiMAIM also outperformed the compared methods by 6–38% in F1 score. [ABSTRACT FROM AUTHOR]

Machine learning approaches are increasingly being employed to forecast the key characteristics of strong ground motions, including the challenging classification of Pulse-Like (PL) ground motions. The PL ground motions are characterized by their impulsive nature and have the potential to cause significant damage to structures. The classification of PL ground motions continues to be a significant challenge due to the absence of consensus on their definition and categorization. This paper investigates the potential benefits of several Machine Learning Classifiers (MLCs) algorithms such as decision tree, random forest, logistic regression, naive Bayes, support vector machine, K-nearest neighbor, ensemble model, and artificial neural network models for predicting PL and Non-Pulse-Like (NPL) ground motions. In this regard, a dataset comprising 200 near-fault ground motions records compiled from active tectonic regions like Taiwan, Turkey, Iran, and Japan, was divided into 2 portions, with 75% used to train the model and the remaining 25% used for testing. Plots of performance metrics, confusion matrix, and receiver operating curve indicate that the ensemble classifier outperforms the other classifier with 86.2% accuracy and the lowest misclassification of PL and NPL ground motions. Additionally, the trained MLC has been compared with the existing ground motion classification models to further assess the accuracy of the different classifiers in the present study. [ABSTRACT FROM AUTHOR]

On average, women menstruate for approximately half of their lives. Little is known about whether and how health-related quality of life (HRQOL) differs across users of different types of menstrual products. To answer this question, this study collected data from 1,245 female university students in Taiwan through an anonymous online survey and compared users of different types of menstrual products in four HRQOL domains. Multivariate linear regression analysis revealed significant differences in all four domains. For instance, regarding physical health, tampon users reported better HRQOL (β =.054) than pad users; regarding social health, tampon (β =.059) and menstrual cup (β =.071) users both reported better HRQOL than pad users. Furthermore, factors influencing HRQOL also differed between pad and tampon users. For example, having many premenstrual symptoms affected both pad (β = -.115) and tampon (β = -.172) users' physical HRQOL; while pad users with many premenstrual symptoms also had worse psychological (β = -.085), social (β = -.100), and environment (β = -.104) HRQOL, their tampon-using counterparts were not significantly affected. Bisexual tampon-using college women reported worse social HRQOL (β = -.149) than their heterosexual peers. In addition, relationship status and varsity team membership had differential significant associations with the four domains. Future menstrual health education could focus more on introducing the different features of various menstrual products. Our empirical findings can help empower women to make informed decisions about which menstrual products could best suit their needs and improve their HRQOL. [ABSTRACT FROM AUTHOR]

To strengthen brand identity, enrich tourist experiences, and promote heritage education, Taijiang National Park proposed to reconstruct Taiwan's Dutch Trading Post in a different location from where it was initially erected in the 17th century. This paper is a case study of the reconstruction proposal for a lost colonial architectural complex in the context of heritage tourism. It discusses the practical and academic issues of rebuilding long-lost colonial heritage sites. The author provided a first-hand account of the technical and practical reasoning for reconstructing a bygone complex erected by Dutch settlers. Historical development phases of the Dutch Trading Post of Taiwan were first introduced, and then a reconstruction strategy was proposed to resolve conflicts with legal constraints. Additionally, a site selection process using GIS, a conceptually driven plan for reconstruction, and a 3D simulation were provided. Three specific issues in heritage rebuilding were further discussed, including the decision to reconstruct a heritage building (complex), the authenticity of the reconstructed building if done in a different location from where it was initially situated, and the need to discover more archaeological facts. [ABSTRACT FROM AUTHOR]

The paper seeks to examine whether and on what basis the international human rights law applies to the territorial non-state entities, having as an example the cases of the Republic of China and the territorial non-state entities from the post-Soviet space. For this purpose, the paper will focus first, on the applicability of the relevant international human rights treaties and general international human rights law regulations. Second, it will look at what place is reserved for the international human rights law in the national legal systems of the analysed territorial non-state entities. It is argued here that these territorial non-state entities proclaim their commitment to the rule of law and human rights by transplanting international regulations, especially the human rights ones, into their national provisions. After analysing the two case studies, it will be claimed that although the territorial non-state entities committed themselves to following international human rights law norms and standards, legal transplant is not sufficient and the territorial non-state entities shall engage more at the practical level in order to ensure the effectiveness of human rights protection on their territories. [ABSTRACT FROM AUTHOR]

With increasing pressure to cut carbon emissions and develop sustainability plans, companies need carbon credits to offset emissions that cannot be eliminated from their operations, new global carbon exchange to launch in Singapore by 2021 end, the high-quality credit can bridge this gap and play an important role in the overall climate change mitigation strategy. The purpose of this research is to use the production data (including carbon emissions) of paper-making companies in Taiwan to establish a circular economy mathematical programming model and the concept based on the activity cost method (ABC) to explore the impact of different carbon emissions costs (such carbon tax, carbon cap-and-trade, etc.) on the company's production structure and profitability impact. The research results show that different carbon emission cost models have different effects on the company's optimal product-mix and profitability. The managerial implication is to combine the extensive application of the carbon emission credit mechanism, which can offset the carbon emissions in the production process and have a significant impact on the company's sustainable competitiveness. In addition, this study can also enable decision makers to understand the impact of different carbon emission cost models on the profitability of the company's product mix, which can be used as a reference for production planning decisions. [ABSTRACT FROM AUTHOR]

Background: Phosphorus (P) is the limiting nutrient in many mature tropical forests. The ecological significance of declining P stocks as soils age is exacerbated by much of the remaining P being progressively sequestered. However, the details of how and where P is sequestered during the ageing in tropical forest soils remains unclear. Results: We examined the relationships between various forms of the Fe and Al sesquioxides and the Hedley fractions of P in soils of an incipient ferralitic chronosequence on an altitudinal series of gently sloping benches on Green Island, off the southeastern coast of Taiwan. These soils contain limited amounts of easily exchangeable P. Of the sesquioxide variables, only Fe and Al crystallinities increased significantly with bench altitude/soil age, indicating that the ferralisation trend is weak. The bulk of the soil P was in the NaOH and residual extractable fractions, and of low lability. The P fractions that correlated best with the sesquioxides were the organic components of the NaHCO3 and NaOH extracts. Conclusions: The amorphous sesquioxides, Feo and Alo, were the forms that correlated best with the P fractions. A substantial proportion of the labile P appears to be organic and to be associated with Alo in organic-aluminium complexes. The progression of P sequestration appears to be slightly slower than the chemical and mineralogical indicators of ferralisation. [ABSTRACT FROM AUTHOR]

This research concentrates on segmenting credit card clients of Taiwan into optimal groups. Unsupervised Learning plays a significant role in dividing customers into similar groups based on several parameters. If customers are clustered in groups optimally, it leads towards the retrieval of better precision from machine learning models applied to customers associated with the clusters. Different machine learning algorithms (Linear discriminant analysis, logistic regression and random forest) were applied on the obtained clusters through K-means, hierarchical and HK Means clustering algorithm, and predictive accuracy is compared with the accuracy obtained via applying mentioned machine learning models on the whole dataset. In this paper, a novel approach of combining K Means and hierarchical clustering (HK Means) is used. In this approach, HK means clustering algorithms are applied on the factorial coordinates, obtained from multiple correspondence analyses for segmenting customers into optimal groups has been proposed. The accuracy of the clustering techniques is evaluated from the decomposition of inertia. The results demonstrate that the combination of K Means and hierarchical clustering proved to be optimal clustering techniques for customer segmentation which can be used further for applying Machine Learning techniques for credit risk analysis. [ABSTRACT FROM AUTHOR]

The wrapping layer's foaming process of the car steering wheel industry usually relies on the manual parameter setting by experienced engineers, but the reliability and validity are usually hard to control due to many foaming factors that affect the hardness of steering wheel wrapping layer (e.g., vulcanization time, mold temperature, material liquid temperature, material discharge pressure, humidity). This paper first proposes an intelligent process parameter recommendation system architecture, then develops a neural network-based hardness prediction (NNHP) model to predict the car steering wheel's wrapping hardness. Consequently, we combine NNHP and genetic algorithm (GA) to develop a foaming process parameter recommendation model (NNHP-GA) to effectively recommend the most suitable combinations of process parameters for achieving the desired wrapping hardness in an IoT-based intelligent manufacturing environment. An empirical study is applied in Taiwan's world-leading car steering wheel company. By analyzing the 16 important process sensor data installed in each casting machine, the five experimental results show that the NNHP-GA recommendation system can successfully predict the hardness of the steering wheel's wrapping layer and recommend appropriate process parameters (e.g., sensors S1-vulcanization time, S2-mold temperature, S5-A.P. pressure, S6-B.I. pressure, and "pressurization time") under a specific hardness target. The manufacturing company may employ the NNHP-GA model to build a process parameter recommendation system and increase the quality of process parameter setting. [ABSTRACT FROM AUTHOR]

Although the business environment is stochastic, deterministic data envelopment analysis (DEA) models are typically used to measure the efficiency of commercial banks for the purpose of simplicity. Bank operations are characterized by a network structure due to the dual role of deposits, which, on the one hand, are the output of the process of borrowing funds from depositors and, on the other hand, are the input of the process of making loans. Since the outputs of the production process of the bank are correlated with its inputs, the model for measuring efficiency in this case is a stochastic program with correlated data. To take the correlation between the inputs and outputs into consideration, in this paper, a standard normal transformation is applied for the correlated data, and a network stochastic model is developed to obtain the distribution of the stochastic efficiency. The model is used to measure the efficiency of twenty-two commercial banks in Taiwan. The results are more reliable, discriminative, and informative than those obtained from the existing models. They also show that the performance of a bank is mainly affected by its loan performance. Different from the stereotype suggesting that private companies usually operate more efficiently than state-owned companies, public banks perform better than private banks in Taiwan. [ABSTRACT FROM AUTHOR]

Taoism and Confucianism both exited simultaneously as philosophies of living in dynastic China. Although there has been an increasing popularity in scientometric studies, religion and health (R&H) literature lacks a holistic evaluation investigating articles relevant to Taoism and Confucianism. All publications produced in Taoism and Confucianism literature and indexed in Web of Science (WoS) databases between 1975 and 2018 were included in this study. Database search on health and Taoism literature retrieved 199 documents from WoS databases. Main research areas were Psychology, Religion and Behavioral Sciences (24.121, 21.608 and 20.603, respectively). The USA ranked first with 38 papers followed China, Taiwan and the UK (n = 35, 20 and 6 documents, respectively). Hong Kong Polytechnic University from China was the most contributor institution in health and Taoism literature. A total of 448 documents were published in health and Confucianism literature between 1975 and 2018, and original articles covered 93.08% of all literature. China was leading country with 126 articles followed by the USA, South Korea and Taiwan (n = 97, 35 and 35 items, respectively). The most productive institutions were City University of Hong Kong (China), Karolinska Institute (Sweden) and University of Hong Kong (China). Researchers from developing and least developed countries should be encouraged to carry out novel scientometric studies in R&H literature. [ABSTRACT FROM AUTHOR]

Purpose: Previous studies found that silicosis was majorly associated with occupation-related risks. However, little evidence was available to clarify the relation between Asian dust storm (ADS) and silicosis hospital admissions. This present paper aims to investigate the association between ADS events and hospital admissions for silicosis. Methods: We applied a Poisson time-series regression on the 2000-2012 National Health Insurance Research Database in Taiwan, linking air quality data and ambient temperature data to estimate the impact of ADS on silicosis hospital admissions in the age-specific groups. Results: A total of 2154 hospital admissions were recorded for silicosis in Taiwan, for a daily average number of 0.45. The number rises from 0.43 on a day without ADS to 0.70 on the outbreak day and continues increasing to 0.83 one day after outbreak. Among patients under 45, the effect of ADS appears on the event day as well as several post-event days (lag2-6) at the significant level of p < 0.1. There is also a significant lag effect on post-event day 2 (p < 0.05) for those aged above 74. Conclusion: Asian dust storms do result in a rise of silicosis hospital admissions, particularly for those above 74, those under 45, and for females. [ABSTRACT FROM AUTHOR]

On modern industrial product lines, assembly is predominantly performed through manual labor or using semi-automatic equipment. With the development of automation, robots are becoming crucial in improving the flexibility of production processes. This paper presents an assembly method that employs image processing to control industrial robots in solving a sphere assembly puzzle. By using image-processing techniques—such as block recognition, circle detection, and camera calibration—the system can detect and move randomly placed blocks to the correct assembly positions. Cooperation is also integrated into the system, allowing operators to intervene in the assembly and improving the system's efficiency while ensuring safety of operators. The results of the application on a practical platform using a HIWIN robot RT605-GB reveal a high rate of successful assembly, providing evidence that the system is effective. [ABSTRACT FROM AUTHOR]

Offshore Wind Turbines (OWTs) are dynamically sensitive structures and as a result estimating the natural frequency of the whole system taking into effect the flexibility of the foundation is one of the major design considerations. The natural frequency is necessary to predict the long-term performance as well as the fatigue life. OWTs are currently being constructed in seismically active regions such as the United States, China, India and Taiwan and there is a need for design considerations for OWTs located in seismic zones. Though OWTs are relatively less sensitive to earthquakes than typical structures, liquefaction of soil surrounding monopiles may have serious implications on the dynamic performance of the system. During liquefaction there is a loss of support along the depth of the monopile which noticeably reduces the stiffness of the system. This results in a decrease of the fundamental frequency and may cause resonating effects with high energy wave loads up until liquefaction effects are reduced with time. Therefore, these resonating effects will increase the fatigue damage and/or the overall accumulated rotation of the structure. Therefore, in this paper, the effect of liquefaction on the natural frequency of OWTs was considered through a parametric study which considers various soil conditions, liquefaction depths (DL), monopile diameters (D) and monopile lengths (LP). The finite element method used in this parametric study was validated via an analytical solution available in literature and a large-scale experiment which considers a fixed base condition. The study shows that the change in the natural frequency under various liquefaction depths is not significantly influenced by monopile diameter when the length is kept constant. On the other hand, the monopile length has a more detrimental effect and the aspect ratio is that LP/D is a significant non-dimensional term governing dynamic behaviour of OWT systems in the case of liquefaction. In addition, it is shown that the overall results are more sensitive in looser soils and special design considerations are provided for different ground conditions. Finally, based on analytical solutions provided in literature, a simplified method is presented to estimate the change of the natural frequency taking into account the liquefaction depth which can be easily programmed in a spreadsheet type program followed by a step-by-step solved example which also serves the purpose of verification and validation. [ABSTRACT FROM AUTHOR]

Pairs trading is an effective statistical arbitrage strategy considering the spread of paired stocks in a stable cointegration relationship. Nevertheless, rapid market changes may break the relationship (namely structural break), which further leads to tremendous loss in intraday trading. In this paper, we design a two-phase pairs trading strategy optimization framework, namely structural break-aware pairs trading strategy (SAPT), by leveraging machine learning techniques. Phase one is a hybrid model extracting frequency- and time-domain features to detect structural breaks. Phase two optimizes pairs trading strategy by sensing important risks, including structural breaks and market-closing risks, with a novel reinforcement learning model. In addition, the transaction cost is factored in a cost-aware objective to avoid significant reduction of profitability. Through large-scale experiments in real Taiwan stock market datasets, SAPT outperforms the state-of-the-art strategies by at least 456% and 934% in terms of profit and Sortino ratio, respectively. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has generated a range of responses from countries across the globe in managing and containing infections. Considerable research has highlighted the importance of trust in ethically and effectively managing infectious diseases in the population; however, considerations of reciprocal trust remain limited in debates on pandemic response. This paper aims to broaden the perspective of good ethical practices in managing an infectious disease outbreak by including the role of reciprocal trust. A synthesis of the approaches drawn from South Korea and Taiwan reveals reciprocal trust as an important ethical response to the COVID-19 pandemic. Reciprocal trust offers the opportunity to reconcile the difficulties arising from restrictive measures for protecting population health and individual rights. [ABSTRACT FROM AUTHOR]

Hydro-meteorological risks are a growing issue for societies, economies and environments around the world. An effective, sustainable response to such risks and their future uncertainty requires a paradigm shift in our research and practical efforts. In this respect, Nature-Based Solutions (NBSs) offer the potential to achieve a more effective and flexible response to hydro-meteorological risks while also enhancing human well-being and biodiversity. The present paper describes a new methodology that incorporates stakeholders' preferences into a multi-criteria analysis framework, as part of a tool for selecting risk mitigation measures. The methodology has been applied to Tamnava river basin in Serbia and Nangang river basin in Taiwan within the EC-funded RECONECT project. The results highlight the importance of involving stakeholders in the early stages of projects in order to achieve successful implementation of NBSs. The methodology can assist decision-makers in formulating desirable benefits and co-benefits and can enable a systematic and transparent NBSs planning process. [ABSTRACT FROM AUTHOR]

The local magnitude scale ML is defined by the difference between the observed amplitude (log A ) and the anchored attenuation amplitude (log A 0 ). A previous study in Taiwan established a model of the anchored amplitude as a function of the hypocentral distance R by matching the ML to the corresponding moment magnitude MW. Although the overall performance of the model is adequate, there remain some drawbacks, namely, the correlated empirical station correction problem and relatively low sample size. In this paper, we adopt the concept of the expectation-maximization (EM) algorithm to develop a new method that can simultaneously estimate the anchored amplitude model coefficients and station corrections. The revised catalog using the latest dataset in Taiwan provides an up-to-date accurate estimate of ML. Additionally, the proposed method can systematically obtain statistically meaningful results and be applied to datasets of other regions in the future. [ABSTRACT FROM AUTHOR]

The copula is well-known for learning scale-free measures of dependence among variables and has invited much interest in recent years. At the very coronary heart of the copula, the concept is the well-known theorem of Sklar. It states that any multivariate distribution function can be disintegrated into the marginal distributions and a copula, which comprises the reliance between variables. On the other hand, the decision tree is a renowned nonparametric dominant modeling approach used for both regression and labeling problems. A decision tree represents a tree-structured classification of the data into surprising instructions for simplicity and prediction reason. In this paper, we are going to appraise with novel nonparametric copula-based decision tree organization using a measure of dependence: maximal information coefficient as classification index for two related variables which best classify the data concerning looking at the factors, but additionally ranked the factors in line with their inferences. Additionally, we pre-test the splitting criteria value to anticipate growing branches of the decision tree at each infant node. For example, we followed our proposed method to credit card records for Taiwan and coronary heart disease records of Pakistan and acquired the desirable outcomes. As a result, the anticipated method of initiating two-variable decision trees is tested using constructive tools for classification, prediction and reconnecting critical factors in statistics, finance, fitness sciences, machine learning, and many other associated fields. [ABSTRACT FROM AUTHOR]