Search

The article offers information on the 39th Annual International Computers, Software & Applications Conference to be held at Tunghai University in Taichung, Taiwan from July 1-5, 2015.

This paper is about spatial–temporal variability of atmospheric temperature across Taiwan, an island with diverse local emission sources partly because of its Asian cultural characteristics. To develop a new land use regression (LUR) model for this study, we used the temperature data collected by the Taiwan Central Weather Bureau from 2000 and 2016, while using the data from 2017 as the external data verification to assess model reliability. Because incense and joss money burning is a cultural-specific emission source in Asia, we further included location of temples, cemeteries, and crematoriums as potential predictors. The overall model performance and tenfold cross-validated are R2 of 0.88 and R2 of 0.87, respectively, which presents a high level of prediction performance. Moreover, we used our LUR model to estimate urban heat islands intensity (UHII) for six metropolises in Taiwan and found Taichung City has the highest UHII value (4.60 °C) among them. These results provide important insights in expanding the remote sensing application on spatial–temporal variation of atmospheric temperature and its further application on UHI effects. [ABSTRACT FROM AUTHOR]

Amid the global dilemma of youth unemployment, youth entrepreneurship has had an important impact on social, cultural and economic progress, and various countries have actively promoted relevant frameworks and strategies. Taiwan has many cultural assets whose original functions are no longer preserved. Fortunately, the public sector has thought a variety of redevelopment strategies to promote sustainable development, and new functions and usage patterns for these sites have emerged. However, there is a lack of research investigating the links between youth entrepreneurship, community participation and place attachment in local-development projects: a gap that this paper intends to fill. Against the backdrop of one such project, this study discusses the interrelationships of youth entrepreneurship, community participation, place dependence and place identity. Its results indicate that the different personal backgrounds of young entrepreneurs had little or no bearing on the extent of their community participation, place dependence or place identity. However, such community participation had a moderately positive correlation with place dependence and place identity, leading the authors to conclude that the participation of a community of young entrepreneurs brings new opportunities for local development that transcend the mere reduction of youth unemployment. That is, in addition to maintaining and preserving historic spaces, it boosts both sustainable development and diversity in the broader local community. They also calls for future research to assess whether community participation influences place attachment in other parts of the world. [ABSTRACT FROM AUTHOR]

Conventional data envelopment analysis (DEA) may generate the non-integer targets for integer-valued inputs and outputs of decision-making units (DMUs). To derive the convincing projections, integer-valued DEA has attracted much attention. Given the integrality restriction, Du et al. (Eur J Oper Res 218(1):186–192, 2012) proposed the super-efficiency approach consisting of additive integer-valued and additive super-efficiency integer-valued models for the differentiation of efficient DMUs, thereby raising the discriminatory power. This paper extends their approach to develop a simpler but stricter version, which we refer to as the unified additive super-efficiency model. The newly-developed model has three advantages. First, the slacks of input excess, input saving, output shortage and output surplus can be directly computed in a single program to obtain the efficiencies of inefficient DMUs and super-efficiencies of efficient DMUs. Secondly, it suggests the strongly Pareto-efficient projections for efficient DMUs. Finally, the identified super-efficiencies allow for the property of continuity. A comparison of the proposed model, with Du et al.'s (2012) and standard additive super-efficiency approaches is discussed using a numerical example. In addition, the applicability of the proposed model is illustrated by a data set covering 13 bus companies operating in the municipal bus system of Taichung. Our work not only provides managerial insights into the primary sources of inefficiency and super-efficiency but also contributes to the current understanding of how super-efficiency would be effectively and accurately measured in the presence of integer-valued data. [ABSTRACT FROM AUTHOR]

Inefficient patient transport in hospitals often leads to delays, overworked staff, and suboptimal resource utilization, ultimately impacting patient care. Existing dispatch management algorithms are often evaluated in simulation environments, raising concerns about their real-world applicability. This study presents a real-world experiment that bridges the gap between theoretical dispatch algorithms and real-world implementation. It applies process capability analysis at Taichung Veterans General Hospital in Taichung, Taiwan, and utilizes IoT for real-time tracking of staff and medical devices to address challenges associated with manual dispatch processes. Experimental data collected from the hospital underwent statistical evaluation between January 2021 and December 2021. The results of our experiment, which compared the use of traditional dispatch methods with the Beacon dispatch method, found that traditional dispatch had an overtime delay of 41.0%; in comparison, the Beacon dispatch method had an overtime delay of 26.5%. These findings demonstrate the transformative potential of this solution for not only hospital operations but also for improving service quality across the healthcare industry in the context of smart hospitals. [ABSTRACT FROM AUTHOR]

The prevalence of gluten-related disorders has risen due to the increased consumption of bakery products made from refined flour in recent decades. This study focused on employing indigenous hill grain flours, such as Taichung 176 rice flour, maize flour, sweet buckwheat flour, and finger millet flour from Nepal, to create gluten-free cookies by incorporating fungal αamylase, baking powder, and baker's yeast as modified leavening agents, in contrast to the typical refined flour-based cookies. 16 different composite flours were made by combining millet, maize, buckwheat, and glutinous rice flours in a 75:25 percentage, then subjected to 30°C proofing for 1 hour for food grade fungal α-amylase with an improver and baker's yeast treated sample before blending with cream and baking for 20 minutes at 200°C.The ash content, moisture content, sensory qualities, microbial load, and shelf life of cookies were studied and compared with control cookies. Over 60-days storage period, most formulated cookies had moisture content below 5%, except BWBY cookies (6%to 8.37%). The ash percentage of cookies significantly increased from 0.81% to 2.59%. The highest ratings for taste (8.0), texture (7.6), and crunchiness (8.1) were achieved for cookies produced with 75:25% Millet: Taichung 176 rice flour, treated with fungal α-amylase, improver, and baker’s yeast.Utilization of proofing techniques in that sample improved their color, taste and resolved the gritty texture issue Formulated gluten-free cookies (GFC) had higher ash and moisture but were still acceptable despite increased microbial load and moisture until the 60th day of storage. Overall acceptability (OAC) score slightly dropped but remained good (7 of 9) after 2 months of storage. Notably, gluten-free cookies exhibited higher nutritional value and retained their acceptability for up to 60 days when stored at ambient temperature (25 ± 2°C). [ABSTRACT FROM AUTHOR]

Climate change has led to more frequent extreme weather events such as heatwaves, droughts, and storms, which significantly impact agriculture, causing crop damage. Greenhouse cultivation not only provides a manageable environment that protects crops from external weather conditions and pests but also requires precise microclimate control. However, greenhouse microclimates are complex since various heat transfer mechanisms would be difficult to model properly. This study proposes an innovative hybrid model (DF-RF-ANN), which seamlessly fuses three components: the dynamic factor (DF) model to extract unobserved factors, the random forest (RF) to identify key input factors, and a backpropagation neural network (BPNN) to predict greenhouse microclimate, including internal temperature, relative humidity, photosynthetically active radiation, and carbon dioxide. The proposed model utilized gridded meteorological big data and was applied to a greenhouse in Taichung, Taiwan. Two comparative models were configured using the BPNN and the Long short-term memory neural network (LSTM). The results demonstrate that DF-RF-ANN effectively captures the trends of the observations and generates predictions much closer to the observations compared to LSTM and BPNN. The proposed DF-RF-ANN model hits a milestone in multi-horizon and multi-factor microclimate predictions and offers a cost-effective and easily accessible approach. This approach could be particularly beneficial for small-scale farmers to make the best use of resources under extreme climatic events for contributing to sustainable development goals (SDGs) and the transition towards a green economy. [ABSTRACT FROM AUTHOR]

An experimental population commonly used in genetic analyses of gene or quantitative trait loci (QTLs) in rice is chromosome segment substitution lines (CSSLs). In the present study, with the typical indica variety Guangluai 4 as a donor and japonica variety Taichung 65 as a recipient, seven CSSLs carrying F1 pollen sterility genes S-b, S-d, S-e, S-b/S-d, S-b/S-e, S-d/S-e, and S-b/S-d/S-e were obtained by specific selection for the target genes, non-specific selection for the genome of the recurrent parents in four backcross populations (BC1F2, BC2F2, BC3F2 and BC3F3). We evaluated the genetic effect of the F1 pollen sterility genes using 35 F1 hybrid individuals in crosses derived from CSSLs and Taichung 65. Pollen fertility of F1 hybrid plants was observed and the results indicated that the single genes S-b, S-d and S-e can cause 67.7%, 14.6% and 53.2% of pollen sterility, respectively. Multiple genes S-b/S-d, S-b/S-e, S-d/S-e, and S-b/S-d/S-e can cause 76.6%, 85%, 68.7%, and 93% of pollen sterility, respectively. [ABSTRACT FROM AUTHOR]

Owing to the diverse treatment outcomes after a botulinum toxin A (BoNT-A) injection to the external sphincter, this study aimed to develop a new technique: an ultrasound-guided BoNT-A external sphincter injection. This single-center prospective cohort study was conducted at a tertiary medical center in Taichung, Taiwan. From December 2020 to September 2022, 12 women were enrolled. The patients were evaluated for lower urinary tract syndrome using patient perception of bladder condition (PPBC), international prostate symptom score (IPSS), uroflowmetry, post-void residual volume (PVR), cystometry, and external sphincter electromyography. We evaluated the patients the day before surgery and 1 week after the BoNT-A injection. For the patients requiring self-catheterization, we recorded the number of times they required clean intermittent catheterization (CIC) per day before the procedure and 1 month after the procedure. The IPSS, PPBC, and PVR were significantly better after the transvaginal ultrasound-guided BoNT-A external sphincter injection. The number of times the patients required daily CIC was also reduced after the injection. Only one patient developed de novo urge urinary incontinence. Our results demonstrated that a transvaginal ultrasound-guided BoNT-A injection was efficacious and safe in the treatment of underactive bladder. [ABSTRACT FROM AUTHOR]

Air pollution is a global problem and can be perceived as a modern-day curse. One way of dealing with it is by finding economical ways to monitor and forecast air quality. Accurately monitoring and forecasting fine particulate matter (PM2.5) concentrations is a challenging prediction task but Internet of Things (IoT) can help in developing economical and agile ways to design such systems. In this paper, we use a historical data-based approach to perform PM2.5 forecasting. A forecasting method is developed which uses exponential smoothing with drift. Experiments and evaluation were performed using the real-time PM2.5 data obtained from large scale deployment of IoT devices in Taichung region in Taiwan. We used the data from 132 monitoring stations to evaluate our model's performance. A comparison of prediction accuracy and computation time between the proposed model and three widely used forecasting models was done. The results suggest that our method can perform PM2.5 forecast for 132 monitoring stations with error as low as 0.16 μ g/ m 3 and also with an acceptable computation time of 30 s. Further evaluation was done by forecasting PM2.5 for next 3 h. The results show that 90 % of the monitoring stations have error under 1.5 μ g/ m 3 which is significantly low. [ABSTRACT FROM AUTHOR]

A virtual tour of the onshore wind farm near Gaomei Wetland, Taichung City, Taiwan, was produced by producing panoramic images of the site by stitching images captured with a full-frame digital single-lens reflex camera and a multi-row panorama instrument, which automatically and precisely divided each scene into several images. Subsequently, the image stitching quality was improved by calculating the root mean square error (RMSE) of tie point matching and adjusting the tie points. Errors due to eccentricity attributed to the camera's relative position to the rotational axis of the multi-row panorama instrument were examined and solved; the effect of the overlap rate on image stitching quality was also investigated. According to the study results, the overlap rate between the original images was inversely proportional to the RMSE and directly proportional to the time required for photography and image processing. The stitching quality was improved by resolving eccentricity and by increasing the number of tie points. The RMSEs of the panoramas of all stations were all less than 5 pixels. Subsequently, multimedia materials providing information on wind turbine attributes were combined with the panorama platform to establish a virtual reality tour platform. The content of the platform could be accessed with a smartphone and viewed with a virtual reality device and could promote both tourist attractions and wind energy. [ABSTRACT FROM AUTHOR]

In the context of extreme climate due to global climate transition, rainwater adaptation in resilient cities is a key issue for countries. The purpose of this study is to identify the rainfall hotspots in urban areas and investigate whether these hotspots have environmental conditions for rainfall adaptation. The study site is located in the Taichung area. This study collects rainfall data from rainfall stations at elevations below 500 m, employs QGIS (quantum GIS) to create an inverse distance weighted graphical distribution of rainfall to determine the hotspots where the maximum and minimum rainfalls occur, identifies the topography, green spaces, water areas, and buildings in the catchment, integrates the coverage area in the project, and estimates the amount of rainwater that could be directly absorbed by the land within the catchment. The results of this study show that, among the rainfall stations at an elevation below 100 m where most urban areas are located, the Taichung rainfall station is the area with the highest number of rainfall events from May to August. Without reliance on gully or river drainage, the natural infiltration of the land in the catchment could only adjust to 80 mm of heavy precipitation within 24 h of the rainfall warning level of the Central Weather Bureau. [ABSTRACT FROM AUTHOR]

Summary: Mesophyll conductance gm determines CO2 diffusion rates from mesophyll intercellular air spaces to the chloroplasts and is an important factor limiting photosynthesis. Increasing gm in cultivated plants is a potential strategy to increase photosynthesis and intrinsic water use efficiency (WUEi). The anatomy of the leaf and metabolic factors such as aquaporins and carbonic anhydrases have been identified as important determinants of gm. However, genes involved in the regulation and modulation of gm remain largely unknown.In this work, we investigated the role of heterotrimeric G proteins in gm and drought tolerance in rice d1 mutants, which harbor a null mutation in the Gα subunit gene, RGA1.d1 mutants in both cv Nipponbare and cv Taichung 65 exhibited increased gm, fostering improvement in photosynthesis, WUEi, and drought tolerance compared with wild‐type. The increased surface area of mesophyll cells and chloroplasts exposed to intercellular airspaces and the reduced cell wall and chloroplast thickness in the d1 mutant are evident contributors to the increase in gm.Our results indicate that manipulation of heterotrimeric G protein signaling has the potential to improve crop WUEi and productivity under drought. [ABSTRACT FROM AUTHOR]

Background: Knee osteoarthritis (OA) is a common clinical disease. Knee pain is the major symptom of knee OA and the primary reason why patients seek treatment. Fu's subcutaneous needling (FSN) has been used to treat knee OA for more than 20 years. However, the establishment of treatment methods and rigorous evaluation of FSN's efficacy are still lacking. A randomized single-blind clinical trial will be conducted to evaluate whether FSN treatment can immediately alleviate pain due to knee OA surrounding the patella and the curative effective of 1-week and 2-week treatments. In addition, the feasibility and initial effect of FSN treatment for patients with knee OA will be discussed. Materials and Methods: Patients with confirmed knee OA, as diagnosed by doctors using X-ray films or from clinical symptoms, who are over 50 years old will be participants recruited. They will be randomly assigned either FSN treatment or transcutaneous electrical nerve stimulation treatment. In addition, their pressure pain threshold, muscle tone of lower leg muscle, and physical ability will be measured. Participants will be asked to complete the questionnaires of Western Ontario and McMaster Universities Osteoarthritis Index and Lequesne' index as the measurements for quality of life. Results: The findings of this study will reveal whether FSN or transcutaneous electrical nerve stimulation is clinically efficacious for treating pain due to knee OA, with respect to muscle stiffness, gait, dynamic balance, the pressure pain threshold, and quality of life before and after treatment. Study Registration: This study is approved by the Research Ethics Committee of China Medical University & Hospital, Taichung, Taiwan (CMUH107-REC3-027) and registered at the ClinicalTrials.gov Protocol Registration and Results System (registration number NCT04356651). [ABSTRACT FROM AUTHOR]

Xanthomonas Oryzae pv. oryzae (Xoo) causes bacterial blight and Rhizoctonia solani (R. solani) causes sheath blight in rice accounting for >75% of crop losses. Therefore, there is an urgent need to develop strategies for the mitigation of these pathogen infections. In this study, we report the antimicrobial efficacy of Cholic Acid-Glycine Conjugates (CAGCs) against Xoo and R. solani. We show that CAGC C6 is a broad-spectrum antimicrobial and is also able to degrade biofilms. The application of C6 did not hamper plant growth and showed minimal effect on the plant cell membranes. Exogenous application of C6 on pre-infection or post-infection of Xoo on rice susceptible genotype Taichung native (TN1) can mitigate the bacterial load and improve resistance through upregulation of plant defense genes. We further demonstrate that C6 can induce plant defense responses when seeds were primed with C6 CAGC. Therefore, this study demonstrates the potential of CAGCs as effective antimicrobials for crop protection that can be further explored for field applications. [ABSTRACT FROM AUTHOR]

In this study, we introduce a newly developed upper-air observational instrument for atmospheric research. The "Storm Tracker" is an ultra-lightweight (about 20 g including battery), multi-channel simultaneous capable radiosonde designed by the Department of Atmospheric Sciences at National Taiwan University. Developed in 2016, the Storm Tracker aims to provide an alternative for observing atmospheric vertical profiles with a high temporal resolution, especially the lower-level atmosphere under severe weather conditions such as extreme thunderstorms and tropical cyclones. Field experiments were conducted as trial runs in Wu-Chi, Taichung, Taiwan, to examine the ability of the Storm Tracker to observe the boundary layer, in addition to the intercomparison between the Storm Tracker and the widely used Vaisala RS41-SGP radiosonde. Among the co-launches of the Storm Tracker and Vaisala RS41 radiosondes, the measurements of pressure, wind speed, and wind direction are highly consistent between the measurements of the Storm Tracker and the Vaisala RS41-SGP. However, a significant daytime warm bias in the Storm Tracker was found due to solar heating. A metal shield specifically for the Storm Tracker was thus installed and showed mitigation for the warm biases and the overall variance. With the much lower costs of the radiosondes and the simultaneous multi-channel receiver, the Storm Tracker system has shown great potential for high-frequency observational needs in atmospheric research. [ABSTRACT FROM AUTHOR]

In recent years, the Taiwan government has been calling for the use of public transportation and has been popularizing pollution-reducing green vehicles. Passenger transport operators are being encouraged to replace traditional buses with electric buses, to increase their use in urban transportation. Reduced energy consumption and operating costs are important operational benefits for passenger transport operators, and driving behavior has a significant impact on fuel consumption. Although many literatures or real-world systems have addressed the issues related to reducing energy consumption with electric buses, these works do not involve the records collected from an on-vehicle battery management system (BMS). Accordingly, the results of analyses of existing works lack in-depth discussions, and therefore the applicability of existing works is insignificant. Therefore, in this study, driving data were collected using a battery management system (BMS), and vehicular power consumption was classified according to energy efficiency. Then, decision trees and random forest were applied to construct energy consumption analytical models. Finally, the driving behaviors that influence energy consumption were investigated. A case study was conducted in which a Taichung passenger transport operator's electric bus driving data on urban routes were collected to construct energy consumption analytical models. The data consisted of two parts, i.e., vehicle records and route records. On the basis of these records, we considered the practicability and applicability of the analytical models by transforming the unstructured records into raw data. Passenger transport operators and drivers can leverage the obtained eco-driving indicators for different bus routes for energy savings and carbon reduction. [ABSTRACT FROM AUTHOR]

In other studies the Integrated Process Rate (IPR) method was widely used to analyze the impact of various physical and chemical processes and their relative significance on PM 2.5 in pollution episodes for specific sites; however, sources of pollution and their effect in planning emission control strategies were not considered. Using results of a brute force source sensitivity (BFSS) method may complement IPR. This paper integrates CMAQ-IPR and BFSS to examine the causes of a PM 2.5 episode on Jan 15, 2010 across two air quality monitoring stations in Taichung, Taiwan (Shalu, a rural station and Situn, an urban station). Two pollution deterioration events (time intervals) were observed and simulated. When only CMAQ-IPR was used for simulation, the results revealed most pollution (>60%) was from local sources at the Situn Station. The two deterioration intervals differed however, as interval 1 showed a contribution from local emissions (49%), vertical advection (41%) and aerosols processes (10%). Interval 2 at Shalu Station was categorized as a downwind monitoring station, where emission from the grid constituted only 37%, and the majority of pollutants travelling by horizontal advection (56%), and to some extent, aerosols process (6%). Simulation by integrating IPR and BFSS (including diesel vehicles, gasoline vehicles/motorcycles, construction/road dust, iron/steel industries, and power plants around Taiwan) rendered to the type of physical or chemical process in which pollutants went through and its impact on the concentration of PM 2.5 in the air quality monitoring station, which helped planning of emission control measures. Simulation results indicated improvement of PM 2.5 concentrations in Situn and Shalu would be limited (only 0.2–4.2% contribution to deteriorating PM 2.5 levels at the stations) even the emissions of the power plants and iron/steel industries in whole Taiwan were under control. However, by controlling the emissions of diesel vehicles, gasoline vehicles/motorcycles, and construction/road dust in whole Taiwan, the improvent is much enhanced (49–79% contribution to deteriorating PM 2.5 levels at the stations), but it cost a lot. Nonethless, the improvement was quite significant by controlling the local emissions (around the monitoring station) of diesel vehicles, gasoline vehicles/motorcycles, and construction/road dust for Situn Station as they accounted for 72–85% of these three sources contribution to deteriorating PM 2.5 levels at the station. For Shalu Station, it required a wide area of controlling the emissions from diesel vehicles, gasoline vehicles/motorcycles, and construction/road dust because there was 22–53% of these three sources contribution to deteriorating PM 2.5 levels at the station from horizontal or vertical advection. Image 1 • Combination of BFSS and IPR is applied in the development of control strategies. • Improving Situn (urban) PM 2.5 requires only controlling the nearby specific sources. • Improving Shalu (rural) PM 2.5 requires a wide area of controlling emission sources. [ABSTRACT FROM AUTHOR]

Air pollution is one of the most important global environmental issues. Taiwan Environmental Protection Agency (EPA) is currently using an Air Quality Index (AQI) to measure and monitor its national air quality. The main objective of this study is to assess the air quality per hour every month in Taichung City of Taiwan from 2014 to 2016 based on the nonconformance probability of the AQI index. The nonconformance probability is defined as the probability that a characteristic of interest falls outside of an acceptance region. A lower confidence bound for the nonconformance probability is applied to test whether the AQI index value exceeds a warning threshold, and then the government could issue warnings according to the decision made by such statistical inference. An unbalanced two-way random effects model is presented for fitting the AQI index values. We evaluate three different lower confidence bound construction methods, including a t-based, an adjusted t-based and a generalized pivotal quantity (GPQ) based methods, through a detailed simulation study. Finally, a hybrid method of the t-based and the adjusted t-based estimators is recommended for practical use. [ABSTRACT FROM AUTHOR]

Although the study of Mazuism has been popular among scholars, few have attempted to touch upon its religious tourist behaviour; however, as the purpose of their travel is to worship at the Mazu Temple, it is thus, a tourism destination. Therefore, from the perspective of religious sustainable operation, it is important to understand the tourist behavior patterns of religious tourists visiting Mazu Temple. The purpose of this study is to analyze the interrelationships between destination image, service quality, perceived value, satisfaction, and behavioural intention. This study is conducted with convenience sampling methods for tourists visiting Jenn Lann Temple in Dajia, Taichung, Taiwan, and a total of 408 valid questionnaires are obtained. The valid questionnaires collected in this study are statistically analysed using descriptive statistics and PLS. The results show that destination image, service quality, perceived value, and satisfaction have positive impacts on tourists' behavioural intention. According to the results of the above analysis, this study constructs a religious tourism behaviour model of Mazu believers and gives management advice to the Mazu Temple. [ABSTRACT FROM AUTHOR]

Recently, the R package has become a popular tool for big data analysis due to its several matured software packages for the data analysis and visualization, including the analysis of air pollution. The air pollution problem is of increasing global concern as it has greatly impacts on the environment and human health. With the rapid development of IoT and the increase in the accuracy of geographical information collected by sensors, a huge amount of air pollution data were generated. Thus, it is difficult to analyze the air pollution data in a single machine environment effectively and reliably due to its inherent characteristic of memory design. In this work, we construct a distributed computing environment based on both the softwares of RHadoop and SparkR for performing the analysis and visualization of air pollution with the R more reliably and effectively. In the work, we firstly use the sensors, called EdiGreen AirBox to collect the air pollution data in Taichung, Taiwan. Then, we adopt the Inverse Distance Weighting method to transform the sensors' data into the density map. Finally, the experimental results show the accuracy of the short-term prediction results of PM2.5 by using the ARIMA model. In addition, the verification with respect to the prediction accuracy with the MAPE method is also presented in the experimental results. [ABSTRACT FROM AUTHOR]

Background: Heading time is an important trait for regional and seasonal adaptabilities in rice, and is controlled by genetic factors in relation with environmental factors, mainly day length and temperature. The following genes controlling heading were examined for their responses to six different environmental conditions involving different day lengths using five early near-isogenic lines (NILs) of T65-R and three late NILs of T65wx: two earliness genes, Ef1 and Efx controlling basic vegetative phase (BVG), and m-Ef1, the enhancer to the former gene; and two lateness genes, Se1-pat(t) and se-pat controlling photo-sensitivity and BVG, respectively. T65-R and T65-T were different accessions of Taichung 65. T65wx is a NIL of T65-T carrying wx. Results: The five early NILs of T65-R were in the order of ER50 (Ef1, Efx, m-Ef1) < ER40 (Ef1, m-Ef1) ≤ ER20 (Ef1, Efx) < ER1 (Ef1) ≤ ER21 (Efx) < T65-R regarding days to heading (DTH) under two spring-sowing and one summer-sowing paddy field (PF) conditions. The three late NILs of T65wx were in the order of LF3 (Se1-pat(t)) ≤ LF2 (Se1-pat(t), se-pat) ≤ T65wx < LF1 (se-pat) under two short-day conditions (10-h photoperiod condition with artificial-light and natural short-day condition from autumn to winter). The NILs and T65wx were in the order of T65wx < LF3 < LF1 < LF2 under the two spring-sowing PF (long day) conditions. T65-R (Ac-ef1) was 2.8 or 5.1 days earlier in DTH than T65-T (ac-ef1) under the two spring-sowing PF conditions. However, T65-R was 19 and 10 days earlier than T65-T under the two short-day conditions. Conclusions: Earliness gene(s) and their combinations reduced DTH regardless of photoperiod lengths. Se1-pat(t) increased DTH under long-day conditions but decreased it under short-day conditions, while se-pat elongated DTH under both short-day and long-day conditions indicating that se-pat is responsible for BVG. The se-pat increased DTH by adding its effect over that of Se1-pat(t) under long-day conditions. However, this increasing effect of DTH by se-pat was almost completely masked when it coexisted with Se1-pat(t) under the short-day conditions. Notably, the response of Ac-ef1 to day length was found to delay heading under the short-day conditions. [ABSTRACT FROM AUTHOR]

Due to the special hydrographic and physiographic conditions in Taiwan, flooding is likely to occur in the middle and lower reaches of a plain whenever serious rainstorm events occurred. Note worthily, the loss of lives and property caused by flooding are always most considerable in a metropolitan area, and the densely distributed buildings would, not only increase the impervious area, but also decrease the water storage area. Furthermore, a large number of intensive buildings have changed the original land flow conditions, resulting in a beam shrinking flow and the additional form drag phenomenon, which makes the flooding phenomenon more serious. The main purpose of this research is to find the correlation between building coverage and the Manning's coefficient n through a water flume model experiment. To probe into this issue, the Manning's roughness adjustment is further divided into a part caused by the surface impedance and a part caused by the building impedance. Thus, building coverage can be added to the general computing grid to reflect the flooding situation with buildings. The two-dimensional inundation model, based on this research, was applied to Taichung City for an actual case simulation. The simulation result of Typhoon Kalmaegi showed that the presented model can obtain a more accurate flooding situation in urban area by considering the blockage effects of buildings and adjusting the surface roughness. [ABSTRACT FROM AUTHOR]

The outbreak of the new coronavirus pneumonia (Coronavirus disease 2019, COVID-19) created a serious impact on the lives of people around the world. Humans, affected by the COVID-19 virus, must reduce related activities to suppress the spread of this disease. However, the pandemic had a positive impact on the environment due to reduced outdoor activities. The correlation between reduced human outdoor activities and health effects was investigated in this study through two Metropolitan parks in Taichung, Taiwan. The developed low-cost air quality sensors were installed in these two parks to detect the variances in PM2.5 concentrations during the epidemic outbreak. Experimental results indicated that PM2.5 concentrations in these two parks were reduced from about 23.25 and 22.96 μg/m3 to 8.19 and 8.48 μg/m3, respectively, the median absolute deviations (MAD) decreased from 4.21 and 4.57 to 1.71 and 1.35, respectively after the epidemic outbreak, and the calculated standard deviation of all normal-to-normal interval (SDNN) and the ratio of low-frequency power to high-frequency (LF/HF) indicated that the drops of PM2.5 concentrations caused the increased health-related benefits by 73.53% with the variances being low. These results showed that the PM2.5 concentrations displayed high correlations with human activities, which also played important roles in human health effects. [ABSTRACT FROM AUTHOR]

With the widespread vaccination against COVID-19, people began to resume regional tourism. Outdoor attractions, such as leisure agricultural parks, are particularly attractive because they are well ventilated and can prevent the spread of COVID-19. However, during the COVID-19 pandemic, the considerations around choosing a leisure agricultural park are different from usual, and will be affected by uncertainty. Therefore, this research proposes a fuzzy collaborative intelligence (FCI) approach to help select leisure agricultural parks suitable for traveler groups during the COVID-19 pandemic. The proposed FCI approach combines asymmetrically calibrated fuzzy geometric mean (acFGM), fuzzy weighted intersection (FWI), and fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (fuzzy VIKOR), which is a novel attempt in this field. The effectiveness of the proposed FCI approach has been verified by a case study in Taichung City, Taiwan. The results of the case study showed that during the COVID-19 pandemic, travelers (especially traveler groups) were very willing to go to leisure agricultural parks. In addition, the most important criterion for choosing a suitable leisure agricultural park was the ease of maintaining social distance, while the least important criterion was the distance from a leisure agricultural park. Further, the successful recommendation rate using the proposed methodology was as high as 90%. [ABSTRACT FROM AUTHOR]

The Community Multiscale Air Quality (CMAQ) measurement was employed for evaluating the effectiveness of fine particulate matter control strategies in Taiwan. There are three scenarios as follows: (I) the 2014 baseline year emission, (II) 2020 emissions reduced via the Clean Air Act (CAA), and (III) other emissions reduced stringently via the Clean Air Act. Based on the Taiwan Emission Data System (TEDs) 8.1, established in 2014, the emission of particulate matter 2.5 (PM2.5) was 73.5 thousand tons y−1, that of SOx was 121.3 thousand tons y−1, and that of NOx was 404.4 thousand tons y−1 in Taiwan. The CMAQ model simulation indicated that the PM2.5 concentration was 21.9 μg m−3. This could be underestimated by 24% in comparison with data from the ambient air quality monitoring stations of the Taiwan Environmental Protection Administration (TEPA). The results of the simulation of the PM2.5 concentration showed high PM2.5 concentrations in central and southwestern Taiwan, especially in Taichung and Kaohsiung. Compared to scenario I, the average annual concentrations of PM2.5 for scenario II and scenario III showed reductions of 20.1% and 28.8%, respectively. From the results derived from the simulation, it can be seen that control of NOx emissions may improve daily airborne PM2.5 concentrations in Taiwan significantly and control of directly emitted PM2.5 emissions may improve airborne PM2.5 concentrations each month. Nevertheless, the results reveal that the preliminary control plan could not achievethe air quality standard. Therefore, the efficacy and effectiveness of the control measures must be considered to better reduce emissions in the future. [ABSTRACT FROM AUTHOR]

To study the effects of deep-ocean water concentrate (DOWC) on sake quality, Taichung No. 10 indica rice (Oryza sativa subsp. indica) and Tainan No. 11 japonica rice (O. sativa subsp. japonica) were used as raw materials, and basic physicochemical property parameters in shochu were analyzed differentially. Sake fermentation mash analysis results revealed that DOWC addition did not significantly affect the basic physicochemical properties during sake brewing, but it significantly reduced citric acid and malic acid contents in Taichung No. 10 indica rice sake sample by 52–66% and 73–93%, respectively. DOWC addition significantly increased citric acid content in Tainan No. 11 japonica rice sake sample by 32–202%. Rice shochu analysis results revealed that DOWC addition significantly increased isoamyl acetate, ethyl hexanoate, and ethyl octanoate contents in shochu made from japonica rice and indica rice, respectively. The results indicate that rice variety directly affects the types of volatile compounds in rice shochu. Principal component analysis and sensory evaluation results revealed that DOWC addition affected the composition of volatile compounds in the two types of rice shochu and resulted in differences in flavor evaluation. DOWC addition affects yeast metabolites and directly changes the volatile compound composition and flavor of rice shochu. [ABSTRACT FROM AUTHOR]

Background: Renal function is a key factor of cardiovascular disease. Carotid intima-media thickness (IMT) has been widely used as a marker of early subclinical atherosclerosis. The determinants of cystatin C, a novel marker of renal function, have not been extensively studied in the Asian population. This study aimed to assess the determinants of cystatin C and explore whether carotid thickening was associated with urinary albumin-creatinine ratio and cystatin C in community-living Taiwanese adults.Methods: A cross-sectional study was conducted on participants from Taichung City, Taiwan. All the participants underwent carotid ultrasonography. Carotid IMT-mean and IMT-maximum were derived. Kidney biomarkers were measured on the basis of urinary albumin-to-creatinine ratio (ACR) and cystatin C. Multiple linear regression analysis was used.Results: A total of 1032 individuals were recruited, and 469 (45.44%) of them were men. An increased cystatin C level was significantly associated with older age, male gender, lack of physical activity, low HDL cholesterol, abdominal obesity, high hs-CRP, and high ACR. The multivariate-adjusted mean carotid IMT-mean and IMT-maximum values significantly increased by 80.49 and 195.23 μm for every one unit of increase in cystatin C level and by 0.07 and 0.14 μm for every one unit of increase in ACR, respectively (all p < 0.001 except ACR on IMT-maximum with p < 0.01). Lack of physical activity, low HDL, abdominal obesity, high hs-CRP, and high ACR were the determinants of cystatin C.Conclusion: Cystatin C and ACR were strongly and linearly associated with carotid thickening, a marker of subclinical atherosclerosis. [ABSTRACT FROM AUTHOR]

Accurate weather data are important for planning our day-to-day activities. In order to monitor and predict weather information, a two-phase weather management system is proposed, which combines information processing, bus mobility, sensors, and deep learning technologies to provide real-time weather monitoring in buses and stations and achieve weather forecasts through predictive models. Based on the sensing measurements from buses, this work incorporates the strengths of local information processing and moving buses for increasing the measurement coverage and supplying new sensing data. In Phase I, given the weather sensing data, the long short-term memory (LSTM) model and the multilayer perceptron (MLP) model are trained and verified using the data of temperature, humidity, and air pressure of the test environment. In Phase II, the trained learning model is applied to predict the time series of weather information. In order to assess the system performance, we compare the predicted weather data with the actual sensing measurements from the Environment Protection Administration (EPA) and Central Weather Bureau (CWB) of Taichung observation station to evaluate the prediction accuracy. The results show that the proposed system has reliable performance at weather monitoring and a good forecast for one-day weather prediction via the trained models. [ABSTRACT FROM AUTHOR]

In this study, we proposed a semi-automated and interactive scheme for organ contouring in radiotherapy planning for patients with non-small cell lung cancers. Several organs were contoured, including the lungs, airway, heart, spinal cord, body, and gross tumor volume (GTV). We proposed some schemes to automatically generate and vanish the seeds of the random walks (RW) algorithm. We considered 25 lung cancer patients, whose computed tomography (CT) images were obtained from the China Medical University Hospital (CMUH) in Taichung, Taiwan. The manual contours made by clinical oncologists were taken as the gold standard for comparison to evaluate the performance of our proposed method. The Dice coefficient between two contours of the same organ was computed to evaluate the similarity. The average Dice coefficients for the lungs, airway, heart, spinal cord, and body and GTV segmentation were 0.92, 0.84, 0.83, 0.73, 0.85 and 0.66, respectively. The computation time was between 2 to 4 min for a whole CT sequence segmentation. The results showed that our method has the potential to assist oncologists in the process of radiotherapy treatment in the CMUH, and hopefully in other hospitals as well, by saving a tremendous amount of time in contouring. [ABSTRACT FROM AUTHOR]

The brown planthopper (BPH: Nilaparvata lugens Stål.) is a major pest of rice, Oryza sativa, in Asia. Host plant resistance has tremendous potential to reduce the damage caused to rice by the planthopper. However, the effectiveness of resistance genes varies spatially and temporally according to BPH virulence. Understanding patterns in BPH virulence against resistance genes is necessary to efficiently and sustainably deploy resistant rice varieties. To survey BPH virulence patterns, seven near-isogenic lines (NILs), each with a single BPH resistance gene (BPH2-NIL, BPH3-NIL, BPH17-NIL, BPH20-NIL, BPH21-NIL, BPH32-NIL and BPH17-ptb-NIL) and fifteen pyramided lines (PYLs) carrying multiple resistance genes were developed with the genetic background of the japonica rice variety, Taichung 65 (T65), and assessed for resistance levels against two BPH populations (Hadano-66 and Koshi-2013 collected in Japan in 1966 and 2013, respectively). Many of the NILs and PYLs were resistant against the Hadano-66 population but were less effective against the Koshi-2013 population. Among PYLs, BPH20+BPH32-PYL and BPH2+BPH3+BPH17-PYL granted relatively high BPH resistance against Koshi-2013. The NILs and PYLs developed in this research will be useful to monitor BPH virulence prior to deploying resistant rice varieties and improve rice's resistance to BPH in the context of regionally increasing levels of virulence. [ABSTRACT FROM AUTHOR]

Wild rice relatives having the same AA genome as domesticated rice (Oryza sativa) comprise the primary gene pool for rice genetic improvement. Among them, O. meridionalis and O. rufipogon are found in the northern part of Australia. Three Australian wild rice strains, Jpn1 (O. rufipogon), Jpn2, and W1297 (O. meridionalis), and one cultivated rice cultivar Taichung 65 (T65) were used in this study. A recurrent backcrossing strategy was adopted to produce chromosomal segment substitution lines (CSSLs) carrying chromosomal segments from wild relatives and used for trait evaluation and genetic analysis. The segregation of the DNA marker RM136 locus on chromosome 6 was found to be highly distorted, and a recessive lethal gene causing abortion at the seed developmental stage was shown to be located between two DNA markers, KGC6_10.09 and KGC6_22.19 on chromosome 6 of W1297. We name this gene as SEED DEVELOPMENT 1 (gene symbol: SDV1). O. sativa is thought to share the functional dominant allele Sdv1-s (s for sativa), and O. meridionalis is thought to share the recessive abortive allele sdv1-m (m for meridionalis). Though carrying the sdv1-m allele, the O. meridionalis accessions can self-fertilize and bear seeds. We speculate that the SDV1 gene may have been duplicated before the divergence between O. meridionalis and the other AA genome Oryza species, and that O. meridionalis has lost the function of the SDV1 gene and has kept the function of another putative gene named SDV2. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) printing has great potential for establishing a ubiquitous service in the medical industry. However, the planning, optimization, and control of a ubiquitous 3D printing network have not been sufficiently discussed. Therefore, this study established a collaborative and ubiquitous system for making dental parts using 3D printing. The collaborative and ubiquitous system split an order for the 3D printing facilities to fulfill the order collaboratively and forms a delivery plan to pick up the 3D objects. To optimize the performance of the two tasks, a mixed-integer linear programming (MILP) model and a mixed-integer quadratic programming (MIQP) model are proposed, respectively. In addition, slack information is derived and provided to each 3D printing facility so that it can determine the feasibility of resuming the same 3D printing process locally from the beginning without violating the optimality of the original printing and delivery plan. Further, more slack is gained by considering the chain effect between two successive 3D printing facilities. The effectiveness of the collaborative and ubiquitous system was validated using a regional experiment in Taichung City, Taiwan. Compared with two existing methods, the collaborative and ubiquitous 3D printing network reduced the manufacturing lead time by 45% on average. Furthermore, with the slack information, a 3D printing facility could make an independent decision about the feasibility of resuming the same 3D printing process locally from the beginning. [ABSTRACT FROM AUTHOR]

Wheat is a staple food worldwide, but its productivity is reduced by salt stress. In this study, the mitigative effects of 22 μM selenium (Se) on seedlings of the wheat (Triticum aestivum L.) cultivar Taichung SEL. 2 were investigated under different salt stress levels (0, 100, 200, 300, and 400 mM NaCl). Results of the antioxidative capacity showed that catalase (CAT) activity, non-enzymatic antioxidants (total phenols, total flavonoids, and anthocyanins), 1,1-Diphenyl-2-Picryl-Hydrazyl (DPPH) radical-scavenging activity, and the reducing power of Se-treated seedlings were enhanced under saline conditions. The more-stabilized chlorophyll fluorescence parameters (maximal quantum yield of photosystem II (Fv/Fm), minimal chlorophyll fluorescence (F0), effective quantum yield of photosystem II (ΦPSII), quantum yield of regulated energy dissipation of photosystem II (Y(NPQ)), and quantum yield of non-regulated energy dissipation of photosystem II (Y(NO)) and the less-extensive degradation of photosynthetic pigments (total chlorophyll and carotenoids) in Se-treated seedlings were also observed under salt stress. The elongation of shoots and roots of Se-treated seedling was also preserved under salt stress. Protection of these physiological traits in Se-treated seedlings might have contributed to stable growth observed under salt stress. The present study showed the protective effect of Se on the growth and physiological traits of wheat seedlings under salt stress. [ABSTRACT FROM AUTHOR]