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While hydrological models aim to represent the hydrological behaviour of catchments, many of them have been streamlined on the exclusive basis of streamflow simulation performance, i.e. among the possible parameter sets, the 'optimal' is the one which brings the best simulation of streamflow during the calibration period. However, we sometimes encounter 'optimal' sets which perform well in discharge simulation but yield unrealistic simulations of other fluxes (e.g. actual evaporation fluxes, inter-catchment groundwater fluxes). Previous studies tried to constrain the exploration of parameter space with measurements complementary to river discharge: this application of extra information aims to increase the physical realism of the model compared to discharge-only calibration. In this study, we carry out an original investigation to take advantage of the spatial patterns of the complementary data in order to drive the calibration towards a more spatially consistent solution.We propose here a feasibility test, to constrain the spatial consistency of fluxes of a semi-distributed GR model (GRSD). Our study area is the Somme catchment (6100 km2 ) with 17 internal gauging stations, each of them having more than 15 years of discharge measurement. As a first step, we use the long-term actual evaporation from Budyko-estimation as an extra constraint, which has been widely used for describing spatial patterns of climate. In the second step, we develop a criterion describing the spatial consistency between the pattern of measured and simulated fluxes. By constraining the model with extra information, the model is expected to yield a more consistent simulation of fluxes in comparison with the classical calibration practice. Moreover, we analysed the impact of this additional constraint on the spatial organisation of IGF over the catchment as both the other components in water balance analysis, actual evaporation and discharge, are constrained.

Banana contains high levels of resistant starch (RSC), which resists digestion. Taiwan is a major producer of banana; however, little work has been reported on their specific characteristics. This study was conducted to investigate the characteristics and RSC of ripe and unripe Taiwanese bananas. The characteristics and RSC significantly differed between varieties and ripening stages. The hardness, L*, pH values, swelling power, total starch, and amylose contents of unripe bananas were significantly higher than ripe bananas, while the starch content depended on the variety and ripening stage. Therefore, Taiwanese bananas could be useful RS source for manufacturing functional foods.

The coronavirus disease 2019 (COVID-19) pandemic with high infectivity and mortality has caused severe social and economic impacts worldwide. Growing reports of COVID-19 patients with multi-organ damage indicated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) may also disturb the cardiovascular system. Herein, we used human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (iCMs) as the in vitro platform to examine the consequence of SARS-CoV2 infection on iCMs. Differentiated iCMs expressed the primary SARS-CoV2 receptor angiotensin-converting enzyme-II (ACE2) and the transmembrane protease serine type 2 (TMPRSS2) receptor suggesting the susceptibility of iCMs to SARS-CoV2. Following the infection of iCMs with SARS-CoV2, the viral nucleocapsid (N) protein was detected in the host cells, demonstrating the successful infection. Bioinformatics analysis revealed that the SARS-CoV2 infection upregulates several inflammation-related genes, including the proinflammatory cytokine tumor necrosis factor-α (TNF-α). The pretreatment of iCMs with TNF-α for 24 h, significantly increased the expression of ACE2 and TMPRSS2, SASR-CoV2 entry receptors. The TNF-α pretreatment enhanced the entry of GFP-expressing SARS-CoV2 pseudovirus into iCMs, and the neutralization of TNF-α ameliorated the TNF-α-enhanced viral entry. Collectively, SARS-CoV2 elevated TNF-α expression, which in turn enhanced the SARS-CoV2 viral entry. Our findings suggest that, TNF-α may participate in the cytokine storm and aggravate the myocardial damage in COVID-19 patients.

This study investigated the efficiency of plasma-activated water (PAW) on the reduction of pesticides, namely, metribuzin and metobromuron, and the effect of PAW treatment on the quality of fresh chrysanthemums. The reduction efficiencies reached 74.3% for metribuzin and 38.2% for metobromuron after 240 s of PAW treatment. Compared with reverse osmosis (RO) water, PAW achieved significantly higher pesticide reductions because of its higher acidity, enhanced oxidizing ability, and increased formation of reactive species. Moreover, when compared with metobromuron, metribuzin was reduced more efficiently irrespective of the RO water or PAW treatments because of its higher water solubility, lower log octanol-water partition coefficient, and more oxidizable chemical structure. Additionally, the PAW treatment did not cause adverse changes to the chrysanthemums' color, total flavonoid content, radical scavenging, or metal chelating activities, but it did cause a slight decrease in the chrysanthemums' aroma compounds and total reducing power. This study successfully demonstrated the effectiveness of PAW for reducing pesticides in herbal flowers like chrysanthemums and reveals PAW's promising potential to treat foods with non-smooth surfaces.

AIM The aim of this study was to develop and initially assess the psychometric properties of the Caregiver Caregiving Self-Efficacy Scale-Oral Cancer (CSES-OC). METHODS In total, 28 items in the Caregiver Caregiving Self-Efficacy Scale-Oral Cancer were originally employed for a reliability and validity test based on expert suggestions and qualitative findings. The Cronbach's alpha coefficient and test-retest reliability were evaluated with the pilot sample, which included 30 caregivers. The main test, which included 107 caregivers during May 2016 to 2018, was used to execute the exploratory factor analysis (EFA) and concurrent validity. RESULTS The results of the main test showed a Cronbach's alpha coefficient of .95 for the revised 18-item total scale after EFA. Four factors (acquiring resources, managing sudden and uncertain patient conditions, managing patient-related nutritional issues and exploring and making decisions on patient care) were classified from EFA of the Caregiver Caregiving Self-Efficacy Scale-Oral Cancer. The r coefficient was .59 (P

Many food safety issues have occurred in Taiwan during the past decade. Therefore, in 2016, the Taiwan government proposed the "Five rings of food safety" policy to comprehensively protect consumer food supply. Among these policies, the "4-labels-1-Q" approach was adopted to ensure the selection of "retrospective foods" with traceable labels. Hence, this study investigated the association between the degree of recognizing the "4-label-1-Q" food traceability system and risk perceptions, in addition to whether a consumer's purchase intention of fresh foods with food labels changed after enlightenment using an educational film on food labels. In this study, the subjects were defined as the family's main food purchasers. Subsequently, 290 valid questionnaire interviews and film educational materials were administered in Tainan markets and stores. Results showed that risk perception for labeling was significantly affected by label knowledge. Alternatively, age, educational level, and the degree of risk perception influenced purchase intention. Results also showed that after administering the video intervention, the label knowledge and purchase intention increased significantly. However, film education after adjustment for age, educational level, income, and purchase places insignificantly affected risk perception, especially for those who had lower educational levels, including those over the age of 65. First, the public's trust can be boosted through label education among age groups using different channels and methods. Therefore, in the future, encouraging the sale of labeled foods in traditional markets would be a useful strategy. Second, the age, educational level, income, and risk perception of the participants significantly affected the purchase intention. Thus, in the future, this study can be a reference for designing risk communication strategies and promoting traceable agricultural products.

Building materials (BMs) are major contributors to indoor emission sources of volatile organic compounds (VOCs). In this study, 8 kinds of BMs (including conventional and green) for ceiling, cabinetry, and flooring commonly used indoors were tested in a 216 L chamber. Primary emissions of carbonyls (C 1 to C 8 aldehydes and ketones) at 48 h were 75–673 μg m −2 h −1 from conventional BMs, and 62–151 μg m −2 h −1 from green BMs. Primary emissions of BTEX at 48 h were 59–264 μg m −2 h −1 from conventional BMs, and 37–56 μg m −2 h −1 from green BMs. Ozone initiated molar yields of carbonyls were 0.10–2.36 from conventional BMs, and 0.13–0.86 from green BMs. Secondary emissions of carbonyls were 7–150 μg m −2 h −1 from conventional BMs, and 4–73 μg m −2 h −1 from green BMs. Green BMs had lower emissions than conventional analogs, especially for wooden flooring and gypsum board. BMs with mineral content are the most promising materials in this study, given moderately high ozone deposition velocity but generating the least byproducts. Secondary emissions determined in this study demonstrate that moderate indoor ozone concentrations may lead to increased concentrations of carbonyls, especially formaldehyde and acetaldehyde that potentially increase adverse chronic health effects.

This study aims to estimate the ozone deposition velocities of eight commonly used building materials (BMs) which include calcium silicate board (CSB), green calcium silicate board (GCSB), mineral fiber ceiling (MFC), green mineral fiber ceiling (GMFC), gypsum board (GB), green gypsum board (GGB), wooden flooring (WF) and green wooden flooring (GWF). In addition, the impact of physical properties (specific surface area and total pore volume of BM) on ozone removal ability was also explored and discussed. Studies were conducted in a small-scale environmental stainless steel chamber. CSB and GCSB showed the highest ozone deposition velocities, while WF and GWF showed the lowest ozone deposition velocities among test BMs materials. All reaction probabilities were estimated to fall within the order of magnitude of 10−6. Green BMs showed lower reaction probabilities with ozone comparing with non-green BMs except for GGB. Consistent with the trends for deposition velocity, fleecy and porous materials exhibit higher reaction probabilities than smooth, non-porous surfaces. Specific surface area of BM is more closely related to ozone removal than total pore volume of BM with R2 of 0.93 vs. R2 of 0.84. Discussion of Thiele modulus for all test BMs indicates surface reactions are occurring quickly relative to internal diffusion and ozone removal is internal diffusion-limited.

Many organizations are developing their competencies in logistics and green supply chain management (GSCM) in order to maintain competitiveness. When an organization decides to implement GSCM, the administrators always encounter internal and external risk items or difficulties which they know even they dont know. This study therefore proposes an analytic hierarchy model to help the administrators understand the critical risk factors influence the GSCM system initiation, and an aggregative risk degree is indicated which risk grade they are in. Successful influences can help the enterprise under their competitive advantages to appropriate allocation of resources, to further improve the efficiency of resource utilization, and provide enterprises to choose business strategy of the green supply chain management has reached the goal of corporate operating performance and brand management.

It is important issue to select and design a suitable Assistive Input Devices (AID) for disabled people. This study applies the Incomplete Linguistic Preference Relations (InLinPreRa) analytical framework to predicting the success of design Assistive Input Devices (AID) for disabled people implementation. The results demonstrate that the five most important influential factors are (C6) User-friendly interface (0.166) (C4) Budget (0.163), (C5) Stability of Device (0.159), (C3) easy to maintain (0.144), (C1) easy to operate (0.126). The prediction success rate for AID for disabled people system implementation is 62.7%.

This paper is presented fuzzy preference relations approach to forecast the success of implementing advanced manufacturing technology (AMT). In the manufacturing environment, performance measurement is based on different quantitative and qualitative factors. This study proposes an analytic hierarchical prediction model based on fuzzy preference relations to help the organizations become aware of the essential factors affecting the AMT implementation, forecasting the chance of successful implementing AMT, as well as identifying the actions necessary before implementing AMT. Then predicted success/failure values are obtained to enable organizations to decide whether to initiate AMT, inhibit adoption or take remedial actions to increase the possibility of successful AMT initiatives.

This research is regarding the optimized tourism destination selection when tourists choose tourist products or travel destinations. This study adopts the method of Incomplete Linguistic Preference Relations to simplify calculation and speed up the process of comparison and selection of alternative. This method considers only judgments, whereas the tradition analytic hierarchy approach (AHP) takes judgments in a preference matrix with n elements to establish a complete preference relation decision making matrix. According to the importance weights of evaluationcriteria, C was the optimize tourism destination.

Tourist attraction not only plays an important part in sightseeing, but also is the major cause that constitutes tourist products as well as the main consideration when tourists choose tourist products or travel destinations. This paper utilizes the fuzzy preference relations to select a travel location. Pairwise comparisons are conducted to obtain the importance weights of evaluation criteria and the performance rating of alternative locations. By multiplying the importance weights of evaluation criteria and the performance rating, a performance value is determined to rank the alternative locations. Compared with the AHP, the major contributions of this proposed framework are: 1) it just takes comparisons rather than comparisons to obtain a complete decision matrix which has elements; 2) This study identifies the factors that influence the tourists' choice of destination and evaluates the preferences of tourists for destinations.

An RFID digital campus system implementation can enhance convenience in teaching environment, teaching quality and administrative efficiency. When administrators decide to implement an RFID digital campus system, they often encounter unexpected internal and external risk factors and difficulties. Therefore, this study proposes a novel analytic hierarchy model for helping administrators to identify the critical risk factors affecting the RFID digital campus system initiation, and measuring the aggregative risk of implementing an RFID digital campus system. The importance weights of risk factors and possible occurrence ratings of four risk grades (high, medium, low and none) are determined by using consistent fuzzy preference relations. The relative priority weights of evaluators are considered simultaneously by using simple additive weighting method. Multiplying the importance weights of risk factors, the possible occurrence ratings of risk grades and the relative priority weights of evaluators, the aggregative risk degree of implementing an RFID digital campus system is derived. University A in Taiwan is used to demonstrate the computation procedures of this proposed methodology.

This study proposes an analytic hierarchical prediction model based on consistent fuzzy preference relations to help the organizations become aware of the essential factors affecting the implementation Assistive Input Devices (AID). Pairwise comparisons are used to determine the priority weights of influential factors and the ratings of success or failure outcomes amongst decision makers. The subjectivity and vagueness in the prediction procedures are dealt with using linguistic terms quantified in an interval scale [0, 1]. Then predicted success/failure values are obtained to enable organizations to decide whether to initiate knowledge management, inhibit adoption or take remedial actions to increase the possibility of successful AID for disabled. This proposed approach is demonstrated with a real case study involving seven influential factors assessed by eleven evaluators solicited from a special school located in Taiwan.

This paper applies an analytic hierarchical prediction model based on the Multi-Criteria Decision Making with Incomplete Linguistic Preference Relations (InLinPreRa) to help the organizations become aware of the essential factors affecting the Enterprise Resource Planning (ERP), as well as identify the actions necessary before implementing ERP. The subjectivity and vagueness in the prediction procedures are dealt with linguistic variables quantified in an interval [-t, t]. Then predicted success/failure values are obtained to enable organizations to decide whether to initiate ERP, inhibit adoption or take remedial actions to increase the success possibility of ERP. Pairwise comparisons are used to determine the priority weights of influential factors, and the possible occurrence ratings of success or failure outcome amongst decision makers. There are not any inconsistency occurred in this procedures because this proposed approach allows every decision expert to choose an explicit criterion or alternative for the without restriction. When there are n criteria in a decision matrix, only n-1 times of pairwise comparisons are taken. This approach not only improves the efficiency of pairwise comparison compared with the traditional AHP, but also avoids the checking the consistency of linguistic preference relation when the decision makers undertake the pairwise comparison processes.

When there are n criteria or alternatives in a decision matrix, a pairwise comparison methodology of analytic hierarchy process (AHP) with the time of n(n-1)/2 is frequently used to select, evaluate or rank the neighboring alternatives. But while the number of criteria or comparison level increase, the efficiency and consistency of a decision matrix decrease. To solve such problems, this study therefore uses horizontal, vertical and oblique pairwise comparisons algorithm to construct multi-criteria decision making with incomplete linguistic preference relations model (InLinPreRa). The use of pairwise comparisons will not produce the inconsistency, even allows every decision maker to choose an explicit criterion or alternative for index unrestrictedly. When there are n criteria, only n-1 pairwise comparisons need to be carried out, then one can rest on incomplete linguistic preference relations to obtain the priority value of alternative for the decision maker's reference. The decision making assessment model that constructed by this study can be extensively applied to every field of decision science and serves as the reference basis for the future research.

When the school decides to implement the RFID campus-safety system, the administrators always encounter internal and external risk items or difficulties which they know even they don’t know. This study therefore proposes an analytic hierarchy model to help the administrators understand the critical risk factors influence the RFID campus-safety system initiation, and an aggregative risk degree is indicated which risk grade they are in. The importance weights of risk factors and possible occurrence ratings of four risk grade (high-risk, medium-risk, low-risk and none-risk) are determined by using consistent fuzzy preference relations. The relative priority weights of evaluators are taken into consideration at the same time and obtained by simple additive weighting method. By multiplying the importance weights of risk factors, possible occurrence ratings of risk grades and the relative priority weights of evaluators, the aggregative risk degree of implementing RFID campus-safety system.

Researchers of decision making have often shown that It is a complex process that a decision maker is quick and accurate at preferences structure or ordering when he was confronted multiple objectives, multiple criteria, and multiple alternatives. Before the enterprise shifts the operation to RFID, needs to carry on the simulation or the construction feasible deliberation and the appraisal first. In the simulation process, the enterprise may understand that what benefit in essence from RFID. Moreover the enterprise may also further estimate possible impact from the RFID. This study not only applies Multi-Criteria Decision Making with Incomplete Linguistic model (InlinPreRa) and uses horizontal, vertical and oblique pairwise comparison algorithms to construct but also expansion group decision making model. When the decision maker is carrying out the pairwise comparison, the following problems can be avoided: time pressure, lack of complete information, the decision maker is lack of this professional knowledge, or the information provided is unreal and thus it is difficult to obtain information. In this study uses group decision making Matrix to elevate the best RFID supply chain will carry effective and immediate for company. To conclude, this study may be importance in explaining the function of the InlinPreRa Model on decision making, as well as in providing decision makers with a better understanding of the process of the InlinPreRa Model.

This study applies an analytic hierarchical prediction model based on Multi-Criteria Decision Making with Incomplete Linguistic Preference Relations(InLinPreRa) to help the organizations become aware of the essential factors affecting the Enterprise Resource Planning(ERP), as well as identify the actions necessary before implementing ERP. The subjectivity and vagueness in the prediction procedures are dealt with using linguistic terms quantified in an interval scale [-t, t] . Then predicted success/failure values are obtained to enable organizations to decide whether to initiate ERP, inhibit adoption or take remedial actions to increase the possibility of successful ERP. The empirical results not only demonstrate the senior manager support degree, organizational and coordination are the three most important influential factors in the ERP initiative process, but also reveal the applicability and feasibility of reciprocal Incomplete Linguistic Preference Relation(InLinPreRa) for solving complicated hierarchical multiple attribute prediction problems.

The proposes of this study is to ascertain the effect of using Incomplete Linguistic Preference Relations based group decision making under a fuzzy environment to help decision makers select the best one amongst multiple criteria and alternatives. This study not only applies Multi-Criteria Decision Making with Incomplete Linguistic model (InlinPreRa) and uses horizontal, vertical and oblique pairwise comparison algorithms to construct but also expansion group decision making model. When the decision maker is carrying out the pairwise comparison, the following problems can be avoided: time pressure, lack of complete information, the decision maker is lack of this professional knowledge, or the information provided is unreal and thus it is difficult to obtain information. In this study, the Web shops' performances will be evaluated effective and immediate in this model.

This study provides a method to solve the incomplete linguistic preference relations under multi-criteria decision making. The method uses simple calculation and can speed up the process of comparison and selection of alternative. Decision-making experts obtain the matrix by choosing a finite and fixed set of alternatives and set a pairwise comparison based on their different preferences and knowledge. The method considers only n-1 judgments, whereas the traditional analytic hierarchy approach takes n(n -1)/2 judgments in a preference matrix with n elements. By using the method described above, this study evaluates the ERP system suppliers.

Escherichia coli isolates from humans (n=110) and swine (n=61) and Salmonella enterica serovar Choleraesuis isolates (n=95) from swine in southern Taiwan were characterised for antimicrobial resistance patterns and class 1 integrons. All E. coli isolates and S. Choleraesuis isolates were multidrug resistant and demonstrated high resistance to beta-lactams, aminoglycosides, tetracycline, sulfonamides, spectinomycin, chloramphenicol and nalidixic acid. By polymerase chain reaction and DNA sequencing, 104 (61%) E. coli isolates and 31 (33%) S. Choleraesuis isolates were found to carry class 1 integrons. The gene cassette array dfrA12-orfF-aadA2 was the most prevalent (24%) among the human and swine E. coli isolates, whilst the gene cassette array dfrA12-orfF-aadA2-sul1 was the most prevalent (24%) among S. Choleraesuis strains. For E. coil isolates, all class 1 integrons were located on conjugated plasmids. Meanwhile, human and swine E. coli isolates carrying identical gene cassettes were genetically unrelated. Our results revealed that multidrug resistance and class 1 integrons were widely present in E. coli and S. Choleraesuis isolates obtained in Taiwan and that class 1 integrons might play an important role in contributing to the horizontal transfer of antimicrobial resistance.

Salmonella serovars are some of the major bacterial pathogens that can cause sporadic cases and outbreaks of foodborne illness. Based on the sequence data in the V3 region of the 16S rRNA gene, two PCR primer pairs have been designed for the detection of all serovars of Salmonella. However, none of these primers were specific for Salmonella because complete sequence homology with certain non-Salmonella strains has been found within each of them. Thus, the specificities of these two primer pairs could not rely on only one of the two primers. In this study, we modified our previous 16SFI primer by extending one base at the 5' end and three bases at the 3' end. The modified primer, 16S-Sal, was designed with one or more mismatched bases near the 3' end of the primer annealing to the corresponding sequences of non-Salmonella strains. Such modification eliminates interference from Citrobacter freundii and Enterobacter cloacae as occurs with the 16SFI primer. When 16S-Sal and a degenerate primer, 16S-CCR, were used as a primer pair, detection specificity of Salmonella serovars was achieved. Because this primer pair was used for PCR detection of the salmonellae in food samples, such as whole milk and chicken meat, as low as 1 to 9 CFU/g (ml) of the food sample could be detected when a 8-h preculture step was performed prior to the PCR. For chicken meat, the endogenous microflora did not interfere with the PCR results.

Escherichia coli has been the appropriate focus for monitoring of potential enteric pathogens in water and foods. Although several methods have been used for the detection or enumeration of E. coli cells in water and foods, the time and accuracy limitations of these methods suggest the need of a rapid and specific method. By comparison of the gene sequences coding for malic acid dehydrogenase (mdh) of E. coli and non-E. coli strains, two oligonucleotides were designed and their possible use as E. coli-specific PCR primers was tested. All of the 110 E. coli strains tested, including non-pathogenic and various pathogenic strains, generated the expected PCR products with Mw equal to 392 bp. On the other hand, only 97 of these 110 E. coli strains were detectable using the BAM gas production method. With the exception of Shigella strains, non-E. coli strains, including strains of the family of Enterobacteriaceae, did not generate any false positive PCR results. When this PCR system was used for the monitoring of E. coli cells inoculated into water and milk samples, as low as 100 cfu per 100 ml of water or per ml of milk sample could be detected if an 8 h preculture step was performed prior to the PCR. Including the preculture step, the whole PCR detection process may be completed within 12 h.