Preference Values Research Articles

A comprehensive analysis of systematically screened laboratory tests: based on a COVID-19 cohort.

The study aimed at screening indicators with differential diagnosis values and investigating the characteristics of laboratory tests in COVID-19 patients. All the laboratory tests from COVID-19 patients and non-COVID-19 patients in this cohort were included. Test values from the groups during the course, days 1-7, and days 8-14 were analyzed. Mann-Whitney U test, univariate logistic regression analysis, and multivariate regression analysis were performed. Regression models were established to verify the diagnostic performance of indicators. 302 laboratory tests were included in this cohort, and 115 indicators were analyzed; the values of 61 indicators had significant differences (p < 0.05) between groups, and 23 indicators were independent risk factors of COVID-19. During days 1-7, the values of 40 indicators had significant differences (p < 0.05) between groups, while 20 indicators were independent risk factors of COVID-19. During days 8-14, the values of 45 indicators had significant differences (p < 0.05) between groups, and 23 indicators were independent risk factors of COVID-19. About 10, 12, and 12 indicators showed significant differences (p < 0.05) in multivariate regression analysis in different courses respectively, and the diagnostic performance of the model from them was 74.9%, 80.3%, and 80.8% separately. The indicators obtained through systematic screening have preferable differential diagnosis values. Compared with non-COVID-19 patients, the screened indicators indicated that COVID-19 patients had more severe inflammatory responses, organ damage, electrolyte and metabolism disturbance, and coagulation disorders. This screening approach could find valuable indicators from a large number of laboratory test indicators.

A Study on Customer Preference and Economic Value of IPHONE and One Plus

A Study on Customer Preference and Economic Value of IPHONE and One Plus

Comparative analysis of the sensitivity test of the SAW and WP methods in scholarship selection

Decision-makers frequently use the MADM (Multiple Attribute Decision Making) method to assist in solving decision-making issues. This approach can use a variety of algorithms, including Simple Additive Weighting (SAW) and Weighted Product (WP). The challenge in this research is determining which of the SAW and WP approaches is more pertinent or acceptable for solving scenarios involving scholarship recipient selection. Five factors were taken into consideration when deciding who would receive a scholarship: academic achievement index (GPA), parents' income, past accomplishments, participation in student organizations, and the number of parents' dependents. A sensitivity test, which involves altering the weight of each test method's criterion and then comparing the percentage change between the two ways, is one method that can be used to gauge the effectiveness of the MADM method. The SAW method implementation results show that alternative nine (MHS9) has the highest preference value, which is 0.95. The WP method implementation results show that alternative nine (MHS9) has the highest preference value, which is 0.12. The total change in the findings of the sensitivity test for the SAW method is 7.64%, compared to 2.06% for the WP method. Thus, it can be inferred that the SAW approach is thought to be pertinent for addressing the issue of choosing scholarship applicants.

Implementation of Operational Competitiveness Rating Analysis (OCRA) and Rank Order Centroid (ROC) to Determination of Minimarket Location

Minimarket location placement is one of the main capital for the business to progress and develop. In determining the location of the minimarket, various considerations must be taken so that nothing is fatal to the sustainability of the business. The problem that occurs in the company in choosing the placement of minmarket locations, namely the various locations that are chosen, each location has its advantages and disadvantages, each of which can affect the analysis of results and takes a long time to make a decision. So that requires a system that can provide a solution to this problem. In this case the resulting system is a system that is useful for determining location placement for minimarkets using the ROC method as its weighting and the OCRA method as a decision generator. This system can provide a solution in determining the location of minimarkets, from various existing locations. The results of each alternative are more objective and definitive in determining the location of minimarkets in a computerized way. For this reason, it is necessary to have supporting criteria for using a decision support system. Determination of importance weight values on conflicting criteria is generated through a weighting method, namely ROC or Rank Order centroid. The OCRA method or Operational Competitiveness Rating Analysis is a method that can calculate and produce rankings efficiently so that the resulting decisions are accurate. The results obtained from the utilization of this system determine the location of minimarkets using the OCRA method and ROC weighting as well as various conflicting criteria determined by the company and development management in Lubuk Pakam resulting in the highest preference value of 0.673 as a location that is suitable for use as a minimarket

Ranking Startups Using DEMATEL-ANP-Based Fuzzy PROMETHEE II

In entrepreneurship management, the evaluation and selection of startups for acceleration programs, especially technology-based startups, are crucial. This process involves considering numerical and qualitative criteria such as sales, prior startup experience, demand validation, and product maturity. To effectively rank startups based on the varying importance of these criteria, a fuzzy multi-criteria decision-making (MCDM) approach is needed. Although MCDM methods have been successful in handling complex problems, their application in startup selection and evaluating criteria interrelationships from the accelerator perspective is underexplored. To address this gap, a hybrid DEMATEL-ANP-based fuzzy PROMETHEE II model is proposed in this study, facilitating startup ranking and examining interrelationships among factors. The resulting preference values are fuzzy numbers, necessitating a fuzzy ranking method for decision-making. An extension of ranking fuzzy numbers using a spread area-based relative maximizing and minimizing set is suggested to enhance the flexibility of existing ranking MCDM methods. Algorithms, formulas, and a comparative analysis validate the proposed method, while a numerical experiment verifies the viability of the hybrid model. The final ranking of four startup projects is A4&lt;A1&lt;A3&lt;A2 which indicates that startup project A2 has the highest comprehensive potential, followed by startup project A3.

Effects of video self‐modeling on the preference and reinforcer value of toys for children diagnosed with autism spectrum disorder

AbstractA primary characteristic of autism spectrum disorder includes restrictive and repetitive patterns of behavior. Because having few preferred items and activities can lead to social, communicative, and educational barriers, it is important to increase the number of preferred stimuli in the individual's environment. One way to do this is through conditioned reinforcement via observation. Such procedures involve the acquisition of a skill or change in behavior as a result of indirect contact (i.e., observation) with contingencies received by others. While conditioning through observation has been shown to be effective, one novel approach is video self‐modeling. The purpose of the current study was to assess the effects of video self‐modeling on the preference and reinforcer value of toys for children diagnosed with autism spectrum disorder.

Incorporating Prior Beliefs Into Meta-Analyses of Health-State Utility Values Using the Bayesian Power Prior

ObjectivesHealth-state utility values (HSUVs) directly affect estimates of Quality-Adjusted Life-Years and thus the cost-utility estimates. In practice a single preferred value (SPV) is often selected for HSUVs, despite meta-analysis being an option when multiple (credible) HSUVs are available. Nevertheless, the SPV approach is often reasonable because meta-analysis implicitly considers all HSUVs as equally relevant. This article presents a method for the incorporation of weights to HSUV synthesis, allowing more relevant studies to have greater influence. MethodsUsing 4 case studies in lung cancer, hemodialysis, compensated liver cirrhosis, and diabetic retinopathy blindness, a Bayesian Power Prior (BPP) approach is used to incorporate beliefs on study applicability, reflecting the authors’ perceived suitability for UK decision making. Older studies, non-UK value sets, and vignette studies are thus downweighted (but not disregarded). BPP HSUV estimates were compared with a SPV, random effects meta-analysis, and fixed effects meta-analysis. Sensitivity analyses were conducted iteratively updating the case studies, using alternative weighting methods, and simulated data. ResultsAcross all case studies, SPVs did not accord with meta-analyzed values, and fixed effects meta-analysis produced unrealistically narrow CIs. Point estimates from random effects meta-analysis and BPP models were similar in the final models, although BPP reflected additional uncertainty as wider credible intervals, particularly when fewer studies were available. Differences in point estimates were seen in iterative updating, weighting approaches, and simulated data. ConclusionsThe concept of the BPP can be adapted for synthesizing HSUVs, incorporating expert opinion on relevance. Because of the downweighting of studies, the BPP reflected structural uncertainty as wider credible intervals, with all forms of synthesis showing meaningful differences compared with SPVs. These differences would have implications for both cost-utility point estimates and probabilistic analyses.

A reliability-based consensus model and regret theory-based selection process for linguistic hesitant-Z multi-attribute group decision making

In real-life decision making problems, reliability of information is one of the most concerning factors. Accordingly, to avoid the involvement of inconsistent information in a multi-attribute group decision making problem, this study aims to develop a consensus model by considering reliability of experts’ opinions in Z-number framework. To do so, first we reflect human uncertainty in the information system by linguistic hesitant-Z-number (LHZN) that has sufficient description power to express hesitancy, vagueness and reliability of evaluation information in a single form. Then, a novel normal cloud model is developed to handle LHZN information rationally without distorting its originality. Furthermore, we develop the Maclaurin symmetric mean operator based on normal cloud to take into account interrelationships among attributes. Thereafter, the weights of the experts are determined based on dynamic importance score of experts which consist of preference similarity score and reliability score. Afterwards, a group consensus degree is measured based on preference values and their reliability to identify the consensus level among experts. Then, to ameliorate the consensus efficiency, experts’ unreliable behaviours are identified and modified with reference to preference value and reliability. Lastly, a regret theory-based selection process is presented to detect the optimal alternative with respect to multiple attributes. The validity, superiority and advantages of the proposed model are exemplified by two case studies of sustainable zero-carbon measures prioritization for Indian transport sector, and failure mode and effect analysis, respectively.

ORGANOLEPTIC TESTS OF PEMPEK WITH VARIOUS SURIMI FORMULATIONS OF SANGKURIANG CATFISH (Clarias gariepsinus)

This study aims to study various surimi formulations of Sangkuriang catfish (Clarias gariepsinus) for the resulting pempek, using the experimental method using a Randomized Block Design (RBD) arranged in a non-factorial manner with one treatment of various formulations of surimi Sangkuriang catfish (Clarias gariepsinus) consisting of of six factors and repeated four times. Pempek organoleptic test results with hedonic tests on color, aroma, and taste. The highest preference value for the color of pempek made from sangkuriang catfish surimi in the L1 treatment (0.25 parts of sangkuriang catfish surimi and 1.00 parts of tapioca flour) with a clean white pempek color typical of fish pempek with an average value of 4.30 (criterion panelists liked). The highest preference value for the taste and aroma of pempek made from sangkuriang catfish surimi was found in treatment L6 (1.50 parts of sangkuriang catfish surimi and 1.00 parts of tapioca flour) with a savory taste and dominant pempek aroma with an average value of 3 .90 (panelists preferred criteria) and 4.30 (panelists preferred criteria).

Unpacking privacy: Valuation of personal data protection.

Information about individual behaviour is collected regularly by organisations. This information has value to businesses, the government and third parties. It is not clear what value this personal data has to consumers themselves. Much of the modern economy is predicated on people sharing personal data, however if individuals value their privacy, they may choose to withhold this data unless the perceived benefits of sharing outweigh the perceived value of keeping the data private. One technique to assess how much individuals value their privacy is to ask them whether they might be willing to pay for an otherwise free service if paying allowed them to avoid sharing personal data. Our research extends previous work on factors affecting individuals' decisions about whether to share personal data. We take an experimental approach and focus on whether consumers place a positive value on protecting their data by examining their willingness to share personal data in a variety of data sharing environments. Using five evaluation techniques, we systematically investigate whether members of the public value keeping their personal data private. We show that the extent to which participants value protecting their information differs by data type, suggesting there is no simple function to assign a value for individual privacy. The majority of participants displayed remarkable consistency in their rankings of the importance of different types of data through a variety of elicitation procedures, a finding consistent with the existence of stable individual privacy preferences in protecting personal data. We discuss our findings in the context of research on the value of privacy and privacy preferences.

105 Botanical composition, yield, horse preference, and forage and soil nutrient values of grass pastures treated with different soil amendments

Forage is the foundation of a horse's diet, therefore, pasture management is critical to improve horse health and pasture productivity. The objective of this study was to evaluate botanical composition, horse preference, yield, and forage and soil nutrient values of pasture treated with horse manure, horse compost, commercial urea fertilizer, and a no amendment control. Researchers hypothesized soil amendments would increase soil nutrients and yield with minimal effects on botanical composition, preference and forage nutrient value. Replicated (n = 3) plots of established cool-season mixed grass pasture were 3 × 6 m and located in St. Paul, Minnesota. The soil was a Waukegan silt loam with a pH of 6.4 and 47 g kg–1 organic matter. Urea was applied based on initial soil test recommendations, 0.64 cm of compost was applied based on common recommendations, and manure was applied at a rate to represent horse manure deposition in May 2022. Sample collection and grazing periods occurred in May, June, July, August, and October 2022, each over a 2-d period. Botanical composition, average forage height and maturity, soil samples, forage samples, and forage yield were taken immediately before grazing. Horses were allowed to graze all plots for 4 h with preference visuallyassessed at 2- and 4 h post-grazing based on percent removal. Data were analyzed as a randomized complete block design using PROC MIXED in SAS with significance set at P ≤ 0.05. Season-long yield ranged from 2,690 to 3,363 kg DM ha-1 and did not differ across treatments (P > 0.05). Botanical composition differed across treatments with the control having the most weeds (32%) and the least amount of grass (62%) while manure treatments resulted in the most bare ground (11%; P ≤ 0.05). The soil nutrients magnesium and phosphate were highest in compost-treated plots and nitrate-nitrogen and sodium were highest in manure-treated plots (P ≤ 0.05). Forage nutrient content did not differ across treatments (P > 0.05). Horses did not prefer pasture treated with manure and only 15 and 33% of forage was consumed after 2 and 4 h, respectively (P ≤ 0.001). All other treatments averaged 53 and 78% removal after 2 and 4 h, respectively. Based on differences observed in botanical composition and horse preference, commercial fertilizer and compost appear to be the most beneficial soil amendments for horse pastures.

Penerapan Metode MOOSRA Dalam Seleksi Pengantaran Pemesanan Kue Online Menggunakan Pembobotan ROC

Each cake shop certainly has its own website that can be used to order cakes and of course has its own advantages and disadvantages which can be used as an assessment of the quality of the application, such as the types of cakes provided vary at more affordable prices and even the existence of discounted prices makes consumers more interested in ordering cakes online. The large number of these applications makes service users confused about choosing a better application among the good ones, therefore a study was made that discussed techniques for solving these problems using a decision support system. In this study, there are two methods used in the SPK method, including the ROC method which is used as an arrangement of weights of importance on five features that are used as rules which include application usability, Rating Reviews, Promos (Discounts), Cake Menu and Handling Fees. The second method is the Multiobjective Optimization on the Basis of Simple Ratio Analysis (MOOSRA) method which will be used to select 8 online cake ordering applications by ranking each alternative based on predetermined criteria. The final result after applying the two SPK methods is that Akul cake delivery is declared the best online cake delivery application with a preference value of 38.012.

Kombinasi Metode Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) dan Pembobotan Rank Order Centroid (ROC) dalam Pemilihan Tablet PC Terbaik

Tablet PC which is one part of technological developments in the field of communication that aims to meet the needs of users where these needs are not found on smartphones or laptops, is an option that can be an alternative communication tool that can meet needs involving a smartphone. such as designing, playing games, and working. related to the many models of tablet PCs in the world of communication causes the selection of the best tablet PC to be a problem for the users themselves. One of them is if the user chooses the wrong type of tablet PC according to their needs, the tablet PC does not make it easier, instead it hinders the activities of the user himself. therefore data from the types of tablet PCs are collected from 5 criteria and 7 alternatives where the criteria have been determined including screen size, memory capacity, memory type, hard disk capacity and price. From these criteria, the use of ROC can be used to giving weight to each criterion which is then determined using the MOORA method included in the decision that can give the maximum and accurate final preference value, so this study determines the best tablet pc choice option is alternative A1 brand apple ipad air with a final value of 0.054 as the best alternative.

Penerapan Metode MOOSRA dan ROC dalam Penentuan Guru Terbaik

The best teacher is a teacher who is given appreciation because he has a high achievement value. There are several specific criteria in selecting the best teacher, namely in terms of achievement, skills possessed, morals/manners, and discipline. To improve quality in the world of education, of course, a teacher is needed who will interact directly with students in the learning process which can indirectly improve the quality of education. With the interaction in the learning process, it is hoped that it will become a resource in improving the quality of education. There is also something the government is doing that is in a way to advance education, namely by empowering teachers and giving an award, especially for those who are entitled to get the title of the best teacher with achievements. Based on the results of interviews and research related to SMK Negeri 2 Medan, in determining the best teacher the assessment is still in a subjective way. This is based only on the opinion of each teacher and does not start with certain criteria, this will affect social events because the method used is not in an objective way and ends in an unfair feeling caused by subjective methods among fellow teachers who teach at the school. Therefore, it is recommended that schools must determine and agree on certain criteria in determining outstanding teachers, even though the assessment in the final process is still carried out by voting from those who have voting rights in determining the outstanding/best teachers, which of course is also carried out by teachers. The system for determining the best teacher is always a problem every year because it can create injustice among fellow teachers. Therefore, to facilitate and eliminate this unfair attitude, a decision support system (SPK) is needed which can facilitate the determination of the best teacher at SMK Negeri 2 Medan. A decision support system is an interactive computer system that can assist decision making by utilizing existing data to solve unstructured and semi-structured problems. In this SPK there are several methods, one of which is the Moosra Method (Multiobjective Optimization on the Basis of Simple Ratio Analysis) and the ROC (Rank Order Centroid) Method. The result of ROC and MOOSRA method calculation showed that Halimah (A10) obtained the highest final preference value of 14.599, making her selected as the best teacher.

Sistem Penentuan Prioritas Penerima Rehab Rumah Dhuafa Menggunakan Metode TOPSIS Berbasis Web

&#x0D; &#x0D; &#x0D; The process of selecting candidates for home rehabilitation of Dhuafa in Desa Ulee Nyeue, Kec. Banda Baro, Aceh Utara still using a manual process and by a subjective assessment. In this study the authors designed a decision support system to determine the candidates for home rehabilitation of Dhuafa in Desa Ulee Nyeue, Kec. Banda Baro using TOPSIS method. The criteria we used in the decision support system process are the area of the house, house building materials, type of floor, occupation and income. In this decision support system, it is supported by a method in making decisions, that is a web- based Topsis method which can support data processing. The sample data analyzed by using Topsis method in this research obtained that several people who had the priority to receive the housing rehabilitation of dhuafa assistance based on the preference value of each alternative are Fatimah Ben, which has a value of 0.534110001, Habsah with a value of 0.481135666 and Mawardi with a value of 0.629027038. Habsah with a value of 0.481135666 and Mawardi with a value of 0.629027038. The final result of this research is that the system built can help the selection team for home rehabilitation of dhuafa in Desa Ulee Nyeue, Kec. Banda Baro, Aceh Utara to make the process of determining more accurate.&#x0D; &#x0D; &#x0D;

Penerapan Metode Multi-Objective Optimization on the Basis of Simple Ratio Analysis Dalam Seleksi Pengangkatan Karyawan Tetap

Improvement of status as a permanent employee is a form of career advancement for a contract employee. because permanent employees are the main asset for a company. In selecting permanent employees for a company, there are some employees who volunteer to take part in the selection to become permanent employees. permanent employee selection is carried out in stages such as file selection, oral or written tests and interviews. Usually the selected employees are sometimes far from what is expected, so it is necessary to use a decision-making system as the final result, so a decision support system is needed using the Multi-Objective Optimization on the Basis of Simple Ratio Analysis (MOOSRA) method. The application of the Multi-Objective Optimization on the Basis of Simple Ratio Analysis (MOOSRA) method used in the selection of permanent employees is to find the best employees in a company. Decision support systems are used to assist decision making to determine permanent employees. The results of this study can assist decision making in determining which employees are selected to become permanent employees. From the results of the calculation of the Multi-Objective Optimization on the Basis of Simple Ratio Analysis (MOOSRA) method, the selection of permanent employees is based on predetermined criteria, an employee named "Eben" alternative A7 with a preference value of 7.086 as an employee who is eligible to become a permanent employee.

Identification of Potential Biomarkers for Group I Pulmonary Hypertension Based on Machine Learning and Bioinformatics Analysis.

A number of processes and pathways have been reported in the development of Group I pulmonary hypertension (Group I PAH); however, novel biomarkers need to be identified for a better diagnosis and management. We employed a robust rank aggregation (RRA) algorithm to shortlist the key differentially expressed genes (DEGs) between Group I PAH patients and controls. An optimal diagnostic model was obtained by comparing seven machine learning algorithms and was verified in an independent dataset. The functional roles of key DEGs and biomarkers were analyzed using various in silico methods. Finally, the biomarkers and a set of key candidates were experimentally validated using patient samples and a cell line model. A total of 48 key DEGs with preferable diagnostic value were identified. A gradient boosting decision tree algorithm was utilized to build a diagnostic model with three biomarkers, PBRM1, CA1, and TXLNG. An immune-cell infiltration analysis revealed significant differences in the relative abundances of seven immune cells between controls and PAH patients and a correlation with the biomarkers. Experimental validation confirmed the upregulation of the three biomarkers in Group I PAH patients. In conclusion, machine learning and a bioinformatics analysis along with experimental techniques identified PBRM1, CA1, and TXLNG as potential biomarkers for Group I PAH.

ETHANOL EXTRACT LIQUID SOAP FORMULATION LEAVES OF CELERY (Apium graveolens L.) AGAINST Escherichia coli BACTERIA

Dirty hands will be a source of disease. Soap is a pharmaceutical preparation used to maintain health. Celery (Apium graveolens L.) is a plant of the Apiaceae tribe with a distinctive menthol aroma. This study aimed to determine the inhibitory power of celery leaf extract formulation (Apium graveolens L.) as an antibacterial hand-washing soap. This research method is a type of experimental research. The stages of the research were collecting samples, identifying plants, making simplicia, characterizing simplicia, screening phytochemicals, making extracts and making hand soap formulations of celery leaf extract (Apium graveolens L) at concentrations of 5%, 10%, 15% and antibacterial testing of celery leaves, against Escherichia coli bacteria. The results showed the celery leaf extract soap formulation contained phytochemical compounds of flavonoids, tannins and saponins. The organoleptic test found that the best soap formulation was the F2 formulation with a concentration of 10% at an average level of preference value, namely 3.67 for colour, 3.27 for aroma, and 3.80 for texture. The homogeneity test performed showed that all formulations produced soap with good homogeneity. The height and stability test of the resulting celery extract soap foam ranged from 61-71 mm. The irritation test of the resulting celery extract soap also showed no irritation for all the formulations. The value of the antibacterial activity test found that the F1 formulation showed antibacterial activity with an inhibition zone diameter of 3 (weak), F2 with an inhibition zone of 9 (moderate) and F3 with the antibacterial activity of 12 (strong).

Community-First Criticism: Reviewing Art and Culture in Local Newspapers

ABSTRACT This article explores community-conforming criticism published in local or community newspapers. Currently, professional cultural criticism is largely focused on capital-based and regional newspapers, as well as cultural magazines, implying the specialisation of work and compartmentalisation of content, while local newspapers cover a wide variety of societal issues and dedicate attention to culture in genres other than the review. The article analyses the findings from a three-year development project launched by the Finnish Critics’ Association (2020–2023) that aimed to rethink reviewing in local journalistic settings. An analysis of the stories published until the summer of 2022 (n = 28) and semistructured theme interviews with the involved critics and staff journalists (n = 14) show the potential and challenges for local journalistic cultural criticism. Based on the analysis, I develop a theoretical framework for community-conforming criticism that places the primary focus on social values of art and preferences that rise from within the local community.

Re-formulating Monascus fermented durian seeds yogurt with strawberry (Fragaria x ananassa) puree to enhance its microbiological, physicochemical and organoleptic properties

Healthy lifestyle and consumption of fermented products, is the trend that is popular among health-conscious individuals. Monascus fermented durian seed (MFDS) is a fermented product of durian seed using the Monascus purpureus culture. Even though MFDS possessed specific bioactive properties, such as competent antioxidant, antidiabetes and anti-hypercholesterolemia. However, the addition of MFDS extract to yogurt has some limitations [e.g.: reduction of colour and taste preference]. Thus, there is a need for an innovative food technology method to enhance key organoleptic characteristics of a newly formulated yogurt product made of MFDS and strawberry puree. The aim of this investigation was to determine the effect of difference concentrations of strawberry puree on microbiology, physicochemical, and organoleptic properties of MFDS yogurt product. The results showed that all concentrations of strawberry puree [5%, 10%, 15%, and 20% (w/v) of the total mixture] have affected the microbial, physicochemical and sensory properties of re-formulated yogurt product. Strawberry purees caused an acidity increase of yogurt with pH value between 4.287 and 4.475. The recorded titratable acidity was 0.74% to 1.17%. The colour parameters such as lightness and yellowness also decreased, however, the values of redness, chroma, and hue increased. The shelf-life experiment (maximum of 7 days) of the re-formulated yogurt revealed a maximum syneresis of 22.52%. Based on the sensory evaluation preferences, re-formulated yogurt with 10% strawberry puree was the most favourable product, with a preferred value of the colour at 5.6 (rather like), the flavour at 5.8 (rather like), and mouthfeel (rather like).