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We propose and test a process where potential entrepreneurs (PEs) prioritize a venture idea consideration set using preference-based decision-specific heuristics to assess idea feasibility and desirability. We test our hypotheses through two studies with PEs. The first experiment shows that prioritization occurs, with 113 of 122 PEs voluntarily changing a randomized list of their ideated ventures into a rank-ordered priority list of potential opportunities. Second, we employ a novel "equivocal forced-choice" conjoint design with 250 PEs. We find empirical support that PEs prioritize via relative preferences for experience-based knowledge, strong social ties, and low risk/low reward venture ideas. We contribute to the entrepreneurship literature by theorizing and providing evidence of a prioritization stage for multiple idea sets before evaluation. Further, we demonstrate the influence of individual and social network factors on prioritization and expand our understanding of how PEs conceptualize risk in venturing. [ABSTRACT FROM AUTHOR]

Textile materials have long been recognised as media supporting the growth of microorganisms. For various applications including sports apparel, textile materials should have an optimum level of antibacterial activity without deteriorating the clothing comfort. This study deals with the multi-objective optimisation of antibacterial activity and comfort of knitted fabrics made from polyester-silver nanocomposite fibres using the desirability function approach. Comfort properties such as air permeability and moisture vapour transmission along with antibacterial activity have been considered to determine the 'overall desirability'. Blend proportion of the polyester-silver nanocomposite fibre (%), yarn count (Ne), knitting machine gauge (inch−1) and type of fabric (100% polyester or polyester-cotton blend) have been considered as the four independent variables. The optimum desirability was found to be 0.64 which is acceptable. To validate the results of optimisation, a new fabric sample was prepared with the optimum combination of input parameters. The validation sample showed good agreement with the optimised values of antibacterial activity and comfort properties. [ABSTRACT FROM AUTHOR]

The maxillary midline diastema (MMD) has experienced a renaissance in popular culture over the last 10 years. Current literature states that MMDs should be eliminated where possible or be reduced to 1 mm or less in width. This literature review explores the evidence for this in a West African population. A systematic search of the literature (Medline and Google Scholar) followed by a hand search was carried out to identify all papers evaluating perceptions of MMDs. In all, 209 papers were identified in the literature search, 8 of which met the inclusion criteria. The review revealed that midline diastemas are desirable in this specific population with a width of 2 to 4 mm deemed as attractive. As many as 95% of participants found the MMD beautiful, and as many as 95% would consider having one created artificially. The literature does not support the position that MMDs larger than 1 mm should always be treated to be perceived as attractive in this population. MMDs are accepted as attractive and should be considered a key feature in smile design for this population.

This paper presents an experimental approach to evaluate the ability of a six-axis industrial robot to drill aluminum alloy parts. A strategy based on statistical tests has been studied to quantify and predict the relative contribution of cutting parameters on cutting force and shape errors during drilling. This technique is based on the identification of relevant sources of error during high-speed robotic fitting. The machining quality was quantified in terms of dimensional and geometric tolerance, chip formation and evacuation, burr formation, edge build-up, tool wear and surface damage. Statistical analysis of the experimental results reveals a strong dependence between part accuracy and drilling force. An experimental model was developed to represent and predict the cutting force during drilling and an accurate error prediction capability was distinguished. It was found that at high cutting speed and feed rate, the cutting force was the main source of error affecting the accuracy of the machined parts. Verification experiments are performed, and the results reveal that dimensional defects are significantly reduced by a heat treatment effect (90 HRE) and the thrust force decreases with an increase in cutting speed. The recommended cutting speed for robotic drilling is 6000 rpm with a feed rate of 0.15 mm/min. This study provides important technical guidance for improving the robotic drilling of aluminum alloy in practice. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is the dominant subtype of liver cancer with very low survival rate but the chemotherapy for HCC is still in grey zone due to the limited efficacy and high toxicity profile of approved drugs raising the heavy demand on drug development for HCC. The study aimed to establish a desirability based quantitative structure activity relation (QSAR) model to predict the activity of chemical compounds against one of HCC cell line (HepG2). Different support vector machine (SVM) models were constructed and ensembled to 10 virtual screening protocols. These protocols were validated by an external dataset in combination with decoys as interference. Results showed that ensemble models exhibited improved area under the Receiver Operating Characteristic Curve (ROC), sensitivity, and specificity compared to base models in training and test set. When being validated for virtual screening to recover known active molecules in the mixture with known inactive and decoy compounds, all virtual screening protocols have good performance with good Boltzmann-Enhanced Discrimination of ROC (BEDROC) and enrichment factor (EF). The best protocol with BEDROC of 0.63 and EF of 29.55 was suitable for further screening of active compounds against HepG2 cell line. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to develop an integrated model finding the antecedents of intention towards digital social entrepreneurship (IDSE). Based on the basic frameworks of entrepreneurial intention theory, the theory of planned behaviour, and expectancy theory the paper proposes that experiences in social organisation and digital organisation lead to IDSE. Empathy, moral obligation, self-efficacy, perceived social support, perceived feasibility and perceived desirability act as mediating variables in the above relationships. The study validates the hypotheses by testing a series of possible empirical models on survey data with 482 responses. The theoretical and policy implications have been discussed in detail. [ABSTRACT FROM AUTHOR]

With one-third of marriages in the United States beginning online, online dating platforms have become important curators of the modern social fabric. Prior work on online dating has elicited two critical frictions in the heterosexual dating market. Women, governed by age-old social norms of not making the first move, are inhibited in their interactions in that they do not initiate contact with men. On the other side, men send an abundance of messages, the majority of which do not convert to matches. A key distinguishing feature of online dating versus its traditional counterpart is the ability to leave a range of digital signals not replicable in the offline world. These digital signals can impact the nature of online dating platform outcomes. In this paper, we study the impact of a feature that reveals "who likes you" (WLY) on engagement, the number of matches, match efficiency, and match sorting in online dating. This feature reveals the identity of the voters who have rated the focal user with a like. To causally identify the effect of this feature, we conduct a large-scale randomized control trial in collaboration with a major North American dating platform. The treatment causes women to be more proactive, sending 7.4% more messages, which is a highly desirable market improvement given that men send double the number of messages compared with women. Further, we find that the women endowed with this feature increase their matches by 14.4%, whereas men increase their matches by 11.5%. Analyzing the moderating impact of desirability—a key aspect of the WLY feature—provides us with nuanced findings. Depending on the levels of each of the two parties' desirability, we see evidence of sorting, encouragement, and discouragement. This paper was accepted by Anandhi Bharadwaj, information systems. Supplemental Material: The Online Appendix is available at https://doi.org/10.1287/mnsc.2022.4576. [ABSTRACT FROM AUTHOR]

Humans are a social species with a high degree of information sharing. Character information is transferred between individuals frequently. Making a decision about who to mate with is one of the most consequential choices an individual makes, hence it pays to attend to any cheaply available mate-relevant information on offer. Building on previous research reporting a mating advantage for men romantically associated with women, here we present 3 studies examining the effects of being popular with the opposite sex. In all three studies men and women were presented with (and asked to evaluate) visual profiles of individuals of the opposite sex. Study 1 (N = 294) found that both men and women evaluate a man as more creative and socially skilled when he is attractive, and that women regard him as having higher mate value when his female friends are attractive. Study 2 (N = 233) found that men, but not women, considered profiles that were highly popular with the opposite sex to be more desirable. Study 3 (N = 765) found that neither men's nor women's desirability ratings of opposite-sex others were influenced by how popular that individual was with members of the opposite sex. It was concluded that while both men and women can be influenced by social information implicitly offered by others, this phenomenon is quite nuanced. Several possible theoretical and methodological explanations are considered, adding valuable knowledge to the existing body of research about mate copying propensity. [ABSTRACT FROM AUTHOR]

Link for citation: Katanov Yu.E., Yagafarov A.K., Aristov A.I. Assessment of well completion quality impact on the volume of explored balance reserves of hydrocarbons. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 9, рр. 91-103. In Rus. The relevance. Traditional methods of hydrodynamics are sufficiently unambiguous to find out how much the actual productivity of the reservoir differs from its potential productivity. Such estimation was not quite satisfied with the production, especially in the conditions of exploration works, where the objectives of achieving the potential productivity of the object, as a rule, are not set during the test. The emergence of requirements of economic nature to the results of the test has further limited the scope of its application. There was an urgent need to create such a methodological approach, which would allow assessing the quality of the activities carried out not by discrete values, but on a continuous scale. For this purpose, the authors proposed to use the «desirability» function, which is widely used for quantitative assessment of the quality of any technological processes. The essence of the approach consists in converting the actual indicators into a dimensionless scale of «desirability», which can be used to assess their qualitative level. The main aim of the work is to develop a primary geological and technological model to assess the impact of well completion quality on the volume of explored balance reserves of hydrocarbons. The objects of the investigation are productive sediments of the Pokurskaya, Vartovskaya, Megionskaya, and Vasyuganskaya formations. Methods. The geological efficiency of exploration works on the basis of retrospective analysis was investigated. The relationship between the productivity factor, complex geophysical parameter, underbalance at development and the depth of the bedrock bedding was investigated through associative analysis and mathematical modeling. Geological and technological modeling was carried out to find the optimal underbalance to cause cost-effective hydrocarbon inflow. Results. The well completion quality estimation scheme was formed. Correlations of optimal underbalance level of significance 0,05 were obtained. The «desirability» function was used to translate the actual productivity coefficient to the «quality level», resulting in a system of equations for the minimum cost-effective productivity coefficient.

Until early 2006, in Brazil, the focus used to be on oil and gas exploration/exploitation of post-salt carbonates. This changed when the industry announced the existence of large fields in pre-salt layers across the South Atlantic Ocean from nearshore zones up to almost 350 [km] from the shore. With the discovery of pre-salt hydrocarbons reservoirs, new challenges appeared. One of the main challenges is the necessity to optimize the drilling processes due to their high operational costs. Drilling costs are considerably high, which leads the oil and gas industry to search for innovative and entrepreneurial methods. The coupling of the mechanical specific energy (MSE) and the rate of penetration (ROP) is a method that allows for the identification of ideal conditions to efficiently enhance the drilling process. In addition, the performance of the drilling process can be estimated through pre-operational tests, which consist in continuously testing the applied drilling mechanic parameters, such as the weight-on-bit (WOB) and drill string rotary speed (RPM), looking for optimum sets that would ultimately provide the most desirable ROP. Thus, the goal of this research was to analyze field data from pre-salt layer operations, using a multi-objective optimization based on the play-back methodology for pre-operational drilling tests, through the ideal combination of the highest ROP and the lowest MSE. The results showed that the new concept of pre-operational tests based on the MSE proved to be effective in the drilling process optimization. The combination of the highest ROP and the lowest MSE allows for a high-performance drilling process. For WOB intervals of 5 and 7 [klb], a good fit of the parameters was obtained. Through the parameters obtained from pre-operational tests, the eventual cost-saving and time-saving values could be estimated, respectively, ranging from USD 1,056,180 to 1,151,898 and 19.50 to 21.27 [h], respectively. In addition, the results of this research can be applied to the exploration of other natural resources, such as natural hydrogen and geothermal sources.

Considering the rising demand for rare earth elements (REEs), researchers are looking for new sources for their extraction, thereby fostering economic and environmentally justified processing solutions. Among potential industrial sources, coal fly ash emerges as one of the most promising. The recovery of REEs from coal fly and bottom ashes derived from different thermal power plants was the main focus of this study. A dual-step methodology was conducted on ash samples, which involved an ultrasonic roasting process to disintegrate the silica matrix, followed by a microwave-assisted acid leaching step to extract REEs. The roasting procedure was studied using the Plackett–Burman design, and the Box–Behnken design was subsequently implemented to optimize the leaching procedure. The optimized ultrasonic roasting procedure was set up at 95 °C for 10 min with an ash-to-roasting agent (3M NaOH) ratio of 0.5:1 (m/V). For acid leaching, the optimal conditions were obtained at 174 °C for 30 min with an HCl ÷ HNO3 mixture (1:1 V/V). The standard reference material (NIST 1633c) was used in the conclusive experiments to estimate the average recovery (80%) of REEs. The green aspects of this methodology were evaluated using several metrics (atom economy, E-factor, and energy consumption). The proposed process outperforms high-temperature roasting procedures in terms of greenness; however, the REE recovery rate is lower.

The photovoltaic sector needs a high-throughput slicing method that produces minimal waste to meet rising demand. Wire electric discharge machining (WEDM) has emerged as an alternative slicing method in recent research efforts. Polycrystalline silicon is sliced using the WEDM process with a zinc-coated electrode of Ø0.25 mm in diameter. Experiments were planned and conducted according to Box Behnken’s design of experiments. As inputs, seven different process parameters were used: pulse on time (PONT), pulse off time (POFFT), peak current (PC), spark gap voltage (SGV), wire feed (WF), wire tension (WT), and water pressure (WP). Response parameters measured were cutting speed (CS), surface roughness (SR), and kerf width (KW). Various process parameters have also been analyzed with ANOVA methods for predictive modeling. Based on experimental data, this study determines the appropriate optimal solutions via desirability functions. During the WEDM process, the PONT, POFFT, PC, and SGV significantly influence the discharge energy on the sliced surface. As a result of this study, CS of 0.78 mm2/min, SR of 2.87 μm, and KW of 0.70 mm were observed at the optimal settings of PONT of 119 μs, POFFT of 42 μs, PC of 38A, SGV of 36V, WF of 3 mm/min, WT of 2 kg and WP of 6 kg/cm2. Surface morphology was determined using scanning electron microscope and Energy dispersive X-ray to investigate the surface characteristics.

The high energy demand along with the fast diminution of fossil fuel reserves as well escalation of carcinogenic emissions leading to global warming has initiated a pragmatic shift in the direction of the adoption of biofuels. In this regard, the present work investigates the twin influence of injection timing and load on the performance, exergy, and emission analysis for a Water Hyacinth (Eichhornia Crassipes) biodiesel-run diesel engine. Furthermore, Response Surface Methodology (RSM) is used for modeling, prediction, and to investigate the optimal value of the operating parameters of the engine. A single-cylinder, water-cooled research test engine with a maximum load capacity of 3.5 kW is considered for experimentation. The operating parameters, four different injection timings (20° bTDC, 23° bTDC, 25° bTDC, 28° bTDC), and five different load conditions (20%, 40%, 60%, 80%, 100%) are considered for the test. The performance, exergy, and emission analysis conclude that the injection timing of 20° bTDC gives improved fuel conversion efficiency as well as reduced exergy destruction and lower emissions for Water Hyacinth biodiesel run diesel engine. As per RSM, the best results were obtained at 81.25% engine load and 20° bTDC corroborating the findings of experimental research. [Display omitted] [ABSTRACT FROM AUTHOR]

Generative adversarial networks (GANs) have shown remarkable success in various generative design tasks, from topology optimization to material design, and shape parametrization. However, most generative design approaches based on GANs lack evaluation mechanisms to ensure the generation of diverse samples. In addition, no GAN-based generative design model incorporates user sentiments in the loss function to generate samples with high desirability from the aggregate perspectives of users. Motivated by these knowledge gaps, this paper builds and validates a novel GAN-based generative design model with an offline design evaluation function to generate samples that are not only realistic but also diverse and desirable. A multimodal data-driven design evaluation (DDE) model is developed to guide the generative process by automatically predicting user sentiments for the generated samples based on large-scale user reviews of previous designs. This paper incorporates DDE into the StyleGAN structure, a state-of-the-art GAN model, to enable data-driven generative processes that are innovative and user-centered. The results of experiments conducted on a large dataset of footwear products demonstrate the effectiveness of the proposed DDE-GAN in generating high-quality, diverse, and desirable concepts. [ABSTRACT FROM AUTHOR]

Laser machining is a cutting-edge thermal energy-based industrial methodology that can be employed to replace the traditional mechanical machining practices in micro-domain applications. In this work, complex hexagonal shape profiles were cut on the surfaces of Nickel-based superalloy (Alloy 276) by fiber optics laser cutting system. Response surface methodology – Central Composite Design approaches were attempted for optimizing laser machining factors to obtain the better output responses. ANOVA was used to identify the significant machining factors which affect the cut quality characteristics. The desirability approach in multi-response optimization was deployed to achieve the minimal kerf width, low surface roughness, minimum heat affected zone while simultaneously increasing the material removal rate. To validate the predicted results obtained from the desirability index analysis, confirmation test was conducted based on a higher desirability index value. The result reveals that the error percentage is less than 5 for all the responses. The results of the confirmation test show that the proposed procedures are effective in improving laser machining parameters for obtaining the better responses. [ABSTRACT FROM AUTHOR]

According to literature survey, many works have dealt with studying the effect of some bags on biological, chemical and physical quality of date fruit. In this study, RSM (response surface methodology) modeling and desirability function methods were applied and compared to predict the overall quality of cover date bunch samples. Five nonwoven bagging product are selected to be examined that are used for the first time on date palm sector. The results proved that a high quality of bagging product could be obtained in optimal conditions. Using the influential parameters and optimized conditions as fabric weight, thickness, air permeability, resistance to water penetration, tear strength and tensile strength, the results indicate that the cover date bunch remains influenced especially by the air permeability properties and tensile strength as well. Desirability function has been proven to be effective to achieve ideal design performance. The results show that the highest desirability reached is 0.6.However, the efficient approaches to identify the relevant parameters and the relation between different quality features and parameters have not been completely studied. To overcome the gap, a combined method including desirability function and response surface methodology (RSM) was proposed. Referring to previous works, desirability function allows a high level of flexibility over classical mathematical methods in evaluating and defining global quality. According to the analytical results obtained, the desirability function method gives a more accurate prediction than the RSM one. [ABSTRACT FROM AUTHOR]

The current research is focused on investigating the influence of bearing irregularities like eccentricities (e), non-circularities (G), L/D ratio (ß), surface roughness coefficient (Y) on hydrodynamic performance of journal bearing such as load bearing capacity, friction force, lubricating oil flow. The performance is evaluated through finite difference method technique implementing a Newton-Raphson method of error convergence. The simulation outputs were than designed using an optimization tool entitled as Design of Experiment (DoE) on basis of response surface methodology (RSM). The outputs of RSM models were meant to forecast the response parameters like, load bearing capacity, friction force, flow of lubricant and further required to identify the noticeable interdependencies within the input parameters while evaluating the lubrication performance. The optimization of the bearing irregularities is done considering desirability approach of the response surface methodology in identifying proper combination of parameters. [ABSTRACT FROM AUTHOR]

Micro wire electric discharge machining (µ-WEDM) has received immense attention due to the tight tolerance requirements of biomedical components and downsizing of sensors. The investigation reports the impact of wire material in machining Inconel 625 superalloy. The quality of machined surface is studied in terms of surface roughness (SR) and erosion rate (ER) by varying the µ-WEDM variables like servo voltage (SV), pulse start time (Tstart), angle of cut (AC), pulse stop time (Tstop) and current (IC). Two different wire electrodes of diameter 150 µm (brass and zinc-coated brass) are used in the study. Machining trials are executed by using central composite design (CCD). Further modeling of responses is carried out using Response Surface Methodology (RSM) and Desirability Analysis (DA) to predict the optimal machining parameters. The zinc-coated brass wire (Wzb) outperforms the plain brass wire (Wb) in terms of machining rate. Servo voltage is identified as a crucial and noteworthy parameter affecting the responses. The SR is decreased by 28.13% at the highest value of SV (70 V), while the ER rose by 41.36% at the minimal value of SV (50 V). The topography of machined surfaces is analyzed using SEM and 3D surface roughness images. [ABSTRACT FROM AUTHOR]

A diesel engine powered with Mesua ferrea Linn oil (20% MLO) and diesel (80%) blend fuel (MLO20) is fortified with diethyl ether (DEE) for possible enhancement of the engine's performance, combustion, and tailpipe emissions. DEE is added to the MLO20 to create three different kinds of ternary blends. This study investigates the combined effects of biodiesel, ether, fuel injection pressure, and engine load on engine performance, emissions, and combustion characteristics. By considering several parameters at the same time, this investigation offers a fresh perspective that extends beyond the individual parameter analysis used in earlier studies. The first contains 5% DEE and 95% MLO20 by volume (MLO20DEE05), whereas the second has 10% DEE and 90% MLO20 by volume (MLO20DEE10) and the third has 15% DEE denoted as MLO20DEE15. The inclusion of DEE in the MLO-diesel mix improves engine thermal efficiency by 1% to 2.47% while reducing both CO emissions by 7.2% to 12.8% and NOx emissions by 3.7% to 11.9%. This generated a multi-input and multi-output predicament in which it was critical to determine the appropriate fuel blend to achieve the most efficiency while emitting the fewest exhaust emissions. In the current study, the response surface methodology (RSM) was used to optimize the control components to attain the optimal engine response variables. The analysis of variance was employed for model development while desirability was used for optimization. The 75.36% engine load, 238 bar injection pressure, and 14.2% DEE addition provided the best engine output as 24.95% BTE, 59.16 bar peak pressure, 0.39 kg/kWh, 298.4 ppm NOx, 42.48 ppm UHC, and 0.051% CO emission. [ABSTRACT FROM AUTHOR]

Despite the prominence of global environmental challenges, promoting publics' engagement with issues related to environmental sustainability has proven difficult. Publics have perceived them as distant issues that do not have imminent impact requiring immediate actions. However, publics' disengagement has in turn accelerated environmental deterioration. Applying construal level theory, this study explores factors that cause publics' disengagement but also ways to promote information behaviors in an environmental sustainability issue. An online survey was conducted of a nationally representative sample of 507 Australians in November 2022. Using food waste as an issue that negatively affects environmental sustainability, structural equation modeling was conducted to test the effects of the dynamics of psychological distance, feasibility, and desirability on publics' disengagement, information seeking and information forwarding. When individuals consider food waste a distant issue, they also consider it to be undesirable and infeasible to act upon, with the result that they disengage. However, this study finds that while psychological distance is negatively associated with desirability and feasibility, it is positively associated with information seeking and forwarding. We find, in particular, that desirability positively contributes to information seeking and forwarding. However, feasibility is negatively associated with information seeking and forwarding. Implications for public relations theory and practice are discussed (203 words). • Explores factors that cause disengagement on the issue of food waste. • Also explores how the same factors promote information behaviors. • Psychological distance increases disengagement. • Feasibility reduces information seeking and forwarding. • Desirability increases information seeking and forwarding. [ABSTRACT FROM AUTHOR]

Sexual racism—including or excluding racial minority members in partner selection based on race—negatively affects Asian men who have sex with men (MSM) across various domains. The current study aims to investigate the effect of potential partners' racial preferences on desirability in Asian MSM. The relationship between sexual racism awareness and partner desirability when evaluating white partners with racial preferences was also investigated. A sample of Asian MSM (N = 128) responded to hypothetical online dating scenarios in which the racial background (Asian/white) and racial preference (none/Asian/white) of facial stimuli were manipulated. A two-way ANOVA with post-hoc Bonferroni analyses confirmed that, as hypothesized, among potential white partners, those that exhibited no racial preferences were most desirable, F(1.66, 210.54) =.11.37, p <.001, ηp2 =.08. Among potential Asian partners, those that preferred white men were least desirable, F(1.82, 231.60) = 81.95, p <.001, ηp2 =.39. Unexpectedly, there was no relationship evident between sexual racism awareness and desirability for potential white partners (in any racial preference condition; all rs <.20). Our findings suggest that overt expression of certain racial preferences can negatively affect desirability in online dating applications. [ABSTRACT FROM AUTHOR]

The study aims to improve biodiesel's fuel quality using optimal oil mixture. Four oils, namely, Karanja, Jatropha, Palm and Waste cooking oil(WCO) were selected and their mixtures were prepared. A simplex lattice mixture design model for biodiesel properties (Kinematic viscosity(KV), Density, Cetane number(CN) and Oxidation stability(OS)) was developed and optimisation of oil mixtures was conducted. Biodiesel fuel properties of the optimum ratio of the mixture of Karanja:Palm oil (51.6:48.4% v/v) are found as KV(3.854 mm2/s), density (860 kg/m3), CN(56.189), and OS (9.565 h), thereby, indicating that the OS of the biodiesel of optimum mixture is improved by 21.47% and CN by 4.2% compared to Karanja biodiesel. Jatropha oil biodiesel does not meet the biodiesel standard (EN 14214), but when mixed with Palm oil in an optimal ratio of 34.8:65.2% v/v (Jatropha:Palm), biodiesel from this optimal mixture obtained are KV(3.822 mm2/s), density(869.95 kg/m3), CN(55.69) and OS(8.16 h) found. So mixing oils improve the biodiesel OS by 46.9% and CN by 11.28% and also satisfies biodiesel standards compared to individual Jatropha oil biodiesel. However, no optimum ratio for the mixture of WCO with Jatropha or Karanja was found suitable for converting biodiesel that can fulfil biodiesel standards. [ABSTRACT FROM AUTHOR]

A microgrid is a group of interconnected loads and distributed energy resources that can fill the gap between the dependence on a bulk power grid and the transition to renewable energies. The islanded mode presents itself as the most interesting scenario, when local controllers should maintain the power quality standards based on several parameters. A tool specifically focused on the process of parameter tuning of the secondary consensus-based control for inverter-based islanded microgrids was proposed in this paper. One often-quoted drawback in this process is the great number of parameters that must be tuned, even for a very simple microgrid structure. To manage such a large number of parameters, the design of experiments was used in this study. The main motivation for this work was to present an optimized way to define the correct parameters for the secondary consensus control for inverter-based islanded microgrids. The study shows how experimental design methodology can be an efficient tool to tune microgrid parameters, which are typically multi-objective-based experiments. From the results, it is correct to state that the design of experiments is able to reach the optimal setting with a minimal number of experiments, which would be almost impossible to obtain with the trial-and-error method. [ABSTRACT FROM AUTHOR]

This study focuses on the optimization and modelling of the green charcoal formulation process using experimental design methodology. The fuel is made from peanut shells, typha, sawdust, charcoal dust and sewage sludge used as a binder. These residues were mixed in the proportions suggested by the plan and underwent a direct densification process. The desirability function used and the physico-chemical analyses carried out revealed that the best results obtained were briquettes made from 50% sludge, 24.29% groundnut shells, 5.71% typha, 10.57% sawdust and 9.43% dust. They therefore have a calorific value of 5619.33 kcal/kg, an ash content of 22.98%, a moisture content of 3.13%, a volatile matter content of 56.75% and a fixed carbon content of 20.27%. Analysis of the elemental composition and calorific values of the fuel briquettes produced shows that they have good combustion properties. However, in order to improve the quality of the briquettes produced, a study on the reduction of smoke content needs to be carried out. [ABSTRACT FROM AUTHOR]

We propose a model of an agent's probability and utility that is a compromise between Savage (The foundations of statistics, Wiley, 1954) and Jeffrey (The Logic of Decision, McGraw Hill, 1965). In Savage's model the probability–utility pair is associated with preferences over acts which are assignments of consequences to states. The probability is defined on the state space, and the utility function on consequences. Jeffrey's model has no consequences, and both probability and utility are defined on the same set of propositions. The probability–utility pair is associated with a desirability relation on propositions. Like Savage we assume a set of consequences and a state space. However, we assume that states are comprehensive, that is, each state describes a consequence, as in Aumann (Econometrica 55:1–18, 1987). Like Jeffrey, we assume that the agent has a preference relation, which we call desirability, over events, which by definition involves uncertainty about consequences. For a given probability and utility of consequences, the desirability relation is presented by conditional expected utility, given an event. We axiomatically characterize desirability relations that are represented by a probability–utility pair. We characterize the family of all the probability–utility pairs that represent a given desirability relation. [ABSTRACT FROM AUTHOR]

BACKGROUND: Solvent‐free microwave‐assisted extraction (MAE) is a green extraction method capable of boosting the yield and quality profile of hemp essential oil when compared with other conventional extraction techniques. During this process, two by‐products are produced, namely the aqueous residue containing bioactive phenolics and the residual deterpenated biomass, which can be used for further extraction and purification of phytocannabinoids. To date, the hemp industry has not utilized these products, although they can be valuable for the food, cosmetic, nutraceutical and pharmaceutical market. RESULTS: This study assessed and optimized the variables affecting MAE efficiency, namely microwave irradiation power, extraction time and added water, which were studied using a central composite design approach, and results were used to optimize the extraction process for recovering three valuable fractions: essential oil, polyphenols and phytocannabinoids. The products obtained using the optimized conditions were characterized in terms of yield, chemical profile and antioxidant potential. Moreover, the by‐products obtained during the optimized run were further analyzed in terms of their biological activity using both enzymatic and non‐enzymatic assays. The aqueous residue demonstrated a powerful α‐glucosidase inhibition, a good activity in terms of superoxide radical scavenging activity, a modest efficacy in terms of inhibition of advanced glycation end products formation and no activity in terms of lipase inhibition. The residual deterpenated biomass did not possess significant biological activity. CONCLUSION: This work demonstrated valorization of industrial hemp essential oil and its by‐products, obtained by a sustainable and eco‐friendly extraction method, through an almost waste‐free approach. Cannabinoids as well as other valuable bioactive compounds such as glycosidic flavones may be recovered from the residues of the essential oil extraction, representing interesting substances in the pharmaceutical, cosmetic and nutraceutical fields. © 2022 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The note puts forward the idea of revealed desirability, a novel instrument, which like revealed preference is observable from choice and important for individual and social welfare. We provide the axiomatic underlying individual's choice model, preliminary experimental results that support the idea, and an appealing allocation rule that uses the revealed desirability information along with the revealed-preference information. [ABSTRACT FROM AUTHOR]

PURPOSE: Although the COVID-19 pandemic has had a catastrophic effect on economic activities worldwide, the paradoxical phenomenon of this black swan situation may be found to facilitate entrepreneurial intentions. This study aims to investigate Thai university students’ perceptions of their entrepreneurial aspirations during the times of the COVID-19 pandemic. METHODOLOGY: Drawing upon social cognitive career theory, this research investigates the profound linkage of university students’ COVID-19 perceptions and attitudes towards situations for self-believing in the adaptation for entrepreneurship. A valid sample of 798 collected from eight provinces, eight districts, and eight cities throughout Thailand was included for further analysis using Structural Equation Modelling (SEM) and Process Macro Model 6. FINDINGS: University students’ COVID-19 pandemic perceptions influence their self-efficacy in situation adaptations and perceived desirability towards individual-level entrepreneurial intentions. Interestingly, self-efficacy and desirability towards entrepreneurship act as serial mediating factors, towards the mediated relationship between attitude towards the situation, COVID-19 perception, and university students’ entrepreneurial intentions. IMPLICATIONS: The results of this research can add to entrepreneurship literature and additional model testing has also been proposed. Besides, practitioners and researchers could collaborate with governors to cultivate entrepreneurial trajectories based on research findings. ORIGINALITY AND VALUE: Social cognitive career theory (SCCT) can rationalize an academic student’s career choice of entrepreneurship by considering their perception of the start-up processes during COVID-19. Future research can also test findings on a representative sample at the national level.

This study aimed to evaluate the effectiveness of education in Imam Ali Military University based on the European Foundation for Quality Management Model (EFQM). This study in terms of purpose was developmental-applied; its method was descriptive-survey and its data collection method was through questionnaire. In this way, 943 researcher-made questionnaires, each of which has been compiled with regard to the components in the "Regulations for evaluating the effectiveness of the education of the Armed Forces of the I.R. of Iran", distributed among 5 types of users (professors, students, heads of departments, scientific-research staff and operational unit commanders) randomly. The validity and reliability have been confirmed by experts and Cronbach's alpha, respectively. The total score of each of the aforementioned areas indicated the relatively favorable situation for the 5 enablers area of the EFQM model (command and management, professors, students, program, teaching-learning process) and the output in result area; The outcome in the results area was also in a good situation. However, the students' grades and the average of 10 of their selected courses showed that the situation in the field of products is unfavorable. These results show that relatively favorable areas will be able to achieve the desired situation in the short and medium term if targeted. But on the other hand, the product area is on a more difficult path and needs serious attention. In the meantime, several solutions can be facilitated to achieve the goals.

In this study, an experimental evaluation on the use of Al2O3 nanoparticles in a circular structure of minichannel heat sink is conducted for heat dissipation from electronic components such as Central Processing Unit (CPU). The experiments are prepared for various hydraulic diameter of channels and different values of coolant flow rates. After a hydro-thermal analysis on the obtained data, as a main outcome, findings indicate that decreasing the channel diameter and increasing the flow rate of Al2O3-water as working fluid are the most effective approaches to improve the cooling performance of heat sinks. An optimization study using Response Surface Methodology (RSM) based on Central Composite Design (CCD) is performed due to complex effect of channel size, nanofluid volume flow rates and channel numbers on pressure drop and heat transfer to reach the best operating design.

In this study, the main task is to identify the best cutting parameters to improve the machining performance during MQL-turning with various cutting fluids like coconut oil, ground nut oil, sunflower oil, soyabean oil, and blassocut oil. Cutting temperature and surface roughness were used as performance metrics, with the goal of minimizing these responses. To construct an experimental plan for turning AISI4130 with uncoated brazed carbide, full factorial design for three levels and three factors (33) design of experiments was used. The optimal cutting parameter was identified using the response surface approach. Aiming to discover the optimum possible cutting settings, the desirability function method was utilized. It was discovered that the best cutting speed, depth of cut, and feed rate for minimizing the temperature and surface roughness are 72.38 m/min, 0.5 mm, and 0.35 mm/rev respectively. According to the ANOVA findings, the feed and depth of cut have a substantial impact on the tool temperature for MQL-soyabean oil.

It seems that distinct differences of opinion regarding the desirability of the portrayal of eroticism in films and the application of censorship are evident in the South African society. This empirical study has attempted to identify amongst young adults the role that their ethical orientation plays in evaluating film eroticism and censorship. For this purpose four ethical orientations (the Individualistically, Transcendentalistically, Relativistically and Altruistically orientated groups) were identified. Research was conducted at four universities in which 418 respondents participated. The most important findings were that respondents supporting the Transcendentalistic ethical orienta tion differed significantly from the other in displaying a more negative attitude towards film eroticism and a more positive view of censorship. It was concluded that researchers should thoroughly take cognisance of the role that respondents' ethical red by the Publisher (dated 2010).

In the present study, bio-apatite/nZVI composite was synthesized through Fe(III) reduction with sodium borohydride and was fully characterized by FTIR, XRD, SEM–EDX, TEM, BET, BJH, and pHPZC. Column experiments were carried out for the removal of phosphate as a function of four operational parameters including initial phosphate concentration (100–200 mg L−1), initial solution pH (2–9), bed height (2–6 cm), and influent flow rate (2.5–7.5 mL min−1) using a response surface methodology (RSM) coupled with Box-Behnken design (BBD). 2D contour and 3D surface plots were employed to analyze the interactive effects of the four operating parameters on the column performance (e.g., uptake capacity and saturation time). According to ANOVA analysis, the influent flow rate and bed height are the most important factor on phosphate uptake capacity and saturation time, respectively. A quadratic polynomial model was excellently fitted to experimental data with a high coefficient of determination (> 0.96). The RSM-BBD model predicted maximum phosphate adsorption capacity of 85.71 mg g−1 with the desirability of 0.995 under the optimal conditions of 135.35 mg L−1, 2, 2 cm, and 7.5 mL min−1 for initial phosphate concentration, initial solution pH, bed height, and influent flow rate, respectively. The XRD analysis demonstrated that the reaction product between bio-apatite/nZVI composite and phosphate anions was Fe3 (PO4)2. 8H2O (vivianite). The suggested adsorbent can be effectively employed up to five fixed-bed adsorption–desorption cycles and was also implemented to adsorb phosphate from real samples. [ABSTRACT FROM AUTHOR]

Inconel-625 is a tough-to-cutting material used in ultra-supercritical power plants for flanges, offshore oil sectors, and turbine blades, among other high-temperature components. The objective of this article is to determine the link between four key process independent variables: traverse speed (TSP), abrasive mass flow rate (AMFR), abrasive aqua jet pressure (AAJP), and gap distance (Gd) to the surface roughness (SRa), kerf angle (KEA), and erosion rate (MRR). The response surface methodology-Central composite design (RSM-CCD) was used to perform the experimental interpretations. The influence of individual abrasive aqua jet cutting (AAJC) factors was determined using analysis of variance technique (ANOVA). It was found that AAJP is the dominant factor in the responses. When the AAJP reached its maximum value of 300 MPa, the SRa and KEA reduced by 27.19% and 13.83%, respectively, the MRR improved by 23.71%. The Desirability analysis is handled to optimize the AAJC parameters of Inconel-625. The optimal values of parameters obtained were 300 MPa AAJP, 75 mm/min TSP, 2.4 mm Gd, and 0.55 kg/min AMFR to minimize SRa, KEA, & maximize the MRR. The scanning electron microscope is used to examine the surface morphology and erosion mechanisms. [ABSTRACT FROM AUTHOR]

The present study focuses on the optimization of the drilling process parameters of treated and untreated Washingtonia filifera (WF) fiber–reinforced polymer biocomposites using the desirability function approach based on the response surface methodology (RSM). Drill diameter, feed rate, and spindle speed were the three main input factors used to evaluate drilling performance. In this study, in order to have a better machinability especially a low delamination factor (Fd), the authors focused on the influence of the fiber treatment rate in the optimization of the drilling parameters. The findings revealed that diameter, feed rate, and treatment ratio were found to be important influencing factors on the delamination factor Fd. The latter was modeled statistically with a central composite design (CCD). The optimized numerical model for the delamination factor of the biocomposite reinforced with treated fiber (with 1% NaOH) showed the lowest delamination factor of 1.035 for a drill diameter of 5 mm, a feed rate of 50 mm/min and a spindle speed of 2500 rev/min. The analysis of variance (ANOVA) established the importance level of each parameter and indicated that the model was significant with a good correlation between the experimental data with R2 = 0.9713 and adjusted R2 = 0.9561. [ABSTRACT FROM AUTHOR]

• Nine DEM parameters were screened using the Plackett-Burman statistical method. • An elasto-plastic DEM soil model with cohesion was calibrated using a uniaxial compression test. • DEM accurately predicted soil forces from two planar blades (RMSE 8.46 N). • DEM accurately predicted soil forces from a 1/8 scaled bulldozer blade (RMSE 7.42 N). The discrete element method (DEM) has become a valuable computational technique for simulating soil dynamic loading during bulldozer cutting processes. It allows for the virtual design of Ground Engaging Tools (GETs) and predicting energy expenditure during earthmoving operations. Few studies exist for modeling dynamic soil-cutting processes of soils exhibiting elasto-plastic behavior with stress-history-dependent cohesive soil behavior. The study aimed to calibrate an elasto-plastic DEM soil model, with cohesion, for a cohesive-frictional artificial soil and predict soil reaction forces from soil-to-blade interaction. Plackett-Burman screening design of experiment (DOE) and inverse profiling techniques were applied to calibrate the elasto-plastic DEM soil model, with cohesion, predicting soil compaction energy with a percent relative error (PRE) of 3 % and maximum normal stress (PRE of 1 %) using cohesive-frictional artificial soil in a uniaxial confined compression test. Validation of the calibrated DEM soil model resulted in good prediction of soil reaction forces versus blade displacement for a narrow planar blade, a wide planer blade, and a geometrically scaled curved bulldozer blade, with RMSE values of 2.04 N, 14.89 N, and 7.42 N, respectively. The findings showed that elasto-plastic soil behavior with stress-dependent cohesion can be modeled using DEM for simulating the cutting and moving of earthen materials, offering valuable insights for optimizing GET design and development of digital twins of earthmoving operations. [ABSTRACT FROM AUTHOR]

Inconel 625, a high-strength superalloy with excellent corrosion resistance, discovers wide applications in critical sectors such as aerospace, nuclear, marine, and petrochemical. Single-Point Incremental Forming (SPIF) has appeared as an adequate fabricating process for shaping superalloy components. This work used a systematic approach, implementing Response Surface Methodology (RSM) to explore the influence of SPIF process variables, including tool nose diameter, step size, tool spindle speed, and wall angle, on microhardness (MH) and surface roughness (SR). The experimental results have been analyzed to determine the influencing process variables and their optimal settings, which simultaneously enhance MH and reduce SR of Inconel 625 superalloy truncated cones using analysis of variance and the desirability function analysis approach. The most significant parameters that influence MH and SR were TND and SS, respectively. The development of quadratic models for MH and SR has been completed successfully. The maximum MH of 486.8 HV and minimum SR of 0.432 µm have been obtained at the optimal parametric setting of TND = 15 mm, SS = 0.4 mm, TSS = 900 rpm, and WA = 57.5° with the desirability values for MH, SR and combined are 0.832, 0.933, 0.881 respectively. The F-value of the MH model = 109.18 and SR Model = 78.24 implies that both models are significant and both models have excellent prediction strength. The percentage error between predicted and actual values of MH and SR in confirmation run results is less than 5 %. • This study introduces the SPIF of Inconel 625, extending its use to critical sectors like aerospace and nuclear demand for high-performance materials, marking a novel approach to fabricating conical shapes. • Utilizing RSM, the research systematically investigates the impact of SPIF process variables on the microhardness and surface roughness of Inconel 625, setting a standard for Inconel 625 superalloy forming. • The study optimizes SPIF parameters to simultaneously improve the microhardness and reduce the surface roughness in Inconel 625 components, showcasing a balanced approach for quality enhancement. • The computation and validation of quadratic models for predicting microhardness and surface roughness based on SPIF parameters represent a major advancement, which shows significant prediction capability with less than 5 % prediction error. • The research identifies critical SPIF parameters and their optimal settings to achieve targeted responses in Inconel 625 components, offering practical guidelines for industry application and enhancing surface quality. [ABSTRACT FROM AUTHOR]