Fishing gear selectivity of wire trap to limbat fish (Clarias nieuhofii) in swamp water Rimbo Ulu, Tebo Regency, Jambi Province

This study aims to analyze the level of selectivity of wire trap fishing gear against limbat fish (Clarias nieuhofii) in the swamp waters of Tebo Regency, Jambi Province. Data collection was carried out by catching trials using 3 units of wire traps with 30 replications, in June-August 2020. The research data were analyzed descriptively using the logistical selectivity model of the maximum likelihood method equation in the solver program from microsoft excel. The results showed that the wire traps were not selective for size but were selective for the limbat fish species (C.nieuhofii). The selectivity curve based on the logistical function shows that the probability of being caught by fish are at 22-48 mm body height, while the size of the fish that can escape has a maximum height of 34 mm or a length of 182 mm.

Borrowing external information to estimate angler size selectivity: model development and application to Murray cod

Estimating the size selectivity of fishery users and sampling methods can be difficult to achieve due to data limitations. However, these limitations can be moderated by borrowed information from other sources such as other systems, times, and species. Here we develop a model that integrates an externally sourced boat electrofishing length–vulnerability model with internally sourced boat electrofishing and angling catch data to estimate length-dependent vulnerability of fish to angling in a data-limited situation. We apply the model to Murray cod (Maccullochella peelii) as an example and show that angling for Murray cod selectively captures a narrow range of sizes that includes medium to large size fish. Although boat electrofishing also followed a similar pattern, the range of fish sizes vulnerable to capture was much broader, including a more uniform vulnerability of all size classes evaluated. Understanding the length selectivity to capture has key implications for effective determination of fisheries regulations, as well as interpreting monitoring data. Thus, we see this modelling approach as a good option when more informative data are not available to support the estimation process.

Bouncing off walls – widths of exit channels from shallow minima can dominate selectivity control

A selectivity model based on the widths of pathways to competing products, rather than barrier heights, is formulated for the butadiene + allyl cation reaction.

Does expressing subjectivity in online reviews enhance persuasion?

Purpose People express subjectivity and objectivity in everyday communication, yet little is known about how such linguistic content affects persuasion in electronic word-of-mouth (eWOM). Drawing on the congruity theory and the selectivity model, the present study proposes that the effectiveness of subjectivity/objectivity expressions in an online review is contingent on whether the consumption experience is primarily hedonic or utilitarian, and whether the decision maker is a male or female. Furthermore, this study aims to examine the psychological mechanism that underlies the proposed effects. Design/methodology/approach This research used an experimental design to test the hypotheses. Four versions of online review stimuli were created. Participants were asked to read the online reviews and to complete a survey. Findings The findings indicate that expressing subjectivity (vs objectivity) in online reviews effectively boosts men’s purchase intention in the hedonic context and women’s purchase intention in the utilitarian context. Furthermore, the mediation analysis reveals that perceived relevance of the review is the psychological mechanism explaining the joint effects of linguistic style, consumption type and gender on purchase intention. Originality/value This research is the first to examine expressing subjectivity (vs objectivity) as a persuasion strategy in online reviews. Findings of this research add to the growing literature on linguistic effects in eWOM. Furthermore, this research deepens the understanding of conversational norms for hedonic vs utilitarian consumption in consumer-generated content and gender differences in processing online reviews.

Model-Based Design of Experiments for Kinetic Study of Anisole Upgrading Process over Pt/γAl2O3: Model Development and Optimization by Application of Response Surface Methodology and Artificial Neural Network

The kinetic of catalytic upgrading of anisole as a lignin−derived bio−oil component is investigated experimentally overPt/γAl2O3at 573−673 K and 14 bar. According to experimental results, benzene, phenol, 2−methylphenol, 2,6−dimethylphenol, 2,4,6−trimethylphenol, and hexamethylbenzene are identified as the main products. The results indicated that the kinetically significant reaction classes are hydrogenolysis, hydrodeoxygenation (HDO), alkylation, and hydrogenation. The response surface methodology (RSM) is applied to optimize the experimental data which obtained at suggested conditions by design of experiment (DOE). Due to the complex nature of the system, artificial neural networks (ANNs) were employed as an efficient tool to model the behavior of the system.RSMandANNmethods were constructed based upon theDOE’s points and then utilized for generating extra−simulated data. Data simulated by theRSM/ANNmethod were used to fit power law kinetic rate expressions for the reactions. The coefficient of determination (R2) was obtained 0.998 and 0.973 for anisole conversion model and benzene selectivity model which represented the high accuracy of model predictions. The correlation coefficient (R) and mean square error (MSE) ofANNmodel equaled to 0.97 and 8.3 × 10−12respectively means high accuracy of the developed model. The results of kinetic modeling with simulated data from theANNandRSMmodels revealed that the highest reaction order during the upgrading process of anisole belongs to hydrogenolysis of anisole to phenol. Also the activation energy of hydrogenolysis reaction was lower thanHDO.