The Serra Spanish mackerel fishery (Scomberomorus brasiliensis – Teleostei) in Southern Brazil: the growing landings of a high trophic level resource

In fisheries, the phenomenon known as fishing down food webs is supposed to be a consequence of overfishing, which would be reflected in a reduction in the trophic level of landings. In such scenarios, the resilience of carnivorous, top predator species is particularly affected, making these resources the first to be depleted. The Serra Spanish mackerel, Scomberomorus brasiliensis, exemplifies a predator resource historically targeted by artisanal fisheries on the Brazilian coast. The present work analyzes landings in three periods within a 50-year timescale on the Parana coast, Southern Brazil, aiming to evaluate whether historical production has supposedly declined. Simultaneously, the diet was analyzed to confirm carnivorous habits and evaluate the trophic level in this region. Surprisingly, the results show that from the 1970’s to 2019 Serra Spanish mackerel production grew relatively to other resources, as well as in individual values. The trophic level was calculated as 4.238, similar to other Scomberomorus species, consisting of a case where landings increase over time, despite the high trophic level and large body size of the resource. The results agree with a recent global assessment that has demystified a necessary correlation between high trophic level and overexploitation, but possible factors acting on the present findings are discussed.

An Empirical Model for Geopolymer Reactions Involving Fly Ash and GGBS

Numerous works are reported in literature regarding the enhancement of compressive strength of fly ash-GGBS geopolymer combinations with addition of alkali activators of varying concentrations. However, a limited study has been chronicled, revealing the specific role of alkali or alkaline earth contributed by the fly ash-GGBS combinations on the compressive strength development. It is well known that the strength of a geopolymer is dependent on gel formation from Al/Si ratio, Ca/Si ratio, and Ca/(Si + Al) ratio but their exact role when cured for various extended periods is unknown as yet. In the present study, alkali concentration in a fly ash-GGBS geopolymer combination was varied from 6 M to 12 M with increments of two mol in six different fly ash-GGBS combinations with a minimum of 20 percent and a maximum of 70 percent GGBS. The correlation coefficients between compressive strength and Al/Si, Ca/Si, and Ca/(Si + Al) ratios exhibited values higher than 0.95 taken individually. Multiple linear regression analysis with compressive strength (as dependent parameter) and individual values of Al/Si, Ca/Si, and Ca/(Si + Al) ratios (as independent parameters) was effectuated. It was observed that, depending on the composition, the compressive strength circumstantiated a changeover from Ca/Si to Ca/(Si + Al) ratio in the intermediate composition range. Such a detailed analysis is considered supportive of developing a suitable composition which will provide the optimum compressive strength of the combination.

Kendall Transformation: A Robust Representation of Continuous Data for Information Theory

Kendall transformation is a conversion of an ordered feature into a vector of pairwise order relations between individual values. This way, it preserves ranking of observations and represents it in a categorical form. Such transformation allows for generalisation of methods requiring strictly categorical input, especially in the limit of small number of observations, when discretisation becomes problematic.In particular, many approaches of information theory can be directly applied to Kendall-transformed continuous data without relying on differential entropy or any additional parameters. Moreover, by filtering information to this contained in ranking, Kendall transformation leads to a better robustness at a reasonable cost of dropping sophisticated interactions which are anyhow unlikely to be correctly estimated. In bivariate analysis, Kendall transformation can be related to popular non-parametric methods, showing the soundness of the approach.The paper also demonstrates its efficiency in multivariate problems, as well as provides an example analysis of a real-world data.

Application of the linear method of discriminant analysis of reflectance spectra in the near infrared region for the species identification of fish of the Salmonidae family

It is well known that fish belonging to the Salmonidae family differ in their nutritional value. Anatomical and morphological features of different salmon species have a certain similarity; therefore, representatives of this family are most often falsified. Assortment falsification of products from fish of this family is usually carried out by replacing more valuable species with cheaper ones with a reduced nutritional value. Most often, counterfeiting of Atlantic salmon (salmon) by Far Eastern ones (chum salmon, pink salmon, chinook salmon, coho salmon) is found. Near infrared spectroscopy (NIR) is now increasingly used for identification and authentication of closely related organisms, in some cases being a rapid method replacing genetic analysis. We have obtained diffusion reflectance spectra of NIR radiation for three species of fish from the Northern Basin belonging to the salmon family. The best classification by fish species has been obtained by analyzing the NIR spectra of pre-dried fat-free muscle tissue samples. In case of wet samples, the observed differences are less significant, up to insignificant differences in individual values from neighboring clusters. The possibility of using the method of linear discriminant analysis of the NIR reflection spectra of muscle proteins for the species identification of fish has been shown.

USING OF MULTILAYER NEURAL NETWORKS FOR THE SOLVING SYSTEMS OF DIFFERENTIAL EQUATIONS

The article considers the study of methods for numerical solution of systems of differential equations using neural networks. To achieve this goal, thefollowing interdependent tasks were solved: an overview of industries that need to solve systems of differential equations, as well as implemented amethod of solving systems of differential equations using neural networks. It is shown that different types of systems of differential equations can besolved by a single method, which requires only the problem of loss function for optimization, which is directly created from differential equations anddoes not require solving equations for the highest derivative. The solution of differential equations’ system using a multilayer neural networks is thefunctions given in analytical form, which can be differentiated or integrated analytically. In the course of this work, an improved form of constructionof a test solution of systems of differential equations was found, which satisfies the initial conditions for construction, but has less impact on thesolution error at a distance from the initial conditions compared to the form of such solution. The way has also been found to modify the calculation ofthe loss function for cases when the solution process stops at the local minimum, which will be caused by the high dependence of the subsequentvalues of the functions on the accuracy of finding the previous values. Among the results, it can be noted that the solution of differential equations’system using artificial neural networks may be more accurate than classical numerical methods for solving differential equations, but usually takesmuch longer to achieve similar results on small problems. The main advantage of using neural networks to solve differential equations` system is thatthe solution is in analytical form and can be found not only for individual values of parameters of equations, but also for all values of parameters in alimited range of values.

Highland amphibians - Recalculation of data from 1990 to 2010 on the effects of extremely diluted thyroxine

Experiments on amphibian metamorphosis can vary considerably in duration. The authors had set themselves the task of defining a generally applicable pooling method for metamorphosis experiments. The problem of artificial differences in variability when comparing and pooling data from several experiments was approached by normalization with respect to time based on the development of both test and the control animals. The range from 0% to 100% over which the fraction of four-legged animals progresses in the course of an experiment is divided into 10%-intervals and the 10% reference points are mapped on a corresponding scale. Each measurement is then assigned to the point on the time scale to which it is closest. In this way each reference point is assigned a value giving the number or percentage of four-legged animals at that point on the scale. Subsequent analysis was then based on the individual values for the test and control groups that corresponded to the joint 10% reference point. Normalization respect to time was done on the assumption that differences in metamorphosis speed attributable to treatment would override differences in duration between experiments. The results of experiments performed over the course of two decades (1990 - 2010) on highland Rana temporaria treated with a homeopathically prepared high dilution of thyroxine (“30x”) are presented in full detail based on this normalization method. Differences found between treatment groups thus calculated were in line with those obtained with other pooling methods. Thyroxine 30x does slow down metamorphosis in inert highland amphibians. This was observed by five researchers in 20 sub-experiments, and it seems to be the most reliable bio-assay found in amphibian research on homeopathy so far. When experiments were performed with highland animals pretreated by hyperstimulation with molecular thyroxine, slowing down of metamorphosis was again observed (by three out of four researchers) in most of 10 sub-experiments.

27 Open Problems in Kolmogorov Complexity

This formula can be informally read as follows: the ith messagemi brings us log(1=pi) "bits of information" (whatever this means), and appears with frequency pi, so H is the expected amount of information provided by one random message (one sample of the random variable). Moreover, we can construct an optimal uniquely decodable code that requires about H (at most H + 1, to be exact) bits per message on average, and it encodes the ith message by approximately log(1=pi) bits, following the natural idea to use short codewords for frequent messages. This fits well the informal reading of the formula given above, and it is tempting to say that the ith message "contains log(1=pi) bits of information." Shannon himself succumbed to this temptation [46, p. 399] when he wrote about entropy estimates and considers Basic English and James Joyces's book "Finnegan's Wake" as two extreme examples of high and low redundancy in English texts. But, strictly speaking, one can speak only of entropies of random variables, not of their individual values, and "Finnegan's Wake" is not a random variable, just a specific string. Can we define the amount of information in individual objects?

Unleashing the Potential Role of CSR and Altruistic Values to Foster Pro-Environmental Behavior by Hotel Employees

The hotel sector, around the globe, has a bad reputation due to its oversized carbon footprint. Therefore, this sector requires different approaches to improve its environmental management efforts. In this regard, the importance of employees’ pro-environmental behavior (PEB) has been recently discussed to reduce an enterprise’s carbon footprint. Reflecting this, the current work aims to improve PEB of employees as an outcome of corporate social responsibility (CSR) and altruistic values (ALV) in the hotel enterprises of an emerging economy. A total of 489 valid responses was collected from hotel employees, which were then analyzed through structural equation modeling (SEM). Different hypotheses were validated by employing SEM, and the results confirmed that CSR, directly and indirectly, via ALV as a mediator, improves PEB. The current work offers insights into the hotel industry for improving its environmental footprint through CSR and ALV. Moreover, academically, the current work advances the literature on CSR and environmental management from the perspective of hotel enterprises and by highlighting the role of individual values, especially ALV.

Connection between basic values and emigration attitudes of Russian youth

The ambiguity and inconsistency of the data on the connection between emigration attitudes and metavalues spurs the research on the relation between emigration attitudes and basic values. Hence, the problem of studying the deterministic character of youth attitudes to emigration is seen as of relevance. The purpose of this research is to determine the nature of the connection between basic values and emigration attitudes. Hypotheses: 1. The basic values that make up metavalues act as the predictors of emigration attitudes. 2. The basic values constituting the contrastive metavalues of Preservation and Openness to Change are simultaneously connected with emigration attitudes, and the nature of their connections is different. 3. The basic values constituting the metavalue of Self-Affirmation have a positive correlation with emigration attitudes. The study is carried out on a sample of respondents (N = 646) aged 17 to 35, including 78% (504) of women. The research applies the “Scales of Migration Attitudes” (S. A. Kuznetsova, I. Yu. Kuznetsov, A. V. Feshchenko) modified to study emigration attitudes. The study also uses PVQ-21–ESS7 versions of the questionnaire measuring individual values (Sh. Schwartz) which enables to document the degree of expression of values. Finally, the research makes use of the method of multiple linear regression analysis. The results show that the attitude of the subject is the most pronounced one among all other components of emigration attitudes (the attitude of the loved ones, the expectations of the loved ones). Basic values have a major impact on the revealed connections between emigration attitudes and metavalues. For example, the values of tradition and security have a negative correlation with the metavalue of Preservation. The values of stimulation have a positive correlation with the metavalue of Openness to Change. The values of power have a positive correlation with the metavalue of Self-Affirmation. Evidently, young adults are more likely to plan to emigrate due to their personal attitudes and motives rather than to those of their close environment. Attitudes towards emigration are expressed by those young adults who: 1) are less focused on traditions and customs but appreciate security; 2) strive to enrich their lives with new sensations and emotions; 3) appreciate material well-being. The results of the study reveal the factors contributing to the emergence of attitudes to emigration in young adults. The results of the study can be used to predict international mobility of young adults. Additionally, they are of importance for the psychological work with potential emigrants.