Covid-19 meets game theory: a proposed experiment

Researchers around the globe are searching for a "combo-drug" against Covid-19 by trying to combine various existing drugs. Given a set of such drugs, various algorithms (based, for example, on artificial intelligence) are used to identify the efficacy of different shares of the constituent drugs in the combo-drug. Namely, the relative weight of each drug in a "cooperative" scheme of therapy is sought-after. In the current note we propose to identify these weights using the theory of cooperative games, and in particular the Shapley value, one of the fundamental solution concepts of such games. We derive the weight of each drug by its (normalized) average marginal contribution over all possible "coalitions" of drugs it is used with, where a drug's marginal contribution to a coalition is defined as the increase in the coalition's probability to act against a virus should the drug become its "member". Hence we endow each drug with a consistent measure of significance (which is due to the consistency that Shapley value is associated with). At a theoretical level, we build the cooperative game, and compute the Shapley values, within a milestone model in drug combination theory, the Bliss independence model. At a practical level, the predictions of our game-theoretic model can be tested by using in-vitro experiments, namely experiments that are conducted in test tubes.

The rapid synthesis of integral stimuli

Integral stimuli (e.g. colours varying in saturation and brightness) are classically considered to be processed holistically (i.e. as undifferentiated stimulus wholes); people analyze such stimuli into their consistent dimensions only with substantial time, effort, training, or instruction (Foard & Kemler Nelson, 1984). In contrast, Combination Theory (Wills et al., 2015) argues that the dimensions of integral stimuli are quickly combined. Through an investigation of the effects of time pressure, we support Combination Theory over the classical holistic-to-analytic account. Specifically, using colored squares varying in saturation and brightness, we demonstrate that the prevalence of single-dimension classification increases as stimulus presentation time is reduced. We conclude that integral stimuli are not slowly analyzed, they are quickly synthesized.

Emotion Analysis of College Students Using a Fuzzy Support Vector Machine

With the rapid development of society, the number of college students in our country is on the rise. College students are under pressure due to challenges from the society, school, and family, but they cannot find a suitable solution. As a result, the psychological problems of college students are diversified and complicated. The mental health problem of college students is becoming more and more serious, which requires urgent attention. This article realizes the monitoring of university mental health by identifying and analyzing the emotions of college students. This article uses EEG to determine the emotional state of college students. First, feature extraction is performed on different rhythm data of EEG, and then a fuzzy support vector machine (FSVM) is used for classification. Finally, a decision fusion mechanism based on the D-S evidence combination theory is used to fuse the classification results and output the final emotion recognition results. The contribution of this research is mainly in three aspects. One is the use of multiple features, which improves the efficiency of data use; the other is the use of a fuzzy support vector machine classifier with higher noise resistance, and the recognition rate of the model is better. The third is that the decision fusion mechanism based on the D-S evidence combination theory takes into account the classification results of each feature, and the classification results assist each other and integrate organically. The experiment compares emotion recognition based on single rhythm, multirhythm combination, and multirhythm fusion. The experimental results fully prove that the proposed emotion recognition method can effectively improve the recognition efficiency. It has a good practical value in the emotion recognition of college students.

Contextual Approach to Industrial Situation Recognition

The article describes the development of multifaceted and efficient approaches to the context information analysis for synthesis of industrial situations context recognition algorithm in automated management systems within the enterprises. The probability theory method and method of statistical analysis, decision theory method, methods of algorithm and combination theory were used while researching. The research resulted in the development of new approaches to the context information analysis framework for pattern recognition which enables us to identify the procedure of contextual recognition for synthesis of working industrial situation recognition algorithm. A correspondence between the recognition error rate and the guaranteed recognition threshold, which can be used for setting up the automated context-based recognition systems, was analytically obtained during the research.

Robust features extraction for general fish classification

Image recognition process could be plagued by many problems including noise, overlap, distortion, errors in the outcomes of segmentation, and impediment of objects within the image. Based on feature selection and combination theory between major extracted features, this study attempts to establish a system that could recognize fish object within the image utilizing texture, anchor points, and statistical measurements. Then, a generic fish classification is executed with the application of an innovative classification evaluation through a meta-heuristic algorithm known as Memetic Algorithm (Genetic Algorithm with Simulated Annealing) with back-propagation algorithm (MA-B Classifier). Here, images of dangerous and non-dangerous fish are recognized. Images of dangerous fish are further recognized as Predatory or Poison fish family, whereas families of non-dangerous fish are classified into garden and food family. A total of 24 fish families were used in testing the proposed prototype, whereby each family encompasses different number of species. The process of classification was successfully undertaken by the proposed prototype, whereby 400 distinct fish images were used in the experimental tests. Of these fish images, 250 were used for training phase while 150 were used for testing phase. The back-propagation algorithm and the proposed MA-B Classifier produced a general accuracy recognition rate of 82.25 and 90% respectively.

Simultaneously Testing for Location and Scale Parameters of Two Multivariate Distributions

In this article, we propose nonparametric tests for simultaneously testing equality of location and scale parameters of two multivariate distributions by using nonparametric combination theory. Our approach is to combine the data depth based location and scale tests using combining function to construct a new data depth based test for testing both location and scale parameters. Based on this approach, we have proposed several tests. Fisher's permutation principle is used to obtain p-values of the proposed tests. Performance of proposed tests has been evaluated in terms of empirical power for symmetric and skewed multivariate distributions and compared to the existing test based on data depth. The proposed tests are also applied to a real-life data set for illustrative purpose.

DESIGN RECIPES OF PUREE FOR CANNED FOOD OF FUNCTIONAL PURPOSE FOR BABY FOOD

Спроектированы рецептуры пюреобразных консервов функционального назначения для детского питания. Проектирование рецептур поликомпонентных пюре проводили на основе принципов пищевой комбинаторики с учетом суточной потребности детского организма в функциональных ингредиентах: инулине, пищевых волокнах, витаминах С и Р, β-каротине, железе и калии. Выбрано овощное сырье – клубни топинамбура, содержащие инулин, обладающий гипогликемическими свойствами, морковь и тыква, содержащие антиоксиданты и антитоксические ингредиенты, а также фруктовое сырье – яблоки, содержащие комплекс антиоксидантов. Эталоном служил продукт, содержащий функциональные ингредиенты в количестве 10–50% суточной нормы, что отвечает требованиям, предъявляемым ГОСТ Р 52349–2005. Наиболее высокие дегустационные оценки получили образцы, содержащие, %: пюре из топинамбура 20–50, пюре из яблок 20–65, пюре из тыквы (смесь 1) или моркови (смесь 2) 10–35. Соотношение компонентов в смеси 3 определяли, приняв количество пюре топинамбура в продукте постоянным и равным 45%, а остальные компоненты варьировали в пределах 0–55% от массы смеси. Исследован химический состав предназначенного для детского питания овощного и фруктового сырья как источник биологически активных веществ. После оптимизации рецептурных компонентов методом компьютерного моделирования изготовлены опытные образцы и проведена органолептическая оценка разработанных рецептур. Установлено, что разработанные рецептуры обеспечивают получение продуктов, сбалансированных по содержанию физиологически функциональных ингредиентов и обладающих высокими органолептическими свойствами. Have been designed formulations of puree canned food of functional use for baby food. Development of compoundings of multicomponent purees was carried out on the basis of the principles of food combination theory taking into account the daily need of a children's organism for functional ingredients: inulin, food fibers, vitamins C and P, β-carotene, iron and potassium. Vegetable raw materials are chosen – Jerusalem artichoke tubers containing inulin, which has hypoglycemic properties, carrots and pumpkin, containing antioxidants and antitoxic ingredients, as well as fruit raw materials – apples, containing a complex of antioxidants. The product containing functional ingredients in number of 10–50% of standard daily rate that meets requirements of GOST P 52349–2005 served as a standard. The highest tasting estimates have received the samples containing, %: Jerusalem artichoke puree 20–50, puree apples 20–65, puree pumpkin (mix 1) or puree carrots (mix 2) 10–35. The ratio of the components in the mixture 3 was determined as follows: the amount of Jerusalem artichoke puree in a product was accepted to constant and equal 45%, and other components – within the limits 0–55% of the mass of mix. The chemical composition of the vegetable and fruit raw materials as a source of biologically active agents for products of baby food is investigated. After optimization of prescription components the method of computer modeling has made prototypes and organoleptic assessment of the developed compoundings is carried out. It is established that the developed compounds provide the products balanced on the content of physiologically functional ingredients and having high organoleptic properties.