Teaching English in preschool age - selection of methods and techniques

The main purpose of this article is to present methods and techniques that can be used in the process of teaching a foreign language at preschool age. The first aspects to be addressed are developmental features of children, such as mechanical memory, short attention span, emotions and physiology of brain. The following issue described in the article refers to conventional methods, such as the Direct Method and the Audiolingual Method. The third part is devoted to unconventional methods, such as the Natural Approach, CLT, the Spiral Language System, as well as methods based on action (TPR), or - observation and words. They are supported by interesting techniques that are considered key factors in the discussed topic.

Derivation-based noncommutative field theories on AF algebras

In this paper, we start the investigation of a new natural approach to “unifying” noncommutative gauge field theories (NCGFT) based on approximately finite-dimensional ([Formula: see text]) [Formula: see text]-algebras. The defining inductive sequence of an [Formula: see text] [Formula: see text]-algebra is lifted to enable the construction of a sequence of NCGFT of Yang–Mills–Higgs types. This paper focuses on derivation-based noncommutative field theories. A mathematical study of the ingredients involved in the construction of a NCGFT is given in the framework of [Formula: see text] [Formula: see text]-algebras: derivation-based differential calculus, modules, connections, metrics and Hodge ⋆-operators, and Lagrangians. Some physical applications concerning mass spectra generated by Spontaneous Symmetry Breaking Mechanisms (SSBM) are proposed using numerical computations for specific situations.

The lytic siphophage vB_StyS-LmqsSP1 reduces Salmonella Typhimurium isolates on chicken skin

Phage-based biocontrol of bacteria is considered as a natural approach to combat food-borne pathogens. Salmonella spp. are notifiable and highly prevalent pathogens that cause foodborne diseases globally. In this study, six bacteriophages were isolated and further characterized that infect food-derived Salmonella isolates from different meat sources. The siphovirus VB_StyS-LmqsSP1, which was isolated from a cow´s nasal swab, was further subjected to in-depth characterization. Phage-host interaction investigations in liquid medium showed that vB_StyS-LmqsSP1 can suppress the growth of Salmonella spp. isolates at 37°C for ten hours and reduce the bacterial titer at 4°C significantly. A reduction of 1.4 to 3 log units was observed in investigations with two food-derived Salmonella isolates and one reference strain under cooling conditions using MOIs of 10 4 and 10 5 . Phage application on chicken skin resulted in a reduction of about 2 log units in the tested Salmonella isolates from the first three hours throughout a one-week experiment at cooling temperature and an MOI of 10 5 . The one-step growth curve analysis using vB_StyS-LmqsSP1 demonstrated a 60-min latent period and a burst size of 50-61 PFU/infected cell for all tested hosts. Furthermore, the genome of the phage was determined to be free from genes causing undesired effects. Based on the phenotypic and genotypic properties, LmqsSP1 was assigned as a promising candidate for biocontrol of Salmonella Typhimurium in food. Importance: Salmonella enterica is one of the major global causes of foodborne enteritis in humans. The use of chemical sanitizers for reducing bacterial pathogens in the food chain can result in the spread of bacterial resistance. Targeted and clean label intervention strategies can reduce Salmonella contamination in food. The significance of our research demonstrates the suitability of a bacteriophage (vB_StyS-LmqsSP1) for biocontrol of Salmonella enterica serovar Typhimurium on poultry due to its lytic efficacy under conditions prevailing in food production environments.

Safe Learning of Lifted Action Models

Creating a domain model, even for classical, domain-independent planning, is a notoriously hard knowledge-engineering task. A natural approach to solve this problem is to learn a domain model from observations. However, model learning approaches frequently do not provide safety guarantees: the learned model may assume actions are applicable when they are not, and may incorrectly capture actions' effects. This may result in generating plans that will fail when executed. In some domains such failures are not acceptable, due to the cost of failure or inability to replan online after failure. In such settings, all learning must be done offline, based on some observations collected, e.g., by some other agents or a human. Through this learning, the task is to generate a plan that is guaranteed to be successful. This is called the model-free planning problem. Prior work proposed an algorithm for solving the model-free planning problem in classical planning. However, they were limited to learning grounded domains, and thus they could not scale. We generalize this prior work and propose the first safe model-free planning algorithm for lifted domains. We prove the correctness of our approach, and provide a statistical analysis showing that the number of trajectories needed to solve future problems with high probability is linear in the potential size of the domain model. We also present experiments on twelve IPC domains showing that our approach is able to learn the real action model in all cases with at most two trajectories.

Optimal Portfolio Diversification via Independent Component Analysis

A natural approach to enhance portfolio diversification is to rely on factor-risk parity, which yields the portfolio whose risk is equally spread among a set of uncorrelated factors. The standard choice is to take the variance as risk measure, and the principal components (PCs) of asset returns as factors. Although PCs are unique and useful for dimension reduction, they are an arbitrary choice: any rotation of the PCs results in uncorrelated factors. This is problematic because we demonstrate that any portfolio is a factor-variance-parity portfolio for some rotation of the PCs. More importantly, choosing the PCs does not account for the higher moments of asset returns. To overcome these issues, we propose using the independent components (ICs) as factors, which are the rotation of the PCs that are maximally independent, and care about higher moments of asset returns. We demonstrate that using the IC-variance-parity portfolio helps to reduce the return kurtosis. We also show how to exploit the near independence of the ICs to parsimoniously estimate the factor-risk-parity portfolio based on value at risk. Finally, we empirically demonstrate that portfolios based on ICs outperform those based on PCs, and several state-of-the-art benchmarks.

A ‘Natural’ Approach to Design

A ‘Natural’ Approach to Design

A ‘Natural’ Approach to Design

A ‘Natural’ Approach to Design

The Formal Framework for Collective Systems

Automated reasoning is becoming crucial for information systems. Building one uniform decision support system has become too complicated. The natural approach is to divide the task and combine the results from different subsystems into one uniform answer. It is the basic idea behind the system approach, where one solution is a composition of multiple subsystems. In this paper, the main emphasis is on establishing the theoretical framework that combines various reasoning methods into a collective system. The system’s formal abstraction uses graph theory and provides a discussion on possible aggregation function definitions. The proposed framework is a tool for building and testing specific approaches rather than the solution itself.