Model Of States Research Articles

Genital anatomy and copulatory interactions in the broad snouted Caiman (Caiman latirostris)

The broad snouted caiman is a crocodylian native to South America that is subject to extensive conservation management in both wild and farming environments. Although reproductive behaviors like egg laying and clutch care have been examined in this species, little else is known about their copulatory system. We examined the anatomy of male and female cloacal and genital tissues ex vivo to build hypotheses of their interactions during copulation and the effects of that interaction on insemination. Male phallic glans tissues were artificially inflated to expand into their copulatory state, allowing the examination and quantification of structural changes at the gross and tissue levels. Digital reconstruction of MRI stacks yielded three-dimensional tissue compartment specific glans models of the inflated state. Silicone molds of female cloacae and oviducts in conjunction with dissection and diceCT analysis allowed us to assess internal geometry and infer how male and female features interact in copulo. We observed glans expansion within the female proctodeum would result in a copulatory lock limiting deeper intromission or retraction. Intromission and subsequent creation of the copulatory lock produces extensive clitoral compression, providing a possible mechanism for female assessment of male copulatory performance. Further, glans expansion forms a distal lumen that positions the glans tip in or near the vaginal openings. A coiled, muscular vagina provides a possible mechanism for postcopulatory sexual selection by excluding semen. Together, the complex male-female interaction supports evidence for cryptic selection by female choice, which can act as a driver of genital coevolution.

Reflections on dynamics, adaptation and control: A cognitive architecture for mental models

In this paper, an overview of the wide variety of occurrences of mental models in the literature is discussed. They are classified according to two dimensions obtaining four categories of them: static-dynamic and world-mental, where static refers to mental models for static world states or for static mental states and dynamic refers to mental models for world processes or for mental processes. In addition, distinctions are made for what can be done by mental models: they can, for example, be (1) used for internal simulation, they can be (2) adapted, and these processes can be (3) controlled. This leads to a global three-level cognitive architecture covering these three ways of handling mental models. It is discussed that in this cognitive architecture reflection principles play an important role to define the interactions between the different levels.

THE PERFECT PERFORMANCE OF THE DEMOCRATIC REPUBLIC GOVERNMENT IN ATHENS (GREEK) THROUGH REFORMS (VI CENTURY BC - V CENTURY BC)

In comparison with ancient Orient nations, the Greek state was born much later and they created a new state institution which was a republic. This state was different from the government of absolute monarchies in the Orient. The state of Athens (Athènes) - an important city-state in ancient Greece, was a democratic republic and was gradually improved through the reforms that took place from the sixth to the fifth century BC. This is the first democratic republic in world history and it had a profound influence on the model of republic and democratic states in the world, especially in Europe and North America in modern times.

Action Generative Networks Planning for Deformable Object with Raw Observations

Synthesizing plans for a deformable object to transit from initial observations to goal observations, both of which are represented by high-dimensional data (namely “raw” data), is challenging due to the difficulty of learning abstract state representations of raw data and transition models of continuous states and continuous actions. Even though there have been some approaches making remarkable progress regarding the planning problem, they often neglect actions between observations and are unable to generate action sequences from initial observations to goal observations. In this paper, we propose a novel algorithm framework, namely AGN. We first learn a state-abstractor model to abstract states from raw observations, a state-generator model to generate raw observations from states, a heuristic model to predict actions to be executed in current states, and a transition model to transform current states to next states after executing specific actions. After that, we directly generate plans for a deformable object by performing the four models. We evaluate our approach in continuous domains and show that our approach is effective with comparison to state-of-the-art algorithms.

Dynamically Polarizable Force Fields for Surface Simulations via Multi-output Classification Neural Networks.

We present a general procedure to introduce electronic polarization into classical Molecular Dynamics (MD) force fields using a Neural Network (NN) model. We apply this framework to the simulation of a solid-liquid interface where the polarization of the surface is essential to correctly capture the main features of the system. By introducing a multi-input, multi-output NN and treating the surface polarization as a discrete classification problem, we are able to obtain very good accuracy in terms of quality of predictions. Through the definition of a custom loss function we are able to impose a physically motivated constraint within the NN itself making this model extremely versatile, especially in the modeling of different surface charge states. The NN is validated considering the redistribution of electronic charge density within a graphene based electrode in contact with an aqueous electrolyte solution, a system highly relevant to the development of next generation low-cost supercapacitors. We compare the performances of our NN/MD model against Quantum Mechanics/Molecular Dynamics simulations where we obtain a most satisfactory agreement.

Enhanced detection techniques of orbital angular momentum states in the classical and quantum regimes

The orbital angular momentum (OAM) of light has been at the center of several classical and quantum applications for imaging, information processing and communication. However, the complex structure inherent in OAM states makes their detection and classification nontrivial in many circumstances. Most of the current detection schemes are based on models of the OAM states built upon the use of Laguerre–Gauss (LG) modes. However, this may not in general be sufficient to capture full information on the generated states. In this paper, we go beyond the LG assumption, and employ hypergeometric-Gaussian (HyGG) modes as the basis states of a refined model that can be used—in certain scenarios—to better tailor OAM detection techniques. We show that enhanced performances in OAM detection are obtained for holographic projection via spatial light modulators in combination with single-mode fibers (SMFs), and for classification techniques based on a machine learning approach. Furthermore, a three-fold enhancement in the SMF coupling efficiency is obtained for the holographic technique, when using the HyGG model with respect to the LG one. This improvement provides a significant boost in the overall efficiency of OAM-encoded single-photon detection systems. Given that most of the experimental works using OAM states are effectively based on the generation of HyGG modes, our findings thus represent a relevant addition to experimental toolboxes for OAM-based protocols in quantum communication, cryptography and simulation.

A model liquid crystal cell in an RC circuit

A nematic liquid-crystal cell subject to an electric field created by electrodes held at constant potential is modeled as a variable capacitor in an RC circuit. The state of the system is characterized in terms of the director field in the cell and the charge on the electrodes. A dynamical system is developed that couples director dynamics in the cell (with no fluid flow) and charge dynamics in the circuit. The dynamical equations are derived from expressions for the total potential energy of the system and a dissipation involving a single rotational viscosity for the director plus Joule heating associated with current in the circuit. An effort is made to quantify effects, in particular the widely differing time scales for the processes involved, and numerical illustrations are given. The exercise illuminates aspects of the modeling of equilibrium states of such a system.

Fabrication, characterization, numerical simulation and compact modeling of P3HT based organic thin film transistors

This paper presents the fabrication, characterization and numerical simulation of poly-3-hexylthiophene (P3HT)-based bottom-gate bottom-contact (BGBC) organic thin film transistors (OTFTs). The simulation is based on a drift diffusion charge transport model and density of defect states (DOS) for the traps in the band gap of the P3HT based channel. It combines two mobility models, a hopping mobility model and the Poole–Frenkel mobility model. It also describes the defect density of states (DOS) for both tail and deep states. The model takes into account all the operating regions of the OTFT and includes sub-threshold and above threshold characteristics of OTFTs. The model has been verified by comparing the numerically simulated results with the experimental results. This model is also used to simulate different structure in four configurations of OTFT e.g. bottom-gate bottom-contact (BGBC), bottom-gate top-contact (BGTC), top-gate bottom-contact (TGBC) and top-gate top-contact (TGTC) configurations of the OTFTs. We also present the compact modeling and model parameter extraction of the P3HT-based OTFTs. The extracted compact model has been further applied in a p-channel OTFT-based inverter and three stage ring oscillator circuit simulation.

Development of estimation and forecasting method in intelligent decision support systems

The method of estimation and forecasting in intelligent decision support systems was developed. The essence of the method is the analysis of the current state of the object and short-term forecasting of the object state. Objective and complete analysis is achieved by using improved fuzzy temporal models of the object state and an improved procedure for processing the original data under uncertainty. Also, the possibility of objective and complete analysis is achieved through an improved procedure for forecasting the object state and an improved procedure for learning evolving artificial neural networks. The concepts of fuzzy cognitive model are related by subsets of influence fuzzy degrees, arranged in chronological order, taking into account the time lags of the corresponding components of the multidimensional time series. The method is based on fuzzy temporal models and evolving artificial neural networks. The peculiarity of the method is the possibility of taking into account the type of a priori uncertainty about the object state (full awareness of the object state, partial awareness of the object state and complete uncertainty about the object state). The possibility to clarify information about the object state is achieved using an advanced training procedure. It consists in training the synaptic weights of the artificial neural network, the type and parameters of the membership function, as well as the architecture of individual elements and the architecture of the artificial neural network as a whole. The object state forecasting procedure allows conducting multidimensional analysis, consideration, and indirect influence of all components of a multidimensional time series with their different time shifts relative to each other under uncertainty. The method provides an increase in data processing efficiency at the level of 15–25% using additional advanced procedures.

Determination of the mechanical properties of 3d-printed polymer products by methods of structural mechanics

Mathematical models of stress-strain state (SSS) for modeling tests of polymer composite samples obtained by fused deposition modeling (FDM) in approximations of isotropic and orthotropic media are formulated. An algorithm for solving the inverse SSS problem to determine the effective mechanical properties in the orthotropic approximation of composite products printed by the FDM method has been developed. Numerical models have been developed to solve inverse SSS problems to determine the effective orthotropic mechanical properties of composite products with different degrees of reinforcement, obtained using additive technologies based on the FDM method. The grid convergence of the developed numerical models by the method of double recalculation is investigated. It is established that the used mesh of geometric models of product samples leads to errors in determining the vector of the modulus of elasticity in the range of 0–3.19%, and the vector of the shear modulus does not exceed 0.05–0.2%. Numerical experiments to determine the effective mechanical properties of samples of composite polymeric materials in the approximation of orthotropic homogeneous medium were performed. The obtained results are compared with the data of calculations by analytical dependences to determine the effective mechanical properties of composite materials. It is shown that the results of numerical studies agree satisfactorily with the corresponding data obtained from analytical dependences in the range of 0.081–5.696%. It is established that all three components of the vectors of modulus of elasticity and shear increase with the degree of reinforcement. The largest increase is observed for the components of vectors and , which is due to the reinforcement in the direction , and the difference between the values ​​of the components of vectors and and and is due to the cross-sectional asymmetry of the strand. Dependences for operative prediction of effective orthotropic mechanical properties of composites based on PLA + KEVLAR 29 within the limits of change in the volume fraction of reinforcing fibers up to 5% are obtained. To develop new composite materials with predetermined properties, it is not necessary to perform multivariate, rather complex and cumbersome numerical experiments in solving the inverse SSS problem.

Modeling of stress-strain states of AMg6 alloy due to impact action of electrode-indenter in electrodynamic treatment

The Paton Welding Journal, 2021, №06. International Scientific-Technical and Production Journal «The Paton Welding Journal» «The Paton Welding Journal» has been published monthly since 2000 in English, ISSN 0957-798X. «The Paton Welding Journal» is a cover-to-cover English translation of the «Avtomaticheskaya Svarka» (Automatic Welding) journal. The «Avtomaticheskaya Svarka» journal has been published monthly since 1948 in Russian, ISSN 005-111X.

Substance use disorder: a model of atmosphere within families living with SUD

ABSTRACT This study shares the experiences of 16 family members who have lived with a close relative with substance use disorder (SUD). Primarily, the study asks, what are the experiences of family members living with an individual with SUD? In particular, what are their experiences of affection and emotional bonds? Moreover, it asks, what are the experiences of each family member regarding cohesion and communication? Qualitative methods were used, and 16 semi-structured interviews were conducted. The participants were organized into groups of four: four parents, four spouses, four adult children and four siblings of individuals affected by SUD. Each group comprised two men and two women. Overall, the participants felt that SUD had harmed their families’ emotional bonds. Parents and adult children reported greater affection toward their relatives with SUD (children and parents) than spouses and siblings did toward their relatives affected by SUD (spouses and siblings). These feelings were expressed in terms of positive emotions such as compassion and hope, whereas spouses and siblings expressed more negative feelings such as hopelessness or rage. From the analysis, a proposed dynamic functional model of emotional states in the study’s families was formed, showing the dynamics of feelings and emotional bonds between specific family members and the family member with SUD (This paper is a part of a larger research project).

УЗАГАЛЬНЕННЯ МОДЕЛІ ФОЛЬКЕРСЕНА НА ВИПАДОК ОСЬОВОЇ СИМЕТРІЇ

Thin-walled structures may contain defects as cracks and holes that are leftovers of the material the construction, is made of or they occur during the operation as a result of, for example, mechanical damage. The presence of holes in the plate causes a concentration of stresses at the boundary of the holes and ultimately leads to premature failure of the structural element. Repair of local damage of modern aircraft structures can be made by creating overlays that are glued to the main structure. The overlay takes on part of the load, unloading the damaged area. This method of repair provides tightness and aerodynamic efficiency to the structure. The calculation of the stress state of such glued structures is usually performed by using the finite element method. The classic models of the stress state of overlapped joints are one-dimensional. That is, the change of the stress state along only one coordinate is considered. At the same time, the connections of a rectangular form are also considered. The purpose of this work is to create a mathematical model of the stress state of circular axisymmetric adhesive joints and to build an appropriate analytical solution to the problem. It is assumed that the bending of the plates is absent; the deformation of the plates is even by thickness. The adhesive layer works only on the shift. The main plate and the overlay are considered isotropic. The solution is built on polar coordinates. The stress state of the connection depends only on the radial coordinate, i.e. one-dimensional. The solution is obtained in analytical form. This mathematical model is a generalization of the classical model of the adhesive connection of Volkersen to a circular or annular region and is considered for the first time. Boundary conditions are met exactly. The satisfaction of marginal conditions, as well as boundary conditions, leads to a system of linear equations with respect to the unknown coefficients of the obtained solutions. The model problem is solved and the numerical results are compared with the results of calculations performed by using the finite element method. It is shown that the proposed model has sufficient accuracy for engineering problems and can be used to solve problems of the design of aerospace structures.

Monitoring of dough fermentation during Chinese steamed bread processing by near‐infrared spectroscopy combined with spectra selection and supervised learning algorithm

AbstractAs a critical control point in the processing of Chinese steamed bread, fermentation is mainly judged by traditional methods. The purpose of this work was to develop an intelligent method of dough fermentation monitoring by near‐infrared (NIR) spectroscopy technology. First, Savitzky–Golay smoothing filter was utilized as the best method to preprocess the original NIR spectra for eliminating spectral noise by comparison, and the frame size was 15. Second, the unrepresentative intervals were eliminated from preprocessed NIR spectra using synergy interval partial least squares (Si‐PLS) preliminarily. Based on the selected intervals, competitive adaptive reweighted sampling (CARS) was adopted to further select variables. Then, 13 significant variables were screened from full wavelength variables by utilizing CARS‐Si‐PLS. Finally, the K‐nearest neighbor (KNN) and support vector machine (SVM) monitoring models of dough fermentation state were established. The results showed that the accuracy of training set and prediction set of KNN model were 89 and 86%, respectively, and that of SVM model were 94 and 92%, respectively. By comparison, the performance of two models, it was found that SVM was superior to KNN. This work verified that NIR spectroscopy couple with multivariate calibration models can replace assessor judgment to realize rapid and online monitoring of dough fermentation.Practical ApplicationsThe method based on NIR spectroscopy coupled with supervised learning algorithm can be used instead of assessor to judge the fermentation state of dough, so as to avoid subjective influence of assessor on the judgment result. In addition, it can realize the rapid online monitoring of dough fermentation state, which is beneficial to enhance the automation level of Chinese steamed bread processing.

Reversal of triboelectric charges on sol–gel oxide films annealed at different temperatures

Using Kelvin probe force microscopy, we studied the contact-electrification (CE) induced charge density on the surfaces of organic–inorganic composite oxide films, such as Nb2O5, ZrO2, and HfO2 films, prepared by a sol–gel method and annealed at different temperatures. The results show that positive triboelectric charges on the film surface gradually turn into negative ones with the increase in the annealing temperature. This phenomenon is attributed to the broken valence bonds between organics and organic–inorganic composites in the film at high temperature, which causes oxygen vacancy defects and consequently changes the surface states of the film. A surface states model is established to understand the process of CE, which further confirms that electron transfer is the dominant mechanism of CE. Moreover, it indicates that in addition to oxygen vacancies, there are also many other factors that can influence CE, including but not limited to non-stoichiometric ratios, impurities, and other types of defects. These factors will modify the surface states through changing the potential barrier energy of the bound electrons on the surface and thus impact the amount and even the direction of electron transfer.

A Damage Model to Trabecular Bone and Similar Materials: Residual Resource, Effective Elasticity Modulus, and Effective Stress under Uniaxial Compression

Experimental research of bone strength remains costly and limited for ethical and technical reasons. Therefore, to predict the mechanical state of bone tissue, as well as similar materials, it is desirable to use computer technology and mathematical modeling. Yet, bone tissue as a bio-mechanical object with a hierarchical structure is difficult to analyze for strength and rigidity; therefore, empirical models are often used, the disadvantage of which is their limited application scope. The use of new analytical solutions overcomes the limitations of empirical models and significantly improves the way engineering problems are solved. Aim of the paper: the development of analytical solutions for computer models of the mechanical state of bone and similar materials. Object of research: a model of trabecular bone tissue as a quasi-brittle material under uniaxial compression (or tension). The new ideas of the fracture mechanics, as well as the methods of mathematical modeling and the biomechanics of bone tissues were used in the work. Compression and tension are considered as asymmetric mechanical states of the material. Results: a new nonlinear function that simulates both tension and compression is justified, analytical solutions for determining the effective and apparent elastic modulus are developed, the residual resource function and the damage function are justified, and the dependences of the initial and effective stresses on strain are obtained. Using the energy criterion, it is proven that the effective stress continuously increases both before and after the extremum point on the load-displacement plot. It is noted that the destruction of bone material is more likely at the inflection point of the load-displacement curve. The model adequacy is explained by the use of the energy criterion of material degradation. The results are consistent with the experimental data available in the literature.

Extended Nappi-Witten geometry for the fractional quantum Hall effect

Motivated by the recent progresses in the formulation of geometric theories for the fractional quantum Hall states, we propose a novel non-relativistic geometric model for the Laughlin states based on an extension of the Nappi-Witten geometry. We show that the U(1) gauge sector responsible for the fractional Hall conductance, the gravitational Chern-Simons action and Wen-Zee term associated to the Hall viscosity can be derived from a single Chern-Simons theory with a gauge connection that takes values in the extended Nappi-Witten algebra. We then provide a new derivation of the chiral boson associated to the gapless edge states from the Wess-Zumino-Witten model that is induced by the Chern-Simons theory on the boundary.

Electroforming-free nonvolatile resistive switching of redox-exfoliated MoS2 nanoflakes loaded polystyrene thin film with synaptic functionality

Here, we report robust and highly reproducible nonvolatile resistive switching (RS) devices with artificial synaptic functionalities utilizing redox-exfoliated few-layered 2H-MoS2 nanoflakes. Advantageous polar solvent compatibility of 2D MoS2 from this method were utilized to fabricate thin film devices very easily and cost-effectively using polystyrene as matrix. Prominent RS property of polystyrene thin film devices with varying MoS2 concentrations strongly favors electroforming-free operation. The conduction band position of 2D MoS2 nanosheet in combination with the work functions of chosen electrodes looks alleviating to switch the current from low to high at a suitable positive bias voltage. We further confirmed the mechanism of charge transport through fitting the results with theoretical models, say injection-dominated Schottky emission model for low-conducting states and space-charge-limited current mechanism for the high-conducting state. Interestingly, a relatively high current On/Off ratio 102 was recorded during the pump-probe testing to show resistive random-access memory (ReRAM) application. Finally, artificial synaptic functionalities- the building blocks of neuromorphic computing architectures is also illustrated by considering the robust RS property and ReRAM application.

Does the exchange rate overshoot in an emerging economy?

PurposeThe sticky-price monetary model of exchange rate states the overshooting hypothesis as, exchange rate depreciation beyond its long-term value in response to an increase in money supply owing to the sticky nature of prices. Because of interest and relevance to policy, there is a huge extant literature on it but with mixed findings that suggest the need for further studies to refine the findings. Pakistan’s rupee exchange rate against the US dollar depreciated 128.44% over the period May 2007–December 2018. Considering this substantial decline in rupee's value, this study aims to examine either the rupee short-run value is over-shot of its long-term value.Design/methodology/approachThis study uses a linear ARDL approach that segregates the short-run and long-run effects thus clarifying the premise of exchange rate overshooting. Furthermore, this study also uses nonlinear ARDL as a robustness check incorporating structural breaks.FindingsFindings based on a linear model show evidence of exchange rate undershooting that means a positive money shock causes the exchange rate to appreciate. A nonlinear analysis also provides support to these findings. However, the increase in relative money supply has more such effect than that of a decrease in the relative money supply. Moreover, the authorities’ inclination to stabilize the exchange rate appreciates its short-run value.Originality/valueThis study substantiates the overshooting hypothesis literature by considering the role of asymmetric effects of exchange rate determinants and structural breaks that is a rare attempt in the extant literature.

The representational structure of mental states generalizes across target people and stimulus modalities

Each individual experiences mental states in their own idiosyncratic way, yet perceivers can accurately understand a huge variety of states across unique individuals. How do they accomplish this feat? Do people think about their own anger in the same ways as another person's anger? Is reading about someone's anxiety the same as seeing it? Here, we test the hypothesis that a common conceptual core unites mental state representations across contexts. Across three studies, participants judged the mental states of multiple targets, including a generic other, the self, a socially close other, and a socially distant other. Participants viewed mental state stimuli in multiple modalities, including written scenarios and images. Using representational similarity analysis, we found that brain regions associated with social cognition expressed stable neural representations of mental states across both targets and modalities. Together, these results suggest that people use stable models of mental states across different people and contexts.