Model Of States Research Articles

Barrier heights and strong fermi-level pinning at epitaxially grown ferromagnet/ZnO/metal Schottky Interfaces for opto-spintronics applications

Schottky contacts at the ferromagnet/ZnO interface are good candidates for the realization and control of several semiconductor emerging magnetic phenomena such spin injection and spin-controlled photonics. In this work, we demonstrate the epitaxial growth of single-phase and wurtzite-ZnO thin films on fcc Pt/Co0.30Pt0.70 (111) electrodes by molecular beam epitaxy technique. While the magnetic properties of the Pt/Co0.30Pt0.70 buffer remain unchanged after the ZnO growth, the electric measurements of back-to-back Schottky diodes reveal Schottky barrier heights at the metal/ZnO interfaces in the range of 590–690 meV using Cu, Pt and Co0.30Pt0.70 contacts. A pinning factor S and a charge neutrality level (CNL) ΦCNL of 0.08 and 4.94 eV, respectively, are obtained indicating a strong Fermi-level pining with a CNL level that lies 0.64 eV bellow the conductance band of ZnO semiconductor. These experimental findings indicate that Co0.30Pt0.70/ZnO interface follows the metal-induced gap states model and can open a pathway for the realization of opto-spintronics applications such spin-LEDs.

Corrections

This article corrects the following: Volume 3 Issue 1 Journal of Dynamics, Monitoring and Diagnostics Statistical Models for Condition Monitoring and State of Health Estimation of Lithium-Ion Batteries for Ships Pages: 11-20 First Published online: 29 Feb 2024 DOI: https://doi.org/10.37965/jdmd.2024.500 On page 19 of the PDF, the following correction should be noted. The acknowledgements in the previously published PDF version were incomplete. An updated PDF version of it is provided below. This correction notice has been linked to the online version of the article.

An electrochemical series for materials

The electrochemical series is a useful tool in electrochemistry, but its effectiveness in materials chemistry is limited by the fact that the standard electrochemical series is based on a relatively small set of reactions, many of which are measured in aqueous solutions. To address this problem, we have used machine learning to create an electrochemical series for inorganic materials from tens of thousands of entries in the Inorganic Crystal Structure Database. We demonstrate that this series is generally more consistent with oxidation states in solid-state materials than the series based on aqueous ions. The electrochemical series was constructed by developing and parameterizing a physical, human-interpretable model of oxidation states in materials. We show that this model enables the prediction of oxidation states from composition in a way that is more accurate than a state-of-the-art transformer-based neural network model. We present applications of our approach to structure prediction, materials discovery, and materials electrochemistry, and we discuss possible additional applications and areas for improvement. To facilitate the use of our approach, we introduce a freely available website and API.

Early Events in G-quadruplex Folding Captured by Time-Resolved Small-Angle X-Ray Scattering.

Time-resolved small-angle X-ray experiments (TR-SAXS) are reported here that capture and quantify a previously unknown rapid collapse of the unfolded oligonucleotide as an early step in G4 folding of hybrid 1 and hybrid 2 telomeric G-quadruplex structures. The rapid collapse, initiated by a pH jump, is characterized by an exponential decrease in the radius of gyration from 20.6 to 12.6 Å. The collapse is monophasic and is complete in less than 600 ms. Additional hand-mixing pH-jump kinetic studies show that slower kinetic steps follow the collapse. The folded and unfolded states at equilibrium were further characterized by SAXS studies and other biophysical tools, to show that G4 unfolding was complete at alkaline pH, but not in LiCl solution as is often claimed. The SAXS Ensemble Optimization Method (EOM) analysis reveals models of the unfolded state as a dynamic ensemble of flexible oligonucleotide chains with a variety of transient hairpin structures. These results suggest a G4 folding pathway in which a rapid collapse, analogous to molten globule formation seen in proteins, is followed by a confined conformational search within the collapsed particle to form the native contacts ultimately found in the stable folded form.

Residual strength and critical state of strain softening–hardening considering thermal effect for brittle rocks

Since the post failure of rock has a significant effect on the performance of excavation, the residual strength of rock considering the thermal effect, is important for deep rock engineering, such as sequencing in underground excavation and tunnel support design. From the micromechanical perspective, this paper presents novel models of residual strength and critical state of strain softening–hardening, considering the thermal effect for brittle rocks. The model of the residual strength for brittle rocks was established by considering the thermal effect. Then, the criterion was proposed under for critical state of stress softening and strain hardening by considering the thermal effect. The new models include independent parameters with physical meaning. Finally, the reliability of the proposed model and criterion was verified by comparing theoretical predictions and experimental data. It was found that the proposed models can provide an effective means to predict the residual strength behavior and critical state of strain softening–hardening, considering the thermal effect for brittle rocks.

The Seeking Proxies for Internal States (SPIS) Model of OCD - A Comprehensive Review of Current Findings and Implications for Future Directions.

The Seeking Proxies for Internal States (SPIS) model of obsessive-compulsive disorder (OCD) explains symptoms of OCD as stemming from attenuated access to internal states, which is compensated for by using proxies, which are indices of these states that are more discernible or less ambiguous. Internal states in the SPIS model are subjective states that are not accessible to others, encompassing physiological states, motivations, preferences, memories, and emotions. Compensatory proxies in OCD include fixed rules and rituals as well as seeking and relying on external information. In the present review, we outline the SPIS model and describe its basic tenets. We then use the SPIS conceptualization to explain two pivotal OCD-related phenomena - obsessive doubt and compulsive rituals. Next, we provide a detailed overview of current empirical evidence supporting the SPIS in several domains, including physiological states, emotions, sense of understanding, decision-making, and sense of agency. We conclude by discussing possible neural correlates of the difficulty in accessing internal states, focusing on the anterior insular cortex (AIC) and highlighting potential clinical implications of the model to the treatment of OCD.

A novel method of steady-state modeling for self-excited induction generators in distributed generation system based on transient space-vector model

Abstract The paper proposes a novel mathematic model for steady states represented by the complex-domain transient space vectors of SEIGs in the stationary coordinate system, where the physical systems are extended to be analyzed by applying the previous approach of holistic analysis based on the stability theorem of Lyapunov. The motion analysis of mechanisms gives analytical formulas of operating points at steady states by solving the novel steady-state model analytically. Good agreement between former numerically computed results and analytically computed results by the analytic formulas proves the validity and effectiveness of the proposed novel model, with extensive engineering referenced and applicable value.

Artificial neural network-based models for short term forecasting of solar PV power output and battery state of charge of solar electric vehicle charging station

The main objective of this study is to develop ANN-based predictive models for short-term forecasting of solar PV power output and battery state of charge. The 3Ds energy model that integrates Decarbonization, Digitalization, and Decentralization of the energy system to facilitate the shift towards sustainable energy sources is used for this electric vehicle project. The experimental set up includes solar PV panels, a solar inverter, a battery inverter, and a battery bank. Additionally, smart meters were installed to collect real-time performance data from the solar PV-powered electric vehicle (EV) charging station. The weather and real-time system performance data were used to develop short term forecasting models based on Artificial Neural Networks (ANN) and the Levenberg-Marquardt method, to predict the performance of the system (power output and state of the charge) ahead. The R values for the prediction models of solar photovoltaic (PV) specific power and battery state of charge fall within the range of 0.9957–0.9969 and 0.9990 to 0.9996, respectively. Furthermore, the mean squared errors (MSEs) for the artificial neural network (ANN) models pertaining to solar photovoltaic (PV) power output and battery state of charge exhibit a variety of values. Specifically, the MSEs for solar PV power output range from 1.242 x 10^-4 to 1.579 x 10^-4, while the MSEs for battery status of charge range from 0.1889 to 0.3402. Artificial neural network (ANN) models possess considerable promise for practical implementations as they simplify intricate connections among inputs, parameters, and outputs in real-world scenarios. The level of accuracy and short-term predictive models of the solar PV powered EV charging station are very important for achieving a balance between the supply of solar photovoltaic (PV) system and the demand for electric vehicles (EVs). Predictive models will help build complex control mechanisms for controlling and optimizing solar PV-powered charging stations, supervising their operation and maintenance, and simplifying renewable energy pre-purchase. Future works will include the development of an energy management system to improve the efficiency of the solar stations charging the EVs, the establishment of blockchain networks for both the solar PV system and battery bank, and the integration of cybersecurity protocols for the charging station.

A Holistic Approach to Nursing Students’ Changing Life and Anxiety in the Pandemic: A Descriptive Cross Sectional Study Utilizing Positive Psychotherapy

The life balance model of positive psychotherapy states that human lives have four dimensions: body, achievement, relationships, and spirituality. When these dimensions are in balance, people are healthy and productive. This study aimed to determine the effects of the COVID-19 pandemic on nursing students’ anxiety levels and life balance. This cross-sectional and descriptive study was conducted with 584 nursing students studying at 3 different universities in Turkey. The participants experienced significant changes in the life balance model’s dimensions of achievement, body, relationships, and spirituality before and during the pandemic. The participants’ anxiety increased with changes in these dimensions. Based on these results, it would be beneficial to support students in order to meet the needs in the life dimensions that students neglect. In addition, it is thought that the life balance model, which is being used for the first time in nursing, can be developed as a tool in the nursing practice.

Russia in the system of functioning models of the modern world market for arms and military equipment

In the context of modern geopolitical conflicts, which have led to complications in the international trade and investment cooperation between countries, there are serious changes in the positions of states in the global export of arms and military equipment (hereinafter referred to as AME). Structural transformations in the international exchange of the AME are also conditioned by the clash of economic interests of individual countries due to globalisation of recent decades as well as by the use of various models of production and export of the AME at the national level. As shown in our article, states of the world are seriously differentiated in their own production of the AME according to the degree of their dependence on imports and foreign suppliers of components and technologies. The fact that countries can be advanced participants in the technological chain or be niche suppliers determines new directions for their international specialisation and, largely, the rules and nature of competition in the modern AME market. As part of the presented analysis of the national specialisation models of states, the competitive advantages and weaknesses of Russia as one of the leading arms exporters in the world are shown. At the same time, the foreign policy and economic risks of strengthening its position in the global AME trade have been assessed. Based on the results of the study, directions for reinforcing the potential of the Russian military-industrial complex in the world AME market have been formulated.

Beyond the Preamble: Legislating the right to self-determination in a NSW Human Rights Act

This article examines the inclusion of the right to self-determination in existing models of state and territory human rights legislation and proposes its inclusion in a future human rights act in New South Wales (NSW), to advance the rights of First Peoples in the criminal justice system. I explore how this would provide a mechanism for state restraint and a legal framework for prioritising self-determined First Nations critique, research and service delivery in carceral systems. The role of courts in holding the state to account and developing legal pluralism in rights jurisprudence is also discussed.

Multifunctional cyanoaryl porphyrazine pigments with push-pull structure of macrocycle framing: Photophysics and possible applications

We report the experimental study of fluorescence properties of three porphyrazine derivatives, distinct in the number of fused aromatic rings in aryl groups contained in the macrocycle frame and/or presence of Pd in the macrocycle, in solutions with biological molecules and in methanol-glycerol mixtures. Spectral and lifetime fluorescence analysis has revealed that all three pigments demonstrated two fluorescence transition bands from the first S1 and the second S2 electronic excited states to the ground state S0, and thus followed the anti-Kasha’s rule. Strong dependence of the quantum yield and lifetimes in the S1 → S0 fluorescence band on solution viscosity was observed. A significant increase of the fluorescence decay times and fluorescence intensity with albumin concentration and with presence of other biological molecules in solution was observed as well. A model of the low-laying energy states of porphyrazine derivatives has been developed for elucidation of the fluorescence properties observed, that took into account several radiative and non-radiative relaxation channels in molecular excited states. In particular, the model suggests that the first electronic excited state consists of planar and bent conformations separated by a potential energy barrier and shows a typical molecular-rotor behavior as a function of solution viscosity. Potential applications of the porphyrazine pigments as viscosity sensors and fluorescence probes were considered.

Signaling by a bacterial phytochrome histidine kinase involves a conformational cascade reorganizing the dimeric photoreceptor

Phytochromes (Phys) are a divergent cohort of bili-proteins that detect light through reversible interconversion between dark-adapted Pr and photoactivated Pfr states. While our understandings of downstream events are emerging, it remains unclear how Phys translate light into an interpretable conformational signal. Here, we present models of both states for a dimeric Phy with histidine kinase (HK) activity from the proteobacterium Pseudomonas syringae, which were built from high-resolution cryo-EM maps (2.8–3.4-Å) of the photosensory module (PSM) and its following signaling (S) helix together with lower resolution maps for the downstream output region augmented by RoseTTAFold and AlphaFold structural predictions. The head-to-head models reveal the PSM and its photointerconversion mechanism with strong clarity, while the HK region is interpretable but relatively mobile. Pr/Pfr comparisons show that bilin phototransformation alters PSM architecture culminating in a scissoring motion of the paired S-helices linking the PSMs to the HK bidomains that ends in reorientation of the paired catalytic ATPase modules relative to the phosphoacceptor histidines. This action apparently primes autophosphorylation enroute to phosphotransfer to the cognate DNA-binding response regulator AlgB which drives quorum-sensing behavior through transient association with the photoreceptor. Collectively, these models illustrate how light absorption conformationally translates into accelerated signaling by Phy-type kinases.

Catalytic Enantioselective Sulfoxidation of Functionalized Thioethers Mediated by Aspartic Acid-Containing Peptides.

A peptide-catalyzed enantioselective oxidation of sulfides to yield pharmaceutically relevant chiral sulfoxides is reported. Experimental evidence suggesting that a hydrogen bond-donating moiety must be present in the substrate to achieve high levels of enantioinduction is supported by computational modeling of transition states. These models also indicate that dual points of contact between the peptidic catalyst and substrate are likely responsible for the formation of one desired sulfoxide in 94:6 er.

Quantum-like states on complex synchronized networks

Recent work has exposed the idea that interesting quantum-like (QL) probability laws, including interference effects, can be manifest in classical systems. Here, we propose a model for QL states and QL bits. We suggest a way that huge, complex systems can host robust states that can process information in a QL fashion. Axioms that such states should satisfy are proposed. Specifically, it is shown that building blocks suited for QL states are networks, possibly very complex, that we defined based on k -regular random graphs. These networks can dynamically encode a lot of information that is distilled into the emergent states we can use for QL processing. Although the emergent states are classical, they have properties analogous to quantum states. Concrete examples of how QL functions are possible are given. The possibility of a ‘QL advantage’ for computing-type operations and the potential relevance for new kinds of function in the brain are discussed and left as open questions.

Modeling of the electronic excited states in high-temperature flows

This article introduces a novel model for describing the electronic excited states in the direct simulation Monte Carlo (DSMC) technique. The model involves the coupling the vibrational and electronic modes of molecular species, enabling each electronic excited state to excite its unique vibrational quantum levels. Numerical techniques are developed for equilibrium and post-collision sampling, as well as for measuring the internal temperature. The DSMC results demonstrate excellent agreement with theoretical predictions, providing verification of the successful implementation in a DSMC solver. For important thermophysical properties of molecular oxygen, such as the specific heat capacity, it is shown that the new model provides a better prediction than a compilation of past studies in comparison to the standard uncoupled approach in DSMC. The model is then applied to simulate a canonical nonreactive oxygen hypersonic flow past a cylindrical body. The population distribution of electronic excited states exhibit significant deviation from the standard approach typically used in the coupling between DSMC and radiation transport solvers.

Outcome prediction in psychological therapy with continuous time dynamic modeling of affective states and emotion regulation.

To date, many prediction studies in psychotherapy research have used cross-sectional data to predict treatment outcome. The present study used intensive longitudinal assessments and continuous time dynamic modeling (CTDM) to investigate the temporal dynamics of affective states and emotion regulation in the early phase of therapy and their ability to predict treatment outcome. Ninety-one patients undergoing psychological treatment at a university outpatient clinic took part in a 2-week ecological momentary assessment (EMA) period. Participants answered self-report measures on positive affect (PA), negative affect, and emotion regulation (ER) four times a day. Hierarchical Bayesian CTDM was conducted to identify temporal effects within (autoregressive) and between (cross-regressive) PA, negative affect, and ER. The resulting CTDM parameters, simple EMA parameters (e.g., mean), and cross-sectional predictors were entered into a LASSO model to be examined as predictors of treatment outcome at Session 15. Two significant predictors were identified: initial impairment and the continuous time cross-effect of PA on ER. The final model explained 40% of variance in treatment outcome, with the cross-effect (PA-ER) accounting for 4% of variance beyond initial impairment. The results demonstrate that temporal patterns of affective EMA data are valuable for the mapping of individual differences and the prediction of treatment outcome. This information can be used to provide therapists with feedback to personalize treatments. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Viscosity of Hydrogen and Methane Blends: Experimental and Modelling Investigations

Understanding of thermophysical and transport properties of H2-NG blends are needed for the gradual introduction of hydrogen into the national gas grid. A capillary tube viscometer was used to measure the viscosity of hydrogen + methane blends (with hydrogen mole fraction = 0, 0.1000, 0.1997, 0.5019, and 1) at temperatures from 213 to 324 K and pressures up to 31 MPa. A total 147 experimental viscosity measurements were made for the three H2 + CH4 blends and compared against the predictions of five different viscosity models: a one-reference corresponding states (Pedersen) model, a two-reference corresponding states (CS2) model, an extended corresponding states (ECS) model, a corresponding states model derived from molecular dynamic simulations of Lennard Jones (LJ) fluids, and a residual entropy scaling (SRES) method. All the model predictions showed a relatively low deviation compared to the measured viscosities. The density required for viscosity model predictions were computed using Multi-Fluid Helmholtz Energy Approximation (MFHEA) equations of state (EoS). To check the experimental procedure and applicability of the viscometer equipment, viscosity validation measurements were carried out for propane, hydrogen, and methane. The measured viscosities of the pure components were in good agreement with the respective viscosity models with AARD of 0.24%, 0.25%, and 0.58% for propane, hydrogen, and methane, respectively.Graphical

Degree of primary care integration predicts job satisfaction and emotional exhaustion among rural medical and behavioral healthcare providers.

Minimal research on integrated primary care (IPC) or integrated behavioral health (IBH) has examined clinics in rural communities. The relationships between provider burnout, job satisfaction, and IBH/IPC practices remain understudied, particularly in rural settings. We employed an online survey of 147 medical and behavioral health care providers in primary care settings throughout Montana. Respondents self-identified as predominantly White/European American (89.4%) and female (76.7%). We tested whether degree of adherence to IBH/IPC practices concurrently predicted providers' reports of emotional exhaustion (EE), a dimension of burnout, and job satisfaction. Data were collected during the COVID-19 pandemic, in 2020. In multiple linear regression analyses, providers' reports of IBH/IPC practices significantly predicted EE (B = -0.036, p < .01) and job satisfaction (B = 0.123, p < .05), suggesting that higher levels of integration were linked to less EE and greater job satisfaction. Our findings contribute to the evidence base regarding the potential usefulness of IBH/IPC models. Specifically, because existing research links provider burnout and low job satisfaction with provider retention difficulties and diminished health, poor patient satisfaction and outcomes, and cost inefficiencies, our findings have potential to inform policy-level discussions regarding the use of IBH/IPC models in rural states like Montana. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Oregon’s K-12 transformative social and emotional learning framework and standard development

In 2021, Oregon's legislature passed House Bill 2166, which mandated that the Oregon Department of Education (ODE), in collaboration with the Early Learning Division and the Teacher Standards and Practices Commission (TSPC), develop K-12 Social and Emotional Learning (SEL) standards for students across the state. This manuscript highlights how Oregon used the Transformative SEL framework to guide their multi-phase process, which involved extensive input and collaboration from a diverse group of educators, policy makers, parents and students. This collaborative approach ensured that the standards reflected a wide range of perspectives and addressed the unique needs of various student populations. The manuscript discusses the challenges encountered in the process, such as resistance to change, resource allocation, and professional development needs. This work contributes to the growing body of research on SEL by providing a model for states and districts to develop and implement SEL standards that align with legislative mandates and educational equity goals.