State Model Research Articles

Log-periodic oscillations as real-time signatures of hierarchical dynamics in proteins.

The time-dependent relaxation of a dynamical system may exhibit a power-law behavior that is superimposed by log-periodic oscillations. D. Sornette [Phys. Rep. 297, 239 (1998)] showed that this behavior can be explained by a discrete scale invariance of the system, which is associated with discrete and equidistant timescales on a logarithmic scale. Examples include such diverse fields as financial crashes, random diffusion, and quantum topological materials. Recent time-resolved experiments and molecular dynamics simulations suggest that discrete scale invariance may also apply to hierarchical dynamics in proteins, where several fast local conformational changes are a prerequisite for a slow global transition to occur. Employing entropy-based timescale analysis and Markov state modeling to a simple one-dimensional hierarchical model and biomolecular simulation data, it is found that hierarchical systems quite generally give rise to logarithmically spaced discrete timescales. By introducing a one-dimensional reaction coordinate that collectively accounts for the hierarchically coupled degrees of freedom, the free energy landscape exhibits a characteristic staircase shape with two metastable end states, which causes the log-periodic time evolution of the system. The period of the log-oscillations reflects the effective roughness of the energy landscape and can, in simple cases, be interpreted in terms of the barriers of the staircase landscape.

Toward physics-based precision medicine: Exploiting protein dynamics to design new therapeutics and interpret variants.

The goal of precision medicine is to utilize our knowledge of the molecular causes of disease to better diagnose and treat patients. However, there is a substantial mismatch between the small number of food and drug administration (FDA)-approved drugs and annotated coding variants compared to the needs of precision medicine. This review introduces the concept of physics-based precision medicine, a scalable framework that promises to improve our understanding of sequence-function relationships and accelerate drug discovery. We show that accounting for the ensemble of structures a protein adopts in solution with computer simulations overcomes many of the limitations imposed by assuming a single protein structure. We highlight studies of protein dynamics and recent methods for the analysis of structural ensembles. These studies demonstrate that differences in conformational distributions predict functional differences within protein families and between variants. Thanks to new computational tools that are providing unprecedented access to protein structural ensembles, this insight may enable accurate predictions of variant pathogenicity for entire libraries of variants. We further show that explicitly accounting for protein ensembles, with methods like alchemical free energy calculations or docking to Markov state models, can uncover novel lead compounds. To conclude, we demonstrate that cryptic pockets, or cavities absent in experimental structures, provide an avenue to target proteins that are currently considered undruggable. Taken together, our review provides a roadmap for the field of protein science to accelerate precision medicine.

CO2 solubility and absorption rate analysis of a mixed poly(oxymethylene) dimethyl ethers (PODE3–5) solution

Efficient and economical carbon capture is critical to counteract the diverse problems of global warming. In this work, the solubility of carbon dioxide (CO2) in different poly(oxymethylene) dimethyl ethers (PODE) solutions was experimentally investigated at temperatures from 278.15 to 308.15 K and pressures up to 1.2 MPa. The Henry's law constants of CO2 in the PODE system were determined and compared with other types of physical absorbents, which revealed PODE3–5 has great CO2 absorption ability in terms of molar and mass fraction. Meanwhile, the initial absorption rate of the physical absorption process of PODE3–5 was calculated and compared with commercially available absorbents using a gas absorption rate relationship. It was shown that the absorption rate of PODE3–5 in the CO2 absorption process is faster than that of other commercial absorbents. The CO2 solubility data of PODE3–5 were also correlated using the Jou-Mather model and the perturbed-chain statistical association fluid theory (PC-SAFT) equation of state model, and the recycling performance of the PODE3–5 absorbent was tested.

On the solutions of the Schrödinger equation with 2nd Pöschl–Teller potentials

We delve into the intricacies of the hyperbolic Pöschl–Teller potential, often referred to as the 2nd Pöschl–Teller potential (PTP), and explore its implications on the Schrödinger equation for arbitrary l state case. This exploration encompasses a comprehensive review of various methodologies employed in studying the exact solutions of the S wave scenario, along with approximations concerning the centrifugal term within the radial equation for the arbitrary l setup. Our investigation yields exact solutions for the quasi-exact arbitrary l state model. We achieve this by employing a novel approach rooted in Fuchsian differential equations, thereby presenting a potential solution for the S wave case as well. This innovative method holds promise, particularly in seeking solutions for the Schrödinger equation involving non-trivial potentials where exact solutions remain elusive.

A radius valley between migrated steam worlds and evaporated rocky cores

AbstractThe radius valley (or gap) in the observed distribution of exoplanet radii, which separates smaller super-Earths from larger sub-Neptunes, is a key feature that theoretical models must explain. Conventionally, it is interpreted as the result of the loss of primordial hydrogen and helium (H/He) envelopes atop rocky cores. However, planet formation models predict that water-rich planets migrate from cold regions outside the snowline towards the star. Assuming water to be in the form of solid ice in their interior, many of these planets would be located in the radius gap contradicting observations. Here we use an advanced coupled formation and evolution model that describes the planets’ growth and evolution starting from solid, moon-sized bodies in the protoplanetary disk to mature Gyr-old planetary systems. Employing new equations of state and interior structure models to treat water as vapour mixed with H/He, we naturally reproduce the valley at the observed location. The model results demonstrate that the observed radius valley can be interpreted as the separation of less massive, rocky super-Earths formed in situ from more massive, ex situ, water-rich sub-Neptunes. Furthermore, the occurrence drop at larger radii, the so-called radius cliff, is matched by planets with water-dominated envelopes. Our statistical approach shows that the synthetic distribution of radii quantitatively agrees with observations for close-in planets, but only if low-mass planets initially containing H/He lose their atmosphere due to photoevaporation, which populates the super-Earth peak with evaporated rocky cores. Therefore, we provide a hybrid theoretical explanation of the radius gap and cliff caused by both planet formation (orbital migration) as well as evolution (atmospheric escape).

A Node Selection Strategy in Space-Air-Ground Information Networks: A Double Deep Q-Network Based on the Federated Learning Training Method

The Space-Air-Ground Information Network (SAGIN) provides extensive coverage, enabling global connectivity across a diverse array of sensors, devices, and objects. These devices generate large amounts of data that require advanced analytics and decision making using artificial intelligence techniques. However, traditional deep learning approaches encounter drawbacks, primarily, the requirement to transmit substantial volumes of raw data to central servers, which raises concerns about user privacy breaches during transmission. Federated learning (FL) has emerged as a viable solution to these challenges, addressing both data volume and privacy issues effectively. Nonetheless, the deployment of FL faces its own set of obstacles, notably the excessive delay and energy consumption caused by the vast number of devices and fluctuating channel conditions. In this paper, by considering the heterogeneity of devices and the instability of the network state, the delay and energy consumption models of each round of federated training are established. Subsequently, we introduce a strategic node selection approach aimed at minimizing training costs. Building upon this, we propose an innovative, empirically driven Double Deep Q Network (DDQN)-based algorithm called low-cost node selection in federated learning (LCNSFL). The LCNSFL algorithm can assist edge servers in selecting the optimal set of devices to participate in federated training before the start of each round, based on the collected system state information. This paper culminates with a simulation-based comparison, showcasing the superior performance of LCNSFL against existing algorithms, thus underscoring its efficacy in practical applications.

Evaluation of the learning state of online video courses based on functional near infrared spectroscopy.

Studying brain activity during online learning will help to improve research on brain function based on real online learning situations, and will also promote the scientific evaluation of online education. Existing research focuses on enhancing learning effects and evaluating the learning process associated with online learning from an attentional perspective. We aimed to comparatively analyze the differences in prefrontal cortex (PFC) activity during resting, studying, and question-answering states in online learning and to establish a classification model of the learning state that would be useful for the evaluation of online learning. Nineteen university students performed experiments using functional near-infrared spectroscopy (fNIRS) to monitor the prefrontal lobes. The resting time at the start of the experiment was the resting state, watching 13 videos was the learning state, and answering questions after the video was the answering state. Differences in student activity between these three states were analyzed using a general linear model, 1s fNIRS data clips, and features, including averages from the three states, were classified using machine learning classification models such as support vector machines and k-nearest neighbor. The results show that the resting state is more active than learning in the dorsolateral prefrontal cortex, while answering questions is the most active of the three states in the entire PFC, and k-nearest neighbor achieves 98.5% classification accuracy for 1s fNIRS data. The results clarify the differences in PFC activity between resting, learning, and question-answering states in online learning scenarios and support the feasibility of developing an online learning assessment system using fNIRS and machine learning techniques.

A novel hybrid deep learning model for accurate state of charge estimation of Li-Ion batteries for electric vehicles under high and low temperature

This paper presents a novel architecture, termed Fusion-Fission Optimisation (FuFi) based Convolutional Neural Network with Bi-Long Short Term Memory Network (FuFi-CNN-Bi-LSTM), to enhance state of charge (SoC) estimation performance. The proposed FuFi-CNN-Bi-LSTM model leverages the power of both Convolutional Neural Networks (CNN) and Bi-Long Short Term Memory Networks (Bi-LSTM) while utilizing FuFi optimization to effectively tune the hyperparameters of the network. This optimization technique facilitates efficient SoC estimation by finding the optimal configuration of the model. A comparative analysis is conducted against FuFi Algorithm-based models, including FuFi-CNN-LSTM, FuFi-Bi-LSTM, FuFi-LSTM, and FuFi-CNN. The comparison involves assessing performance on SoC estimation tasks and identifying the strengths and limitations of models. Furthermore, the proposed FuFi-CNN-Bi-LSTM model undergoes rigorous testing on various drive cycle tests, including HPPC, HWFET, UDDS, and US06, at different temperatures ranging from -20 to 25 degrees Celsius. The model’s robustness and reliability are assessed under different real-world operating conditions using well-established evaluation indexes, including Relative Error (RE),Mean Absolute Error (MAE), R Square (R2), and Granger Causality Test. The results demonstrate that the proposed FuFi-CNN-Bi-LSTM model achieves efficient SoC estimation performance across a wide range of temperatures at higher and lower ranges. This finding signifies the model’s efficacy in accurately estimating SoC in various operating conditions.

Army and Progress? The Russian and Greek Reactions to the 1903 Coup in Serbia and to the 1908 Young Turk Revolution

In the early twentieth century, Greece and Russia represented two strikingly different state and social models for the Christian Orthodox world – its first ethnocentric nation-state vs. its last confessional dynastic empire. Yet they demonstrated similar reactions to the military coups in Serbia and the Ottoman Empire. Except for rightwing monarchists, most commentators, diplomats, and officers shared a belief in the potential of army-led modernization to promote financial efficiency and legitimacy based on constitutional parliamentary institutions. As such, the article contributes to the studies of military political involvement in the context of nationalist and socialist challenges to established monarchical regimes. The article also adds to the literature emphasizing Ottoman agency and influence abroad. While there are some valuable works on Russian and Greek responses to the Young Turk Revolution, there have not been any attempts to compare them in a single book or paper based on a variety of archival and print sources. The repercussions of the 1903 Serbian coup are researched even less (not at all on the Greek side).

Asymmetric Transfer Hydrogenation of Cyclobutenediones.

Four-membered carbocycles are fundamental substructures in bioactive molecules and approved drugs and serve as irreplaceable building blocks in organic synthesis. However, developing efficient protocols furnishing diversified four-membered ring compounds in a highly regio-, diastereo-, and enantioselective fashion remains challenging but very desirable. Here, we report the unprecedented asymmetric transfer hydrogenation of cyclobutenediones. The reaction can selectively afford three types of four-membered products in high yields with high stereoselectivities, and the highly functionalized products enable a series of further transformations to form more diversified four-membered compounds. Asymmetric synthesis of di-, tri-, and tetrasubstituted bioactive molecules has also been achieved. Systematic mechanistic studies and theoretical calculations have revealed the origin of the regioselectivity, the key hydrogenation transition state models, and the sequence of the double and triple hydrogenation processes. The work provides a new choice for the catalytic asymmetric synthesis of cyclobutanes and related structures and demonstrates the robustness of asymmetric transfer hydrogenation in the accurate selectivity control of highly functionalized substrates.

Improving the Efficiency of the Drive of the Test Bench of Rotary Hydraulic Machines

Volumetric hydraulic drive systems are quite widespread in many industrial sectors. To determine the degree of reliability of hydraulic machines, it is necessary to conduct resource tests. The main requirement for such tests is the compliance of the load level with the operating mode of the hydraulic machine. Analysis of existing methods of creating such a load showed a significant drawback of bench tests—the lack of useful work. Therefore, a number of authors suggest the use of stands with a regenerative drive system. One peculiarity of the work of such stands is the possibility of returning part of the spent energy back to the test system. However, such systems are insufficiently studied and have significant drawbacks. The purpose of this work is to increase the efficiency of the regenerative drive system of the test bench of volumetric hydraulic machines of rotational action by improving the theory and methodology of its calculation and design. This article describes the principle of operation of the circuit of the regenerative drive of the test bench of rotary hydraulic machines. A model of the elastic-dissipative state of the sections of the elements of the hydro-mechanical drive system of the stand is also proposed, which allows for the calculation of the structural and energy parameters of the regenerative hydro-mechanical system. The main structural and functional parameters affecting the operational performance of the system as a whole are also identified. A “test efficiency coefficient” is proposed, which allows for evaluation of the energy efficiency of the test process.

Unraveling the Interplay of Extracellular Domain Conformational Changes and Parathyroid Hormone Type 1 Receptor Activation in Class B1 G Protein-Coupled Receptors: Integrating Enhanced Sampling Molecular Dynamics Simulations and Markov State Models.

Parathyroid hormone (PTH) type 1 receptor (PTH1R), as a typical class B1 G protein-coupled receptor (GPCR), is responsible for regulating bone turnover and maintaining calcium homeostasis, and its dysregulation has been implicated in the development of several diseases. The extracellular domain (ECD) of PTH1R is crucial for the recognition and binding of ligands, and the receptor may exhibit an autoinhibited state with the closure of the ECD in the absence of ligands. However, the correlation between ECD conformations and PTH1R activation remains unclear. Thus, this study combines enhanced sampling molecular dynamics (MD) simulations and Markov state models (MSMs) to reveal the possible relevance between the ECD conformations and the activation of PTH1R. First, 22 intermediate structures are generated from the autoinhibited state to the active state and conducted for 10 independent 200 ns simulations each. Then, the MSM is constructed based on the cumulative 44 μs simulations with six identified microstates. Finally, the potential interplay between ECD conformational changes and PTH1R activation as well as cryptic allosteric pockets in the intermediate states during receptor activation is revealed. Overall, our findings reveal that the activation of PTH1R has a specific correlation with ECD conformational changes and provide essential insights for GPCR biology and developing novel allosteric modulators targeting cryptic sites.

Free energy profile of the substrate-induced occlusion of the human serotonin transporter.

The serotonin transporter (SERT) is a member of the Solute Carrier 6 (SLC6) family and is responsible for maintaining the appropriate level of serotonin in the brain. Dysfunction of SERT has been linked to several neuropsychiatric disorders, including depression, anxiety and obsessive-compulsive disorder. Therefore, an in-depth understanding of the mechanism on an atomistic level, coupled with a quantification of transporter dynamics and the associated free energies is required. Here, we constructed Markov state models (MSMs) from extensive unbiased molecular dynamics simulations to quantify the free energy profile of serotonin (5HT) triggered SERT occlusion and explored the driving forces of the mechanism of occlusion. Our results reveal that SERT occludes via multiple intermediate conformations and show that the motion of occlusion is energetically downhill for the 5HT-bound transporter. Force distribution analyses show that the interactions of 5HT with the bundle domain are crucial. During occlusion, attractive forces steadily increase and pull on the bundle domain, which leads to SERT occlusion. Some interactions become repulsive upon full occlusion, suggesting that SERT creates pressure on 5HT to promote its movement towards the cytosol.

The experience of the camp Tiago Campin dos Santos in Rondônia in the light of critical criminology

The present work intends to briefly tell the history of repression and resistance of the Tiago Campin dos Santos Camp, located in the rural area of ​​Porto Velho/RO. The Camp, organized by the LCP (Liga dos Camponeses Pobres de Rondônia e Amazônia Occidental) has more than 700 families, who occupy the area, which in turn is public land illegally occupied by the biggest land grabber in the region, known as ''Old Rooster''. After systematically suffering several attacks from the State police forces, in fulfillment of illegal Repossessions, violations of rights were reported by local peasants, committed by police with gunslinger hired by the land grabber, which culminated in physical violence, psychological violence, destruction property, humiliations, evictions and murders. Since its formation, in 2020, 11 murders have already been recorded as a result of these reported attacks. Secondly, it is intended to use the example of the Camp to reflect on the system of control and penal selectivity that place an impoverished peasant mass under the ‘’sight’’ of the State, who struggles for democratic access to land. The repressive and classist character of the State and consequently of the Judiciary leads it to face a social problem, which is the poor distribution of land in Brazil, as a public security problem, individualizing the agents of this conflict, criminalizing them, intentionally suppressing the dimension social conflict. In the essence of the Maximum Penal State model, the management of poverty through the penal control system, especially through the selective and neutralizing use of prison, makes it unnecessary to discuss structural problems, such as the social ills generated by the capitalist system on the use of the land, heightened in the latifundist production model. The agrarian question starts to be colonized by the performance of penal control over “invaders” and, with very little frequency, over landowners, land grabbers, and gunslinger.

Expansion Injection Molding Process Using Clamping Force for Melt Compression.

Melt expansion followed by compression has been utilized for high-speed filling. In general, this technology was developed for a machine level. Recently, mold-level technology has been tried. In this study, an expansion injection molding process was examined, which included compressing a polymer melt through cylinder action facilitated by the movement of the platen, followed by the expansion of the polymer melt into a mold cavity. A mold system including temperature control and valve actions, similar to hot runner systems, was designed and built. The test results show good filling when the injection pressure was high. Simulations were also carried out, highlighting consistent pressure and filling trends, while revealing limitations tied to the characteristics of the state model. This research indicates promise for expansion injection molding through platen compression but emphasizes the need for the seamless integration of valve action with the injection molding machine for large-scale production.

Remediation of neonicotinoid-contaminated soils using peanut shell biochar and composted chicken manure: Transformation mechanisms of geochemical fractions

Soil remediation techniques are promising approaches to relieve the adverse environmental impacts in soils caused by neonicotinoids application. This study systematically investigated the remediation mechanisms for peanut shell biochar (PSB) and composted chicken manure (CCM) on neonicotinoid-contaminated soils from the perspective of transformation of geochemical fractions by combining a 3-step sequential extraction procedure and non-steady state model. The neonicotinoid geochemical fractions were divided into labile, moderate-adsorbed, stable-adsorbed, bound, and degradable fractions. The PSB and CCM addition stimulated the neonicotinoid transformation in soils from labile fraction to moderate-adsorbed and stable-adsorbed fractions. Compared with unamended soils, the labile fractions decreased from 47.6% ± 11.8% of the initial concentrations to 12.1 ± 9.3% in PSB-amended soils, and 7.1 ± 4.9% in PSB and CCM-amended soils, while the proportions of moderate-adsorbed and stable-adsorbed fractions correspondingly increased by 1.8–2.4 times and 2.3–4.8 times, respectively. A small proportion (<4.8%) in bound fractions suggested there were rather limited bound-residues after 48 days incubation. The PSB stimulated the -NO2-containing neonicotinoid-degraders, which promoted the degradable fractions of corresponding neonicotinoids by 8.2 ± 6.3%. Degradable fraction of neonicotinoids was the dominant fate in soils, which accounted for 58.3 ± 16.7%. The findings made beneficial theoretical supplements and provided valuable empirical evidence for the remediation of neonicotinoid-contaminated soils.

On the geometry of two state models for the colored Jones polynomial

Using the flow property of the [Formula: see text]-matrix defining the colored Jones polynomial, we establish a natural bijection between the set of states on the part arc-graph of a link projection and the set of states on a corresponding bichromatic digraph, called arc-graph, as defined by Garoufalidis and Loebl [A non-commutative formula for the colored Jones function, Math. Ann. 336 (2006) 867–900]. We use this to give a new and essentially elementary proof for the knot state-sum formula in [S. Garoufalidis and M. Loebl, A non-commutative formula for the colored Jones function, Math. Ann. 336 (2006) 867–900]. We will show that the state-sum contributions of states on the part arc-graph defined by the universal [Formula: see text]-matrix of [Formula: see text] correspond, under our bijection of sets of states, to the contributions in [S. Garoufalidis and M. Loebl, A non-commutative formula for the colored Jones function, Math. Ann. 336 (2006) 867–900]. This will show that the two state models are in fact not essentially distinct. Our approach will also extend the formula of Garoufalidis and Loebl to links. This requires some additional nontrivial observations concerning the geometry of states on the part arc-graphs. We will discuss in detail the computation of the arc-graph state-sum, in particular for [Formula: see text]-braid closures.

Beam Tracking Based on a New State Model for mmWave V2I Communication on 3D Roads

&lt;p&gt;The expansion of 5G and Internet of Things has laid a good foundation for the in-depth research of Internet of vehicles. Low frequency resources are scarce, and Internet of vehicles communication requires extremely high communication rate. Millimeter wave can meet the above two requirements, but its characteristics and the complicated communication conditions of Internet of vehicles make it difficult to combine the two. Overcoming these problems and making beam tracking accurate and steady is a major challenge at present. In this paper, a new extended Kalman filter tracking algorithm is proposed for mmWave V2I scenarios. On the basis of the original algorithm, a threshold prediction update mechanism is added. A new scheme is adopted, which takes position and velocity as tracking variables, and the tracking model is derived for the first time in MIMO 3D scenarios based on this scheme. The model considers the three-dimensional road conditions, including the vehicle deflection motion and the millimeter wave link blocked by large vehicles, which is more suitable for practical application scenarios. The simulation results reveal that the position and velocity tracking scheme is superior to the angle and gain tracking scheme, and the tracking error of the proposed algorithm is lower than that of the algorithms using similar state models. Based on the three-dimensional scene, it considers more realistic situations, and is more consistent with the kinematic characteristics of the vehicle and has more practical significance.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Preliminary validation results: improving AHI scoring accuracy using an AI model for Sleep state and arousal classification from Home Sleep Apnea Testing

Preliminary validation results: improving AHI scoring accuracy using an AI model for Sleep state and arousal classification from Home Sleep Apnea Testing

WITHDRAWN: Comparative Analysis of Asphaltene Deposition Methods : Stability indices, Stability plots, and Equation of state

Asphaltene deposition is one of the major problems that hinder hydrocarbon production. It can occur anywhere between the reservoir and the surface. Therefore, it is imperative that there be a procedure for minimizing the deposition of asphaltene in the production flow lines. There are several screening criteria that can be considered to determine the asphaltene deposition. This research will conduct a comprehensive study on different methodologies to determine the stability of asphaltene: the first category is the stability criteria using indices such as: the colloidal instability index (CII), the colloidal stability index (CSI), the stability index (SI), and the asphaltene stability predicting model (ANJIS). These four methods are used to predict the stability of asphaltene using SARA analysis. The fifth one is called modified CII which uses the compositions analysis of reservoir fluids, instead of SARA analysis, to determine the stability of asphaltene. The second method uses SARA Analysis to predict the stability via plots such as: Stankiewics plot (SP), De Boer plot, Sepulveda stability criterion (SCP). The third method is using compositional analysis of reservoir fluids and the equation of state model to predict the asphaltene onset pressure (AOP). In the last method Soave Redlich Kwong (SRK) equation of state model was used to predict asphaltene precipitations.In this work, a dataset of 166 was created which includes reservoir information, depth, compositional analysis, and SARA analysis. These data are used to study the potential of asphaltene deposition at the reservoir level. It was found that the stability criteria using indices and plots shows discrepancy in the results. The only two methods that show all the datasets are stable are the modified CII and the EOS model. As far as predicting asphaltene stability is concerned, the EOS method, based on compositional analysis and the thermodynamic model, appears to be the most reliable and trustworthy method. The other methods presented are observational rather than thermodynamic. Using these criteria is intended as a quick and fast estimate of the stability potential of asphaltene, not for planning or management of asphaltene deposition issues.