Exhaustive Model Research Articles

Asymmetric fluctuation of overlapping dinucleosome studied by cryo-electron microscopy and small-angle X-ray scattering

Abstract Nucleosome remodelers modify the local structure of chromatin to release the region from nucleosome-mediated transcriptional suppression. Overlapping dinucleosomes (OLDNs) are nucleoprotein complexes formed around transcription start sites as a result of remodeling, and they consist of two nucleosome moieties: a histone octamer wrapped by DNA (octasome) and a histone hexamer wrapped by DNA (hexasome). While OLDN formation alters chromatin accessibility to proteins, the structural mechanism behind this process is poorly understood. Thus, this study investigated the characteristics of structural fluctuations in OLDNs. First, multiple structures of the OLDN were visualized through cryo-electron microscopy (cryo-EM), providing an overview of the tilting motion of the hexasome relative to the octasome at the near-atomistic resolution. Second, small-angle X-ray scattering (SAXS) revealed the presence of OLDN conformations with a larger radius of gyration than cryo-EM structures. A more complete description of OLDN fluctuation was proposed by SAXS-based ensemble modeling, which included possible transient structures. The ensemble model supported the tilting motion of the OLDN outlined by the cryo-EM models, further suggesting the presence of more diverse conformations. The amplitude of the relative tilting motion of the hexasome was larger, and the nanoscale fluctuation in distance between the octasome and hexasome was also proposed. The cryo-EM models were found to be mapped in the energetically stable region of the conformational distribution of the ensemble. Exhaustive complex modeling using all conformations that appeared in the structural ensemble suggested that conformational and motional asymmetries of the OLDN result in asymmetries in the accessibility of OLDN-binding proteins.

Assessing tumor microstructure with time-dependent diffusion imaging: Considerations and feasibility on clinical MRI and MRI-Linac.

Quantitative imaging biomarkers (QIBs) can characterize tumor heterogeneity and provide information for biological guidance in radiotherapy (RT). Time-dependent diffusion MRI (TDD-MRI) derived parameters are promising QIBs, as they describe tissue microstructure with more specificity than traditional diffusion-weighted MRI (DW-MRI). Specifically, TDD-MRI can provide information about both restricted diffusion and diffusional exchange, which are the two time-dependent effects affecting diffusion in tissue, and relevant in tumors. However, exhaustive modeling of both effects can require long acquisitions and complex model fitting. Furthermore, several introduced TDD-MRI measurements can require high gradient strengths and/or complex gradient waveforms that are possibly not available in RT settings. In this study, we investigated the feasibility of a simple analysis framework for the detection of restricted diffusion and diffusional exchange effects in the TDD-MRI signal. To promote the clinical applicability, we use standard gradient waveforms on a conventional 1.5 T MRI system with moderate gradient strength (Gmax=45 mT/m), and on a hybrid 1.5 T MRI-Linac system with low gradient strength (Gmax=15 mT/m). Restricted diffusion and diffusional exchange were simulated in geometries mimicking tumor microstructure to investigate the DW-MRI signal behavior and to determine optimal experimental parameters. TDD-MRI was implemented using pulsed field gradient spin echo with the optimized parameters on a conventional MRI system and a MRI-Linac. Experiments in green asparagus and 10 patients with brain lesions were performed to evaluate the time-dependent diffusion (TDD) contrast in the source DW-images. Simulations demonstrated how the TDD contrast was able to differentiate only dominating diffusional exchange in smaller cells from dominating restricted diffusion in larger cells. The maximal TDD contrast in simulations with typical cancer cell sizes and in asparagus measurements exceeded 5% on the conventional MRI but remained below 5% on the MRI-Linac. In particular, the simulated TDD contrast in typical cancer cell sizes (r=5-10µm) remained below or around 2% with the MRI-Linac gradient strength. In patients measured with the conventional MRI, we found sub-regions reflecting either dominating restricted diffusion or dominating diffusional exchange in and around brain lesions compared to the noisy appearing white matter. On the conventional MRI system, the TDD contrast maps showed consistent tumor sub-regions indicating different dominating TDD effects, potentially providing information on the spatial tumor heterogeneity. On the MRI-Linac, the available TDD contrast measured in asparagus showed the same trends as with the conventional MRI but remained close to typical measurement noise levels when simulated in common cancer cell sizes. On conventional MRI systems with moderate gradient strengths, the TDD contrast could potentially be used as a tool to identify which time-dependent effects to include when choosing a biophysical model for more specific tumor characterization.

Dynamic characteristics and prediction and control models of subsonic exhaust from a container

This study combines experimental measurements, numerical simulations, and theoretical analysis to investigate the subsonic discharge process in a container under normal temperature and pressure conditions. Experimental data captured the internal pressure dynamics during exhaust at the atmospheric environmental pressure. Numerical simulations using OpenFOAM validated the isothermal exhaust model against the experimental results. Under the assumption of ideal gas and isothermal processes, a nonlinear differential equation was derived to describe the evolution of the container's internal pressure. This equation was simplified for a specific range of pressure ratios, yielding analytical solutions for the internal pressure of the container under both constant and variable external pressures. The effectiveness of the expressions of pressure inside the container was verified by comparing them with experimental and numerical simulation data. We further developed a formula for predicting exhaust mass flow rate, with a prediction error within 9%. An improved formula was subsequently proposed to reduce the error to below 0.4%, enhancing prediction accuracy. For containers with variable external pressure, a method for controlling the exhaust mass flow rate by predicting external pressure changes was proposed, demonstrating its effectiveness in achieving precise control.

Exhaustive computational studies on pyrimidine derivatives as GPR119 agonist for the development of compounds against NIDDM

BackgroundType-2 Diabetes (T2DM) is a long-term medical disorder characterized by Insulin deficiency and high blood glucose levels. Among other medications to cure T2DM, the review of the literature found that various Pyrimidine derivatives act as an agonist for G-protein-coupled receptor 119 (GPR119) was proposed to control blood glucose levels by enhancing the function of pancreatic Beta-cells and its mechanism of action with fewer adverse effects. In the present research work, In-silico investigations were carried out to investigate the potential of the Pyrimidine analog as an agonist to the protein target GPR119 receptor. We performed exhaustive molecular modeling and protein modeling methodologies such as homology modeling, and molecular docking along with various drug designing tools such as 3D-QSAR and Pharmacophore Mapping to ascertain the design of better GPR119 agonists.ResultsBased on in-depth computational studies, we designed new pyrimidine moiety and analyzed them for GPR119 receptor agonist and further explored the ADMET properties. Designed compounds were found to exhibit better-predicted activities as compared to reference compound.ConclusionsThe current research on pyrimidine derivatives, using molecular docking, 3D-QSAR and Pharmacophore mapping demonstrated that the obtained computational model has significant properties and the designed molecules and Dataset from this model, produced antidiabetic compound against the target GPR119 i.e., compound 1S, 1Z and 1D with the docking score of − 11.696, − 9.314 and − 8.721, respectively. The pharmacokinetics and drug-likeness studies revealed that these compounds may be the future candidates for the treatment of diabetes acting via the GPR119 agonist mechanism.

Hybrid work stressors and psychological withdrawal behavior: A moderated mediation model of emotional exhaustion and proactive personality

This study proposes a theoretical model of challenge/hindrance stressors of hybrid work on emotional and behavioral reactions based on the conservation of resources theory. We investigate a mediation model by incorporating emotional exhaustion as a mediator to connect the relationship between two stressors and psychological withdrawal behavior. In addition, we identify proactive personality as a key personal resource to moderator the above mediating effects. The two-wave panel data was collected through online questionnaire surveys with a one-month interval. This study targeted at employees worked in the United States and 213 valid questionnaires were collected. Our results show that: (1) challenge/hindrance stressors of hybrid work are positively related to emotional exhaustion; (2) emotional exhaustion mediates the relationship between challenge/hindrance stressors of hybrid work and psychological withdrawal behavior; (3) proactive personality weakens the positive relationship between challenge stressors of hybrid work and emotional exhaustion. However, the moderating effect of proactive personality on the indirect effect of hindrance stressors of hybrid work on psychological withdrawal behavior via emotional exhaustion was not found. The implications of this study for theory and practice are discussed.

The etiology of the association between parental nurturance and youth antisocial behavior: Evidence from a twin differences study

AbstractBackgroundLower parental nurturance is consistently associated with higher levels of youth antisocial behavior (ASB), but the etiology of this association remains unclear. To fill this gap, we employed a twin differences approach to illuminate the environmental and genetic origins of the association between parental nurturance and children's ASB.MethodsParticipants were 2060 twins (49% female) ages 6–10 from the Michigan State University Twin Registry. Parental nurturance and youth ASB were assessed using multiple measures (e.g., questionnaires, interviews) and informant reports (e.g., twins, parents, teachers). Co‐twin difference‐score correlations were analyzed separately by zygosity using specification curve analysis, an exhaustive modeling approach that examined associations across all possible specifications of the nurturance and ASB data.ResultsParental nurturance demonstrated clear, negatively signed associations with youth ASB at the individual level. However, these associations generally did not persist within twin pairs. We observed no significant twin difference correlations within monozygotic (MZ) pairs and only a handful of significant twin difference correlations among dizygotic (DZ) pairs, in which the DZ co‐twin who experienced more nurturance exhibited less ASB. Post‐hoc analyses in these data revealed that these associations differed markedly from those with harsh parenting that suggested environmental influences on youth ASB.ConclusionsThese results strongly argue against a causal influence of low parental nurturance on youth ASB, and instead suggest that genetic influences and shared environmental confounds underlie their association. Further, findings strongly suggest that different parenting behaviors are associated with child ASB via different etiologic mechanisms.

Particle Swarm Optimization for a redundant repairable machining system with working vacations and impatience in a multi-phase random environment

With the increasing reliance on cloud computing as the foundational manufacturing systems with intricate dynamics, featuring multiple service areas, varying job arrival rates, diverse service requirements, and the interplay of failures and impatience, significant analytical challenges arise. Queueing networks offer a powerful stochastic modeling framework to capture such complex dynamics. This paper develops a novel, exhaustive queueing model for a finite-capacity redundant multi-server system operating in a multi-phase random environment. The proposed model uniquely integrates real-world factors, including server breakdowns and repairs, waiting servers, synchronous working vacations, and state dependent balking and reneging, into a single queueing model, representing a significant advancement in the field. Using the matrix-analytic method, we establish the steady-state solution and derive key performance metrics. Numerical experiments and sensitivity analyses elucidate the impact of system parameters on performance measures. Additionally, a cost model is formulated, enabling cost optimization analysis using direct search method and Particle Swarm Optimization (PSO) to identify efficient operating configurations.

Techno economic and life cycle assessment of olefin production through CO2 hydrogenation within the power-to-X concept

The paper deals with exhaustive process modelling, techno-economic and life cycle assessment (TEA/LCA) of olefin (ethylene and propylene) production through captured CO2 and electrolytic hydrogen. Olefins are important building block chemicals with several applications and carbon capture and utilisation (CCU) can provide a sustainable production route. The proposed system involves direct air capture (DAC) of CO2; proton exchange membrane (PEM) water electrolysis for hydrogen production, methanol synthesis, methanol to olefins (MTO) upgrade, and power generation from off-shore wind turbines. This study proposes a new integrated process as the first attempt to holistically assess a whole CCU assembly aiming at olefins production. Processing modelling has been implemented using the Aspen plus V12.1 and MATLAB R2022a software to solve the mass and energy balances of each unit operation. The modelling results showed a carbon efficiency of 72.3% to ethylene and propylene. In addition, the process is designed and integrated in such a way that no external heat supply is required. A specific energy consumption (SEC) of 150 MJ/kg olefins (41 kWh/kg) has been estimated. A minimum selling price of £3.67 per kg of olefins is required for the proposed process to break-even. The sensitivity analysis has revealed that the major cost driver is the cost of electricity. In addition, the life cycle assessment (LCA) has exposed that the proposed synthesis route of olefins has the potential to reduce the global warming potential (GWP) by 47% compared to fossil - based production. The outcomes of this study can be beneficial to engineering conceptual studies, policy makers and contribute new information to the CCU academic community.

Consideration of the effect of nanoscale porosity on mass transport phenomena in PECVD coatings

Here we show a novel approach to characterize the gas transfer behavior of silicon-oxide (SiO x ) coatings and explain the underlying dynamics. For this, we investigate the coating on a nm-scale both by measurement and simulation. Positron annihilation spectroscopy (PAS) and quantum mechanical electronic structure-based molecular dynamics simulations are combined to characterize the porous landscape of SiO x coatings. This approach analyses the influence of micropores smaller than 2 nm in diameter on gas permeation which are difficult to study with conventional methods. We lay out the main pore diameter ranges and their associated porosity estimates. An influence of layer growth on pore size and porosity was found, with an increased energy input during layer deposition leading to smaller pore sizes and a reduced porosity. The molecular dynamics simulations quantify the self-diffusion of oxygen and water vapor through those PAS deducted micropore ranges for hydrophilic and hydrophobic systems. The theoretical pore size ranges are fitting to our PAS results and complete them by giving diffusion coefficients. This approach enables detailed analysis of pore morphology on mass transport through thin film coatings and characterization of their barrier or membrane performance. This is a crucial prerequisite for the development of an exhaustive model of pore dominated mass transports in PECVD coatings.

Associations between delay discounting and unhealthy behaviors in substance use recovery

BackgroundResearch on delay discounting (DD) is mixed on whether DD is a domain-specific component related to specific behaviors or a domain-general process that cuts across various behaviors. A pivotal group to test the associations between DD and unhealthy behaviors is individuals in recovery from substance use disorders (SUD), as they are moving away from a disorder toward a healthier state. MethodsIndividuals in SUD recovery (n = 317) completed the Temptation Scale, the Health Behaviors Questionnaire, and an Adjusting Delay Discounting Task. An exhaustive model space search was performed using linear regression to examine associations between DD with temptation, engagement in unhealthy behaviors, and the total number of unhealthy behaviors participants engage in. We also tested whether remission status is associated with the total number of unhealthy behaviors participants engage in. ResultsResults revealed that DD was positively associated with poor eating (p<.001), physical inactivity (p=.003), financial irresponsibility (p<.001), risky behaviors (p<.001), lack of personal development goals (p<.001), lack of household savings (p=.004), and lack of health behaviors (p=.003). DD was also positively associated with the total number of unhealthy behaviors participants engage in (p<.001). Participants who were not in remission engaged in more unhealthy behaviors compared to those who were in remission (p<.001). ConclusionIn a sample of individuals in recovery from SUD, DD is not domain-specific and undergirds engagement in several maladaptive health behaviors that can negatively impact recovery. Thus, DD can be a target for interventions aiming to reduce other maladaptive behaviors in SUD recovery.

Unraveling Conductive Filament Formation in High Performance Halide Perovskite Memristor

AbstractHalide perovskites (HPs) are promising materials for memristor devices because of their unique characteristics. In this study, nonvolatile resistive switching memory devices based on thick MAPbI3 perovskite (800 nm) films with structure FTO/MAPbI3/polymethyl methacrylate (PMMA)/Ag are presented. Reproducible and reliable bipolar switching characteristics are demonstrated with an ultra‐low operating voltage (−0.1 V), high ON/OFF ratio (106), endurance (&gt;2 × 103 times) and a record retention time (&gt;105 s). The I–V curve of the first cycle exhibits self‐formed conductive filaments. These are attributed to the presence of metallic Pb resulting from an excess of PbI2 in the perovskite film. The subsequent activation process involves the formation of conductive filaments, consisting of either iodide vacancies or migrated charged metals. Numerical simulations are then carried out to understand the nature of these conductive filaments and the role of the internal electric field in the migration of iodide ions, iodide vacancies, and Ag cations. Finally, an exhaustive model is proposed that explains the set and reset processes governing the first voltage cycle and the steady state, at different voltage ranges. In summary, this work offers a novel and thorough perspective of the complete resistive switching (RS) behavior in a MAPbI3/buffer/Ag memristor, supported by numerical simulations.

Correctness Verification of Mutual Exclusion Algorithms by Model Checking

Mutual exclusion algorithms are at the heart of concurrent/parallel and distributed systems. It is well known that such algorithms are very difficult to analyze, and in the literature, different conjectures about starvation freedom and the number of by-passes (also called the overtaking factor) exist. The overtaking factor affects the (hopefully) bounded waiting time that a process competing for entering the critical section has to suffer before accessing the shared resource. This paper proposes a novel modeling approach based on Timed Automata and the Uppaal toolset, which proves effective for studying all the properties of a mutual exclusion algorithm for N≥2 processes, by exhaustive model checking. Although the approach, as already confirmed by similar experiments reported in the literature, is not scalable due to state explosion problems and can be practically applied until N≤5, it is of great value for revealing the true properties of analyzed algorithms. For dimensions N&gt;5, the Statistical Model Checker of Uppaal can be used, which, although based on simulations, can confirm properties by estimations and probabilities. This paper describes the proposed modeling and verification method and applies it to several mutual exclusion algorithms, thus retrieving known properties but also showing new results about properties often studied by informal reasoning.

Multiaxial creep–fatigue failure mechanism and life prediction of a turbine blade based on a unified numerical solution approach

AbstractExposure of turbine blades to cyclic torsional loading at high temperature, stemming from pre‐torque installation and the aerodynamic forces during operation, has the potential to induce substantial creep–fatigue damage, thereby contributing to the likelihood of premature failure. Investigating the deformation mechanisms and proposing a reliable life prediction method aiming at torsional loading is critical to ensure the structural integrity of turbine blades. This study conducted strain‐controlled fatigue and creep–fatigue tests on Inconel 718 superalloy, employing a multiaxial servo‐hydraulic testing machine. Electron backscattering diffraction elucidated deformation and damage mechanisms, forming a basis for subsequent constitutive modeling and life prediction. The lack of creep–fatigue mechanical behavior and microscopic failure mechanism when stress triaxiality equal to 0 is filled, which provides the theoretical basis and data support for the life design and damage assessment of this material under extreme service conditions. The unified viscoplasticity constitutive model effectively characterized macroscopic deformation under torsional loading. Prediction of creep–fatigue life under torsional loading, utilizing the multiaxial ductility factor‐modified strain energy density exhaustion model, demonstrated excellent alignment with experimental findings. Finally, parametric analyses of stress distribution and damage assessment under different conditions were carried out for the example of a turbine blade with relatively rarely considered aerodynamic loading as a variable. It is expected to be popularized and applied in life design and damage assessment of high‐temperature structures under multiaxial loading in engineering.

Abusive supervision and nursing students’ intention to leave the nursing profession: a moderated mediation model of emotional exhaustion and the nurse-patient relationship

BackgroundExploration of the relationship between nursing students’ abusive supervision and their future intention to leave the nursing profession before completing the final clinical practicum is critical to the issue of nursing staff shortages and how to alleviate them. In order to further dissect the factors influencing turnover intention among student nurses in clinical practice, our study used the conservation of resources theory and job demands-resources model to explain the specific pathways that influence student nurses’ intention to leave the nursing profession, with particular focus on nursing students’ personality traits and certain organizational factors.MethodThis study followed a cross-sectional design. Between March and May 2022, a convenience sampling method was used to select 531 nursing students from two medical universities in Fuzhou. The Abusive Supervision, Emotional Exhaustion, Nurse-Patient Relationship, and Turnover Intention Scales were employed to collect data. The PROCESS macro (Models 4 and 7) for SPSS 25.0 by Hayes and 5,000 bootstrap samples were used to examine the moderation and mediation impacts.ResultsAbusive supervision was found to significantly positively predict nursing students’ intention to leave the nursing profession. Emotional exhaustion significantly mediated the relationship between abusive supervision and an intention to leave the nursing profession. The moderating effect of the nurse-patient relationship in the mediation model was also found to be significant.ConclusionsAbusive supervision by clinical teaching staff is a work-related stressor that leads to emotional exhaustion, consequently decreasing nursing students’ future intention to work as a nurse. A nurse-patient relationship based on trust could buffer the negative effect of abusive supervision on emotional exhaustion. Healthcare organizations and nurse educators should implement programs that educate and train individuals about abusive supervision, emotion regulation, and positive nurse-patient relationships; this would serve to decrease nursing students’ intention to leave the nursing profession. This study provides relevant implications for helping nursing instructors develop effective intervention strategies to retain talented nursing personnel.

Unified framework for geometric error compensation and shape-adaptive scanning in five-axis metrology systems

In response to the escalating demand for precise shape metrology of complex optical surfaces, this study unveils a unified geometric error compensation and trajectory planning framework tailored for high-accuracy five-axis scanning metrology systems, which remains a notably underexplored field compared to error compensation in machine tools. Founded on a unified geometric model, the proposed framework seamlessly integrates a versatile shape-adaptive trajectory planning strategy, a thorough global error sensitivity analysis approach, and an exhaustive geometric error compensation scheme. Leveraging inverse kinematics, an innovative shape-adaptive scanning trajectory generation strategy is mathematically formulated, thereby facilitating adaptable measurement trajectory generation for diverse surface geometries. Employing forward kinematics, an exhaustive geometric error model is established to extensively address the 53 distinct geometric errors in the metrology system. This proposed error model fundamentally augments conventional geometric error models in machine tool by managing not only the geometric errors from the motion system, but also those from the probe and workpiece. To streamline the error compensation procedure, a novel global error sensitivity analysis approach is introduced, identifying both system-oriented and process-oriented sensitive geometric errors for targeted compensation. Experimental validation using a standard ball, which achieved an exceptional 89.35% reduction in the root mean square of the measurement errors, further confirms the feasibility and effectiveness of the proposed framework. By offering an universal trajectory planning, sensitivity analysis and error compensation trinity for five-axis scanning metrology systems, this study sets the stage for precision advancements and design optimization across diverse configurations of metrology systems.

Modeling and Analysis of Dekker-Based Mutual Exclusion Algorithms

Mutual exclusion is a fundamental problem in concurrent/parallel/distributed systems. The first pure-software solution to this problem for two processes, which is not based on hardware instructions like test-and-set, was proposed in 1965 by Th.J. Dekker and communicated by E.W. Dijkstra. The correctness of this algorithm has generally been studied under the strong memory model, where the read and write operations on a memory cell are atomic or indivisible. In recent years, some variants of the algorithm have been proposed to make it RW-safe when using the weak memory model, which makes it possible, e.g., for multiple read operations to occur simultaneously to a write operation on the same variable, with the read operations returning (flickering) a non-deterministic value. This paper proposes a novel approach to formal modeling and reasoning on a mutual exclusion algorithm using Timed Automata and the Uppaal tool, and it applies this approach through exhaustive model checking to conduct a thorough analysis of the Dekker’s algorithm and some of its variants proposed in the literature. This paper aims to demonstrate that model checking, although necessarily limited in the scalability of the number N of the processes due to the state explosions problem, is effective yet powerful for reasoning on concurrency and process action interleaving, and it can provide significant results about the correctness and robustness of the basic version and variants of the Dekker’s algorithm under both the strong and weak memory models. In addition, the properties of these algorithms are also carefully studied in the context of a tournament-based binary tree for N≥2 processes.

Motor network dynamic resting state fMRI connectivity of neurotypical children in regions affected by cerebral palsy.

Normative childhood motor network resting-state fMRI effective connectivity is undefined, yet necessary for translatable dynamic resting-state-network-informed evaluation in pediatric cerebral palsy. Cross-spectral dynamic causal modeling of resting-state-fMRI was investigated in 50 neurotypically developing 5- to 13-year-old children. Fully connected six-node network models per hemisphere included primary motor cortex, striatum, subthalamic nucleus, globus pallidus internus, thalamus, and contralateral cerebellum. Parametric Empirical Bayes with exhaustive Bayesian model reduction and Bayesian modeling averaging informed the model; Purdue Pegboard Test scores of hand motor behavior were the covariate at the group level to determine the effective-connectivity-functional behavior relationship. Although both hemispheres exhibited similar effective connectivity of motor cortico-basal ganglia-cerebellar networks, magnitudes were slightly greater on the right, except for left-sided connections of the striatum which were more numerous and of opposite polarity. Inter-nodal motor network effective connectivity remained consistent and robust across subjects. Age had a greater impact on connections to the contralateral cerebellum, bilaterally. Motor behavior, however, affected different connections in each hemisphere, exerting a more prominent effect on the left modulatory connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. This study revealed a consistent pattern of directed resting-state effective connectivity in healthy children aged 5-13 years within the motor network, encompassing cortical, subcortical, and cerebellar regions, correlated with motor skill proficiency. Both hemispheres exhibited similar effective connectivity within motor cortico-basal ganglia-cerebellar networks reflecting inter-nodal signal direction predicted by other modalities, mainly differing from task-dependent studies due to network differences at rest. Notably, age-related changes were more pronounced in connections to the contralateral cerebellum. Conversely, motor behavior distinctly impacted connections in each hemisphere, emphasizing its role in modulating left sided connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Motor network effective connectivity was correlated with motor behavior, validating its physiological significance. This study is the first to evaluate a normative effective connectivity model for the pediatric motor network using resting-state functional MRI correlating with behavior and serves as a foundation for identifying abnormal findings and optimizing targeted interventions like deep brain stimulation, potentially influencing future therapeutic approaches for children with movement disorders.

Design, assembly and testing of an upgraded aeroacoustics wind tunnel facility

The Aeroacoustics Laboratory in the Department of Aerospace Engineering at Penn State currently serves several areas of experimental research. Most notable in the laboratory is the Anechoic Chamber of which the Aeroacoustics Wind Tunnel is an integral part. In recent years the dominant areas of research have included model aircraft exhaust jets and model rotors for helicopter applications involving detailed noise experiments. In the jet noise area, the applications have included aircraft in both flyover and take-off configurations. In the flyover application the air flow surrounding the exhaust jet has a significant effect on the radiated noise and must be simulated to produce experimental results that will be most useful in preliminary design of noise suppression applications. The Aeroacoustics Wind Tunnel at Penn State serves the purpose for this simulation. During aircraft take-off, the aircraft airspeed is in a range exceeding 250 ft per second, or Mach number of over M = 0.22. In the years preceding 2022, the velocity of the free jet flow of the Penn State facility was limited to less than 200 ft/sec. This paper reports on a project to design upgrades to the existing wind tunnel to improve the test section flow velocity to values closer to the 250 ft/sec target. The approach began with a preliminary design of the return flow ducting to convert the open jet, open return wind tunnel to a closed return tunnel. The concept is to make use of the flow energy in the exhaust of the tunnel to boost the input energy to the inlet fan that drives the flow to the test section. An integral part of the preliminary design involved making use of an upgraded flow analysis computer code to predict the gain in test section velocity of the new facility. For the available horsepower of two fans in the facility, the configurations of the existing and upgraded wind tunnel were entered into this analysis code based on a quasi-one-dimensional formulation. The code included empirical data formulated to include the various shapes of the components of the tunnels. The relative flow velocities in each section used simple incompressible continuity to calculate all velocities in the component sections. The average dynamic pressure in each section is calculated from the flow (constant) density and the velocity squared. Each section had a non-dimensional pressure loss parameter calculated from empirical data (from the relevant literature). The basic code (using the Excel algorithms) was based on a predictor-corrector concept in which the calculation was initialized with the estimated velocity and pressure of the flow at the entrance to the test section. The loss in each following section is estimated to determine the loss in the total pressure and the cumulated loss compared to the gains made at the two fans in the circuit. The initial guess is adjusted based on the total pressure value at the end of the circuit. During the related experiments, measurements of the total and dynamic pressure were performed at several joints between sections and compared to the values predicted in the analysis code. Various settings of the horsepower of the drive fans were used and the results were compared to flow measurements for the tunnel configurations (predominantly for the open return and closed return tunnel setups available before and after the upgrade project.) Results of the analysis and experiments are presented and analyzed together with the remaining activities planned for the coming months.

Optical snake states in a photonic graphene.

We propose an optical analog of electron snake states based on an artificial gauge magnetic field in a photonic graphene implemented by varying distances between cavity pillars. We develop an intuitive and exhaustive continuous model based on tight-binding approximation and compare it with numerical simulations of a realistic photonic structure. The allowed lateral propagation direction is shown to be strongly coupled to the valley degree of freedom, and the proposed photonic structure may be used as a valley filter.

Corrigendum to “Illuminating associations between parenting and deleterious neighborhood characteristics via exhaustive modeling”

Corrigendum to “Illuminating associations between parenting and deleterious neighborhood characteristics via exhaustive modeling”