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Here we study the evolution of the Berry phase ( Φ B ) and the topological properties of a Chern insulator in the presence of a band deformation en route from a Dirac dispersion to an anisotropic Dirac one. Such a scenario can be achieved by tuning one of the hopping amplitudes among a pair of sites in a honeycomb lattice (say, t 1 ) with respect to those corresponding to the other two pairs ( t ). The anisotropic Dirac dispersion characterized by different velocities corresponding to different directions in the k -space is further confirmed by computing the energy ( E ) dependence of the cyclotron mass which changes from being proportional to E in the absence of the Haldane flux to linearly in E in its presence. At t 1 = 2 t (known as the semi-Dirac limit), the two Dirac points merge at an intermediate M point where both the energy gap and the Berry phase vanish in the absence of a Haldane flux, whereas the presence of a flux yields a non-zero Berry phase, even though the spectrum still remains gapless. Moreover, in the absence of the Haldane flux, the Berry phase remains insensitive to the energy of the particle, while in its presence, Φ B is altered corresponding to different radii of the paths traversed by the particle in the k -space. As t 1 exceeds a value greater than 2 t , a gap re-opens in the energy spectrum, and the Berry phase vanishes even in presence of a Haldane flux indicating the onset of a transition from a topological phase to a trivial one. This transition is further supported by the existence of the edge modes that are present only in the topological regime.

It is well accepted that atherosclerosis initiation and progression correlate positively with low and oscillating flow wall shear stresses (FSS). However, this mechanism cannot explain why advanced plaques continue to grow under elevated FSS conditions. In vivo magnetic resonance imaging (MRI)-based 2D/3D multi-component models with fluid–structure interactions (FSI, 3D only) for human carotid atherosclerotic plaques were introduced to quantify correlations between plaque progression measured by wall thickness increase (WTI) and plaque wall (structure) stress (PWS) conditions. A histologically validated multi-contrast MRI protocol was used to acquire multi-year in vivo MRI images. Our results using 2D models (200–700 data points/patient) indicated that 18 out of 21 patients studied showed significant negative correlation between WTI and PWS at time 2 (T2). The 95% confidence interval for the Pearson correlation coefficient is ( - 0.443 ,- 0.246 ) , p < 0.0001 . Our 3D FSI model supported the 2D correlation results and further indicated that combining both plaque structure stress and flow shear stress gave better approximation results (PWS, T2: R 2 = 0.279 ; FSS, T1: R 2 = 0.276 ; combining both: R 2 = 0.637 ). These pilot studies suggest that both lower PWS and lower FSS may contribute to continued plaque progression and should be taken into consideration in future investigations of diseases related to atherosclerosis.

Amino acid-based formulas (AAF) contain free amino acids as their protein source and are indicated for certain gastrointestinal and medical conditions. When switching formulas, monitoring tolerance helps assure adequate nutritional management. A cross-sectional retrospective study was conducted using U.S. insurance claims data from 402 children switched from one AAF (Formula1) to a different AAF (Formula2) between June 2021 and April 2023 during the nationwide formula shortage. Database was analyzed for age, sex, comorbidities, clinical symptoms, and healthcare encounters. Mean age was 5.3 ± 4.7 years (60% male). Significantly fewer children experienced abdominal distention, diarrhea, flatulence, nausea/vomiting, and allergy symptoms 1-, 3-, 6-months post-switch to Formula2 (P < .05). Significant reductions for total mean adjusted costs, emergency department, inpatient, outpatient, urgent care, and telemedicine visits were observed 1-, 3-, and 6-months post-switch (P < .001). Children in post-acute care settings who transitioned to an alternate AAF (Formula2) experienced significantly improved clinical outcomes and reduced healthcare costs.

Channelrhodopsin-2 (ChR2) is a light-gated ion channel that conducts cations of multiple valencies down the electrochemical gradient. This light-gated property has made ChR2 a popular tool in the field of optogenetics, allowing for the spatial and temporal control of excitable cells with light. A central aspect of protein function is the interaction with the surrounding lipid environment. To further explore these membrane-protein interactions, we demonstrate the role of residual hydrophobic mismatch (RHM) as a mechanistically important component of ChR2 function. We combined computational and functional experiments to understand how RHM between the lipid environment and ChR2 alters the structural and biophysical properties of the channel. Analysis of our results revealed significant RHM at the intracellular/lipid interface of ChR2 from a triad of residues. The resulting energy penalty is substantial and can be lowered via mutagenesis to evaluate the functional effects of this change in lipid-protein interaction energy. The experimental measurement of channel stability, conductance and selectivity resulting from the reduction of the RHM energy penalty showed changes in progressive H+ permeability, kinetics and open-state stability, suggesting how the modulation of ChR2 by the surrounding lipid membrane can play an important biological role and contribute to the design of targeted optogenetic constructs for specific cell types.

We show that the nearest neighbour entanglement in a mixture of ground and first excited states—a subjacent state—of the J 1 − J 2 Heisenberg quantum spin chain can be used as an order parameter to detect the phase transition of the chain from a gapless spin fluid to a gapped dimer phase. We study the effectiveness of the order parameter for varying relative mixing probabilities between the ground and first excited states in the subjacent state for different system sizes, and extrapolate the results to the thermodynamic limit. We observe that the nearest neighbour concurrence can play a role of a good order parameter even if the system is in the ground state, but with a small finite probability of leaking into the first excited state. Moreover, we apply the order parameter of the subjacent state to investigate the response to separate introductions of anisotropy and of glassy disorder on the phase diagram of the model, and analyse the corresponding finite-size scale exponents and the emergent tricritical point in the former case. The anisotropic J 1 − J 2 chain has a richer phase diagram which is also clearly visible by using the same order parameter.

Existing Optical Mark Recognition (OMR) systems tend to be expensive and rigid in their operation, often resulting in erroneous evaluations due to strict correction protocols. This scenario airs the need for a flexible OMR system. Hence, in this work, we propose a lightweight transfer learning based Convolutional Neural Network (CNN) model, dubbed as OMRNet, which can classify answer boxes on any generalized OMR test sheet. Unlike most existing techniques that rely on image processing algorithms to recognize extracted answer boxes in two classes: confirmed and empty, the OMRNet is designed to classify the answer boxes into confirmed, crossed-out, and empty categories. That is, OMRNet is facilitating the crossing out of previously answered questions and thus removing the rigidity of templates in Multiple Choice Question (MCQ) tests. We have built OMRNet on top of a MobileNetV2 backbone connected to four fully connected layers with appropriate dropouts and activation functions in between. We have evaluated OMRNet on the Multiple Choice Answer Boxes dataset available at https://sites.google.com/view/mcq-dataset . We have performed experiments following a 5 fold cross validation scheme, and OMRNet has achieved accuracies of 95.29%, 95.88%, 93.97%, 97.45%, and 97.20%, with an average accuracy of 95.96%. Also, the experimental results confirm that the present model performs better than the compared state-of-the-art methods and standard CNN models in terms of accuracy, execution time, and memory required to store the trained module. Moreover, we have employed a quantization technique to make the trained module more memory efficient and deployed it to a web app using our own Representational State Transfer Application Programming Interface (REST API). It makes OMRNet available via a Hypertext Transfer Protocol (HTTP) endpoint, allowing potential users to connect to it via the Internet. The source code for the work is available at the following link: https://github.com/sa-y-an/OMRNet .

From computational simulations of a serotonin 2A receptor (5-HT(2A)R) model complexed with pharmacologically and structurally diverse ligands we identify different conformational states and dynamics adopted by the receptor bound to the full agonist 5-HT, the partial agonist LSD, and the inverse agonist Ketanserin. The results from the unbiased all-atom molecular dynamics (MD) simulations show that the three ligands affect differently the known GPCR activation elements including the toggle switch at W6.48, the changes in the ionic lock between E6.30 and R3.50 of the DRY motif in TM3, and the dynamics of the NPxxY motif in TM7. The computational results uncover a sequence of steps connecting these experimentally-identified elements of GPCR activation. The differences among the properties of the receptor molecule interacting with the ligands correlate with their distinct pharmacological properties. Combining these results with quantitative analysis of membrane deformation obtained with our new method (Mondal et al, Biophysical Journal 2011), we show that distinct conformational rearrangements produced by the three ligands also elicit different responses in the surrounding membrane. The differential reorganization of the receptor environment is reflected in (i)-the involvement of cholesterol in the activation of the 5-HT(2A)R, and (ii)-different extents and patterns of membrane deformations. These findings are discussed in the context of their likely functional consequences and a predicted mechanism of ligand-specific GPCR oligomerization.

Spatial organization of G-protein coupled receptors (GPCRs) into dimers and higher order oligomers has been demonstrated in vitro and in vivo . The pharmacological readout was shown to depend on the specific interfaces, but why particular regions of the GPCR structure are involved and how ligand-determined states change them remains unknown. Here we show why protein-membrane hydrophobic matching is attained upon oligomerization at specific interfaces from an analysis of coarse-grained molecular dynamics simulations of the spontaneous diffusion-interaction of the prototypical beta2-adrenergic (β 2 AR) receptors in a POPC lipid bilayer. The energy penalty from mismatch is significantly reduced in the spontaneously emerging oligomeric arrays, making the spatial organization of the GPCRs dependent on the pattern of mismatch in the monomer. This mismatch pattern is very different for β 2 AR compared to the highly homologous and structurally similar β 1 AR, consonant with experimentally observed oligomerization patterns of β 2 AR and β 1 AR. The results provide a mechanistic understanding of the structural context of oligomerization.

From computational simulations of a serotonin 2A receptor (5-HT2AR) model complexed with pharmacologically and structurally diverse ligands we identify different conformational states and dynamics adopted by the receptor bound to the full agonist 5-HT, the partial agonist LSD, and the inverse agonist Ketanserin. The results from the unbiased all-atom molecular dynamics (MD) simulations show that the three ligands affect differently the known GPCR activation elements including the toggle switch at W6.48, the changes in the ionic lock between E6.30 and R3.50 of the DRY motif in TM3, and the dynamics of the NPxxY motif in TM7. The computational results uncover a sequence of steps connecting these experimentally-identified elements of GPCR activation. The differences among the properties of the receptor molecule interacting with the ligands correlate with their distinct pharmacological properties. Combining these results with quantitative analysis of membrane deformation obtained with our new method (Mondal et al, Biophysical Journal 2011), we show that distinct conformational rearrangements produced by the three ligands also elicit different responses in the surrounding membrane. The differential reorganization of the receptor environment is reflected in (i)-the involvement of cholesterol in the activation of the 5-HT2AR, and (ii)-different extents and patterns of membrane deformations. These findings are discussed in the context of their likely functional consequences and a predicted mechanism of ligand-specific GPCR oligomerization.

Automatic light control systems have garnered significant attention for their potential to enhance energy efficiency and user convenience across various settings. This paper provides a comprehensive overview of these systems, elucidating their principles, components, applications, and associated benefits. The primary objective of automatic light control systems is to intelligently regulate lighting levels based on environmental factors such as occupancy, ambient light, and time of day. Various sensors, including Passive Infrared (PIR), ultrasonic, and photoresistors, are commonly employed to detect changes in the surroundings and trigger appropriate lighting adjustments. Advanced control algorithms and communication protocols facilitate seamless integration with building automation systems, enabling centralized management and optimization of lighting across diverse zones. Moreover, the advent of smart lighting solutions leveraging Internet of Things (IoT) platforms enables remote monitoring and control, empowering users to personalize lighting preferences and further optimize energy consumption. The paper critically reviews the key features, benefits, and challenges associated with automatic light control systems, underscoring their pivotal role in promoting sustainability, comfort, and cost-effectiveness in both residential and commercial environments. Additionally, the paper discusses future research directions, highlighting opportunities for innovation in sensor technology, data analytics, and human-centric lighting design to propel the capabilities and adoption of these systems.