Relative Energies Research Articles

Mapping the Extended Ground State Reactivity Landscape of a Photoswitchable Molecule at a Single Molecular Level.

Photoswitchable molecules with structural flexibility can exhibit a complex ground state potential energy landscape due to the accessibility of multiple metastable states at merely low energy barriers. However, conventional bulk analytical techniques are limited in their ability to probe these metastable ground states and their relative energies. This is partially due to the difficulty of inducing changes in small molecules in their ground state, as they do not respond to external stimuli, such as mechanical force, unless they are incorporated into larger polymer networks. This hinders the understanding of ground-state reactivity and the associated dynamics. In this study, we leverage the "perturb-probe" capability of the single molecular break junction technique to explore the ground state 6π electrocyclization of a dithienylethene (DTE) derivative, a process traditionally achieved through electro- or photochromism. Our findings reveal that this reaction can also be triggered by mechanical force and an oriented electric field at the single-molecule level via ground state dynamics. We demonstrated that external perturbations could control the ground state reaction dynamics and steer the reaction trajectories away from constraints imposed by typical excited state dynamics. This strategy will thus offer access to a whole new dimension of single molecular electromechanical conversions and extend our knowledge of the ground state potential energy surface available to molecules under external force fields.

Leveraging a Separation of States Method for Relative Binding Free Energy Calculations in Systems with Trapped Waters.

Methods for calculating the relative binding free energy (RBFE) between ligands to a target protein are gaining importance in the structure-based drug discovery domain, especially as methodological advances and automation improve accuracy and ease of use. In an RBFE calculation, the difference between the binding affinities of two ligands to a protein is calculated by transforming one ligand into another, in the protein-ligand complex, and in solvent. Alchemical binding free energy calculations are often used for such ligand transformations. Such calculations are not without challenges, however; for example, it can be challenging to handle interfacial waters when these play a crucial role in mediating protein-ligand binding. In some cases, the exchange of the interfacial waters with solvent water might be very infrequent in the course of typical molecular simulations, and such interfacial waters can be considered trapped on the simulation time scale. In these cases, RBFE calculation between two ligands, where one ligand binds with a trapped water while the other ligand displaces it, can result in inaccuracies if the surrounding water structure is not sampled adequately for both ligands. So far, a popular choice for treating the trapped waters in RBFE calculations is to combine free energy calculations with enhanced sampling methods that insert/delete waters in the binding site. Despite recent developments in the enhanced sampling methods, they can result in hysteresis in the RBFE estimate, depending on whether the simulations were started with or without the trapped waters. In this study, we introduce an alternative method, separation of states, to calculate the RBFE between ligand pairs where the ligands bind to the protein with different numbers/positions of trapped waters. The separation of states approach treats the sampling of the trapped waters separately from the free energy calculation of the ligand transformation. In our method, a trapped water in protein's binding site is decoupled from the system first, and the cavity created by its decoupling is stabilized. We then grow a larger ligand into this cavity- a ligand that is known to displace the trapped water. In this study, we show that our method results in precise and accurate estimates of RBFEs for ligand pairs involving the rearrangement of trapped water via RBFE calculations for five such ligand pairs. We have optimized our simulation protocol to be suited for large distributed computational resources and have automated our RBFE calculation workflow.

Protocols for Metallo- and Serine-β-Lactamase Free Energy Predictions: Insights from Cross-Class Inhibitors.

While relative binding free energy (RBFE) calculations using alchemical methods are routinely carried out for many pharmaceutically relevant protein targets, challenges remain. For example, open-source tools do not support the easy setup and simulation of metalloproteins, particularly when ligands directly coordinate to the metal site. Here, we evaluate the performance of RBFE methods for KPC-2, a serine-β-lactamase (SBL), and two nonbonded metal parameter setups for VIM-2, a metallo-β-lactamase (MBL) with two active site zinc ions. We tested two different ways of modeling the ligand-zinc interactions. First, a restraint-based approach, in which FF14SB zinc parameters are combined with harmonic restraints between the zincs and their coordinating residues. The second approach uses an upgraded Amber force field (UAFF) for zinc-metalloproteins with adjusted partial charges and nonbonded terms of zinc-coordinating residues. Molecular mechanics (MM) and quantum mechanics/molecular mechanics (QM/MM) simulations show that the crystallographically observed zinc coordination is not retained in MM simulations with either zinc parameter set for a series of known phosphonic acid-based inhibitors bound to VIM-2. These phosphonic acid-based inhibitors exhibit known cross-class affinity for SBLs and MBLs and serve as a benchmark for RBFE calculations for VIM-2, after validation with KPC-2. The KPC-2 free energy of binding estimates are within expected literature accuracies for the ligand series with a mean absolute error of kcal/mol and a Pearson's correlation coefficient of . For VIM-2, the UAFF approach has improved correlation from to , compared to the restraint approach. The presented strategies for handling ligands coordinating to metal sites highlight that simple metal parameter models can provide some predictive free energy estimates for metalloprotein-ligand systems, but leave room for improvement in their ease of use, modeling of coordination sites and as a result, their accuracy.

Characteristics of hydraulic jump in asymmetrical trapezoidal channel with rough beds: experimental investigations

Understanding the dynamics of hydraulic jumps is crucial for optimizing the design of stilling basins in dams, enhancing energy dissipation efficiency, and reducing corrosion risks in hydraulic structures. This work aims to investigate the effect of bed geometry and roughness on the properties of hydraulic jump in an asymmetric trapezoidal channel, including parameters such as sequential depths, roller length and energy loss. Experiments were carried out under open channel flow conditions using three different bottom roughness element heights and mm. The channel's bottom is inclined transversely with a slope of covering a wide range of inflow Froude Number . Results indicate that the increase in bottom roughness leads to a decrease in the subsequent depth ratio by 28.91% compared to a hydraulic jump in a smooth bed. It was also found that the average reduction in roller length on the shallow and deep sides is 21.62% and 20.4%, respectively. Increasing the height of the roughness element enhances the relative energy dissipation by 8.53%. Finally, empirical equations were developed to describe hydraulic jump characteristics based on the Froude number and roughness element height, aiding in the optimal design of stilling basins.

Study on Mechanical Characteristics of Discontinuous Cut-Off Wall of Dam Foundation Based on Plastic Damage Calculation Method

Dam foundations are prone to leakage damage after being exposed to long-term water action, which seriously affects the operation safety of the dam. At present, concrete cut-off walls serve an important means of anti-seepage for dam foundations. However, due to construction challenges, the cut-off wall needs to be poured segment-by-segment during the construction process, and the joints between adjacent segments become weak parts for seepage prevention. Therefore, it is crucial to clarify the stress state of segmented discontinuous concrete cut-off walls. Based on the Lee-Fenves framework and the tension–compression constitutive relationship of fracture energy, a plastic damage calculation method was established in this paper to characterize the mechanical behavior of discontinuous cut-off walls. The method was then used to analyze the mechanical performance of discontinuous walls with segment joints containing slurry cake. The research results showed that compared to the continuous cut-off wall, the vertical settlement in the middle part of the discontinuous cut-off wall increased by 5.8%, and the displacement along the river flow direction decreased by 35.3%. As the wall segment width decreased, the joint opening and the degree of tensile damage were reduced accordingly, while the compressive damage in the middle and lower parts of the wall was intensified. As the wall depth decreased, the constraints and load on the bottom of the wall showed obvious changes, leading to a reduced stress and damage level of the wall. The findings provide reference for the design and safety control of cut-off walls.

Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System

This study introduces an advanced Mixed-Integer Linear Programming model tailored for comprehensive electrical and thermal energy management in small-scale smart grids, addressing emergency load shedding and overload situations. The model integrates combined heat and power sources, capable of simultaneous electricity and heat generation, alongside a mobile photovoltaic battery storage system, a wind resource, a thermal storage tank, and demand response programs (DRPs) for both electrical and thermal demands. Power-to-hydrogen systems are also incorporated to efficiently convert electrical energy into heat, enhancing network synergies. Utilizing the robust Gurobi solver, the model aims to minimize operating, fuel, and maintenance costs while mitigating environmental impact. Simulation results under various scenarios demonstrate the model’s superior performance. Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. This study emphasizes the advantages of employing DRP and heat tank equations to balance electrical and thermal energy relationships, reduce heat losses, and enable the integration of larger photovoltaic systems to meet thermal constraints, thus broadening the problem’s feasible solution space.

Numerical simulation and energy consumption analysis of ventilation patterns in grain silo

Mechanical ventilation is an effective method to ensure the security of grain storage, which directly impacts the storage duration and storage quality. In this work, considering the coupling effect of grain physical parameters and gas-solid phase interaction on ventilation, the porous media, non-thermal equilibrium and turbulence models were employed to investigate the variation of velocity field and temperature field under four ventilation patterns: vertical ventilation duct (VD), transverse ventilation duct (HD), combined roof inhalation duct (CRD), and combined bottom inhalation duct (CBD). The relative standard deviation (RSD) and unit energy consumption were used to evaluate the performance of different ventilation patterns quantitatively. The results show a relative deviation of 5.12 % between simulation and experiments. Compared with VD and HD, CRD and CBD exhibit higher velocity values and gradient in the center of grain silo. The physical parameters of grain have obvious impacts on velocity field, and paddy has the highest velocity values due to its higher porosity. CRD has a significant advantage in cooling speed and effect, with the grain surface temperature at 12 m and 25 m lower than other patterns by 1.2 °C and 1.8 °C, respectively. The large porosity of paddy can advance cooling time by up to 5–10 h, while the lower specific heat capacity and higher thermal conductivity of peanut result in cooling temperatures 1.5 °C–2.4 °C lower than other grain. The temperature RSD of VD is lower than other ventilation patterns, and the unit energy consumption of CRD and CBD is better.

Kinetic simulations of nuclear burning plasmas in inertial confinement fusions taking into account the large-angle collisions

Although ignition had been achieved at the National Ignition Facility (NIF), recent observations of the experiments indicate novel physics that beyond theoretical predictions emerge, e.g., the neutron analysis of experiments has revealed deviations from the Maxwellian distributions in ion relative kinetic energies of burning plasmas, with the surprising emergence of supra-thermal deuterium and tritium (DT) ions that fall outside the predictions of macroscopic statistical hydrodynamic models. Via our newly developed hybrid-particle-in-cell code, incorporating the newly-proposed model of large-angle collisions, we infer that this could be attributed to the increased significance of large-angle collisions among DT ions and α-particles in the burning plasma. Extensive and unprecedented kinetic investigations into the implications of large-angle collisions in the burning plasma have yield several key findings, including an ignition moment promotion by ∼10ps, the presence of supra-thermal ions below an energy threshold, and approximately twice the expected deposition of α-particles densities. The rationality of our findings is confirmed through the congruency between the neutron spectral moment analyses conducted by the NIF and our kinetic simulations, both highlighting progressively widening disparities between neutron spectral moment analyses and hydrodynamics predictions, which becomes more pronounced as the yield increases. Our kinetic simulations with large-angle collisions not only provide novel insights for experiment interpretation but also open new research opportunities for the largely unexplored regime of the nuclear burning plasmas, which are distinguished by their exceptionally high energy densities and hold immense potential for illuminating the intricate physics that underpins the evolution of the early universe.

The barriers and facilitators of improving energy availability amongst females clinically diagnosed with Relative Energy Deficiency in Sport (REDs).

Relative Energy Deficiency in Sport (REDs) is a serious clinical condition. However, there is little research in athletes with a clinical diagnosis and limited evidence on the recovery of REDs. This is a cross-sectional retrospective study whereby 55 (25.62±6.33 years) female patients with a prior diagnosis of REDs by an experienced medical specialist participated in an online questionnaire designed to capture their experience of a sports dietitian consultation and subsequent implementation of a personalized energy availability (EA) plan. A 31% increase (N.=4 vs. N.=16, P=0.002) in normal menstruation, a 22% reduction (N.=39 vs. N.=27, P=0.032) in gastrointestinal symptoms, and a 94% reduction (N.=16 to N.=1) in a very poor/poor appetite were reported following the consultation and plan implementation. Required energy intake (EI) was under-estimated by 93% of participants. Intake pre-exercise was implemented most frequently (69%, N.=38), and least likely to elicit feelings of stress and anxiety (69%, N.=38). Weight gain/shape change was the most frequently reported barrier to implementation (62%, N.=34). Eating to a planned regime (35%, N.=19) and following a timing of intake (33%, N.=18) gave the most confidence. Providing an athlete with an education of their current and required EA, alongside an illustrated personalized EI plan structured around exercise, may provide the "lightbulb" moment needed to overcome the associated anxiety when increasing their EI when recovering from REDs.

Eating- and Weight-Related Disorders in the Armed Forces

Background/Objectives: Like in the general population, the prevalences of eating- and weight-related health issues in the armed forces are increasing. Relevant medical conditions include the eating disorders (EDs) anorexia nervosa, bulimia nervosa, binge eating disorder, and avoidant restrictive food intake disorder (ARFID), as well as body dysmorphic disorder, muscle dysmorphia, and the relative energy deficiency in sport (RED-S) syndrome. Methods: We performed a narrative literature review on eating- and weight-related disorders in the armed forces. Results: Entry standards might exclude people with obesity, with EDs, or at high risk for EDs from entering the armed forces for military reasons and to protect the individual’s health. Relevant potential risk factors of eating- and weight-related disorders in the military are the emphasis on appearance and fitness in the military, high levels of stress, military sexual trauma, post-traumatic stress disorder, deployment, relocation, long commutes, consumption of ultra-processed foods and beverages, limitations on food selection and physical exercise, and intensive combat training and field exercises. Eating- and weight-related disorders negatively impact professional military appearance and lead to problems with cardiorespiratory and neuromuscular fitness; daytime sleepiness; and a higher risk of musculoskeletal injuries, and other physical and mental health problems. Current and potential future therapeutic options include occupational health measures, psychosocial therapies, neuromodulation, and drug treatments. Conclusions: Even though randomized controlled trials (RCTs) have been performed to test treatments for obesity in the armed forces, RCTs for the treatment of EDs, body dysmorphic disorder, muscle dysmorphia, and RED-S syndrome are lacking in the military context.

The Awareness of Sports Physicians about Relative Energy Deficiency in Sport

The Awareness of Sports Physicians about Relative Energy Deficiency in Sport

The associations between calorie tracking, body image dissatisfaction, eating disorders, and menstrual cycle characteristics in resistance-trained athletes.

While body image dissatisfaction (BID) and eating disorders (EDs) are relatively common in athletes (ranging from 11% to 67% of athletes, depending on the sport) [1], they are also prevalent in weight-class restricted sports (a common format in strength sports), and among physique athletes [2]. These athletes manipulate their nutrition to reach aesthetic or body weight standards and, in that process, may undergo prolonged periods of low energy availability. Low energy availability, defined as consuming insufficient energy for one's lean mass and exercise activity, can lead to Relative Energy Deficiency in sport (REDs), a syndrome that can impact menstrual cycle (MC) symptoms (and many other aspects of physiology and psychology) [3]. There has not been an investigation into the relationships between these resistance-trained (RT) athletes' nutritional habits, MC-related symptoms, BIDs, and EDs. A survey was implemented to explore the dieting habits, MC characteristics, BID, and EDs in RT females. 64.6% (n = 469) of participants reported tracking calories, with a slightly higher percentage of competitive athletes tracking calories 71.8% (n = 181) than recreational-level athletes. Competitive athletes were significantly more likely to track calories than recreational-level athletes (p = 0.003). When asked what the primary purpose of calorie restriction was, most participants selected weight loss for aesthetic purposes 58.8% (n = 356). Competitive athletes were less likely to select weight loss for aesthetic purposes 35.7% (n = 77), but weight loss for the purpose of a weight class-based sport was higher at 43.5% (n = 94). There were no significant associations between BID and MC characteristics or most MC symptoms and limited associations between EDs and MC characteristics and symptoms. RT athletes exhibited a higher prevalence of calorie tracking than the general population. Competitive RT athletes were less likely to calorie restrict for aesthetic purposes than non-athletes, but more likely to calorie restrict for the purpose of weight-class-based sports. There were limited significant associations between BID and MC characteristics or MC symptoms, as well as between EDs and MC characteristics. However, there was a significant association between amenorrhea and EDs, which aligns with previous research in this area. Both BID and EDs were significantly associated with MC-based mental health effects; this is likely due to the interconnected nature of mental health concerns, such as EDs with depression and anxiety.

The Schrödinger Equation Used the Wrong Energy Relationship

According to the energy relationship of the ground state solution of a hydrogen atom using the Schrödinger equation, the kinetic energy of an electron at twice the Bohr radius becomes zero. The electron has zero kinetic energy, which means it is dead, indicating that the energy relationship used in the Schrödinger equation is incorrect. Then, the reasons for both the chaotic energy relationship of the Schrödinger equation and the half frequency problem encountered by Bohr are analyzed. Bohr only considered Coulomb force and established an equation with centrifugal force, but he did not consider Lorentz force. So, the frequency he obtained must be multiplied by 1/2 to match the experimental value. This article also analyzes other issues related to the Schrödinger equation.

A survey of energies from pure metals to multi-principal element alloys

In materials science, a wide range of properties of materials are governed by various types of energies, including thermal, physicochemical, structural, and mechanical energies. In 2005, Dr. Frans Spaepen used crystalline face-centered cubic (fcc) copper as an example to discuss a variety of phenomena that are associated with energies. Inspired by his pioneering work, we broaden our analysis to include a selection of representative pure metals with fcc, hexagonal close-packed (hcp), and body-centered cubic (bcc) structures. Additionally, we extend our comparison to energies between pure metals and equiatomic binary, ternary, and multi-principal element alloys [sometimes also known as high-entropy alloys (HEAs)]. Through an extensive collection of data and calculations, we compile energy tables that provide a comprehensive view of how structure and alloying influence the energy profiles of these metals and alloys. We highlight the significant impact of constituent elements on the energies of alloys compared to pure metals and reveal a notable disparity in mechanical energies among materials in fcc-, hcp- and bcc-structured metals and alloys. Furthermore, we discuss the energy relationships, the implications for structural transformations and potential applications, providing insights into the broader context of these energy variations.

Family roots, green shoots: exploring the impact of work–family interpersonal capitalization on employee green behavior

Purpose This study aims to explore the influence of extra-workplace factors, specifically work−family interpersonal capitalization, on employee green behavior. Based on the conservation of resources theory, the research sought to understand how resources gained from positive family interactions spill over into the workplace, enhancing green behavior. In addition, the study investigated the mediating role of relational energy and the moderating effects of work green climate and environmental self-accountability, providing a nuanced understanding of the mechanisms involved. Design/methodology/approach This study used a multiwave field study combined with an experimental study to investigate the impact of work−family interpersonal capitalization on employee green behavior. Data were collected in several phases to capture changes over time and to understand causal relationships. The multiwave design allowed for observing the dynamic interplay between family and work domains, while the experimental component provided controlled conditions to validate the findings. This approach ensured robust and comprehensive analysis, integrating both real-world and experimental data. Findings The study revealed that work−family interpersonal capitalization significantly enhances employee green behavior. Relational energy emerged as a crucial mediator in this relationship. Furthermore, the study found that both work green climate and environmental self-accountability positively moderated the relationship between relational energy and green behavior. Notably, the interaction of work green climate and environmental self-accountability further strengthened this relationship, ultimately influencing the indirect effect of relational energy on employee green behavior. These findings highlight the complex interplay between personal and organizational factors in promoting sustainable practices at work. Originality/value This study provides valuable insights into the spillover effects from family to work, emphasizing the importance of considering “nongreen” factors in understanding employee green behavior. By identifying relational energy as a key mediator and uncovering the moderating roles of work green climate and environmental self-accountability, the research contributes to the broader literature on environmental sustainability and organizational behavior. The findings suggest practical implications for organizations aiming to foster green behavior, highlighting the potential of enhancing family−work interactions and cultivating a supportive green work environment.

Activation of Strong π-Acids at [Fe4S4]+ Clusters Enabled by a Noncanonical Electronic Structure.

Although Fe-S clusters are privileged metallocofactors for the reduction of N2, CO, and other π-acidic substrates, their constituent metal ions─high-spin Fe2+ and Fe3+─are typically not amenable to binding and activating strong π-acids. Here, we demonstrate that [Fe4S4]+ clusters can overcome this limitation by adopting a noncanonical electronic structure. Specifically, we report the synthesis and characterization of a series of 3:1 site-differentiated [Fe4S4]+ clusters in which the unique Fe site is bound by one of 10 electronically variable arylisocyanide ligands. Rather than being continuously tuned as a function of the arylisocyanides' electronic properties (e.g., as quantified by linear free energy relationships), the structures of the clusters are divided into two groups: (i) those with moderately π-acidic isocyanides, which adopt a "typical" structure characterized by standard bond metrics and geometric distortions from tetrahedral symmetry, and (ii) those with more strongly π-acidic isocyanides, which adopt a "contracted" structure with an unusually symmetric geometry and a compressed cluster core. Computational studies revealed that although the "typical" structure has a canonical electronic structure, the "contracted" structure has a noncanonical arrangement of spin density, with a full complement of π-backbonding electrons and more substantial Fe-Fe delocalization. These features of the "contracted" structure enable substantial C≡N bond weakening of the strongest π-acceptors in the series. More generally, the experimental characterization of the "contracted" electronic isomer suggests that other noncanonical electronic structures of Fe-S clusters remain to be discovered.

Predicting multi-frequency crude oil price dynamics: Based on MIDAS and STL methods

Accurate prediction of crude oil prices is important for national energy security and socioeconomic development. Research on crude oil price forecasting has primarily focused on the overall price, overlooking the differentiated investment needs of different entities. To solve this problem, we introduce the Seasonal and Trend decomposition using Loess (STL) method into the Mixed Data Sampling (MIDAS) model. This enables us to more accurately analyze the predictive capability of predictors for crude oil prices at different frequencies. Selected predictors include the Dow Jones Index, US Dollar exchange rate, economic policy uncertainty, related crude oil and energy prices, carbon asset prices, and investor attention. Empirical results indicate that these predictors significantly enhance the forecasting accuracy across all components, with the strongest impact in the trend component. Interestingly, a lag effect is observed in the predictors' impact on the seasonal and residual components, but not on the trend component. Moreover, we calculate the duration of each predictor's effectiveness for different components of crude oil prices, distinguishing short-term and long-term effective predictors. This research offers novel insights into the design of crude oil price forecasting models, which is crucial for enhancing investor returns and maintaining stability in the energy market.

Prediction of synthesis of ternary-layered double transition metal MAX phases and the possibility of their exfoliation for formation of 2D MXenes

The MXenes family has already demonstrated considerable potential in energy storage, electromagnetic, and electrochemical applications. It is usually created by selectively etching the A layer from the bulk MAX phase. The goal of this work is to broaden the family of MAX phases and examine the possibility of etching them to create a 2D system. Here, we provide a machine learning (ML) approach that is able to accurately predict the relative formation energy (ΔH) on small dataset. From the calculated results, our model shows high prediction accuracy as proved by the RMSE of 0.052 for ΔH. From a dataset of 1320 potential MAX candidates, we predicted 734 MAX phases that could be synthesized by experimental. Moreover, we observed that exfoliating 2D MXenes is more difficult when picking an A atom of S element in the MAX phase, however it is simpler when selecting a group III-A and Ⅳ-A element with a high atomic number. Finally, we identified 75 MXenes candidates with the most potential to be exfoliated from their layered bulk phase. Our machine learning technique can speed up the prediction of possible 2D MXenes while reducing calculation time by more than an order of magnitude.

Comprehensive analysis of orofacial motor skills in children with obstructive sleep apnea.

The neuromuscular activity has a critical role in the permeability of the upper airways. The present study aimed to conduct a detailed and comparative investigation of the orofacial musculature and motor skills of children with obstructive sleep apnea (OSA). Children aged 7 to 12 years with OSA (OSA group, n = 12) and without OSA (Control group, n = 12) were compared. Orofacial appearance/posture and motor skills were assessed using the orofacial myofunctional evaluation protocol with scores. Bite force, tongue pressure measurements, and surface electromyography of swallowing were also performed. Compared to the control group, the OSA group obtained lower scores in appearance/posture, mobility, and orofacial functions (P < 0.0001), and lower values of bite force (P = 0.019) and tongue strength in protrusion (P = 0.008) and deglutition (P = 0.004). The OSA group also displayed lower values of maximum speed (P = 0.003) and peak activity (P = 0.0005) during spontaneous swallowing and higher relative energy expenditure (integral) of the muscles in the water swallowing task (50 mL) (P ≤ 0.01). Notably, the effect size ranged from moderate to large for all groups differences. The children with OSA showed impairments in orofacial musculature and motor skills, as evidenced by reduced muscle recruitment capacity and coordination in applying pressure/force and performing orofacial movements and functions. This study contributes to the understanding of non-anatomical factors associated with OSA in children and to the development of therapeutic strategies.

Computational Library Enables Pattern Recognition of Noncovalent Interactions and Application as a Modern Linear Free Energy Relationship.

A quantitative and predictive understanding of how attractive noncovalent interactions (NCIs) influence functional outcomes is a long-standing goal in mechanistic chemistry. In that context, better comprehension of how substituent effects influence NCI strengths, and the origin of those effects, is still needed. We sought to build a resource capable of elucidating fundamental origins of substituent effects in NCIs and diagnosing NCIs in chemical systems. To accomplish this, a library of 893 NCI energies was calculated encompassing cation-π, anion-π, CH-π, and π-π interactions across 60 different arenes and heteroarenes. The interaction energies (IEs) were calculated using symmetry-adapted perturbation theory (SAPT), which identifies electrostatic, inductive, exchange-repulsive, and dispersive contributions to total IE. This descriptor library provides a comprehensive platform for evaluating substituent effect trends beyond traditional molecular descriptors such as Hammett values, frontier molecular orbital energies, and electrostatic potential, thereby expanding the tools available to analyze modern chemical processes that involve NCIs. To demonstrate the application of this library, three case studies in asymmetric catalysis and supramolecular chemistry are presented. These case studies informed the development of an automated NCI analysis tool, which employs statistical analyses to diagnose a particular NCI in a chemical system of interest.