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In the study of stochastic systems, the committor function describes the probability that a system starting from an initial configuration x will reach a set B before a set A. This paper introduces an efficient and interpretable algorithm for approximating the committor, called the "fast committor machine" (FCM). The FCM uses simulated trajectory data to build a kernel-based model of the committor. The kernel function is constructed to emphasize low-dimensional subspaces that optimally describe the A to B transitions. The coefficients in the kernel model are determined using randomized linear algebra, leading to a runtime that scales linearly with the number of data points. In numerical experiments involving a triple-well potential and alanine dipeptide, the FCM yields higher accuracy and trains more quickly than a neural network with the same number of parameters. The FCM is also more interpretable than the neural net. [ABSTRACT FROM AUTHOR]

Global diabatic potential energy surfaces (PESs) of CH2+ are constructed using the neural network method with a specific function based on 18 213 ab initio points. The multi-reference configuration interaction method with the aug-cc-pVQZ basis set is adopted to perform the ab initio calculations. The topographical properties of the diabatic PESs are examined in detail. In general, the diabatic PESs provide an accurate quasi-diabatic representation. To validate the diabatic PESs, the dynamics studies of the C+(2P1/2, 3/2) + H2 (v0 = 0, j0 = 0) → H + CH+(X1Σ+) reaction are performed using the time-dependent wave packet method. The reaction probabilities, integral cross sections, differential cross sections, and rate constants are calculated and compared with the experimental and theoretical results. Non-adiabatic dynamics results are in good agreement with experimental data. In addition, the non-adiabatic effect in the C+(2P1/2, 3/2) + H2 reaction is significant due to the non-adiabatic results being obviously larger than adiabatic values. The reasonable non-adiabatic dynamics results indicate that present diabatic PESs can be recommended for any type of dynamics study. [ABSTRACT FROM AUTHOR]

While the linear Pearson correlation coefficient represents a well-established normalized measure to quantify the inter-relation of two stochastic variables X and Y, it fails for multidimensional variables, such as Cartesian coordinates. Avoiding any assumption about the underlying data, the mutual information I(X, Y) does account for multidimensional correlations. However, unlike the normalized Pearson correlation, it has no upper bound (I ∈ [0, ∞)), i.e., it is not clear if say, I = 0.4 corresponds to a low or a high correlation. Moreover, the mutual information (MI) involves the estimation of high-dimensional probability densities (e.g., six-dimensional for Cartesian coordinates), which requires a k nearest-neighbor algorithm, such as the estimator by Kraskov et al. [Phys. Rev. E 69, 066138 (2004)]. As existing methods to normalize the MI cannot be used in connection with this estimator, a new approach is presented, which uses an entropy estimation method that is invariant under variable transformations. The algorithm is numerically efficient and does not require more effort than the calculation of the (un-normalized) MI. After validating the method by applying it to various toy models, the normalized MI between the Cα-coordinates of T4 lysozyme is considered and compared to a correlation analysis of inter-residue contacts. [ABSTRACT FROM AUTHOR]

We introduce a general definition of a quantum committor in order to clarify reaction mechanisms and facilitate control in processes where coherent effects are important. With a quantum committor, we generalize the notion of a transition state to quantum superpositions and quantify the effect of interference on the progress of the reaction. The formalism is applicable to any linear quantum master equation supporting metastability for which absorbing boundary conditions designating the reactant and product states can be applied. We use this formalism to determine the dependence of the quantum transition state on coherences in a polaritonic system and optimize the initialization state of a conical intersection model to control reactive outcomes, achieving yields of the desired state approaching 100%. In addition to providing a practical tool, the quantum committor provides a conceptual framework for understanding reactions in cases when classical intuitions fail. [ABSTRACT FROM AUTHOR]

We propose a theoretical approach to estimate the permeability coefficients of substrates (permeants) for crossing membranes from donor (D) phase to acceptor (A) phase by means of molecular dynamics (MD) simulation. A fundamental aspect of our approach involves reformulating the returning probability (RP) theory, a rigorous bimolecular reaction theory, to describe permeation phenomena. This reformulation relies on the parallelism between permeation and bimolecular reaction processes. In the present method, the permeability coefficient is represented in terms of the thermodynamic and kinetic quantities for the reactive (R) phase that exists within the inner region of a membrane. One can evaluate these quantities using multiple MD trajectories starting from phase R. We apply the RP theory to the permeation of ethanol and methylamine at different concentrations (infinitely dilute and 1 mol % conditions of permeants). Under the 1 mol% condition, the present method yields a larger permeability coefficient for ethanol (0.12 ± 0.01 cm s−1) than for methylamine (0.069 ± 0.006 cm s−1), while the values of the permeability coefficient are satisfactorily close to those obtained from the brute-force MD simulations (0.18 ± 0.03 and 0.052 ± 0.005 cm s−1 for ethanol and methylamine, respectively). Moreover, upon analyzing the thermodynamic and kinetic contributions to the permeability, we clarify that a higher concentration dependency of permeability for ethanol, as compared to methylamine, arises from the sensitive nature of ethanol's free-energy barrier within the inner region of the membrane against ethanol concentration. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to compare the maximum and rapid force production of Spanish football players and explore the differences between age group and level of competition. Methods: A cross-sectional study was developed to evaluate the peak force (PF), relative PF, and rate of force development over 250 ms (RFD0−250) during the isometric midthigh pull between groups of football players based on age group (senior vs junior) and level of competition (national vs regional). Using a portable isometric rig, 111 football players performed 2 isometric midthigh-pull trials on a force plate. Two-way analysis of variance with Bonferroni post hoc correction was applied, and statistical significance was set at P ≤.05. The PF, relative PF, and RFD0−250 0, 25, 50, 75, and 100 percentiles were also calculated and descriptively reported, separated by age group and level of competition. Results: The analysis of variance revealed a significant main effect of the level of competition for the PF (P <.001), relative PF (P =.003), and RFD0−250 (P <.001). There was a significant main effect of age group for the PF (P <.001). There was a significant interaction effect of the age group × level of competition for relative PF (P =.014). National players were stronger than regional players on the PF and RFD0−250 (P <.001). Senior players were stronger than junior players for the PF (P <.001). Conclusions: Maximum and rapid force production are crucial for Spanish football players as they progress in both level of competition and age group. Practitioners should encourage young football players to prioritize strength development to improve their athletic performance. [ABSTRACT FROM AUTHOR]

Purpose: To assess the survival of double-crown-retained implant-and-tooth-supported removable partial dentures (DCR-ITSRPDs), evaluate abutment survival, and identify first aftercare measures. Materials and Methods: The influence of various factors on the survival of the DCR-ITSRPDs and the abutments were observed in this retrospective and clinical follow-up study using the Kaplan-Meier estimate. In addition, the first-required aftercare measure for each prosthesis was evaluated. Results: In total, 47 DCR-ITSRPDs were investigated (mean observation: 4.3 ± 3.8 years; max: 14.3 years), 3 of which (6.4%) had to be replaced. The survival probability for DCR-ITSRPDs was 100% at 5 years and 75% at 10 years. A total of 297 abutments (120 natural teeth and 177 dental implants) were observed, 22 of which (7.4%; 6 teeth and 16 implants) failed. The survival probability for teeth was 90.2% at the 5- and 10-year mark; for dental implants, it was 90.4% at 5 years and 76.3% at 10 years. Conclusions: DCR-ITSRPDs are a successful and durable treatment option for patients with substantially reduced residual dentitions. Both prostheses and abutments show good survival times after 5 and 10 years in function. The patient-associated factors tested showed no influence on the survival of DCR-ITSRPDs and abutments. Peri-implant infection was the decisive factor for abutment loss; therefore, regular dental prophylaxis and examinations are of major importance. [ABSTRACT FROM AUTHOR]

Several types of dynamics at stationarity can be described in terms of a Markov jump process among a finite number N of representative sites. Before dealing with the dynamical aspects, one basic problem consists in expressing the a priori steady-state occupation probabilities of the sites. In particular, one wishes to go beyond the mere black-box computational tools and find expressions in which the jump rate constants appear explicitly, therefore allowing for a potential design/control of the network. For strongly connected networks admitting a unique stationary state with all sites populated, here we express the occupation probabilities in terms of a formula that involves powers of the transition rate matrix up to order N − 1. We also provide an expression of the derivatives with respect to the jump rate constants, possibly useful in sensitivity analysis frameworks. Although we refer to dynamics in (bio)chemical networks at thermal equilibrium or under nonequilibrium steady-state conditions, the results are valid for any Markov jump process under the same assumptions. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to cross-validate a recently proposed equation for the prediction of maximal oxygen uptake ( V ˙ O 2 max) in cycling exercise by using the average power output normalized by the body mass from a 5-minute time trial (RPO5-min) as the independent variable. Further, the study aimed to update the predictive equation using Bayesian informative prior distributions and meta-analysis. Methods: On different days, 49 male cyclists performed an incremental graded exercise test until exhaustion and a 5-minute time trial on a stationary cycle ergometer. We compared the actual V ˙ O 2 max with the predicted value obtained from the RPO5-min, using a modified Bayesian Bland–Altman agreement analysis. In addition, this study updated the data on the linear regression between V ˙ O 2 max and RPO5-min, by incorporating information from a previous study as a Bayesian informative prior distribution or via meta-analysis. Results: On average, the predicted V ˙ O 2 max using RPO5-min underestimated the actual V ˙ O 2 max by −6.6 mL·kg–1·min–1 (95% credible interval, −8.6 to −4.7 mL·kg–1·min–1). The lower and upper 95% limits of agreement were −17.2 (−22.7 to −12.3) and 3.8 (−1.0 to 9.5) mL·kg–1·min–1, respectively. When the current study's data were analyzed using the previously published data as a Bayesian informative prior distribution, the accuracy of predicting sample means was found to be better when compared with the data combined via meta-analyses. Conclusions: The proposed equation presented systematic bias in our sample, in which the prediction underestimated the actual V ˙ O 2 max. We provide an updated equation using the previous one as the prior distribution, which could be generalized to a greater audience of cyclists. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the peak performance characteristics of the world top-8 swimmers and the key factors involved in the journey toward achieving better peak performance. Methods: The results of the world top-8 swimmers from 2001 to 2022 were collected from the World Aquatics performance database. Progression to peak performance was tracked with individual quadratic trajectories (1191 cases). Utilizing k-means clustering to group competitive feature variables, this study investigated key developmental factors through a binary logistic regression model, using the odds ratio (OR) to represent whether a factor was favorable (OR > 1) or unfavorable (OR < 1). Results: Significant differences (P <.001) in the peak age between men (23.54/3.80) and women (22.31/4.60) were noticed, while no significant differences (P >.05) in the peak-performance window for both sexes appeared. Peak performance occurred at later ages for the sprint for both sexes, and women had a longer duration in peak-performance window for sprint (P <.05). Peak-performance occurred at later ages for the breaststroke and butterfly for both sexes (P <.05). Binary logistic regression revealed that high first-participation performance (OR = 1.502), high major-competition performance (OR = 4.165), early first-major-competition age (OR = 1.441), participation frequency above 4 times/year in both phase 2 (4.3–8.0 times/y, OR = 3.940; 8.1–20.0 times/y, OR = 5.122) and phase 3 (4.1–7.5 times/y: OR = 5.548; 7.7–15.0 times/y: OR = 7.526), and a career length of 10 years or more (10–15 y, OR = 2.102; 16–31 y, OR = 3.480) were favorable factors for achieving better peak performance. Conclusions: Peak performance characteristics varied across sex, swimming stroke, and race distance in the world top-8 swimmers. Meanwhile, the research indicated that certain specific developmental factors were key conditions for the world top-8 swimmers to achieve better peak performance in the future. [ABSTRACT FROM AUTHOR]

This study focuses on the stochastic modelling and analysis of a serial production network consisting of two manufacturing stations operating under a make-to-stock inventory policy. The outcome is a single type of product and every manufacturing station includes a machine and an output buffer. Both machines are gradually deteriorating during their operation. Deterioration results in a reduced production rate. Continuous-time Markov chain was used to model all the possible states the network transits over time due to the occurrence of certain events, such as client arrival, deterioration failure, production or repair completion. The structure of the Markov chain was thoroughly studied providing useful information, supporting the effort of numerical solving to determine the steady-state probabilities enabling the calculation of useful performance metrics like equipment availability, down time, idle time, utilisation and average inventory. Through a series of numerical experiments, the behaviour of the serial production network was examined while alternating its parameters. Interesting conclusions emerged regarding the factors affecting the operation of such production systems subjected to gradual deterioration. [ABSTRACT FROM AUTHOR]

Purpose: This study analyzed the sequences of actions in professional men and women padel players to identify common game patterns. Methods: The sample comprised 17,557 stroke-by-stroke actions (N = 1640 rallies) of the championship World Padel Tour. Multistep Markov chains were used to calculate the conditional probabilities of occurrence of actions during the rally. Results: Results revealed that men's and women's padel is mainly defined by 36 patterns constituting 55% and 63% of all actions in the game, respectively, with the 10 most common sequences accounting for 42% to 45% of the game. There were recurrent technical–tactical actions with specific offensive and defensive functions that were constantly reiterated during the rallies. In men, the use of smash, volley, bandeja, direct, back wall, back-wall lobs, and direct lobs followed a foreseeable pattern up to 8 lags, whereas women described predictable interactions for volley, bandeja, direct, lobs, and direct lobs up to 5 lags and for smash and back wall up to 4 lags. Conclusions: The ability of padel players to recall these patterns and enhance their anticipation skills may potentially improve their performance. These findings contribute to a better knowledge of professional padel game dynamics while providing coaches and players with useful information to optimize training and decision-making strategies. [ABSTRACT FROM AUTHOR]

The paper presents an analytical model for travel time evaluation in double-deep, triple-deep, quadruple-deep and fivefold-deep tier-captive shuttle-based storage and retrieval system (SBS/RS). Under the assumption of the deepest location rule for the storage process and the nearest neighbour rule for the retrieval process, the expressions for single-command and dual-command cycle times of the shuttle vehicle and elevator are developed, from which the SBS/RS performance can be estimated. The model based on the probability theory enables the evaluation of all individual times that make up the cycle times and assessment of the average number of totes relocated during a retrieval process. Special attention is devoted to the modelling of the relocation of totes which block access to the requested tote during the retrieval process. The validity of the analytical model is examined via the developed simulation model. The given case study shows that the proposed analytical travel time model results match the results of the simulation model. The presented modelling strategy could be applied to bigger system racking depths following the same modelling logic. [ABSTRACT FROM AUTHOR]

We spell out the paradigm of exact conditioning as an intuitive and powerful way of conditioning on observations in probabilistic programs. This is contrasted with likelihood-based scoring known from languages such as Stan. We study exact conditioning in the cases of discrete and Gaussian probability, presenting prototypical languages for each case and giving semantics to them. We make use of categorical probability (namely Markov and CD categories) to give a general account of exact conditioning, which avoids limits and measure theory, instead focusing on restructuring dataflow and program equations. The correspondence between such categories and a class of programming languages is made precise by defining the internal language of a CD category. [ABSTRACT FROM AUTHOR]

Purpose: As a multidisciplined combat sport, relationships between external and internal training loads and intensities of mixed martial arts (MMA) have not been described. The aim of this study was to determine the external loads and intensities of MMA training categories and their relationship to internal loads and intensities. Methods: Twenty MMA athletes (age = 23.3 [5.3] y, mass = 72.1 [7.2] kg, stature = 171.5 [8.4] cm) were observed for 2 consecutive weeks. Internal load and intensity (session rating of perceived exertion [sRPE]) were calculated using the Foster RPE for the session overall (sRPE-training load [TL]) and segmented RPE (segRPE-TL) for each training category: warm-up, striking drills, wrestling drills, Brazilian jiujitsu (BJJ) drills, striking sparring, wrestling sparring, BJJ sparring, and MMA sparring. External load and intensity were measured via Catapult OptimEye S5 for the full duration of each session using accumulated Playerload (PLdACC) and PLdACC per minute (PLdACC·min−1). Differences in loads between categories and days were assessed via Bayesian analysis of variance (BF10 ≥ 3). Predictive relationships between internal and external variables were calculated using Bayesian regression. Results: Session overall sRPE-TL = 448.6 (191.1) arbitrary units (AU); PLdACC = 310.6 (112) AU. Category segRPE-TL range = 33.8 (22.6) AU (warm-up) to 122.8 (54.6) AU (BJJ drills). Category PLdACC range = 44 (36.3) AU (warm-up) to 125 (58.8) AU (MMA sparring). Neither sRPE-TL nor PLdACC changed between days. PLdACC was different between categories. Evidence for regressions was strong-decisive except for BJJ drills (BF10 = 7, moderate). R2 range =.50 to.77, except for warm-up (R2 =.17), BJJ drills (R2 =.27), BJJ sparring (R2 =.49), and session overall (R2 =.13). Conclusions: While MMA training categories may be differentiated in terms of external load, overall session external load does not change within or between weeks. Resultant regression equations may be used to appropriately plan MMA technical/tactical training loads. [ABSTRACT FROM AUTHOR]

In response to a financial crisis, many organizations adjust their pay systems to reduce labor costs. In this research, we focus on the use of delayed pay (the postponement of employees' contractual compensation) and examine its effect on employee voluntary turnover outcomes. In a field study (Study 1) with data collected from the executive managers of 129 Chinese hotels experiencing a financial crisis caused by coronavirus disease 2019 (COVID‐19), we find a positive relationship between delayed pay and the voluntary turnover rate at the organizational level. In addition, this relationship becomes weaker when delayed pay consists of a larger proportion of pay‐for‐performance (PFP). We then conduct an experiment (Study 2) to extend our theoretical framework to the individual level, establish causality, and examine the underlying mechanism. The results show that the perceived negative instrumentality of stay (i.e., expected economic losses associated with staying in an organization) explains why individuals intend to leave organizations adopting delayed base pay but not delayed PFP. We further replicate these findings in a critical incident technique study (Study 3). We also discuss the theoretical and practical implications of these findings. [ABSTRACT FROM AUTHOR]

The probability of inserting, without overlap, a hard spherical particle of diameter σ in a hard-sphere fluid of diameter σ0 and packing fraction η determines its excess chemical potential at infinite dilution, μex(σ, η). In our previous work [R. L. Davidchack and B. B. Laird, J. Chem. Phys. 157, 074701 (2022)], we used Widom's particle insertion method within molecular dynamics simulations to obtain high precision results for μex(σ, η) with σ/σ0 ≤ 4 and η ≤ 0.5. In the current work, we investigate the behavior of this quantity at small σ. In particular, using the inclusion-exclusion principle, we relate the insertion probability to the hard-sphere fluid distribution functions and thus derive the higher-order terms in the Taylor expansion of μex(σ, η) at σ = 0. We also use direct evaluation of the excluded volume for pairs and triplets of hard spheres to obtain simulation results for μex(σ, η) at σ/σ0 ≤ 0.2247 that are of much higher precision than those obtained earlier with Widom's method. These results allow us to improve the quality of the small-σ correction in the empirical expression for μex(σ, η) presented in our previous work. [ABSTRACT FROM AUTHOR]

The three body fragmentation of methane dication has been studied using the technique of cold target recoil ion momentum spectroscopy. The process is initiated by impact of energetic Ar9+ ions on neutral methane and the data is subsequently collected in coincidence with Ar8+ projectile. By analysing the dissociation channels leading to (H + H+ + CH 2 + ) and (H + H 2 + + CH+) fragments, it is concluded that these fragments are formed in a sequential manner via formation of molecular intermediates CH 3 + and CH 2 + respectively. It is shown that these molecular intermediates carry a few eVs as their internal energies, part of which is released when they emit an H-atom with the open possibility that the final detected fragments may still be internally excited. This was accomplished by analysing the two-steps of the sequential process in their own native frames. For a molecular system having three-dimensional structure, our results prove to be an ideal example to highlight the importance of using native frames for correct interpretation of the obtained results. Our results indicate that the dissociation of methane dication can be a major source of production of H-atoms in addition to H+ fragments with the probability of the two being of similar order. [ABSTRACT FROM AUTHOR]

In this paper, we examine a supply chain consisting of a supplier with capital constraint and multiple retailers with no working capital. The retailers can get either trade credit from the supplier or loan from banks. All the retailers are differentiated by their credit scores, which measure the possibility that they default. We show that when the retailer's default probability is high compared with the marginal cost, the retailer cannot get financial support. If the retailers only get money from banks, the more reliable a retailer is, the higher the wholesale price the supplier may charge him. We also find out that the supplier has the motivation to provide trade credit even when the retailers can get money from banks. And no matter where the retailers get money from, when the initial capital is a little insufficient, the supplier will reduce the quantity of the products provided to all retailers. As the initial capital becomes less, the supplier will cut off all the supply to the lowest-score retailer first no matter whether the supplier undertakes the default risk or not. In other words, when the retailers are heterogeneous, for supplier, it is not always the more retailers, the better. [ABSTRACT FROM AUTHOR]

The returning probability (RP) theory, a rigorous diffusion-influenced reaction theory, enables us to analyze the binding process systematically in terms of thermodynamics and kinetics using molecular dynamics (MD) simulations. Recently, the theory was extended to atomistically describe binding processes by adopting the host–guest interaction energy as the reaction coordinate. The binding rate constants can be estimated by computing the thermodynamic and kinetic properties of the reactive state existing in the binding processes. Here, we propose a methodology based on the RP theory in conjunction with the energy representation theory of solution, applicable to complex binding phenomena, such as protein–ligand binding. The derived scheme of calculating the equilibrium constant between the reactive and dissociate states, required in the RP theory, can be used for arbitrary types of reactive states. We apply the present method to the bindings of small fragment molecules [4-hydroxy-2-butanone (BUT) and methyl methylthiomethyl sulphoxide (DSS)] to FK506 binding protein (FKBP) in an aqueous solution. Estimated binding rate constants are consistent with those obtained from long-timescale MD simulations. Furthermore, by decomposing the rate constants to the thermodynamic and kinetic contributions, we clarify that the higher thermodynamic stability of the reactive state for DSS causes the faster binding kinetics compared with BUT. [ABSTRACT FROM AUTHOR]

Ultrafast spectroscopy is a powerful technique that utilizes short pulses on the femtosecond time scale to generate and probe coherent responses in molecular systems. While the specific ultrafast methodologies vary, the most common data analysis tools rely on discrete Fourier transformation for recovering coherences that report on electronic or vibrational states and multi-exponential fitting for probing population dynamics, such as excited-state relaxation. These analysis tools are widely used due to their perceived reliability in estimating frequencies and decay rates. Here, we demonstrate that such "black box" methods for parameter estimation often lead to inaccurate results even in the absence of noise. To address this issue, we propose an alternative approach based on Bayes probability theory that simultaneously accounts for both population and coherence contributions to the signal. This Bayesian inference method offers accurate parameter estimations across a broad range of experimental conditions, including scenarios with high noise and data truncation. In contrast to traditional methods, Bayesian inference incorporates prior information about the measured signal and noise, leading to improved accuracy. Moreover, it provides estimator error bounds, enabling a systematic statistical framework for interpreting confidence in the results. By employing Bayesian inference, all parameters of a realistic model system may be accurately recovered, even in extremely challenging scenarios where Fourier and multi-exponential fitting methods fail. This approach offers a more reliable and comprehensive analysis tool for time-resolved coherent spectroscopy, enhancing our understanding of molecular systems and enabling a better interpretation of experimental data. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to determine the effects of a field-based priming session on perceptual, physiological, and performance responses in female rugby sevens athletes. Methods: Thirteen highly trained female rugby sevens players (age: 20.7 [2.0] y; height: 169.3 [4.8] cm; weight: 68.8 [7.9] kg) completed either a 20-minute field-based priming session or a control condition. Perceptual, physiological, and performance variables were collected at baseline (PRE) and 5 (POST5), 30 (POST30), and 120 minutes (POST120) postintervention. Data were analyzed using Bayesian mixed effects models. Results: The priming protocol had a larger increase in mental readiness (maximum a posteriori [MAP] = 20, 95% high-density intervals [HDI] = −4 to 42, probability of direction [PD]% = 95, % in region of practical equivalence [ROPE] = 9.7), physical readiness (MAP = 20.1, 95% HDI = −4.6 to 42.1, PD% = 93, % in ROPE = 10.6), and testosterone (MAP = 14.9, 95% HDI = 0.5 to 27.7, PD% = 98, % in ROPE = 5.6) than the control POST30. Cognitive performance decreased POST120 in the priming condition for congruent (MAP = 0.02, 95% HDI = −0.06 to 0.00, PD% = 95, % in ROPE = 6.4) and incongruent tasks (MAP = 0.00, 95% HDI = −0.07 to 0.00, PD% = 98, % in ROPE = 3.2) when compared with the control. Conclusions: Perceptual and physiological markers improved POST30 in the priming condition. Findings indicate that perceptual and physiological responses to priming were not coupled with performance improvements. Priming was not accompanied by perceptual, physiological, or performance improvements at POST120. [ABSTRACT FROM AUTHOR]

In this paper, a novel decentralized adaptive state‐feedback design method is proposed for large‐scale stochastic nonlinear systems. Different from the existing results, we consider more practical and more general systems, that is, systems with both unknown covariance and time‐varying powers. When dealing with the unknown time‐varying covariance, we do not need to know its bound, but use the estimator to design an adaptive law function. Then, a new adaptive controller is constructed with the backstepping method to ensure that the closed‐loop system is globally stable in probability, and that the states are regulated to the origin almost surely. Finally, a simulation example is given to illustrate the effectiveness of the design scheme. [ABSTRACT FROM AUTHOR]

High Efficiency Video Coding (HEVC) offers superior compression rates, but its adoption introduces increased coding complexity due to its reliance on a recursive quad-tree for partitioning frames into varying block sizes. This quad-tree process is a central feature in upcoming video coding standards. Our paper presents a novel framework, SVG-CNN, which integrates three shallow Convolutional Neural Networks (CNNs) inspired by VGGNet. Each CNN is specifically designed for individual quad-tree levels to predict the Code Unit (CU) partition in HEVC, leading to reduced intra-frame coding time. SVG-CNN has an inherent capability for early terminations, leveraging sequential CNN feeding based on quad-tree level probabilities. This provides a mechanism to halt processes when further refinement is seemed unlikely. Enhancing the model's efficacy, we have crafted three specialized datasets, each focusing on distinct quad-tree levels and quantization parameter (QP) contexts. This allows each CNN within our framework to undergo targeted training, establishing a cutting-edge training methodology. Our study shows that performance, in terms of accuracy and F1 metrics, is highly dependent on QP settings, with lower QPs yielding better results, and higher QPs diminishing performance due to potential loss of critical features. To enhance our model, we tackled hyperparameter selection and CU split threshold determination for HEVC prediction. We utilized Grid Search Cross-Validation for the former and assessed multiple thresholds across selected videos for the latter. The model has a moderate complexity with over 328,000 parameters across 18 layers, which ensures memory efficiency. It boasts a swift prediction time of 0.05 ms and reduces HEVC encoding time by 61.64%, while slightly improving the bitrate-distortion performance by -0.24% BDBR, indicating better compression without notable PSNR loss. Significantly, our approach outperforms other CNN-based quad-tree partitioning methods that reduce HEVC coding complexity but sacrifice compression performance. [ABSTRACT FROM AUTHOR]

Video security has emerged as a critical study issue in multimedia security in recent years as videos are the most effective and widely used multimedia format. They immediately establish a connection with users. It is necessary to prevent this sensitive information from being stolen or destroyed in various domains, including the military, finance, and education. It can be achieved by either hiding its significance, turning it into a secret code through encryption, or doing both simultaneously. Because video data is generated, transmitting it securely is challenging, and there is resource wastage of memory, processing, and bandwidth. Users must spend a lot of time and effort scanning through this enormous amount of video information in search of the required information. Therefore, a secure keyframes-based generic video summarization (VS) model is proposed to generate a secure video summary. First, Secret Keyframes (SKs) are extracted from the video through proposed Probability VS (PBVS) and Extended (E-PBVS). Second, multi-secret image sharing is provided to the SKs by the proposed EBEMSS (Enhanced Blockwise Encryption based Multi Secret Sharing) scheme, which uses a polynomial congruence concept for keyframe security. The proposed model E-PBVS achieved an average F-score of 0.76 and 0.81 on two benchmark (OV and YT) datasets, respectively, showing its effectiveness in producing informative video summaries. Additionally, EBEMSS outperforms the other related security models. The proposed model outperforms with generated summary and security compared to other keyframe-based VS and MSS techniques. [ABSTRACT FROM AUTHOR]

We present a trial design for sequential multiple assignment randomized trials (SMARTs) that use a tailoring function instead of a binary tailoring variable allowing for simultaneous development of the tailoring variable and estimation of dynamic treatment regimens (DTRs). We apply methods for developing DTRs from observational data: tree‐based regression learning and Q‐learning. We compare this to a balanced randomized SMART with equal re‐randomization probabilities and a typical SMART design where re‐randomization depends on a binary tailoring variable and DTRs are analyzed with weighted and replicated regression. This project addresses a gap in clinical trial methodology by presenting SMARTs where second stage treatment is based on a continuous outcome removing the need for a binary tailoring variable. We demonstrate that data from a SMART using a tailoring function can be used to efficiently estimate DTRs and is more flexible under varying scenarios than a SMART using a tailoring variable. [ABSTRACT FROM AUTHOR]

In order to reduce the probability of leakage and improve detection accuracy, multiple radar equipment is required to perform multiple detections on the same airspace. Due to the overlap of airspace, there are multiple local tracks reported by various radar equipment that belong to the same target. The local tracks reported by each radar require track fusion to form a system track, and track association is a prerequisite for track fusion. This paper proposes a multi-target and multi-sensor track association analysis method, which can distinguish whether local tracks come from the same target and associate local tracks with the same target, providing conditions for track fusion to form system tracks. This method divides track association into two steps: Coarse association and fine association, which greatly improves the accuracy of track association. [ABSTRACT FROM AUTHOR]

This article considers wavelet estimations for density functions in Besov spaces based on negatively dependent biased random samples. More precisely, wavelet estimators are defined and their L p (1 ≤ p < ∞) convergence rates are provided when the parameter μ is known and unknown, respectively. [ABSTRACT FROM AUTHOR]

Network Intrusion Detection Systems (NIDSs) have been proposed in the literature as security tools for detecting anomalous and intrusive network data traffic. However, the existing NIDS frameworks are computation-intensive, thereby making them unsuitable for deployment in resource-constrained networks with limited computational capabilities. This paper aims to address this issue by proposing computationally efficient NIDS framework for detecting anomalous data traffic in resource-constrained networks. The proposed NIDS framework uses an ensemble-based classifier model comprising multiple classifiers, which enables it to achieve high accuracy and detection rate across a wide range of low-footprint and stealth network attacks. The proposed framework also uses feature scaling and dimensionality reduction techniques to minimize the overall computational overhead. The proposed framework consists of two stages. In the first stage, four distinct base-level classifiers are utilized. The classification probabilities of the first stage are used in the modified meta-level classifier. The modified meta-level classifier is trained on the class probabilities of the base-level classifiers combined using a novel proposed probability function. The performance of the proposed NIDS framework is evaluated on a proprietary testbed dataset and two benchmark datasets namely CICIDS-2017 and UNSW-NB15. The results reveal that the proposed NIDS framework provides better performance than the existing NIDS frameworks in terms of false positive rate, despite using a significantly lower number of input features for its analysis. [ABSTRACT FROM AUTHOR]

This study examines the relationship between Right-to-Work (RTW) laws and creativity. Using data from the Kickstarter crowdfunding platform for the period 2010–2019, we find that the number of projects launched, the probability of success, the average amount of capital pledged, and the average number of backers are all significantly higher in states without RTW laws than in states with RTW laws. This finding holds for both Art- and Product- focused projects. Thus, our findings are consistent with the view that states without RTW laws provide a better outlet for creativity than states with RTW laws. [ABSTRACT FROM AUTHOR]

Background: Postoperative time to extubation plays a role in prognosis after heart valve surgery; however, its exact impact has not been clarified. This study compared the postoperative outcomes of minimally invasive surgery and conventional sternotomy, focusing on early extubation and factors influencing prolonged mechanical ventilation. Methods: Data from 744 patients who underwent heart valve surgery at the Zhejiang Provincial People's Hospital between August 2019 and June 2022 were retrospectively analyzed. The outcomes in patients who underwent conventional median sternotomy (MS) and minimally invasive (MI) video-assisted thoracoscopic surgery were compared using inverse probability of treatment weighting (IPTW) and Kaplan–Meier curves. Clinical data, including surgical data, postoperative cardiac function, postoperative complications, and intensive care monitoring data, were analyzed. Results: After propensity score matching and IPTW, 196 cases of conventional MS were compared with 196 cases of MI video-assisted thoracoscopic surgery. Compared to patients in the conventional MS group, those in the MI video-assisted thoracoscopic surgery group in the matched cohort had a higher early postoperative extubation rate (P < 0.01), reduced incidence of postoperative pleural effusion (P < 0.05), significantly shorter length of stay in the intensive care unit (P < 0.01), shorter overall length of hospital stay (P < 0.01), and lower total cost of hospitalization (P < 0.01). Conclusions: Successful early tracheal extubation is important for the intensive care management of patients after heart valve surgery. The advantages of MI video-assisted thoracoscopic surgery over conventional MS include significant reductions in the duration of use of mechanical ventilation support, reduced length of intensive care unit stay, reduced total length of hospitalization, and a favorable patient recovery rate. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) hold great promise in summarizing medical evidence. Most recent studies focus on the application of proprietary LLMs. Using proprietary LLMs introduces multiple risk factors, including a lack of transparency and vendor dependency. While open-source LLMs allow better transparency and customization, their performance falls short compared to the proprietary ones. In this study, we investigated to what extent fine-tuning open-source LLMs can further improve their performance. Utilizing a benchmark dataset, MedReview, consisting of 8161 pairs of systematic reviews and summaries, we fine-tuned three broadly-used, open-sourced LLMs, namely PRIMERA, LongT5, and Llama-2. Overall, the performance of open-source models was all improved after fine-tuning. The performance of fine-tuned LongT5 is close to GPT-3.5 with zero-shot settings. Furthermore, smaller fine-tuned models sometimes even demonstrated superior performance compared to larger zero-shot models. The above trends of improvement were manifested in both a human evaluation and a larger-scale GPT4-simulated evaluation. [ABSTRACT FROM AUTHOR]

The Fezouata Biota (Morocco) is a Burgess Shale-type (BST) assemblage that provides a wealth of information on Early Ordovician ecosystems. Much work has been done to compare the preservation of the Fezouata Biota to other BSTs. However, studies investigating preservation variations within the Fezouata Biota are rare. Here, we use probabilities to investigate the preservation of various ecological categories of Fezouata eumetazoans. Complex taphonomic processes and phylum-specific constraints have led to the better preservation of predators/scavengers in this biota. However, no differences in preservation are observed between vagile and sessile taxa. Importantly, Tremadocian taxa are better preserved than Floian ones. As such, this study highlights the gradual closure of the BST window of preservation in the Zagora region of Morocco and constitutes a benchmark for future palaeoecological and evolutionary studies on the Fezouata Biota. [ABSTRACT FROM AUTHOR]

Background: U.S. firearm sales surged during the COVID-19 pandemic, with many purchases by first-time firearm owners. The 2023 National Survey of Gun Policy sought to understand the public health implications of this surge by comparing the purchasing motivations and firearm policy views of pandemic-era first-time purchasers to prior gun owners. Methods: We fielded a nationally representative public opinion survey of U.S. adults (n = 3096) from 1/4/23 to 2/6/23. We oversampled for gun owners and Black, Hispanic, and Asian Americans. Survey weights were applied to generate representative estimates. New gun owners were identified through affirmative responses to: "Have you bought any guns since January 1, 2020?" and "Did you buy your first gun after January 1, 2020?" Recent purchasers were additionally asked whether concerns of 1) political or 2) racial violence motivated their purchase. Purchase motivations and gun policy support were examined among new and prior gun owners (n = 1002) and compared using logistic regression and predictive probabilities. Results: Overall, 11% of respondents reported purchasing a gun since 1/1/20, 35% for the first time. Among recent purchasers, larger proportions of Democrat, Black, Asian, and Hispanic respondents were new gun owners than Republican or white respondents. Compared to prior owners, odds were 4.5-times higher that new gun owners' recent purchase was motivated by racial violence and 3.2-times higher for political violence. Majority support was found for protective gun policies, with few differences by purchase recency or motivations. The only policy for which support by new and prior gun owners differed significantly was the permit-to-purchase policy (76% v. 63%, respectively). Similarly, few significant differences in support were observed when stratifying by purchase motivation. Notably, both those who reported recent purchase motivations of racial violence and of political violence expressed significantly higher support for a "stand-your-ground" policy compared to those who did not report such motivations. Conclusions: Racial and political violence appear to be larger concerns among new gun owners, motivating purchasing among demographic groups with traditionally lower gun ownership rates. These findings suggest a need for safety assurances amid racial and political tensions and growing gun ownership. Gun owners' support for such policies remains strong. [ABSTRACT FROM AUTHOR]

A computational methodology, founded on chemical concepts, is presented for interpreting the role of nuclear motion in the electron transport through single‐molecule junctions (SMJ) using many‐electron ab initio quantum chemical calculations. Within this approach the many‐electron states of the system, computed at the SOS‐ADC(2) level, are followed along the individual normal modes of the encapsulated molecules. The inspection of the changes in the partial charge distribution of the many‐electron states allows the quantification of the electron transport and the estimation of transmission probabilities. This analysis improves the understanding of the relationship between internal motions and electron transport. Two SMJ model systems are studied for validation purposes, constructed from a conductor (BDA, benzene‐1,4‐diamine) and an insulator molecule (DABCO, 1,4‐diazabicyclo[2.2.2]octane). The trends of the resulting transmission probabilities are in agreement with the experimental observations, demonstrating the capability of the approach to distinguish between conductor and insulator type systems, thereby offering a straightforward and cost‐effective tool for such classifications via quantum chemical calculations. [ABSTRACT FROM AUTHOR]

Background: Brazil is one of the countries with the highest rates of caesarean sections (CS), reaching almost 90% of births in the private sector. A quality improvement project called "Adequate Childbirth Project (PPA)" was conceived to reduce CS in the private sector. This project consisted of four primary components: "Governance", "Participation of Women", "Reorganization of Care" and "Monitoring". This paper aims to evaluate: (1) which specific activities of the PPA had the largest effect on the probability of a woman having a vaginal delivery; (2) which primary component of the PPA had the largest effect on the probability of vaginal delivery and (3) which scenarios combining the implementation of different activities planned in the PPA had a higher effect on the probability of vaginal delivery. Methods: A sample of 12 private hospitals participating in the PPA was evaluated. We used a Bayesian Network (BN) to capture both non-linearities and complex cause-effect relations. The BN integrated knowledge from experts and data from women to estimate 26 model parameters. The PPA was evaluated in 2473 women belonging to groups 1–4 of the Robson classification, who were divided into two groups: those participating or not participating in the PPA. Results: The probability of a woman having a vaginal delivery was 37.7% higher in women participating in the PPA. The most important component of the project that led to an increase in the probability of vaginal delivery was "Reorganization of Care", leading to a 73% probability of vaginal delivery among women in labor. The activity that had the greatest effect on the type of delivery was access to best practices during labor, with a 72% probability of vaginal delivery. Considering the 12 scenarios combining the different activities of the PPA, the best scenarios included: a non-scheduled delivery, access to information about best practices, access to at least 4 best practices during labor and respect of the birth plan, with an 80% probability of vaginal delivery in the best combinations. Conclusion: PPA has been shown to be an effective quality improvement program, increasing the likelihood of vaginal delivery in private Brazilian hospitals. Plain English Summary: Introduction: Brazil boasts one of the highest rates of caesarean sections (CS) globally, with nearly 90% of births in private facilities being delivered via CS. In response, the 'Adequate Childbirth Project – PPA' was launched as a quality improvement initiative aimed at curbing CS rates in private healthcare. Its goal is to improve the quality of childbirth and reduce the number of CS in private healthcare. The project has four main parts: 'Governance', 'Participation of Women', 'Reorganization of Care', and 'Monitoring'. Method: an evaluative study was conducted across 12 private hospitals involved in the PPA, involving 2473 women who were categorized into PPA participants and non-participants. They used a method called a cause-effect network to see which parts of the PPA helped more women have vaginal deliveries. Results: They found that women in the PPA were 37.7% more likely to have a vaginal delivery. Giving women access to good practices during labor and birth was really important. Also, 'Reorganization of Care' was the most important part of the project. It led to a 73% chance of vaginal delivery for women in labor. Conclusion: The PPA is effective in helping more women in private hospitals have vaginal deliveries. This means it's a good program for improving childbirth in Brazil's private hospitals. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) demonstrates various opportunities and risks. Our study explores the trade-off of AI technology, including existential risks. We develop a theory and a Bayesian simulation model in order to explore what is at stake. The study reveals four tangible outcomes: (i) regulating existential risks has a boundary solution of either prohibiting the technology or allowing a laissez-faire regulation. (ii) the degree of 'normal' risks follows a trade-off and is dependent on AI-intensity. (iii) we estimate the probability of 'normal' risks to be between 0.002% to 0.006% over a century. (iv) regulating AI requires a balanced and international approach due to the dynamic risks and its global nature. [ABSTRACT FROM AUTHOR]

This paper addresses the limitations of existing interest forwarding strategies in Named Data Networks (NDN) over Low-power and Lossy Networks (LLNs). While current strategies utilize listening periods to minimize duplicate retransmissions, they suffer from indiscriminately propagating interests across the network, resulting in excessive retransmissions. Conversely, strategies with propagation control often neglect challenges posed by producer mobility. In response, we propose an efficient forwarding strategy that not only mitigates duplicate retransmissions but also governs interest propagation through the integration of probabilities and estimated distances to data producers. Additionally, the strategy adeptly manages producer mobility through judicious flooding control. In contrast to prior studies primarily benchmarking against Blind Flooding (BF) and Deferred Blind Flooding (DBF), our work presents the first comprehensive evaluation of the new forwarding scheme against six established strategies. Through extensive simulations, we demonstrate the superiority of our proposed forwarding solution across key performance metrics, including sent packets, retrieval latency, success rate, and energy consumption in various scenarios. [ABSTRACT FROM AUTHOR]

Background: Allostatic load (AL) is the accumulation of physiological dysregulation attributed to repeated activation of the stress response over a lifetime. We assessed the utility of AL as a prognostic measure for high-risk benign breast biopsy pathology results. Method: Eligible patients were women 18 years or older, with a false-positive outpatient breast biopsy between January and December 2022 at a tertiary academic health center. AL was calculated using 12 variables representing four physiological systems: cardiovascular (pulse rate, systolic and diastolic blood pressures, total cholesterol, high-density lipoprotein, and low-density lipoprotein); metabolic (body mass index, albumin, and hemoglobin A1C); renal (creatinine and estimated glomerular filtration rate); and immune (white blood cell count). Multivariable logistic regression was used to assess the association between AL before biopsy and breast biopsy outcomes controlling for patients' sociodemographics. Results: In total, 170 women were included (mean age, 54.1 ± 12.9 years): 89.4% had benign and 10.6% had high-risk pathologies (radial scar/complex sclerosing lesion, atypical ductal or lobular hyperplasia, flat epithelial atypia, intraductal papilloma, or lobular carcinoma in-situ). A total of 56.5% were White, 24.7% Asian, and 17.1% other races. A total of 32.5% identified as Hispanic. The mean breast cancer risk score using the Tyrer–Cuzick model was 11.9 ± 7.0. In multivariable analysis, with every one unit increase in AL, the probability of high-risk pathology increased by 37% (odds ratio, 1.37; 95% confidence interval, 1.03, 1.81; p = 0.03). No significant association was seen between high-risk pathology and age, ethnicity, breast cancer risk, or area deprivation index. Conclusion: Our findings support that increased AL, a biological marker of stress, is associated with high-risk pathology among patients with false-positive breast biopsy results. [ABSTRACT FROM AUTHOR]

In prevalent cohort studies with follow-up, the time-to-event outcome is subject to left truncation leading to selection bias. For estimation of the distribution of the time to event, conventional methods adjusting for left truncation tend to rely on the quasi-independence assumption that the truncation time and the event time are independent on the observed region. This assumption is violated when there is dependence between the truncation time and the event time, possibly induced by measured covariates. Inverse probability of truncation weighting can be used in this case, but it is sensitive to misspecification of the truncation model. In this work, we apply semiparametric theory to find the efficient influence curve of the expectation of an arbitrarily transformed survival time in the presence of covariate-induced dependent left truncation. We then use it to construct estimators that are shown to enjoy double-robustness properties. Our work represents the first attempt to construct doubly robust estimators in the presence of left truncation, which does not fall under the established framework of coarsened data where doubly robust approaches were developed. We provide technical conditions for the asymptotic properties that appear to not have been carefully examined in the literature for time-to-event data, and study the estimators via extensive simulation. We apply the estimators to two datasets from practice, with different right-censoring patterns. [ABSTRACT FROM AUTHOR]

Direct use of the likelihood function typically produces severely biased estimates when the dimension of the parameter vector is large relative to the effective sample size. With linearly separable data generated from a logistic regression model, the loglikelihood function asymptotes and the maximum likelihood estimator does not exist. We show that an exact analysis for each regression coefficient produces half-infinite confidence sets for some parameters when the data are separable. Such conclusions are not vacuous, but an honest portrayal of the limitations of the data. Finite confidence sets are only achievable when additional, perhaps implicit, assumptions are made. Under a notional double-asymptotic regime in which the dimension of the logistic coefficient vector increases with the sample size, the present paper considers the implications of enforcing a natural constraint on the vector of logistic transformed probabilities. We derive a relationship between the logistic coefficients and a notional parameter obtained as a probability limit of an ordinary least-squares estimator. The latter exists even when the data are separable. Consistency is ascertained under weak conditions on the design matrix. [ABSTRACT FROM AUTHOR]

Objective To determine the safety and efficacy of anifrolumab in patients with systemic lupus erythematosus (SLE) classified based on the Lupus Low Disease Activity State (LLDAS) in real-world clinical practice. Methods This retrospective observational study involved SLE patients who started anifrolumab therapy. The primary end point was the retention rate over 26 weeks after initiating anifrolumab therapy; 45 patients followed up for 12 weeks or longer were analysed in the following groups to determine the safety and efficacy up to week 12 after treatment initiation: (i) non-LLDAS achievement group and (ii) minor flare group. Safety and efficacy were compared between the minor flare group and the standard of care (SoC) group (treated by adding glucocorticoids [GCs] or immunosuppressants) after adjustment with inverse probability of treatment weighting using propensity score (PS-IPTW). Results The retention rate of anifrolumab was 89.7% at week 26.The LLDAS achievement rates at week 12 were 42.9% and 66.7% in the non-LLDAS achievement and minor flare groups, respectively. In both groups, GC doses and SELENA–SLEDAI score significantly decreased. When the anifrolumab group with minor flare was compared with the SoC group or the GC dose increase group, the GC dose and SLEDAI score were significantly lower in the anifrolumab group than in either of the other groups; there was no significant difference in LLDAS achievement. Conclusion At week 26 after initiating anifrolumab therapy, ∼90% of patients remained on therapy. Anifrolumab might lower disease activity without initiating GCs and reduce GC doses, especially in patients who experience minor flares after LLDAS achievement. [ABSTRACT FROM AUTHOR]

The role of coalgebras as well as algebraic groups in non-commutative probability has long been advocated by the school of von Waldenfels and Schürmann. Another algebraic approach was introduced more recently, based on shuffle and pre-Lie calculus, and results in another construction of groups of characters encoding the behavior of states. Comparing the two, the first approach, recast recently in a general categorical language by Manzel and Schürmann, can be seen as largely driven by the theory of universal products, whereas the second construction builds on Hopf algebras and a suitable algebraization of the combinatorics of non-crossing set partitions. Although both address the same phenomena, moving between the two viewpoints is not obvious. We present here an attempt to unify the two approaches by making explicit the Hopf algebraic connections between them. Our presentation, although relying largely on classical ideas as well as results closely related to Manzel and Schürmann's aforementioned work, is nevertheless original on several points and fills a gap in the non-commutative probability literature. In particular, we systematically use the language and techniques of algebraic groups together with shuffle group techniques to prove that two notions of algebraic groups naturally associated with free, respectively, Boolean and monotone, probability theories identify. We also obtain explicit formulas for various Hopf algebraic structures and detail arguments that had been left implicit in the literature. [ABSTRACT FROM AUTHOR]

Today, with the growth of the population and increasing trend in the use of electrical energy, the importance of the reliability and stability of the power grid has increased. The ever-increasing development of the power grid and subsequent blackouts of the power grid can lead to serious problems in the daily life and economy of a country. In addition to economic damages, power losses in the power network can lead to dissatisfaction and decreased consumer confidence in the power grid. This research has been carried out to check the application of the genetic algorithm to calculate reliability indices including SAIFI, SAIDI, etc., and its impact on enhancing the reliability of the standard IEEE 33 and 69 bus distribution networks. Additionally, this study explores the GA effectiveness in minimizing both active and reactive power losses. The simulation results in MATLAB, show the constructive effect of applying the GA, shedding light on its potential to optimize the distribution network reliability and minimize power losses, offering valuable insights for power system optimization and reliability improvement. [ABSTRACT FROM AUTHOR]

Due to intermittent renewable energy and fluctuating load demand, distribution networks with renewable distributed generation (DG) installations are more likely to suffer voltage issues and significant power losses. The performance of conservation voltage regulation (CVR) schemes may be adversely affected by the undesirable voltage profile at specific nodes. This paper aims to reduce power losses in CVR‐implemented networks by optimally planning new renewable DGs without changing the existing ones. A scenario‐based optimal renewable DG planning model is proposed with a novel scenario formation method. The uncertainties of load demand and renewables are captured jointly and formed into a finite number of scenarios based on a multivariate Gaussian mixture model (MultiGMM). The locations and capacities of different types of new renewable DGs are optimally planned for CVR performance improvements on power loss saving by aggregating the operation status and probabilities of the scenarios using mixed‐integer non‐linear programming (MINLP). A time‐series simulation is formulated for accuracy verification. The results of case studies show that the proposed model can significantly reduce power losses, active load demand, and reactive load demand. The accuracy of the planning results can be guaranteed with fewer scenarios compared to a widely used classical scenario‐based planning method. [ABSTRACT FROM AUTHOR]

Shadowed Beaulieu-Xie (SBX) is a composite fading model suitable for an environment with a random number of non-line-of-sight and line-of-sight signals encountered in the wireless communication system. There are many effects that undergo in the wireless channel that may degrade the performance of the system. Diversity is one popular technique to mitigate the effects of fading. Investigation of the influence of various parameters of SBX fading channels on the performance of dual-branch selection combining (SC) diversity receiver is carried out. In this paper, mathematical expressions for the probability density function (PDF) of the output signal-to-noise ratio of dual-SC diversity receiver are calculated for SBX fading channels. Outage probability and average bit error rate (ABER) for different kinds of modulation methods are obtained using the PDF-based method. A unified ABER expression for coherent and non-coherent modulations for dual-SC diversity receivers over SBX fading channels is also derived. The effect of shadowing and fading parameters on the performance of dual-SC diversity receivers is studied. [ABSTRACT FROM AUTHOR]