Search

• l -Theanine is a unique non-protein amino acid found abundantly in tea leaves. • Interest in its potential use as a dietary supplement is growing. • The evidence supporting many popular health claims remains limited. • Caution is warranted regarding the purported health benefits of l -theanine. l -Theanine is a unique non-protein amino acid found abundantly in tea leaves. Interest in its potential use as a dietary supplement has surged recently, especially claims related to promoting relaxation and cognitive enhancement. This review surveys the chemistry, metabolism, and purported biological activities of l -theanine. It is well absorbed from the intestine and can cross the blood-brain barrier. Some studies suggest l -theanine may increase alpha waves in the brain associated with relaxation and selective attention, reduce stress and anxiety, and improve sleep quality, though findings are often inconsistent. Potential neuroprotective and anti-seizure effects have also been reported in animal models. When combined with caffeine, l -theanine may improve cognitive performance, alertness and focus. However, the evidence supporting many health claims remains limited, especially the lack of rigorous human clinical trials. While l -theanine exhibits a good safety profile based on toxicology studies, caution is warranted regarding the purported health benefits, until stronger scientific substantiation emerges. Overall, the mechanisms of action and therapeutic potential of l -theanine require further investigation, given the current interest and increasing popularity of this nutraceutical supplement marketed for brain health and relaxation. In the absence of well-designed and carefully controlled human clinical trials, we would urge caution in the use of l -theanine supplements at pharmacologic doses by the wider population, and believe that the science does not yet match the hype behind this trending supplement for brain health and relaxation. l -Theanine is found naturally in tea leaves. It is well absorbed from the intestine and can cross the blood brain barrier. Putative biological activities include relaxation and cognitive enhancement. The rationale is that l -theanine increases alpha brain waves in the brain, which is associated with relaxation and selective attention. However, human research is scant and more of it is needed to fully understand the mechanisms of action and potential side effects. [Display omitted] [ABSTRACT FROM AUTHOR]

We consider the classic budgeted maximum weight independent set (BMWIS) problem. The input is a graph G = (V , E) , where each vertex v ∈ V has a weight w (v) and a cost c (v) , and a budget B. The goal is to find an independent set S ⊆ V in G such that ∑ v ∈ S c (v) ≤ B , which maximizes the total weight ∑ v ∈ S w (v). Since the problem on general graphs cannot be approximated within ratio | V | 1 − ɛ for any ɛ > 0 , BMWIS has attracted significant attention on graph families for which a maximum weight independent set can be computed in polynomial time. Two notable such graph families are bipartite and perfect graphs. BMWIS is known to be NP-hard on both of these graph families; however, prior to this work, the best possible approximation guarantees for these graphs were wide open. In this paper, we give a tight 2-approximation for BMWIS on perfect graphs and bipartite graphs. In particular, we give a (2 − ɛ) lower bound for BMWIS on bipartite graphs, already for the special case where the budget is replaced by a cardinality constraint, based on the Small Set Expansion Hypothesis (SSEH). For the upper bound, we design a 2-approximation for BMWIS on perfect graphs using a Lagrangian relaxation based technique. Finally, we obtain a tight lower bound for the capacitated maximum weight independent set (CMWIS) problem, the special case of BMWIS where w (v) = c (v) ∀ v ∈ V. We show that CMWIS on bipartite and perfect graphs is unlikely to admit an efficient polynomial-time approximation scheme (EPTAS). Thus, the existing PTAS for CMWIS is essentially the best we can expect. [ABSTRACT FROM AUTHOR]

The complexity of the three-dimensional entry trajectory optimization problem has escalated due to the need to liberalize the angle of attack and bank angle as control variables, thereby enhancing the inherent maneuverability and control capabilities of lifting-body vehicles. The difference-of-convex (DC) properties inherent in the constraints of the problem are exploited in this paper. A DC decomposition approach is utilized to address the nonlinear auxiliary control equations, and the DC relaxation technique is applied to resolve iteration infeasibilities arising from Taylor expansion. The dependence on the initial trajectory is diminished by the implementation of an exact penalty method, thus improving the applicability of the methods. Furthermore, a control variable oscillation suppression mechanism has been constructed to tackle the control variable oscillation issues arising from the relaxation of the angle of attack and bank angle. This mechanism effectively suppresses large jumps in the angle of attack and high-frequency oscillations in the bank angle. Two novel successive DC programming methods are proposed: the successive concave-convex procedure and the successive proximal bundle method, functioning independently of trust-region constraints. Numerical experiments have demonstrated that the two proposed successive DC optimization methods exhibit exceptional performance in accuracy, feasibility, adaptability, and low sensitivity to initial values when applied to solving the three-dimensional entry trajectory optimization problem. [ABSTRACT FROM AUTHOR]

Efficient fire response and the coordination of various fire vehicles are paramount for delivering optimal services and conducting effective rescue operations. This study explores the challenges of cooperative station location and vehicle assignment, focusing on the synergistic dispatch of fire vehicles from multiple stations. It highlights that the response time of the last arriving vehicle, crucial for forming a complete and effective response unit, is a critical determinant in the overall success of fire rescue operations. The primary objective of the model is to minimize the total system cost, encompassing both the capital investment in fire stations and the potential losses from fire incidents. By employing a Lagrangian relaxation technique, the model effectively simplifies the optimization challenge into more manageable sub-problems, thereby enhancing solution accuracy. The robustness and flexibility of the model were tested through simulations in a hypothetical network and a real-world scenario, using data from urban fire services. The results demonstrate the model's scalability and adaptability to different network configurations and operational constraints, showcasing its potential to substantially enhance emergency response efficiency and decision-making in urban fire management. This research makes a significant contribution to emergency response management by providing a validated framework that improves the coordination and effectiveness of fire rescue operations, thereby reducing fire damage and enhancing public safety. [ABSTRACT FROM AUTHOR]

Due to the complex aerodynamic effects, the reentry trajectory optimization problem is highly nonlinear. When using sequential convex programming (SCP) methods to solve it, the iteration solution is difficult to converge. To improve this, we propose a hybrid-order soft trust region-based SCP method. We analyze the penalty effect of typical trust regions. Based on the analysis, we develop a hybrid-order soft trust region combining a small-weight first-order component and a higher-order components. To solve the subproblem reliably and effectively, we equivalently reformulate it as a second-order cone programming (SOCP) form through the relaxation technique. Combined with the line search method, we further design an SCP algorithm with guaranteed convergence under some assumptions. In the numerical simulations, the effectiveness and robustness of the proposed method have been verified using a nominal case and 200 Monte Carlo cases. [ABSTRACT FROM AUTHOR]

Despite cross-sectional population and clinical studies finding individuals with existing mood disorders being adversely impacted by the COVID-19 pandemic, longitudinal studies have not shown a worsening of psychiatric symptoms. In response to these findings, we explored opportunities to engage in positive activities during the pandemic from the perspectives of individuals with mood disorders. A bespoke survey, containing closed and open questions, was sent to participants with mood disorders who were part of the UK Bipolar Disorder Research Network (BDRN). Questions related to experiences of positive impacts of the pandemic, levels of engagement in positive activities and coping strategies. Response rate was 46.4 % (N = 1688). 61.9 % reported positive life changes during the pandemic, with slower pace of life reported most frequently (52.8 %). 47.3 % reported no adverse impact of the pandemic on implementing their usual coping strategies. Activities that respondents most commonly reported the same or greater level of engagement in compared to before the pandemic were avoiding known mood triggers (82.3 %), relaxation techniques (78.8 %) and the ability to maintain set routines (69.4 %). Responder bias may be present and experiences during the pandemic are likely to differ among other clinical and research mood disorders cohorts. Our findings may help to explain why longitudinal studies have not found a worsening of mental health symptoms during the COVID-19 pandemic. Identifying potential facilitators to maintaining mental health have wider applicability, and may help to inform future evidence-based psychoeducation and self-management programmes for mood disorders. • Opportunities to engage in positive activities during the pandemic assessed among 1688 individuals with mood disorders. • 62 % reported positive life changes during the pandemic, including slower pace of life. • Approximately half reported usual coping strategies unaffected or facilitated by pandemic. • Majority reported no adverse impact of the pandemic on level of engagement in positive activities. • Reduced opportunities to engage in positive activities during the pandemic reported by some respondents. [ABSTRACT FROM AUTHOR]

Existing exoatmospheric guidance laws become ineffective when a thrust loss fault (like one or more engines unexpectedly shut down) occurs in a launch vehicle, which makes the nominal orbit unreachable. This paper presents a new abort orbit determination process to determine an abort orbit which the launch vehicle is able to reach. It involves solving at most two optimization problems and the abort orbit may be circular or elliptical. We will present how to transform the nonconvex optimization problems into difference of convex (DC) programming problems which can be solved by existing methods with guaranteed convergence. The main contribution of this paper lies in proposing a relaxation technique to convexify a nonconvex control constraint and the combination of the introduction of new constraints and a relaxation technique to deal with the strict terminal constraints. Validity of the relaxation technique is ensured by theoretical analysis. A unique feature of the transformation process is that the feasible sets defined by both the control constraint and the strict terminal constraints are all enlarged. This brings a critical benefit that the resulting DC programming problems can be very efficiently solved. Thus, an abort orbit determination algorithm, which is based on DC programming, can be designed to very reliably and efficiently determine an abort orbit, which will be demonstrated by numerical examples. • A new concise and practical abort-orbit determination process is proposed. • Relaxation techniques and the introduction of new constraints are properly combined. • Validity of the relaxation techniques are theoretically proved. • An abort orbit can be determined by solving at most two DC programming problems. [ABSTRACT FROM AUTHOR]

Burn patients feel a lot of physiological and mental stress during treatment and rehabilitation which often cause anxiety and body image dissatisfaction. This study aimed to compare the effects of the Benson relaxation technique and nature sounds on pain anxiety and body image in burn-injured patients admitted to a burn intensive care unit (BICU). This single-blind randomized clinical trial studied 60 burn patients allocated into three groups (Benson relaxation, nature sounds, and control) from September 2021 to February 2022. The patients received the intervention for seven consecutive days in person. Burn Specific Pain Anxiety Scale (BSPAS), was completed on the 1st, 4th, and 7th days. The intervention continued for four weeks measuring body image using the Satisfaction with Appearance Scale (SWAP) at the end of the 1st, 3rd, and 5th weeks. Finally, the data were statistically analyzed using the Shapiro–Wilk test, chi-square test, Fisher's exact test, Bonferroni post hoc test, repeated measures ANOVA, Kruskal Wallis test, and Generalize Estimating Equations (GEE). The mean pain anxiety and dissatisfaction with the appearance were high in the three groups in the pretest. On the 7th day after the intervention, the ANOVA showed that the mean pain anxiety decreased significantly in Benson's relaxation and nature sounds groups in three stages (before intervention (S1), after intervention (S2) and immediately after dressing change (S3) (P < 0.001). Correspondingly, the Kruskal Wallis test revealed that the body image dissatisfaction decreased significantly in the three groups at the end of the 3rd and 5th weeks (P < 0.001). The mean scores of pain anxiety showed that the nature sounds group proved more effective than the Benson relaxation technique. Also, the means scores of body image satisfaction showed that the Benson relaxation technique proved more effective than nature sounds. The study findings suggested that the Benson relaxation technique and nature sounds effectively reduces pain, anxiety, and improves body image satisfaction in patients with burn injuries. • This single-blind randomized clinical trial study was conducted on burn patients hospitalized in the intensive care unit. • The evaluator nurse, unaware of the kind of intervention for each patient, completed the questionnaires. • The mean scores of pain anxiety showed that the nature sounds proved more effective than the Benson relaxation technique. • The mean scores of body image showed that the Benson relaxation technique proved more effective than nature sounds. [ABSTRACT FROM AUTHOR]

In this paper, the issue of disturbances rejection for a class of interval type-2 T-S fuzzy systems (IT-2 TSFSs) with time-varying delay is studied. First, an augmented dynamic IT-2 TSFS composed of an internal model, observer, and improved equivalent input disturbance (IEID) is constructed. The IEID estimator is inserted into the fuzzy controller to compensate for unknown external disturbances. Meanwhile, a controller structure including state feedback, internal model feedforward, error feedback, and IEID is designed to improve the disturbance rejection performance of the IT-2 TSFSs. Then, the controller design problem is transformed into a stability problem of the augmented dynamic system. In addition, a Lyapunov-Krasovskii functional (LKF) is constructed which relies on the information of integral variables and membership functions (MFs). Using the time derivative information of the MFS, the controller with switching rules is designed. To reduce the conservatism of the system design conditions and improve the degree of freedom, the slack matrix and upper and lower MFs information are introduced in the stability analysis of the control system. Finally, the availability and advantages of our proposed method are validated through a numerical simulation. • An active disturbance rejection control framework is built for the IT-2 TSFS subject to external interference and time-varying delay. • A switching mechanism is devised that can select the appropriate fuzzy controller according to MFs information of the IT-2 TSFS. • A relaxation technique is proposed based on the algebraic properties of the MFs. [ABSTRACT FROM AUTHOR]

Recently, the relaxation technique has been widely used to impose conservation of invariants while retaining the full accuracy of the original method. So far, only a single invariant of a system has been considered. In this work, by a mild generalization of the relaxation technique, the Runge–Kutta–Nyström (RKN) integrators are modified to preserve two invariants for second-order system of Ordinary Differential Equations (ODEs). The proposed integrators can be explicit and of arbitrarily high order. The accuracy of the relaxation RKN integrators and the existence of valid relaxation parameters have been proved. The construction of the new integrators is under the framework of adapted RKN (ARKN) integrators which are specially designed for numerical solving second-order oscillatory systems. Therefore, the proposed integrators could be oscillation-preserving in the sense that they exactly integrate homogeneous oscillatory system q ′ ′ + K q = 0. Some numerical experiments are conducted to show the advantage and efficiency of the proposed integrators in comparison with the standard (A)RKN integrators. [ABSTRACT FROM AUTHOR]

• Introduces a joint GNSS and distance noise model for accurate real-world localization estimations. • Proposes hierarchical optimization with global estimation and local refinement for enhanced positioning accuracy. • Enhances convergence via adaptive learning rates and early stopping in iterative optimization. • Demonstrates model robustness against varying noise levels and conditions through comprehensive experiments. Vehicle localization plays a crucial role in intelligent transportation systems. However, traditional Global Navigation Satellite Systems often struggle to provide the high-precision positioning required in complex environments. To address this challenge, VANET-based localization methods have emerged as a promising alternative with significant potential. This paper proposes an adaptive iterative algorithm based on a maximum likelihood strategy, which integrates GNSS and relative distance information to significantly enhance vehicle localization accuracy in VANET scenarios. The method uses convex relaxation techniques to transform the problem into a series of convex subproblems, effectively solving the non-convex optimization problem and providing more reliable position estimation. During the iterative optimization process, the algorithm progressively improves the position estimates, avoiding local optima, and employs adaptive step sizes and weighted quadratic cost functions to maintain high computational efficiency. Experimental results show that the proposed method outperforms Weighted Least Squares and Lagrange Relaxation methods across several key performance metrics. In low-noise environments, vehicle positioning accuracy can reach centimeter-level, with an average iteration time of only 0.000201 s. These results demonstrate the advantages of the method in terms of both localization accuracy and real-time performance, showcasing its potential for application in intelligent transportation systems. [ABSTRACT FROM AUTHOR]

In the multi-feeder distribution network, the power balance between photovoltaics generations and load demands across regions is more complex. To solve the above problems, this paper proposes a multi-agent distributed voltage control strategy based on robust deep reinforcement learning to reduce voltage deviation. The whole multi-feeder distribution network is divided into a main agent and several sub-agents, and a multi-agent distributed voltage control model considering the transmission network voltage fluctuations and the corresponding power fluctuations is established. Based on the information uploaded by sub-agents, the main agent models the uncertainty of the transmission network voltage fluctuations and the corresponding power fluctuations as a disturbance to the state, and a RDRL method is employed to determine the tap position of on-load tap changer. Furtherly, each sub-agent uses the second-order cone relaxation technique to adjust the reactive power outputs of the inverters on each feeder. The effectiveness of the proposed method has been verified in two real-world multi-feeder systems. The results show that the proposed method can achieve millisecond-level decision-making, with a voltage deviation only 1.28 % higher than the global optimal results, achieving near-optimal control. The proposed method also demonstrates robustness in handling transmission network uncertainties and partial measurement loss. • A multi-agent distributed voltage control strategy is proposed for multi-feeder distribution network. • Modeling voltage fluctuations of transmission grids using adversarial Markov processes. • Control on-load tap changer under uncertainty using robust deep reinforcement learning. • Adjust reactive power outputs of inverters on each feeder using the second-order cone relaxation technique. [ABSTRACT FROM AUTHOR]

Recent advances in quaternion signal processing have drawn attention to the Quaternion Beamforming Problem (QBP). By leveraging appropriate relaxation techniques, QBP can be transformed into a constrained quaternion matrix optimization problem, aiming to develop a simple and effective solution. To this end, this paper first establishes a comprehensive theory of convex optimization for quaternion matrices based on the GHR calculus, covering quadratic upper bounds and projection theorems. In particular, we propose a quaternion projected gradient descent (QPGD) for constrained quaternion matrix optimization problems and prove the convergence of the QPGD algorithms, showing the monotonic decrease of the objective function. The numerical experiments verify the applicability and effectiveness of the QPGD algorithm in solving constrained quaternion matrices least squares problems in Frobenius norm and the quaternion beamforming problem. • We establish quadratic upper bounds and a projection theorem using GHR calculus. • We propose a quaternion projected gradient descent (QPGD) algorithm. • We provide detailed convergence proofs for the QPGD algorithm. • The QPGD algorithm outperforms the quaternion dual ascent method in F -norm least squares. • The QPGD algorithm effectively solves the quaternion beamforming problem. [ABSTRACT FROM AUTHOR]

With California's ambitious goals to decarbonize the electrical grid by 2045, significant challenges arise in power system investment planning. Existing modeling methods and software focus on computational efficiency, which is currently achieved by simplifying the associated formulations. The simplifications, such as linear relaxation of binary decisions, may lead to significant inaccuracies in the cost and constraints of generation operations and may affect both the timing and the extent of investment in new resources, such as renewable energy and energy storage. To address this issue, this paper develops a more detailed and rigorous mixed-integer linear programming model where the discrete nature of the problem is properly captured. Further, a solution methodology utilizing surrogate level-based Lagrangian relaxation is adapted to address the combinatorial complexity that results from the enhanced level of model detail. Our methodology is capable of efficiently handling the decarbonization model with approximately 12 million binary and 100 million total variables in under 48 h, representing a massive leap in the ability to solve complex planning models in acceptable time. The solution obtained by our method leads to an investment plan, which is then compared with the plan produced by E3's RESOLVE software currently employed by the California Energy Commission, California Public Utilities Commission as well as by three major California utilities: SCE, PG&E, and SDGE. Our model produces an investment plan that leads to substantial savings to the State of California of over 4 billion dollars over the investment horizon as compared to the existing method. • A high-fidelity generation expansion model is developed for California's decarbonization. • A surrogate Lagrangian relaxation technique shortens computation time for large MILPs. • Detailed MILP modeling cuts costs, while the status quo model has major emission violations. [ABSTRACT FROM AUTHOR]

Objective: To map the evidence on a Perinatal Mental Health Counselling Programme, identifying its characteristics, participants, and outcomes.Methods: This review followed the guidelines of the Joanna Briggs Institute and PRISMA-ScR. Published and unpublished studies, from 2011 to 2021, written in English, Portuguese or Spanish were included.Results: Despite the high number of articles identified, only nine articles were included in the final analysis, mainly from Iran, Italy and one Portuguese study. All articles referred to community health care centres and hospitals. The sessions varied between 6 and 16 and lasted 30-90 min. The method used was either individual and/or group, with weekly or monthly sessions or whenever deemed necessary throughout the evaluation. Different techniques were found, but emotional management, problem-solving, relaxation and mindfulness techniques were highlighted. Participants are pregnant women, partners, or family members. All articles suggest a decrease in the levels of stress, anxiety, and depression after the counselling intervention.Conclusion: Perinatal counselling programme have varied characteristics and mental health nurses are potential facilitators. [ABSTRACT FROM AUTHOR]

The dissipative control problem for nonlinear discrete-time switched singular systems (NDSSSs) is investigated via a novel reduced-order observer in this paper. Firstly, based on the generalized Sylvester equations and the introduced nonlinear injection term, a novel reduced-order observer is designed for each subsystem. The designed reduced-order observer can still produce accurate full-information estimation even though the dynamics and the output of the systems both contain unknown inputs. Then, by using average dwell-time scheme and multi-Lyapunov functions, some new sufficient conditions are proposed such that the resulted closed-loop NDSSSs are regular and causal, have a unique solution, and are globally uniformly asymptotically stable with a strict (Q , S , V) - γ -dissipative. A novel relaxation technique is proposed for decoupling nonlinear inequalities involving products of multiple nonsquare unknown variables. The design procedures of reduced-order observer and controller are presented by a specific algorithm. Finally, two numerical examples and an electronic circuit example are provided to illustrate the effectiveness of the theoretical results. • The dissipative control problem for nonlinear discrete-time switched singular systems based on reduced-order observer is considered. • By generalized Sylvester equations, a novel reduced-order observer is designed to perform accurate full-information estimation. • A new lemma for decoupling matrix inequalities is proposed, enabling a less conservative design approach for observers and controllers. • The sufficient conditions ensure closed-loop systems are regular, causal, have a unique solution, and are GUAS with (Q , S , V) - γ -dissipative [ABSTRACT FROM AUTHOR]

We propose an energy-optimized invariant energy quadratization method to solve the gradient flow models in this paper, which requires only one linear energy-optimized step to correct the auxiliary variables on each time step. In addition to inheriting the benefits of the baseline and relaxed invariant energy quadratization method, our approach has several other advantages. Firstly, in the process of correcting auxiliary variables, we can directly solve linear programming problem by the energy-optimized technique, which greatly simplifies the nonlinear optimization problem in the previous relaxed invariant energy quadratization method. Secondly, we construct new linear unconditionally energy stable schemes by applying backward differentiation formulas and Crank–Nicolson formula, so that the accuracy in time can reach the first- and second-order. Thirdly, comparing with relaxation technique, the modified energy obtained by energy-optimized technique is closer to the original energy, and the accuracy and consistency of the numerical solutions can be improved. Ample numerical examples have been presented to demonstrate the accuracy, efficiency and energy stability of the proposed schemes. [ABSTRACT FROM AUTHOR]

• Desire thinking is a candidate target for therapeutic techniques to reduce gaming urge. • Study of 337 gamers evaluating effects of detached mindfulness and relaxation on gaming urge. • A brief desire thinking exercise was capable of increasing urge to game. • Detached mindfulness did not appear to modify gaming-related urges. • Relaxation reduced gaming urges, and this effect was more prominent in more impulsive gamers. Individuals who struggle to regulate their gaming involvement, particularly those with gaming disorder, often report strong subjective urges to play games. Desire thinking has been proposed to be an active driver of urge, and therefore disrupting desire thinking processes may reduce urges to play. Detached mindfulness, a meta-cognitive therapy technique, is a candidate option for reducing desire thinking, but the available research in relation to gaming is limited. To address this gap, this pre-registered study employed a 3 (Group: mindfulness, relaxation, control) x 3 (Time: baseline, pre-task, post-task) mixed experimental design to evaluate the effectiveness of different techniques to reduce gaming urges. Gamers (N = 337) were recruited via the crowd-sourcing platform Prolific. Participants were administered interactive video-based tasks that induced gaming-related desire thinking and were then randomly delivered one of three techniques. Results showed that the desire thinking exercise significantly increased gaming urge. However, the detached mindfulness technique had no significant effect on urge to play, whereas relaxation significantly reduced urge compared to control. The effect of relaxation on urge was stronger for those with moderate to high impulsivity. These results support the proposed link between desire thinking and gaming urge. Gaming urges may be reliably induced using a brief self-guided protocol, which has applications for interventions involving exposure exercises without the use of physical gaming stimuli. Relaxation techniques may have short-term utility in reducing gaming-related urges. Further research should examine other meta-cognitive therapy-based techniques to support a broader research program on CBT for gaming disorder. [ABSTRACT FROM AUTHOR]

This study focuses on finding a global optimal solution to a generalized fractional programming problem (GFP) in the perspective of large-scale applications. However, few algorithms exist to solve the GFP due to its nonconvexity and NP-hard. Therefore, it is significant to propose an efficient algorithm for the GFP. For this purpose, first of all, using logarithmic and exponential properties, we transform the GFP into an equivalent problem (EP) by introducing some image space variables. Next, the relaxation problem (RP) is constructed using a two-phase relaxation method and bilinear relaxation technique based on the structure of the EP. Furthermore, through the comprehensive utilization of the unique structures of EP and RP, along with the attributes of branch and bound algorithms, some novel region-reduction techniques have been introduced to eliminate regions devoid of the global optimal solution. Subsequently, the integration of the two-phase relaxation method and region-reduction techniques within the branch-and-bound framework has led to the design of the image space branch-reduction-bound algorithm (ISBRBA). Moreover, the convergence and computational complexity of the ISBRBA are analyzed by considering the infinite approximation property between the objective functions of the EP and RP. Finally, the effectiveness and robustness of the ISBRBA are demonstrated through numerous numerical experiments. [ABSTRACT FROM AUTHOR]

In this article, we consider consistent, efficient, and accurate numerical approximations for a recently developed Cahn–Hilliard type phase-field surfactant model enjoying the bounded-from-below condition of total energy. The phase-field surfactant model naturally satisfies the energy dissipation property in time. Based on this feature, we construct linearly decoupled and unconditionally energy-stable time-marching schemes based on an efficient variant of scalar auxiliary variable approach. To enhance the consistency of discrete modified energy and discrete original energy, a practical energy relaxation technique is adopted. We analytically proved the unique solvability and unconditional energy stability of the proposed schemes. In each time step, only two linear elliptic type equations with constants coefficients need to be solved and several algebraic operations need to be performed. Therefore, the proposed schemes are highly efficient and easy to implement. The space is discretized by the finite difference method and the linear multigrid algorithm is used to accelerate the convergence. The numerical results indicate that the proposed method not only has desired accuracy in time but also satisfies the energy dissipation law even if larger time steps are used. Furthermore, the surfactant laden spinodal decompositions and surfactant absorptions can be well simulated. [ABSTRACT FROM AUTHOR]

We pose the problem of the optimal approximation of a given nonnegative signal y t with the scalar autoconvolution (x ∗ x) t of a nonnegative signal x t , where x t and y t are signals of equal length. The I -divergence has been adopted as optimality criterion, being well suited to incorporate nonnegativity constraints. To find a minimizer we derive an iterative descent algorithm of the alternating minimization type. The algorithm is based on the lifting of the original problem to a larger space, a relaxation technique developed by Csiszár and Tusnády in [Statistics & Decisions (S1) (1984), 205–237] which, in the present context, requires the solution of a hard partial minimization problem. We study the asymptotic behavior of the algorithm exploiting the optimality properties of the partial minimization problems and prove, among other results, that its limit points are Kuhn–Tucker points of the original minimization problem. Numerical experiments illustrate the results. [ABSTRACT FROM AUTHOR]

Addressing the challenges of constrained multiobjective optimization problems (CMOPs) with evolutionary algorithms requires balancing constraint satisfaction and optimization objectives. Coevolutionary multitasking (CEMT) offers a promising strategy by leveraging synergies from distinct, complementary tasks. The primary challenge in CEMT frameworks is constructing suitable auxiliary tasks that effectively complement the main CMOP task. In this paper, we propose an adaptive CEMT framework (ACEMT), which customizes two adaptive auxiliary tasks to enhance CMOP-solving efficiency. The first auxiliary task dynamically narrows constraint boundaries, facilitating exploration in regions with smaller feasible spaces. The second task focuses specifically on individual constraints, continuously adapting to expedite convergence and uncover optimal regions. In solving the main CMOP task, this dual-auxiliary-task strategy not only improves search thoroughness but also clarifies the balance between constraints and objectives. Concretely, ACEMT incorporates an adaptive constraint relaxation technique for the first auxiliary task and a specialized constraint selection strategy for the second. These innovations foster effective knowledge transfer and task synergy, addressing the key challenge of auxiliary task construction in CEMT frameworks. Extensive experiments on three benchmark suites and real-world applications demonstrate ACEMT's superior performance compared to state-of-the-art constrained evolutionary algorithms. ACEMT sets a new standard in CMOP-solving by strategically constructing and adapting auxiliary tasks, representing a significant advancement in this research direction. [ABSTRACT FROM AUTHOR]

The state of health (SOH) estimation of lithium-ion batteries is crucial for the operational reliability and safety of electric vehicles. However, traditional data-driven methods face problems of label shortage and domain discrepancy caused by diverse battery types and operating conditions. This paper proposes a label-free SOH estimation method based on adversarial multi-domain adaptation technique and relaxation voltage (RV). Firstly, the raw RV and integral voltage are proposed to construct the two-dimensional input sequence to ensure high adaptability across various target domains. Secondly, a two-dimensional convolutional neural network integrated with fully connected layers is developed to establish the feature extractor and SOH estimator, which paves the way for effective knowledge transfer. Furthermore, an adversarial multi-domain adaptation method with a domain discriminator is developed to optimize the extraction of domain-invariant features and enable accurate SOH estimation without SOH labels. Datasets of 50 batteries with different temperatures and materials are used for the validation. The proposed method shows outstanding performance, achieving the average RMSE and MAE of 0.0274 and 0.0240 across various working temperatures, and 0.0177 and 0.0148 across different battery types. It suggests that the proposed method can achieve robust adaptive battery SOH estimation across multiple target domains without using SOH labels. • 2D input sequence is constructed using the proposed integral voltage and raw RV. • A 2D-CNN integrated with FCL is developed to establish the feature extractor and SOH estimator. • An adversarial multi-domain adaptation method is proposed for label-free SOH estimation. • Datasets of 50 batteries with different temperatures and materials are used for the validation. [ABSTRACT FROM AUTHOR]

Women with breast cancer experience social disruption during and after treatment. Brief cognitive-behavioral (CBT) and relaxation (RT) interventions may improve social disruption by increasing positive affect. Using the Broaden-and-Build Theory as a framework, this study examined whether short-term CBT- and RT-related increases in positive affect mediate long-term reductions in social disruption in women with breast cancer undergoing treatment (N = 183). This secondary analysis used latent change score and growth models to test 6- and 12-month intervention effects on positive affect and social disruption, respectively; a parallel-process model assessed mediation. RT demonstrated larger reductions in social disruption across 12 months compared to CBT and a health education control. Six-month latent change in positive affect was significant but not driven by condition. There was a significant direct effect linking the latent slopes of positive affect and social disruption but meditation was not observed. These preliminary findings hint at the value of promoting positive affect and inform the development of brief behavioral interventions that aim to augment social functioning among women surviving breast cancer. [ABSTRACT FROM AUTHOR]

Background and Purpose: Most women suffer some degree of perineal trauma during vaginal delivery. Second stage management strategies, including vocalization, to protect the perineum have been investigated.Objective: To compare the frequency and degree of perineal trauma at vaginal delivery, with and without use of the vocalization maneuver during the second stage of labor.Materials and Methods: This is an open-label, randomized controlled trial. We conducted the study at the Center for Normal Deliveries of IMIP. We included low-risk women without prior cesarean deliveries. Women who met the inclusion criteria and signed the informed consent form were randomized to one of two groups: Group A (experimental) and Group B (control). A physical therapist encouraged women in Group A to maintain an open glottis during pushing and to emit sounds when exhaling (vocalization). Women in Group B underwent routine humanized vaginal deliveries. The outcomes of the study were perineal integrity and degree of perineal laceration. These were measured by the study team immediately after completion of the third stage of labor.Results: Women in Group A tended to have less severe perineal tear (less second and third degree lacerations) and smaller lacerations than women in group B. The vocalization maneuver reduced the risk of a perineal tear greater than 2 cm by 68% (NNT 2.2). There was no difference in other outcomes.Conclusion: Encouraging women to follow a vocalization protocol coached by a physical therapist during the second stage of labor can be a helpful labor assistance technique, since this study showed that vocalization is associated with less extensive perineal tears.Clinical Trial Registration: This study was registered on ClinicalTrials.gov (www.Clinicaltrial: gov) registration number: NCT03605615. [ABSTRACT FROM AUTHOR]

• Level-set method is applied for stress-based topology optimization of plate problems. • Solving optimization problems with arbitrarily complex geometries and boundaries. • A stabilized least-squares method is applied for solving level-set-based equations. • The shape derivatives, adjoint method, and p -norm aggregation function are used. In this paper, we present a stress-based topology optimization of plate structures by using a finite element level-set (LS) method. Since stress constraints are independent with LS-based design variables, the singularity phenomenon arising in topology optimization under stress constraints can be resolved without using any relaxation technique. The finite element method is used for solving LS-based equations of design variables and the state and adjoint equations of plate structures with arbitrary complex geometries and boundaries of the design domain. To obtain stable finite element solutions without any oscillation, both unsteady LS convection-diffusion equation and LS re-initialization convection-reaction equation are solved using a stabilized least-squares finite element method. [ABSTRACT FROM AUTHOR]

This study examines a ride-hailing platform that employs a mixed fleet of autonomous vehicles (AVs) and human drivers to offer on-demand ride-hailing services across a network over a finite planning horizon. In the mixed fleet, AVs have a fixed fleet size and are centrally managed by the platform, while human drivers can dynamically enter and exit from the ride-hailing market based on the prospective earning opportunities at various time periods. We introduce a game-theoretic model that encapsulates the strategic behavior of human drivers, passengers, and the ride-hailing platform. In this model, passengers choose between ride-hailing and alternative transportation options by considering fares and waiting times. Human drivers schedule their working hours in response to potential earnings and strategically relocate to maximize passenger pickups, while the platform adjusts pricing and AV repositioning strategies to maximize its profit. The solution is characterized as a Nash equilibrium within a two-player game, with one player representing the ride-hailing platform, and the other as a virtual representative of the collective human drivers. To address the non-convex nature of the game, we employ a convex relaxation technique to ascertain a near-optimal solution framed as an ϵ -Nash equilibrium, with ϵ accurately characterized. The proposed model and solution algorithm are validated in a case study for Manhattan, New York City. The simulation results underscore that the distribution of human drivers is closely aligned with the immediate, minute-to-minute fluctuations in passenger demand, enabling them to effectively meet the surge during peak demand windows. Conversely, the deployment patterns of AVs are more attuned to the extended, daily cycles of passenger movements throughout different city zones, from daytime to nighttime. We further compare the mixed fleet model with scenarios where the platform exclusively utilizes human drivers or AVs, respectively. The comparison show that the mixed fleet model excels in balancing the supply and demand over space and time, thereby leading to shorter wait times and reduced travel cost for ride-hailing passengers, as well as improved profit for the ride-hailing platform. • Investigated the synergy between human drivers and AVs on ride-hailing platforms. • Developed a dynamic network model for the platform to make optimal decisions over space and time. • Characterize the interaction between the platform and human drivers using a game-theoretic framework. • Derived the Approximate Nash equilibrium of the game. [ABSTRACT FROM AUTHOR]

To examine the effects of six relaxation techniques on perceived momentary relaxation and a possible association of relaxation effects with time and practice experience in people with cancer. We used data from participants with cancer in a larger study practicing app-based relaxation techniques over 10 weeks, assessed momentary relaxation before and after every third relaxation practice, and analyzed momentary relaxation changes with a linear mixed-effects model. The sample included 611 before-after observations from 91 participants (70 females (76.9%)) with a mean age of 55.43 years (SD 10.88). We found moderate evidence for variations in momentary relaxation changes across different techniques (P =.026), with short meditation, mindfulness meditation, guided imagery, and progressive muscle relaxation more frequently observed and leading to more relaxation than body scan and walking meditation. Furthermore, we found moderate evidence for increasing momentary relaxation changes over time (P =.046), but no evidence for an association between momentary relaxation and the number of previous observations (proxy for practice experience; P =.47). We compared six app-based relaxation techniques in a real-life setting of people with cancer. The observed variations in perceived momentary relaxation appear to correspond with the popularity of the techniques used: The most popular relaxation techniques were the most effective and the least popular were the least effective. The effects increased over time, likely caused by dropout of individuals who gained no immediate benefit. Our findings open an interesting avenue for future research to better understand which relaxation techniques work best for whom in which situations. DRKS00027546; https://drks.de/search/en/trial/DRKS00027546 • Relaxation techniques can reduce cancer-related distress in the long term. • It is unclear if relaxation techniques give immediate benefit to people with cancer. • We show that different relaxation techniques have different immediate effects. • Popular relaxation techniques relax people with cancer, unpopular techniques do not. • Relaxation apps should offer a variety of relaxation techniques to choose from. [ABSTRACT FROM AUTHOR]

Exposure to occupational stressors is an issue for staff working in emergency departments, managers and health services. The aim of this review was to identify, map, and synthesise the range and scope of current evidence for work-based strategies or interventions used in emergency departments to reduce occupational stressors and/or improve staff coping. The framework proposed by Arksey and O'Malley guided this review. A search of CINAHL, MEDLINE, Scopus, Cochrane and PsycINFO databases from January 2007 to June 2019 was applied. A total of thirty-one articles were included in this review. Quality appraisal was undertaken. Exposure to or impact of occupational stress and workplace violence were common foci. A range of outcomes (such as burnout levels, stress levels and quality of life) were measured in the included studies. All studies demonstrated some improvement in outcomes measured although most were evaluated for relatively short duration. Quality of evidence varied. Strategies ranging from mindfulness to organisational redesign have been trialed to diminish stress and enhance coping of emergency department staff. Understanding the effectiveness of strategies is an important early step in improving the working environment for emergency department clinicians in an evidence-informed manner. Such information may be of use to managers to inform decision making regarding the most appropriate strategy to implement in their emergency department. [ABSTRACT FROM AUTHOR]

Migraine is a debilitating neurological condition with symptoms typically consisting of unilateral and pulsating headache, sensitivity to sensory stimuli, nausea, and vomiting. The World Health Organization (WHO) reports that migraine is the third most prevalent medical disorder and second most disabling neurological condition in the world. There are several options for preventive migraine treatments that include, but are not limited to, anticonvulsants, antidepressants, beta blockers, calcium channel blockers, botulinum toxins, NSAIDs, riboflavin, and magnesium. Patients may also benefit from adjunct nonpharmacological options in the comprehensive prevention of migraines, such as cognitive behavior therapy, relaxation therapies, biofeedback, lifestyle guidance, and education. Preventative therapies are an essential component of the overall approach to the pharmacological treatment of migraine. Comparative studies of newer therapies are needed to help patients receive the best treatment option for chronic migraine pain. [ABSTRACT FROM AUTHOR]

This paper presents a convex optimization-based approach to efficiently obtain the numerical solution of the fuel-optimal powered descent problem with free final-time and path constraints. To avoid guessing the final-time, we propose to choose altitude, instead of time, as the independent variable in the system dynamics. This selection also brings great convenience in incorporating the glide-slope and thrust direction constraints in which the bounds can be altitude-dependent. Then, the formulated optimal control problem is converted into a convex problem via appropriate convexification techniques, such as the nonlinearity-kept & linearization approach and relaxation, etc. Relaxation is a critical technique, but analyzing its validity is generally very challenging, especially when path constraints are present. In this paper we can prove that the relaxation used is valid. Next, we discretize the convex problem and apply successive convex optimization to get the solution of the original problem. Nevertheless, in order to obtain the solution with high accuracy and low computational cost, we propose a new strategy of selecting nonuniform discretized points plus the Runge-Kutta 4th order or trapezoidal discretization method. Numerical results are provided to show the effectiveness and high efficiency of the proposed method in solving the powered descent problem and reveal an interesting structure of the optimal thrust magnitude profile when path constraints become active. • No need to guess or specify the final time. • The relaxation technique is theoretically proved to be valid. • High solution accuracy is achieved in low computational cost. • The proposed algorithm can converge quickly within a few iterations. • Fuel-optimal descent shows existence of bang-bang control with three switches. [ABSTRACT FROM AUTHOR]

Differences in expectations between experimental and control groups can influence the outcomes of exercise interventions, emphasizing the need to match expectations across study groups. This online study examined whether the expectations to improve the performance of different cognitive tasks differ between various activities commonly used in research on the effects of exercise and cognitive function. Two hundred and five middle-aged adults performed two reaction-time tasks and one memory task. They were then asked to rate, on a 1–5 Likert scale, their expectations to improve performance in those tasks should they engage in six types of activities for three months: brisk walking, resistance exercise, stretching and balance exercises, watching videos with lectures on art, history, and science, a program of relaxation techniques, and yoga/tai chi/meditation. Results revealed that the highest expectations for improvement were associated with relaxation techniques and yoga/tai chi/meditation. Some activities, such as brisk walking and stretch and balance exercises, shared similar expectations. Previous knowledge of the possible beneficial effects of exercise on cognitive performance also led to higher expectations. To establish causal relationships, researchers should strive to use activities that share similar expectations to improve performance for the experimental and control groups. The findings of this study provide such activity pairs. Finally, researchers should also try to match participants with and without prior knowledge of the benefits of exercise to cognitive function between experimental and control groups. • Expectations to improve cognitive performance vary among different activities. • Prior knowledge of the beneficial effects of exercise leads to higher expectations. • Stretch & balance can be used as active control for aerobic exercise intervention. • Performance in cognitive tasks does not correlate with expectations to improve. • Exercise habits do not correlate with expectations to improve. [ABSTRACT FROM AUTHOR]

Mind-body practices are complementary approaches recognized by the World Health Organization (WHO). While these practices are very diverse, they all focus on the interaction between mind and body. These include mindful meditation, yoga, Tai Chi, sophrology, hypnosis and various relaxation techniques. There is growing interest in incorporating these strategies in the management of chronic rheumatic diseases including rheumatoid arthritis. The aim of this review is to describe the main mind-body practices and analyze the existing evidence in chronic rheumatic diseases. In rheumatoid arthritis, the Mindfulness-Based Stress Reduction program, yoga, Tai Chi and relaxation may improve patient-reported outcomes, but the benefit on inflammation and structural progression is unclear. In spondyloarthritis, very few studies are available but similar evidence exist. Further evaluations of these practices in chronic rheumatic diseases are needed since their risk/benefit ratio appears excellent. [ABSTRACT FROM AUTHOR]

Cancer-related fatigue is one of the most common symptoms in cancer patients, usually accompanied by anxiety, depression and insomnia, which seriously affect patients' quality of life. Progressive muscle relaxation training is widely used for cancer-related fatigue, but the overall effect is unclear. The aim of this study was to summarize the evidence on the effects of progressive muscle relaxation training on cancer-related fatigue and quality of life in cancer patients. Systematic review and meta-analysis. Nine electronic databases (PubMed, Excerpta Medica Database (Embase), The Cochrane Library (Cochrane Central Register of Controlled Trials, CENTRAL), Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP) and Wanfang Database) were explored for randomized controlled trials (RCTs) published before February 2023. This study was reported based on the PRISMA 2020 statement. The Cochrane Collaboration's risk of bias assessment tool was used for methodological assessment, and the GRADE pro online assessment tool was used for evidence evaluation. The data were analyzed with the Review Manager 5.4 software. Twelve studies involving 1047 patients were included. Meta-analysis showed that progressive muscle relaxation training plus routine nursing produced more positive effects than routine nursing in improving cancer-related fatigue [SMD = − 1.06, 95 % CI − 1.49, − 0.62, P < 0.00001], anxiety [SMD = − 1.09, 95 % CI − 1.40, − 0.77, P < 0.00001], depression [SMD = − 1.43, 95 % CI − 1.76, − 1.10, P < 0.00001], and quality of sleep [MD = − 1.41, 95 % CI − 1.74, − 1.08, P < 0.00001]. However, there was no significant difference in improving quality of life [SMD = 0.27, 95 % CI − 0.62, 1.15, P = 0.55]. Progressive resistance exercise plus routine nursing improved cancer-related fatigue more than progressive muscle relaxation training plus routine nursing [SMD = 1.11, 95 % CI 0.43, 1.78, P = 0.001]. There was low certainty of evidence that progressive muscle relaxation training improved cancer-related fatigue and quality of sleep, and the evidence that improved quality of life, anxiety and depression was very low. Current evidence suggested that progressive muscle relaxation training has the potential to improve cancer-related fatigue, anxiety, depression and quality of sleep in patients with cancer and is a low-load, simple exercise worthy of recommendation for cancer patients in fatigue state. Future research should focus on improving the methodological quality of randomized controlled trials to enhance the persuasive evidence of progressive muscle relaxation training efficacy. [ABSTRACT FROM AUTHOR]

Background: Mindfulness-Based Interventions (MBIs) have shown promising effects on mental health among children and adolescents, but high-quality studies examining the topic are lacking. The present study assessed the effects of MBI on mental health in school-setting in an extensive randomised controlled trial.Methods: Finnish school children and adolescents (N = 3519), aged 12-15 years (6th to 8th graders), from 56 schools were randomized into a 9 week MBI group, and control groups with a relaxation program or teaching as usual. The primary outcomes were resilience, socio-emotional functioning, and depressive symptoms at baseline, at completion of the programs at 9 weeks (T9), and at follow-up at 26 weeks (T26).Results: Overall, mindfulness did not show more beneficial effects on the primary outcomes compared to the controls except for resilience for which a positive intervention effect was found at T9 in all participants (β=1.18, SE 0.57, p = 0.04) as compared to the relaxation group. In addition, in gender and grade related analyses, MBI lowered depressive symptoms in girls at T26 (β=-0.49, SE 0.21, p = 0.02) and improved socio-emotional functioning at T9 (β=-1.37, SE 0.69, p = 0.049) and at T26 (β=-1.71, SE 0.73, p = 0.02) among 7th graders as compared to relaxation.Limitations: The inactive control group was smaller than the intervention and active control groups, reducing statistical power.Conclusions: A short 9-week MBI in school-setting provides slight benefits over a relaxation program and teaching as usual. Future research should investigate whether embedding regular mindfulness-based practice in curriculums could intensify the effects. [ABSTRACT FROM AUTHOR]

Detecting errors is crucial for adapting one's own actions. Moreover, behavior is often optimized by adapting to maladaptive actions, i.e. errors. In this regard, recent studies and models of error monitoring point to an involvement of emotional states in error monitoring. A psychophysiological correlate of the latter is the error negativity or error-related negativity (N e /ERN), reflecting partly the functional implementation of anterior cingulate cortex functions. In the present study, we aimed to test whether neurophysiological aspects of error monitoring can be altered by a relaxation technique, i.e. slow-paced breathing. Slow-paced breathing has been shown to increase cardiac vagal activity. According to the neurovisceral integration model, cardiac vagal activity is thought to be a marker of the effectiveness of executive functions. We tested the effect of slow-paced breathing on error monitoring, i.e. the N e /ERN and behavioral adaptation in a modified flanker task, a cognitive task during which performance depends on executive control. The N e was increased following slow-paced breathing compared to a passive control condition. Furthermore, behavioral results indicate that response variability decreased in the slow-paced breathing condition whereas overall performance remained constant. We conclude that slow-paced breathing improves the ability to focus on the task at hand. Thus, the error monitoring system is being supported in keeping the pace, i.e. tracking responses. • The error negativity (Ne), an EEG correlate of error monitoring can be affected by a relaxation technique, i.e. slow-paced breathing. • Slow-paced breathing has been shown to increase cardiac vagal activity. • Cardiac vagal activity is thought to be a marker of the effectiveness of executive functions and to be linked to the Dopamine system via Norepinephrine. • The Ne was increased following slow-paced breathing compared to a passive control condition whereas response variability was reduced. • Slow-paced breathing improves the ability to focus on the task at hand and supports the error monitoring system in keeping the pace, i.e. tracking responses. [ABSTRACT FROM AUTHOR]

Background: The Contrast Avoidance Model postulates that individuals with generalized anxiety disorder (GAD) fear a sharp spike in negative emotion, and thus, prefer to worry to maintain their negative affect rather than being in a more euthymic state, such as relaxation. Relaxation induced anxiety (RIA) is a paradoxical phenomenon wherein people experience a spike in their anxiety during relaxation training. Because these phenomena may be related and may also operate among individuals with major depressive disorder (MDD), we attempted to test whether negative contrast sensitivity was a mediator of GAD or MDD in the prediction of RIA.Methods: Individuals with GAD (n = 32), MDD (n = 34), and healthy controls (n = 30) were exposed to a negative emotional contrast by engaging with relaxation practice and then watching a negative emotional video. This was followed by the assessment of their negative contrast sensitivity. After this, participants engaged again with relaxation and RIA was measured. We examined mediation effects of negative contrast on the relationship between diagnostic status and RIA.Results: Negative contrast sensitivity fully mediated GAD and partially mediated MDD in predicting RIA.Conclusions: Our findings support the hypotheses that negative contrast sensitivity is the mediator of both GAD and MDD in predicting RIA. This may have implications for assessment and treatment of GAD and MDD. [ABSTRACT FROM AUTHOR]

As space missions move from low-earth orbit operations to long duration exploration, the mission's crews will face a different set of experiences and stressors. In order to help prevent the development of cognitive or behavioral symptoms during these missions it is important to define preventative countermeasures. Recent evidence points to mindfulness and relaxation techniques as promising countermeasures for promoting cognitive and behavioral health. We conducted a narrative review of the scientific literature to identify key factors relevant to the role of mindfulness and relaxation techniques in the military and other analog settings, which share some important similarities with the space exploration context. Our results indicate that cognitive (non-meditative) mindfulness is an important psychological construct that can help to promote resilience and to reduce stress in analog environments and particularly in the military. While the literature suggests that mindfulness can be promoted through focused interventions, most of the studied interventions to date are based on meditation. While efficacious, meditation-based interventions generally require a significant amount of time for training. Alternative mindfulness approaches have not yet been explored in these settings but have yielded potentially relevant results for space. Relaxation training is a helpful tool to manage stress and to reduce anxiety. In the military, relaxation techniques are sometimes integrated into psychological training before deployment, leading to improved performance and reduced negative emotions. Even with a lack of specific literature about the application of these concepts in space, literature that describes the experiences from analog environments and military contexts as well as other studies on challenging conditions, suggest further exploration of interventions in these areas. • Mindfulness can promote adaptation in analogue environments and military settings. • Relaxation training can improve performance and reduce negative emotions. • Mindfulness and relaxation training could be important for astronaut training. • Further studies on mindfulness and relaxation in these settings are required. [ABSTRACT FROM AUTHOR]

Objective: Dysfunction in positive affect is a defining symptom of bipolar I disorder (BD), both during and between mood episodes. We hypothesize that helping people with BD learn skills to create balance in their affective experiences by engaging in strategies that increase low activation positive emotion (LAP; e.g., relaxation) could help to improve well-being during periods of symptom remission. We discuss the development and preliminary outcomes of a positive emotion regulation (PER) group treatment for people with BD, designed as a supplement to pharmacological treatment. Method: The Learning Affective Understanding for a Rich Emotional Life (LAUREL) intervention is a group-based intervention covering 10 empirically supported skills designed to increase LAP. Sixteen people with BD enrolled in the LAUREL intervention and twelve completed baseline and post-intervention assessments. Results: Participants who completed the study (n = 12) attended the majority of groups (87.96%) and reported practicing skills, on average, 16 times a week. We were unable to detect significant differences in mania symptoms following engagement in this PER intervention. Finally, participants reported increases in several areas associated with well-being post-intervention, including mindfulness, reappraisal, and self-compassion. Conclusion: This study provides a theoretical framework and preliminary support for a PER intervention for BD. [ABSTRACT FROM AUTHOR]

The mechanical characterization of skeletal muscle under high-rate loading regimes is important for predicting traumatic injuries due to traffic accidents and contact sports. However, it is difficult to perform dynamic mechanical tests at rates relevant to such rapid loading events. In the present study, a series of stress relaxation tests were conducted on rabbit hind-limb muscle fiber bundles using a custom tensile tester. Using relatively moderate loading conditions compared to those typically associated with traumatic injuries, the passive stress-decaying mechanical properties of muscle fiber bundles were characterized. In addition, stress relaxation responses to various ramp-hold stretches were theoretically predicted by a custom-built code. The results showed that the muscle fiber bundles exhibit greater stress relaxation at higher loading rates and greater stretch magnitudes. Based on these results, the data points representing the "elastic" stress–strain tensile behavior typical of traumatic injury were extrapolated using curve fitting. The theoretical model revealed rate-dependent characteristics of the muscle fiber bundles under traumatic loading conditions, which would result in tensile strengths of 300–500 kPa at the maximum engineering strain of 54%. This strength is on the order of magnitude as the maximum isometric stress of an active muscle contraction. The proposed numerical model is expected to serve as a powerful research tool to investigate injury mechanisms of the skeletal muscle. Moreover, the elastic response that was theoretically predicted here will be useful in the development of effective countermeasures to prevent traumatic injuries due to rapid loading events. • Rapidly stretched muscle fiber bundles showed 20% stress relaxation for 0.4 s after the ramp period. • Traumatic loading condition will theoretically lead to tensile strength of~400 kPa at 54% strain. • Predicted tensile strength was equivalent to the maximum isometric stress of muscle contraction. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Medical Imaging & Radiation Sciences is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Burn injuries are often accompanied by painful and distressing consequences, which can lead to long-term psychological issues. The most common form of anxiety in burn patients is pain anxiety. It is described as the feeling of fear and pain prediction caused by painful procedures.Aim: To compare the effects of inhalation aromatherapy using damask rose aroma and the Benson relaxation technique on pain anxiety in burn patients.Methods: This randomized clinical trial was conducted on 132 patients hospitalized in Motahari Burn Hospital from October 2017 to March 2018. The subjects were selected using a sequential sampling method. Next, they were randomly allocated by the Permuted block randomization method into four groups of rose aroma (5 drops of 40% rose aroma), the Benson relaxation technique, combined rose aroma-Benson relaxation and control. The interventions were performed for three consecutive days and once a day for 20 min, and each session lasted from 45 to 30 min before the daily dressing change. Data was collected using the Persian version of burn specific pain anxiety scale (BSPAS). Data was analyzed using descriptive and inferential statistics via the SPSS software version 16.Results: Immediately after the intervention, on the first, second and third days, significant differences in pain anxiety among four groups were reported. On the first day, the Scheffé ad hoc test indicated statistically significant differences in pain anxiety between all groups (p < 0.001), except rose aroma-plus-Benson relaxation and rose aroma groups (p = 0.15). On the second and third days, there were significant differences between the groups in pain anxiety (p < 0.001). Furthermore, after wound dressing, on the first, second and third days, statistically significant differences in pain anxiety among four groups were reported. On the first day, the Scheffé ad hoc test revealed statistically significant differences in pain anxiety between all groups (p < 0.001). On the second and third days, there were statistically significant differences in pain anxiety between the groups (p < 0.001), except the rose aroma and Benson relaxation groups. Immediately after the intervention, the maximum effect size was on the first day in the group of rose aroma-plus-Benson relaxation and the lowest effect size was on the first day in the Benson relaxation group. However, after wound dressing, the maximum effect size was on the third day in the rose aroma-pus-Benson relaxation group and the lowest effect size was on the first day in the Benson relaxation group.Conclusion: The combination of the rose aroma and Benson relaxation has a synergistic effect and has more effects in the reduction of pain anxiety in burn patients than a single intervention. Health care providers can provide these interventions simultaneously and help reduce pain anxiety in burn patients before conducting painful interventions. [ABSTRACT FROM AUTHOR]

Background Biological signaling and communication between mothers and infants during breastfeeding may shape infant behavior and feeding. This signaling is complex and little explored in humans, although it is potentially relevant for initiatives to improve breastfeeding rates. Objectives The aim of this study was to investigate physiological and psychological aspects of mother–infant signaling during breastfeeding experimentally, testing the effects of a relaxation intervention on maternal psychological state, breast milk intake, milk cortisol levels, and infant behavior and growth. Methods Primiparous breastfeeding mothers and full-term infants were randomly assigned to receive relaxation therapy [intervention relaxation group; n  = 33 (RG)] or to the control group [ n  = 31 (CG); no relaxation therapy] at 2 wk postpartum. Both groups received standard breastfeeding support. Home visits were conducted at 2 (HV1), 6 (HV2), 12 (HV3) and 14 (HV4) wk to measure maternal stress and anxiety, breast milk intake and milk cortisol, and infant behavior and growth. Results RG mothers had lower stress scores postintervention than the CG (HV3 ∆ = −3.13; 95% CI: −5.9, −0.3) and lower hindmilk cortisol at HV1 (∆ = −44.5%; 95% CI: −76.1%, −12.9%) but not at HV2. RG infants had longer sleep duration (∆ = 82 min/d; 95% CI: 16, 149 min/d) at HV2 and higher gains in weight and body mass index standardized deviation score than the CG infants (∆ = 0.76; 95% CI: 0.3, 1.22; and ∆ = 0.59; 95% CI: 0.09, 1.1, respectively). RG infants had a mean milk intake at HV3 that was 227 g/d higher than that of the CG infants (P  = 0.031) after controlling for gender and milk intake at HV1. Conclusions The trial shows the effectiveness of a simple relaxation intervention for improving maternal and infant outcomes and identifies some potential signaling mechanisms for investigation in future and larger studies, especially in settings where mothers are more stressed, such as those with preterm or low birth weight infants. This trial was registered at clinicaltrials.gov as NCT01971216. [ABSTRACT FROM AUTHOR]