Flexible Parameters Research Articles

Flexibility and mobility parameters in climbers and non-climbers

Purpose: In recent years, climbing has become increasingly popular and now has more enthusiasts and research interest than ever before. However, no study has yet considered the relationships between the functional mobility of the upper and lower limbs, climbing experience, climbing-specific hip mobility, and muscle strength. The purpose of this study was to determine whether functional mobility (measured using shoulder mobility and active straight leg raise tests) or climbing-specific hip mobility (measured using an adapted Grant foot raise test [hip flexion] and lateral foot reach test [hip abduction and external rotation determines climbing skills. Methods: A total of 59 volunteer climbers in 3 groups (elite climbers, intermediate climbers, and non-climbers) were assessed according to anthropometry, muscle strength, functional mobility, and hip mobility. Results: Elite climbers performed significantly better than intermediate climbers and non-climbers in tests of the external mobility of the left shoulder (p = .043; η2 = 0.112) and in the adapted Grant foot raise test (p = .023; η2 = 0.126). Conclusions: Elite climbers have greater hip mobility than intermediate climbers and non-climbers. Functional shoulder mobility, especially external rotation, may play a role in effective climbing.

Full-scale experiments and modeling of precast two-wall-in-one diaphragm wall components for oceanic artificial cities

An oceanic artificial city built by reclamation is an important solution for Hong Kong to solve the land supply conflicts. Traditional cast-in-situ enclosure structures face challenges for adapting to ocean geology, climate and environment. This study thus proposed a precast two-walls-in-one diaphragm wall (PTDW). This study first conducted a full-scale experiment for PTDW. Second, numerical studies of PTDW were performed. Third, a PTDW Bending-performance Assessment Model (PTDW-BAM) was developed. Finally, the parameter analysis and decision making were performed. The main conclusions are (1) PTDW using welded joints presented a resilient damage pattern. The joint damage was slighter and lagged behind the hollow section. (2) The PTDW components with welded joint constraint exhibited high adaptability to the oceanic artificial city project. The damage pattern exhibited joint closure and cracks without penetration. (3) Hollow section parameters are central for the bending performance of PTDW. PTDW-BAM comprehensively designed the hollow section parameters and obtained the optimal parameters. (4) PTDW-BAM has a designable and flexible parameter decision-making capability for oceanic artificial city projects. The results of PTDW-BAM in the case study presented resilience, weight reduction and tightness. This achievements provide green products and assessment tool for the oceanic artificial city construction in Hong Kong.

New Construction of Asynchronous Channel Hopping Sequences in Cognitive Radio Networks.

The channel-hopping-based rendezvous is essential to alleviate the problem of under-utilization and scarcity of the spectrum in cognitive radio networks. It dynamically allows unlicensed secondary users to schedule rendezvous channels using the assigned hopping sequence to guarantee the self-organization property in a limited time. In this paper, we use the interleaving technique to cleverly construct a set of asynchronous channel-hopping sequences consisting of d sequences of period xN2 with flexible parameters, which can generate sequences of different lengths. By this advantage, the new designed CHSs can be used to adapt to the demands of various communication scenarios. Furthermore, we focus on the improved maximum-time-to-rendezvous and maximum-first-time-to-rendezvous performance of the new construction compared to the prior research at the same sequence length. The new channel-hopping sequences ensure that rendezvous occurs between any two sequences and the rendezvous times are random and unpredictable when using licensed channels under asynchronous access, although the full degree-of-rendezvous is not satisfied. Our simulation results show that the new construction is more balanced and unpredictable between the maximum-time-to-rendezvous and the mean and variance of time-to-rendezvous.

Chance-constrained coordinated generation and transmission expansion planning considering demand response and high penetration of renewable energy

The integration of high-penetration renewable energy has led to a significant increase in the uncertainties of power systems, and coordinated generation and transmission expansion planning has attracted more and more attention. Demand response resources are regarded as a kind of virtual power supply, which can improve the flexibility of power systems and delay generation and transmission investment to a certain extent. This paper establishes a stochastic coordinated generation and transmission expansion planning model taking into account the impact of demand response programs. In particular, the demand response model describes the operating characteristics such as power, energy, reserve, response period, and response number in detail. Considering the difference in the degree of invocation of demand response programs by different power systems, the chance-constrained method is adopted, which can make the planning schemes flexibly adapt to different demand response levels and improve the practicability of the model. In the case study, numerical results of construction and operation indicate that demand response programs can play a role in replacing generation and transmission capacity. Specifically, although the response energy does not exceed 0.3% of the total load energy, the investment cost can be saved up to more than 20%. Moreover, the response level, flexibility parameters, response capacity, and the proportion of renewable energy will all affect the capacity substitution effect of demand response, which verifies the rationality and necessity of considering these factors in this paper.

Effects of aquatic and step aerobic exercises on flexibility parameters in sedentary women

The aim of this study was to investigate the effects of aquatic and step aerobic exercises on flexibility parameters in sedentary individuals. A total of n=45 sedentary women between the ages of 25-50 years, n=15 for aquatic exercise, n=15 for step aerobic exercise and n=15 for control group, who came to municipal sports centres, participated in this study. All measurements were taken before and after 8 weeks of aquatic and step aerobic exercises. In our study, after measuring body weight, body mass index, fat percentage, lean body mass, chest circumference, waist circumference, hip circumference, thigh circumference, sit-lie flexibility, hand flexibility at waist, hand flexibility at neck, planter flex right, planter flex left, dorsi flex right, dorsi flex left were measured respectively. For statistical analyses, paired t-test was used for dependent group comparisons for continuous variables and Wilcoxon test was used for non-normally distributed data. In comparisons of numerical variables between more than two independent groups, one-way analysis of variance (ANOVA) was used for normally distributed data and Kruskal-Wallis test for non-normally distributed data. After ANOVA and Kruskal-Wallis test, Tukey or Mann Whitney U post-hoc multiple comparison tests with Bonferroni correction were used to determine the groups in which the difference originated. When the in-group comparisons of aquatic exercise were evaluated, the pre-test and post-test values of sit-lie flexibility, flexibility at hand waist, flexibility at hand neck, planter flexion right, planter flexion left, dorsi flex right, dorsi flex left variables were statistically significantly different (P< 0.001, P< 0.001, P< 0.001, P< 0.001, P< 0.001, P< 0.001, P< 0.001, P< 0.001, respectively). In step aerobic exercise, the pre-test and post-test values of sit-lie flexibility, flexibility at hand waist, flexibility at hand neck, planter flexion right, planter flexion left, dorsi flex right, dorsi flex left variables were statistically significantly different (respectively; P< 0.001, P< 0.001, P< 0.001, P< 0.001, P< 0.001, P< 0.001, P< 0.001, P< 0.001, P< 0.001).

Agricultural emission reduction targets at country and global levels: a bottom-up analysis

ABSTRACT Few countries have declared sector-specific emission reduction targets in agriculture, making it difficult to construct and assess realistic climate mitigation scenarios for analytical and policymaking purposes. We aim to fill this analytical gap by using a set of cluster analyses to gauge likely ambitions levels in reducing agricultural emission at country-level, taking into consideration important country-level characteristics and referencing the ‘common but differentiated responsibilities’ principle. We then use the results from the cluster analysis together with information from submitted NDCs and other considerations to design formulas for assigning numerical reduction targets to individual countries. Our main results indicate a global agricultural emission level in 2030 exceeding the limit for the 1.5°C temperature target, but representing substantially lower emissions than the no-policy scenario. At individual country-level, the scenarios consist of large emission reductions in Northern and Western Europe, followed by the USA and other developed economies, and emission increases in many developing countries. To facilitate the construction of alternative scenarios, our method also contains parameters for flexibility to scale up or down ambition levels at both country and global levels, making the method useful for other researchers to develop alternative scenarios.

A Versatile Unitary Transformation Framework for an Optimal Bath Construction in Density-Matrix Based Quantum Embedding Approaches

The performance of embedding methods is directly tied to the quality of the bath orbital construction. In this paper, we develop a versatile framework, enabling the investigation of the optimal construction of the orbitals of the bath. As of today, in state-of-the-art embedding methods, the orbitals of the bath are constructed by performing a Singular Value Decomposition (SVD) on the impurity-environment part of the one-body reduced density matrix, as originally presented in Density Matrix Embedding Theory. Recently, the equivalence between the SVD protocol and the use of unitary transformation, the so-called Block-Householder transformation, has been established. We present a generalization of the Block-Householder transformation by introducing additional flexible parameters. The additional parameters are optimized such that the bath-orbitals fulfill physically motivated constraints. The efficiency of the approach is discussed and exemplified in the context of the half-filled Hubbard model in one-dimension.

Smart carrot chasing guidance law for path following of unmanned surface vehicles

Carrot chasing guidance law is one of the most widely used path following algorithms due to its simplicity and ease of implementation; however, it has a fixed parameter which leads to large cross-tracking errors during different navigational conditions. This study proposes an innovative approach to carrot chasing algorithm to minimize cross-tracking errors. Pattern search optimization technique is integrated with carrot chasing guidance law to determine unique virtual target points obtained by flexible parameters instead of a fixed parameter. Proposed smart carrot chasing guidance law (SCCGL) provides stable and accurate path following even for different navigational conditions of unmanned surface vehicle (USV). To the best of our knowledge, we are the first to apply pattern search optimization technique to carrot chasing guidance law while USV is performing multi-tasks of predefined paths. This novelty significantly reduces both cross tracking errors and computational costs. Firstly, SCCGL is tested and compared with traditional carrot chasing algorithm in the numerical simulator for several navigational conditions such as different lists of waypoints, different initial locations, and different maximum turning rates of USV. SCCGL automatically determines optimal parameters to make stable and accurate navigation. SCCGL significantly reduces cross tracking errors compared to classical carrot chasing algorithm. This is the first contribution of this paper. Secondly, genetic algorithm optimization method has been implemented to carrot chasing guidance law instead of pattern search optimization technique. Genetic algorithm causes the total simulation time to be quite long. The proposed SCCGL (pattern search integrated carrot chasing guidance law) gives optimum results 20 times faster than the genetic algorithm. This is the second and main contribution of developed SCCGL method. It is observed that SCCGL provides best navigation with minimum cross-tracking errors and minimum computational cost compared to the classical carrot chasing algorithm and other optimization technique.

Toward value co-creation in private youth sport for ‘secondary’ consumers: expert coaches’ perceptions of parent–coach collaboration

ABSTRACT Research question Recent evidence suggests parents and coaches would find value in a collaborative relationship. However, the specific roles of parents and coaches in co-creating value remain unclear. Therefore, this research aims to establish expert coaches’ perception of effective collaboration between parents and coaches in the market-driven private youth sport setting. Research methods Semi-structured interviews were conducted with 12 expert coaches to examine their perceptions of effective parent–coach collaboration. Results and findings Through a reflexive thematic analysis, the authors identified four themes explaining expert coaches’ perceptions of parent–coach collaboration in market-driven youth sport experiences. The themes include: (1) balancing individual circumstance and private sport system demands; (2) collaboratively developing programming; (3) establishing flexible relationship parameters and (4) navigating involvement boundaries. Implications These themes were used to create a practical guide for coaches in navigating relationships with ‘secondary’ consumers of youth sport (i.e. parents). Moreover, a theoretical conceptualization of value co-creation for ‘secondary’ consumers of youth sport is offered.

State-of-the-Art: the Use of Extracellular Vesicles and Preparations Based on Them for Neuroprotection and Stimulation of Brain Tissue Regeneration after Injury

Extracellular vesicles are macromolecular complexes produced by virtually all types of eukaryotic and prokaryotic cells. According to modern concepts, they allow cells to exchange information, regulate each other’s activity and coordinate their actions during the complex processes of development, maintaining homeostasis, tissue regeneration, etc. Extracellular vesicles have a number of unique properties: the ability to accumulate certain types of proteins and nucleic acids, protect them from degradation and ensure their delivery to target cells, which can be used to create biomimetic approaches to the therapy of a wide range of diseases. The composition of vesicles, the preference for docking with a particular cell type, and ultimately their therapeutic potential are very flexible parameters and are highly dependent on the type and properties of the producer cell culture, as well as cultivation conditions. This review gives an idea of the state and prospects of the therapeutic strategies implied the application of extracellular vesicles for neuroprotection and stimulation of brain tissue regeneration after injury, and also considers existing clinical studies which use extracellular vesicles in the field of neurology and neurosurgery. Particular attention in the review is given to new promising approaches to increasing the production of extracellular vesicles, manipulating their contents, and increasing the efficiency of targeted docking in order to increase their therapeutic activity and specificity.

Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology

Physics-Informed Neural Networks (PINNs) and extended PINNs (XPINNs) have emerged as a promising approach in computational science and engineering for solving partial differential equations (PDEs) by combining the power of artificial intelligence (AI) with the underlying physics to accurately model and predict the solutions to complex problems in science and engineering. In this work, we propose the augmented physics-informed neural network (APINN), which adopts soft and trainable domain decomposition and flexible parameter sharing to further improve the extended PINN (XPINN) as well as the vanilla PINN methods. Concretely, a trainable gate network is employed to mimic the hard decomposition of XPINN, which can be flexibly fine-tuned for discovering a potentially better partition. The gate network satisfying the partition-of-unity property, weighted averages several sub-networks as the final output. APINN does not require complex interface conditions, whose sub-nets can utilize all training samples rather than just part of the training data in their subdomains. Lastly, each sub-net shares part of the common parameters to capture the similar components in each decomposed function. Furthermore, following the PINN generalization theory (Hu et al., 2022), APINN is shown to improve generalization by proper gate network initialization and general domain & function decomposition. Extensive experiments on different partial differential equations (PDEs) demonstrate how APINN improves PINN and XPINN. Specifically, we present examples where XPINN performs similarly to or worse than PINN, so that APINN can significantly improve both. We also show cases where XPINN is already better than PINN, so APINN can still slightly improve XPINN. Furthermore, we visualize the optimized gating networks and their optimization trajectories, and connect them with their performance, which helps discover the possibly optimal decomposition. Interestingly, if initialized by different decomposition, the performances of corresponding APINNs can differ drastically. This, in turn, shows the potential to design an optimal domain decomposition for the PDE under consideration.

A nomothetic theory of well-being: four functional abilities that promote psychological stability and resilience

As longevity increases, understanding how a person maintains well-being and builds resilience to adversity becomes increasingly important. The present work (a) composes main cognitive elements into a universal psychological multisystem and (b) explains the factors that contribute to the function of this multisystem within physical space and across time. Drawing on established theories and previous findings, a theoretical reconstruction of a universal architecture serves to identify the principles a person needs to satisfy as a dynamic system that is governed by physical laws. A novel conceptual model generates testable hypotheses regarding how a universal cognitive multisystem, which is aided by a universal embodied emotional system, facilitates endless behavioral patterns in response to the environment. This theoretical framework compliments previous models and proposes that the nomothetic parameters of consistency, flexibility, self/others ratio and speed of meaning can explain inter- and intra-individual differences in psychological stability and resilience. The present work provides a comprehensive theory and methodological guidelines for the systematic assessment of well-being. This new approach to investigating well-being may open a new research direction and inform preventive and therapeutic interventions.

Design of A High-Precision Component-Type Vertical Pendulum Tiltmeter Based on FPGA.

This paper presents a high-precision component-type vertical pendulum tiltmeter based on an FPGA (Field Programmable Gate Array) that improves the utility and reliability of geophysical field tilt observation instruments. The system is designed for rapid deployment and offers flexible and efficient adaptability. It comprises a pendulum body, a triangular platform, a locking motor and sealing cover, a ratiometric measurement bridge, a high-speed ADC, and an FPGA embedded system. The pendulum body is a plumb-bob-type single-suspension wire vertical pendulum capable of measuring ground tilt in two orthogonal directions simultaneously. It is installed on a triangular platform, sealed as a whole, and equipped with a locking motor to withstand a free-fall impact of 2 m. The system utilizes a differential capacitance ratio bridge in the measurement circuit, replacing analog circuits with high-speed AD sampling and FPGA digital signal processing technology. This approach reduces hardware expenses and interferences from active devices. The system also features online compilation functionality for flexible measurement parameter settings, high reliability, ease of use, and rapid deployment without the need for professional technical personnel. The proposed tiltmeter holds significant importance for further research in geophysics.

Modeling water transport properties in carbon nanotubes: Interplay between force-field flexibility and geometrical parameters.

Modeling water and other liquids in computational simulations requires a large set of parameters. Many works have been devoted to finding new, improved water models, with almost all of them designed for bulk systems. Here, we use carbon nanotubes as a play model to investigate the effects of introducing flexibility in water force fields during molecular dynamics simulations of nanoconfined water. We explore six different models to show that viscosity, diffusion, and dipole orientation are vastly influenced by the flexibility and the family of force fields used. Particularly, we found the level of confinement (decreasing the nanotube's diameter) to increase discrepancies in the description of the dipole alignment. In smaller (10,10) nanotubes, the flexible version of the transferable intermolecular potential with three points (TIP3P/Fs) features a high directionality, while its rigid counterpart shows a more distributed dipole orientation. Both viscosity and diffusion are also extremely dependent on the force-field family, with the flexible version of the simple point charge (SPC/Fw) featuring the lower confidence interval.

Adaptive VSG control strategy considering energy storage SOC constraints

The virtual synchronous generator (VSG) control strategy is proposed to mitigate the low inertia problem in the power system brought about by the high percentage of distributed generation connected to the grid and the application of power electronic devices. In order to maximize the effectiveness of the advantages of the flexible and adjustable parameters of VSG control, an adaptive VSG control strategy considering SOC constraint of the energy storage unit is proposed in this paper. Considering the significant loss of service life by operating the energy storage unit at its limit state, based on the rate and degree of change in system frequency, the adaptive control strategy realizes the online adaptive adjustment of the inertia factor and damping factor under different perturbation conditions by adaptively adjusting the control parameters when the system frequency oscillates. Finally, the effects of this adaptive VSG control method and conventional VSG control method are compared by simulation in PLECS. Hardware-in-the-loop (HIL) experimental platforms and semi-physical simulation experiments are constructed on RTBOX, and the feasibility and validity of this adaptive VSG control strategy are verified.

Ruling Out New Physics at Low Redshift as a Solution to the H_{0} Tension.

We make the case that there can be no low-redshift solution to the H_{0} tension. To robustly answer this question, we use a very flexible parametrization for the dark energy equation of state such that every cosmological distance still allowed by data exists within this prior volume. To then answer whether there exists a satisfactory solution to the H_{0} tension within this comprehensive parametrization, we constrained the parametric form using different partitions of the Planck cosmic microwave background, SDSS-IV/eBOSS DR16 baryon acoustic oscillation, and Pantheon supernova datasets. When constrained by just the cosmic microwave background dataset, there exists a set of equations of state which yields high H_{0} values, but these equations of state are ruled out by the combination of the supernova and baryon acoustic oscillation datasets. In other words, the constraint from the cosmic microwave background, baryon acoustic oscillation, and supernova datasets together does not allow for high H_{0} values and converges around an equation of state consistent with a cosmological constant. Thus, since this very flexible parametrization does not offer a solution to the H_{0} tension, there can be no solution to the H_{0} tension that adds physics at only low redshifts. This is directly related to the expansion history of the Universe and its geometrical properties and would include models beyond those parametrized by w(z).

Analysis of layout flexibility on the efficiency of airport passenger terminals

The usage of concepts that add flexibility to built spaces by generating the capacity to adapt to new demands is an economically viable and operationally attractive alternative to deal with demand fluctuation. This study aims to analyze the influence of those concepts on the Airport Passenger Terminal's layout by evaluating the performance of the 13 busiest Brazilian airports' check-in areas. It carries out a comparative assessment to establish the main flexibility parameters within the Airport Passenger Terminals. Moreover, it identifies the most efficient characteristics used in the built spaces at the airports. For that, this examination applies the DEA-BCC model oriented to input, analyzing as input data the relation between the check-in area and the total area of the Airport Passenger Terminal building, the number of check-in counters and the waiting time at the queue, and output data the installed capacity of the airports. The results indicate that change in the percentage of check-in area used is the criteria that best reflects the efficiency of an Airport Passenger Terminal.

Quantum MDS codes with new length and large minimum distance

According to the well-known CSS construction, constructing quantum MDS codes are extensively investigated via Hermitian self-orthogonal generalized Reed-Solomon (GRS) codes. In this paper, given two Hermitian self-orthogonal GRS codes GRSk1(A,vA) and GRSk2(B,vB), we propose a sufficient condition to ensure that GRSk(A∪B,vA∪B) is still a Hermitian self-orthogonal code. Consequently, we first present a new general construction of infinitely families of quantum MDS codes from known ones. Moreover, applying the trace function and norm function over finite fields, we give another two new constructions of quantum MDS codes with flexible parameters. It turns out that the forms of the lengths of our quantum MDS codes are quite different from previous known results in the literature. Meanwhile, the minimum distances of all the q-ary quantum MDS codes are bigger than q/2+1.

Using knowledge graphs and contrastive learning for detecting APT Malware on Endpoint systems

Advanced persistent threat (APT) attacking campaigns have been a common method for cyber-attackers to attack and exploit end-user computers (workstations) in recent years. In this study, to enhance the effectiveness of the APT malware detection, a combination of deep graph networks and contrastive learning is proposed. The idea is that several deep graph networks such as Graph Convolution Networks (GCN), Graph Isomorphism Networks (GIN), are combined with some popular contrastive learning models like N-pair Loss, Contrastive Loss, and Triplet Loss, in order to optimize the process of APT malware detection and classification in endpoint workstations. The proposed approach consists of three main phases as follows. First, the behaviors of APT malware are collected and represented as graphs. Second, GIN and GCN networks are used to extract feature vectors from the graphs of APT malware. Finally, different contrastive learning models, i.e. N-pair Loss, Contrastive Loss, and Triplet Loss are applied to determine which feature vectors belong to APT malware, and which ones belong to normal files. This combination of deep graph networks and contrastive learning algorithm is a novel approach, that not only enhances the ability to accurately detect APT malware but also reduces false alarms for normal behaviors. The experimental results demonstrate that the proposed model, whose effectiveness ranges from 88% to 94% across all performance metrics, is not only scientifically effective but also practically significant. Additionally, the results show that the combination of GIN and N-pair Loss performs better than other combined models. This provides a base malware detection system with flexible parameter selection and mathematical model choices for optimal real-world applications.

Analysis of passenger car powertrain system measurements in road conditions

The paper is focused on presenting a methodology for measuring power and torque based on diagnostic equipment available in most diagnostic workshops, such as OBD interfaces or the CAN Bus on-board data transmission network, under real-world road conditions. The publication presents an algorithm for calculating the powertrain’s torque and power based on measurements of changes in vehicle speed or acceleration recording during a two-phase road test. The results presented, based on the method described, apply to both the internal combustion and electric vehicle. Common powertrain operating parameters, such as maximum power, maximum torque and the powertrain’s flexibility parameters described in the literature are proposed for the final evaluation of the vehicle’s traction system.