Central Path Research Articles

The effect of fatigue on climbing fluidity and hand movements

ABSTRACT In rock climbing, climbers use their arms to regulate their posture on the wall, which can lead to localised muscle fatigue. Evidence shows fatigue is the primary cause of falls, but little is known about how fatigue specifically affects climbing rhythm and hand movements. The present study examined climbing fluidity and hand movements on an indoor climbing wall before and after a specific fatiguing protocol. Seventeen climbers completed three repetitions of a challenging climbing route (21 on Ewbank scale) with different levels of localised arm fatigue. Climbers’ movements were tracked using 3D motion capture, and their hand actions assessed using notational analysis. Seventy markers were used to create 15 rigid body segments and the participants' centre of mass. The global entropy index was calculated on the path of the participants' centre of mass. Climbers fell more often when fatigued, but there were no significant differences in hip jerk or global entropy index when fatigued. No significant differences were found between the number of exploratory or performatory hand movements with different amounts of fatigue. The results suggest that localised arm fatigue affects a climber’s ability to prevent themselves from falling, but it does not specifically affect their fluidity.

Urban Surface Ozone Concentration in Mainland China during 2015-2020: Spatial Clustering and Temporal Dynamics.

Urban ozone (O3) pollution in the atmosphere has become increasingly prominent on a national scale in mainland China, although the atmospheric particulate matter pollution has been significantly reduced in recent years. The clustering and dynamic variation characteristics of the O3 concentrations in cities across the country, however, have not been accurately explored at relevant spatiotemporal scales. In this study, a standard deviational ellipse analysis and multiscale geographically weighted regression models were applied to explore the migration process and influencing factors of O3 pollution based on measured data from urban monitoring sites in mainland China. The results suggested that the urban O3 concentration in mainland China reached its peak in 2018, and the annual O3 concentration reached 157 ± 27 μg/m3 from 2015 to 2020. On the scale of the whole Chinese mainland, the distribution of O3 exhibited spatial dependence and aggregation. On the regional scale, the areas of high O3 concentrations were mainly concentrated in Beijing-Tianjin-Hebei, Shandong, Jiangsu, Henan, and other regions. In addition, the standard deviation ellipse of the urban O3 concentration covered the entire eastern part of mainland China. Overall, the geographic center of ozone pollution has a tendency to move to the south with the time variation. The interaction between sunshine hours and other factors (precipitation, NO2, DEM, SO2, PM2.5) significantly affected the variation of urban O3 concentration. In Southwest China, Northwest China, and Central China, the suppression effect of vegetation on local O3 was more obvious than that in other regions. Therefore, this study clarified for the first time the migration path of the gravity center of the urban O3 pollution and identified the key areas for the prevention and control of O3 pollution in mainland China.

Emergence of Classicality in Stern–Gerlach Experiment via Self‐Gravity

AbstractEmergence of classicality from quantum mechanics, a hotly debated topic, has had no satisfactory resolution so far. Various approaches including decoherence and gravitational interactions have been suggested. In the present work, the Schrödinger–Newton model is used to study the role of semi‐classical self‐gravity in the evolution of massive spin‐1/2 particles in a Stern‐Gerlach experiment. For small mass, evolution of the initial wavepacket in a spin superposition shows a splitting in the magnetic field gradient into two trajectories as in the standard Stern–Gerlach experiment. For larger mass, the deviations from the central path are less than in the standard Stern–Gerlach case, while for high enough mass, the wavepacket does not split, and instead follows the classical trajectory for a magnetic moment in inhomogeneous magnetic field. This indicates the emergence of classicality due to self‐gravitational interaction when the mass is increased. In contrast, decoherence which is a strong contender for emergence of classicality, leads to a mixed state of two trajectories corresponding to the spin‐up and spin‐down states, and not the classically expected path. The classically expected path of the particle probably cannot be explained even in the many‐worlds interpretation of quantum mechanics. Stern–Gerlach experiments in the macroscopic domain are needed to settle this question.

A new search direction of IPM for horizontal linear complementarity problems

This study presents a new search direction for the horizontal linear complementarity problem. A vector-valued function is applied to the system of xy=μe, which defines the central path. Usually, the way to get the equivalent form of the central path is using the square root function. However, in our study, we substitute a new search function formed by a different identity map, which obtains the equivalent shape of the central path using the square root function. We get the new search directions from Newton’s Method. Given this framework, we prove polynomial complexity for the Newton directions. We show that the algorithm’s complexity is O(nlognϵ), which is the same as the best-given algorithms for the horizontal linear complementarity problem.

Clearness qualitative comparative analysis of the spread of TikTok health science knowledge popularization accounts.

This study analyzed the popularity of TikTok health knowledge popularization accounts with the objective of creating a template for accounts suited to widely disseminating information, thereby enhancing the public's access to health knowledge on a broader scale. This study is based on 40 Chinese TikTok short video accounts that were active from February to April 2022 and were engaged in health science popularization. Data were validated by structured calibration using three qualitative anchors. It employs the "content-context" and the elaboration likelihood models as the theoretical framework. A qualitative comparative analysis is used to explore the factors affecting the popularity of this type of account mechanism. Among the nine variables involved in the calculation, one reached 0.909091, demonstrating that the number of followers was both a necessary factor and a condition for the popularity of short health science video accounts. There were 16 paths in the complex solution with a consistency of 1, and their overall coverage reached 0.878788, indicating that approximately 87% of the cases could be explained. From the spread of the content and communication situation, professional medical knowledge, current hot topics, professionals, and serious issues were the most likely combinations for rapid spread. From the perspective of the central and edge paths, "likes" exceeding 100,000 and fans exceeding 1 million were essential combinations. The dissemination of medical knowledge has gained significant traction, especially with regard to trending and popular topics. When it comes to the tone of communication, a serious style proved effective in fostering what can be termed "hot communication." From the standpoint of central and peripheral paths, it is crucial that the number of likes in the past month and the total number of fans surpass 100,000 and one million, respectively.

Tikhonov regularization of a nonhomogeneous first-order evolution equation

We consider a nonhomogeneous first-order evolution equation governed by a maximal monotone operator $ A $ in a Hilbert space in the presence of a Tikhonov regularization term. We study the existence and strong convergence of weak solutions to such systems. With boundedness conditions on the central path or on the solution trajectory, without assuming the zero set of $ A $ to be nonempty and with suitable assumptions on the Tikhonov regularization coefficient, we prove that the weak solutions to the system converge strongly to the element of least norm in the zero set of $ A $. As a consequence, we provide sufficient conditions where the boundedness of the weak solutions to the nonhomogeneous Tikhonov system is equivalent to the zero set of $ A $ to be nonempty. Our work is motivated by [4,17,22] and extends some results by those authors.

Large-step predictor-corrector interior point method for sufficient linear complementarity problems based on the algebraic equivalent transformation

We introduce a new predictor-corrector interior-point algorithm for solving P⁎(κ)-linear complementarity problems which works in a wide neighbourhood of the central path. We use the technique of algebraic equivalent transformation of the centering equations of the central path system. In this technique, we apply the function φ(t)=t in order to obtain the new search directions. We define the new wide neighbourhood Dφ. In this way, we obtain the first interior-point method, where not only the central path system is transformed, but the definition of the neighbourhood is also modified taking into consideration the algebraic equivalent transformation technique. This gives a new direction in the research of interior-point algorithms. We prove that the interior-point method has O((1+κ)nlog⁡((x0)Ts0ϵ)) iteration complexity. Furthermore, we show the efficiency of the proposed predictor-corrector algorithm by providing numerical results. To our best knowledge, this is the first predictor-corrector interior-point algorithm which works in the Dφ neighbourhood using φ(t)=t.

CFD Analysis of Spiral Flow Fields in Proton Exchange Membrane Fuel Cells

Proton exchange membrane fuel cells (PEMFCs) are largely used in various applications because of their pollution-free products and high energy conversion efficiency. In order to improve the related design, in the present work a new spiral flow field with a bypass is proposed. The reaction gas enters the flow field in the central path and diffuses in two directions through the flow channel and the bypass. The bypasses are arranged incrementally. The number of bypasses and the cross-section size of the bypasses are varied parametrically while a single-cell model of the PEMFC is used. The influence of the concentration of liquid water and oxygen in the cell on the performance of different flow fields is determined by means of Computational fluid dynamics (COMSOL Multiphysics software). Results show that when the bypass number is 48 and its cross-sectional area is 0.5 mm2, the cell exhibits the best performances.

Research on Cold Chain Routing Optimization of Multi-distribution Center Considering Traffic Performance Index

In response to the practical situation where traffic congestion factors reduce the distribution efficiency and increase the cost of cold chain logistics in the actual transportation process, a mathematical model for optimizing the cold chain path of multiple distribution centers is established, with the goal of minimizing the comprehensive cost and incorporating a traffic congestion index. By analyzing routine factors such as customer requested time windows, loading and unloading time, and road congestion, an improved particle swarm algorithm that introduces exchange offspring is proposed. The proposed method is tested through experimental simulations and the results are compared with traditional methods. The results show that considering the traffic congestion index saves 7.12% of the comprehensive cost compared to not considering the traffic congestion index, and completes the delivery service with a shorter path length.

A new search direction for full-Newton step infeasible interior-point method in linear optimization

In this work, we investigate a full Newton step infeasible interior-point method for linear optimization based on a new search direction which is obtained from an algebraic equivalent transformation of the central path system. Furthermore, we prove that the proposed method obtains an ε-optimal solution to the original problem in polynomial time.

Tube-based MPC of hierarchical distribution network for voltage regulation considering uncertainties of renewable energy

• A novel model for low-voltage distribution areas based on genetic algorithm is developed, which simplifies the complexity of online computation and suppresses the inner voltage deviations in a safe section. • The coordination of PVs and ESs at different voltage levels is promoted to improve the voltage regulation while short of the reactive power capacity of PVs. • A tube-based MPC controller is proposed for voltage fluctuation under uncertainties introduced by power disturbance and a genetic-algorithm-based equivalent model of low-voltage areas, with which a distribution network can work in common conditions under variable operations of PVs. With the ever-growing penetration of distributed generators (DGs), voltage deviation caused by randomness and fluctuation has become increasingly prominent in distribution networks. Conventional voltage control cannot sufficiently utilize the rapid and flexible characteristics of DGs. In this paper, a tube-based model predictive control (TMPC) method is proposed to address voltage violation and fluctuation difficulties considering the uncertainties of renewable energy. Firstly, a simplified model approach based on a genetic algorithm (GA) is proposed to unify numerous DGs in low-voltage distribution areas. Then, based on this simplified model combined with the voltage sensitivity model, the TMPC controller is designed for the whole distribution network, which consists of two subsidiary controllers to suppress voltage deviation caused by uncertainties. The former is used to generate a central path for different operating points of the grid, and the latter is designed to track the path in a bound tube. The proposed method can cope with the uncertainties caused by external disturbances such as drastic power fluctuations. Finally, the numerical simulation in the case studies demonstrates the effectiveness of the proposed method in accuracy and efficiency.

Finding the most degree-central walks and paths in a graph: Exact and heuristic approaches

In network analysis, node centrality is used to quantify the importance of a node to the structure of the network. One of the most natural and widely used centrality measures is degree centrality, defined as the number of nodes adjacent to a given node. A simple generalization of this concept that arises in many real-life applications is to consider the centrality of node groups, including subgraphs with specific connectivity properties. In this paper, we consider the problem of finding the most central walk in a network, where the centrality of the walk is given by the size of its immediate neighborhood. We begin with the problem of finding the most central shortest path and show that this problem can be solved in polynomial time. We then focus on finding other types of most central walks, such as general walks, trails, paths, and induced paths of some pre-defined length. We demonstrate that in contrast to the most central shortest path problem, these problems are NP-hard. We propose two types of linear MIP formulations to solve these problems exactly that rely on two interpretations of a walk: a sequence of visited nodes and a sequence of traversed edges. In addition, we develop two heuristic algorithms and demonstrate their effectiveness by comparing them with the exact solutions obtained using MIPs; we also exploit heuristic solutions to warm-start the MIP solver. Finally, we test our solution approaches using synthetic and real-life networks in an extensive computational study, which allows us to provide some interesting insights and observations.

The Impact of Popular Science Articles by Physicians on Their Performance on Online Medical Platforms.

The public demand for popular science knowledge regarding health is increasing, and physicians' popular science practices on online medical platforms are becoming frequent. Few studies have been conducted to address the relationship between specific characteristics of popular science articles by physicians and their performance. This study explored the impact of the characteristics of popular science articles on physicians' performance based on the elaboration likelihood model (ELM) from the central path (topic focus and readability) and the peripheral path (form diversity). Data on four diseases, namely, lung cancer, brain hemorrhage, hypertension, and depression, were collected from an online medical platform, resulting in relevant personal data from 1295 doctors and their published popular science articles. Subsequently, the independent variables were quantified using thematic analysis and formula calculation, and the research model and hypotheses proposed in this paper were verified through empirical analysis. The results revealed that the topic focus, readability, and form diversity of popular science articles by physicians had a significant positive effect on physicians' performance. This study enriches the research perspective on the factors influencing physicians' performance, which has guiding implications for both physicians and platforms, thereby providing a basis for patients to choose physicians and enabling patients to receive popular science knowledge regarding health in an effective manner.

The ciliary zonules provide a pathway for immune cells to populate the avascular lens during eye development.

The eye is an immune-privileged site, with both vasculature and lymphatics absent from the central light path. Unique adaptations have made it possible for immune cells to be recruited to this region of the eye in response to ocular injuries and pathogenic insults. The induction of such immune responses is typically activated by tissue resident immune cells, considered the sentinels of the immune system. We discovered that, despite the absence of an embedded vasculature, the embryonic lens becomes populated by resident immune cells. The paths by which they travel to the lens during development were not known. However, our previous studies show that in response to corneal wounding immune cells travel to the lens from the vascular-rich ciliary body across the zonules that link these two tissues. We now examined whether the zonule fibers provide a path for immune cells to the embryonic lens, and the zonule-associated matrix molecules that could promote immune cell migration. The vitreous also was examined as a potential source of lens resident immune cells. This matrix-rich site in the posterior of the eye harbors hyalocytes, an immune cell type with macrophage-like properties. We found that both the zonules and the vitreous of the embryonic eye contained fibrillin-2-based networks and that migration-promoting matrix proteins like fibronectin and tenascin-C were linked to these fibrils. Immune cells were seen emerging from the ciliary body, migrating along the ciliary zonules to the lens, and invading through the lens capsule at its equator. This is just adjacent to where immune cells take up residence in the embryonic lens. In contrast, the immune cells of the vitreous were not detected in the region of the lens. These results strongly suggest that the ciliary zonules are a primary path of immune cell delivery to the developing lens.

A novel joint element parameter calibration procedure for the combined finite-discrete element method

The combined finite–discrete element method (FDEM) has been widely used to simulate the fracture process of rock materials. The FDEM simulation requires many material parameters which should be calibrated through laboratory tests or directly cited from previous conclusions. However, it is difficult to obtain the joint element parameters, including the joint element penalty Pf and the type I and type II fracture energies GI and GII. Therefore, a novel calibration method for the above three parameters must be proposed. First, Pf can be obtained by uniaxial compression simulation, and Pf = 30E (E is Young’s modulus) is applicable for homogeneous and isotropic rock materials. Second, an accurate GI value in the static loading state can be obtained by Brazilian disc simulation with a central preprepared failure path. Third, an accurate GII value can be calibrated by the modified variable-angle shear model. Finally, the GI and GII values with different element sizes can be calculated by the proposed linear equations. In addition, normal uniaxial and triaxial compression simulations can be used to verify the reliability of the calibrated GI and GII values. Moreover, the tunnel excavation simulation results show that the joint element parameters calibrated by the modified method can achieve cross-scale simulation, and the simulation results are more accurate.

Nasal-Skull Base Fast Path Extraction and Automatic Navigation

In the nasal-skull base virtual endoscope, the existing navigation path extraction algorithms have low operation efficiency, and automatic navigation algorithm is easy to cause violent rotation of image. Therefore, a center path extraction algorithm based on navigation area pre-planning and an automatic navigation algorithm based on adaptive speed and rotation are proposed. The former improves the distance transformation method. The navigation area is pre-planned based on the fast expanding random tree and calculate the boundary distance field map, and construct the maximum cost tree to extract the center path. The latter improves the DoTween method. The camera moving speed is adjusted according to the length of the shortest line segment in the path, and the predicted steering distance is adjusted according to the cavity diameter at the vertex in the path. Experiments are conducted with nasal models from DICOM. The results show that the path extraction speed of the center path extraction algorithm based on navigation area pre-planning method is about 49 times faster than the distance transformation method, and the automatic navigation algorithm of adaptive speed and rotation is more natural at the vertices comparing with methods such as DoTween.

Controlling the photoluminescence of quantum emitters in hexagonal boron nitride by external magnetic fields

The recent observation of room temperature spin-dependent photoluminescence (PL) emission from hexagonal boron nitride’s (h-BN’s) defect centers motivates for performing a complementary low-temperature photophysical study of quantum emitters under relatively high magnetic fields. Here, we investigate the PL emission dynamics of h-BN’s visible single-photon emitters under an applied out-of-plane magnetic field at cryogenic temperatures. The PL intensity of the emitters in our work strikingly exhibits strong magnetic field dependence and decreases with the increased magnetic field. A substantial decrease in the integrated PL intensity of the emitters by up to one order of magnitude was observed when the applied field is increased from 0 T to 7 T. The observed reversible photodarkening of PL emission due to the applied magnetic field is in very well agreement with the predictions of a recent joint experimental and theoretical study and can happen only if the spin-selective, non-radiative, and asymmetric intersystem crossing transitions proceed from the triplet excited state to the lowest-lying spin-singlet metastable state and from the metastable state to the triplet ground state. Our results not only shed more light on the light emission paths of defect centers in h-BN but also show the use of the magnetic field as an efficient control knob in the development of magneto-optical devices.

A New Ai–Zhang Type Interior Point Algorithm for Sufficient Linear Complementarity Problems

In this paper, we propose a new long-step interior point method for solving sufficient linear complementarity problems. The new algorithm combines two important approaches from the literature: the main ideas of the long-step interior point algorithm introduced by Ai and Zhang and the algebraic equivalent transformation technique proposed by Darvay. Similar to the method of Ai and Zhang, our algorithm also works in a wide neighborhood of the central path and has the best known iteration complexity of short-step variants. However, due to the properties of the applied transforming function in Darvay’s technique, the wide neighborhood definition in the analysis depends on the value of the handicap. We implemented not only the theoretical algorithm but a greedy variant of the new method (working in a neighborhood independent of the handicap) in MATLAB and tested its efficiency on both sufficient and non-sufficient problem instances. In addition to presenting our numerical results, we also make some interesting observations regarding the analysis of Ai–Zhang type methods.

Analytical Study on the Steady-State Thermal Blooming of Incoherent Combining Beam

The incoherent combined beam of lasers has many important applications due to its simple technology and excellent expansibility. Thermal blooming is one factor that will seriously affect the propagation of the combined beam in the atmosphere. Based on the analytical expression of thermal blooming for a Gaussian beam, the thermal blooming of the incoherent combined beam with a basic arrangement was studied and analyzed. From the evolution of thermal blooming for the incoherent combined beam with a basic arrangement, the thermal blooming for the incoherent combined beam with a complex arrangement can be predicted. As an example, incoherent beams with seven channels were studied. Results show that the thermal lens effect will split the beam located at the central path of heat into two parts.

Project Attribute Information and Initiator’s Commitment in Crowdfunding Message Strategy: An Empirical Investigation of Financing Performance in Agri-Food Crowdfunding

Agri-food crowdfunding, a new financing method, not only solves the financing constraints in agricultural development, but also realizes the effective connection between agricultural products and the market. Thus, exploring the impact of project factors on financing performance can help initiators design scientific and reasonable crowdfunding project plans. Based on the trust theory and the elaboration likelihood model (ELM), the trust mechanism is constructed with the characteristic attributes as the central path, the competitive attributes as the edge path, and the commitment as the mediator. Using the data of 1166 agri-food crowdfunding projects on the Taobao crowdfunding platform, I investigate the impact of disclosed project attribute information on financing performance and the mediating role of project risk. The results show that projects with a detailed explanation of the crowdfunding reason and the capital uses, a low funding goal, product qualification certificates issued by authoritative institutions, multiple types of rewards, a short reward delivery time, and a low investment threshold achieve good financing performance. The factor of commitment plays an intermediary role in the relationship between project attributes and financing performance. Based on the research conclusions, practical enlightenment is proposed for initiators, crowdfunding platforms, and regulators.