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Bottom-up methods for coarse-grained (CG) molecular modeling are critically needed to establish rigorous links between atomistic reference data and reduced molecular representations. For a target molecule, the ideal reduced CG representation is a function of both the conformational ensemble of the system and the target physical observable(s) to be reproduced at the CG resolution. However, there is an absence of algorithms for selecting CG representations of molecules from which complex properties, including molecular electronic structure, can be accurately modeled. We introduce continuously gated message passing (CGMP), a graph neural network (GNN) method for atomically decomposing molecular electronic structure sampled over conformational ensembles. CGMP integrates 3D-invariant GNNs and a novel gated message passing system to continuously reduce the atomic degrees of freedom accessible for electronic predictions, resulting in a one-shot importance ranking of atoms contributing to a target molecular property. Moreover, CGMP provides the first approach by which to quantify the degeneracy of "good" CG representations conditioned on specific prediction targets, facilitating the development of more transferable CG representations. We further show how CGMP can be used to highlight multiatom correlations, illuminating a path to developing CG electronic Hamiltonians in terms of interpretable collective variables for arbitrarily complex molecules. [ABSTRACT FROM AUTHOR]

In recent years, it has been demonstrated that the energetic properties of many tetrazole-containing compounds can be enhanced through the formation of the corresponding N-oxides. The introduction of N–O groups increases the oxygen balance of tetrazole compounds, while providing additional coordination sites and enriching the coordination modes between tetrazole compounds and metal ions. The introduction of O atoms alters the polarity of the substance from N to N–O, the packing and density increase and therefore the detonation velocity (VD) and pressure (P) also increase. Based on this, energetic coordination polymers (ECPs) with tetrazole N-oxides serving as ligands possess extremely high research value. In this paper, we aim to summarize the existing ECPs based on tetrazole N-oxides briefly and discuss their advantages, emphasizing their excellent stability and application prospects. [ABSTRACT FROM AUTHOR]

Reconfigurable soft robots exhibit superior flexibility and adaptability when coping with complex environments and variable tasks. However, conventional modular design strategy based on soft actuator modules with specific structure and actuation mode as the basic constructing element for reconfigurable soft robots always has limited reprogrammability or scalability. Here, a hierarchical reconfigurable strategy is reported that not only offers conventional module reconfiguration as the first level to build different robot prototypes, but also provides the elastically‐guided multimodal actuation (contraction, bend, and twist) as the second level which can be reprogrammed to construct different actuator modules. This strategy deepens the modularity to a higher dimensionality and provides more choices for robots to adjust various conformations and functions as needed, for example, a peristalsis robot, an omnidirectional crawling robot, and a soft manipulator can be easily constructed using the module‐level reconfiguration. Moreover, soft manipulators with various preprogrammed deformation trajectories based on the mode reconfiguration are proven to dramatically reduce the operation difficulty and cost in potential applications such as environment detection and human‐robot interaction. This work provides a hierarchical framework for reconfigurable soft robots and may open up a new way for modular design. [ABSTRACT FROM AUTHOR]

The auxetic structure with negative Poisson's ratio has broad application prospects in many engineering fields. Although it is often simplified as a linear elastic problem in theoretical models, the generally used slender structure, such as the reentrant honeycombs, will inevitably undergo large deformation resulting in significant non-conservative load effects in the service conditions. Therefore, a numerical framework for modeling nonlinear deformation of the auxetic structures under follower loads with the complex variable element-free Galerkin method is developed in this paper. The application of the complex variable meshfree method is to deal with the numerical difficulties caused by mesh distortion that may occur in large deformation problems, and at the same time, it can improve the construction efficiency of meshfree shape functions through the complex variable moving least-squares approximation. The Galerkin weak form of the incremental total Lagrangian formula for large deformation problems with the enforced essential boundary conditions using the penalty method is derived and then discretized in the complex variable meshless implementation. Five numerical examples are presented with detailed convergence study to demonstrate the accuracy of the proposed approach in dealing with non-conservative large deformation of the slender auxetic structures. [ABSTRACT FROM AUTHOR]

This paper aims to obtain solutions in terms of the complex potential structure for the plain strain problem of an elastic micropolar and isotropic body with pores. The constitutive equations on which the method is applied and is useful are the well-known equations of the elasticity theory for the above-mentioned body. We intend to solve the Kirch problem using the procedure of complex variables. [ABSTRACT FROM AUTHOR]

To improve data usage in an interdisciplinary context, a clear understanding of the variables being measured is required for both humans and machines. In this paper, the I-ADOPT framework, which decomposes variable names into atomic elements, was tested within the context of continental surfaces and critical zone science, characterized by a large number and variety of observed environmental variables. We showed that the I-ADOPT framework can be used effectively to describe environmental variables with precision and that it was flexible enough to be used in the critical zone science context. Variable names can be documented in detail while allowing alignment with other ontologies or thesauri. We have identified difficulties in modeling complex variables, such as those monitoring fluxes between different environmental compartments and for variables monitoring ratios of physical quantities. We also showed that, for some variables, different decompositions were possible, which could make alignments with other ontologies and thesauri more difficult. The precision of variable names proved inadequate for data discovery services and a non-standard label (SimplifiedLabel) had to be defined for this purpose. In the context of open science and interdisciplinary research, the I-ADOPT framework has the potential to improve the interoperability of information systems and the use of data from various sources and disciplines. [ABSTRACT FROM AUTHOR]

Occlusion presents a major obstacle in the development of pedestrian detection technologies utilizing computer vision. This challenge includes both inter-class occlusion caused by environmental objects obscuring pedestrians, and intra-class occlusion resulting from interactions between pedestrians. In complex and variable urban settings, these compounded occlusion patterns critically limit the efficacy of both one-stage and two-stage pedestrian detectors, leading to suboptimal detection performance. To address this, we introduce a novel architecture termed the Attention-Guided Feature Enhancement Network (AGFEN), designed within the deep convolutional neural network framework. AGFEN improves the semantic information of high-level features by mapping it onto low-level feature details through sampling, creating an effect comparable to mask modulation. This technique enhances both channel-level and spatial-level features concurrently without incurring additional annotation costs. Furthermore, we transition from a traditional one-to-one correspondence between proposals and predictions to a one-to-multiple paradigm, facilitating non-maximum suppression using the prediction set as the fundamental unit. Additionally, we integrate these methodologies by aggregating local features between regions of interest (RoI) through the reuse of classification weights, effectively mitigating false positives. Our experimental evaluations on three widely used datasets demonstrate that AGFEN achieves a 2.38% improvement over the baseline detector on the CrowdHuman dataset, underscoring its effectiveness and potential for advancing pedestrian detection technologies. [ABSTRACT FROM AUTHOR]

A basic solution to the problem of three collinear equal cracks in a transversely isotropic piezoelectric material plate is obtained under the influence of electromechanical forces. Stroh formalism and complex variable methods are used to derive the mathematical expressions for SIF (stress intensity factor), COD (crack opening displacement), and COP (crack opening potential). The length of the saturation zones is investigated at each crack tip under the influence of quadratically varying electric displacement. Furthermore, a numerical study is carried out to discuss the effect of quadratically varying electrical potential on the saturation zone, COD, and COP. The results obtained numerically are reported graphically. [ABSTRACT FROM AUTHOR]

Recent advancements in deep neural networks have shown great potential in generating realistic data and performing clustering tasks. This is due to their ability to capture intricate patterns. However, current generative models face challenges such as poor performance and computational complexity caused by the issue of dimension disaster. The variational autoencoder (VAE), a commonly used method, also encounters problems such as posterior collapse and poor performance in multiclass classification when using the latent variables of VAE. Our goal in this study is to tackle the issue of effective disentanglement in image generation, classification and clustering tasks. We develop a generative network based on VAE incorporating a Gaussian mixture distribution as the prior. This enhancement improves the representation of latent variables and helps to overcome the challenges of matching the ground truth posterior. To further improve clustering performance, we introduce the total correlation as a kernel for computing latent features between embedding points and cluster centers. This technique is particularly useful in cases with complex latent variables and can also be applied for hierarchical disentanglement. Moreover, we employ the Fisher discriminant as a regularization term to minimize the within-class distance and maximize the between-class distance for samples, which has an important effect on the performance of our model viewed from the experimental results. We evaluate our proposed network on four datasets, and the experimental results demonstrate its effectiveness across multiple metrics. [ABSTRACT FROM AUTHOR]

We derive a series-form analytical solution to the thermoelastic problem of an insulated and traction-free crack in a confocal elliptical isotropic elastic inhomogeneity embedded in an infinite isotropic elastic matrix subjected to uniform remote heat flux. Using complex variable techniques such as conformal mapping, analytic continuation and Laurent series expansions, the original thermoelastic problem is reduced to an infinite system of linear algebraic equations, the solution of which will yield the mode I and mode II stress intensity factors at the crack tip. An exact closed-form solution is derived when the inhomogeneity and the matrix have identical shear moduli. Detailed numerical results are presented to demonstrate the series-form and closed-form solutions with an emphasis on the particular case of a vanishingly thin inhomogeneity. [ABSTRACT FROM AUTHOR]

In this article we introduce the notion of double sequences of complex uncertain variables associated with multiplier sequences. We study their different algebraic and topological properties like solidity, symmetricity, completeness etc. [ABSTRACT FROM AUTHOR]

The crux of the present investigation is to come up with a mathematical model for the analysis of moving interfacial crack caused by SH-wave propagating in a composite strip featuring dissimilar orthotropic material. Wiener–Hopf methodology along with complex variable transform technique has been applied to determine the closed form analytical expression of SIF (stress intensity factor). Two different types of loading constraints, viz. NHL (non-harmonic loading) and HL (harmonic loading), on the edges of the crack have been studied. In addition to this, some special cases, viz. constant loading and stress free condition, following aforementioned loading constraints have also been taken into account for the moving crack in the considered composite strip. The limiting case for static condition leading to resonance-type phenomena has been presented for the subject under investigation. When computed numerically and depicted graphically, the profound impacts of distinct material and geometrical parameters on SIF for distinct loading constraints have also been manifested. The computational results bring out the fact that stress intensity factor falls off with rise in crack velocity when the edges of the crack are under NHL, whereas SIF shows reverse nature for HL. [ABSTRACT FROM AUTHOR]

How does right‐wing populism affect public preferences for foreign development aid spending across the liberal/conservative ideological spectrum? This research examines the complex interplay between exposure to right‐wing populist messages targeting aid and political ideology at the mass level in Germany, the United States (U.S.), and the United Kingdom (UK) with data from original survey experiments. First, the experiments indicate that populist rhetoric reduces public support for foreign aid across all countries albeit to varying degrees. Second, the moderating role of political ideology is variable and complex across the different countries. In Germany, populist anti‐aid messages reduce support among voters on the center of the ideological spectrum and among those without clear ideological preferences. In the U.S., anti‐aid messages affect those on the left. In the UK, the effect of populist anti‐aid rhetoric surprisingly does not vary cross ideological groups. Our results have implications for the prospects of public support for development cooperation in the shadow of populism. [ABSTRACT FROM AUTHOR]

Highlights: A LightGBM-based water level prediction model was developed for floodplain lakes. The RMSE values of the model's one-day-ahead prediction range from 0.09 to 0.10 m. The rank of the driving factors of Poyang Lake water level change was identified. Timely and accurate prediction of water levels is crucial for managing floodplain lakes with important ecosystem services, especially for flood prevention. Floodplain lakes are hydrologically complex and incredibly variable systems. Their water levels respond nonlinearly to external disturbances, complicating their prediction. Machine learning methods, especially the ensemble learning strategy, provide an excellent choice for solving such nonlinear problems. Based on the Light Gradient Boosting Machine (LightGBM) method, a water level prediction model was developed for Poyang Lake, the largest freshwater lake in China, featuring seasonal flooding and drying under strong river-lake interaction. Daily lake water levels at typical stations and discharge of the Yangtze River and the five main inflowing rivers from 2003 to 2019 were collected for training and testing the proposed model. Combinations of input variables are important for the model performance. The past information of water levels in Poyang Lake can improve the prediction accuracy significantly. Compared with the predictions without considering past water level information, the root mean square error values of the model considering past water levels have decreased from 0.49 to 0.62 m to 0.09–0.10 m for one-day ahead prediction. Therefore, the proposed model with optimized input variables can be an effective tool for the water level prediction of floodplain lakes. Note that the prediction accuracy decreases with the extension of the prediction period. Importance rank analysis shows that the water levels at different typical stations of Poyang Lake have diverse responses to the Yangtze River and the main five inflowing rivers, providing new insights into river-lake interaction. It also implied that the lake regulation should be deliberately conducted for such a large lake with a complex flow regime. [ABSTRACT FROM AUTHOR]

There are many situations where groundwater flow has high flow rates, causing large seepage forces. Examples are flows around highly conductive fractures and tunnels. We present a new analytic element for a tunnel in an elastic medium. We combined the analytic element method for groundwater flow with that for linear elasticity, and include the seepage force as a body force in the linearly elastic model. We represent tunnels and fractures as analytic elements. The solution for the case considered is limited to steady state flow and fluid-to-solid coupling. We present examples of the computed seepage forces around a tunnel and a fracture as well as a comparison with another numerical model. [ABSTRACT FROM AUTHOR]

Background: Retention of apolipoprotein B (apoB)-containing lipoproteins within the arterial wall plays a major causal role in atherosclerotic cardiovascular disease (ASCVD). There is a single apoB molecule in all apoB-containing lipoproteins. Therefore, quantitation of apoB directly estimates the number of atherogenic particles in plasma. ApoB is the preferred measurement to refine the estimate of ASCVD risk. Low-density lipoprotein (LDL) particles are by far the most abundant apoB-containing particles. In patients with elevated lipoprotein(a) (Lp(a)), apoB may considerably underestimate risk because Mendelian randomization studies have shown that the atherogenicity of Lp(a) is approximately 7-fold greater than that of LDL on a per apoB particle basis. In subjects with increased Lp(a), the association between LDL-cholesterol and incident CHD (coronary heart disease) is increased, but the association between apoB and incident CHD is diminished or even lost. Thus, there is a need to understand the mechanisms of Lp(a), LDL-cholesterol and apoB-related CHD risk and to provide clinicians with a simple practical tool to address these complex and variable relationships. How can we understand a patient's overall lipid-driven atherogenic risk? What proportion of this risk does apoB capture? What proportion of this risk do Lp(a) particles carry? To answer these questions, we created a novel metric of atherogenic risk: risk-weighted apolipoprotein B. Methods: In nmol/L: Risk-weighted apoB = apoB - Lp(a) + Lp(a) x 7 = apoB + Lp(a) x 6. Proportion of risk captured by apoB = apoB divided by risk-weighted apoB. Proportion of risk carried by Lp(a) = Lp(a) × 7 divided by risk-weighted apoB. Results: Risk-weighted apoB agrees with risk estimation from large epidemiological studies and from several Mendelian randomization studies. Conclusions: ApoB considerably underestimates risk in individuals with high Lp(a) levels. The association between apoB and incident CHD is diminished or even lost. These phenomena can be overcome and explained by risk-weighted apoB. [ABSTRACT FROM AUTHOR]

This paper addresses the classification problem of integrable deformations of solutions of “degenerate” Riemann–Hilbert–Birkhoff (RHB) problems. These consist of those RHB problems whose initial datum has diagonal pole part with coalescing eigenvalues. On the one hand, according to theorems of Malgrange, Jimbo, Miwa, and Ueno, in the non-degenerate case, there exists a universal integrable deformation inducing (via a unique map) all other deformations [M. Jimbo, T. Miwa and K. Ueno, Monodromy preserving deformations of linear ordinary differential equations with rational coefficients I, Physica D 2 (1981) 306–352; B. Malgrange, Déformations de systèmes différentiels et microdifférentiels, in Séminaire E.N.S. Mathématique et Physique, eds. L. Boutet de Monvel, A. Douady and J.-L. Verdier, Progress in Mathematics, Vol. 37 (Birkhäuser, Basel, 1983), pp. 351–379; B.Malgrange, Sur les déformations isomonodromiques, II, in Séminaire E.N.S. Mathématique et Physique, eds. L. Boutet de Monvel, A. Douady and J.-L. Verdier, Progress in Mathematics, Vol. 37 (Birkhäuser, Basel, 1983), pp. 427–438; B. Malgrange, Deformations of differential systems, II, J. Ramanujan Math. Soc. 1 (1986) 3–15]. On the other hand, in the degenerate case, Sabbah proved, under sharp conditions, the existence of an integrable deformation of solutions, sharing many properties of the one constructed by Malgrange–Jimbo–Miwa–Ueno [C.Sabbah, Integrable deformations and degenerations of some irregular singularities, Publ. RIMS Kyoto Univ. 57(3–4) (2021) 755–794; arXiv:1711.08514v3]. Albeit the integrable deformation constructed by Sabbah is not, stricto sensu, universal, we prove that it satisfies a relative universal property. We show the existence and uniqueness of a maximal class of integrable deformations all induced (via a unique map) by Sabbah’s integrable deformation. Furthermore, we show that such a class is large enough to include all generic integrable deformations whose pole and deformation parts are locally holomorphically diagonalizable. In itinere, we also obtain a characterization of holomorphic matrix-valued maps which are locally holomorphically Jordanizable. This extends, to the case of several complex variables, already known results independently obtained by Thijsse and Wasow [Ph. G. A.Thijsse, Global holomorphic similarity to a Jordan form, Results Math. 8 (1985) 78–87; W.Wasow, Linear Turning Point Theory (Springer-Verlag, New York, 1985)]. [ABSTRACT FROM AUTHOR]

ABSTRACT The Great Tumulus of Apollonia in northern Greece, with a diameter of ~100 m and a height of 19 m, is among the largest of its kind in the region of the ancient kingdom of Macedonia. It is located north of the ancient city of Apollonia and recently became the focus of limited archaeological excavations, which revealed a looted Macedonian tomb. Archaeological findings and other evidence from the tumulus and its surroundings suggest that it may have been used more than once; therefore, the existence of more tombs in its interior is possible. In this work, we investigate the internal structure of the monument by means of 3‐D seismic travel time tomography. Using direct sparse methods, we calculate efficiently the full model resolution matrix that allows us to investigate the robustness of the tomographic model. Our results suggest a complex structure with variable properties between the east and the western side of the tumulus. We also detect several regions that may be associated with additional burial locations or other possible targets of archaeological interest. [ABSTRACT FROM AUTHOR]

In the geometric theory of functions of a complex variable, the well-known direction is related to the estimates of the products of the inner radii of pairwise non-overlapping domains. This direction is called extreme problems in classes of pairwise non-overlapping domains. One of the problems of this type is considered in the present work. [ABSTRACT FROM AUTHOR]

Consider the motion of a thin layer of electrically conducting fluid, between two closely spaced parallel plates, in a classical Hele-Shaw geometry. Furthermore, let the system be immersed in a uniform external magnetic field (normal to the plates) and let electrical current be driven between conducting probes immersed in the fluid layer. In the present paper, we analyse the ensuing fluid flow at low Hartmann numbers. Physically, the system is particularly interesting because it allows for circulation in the flow, which is not possible in the standard pressure-driven Hele-Shaw cell. We first elucidate the mechanism of flow generation both physically and mathematically. After formulating the problem using complex variables, we present mathematical solutions for a class of canonical multiply connected geometries in terms of the prime function framework developed by Crowdy (Solving Problems in Multiply Connected Domains , SIAM, 2020). We then demonstrate how recently developed fast numerical methods may be applied to accurately determine the flow field in arbitrary geometries. [ABSTRACT FROM AUTHOR]

Considering the holomorphic functions in a polycylindrical domain which are rational in some of the variables for the arbitrary fixed values of other variables, we prove that the functions are representable as a ratio of polynomials in these variables whose coefficients are holomorphic in the remaining variables. We use the Kronecker method for establishing some criterion for the rationality of a holomorphic function of one complex variable in a neighborhood of zero by using the properties of Hankel matrices. [ABSTRACT FROM AUTHOR]

Triple hybrid nanocomplexes based on selenium (Se0) nanoparticles, cellulose polymer carrier (CPC), and the photosensitizer fotoditazine (FD) were synthesized with different sequences of component addition and ratios. The spectral characteristics of these triple nanocomplexes were compared with analogous characteristics of FD and double complexes of variable composition (FD/Se0, CPC/FD, and CPC/Se0) using spectral methods. The synthesized triple hybrid Se-containing nanocomplexes could be promising for photodynamic therapy and diagnostics. [ABSTRACT FROM AUTHOR]

In the rapidly evolving landscape of academic and industrial research, integrating Information Technology (IT) and Multi-Competence (MC) has become crucial for enhancing research quality (RQ). Despite growing recognition of their importance, the mechanisms through which IT and MC influence RQ, particularly through mediating tools like the Research Model Canvas (RM), remain underexplored. This study investigates the relationships between IT, MC, and RQ, with a specific focus on the mediating role of RM. The objective is to identify how IT and MC contribute to improving RQ and determine how much RM facilitates this process. A purposive sampling method was used to select 110 respondents, and data were collected through structured surveys and in-depth interviews. The data were analysed using Structural Equation Modeling with SmartPLS 4, a robust statistical tool for examining complex variable relationships. The findings reveal that while IT directly enhances RQ, it does not significantly affect RM, nor does RM mediate its effect on RQ. Conversely, MC significantly improves RM, which fully mediates its positive impact on RQ, highlighting the critical role of RM in translating competencies into research quality. The implications of this research suggest that organizations aiming to enhance research quality should focus on directly leveraging IT and utilizing strategic frameworks like RM to effectively channel multi-competence resources into improved research outcomes. This approach ensures that diverse skills meaningfully contribute to research success, particularly when mediated through structured models like the Research Model Canvas. [ABSTRACT FROM AUTHOR]

Aiming at the problem of difficulty in allocating channels efficiently for secondary users (SU) in complex and variable cognitive radio systems, this paper proposed a high throughput channel allocation protocol, TKMA protocol. The protocol constructed an utility matrix of user and channel based on primary user (PU) activities, SU real-time service demands, and channel conditions, etc., allocated channels with the objective of maximizing the total utility value of the SU system under the premise of guaranteeing the communication quality of the PUs, and solved the problem by using the improved Kuhn-Munkras algorithm and polling scheduling. To evaluate the performance of the protocol, it established a universal multi-user multi-channel cognitive radio system model, described the packet transmission process using queuing theory, and derived the performance indicators of SU through Markov steady-state solution. The experimental results show that the use of TKMA protocol yields better results in terms of total SU system throughput, average delay, average queue length, rejection rate and other metrics compared with the previously proposed simplification algorithm and the traditional equitable random assignment protocol, which proves the effectiveness of the proposed protocol and system model. [ABSTRACT FROM AUTHOR]

In modern manufacturing, dynamic allocation of resources is key to enhancing production efficiency and competitiveness. With the advancement of intelligent manufacturing and Industry 4.0, the manufacturing environment has become increasingly complex and variable, making traditional static resource allocation methods insufficient for practical needs. This paper aims to explore multi-objective optimization methods for dynamic manufacturing resource allocation by constructing a multi-objective optimization model and proposing an improved NSGA-II algorithm to address this issue. The study demonstrates that the improved algorithm significantly enhances population diversity and global search capability, effectively coping with dynamic manufacturing environments to provide efficient and reliable resource allocation solutions. This research not only offers new insights into dynamic resource allocation but also serves as a valuable reference for related fields. [ABSTRACT FROM AUTHOR]

During the operation of jack-up offshore platforms, the complex and variable seabed geological conditions involved can lead to serious accidents, such as pile leg punctures and platform tilt. The aim of this study is to introduce an early warning method for punctures that ensures the operational safety of these platforms. To accomplish this, a real-time monitoring and controlling system is designed using a programmable logic controller that shares data from sensors measuring displacement, tilt, and pressure. In addition, an experimental device is constructed to simulate a jack-up offshore platform in order to assess the safety response of the control system. The working state of the platform under different working conditions (puncture of one independent pile, same side or diagonal piles, and three-pile linkage) is evaluated by analysing the structural motion response, including platform tilt and foundation pressure. The findings reveal that the system developed in this study accurately detects the tilt condition of the offshore platform, and can ensure the operational safety of jack-up offshore platforms. [ABSTRACT FROM AUTHOR]

The USACE boasts a navigation portfolio of over 19,312 km (12,000 mi) of shallow draft [from 2.74 m (9 ft) to 4.27 m (14 ft)] inland and intracoastal waterways, 20,921 km (13,000 mi) of deep draft [4.27 m (14 ft) and greater] channels, and 400 ports, harbors, and turning basins. To ensure that these channels remain navigable and at congressionally authorized dimensions, channel maintenance practices are performed annually by dredging. Most of these dredging operations are performed by private companies under contract to the USACE districts. With an abundance of navigation channel maintenance needs and a limited dredging fleet, accurate scheduling and the timely arrival of the dredging fleet is required. Project delays due to production issues, weather delays, contracting issues, or both will generally impact future scheduled projects, navigation, and commerce. Nonawardable bids happen when the contractor(s) proposal(s) are too high compared with the Independent Government Estimate (IGE). These nonawardable bids lead to significant time delays, because the USACE district must then engage in bid verification calls, negotiations, the potential cancellation of the contract solicitation, or both and the subsequent resolicitation for work. Therefore, it is extremely important that USACE cost estimates adequately reflect the level of effort the project requires when capturing all project-associated costs. This paper aims to summarize the USACE conceptual approach to dredge cost estimating by highlighting the complex variables that are associated with this type of estimate. [ABSTRACT FROM AUTHOR]

A non‐iterative stress‐displacement solution is proposed in this paper to investigate surrounding rock mass with multiple non‐circular deep tunnels. Compared with the Schwarz alternating method, the proposed method only spends one‐time matrix operation, showing considerable efficiency and accuracy of the matrix solution. First, a matrix solution is formulated to obtain the conformal mapping function for the non‐circular tunnel. Then, in consideration of multiple boundary conditions, the generalized complex variable theory and fast Fourier transform (FFT) algorithm are used to formulate a matrix solution of potential functions. The stress and displacement fields around multiple non‐circular tunnels can be further determined from the matrix solution. A series of numerical examples are conducted to verify the proposed method, perform the convergency study, and discuss the effects of tunnel geometries, distances, and arrangements. The convergency study shows that the more accurate conformal mapping function requires more sampling points in the FFT. In addition, the high stress zone would be amplified if the arrangement of multiple tunnels makes the high stress zone adjacent or overlapped. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology 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.)

We characterize all the Toeplitz operators that are complex symmetric with respect to a class of conjugations induced by a permutation. Our results provide an affirmative answer to a conjecture from a paper of Chattopadhyay et al. (2023) [1]. [ABSTRACT FROM AUTHOR]

Regenerative braking technology is essential for reducing energy consumption in electric vehicles (EVs). This study introduces a method for optimizing the distribution of deceleration forces in front-wheel-drive electric vehicles that complies with the distribution range outlined by ECE-R13 braking regulations and aligns with an ideal braking distribution curve. In addition, using a fuzzy control strategy to manage the complex variables of the regenerative braking process, a robust and adaptable system is developed on the Simulink platform. Tested across various driving cycles are NEDC (New European Driving Cycle), WLTC (World Light Duty Vehicle Test Cycle), FTP-72 (Federal Test Procedure 72), and FTP-75 (Federal Test Procedure 75). The method significantly improves energy efficiency: 13% for WLTC, 16% for NEDC, and 30% for both FTP-72 and FTP-75. The simulation results were compared to regenerative braking control techniques A and B, showing that the proposed control method achieves a higher brake energy recovery rate. This leads to a considerable improvement in the vehicle's energy recovery efficiency. These findings confirm the efficacy of the proposed regenerative brake control system, highlighting its potential to significantly enhance the energy efficiency of electric vehicles. [ABSTRACT FROM AUTHOR]

This paper considers the extension of classical Lagrange interpolation in one real or complex variable to "polynomials of one quaternionic variable". To do this, we develop some aspects of the theory of such polynomials. We then give a number of related multivariate polynomial interpolation schemes for R4 and C2 with good geometric properties, and some aspects of least interpolation and of Kergin interpolation. [ABSTRACT FROM AUTHOR]

Soil erosion is considered to be a prominent problem, and its regular spatial assessment in the watershed is required. Thus, for the present study, the Kodar river basin in Chhattisgarh, India, was chosen for the investigation. Three different models, namely Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), and Unit Power-Based Soil Erosion and Deposition (USPED), were chosen by incorporating remote sensing and GIS platforms and their performance were compared. On the basis of area's varied slope and land usage, the erosion rate was calculated. It was noted that a difference of 33,68632 t, −11570.08 t, and 1023.99 t in the sedimentation values of the USLE, RUSLE, and USPED models, respectively were observed. The observed sedimentation data was validated, and the USPED model was found to be the most authentic model among the selected three models. Hence, the present study will be helpful in better understanding of the complex interactions of the variables involved in predicting net erosion of soil. [ABSTRACT FROM AUTHOR]

Picard's theorem is among the most striking results in complex analysis and plays a decisive role in the development of the theory of entire and meromorphic functions. In this paper, we give an equivalence between Picard's theorem and entire solutions of (i) difference equation Δ η f + a (z) P (f) = 0 in C and (ii) differential equation D k f + h (z) g (f (z)) = 0 in terms of total derivatives in C n . We prove two Picard-type theorems that generalize the results of Lu (Kodai Math J 26:221–229, 2003). In addition, examples have been exhibited to show that certain assumptions in the main result cannot be improved. [ABSTRACT FROM AUTHOR]

Highlights To efficiently design the stiffness of the laminated composite blade‐like structure, an analytical method to assess deformation of variable cross‐section laminated beam under cantilever bending load was developed, in which a local ply density matrix method was introduced to characterize the ply‐up in arbitrary cross‐section after ply drop‐off process and infinitesimal element segment method was used to convert complex variable cross‐section specimen into local equal cross‐section beam structure. The model was validated by the cantilever beam experiment with relative predicted error of stiffness of 5.7%. Inner and outer ply drop‐off models were analyzed using the proposed analytical method. The results show that: (1) stiffness of the outer ply drop‐off model is the highest, at 13.07 N/mm, while that of the inner ply drop‐off model 2 is the lowest, about 17.8% lower than the outer ply drop‐off model; (2) maximum relative deformation difference between the inner ply drop‐off model 2 and outer ply drop‐off model is 21.7% at the free side of the cantilever beam. It indicates that anti‐deformation ability of the variable cross‐section laminated structure can be efficiently designed by the proposed analytical method, especially for the section close to the free side. Developed a bending stiffness prediction method for composite beam. Variable cross‐section feature of the composite laminate was considered. Local ply density matrix method was introduced to characterize ply drop‐off. Proposed method was validated by cantilever beam bending experiment. Inner and outer ply drop‐off models were compared by the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) 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.)

The route to chaos and the phase dynamics of the large scales in a rotating shallow-water model have been rigorously examined through the construction of an autonomous five-mode Galerkin truncated system employing complex variables, useful in investigating how large/meso-scales are destabilized and how their dynamics evolves and transits to chaos. This investigation revealed two distinct transitions into chaotic behaviour as the level of energy introduced into the system was incrementally increased. The initial transition manifests through a succession of bifurcations that adhere to the established Feigenbaum sequence. Conversely, the subsequent transition, which emerges at elevated levels of injected energy, is marked by a pronounced shift from quasi-periodic states to chaotic regimes. The genesis of the first chaotic state is predominantly attributed to the preeminence of inertial forces in governing nonlinear interactions. The second chaotic state, however, arises from the augmented significance of free surface elevation in the dynamical process. A novel reformulation of the system, employing phase and amplitude representations for each truncated variable, elucidated that the phase components present a temporal piece-wise locking behaviour by maintaining a constant value for a protracted interval, preceding an abrupt transition characterised by a simple rotation of ±π, even as the amplitudes display chaotic behaviour. It was observed that the duration of phase stability diminishes with an increase in injected energy, culminating in the onset of chaos within the phase components at high energy levels. This phenomenon is attributed to the nonlinear term of the equations, wherein the phase components are introduced through linear combinations of triads encompassing disparate modes. When the locking durations vary across modes, the resultant dynamics is a stochastic interplay of multiple π phase shifts, generating a stochastic dynamic within the coupled phase triads, observable even at minimal energy injections. [ABSTRACT FROM AUTHOR]

It is the first time in the world that the integrated preset underwater push-out final joint of immersed tube tunnel in the Shenzhen-Zhongshan Link is applied. The final joint push-out section will be pushed out underwater through support rails arranged within the final joint expansion section to complete the closure of the immersed tube tunnel. As an auxiliary installation device that is constantly in contact with the final joint push-out section, the effectiveness of this slide rail directly affects whether the final joint push-out section can be successfully implemented. Therefore, a segmented ultra-high flatness and low friction coefficient final joint push-out section supporting slide rail is developed, which solves the design and process problems such as poor adaptability of the conventional slide rail scheme when bearing complex variable loads, the slide rail structure cannot effectively fix the top slide of the slide rail, the lack of surface flatness of the slide rail steel structure and the difficulty of overall leveling. The reliability of the slide rail in each construction stage is verified by the physical model test. Finally, the slide rail has been successfully applied in the underwater push-out stage of the final joint push-out section, which provides a strong guarantee for the first successful implementation of the whole preset underwater push -out type final joint push-out section. This slide rail structure can provide reference and guidance for similar large-scale structural transportation projects. [ABSTRACT FROM AUTHOR]

Purpose: To develop effective and personalized interventions, it is essential to identify the most critical processes or psychological drivers that impact an individual's well-being. Some processes may be universally beneficial to well-being across many contexts and people, while others may only be beneficial to certain individuals in specific contexts. Method: We conducted three intensive daily diary studies, each with more than 50 within-person measurement occasions, across three data sets (n1 = 44; n2 = 37; n3 = 141). We aimed to investigate individual differences in the strength of within-person associations between three distinct process measures and a variety of outcomes. We utilized a unique idiographic algorithm, known as i-ARIMAX (Autoregressive Integrated Moving Average), to determine the strength of the relationship (Beta) between each process and outcome within individuals ("i"). All of the computed betas were then subjected to meta-analyses, with individuals treated as the "study". Results: The results revealed that the process-outcome links varied significantly between individuals, surpassing the homogeneity typically seen in meta-analyses of studies. Although several processes showed group-level effects, no process was found to be universally beneficial when considered individually. For instance, processes involving social behavior, like being assertive, did not demonstrate any group-level links to loneliness but still had significant individual-level effects that varied from positive to negative. Discussion: Using i-ARIMAX might help reduce the number of candidate variables for complex within-person analyses. Additionally, the size and pattern of i-ARIMAX betas could prove useful in guiding personalized interventions. [ABSTRACT FROM AUTHOR]

The accurate prediction of urban road collapses is of paramount importance for public safety and infrastructure management. However, the complex and variable nature of road subsidence mechanisms, coupled with the inherent noise and non-stationarity in the data, poses significant challenges to the development of precise and real-time prediction models. To address these challenges, this paper develops an Adaptive Difference Least Squares Support Vector Regression (AD-LSSVR) model. The AD-LSSVR model employs a difference transformation to process the input and output data, effectively reducing noise and enhancing model stability. This transformation extracts trends and features from the data, leveraging the symmetrical characteristics inherent within it. Additionally, the model parameters were optimized using grid search and cross-validation techniques, which systematically explore the parameter space and evaluate model performance of multiple subsets of data, ensuring both precision and generalizability of the selected parameters. Moreover, a sliding window method was employed to address data sparsity and anomalies, ensuring the robustness and adaptability of the model. The experimental results demonstrate the superior adaptability and precision of the AD-LSSVR model in predicting road collapse timing, highlighting its effectiveness in handling the complex nonlinear data. [ABSTRACT FROM AUTHOR]

This study provides an in-depth analysis of GAF-Net, a novel model for video-based person re-identification (Re-ID) that matches individuals across different video sequences. GAF-Net combines appearance-based features with gait-based features derived from skeletal data, offering a new approach that diverges from traditional silhouette-based methods. We thoroughly examine each module of GAF-Net and explore various fusion methods at the both score and feature levels, extending beyond initial simple concatenation. Comprehensive evaluations on the iLIDS-VID and MARS datasets demonstrate GAF-Net's effectiveness across scenarios. GAF-Net achieves state-of-the-art 93.2 % rank-1 accuracy on iLIDS-VID's long sequences, while MARS results ( 86.09 % mAP, 89.78 % rank-1) reveal challenges with shorter, variable sequences in complex real-world settings. We demonstrate that integrating skeleton-based gait features consistently improves Re-ID performance, particularly with long, more informative sequences. This research provides crucial insights into multi-modal feature integration in Re-ID tasks, laying a foundation for the advancement of multi-modal biometric systems for diverse computer vision applications. [ABSTRACT FROM AUTHOR]

Lignin represents one of the most abundant plant-derived polymers. It is mostly present in the cell wall, and its primary role is to provide mechanical support to the plant. Chemical processes during wood-pulping yield diverse technical lignins with distinct characteristics. Due to their complex and variable nature, technical lignins are often undervalued and are mainly used as burning fuel in mills. However, various technical lignins have been shown to possess antimicrobial properties. Consequently, there is an increasing interest in understanding the properties and conditions that underlie their antimicrobial characteristics and how we can utilize them for practical applications. This review, for the first time, comprehensively summarized the antimicrobial activities of technical lignins and their potential antimicrobial applications. [ABSTRACT FROM AUTHOR]

In this paper, we take an axiomatic approach to the design of ecological footprint indices. Our focus is put on the heterogeneity of land with respect to types and regions, at the core of an inherent aggregation problem. We propose an axiomatic characterization of the ecological footprint index with two fundamentally new axioms, symmetry and independence, which can resolve the problem of land heterogeneity. It is shown that a unique index, up to an affine transformation, exists meeting the axiom system. This index simplifies the aggregation procedure considerably and avoids the need for a synthetic unit of measurement, like global hectares, as well as complex transformations of variables by means of weighting schemes. Our findings reveal differences with the Global Footprint Network (GFN) index, in particular with regard to the treatment of land heterogeneity. Finally, the axiomatic methodology employed may open up perspectives for the development of ecological measures in general, and especially of measures for sustainability and tipping points. [ABSTRACT FROM AUTHOR]

Unmanned sailboats can convert wind energy with sails to provide power for navigation, which can independently plan routes and collect data without human intervention. They have received increasing attention in recent years due to their low power consumption and strong self-sustainability. Due to the greater difficulty of manipulation, the unmanned sailboats have a weaker maneuverability than the propeller-driven vessels in the complex and variable marine environment. Typically, the turning motion is evaluated to characterize the maneuverability of a vessel, which has rarely been investigated in the existing research on unmanned sailboats. Therefore, this study builds a motion simulation platform for unmanned sailboats based on the 3 m class Petrel Sail to investigate the turning characteristics. The index of the approximate turning circle is introduced based on the turning motion trajectory, which is used to obtain the effect of rudder angle, wind angle, wind speed, and current speed on the turning performance of the sailboat in ideal hydrostatic conditions and under flow disturbance, respectively. Finally, a harbor pool test is conducted with an unmanned sailboat to verify the analysis results, and the errors in maximum transverse distance and maximum advance distance are in the reasonable range, proving the correctness of the theoretical results. The current study also provides theoretical guidance for subsequent research on sailboat manipulation and maneuverability. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Educational Practice & Research is the property of National Taipei University of Education 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.)

This study aims to analyze the distribution characteristics of energy in deeply buried circular tunnels with a revealed cave. Analytical solutions for the stress and elastic strain energies in these tunnels are derived using the complex variable method and compared with numerical solutions obtained from finite element simulations. Subsequently, a parametric study investigates the effects of the cave's orientation, shape, and protrusion on the distribution of elastic strain energy. Finally, the influence of the revealed cave on the stability of the surrounding rock is analyzed using the evaluation index based on energy theory. The conclusions are as follows: the presence of the cave causes elastic strain energy to accumulate in the surrounding rock near the middle of the cave. The smaller the angle between the cave direction and the minimum principal stress, the more severe the energy accumulation near the cave. As the cave's protrusion increases and the b/a ratio of its shape decreases, energy accumulation near the cave becomes more severe. The presence of the cave increases the tendency for tunnel failure. The middle of the cave is susceptible to damage due to the accumulation of strain energy, while the intersection of the cave and the tunnel is more prone to damage because tensile stresses lower the energy threshold for surrounding rock failure. The study indicates that the middle of the cave and the junction between the cave and the tunnel are key areas requiring safety protection during construction. [ABSTRACT FROM AUTHOR]

Global warming has accelerated the frequency and intensity of extreme rainfall events in mountainous areas. Coupled with their vulnerable environment and the impact of intensive human activities, along with the complex and variable causes of flash floods, this exacerbates casualties and property losses. Therefore, this article investigates the triggering mechanisms and potential disaster-causing factors of the extreme "720"flood in the WZD-HGZ basin of Henan. The research results indicate that the flash floods in the WZD-HGZ basin were primarily caused by prolonged heavy rainfall, combined with the complex terrain, obstructive backwater, and human activities. The amplification of the flood mainly occurred in three stages: concentrated runoff from multiple channels, water obstruction caused by the successive collapse of roadbeds and bridges, and the generation of backwater. Besides, due to the lack of basic flood prevention awareness, unclear warnings, and inadequate guidance, the transition chain from issuing warnings to taking action was disrupted. The aforementioned research findings provide references for current flash flood disaster prevention efforts. [ABSTRACT FROM AUTHOR]

Trajectory prediction plays a crucial and indispensable role in autonomous driving, enhancing safety and reliability, particularly in complex intersections with variable vehicle trajectories. This study aims to investigate the application of vehicle trajectory prediction in intersections and to improve the prediction accuracy of the model by utilizing multicolumn neural networks and self-attention mechanisms. Trajectory data were extracted using DataFromSky software from unmanned aerial vehicle (UAV)-captured aerial footage at specific intersections in Xi'an, Shaanxi Province, China. The deep learning model developed for trajectory prediction included a multicolumn (MC) neural network and a self-attention (SA) mechanism based on the gated recurrent unit (GRU). The model was abbreviated as MC-SA-GRU in this study. The multicolumn structure captures richer feature representations, whereas SA captures temporal correlations in time-series data. Experimental comparisons on corresponding data sets demonstrate the exceptional performance of these models in accurately predicting vehicle trajectories at intersections. This study contributes valuable insights for improving autonomous driving systems, advancing safety and reliability in real-world scenarios. Practical Applications: The results of this case study showed that combining deep learning time series models with plug-in modules effectively improved the accuracy of vehicle trajectory prediction. Vehicle trajectory prediction was a highly significant research problem in the field of autonomous driving, particularly in complex intersection scenarios. Accurate vehicle trajectory prediction had the potential to significantly enhance the safety and reliability of self-driving vehicles. The data utilized in this study were collected by an unmanned aerial vehicle at several specific intersections in Xi'an, Shaanxi Province, China. The proposed method was based on gated recurrent units, incorporating multicolumn neural networks to fully explore the potential features of the data, and included a self-attention (SA) mechanism to consider the temporal correlation of the data. It was compared with various benchmark methods, demonstrating excellent performance across various evaluation metrics. Experimental results validated the effectiveness of this approach. Thus, this research provided valuable insights for improving the safety and reliability of real-world autonomous driving systems. [ABSTRACT FROM AUTHOR]

The process of high-speed and high-precision machining is highly dependent on the wear process of the tool, so it is necessary to obtain the accurate identification of the wear state of the tool and the timely prediction of the degradation trend through effective detection methods. However, the influencing factors of the real cutting process are complex and variable. The milling process is a complex spatial deformation process, accompanied by very high cutting accuracy requirements, and it is hard to use VB value, the currently popular singular linear indicator of wear state evaluation, to describe the current wear state of end mills precisely and difficult to make a valid decision proof for subsequent dynamic degradation trends. For these issues, a three-dimensional wear region reconstruction and calculation method for end milling cutters based on bi-sensor monitoring information is proposed in this paper, which can be accurately used to estimate the volume of current wear areas and give more reasonable predictions of future wear trends. Firstly, an in situ wear detection device with a bi-sensor based on an industrial camera and line laser scanner is designed, which can obtain the wear shape and depth information synchronously with high precision. Secondly, aiming at the problem of missing wear information due to uneven furring wear on the rear tool face of the end milling tool, this paper proposes a combined threshold segmentation method to extract the complete tool wear region, which improves the calculation precision of the wear region. Thirdly, the SFS algorithm, which integrates high-precision scale information from line laser data, is utilized to reconstruct the rear tool surface topography. This reconstruction allows for accurate estimation of the wear volume. Finally, the experiment results have shown that the wear volume can reflect the wear state of the tool more quickly and comprehensively compared with the traditional tool wear width standard, and it can provide early warning before the tool enters severe wear condition. [ABSTRACT FROM AUTHOR]

A theoretical model was established to investigate the interaction between hydrogen clusters and edge dislocations emitted from a semi-elliptical surface crack tip in deformed nanometallic materials. The model's solution was obtained by using the complex method, and the influence of the concentration and location of hydrogen clusters, temperature, crack shape, material constants, and the dislocation emission angle on the critical stress intensity factor (SIFs) corresponding to the first dislocation emission from crack tips was investigated through numerical analysis. The results show that dislocations are easily emitted from the crack tip at high hydrogen concentration, and hydrogen clusters close to the crack tip will hinder the emission of dislocations from its crack tip. When considering the influence of hydrogen cluster, an increase in temperature, an extension of crack length or an increase in crack tip curvature radius can all make the emission of dislocations at the crack tip difficult, thereby reducing the toughness of the material caused by dislocation emission. [ABSTRACT FROM AUTHOR]