Discrete Mechanics Research Articles

Relative-kinematic formulation of geometrically exact beam dynamics based on Lie group variational integrators

Geometrically exact beam models can accurately describe the statics and dynamics of elastic, slender beams undergoing large deformations. This work introduces a variational integrator for such models based on a relative-kinematic formulation, in which positions and velocities of nodes in the discretized beam are expressed relative to the respective preceding nodes in the kinematic chain. The resulting model is especially suited for applications in robotics and control, since it has a minimum number of states and possesses the same structure as rigid mechanical systems, simplifying the combined modeling of rigid–flexible systems. Moreover, this approach allows to specifically select the modeled deformation modes, avoiding numerical issues associated with stiff, high-frequency modes and greatly increasing numerical efficiency. The proposed model is derived fully variationally in the discrete mechanics framework and under consistent consideration of the underlying Lie group structure, which translates into beneficial numerical properties. We provide a detailed treatment of the inclusion of dissipation and propose two solver strategies for time integration, including a linear-time solver based on recursive rigid-body dynamics algorithms. The model is validated and analyzed in detailed simulation studies underlining its efficiency for the simulation of stiff and slender beams, where the straightforward, but exact reduction to a Kirchhoff beam in the presented frame leads to a substantial speed-up of the simulations.

Highly Effective Biocides against Pseudomonas aeruginosa Reveal New Mechanistic Insights Across Gram-Negative Bacteria.

Pseudomonas aeruginosa is a major nosocomial pathogen that persists in healthcare settings despite rigorous disinfection protocols due to intrinsic mechanisms conferring resistance. We sought to systematically assess cationic biocide efficacy against this pathogen using a panel of multidrug-resistant P. aeruginosa clinical isolates. Our studies revealed widespread resistance to commercial cationic disinfectants that are the current standard of care, raising concerns about their efficacy. To address this shortcoming, we highlight a new class of quaternary phosphonium compounds that are highly effective against all members of the panel. To understand the difference in efficacy, mechanism of action studies were carried out, which identified a discrete inner-membrane selective target. Resistance selection studies implicated the SmvRA efflux system (a transcriptionally regulated, inner membrane-associated efflux system) as a major determinant of resistance. This system is also implicated in resistance to two commercial bolaamphiphile antiseptics, octenidine and chlorhexidine, which was further validated herein. In sum, this work highlights, for the first time, a discrete inner-membrane specific mechanism for the bolaamphiphile class of disinfectants that contrasts with the prevailing model of indiscriminate membrane interactions of commercial amphiphiles paving the way for future innovations in disinfectant research.

Discrete event-triggered security control for Markovian CVNNs with additive time-varying delays under random deception attacks

This paper is concerned with the security stabilization problem for a class of Complex-valued Neural Networks (CVNNs) with Markov Jump Parameters (MJPs) and Additive Time-varying Delays (ATVDs) under Random Deception Attacks (RDAs). Different from the existing literature, the instant and strength of RDAs considered in this paper is both random, which is more in line with the real situation. Secondly, a general Lyapunov–Krasovskii Functional (LKF) contains more information about MJPs and ATVDs is constructed, and a new Complex-valued Reciprocally Convex Inequality (CVRCI) containing more free matrices and ATVDs parameters is proposed, which play a key role in reducing the conservativeness of security stabilization criteria. Thirdly, a Discrete Event-triggered Mechanism (DETM) is introduced to mitigate the transmission burden of communication networks, in which the triggering condition of DETM mainly relies on the current sampled state and the last triggered state. Then, by combining with the LKF, CVRCI, DETM, and other analysis techniques, some less conservative security stabilization criteria for the underlying systems are provided in terms of Linear Matrix Inequalities (LMIs). Finally, the effectiveness of our results are verified by two numerical examples and a practical example.

Opioid receptors reveal a discrete cellular mechanism of endosomal G protein activation.

Many GPCRs initiate a second phase of G protein-mediated signaling from endosomes, which inherently requires an increase in G protein activity on the endosome surface. Gs-coupled GPCRs are thought to achieve this by internalizing and allosterically activating cognate G proteins again on the endosome membrane. Here we demonstrate that the μ-opioid receptor (MOR), a Gi-coupled GPCR, increases endosomal G protein activity in a different way. Leveraging conformational biosensors, we resolve the subcellular activation dynamics of endogenously expressed MOR and Gi/o-subclass G proteins. We show that MOR activation triggers a transient increase of active-state Gi/o on the plasma membrane that is followed by a prolonged increase on endosomes. Contrary to the Gs-coupled GPCR paradigm, however, we show that the MOR-induced increase of active-state Gi/o on endosomes requires neither internalization of MOR nor activation of MOR in the endosome membrane. We propose a distinct and additional cellular mechanism for GPCR-triggered elevation of G protein activity on endosomes that is mediated by regulated trafficking of the activated G protein rather than its activating GPCR.

Second messenger c-di-AMP regulates multiple antibiotic sensitivity pathways in Mycobacterium smegmatis by discrete mechanisms.

One of the debilitating causes of high mortality in the case of tuberculosis and other bacterial infections is the resistance development against standard drugs. There are limited studies so far to describe how a bacterial second messenger molecule can directly participate in distinctive antibiotic tolerance characteristics of a cell in a mechanism-dependent manner. Here we show that intracellular cyclic di-AMP (c-di-AMP) concentration can modulate drug sensitivity of Mycobacterium smegmatis by interacting with an effector protein or interfering with the 5'-UTR regions in mRNA of the genes and thus causing transcriptional downregulation of important genes in the pathways. We studied four antibiotics with different mechanisms of action: rifampicin, ciprofloxacin, erythromycin, and tobramycin and subsequently found that the level of drug sensitivity of the bacteria is directly proportional to the c-di-AMP concentration inside the cell. Further, we unraveled the underlying molecular mechanisms to delineate the specific genes and pathways regulated by c-di-AMP and hence result in differential drug sensitivity in M. smegmatis.

Measurement method of flexible component pose based on discrete motion actuators

Abstract In order to address the limitations of traditional large discrete motion actuator mechanisms in realizing high-precision inter-axis relationship calibration in manufacturing environments, this paper proposes a new convolutional neural network-based attitude mapping estimation method, component pose using convolutional neural network (CPCNN). The method implicitly encodes the inter-axis relation matrix into the weight parameters of the training neural network, which results in a high degree of integration with existing large discrete motion actuator mechanisms. The CPCNN-based method directly obtains the attitude change of the adjustment cabin by reading the change of each axis of the current motion actuator mechanism in its own coordinate system. This method can overcome the limitations of the experimental process in the traditional calibration methods and improve the accuracy of attitude mapping under the influence of self-weight by selecting better motion parameters through redundant degrees of freedom. The application of this new method will provide an effective solution for the high-precision inter-axis relationship calibration of large discrete motion actuator mechanisms in manufacturing environments, offering new possibilities for improving production efficiency and product quality.

Repositioning Brusatol as a Transmission Blocker of Malaria Parasites.

Currently, primaquine is the only malaria transmission-blocking drug recommended by the WHO. Recent efforts have highlighted the importance of discovering new agents that regulate malarial transmission, with particular interest in agents that can be administered in a single low dose, ideally with a discrete and Plasmodium-selective mechanism of action. Here, our team demonstrates an approach to identify malaria transmission-blocking agents through a combination of in vitro screening and in vivo analyses. Using a panel of natural products, our approach identified potent transmission blockers, as illustrated by the discovery of the transmission-blocking efficacy of brusatol. As a member of a large family of biologically active natural products, this discovery provides a critical next step toward developing methods to rapidly identify quassinoids and related agents with valuable pharmacological therapeutic properties.

Efficient and Effective One-Step Multiview Clustering.

Multiview clustering algorithms have attracted intensive attention and achieved superior performance in various fields recently. Despite the great success of multiview clustering methods in realistic applications, we observe that most of them are difficult to apply to large-scale datasets due to their cubic complexity. Moreover, they usually use a two-stage scheme to obtain the discrete clustering labels, which inevitably causes a suboptimal solution. In light of this, an efficient and effective one-step multiview clustering (E2OMVC) method is proposed to directly obtain clustering indicators with a small-time burden. Specifically, according to the anchor graphs, the smaller similarity graph of each view is constructed, from which the low-dimensional latent features are generated to form the latent partition representation. By introducing a label discretization mechanism, the binary indicator matrix can be directly obtained from the unified partition representation which is formed by fusing all latent partition representations from different views. In addition, by coupling the fusion of all latent information and the clustering task into a joint framework, the two processes can help each other and obtain a better clustering result. Extensive experimental results demonstrate that the proposed method can achieve comparable or better performance than the state-of-the-art methods. The demo code of this work is publicly available at https://github.com/WangJun2023/EEOMVC.

A theory building critical realist evaluation of an integrated cognitive-behavioural fluency enhancing stuttering treatment for school-age children. Part 1: Development of a preliminary program theory from expert speech-language pathologist data.

PurposeThis study initiated a program of research that aims to develop a program theory underlying integrated cognitive-behavioural fluency enhancing stuttering treatments for school-age children. This research asks, what in the treatment program works (or does not work), for whom, in what contexts, and why. MethodsUsing a critical realist evaluation approach, seven speech-language pathologists (SLPs) with extensive experience in treating children who stutter were asked about barriers and facilitators of optimal treatment outcomes within the context of the Comprehensive Stuttering Program - School-aged Children (CSP-SC). From these data discrete resource mechanisms, contexts, within child reasoning mechanisms, and outcomes were derived and a preliminary program theory was proposed. ResultsFacilitating and impeding child physiology, treatment and SLP resource mechanisms, family and school contexts, and within-child mechanisms were identified. Facilitating mechanisms included motivation, personality/psychological characteristics, understanding and trust of the treatment process, experience of speaking with less effort, and self-efficacy. Impeding mechanisms included reduced motivation, impeding personality/psychological characteristics, lack of buy-in, and, for some children, a prohibitive cost of effort in using learned strategies. ConclusionA preliminary program theory was hypothesized which will be further developed in future analysis of data obtained from children and parents who participated in the CSP-SC at the same centre from which the SLPs came. Subsequent research with new cohorts of SLPs, children, and parents from other treatment programs and centres will be needed to establish the generalizability of the program theory generated in this program of research

State of the Art of Coupled Thermo–hydro-Mechanical–Chemical Modelling for Frozen Soils

AbstractNumerous studies have investigated the coupled multi-field processes in frozen soils, focusing on the variation in frozen soils and addressing the influences of climate change, hydrological processes, and ecosystems in cold regions. The investigation of coupled multi-physics field processes in frozen soils has emerged as a prominent research area, leading to significant advancements in coupling models and simulation solvers. However, substantial differences remain among various coupled models due to the insufficient observations and in-depth understanding of multi-field coupling processes. Therefore, this study comprehensively reviews the latest research process on multi-field models and numerical simulation methods, including thermo-hydraulic (TH) coupling, thermo-mechanical (TM) coupling, hydro-mechanical (HM) coupling, thermo–hydro-mechanical (THM) coupling, thermo–hydro-chemical (THC) coupling and thermo–hydro-mechanical–chemical (THMC) coupling. Furthermore, the primary simulation methods are summarised, including the continuum mechanics method, discrete or discontinuous mechanics method, and simulators specifically designed for heat and mass transfer modelling. Finally, this study outlines critical findings and proposes future research directions on multi-physical field modelling of frozen soils. This study provides the theoretical basis for in-depth mechanism analyses and practical engineering applications, contributing to the advancement of understanding and management of frozen soils.

Persistently elevated joint contact stress after periacetabular osteotomy is associated with joint failure at minimum 10-year follow-up.

Periacetabular osteotomy (PAO) is a common treatment for prearthritic hip dysplasia. The goal of this investigation was to determine if computationally assessed hip contact mechanics are associated with joint failure at minimum 10-year follow-up. One hundred patients with hip dysplasia (125 hips) completed patient-reported outcomes an average of 13.8 years (range 10.0-18.0 years) after PAO. 63/125 hips were classified as having failed: 26 converted to total hip arthroplasty (THA) and 37 with significant disability indicated by modified Harris Hip Score (mHHS) ≤ 70. Differences in discrete element analysis-computed contact mechanics were compared between (1) preserved and failed hips, (2) preserved hips and hips that failed by THA, and (3) preserved hips and hips that failed by mHHS ≤ 70. Failed hips had significantly higher preoperative contact stress and exposure metrics (p < 0.001-0.009) than preserved hips. Failed hips also had significantly higher postoperative peak contact stress (p = 0.018), higher mean contact stress (p < 0.001), and smaller contact area (p = 0.044). When assessed based on type of failure, hips that failed by THA had significantly higher postoperative contact stress and exposure metrics than preserved hips (p < 0.001-0.020). In hips that failed by mHHS ≤ 70, mean postoperative contact stress exposure was significantly higher compared to preserved hips (p = 0.043). Despite improved radiographic measures of dysplasia after PAO, pathologic joint contact mechanics can persist and predict treatment failure at minimum 10 years after surgery. Operative and nonoperative techniques specifically intended to reduce harmful contact mechanics in dysplastic hips may have the potential to further improve clinical outcomes after PAO.

Asymptotic in a class of network models with an increasing sub-Gamma degree sequence

. For differential privacy under sub-Gamma noise, we derive the asymptotic properties of a class of network models with binary values with a general link function. In this article, we release the degree sequences of the binary networks under a general noisy mechanism, with the discrete Laplace mechanism as a special case. We establish the asymptotic result, including both consistency and asymptotically normality, of the parameter estimator when the number of parameters goes to infinity in a class of network models. Simulations and a real-data example are provided to illustrate the asymptotic results.

Deciphering the seasonal dynamics of multifaceted aerosol-ozone interplay: Implications for air quality management in Eastern China

We employed an enhanced WRF-Chem to investigate the discrete mechanisms of aerosol-radiation-feedback (ARF), extinction-photochemistry (AEP), and heterogeneous-reactions (AHR) across different seasons in eastern China, aiming to assess the synergistic effects arising from the simultaneous operation of multiple processes on O3 and PM2.5. Our findings demonstrated that ARF fostered the accumulation of pollutants and moisture, initiating two distinct feedback mechanisms concerning O3. The elevation in the NO/NO2 ratio amplified O3 consumption. Increased near-surface moisture diminished upper-level cloud formation, thereby enhancing photolysis rates and O3 photochemical production. The pronounced impact of heightened NO/NO2 on O3 led to a decrease of 0.1–2.7 ppb. When decoupled from ARF, AEP led to a more significant reduction in photolysis rates, resulting in declines in both O3 and PM2.5, except for an anomalous increase observed in summer, with O3 increasing by 1.6 ppb and PM2.5 by 2.5 μg m−3. The heterogeneous absorption of hydroxides in spring, autumn, and winter predominantly governed the AHR-induced variation of O3, leading to a decrease in O3 by 0.7–1 ppb. Conversely, O3 variations in summer were primarily dictated by O3-sensitive chemistry, with heterogeneous absorption of NOy catalyzing a decrease of 2.4 ppb in O3. Furthermore, AHR accentuated PM2.5 by facilitating the formation of fine sulfates and ammonium while impeding nitrate formation. In summer, the collective impact of ARF, AEP, and AHR (ALL) led to a substantial reduction of 6.2 ppb in O3, alleviating the secondary oxidation of PM2.5 and leading to a decrease of 0.3 μg m−3 in PM2.5. Conversely, albeit aerosol substantially depleted O3 by 0.4–4 ppb through their interactions except for summer, aerosol feedback on PM2.5 was more pronounced, resulting in a significant increase of 1.7–6.1 μg m−3 in PM2.5. Our study underscored the seasonal disparities in the ramifications of multifaceted aerosol-ozone interplay on air quality.

A Systematic Deconstruction of Human-Centric Privacy & Security Threats on Mobile Phones

Mobile phones are most likely the subject of targeted attacks, such as software exploits. The resources needed to carry out such attacks are becoming increasingly available and, hence, easily executable, putting users’ privacy at risk. We conducted a systematic literature analysis to understand the relationship between resources and attack feasibility and present a categorisation of social engineering and side-channel attacks on mobile phones focusing on the resources attackers require. Our proposed categorisation levels facilitate an in-depth understanding of how mobile phone attacks can be executed using different combinations of partly simple resources. The analysis reveals that discrete protection mechanisms are insufficient to provide all-inclusive protection. The proposed categorisation assists in building novel solutions for safeguarding users’ privacy from diverse attacks by carefully considering the potential misuse of resources. We conclude by outlining future research directions highlighting the urgent need for a holistic user defense.

Direct Synthesis of Zinc-Blende ZnSe Nanoplatelets.

The distinct optical properties and electronic structures of two-dimensional colloidal nanoplatelets (NPLs) have garnered significant scientific and practical interest. However, concerns regarding the toxicity of cadmium-based NPLs and their limited spectral coverage show the importance of developing nontoxic alternatives. In this study, we devised a new synthetic approach for the direct synthesis of zinc-blende (ZB) ZnSe NPLs. By introducing two different zinc precursors, short-chain metal carboxylate- zinc acetate, and metal halide-zinc chloride, we successfully synthesized two-dimensional ZB ZnSe NPLs. By modifying the reaction parameters, we obtained two different populations of ZnSe NPLs, characterized by the first absorption peak at "343" and "367 nm". Ostwald ripening experiments further confirmed the formation of 2D ZnSe NPLs by the observed discrete growth mechanism. Lastly, we investigated the impact of surface ligands on the excitonic properties of ZB ZnSe NPLs by treating their initially carboxylic acid-capped surface with oleylamine. Remarkably, we observed significant red-shifting in the first excitonic peaks, up to 130 meV, in a reversible manner, demonstrating further tunability of excitonic features in ZnSe NPLs. We anticipate that our findings will serve as a catalyst for further exploration of nontoxic two-dimensional materials, fostering their investigation and application in various fields.

EXPRESS: Constrained Assortment Optimization under the Cross-Nested Logit Model

We study the assortment optimization problem under general linear constraints, where the customer choice behavior is captured by the Cross-Nested Logit model. In this problem, there is a set of products organized into multiple subsets (or nests), where each product can belong to more than one nest. The aim is to find an assortment to offer to customers so that the expected revenue is maximized. We show that, under the Cross-Nested Logit model, the unconstrained assortment problem is NP-hard even when there are only two nests, and the problem is generally NP-hard to approximate to any constant factors. To tackle this challenging problem, we develop a new discretization mechanism to approximate the problem by a linear fractional program with a performance guarantee of [Formula: see text], for any accuracy level ε &gt; 0. We then show that optimal solutions to the approximate problem can be obtained by solving mixed-integer linear programs. We further show that our discretization approach can also be applied to solve a joint assortment optimization and pricing problem, as well as an assortment problem under a mixture of Cross-Nested Logit models to account for multiple classes of customers. Our empirical results on a large number of randomly generated test instances demonstrate that, under a performance guarantee of 90% (i.e., expected revenues are guaranteed to be at least 90% of the optimal revenue), the percentage gaps between the objective values obtained from our approximation methods and the optimal expected revenues are no larger than 1.2%.

Cyclic damage quantification in composite materials using discrete damage mechanics

A method for fatigue damage quantification in composite materials, based on experimental stiffness degradation data for composite laminates subjected to cyclic load is proposed. Discrete damage mechanics theory is used to calculate crack density vs. number of cycles from elastic moduli-reduction data obtained during fatigue experiments. The calculated crack density simplifies fatigue testing by diminishing the need for counting cracks during testing. Accurate results are achieved and reported. The defect-nucleation rate, which controls the fatigue damage rate, is also obtained from processing the modulus-reduction data. It is observed that the defect-nucleation rate has a small scatter and is independent of applied load magnitude. Furthermore, the onset of delamination observed in the experiments correlates very well with the onset of deviation between the predicted and experimental curves of elastic moduli-reduction versus accumulated crack density. An additional parameter, the defect-nucleation threshold, is here proposed to further characterize the fatigue performance of the composite material under stress-controlled fatigue loading, in contrast to thermal fatigue results from the literature. Furthermore, the difference in damage nucleation rate between strain-controlled and stress-controlled was observed and discussed.

A dimension-aware gaining-sharing knowledge algorithm for distributed hybrid flowshop scheduling with resource-dependent processing time

The resource-assisted processing operation involves the coupling of multi-dimensional sub-problem, which poses a challenge in scheduling system. In this study, a dimension-aware gain-sharing knowledge algorithm (DGSK) is presented to address the distributed hybrid flowshop scheduling problem with resource-dependent processing times (DHFSP-RDPT), where the makespan is to be minimized. Firstly, by analyzing the mathematical model of the DHFSP-RDPT, four problem-specific lemmas and two novel resource reallocation rules are proposed. The DGSK begin with a high-performance initial population, which is generated by three knowledge-driven heuristics in hybrid way. Next, a discrete evolution-based search mechanism assists the DGSK to extend the search in solution space. Furthermore, a dimension-aware two-stage local search combined with meta-Lamarckian learning method is embedded to enhance the local search ability for the multidimensional problems. Finally, the proposed algorithm is measured on a series of instances based on real production data. The results demonstrate that the DGSK improves the performance by in solving DHFSP-RDPT compared to the state-of-the-art methods.

Busting the blackbox between managerial coaching behaviors and employee outcomes from a perspective of discrete emotional process mechanism

PurposeAs coaching assumes an increasingly critical role in satisfying employees' demands for growth, the function of coaching has progressively shifted towards direct supervisors. This study seeks to investigate the distinct effects of managerial coaching behaviors on employee outcomes from an emotional perspective. Specifically, we aim to explore whether leaders' encourage-to-explore and guide-to-learn behaviors impact employees' creativity and performance through discrete emotional mechanisms upon appraisal theory of emotion.Design/methodology/approachWe conducted two studies to test our proposition. In study 1, an experiment using coaching scenarios was performed with 128 students majoring in management. In study 2, data were collected from 311 supervisor-subordinate dyads.FindingsThe results indicate that encourage-to-explore behaviors are positively related to employee creativity by fostering feelings of inspiration, and guide-to-learn behaviors are positively related to employee performance by alleviating anxiety. These findings suggest that different leaders’ coaching behaviors influence employee outcomes through different emotional processes. The theoretical and practical implications of the findings are also discussed.Originality/valueThese findings suggest that different leaders’ coaching behaviors influence employee outcomes through different emotional processes. The theoretical and practical implications of the findings are also discussed.

Comparative cofactor screens show the influence of transactivation domains and core promoters on the mechanisms of transcription.

Eukaryotic transcription factors (TFs) activate gene expression by recruiting cofactors to promoters. However, the relationships between TFs, promoters and their associated cofactors remain poorly understood. Here we combine GAL4-transactivation assays with comparative CRISPR-Cas9 screens to identify the cofactors used by nine different TFs and core promoters in human cells. Using this dataset, we associate TFs with cofactors, classify cofactors as ubiquitous or specific and discover transcriptional co-dependencies. Through a reductionistic, comparative approach, we demonstrate that TFs do not display discrete mechanisms of activation. Instead, each TF depends on a unique combination of cofactors, which influences distinct steps in transcription. By contrast, the influence of core promoters appears relatively discrete. Different promoter classes are constrained by either initiation or pause-release, which influences their dynamic range and compatibility with cofactors. Overall, our comparative cofactor screens characterize the interplay between TFs, cofactors and core promoters, identifying general principles by which they influence transcription.