Current Models Research Articles

Evidence for an RNAi-independent role of Arabidopsis DICER-LIKE2 in growth inhibition and basal antiviral resistance.

Flowering plant genomes encode four or five DICER-LIKE (DCL) enzymes that produce small interfering RNAs (siRNAs) and microRNAs, which function in RNA interference (RNAi). Different RNAi pathways in plants effect transposon silencing, antiviral defense, and endogenous gene regulation. DCL2 acts genetically redundantly with DCL4 to confer basal antiviral defense. However, DCL2 may also counteract DCL4 since knockout of DCL4 causes growth defects that are suppressed by DCL2 inactivation. Current models maintain that RNAi via DCL2-dependent siRNAs is the biochemical basis of both effects. Here, we report that DCL2-mediated antiviral resistance and growth defects cannot be explained by the silencing effects of DCL2-dependent siRNAs. Both functions are defective in genetic backgrounds that maintain high levels of DCL2-dependent siRNAs, either with specific point mutations in DCL2 or with reduced DCL2 dosage because of heterozygosity for dcl2 knockout alleles. Intriguingly, all DCL2 functions require its catalytic activity, and the penetrance of DCL2-dependent growth phenotypes in dcl4 mutants correlates with DCL2 protein levels but not with levels of major DCL2-dependent siRNAs. We discuss this requirement and correlation with catalytic activity but not with resulting siRNAs, in light of other findings that reveal a DCL2 function in innate immunity activation triggered by cytoplasmic double-stranded RNA.

Localized Oxygen Control in a Microfluidic Osteochondral Interface Model Recapitulates Bone–Cartilage Crosstalk During Osteoarthritis

AbstractOsteoarthritis (OA) is characterized by the dysregulation of the osteochondral interface between bone and cartilage. In vitro, osteochondral models are crucial for studying OA and testing treatments. However, current models are limited to replicating the extracellular matrix's structural and mechanical heterogeneity and do not account for the distinct oxygen gradients that chondrocytes and osteoblasts experience at the osteochondral interface. By using micropatterned granular hydrogels to control oxygen scavenging agents' delivery, maintaining <1% oxygen concentration in standard cell culture conditions. These hypoxic hydrogels allow primary human chondrocytes to exhibit a more anabolic phenotype, akin to hypoxic incubator conditions. Patterning of the hydrogels in a microfluidic device creates localized hypoxic environments that mimic the osteochondral interface, enabling co‐culture of chondrocytes with osteoblasts from non‐sclerotic and sclerotic subchondral bone. This co‐culture in differential oxygen conditions revealed that sclerotic osteoblasts induce collagen expression changes in chondrocytes through MMP13 and ADAM15 production, a phenomenon not observed in uniform oxygen environments. Additionally, this model uncovered extensive transcriptional changes involving NF‐κβ, TGF‐β/BMP, and IGF signaling pathways, induced by sclerotic osteoblasts, which are undetectable in normoxic co‐cultures. The microfluidic model with localized oxygen variations effectively simulates osteoblast‐chondrocyte interactions, offering significant insights into OA pathophysiology.

Robust adaptive Kalman filter for structural performance assessment

SummaryStructural performance assessment is a critical stage in the health monitoring for the maintenance and risk management of engineering structures, in which the interstory drift is a key indicator. In this paper, a robust adaptive Kalman filter is proposed for an interstory drift estimation problem to show the health condition of steel structures in the case that the statistics or internal dynamics describing the signals and measurements are not known precisely. More precisely, we build an adaptive current Jerk model (ACJM) where the model parameters are updated in each time step to presuppose the statistics characterization of the steel dynamic, while the unknown measurement noise covariance is adapted based on a fixed‐lag innovation with respect to measurements. Moreover, a robust adaptive Kalman filter is designed for the modelling uncertainties in each time increment by solving a minimax game: one player tries to select an “actual” model far from the proposed ACJM with an exponential decay tolerance, while its “hostile” player, namely, the optimum filter, is designed by minimizing the estimation error according to the selected “actual” model. Finally, some simulation and experimental results show the effectiveness of the proposed algorithm.

Orthopaedic Manual Physical Therapy: A Modern Definition and Description.

Currently, orthopaedic manual physical therapy (OMPT) lacks a description of practice that reflects contemporary thinking and embraces advances across the scientific, clinical, and educational arms of the profession. The absence of a clear definition of OMPT reduces understanding of the approach across health care professions and potentially limits OMPT from inclusion in scientific reviews and clinical practice guidelines. For example, it is often incorrectly classified as passive care or incorrectly contrasted with exercise-therapy approaches. This perspective aims to provide clinicians, researchers, and stakeholders a modern definition of OMPT that improves the understanding of this approach both inside and outside the physical therapist profession. The authors also aim to outline the unique and essential aspects of advanced OMPT training with the corresponding examination and treatment competencies. This definition of practice and illustration of its defining characteristics is necessary to improve the understanding of this approach and to help classify it correctly for study in the scientific literature. This perspective provides a current definition and conceptual model of OMPT, defining the distinguishing characteristics and key elements of this systematic and active patient-centered approach to improve understanding and help classify it correctly for study in the scientific literature.

A semi-analytical rate-transient analysis model for fractured horizontal well in tight reservoirs under multiphase flow conditions

Abstract Rate-transient analysis (RTA) has been widely applied to extract reservoir/fracture properties using analytical and semi-analytical methods with simplifying assumptions. However, current RTA models may lead to misdiagnosis of flow regimes and incorrect estimates of reservoir/fracture information when complex fracture network, multiphase flow, and pressure-dependent properties occur in tight reservoirs simultaneously. A semi-analytical model is developed to account for multiphase flow, complex fracture network, and pressure-dependent properties. The technique uses the black oil formulation and butterfly model to determine three nonlinear partial differential equations (PDEs) that describe the flow of oil, gas, and water in the reservoir with complex fracture network. A modified Boltzmann variable considering the heterogeneity of complex fracture network is proposed to convert the fluid flow PDEs to a set of ordinary differential equations (ODEs) that can be solved through the Runge-Kutta method. A new rate-transient analysis workflow is also developed to improve flow regime identification (ID) and the accuracy for tight oil reservoirs with complex fracture network. It is applied to a synthetic case with equivalently modeled complex fracture network and multiphase flow. The estimated fracture properties are in excellent agreement with model inputs.

DEVELOPING 4D MALAYSIAN MARINE CADASTRE DATA MODEL BASED ON LADM - PRELIMINARY WORKS

Abstract. The complex interactions between terrestrial and aquatic dimensions make effective land management in coastal and marine settings particularly difficult. For thorough spatial data administration, it has been acknowledged that the traditional Land Administration Domain Model (LADM) must incorporate temporal and three-dimensional (3D) elements. The main goal of this work is to develop a 4D Malaysian marine cadastre data model based on LADM that integrates the temporal dimensions (3D + T= 4D) to the current 3D Malaysian marine cadastre data model and to assess how well the extended model handles issues with the representation of 3D marine environment. The depiction and management of temporal data related to shifting coastlines, fluctuating tides, and seasonal fluctuations in the maritime environment are some of the key questions investigated. The findings of this study are expected to provide valuable insights for augmenting land administration methodologies in dynamic marine settings. The outcomes of this research hold significance for sustainable marine development and effective spatial data management in coastal regions.

Digital Library Management using Cloud Computing

Libraries may soon be building and managing their own data centers. This model would let libraries maintain more control over the applications and data stores that contain sensitive, private information about patrons. Provisioning and maintenance of infrastructure for Web based digital library present several challenges. In this paper we discuss problems faced with digital library and development efforts to overcome that problem. Infrastructure virtualization and cloud computing are particularly attractive choices which is challenged by both growth in the size of the indexed document collection, new features and most prominently usage. With the purpose of applying Cloud Computing to university library, the paper describes the current status of user service models in university libraries. Then it proposed to improve current user service model with Cloud Computing. This paper explores some of the security issues surrounding data location, mobility and availability

Type III intermediate filaments in redox interplay: key role of the conserved cysteine residue.

Intermediate filaments (IFs) are cytoskeletal elements involved in mechanotransduction and in the integration of cellular responses. They are versatile structures and their assembly and organization are finely tuned by posttranslational modifications. Among them, type III IFs, mainly vimentin, have been identified as targets of multiple oxidative and electrophilic modifications. A characteristic of most type III IF proteins is the presence in their sequence of a single, conserved cysteine residue (C328 in vimentin), that is a hot spot for these modifications and appears to play a key role in the ability of the filament network to respond to oxidative stress. Current structural models and experimental evidence indicate that this cysteine residue may occupy a strategic position in the filaments in such a way that perturbations at this site, due to chemical modification or mutation, impact filament assembly or organization in a structure-dependent manner. Cysteine-dependent regulation of vimentin can be modulated by interaction with divalent cations, such as zinc, and by pH. Importantly, vimentin remodeling induced by C328 modification may affect its interaction with cellular organelles, as well as the cross-talk between cytoskeletal networks, as seems to be the case for the reorganization of actin filaments in response to oxidants and electrophiles. In summary, the evidence herein reviewed delineates a complex interplay in which type III IFs emerge both as targets and modulators of redox signaling.

From coercion to consent: Dutch rape law reform and the complexities of consent

Rape law reform currently ranks high on the agenda of many criminal justice systems. In this context, the distinction between different conceptions of rape as either consent- or coercion-based has traditionally played an important role. This paper analyses the shift from a coercion to a consent-based model of rape, using Dutch law as a backdrop to take a closer look at the ongoing discussion on how to regulate rape, as well as the uncertainties and complexities that reforms need to address. It departs from a theoretical level and first outlines the main features of the two aforementioned models of rape. Subsequently, the paper looks at the international level and the emerging European definition of rape. Next, the current Dutch coercion-based model as well as the pending consent-based reform proposal are discussed. To shed further light on the conceptual architecture and inherent definitional complexities of consent, a comparison with the consent-based system of England and Wales is undertaken. This helps to gauge the current Dutch proposal and highlights complex (normative) questions that rape law reform needs to address, providing impetus for future discussions as to how the guidance and scope of protection of sexual autonomy provided by consent-based models of rape may be further improved.

Sorghum SbGhd7 is a major regulator of floral transition and directly represses genes crucial for flowering activation.

Molecular genetic understanding of flowering time regulation is crucial for sorghum development. GRAIN NUMBER, PLANT HEIGHT AND HEADING DATE 7 (SbGhd7) is one of the six classical loci conferring photoperiod sensitivity of sorghum flowering. However, its functions remain poorly studied. The molecular functions of SbGhd7 were characterized. The gene regulatory network controlled by SbGhd7 was constructed and validated. The biological roles of SbGhd7 and its major targets were studied. SbGhd7 overexpression (OE) completely prevented sorghum flowering. Additionally, we show that SbGhd7 is a major negative regulator of flowering, binding to the promoter motif TGAATG(A/T)(A/T/C) and repressing transcription of the major florigen FLOWERING LOCUS T 10 (SbFT10) and floral activators EARLY HEADING DATE (SbEhd1), FLAVIN-BINDING, KELCH REPEAT, F-BOX1 (SbFKF1) and EARLY FLOWERING 3 (SbELF3). Reinforcing the direct effect of SbGhd7, SbEhd1 OE activated the promoters of three functional florigens (SbFT1, SbFT8 and SbFT10), dramatically accelerating flowering. Our studies demonstrate that SbGhd7 is a major repressor of sorghum flowering by directly and indirectly targeting genes for flowering activation. The mechanism appears ancient. Our study extends the current model of floral transition regulation in sorghum and provides a framework for a comprehensive understanding of sorghum photoperiod response.

Estuarine environmental flow assessment based on the flow-ecological health index relation model: a case study in Yangtze River Estuary, China.

Environmental flow (e-flow) is the water demand of one given ecosystem, which can become the flow regulation target for protection and restoration of river or estuarine ecosystems. In this study, an e-flow assessment based on the flow-ecological health index (EHI) relation model was conducted to improve ecosystem health of the Yangtze River Estuary (YRE). Monitoring data of hydrology, biology, and water environment in the last decades were used for the model establishment. For the description of the YRE ecosystem, an EHI system was developed by cumulative frequency distribution curves and adaption of national standards. After preprocessing original flow values into proportional flow values, the generalized additive model and Monte Carlo random sampling were used for the establishment of the flow-EHI relation model. From the model calculation, the e-flow assessment results were that, in proportional flow values, the suitable flow range was 1.05-1.35, and the optimum flow range was 1.15-1.25 (flows in Yangtze River Datong Station). For flow regulation in two crucial periods, flows of 42,630-65,545 m3/s or over 14,675 m3/s are needed for the suitable flow of YRE in summer (June-August) or January, respectively. An adaptive management framework of ecological health-based estuarine e-flow assessment for YRE was contrived due to the limitation of current established model when facing the extreme drought in summer, 2022. The methodology and framework in this study are expected to provide valuable management and data support for the sustainable development of estuarine ecosystems and to bring inspiration for further studies at even continental or global levels.

The Current Normative Model of the Child’s Origin in the context of Biomedical Achievements

The Current Normative Model of the Child’s Origin in the context of Biomedical Achievements

Axial Compression Damage Model and Damage Evolution of Crumb Rubber Concrete Based on the Energy Method

The current constitutive model and damage evolution law of crumb rubber concrete (CRC) were obtained by fitting and changing parameters based on the normal concrete model. However, this model does not accurately reflect the characteristics of the material. In this paper, we studied the energy dissipation in the failure process of CRC to derive the constitutive model and damage evolution law of CRC based on the energy method. Four substitution rates of 5%, 10%, 15%, and 20% were selected, and the rubber concrete prism was prepared by replacing the natural fine aggregate with the same volume of crumb rubber aggregate. After that, uniaxial compressive tests were conducted. The energy lost due to the damage was calculated and analyzed, and the energy method was used to establish the damage evolution law and damage model of the crumb rubber concrete. The results demonstrated that the Guo Zhenhai damage model, which is based on the energy method, can more effectively explain the crumb rubber concrete stress–strain full curve, and the energy consumed as a result of the damage exhibits a growing and then reducing pattern with the increase in rubber doses. When the energy-based method is used, the Guo Zhenhai damage evolution model is similar to the damage evolution law calculated using the SIR damage evolution model. During uniaxial compression damage, rubber concrete with various rubber dosages demonstrated varying energy absorption in different deformation phases. When the rubber particle content was 10%, the energy absorption capacity of the specimen was 6.9% higher than that of normal concrete.

Understanding regional growth of social enterprises: the art of the state

PurposeThe paper examines the key driving factors behind the rapid and uneven growth of social enterprises in China based on Kerlin’s Macro-Institutional Social Enterprise (MISE) model of social enterprise development, with an emphasis on testing key local institutional factors.Design/methodology/approachThe study adopts the quantitative method approach. The hypotheses have been tested based on a cross-regional empirical analysis with two national datasets on China.FindingsThis study shows that among the state, market and civil society, local government support in terms of favorable policies is the sole determinant factor driving China’s social enterprise growth. On the other hand, the market is irrelevant and local civil society impedes social enterprise growth. This demonstrates that the current growth model is the result of government intervention.Research limitations/implicationsThe datasets have a limited sample size. We suggest that future studies may collect a larger sample size with more comprehensive information. We think this study will encourage more comparative qualitative studies at the local level to reveal the underlying mechanisms of growth.Practical implicationsSince government policy is the determinant factor, the quality and quantity of government-backed incubation programs and platforms would matter the most for social enterprise growth. Our study also helps social entrepreneurs understand what factors matter when they try to develop social enterprises in China. They are advised to work on aspects of gaining legal legitimacy and political support in order to grow the sector.Social implicationsThis conclusion suggests that professionals and practitioners should review the implications of the current growth of social enterprises in China, in terms of their sustainability, given their institutional isolation from other sectors.Originality/valueCurrent studies have yet to thoroughly explore the role of meso- and micro-institutional factors in social enterprise development, especially in different contexts. With reference to Kerlin’s framework and the tri-sector model, this paper advances the understanding of social enterprise growth in China.

HyperHAR

Human activity recognition (HAR) has emerged as a prominent research field in recent years. Current HAR models are only able to model bilateral correlations between two sensing devices for feature extraction. However, for some activities, exploiting correlations among more than two sensing devices, which we call hyper-correlations in this paper, is essential for extracting discriminatory features. In this work, we propose a novel HyperHAR framework that automatically models both bilateral and hyper-correlations among sensing devices. The HyperHAR consists of three modules. The Intra-sensing Device Feature Extraction Module generates latent representation across the data of each sensing device, based on which the Inter-sensing Device Multi-order Correlations Learning Module simultaneously learns both bilateral correlations and hyper-correlations. Lastly, the Information Aggregation Module generates a representation for an individual sensing device by aggregating the bilateral correlations and hyper-correlations it involves in. It also generates the representation for a pair of sensing devices by aggregating the hyper-correlations between the pair and other different individual sensing devices. We also propose a computationally more efficient HyperHAR-Lite framework, a lightweight variant of the HyperHAR framework, at a small cost of accuracy. Both the HyperHAR and HyperHAR-Lite outperform SOTA models across three commonly used benchmark datasets with significant margins. We validate the efficiency and effectiveness of the proposed frameworks through an ablation study and quantitative and qualitative analysis.

Social problem-solving in intimate partner violence victims: Exploring the relative contributions of shame and PTSD symptoms.

This study examined the contributions of shame and posttraumatic stress disorder(PTSD) symptoms to two dimensions of social problem-solving. A sample of 426 women who were seeking mental health assistance following experiences of intimate partner violencecompleted self-report and clinician measures. Separate path analyses were conducted for problem orientation and problem-solving styles. In the model examining problem orientation, higher levels of shame were significantly associated with lower levels of positive problem orientation (f2 = 0.32) and higher levels of negative problem orientation (f2 = 0.92), with large effects noted. PTSD symptoms were significantly, positively associated with negative problem orientation (f2 = 0.3, large effect). When examining problem-solving styles, shame showed a significant negative association with rational style (f2 = 0.08, small effect) and significant positive associations with impulsive style (f2 = 0.45, large effect) and avoidant style (f2 = 0.48, large effect). PTSD symptoms did not return significant associations with any of the three problem-solving styles. Results indicate that shame holds notable associations with both dimensions of social problem-solving, relative to PTSD symptoms, and are discussed in light of current models of post-trauma functioning. Implications for clinical care and early intervention efforts are highlighted.

Building Environmental and Sociological Predictive Intelligence to Understand the Seasonal Threat of SARS-CoV-2 in Human Populations.

Current modeling practices for environmental and sociological modulated infectious diseases remain inadequate to forecast the risk of outbreak(s) in human populations, partly due to a lack of integration of disciplinary knowledge, limited availability of disease surveillance datasets, and overreliance on compartmental epidemiological modeling methods. Harvesting data knowledge from virus transmission (aerosols) and detection (wastewater) of SARS-CoV-2, a heuristic score-based environmental predictive intelligence system was developed that calculates the risk of COVID-19 in the human population. Seasonal validation of the algorithm was uniquely associated with wastewater surveillance of the virus, providing a lead time of 7-14 days before a county-level outbreak. Using county-scale disease prevalence data from the United States, the algorithm could predict COVID-19 risk with an overall accuracy ranging between 81% and 98%. Similarly, using wastewater surveillance data from Illinois and Maryland, the SARS-CoV-2 detection rate was greater than 80% for 75% of the locations during the same time the risk was predicted to be high. Results suggest the importance of a holistic approach across disciplinary boundaries that can potentially allow anticipatory decision-making policies of saving lives and maximizing the use of available capacity and resources.

MHD viscoelastic nanofluid flow across an extended plate using mixed convection and thermal radiation

Opportunities for magnetohydrodynamic mixed convection include modeling firefighting, combustion engineering, and cooling of electronic components. Nanotechnology has just provided a novel passive technique for improving heat transfer. Structured colloidal suspensions of magnetite nanoparticles in a base fluid are known as magneto nanofluids, and they are intended for use in thermal transfer uses, such as micro device cooling mechanisms. The current model is intended for examination of the nanofluid stagnation point flow using magnetohydrodynamics. A stretched sheet was exposed to magnetic strength and thermal radiation effects with outstanding results on heat transfer enhancements under mixed convection conditions. Furthermore, over the boundary effects of thermal slip and velocity are considered. The persuading system of partial differential equations of the governed fluid model is transformed into a scheme of coupled non-linear ordinary differential equations and expounded using a suitable numerical method. The fluid’s velocity, temperature, and concentration of nanoparticles are discussed graphically for a range of newly emerging parametric values. It has been noted that when there is a magnetic field, the fluid’s temperature increases, but its velocity decreases. After obtaining the numerical solution, parameters characterizing the flow, such as the local skin friction coefficient, local Sherwood number, and local Nusselt number, are thoroughly investigated.

An intelligent prediction model of epidemic characters based on multi‐feature

AbstractThe epidemic characters of Omicron (e.g. large‐scale transmission) are significantly different from the initial variants of COVID‐19. The data generated by large‐scale transmission is important to predict the trend of epidemic characters. However, the results of current prediction models are inaccurate since they are not closely combined with the actual situation of Omicron transmission. In consequence, these inaccurate results have negative impacts on the process of the manufacturing and the service industry, for example, the production of masks and the recovery of the tourism industry. The authors have studied the epidemic characters in two ways, that is, investigation and prediction. First, a large amount of data is collected by utilising the Baidu index and conduct questionnaire survey concerning epidemic characters. Second, the β‐SEIDR model is established, where the population is classified as Susceptible, Exposed, Infected, Dead and β‐Recovered persons, to intelligently predict the epidemic characters of COVID‐19. Note that β‐Recovered persons denote that the Recovered persons may become Susceptible persons with probability β. The simulation results show that the model can accurately predict the epidemic characters.

General model of nonradiative excitation energy migration on a spherical nanoparticle with attached chromophores

Theory of multistep excitation energy migration within the set of chemically identical chromophores distributed on the surface of a spherical nanoparticle is presented. The Green function solution to the master equation is expanded as a diagrammatic series. Topological reduction of the series leads to the expression for emission anisotropy decay. The solution obtained behaves very well over the whole time range and it remains accurate even for a high number of the attached chromophores. Emission anisotropy decay depends strongly not only on the number of fluorophores linked to the spherical nanoparticle but also on the ratio of critical radius to spherical nanoparticle radius, which may be crucial for optimal design of antenna-like fluorescent nanostructures. The results for mean squared excitation displacement are provided as well. Excellent quantitative agreement between the theoretical model and Monte–Carlo simulation results was found. The current model shows clear advantage over previously elaborated approach based on the Padé approximant.