Explicit Mechanism Research Articles

Extension of CMSA with a Learning Mechanism: Application to the Far from Most String Problem

One of the problems with exact techniques for solving combinatorial optimization problems is that they tend to run into problems with growing problem instance size. Nevertheless, they might still be very usefully employed, even in the context of large problem instances, as a sub-ordinate method within so-called hybrid metaheuristics. “Construct, Merge, Solve and Adapt” (Cmsa) is a hybrid metaheuristic technique that allows the application of exact methods to large-scale problem instances through intelligent instance reduction. However, Cmsa does not make use of an explicit learning mechanism. In this work, an algorithm called LEARN_CMSA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsc {Learn}\\_\ extsc {Cmsa}$$\\end{document} is presented for the application to the far from most string problem (FFMSP), which is an NP-hard combinatorial optimization problem from the field of string consensus problems. LEARN_CMSA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsc {Learn}\\_\ extsc {Cmsa}$$\\end{document} results from hybridization between Cmsa and a population-based algorithm. By means of this hybridization, explicit learning is introduced to Cmsa. Even though the FFMSP is a well-studied problem, LEARN_CMSA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsc {Learn}\\_\ extsc {Cmsa}$$\\end{document} achieves superior performance when compared to current state-of-the-art solvers.

Adults With IDD in Supported Accommodation During COVID-19 Lockdown: The Families' Perspective.

The present study aims to understand and describe family caregivers' perceptions and experiences regarding contact and relationships with their adult relatives with intellectual and developmental disabilities (IDD) living in supported accommodation during the COVID-19 lockdown. A qualitative phenomenological approach was applied in which 19 Israeli family caregivers (parents and siblings) were interviewed. Inductive thematic analysis revealed themes at the microsystem level (the resident, the caregiver, and their relationship), and at the mesosystem level (the caregivers' interactions with service providers and other residents' families). The findings highlight the pivotal role of family caregivers in times of uncertainty and the need to develop explicit policies and mechanisms to facilitate family engagement in the residents' lives.

Chemotaxis in heterogeneous environments: A multi-agent model of decentralized gathering past obstacles

Chemotaxis, cell migration in response to chemical gradients, is known to promote self-organization of microbiological populations. However, the modeling of chemotaxis in heterogeneous environments is still limited. This study analyzes a decentralized gathering process in environments with physical as well as chemical barriers, using a multi-agent model for Disctyostelium discoideum colonies. Employing a topology-independent metric to quantify the system evolution, we study dynamical features emerging from complex social interactions. The results show that obstacles may hamper the gathering process by altering the flux of chemical signals among amoebas, acting as local topological perturbations. We also find that a minimal set of agent’s rules for robust gathering does not require explicit mechanisms for obstacle sensing and avoidance; moreover, random cell movements concur in preventing multiple stable clusters and improve the gathering efficacy. Hence, we speculate that chemotactic cells can avoid obstacles without needing specialized mechanisms: tradeoffs of social interactions and individual fluctuations are sufficient to guarantee the aggregation of the whole colony past numerous obstacles.

Affinity targeting of therapeutic proteins to the bone surface-local delivery of sclerostin-neutralizing antibody enhances efficacy.

Currently available biotherapeutics for the treatment of osteoporosis lack explicit mechanisms for bone localization, potentially limiting efficacy and inducing off-target toxicities. While various strategies have been explored for targeting the bone surface, critical aspects remain poorly understood, including the optimal affinity ligand, the role of binding avidity and circulation time, and, most importantly, whether or not this strategy can enhance the functional activity of clinically relevant protein therapeutics. To investigate, we generated fluorescent proteins (eg, mCherry) with site-specifically attached small molecule (bisphosphonate) or peptide (deca-aspartate, D10) affinity ligands. While both affinity ligands successfully anchored fluorescent protein to the bone surface, quantitative radiotracing revealed only modest femoral and vertebral accumulation and suggested a need for enhanced circulation time. To achieve this, we fused mCherry to the Fc fragment of human IgG1 and attached D10 peptides to each C-terminus. The mCherry-Fc-D10 demonstrated an ~80-fold increase in plasma exposure and marked increases in femoral and vertebral accumulation (13.6% ± 1.4% and 11.4% ± 1.3% of the injected dose/g [%ID/g] at 24h, respectively). To determine if bone surface targeting could enhance the efficacy of a clinically relevant therapeutic, we generated a bone-targeted sclerostin-neutralizing antibody, anti-sclerostin-D10. The targeted antibody demonstrated marked increases in bone accumulation and retention (20.9 ± 2.5% and 19.5 ± 2.5% ID/g in femur and vertebrae at 7days) and enhanced effects in a murine model of ovariectomy-induced bone loss (bone volume/total volume, connectivity density, and structure model index all increased [P< .001] vs untargeted anti-sclerostin). Collectively, our results indicate the importance of both bone affinity and circulation time in achieving robust targeting of therapeutic proteins to the bone surface and suggest that this approach may enable lower doses and/or longer dosing intervals without reduction in biotherapeutic efficacy. Future studies will be needed to determine the translational potential of this strategy and its potential impact on off-site toxicities.

How external and agency characteristics are related to coordination in homecare – findings of the national multicenter, cross-sectional SPOTnat study

BackgroundHomecare client services are often distributed across several interdependent healthcare providers, making proper care coordination essential. However, as studies exploring care coordination in the homecare setting are scarce, serious knowledge gaps exist regarding how various factors influence coordination in this care sector. To fill such gaps, this study’s central aim was to explore how external factors (i.e., financial and regulatory mechanisms) and homecare agency characteristics (i.e., work environment, workforce, and client characteristics) are related to care coordination in homecare.MethodsThis analysis was part of a national multicentre, cross-sectional study in the Swiss homecare setting that included a stratified random sample of 88 Swiss homecare agencies. Data were collected between January and September 2021 through agency and employee questionnaires. Using our newly developed care coordination framework, COORA, we modelled our variables to assess the relevant components of care coordination on the structural, process, and outcome levels. We conducted both descriptive and multilevel regression analyses—with the latter adjusting for dependencies within agencies—to explore which key factors are associated with coordination.ResultsThe final sample size consisted of 1450 employees of 71 homecare agencies. We found that one explicit coordination mechanism (“communication and information exchange” (beta = 0.10, p <.001)) and four implicit coordination mechanisms—“knowledge of the health system” (beta = -0.07, p <.01), “role clarity” (beta = 0.07, p <.001), “mutual respect and trust” (beta = 0.07, p <.001), and “accountability, predictability, common perspective” (beta = 0.19, p <.001)—were significantly positively associated with employee-perceived coordination. We also found that the effects of agency characteristics and external factors were mediated through coordination processes.ConclusionImplicit coordination mechanisms, which enable and enhance team communication, require closer examination. While developing strategies to strengthen implicit mechanisms, the involvement of the entire care team is vital to create structures (i.e., explicit mechanisms) that enable communication and information exchange. Appropriate coordination processes seem to mitigate the association between staffing and coordination. This suggests that they support coordination even when workload and overtime are higher.

HNF1A induces glioblastoma by upregulating EPS8 and activating PI3K/AKT signaling pathway

Despite the exact biological role of HNF1 homolog A (HNF1A) in the regulatory mechanism of glioblastoma (GBM), the molecular mechanism, especially the downstream regulation as a transcription factor, remains to be further elucidated. Immunohistochemistry was used to detect the expression and clinical relevance of HNF1A in GBM patients. CCK8, TUNEL, and subcutaneous tumor formation in nude mice were used to evaluate the effect of HNF1A on GBM in vitro and in vivo. The correction between HNF1A and epidermal growth factor receptor pathway substrate 8 (EPS8) was illustrated by bioinformatics analysis and luciferase assay. Further mechanism was explored that the transcription factor HNF1A regulated the expression of EPS8 and downstream signaling pathways by directly binding to the promoter region of EPS8. Our comprehensive analysis of clinical samples in this study showed that upregulated expression of HNF1A was associated with poor survival in GBM patients. Further, we found that knockdown of HNF1A markedly suppressed the malignant phenotype of GBM cells in vivo and in vitro as well as promoted apoptosis of tumor cells, which was reversed by upregulation of HNF1A. Mechanistically, HNF1A could significantly activate PI3K/AKT signaling pathway by specifically binding to the promoter regions of EPS8. Moreover, overexpression of EPS8 was able to reverse the apoptosis of tumor cells caused by HNF1A knockdown, thereby exacerbating the GBM progression. Correctively, our study has clarified the explicit mechanism by which HNF1A promotes GBM malignancy and provides a new therapeutic target for further clinical application.

Selenium Nanoparticles Enhance NK Cell‐Mediated Tumoricidal Activity in Malignant Pleural Effusion via the TrxR1‐IL‐18RAP‐pSTAT3 Pathway

AbstractMalignant pleural effusion (MPE) poses a significant challenge in local treatment, primarily attributed to its intricate tumor immune microenvironment. The immunosuppression of natural killer (NK) cells within the microenvironment, exacerbated by selenium (Se) deficiency, constitutes a pivotal treatment bottleneck. Building upon prior investigations, this study delves into the impact and mechanisms of functionalized lentinan selenium nanoparticles (LET‐SeNPs) on NK cells in MPE, presenting a novel local treatment strategy for lung adenocarcinoma with malignant pleural effusion (MPE‐LA). The synergistic application of LET‐SeNPs serves to replenish Se levels in MPE, modulate NK cells, augment their quantity, restore and enhance their functionality. Additionally, LET‐SeNPs facilitate NK cells activation through the TrxR1‐IL18RAP‐pSTAT3 pathway, resulting in effective lung cancer cell eradication and reduced pleural effusion production. Furthermore, pre‐stimulation of NK cells by LET‐SeNPs, combined with CAR‐NK cell therapy, harnesses the innate immune system, exhibiting a potent anti‐tumor effect. This research introduces a compelling strategy to advance the clinical implementation of targeted nanomaterials or lead compounds with explicit targets and mechanisms, thereby enhancing NK cell therapy for comprehensive diagnosis and treatment of MPE.

Seq2Set2Seq: A Two-stage Disentangled Method for Reply Keyword Generation in Social Media

Social media produces large amounts of content every day. How to predict the potential influences of the contents from a social reply feedback perspective is a key issue that has not been explored. Thus, we propose a novel task named reply keyword prediction in social media, which aims to predict the keywords in the potential replies in as many aspects as possible. One prerequisite challenge is that the accessible social media datasets labeling such keywords remain absent. To solve this issue, we propose a new dataset, 1 to study the reply keyword prediction in social media. This task could be seen as a single-turn dialogue keyword prediction for open-domain dialogue system. However, existing methods for dialogue keyword prediction cannot be adopted directly, which has two main drawbacks. First, they do not provide an explicit mechanism to model topic complementarity between keywords which is crucial in social media to controllably model all aspects of replies. Second, the collocations of keywords are not explicitly modeled, which also makes it less controllable to optimize for fine-grained prediction since the context information is much less than that in dialogue. To address these issues, we propose a two-stage disentangled framework, which can optimize the complementarity and collocation explicitly in a disentangled fashion. In the first stage, we use a sequence-to-set paradigm via multi-label prediction and determinantal point processes, to generate a set of keyword seeds satisfying the complementarity. In the second stage, we adopt a set-to-sequence paradigm via seq2seq model with the keyword seeds guidance from the set, to generate the more-fine-grained keywords with collocation. Experiments show that this method can generate not only a more diverse set of keywords but also more relevant and consistent keywords. Furthermore, the keywords obtained based on this method can achieve better reply generation results in the retrieval-based system than others.

Revisiting the impact of public spaces on the mental health of rural migrants in Wuhan: an integrated multi-source data analysis

Current research on public spaces and mental health often focuses on the independent relationship of one or more social mediators, neglecting the nuanced implications and serial mechanisms inherent in the progressive social process. Using Wuhan city, China, as a study case with multi-source data, this research applies Multilevel Generalized Structural Equation Modeling and deep learning techniques to explore the differential effects of public spaces with varying degrees of publicness (i.e., typical, semi-, and privately owned) on rural migrants’ mental health. Crucially, this study scrutinizes both explicit (social interaction) and implicit (perceived integration) social mechanisms to revisit the relationships. The findings reveal that not all public spaces equally influence mental health, with typical and privately owned public spaces conferring profound benefits. Notably, public spaces impact mental health chiefly through perceived integration instead of through direct social interaction. Social interaction improves mental health primarily by enhancing perceived integration, suggesting that meaningful connections beyond superficial encounters are critical. In particular, we observed significant social effects in typical and privately owned public spaces but limited social functionality in semi-public spaces. This evidence contributes to the knowledge required to create supportive social environments within public spaces, integral to nurturing inclusive urban development.

Ризома как механизм манипуляции в немецкоязычном журналистском тексте

The research focuses on the pressing issue of contemporary political discourse – the technologies of manipulation in the media space, specifically the linguistic mechanisms for transmitting pragmatic attitudes and value orientations in journalistic texts. These processes directly correlate with the phenomenon of increasing entropy in the text and, as the study has shown, largely arise from the rhizome - the nonlinear nature of organizing integrity. The research aim is to identify the linguistic mechanisms underlying the rhizomatic structure of media text. The scientific novelty of the research lies in the fact that for the first time, using a specific info-cause as an example, the rhizome is examined as a mechanism for implementing manipulative strategies in the modern German-speaking media space; the conditioned technologies of modeling pragmatic attitudes by the rhizome are revealed; the explicit and implicit mechanisms of implementing this process are described. The obtained results have shown that in journalistic texts, the rhizome manifests itself as multi-vectorial and the contradictory transmission of information, greatly enhancing the possibilities of interpretations inherent in the language structure, becoming a significant mechanism for implementing manipulative strategies.

Exploring ozone production sensitivity to NOx and VOCs in the New York City airshed in the spring and summers of 2017–2019

Reducing ozone in the New York City (NYC) region requires understanding the nonlinearity of ozone production (PO3) and its sensitivity to volatile organic compounds (VOCs) and nitrogen oxides (NOx = NO2 + NO). Using observations from the Long Island Sound Tropospheric Ozone Study (LISTOS) in the late spring and summers of 2017–2019 and a 0-D box model, we test the sensitivity of PO3 to ozone precursors. PO3 is greater in the morning than the afternoon due to increased concentrations of NO2 and VOC. This diurnal variation in PO3 is enhanced in the late summer. Based on the model response of PO3 to changes in initial NO2, 14% of samples are within a VOC-limited regime. The metric LROx/LNOx, which compares the radical loss rates via self-reaction to their reaction with NO2, indicates an additional 17% of samples are in transition between NOx and VOC-limited regimes (0.30 <= LROx/LNOx <= 1). We often find PO3 to be VOC-limited in NYC and along the Connecticut coastline (I-95 corridor). In these samples, PO3 is most sensitive to isoprene, propene, and isopentane, and individual VOCs have strong diurnal and seasonal variations. We further compare PO3 calculations using the near explicit Master Chemical Mechanism (MCMv3.3.1) and Carbon Bond 6 revision 2 (CB6r2) for a more direct link to regulatory air quality models. Modeled PO3 is 20% greater in MCMv3.3.1, due largely to the speciation of VOC and organic peroxy radicals, however the bounds of LROx/LNOx used to determine the transition range between PO3 regimes remain the same.

Photochemical Mechanism and Control Strategy Optimization for Summertime Ozone Pollution in Yining City

To explore the formation mechanism of the ozone （O3） and emission reduction strategy in a northwestern city， an extensive field campaign was conducted in summertime in 2021 in Yining City， in which the 0-D box model incorporating the latest explicit chemical mechanism （MCMv3.3.1） was applied for the first time to quantify the O3-NOx-VOCs sensitivity and formulate a precise O3 control strategy in this city. The results showed that： ① the three indicators ［i.e.， O3 formation potential （OFP）， ·OH reaction rate （k·OH）， and relative incremental reactivity （RIR）］ jointly indicated that alkenes， oxygenated volatile organic compounds （OVOCs）， and aromatics were the highest contributors among anthropogenic volatile organic compounds （AVOC） to O3 formation， and the contribution of biogenic volatile organic compounds （BVOC） also could not be ignored. Additionally， the results based on RIR calculation implied that that the acetaldehyde， ethylene， and propylene were the most sensitive individual VOCs species in Yining City. ② The in-situ photochemical O3 variations were primarily influenced by the local photochemical production and export process horizontally to downwind areas or vertically to the upper layer， and the reaction pathways of HO2·+ NO and ·OH + NO2 contributed the most to the gross Ox photochemical production （60%） and photochemical destruction production （53%）， respectively. Hence， the reduction in local emissions for O3 precursors was more essential to alleviate O3 pollution in this city. ③ The outcome based on RIR（NOx） / RIR（AVOC） and EKMA jointly suggested that the photochemical regime in this city can be considered a transitional regime that was also nearly a VOCs-limited regime. Detailed mechanism modeling based on multiple scenarios further suggested that the NOx and VOCs synergic emission reduction strategies was helpful to alleviate O3 pollution. These results are useful to provide policy-related guidance for other cities facing similar O3 pollution in northwest China.

Maternal pertussis immunization and the blunting of routine vaccine effectiveness: a meta-analysis and modeling study

A key goal of pertussis control is to protect infants too young to be vaccinated, the age group most vulnerable to this highly contagious respiratory infection. In the last decade, maternal immunization has been deployed in many countries, successfully reducing pertussis in this age group. Because of immunological blunting, however, this strategy may erode the effectiveness of primary vaccination at later ages. Here, we systematically reviewed the literature on the relative risk (RR) of pertussis after primary immunization of infants born to vaccinated vs. unvaccinated mothers. The four studies identified had ≤6 years of follow-up and large statistical uncertainty (meta-analysis weighted mean RR: 0.71, 95% CI: 0.38–1.32). To interpret this evidence, we designed a new mathematical model with explicit blunting mechanisms and evaluated maternal immunization’s short- and long-term impact on pertussis transmission dynamics. We show that transient dynamics can mask blunting for at least a decade after rolling out maternal immunization. Hence, the current epidemiological evidence may be insufficient to rule out modest reductions in the effectiveness of primary vaccination. Irrespective of this potential collateral cost, we predict that maternal immunization will remain effective at protecting unvaccinated newborns, supporting current public health recommendations.

Interfacial Charge Transfer for Enhancing Nonlinear Saturable Absorption in WS2/graphene Heterostructure.

Interlayer charge-transfer (CT) in 2D atomically thin vertical stacks heterostructures offers an unparalleled new approach to regulation of device performance in optoelectronic and photonics applications. Despite the fact that the saturable absorption (SA) in 2D heterostructures involves highly efficient optical modulation in the space and time domain, the lack of explicit SA regulation mechanism at the nanoscale prevents this feature from realizing nanophotonic modulation. Here, the enhancement of SA response via CT in WS2/graphene vertical heterostructure is proposed and the related mechanism is demonstrated through simulations and experiments. Leveraging this mechanism, CT-induced SA enhancement can be expanded to a wide range of nonlinear optical modulation applications for 2D materials. The results suggest that CT between 2D heterostructures enables efficient nonlinear optical response regulation.

Engineering a Z-Scheme Heterostructure on ZnIn2S4@NH2-MIL-125 Composites for Boosting the Photocatalytic Performance.

Constructing a Z-scheme heterostructure on a metal-organic framework (MOF) composite with an explicit charge transfer mechanism at the interface is considered to be an effective strategy for improving the photocatalytic performance of MOFs. Herein, an internal electric field (IEF)-induced Z-scheme heterostructure on the ZnIn2S4@NH2-MIL-125 composite is designed and fabricated by a facile electrostatic self-assembly process. Systematic investigations reveal that close interfacial contact and difference in work function between NH2-MIL-125 and ZnIn2S4 enable the formation of the IEF, which drives the Z-scheme charge transfer as revealed by the in situ irradiated X-ray photoelectron spectroscopy (ISI-XPS), photoirradiated Kelvin probe force microscope (KPFM) measurement, electron paramagnetic resonance (EPR) radical trapping experiment, as well as density functional theory (DFT) calculation; meanwhile, directions of the interfacial IEFs are determined. Benefiting from the unique merit of IEF-induced Z-scheme charge transfer, the optimized ZnIn2S4@NH2-MIL-125 composite exhibits significantly enhanced photocatalytic activity for the photoreduction of 4-nitroaniline (4-NA) to p-phenylenediamine (PPD) under visible light irradiation. This work not only provides in-depth insights for charge transfer in the IEF-induced Z scheme heterostructure but also affords useful inspirations on designing the Z-scheme MOF composite to boost the photocatalytic performance.

A novel intelligent fault diagnosis method of bearing based on multi-head self-attention convolutional neural network

Abstract Deep learning (DL) has been widely used in bearing fault diagnosis. In particular, convolutional neural networks (CNNs) improve diagnosis accuracy by extracting excellent fault features. However, CNN lacks an explicit learning mechanism to distinguish between different fault characteristics in the input signal to the diagnosis results. This article presents a new end-to-end depth framework called multi-head self-attention convolution neural network (MSA-CNN) for bearing fault diagnosis. Firstly, we adopt a data pre-processing method that directly converts one-dimensional (1D) original signals into two-dimensional (2D) grayscale images, which is simple to implement and preserves the complete information of the original signal. Secondly, multi-head self-attention (MSA) is first constructed to aggregate the global information and adaptively assign weights to the input signal's features. Thirdly, the CNN with small-scale kernels extracted detailed local features. Finally, the learned high-level representations are fed into the full connect (FC) layer for fault diagnosis. The performance of the MSA-CNN is validated on different datasets. The results show that the proposed MSA-CNN can significantly improve fault diagnosis accuracy compared with the other state-of-the-art methods and has excellent noise immunity performance.

Writing Modern Geoscience

Scientific writing is a cornerstone component of modern geoscience practice. Despite this, the subject rarely benefits from any explicit instruction during graduate training. This editorial attempts to address that gap by providing a simplified approach to writing modern geoscience papers. Implementation of this approach requires aspiring scientific writers to first consider why we as scientists write papers and what our goals should be for our audience. From there, specific and detailed advice is provided on how to best structure the idea flow and presentation within each of the primary components of a peer-reviewed manuscript (e.g. introduction, methods, results, discussion, conclusions, and abstracts). Examples of annotated, illustrative text are provided throughout. Considerable attention is paid to the notion of a scientific paper as an argument (as presented primarily in it's discussion section) in favor of some proposition, and the key aspects of what makes an argument compelling. The goal is to provide new or struggling scientific writers with an explicit mechanism to construct impactful peer-reviewed manuscripts more easily.

Targeting Src homology phosphatase 2 ameliorates mouse diabetic nephropathy by attenuating ERK/NF-κB pathway-mediated renal inflammation

Renal inflammation is a pivotal mechanism underlying the pathophysiology of diabetic nephropathy (DN). The Src homology phosphatase 2 (SHP2) has been demonstrated to be linked to diabetes-induced inflammation, yet its roles and explicit molecular mechanisms in DN remain unexplored. Here, we report that SHP2 activity is upregulated in both DN patients and db/db mice. In addition, pharmacological inhibition of SHP2 with its specific inhibitor PHPS1 alleviates DN in db/db mice and attenuates renal inflammation. In vitro, PHPS1 administration prevents inflammatory responses in HK-2 cells stimulated by high glucose (HG). Mechanistically, PHPS1 represses HG-induced activation of the proinflammatory ERK/NF-κB signaling pathway, and these inhibitory effects are blocked in the presence of an ERK specific inhibitor, hence demonstrating that PHPS1 suppresses ERK/NF-κB pathway-mediated inflammation. Moreover, PHPS1 retards ERK/NF-κB pathway activation in db/db mice, and histologically, SHP2 activity is positively correlated with ERK/NF-κB activation in DN patients. Taken together, these findings identify SHP2 as a potential therapeutic target and show that its pharmacological inhibition might be a promising strategy to mitigate DN.-rV21qwpHSeiT1S94nwGvkVideo

Comprehensive multiphase chlorine chemistry in the box model CAABA/MECCA: implications for atmospheric oxidative capacity

Abstract. Tropospheric chlorine chemistry can strongly impact the atmospheric oxidation capacity and composition, especially in urban environments. To account for these reactions, the gas- and aqueous-phase Cl chemistry of the community atmospheric chemistry box model Chemistry As A Boxmodel Application/Module Efficiently Calculating the Chemistry of the Atmosphere (CAABA/MECCA) has been extended. In particular, an explicit mechanism for ClNO2 formation following N2O5 uptake to aerosols has been developed. The updated model has been applied to two urban environments with different concentrations of NOx (NO + NO2): New Delhi (India) and Leicester (United Kingdom). The model shows a sharp build-up of Cl at sunrise through Cl2 photolysis in both the urban environments. Besides Cl2 photolysis, ClO+NO reaction and photolysis of ClNO2 and ClONO are also prominent sources of Cl in Leicester. High-NOx conditions in Delhi tend to suppress the nighttime build-up of N2O5 due to titration of O3 and thus lead to lower ClNO2, in contrast to Leicester. Major loss of ClNO2 is through its uptake on chloride, producing Cl2, which consequently leads to the formation of Cl through photolysis. The reactivities of Cl and OH are much higher in Delhi; however, the Cl/OH reactivity ratio is up to ≈ 9 times greater in Leicester. The contribution of Cl to the atmospheric oxidation capacity is significant and even exceeds (by ≈ 2.9 times) that of OH during the morning hours in Leicester. Sensitivity simulations suggest that the additional consumption of volatile organic compounds (VOCs) due to active gas- and aqueous-phase chlorine chemistry enhances OH, HO2, and RO2 near sunrise. The simulation results of the updated model have important implications for future studies on atmospheric chemistry and urban air quality.

A topology constrained phase field model

This paper presents a topology constrained phase field model based on a variable mobility Cahn-Hilliard equation. Mostly in the level set framework, this issue has been addressed using concepts from digital topology. However, point based specifications can not be effective in phase fields where the interface is represented by a diffuse region. In phase field models, topology constraints are included in the energy as a penalty term. However, there are no studies which provide topological constraints in the Cahn-Hilliard model to our knowledge. In this work, we use the mobility parameter to enforce topology constraints; this allows local, explicit control of topological events, unlike the optimization based solutions. We define topologically critical regions in phase fields based on a topological analysis of phase field evolution. This analysis shows that diffuse layers formed at topological encounters behave like a Morse function and the critical points of these transitional layers give topologically critical points in phase fields. Using this property, we first detect critical points using an efficient image analysis method. Then we detect the transitional region (critical region) around each critical point using a local morphological segmentation algorithm. We define a mobility function which both has a spatial and concentration dependence. This function is designed to reverse the effect of diffuse layers formed at topological encounters and prevent the further development of topological events. Being extracted from phase field values, the mobility map naturally aligns with phase field evolution. Together with the use of an unconditionally stable semi-implicit Fourier spectral method for the variable mobility Cahn-Hilliard equation, an efficient model is provided. Local, explicit control mechanism allows the design of free energy functional for modeling different materials; this extends the use of Cahn-Hilliard equation to applications which require topology control.