Selective Inclusion Research Articles

Selective inclusion: Civil society involvement in the smart city ecology of Amsterdam

Although research on smart cities increasingly acknowledges the involvement of civil society actors, most studies fall short when it comes to clarifying the specific modalities of civil society involvement. By probing into the smart city ecology that has developed around the Amsterdam Smart City-Foundation, we explore not only the extent to which the civil society is part of a smart city ecology but also what role civil society actors hold within this ecology. This article draws on data gathered and analyzed through quantitative and qualitative methods. The qualitative analysis focuses on analyzing the institutional dynamics that shape civil society involvement in Amsterdam’s smart city ecology. The quantitative data are used to unravel the relational dynamics by quantifying collaborative patterns between different types of organizations in Amsterdam’s smart city ecology. Our findings reveal that powerful institutional dynamics, manifested through normative pressures, favor the involvement of socially oriented civil society actors. At the same time, however, relational dynamics that shape the collaborative patterns in the projects of the ecology rather exclude the socially oriented civil society at the benefit of an economically oriented civil society. In other words, while the entire ecology rhetorically adheres to an ethos of pervasive civil society involvement, politically, socially, and civically oriented civil society actors lack inter-organizational collaboration—even in the supposedly inclusive context of Amsterdam.

Private Sector Engagement for Infectious Disease Surveillance in Mixed Health Systems: Lessons from a Model Dengue Reporting Network in India

Disease estimates from surveillance in mixed health systems is affected by lack of data from the private sector. We aimed to characterize private sector engagement and reporting to a disease surveillance network, and determine the implications on dengue case detection. We developed and set up a public–private network (CODREN—Community Disease Detection and Response Network) with recruitment of eligible health resources ( n = 462) in a municipal ward of Pune city, India (population 209,331). Dengue cases reported through CODREN were compared with reports of the local dengue surveillance (LDS) over 1 year. Private clinics constituted the majority of eligible providers (60%, 276). Retention of participants was 81.7% with 13.9% reporting dengue cases. Phone call was the preferred reporting method (85.5%, 564 reports). CODREN captured a higher number of cases than LDS (78.9%, 251 vs 50.6%, 161), increasing case detection by 18% due to increased private reporting points. A twofold lower number of cases was reported by LDS from shared reporting points with CODREN, due to discrepancies in case definitions and diagnostic test preferences among private providers. We conclude that private sector engagement can improve dengue case detection with the selective inclusion of providers, sustained contact, feedback and simple reporting methods. Testing guidelines and case definitions adopted by the LDS need to address heterogeneity of private practice in mixed health systems, in order to improve dengue estimates in India.

Composite Lung Transplant Suitability Score (CLaSS): A Novel Predictor of Survival Following Lung Transplantation

<h3>Purpose</h3> Lung transplantation is indicated in patients with respiratory failure who progress despite optimal therapy. The selection of suitable transplant recipients considers internationally accepted absolute and relative contra-indications that are known to negatively influence survival, and typically involves a multi-disciplinary assessment. We assessed the impact on routinely collected pre-transplant variables on post-transplant survival and created a composite model that predicted post-transplant survival. <h3>Methods</h3> Adult patients (n = 916) undergoing lung transplant assessment at a single center between 2013 and 2021 had the following variables analyzed: age, gender, pre-transplant diagnosis, BMI, eGFR, HbA1c, albumin, 6-minute walk distance (6MWD) and Stanford Integrated Psychosocial Assessment for Transplant (SIPAT) score. Logistic regression was performed for post-transplant survival. Multiple imputation was used for missing data. Variables for inclusion in the final model were selected using backward elimination and confirmed using forward elimination (p-value <0.1). Internal validation of the model was performed using-one-out cross validation and 70/30 data split. <h3>Results</h3> Variables as assessed by univariate analysis predicting worse survival included pre-transplant diagnosis (CLAD), limited renal reserve and reduced 6MWD, with CLAD and 6MWD remaining significant predictors of death in the multivariate analysis. All variables were initially included in the predictive model, however the model performance improved with the selective inclusion of pre-transplant diagnosis, 6MWD and HbA1c (ROC 0.672, sensitivity 98.7%). Case examples demonstrated the practical utility of the model. Scenario #1. CF, HbA1c 5, Albumin 40 and 6MWD 400m; predicted probability of survival is 85%. Scenario #2. CLAD, HbA1c 5, albumin 20, 6MWD 250m; predicted probability of survival is 36%. <h3>Conclusion</h3> Using variables that are commonly collected during a pre-transplant assessment, we have created a clinically applicable model that predicts post-transplant survival. The model can aid in recipient selection and inform discussion with potential transplant candidates on expected post-transplant outcomes, including survival.

How effective is toluidine blue for screening and diagnosis of oral cancer and premalignant lesions?

Design A systematic review and bivariate meta-analysis was designed to determine the efficacy of toluidine blue (TB) in the screening and diagnosis of oral cancer and premalignant lesions. Six databases were reviewed independently by two authors to identify relevant studies.Case selection Inclusion criteria comprised prospective or retrospective studies comparing TB with chemiluminescence or clinical examination, which incorporated sensitivity and specificity analyses. Studies regarding diagnosis of non-oral tumours were excluded, as well as case reports and review articles.Data analysis Diagnostic accuracy was analysed using diagnostic odds ratio (DOR) with 95% confidence intervals (CI). Summary receiver operating characteristic (SROC) curves and the inter-rater agreement were also analysed. Cohen's kappa coefficient and Fisher z-values were used to estimate reliability and stabilise variance. Homogeneity analyses were performed using the Q statistic. Forest plots were drawn for the sensitivity, specificity, negative predictive values, and SROC curves.Results Twenty-nine studies comprising 1,921 participants were included in the meta-analysis. The DOR of TB was 7.017 (95% CI, 4.544; 10.836). Nine studies compared TB with chemiluminescence; TB had a lower sensitivity but a higher specificity. Compared with clinical examination in four studies, TB had a higher sensitivity and specificity. TB has a sensitivity of 73% and specificity of 69%, and was found to be more sensitive in severe dysplasia but more specific in benign lesions.Conclusions The diagnostic accuracy of TB for oral cancer or premalignant lesions is greater than clinical examination alone; however, it is not reliable enough for TB to be used as a screening method in isolation. TB is a diagnostic aid that can be recommended in adjunct with chemiluminescence or other techniques.

Do Safe Bike Lanes Really Slow Down Cars? A Simulation-Based Approach to Investigate the Effect of Retrofitting Safe Cycling Lanes on Vehicular Traffic

Cycling is a sustainable transportation mode that provides many health, economic and environmental benefits to society. Cities with high rates of cycling are better placed to address modern challenges of densification, carbon-neutral and connected 20-min neighbourhood goals. Despite the known benefits of cycling, participation rates in Australian cities are critically low and declining. Frequently, this low participation rate is attributed to the dangers of Australian cycle infrastructure that often necessitates the mixing of cyclists with car traffic. In addition, residents of car-dependent Australian suburbs can be resistant to the installation of cycle infrastructure where threats to traffic flow, or decreased on-street parking availability are perceived and the prohibitive cost of reconfiguration of other infrastructure maintained by the local councils to retrofit safe bike paths. This study investigates the effects on traffic behaviour of retrofitting safe, separate cycling lanes into existing residential streets in a Melbourne suburb suitable for accessing the primary neighbourhood destinations. We utilise only the widths available on the existing roadway of these streets, with minimal incursion on other facilities, such as the vehicle network and parking. Using only the existing roadway reflects the common need for municipal asset managers to minimise disruption and costs associated with street redesign. Using a traffic simulation approach, we modelled travel demand that suits suburban trips to services and shops, and we selectively applied separate cycling lanes to suitable residential streets and varied the effect of lowering speed limits. Simulations show that the selective inclusion of safe cycling lanes in some streets leads to a mere 7% increase in the average car travel times in the worst case, while requiring cyclists to increase their travel distance only marginally to avoid streets without dedicated cycling lanes. These results demonstrate that reasonable compromises are possible to make suburbs safer for cyclists and bring them closer to the 20-min neighbourhood goal. There is significant potential to enhance the result by including more street types and alternative designs. The results can inform councils in their cycle path infrastructure decisions and disprove assumptions about the influence of cyclists on car infrastructure.

Comprehensive profiling of conjugated fatty acid isomers and their lipid oxidation products by two-dimensional chiral RP×RP liquid chromatography hyphenated to UV- and SWATH-MS-detection

This research reports on the development of a comprehensive two-dimensional liquid chromatography (2D-LC) method hyphenated to inline DAD-UV and ESI-QTOF-MS/MS-detection for the separation of conjugated polyunsaturated fatty acid isomers and structurally related (saturated, unconjugated, oxidized) compounds. In pharmaceutical lipid formulations conjugated fatty acids can be found as impurities, generated by oxidation of polyunsaturated fatty acids. Due to the structural complexity of resultant multi-component samples one dimensional liquid chromatography may be suboptimal for quality control and impurity profiling. The screened reversed-phase columns showed a lack of selectivity for the conjugated fatty acid isomers but the resolutions improved with the shape selectivity of the stationary phases (C18- < C30- < cholesteryl-ether-bonded). Further enhanced selectivity for the non-chiral conjugated FAs could be achieved with amylose/cellulose-based chiral stationary phases (CSPs) which harbor cavities for selective inclusion depending on E/Z configurations of the double bonds of the analytes. Amylose-based CSPs showed higher selectivity for conjugated fatty acids than the cellulose-based polysaccharide CSPs. Hyphenating the chiral and reversed-phase columns in a comprehensive 2D-LC-setup was favorable since they showed orthogonality and good compatibility, because both were operated under RP-conditions. The chiral dimension (1D) mainly separated the different isomers, while the reversed-phase dimension (2D) separated according to number of double bonds and degree of oxidation. Using this setup, advanced structural annotation of unknowns was possible based on UV-, MS1- and MS2-spectra. Data-independent acquisition (by SWATH) enabled differentiation of positional isomers of oxidized lipids by characteristic MS2-fragments and elucidation of co-eluted compounds by selective extracted ion chromatograms of fragment ions (MS2 EICs).

Intelligent Feature Subset Selection with Machine Learning Based Detection and Mitigation of DDoS Attacks in 5G Environment

The fifth-generation (5G) technology is anticipated to permit connectivity to billions of devices, called the Internet of Things (IoT). The primary benefit of 5G is that it has maximum bandwidth and can drastically expand service beyond cell phones to standard internet service for conventionally fixed connectivity to homes, offices, factories, etc. But IoT devices will unavoidably be the primary target of diverse kinds of cyberattacks, notably distributed denial of service (DDoS) attacks. Since the conventional DDoS mitigation techniques are ineffective for 5G networks, machine learning (ML) approaches find helpful to accomplish better security. With this motivation, this study resolves the network security issues posed by network devices in the 5G networks and mitigates the harmful effects of DDoS attacks. This paper presents a new pigeon-inspired optimization-based feature selection with optimal functional link neural network (FLNN), PIOFS-OFLNN model for mitigating DDoS attacks in the 5G environment. The proposed PIOFS-OFLNN model aims to detect DDoS attacks with the inclusion of feature selection and classification processes. The proposed PIOFS-OFLNN model incorporates different techniques such as pre-processing, feature selection, classification, and parameter tuning. In addition, the PIOFS algorithm is employed to choose an optimal subset of features from the pre-processed data. Besides, the OFLNN based classification model is applied to determine DDoS attacks where the Rat Swarm Optimizer (RSO) parameter tuning takes place to adjust the parameters involved in the FLNN model optimally. FLNN is a low computational interconnectivity higher cognitive neural network. There are still no hidden layers. FLNN’s input vector is operationally enlarged to produce non-linear remedies. More details can be accessed application of Nature-Inspired Method to Odia Written by hand Number system Recognition. To validate the improved DDoS detection performance of the proposed model, a benchmark dataset is used.

Bodies of transnational island urbanism: Spatial narratives of inclusion/exclusion of Filipinas in Philippine islands

Tropical islands can become terrains of urbanisation worthy of examination. In the Philippines, several islands have experienced urban transformation (capital accumulation, immigration, diversification, land conversion) through tourism. At the forefront of these urban transformations are Filipinas, particularly those in interracial relationships with foreign men who invest in island properties and establish resorts. These resorts stimulate a transnationally-oriented mode of urban transformation reliant on the transnational mobilities of tourists, expats and capital. This paper examines this by foregrounding the experiences of Filipinas, concentrating on how they are differentially included and excluded throughout the multi-scalar process of island urban accumulation. I locate these differential experiences in various spaces (nation, community, resort, households), noting in particular the (1) national discourses underlying state tourism and foreign retirement programmes, (2) transactions enabling property purchases and resorts, and (3) translocal mobilities sustaining urban accumulation. What emerge from these accounts are the selective inclusions and exclusions of Filipinas in transnational urban accumulation in the islands. While their role in facilitating island urban accumulation may suggest a form of ‘empowered’ inclusivity, this can easily be undercut by sexist micropolitics of exclusion that tend to reduce them to ‘mere women’ and/or ‘prostitutes’. Such differential practices of inclusion/exclusion demonstrate the gendered dynamics that unequally put a double burden on Filipinas. Unravelling these accounts demonstrates how gendered relations and sexuality are important forces underpinning urban transformation and transnational mobilities that constitute diversification.

AI-Radiomics Can Improve Inclusion Criteria and Clinical Trial Performance.

Purpose: Success of clinical trials increasingly relies on effective selection of the target patient populations. We hypothesize that computational analysis of pre-accrual imaging data can be used for patient enrichment to better identify patients who can potentially benefit from investigational agents. Methods: This was tested retrospectively in soft-tissue sarcoma (STS) patients accrued into a randomized clinical trial (SARC021) that evaluated the efficacy of evofosfamide (Evo), a hypoxia activated prodrug, in combination with doxorubicin (Dox). Notably, SARC021 failed to meet its overall survival (OS) objective. We tested whether a radiomic biomarker-driven inclusion/exclusion criterion could have been used to improve the difference between the two arms (Evo + Dox vs. Dox) of the study. 164 radiomics features were extracted from 296 SARC021 patients with lung metastases, divided into training and test sets. Results: A single radiomics feature, Short Run Emphasis (SRE), was representative of a group of correlated features that were the most informative. The SRE feature value was combined into a model along with histological classification and smoking history. This model as able to identify an enriched subset (52%) of patients who had a significantly longer OS in Evo + Dox vs. Dox groups [p = 0.036, Hazard Ratio (HR) = 0.64 (0.42–0.97)]. Applying the same model and threshold value in an independent test set confirmed the significant survival difference [p = 0.016, HR = 0.42 (0.20–0.85)]. Notably, this model was best at identifying exclusion criteria for patients most likely to benefit from doxorubicin alone. Conclusions: The study presents a first of its kind clinical-radiomic approach for patient enrichment in clinical trials. We show that, had an appropriate model been used for selective patient inclusion, SARC021 trial could have met its primary survival objective for patients with metastatic STS.

Systematic review of the use of CRP in clinical trials for psoriatic arthritis: a concern for clinical practice?

BackgroundC reactive protein (CRP) levels are suggested as serum biomarkers in the diagnosis and prognosis of psoriatic arthritis (PsA). However, increased CRP levels are found in less than 50% of...

Moving Toward an Inclusive Housing Policy?: Migrants’ Access to Subsidized Housing in Urban China

ABSTRACT China is rapidly urbanizing, with hundreds of millions of migrants leaving villages for cities. Under the discriminatory Household Registration (Hukou) System, migrants have been denied urban welfare benefits. The Chinese government has been promoting inclusive urbanization with significant policy changes in recent decades, yet its impact on migrants is not clear. This article examines whether housing is becoming more inclusive to migrants in Chinese cities. A review of recent policy changes at both central and local levels shows that although central housing policy is becoming more inclusive of migrants, local governments have largely remained exclusionary and exercise selective inclusion—allowing only migrants who meet additional, strict requirements to access subsidized housing. The empirical analyses, using two waves of the China Migrants Dynamic Survey, reveal that few migrants have access to subsidized housing despite the policy changes. Institutional barriers continue to exclude migrants from subsidized housing, although many barriers have become less important over time. It is clear that housing discrimination persists, and housing inclusion remains a distant dream for most migrants in China. This research highlights exclusion based on an important but uncommon birth-ascribed status defined by the government and provides a multiscalar perspective on the inclusion of domestic migrants.

Selective inclusion of p-xylene by bis-hydrazone compounds

p-Xylene can be separated from a mixture of xylene isomers by the selective inclusion property of three novel bis-hydrazone compounds. Crystallization of these compounds in solvents containing p-XY generate voids which are complementary to only p-XY.

Realness as Resistance: Queer Feminism, Neoliberalism, and Early Trans Critiques of Butler

AbstractIn this article, I argue that scholarship on the cultural impact of neoliberalism provides a vital framework with which to revisit early trans critiques of Butlerian queer feminism. Drawing on this scholarship, I reread the appeals to the real and realness in these critiques through the neoliberal transformation of social difference. I link the early argument that some trans figures were problematically used in queer feminism to represent the fluidity of identity with the more recent argument that the flexibility of identity has become a core part of neoliberal cultures. This context challenges the current dominant view of early trans critiques of Butler as misreadings and instead casts them as resistant to a superficial encouragement of individual flexibility. As a result, revisiting this debate demonstrates the need to rework theoretical frameworks that may continue to inadvertently lead to selective trans inclusion in queer feminism and points the way to trans-queer-feminist theory that is more attuned to shifting models of power.

Application of predictive models in boosting power of Alzheimer's disease clinical trials: A post hoc analysis of phase 3 solanezumab trials.

BackgroundThe ideal participants for Alzheimer's disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e., placebo arm) and would also respond to the therapeutic intervention.ObjectiveTo investigate if predictive models can be an effective tool for identifying and excluding people unlikely to show cognitive decline as an enrichment strategy in AD trials.MethodWe used data from the placebo arms of two phase 3, double‐blind trials, EXPEDITION and EXPEDITION2. Patients had 18 months of follow‐up. Based on the longitudinal data from the placebo arm, we classified participants into two groups: one showed cognitive decline (any negative slope) and the other showed no cognitive decline (slope is zero or positive) on the Alzheimer's Disease Assessment Scale–Cognitive subscale (ADAS‐cog). We used baseline data for EXPEDITION to train regression‐based classifiers and machine learning classifiers to estimate probability of cognitive decline. Models were applied to EXPEDITION2 data to assess predicted performance in an independent sample. Features used in predictive models included baseline demographics, apolipoprotein E ε4 genotype, neuropsychological scores, functional scores, and volumetric magnetic resonance imaging.ResultIn EXPEDITION, 46.3% of placebo‐treated patients showed no cognitive decline and the proportion was similar in EXPEDITION2 (45.6%). Models had high sensitivity and modest specificity in both the training (EXPEDITION) and replication samples (EXPEDITION2) for detecting the stable group. Positive predictive value of models was higher than the base prevalence of cognitive decline, and negative predictive value of models were higher than the base rate of participants who had stable cognition.ConclusionExcluding persons with AD unlikely to decline from the active and placebo arms of clinical trials using predictive models may boost the power of AD trials through selective inclusion of participants expected to decline.

Using Focus Groups to Understand Dialysis Staff Perspectives on Delivering Transplant Education.

Kidney transplant education in dialysis facilities could be optimized with internet resources, like videos, but most qualitative research predates widespread availability of online video education about kidney transplantation. To improve understanding of dialysis staff transplant education practices, as well as the potential value of video, we conducted focus groups of dialysis center staff members in Buffalo, NY. Seventeen focus groups (97 participants: 53 nurses, 10 dialysis technicians, 6 social workers, 6 dieticians, 7 administrative personnel, 2 trainees, and 1 insurance coordinator) from 8 dialysis facilities in Buffalo, NY, were conducted, audio-recorded, transcribed, and analyzed. After thematic data analysis, a diverse patient and caregiver community advisory board was invited to comment, and their voices were integrated. Findings: Five key themes were identified that captured barriers to transplant education delivery and how online video could be a facilitator: (1) delivery of transplant education was reliant on one person, (2) other dialysis staff had time to answer transplant questions but felt uninformed, (3) patient lack of interest in existing supplementary transplant education, (4) patient disinterest in transplantation education was due to education timing, feeling overwhelmed, and transplant fear/ambivalence, and (5) video education could be flexible, low effort, and spark transplant interest. Study limitations are potential selection bias and inclusion of English-speaking participants only. Dialysis staff barriers of time, insufficient knowledge, and limited resources to provide education to patients and their care partners may be mitigated with online educational videos without increasing staff workload.

Finite element method in computer simulation for improved patient care in dentistry: A systematic review

Background. The fi nite element method is gaining acknowledgment in Russia and other developed countries in a range of areas, including medicine. In stomatology, the method is applicable in research and implication of novel treatment and relevant material design.Objective. The review highlights usage of the fi nite element method in computer simulation to improve quality of patient dental care.Methods. The review analyses the state-of-the-art in current scientific literature. Records were mined in the PubMed and e-Library databases at a depth of 10 years, with selective inclusion of earlier articles. The query keywords were: finite element method [метод конечных элементов], computer simulation [компьютерная симуляция], quality of life improvement [повышение качества жизни], oral diseases [заболевания полости рта], dental treatment [стоматологическое лечение].Results. The review systematically surveys 56 scientific papers in the focus area for current state-of-the-art in the finite element analysis-empowered simulation in dentistry. The method’s rising employment is conditioned by its flexibility, 3D-object modelling simplicity and the rapid acquisition of reliable high-quality output. Its undoubted paramount advantage in dentistry is an explicit software visualisation of reliable results through co-modelling of multiple oral parameters.Conclusion. The growing acquaintance, mastering and use of this technique among researchers around the globe will give impetus to novel diagnosis and treatment, as well as relevant management algorithms in particular patient categories to enable personalisation of even mass dental check-up. This will reduce the number of visits, peri- and posttreatment error and complication rates for the improved patient’s quality of life and social rehabilitation.

Mesoporous One-Component Gold Microshells as 3D SERS Substrates.

Surface-enhanced Raman scattering (SERS) is a powerful analytical tool for label-free analysis that has found a broad spectrum of applications in material, chemical, and biomedical sciences. In recent years, a great interest has been witnessed in the rational design of SERS substrates to amplify Raman signals and optionally allow for the selective detection of analytes, which is especially essential and challenging for biomedical applications. In this study, hard templating of noble metals is proposed as a novel approach for the design of one-component tailor-made SERS platforms. Porous Au microparticles were fabricated via dual ex situ adsorption of Au nanoparticles and in situ reduction of HAuCl4 on mesoporous sacrificial microcrystals of vaterite CaCO3. Elimination of the microcrystals at mild conditions resulted in the formation of stable mesoporous one-component Au microshells. SERS performance of the microshells at very low 0.4 µW laser power was probed using rhodamine B and bovine serum albumin showing enhancement factors of 2 × 108 and 8 × 108, respectively. The proposed strategy opens broad avenues for the design and scalable fabrication of one-component porous metal particles that can serve as superior SERS platforms possessing both excellent plasmonic properties and the possibility of selective inclusion of analyte molecules and/or SERS nanotags for highly specific SERS analysis.

Thermomechanical Combination Injuries: A Rare But Life-Threatening Entity.

Thermomechanical combination injuries (TMCIs) are feared for their demanding preclinical and clinical management and bear the risk of high mortality compared to the single injury of a severe burn or multiple trauma. There remains a significant lack of standardized algorithms for diagnostics and therapy of this rare entity. The objective of the present study was to profile TMCI aiming at standardized procedures. In this study, TMCIs were extracted from our burn database of a level 1 burn and trauma center. From 2004 to 2017, all patients with TMCI were retrospectively analyzed. Further inclusion criteria were multiple trauma accompanied by burn with ≥10% TBSA. Patient and injury characteristics including injury severity score and outcome parameter were analyzed. A total of 45 patients matched the selective inclusion criteria of TMCI, comprising 4% of all burn injuries during the period. The average age was 38 years (range: 14-86), with a mean TBSA of 43% (range: 10-97%). The mean recorded temperature at admission was 34.8°C (range: 29.6-37.1) with 2215 ml volume of resuscitation fluids (range: 500-8000) administered preclinically in total. The mean injury severity score was 16. The overall mortality rate was 22%. TMCIs are rare and life-threatening events that require highly qualified management in combined level 1 trauma and burn centers to address both burn and trauma treatment. The multiple injury pattern is diverse, complicating standardized management in view of burn care-specific measures, as normothermia and restrictive volume management. The present study reveals further profiles and underlines the need for addressing TMCIs in ABLS®, ATLS®, and PHTLS® programs.

Protein Response Effects on Cofactor Excitation Energies from First Principles: Augmenting Subsystem Time-Dependent Density-Functional Theory with Many-Body Expansion Techniques

We investigate the possibility of describing protein response effects on a chromophore excitation by means of subsystem time-dependent density-functional theory (sTDDFT) in combination with a many-body expansion (MBE) approach. While sTDDFT is in principle intrinsically able to include such contributions, addressing cofactor excitations in protein models or entire proteins with full environment-response treatments is currently out of reach. Taking different model structures of the green fluorescent protein (GFP) and bovine rhodopsin as examples, we demonstrate that an embedded-MBE approach based on sTDDFT in its simplest version leads to a good agreement of the predicted protein response effect already at second order. To reproduce reference response effects from nonsubsystem TDDFT calculations quantitatively (error ≤ 5%), however, a third- or even fourth-order MBE may be required. For the latter case, we explore a selective inclusion of fourth-order terms that drastically reduces the computational burden. In addition, we demonstrate how this sTDDFT-MBE treatment can be utilized as an analysis tool to identify residues with dominant response contributions. This, in turn, can be employed to arrive at smaller structural models for light-absorbing proteins, which still feature all of the main characteristics in terms of photoresponse properties.

Effects of SiC particles codeposition and ultrasound agitation on the electrocrystallisation of nickel-based composite coatings

This study analysed the influence of the codeposition of SiC particles with different sizes: 50 nm, 500 nm and 5 μm, and the type of bath agitation (stirring or ultrasonic) on the electrocrystallisation of nickel coatings. The composites matrix microstructure was analysed by means of SEM, EBSD and XRD, to evaluate the grain size, crystal orientation, and internal stresses and was benchmarked against pure nickel samples electrodeposited in equivalent conditions. The codeposition of nano- and microsize particles with an approximate content of 0.8 and 4 vol.%, respectively, caused only a minor grain refinement and did not vary the dominant < 100 > crystal orientation observed in pure Ni. The internal stress was, however, increased by particles codeposition, up to 104 MPa by nanoparticles and 57 MPa by microparticles, compared to the values observed in pure nickel (41 MPa). The higher codeposition rate (11 vol.%) obtained by the addition of submicron-size particles caused a change in the grain growth from columnar to equiaxial, resulting in deposits with a fully random crystal orientation and pronounced grain refinement. The internal stress was also increased by 800% compared to pure nickel. The ultrasound (US) agitation during the deposition caused grain refinement and a selective particle inclusion prompting a decrease in the content of the particles with the larger particles. The deposits produced under US agitation showed an increase in the internal stresses, with double values compared to stirring. The increase in the deposits microhardness, from 280 HV in pure Ni to 560 HV in Ni/SiC submicron-US, was linked to the microstructural changes and particles content.Graphical abstract