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Accurate prediction of catalyst performance is crucial for designing materials with specific catalytic functions. While the density functional theory (DFT) method is widely used for its accuracy, modeling heterogeneous systems, especially supported transition metals, poses significant computational challenges. To address these challenges, we introduce the Electronic Structure Decomposition Approach (ESDA), a novel method that identifies specific density of states (DOS) areas responsible for adsorbate interaction and activation on the catalyst. As a case study, we investigate the influence of α-Al2O3(0001) as a support material on CO adsorption energy and the stretching frequency of the C-O bond on Ru nanoparticles (NPs). Using multiple linear regression analysis, ESDA models were trained with data from isolated Ru NPs and adjusted using supported NP sample data. The ESDA models accurately predict the CO adsorption energies and C-O vibrational frequencies, demonstrating strong linear correlations between predicted and DFT-calculated values with low errors across various adsorption sites for both isolated and supported Ru NPs. Beyond pinpointing the DOS areas responsible for CO adsorption and C-O bond activation, this study provides insights into manipulating these DOS areas to control CO activation, hence facilitating CO dissociation. Additionally, ESDA significantly accelerates the characterization and prediction of CO adsorption and activation on both isolated and supported Ru NPs compared to DFT calculations, expediting the design of new catalytic materials and advancing catalysis research. Furthermore, ESDA's reliance on the electronic structure as a descriptor suggests its potential for predicting various properties beyond catalysis, broadening its applicability across diverse scientific domains.

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OBJECTIVES: To delineate specific family needs during the postpartum period using data from Family Connects (FC), a universal home-visiting initiative, and to scrutinize potential racial and ethnic disparities in these needs. METHOD: FC implementation data spanned from July 1, 2009, to August 31, 2021, in seven counties across the USA. Data encompassed nurse-led in-home assessments for 34,119 families. Nurses evaluated needs across four domains (healthcare, parenting/childcare, safe home, and parent support) comprising 12 risk factors. FINDINGS: Overall, families reported high levels of need, and community connections were facilitated for 57% of visited families. Significant differences in need profiles between whites and minority groups were revealed, reflecting both disparity and uniqueness. Employing the Oaxaca decomposition approach, we found that racial/ethnic disparities in socioeconomic attributes were associated with racial/ethnic gaps in the need profiles. CONCLUSIONS: The event of giving birth is both high risk and high opportunity for preventive intervention. Home-visiting programs, as an evidence-based approach, must address the diverse spectrum of familial needs comprehensively.

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BACKGROUND: Health inequities have a profound impact on all dimensions of people's lives, with invariably worse results among the most disadvantaged, transforming them into a more fragile and vulnerable population. These unfair inequalities also affect dimensions focused on subjectivity, such as health-related quality of life (HRQoL), which has been positioned, in recent decades, as an important outcome in health decision-making. The main objective of this study is to estimate socioeconomic inequality in HRQoL of Chilean by household income.  METHODS: Secondary analysis of the National Health Survey (ENS 2016-2017, Chile). This survey includes a nationally representative, stratified, and multistage household sample of people aged 15 and above. Socioeconomic inequality in HRQoL (EQ5D) is estimated by the concentration index (CI) ranked by household income. Decomposition analysis is conducted to examine potential explanatory sociodemographic factors.  RESULTS: The CI for household income inequality in HRQoL was -0.063. The lower the household income, the worse the HRQoL reported by in Chile. The decomposition analysis revealed that socioeconomic position contributes 75,7% to inequality in the quality of life, followed by educational level (21.8%), female gender (17.3%), and type of Health Insurance (15%), age (-19.7%) and residence (-10.8%). Less than 1% corresponds to the unexplained residual component. CONCLUSIONS: Our findings suggest the existence of a disproportionate concentration of worse HRQoL in the most disadvantaged socioeconomic groups in Chile. This inequality is largely, yet not completely, associated with household income. Other significant factors associated with this inequality are education, gender, and healthcare insurance. These results suggest the need of strengthening efforts to reducing socioeconomic gaps in health outcomes in Chile, as a means to achieve social justice and equity in health and healthcare.

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Background: Inequalities undermine efforts to end AIDS by 2030. We examined socioeconomic inequalities in the 90-90-90 target among people living with HIV (PLHIV) -men (MLHIV), women (WLHIV) and adolescents (ALHIV). Methods: We analysed the available Population HIV Impact Assessment (PHIA) survey data for each of the 12 sub-Saharan African countries, collected between 2015 and 2018 to estimate the attainment of each step of the 90-90-90 target by wealth quintiles. We constructed concentration curves, computed concentration indices (CIX) -a negative (positive) CIX indicated pro-poor (pro-rich) inequalities- and identified factors associated with, and contributing to inequality. Findings: Socioeconomic inequalities in achieving the 90-90-90 target components among PLHIV were noted in 11 of the 12 countries surveyed: not in Rwanda. Awareness of HIV positive status was pro-rich in 5/12 countries (Côte d'Ivoire, Tanzania, Uganda, Malawi, and Zambia) ranging from CIX=0·085 (p< 0·05) in Tanzania for PLHIV, to CIX = 0·378 (p<0·1) in Côte d'Ivoire for ALHIV. It was pro-poor in 5/12 countries (Côte d'Ivoire, Ethiopia, Malawi, Namibia and Eswatini), ranging from CIX = -0·076 (p<0·05) for PLHIV in Eswatini, and CIX = -0·192 (p<0·05) for WLHIV in Ethiopia. Inequalities in accessing ART were pro-rich in 5/12 countries (Cameroun, Tanzania, Uganda, Malawi and Zambia) ranging from CIX=0·101 (p<0·05) among PLHIV in Zambia to CIX=0·774 (p<0·1) among ALHIV in Cameroun and pro-poor in 4/12 countries (Tanzania, Zimbabwe, Lesotho and Eswatini), ranging from CIX = -0·072 (p<0·1) among PLHIV in Zimbabwe to CIX = -0·203 (p<0·05) among WLHIV in Tanzania. Inequalities in HIV viral load suppression were pro-rich in 3/12 countries (Ethiopia, Uganda, and Lesotho), ranging from CIX = 0·089 (p< 0·1) among PLHIV in Uganda to CIX = 0·275 (p<0·01) among WLHIV in Ethiopia. Three countries (Tanzania CIX = 0·069 (p< 0·5), Uganda CIX = 0·077 (p< 0·1), and Zambia CIX = 0·116 (p< 0·1)) reported pro-rich and three countries (Côte d'Ivoire CIX = -0·125 (p< 0·1), Namibia CIX = -0·076 (p< 0·05), and Eswatini CIX = -0·050 (p< 0·05) pro-poor inequalities for the cumulative CIX for HIV viral load suppression. The decomposition analysis showed that age, rural-urban residence, education, and wealth were associated with and contributed the most to inequalities observed in achieving the 90-90-90 target. Interpretation: Some PLHIV in 11 of 12 countries were not receiving life-saving HIV testing, treatment, or achieving HIV viral load suppression due to socioeconomic inequalities. Socioeconomic factors were associated with and explained the inequalities observed in the 90-90-90 target among PLHIV. Governments should scale up equitable 95-95-95 target interventions, prioritizing the reduction of age, rural-urban, education and wealth-related inequalities. Research is needed to understand interventions to reduce socioeconomic inequities in achieving the 95-95-95 target. Funding: This study was supported by the Swiss National Science Foundation (grant 202660).

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The decomposition analysis has been employed to discover the driving factors of carbon emission intensity, but the current studies assume that production functions are under the condition of the neutral technical change. Grounded on biased technical change production theory, this paper proposes a novel multidimensional decomposition approach which combines production-theory decomposition analysis (PDA) and index decomposition analysis (IDA). This novel approach can illustrate how energy structure effect, element substitution effect, efficiency change effect, input biased technical change, output biased technical change and magnitude of technical change affect carbon emission intensity of China's 30 provinces. The results indicate that during the 11th FYP and 13th FYP, output biased technical change and the magnitude of technical change are the critical factors in China's carbon emission intensity, while other four drivers increase carbon emissions. But, during the 12th FYP, the role of six drivers has been reversed contrasting 11th FYP and 13th FYP. In addition, we also explore the impact of each driver from the perspective of regional heterogeneity.

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By using the crystalline precursor decomposition approach and direct co-precipitation the composition and mesostructure of cobalt-based spinels can be controlled. A systematic substitution of cobalt with redox-active iron and redox-inactive magnesium and aluminum in a cobalt spinel with anisotropic particle morphology with a preferred 111 surface termination is presented, resulting in a substitution series including Co3 O4 , MgCo2 O4 , Co2 FeO4 , Co2 AlO4 and CoFe2 O4 . The role of redox pairs in the spinels is investigated in chemical water oxidation by using ceric ammonium nitrate (CAN test), electrochemical oxygen evolution reaction (OER) and H2 O2 decomposition. Studying the effect of dominant surface termination, isotropic Co3 O4 and CoFe2 O4 catalysts with more or less spherical particles are compared to their anisotropic analogues. For CAN-test and OER, Co3+ plays the major role for high activity. In H2 O2 decomposition, Co2+ reveals itself to be of major importance. Redox active cations in the structure enhance the catalytic activity in all reactions. A benefit of a predominant 111 surface termination depends on the cobalt oxidation state in the as-prepared catalysts and the investigated reaction.

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Some organism-specific databases about regulation in bacteria have become larger, accelerated by high-throughput methodologies, while others are no longer updated or accessible. Each database homogenize its datasets, giving rise to heterogeneity across databases. Such heterogeneity mainly encompasses different names for a gene and different network representations, generating duplicated interactions that could bias network analyses. Abasy (Across-bacteria systems) Atlas consolidates information from different sources into meta-curated regulatory networks in bacteria. The high-quality networks in Abasy Atlas enable cross-organisms analyses, such as benchmarking studies where gold standards are required. Nevertheless, network incompleteness still casts doubts on the conclusions of network analyses, and available sampling methods cannot reflect the curation process. To tackle this problem, the updated version of Abasy Atlas presented in this work provides historical snapshots of regulatory networks. Thus, network analyses can be performed at different completeness levels, making possible to identify potential bias and to predict future results. We leverage the recently found constraint in the complexity of regulatory networks to develop a novel model to quantify the total number of regulatory interactions as a function of the genome size. This completeness estimation is a valuable insight that may aid in the daunting task of network curation, prediction, and validation. The new version of Abasy Atlas provides 76 networks (204,282 regulatory interactions) covering 42 bacteria (64% Gram-positive and 36% Gram-negative) distributed in 9 species (Mycobacterium tuberculosis, Bacillus subtilis, Escherichia coli, Corynebacterium glutamicum, Staphylococcus aureus, Pseudomonas aeruginosa, Streptococcus pyogenes, Streptococcus pneumoniae, and Streptomyces coelicolor), containing 8459 regulons and 4335 modules. Database URL: https://abasy.ccg.unam.mx/.

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Based on a structural decomposition approach, the present paper simultaneously analyzes seven driving factors and forty sectors, which contribute to CO2 emission changes for China's transportation sector during 1992-2015. Based on the analysis of the driving factors, the total output and the energy intensity are found to be the primary positive and negative factor, respectively. From the sector analysis, top five sectors causing the increase of the transportation CO2 emissions are identified. Particularly, information transmission, computer services and software sector (no. 28); construction sector (no. 26); transportation sector (no. 27); chemical sector (no. 12); and leasing and business service sector (no. 33) are the five most relevant contributions to the increase of CO2 emissions of the transportation sector during 2002-2015. As a view to suppress CO2 emission growth, besides the promotion of public transportation, low-carbon emission energy, and energy-saving technologies, policymakers should pay attention to the impacts of key sectors on transportation.

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This paper presents a linear decomposition approach for a class of nonconvex programming problems by dividing the input space into polynomially many grids. It shows that under certain assumptions the original problem can be transformed and decomposed into a polynomial number of equivalent linear programming subproblems. Based on solving a series of liner programming subproblems corresponding to those grid points we can obtain the near-optimal solution of the original problem. Compared to existing results in the literature, the proposed algorithm does not require the assumptions of quasi-concavity and differentiability of the objective function, and it differs significantly giving an interesting approach to solving the problem with a reduced running time.

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This paper investigates stability analysis and stabilization for networked control systems. By a refined delay decomposition approach, slightly different Lyapunov-Krasovskii functionals (LKFs) with quadruple-integral terms and augmented vectors containing triple-integral forms of state are constructed. New integral inequalities are proposed to estimate the cross terms from derivatives of the LKFs, which can be proved to offer tighter bounds than what the Jensen one produces theoretically. Moreover, the non-strictly proper rational functions in deriving process are fully handled via reciprocally convex approach. A state feedback controller design approach is also developed. Numerical examples and applications to practical power and oscillator systems demonstrate the superiority of the proposed criteria in conservatism reduction compared to some existing ones.

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In this paper, the [Formula: see text] filtering problem is treated for N coupled genetic oscillator networks with time-varying delays and extrinsic molecular noises. Each individual genetic oscillator is a complex dynamical network that represents the genetic oscillations in terms of complicated biological functions with inner or outer couplings denote the biochemical interactions of mRNAs, proteins and other small molecules. Throughout the paper, first, by constructing appropriate delay decomposition dependent Lyapunov-Krasovskii functional combined with reciprocal convex approach, improved delay-dependent sufficient conditions are obtained to ensure the asymptotic stability of the filtering error system with a prescribed [Formula: see text] performance. Second, based on the above analysis, the existence of the designed [Formula: see text] filters are established in terms of linear matrix inequalities with Kronecker product. Finally, numerical examples including a coupled Goodwin oscillator model are inferred to illustrate the effectiveness and less conservatism of the proposed techniques.

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In this paper, we consider the problem of delay-interval-dependent robust stability and stabilization of a class of linear uncertain neutral-type systems with time-varying delay. By constructing a candidate Lyapunov-Krasovskii functional (LKF), that takes into account the delay-range information appropriately, less conservative robust stability criteria are proposed in terms of linear matrix inequalities (LMIs) to compute the maximum allowable upper bounds (MAUB) for the delay-interval within which the uncertain neutral-type system under consideration remains asymptotically stable. The verifiable stabilizability conditions and memoryless state feedback control design are stated. Finally, numerical examples are also designated to demonstrate the effectiveness and reduced conservatism of the developed results.

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This paper investigates improved delay-range-dependent robust absolute stability criteria for a class of Lur'e uncertain systems with interval time-varying delays. By using delayed decomposition approach (DDA), a tighter upper bound of the derivative of Lyapunov functional can be obtained, and thus the proposed criteria give results with less conservatism compared with some previous ones. An integral inequality approach (IIA) is proposed to reduce the conservativeness in computing the allowable maximum admissible upper bound (MAUB) of the time-delay. The developed stability condition is expressed in terms of linear matrix inequality (LMI) that manipulates fewer decision variables and requires reduced computational load. Finally, three numerical examples are given to show the effectiveness of the proposed stability criteria.

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This paper investigates the asymptotical stability problem for a class of neutral type neural networks with mixed time-varying delays. The system not only has time-varying discrete delay, but also distributed delay, which has never been discussed in the previous literature. Firstly, improved stability criteria are derived by employing the more general delay partitioning approach and generalizing the famous Jensen inequality. Secondly, by constructing a newly augmented Lyapunov-Krasovskii functionals, some less conservative stability criteria are established in terms of linear matrix inequalities (LMIs). Finally, four numerical examples are given to illustrate the effectiveness and the advantage of the proposed main results.

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This paper studies the problem of the stability analysis of interval time-varying delay systems with nonlinear perturbations. Based on the Lyapunov-Krasovskii functional (LKF), a sufficient delay-range-dependent criterion for asymptotic stability is derived in terms of linear matrix inequality (LMI) and integral inequality approach (IIA) and delayed decomposition approach (DDA). Further, the delay range is divided into two equal segments for stability analysis. Both theoretical and numerical comparisons have been provided to show the effectiveness and efficiency of the present method. Two well-known examples are given to show less conservatism of our obtained results and the effectiveness of the proposed method.

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This paper is concerned with the improved delay-range-dependent stability and robust stability criteria for linear systems with time-varying delay and norm-bounded uncertainties. In order to obtain much less conservative criteria, a Lyapunov-Krasovskii functional (LKF), which makes use of the information of both the lower and upper bounds of the interval time-varying delay, is proposed to derive new stability criteria. By using delayed decomposition approach (DDA), a tighter upper bound of the derivative of Lyapunov functional can be obtained, and thus the proposed criteria give results with less conservatism compared with some previous ones. The resulting criteria have advantages over some previous ones in that it involves fewer matrix variables but has less conservatism, which are established theoretically. We show, by four well known examples, that our result overcomes the previous allowable maximum admissible upper bound (MAUB) of the time-delay and it is less conservative than the previous results having a relatively small upper bound in the derivative of time delay.

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Increased serum uric acid (SUA) is a risk factor for gout and renal and cardiovascular disease (CVD). The purpose of this study was to identify genetic factors that affect the variation in SUA in 632 Mexican Americans participants of the San Antonio Family Heart Study (SAFHS). A genome-wide association (GWA) analysis was performed using the Illumina Human Hap 550K single nucleotide polymorphism (SNP) microarray. We used a linear regression-based association test under an additive model of allelic effect, while accounting for non-independence among family members via a kinship variance component. All analyses were performed in the software package SOLAR. SNPs rs6832439, rs13131257, and rs737267 in solute carrier protein 2 family, member 9 (SLC2A9) were associated with SUA at genome-wide significance (p < 1.3 × 10(-7)). The minor alleles of these SNPs had frequencies of 36.2, 36.2, and 38.2%, respectively, and were associated with decreasing SUA levels. All of these SNPs were located in introns 3-7 of SLC2A9, the location of the previously reported associations in European populations. When analyzed for association with cardiovascular-renal disease risk factors, conditional on SLC2A9 SNPs strongly associated with SUA, significant associations were found for SLC2A9 SNPs with BMI, body weight, and waist circumference (p < 1.4 × 10(-3)) and suggestive associations with albumin-creatinine ratio and total antioxidant status (TAS). The SLC2A9 gene encodes an urate transporter that has considerable influence on variation in SUA. In addition to the primary association locus, suggestive evidence (p < 1.9 × 10(-6)) for joint linkage/association (JLA) was found at a previously-reported urate quantitative trait locus (Logarithm of odds score = 3.6) on 3p26.3. In summary, our GWAS extends and confirms the association of SLC2A9 with SUA for the first time in a Mexican American cohort and also shows for the first time its association with cardiovascular-renal disease risk factors.