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Hydrogen production from electrolytic water is a key component in realising a hydrogen economy. At the same time, resourceful utilization of nickel slag can reduce environmental and health hazards. The aim of this study is to prepare clean and efficient hydrogen evolution electrodes from nickel slag by modulating the crystal surface of electrolytic catalyst. According to the density functional theory calculations, the crystal surface with the best catalytic properties is Ni (111). Based on the theoretical calculations, this work proposed controlling the reduction order and reduction efficiency of Ni2+ and H 2 O in the nickel slag leachate during electrolysis to modulation of crystal surface growth of Ni. Moreover, amorphous Ni(OH) 2 was designed to selectively grow in Ni product to further improve the catalytic performance of Ni (1 1 1). The electrodes with the best catalytic performance for hydrogen evolution were obtained when the electrodeposition conditions were 30 min, 0.05 M, and 12.5 mA/cm2. A current density of 10 mA/cm2 was achieved with an overpotential of only 17.46 mV. The Tafel slope was 31.2 mV·dec−1. The proposed method is a straightforward and clean approach that does not require membrane addition. At the same time, using nickel slag as raw material can not only reduce the harm of nickel slag to the environment, but also reduce the cost of preparing electrodes. Therefore, this method offers an efficient, environmentally friendly, and cost-effective approach to preparing high-performance catalytic electrodes for hydrogen evolution. • A clean electrolysis was designed to prepare hydrogen evolution electrode from nickel slag. • Resource reuse of nickel slag has economic and environmental benefits. • The entire electrolysis process produces no pollutants. • The overpotential of prepared electrode is only 17.46 mV at 10 mA/cm2. [ABSTRACT FROM AUTHOR]

Motivating manufacturers to reduce carbon emissions is an effective way to achieve sustainable development goals (SDGs). However, the carbon-constrained manufacturers are under pressure to consider market uncertainty, consumer’s green behavior, and supply chain cooperation when optimizing strategies under government regulations. Therefore, we deserve a detailed theoretical examination of cap-and-trade policy with supply chain cooperative contracts, depict uncertain demand by the newsvendor model, and optimize the emission reduction, order quantity, and pricing strategies in three cooperative cases: wholesale price, cost-sharing, and collaborative contract. Moreover, we analyze the effects of carbon regulations on the optimal decisions and profits, then conduct a comparative study on these results under three cooperative contracts. Our findings show that the manufacturer will purchase more emission rights rather than invest in reduction when the government-given carbon quotas decrease. Besides, the cost-sharing contract promotes greener production and higher reduction level compared to the wholesale price contract, but damages the manufacturer’s profit as the cost-sharing ratio and green preference rise. In this case, the government should increase the emission quotas and meanwhile enhance consumer’s green awareness based on a substantial growth of potential market. Furthermore, to improve the positive effect of cost-sharing contract on emission reduction levels, the government should increase carbon quotas when the carbon trading price fluctuates in a relatively higher range. [ABSTRACT FROM AUTHOR]

The 3D vibration model of metaconcrete single aggregate is established under the linear elastic deformation. The soft coating and mortar are replaced by equivalent spring. Their equivalent mass, length and stiffness are calculated. The nonlinear control equation of free vibration is derived. The analytical expression of solution was acquired. A kind of method for solving such equation was given. The analytical expression of non-damping and damping nonlinear frequency are obtained. The effects of material parameters, geometrical parameters and initial conditions of aggregate on vibration were analyzed. The backbone curves of free vibration are studied. The influence of elastic modulus of soft coating on the backbone curves, the time history curve of displacement, etc. are investigated. The selection of aggregates is optimized. It can provide theoretical reference for engineering design such as designing aggregates attenuating high-frequency wave, low-frequency vibrations, etc. and for the theoretical study of multiple cells aggregate vibration. [ABSTRACT FROM AUTHOR]

Background: Research on carceral institutions and mortality finds that people in prisons and jails have a high risk of death immediately following release from custody and that while incarcerated, racial disparities in prisoner mortality counter observed death patterns among similarly situated non-incarcerated, demographic groups. Yet, many of these studies rely on data prior to the millennium, during the COVID-19 pandemic, or are relegated to a small number or select group of states. In this paper, we explore changes in mortality and life-expectancy among different demographic groups, before and after the Great Recession, across forty-four states that reported deaths in custody to the federal government between 2000 and 2014. Methods: Drawing on a novel dataset created and curated, we calculate standard, age- specific quantities (death rates and life-expectancy) using period lifetable methods, disaggregated by race and sex, across three different periods (2000–2004, 2005–2009, and 2010–2014) for each state. Ordinary least squares regression models with state and year fixed-effects are included to examine state-level factors that may explain differences in prisoner mortality rates between 2000 and 2014. We also benchmark death counts reported to federal agencies with official state reports to cross-validate general mortality patterns. Results: Among imprisoned men, age-specific trends in mortality have shifted across the three periods. Following the Great Recession and the push for criminal justice reforms, prisoner mortality dropped significantly and is concentrated at older ages among men during 2010–2014; the shifting pattern of mortality means that men age 30 in 2010–2014 had similar death rates as men in their early 20s during 2000–2004, representing a 7.5 year shift in age-specific mortality rates. Gains in the mortality decline were disproportionately experienced by Non-Hispanic White and Non-Hispanic Black men, with the latter experiencing the greatest gains in life-expectancy of any demographic group. State-level violent crime rates are strongly and positively associated with prison mortality rates across states, net of socioeconomic and political factors. The large and significant disappearance of deaths in prisons from official data reported to federal agencies calls into question the narrowing gap in racial disparities among people in carceral facilities. Conclusions: Legal decisions and social policies aimed at reducing mortality may be most effective in the short-run; however, the effects of these policy changes may fadeout over time. Research should clearly discern whether changes in mortality rates across states are due to diminished gains in social policies or increases in the disappearance (or underreporting) of deaths in custody. Understanding how and why gains in survivorship may stall is important for aligning health initiatives with social policy to facilitate maximal and consistent mortality declines for all demographic groups. [ABSTRACT FROM AUTHOR]

Urban heritage areas are characterized by unique architectural and cultural elements, often coupled with specific challenges such as vulnerability to climate change and urban heat islands (UHIs). Investigating thermal performance at the neighborhood scale is crucial for preserving these areas while enhancing thermal comfort and sustainability. The aim of this research is to prove that the application of passive cooling techniques and urban green spaces can reduce the urban temperature and upgrade the conditions of thermal comfort, even in densely populated areas with small urban void spaces. ENVI-Met, a microclimate modeling software for evaluating the thermal performance of heritage urban neighborhoods, is applied in order to assess current thermal conditions, identify hotspots, perform simulations, and propose mitigation strategies to improve thermal comfort while preserving the architectural and cultural integrity of these areas. The test bed of this study is a historical urban area in central Athens, "Academia Platonos". The methodology is mainly based on the design of different parametric scenarios for the study area, by integrating specific parameters that characterize the area of Academia Platonos (elevation distribution, materials, vegetation, etc.) and the microclimatic simulations of the area, designed in the digital environment of ENVI-Met. Five scenarios are implemented and studied in the study area, four of which are based on the existing situation of the study area, either by changing the construction materials of the built environment (passive cooling through cool material techniques) or by enhancing the area with vegetation. One of the most important findings of this study is that the use of plants with a high foliage density is more effective in reducing air temperature than the selection of species with sparse foliage. [ABSTRACT FROM AUTHOR]

A data transmission delay compensation algorithm for an interactive communication network of an offshore oil field operation scene in severe weather is proposed. To solve the problem of unstable microwave signals and a large amount of noise in the communication network caused by bad weather, the communication network signal denoising method based on Lagrange multiplier symplectic singular value mode decomposition is adopted, and the communication network data denoising process is realized through five steps; phase space reconstruction, symplectic geometric similarity transformation, grouping, diagonal averaging, and adaptive reconstruction. Simultaneously, the weak communication signal is compensated after being captured, that is, the characteristics of the weak signal are enhanced. On this basis, the communication network signals are collected to obtain delay information, and the data transmission delay of the communication network is predicted using the neural network algorithm based on long-term and short-term memory; Based on the prediction result of transmission delay, the PID controller is used to calculate the transmission delay compensation amount of the communication network, and the calculation result of the compensation amount is input into the delay compensator to realize transmission delay compensation. The experimental results show that the algorithm can effectively improve the quality of data transmission in the communication network and has a good delay compensation effect to ensure real-time communication. [ABSTRACT FROM AUTHOR]