Chemical durability and surface alteration of lanthanide zirconates (A2Zr2O7: A = La-Yb)

Chemical durability of lanthanide zirconates (A₂Zr₂O₇) (A = La-Yb) under near-field environments is important for evaluating their application as potential nuclear waste forms. In this work, A₂Zr₂O₇ (A = La-Yb) are synthesized by spark plasma sintering with controlled microstructure and their chemical durability are evaluated in a nitric acid solution (pH = 1). Scanning transmission electron microscopy analysis reveals an amorphous passivation film either enriched with Zr or lanthanide. The complex chemistry of the passivation films can be correlated with a transition in corrosion mechanisms from a preferential release of lanthanide in La₂Zr₂O₇ to a preferential release of Zr in Er₂Zr₂O₇ and Yb₂Zr₂O₇. These results suggest a dominant mechanism of incongruent dissolution and surface reorganization for the formation of passivation films. Strong correlations are identified between the leaching rates and cation ionic size, ionic potential, electronegativity differences between A-site cation and Zr, and bonding valence sum of oxygen, suggesting important impacts of structural and bonding characteristics in controlling chemical durability of lanthanide zirconates.     

Sustainable optimization of waste management network over extended planning time horizon

This study proposes a multiperiod mixed integer linear programming model for the management of a single municipal solid waste (MSW) treatment plant with sustainability as the objective. Discrete and continuous variables define the capacity selections for diverse MSW technologies, and the operation of the MSW network, respectively. The economic target is considered to maximize the net present value. The environmental impact is the minimization of a normalized environmental objective function (NEOF). The social target is the maximization of jobs. An interesting feature about the research work is the requirement of biodrying technologies for MSW moisture content control. Due to the conflicted nature among the sustainability components, a multiobjective optimization (MO) is carried out to find the Pareto optimal solutions. The MO results show that the Pareto optimal solutions vary around profit range of $4.9–8.5 billion, NEOF impact range of 3.2–3.6 units, and social benefit range of 2700–4828 jobs.     

海南小型露天采石场矿山地质环境治理方法探讨：以日富石场为例

海南小型露天采石场矿山数量多且呈遍地开花式分布，且不规范的开采对环境造成较大的破坏，与绿色矿山之路背道而行，相对大型矿山规范化的治理，小型矿山治理比较滞后，本文以日富采石场地质环境治理为例，通过摸清当地的地质环境条件，结合矿山现状，因地制宜地制定出日富采石场地质环境治理的具体措施，通过治理可获得林地2.6hm2，矿山安全隐患及地貌景观等矿山地质环境问题得到有效地防治，有效解决农业灌溉及周边虾塘养殖用水缺乏问题，实现较好的社会经济效益，为今后治理类似矿山提供参考。     

Mechanisms of Reciprocal Regulation of Gonadotropin-Releasing Hormone (GnRH)-Producing and Immune Systems: The Role of GnRH,Cytokines and Their Receptors in Early Ontogenesis in Normal and Pathological Conditions

Different aspects of the reciprocal regulatory influence on the development of gonadotropin-releasing hormone (GnRH)-producing- and immune systems in the perinatal ontogenesis and their functioning in adults in normal and pathological conditions are discussed. The influence of GnRH on the development of the immune system, on the one hand, and the influence of proinflammatory cytokines on the development of the hypothalamic-pituitary-gonadal system, on the other hand, and their functioning in adult offspring are analyzed. We have focused on the effects of GnRH on the formation and functional activity of the thymus, as the central organ of the immune system, in the perinatal period. The main mechanisms of reciprocal regulation of these systems are discussed. The reproductive health of an individual is programmed by the establishment and development of physiological systems during critical periods. Regulatory epigenetic mechanisms of development are not strictly genetically controlled. These processes are characterized by a high sensitivity to various regulatory factors, which provides possible corrections for disorders.     

Ammonia mitigation and induction effects on hydrogen environment embrittlement of SCM440 low-alloy steel

The effect of ammonia (NH₃) contained in hydrogen (H₂) gas on hydrogen environment embrittlement (HEE) of SCM440 low-alloy steel was studied in association with the NH₃ concentration, loading rate, and gas pressure. NH₃ worked as both mitigator of the HEE and inducer of hydrogen embrittlement (HE) depending on the testing conditions. The mitigation of the HEE was achieved by the deactivation of the iron (Fe) surface for H₂ dissociation caused by the preferential adsorption of NH₃ on the Fe surface, which is enhanced by the increase in the NH₃ concentration and decrease in the H₂ gas pressure. NH₃ induced HE was caused due to creating hydrogen by the NH₃ decomposition. Since the NH₃ decomposition rate is low, the induction effect was observed when the loading rate was low. The effect of NH₃ was determined by the competition of the mitigation and induction effects.     

Graduate Student Literature Review: Considerations for nutritional grouping in dairy farms

Each cow in a group has different nutritional requirements even if the group is formed by cows of similar age, number of lactations, and lactation stage. Common dairy farm management setup does not support formulating a diet that accurately matches individual nutritional requirements for each cow; therefore, a proportion of cows in the group will be overfed and another proportion underfed. Overfeeding and underfeeding cows increases the risk of metabolic diseases, decreases milk production, and increases nutrient waste. Consequently, profitability of dairy farms and the environment are negatively affected. Nutritional grouping is a management strategy that aims to allocate lactating cows homogeneously according to their nutritional requirements. Groups of cows with more uniform nutritional requirements facilitates the formulation of more accurate diets for the group. Current availability of large data streams on dairy farms facilitates the design of algorithms to implement nutritional grouping. Our review summarizes important factors to consider when grouping cows, describes nutritional grouping approaches, and summarizes benefits of implementing nutritional grouping in dairy farms.     

No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

Motion trajectory prediction model of hydrogen leak and diffusion in a stable thermally-stratified environment

The motion trajectory of hydrogen leakage is an essential safe issue for the application of hydrogen energy. A dimensionless fast-running motion trajectory prediction model is proposed to predict the dispersion characteristics of the buoyant jet of hydrogen leakage for the accident. The impact of different leakage angles, leakage velocity and thermal stratification of ambient air on hydrogen leakage behavior was analyzed. The new developed model was verified by experimental results in literatures. Leakage hydrogen can flow upwards freely in a uniform environment. However, it shows an oscillating trajectory at a certain height in a thermally stratified environment, which is so called “locking phenomenon”. The trajectory of hydrogen leakage is upward and hydrogen gathers at the top of the space to form stratification in a uniform environment, while the hydrogen leakage shows an oscillating trajectory at a certain height in a thermal stratification environment. With the increase of Froude number Fr, it shows that the stable height and maximum height of the leakage airflow have a trend of rising first and then falling in a thermally stratified environment. The findings are expected to give guidance in real-world situations, for example, a larger Fr value and a larger temperature gradient can lead to a decrease in the stable height in the thermally stratified environment. It is found that the fitting of the stable height with different temperature gradients satisfies the power function relationship. This work is expected to be helpful for reducing hydrogen leakage accumulation and explosion risk.     

Ion migration behavior and its interaction with sintering environment in cation conductor during flash sintering

Flash sintering has been reported in various ceramics. Nevertheless, anion and cation conductors exhibit different flash-sintering behaviors, and the interaction mechanism between the conductive species and the sintering environment has remained unclear. Herein, we report the flash-sintering phenomena of a typical cation conductor, Na₃Zr₂(SiO₄)₂(PO₄) with anode region surrounded by air and NaNO₃ environments. The results prove that the ionic behavior and joule heating distribution can be controlled by changing the electrode environment. Four possible scenarios describing the ion migration behavior and interaction with the environment are proposed for providing a guidance for controlling the ion interaction behavior during flash sintering.     

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

Prediction of mode I fracture toughness (K_IC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression (LMR) and gene expression programming (GEP) methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and elastic modulus (E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets. Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of K_IC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were utilized herein. In the case of testing datasets, the values of R², RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156, respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R² value and lower errors.