Applying Theories of Particle Packing and Rheology to Concrete for Sustainable Development

Concrete is one of the most important construction materials. However, it is not so compatible with the demands of sustainable development because manufacturing of cement generates a large amount of carbon dioxide and therefore cement consumption produces a huge carbon footprint. Currently, the cement consumption is generally lowered by adding supplementary cementitious materials to replace part of the cement. Nonetheless, in order to maintain performance, there is a limit to such cement replacement by supplementary cementitious materials. To further reduce the cement consumption, the total cementitious materials content has to be reduced. This requires the packing density of the aggregate particles to be maximized so that the amount of voids in the bulk volume of aggregate to be filled with cement paste could be minimized and the surface area of the aggregate particles to be minimized so that the amount of cement paste needed to form paste films coating the surfaces of aggregate particle for rheological performance could be minimized. Such optimization is not straightforward and modern concrete science based on particuology is needed. Herein, a number of new theories regarding particle packing and rheology of concrete, which are transforming conventional concrete technology into modern concrete science, are presented. These theories would help to develop a more scientific and systematic concrete mix design method for the production of high-performance concrete with minimum cement consumption

The Effect of Social Fathers on the Cognitive Skills of Out-of-Wedlock Children

There are two competing views regarding the presence of social fathers on childrens’ cognitive ability: either the social father provides more financial need to the children or the mother with new partners may shift the focus away from the children. Previous research focused more on such effect on older children or adolescents and ignored the self-selection problem. We use data from the Fragile Families and Child Wellbeing Study (FFCWS), and a sample of younger children. Assuming that self-selection is based on observables and using ordinary least square, propensity score matching method (nonparametric methods), we find that children with social fathers scored around three points less in a cognitive ability test than children living only with biological mothers. The result remains the same when using a control-function analysis (parametric)

Predation Due to Bargaining Power Difference in Financial Contracting

Previous literature presented a predation model based on agency problems in financial contracting. In that model, predation reduced prey’s cash flow through breaking the relationship between the prey and its investors as the prey is financially constrained. This paper presents a different model in which both the predator and the prey are financially constrained and in need of external funding. The only dissimilarity between the predator and the prey is their corresponding level of bargaining power in financial contracting over their respective investors. The asymmetry of bargaining power is the unique source of predatory behavior. Financial contract between firm with less bargaining power (prey) and its investor can deter predation if the predator cannot renegotiate the contract with its own investor. If renegotiation is available for the predator, no financial contract can successfully deter predation

Semi-supervised Domain Adaptation on Graphs with Contrastive Learning and Minimax Entropy

Label scarcity in a graph is frequently encountered in real-world applications due to the high cost of data labeling. To this end, semi-supervised domain adaptation (SSDA) on graphs aims to leverage the knowledge of a labeled source graph to aid in node classification on a target graph with limited labels. SSDA tasks need to overcome the domain gap between the source and target graphs. However, to date, this challenging research problem has yet to be formally considered by the existing approaches designed for cross-graph node classification. To tackle the SSDA problem on graphs, a novel method called SemiGCL is proposed, which benefits from graph contrastive learning and minimax entropy training. SemiGCL generates informative node representations by contrasting the representations learned from a graph's local and global views. Additionally, SemiGCL is adversarially optimized with the entropy loss of unlabeled target nodes to reduce domain divergence. Experimental results on benchmark datasets demonstrate that SemiGCL outperforms the state-of-the-art baselines on the SSDA tasks

Cigarette Smoke-Induced Cerebral Cortical Interleukin-6 Elevation is not Mediated Through Oxidative Stress

The author group has previously established an in vivo subchronic cigarette smoke (CS) exposure rat model, in which the systemic oxidative burden as well as the modulation of local anti-oxidative enzymes in the lung has been demonstrated. Oxidative stress has been shown to induce pro-inflammatory cytokine release, including interleukin (IL)-6 in the airways. In this study, we aimed to investigate the changes in IL-6 production, as well as the oxidative/anti-oxidative responses in the cerebral cortex using the same in vivo model. IL-6 was determined by RT-PCR and western-blot analysis. Local oxidative and anti-oxidative responses were determined by measuring cerebral cortical malondialdehyde (MDA) and advanced oxidation protein product (AOPP) levels, superoxide dismutase (SOD) and catalase activities, and the reduced to oxidized glutathione (GSH/GSSG) ratio. Nitrite level was measured by fluorescent spectrophotometry. Our results demonstrated a significant increase in both IL-6 mRNA and protein levels. Reductions of SOD activity and manganese (Mn)SOD protein level were observed together with the increased level of superoxide measured by chemiluminescent signal, after 56 days of CS exposure. There were no significant changes in the cerebral cortical levels of MDA, AOPP, catalase activity, and the GSH/GSSG ratio. Nitrite level was significantly reduced, together with the decreased protein level of nNOS in the cerebral cortex, after 56 days of CS exposure. Our results suggest that exposure to CS induces IL-6 expression in the cerebral cortex, which is not mediated by the oxidative/anti-oxidative imbalance

A R&D Based Real Business Cycle Model

The New Keynesian Real Business Cycle model with staggered price adjustment is augmented with a R&D producing sector. Two sources of economic shocks are considered, namely random paritcipation (perturbances to value of alternative investment opportunities in another sector) and financial intermediation (shocks to the cost of raising capital in the financial intermediation market). We find that, when comparing to the baseline model, both models can explain pro-cyclical R&D spending. Additionally, the investment oversensitivity problem is corrected. However, only the financial intermediation model is consistent with the observed finding that volatility of R&D is larger than that of investment and output

The Conditional CAPM, Cross-Section Returns and Stochastic Volatility

Bansal and Yaron (2004) demonstrate, by calibration, that the Consumption-Based Capital Asset Pricing Model (CCAPM) can be rescued by assuming that consumption growth rate follows a stochastic volatility model. They show that the conditional equity premium is a linear function of conditional consumption and market return volatilities, which can be estimated handily by various Generalized Autoregressive Conditonal Heterskedasticity (GARCH) and Stochastic Volatility (SV) models.We find that conditional consumption and market volatilities are capable of explaining cross-sectional return differences. The Exponential GARCH (EGARCH) volatility can explain up to 55% variation of return and the EGARCH model augmented with (cay) ̂ -a cointegrating factor of consumption, labor income and asset wealth growth- greatly enhance model performance. We proceed to test another hypothesis: if Bansal and Yaron estimator is an unbiased estimator of true conditional equity premium, then the instrumental variables for estimating conditional equity premium should no longer be significant.We demonstrate that once the theoretical conditional risk premium is added to the model, it renders all instrumental variables redundant. Also, the model prediction is consistent with observed declining equity premium

Thermal comfort and energy performance of public rental housing under typical and near-extreme weather conditions in Hong Kong

© 2017 Elsevier B.V. Building performance evaluation is crucial for sustainable urban developments. In high-density cities, occupants suffer from poor living conditions due to building overheating, especially during increasingly frequent near-extreme summer conditions caused by climate change. To represent this situation, the summer reference year weather data was employed for building simulations using DesignBuilder. This study aims to evaluate the thermal comfort and energy consumption of four typical public rental housing (PRH) building types in Hong Kong. For free-running flats, results show generally higher air temperatures in the oldest PRH type (Slab) with a compact linear building form and the most sensitive response to outdoor temperature changes for another older PRH type (Trident) with a Y-shaped design, possibly owing to its high wall conductivity. Occupants in all building types experience a ???10% increase in the proportion of discomfort hours when compared to results for typical summer conditions, but overheating is the most severe in Slab type PRH. Following an initial assessment of the cooling energy usage, a simple sensitivity test was conducted to explore the potential energy savings by various passive design strategies, including shading and reducing the exposed cooled space. A cross-shaped building form also appears to be more energy efficient. These findings, complemented by further parametric analyses, may prove useful when designing buildings for climate change