Abstract: In the last decade, the highest levels of greenhouse gases (GHG) in the atmosphere have been recorded, with carbon dioxide (CO2) being one of the GHGs that most concerns mankind due to the rate at which it is generated on the planet. Given its long time of permanence in the atmosphere (between 100 to 150 years); this has deployed research in the scientific field focused on the absorption and desorption of CO2 in the atmosphere. This work presents the study of CO2 adsorption employing
materials based on graphene oxide (GO), such as GO foams with different oxidation percentages (3.00%, 5.25%, and 9.00%) in their structure, obtained via an environmentally friendly method. The characterization of CO2 adsorption was carried out in a closed system, within which were placed the GO foams and other CO2 adsorbent materials (zeolite and silica gel). Through a controlled chemical reaction, production of CO2 was conducted to obtain CO2 concentration curves inside the system and calculate from these the efficiency, obtained between 86.28 and 92.20%, yield between 60.10 and 99.50%, and effectiveness of CO2 adsorption of the materials under study. The results obtained suggest that GO foams are a promising material for carbon capture and the future development of a new clean technology, given their highest CO2 adsorption efficiency and yield.

Abstract: This paper investigates the hemp limecrete mechanical and microstructural performance of a new sustainable and environmental friendly building material. Several studies have investigated the hemp limecrete focusing on the non-structural applications. The newly developed hemp limecrete consists of high mechanical and microstructural properties. The specimens were prepared with varying lengths and proportions of hemp fibers with lime and tested for compressive strength, flexural strength, thermal conductivity and microstructural analysis like SEM and EDS. The study found that the optimal fiber content for making mortars was between 2 and 4%. This conclusion was reached after analyzing the influence of fiber length and ratio on the properties of the mortars. The dry unit weight decreased when the fiber content was higher than 4%. In terms of strength, the study found that the flexural strength of the hemp limecrete improved with an increase in fiber ratio, but the compressive strength decreased. However, with 2% hemp fiber, compressive strengths of 3.48 MPa and above were obtained. The study also highlighted the good thermal insulation properties and dimensional stability of hemp limecrete. These findings have important implications for the use of hemp limecrete as a sustainable building material. The results suggest that hemp limecrete has the potential to be a viable alternative to conventional concrete in specific applications, particularly in areas where environmental sustainability is a priority.

Abstract: We explore the data-parallel acceleration of physics-informed machine learning (PIML) schemes, with a focus on physics-informed neural networks (PINNs) for multiple graphics processing units (GPUs) architectures. In order to develop scale-robust and high-throughput PIML models for sophisticated applications which may require a large number of training points (e.g., involving complex and high-dimensional domains, non-linear operators or multi-physics), we detail a novel protocol based on h-analysis and data-parallel acceleration through the Horovod training framework. The protocol is backed by new convergence bounds for the generalization error and the train-test gap. We show that the acceleration is straightforward to implement, does not compromise training, and proves to be highly efficient and controllable, paving the way towards generic scale-robust PIML. Extensive numerical experiments with increasing complexity illustrate its robustness and consistency, offering a wide range of possibilities for real-world simulations.

Abstract: We study the dynamics of three populations evolving in a two-dimensional discrete grid according to rules of attraction, rejection, or indifference following the framework of the seminal model by Sakoda and we apply it to migration phenomena. An interesting feature of the Sakoda model is the existence of a Potts-like energy which, as a common principle, decreases as time passes by. Here we consider the evolution of two populations until stabilization, then, we perturb this attractor by the inclusion of a third arrival: the immigrants. We show the conditions under which this irruption does not alter significantly the previous attractor (a sociological morphostatic behaviour) or it is dramatically changed (morphogenetic behaviour). We observe empirically that for a morphostatic behaviour the energy decreases while for morphogenesis this energy increases, revealing an escalation of social tension.

Abstract: Human interactions and perceptions about health risk are essential to understand the evolution over the course of a pandemic. We present a Susceptible-Exposed-Asymptomatic-Infectious-Recovered-Susceptible mathematical model with quarantine and social-distance-dependent transmission rates, to study COVID-19 dynamics. Human activities are split across different location settings: home, work, school, and elsewhere. Individuals move from home to the other locations at rates dependent on their epidemiological conditions and maintain a social distancing behavior, which varies with their location. We perform simulations and analyze how distinct social behaviors and restrictive measures affect the dynamic of the disease within a population. The model proposed in this study revealed that the main focus on the transmission of COVID-19 is attributed to the “home” location setting, which is understood as family gatherings including relatives and close friends. Limiting encounters at work, school and other locations will only be effective if COVID-19 restrictions occur simultaneously at all those locations and/or contact tracing or social distancing measures are effectively and strictly implemented, especially at the home setting.

Abstract: The exposure to environmental variations in pH and temperature has proven impacts on benthic ectotherms calcifiers, as evidenced by tradeoffs between physiological processes. However, how these stressors affect structure and functionality of mollusk shells has received less attention. Episodic events of upwelling of deep cold and low pH waters are well documented in eastern boundary systems and may be stressful to mollusks, impairing both physiological and biomechanical performance. These events are projected to become more intense, and extensive in time with ongoing global warming. In this study, we evaluate the independent and interactive effects of temperature and pH on the biomineral and biomechanical properties of Argopecten purpuratus scallop shells. Total organic matter in the shell mineral increased under reduced pH (similar to 7.7) and control conditions (pH similar to 8.0). The periostracum layer coating the outer shell surface showed increased protein content under low pH conditions but decreasing sulfate and polysaccharides content. Reduced pH negatively impacts shell density and increases the disorder in the orientation of calcite crystals. At elevated temperatures (18 degrees C), shell microhardness increased. Other biomechanical properties were not affected by pH/temperature treatments. Thus, under a reduction of 0.3 pH units and low temperature, the response of A. purpuratus was a tradeoff among organic compounds (biopolymer plasticity), density, and crystal organization (mineral plasticity) to maintain shell biomechanical performance, while increased temperature ameliorated the impacts on shell hardness. Biopolymer plasticity was associated with ecophysiological performance, indicating that, under the influence of natural fluctuations in pH and temperature, energetic constraints might be critical in modulating the long-term sustainability of this compensatory mechanism.

Abstract: We study a simple magnetic system composed of periodically modulated magnetic dipoles with an easy axis. Upon adjusting the geometric modulation amplitude alone, chains and two-dimensional stacked chains exhibit a rich magnon spectrum where frequency gaps and magnon speeds are easily manipulable. The blend of anisotropy due to dipolar interactions between magnets and geometrical modulation induces a magnetic phase with fractional Zak number in infinite chains and end states in open one-dimensional systems. In two dimensions it gives rise to topological modes at the edges of stripes. Tuning the amplitude in two-dimensional lattices causes a band touching, which triggers the exchange of the Chern numbers of the volume bands and switches the sign of the thermal conductivity.

Abstract: Glucokinase (GK), the hexokinase involved in glucosensing in pancreatic beta-cells, is also expressed in arcuate nucleus (AN) neurons and hypothalamic tanycytes, the cells that surround the basal third ventricle (3V). Several lines of evidence suggest that tanycytes may be involved in the regulation of energy homeostasis. Tanycytes have extended cell processes that contact the feeding-regulating neurons in the AN, particularly, agouti-related protein (AgRP), neuropeptide Y (NPY), cocaine-and amphetamine-regulated transcript (CART) and proopiomelanocortin (POMC) neurons. In this study, we developed an adenovirus expressing GK shRNA to inhibit GK expression in vivo. When injected into the 3V of rats, this adenovirus preferentially transduced tanycytes. qRT-PCR and Western blot assays confirmed GK mRNA and protein levels were lower in GK knockdown animals compared to the controls. In response to an intracerebroventricular glucose injection, the mRNA levels of anorexigenic POMC and CART and orexigenic AgRP and NPY neuropeptides were altered in GK knockdown animals. Similarly, food intake, meal duration, frequency of eating events and the cumulative eating time were increased, whereas the intervals between meals were decreased in GK knockdown rats, suggesting a decrease in satiety. Thus, GK expression in the ventricular cells appears to play an important role in feeding behavior.

Abstract: Soot emissions from flaming combustion are relevant as a significant source of atmospheric pollution and as a source of nanomaterials. Candles are interesting targets for soot characterization studies since they burn complex fuels with a large number of carbon atoms, and yield stable and repeatable flames. We characterized the soot particle size distributions in a candle flame using the planar two-color time-resolved laser induced incandescence (2D-2C TiRe-LII) technique, which has been successfully applied to different combustion applications, but never before on a candle flame. Soot particles are heated with a planar laser sheet to temperatures above the normal flame temperatures. The incandescent soot particles emit thermal radiation, which decays over time when the particles cool down to the flame temperature. By analyzing the temporal decay of the incandescence signal, soot particle size distributions within the flame are obtained. Our results are consistent with previous works, and show that the outer edges of the flame are characterized by larger particles (approximate to 60 nm), whereas smaller particles (approximate to 25 nm) are found in the central regions. We also show that our effective temperature estimates have a maximum error of 100 K at early times, which decreases as the particles cool.