Thermal Conductivity of Carbon Nanotubes and their Polymer Nanocomposites: A Review

Thermally conductive polymer composites offer new possibilities for replacing metal parts in several applications, including power electronics, electric motors and generators, heat exchangers, etc., thanks to the polymer advantages such as light weight, corrosion resistance and ease of processing. Current interest to improve the thermal conductivity of polymers is focused on the selective addition of nanofillers with high thermal conductivity. Unusually high thermal conductivity makes carbon nanotube (CNT) the best promising candidate material for thermally conductive composites. However, the thermal conductivities of polymer/CNT nanocomposites are relatively low compared with expectations from the intrinsic thermal conductivity of CNTs. The challenge primarily comes from the large interfacial thermal resistance between the CNT and the surrounding polymer matrix, which hinders the transfer of phonon dominating heat conduction in polymer and CNT. This article reviews the status of worldwide research in the thermal conductivity of CNTs and their polymer nanocomposites. The dependence of thermal conductivity of nanotubes on the atomic structure, the tube size, the morphology, the defect and the purification is reviewed. The roles of particle/polymer and particle/particle interfaces on the thermal conductivity of polymer/CNT nanocomposites are discussed in detail, as well as the relationship between the thermal conductivity and the micro- and nano-structure of the composite

Paternity analysis of pollen-mediated gene flow for Fraxinus excelsior L. in a chronically fragmented landscape

Paternity analysis based on microsatellite marker genotyping was used to infer contemporary genetic connectivity by pollen of three population remnants of the wind-pollinated, wind-dispersed tree Fraxinus excelsior, in a deforested Scottish landscape. By deterministically accounting for genotyping error and comparing a range of assignment methods, individual-based paternity assignments were used to derive population-level estimates of gene flow. Pollen immigration into a 300ha landscape represents between 43% and 68% of effective pollination, mostly depending on assignment method. Individual male reproductive success is unequal, with 31 of 48 trees fertilising one seed or more, but only three trees fertilising more than ten seeds. Spatial analysis suggests a fat-tailed pollen dispersal curve with 85% of detected pollination occurring within 100m, and 15% spreading between 300m and 1900m from the source. Identification of immigrating pollen sourced from two neighbouring remnants indicates further effective dispersal at 2900m. Pollen exchange among remnants is driven by population size rather than geographic distance, with larger remnants acting predominantly as pollen donors, and smaller remnants as pollen recipients. Enhanced wind dispersal of pollen in a barren landscape ensures that the seed produced within the catchment includes genetic material from a wide geographic area. However, gene flow estimates based on analysis of non-dispersed seeds were shown to underestimate realised gene immigration into the remnants by a factor of two suggesting that predictive landscape conservation requires integrated estimates of post-recruitment gene flow occurring via both pollen and seed

A Very Large Number of GABAergic Neurons Are Activated in the Tuberal Hypothalamus during Paradoxical (REM) Sleep Hypersomnia

We recently discovered, using Fos immunostaining, that the tuberal and mammillary hypothalamus contain a massive population of neurons specifically activated during paradoxical sleep (PS) hypersomnia. We further showed that some of the activated neurons of the tuberal hypothalamus express the melanin concentrating hormone (MCH) neuropeptide and that icv injection of MCH induces a strong increase in PS quantity. However, the chemical nature of the majority of the neurons activated during PS had not been characterized. To determine whether these neurons are GABAergic, we combined in situ hybridization of GAD67 mRNA with immunohistochemical detection of Fos in control, PS deprived and PS hypersomniac rats. We found that 74% of the very large population of Fos-labeled neurons located in the tuberal hypothalamus after PS hypersomnia were GAD-positive. We further demonstrated combining MCH immunohistochemistry and GAD67 in situ hybridization that 85% of the MCH neurons were also GAD-positive. Finally, based on the number of Fos-ir/GAD+, Fos-ir/MCH+, and GAD+/MCH+ double-labeled neurons counted from three sets of double-staining, we uncovered that around 80% of the large number of the Fos-ir/GAD+ neurons located in the tuberal hypothalamus after PS hypersomnia do not contain MCH. Based on these and previous results, we propose that the non-MCH Fos/GABAergic neuronal population could be involved in PS induction and maintenance while the Fos/MCH/GABAergic neurons could be involved in the homeostatic regulation of PS. Further investigations will be needed to corroborate this original hypothesis

Dynamic multi-objective optimisation using deep reinforcement learning::benchmark, algorithm and an application to identify vulnerable zones based on water quality

Dynamic multi-objective optimisation problem (DMOP) has brought a great challenge to the reinforcement learning (RL) research area due to its dynamic nature such as objective functions, constraints and problem parameters that may change over time. This study aims to identify the lacking in the existing benchmarks for multi-objective optimisation for the dynamic environment in the RL settings. Hence, a dynamic multi-objective testbed has been created which is a modified version of the conventional deep-sea treasure (DST) hunt testbed. This modified testbed fulfils the changing aspects of the dynamic environment in terms of the characteristics where the changes occur based on time. To the authors’ knowledge, this is the first dynamic multi-objective testbed for RL research, especially for deep reinforcement learning. In addition to that, a generic algorithm is proposed to solve the multi-objective optimisation problem in a dynamic constrained environment that maintains equilibrium by mapping different objectives simultaneously to provide the most compromised solution that closed to the true Pareto front (PF). As a proof of concept, the developed algorithm has been implemented to build an expert system for a real-world scenario using Markov decision process to identify the vulnerable zones based on water quality resilience in São Paulo, Brazil. The outcome of the implementation reveals that the proposed parity-Q deep Q network (PQDQN) algorithm is an efficient way to optimise the decision in a dynamic environment. Moreover, the result shows PQDQN algorithm performs better compared to the other state-of-the-art solutions both in the simulated and the real-world scenario

Genetic Ancestry, Race, and Severity of Acutely Decompensated Cirrhosis in Latin America

Background & Aims: Genetic ancestry or racial differences in health outcomes exist in diseases associated with systemic inflammation (eg, COVID-19). This study aimed to investigate the association of genetic ancestry and race with acute-on-chronic liver failure (ACLF), which is characterized by acute systemic inflammation, multi-organ failure, and high risk of short-term death. / Methods: This prospective cohort study analyzed a comprehensive set of data, including genetic ancestry and race among several others, in 1274 patients with acutely decompensated cirrhosis who were nonelectively admitted to 44 hospitals from 7 Latin American countries. / Results: Three hundred ninety-five patients (31.0%) had ACLF of any grade at enrollment. Patients with ACLF had a higher median percentage of Native American genetic ancestry and lower median percentage of European ancestry than patients without ACLF (22.6% vs 12.9% and 53.4% vs 59.6%, respectively). The median percentage of African genetic ancestry was low among patients with ACLF and among those without ACLF. In terms of race, a higher percentage of patients with ACLF than patients without ACLF were Native American and a lower percentage of patients with ACLF than patients without ACLF were European American or African American. In multivariable analyses that adjusted for differences in sociodemographic and clinical characteristics, the odds ratio for ACLF at enrollment was 1.08 (95% CI, 1.03–1.13) with Native American genetic ancestry and 2.57 (95% CI, 1.84–3.58) for Native American race vs European American race. / Conclusions: In a large cohort of Latin American patients with acutely decompensated cirrhosis, increasing percentages of Native American ancestry and Native American race were factors independently associated with ACLF at enrollment

Preclinical evidence implicating corticotropin-releasing factor signaling in ethanol consumption and neuroadaptation

The results of many studies support the influence of the corticotropin-releasing factor (CRF) system on ethanol (EtOH) consumption and EtOH-induced neuroadaptations that are critical in the addiction process. This review summarizes the preclinical data in this area after first providing an overview of the components of the CRF system. This complex system involves hypothalamic and extra-hypothalamic mechanisms that play a role in the central and peripheral consequences of stressors, including EtOH and other drugs of abuse. In addition, several endogenous ligands and targets make up this system and show differences in their involvement in EtOH drinking and in the effects of chronic or repeated EtOH treatment. In general, genetic and pharmacological approaches paint a consistent picture of the importance of CRF signaling via type 1 CRF receptors (CRF1) in EtOH-induced neuroadaptations that result in higher levels of intake, encourage alcohol seeking during abstinence and alter EtOH sensitivity. Furthermore, genetic findings in rodents, non-human primates and humans have provided some evidence of associations of genetic polymorphisms in CRF-related genes with EtOH drinking, although additional data are needed. These results suggest that CRF1 antagonists have potential as pharmacotherapeutics for alcohol use disorders. However, given the broad and important role of these receptors in adaptation to environmental and other challenges, full antagonist effects may be too profound and consideration should be given to treatments with modulatory effects.The authors were supported by the Department of Veterans Affairs; NIH NIAAA grants P60AA010760, R24AA020245 and U01AA013519 and NIH NIDA grant P50DA018165, during the writing of this manuscript. The authors have no financial conflict of interest to disclose

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Transformative Effects of IoT, Blockchain and Artificial Intelligence on Cloud Computing: Evolution, Vision, Trends and Open Challenges

Cloud computing plays a critical role in modern society and enables a range of applications from infrastructure to social media. Such system must cope with varying load and evolving usage reflecting societies’ interaction and dependency on automated computing systems whilst satisfying Quality of Service (QoS) guarantees. Enabling these systems are a cohort of conceptual technologies, synthesised to meet demand of evolving computing applications. In order to understand current and future challenges of such system, there is a need to identify key technologies enabling future applications. In this study, we aim to explore how three emerging paradigms (Blockchain, IoT and Artificial Intelligence) will influence future cloud computing systems. Further, we identify several technologies driving these paradigms and invite international experts to discuss the current status and future directions of cloud computing. Finally, we proposed a conceptual model for cloud futurology to explore the influence of emerging paradigms and technologies on evolution of cloud computing