Smoke in the river: an AEROCLO-sA case study

The formation of a river of smoke crossing southern Africa is investigated during the Aerosols, Radiation and Clouds in southern Africa (AEROCLO-sA) campaign in September 2017. A complementary set of global and mesoscale numerical simulations as well as ground-based, airborne and space-borne observations of the dynamics, thermodynamics and composition of the atmosphere are used to characterize the river of smoke in terms of timing and vertical extent of the biomass burning aerosol (BBA) layer. The study area was under the synoptic influence of a coastal low rooted in a tropical easterly wave, a high-pressure system over the continent and westerly waves in mid-latitudes, one of which had an embedded cut-off low (CoL). The coastal low interacted with the second of two approaching westerly waves and ultimately formed a mid-level temperate tropical trough (TTT). The TTT created the fast moving air mass transported to the southwestern Indian Ocean as a river of smoke. The CoL, which developed and intensified in the upper levels associated with the first (easternmost) westerly wave, remained stationary above northern Namibia prior to the formation of the TTT and was responsible for the thickening of the BBA layer. This shows that the evolution of the river of smoke is very much tied to the evolution of the TTT while its vertical extent is related to the presence of the CoL. The mechanisms by which the CoL, observed over Namibia in the entrance region of the river of smoke, influences the vertical structure of the BBA layer is mainly associated with the ascending motion above the BBA layer. In the presence of the CoL, the top of the BBA layer over northern Namibia reaches altitudes above 8 km. This is much higher than the average height of the top of the BBA layer over the regions where the smoke comes from (Angola, Zambia, Zimbabwe, Mozambique) which is 5 to 6 km. The results suggest that the interaction between the TTTs and the CoLs which form during the winter may have a role in promoting the transport of BBA from fire-prone regions in the tropical band to the temperate mid-latitudes and southwestern Indian Ocean.

The Identification of Cu–O–C Bond in Cu/MWCNTs Hybrid Nanocomposite by XPS and NEXAFS Spectroscopy

The results of the research of a composite based on multi-walled carbon nanotubes (MWCNTs) decorated with CuO/Cu2O/Cu nanoparticles deposited by the cupric formate pyrolysis are discussed. The study used a complementary set of methods, including scanning and transmission electron microscopy, X-ray diffractometry, Raman, and ultrasoft X-ray spectroscopy. The investigation results show the good adhesion between the copper nanoparticles coating and the MWCNT surface through the oxygen atom bridge formation between the carbon atoms of the MWCNT outer graphene layer and the oxygen atoms of CuO and Cu2O oxides. The formation of the Cu–O–C bond between the coating layer and the outer nanotube surface is clearly confirmed by the results of the O 1s near edge X-ray absorption fine structure (NEXAFS) and X-ray photoelectron spectroscopy (XPS) of the Cu/MWCNTs nanocomposite. The XPS measurements were performed using a laboratory spectrometer with sample charge compensation, and the NEXAFS studies were carried out using the synchrotron radiation of the Russian–German dipole beamline at BESSY-II (Berlin, Germany) and the NanoPES station at the Kurchatov Center for Synchrotron Radiation and Nanotechnology (Moscow, Russia).

Mechanical adaptation of brachiopod shells via hydration-induced structural changes

The function-optimized properties of biominerals arise from the hierarchical organization of primary building blocks. Alteration of properties in response to environmental stresses generally involves time-intensive processes of resorption and reprecipitation of mineral in the underlying organic scaffold. Here, we report that the load-bearing shells of the brachiopod Discinisca tenuis are an exception to this process. These shells can dynamically modulate their mechanical properties in response to a change in environment, switching from hard and stiff when dry to malleable when hydrated within minutes. Using ptychographic X-ray tomography, electron microscopy and spectroscopy, we describe their hierarchical structure and composition as a function of hydration to understand the structural motifs that generate this adaptability. Key is a complementary set of structural modifications, starting with the swelling of an organic matrix on the micron level via nanocrystal reorganization and ending in an intercalation process on the molecular level in response to hydration.

A Critical Review of Alien Limb-Related Phenomena and Implications for Functional Magnetic Resonance Imaging Studies

Consensus criteria on corticobasal degeneration (CBD) include alien limb (AL) phenomena. However, the gist of the behavioral features of AL is still “a matter of debate.” CBD-related AL has so far included the description of involuntary movements, frontal release phenomena (frontal AL), or asomatognosia (posterior or “real” AL). In this context, the most frequent symptoms are language and praxis deficits and cortical sensory misperception. However, asomatognosia requires, by definition, intact perception and cognition. Thus, to make a proper diagnosis of AL in the context of CBD, cognitive and language dysfunctions must be carefully verified and objectively assessed. We reviewed the current literature on AL in CBD and now propose that the generic use of the term AL should be avoided. This catchall AL term should instead be deconstructed. We propose that the term AL is appropriate to describe clinical features associated with specific brain lesions. More discrete sets of regionally bound clinical signs that depend on dysfunctions of specific brain areas need to be assessed and presented when posing the diagnosis. Thus, in our opinion, the AL term should be employed in association with precise descriptions of the accompanying involuntary movements, sensory misperceptions, agnosia-asomatognosia contents, and the presence of utilization behavior. The review also offers an overview of functional magnetic resonance imaging-based studies evaluating AL-related phenomena. In addition, we provide a complementary set of video clips depicting CBD-related involuntary movements that should not mistakenly be interpreted as signs of AL.

Interdisciplinary Models and Frameworks for the Study of Artificial Social Intelligence

This symposium provides a complementary set of papers exploring frameworks and models for developing artificial social intelligence (ASI) for teams. ASI consists of components of social cognition that support teamwork and more general interpersonal interactions. Although AI is rapidly evolving and fielded in a variety of operational settings, the implementation of such systems is vastly outpacing our ability to understand how to design and develop technologies appropriately. This symposium is meant to help redress this gap. Consisting of scholars representing the cognitive, computational, and organizational sciences, the papers discuss how they integrate theory and methods to inform development of agents capable of complex collaborative processes. Collectively, these papers synthesize perspectives across disciplines in support of an interdisciplinary research approach for ASL The goal is to contribute to research and development in the area of Human- AI- Robot Teaming effectiveness.

A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets

Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have advanced rapidly in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been adequately explored. Here we deployed an NLP framework to objectively quantify associations between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type terms across over 26 million biomedical documents. The resultant gene-cell type associations (GCAs) are significantly stronger between a curated set of matched cell type-marker pairs than the complementary set of mismatched pairs (Mann Whitney p = 6.15 × 10−76, r = 0.24; cohen’s D = 2.6). Building on this, we developed an augmented annotation algorithm (single cell Annotation via Literature Encoding, or scALE) that leverages GCAs to categorize cell clusters identified in scRNA-seq datasets, and we tested its ability to predict the cellular identity of 133 clusters from nine datasets of human breast, colon, heart, joint, ovary, prostate, skin, and small intestine tissues. With the optimized settings, the true cellular identity matched the top prediction in 59% of tested clusters and was present among the top five predictions for 91% of clusters. scALE slightly outperformed an existing method for reference data driven automated cluster annotation, and we demonstrate that integration of scALE can meaningfully improve the annotations derived from such methods. Further, contextualization of differential expression analyses with these GCAs highlights poorly characterized markers of well-studied cell types, such as CLIC6 and DNASE1L3 in retinal pigment epithelial cells and endothelial cells, respectively. Taken together, this study illustrates for the first time how the systematic application of a literature-derived knowledge graph can expedite and enhance the annotation and interpretation of scRNA-seq data.

A Shape Optimization Problem on Planar Sets with Prescribed Topology

We consider shape optimization problems involving functionals depending on perimeter, torsional rigidity and Lebesgue measure. The scaling free cost functionals are of the form $$P(\Omega )T^q(\Omega )|\Omega |^{-2q-1/2}$$ P ( Ω ) T q ( Ω ) | Ω | - 2 q - 1 / 2 , and the class of admissible domains consists of two-dimensional open sets $$\Omega $$ Ω satisfying the topological constraints of having a prescribed number k of bounded connected components of the complementary set. A relaxed procedure is needed to have a well-posed problem, and we show that when $$q<1/2$$ q < 1 / 2 an optimal relaxed domain exists. When $$q>1/2$$ q > 1 / 2 , the problem is ill-posed, and for $$q=1/2$$ q = 1 / 2 , the explicit value of the infimum is provided in the cases $$k=0$$ k = 0 and $$k=1$$ k = 1 .

Complementary Contribution of Fungi and Bacteria to Lignocellulose Digestion in the Food Stored by a Neotropical Higher Termite

Lignocellulose digestion in termites is achieved through the functional synergy between gut symbionts and host enzymes. However, some species have evolved additional associations with nest microorganisms that collaborate in the decomposition of plant biomass. In a previous study, we determined that plant material packed with feces inside the nests of Cornitermes cumulans (Syntermitinae) harbors a distinct microbial assemblage. These food nodules also showed a high hemicellulolytic activity, possibly acting as an external place for complementary lignocellulose digestion. In this study, we used a combination of ITS sequence analysis, metagenomics, and metatranscriptomics to investigate the presence and differential expression of genes coding for carbohydrate-active enzymes (CAZy) in the food nodules and the gut of workers and soldiers. Our results confirm that food nodules express a distinct set of CAZy genes suggesting that stored plant material is initially decomposed by enzymes that target the lignin and complex polysaccharides from fungi and bacteria before the passage through the gut, where it is further targeted by a complementary set of cellulases, xylanases, and esterases produced by the gut microbiota and the termite host. We also showed that the expression of CAZy transcripts associated to endoglucanases and xylanases was higher in the gut of termites than in the food nodules. An additional finding in this study was the presence of fungi in the termite gut that expressed CAZy genes. This study highlights the importance of externalization of digestion by nest microbes and provides new evidence of complementary digestion in the context of higher termite evolution.

Fermentation of Biodegradable Organic Waste by the Family Thermotogaceae

The abundance of organic waste generated from agro-industrial processes throughout the world has become an environmental concern that requires immediate action in order to make the global economy sustainable and circular. Great attention has been paid to convert such nutrient-rich organic waste into useful materials for sustainable agricultural practices. Instead of being an environmental hazard, biodegradable organic waste represents a promising resource for the production of high value-added products such as bioenergy, biofertilizers, and biopolymers. The ability of some hyperthermophilic bacteria, e.g., the genera Thermotoga and Pseudothermotoga, to anaerobically ferment waste with the concomitant formation of bioproducts has generated great interest in the waste management sector. These biotechnologically significant bacteria possess a complementary set of thermostable enzymes to degrade complex sugars, with high production rates of biohydrogen gas and organic molecules such as acetate and lactate. Their high growth temperatures allow not only lower contamination risks but also improve substrate solubilization. This review highlights the promises and challenges related to using Thermotoga and Pseudothermotoga spp. as sustainable systems to convert a wide range of biodegradable organic waste into high value-added products.

A literature-derived knowledge graph augments the interpretation of single cell RNA-seq datasets

Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have rapidly advanced in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been adequately explored. Here we deployed an NLP framework to objectively quantify associations between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type terms across over 26 million biomedical documents. The resultant gene-cell type associations (GCAs) are significantly stronger between a curated set of matched cell type-marker pairs than the complementary set of mismatched pairs (Mann Whitney p < 6.15x10-76, r = 0.24; Cohens D = 2.6). Building on this, we developed an augmented annotation algorithm that leverages GCAs to categorize cell clusters identified in scRNA-seq datasets, and we tested its ability to predict the cellular identity of 185 clusters in 13 datasets from human blood, pancreas, lung, liver, kidney, retina, and placenta. With the optimized settings, the true cellular identity matched the top prediction in 66% of tested clusters and was present among the top five predictions for 94% of clusters. Further, contextualization of differential expression analyses with these GCAs highlights poorly characterized markers of established cell types, such as CLIC6 and DNASE1L3 in retinal pigment epithelial cells and endothelial cells, respectively. Taken together, this study illustrates for the first time how the systematic application of a literature derived knowledge graph can expedite and enhance the annotation and interpretation of scRNA-seq data.