Showing papers by "Karlsruhe Institute of Technology published in 2021"

Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges

Abstract: Recent advancements in perception for autonomous driving are driven by deep learning. In order to achieve robust and accurate scene understanding, autonomous vehicles are usually equipped with different sensors (e.g. cameras, LiDARs, Radars), and multiple sensing modalities can be fused to exploit their complementary properties. In this context, many methods have been proposed for deep multi-modal perception problems. However, there is no general guideline for network architecture design, and questions of “what to fuse”, “when to fuse”, and “how to fuse” remain open. This review paper attempts to systematically summarize methodologies and discuss challenges for deep multi-modal object detection and semantic segmentation in autonomous driving. To this end, we first provide an overview of on-board sensors on test vehicles, open datasets, and background information for object detection and semantic segmentation in autonomous driving research. We then summarize the fusion methodologies and discuss challenges and open questions. In the appendix, we provide tables that summarize topics and methods. We also provide an interactive online platform to navigate each reference: https://boschresearch.github.io/multimodalperception/ .

Review on Convolutional Neural Networks (CNN) in vegetation remote sensing

Abstract: Identifying and characterizing vascular plants in time and space is required in various disciplines, e.g. in forestry, conservation and agriculture. Remote sensing emerged as a key technology revealing both spatial and temporal vegetation patterns. Harnessing the ever growing streams of remote sensing data for the increasing demands on vegetation assessments and monitoring requires efficient, accurate and flexible methods for data analysis. In this respect, the use of deep learning methods is trend-setting, enabling high predictive accuracy, while learning the relevant data features independently in an end-to-end fashion. Very recently, a series of studies have demonstrated that the deep learning method of Convolutional Neural Networks (CNN) is very effective to represent spatial patterns enabling to extract a wide array of vegetation properties from remote sensing imagery. This review introduces the principles of CNN and distils why they are particularly suitable for vegetation remote sensing. The main part synthesizes current trends and developments, including considerations about spectral resolution, spatial grain, different sensors types, modes of reference data generation, sources of existing reference data, as well as CNN approaches and architectures. The literature review showed that CNN can be applied to various problems, including the detection of individual plants or the pixel-wise segmentation of vegetation classes, while numerous studies have evinced that CNN outperform shallow machine learning methods. Several studies suggest that the ability of CNN to exploit spatial patterns particularly facilitates the value of very high spatial resolution data. The modularity in the common deep learning frameworks allows a high flexibility for the adaptation of architectures, whereby especially multi-modal or multi-temporal applications can benefit. An increasing availability of techniques for visualizing features learned by CNNs will not only contribute to interpret but to learn from such models and improve our understanding of remotely sensed signals of vegetation. Although CNN has not been around for long, it seems obvious that they will usher in a new era of vegetation remote sensing.

A Brief History of OLEDs-Emitter Development and Industry Milestones.

Abstract: Organic light-emitting diodes (OLEDs) have come a long way ever since their first introduction in 1987 at Eastman Kodak. Today, OLEDs are especially valued in the display and lighting industry for their promising features. As one of the research fields that equally inspires and drives development in academia and industry, OLED device technology has continuously evolved over more than 30 years. OLED devices have come forward based on three generations of emitter materials relying on fluorescence (first generation), phosphorescence (second generation), and thermally activated delayed fluorescence (third generation). Furthermore, research in academia and industry toward the fourth generation of OLEDs is in progress. Excerpts from the history of green, orange-red, and blue OLED emitter development on the side of academia and milestones achieved by key players in the industry are included in this report.

Global land use changes are four times greater than previously estimated

Abstract: Quantifying the dynamics of land use change is critical in tackling global societal challenges such as food security, climate change, and biodiversity loss. Here we analyse the dynamics of global land use change at an unprecedented spatial resolution by combining multiple open data streams (remote sensing, reconstructions and statistics) to create the HIstoric Land Dynamics Assessment + (HILDA +). We estimate that land use change has affected almost a third (32%) of the global land area in just six decades (1960-2019) and, thus, is around four times greater in extent than previously estimated from long-term land change assessments. We also identify geographically diverging land use change processes, with afforestation and cropland abandonment in the Global North and deforestation and agricultural expansion in the South. Here, we show that observed phases of accelerating (~1960–2005) and decelerating (2006–2019) land use change can be explained by the effects of global trade on agricultural production. Quantifying land use change is critical in tackling global challenges related to food, climate and biodiversity. Here the authors show that land use change has affected 32 % of the global land area in six decades (1960- 2019) by combining multiple open datasets to create the HIstoric Land Dynamics Assessment +.

Challenges and Strategies for High-Energy Aqueous Electrolyte Rechargeable Batteries.

Abstract: Aqueous rechargeable batteries are becoming increasingly important to the development of renewable energy sources, because they promise to meet cost-efficiency, energy and power demands for stationary applications. Over the past decade, efforts have been devoted to the improvement of electrode materials and their use in combination with highly concentrated aqueous electrolytes. Here the latest ground-breaking advances in using such electrolytes to construct aqueous battery systems efficiently storing electrical energy, i.e., offering improved energy density, cyclability and safety, are highlighted. This Review aims to timely provide a summary of the strategies proposed so far to overcome the still existing hurdles limiting the present aqueous batteries technologies employing concentrated electrolytes. Emphasis is placed on aqueous batteries for lithium and post-lithium chemistries, with potentially improved energy density, resulting from the unique advantages of concentrated electrolytes.

A guide to the composition and functions of the extracellular matrix.

Abstract: Extracellular matrix (ECM) is a dynamic 3-dimensional network of macromolecules that provides structural support for the cells and tissues. Accumulated knowledge clearly demonstrated over the last decade that ECM plays key regulatory roles since it orchestrates cell signaling, functions, properties and morphology. Extracellularly secreted as well as cell-bound factors are among the major members of the ECM family. Proteins/glycoproteins, such as collagens, elastin, laminins and tenascins, proteoglycans and glycosaminoglycans, hyaluronan, and their cell receptors such as CD44 and integrins, responsible for cell adhesion, comprise a well-organized functional network with significant roles in health and disease. On the other hand, enzymes such as matrix metalloproteinases and specific glycosidases including heparanase and hyaluronidases contribute to matrix remodeling and affect human health. Several cell processes and functions, among them cell proliferation and survival, migration, differentiation, autophagy, angiogenesis, and immunity regulation are affected by certain matrix components. Structural alterations have been also well associated with disease progression. This guide on the composition and functions of the ECM gives a broad overview of the matrisome, the major ECM macromolecules, and their interaction networks within the ECM and with the cell surface, summarizes their main structural features and their roles in tissue organization and cell functions, and emphasizes the importance of specific ECM constituents in disease development and progression as well as the advances in molecular targeting of ECM to design new therapeutic strategies.

Averages of b-hadron, c-hadron, and $$\tau $$-lepton properties as of 2018: Heavy Flavor Averaging Group (HFLAV)

Abstract: This paper reports world averages of measurements of b -hadron, c -hadron, and -lepton properties obtained by the Heavy Flavour Averaging Group using results available through September 2018. In rare cases, significant results obtained several months later are also used. For the averaging, common input parameters used in the various analyses are adjusted (rescaled) to common values, and known correlations are taken into account. The averages include branching fractions, lifetimes, neutral meson mixing parameters, violation parameters, parameters of semileptonic decays, and Cabibbo–Kobayashi–Maskawa matrix elements.

High-entropy energy materials: challenges and new opportunities

Abstract: The essential demand for functional materials enabling the realization of new energy technologies has triggered tremendous efforts in scientific and industrial research in recent years. Recently, high-entropy materials, with their unique structural characteristics, tailorable chemical composition and correspondingly tunable functional properties, have drawn increasing interest in the fields of environmental science and renewable energy technology. Herein, we provide a comprehensive review of this new class of materials in the energy field. We begin with discussions on the latest reports on the applications of high-entropy materials, including alloys, oxides and other entropy-stabilized compounds and composites, in various energy storage and conversion systems. In addition, we describe effective strategies for rationally designing high-entropy materials from computational techniques and experimental aspects. Based on this overview, we subsequently present the fundamental insights and give a summary of their potential advantages and remaining challenges, which will ideally provide researchers with some general guides and principles for the investigation and development of advanced high-entropy materials.

IceCube-Gen2: the window to the extreme Universe

Abstract: The observation of electromagnetic radiation from radio to γ-ray wavelengths has provided a wealth of information about the Universe. However, at PeV (1015 eV) energies and above, most of the Universe is impenetrable to photons. New messengers, namely cosmic neutrinos, are needed to explore the most extreme environments of the Universe where black holes, neutron stars, and stellar explosions transform gravitational energy into non-thermal cosmic rays. These energetic particles havemillions of times higher energies than those produced in the most powerful particle accelerators on Earth. As neutrinos can escape from regions otherwise opaque to radiation, they allow an unique view deep into exploding stars and the vicinity of the event horizons of black holes. The discovery of cosmic neutrinos with IceCube has opened this new window on the Universe. IceCube has been successful in finding first evidence for cosmic particle acceleration in the jet of an active galactic nucleus. Yet, ultimately, its sensitivity is too limited to detect even the brightest neutrino sources with high significance, or to detect populations of less luminous sources. In thiswhite paper, we present an overview of a next-generation instrument, IceCube-Gen2, which will sharpen our understanding of the processes and environments that govern the Universe at the highest energies. IceCube-Gen2 is designed to: (a) Resolve the high-energy neutrino sky from TeV to EeV energies (b) Investigate cosmic particle acceleration through multi-messenger observations (c) Reveal the sources and propagation of the highest energy particles in the Universe (d) Probe fundamental physics with high-energy neutrinos IceCube-Gen2 will enhance the existing IceCube detector at the South Pole. It will increase the annual rate of observed cosmic neutrinos by a factor of ten compared to IceCube, and will be able to detect sources five times fainter than its predecessor. Furthermore, through the addition of a radio array, IceCube- Gen2 will extend the energy range by several orders of magnitude compared to IceCube. Construction will take 8 years and cost about $350M. The goal is to have IceCube-Gen2 fully operational by 2033. IceCube-Gen2 will play an essential role in shaping the new era of multimessenger astronomy, fundamentally advancing our knowledge of the highenergy Universe. This challenging mission can be fully addressed only through the combination of the information from the neutrino, electromagnetic, and gravitational wave emission of high-energy sources, in concert with the new survey instruments across the electromagnetic spectrum and gravitational wave detectors which will be available in the coming years.

IBM ILOG CPLEX Optimization Studio

Abstract: Dieses Kapitel liefert eine Einfuhrung in die grafische Entwicklungsumgebung (engl. Integrated Development Environment), welche die zentrale Komponente zur Modellentwicklung darstellt und im Folgenden auch als Studio (im engeren Sinne) bezeichnet wird. Es wird erlautert, wie CPLEX Optimization Studio auf einem Computer installiert und das Studio gestartet wird, welche grundlegenden Funktionalitaten und Teilkomponenten dort zur Verfugung stehen und wie man Projekte erstellt, Optimierungsmodelle hinzufugt und die eigentliche Optimierung durchfuhrt. Nach dem Studium dieses Kapitels sollte die Software insoweit beherrschbar sein, dass alle Beispiele, die im vorliegenden Buch beschrieben sind, importiert bzw.

Test of Lepton-Flavor Universality in B →k∗ℓ+ℓ- Decays at Belle

Abstract: We acknowledge support from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan, the Japan Society for the Promotion of Science (JSPS), and the Tau-Lepton Physics Research Center of Nagoya University; the Australian Research Council including Grants No. DP180102629, No. DP170102389, No. DP170102204, No. DP150103061, No. FT130100303; Austrian Science Fund (FWF); the National Natural Science Foundation of China under Contracts No. 11435013, No. 11475187, No. 11521505, No. 11575017, No. 11675166, No. 11705209; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS), Grant No. QYZDJ-SSWSLH011; the CAS Center for Excellence in Particle Physics (CCEPP); the Shanghai Pujiang Program under Grant No. 18PJ1401000; the Ministry of Education, Youth and Sports of the Czech Republic under Contract No. LTT17020; the Carl Zeiss Foundation, the Deutsche Forschungsgemeinschaft, the Excellence Cluster Universe, and the VolkswagenStiftung; the Department of Science and Technology of India; the Istituto Nazionale di Fisica Nucleare of Italy; National Research Foundation (NRF) of Korea Grants No. 2016R1D1A1B01010135, No. 2016R1D1A1B02012900, No. 2018R1A2B3003643, No. 2018R1A6A1A06024970, No. 2018R1D1A1B07047294, No. 2019K1A3A7A09033840, No. 2019R1I1A3A01058933; Radiation Science Research Institute, Foreign Large-size Research Facility Application Supporting project, the Global Science Experimental Data Hub Center of the Korea Institute of Science and Technology Information, and KREONET/GLORIAD the Polish Ministry of Science and Higher Education and the National Science Center; the Ministry of Science and Higher Education of the Russian Federation, Agreement No. 14.W03.31.0026; University of Tabuk research Grants No. S-1440-0321, No. S-0256-1438, and No. S-0280-1439 (Saudi Arabia); the Slovenian Research Agency; Ikerbasque, Basque Foundation for Science, Spain; the Swiss National Science Foundation; the Ministry of Education and the Ministry of Science and Technology of Taiwan; and the U.S. Department of Energy and the National Science Foundation.

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models

Abstract: Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project’s Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to −6% (SSP126) and from +1% to −24% (SSP585)—explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts consistently occurs earlier in the new projections—before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated. Climate change affects agricultural productivity. New systematic global agricultural yield projections of the major crops were conducted using ensembles of the latest generation of crop and climate models. Substantial shifts in global crop productivity due to climate change will occur within the next 20 years—several decades sooner than previous projections—highlighting the need for targeted food system adaptation and risk management in the coming decades.

Two birds with one stone: dual grain-boundary and interface passivation enables >22% efficient inverted methylammonium-free perovskite solar cells

Abstract: Advancing inverted (p–i–n) perovskite solar cells (PSCs) is key to further enhance the power conversion efficiency (PCE) and stability of flexible and perovskite-based tandem photovoltaics. Yet, the presence of defects at grain boundaries and in particular interfacial recombination at the perovskite/electron transporting layer interface induce severe non-radiative recombination losses, limiting the open-circuit voltage (VOC) and fill factor (FF) of PSCs in this architecture. In this work, we introduce a dual passivation strategy using the long chain alkylammonium salt phenethylammonium chloride (PEACl) both as an additive and for surface treatment to simultaneously passivate the grain boundaries and the perovskite/C60 interface. Using [2-(9H-carbazol-9-yl)ethyl]phosphonic acid (2PACz) as a hole transporting layer and a methylammonium (MA)-free Cs0.18FA0.82PbI3 perovskite absorber with a bandgap of ∼1.57 eV, prolonged charge carrier lifetime and an on average 63 meV enhanced internal quasi-Fermi level splitting are achieved upon dual passivation compared to reference p–i–n PSCs. Thereby, we achieve one of the highest PCEs for p–i–n PSCs of 22.7% (stabilized at 22.3%) by advancing simultaneously the VOC and FF up to 1.162 V and 83.2%, respectively. Using a variety of experimental techniques, we attribute the positive effects to the formation of a heterogeneous 2D Ruddlesden–Popper (PEA)2(Cs1−xFAx)n−1Pbn(I1−yCly)3n+1 phase at the grain boundaries and surface of the perovskite films. At the same time, the activation energy for ion migration is significantly increased, resulting in enhanced stability of the PSCs under light, humidity, and thermal stress. The presented dual passivation strategy highlights the importance of defect management both in the grain boundaries and the surface of the perovskite absorber layer using a proper passivation material to achieve both highly efficient and stable inverted p–i–n PSCs.

Efficient bifacial monolithic perovskite/silicon tandem solar cells via bandgap engineering

Abstract: Bifacial monolithic perovskite/silicon tandem solar cells exploit albedo—the diffuse reflected light from the environment—to increase their performance above that of monofacial perovskite/silicon tandems. Here we report bifacial tandems with certified power conversion efficiencies >25% under monofacial AM1.5G 1 sun illumination that reach power-generation densities as high as ~26 mW cm–2 under outdoor testing. We investigated the perovskite bandgap required to attain optimized current matching under a variety of realistic illumination and albedo conditions. We then compared the properties of these bifacial tandems exposed to different albedos and provide energy yield calculations for two locations with different environmental conditions. Finally, we present a comparison of outdoor test fields of monofacial and bifacial perovskite/silicon tandems to demonstrate the added value of tandem bifaciality for locations with albedos of practical relevance. Bifacial solar cells can outperform monofacial cells by exploiting sunlight reflected off the ground surface. De Bastiani et al. show that bifacial perovskite/silicon tandem with an optimized bandgap can deliver a power density of 26 mW cm–2 and compare its performance to monofacial cells under outdoor conditions.

Sublimable Spin-Crossover Complexes: From Spin-State Switching to Molecular Devices.

Abstract: Spin-crossover (SCO) active transition metal complexes are an important class of switchable molecular materials due to their bistable spin-state switching characteristics at or around room temperature. Vacuum-sublimable SCO complexes are a subclass of SCO complexes suitable for fabricating ultraclean spin-switchable films desirable for applications, especially in molecular electronics/spintronics. Consequently, on-surface SCO of thin-films of sublimable SCO complexes have been studied employing spectroscopy and microscopy techniques, and results of fundamental and technological importance have been obtained. This Review provides complete coverage of advances made in the field of vacuum-sublimable SCO complexes: progress made in the design and synthesis of sublimable functional SCO complexes, on-surface SCO of molecular and multilayer thick films, and various molecular and thin-film device architectures based on the sublimable SCO complexes.

Trustworthy artificial intelligence

Abstract: Artificial intelligence (AI) brings forth many opportunities to contribute to the wellbeing of individuals and the advancement of economies and societies, but also a variety of novel ethical, legal, social, and technological challenges. Trustworthy AI (TAI) bases on the idea that trust builds the foundation of societies, economies, and sustainable development, and that individuals, organizations, and societies will therefore only ever be able to realize the full potential of AI, if trust can be established in its development, deployment, and use. With this article we aim to introduce the concept of TAI and its five foundational principles (1) beneficence, (2) non-maleficence, (3) autonomy, (4) justice, and (5) explicability. We further draw on these five principles to develop a data-driven research framework for TAI and demonstrate its utility by delineating fruitful avenues for future research, particularly with regard to the distributed ledger technology-based realization of TAI.

25 Years of Reticular Chemistry.

Abstract: At its core, reticular chemistry has translated the precision and expertise of organic and inorganic synthesis to the solid state. While initial excitement over metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) was undoubtedly fueled by their unprecedented porosity and surface areas, the most profound scientific innovation of the field has been the elaboration of design strategies for the synthesis of extended crystalline solids through strong directional bonds. In this contribution we highlight the different classes of reticular materials that have been developed, how these frameworks can be functionalized, and how complexity can be introduced into their backbones. Finally, we show how the structural control over these materials is being extended from the molecular scale to their crystal morphology and shape on the nanoscale, all the way to their shaping on the bulk scale.

Photon Upconversion for Photovoltaics and Photocatalysis: A Critical Review – Focus Review

Abstract: Opportunities for enhancing solar energy harvesting using photon upconversion are reviewed. The increasing prominence of bifacial solar cells is an enabling factor for the implementation of upconversion, however, when the realistic constraints of current best-performing silicon devices are considered, many challenges remain before silicon photovoltaics operating under nonconcentrated sunlight can be enhanced via lanthanide-based upconversion. A photophysical model reveals that >1-2 orders of magnitude increase in the intermediate state lifetime, energy transfer rate, or generation rate would be needed before such solar upconversion could start to become efficient. Methods to increase the generation rate such as the use of cosensitizers to expand the absorption range and the use of plasmonics or photonic structures are reviewed. The opportunities and challenges for these approaches (or combinations thereof) to achieve efficient solar upconversion are discussed. The opportunity for enhancing the performance of technologies such as luminescent solar concentrators by combining upconversion together with micro-optics is also reviewed. Triplet-triplet annihilation-based upconversion is progressing steadily toward being relevant to lower-bandgap solar cells. Looking toward photocatalysis, photophysical modeling indicates that current blue-to-ultraviolet lanthanide upconversion systems are very inefficient. However, hope remains in this direction for organic upconversion enhancing the performance of visible-light-active photocatalysts.

The passivity of lithium electrodes in liquid electrolytes for secondary batteries

Abstract: Rechargeable Li metal batteries are currently limited by safety concerns, continuous electrolyte decomposition and rapid consumption of Li. These issues are mainly related to reactions occurring at the Li metal–liquid electrolyte interface. The formation of a passivation film (that is, a solid electrolyte interphase) determines ionic diffusion and the structural and morphological evolution of the Li metal electrode upon cycling. In this Review, we discuss spontaneous and operation-induced reactions at the Li metal–electrolyte interface from a corrosion science perspective. We highlight that the instantaneous formation of a thin protective film of corrosion products at the Li surface, which acts as a barrier to further chemical reactions with the electrolyte, precedes film reformation, which occurs during subsequent electrochemical stripping and plating of Li during battery operation. Finally, we discuss solutions to overcoming remaining challenges of Li metal batteries related to Li surface science, electrolyte chemistry, cell engineering and the intrinsic instability of the Li metal–electrolyte interface. Rechargeable Li metal batteries are currently limited by electrolyte decomposition and rapid Li consumption. Li plating and stripping greatly depend on the solid electrolyte interphase formed at the Li metal–liquid electrolyte interface. This Review discusses the reactions occurring at this interface from a corrosion science perspective, highlighting the requirements for an ideal passivation layer.

Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC

Abstract: The performance is presented of the reconstruction and identification algorithms for electrons and photons with the CMS experiment at the LHC. The reported results are based on proton-proton collision data collected at a center-of-mass energy of 13 TeV and recorded in 2016-2018, corresponding to an integrated luminosity of 136 fb$^{-1}$. Results obtained from lead-lead collision data collected at $\sqrt{s_\mathrm{NN}}=$ 5.02 TeV are also presented. Innovative techniques are used to reconstruct the electron and photon signals in the detector and to optimize the energy resolution. Events with electrons and photons in the final state are used to measure the energy resolution and energy scale uncertainty in the recorded events. The measured energy resolution for electrons produced in Z boson decays in proton-proton collision data ranges from 2 to 5%, depending on electron pseudorapidity and energy loss through bremsstrahlung in the detector material. The energy scale in the same range of energies is measured with an uncertainty smaller than 0.1 (0.3)% in the barrel (endcap) region in proton-proton collisions and better than 1 (3)% in the barrel (endcap) region in heavy ion collisions. The timing resolution for electrons from Z boson decays with the full 2016-2018 proton-proton collision data set is measured to be 200 ps.

Evaluating epidemic forecasts in an interval format.

Abstract: For practical reasons, many forecasts of case, hospitalization, and death counts in the context of the current Coronavirus Disease 2019 (COVID-19) pandemic are issued in the form of central predictive intervals at various levels. This is also the case for the forecasts collected in the COVID-19 Forecast Hub (https://covid19forecasthub.org/). Forecast evaluation metrics like the logarithmic score, which has been applied in several infectious disease forecasting challenges, are then not available as they require full predictive distributions. This article provides an overview of how established methods for the evaluation of quantile and interval forecasts can be applied to epidemic forecasts in this format. Specifically, we discuss the computation and interpretation of the weighted interval score, which is a proper score that approximates the continuous ranked probability score. It can be interpreted as a generalization of the absolute error to probabilistic forecasts and allows for a decomposition into a measure of sharpness and penalties for over- and underprediction.

Phylogenetic analysis of SARS-CoV-2 data is difficult.

Abstract: Numerous studies covering some aspects of SARS-CoV-2 data analyses are being published on a daily basis, including a regularly updated phylogeny on nextstrain.org. Here, we review the difficulties of inferring reliable phylogenies by example of a data snapshot comprising a quality-filtered subset of 8,736 out of all 16,453 virus sequences available on May 5, 2020 from gisaid.org. We find that it is difficult to infer a reliable phylogeny on these data due to the large number of sequences in conjunction with the low number of mutations. We further find that rooting the inferred phylogeny with some degree of confidence either via the bat and pangolin outgroups or by applying novel computational methods on the ingroup phylogeny does not appear to be credible. Finally, an automatic classification of the current sequences into subclasses using the mPTP tool for molecular species delimitation is also, as might be expected, not possible, as the sequences are too closely related. We conclude that, although the application of phylogenetic methods to disentangle the evolution and spread of COVID-19 provides some insight, results of phylogenetic analyses, in particular those conducted under the default settings of current phylogenetic inference tools, as well as downstream analyses on the inferred phylogenies, should be considered and interpreted with extreme caution.

Globally altered sleep patterns and physical activity levels by confinement in 5056 individuals: ECLB COVID-19 international online survey

Abstract: Symptoms of psychological distress and disorder have been widely reported in people under quarantine during the COVID-19 pandemic;in addition to severe disruption of peoples’ daily activity and sleep patterns This study investigates the association between physical-activity levels and sleep patterns in quarantined individuals An international Google online survey was launched in April 6th, 2020 for 12-weeks Forty-one research organizations from Europe, North-Africa, Western-Asia, and the Americas promoted the survey through their networks to the general society, which was made available in 14 languages The survey was presented in a differential format with questions related to responses “before” and “during” the confinement period Participants responded to the Pittsburgh Sleep Quality Index (PSQI) questionnaire and the short form of the International Physical Activity Questionnaire 5056 replies (59 4% female), from Europe (46 4%), Western-Asia (25 4%), America (14 8%) and North-Africa (13 3%) were analysed The COVID-19 home confinement led to impaired sleep quality, as evidenced by the increase in the global PSQI score (4 37 ± 2 71 before home confinement vs 5 32 ± 3 23 during home confinement) (p <0 001) The frequency of individuals experiencing a good sleep decreased from 61% (n = 3063) before home confinement to 48% (n = 2405) during home confinement with highly active individuals experienced better sleep quality (p <0 001) in both conditions Time spent engaged in all physical-activity and the metabolic equivalent of task in each physical-activity category (i e , vigorous, moderate, walking) decreased significantly during COVID-19 home confinement (p <0 001) The number of hours of daily-sitting increased by ~2 hours/days during home confinement (p <0 001) COVID-19 home confinement resulted in significantly negative alterations in sleep patterns and physical-activity levels To maintain health during home confinement, physical-activity promotion and sleep hygiene education and support are strongly warranted © 2021 Institute of Sport All rights reserved

Production of high-energy Li-ion batteries comprising silicon-containing anodes and insertion-type cathodes.

Abstract: Rechargeable Li-based battery technologies utilising silicon, silicon-based, and Si-derivative anodes coupled with high-capacity/high-voltage insertion-type cathodes have reaped significant interest from both academic and industrial sectors. This stems from their practically achievable energy density, offering a new avenue towards the mass-market adoption of electric vehicles and renewable energy sources. Nevertheless, such high-energy systems are limited by their complex chemistry and intrinsic drawbacks. From this perspective, we present the progress, current status, prevailing challenges and mitigating strategies of Li-based battery systems comprising silicon-containing anodes and insertion-type cathodes. This is accompanied by an assessment of their potential to meet the targets for evolving volume- and weight-sensitive applications such as electro-mobility.

Modulating electron density of vacancy site by single Au atom for effective CO2 photoreduction

Abstract: The surface electron density significantly affects the photocatalytic efficiency, especially the photocatalytic CO2 reduction reaction, which involves multi-electron participation in the conversion process. Herein, we propose a conceptually different mechanism for surface electron density modulation based on the model of Au anchored CdS. We firstly manipulate the direction of electron transfer by regulating the vacancy types of CdS. When electrons accumulate on vacancies instead of single Au atoms, the adsorption types of CO2 change from physical adsorption to chemical adsorption. More importantly, the surface electron density is manipulated by controlling the size of Au nanostructures. When Au nanoclusters downsize to single Au atoms, the strong hybridization of Au 5d and S 2p orbits accelerates the photo-electrons transfer onto the surface, resulting in more electrons available for CO2 reduction. As a result, the product generation rate of AuSA/Cd1-xS manifests a remarkable at least 113-fold enhancement compared with pristine Cd1-xS.