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The capabilities of discovering new knowledge and updating the previously acquired one are crucial for deploying autonomous robots in unknown and changing environments. Spatial and objectness concepts are at the basis of several robotic functionalities and are part of the intuitive understanding of the physical world for us humans. In this paper, we propose a method, which we call Modelify, to incrementally map the environment at the level of objects in a consistent manner. We follow an approach where no prior knowledge of the environment is required. The only assumption we make is that objects in the environment are separated by concave boundaries. The approach works on an RGB-D camera stream, where object-like segments are extracted and stored in an incremental database. Segment description and matching are performed by exploiting 2D and 3D information, allowing to build a graph of all segments. Finally, a matching score guides a Markov clustering algorithm to merge segments, thus completing object representations. Our approach allows creating single (merged) instances of repeating objects, objects that were observed from different viewpoints, and objects that were observed in previous mapping sessions. Thanks to our matching and merging strategies this also works with only partially overlapping segments. We perform evaluations on indoor and outdoor datasets recorded with different RGB-D sensors and show the benefit of using a clustering method to form merge candidates and keypoints detected in both 2D and 3D. Our new method shows better results than previous approaches while being significantly faster. A newly recorded dataset and the source code are released with this publication. [ABSTRACT FROM AUTHOR]

Network integration of quantum key distribution is crucial for its future widespread deployment due to the high cost of using optical fibers dedicated for the quantum channel only. We studied the performance of a system running a simplified BB84 protocol at 2.5 GHz repetition rate, operating in the original wavelength band, the short O-band, when multiplexed with communication channels in the conventional wavelength band, and the short C-band. Our system could successfully generate secret keys over a single-mode fiber with a length of 95.5 km and with co-propagating classical signals at a launch power of 8.9 dBm. Furthermore, we discuss the performance of an ideal system under the same conditions, showing the limits of what is possible with a discrete variable system in the O-band. We also considered a short and lossy link with 51 km optical fiber resembling a real link in a metropolitan area network. In this scenario, we could exchange a secret key with a launch power up to 16.7 dBm in the classical channels. [ABSTRACT FROM AUTHOR]

The article explores about the systematic engineering of artificial metalloenzymes for new-to-nature reactions. It mentions that artificial metalloenzymes (ArMs) catalyzing new-to-nature reactions could play an important role in transitioning toward a sustainable economy. It mentions that smart screening strategies and build machine learning models that accurately predict ArM activity from sequence, which has crucial implications for future ArM development.

We present and characterize a source for a 5 GHz clocked polarization-based simplified BB84 protocol. Secret keys are distributed over 151.5 km of standard telecom fiber at a rate of 54.5 kbps. Potentially, an increased clock frequency of the experiment introduces correlations between succeeding pulses. We discuss the impact of these correlations and propose measurements to estimate the relevant parameters. [ABSTRACT FROM AUTHOR]

With the progress of machine learning, the demand for realistic data with high-quality annotations has been thriving. In order to generalize well, considerable amounts of data are required, especially realistic ground-truth data, for tasks such as object detection and scene segmentation. Such data can be difficult, time-consuming, and expensive to collect. This article presents a dataset of household objects and box scenes commonly found in warehouse environments. The dataset was obtained using a robotic setup with four different cameras. It contains reconstructed objects and scenes, as well as raw RGB and depth images, camera poses, pixel-wise labels of objects directly in the RGB images, and 3D bounding boxes with poses in the world frame. Furthermore, raw calibration data are provided, together with the intrinsic and extrinsic parameters for all the sensors. By providing object labels as pixel-wise masks, 3D, and 2D object bounding boxes, this dataset is useful for both object recognition and instance segmentation. The realistic scenes provided will serve for learning-based algorithms applied to scenarios where boxes of objects are often found, such as in the logistics sector. Both the dataset and the tools for data processing are published and available online. [ABSTRACT FROM AUTHOR]

Abstract: A mild and practical Barbier–Negishi coupling of secondary alkyl bromides with aryl and alkenyl triflates and nonaflates has been developed. This challenging reaction was enabled by the use of a very bulky imidazole‐based phosphine ligand, which resulted in good yields as well as good chemo‐ and site selectivities for a broad range of substrates at room temperature and under non‐aqueous conditions. This reaction was extended to primary alkyl bromides by using an analogous pyrazole‐based ligand. [ABSTRACT FROM AUTHOR]

Abstract: A mild and practical Barbier–Negishi coupling of secondary alkyl bromides with aryl and alkenyl triflates and nonaflates has been developed. This challenging reaction was enabled by the use of a very bulky imidazole‐based phosphine ligand, which resulted in good yields as well as good chemo‐ and site selectivities for a broad range of substrates at room temperature and under non‐aqueous conditions. This reaction was extended to primary alkyl bromides by using an analogous pyrazole‐based ligand. [ABSTRACT FROM AUTHOR]

Abstract: Palladium-catalyzed cross-coupling reactions have emerged as one of the most versatile tools in organic chemistry. Extensive efforts were made to adapt these reactions to aqueous media, not only for the purpose of environmental conservation but also to expand the scope, increase the efficiency and implement bio-compatible protocols. Among different palladium cross-coupling reactions, the Heck reaction turned out to be the most challenging in an aqueous environment. This led to various original developments in catalyst design. This review summarizes the different approaches pursued to perform Heck reactions in neat water as well as aqueous mixtures. Both, homogeneous and immobilized catalysts, including nanoparticles are presented herein.Graphical Abstract: [ABSTRACT FROM AUTHOR]

Nuclear distribution protein C (NudC) is a mitotic regulator that plays a role in cytokinesis. However, how NudC is regulated during cytokinesis remains unclear. Here, we show that NudC is phosphorylated by Aurora B, a kinase critical for cell abscission. NudC is co-localized with Aurora B at the midbody and co-immunoprecipitated with Aurora B in mitosis. Inhibition of Aurora B by ZM447439 reduced NudC phosphorylation, suggesting that NudC is an Aurora B substrate in vivo. We identified T40 on NudC as an Aurora B phosphorylation site. NudC depletion resulted in cytokinesis failure with a dramatic elongation of the intercellular bridge between daughter cells, sustained Aurora B activity at the midbody, and reduced cell abscission. These cytokinetic defects can be rescued by the ectopic expression of wild-type NudC. Reconstitution with T40A phospho-defective NudC was found to rescue the cytokinesis defect. In contrast, reconstitution with the T40D phospho-mimetic NudC was inefficient in supporting the completion of cytokinesis. These results suggest that that dynamic phosphorylation of NudC by Aurora B regulates cytokinesis. [ABSTRACT FROM AUTHOR]

Worldwide waste is increasing and can contain engineered nanoparticles (ENP) made from almost the entire spectrum of the periodic table. An increasing amount of waste (including nanowaste) is incinerated. A full-scale experiment in a modern waste incineration plant showed that even inert nanoparticles (nano-CeO2) are successfully removed from the flue gas and transferred to the solid incineration residues. Predicting the fate of nanomaterials in incineration plants with models based on real measurements would reduce the immense efforts (time and resources) for real-scale experiments. Here, we develop a model for the ENP fate in incineration plants, based on the data of the nanoCeO2-experiment. We investigated all possible transfers and sinks of ENP throughout the incineration by linking ENP concentration measurements to the nanomaterial flows and retention times. The model also delivers information on the associated uncertainties and how they propagate through the incineration system by using a fully probabilistic material flow analysis. The model can be generalized to other ENP and also to other incineration plants. We show that the output of the measurements was consistent albeit relying on multiple measurement methods, and that a one day sampling period is sufficient to obtain an overview on the fate of nanoparticles in incineration plants. In addition to the dynamic results, a generalized steady state mass flow with transfer factors is provided and can be used for modeling purposes of CeO2 or other nano sized metals with similar physic-chemical properties. [ABSTRACT FROM AUTHOR]

The production and use of engineered nanomaterials (ENMs) are increasing rapidly, and therefore, the need to assess their environmental exposure and associated risks has become increasingly important. Only a handful of studies have quantified the release and environmental concentrations of ENMs, but much work has been done to investigate the effects of these materials on organisms. The aim of the present study was to quantify probabilistically the environmental risks of ENMs, producing species sensitivity distributions that were then compared with probability distributions of predicted environmental concentrations. Five nanomaterials (nano-Ag, nano-TiO2, nano-ZnO, carbon nanotubes [CNTs], and fullerenes) and 4 environmental compartments (surface water, sewage treatment plant effluents, soils, and sludge-treated soils) were considered. From 60 ecotoxicological studies, the authors extracted 112 single values to work with (25 values in 13 studies for nano-Ag, 17 values in 10 studies for CNTs, 7 values in 7 studies for fullerenes, 34 values in 23 studies for nano-TiO2, and 29 values in 17 studies for nano-ZnO). The results indicate there is only a marginal risk for these metal-based nanomaterials in surface water (0.7% risk for nano-Ag and <0.1% for nano-TiO2) and some risk in sewage treatment plant effluents (nano-Ag 39.7%, nano-TiO2 18.7%, and nano-ZnO 1.1%). Apart from a marginal value of <0.1% for nano-TiO2 in sludge-treated soils, no risk from the other evaluated ENMs in terrestrial compartments is currently predicted. The discussion of the results considers the influence of the effects of different forms of 1 ENM (coating, agglomeration state, and mineralogy), the test conditions (dissolution and agglomeration), and transformation reactions. Environ Toxicol Chem 2013;32:1278-1287. © 2013 SETAC [ABSTRACT FROM AUTHOR]

Protein acetylation has been implicated in playing an important role during mitotic progression. Aurora B kinase is known to play a critical role in mitosis. However, whether Aurora B is regulated by acetylation is not known. Using IP with an anti-acetyl lysine antibody, we identified Aurora B as an acetylated protein in PC3 prostate cancer cells. Knockdown of HDAC3 or inhibiting HDAC3 deacetylase activity led to a significant increase (P<0.01 and P<0.05, respectively) in Aurora B acetylation as compared to siLuc or vehicle-treated controls. Increased Aurora B acetylation is correlated with a 30% reduction in Aurora B kinase activity in vitro and resulted in significant defects in Aurora B-dependent mitotic processes, including kine-tochore-microtubule attachment and chromosome con-gression. Furthermore, Aurora B transiently interacts with HDAC3 at the kinetochore-microtubule interface of congressing chromosomes during prometaphase. This window of interaction corresponded with a transient but significant reduction (P=0.02) in Aurora B acetylation during early mitosis. Together, these results indicate that Aurora B is more active in its deacetylated state and further suggest a new mechanism by which dynamic acetylation/deacetylation acts as a rheostat to fine-tune Aurora B activity during mitotic progression. [ABSTRACT FROM AUTHOR]

Not much is known so far about the amounts of engineered nanomaterials (ENM) that are produced but this information is crucial for environmental exposure assessment. This paper provides worldwide and Europe-wide estimates for the production and use of ten different ENM (TiO, ZnO, FeO, AlO, SiO, CeO, Ag, quantum dots, CNT, and fullerenes) based on a survey sent to companies producing and using ENM. The companies were asked about their estimate of the worldwide or regional market and not about their company-specific production, information that they would be less likely to communicate. The study focused on the actual production quantities and not the production capacities. The survey also addressed information on distribution of the produced ENM to different product categories. The results reveal that some ENM are produced in Europe in small amounts (less than 10 t/year for Ag, QDs and fullerenes). The most produced ENM is TiO with up to 10,000 t of worldwide production. CeO, FeO, AlO, ZnO, and CNT are produced between 100 and 1000 t/year. The data for SiO cover the whole range from less than 10 to more than 10,000 t/year, which is indicative of problems related to the definition of this material (is pyrogenic silica considered an ENM or not?). For seven ENM we have obtained the first estimates for their distribution to different product categories, information that also forms the base for life-cycle based exposure analysis. [ABSTRACT FROM AUTHOR]

Information on environmental concentrations is needed to assess the risks that engineered nanomaterials (ENM) may pose to the environment. In this study, predicted environmental concentrations (PEC) were modeled for nano-TiO2, carbon nanotubes (CNT) and nano-Ag for Switzerland. Based on a life-cycle perspective, the model considered as input parameters the production volumes of the ENMs, the manufacturing and consumption quantities of products containing those materials, and the fate and pathways of ENMs in natural and technical environments. Faced with a distinct scarcity of data, we used a probabilistic material flow analysis model, treating all parameters as probability distributions. The modeling included Monte Carlo and Markov Chain Monte Carlo simulations as well as a sensitivity and uncertainty analysis. The PEC values of the ENMs in the different environmental compartments vary widely due to different ENM production volumes and different life cycles of the nanoproducts. The use of ENM in products with high water relevance leads to higher water and sediment concentrations for nano-TiO2 and nano-Ag, compared to CNTs, where smaller amounts of ENM reach the aquatic compartments. This study also presents a sensitivity analysis and a comprehensive discussion of the uncertainties of the simulation results and the limitations of the used approach. To estimate potential risks, the PEC values were compared to the predicted-no-effect concentrations (PNEC) derived from published data. The risk quotients (PEC/PNEC) for nano-TiO2 and nano-Ag were larger than one for treated wastewater and much smaller for all other environmental compartments (e.g., water, sediments, soils). We conclude that probabilistic modeling is very useful for predicting environmental concentrations of ENMs given the current lack of substantiated data. Environ. Toxicol. Chem. 2010;29:1036–1048. © 2010 SETAC [ABSTRACT FROM AUTHOR]

Abstract: An elementary step towards a quantitative assessment of the risks of new compounds or pollutants (chemicals, materials) to the environment is to estimate their environmental concentrations. Thus, the calculation of predicted environmental concentrations (PECs) builds the basis of a first exposure assessment. This paper presents a probabilistic method to compute distributions of PECs by means of a stochastic stationary substance/material flow modeling. The evolved model is basically applicable to any substance with a distinct lack of data concerning environmental fate, exposure, emission and transmission characteristics. The model input parameters and variables consider production, application quantities and fate of the compounds in natural and technical environments. To cope with uncertainties concerning the estimation of the model parameters (e.g. transfer and partitioning coefficients, emission factors) as well as uncertainties about the exposure causal mechanisms (e.g. level of compound production and application) themselves, we utilized and combined sensitivity and uncertainty analysis, Monte Carlo simulation and Markov Chain Monte Carlo modeling. The combination of these methods is appropriate to calculate realistic PECs when facing a lack of data. The proposed model is programmed and carried out with the computational tool R and implemented and validated with data for an exemplary case study of flows of the engineered nanoparticle nano-TiO2 in Switzerland. [Copyright &y& Elsevier]

Engineered nanomaterials (ENM) are already used in many products and consequently released into environmental compartments. In this study, we calculated predicted environmental concentrations (PEC) based on a probabilistic material flow analysis from a life-cycle perspective of ENM-containing products. We modeled nano-TiO2, nano-ZnO, nano-Ag, carbon nanotubes (CNT), and fullerenes for the U.S., Europe and Switzerland. The environmental concentrations were calculated as probabilistic density functions and were compared to data from ecotoxicological studies. The simulated modes (most frequent values) range from 0.003 ng L-1 (fullerenes) to 21 ng L-1 (nano-TiO2) for surface waters and from 4 ng L-1 (fullerenes) to 4 μg L-1 (nano-TiO2) for sewage treatment effluents. For Europe and the U.S., the annual increase of ENMs on sludge-treated soil ranges from 1 ng kg-1 for fullerenes to 89 μg kg-1 for nano-TiO2. The results of this study indicate that risks to aquatic organisms may currently emanate from nano-Ag, nano-TiO2, and nano-ZnO in sewage treatment effluents for all considered regions and for nano-Ag in surface waters. For the other environmental compartments for which ecotoxicological data were available, no risks to organisms are presently expected. [ABSTRACT FROM AUTHOR]

The thermodynamic properties of three halocarbon molecules relevant in atmospheric and public health applications are presented from ab initio calculations. Our technique makes use of a reaction path-like Hamiltonian to couple all the vibrational modes to a large-amplitude torsion for 1,2-difluoroethane, 1,2-dichloroethane, and 1,2-dibromoethane, each of which possesses a heavy asymmetric rotor. Optimized ab initio energies and Hessians were calculated at the CCSD(T) and MP2 levels of theory, respectively. In addition, to investigate the contribution of electronically excited states to thermodynamic properties, several excited singlet and triplet states for each of the halocarbons were computed at the CASSCF/MRCI level. Using the resulting potentials and projected frequencies, the couplings of all the vibrational modes to the large-amplitude torsion are calculated using the new STAR-P 2.4.0 software platform that automatically parallelizes our codes with distributed memory via a familiar MATLAB interface. Utilizing the efficient parallelization scheme of STAR-P, we obtain thermodynamic properties for each of the halocarbons, with temperatures ranging from 298.15 to 1000 K. We propose that the free energies, entropies, and heat capacities obtained from our methods be used to supplement theoretical and experimental values found in current thermodynamic tables. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008 [ABSTRACT FROM AUTHOR]

Simple Summary: The discovery of Comperiella calauanica a parasitoid confirmed to be the major natural enemy of the invasive diaspidid, Aspidiotus rigidus, has led to the promise of biological control in sustainable pest management of this devastating coconut pest. In this study, we employed Maximum Entropy (Maxent) to develop a bioclimate-based species distribution model (SDM) for the parasitoid from presence-only data recorded from field surveys conducted in select points the Philippines. Results of assessment of the generated model point to its excellent power in predicting either suitability of habitat, or potential occurrence or distribution of C. calauanica. Since the parasitoid is highly host-specific, the model may also apply to A. rigidus. Field surveys in select areas in the Philippines confirmed the occurrence of the invasive coconut scale in areas predicted by the model as having considerable probability of occurrence, or habitat suitability. Our findings strongly suggest the potential utility of Maxent SDMs as tools for pest invasion forecasting and GIS-aided surveillance for integrated pest management (IPM). Comperiella calauanica is a host-specific endoparasitoid and effective biological control agent of the diaspidid Aspidiotus rigidus, whose outbreak from 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (Maxent) algorithm, we developed a species distribution model (SDM) for C. calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016. The calculated the area under the ROC curve (AUC) values for the model were very high (0.966, standard deviation = 0.005), indicating the model's high predictive power. Precipitation seasonality was found to have the highest relative contribution to model development. Response curves produced by Maxent suggested the positive influence of mean temperature of the driest quarter, and negative influence of precipitation of the driest and coldest quarters on habitat suitability. Given that C. calauanica has been found to always occur with A. rigidus in Luzon Island due to high host-specificity, the SDM for the parasitoid may also be considered and used as a predictive model for its host. This was confirmed through field surveys conducted between late 2016 and early 2018, which found and confirmed the occurrence of A. rigidus in three areas predicted by the SDM to have moderate to high habitat suitability or probability of occurrence of C. calauanica: Zamboanga City in Mindanao; Isabela City in Basilan Island; and Tablas Island in Romblon. This validation in the field demonstrated the utility of the bioclimate-based SDM for C. calauanica in predicting habitat suitability or probability of occurrence of A. rigidus in the Philippines. [ABSTRACT FROM AUTHOR]

We present a simplified BB84 protocol with only three quantum states and one decoy-state level. We implement this scheme using the polarization degree of freedom at telecom wavelength. Only one pulsed laser is used in order to reduce possible side-channel attacks. The repetition rate of 625 MHz and the achieved secret bit rate of 23 bps over 200 km of standard fiber are the actual state of the art. [ABSTRACT FROM AUTHOR]

A personal narrative is presented which explores the author's experience of being married to a fellow scientist on topics including the challenges of living apart while pursuing careers in science, the desire of wanting a career and a family, and the strength of she and her husband's relationship.

The PH domain-containing proteins Slm1 and Slm2 were previously identified as effectors of the phosphatidylinositol-4,5-bisphosphate (PI4,5P2) and TORC2 signaling pathways. Here, we demonstrate that Slm1 and Slm2 are also targets of sphingolipid signaling during the heat shock response. We show that upon depletion of cellular sphingolipid levels, Slm1 function becomes essential for survival under heat stress. We further demonstrate that Slm proteins are regulated by a phosphorylation/dephosphorylation cycle involving the sphingolipid-activated protein kinases Pkh1 and Pkh2 and the calcium/calmodulin-dependent protein phosphatase calcineurin. By using a combination of mass spectrometry and mutational analysis, we identified serine residue 659 in Slm1 as a site of phosphorylation. Characterization of Slm1 mutants that mimic dephosphorylated and phosphorylated states demonstrated that phosphorylation at serine 659 is vital for survival under heat stress and promotes the proper polarization of the actin cytoskeleton. Finally, we present evidence that Slm proteins are also required for the trafficking of the raft-associated arginine permease Can1 to the plasma membrane, a process that requires sphingolipid synthesis and actin polymerization. Together with previous work, our findings suggest that Slm proteins are subject to regulation by multiple signals, including PI4,5P2, TORC2, and sphingolipids, and may thus integrate inputs from different signaling pathways to temporally and spatially control actin polarization. [ABSTRACT FROM AUTHOR]

The environmental risks of five engineered nanomaterials (nano-TiO2, nano-Ag, nano-ZnO, CNT, and fullerenes) were quantified in water, soils, and sediments using probabilistic Species Sensitivity Distributions (pSSDs) and probabilistic predicted environmental concentrations (PECs). For water and soil, enough ecotoxicological endpoints were found for a full risk characterization (between 17 and 73 data points per nanomaterial for water and between 4 and 20 for soil) whereas for sediments, the data availability was not sufficient. Predicted No Effect Concentrations (PNECs) were obtained from the pSSD and used to calculate risk characterization ratios (PEC/PNEC). For most materials and environmental compartments, exposure and effect concentrations were separated by several orders of magnitude. Nano-ZnO in freshwaters and nano-TiO2in soils were the combinations where the risk characterization ratio was closest to one, meaning that these are compartment/ENM combinations to be studied in more depth with the highest priority. The probabilistic risk quantification allows us to consider the large variability of observed effects in different ecotoxicological studies and the uncertainty in modeled exposure concentrations. The risk characterization results presented in this work allows for a more focused investigation of environmental risks of nanomaterials by consideration of material/compartment combinations where the highest probability for effects with predicted environmental concentrations is likely. [ABSTRACT FROM AUTHOR]

It has been shown that in the asymptotic case of infinite-key length, the 2-decoy state Quantum Key Distribution (QKD) protocol outperforms the 1-decoy state protocol. Here, we present a finite-key analysis of the 1-decoy method. Interestingly, we find that for practical block sizes of up to 108 bits, the 1-decoy protocol achieves for almost all experimental settings higher secret key rates than the 2-decoy protocol. Since using only one decoy is also easier to implement, we conclude that it is the best choice for QKD, in most common practical scenarios. [ABSTRACT FROM AUTHOR]

During the first year of the COVID-19 pandemic, healthcare facilities worldwide struggled to adequately care for the increasing number of COVID-19 patients while maintaining quality of care for all other patients. The aim of this study was to investigate the displacement and underuse of non-COVID-19 patient care in a medical department of a tertiary hospital in Switzerland. In this retrospective cross-sectional study, internal medicine admissions from 2017 to 2020, emergency outpatient visits from 2019 to 2020 and COVID-19 admissions in 2020 were analyzed and compared using a regression model. Internal medicine admissions were also stratified by diagnosis. A questionnaire was used to assess the pandemic experience of local general practitioners, referring hospitals, and nursing homes. The total number of admissions decreased during the 1st and 2nd waves of the pandemic but increased between the two waves. Elective admissions decreased in 2020 compared to pre-pandemic years: they represented 25% of total admissions in 2020 versus 30% of the total admissions during 2017–2019, p <0.001. Admissions for emergency reasons increased: 71% in 2020 versus 65% in 2017–2019, p < 0.001. Emergency outpatient consultations decreased in 2020 compared to 2019, 62.77 (14.70), mean (SD), weekly visits in 2020 versus 74.13 (13.98) in 2019, p<0.001. Most general practitioners and heads of referring hospitals also reported a decrease in consultations, especially during the 1st wave of the pandemic. Mental illnesses, anxiety or burn-out were perceived in both patients and staff in general practices and nursing homes. In conclusion, the COVID-19 pandemic negatively affected the care of non-COVID-19 patients, particularly those with chronic illnesses. A shift of health care resources from non-COVID patients to COVID patients was observed. These findings could help institutions better manage such a situation in the future. [ABSTRACT FROM AUTHOR]

• Environmental impacts induced by innovative recycling processes applied to epoxy / carbon fiber composites. • Supercritical hydrolysis and electrodynamic fragmentation versus pyrolysis, incineration and landfilling. • Reduction of the supercritical hydrolysis and electrodynamic fragmentation environmental impact through optimization. Global consumption of carbon fibers reinforced polymer (CFRP) is rising and the management of waste is an issue of high concern. In order to implement a sustainable carbon fiber recycling sector, there is a need to evaluate the potential environmental impacts of recycling processes. In this context, we compared current end-of-life scenarios (landfilling and incineration) with recycling technologies: pyrolysis, supercritical solvolysis and electrodynamic fragmentation using life cycle assessment. We conducted two analyses: a comparison between the CFRP end-of-life processes and a comparison including the substituted products from the recycled carbon fibers. When only considering the end-of-life processes, recycling processes have a higher environmental impact as they require higher energy demand than incineration or landfilling. When considering product substitution, recycling is environmentally beneficial since they replace the production of virgin products. Results are variable depending on the technology readiness level and the quality of fibers recovered from the recycling processes. [ABSTRACT FROM AUTHOR]

The aim of this paper is to describe the process and challenges in building exposure scenarios for engineered nanomaterials (ENM), using an exposure scenario format similar to that used for the European Chemicals regulation (REACH). Over 60 exposure scenarios were developed based on information from publicly available sources (literature, books, and reports), publicly available exposure estimation models, occupational sampling campaign data from partnering institutions, and industrial partners regarding their own facilities. The primary focus was on carbon-based nanomaterials, nano-silver (nano-Ag) and nano-titanium dioxide (nano-TiO), and included occupational and consumer uses of these materials with consideration of the associated environmental release. The process of building exposure scenarios illustrated the availability and limitations of existing information and exposure assessment tools for characterizing exposure to ENM, particularly as it relates to risk assessment. This article describes the gaps in the information reviewed, recommends future areas of ENM exposure research, and proposes types of information that should, at a minimum, be included when reporting the results of such research, so that the information is useful in a wider context. [ABSTRACT FROM AUTHOR]

Abstract: Carbon nanotubes (CNT) are expected to be applied in a wide range of industrial applications and consumer products. As a consequence of widespread usage and their supposed persistence against degradation, human and environmental exposure to CNT is likely to increase. There are still many open questions regarding the effects of human or ecological exposure. However, the results of toxicological studies suggest that nanotubes may affect human health. Here we study possible sources of CNT-release on the basis of two case studies. In order to investigate whether and under which conditions CNT may be released from applications, we track the CNT throughout their life cycle as part of two types of consumer products: lithium-ion secondary batteries and synthetic textiles. The findings of the case studies suggest that a release of nanotubes can occur not only in the production phase, but also in the usage and disposal phases of nanotube applications. The likelihood and form of release is determined by the way CNT are incorporated into the material. A considerable part of all CNT used may finally be dispersed somewhere in the technosphere or the environment, e.g. by cross-product contamination during recycling. As long as potential adverse effects of CNT cannot be ruled out, we recommend implementing precautionary measures along the value chain (including the end-of-life treatment) in order to reduce the release and possible negative environmental or human health effects of CNT. [Copyright &y& Elsevier]

Robust and accurate pose estimation is crucial for many applications in mobile robotics. Extending visual Simultaneous Localization and Mapping (SLAM) with other modalities such as an inertial measurement unit (IMU) can boost robustness and accuracy. However, for a tight sensor fusion, accurate time synchronization of the sensors is often crucial. Changing exposure times, internal sensor filtering, multiple clock sources and unpredictable delays from operation system scheduling and data transfer can make sensor synchronization challenging. In this paper, we present VersaVIS, an Open Versatile Multi-Camera Visual-Inertial Sensor Suite aimed to be an efficient research platform for easy deployment, integration and extension for many mobile robotic applications. VersaVIS provides a complete, open-source hardware, firmware and software bundle to perform time synchronization of multiple cameras with an IMU featuring exposure compensation, host clock translation and independent and stereo camera triggering. The sensor suite supports a wide range of cameras and IMUs to match the requirements of the application. The synchronization accuracy of the framework is evaluated on multiple experiments achieving timing accuracy of less than 1   ms . Furthermore, the applicability and versatility of the sensor suite is demonstrated in multiple applications including visual-inertial SLAM, multi-camera applications, multi-modal mapping, reconstruction and object based mapping. [ABSTRACT FROM AUTHOR]