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Tensor analytics lays the mathematical basis for the prosperous promotion of multiway signal processing. To increase computing throughput, mainstream processors transform tensor convolutions into matrix multiplications to enhance the parallelism of computing. However, such order-reducing transformation produces data duplicates and consumes additional memory. Here, we propose an integrated photonic tensor flow processor (PTFP) without digitally duplicating the input data. It outputs the convolved tensor as the input tensor ‘flows’ through the processor. The hybrid manipulation of optical wavelengths, space dimensions, and time delay steps, enables the direct representation and processing of high-order tensors in the optical domain. In the proof-of-concept experiment, an integrated processor manipulating wavelengths and delay steps is implemented for demonstrating the key functionalities of PTFP. The multi-channel images and videos are processed at the modulation rate of 20 Gbaud. A convolutional neural network for video action recognition is demonstrated on the processor, which achieves an accuracy of 97.9%. Convolutional operation is a very efficient way to handle tensor analytics, but it consumes a large quantity of additional memory. Here, the authors demonstrate an integrated photonic tensor processor which directly handles high-order tensors without tensor-matrix transformation.

We show that there are well-defined maps on sutured ECH induced by contact 2-handle attachments and that the sutured ECH contact class is functorial under such maps.

Opening doors and drawers will be an important ability for future service robots used in domestic and industrial environments. However, in recent years, the methods for opening doors and drawers have become more diverse and difficult for robots to determine and manipulate. We can divide doors into three distinct handling types: regular handles, hidden handles, and push mechanisms. While extensive research has been done on the detection and handling of regular handles, the other types of handling have not been explored as much. In this paper, we set out to classify the types of cabinet door handling types. To this end, we collect and label a dataset consisting of RGB-D images of cabinets in their natural environment. As part of the dataset, we provide images of humans demonstrating the handling of these doors. We detect the poses of human hands and then train a classifier to determine the type of cabinet door handling. With this research, we hope to provide a starting point for exploring the different types of cabinet door openings in real-world environments.

Given a handle decomposition of a 4-manifold with boundary and an open book decomposition of the boundary, we show how to produce a trisection diagram of a trisection of the 4-manifold inducing the given open book. We do this by making the original proof of the existence of relative trisections more explicit in terms of handles. Furthermore, we extend this existence result to the case of 4-manifolds with multiple boundary components and show how trisected 4-manifolds with multiple boundary components glue together.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) emerged in March 2020 in Italy, leading to the pandemic of coronavirus disease 2019 (COVID-19) that continues to cause high global morbidity and mortality in human populations. Numerous studies have focused on the spread and persistence of the virus in the hospital setting. New scientific evidence shows that SARS-CoV-2 is present in different community environments. Although aerosol is one of the main routes of transmission for SARS-CoV-2, indirect contact through virus-contaminated surfaces could also play a key role. The survival and persistence of SARS-CoV-2 on surfaces appear to be influenced by the characteristics of the material, temperature, and humidity. In this study, we investigated the presence of SARS-CoV-2 RNA on surfaces in 20 supermarkets throughout the Apulia region during the lockdown period. We collected a total of 300 swab samples from various surfaces including supermarket scales, trolley handles, refrigerator and freezer handles, and keyboards. In total, 13 (4.3%) surfaces were positive for SARS-CoV-2 RNA contamination, with shopping trolley handles being the most frequently contaminated. This study showed that contamination in public spaces can occur, so we remark the importance to adopt adequate preventive measures, including environment ventilation, careful surfaces sanitation, hand hygiene, and correct usage of masks, to reduce the likelihood of virus transmission.

We generalize Newton-type methods for minimizing smooth functions to handle a sum of two convex functions: a smooth function and a nonsmooth function with a simple proximal mapping. We show that the resulting proximal Newton-type methods inherit the desirable convergence behavior of Newton-type methods for minimizing smooth functions, even when search directions are computed inexactly. Many popular methods tailored to problems arising in bioinformatics, signal processing, and statistical learning are special cases of proximal Newton-type methods, and our analysis yields new convergence results for some of these methods. [PUBLICATION ABSTRACT]

• Reciprocal symbiosis of > 70% of terrestrial vascular plants with arbuscular mycorrhizal (AM) fungi provides the fungi with fatty acids and sugars. In return, AM fungi facilitate plant phosphate (Pi) uptake from soil. However, how AM fungi handle Pi transport and homeostasis at the symbiotic interface of AM symbiosis is poorly understood. • Here, we identify an SPX (SYG1/Pho81/XPR1) domain-containing phosphate transporter, RiPT7 from Rhizophagus irregularis. To characterize the RiPT7 transporter, we combined subcellular localization and heterologous expression studies in yeasts with reverse genetics approaches during the in planta phase. • The results show that RiPT7 is conserved across fungal species and expressed in the intraradical mycelia. It is expressed in the arbuscules, intraradical hyphae and vesicles, independently of Pi availability. The plasma membrane-localized RiPT7 facilitates bidirectional Pi transport, depending on Pi gradient across the plasma membrane, whereas the SPX domain of RiPT7 inhibits Pi transport activity and mediates the vacuolar targeting of RiPT7 in yeast in response to Pi starvation. Importantly, RiPT7 silencing hampers arbuscule development of R. irregularis and symbiotic Pi delivery under medium- to low-Pi conditions. • Collectively, our findings reveal a role for RiPT7 in fine-tuning of Pi homeostasis across the fungal membrane to maintain the AM development.

Using a demolition hammer among the power tools is one of the most challenging job tasks for the operators of these tools, which exposes users to high levels of hand-transmitted vibrations. The focus of this study was for finding the vibration levels transmitted to the handles, the frequency content transmitted by the tool, and the effect of using insert bits with different tip shapes and lengths using conventional demolition hammers under controlled operating conditions on typical concrete slabs in the field. Three demolition hammers (weighing between 14 and 27 kg) with two handles installed were subjected to simultaneous measurements based on ISO 5349 as the field measurement technique. The findings demonstrated that even while the vertical axis dominated, several samples also produced equivalent x-axis results. The impact energy of the tools employed and the transmitted vibration to the tool handles are not significantly correlated with each other. All mean values were higher in the slabs with a thickness of 15 than those with 10 cm. The mean values of the total results for the two forms of flat and point tip inserted bits were 16.85 and 15.86 m/s2, respectively, and in the samples with the same operating factors, this difference was more than 3 m/s2 (p < .03). The a wrms (frequency-weighted root mean square acceleration) produced at tools using 60 cm bits were more than those with a length of 40 cm, both for the average of the total results and the average of the results of each hammer. The difference between the average bit length groups over samples with the same factors reached 4.65 m/s2 (p = .02). Frequency analysis for the flat and point insert bits with 60 cm length in the concrete slabs with a thickness of 15 cm showed that the dominant frequencies detected at lower frequencies for point bits. This difference is almost two frequency parts of 1/3 octave band.

Multiple-point geostatistics enable the realistic simulation of complex spatial structures by inferring statistics from a training image. These methods are typically computationally expensive and require complex algorithmic parametrizations. The approach that is presented in this paper is easier to use than existing algorithms, as it requires few independent algorithmic parameters. It is natively designed for handling continuous variables and quickly implemented by capitalizing on standard libraries. The algorithm can handle incomplete training images of any dimensionality, with categorical and/or continuous variables, and stationarity is not explicitly required. It is possible to perform unconditional or conditional simulations, even with exhaustively informed covariates. The method provides new degrees of freedom by allowing kernel weighting for pattern matching. Computationally, it is adapted to modern architectures and runs in constant time. The approach is benchmarked against a state-of-the-art method. An efficient open-source implementation of the algorithm is released and can be found here (https://github.com/GAIA-UNIL/G2S, last access: 19 May 2020) to promote reuse and further evolution.The highlights are the following:A new approach is proposed for pixel-based multiple-point geostatistics simulation.The method is flexible and straightforward to parametrize.It natively handles continuous and multivariate simulations.It has high computational performance with predictable simulation times.A free and open-source implementation is provided.

Free energy calculations based on molecular dynamics simulations show considerable promise for applications ranging from drug discovery to prediction of physical properties and structure-function studies. But these calculations are still difficult and tedious to analyze, and best practices for analysis are not well defined or propagated. Essentially, each group analyzing these calculations needs to decide how to conduct the analysis and, usually, develop its own analysis tools. Here, we review and recommend best practices for analysis yielding reliable free energies from molecular simulations. Additionally, we provide a Python tool, alchemical-analysis.py , freely available on GitHub as part of the pymbar package (located at http://github.com/choderalab/pymbar ), that implements the analysis practices reviewed here for several reference simulation packages, which can be adapted to handle data from other packages. Both this review and the tool covers analysis of alchemical calculations generally, including free energy estimates via both thermodynamic integration and free energy perturbation-based estimators. Our Python tool also handles output from multiple types of free energy calculations, including expanded ensemble and Hamiltonian replica exchange, as well as standard fixed ensemble calculations. We also survey a range of statistical and graphical ways of assessing the quality of the data and free energy estimates, and provide prototypes of these in our tool. We hope this tool  and discussion will serve as a foundation for more standardization of and agreement on best practices for analysis of free energy calculations.