Exploring the abundant resources in the ocean requires underwater acoustic detectors with a high-sensitivity reception of low-frequency sound from greater distances and zero reflections. Here we address both challenges by integrating an easily deformable network of metal nanoparticles in a hydrogel matrix for use as a cavity-free microphone. Since metal nanoparticles can be densely implanted as inclusions, and can even be arranged in coherent arrays, this microphone can detect static loads and air breezes from different angles, as well as underwater acoustic signals from 20 Hz to 3 kHz at amplitudes as low as 4 Pa. Unlike dielectric capacitors or cavity-based microphones that respond to stimuli by deforming the device in thickness directions, this hydrogel device responds with a transient modulation of electric double layers, resulting in an extraordinary sensitivity (217 nF kPa−1 or 24 μC N−1 at a bias of 1.0 V) without using any signal amplification tools.

N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present miCLIP2 in combination with machine learning to significantly improve m6A detection. The optimized miCLIP2 results in high-complexity libraries from less input material. Importantly, we established a robust computational pipeline to tackle the inherent issue of false positives in antibody-based m6A detection. The analyses were calibrated with Mettl3 knockout cells to learn the characteristics of m6A deposition, including m6A sites outside of DRACH motifs. To make our results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP2 data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.

Identifying predictability sources of heatwave variations is a scientific challenge and of practical importance. This study investigates the summertime heatwave frequency (HWF) over Eurasia for 1950-2014. The Eurasian HWF is dominated by two distinct modes: the interdecadal (ID) mode, featured by an increasing pattern overall, centred around eastern Europe-central Asia and Mongolia-southwestern China; and the interannual (IA) mode, resembling a tripole anomaly pattern with three centres over western-northern Europe, northeastern Asia and East Asia. The ID mode is found to be influenced by mega-El Niño/Southern Oscillation (mega-ENSO) and the Atlantic Multidecadal Oscillation (AMO), and the latter has far more effect, whereas the IA mode is connected with mega-ENSO.Further analysis suggests that mega-ENSO variations can incite a Gill-type response spreading to Eurasia, while the AMO changes cause eastward-propagating Rossby wave trains toward Eurasia. These two teleconnection patterns together contribute to the largescale circulation anomalies of the ID mode, and those related to the IA mode arise from the teleconnection pattern excited by mega-ENSO. A strong mega-ENSO triggers subsidence with high pressure anomalies, warms the surface and increases the HWF significantly over northeastern Asia particularly. Likewise, the warm AMO-induced circulation anomalies engender surface radiative heating and HWF growth in most of the Eurasian continent except some localized Siberian and Asian regions. The situation is opposite for a weak mega-ENSO and AMO. Those models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) which realistically capture the features of the ID mode can reproduce the AMO-like sea-surface temperature anomalies (SSTAs), while signals resembling mega-ENSO are found in those with favourable capability of simulating the IA mode. On the contrary, these relevant SSTAs linked to the respective modes vanish in the models with little skills. Thus, mega-ENSO and the AMO might provide two critical predictability sources for heat waves over Eurasia.

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Modern smartphone operating systems (OSs) have been developed with a greater emphasis on security and protecting privacy. One of the mechanisms these systems use to protect users is a permission system, which requires developers to declare what sensitive resources their applications will use, has users agree with this request when they install the application and constrains the application to the requested resources during runtime. As these permission systems become more common, questions have risen about their design and implementation. In this paper, we perform an analysis of the permission system of the Android smartphone OS in an attempt to begin answering some of these questions. Because the documentation of Android's permission system is incomplete and because we wanted to be able to analyze several versions of Android, we developed PScout, a tool that extracts the permission specification from the Android OS source code using static analysis. PScout overcomes several challenges, such as scalability due to Android's 3.4 million line code base, accounting for permission enforcement across processes due to Android's use of IPC, and abstracting Android's diverse permission checking mechanisms into a single primitive for analysis.We use PScout to analyze 4 versions of Android spanning version 2.2 up to the recently released Android 4.0. Our main findings are that while Android has over 75 permissions, there is little redundancy in the permission specification. However, if applications could be constrained to only use documented APIs, then about 22% of the non-system permissions are actually unnecessary. Finally, we find that a trade-off exists between enabling least-privilege security with fine-grained permissions and maintaining stability of the permission specification as the Android OS evolves.

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The disposal of sewage sludge ash (SSA) has become an environmental issue due to the limited available landfilling space. This study aims at applying the finely-ground sewage sludge ash (FSSA) with quicklime and hydrated lime respectively to develop a new type of lime-pozzolan system and study the effects of different types of lime on the mechanical properties of the systems. A traditional pozzolanic material (i.e. coal fly ash (FA)) was also used to compare with the FSSA. Multiple techniques including X-ray diffraction (XRD), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA) were used to assess the hydration kinetics and microscopic characteristics of the lime-pozzolan systems. The results showed that the quicklime system exhibited lower strength than the hydrated lime system, which was due to its lower reaction degree with the FSSA and the higher porosity caused by the expansion during the vigorous hydration reaction of quicklime. Compared to FA, the FSSA attained higher strength for the whole curing period (up to 90 d) in the lime system due to the highly porous nature of FSSA leading to a lower effective water to binder ratio. However, in the hydrated lime system, due to the higher overall pozzolanic activity of FA, its long-term strength values gradually improved. Besides, calcium phosphate hydrate crystals were detected by XRD in the FSSA; while some clinotobermorite was found in the FA both from XRD and SEM, which might govern the strength gain in the lime-FA system. Overall, the application of FSSA as a pozzolan in the lime-pozzolan system could be a promising option to both relieve the waste disposal pressure and provide a potential sustainable construction material.

No abstract