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This study aims to detect the bioacoustics signal in the underwater soundscape, specifically those produced by snapping shrimp, using adaptive iterative transfer learning. The proposed network is initially trained with pre-classified snapping shrimp sounds and Gaussian noise, then applied to classify and remove snapping-free noise from field data. This separated ambient noise is subsequently used for transfer learning. This process was iterated to distinguish more effectively between ambient noise and snapping shrimp sounds characteristics, resulting in improved classification. Through iterative transfer learning, significant improvements in precision and recall were observed. The application to field data confirmed that the trained network could detect signals that were difficult to identify using existing threshold classification methods. Furthermore, it was found that the rate of false detection decreased, and detection probability improved with each stage. This research demonstrates that incorporating the noise characteristics of field data into the trained network via iterative transfer learning can generate more realistic training data. The proposed network can successfully detect signals that are challenging to identify using existing threshold classification methods. [ABSTRACT FROM AUTHOR]

Employment can provide numerous benefits to quality of life, mental health, and social inclusion, which can be particularly important for people with disabilities. In a pilot study, the feasibility of Conversing with Others, a direct skills teaching (DST) group intervention to teach individuals with disabilities a work‐related soft skill focused on conversational skills, was assessed. This mixed methods study delivered the Conversing with Others curriculum in‐person or via telehealth to 119 participants. The intervention was based on the DST method of teaching skills through smaller, digestible, structured lessons. Both modalities showed improvement in participants' perceptions of their conversational skills. A non‐inferiority test indicated that the telehealth and in‐person group interventions were comparable. Overall, the study supported the feasibility of in‐person and telehealth interventions for teaching workplace conversational skills. [ABSTRACT FROM AUTHOR]

New ionic‐gel polymer electrolytes (IGPEs) are designed for use as electrolytes for all‐solid‐state supercapacitors (ASSSs) with excellent deformability and stability. The combination of the photochemical reaction‐based polymer matrix, weak‐binding lithium salt with ionic liquid, and ion dissociating solvator is employed to construct the nano‐canyon structured IGPE with high ionic conductivity (σDC = 1.2 mS cm−1 at 25 °C), high dielectric constant (εs = 131), and even high mechanical robustness (bending deformation for 10 000 cycles with superior conductivity retention [≈91%]). This gives rise to ASSS with high compatibility and stability, which is compliant with foldable electronics. Consequently, this ASSS delivers remarkable electrochemical performance (specific capacitance of ≈105 F g−1 at 0.22 A g−1, maximum energy density and power density of 23 and 17.2 kW kg−1), long lifetime (≈93% retention after 30 days), wider operating temperature (≈0–120 °C), and mechanical stabilities with no significant capacitance reduction after mechanical bending and multiple folding, confirming the superior electrochemical durability under serious deformation states. Therefore, this ultra‐flexible and environmentally stable ASSS based on the IGPE having the nano‐canyon morphology can be a novel approach for powering up the ultra‐deformable and durable next‐generation wearable energy storage devices. [ABSTRACT FROM AUTHOR]

The reverse time migration (RTM) aims to image subsurface reflectors by incorporating with the two-way wave equation. RTM has advantages that it does not have dip limitations and can generate subsurface images clearly even in the case of complex geological structures in the near surface. We have proposed a reproduction wavefield reverse time migration (RWRTM) algorithm implemented with backward reproduced wavefield instead of the back-propagation of the observed data. Reproduced wavefield can be achieved by using the same modelling algorithm used in the source propagation. In general acquisition systems, e.g. streamer in marine or surface geophone in land, conventional RTM back-propagates data acquired on the top grid points in the numerical domain while RWRTM back-propagates reproduced data located on all grid points in the numerical domain, which lead to the generation of migration images with less migration noises and well-balanced migrated events. To validate RWRTM, numerical tests are conducted. For our examples, RWRTM images have better resolution, improved continuity of structure, reduced migration noises, and balanced amplitude compared to the conventional RTM. [ABSTRACT FROM AUTHOR]