Recombination resistance identification through current-voltage curve reconstruction in perovskite solar cells.

Perovskite solar cells (PSCs) have demonstrated remarkable advancements in efficiency and stability, yet fully understanding the dynamic processes governing their performance remains a challenge. Impedance spectroscopy (IS) offers a powerful means to characterize PSCs over a wide range of time scales, revealing insights into the internal electronic and ionic processes. However, critical factors like recombination, charge extraction, and transport resistance are often coupled in the same spectra response, affecting their accurate identification.

Adjusting the Crystallization of Tin Perovskites through Thiophene Additives for Improved Photovoltaic Stability.

Tin-based perovskites (Sn-PVK) are promising lead-free alternatives for efficient photovoltaic technology, but they face challenges related to bulk and surface defects due to suboptimal crystallization and Sn oxidation. Introducing thiophene-2-ethylammonium halides (TEAX, where X = I, Br, Cl) improves FASnI crystallization and reduces Sn formation. This is achieved by adjusting the crystallization dynamics through the formation of a complex between S and Sn during the preparation of the precursor solution, which also inhibits Sn oxidation in the resulting films.

Improving Radiology Report Generation Quality and Diversity through Reinforcement Learning and Text Augmentation.

Deep learning is revolutionizing radiology report generation (RRG) with the adoption of vision encoder-decoder (VED) frameworks, which transform radiographs into detailed medical reports. Traditional methods, however, often generate reports of limited diversity and struggle with generalization. Our research introduces reinforcement learning and text augmentation to tackle these issues, significantly improving report quality and variability.

A comparison of Covid-19 early detection between convolutional neural networks and radiologists.

Background: The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists.

Ethical Decision Making in Iot Data Driven Research: A Case Study of a Large-Scale Pilot.

IoT technologies generate intelligence and connectivity and develop knowledge to be used in the decision-making process. However, research that uses big data through global interconnected infrastructures, such as the 'Internet of Things' (IoT) for Active and Healthy Ageing (AHA), is fraught with several ethical concerns. A large-scale application of IoT operating in diverse piloting contexts and case studies needs to be orchestrated by a robust framework to guide ethical and sustainable decision making in respect to data management of AHA and IoT based solutions.

Automatic Rule Generation for Decision-Making in Context-Aware Systems Using Machine Learning.

With the increasing interest devoted to dynamic environments, a crucial aspect is revealed in context-aware systems to deal with the rapid changes occurring in users' surrounding environments at runtime. However, most context-aware systems with predefined context-aware rules may not support effective decision-making in dynamic environments. These context-aware rules, which take into account different context information to reach an appropriate decision, could lose their efficiency at runtime.

Coastal Monitoring Using Unmanned Aerial Vehicles (UAVs) for the Management of the Spanish Mediterranean Coast: The Case of Almenara-Sagunto.

The concentration of the world's population in coastal areas means an increase in pressure on the environment and coastal ecosystems. The impacts of climate change affect natural biophysical and ecological systems and human health. Research has been developed to create coastal monitoring with Unmanned Aerial Vehicles (UAVs) that allow data to be obtained and methodologies that integrate computer vision algorithms for 3D and image processing techniques for analysis, combined with maritime information.

CRISPR-Mediated Strand Displacement Logic Circuits with Toehold-Free DNA.

DNA nanotechnology, and DNA computing in particular, has grown extensively over the past decade to end with a variety of functional stable structures and dynamic circuits. However, the use as designer elements of regular DNA pieces, perfectly complementary double strands, has remained elusive. Here, we report the exploitation of CRISPR-Cas systems to engineer logic circuits based on isothermal strand displacement that perform with toehold-free double-stranded DNA.

Programmable photonic circuits.

The growing maturity of integrated photonic technology makes it possible to build increasingly large and complex photonic circuits on the surface of a chip. Today, most of these circuits are designed for a specific application, but the increase in complexity has introduced a generation of photonic circuits that can be programmed using software for a wide variety of functions through a mesh of on-chip waveguides, tunable beam couplers and optical phase shifters. Here we discuss the state of this emerging technology, including recent developments in photonic building blocks and circuit architectures, as well as electronic control and programming strategies.

Preferential flow modelling of chlorpyrifos leaching in two arid soils of irrigated agricultural production areas in Argentine Patagonia.

An analysis was made of the transport and fate of the organophosphate pesticide chlorpyrifos in productive soils from the Alto Valle of the Río Negro in Argentine Patagonia. The climate of the region is arid, so traditional fruit production is under flood irrigation. The soils in the floodplain are predominantly Aridisols with textures ranging from sandy loam to clay loam.

Large Pockels effect in micro- and nanostructured barium titanate integrated on silicon.

The electro-optical Pockels effect is an essential nonlinear effect used in many applications. The ultrafast modulation of the refractive index is, for example, crucial to optical modulators in photonic circuits. Silicon has emerged as a platform for integrating such compact circuits, but a strong Pockels effect is not available on silicon platforms.

On the influence of interface charging dynamics and stressing conditions in strained silicon devices.

The performance of strained silicon devices based on the deposition of a top silicon nitride layer with high stress have been thoroughly analyzed by means of simulations and experimental results. Results clearly indicate that the electro-optic static response is basically governed by carrier effects. A first evidence is the appearance of a variable optical absorption with the applied voltage that should not occur in case of having a purely electro-optic Pockels effect.

Increased sensitivity through maximizing the extinction ratio of SOI delay-interferometer receiver for 10G DPSK.

We present an optimized design for a 10G- differential-phase-shift-keyed (DPSK) receiver based on a silicon-on-insulator (SOI) unbalanced tunable Mach-Zehnder interferometer (MZI) switch in sequence with a Mach-Zehnder delay interferometer (MZDI). The proposed design eliminates the limitation in sensitivity of the device produced by the waveguide propagation losses in the delay line. A 2.

Silicon slow-light-based photonic mixer for microwave-frequency conversion applications.

We describe and demonstrate experimentally a method for photonic mixing of microwave signals by using a silicon electro-optical Mach-Zehnder modulator enhanced via slow-light propagation. Slow light with a group index of ~11, achieved in a one-dimensional periodic structure, is exploited to improve the upconversion performance of an input frequency signal from 1 to 10.25 GHz.

A solar energy powered autonomous wireless actuator node for irrigation systems.

The design of a fully autonomous and wireless actuator node ("wEcoValve mote") based on the IEEE 802.15.4 standard is presented.

Power consumption analysis of operating systems for wireless sensor networks.

In this paper four wireless sensor network operating systems are compared in terms of power consumption. The analysis takes into account the most common operating systems--TinyOS v1.0, TinyOS v2.