A repetition-rate-stabilized frequency comb ranging from the violet to the mid-infrared $(0.4–2.4\mathrm{\mu }\mathrm{m})$ is obtained by phase locking a femtosecond Ti:sapphire laser and a synchronously pumped optical parametric oscillator to a common supercontinuum reference. The locking results have bandwidths lower than $3\mathrm{kHz}$. By changing the locking frequencies, different relative and absolute offsets of the constituent frequency combs are achievable.

Numerous pathologies are harmful to the world population, such as pulmonary problems and Cerebral vascular accident (CVA). Chronic Obstructive Pulmonary Disease (COPD) is the leading cause of respiratory mortality worldwide, according to the World Health Organization (WHO), about 3.2 million deaths were caused by COPD in 2015. By 2020, 200 million people worldwide will be diagnosed with COPD. Similar to COPDs, in 2016, CVA was the second leading cause of death in the world, reaching 5.5 million. In the USA alone, there are more than 2 million people with sequelae due to stroke, causing an estimated cost of US$ 316.1 billion per year. Computed tomography (CT) is among the main tests for the clinical diagnosis of lung diseases and CVA. In order to facilitate and speed up the process of locating and segmenting the region of interest, Computer-Aided Diagnoses (CAD) systems are increasingly being employed as it reduces the effort, increases the safety of the diagnosis, and the performance of the specialist. In this work, we propose a method based on health of things for classification and segmentation of medical images in computed tomography (CT) images of the lung and hemorrhagic stroke. The system called SHTCS - Medical Images: System Health of Things for Classification and Segmentation Medical Images, uses transfer learning between models based on deep learning (Detectron2) combined with classic methods through fine-tuning. Our method obtained excellent results, both in the classification of hemorrhagic strokes with 100% Accuracy and for pulmonary regions reaching 97% Accuracy. For segmentation, the models obtained excellent performances, with Accuracy above 99% and Dice coefficient (DICE) above 97% in the best cases for segmentation of pulmonary regions with an average segmentation time reaching approximately 1.7 seconds. The experiments continued with excellent performance for segmentation of hemorrhagic stroke with 99% accuracy and 94% DICE and an average segmentation time of 0.095 per image. In order to validate our approach, we compared our best models for the segmentation of lung and hemorrhagic stroke in CT, thus surpassing related works found in state of the art. Our method brings an innovative approach through the use of Health of Things for different types of medical images with promising results for the fields of medicine and computer vision.

ZnO@ZIF-8 was synthesized by dry gel conversion (DGC) method, which is a green atom-economical synthesis with very small amount of raw materials. As-synthesized ZnO@ZIF-8 showed potential application as a selective H₂ detector over toluene.

Application of MXene materials in perovskite solar cells (PSCs) has attracted considerable attention owing to their supreme electrical conductivity, excellent carrier mobility, adjustable surface functional groups, excellent transparency and superior mechanical properties. This article reviews the progress made so far in using Ti₃C₂T_x MXene materials in the building blocks of perovskite solar cells such as electrodes, hole transport layer (HTL), electron transport layer (ETL) and perovskite photoactive layer. Moreover, we provide an outlook on the exciting opportunities this recently developed field offers, and the challenges faced in effectively incorporating MXene materials in the building blocks of PSCs for better operational stability and enhanced performance.

Since its invention in 2009, Perovskite solar cells (PSCs) has attracted great attention because of its low cost, numerous options of efficiency enhancement, ease of manufacturing and high-performance. Within a short span of time, the PSC has already outperformed thin-film and multicrystalline silicon solar cells. A current certified efficiency of 25.2% demonstrates that it has the potential to replace its forerunner generations. However, to commercialize PSCs, some problems need to be addressed. The toxic nature of lead which is the major component of light absorbing layer, and inherited stability issues of fabricated devices are the major hurdles in the industrialization of this technology. Therefore, new researching areas focus on the lead-free metal halide perovskites with analogous optical and photovoltaic performances. Tin being nontoxic and as one of group IV(A) elements, is considered as the most suitable alternate for lead because of their similarities in chemical properties. Efficiencies exceeding 13% have been recorded using Tin halide perovskite based devices. This review summarizes progress made so far in this field, mainly focusing on the stability and photovoltaic performances. Role of different cations and their composition on device performances and stability have been involved and discussed. With a considerable room for enhancement of both efficiency and device stability, different optimized strategies reported so far have also been presented. Finally, the future developing trends and prospects of the PSCs are analyzed and forecasted.

Two asynchronous, broadband 3.3 µm pulse trains with a stabilized repetition-rate difference of up to 5 kHz were generated using an ultrafast optical parametric oscillator. The two oscillation channels, each producing $\sim 100\mathrm{mW}$ average power, ran essentially independently, and weak non-phase-matched sum-frequency mixing between them provided a timing signal that indicated when the asynchronous pulses coincided. The system has immediate applications in incoherent asynchronous optical sampling and, with additional carrier-envelope-offset stabilization, could be applied to coherent dual-frequency-comb spectroscopy.