The cultivation of vegetables serves as a vital pillar in horticulture, offering an alternative avenue towards achieving economic sustainability. Unfortunately, farmers often lack adequate knowledge on optimizing resource utilization, which subsequently results in low productivity. Furthermore, there has been insufficient research conducted on the comparative profitability and efficient use of resources for pea cultivation. So, the present study was conducted to examine the profitability and resource use efficiency of conventional and organic pea production in Northwestern Himalayan state. Using the technique of purposive sampling, the districts and villages were selected based on the highest area. By using simple random sampling, a sample of 100 farmers was selected, out of which 50 were organic growers and 50 were inorganic growers, who were further categorized as marginal and small. The cost incurred was higher for the cultivation of inorganic vegetable crops, whereas returns and output-input ratio was higher in organic cultivation. The cultivation of peas revealed that the majority of inputs were being underutilized, and there was a need for proper reallocation of the resources, which would result in enhanced production. Further, major problems in the cultivation of vegetable crops were a high wage rate, a lack of organic certification, a shortage of skilled labour and a lack of technical knowledge.

Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.

The conversion of the energy supply to renewable sources (wind, photovoltaics) will increase the volatility in electricity generation in the future. In order to ensure a balanced power balance in the power grid, storage is required - not only for a short time, but also seasonally. The bidirectional coupling of existing energy infrastructure with the power grid can help here by using the electricity in electrolysis systems to produce hydrogen. The hydrogen can be mixed with natural gas in the existing infrastructure (gas storage, pipelines) to a limited extent or converted directly to methane in a gas-catalytic reaction, methanation, with carbon dioxide and/or carbon monoxide. By using the natural gas infrastructure, the electricity grids are relieved and renewable energies can also be stored over long periods of time. Another advantage of this technology, known as “Power-to-Gas”, is that the methane produced in this way represents a sink for CO₂ emissions, as it replaces fossil sources and CO₂ is thus fed into a closed cycle.

Research in the field of Power-to-Gas technology is currently addressing technological advances both in the field of electrolysis and for the subsequent methanation, in particular to reduce investment costs. In the field of methanation, load-flexible processes are to be developed that are adapted to the fluctuating supply of hydrogen. The profitability of the Power-to-Gas process chain can be increased through synergistic integration into existing industrial processes. For example, an integrated smelting works offers a promising infrastructural environment, since, on the one hand, process gases containing carbon are produced in large quantities and, on the other hand, the oxygen as a by-product from the water electrolysis can be used directly. Such concepts suggest an economic application of Power-to-Gas technology in the near future.

Amyloidosis is a systemic disorder produced by the deposition of insoluble protein fibrils that fold and deposit in the myocardium. Patients with amyloidosis and cardiac involvement have higher mortality than patients without cardiac involvement. The two most prevalent forms of amyloidosis associated with cardiac involvement are AL amyloidosis, due to the deposition of immunoglobulin light chains, and ATTR amyloidosis, due to the deposition of the transthyretin (TTR) protein in mutated or senile form. This article aims to review the different cardiac imaging modalities (echocardiography, cardiac magnetic resonance imaging, nuclear medicine and tomography) that allow to determine the severity of cardiac involvement in patients with amyloidosis, the type of amyloidosis and its prognosis. Finally, we suggest a diagnostic algorithm to determine cardiac involvement in amyloidosis adapted to locally available diagnostic tools, with a practical and clinical approach.

Currently there is a great acceptance in medicine and dentistry that clinical practice should be “evidence-based” as much as possible. That is why multiple works have been published aimed at decreasing radiation doses in the different types of imaging modalities used in dentistry, since the greater effect of radiation, especially in children, forces us to take necessary measures to rationalize its use, especially with Cone Beam computed tomography (CBCT), the method that provides the highest doses in dentistry. This review was written using such an approach with the purpose of rationalizing the radiation dose in our patients. In order to formulate recommendations that contribute to the optimization of the use of ionizing radiation in dentistry, the SEDENTEXCT project team compiled and analyzed relevant publications in the literature, guidelines that have demonstrated their efficiency in the past, thus helping to see with different perspectives the dose received by patients, and with this, it is recommended taking into account this document so as to prescribe more adequately the complementary examinations that we use on a daily basis.

Magnetite magnetic nanoparticles (MNP) exhibit superparamagnetic behavior, which gives them important properties such as low coercive field, easy superficial modification and acceptable magnetization levels. This makes them useful in separation techniques. However, few studies have experimented with the interactions of MNP with magnetic fields. Therefore, the aim of this research was to study the influence of an oscillating magnetic field (OMF) on polymeric monolithic columns with vinylated magnetic nanoparticles (VMNP) for capillary liquid chromatography (cLC). For this purpose, MNP were synthesized by coprecipitation of iron salts. The preparation of polymeric monolithic columns was performed by copolymerization and aggregation of VMNP. Taking advantage of the magnetic properties of MNP, the influence of parameters such as resonance frequency, intensity and exposure time of a OMF applied to the synthesized columns was studied. As a result, a better separation of a sample according to the measured parameters was obtained, so that a column resolution (R_s) of 1.35 was achieved. The morphological properties of the columns were evaluated by scanning electron microscopy (SEM). The results of the chromatographic properties revealed that the best separation of the alkylbenzenes sample occurs under conditions of 5.5 kHz and 10 min of exposure in the OMF. This study constitutes a first application in chromatographic separation techniques for future research in nanotechnology.