Horticultural crops are rich in constituents such as proteins, carbohydrates, vitamins, and minerals important for human health. Under biotic and abiotic stress conditions, rhizospheric bacteria are powerful sources of phytohormones such as indole acetic acid (IAA), gibberellic acid (GA), abscisic acid (ABA) and Plant growth regulators including cytokines, ammonia, nitrogen, siderophores, phosphate, and extra cellular enzymes. These phytohormones help horticultural crops grow both directly and indirectly. In recent agricultural practices, the massive use of chemical fertilizers causes a major loss of agricultural land that can be resolved by using the potent plant growth-promoting rhizospheric bacteria that protect the agricultural and horticultural crops from the adverse effect of phytopathogens and increase crop quality and yield. This review highlights the role of multifunctional rhizospheric bacteria in the growth promotion of horticultural crops in greenhouse conditions and agricultural fields. The relevance of plant growth hormones in horticultural crops highlighted in the current study is crucial for sustainable agriculture.

The melon culture is one of the Brazilian horticultural crops, due to its productive potential and socio-economic role. It is recommended for the State of Goiás and the Federal District for it is easy to plant and having need of zoning of climatic conditions and thus, being able to perform their sowing. The present work used the Sarazon program to perform the water balance of the melon crop, for the 2nd, 4th and 6th five-day sowing dates in August, September and October and in relation to the water reserves in the soil of 50 mm and 75 mm. The data were spatialized using the SPRING 4.3 program. It was observed that the producers are performing in practice what can be demonstrated in theory that the period October 16–20 is the most indicated for sowing in soils of 50 mm of water reserve and October 6–10 the beginning of sowing in soil of 75 mm of water reserve for the cultivation of melon and have adequate profitability.

The properties of the beta batteries are compared, which are made on the basis of the different β-isotopes with beta decay. Tritium and Ni-63 make it possible to make β-sources of high activity, without harmful associated emissions, with low self-absorption, emitting high-energy β-electrons that penetrate deep into the semiconductor and generate a large number of electron-hole pairs. The efficiency of beta batteries needs to be analyzed based on the real energy distribution of β-electrons. It makes possible to obtain the real value of the energy absorbed inside the β-source, correctly estimate the amount of self-absorption of the β-electrons and part of the β-electronsthere is a penetrate into the semiconductor, the number of electrons and holes that are generated in the semiconductor, and the magnitude of the idling voltage. Formulas for these quantities are calculated in this paper.

Several studies have discussed the benefits of blockchain in human resources management (HRM) policies to support the efficiency of HRM routine practices in organizations. The discussion ranges from selection and recruitment to employee separation. With the growing interest in digital application usage, research focused on utilization and effective measurement is needed. However, the existing literature review on blockchain-based HRM practices linked to cost efficiency still needs to be improved. Hence, this study aims to review current studies on blockchain human resources management systematically. This study investigates the trends in blockchain application usage in terms of practices, methodologies, and settings. This study used a literature survey and Publish or Perish software with Google Scholar and Scopus as the databases. 123 articles published in 19 journals from 2010 to 2022 were selected. This study used systematic data to reveal trends in HRM practices and qualitative inductive analysis to define relevant themes within the topic. The results show that blockchain applications for efficiency are used mainly in the recruitment and selection process, ranging from personal data verification to the quality of decision-making in skill development and maintenance. Five HRM practices have been discussed, indicating potential explorative and exploitative future research to improve the effectiveness of using blockchain in HRM practices.

To save patients’ lives, it is important to go for an early diagnosis of intracranial hemorrhage (ICH). For diagnosing ICH, the widely used method is non-contrast computed tomography (NCCT). It has fast acquisition and availability in medical emergency facilities. To predict hematoma progression and mortality, it is important to estimate the volume of intracranial hemorrhage. Radiologists can manually delineate the ICH region to estimate the hematoma volume. This process takes time and undergoes inter-rater variability. In this research paper, we develop and discuss a fine segmentation model and a coarse model for intracranial hemorrhage segmentations. Basically, two different models are discussed for intracranial hemorrhage segmentation. We trained a 2DDensNet in the first model for coarse segmentation and cascaded the coarse segmentation mask output in the fine segmentation model along with input training samples. A nnUNet model is trained in the second fine stage and will use the segmentation labels of the coarse model with true labels for intracranial hemorrhage segmentation. An optimal performance for intracranial hemorrhage segmentation solution is obtained.

The characteristics of agricultural products are influenced by the ecosystem, from the perspective of biotic and abiotic factors, which produce in the plant physiological responses and in turn in the fruit unique physicochemical properties, which are the basis for designations of origin and strategies to add value to the product in the current market. In the present work, ten cocoa materials (Theobroma cacao L.) were selected for their outstanding productivity (FSV41, FLE3, FEAR5, FSA12, FEC2, SCC23, SCC80, SCC55, ICS95 and CCN51), which were established in the departments of Santander (931 m a.s.l.), Huila (931 m a.s.l.), Huila (931 m a.s.l.), Huila (931 m a.s.l.), Huila (931 m a.s.l.), Huila (931 m a.s.l.) and Huila (931 m a.s.l.). These were established in the departments of Santander (931 m a.s.l.), Huila (885 m a.s.l.) and Arauca (204 m a.s.l.), the main cocoa-producing areas in Colombia. For the evaluation of the physical characteristics of the collected materials, 21 quantitative descriptors were used to determine the physical variability of the fruit according to clone and place of collection. The data collected were analyzed by means of Pearson’s correlation matrix and principal component analysis, it was possible to identify those descriptors that contribute most to the variability among materials (ear index, diameter length ratio, seed weight and diameter, and fruit weight and length). In addition, it was possible to verify the effect of the place of harvest on the physical characteristics of the materials, high-lighting the importance of the adaptation study prior to the planting of the cocoa material, with the objective of guaranteeing a premium, productive and quality cocoa crop for the industry, which is competitive in the market.