Horticulture is a widespread activity in family farming in the Transamazonian region—Pará, with emphasis on production aimed at the family’s own consumption. The lettuce cultivar Vanda (Lactuca sativa L.) represents a significant part of this production, which prioritizes the use of internal labor. The main objective of this work was to evaluate the development of lettuce CV Vanda grown in beds using organic compost and chemical fertilization (NPK). The criteria considered to evaluate this performance were: Root system development, plant height and total fresh mass production. The best averages in relation to root development occurred in the plots cultivated with organic compost in the proportion of 5 kg/m2, due to its characteristics as a fertilizer and soil conditioner. The cultivation with the use of NPK provided the best averages in relation to the production of total fresh mass and plant height, results that were mainly attributed to the extra supply of nitrogen in the covering fertilization, which consisted in the addition of 10 g urea per square meter via soil. Statistical analysis showed no statistically significant difference regarding plant height for both treatments. And in relation to root development, the difference was statistically significant.
Magnesium hydroxide/melamine phosphate borate (nano MH/MPB), a novel nano-composition intumescent flame retardant, was synthesized with the in-situ reaction method from MgCl2·6H2O sodium hydroxide (NaOH) and melamine phosphate borate (MPB) in the absence of H2O. The structure of the product was confirmed by EDAX IR and XRD. The effects of reaction temperature and time on the dimension of magnesium hydroxide were observed. The effects of mass ratio of magnesium hydroxide to MPB on the flame retardancy of nano-MH/MPB/EP were examined with the limiting oxygen test. The results show that the optimal condition of synthesis of MH/MPB is mMH/mMPB = 0.25, reacting under 75 ℃ for 30 minutes. Finally, the mechanism for flame retardancy of nano-MH/MPB/EP was pilot studied by means of IR of char layer and TG of MH/MPB.
This study aims to identify the impact of inheritance literacy, inheritance socialization, inheritance stress, and peer influence on the inheritance behaviors among FELDA communities in Malaysia. Inheritance literacy pertains to individuals’ comprehension of wealth transfer and estate planning, while peer influencer evaluates friends’ impact on inheritance attitudes; inheritance socialization explores family interactions’ role in shaping inheritance attitudes, and inheritance stress measures emotional strain in inheritance matters, with inheritance behaviors encompassing asset management and wealth transfer decisions for future generations by individuals and families. Understanding inheritance behaviors is crucial, as it helps individuals depict their inheritance knowledge and attitudes toward FELDA inheritance better, fostering a more favorable inheritance attitude. Through self-administered survey questionnaires, data related to FELDA communities are obtained using convenience sampling from 413 respondents. This study applies Partial Least Squares Structural Equation Modeling (PLS-SEM) technique to test the research hypotheses. The present study’s outcome confirms that two determinants, which are inheritance literacy and inheritance socialization significantly influence the inheritance behavior of FELDA communities. However, inheritance stress and peer influence determinants have statistically insignificant influence inheritance behavior. This study’s theoretical framework enriches the discussions on wealth management and financial behavior by refining and expanding upon existing financial behavior theories to incorporate inheritance-specific behaviors. The present study is exclusive in its effort to ascertain the relative importance of both inheritance behavior and the FELDA communities. This paper will assist the government, inheritance service providers, and policymakers in offering innovative economic schemes and designing policies that may enhance the inheritance behavior wellbeing of FELDA communities. This article also provides a roadmap to guide future research in this area.
The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.
Context: Noise in the work environment, in all types of productive activities, represents a hazard and has not really been valued in its real dimension. Little has been seen that stakeholders have determined the urgency of managing noise control programs. Therefore, losses resulting from medical treatment and absenteeism, represented in health care and social services, result in hidden work-related costs that directly affect the gross domestic product in any country.
Method: This article compiles different case studies from around the world. The studies were divided for review into general studies on the effects of workforce noise and then particularized according to the effects of industrial noise on workers’ health. At a control level, the assessment and measurement of noise is defined through the use of tools such as noise maps and their respective derivations, in addition to spatial databases.
Results: According to the collection of information and its analysis, we observe that in the medium term, the economies will be diminished in an important percentage due to the consequences generated by the exposure to noise. Specific information can be found in the development of the article.
Conclusions: The data provided by the case studies point to the need for Colombia, a country that is no stranger to this phenomenon, and which additionally has the great disadvantage of not having significant studies in the field of noise analysis, should strengthen studies based on spatial data as a mechanism for measurement and control.
Financing: Fundación universitaria Los Libertadores.
In recent years, the foundry sector has been showing an increased interest in reclamation of used sands. Grain shape, sieve analysis, chemical and thermal characteristics must be uniform while molding the sand for better casting characteristics. The problem that tackled by every foundry industry is that of processing an adequate supply of sand which has the properties to meet many requirements imposed upon while molding and core making. Recently, fluidized bed combustors are becoming core of ‘clean wastes technology’ due to their efficient and clean burning of sand. For proven energy efficient sand reclamation processing, analysis of heating system in fluidized bed combustor (FBC) is required. The objective of current study is to design heating element and analysis of heating system by calculation of heat losses and thermal analysis offluidized bed combustorfor improving efficiency.
Copyright © by EnPress Publisher. All rights reserved.