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.

The effects of climate change are already being felt, including the failure to harvest several agricultural products. On the other hand, peatland requires good management because it is a high carbon store and is vulnerable as a contributor to high emissions if it catches fire. This study aims to determine the potential for livelihood options through land management with an agroforestry pattern in peatlands. The methods used are field observation and in-depth interviews. The research location is in Kuburaya Regency, West Kalimantan, Indonesia. Several land use scenarios are presented using additional secondary data. The results show that agroforestry provides more livelihood options than monoculture farming or wood. The economic contribution is very important so that people reduce slash-and-burn activities that can increase carbon emissions and threaten the sustainability of peatland.

We analyzed the relationship between nutrient (N and K) parceling and population density on the severity of onion downy mildew under no-tillage fertigation cultivation in the conditions of Alto Vale do Itajaí (Barzil). For this purpose, field trials were conducted in the years 2017, 2018 and 2019, in Ituporanga (Barzil). The treatments corresponded to four population densities (300, 400, 500 and 600 mil plants ha^-1) subjected to applications of nitrogen (150 kg N ha^-1) and potassium (127.5 kg K₂O ha^-1) distributed throughout the vegetative cycle of the crop via fertigation on a weekly, biweekly and monthly basis, based on the absorption curve of these nutrients for the cultivar Empasc 352-Bola Precoce. In fertigated no-tillage systems, nutrient (N and K) tranches do not influence the severity of downy mildew. The severity of downy mildew increases linearly with increasing population density, especially from 500 mil plants per ha^-1.

Technology development in the agricultural sector is important in the development of Thailand’s economy. The purpose of this research was to study the approach of guidelines for future agricultural technology development to increase productivity in the Agricultural sector in order to develop a structural equation model. The research applied mixed-methodology. Qualitative research by in depth interview from 9 experts and focus group with 11 successful businesspersons for approve this model. The quantitative data gather from firm, in the 500 of agricultural sector by using questionnaire, using statistical tests of descriptive analysis, inferential analysis, and multivariate analysis. The research found guidelines for future agricultural technology development to increase productivity in the Agricultural sector composed of 4 latent. The most important item of each latent were as following: 1) Agrobiology Technology (= 4.41), in important item as choose seeds that for disease resistance and tolerate the environment to suit the cultivation area, 2) Environmental Assessment (= 4.37),, in important item as survey of cultivated areas according to topography with geographic information system, 3) Agricultural Innovation (= 4.30), in important item as technology reduces operational procedures, reduce the workforce and can reduce operating costs, and 4) Modern Management Systems (= 4.13), in important item as grouping and manage as a cooperative to mega farms. In addition, the hypothesis test found that the difference in manufacturing firm sizes. Medium and Small size and large size revealed overall aspects that were significantly different at the level of 0.05. The analysis of the developed structural equation model found that there was in accordance and fit with the empirical data and passed the evaluation criteria. Its Chi-square probability level, relative Chi-square, the goodness of fit index, and root mean square error of approximation were 0.062, 1.165, 0.961, and 0.018, respectively.

This paper aims to explore the relationship between corporate overinvestment and management incentives, focusing particularly on the influence of different ownership structures. Utilizing agency theory and ownership structure theory, this study constructs a theoretical framework and posits hypotheses on how management incentives might influence corporate overinvestment behaviors under different ownership structures. Listed companies from 2010 to 2020 were selected as the research sample, and the hypotheses were empirically tested using descriptive statistics, correlation analysis, and regression analysis. The findings suggest that a relatively concentrated ownership structure may encourage management to adopt more cautious investment strategies, thus reducing overinvestment behaviors; while under a dispersed ownership structure, the relationship between management incentives and overinvestment is more complex. This study provides new evidence on how management incentive mechanisms influence corporate decision-making in different ownership environments, offering significant theoretical and practical implications for improving internal control and incentive mechanisms.

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.