Terahertz (THz) technology, which uses radiation lying between microwave and infrared in the electromagnetic spectrum, could revolutionize digital agriculture through terahertz’s ability to assess agricultural materials accurately and non-destructively. The review discusses notable developments in THz applications to digital agriculture: real-time crop monitoring, nutrient and disease detection, soil moisture and contaminant analysis, and supply chain traceability. The developments have emerged from studies in time-domain spectroscopy, imaging, machine learning (ML), and blockchain integration. Despite the promising advances in THz agricultural applications, limitations remain, such as limited penetration depth, high system costs, and operational robustness. Further research is needed to reach the full potential of THz technology in achieving sustainable agriculture. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
Simultaneous determination of Furosemide, Carbamazepine, Diazepam, and Carvedilol in bulk and pharmaceutical formulation using the partial least squares regression (PLS-1 and PLS-2) is described in this study. The two methods were successfully applied to estimate the four drugs in their quaternary mixture using UV spectral data of 84synthetic mixtures in the range of 200-350nm with the intervals Δλ=0.5nm. The linear concentration range were 1-20 μg.mL-1 for all, with correlation coefficient (R2) and root mean squares error for the calibration (RMSE) for FURO, CARB, DIAZ, and CARV were 0.9996, 0.9998, 0.9997, 0.9997, and 0.1128, 0.1292, 0.1868,0.1562 respectively for PLS-1, and for PLS-2 were 0.9995, 0.9999, 0.9997, 0.9998, and 0.1127, 0.
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreThe research aims to verify the presence of correlation between the financial cycle and the economic cycle in the Iraqi economy. During the research period, the Iraqi economy witnessed a crisis cycle due to the permanent deviations in the state budget and the occurrence of sustainable deficits during the period of the economic blockade with the coincidence of an inflationary economic cycle due to the cheap money policy and the occurrence of Negative supply shocks due to the blockade and the madly high general level of prices, in addition to the weak financial planning of the state budget during the post-economic blockade and the entry of the economy into a stagnant economic cycle due to security and political instability, low levels of priv
... Show MoreThe research seeks to identify the impact of fraud detection skills in the settlement of compensatory claims for the fire and accident insurance portfolio and the reflection of these skills in preventing and reducing the payment of undue compensation to some who seek profit and enrichment at the expense of the insurance contract. And compensatory claims in the portfolio of fire and accident insurance in the two research companies, which show the effect and positive return of the detection skills and settlement of the compensation on the amount of actual compensation against the claims inflated by some of the insured, The research sample consisted of (70) respondents from a community size (85) individuals between the director and assistan
... Show MoreIn the present study, a total of 245 flour samples were collected from 49 mills on both sides of Baghdad city (Al- Karkh and Al- Resafa), during the period from 1/6 - 1/12/ 2015 to detect the prolportion of iron added to the flour samples. It is found that only 45% of mills produced flour contain the prescribed percentage of iron (30-60 ppm) while 51.9% of the mills produced flour at rate is less or much more than the prescribed percentage, while only 4.1% of the mills were not added iron to the flour.
The levels of lead (pb), copper (cu), cobalt (co) and cadmium (cd) were determined in different kinds of milk and the health risks were evaluated. The mean levels were 0.73±0.21, 0.06±0.01, 0.12±0.01 and 0.14±0.01 ppm for these metals respectively. The levels of pb and cu were found to be insignificant differences (p<0.05), whereas the levels of co and cd, were no significant differences (p>0.05). The dry and liquid kinds of milk were different significantly (p<0.05), whereas the original, was no significant differences (p>0.05). The values for all metals were more than one. The metals pb and cd were detected at highest concentrations in most dry and liquid milk samples.
As material flow cost accounting technology focuses on the most efficient use of resources like energy and materials while minimizing negative environmental effects, the research aims to show how this technology can be applied to promote green productivity and its reflection in attaining sustainable development. In addition to studying sustainability, which helps to reduce environmental impacts and increase green productivity, the research aims to demonstrate the knowledge bases for accounting for the costs of material flow and green productivity. It also studies the technology of accounting for the costs of material flow in achieving sustainable development and the role of green productivity in achieving sustainable development. According
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