Creating a crop type map is a dominant yet complicated model to produce. This study aims to determine the best model to identify the wheat crop in the Haridwar district, Uttarakhand, India, by presenting a novel approach using machine learning techniques for time series data derived from the Sentinel-2 satellite spanned from mid-November to April. The proposed methodology combines the Normalized Difference Vegetation Index (NDVI), satellite bands like red, green, blue, and NIR, feature extraction, and classification algorithms to capture crop growth's temporal dynamics effectively. Three models, Random Forest, Convolutional Neural Networks, and Support Vector Machine, were compared to obtain the start of season (SOS). It is validated and evaluated using the performance metrics. Further, Random Forest stood out as the best model statistically and spatially for phenology parameter extraction with the least RMSE value at 19 days. CNN and Random Forest models were used to classify wheat crops by combining SOS, blue, green, red, NIR bands, and NDVI. Random Forest produces a more accurate wheat map with an accuracy of 69% and 0.5 MeanIoU. It was observed that CNN is not able to distinguish between wheat and other crops. The result revealed that incorporating the Sentinel-2 satellite data bearing a high spatial and temporal resolution with supervised machine-learning models and crop phenology metrics can empower the crop type classification process.

The role of trace gases in the storage of heat in the atmosphere of the Earth and in the exchange of energy between the atmosphere and outer space is discussed. The molar heat capacities of the trace gases water vapor, carbon dioxide and methane are only slightly higher than those of nitrogen and oxygen. The contribution of trace gases carbon dioxide and methane to heat storage is negligible. Water vapor, with its higher concentration and conversion energies, contributes significantly to the heat storage in the atmosphere. Most of the heat in the Earth’s atmosphere is stored in nitrogen and oxygen, the main components of the atmosphere. The trace gases act as converters of infrared radiation into heat and vice versa. They are receivers and transmitters in the exchange of energy with outer space. The radiation towards space is favored compared to the reflection towards the surface of the Earth with increasing altitude by decreasing the density of the atmosphere and condensation of water vapor. Predictions of the development of the climate over a century by extrapolation are critically assessed.

This research aims to investigate the impact of knowledge-based human resource management (KBHRM) practices on organizational performance through the mediating role of quality and quantity of knowledge worker productivity (QQKWP). The data were collected from 325 employees working in different private universities of Pakistan by using convenience and purposive sampling techniques. The quantitative research technique was used to perform analysis on WarpPLS software. The result revealed that only knowledge-based recruiting practices have a positive and significant direct effect on organizational performance. While knowledge-based performance appraisal practices, training and development practices and compensation practices all were insignificant in this regard. However, through mediator QQKWP, the knowledge-based recruiting practices (KBRP), knowledge-based training and development (KBTD), and knowledge-based compensation practices (KBCP) all were positively and significantly influencing organizational performance but only knowledge-based performance appraisal (KBPA) was insignificant in this mediating relationship. Lastly, the current study provides useful insights into the knowledge management (KM) literature in the context of private higher educational institutes of developing countries like Pakistan. The future studies should consider the impact of KBHRM practices on knowledge workers’ productivity and firms’ performances in the context of public universities.

The study has formulated the objective of synthesizing the extent to which technological barriers intervene in the transparency and effectiveness of public management (PM). Methodologically, the study was of a fundamental or basic nature, with a systematic review design, the databases of Scopus (369), SciELO (2), Web of Science (184) were explored, after the review process a set of 22 articles was available. The registration was made in an Excel table where the main data of the articles were included. 32% of the articles selected for the analysis of the evidence are from the period 2020, 27% were from 2022 and 18% from the year 2023; as far as origin is concerned, 14% of the articles come from Peru and 9% from Australia, Brazil, South Korea, Spain and Indonesia. In summary, the study points out that government institutions are making progress in digitizing and improving the citizen experience through electronic services, but they face challenges in areas such as resource management, the low adoption of advanced technologies such as blockchain and artificial intelligence, as well as the lack of transparency in PM. Despite this, it is highlighted that e-government improves citizen satisfaction, and the need to invest in digital innovation, training and overcoming technological barriers to achieve an effective transformation in state administration and promote a more inclusive and advanced society is emphasized.

Conspiracy theories during Covid-19 pandemic spread worldwide, including in Indonesia. What political and religious factors explain their spread in Indonesia with particular reference to the DKI Jakarta province, its surrounding municipalities, and West Sumatera province? This study aimed to answer the questions. It employed a qualitative approach with multi-data collection methods, including those from media, documents, and interviews. The spread of Conspiracy theories benefited from the democratic system that promotes the freedom of information in using social media. First, the government officials initially spread conspiracy theories to satisfy people’s anxiety about the obscured Pandemic. However, they resulted in the government’s ambiguous, controversial, and reckless policies leading to people’s distrust of the government. Jokowi-Makruf Amien, political opponents capitalized on the government’s poor policies to spread conspiracy theories which partly discredited the Jokowi-Amien administration. Both government officials and the opposition capitalized on politics and religious teaching or supra-natural pretexts to posit their conspiracy theories.

Our study evaluated the effect of vanadium (V) on the behavior of Zinnia elegans “double variegated”. In this experiment, Zinnia plants grown in a greenhouse were fed with a nutrient solution and two concentrations of vanadium (0, 6, and 10 μm) applied four times during the experiment. The V at its levels of 6 µm and 10 µm increased plant length, number of inflorescences and fresh weight. We observed that during the development and appearance of flower buds, and flowering were earlier with the addition of 6 µm and 10 µm. During harvest the changes in size and shape were homogeneous with the control treatment. With the addition of 6 µm, flowers of different sizes were induced, with non-uniform petals, but with different shades of color. With 10 µm the shape of the petals, the distance between them and changes in the shades of the flowers were modified. The postharvest life for the flowers of the control treatment was shorter (15 days), the petals, anthers and floral disc at this time were observed in a poor condition. While 6 µm and 10 µm had a longer postharvest life (20 days), the flowers had a good presentation, their colors were more intense compared to the harvest stage. The application of this beneficial element contributed to the development and flowering of Zinnia in the greenhouse. It is suggested that future research be carried out on the accumulation and/or concentration of vanadium in the different stages of growth or its effect on the concentration of other nutrients.