The wave effect and the shyness phenomenon in Alnus acuminata (Kunth) are crown parameters rarely studied, but important in the quality of the wood of standing trees, therefore, a morphometric modeling of the crowns of Alnus acuminata in homogeneous forests in the Sierra Norte de Puebla was carried out. In 20 rectangular sites of 1,000 m², the following were evaluated: total height (TA), normal diameter (ND), crown diameter (CD) and crown cover (CC). The Kruskal Wallis test was applied to data that did not meet the assumption of normality; for those that did, analysis of variance (ANOVA) was used, with Tukey mean comparison tests (α ≤ 0.05). The forest value index was 14.99, so its two-dimensional structure is normal based on DN, AT and CC. Its average slenderness index was 93.52, which makes the tree not very stable to mechanical damage. The life-space index was 38.92, which is high indicating that trees with low intraspecific competition developed better. At the canopy level, a pattern following an upward, oscillatory and constant wave effect was observed in groups of 10 trees. The shyness phenomenon showed an average crack opening of 27.39 cm between canopies, so this phenomenon is well defined for the species. It is concluded that in the crowns of Alnus acuminata, the wave effect is observed as a consequence of inequality in the acquisition of resources, and one way to minimize this inequality is through the phenomenon of botanical shyness.

The main objective of the study was to examine factors that influence employee performance in general and, more specifically, in public enterprises. The research approach was qualitative, with an in-depth literature review and content analysis. The findings of the study reflect that some factors have a positive and some have a negative influence on employee performance. The study also shows a significant relationship between factors and employee performance, which in turn has a multiplier effect on employee development. Recommendations include the need to provide resources for employee training and development, and the strategic aims and objectives of public enterprises should be aligned with the training and development programs.

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.

A Detailed geophysical investigation was conducted on Knossos territory of Crete Island. Main scope was the detection of underground archaeological settlements. Geophysical prospecting applied by an experienced geophysical team. According to area dimensions in relation to geological and structural conditions, the team designed specific geophysical techniques, by adopted non-catastrophic methods. Three different types of geophysical techniques performed gradually. Geophysical investigation consisted of the application of geoelectric mapping and geomagnetic prospecting. Electric mapping focusses on recording soil resistance distribution. Geomagnetic survey was performed by using two different types of magnetometers. Firstly, recorded distribution of geomagnetic intensity and secondly alteration of vertical gradient. Measured stations laid along the south-north axis with intervals equal to one meter. Both magnetometers were adjusted on a quiet magnetic station. Values were stored in files readable by geophysical interpretation software in XYZ format. Oasis Montaj was adopted for interpretation of measured physical properties distribution. Interpretation results were illustrated as color scale maps. Further processing applied on magnetic measurements. Results are confirmed by overlaying results from three different techniques. Geoelectric mapping contributed to detection of a few archaeological targets. Most of them were recorded by geomagnetic technique. Total intensity aimed to report the existence of magnetized bodies. Vertical gradient detected subsurface targets with clearly geometrical characteristics.