Marine geological maps of the Campania region have been constructed both to a 1:25.000 and to a 1:10.000 scale in the frame of the research projects financed by the Italian National Geological Survey, focusing, in particular, on the Gulf of Naples (Southern Tyrrhenian Sea), a complex volcanic area where volcanic and sedimentary processes strongly interacted during the Late Quaternary and on the Cilento Promontory offshore. In this paper, the examples of the geological sheets n. 464 “Isola di Ischia” and n. 502 “Agropoli” have been studied. The integration of the geological maps with the seismo-stratigraphic setting of the study areas has also been performed based on the realization of interpreted seismic profiles, providing interesting data on the geological setting of the subsurface. The coastal geological sedimentation in the Ischia and Agropoli offshore has been studied in detail. The mapped geological units are represented by: i) the rocky units of the acoustic basement (volcanic and/or sedimentary); ii) the deposits of the littoral environment, including the deposits of submerged beach and the deposits of toe of coastal cliff; iii) the deposits of the inner shelf environment, including the inner shelf deposits and the bioclastic deposits; iv) the deposits of the outer shelf environment, including the clastic deposits and the bioclastic deposits; v) the lowstand system tract; vi) the Pleistocene relict marine units; vii) different volcanic units in Pleistocene age. The seismo-stratigraphic data, coupled with the sedimentological and environmental data provided by the geological maps, provided us with new insights on the geologic evolution of this area during the Late Quaternary.

This study aims to elucidate the digital transformation process in Tunisian companies, identify its driving factors, and explain its key success factors. We examine a sample of 70 companies across various economic sectors using a Multinomial Logistic regression to assess the impact of digital strategy, corporate culture, and leadership on digital transformation success. The dependent variable “digital maturity” is categorized into low, medium, and high, with medium serving as the reference category. The results indicate a significant and positive effect of digital strategy on digital transformation success. Leadership influences companies at a low level of digital maturity but does not significantly impact those at a high maturity level. Corporate culture does not significantly affect digital transformation. Digital strategy is crucial for the success of digital transformation in Tunisian companies, while leadership plays a role primarily at lower maturity levels. Corporate culture, however, does not significantly contribute to digital maturity. The study provides insights for Tunisian companies and policymakers to focus on developing robust digital strategies and leadership qualities to enhance digital transformation efforts. This research expands the theoretical base on digital transformation in the Tunisian context, identifying critical success factors and barriers, and confirming the significant role of digital strategy in successful digital transformations.

Water splitting, the process of converting water into hydrogen and oxygen gases, has garnered significant attention as a promising avenue for sustainable energy production. One area of focus has been the development of efficient and cost-effective catalysts for water splitting. Researchers have explored catalysts based on abundant and inexpensive materials such as nickel, iron, and cobalt, which have demonstrated improved performance and stability. These catalysts show promise for large-scale implementation and offer potential for reducing the reliance on expensive and scarce materials. Another avenue of research involves photoelectrochemical (PEC) cells, which utilize solar energy to drive the water-splitting reaction. Scientists have been working on designing novel materials, including metal oxides and semiconductors, to enhance light absorption and charge separation properties. These advancements in PEC technology aim to maximize the conversion of sunlight into chemical energy. Inspired by natural photosynthesis, artificial photosynthesis approaches have also gained traction. By integrating light-absorbing materials, catalysts, and membranes, these systems aim to mimic the complex processes of natural photosynthesis and produce hydrogen fuel from water. The development of efficient and stable artificial photosynthesis systems holds promise for sustainable and clean energy production. Tandem cells, which combine multiple light-absorbing materials with different bandgaps, have emerged as a strategy to enhance the efficiency of water-splitting systems. By capturing a broader range of the solar spectrum, tandem cells optimize light absorption and improve overall system performance. Lastly, advancements in electrocatalysis have played a critical role in water splitting. Researchers have focused on developing advanced electrocatalysts with high activity, selectivity, and stability for the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). These electrocatalysts contribute to overall water-splitting efficiency and pave the way for practical implementation.

Every plant is significantly important in tackling climate change, including Makila (Litsea angulata BI) an endemic wood species found in the forest of Moluccas Provinces. Therefore, this research aimed to examine the role of the Makila plant in tackling climate change by measuring biomass content using constructing an allometric equation. The method used was a destructive sampling, where 40 units of Makila plant at the sampling level were felled, and sorted according to root, stem, branch, rating, and leaf segments. Each segment was weighed both at wet and after drying, followed by a classical assumption test in data processing, and the formulation of an allometric equation. The regression model was examined for normality and suitability in predicting independent variables, ensuring there were no issues with multicollinearity, heteroscedasticity, and autocorrelation. The results yielded a multiple linear regression, namely: Y = −1131.146 + 684.799X₁ + 4.276X₂, where Y is biomass, X₁ is the diameter, and X₂ is the tree height. Based on the results of the t-test: variable X₁ partially affected Y while variable X₂ partially had no effect on Y. The F-test indicated that variables X₁ and X₂ jointly affected Y with R Square: 0.919 or 91.9% and the rest was influenced by other unexplored factors. To simplify biomass prediction and field measurement, a regression equation that used only 1 independent variable, namely tree diameter, was used for the experiment. Allometric equation only used 1 variable, Y = −1,084,626 + 675,090X₁, where X₁ = tree diameter, Y = Total biomass with R = 0.957, and R² = 0.915. Considering the potential for time, cost, and energy savings, as well as ease of measurement in the field, the biomass of young Makila trees was simply predicted by measuring the tree diameter and avoiding the height. This method used the strong relationship between biomass, plant diameter, and height to facilitate the estimation of biomass content accurately by entering the results of field measurements.

Puppetry is one of the traditional folk art forms with a long history in China.Puppetry is one of the traditional folk art forms with a long history in China. After it was transmitted to the Gaozhou Prefecture of Guangdong by the Fujian Zhangzhou Puppet Show during the Wanli period of the Ming Dynasty, it gradually took root in the local culture of Guangdong, and the Gaozhou Puppet Theatre was born as a result. Under the radiant influence of Cantonese Opera, the number one theatre in Lingnan, in the western part of Guangdong, the Gaozhou Puppet Theatre has been passed down through the generations, and has used the Cantonese Opera cantata, an element of Cantonese Opera that is the essence of the art, in its unique puppetry accent. Nowadays, when many "non-heritage" cultures are facing difficulties in inheritance and development, it is especially crucial for the puppet theatre of Gaozhou to be able to use the elements of Cantonese Opera's singing in the new era, so as to make Gaozhou Puppet Theatre a new life and make the public appreciate the art again by incorporating the elements of Cantonese Opera's singing.

To save patients’ lives, it is important to go for an early diagnosis of intracranial hemorrhage (ICH). For diagnosing ICH, the widely used method is non-contrast computed tomography (NCCT). It has fast acquisition and availability in medical emergency facilities. To predict hematoma progression and mortality, it is important to estimate the volume of intracranial hemorrhage. Radiologists can manually delineate the ICH region to estimate the hematoma volume. This process takes time and undergoes inter-rater variability. In this research paper, we develop and discuss a fine segmentation model and a coarse model for intracranial hemorrhage segmentations. Basically, two different models are discussed for intracranial hemorrhage segmentation. We trained a 2DDensNet in the first model for coarse segmentation and cascaded the coarse segmentation mask output in the fine segmentation model along with input training samples. A nnUNet model is trained in the second fine stage and will use the segmentation labels of the coarse model with true labels for intracranial hemorrhage segmentation. An optimal performance for intracranial hemorrhage segmentation solution is obtained.