The power of Artificial Intelligence (AI) combined with the surgeons’ expertise leads to breakthroughs in surgical care, bringing new hope to patients. Utilizing deep learning-based computer vision techniques in surgical procedures will enhance the healthcare industry. Laparoscopic surgery holds excellent potential for computer vision due to the abundance of real-time laparoscopic recordings captured by digital cameras containing significant unexplored information. Furthermore, with computing power resources becoming increasingly accessible and Machine Learning methods expanding across various industries, the potential for AI in healthcare is vast. There are several objectives of AI’s contribution to laparoscopic surgery; one is an image guidance system to identify anatomical structures in real-time. However, few studies are concerned with intraoperative anatomy recognition in laparoscopic surgery. This study provides a comprehensive review of the current state-of-the-art semantic segmentation techniques, which can guide surgeons during laparoscopic procedures by identifying specific anatomical structures for dissection or avoiding hazardous areas. This review aims to enhance research in AI for surgery to guide innovations towards more successful experiments that can be applied in real-world clinical settings. This AI contribution could revolutionize the field of laparoscopic surgery and improve patient outcomes.

In order to replace conventional materials in the existing composite world, there has been a focus on adopting coir fibres, which are lightweight, adaptable, efficient, and have great mechanical qualities. This study describes the creation of environmentally responsible bio-composites with good mechanical characteristics that employ coir powder as a reinforcement, which has good interfacial integrity with an epoxy matrix. And these epoxy-coir composites supplemented with coir particles are predicted to function as a reliable substitute for traditional materials used in industrial applications. Here, untreated and alkali-treated coir fibres powder were employed as reinforcement, with epoxy resin serving as a matrix. An experimental investigation has been carried out to study the effect of coir powder reinforcement at different weight percentages (5 wt%, 10 wt%, 15 wt%, 20 wt%, 25 wt%, and 30 wt%). The morphological study, followed by a scanning electron microscope (SEM) and an optical microscope (OM), demonstrated that the powder and matrix had the strongest adhesion at 20 wt% coir powder-reinforced composite, with no voids, bubbles, or cracks. Based on the entire investigation, the polymer composite with 20 wt% reinforcement exhibited better mechanical qualities than the other combinations.

In this study, the effect of porogenic solvents on pore size distribution of the polycaprolactone (PCL) thin films was investigated. Five thin PCL films were prepared using the solvent-casting method. Chloroform, Methylene Chloride (MC) and three different compositions of MC/ Dimethylformamide (DMF) (80/20, 50/50 and 20/80) were used as solvents. Scanning Electron Microscopy (SEM) investigations were employed to study morphology and consequently the pore size distribution of the prepared films. The PCL films made by chloroform and MC as a solvent were completely non-porous. Whereas the other films (made by a combination of MC and DMF) showed both uni-modal and bi-modal pore size distributions.

The semi-arid is a climate characterized by precipitation that is. insufficient to maintain crops and where evaporation often exceeds rainfall. Vegetation is one of the most sensitive indicators of environmental changes understanding the patterns of biodiversity distribution and what influences them is a fundamental pre-requisite for effective conservation and sustainable utilization of biodiversity. In this study. our focus was on examining the vegetation diversity in the semi-arid region of Tebessa. which falls within the Eastern Saharan Atlas domain in North Africa’s semi-arid zone. Plants were sampled at 15 sites distributed across the study area. The quadrat method was used to conduct floral surveys. The sampling area of each sample was 100 square meters 10 m × 10 m (quadrat). Each quadrat was measured for species richness (number of species). abundance (number of individuals). and Richness generic (plant cover). Based on the floristic research. 48 species were found. classified into 21 families. with Asteraceae accounting for 34.69% of the species and Poaceae accounting for 14.28%.

Beta macrocarpa, Guss is an interesting species showing very low germination rates. The leading objectives of this work were to investigate the dormancy mechanism and to find methods to break dormancy in order to achieve rapid, uniform and high germination. Macro and micro-morphologic analyses were performed by stereo microscopy and scanning electron microscopy showed two fruit coats. The yellow external coat or persistent perianth coat (PPC) was accrescent with 5 erect segments contiguous to the operculum of the seed capsule. This coat forms spongy layers (50 to 300 µm thick) that could be eliminated manually. The narrow internal coat or pericarp or achene coat (AC) forms woody joined seed capsules, each presenting a pressed operculum that cannot be manually opened. This coat was not adherent to seeds and was composed of compressed cells (50 to 200 µm thick) which form pockets for salt cristal. Seeds were lentiform (1 to 2 mm diameter and 0.5 to 0.8 mm thick) and highly fragile. The embryo was whitish surrounded peripherally by the perisperm with two highly developed cotyledons and radical. Polyphenol concentrations in both coats showed that after 4 months of collection, total polyphenol concentrations were 4-fold higher in the pericarp than in the persistent perianth. However, after one year, this parameter decreases significantly in the pericarp, whereas, it increases to a larger extent in the perianth. Different germination tests indicated that the pericarp provides a chemical and a physical resistance to seed germination during the first 4 months of the experiment after collection. The chemical dormancy was released to higher levels of total polyphenol compounds that inhibited seed germination and seedling growth. However, the physical dormancy was associated with the hardness of this intern coat which caused a mechanical resistance to radicle emergence. After one year of storage, total polyphenol pericarp concentration decreased notably, and chemical resistance disappeared, whereas the physical one persisted. Consequently, one year of storage pericarp removal is sufficient to break this exogenous dormancy.

Implementing green retrofitting can save 50–90% of energy use in buildings built worldwide. Government policies in several developed countries have begun to increase the implementation of green retrofitting buildings in those countries, which must rise by up to 2.5% of the lifespan of buildings by 2030. By 2050, it is hoped that more than 85% of all buildings will have been retrofitted. The high costs of implementing green retrofitting amounting to 20% of the total initial construction costs, as well as the uncertainty of costs due to cost overruns are one of the main problems in achieving the implementation target in 2050. Therefore, increasing the accuracy of the costs of implementing green retrofitting is the best solution to overcome this. This research is limited to analyzing the factors that influence increasing the accuracy of green retrofitting costs based on WBS, BIM, and Information Systems. The results show that there are 10 factors affecting the cost accuracy of retrofitting or customizing high-rise office buildings, namely Energy Use Efficiency, Water Use Efficiency, Use of Environmentally Friendly Materials, Maintenance of Green Building Performance during the Use Period, Initial Survey, Project Information Documents, Cost Estimation Process, Resources, Legal, and Quantity Extraction applied. These factors are shown to increase the accuracy of green retrofitting costs.