Cancer is the 3rd leading cause of death globally, and the countries with low-to-middle income account for most cancer cases. The current diagnostic tools, including imaging, molecular detection, and immune histochemistry (IHC), have intrinsic limitations, such as poor accuracy. However, researchers have been working to improve anti-cancer treatment using different drug delivery systems (DDS) to target tumor cells more precisely. Current advances, however, are enough to meet the growing call for more efficient drug delivery systems, but the adverse effects of these systems are a major problem. Nanorobots are typically controlled devices made up of nanometric component assemblies that can interact with and even diffuse the cellular membrane due to their small size, offering a direct channel to the cellular level. The nanorobots improve treatment efficiency by performing advanced biomedical therapies using minimally invasive operations. Chemotherapy’s harsh side effects and untargeted drug distribution necessitate new cancer treatment trials. The nanorobots are currently designed to recognize 12 different types of cancer cells. Nanorobots are an emerging field of nanotechnology with nanoscale dimensions and are predictable to work at an atomic, molecular, and cellular level. Nanorobots to date are under the line of investigation, but some primary molecular models of these medically programmable machines have been tested. This review on nanorobots presents the various aspects allied, i.e., introduction, history, ideal characteristics, approaches in nanorobots, basis for the development, tool kit recognition and retrieval from the body, and application considering diagnosis and treatment.

Idiomatic phrase are one of the lexical units.Many second-language learners showing great enthusiasm for using idiomatic expressions because of the rich cultural factors inherent in them and the vibrant,hilarious language that is close to life-like.However,  the idiomatic terms are so complicated that they frequently cause foreign learners to struggle with learning and comprehending Chinese.With its own advantages, the idea of lexical chunks has the potential to be a game changer in the teaching of idiomatic.

In most studies on hydroclimatic variability and trend, the notion of change point detection analysis of time series data has not been considered. Understanding the system is crucial for managing water resources sustainably in the future since it denotes a change in the status quo. If this happened, it is difficult to distinguish the time series data’s rising or falling tendencies in various areas when we look at the trend analysis alone. This study’s primary goal was to describe, quantify, and confirm the homogeneity and change point detection of hydroclimatic variables, including mean annual, seasonal, and monthly rainfall, air temperature, and streamflow. The method was employed using the four-homogeneity test, i.e., Pettitt’s test, Buishand’s test, standard normal homogeneity test, and von Neumann ratio test at 5% significance level. In order to choose the homogenous stations, the test outputs were divided into three categories: “useful”, “doubtful”, and “suspect”. The results showed that most of the stations for annual rainfall and air temperature were homogenous. It is found that 68.8% and 56.2% of the air temperature and rainfall stations respectively, were classified as useful. Whereas, the streamflow stations were classified 100% as useful. Overall, the change point detection analyses timings were found at monthly, seasonal, and annual time scales. In the rainfall time series, no annual change points were detected. In the air temperature time series except at Edagahamus station, all stations experienced an increasing change point while the streamflow time series experienced a decreasing change point except at Agulai and Genfel hydro stations. While alterations in streamflow time series without a noticeable change in rainfall time series recommend the change is caused by variables besides rainfall. Most probably the observed abrupt alterations in streamflow could result from alterations in catchment characteristics like the subbasin’s land use and cover. These research findings offered important details on the homogeneity and change point detection of the research area’s air temperature, rainfall, and streamflow necessary for the planers, decision-makers, hydrologists, and engineers for a better water allocation strategy, impact assessment and trend analyses.

Recent research efforts have increasingly concentrated on creating innovative biomaterials to improve bone tissue engineering techniques. Among these, hybrid nanomaterials stand out as a promising category of biomaterials. In this study, we present a straightforward, cost-efficient, and optimized hydrothermal synthesis method to produce high-purity Ta-doped potassium titanate nanofibers. Morphological characterizations revealed that Ta-doping maintained the native crystal structure of potassium titanate, highlighting its exciting potential in bone tissue engineering.

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.

This paper is devoted to the determination of the dispersive component of the surface energy of two boron materials such as h-BN and BPO₄ surfaces by using the inverse gas chromatography (IGC) at infinite dilution. The specific interactions and Lewis’s acid-base parameters of these materials were calculated on the light of the new thermal model concerning the dependency of the surface area of organic molecules on the temperature, and by using also the classical methods of the inverse gas chromatography as well as the different molecular models such as Van der Waals, Redlich-Kwong, Kiselev, geometric, Gray, spherical, cylindrical and Hamieh models. It was proved that h-BN surface exhibits higher dispersive surface energy than BPO₄ material.

The specific properties of interaction of the two boron materials were determined. The results obtained by using the new thermal model taking into account the effect of the temperature on the surface area of molecules, proved that the classical IGC methods, gave inaccurate values of the specific parameters and Lewis’s acid base constants of the solid surfaces. The use of the thermal model allowed to conclude that h-BN surface has a Lewis basicity twice stronger than its acidity, whereas, BPO₄ surface presents an amphoteric character.