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.

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.

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.

The boom in nanotechnology over the last three decades is undeniable. Responsible for this interest in nanomaterials are mainly the nanostructured forms of carbon, since historically they were the ones that inaugurated the study of nanomaterials with the discovery of fullerenes in 1985 and carbon nanotubes in 1991. Although a variety of techniques exist to produce these materials, chemical vapor deposition (CVD) is particularly valuable as it allows the production of a wide variety of carbon nanostructures, is versatile, scalable, easy to implement and relatively low cost. This review article highlights the importance of CVD and details its principles, operating conditions and parameters, as well as its main variants. A description of the technique used to produce fullerenes, nano-ceramics, carbon nanotubes, nanospheres, graphene and others is made, emphasizing the specific parameters for each synthesis.

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.