The paper examines the underlying science determining the performance of hybrid engines. It scrutinizes a full range of orthodox gasoline engine performance data, drawn from two sources, and how it would be modified by hybrid gasoline vehicle engine operation. The most significant change would be the elimination of the negative consequences of urban congestion, stop-start, and engine driving, in favour of a hybrid electric motor drive. At intermediate speeds there can be other instances where electric motors might give a more efficient drive than an engine. Hybrid operation is scrutinised and the electrical losses estimated. There also remains scope for improvements in engine combustion. 

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.

Due to the short cost-effective heat transportation distance, the existing geothermal heating technologies cannot be used to develop deep hydrothermal-type geothermal fields situated far away from urban areas. To solve the problem, a new multi-energy source coupling a low-temperature sustainable central heating system with a multifunctional relay energy station is put forward. As for the proposed central heating system, a compression heat pump integrated with a heat exchanger in the heating substation and a gas-fired water/lithium bromide single-effect absorption heat pump in the multifunctional relay energy station are used to lower the return temperature of the primary network step by step. The proposed central heating system is analyzed using thermodynamics and economics, and matching relationships between the design temperature of the return water and the main line length of the primary network are discussed. The studied results indicate that, as for the proposed central heating system, the cost-effective main line length of the primary network can approach 33.8 km, and the optimal design return temperature of the primary network is 23 ℃. Besides, the annual coefficient of performance and annual energy efficiency of the proposed central heating system are about 3.01 and 42.7%, respectively.

Remote sensing technologies have revolutionized forestry analysis by providing valuable information about forest ecosystems on a large scale. This review article explores the latest advancements in remote sensing tools that leverage optical, thermal, RADAR, and LiDAR data, along with state-of-the-art methods of data processing and analysis. We investigate how these tools, combined with artificial intelligence (AI) techniques and cloud-computing facilities, enhance the analytical outreach and offer new insights in the fields of remote sensing and forestry disciplines. The article aims to provide a comprehensive overview of these advancements, discuss their potential applications, and highlight the challenges and future directions. Through this examination, we demonstrate the immense potential of integrating remote sensing and AI to revolutionize forest management and conservation practices.

Heat conduction theory stipulates that two thermo-physical properties of materials: the thermal conductivity “k” and the thermal diffusivity “α” influence the temperature evolution in regular and irregular bodies as a response to various cooling/heating conditions. The traditional statement involving the two thermo-physical properties is examined at length in the present study for the case of a semi-infinite region. The primary objective of the present study is to investigate the influence of the less known thermo-physical property called the thermal effusivity “e” on the incipient surface temperature rise in a semi-infinite body affected by uniform surface heat flux. The secondary objective of the study is to identify a key figure of merit named the dimensionless threshold time that separates the incipient temperature elevation in a semi-infinite region from the incipient temperature elevation in a large wall of finite thickness under the same uniform surface heat flux. The outcome of the methodical analysis suggests that the accurate estimate for the dimensionless threshold time τ_th in the semi-infinite region should be 0.10.

Hybrid nanofluids have several potential applications in various industries, including electronics cooling, automotive cooling systems, aerospace engineering, and biomedical applications. The primary goal of the study is to provide more information about the characteristics of a steady and incompressible stream of a hybrid nanofluid flowing over a thin, inclined needle. This fluid consists of two types of nanoparticles: non-magnetic nanoparticles (aluminium oxide) and magnetic nanoparticles (ferrous oxide). The base fluid for this nanofluid is a mixture of water and ethylene glycol in a 50:50 ratio. The effects of inclined magnetic fields and joule heating on the hybrid nanofluid flow are considered. The Runge-Kutta fourth-order method is used to numerically solve the partial differential equations and governing equations, which are then converted into ordinary differential equations using similarity transformations. Natural convection refers to the fluid flow that arises due to buoyancy forces caused by temperature differences in a fluid. In the context of an inclined needle, the shape and orientation of the needle have significantly affected the flow patterns and heat transfer characteristics of the nanofluid. These analyses protest that raising the magnetic parameter results in an increase in the hybrid nanofluid thermal profile under slip circumstances. Utilizing the potential of hybrid nanofluids in a variety of technical applications, such as energy systems, biomedicine, and thermal management, requires an understanding of and ability to manipulate these effects.