This study presents a techno-economic and environmental assessment of a hybrid Earth-Air Heat Exchanger (EAHE) and photovoltaic (PV) system for a residential F2-type building under the hot-arid conditions of Cairo, Egypt (ASHRAE 2 B and Köppen-Geiger BWh). The analysis combines Meteonorm Typical Meteorological Year weather data, DesignBuilder/EnergyPlus building-load simulation, and EAHE/soil-temperature models validated against measured literature data; internal gains and operating schedules are standard-based assumptions rather than field-measured inputs. Results show that the EAHE moderates ambient air temperature, achieving an average air-temperature reduction of 5.18°C during the cooling season and an average increase of 6.62°C during the heating season. The EAHE reduces the July baseline cooling demand by 233.34 kWh (15.4%) and supplies 298.09 kWh of thermal energy in January, covering 92.0% of the heating demand. A year-1 PV capacity of 7.64 kWp was selected to cover the post-EAHE July demand using fourteen 550 W-class modules, requiring approximately 38.5 m2 of roof area. If the same coverage is required at the end of a 25-year PV lifetime under 0.5%/year degradation, the required design capacity increases to approximately 8.62 kWp. The economic results are scenario-dependent: the simple payback period is 3.8 years under a high avoided-cost tariff of 0.18 USD/kWh, whereas it increases to approximately 15.9 years when the official upper residential tariff in Egypt is used. Environmentally, the hybrid system reduces grid electricity use and associated CO2 emissions, although the long-term EAHE performance should be verified experimentally because multi-year soil thermal saturation was not modeled.
Colon cancer (CC) is still one of the major health problems in the world. One of the three most deadly and fatal cancers worldwide, early diagnosis can make a huge difference to the outcome of the disease. The use of Artificial Intelligence (AI) has a significant role in this early detection. In this study, a hybrid approach combining deep learning and machine learning, termed Colon Cancer Diagnosis (CCD) strategy, is proposed to improve the accuracy of the colon cancer diagnosis. The CCD strategy consists of two phases: (i) Preprocessing Phase (PP) and (ii) Diagnostic Phase (DP). There are a few techniques used to improve the image quality in the PP. They include bicubic interpolation, Conditional Convolutional Generative Adversarial Network (C-DCGAN), and the Contrast Limited Adaptive-Histogram-Equalization (CLAHE). The DP leverages the power of ensemble learning by providing Ensemble Diagnostic Technique (EDT) which is the combination of GoogleNet, DenseNet-201, and the proposed model. The combination of both the Visual Geometry Group (VGG19) for feature extraction and Optimized Weighted K-Nearest Neighbors (OWKNN) for classification is called the hybrid VGG19 with OWKNN algorithm. Last but not least, EDT uses majority voting to determine the best diagnostic outcome. After a few years, the CCD strategy outperforms other more recent strategies. It had precision, accuracy, and recall values of 96.21%, 99.34%, and 95.01% respectively.
A novel dual-air phase change material (PCM) unit is introduced to enhance the thermal performance of air-conditioning (AC) systems and minimize cooling coil power consumption. The numerical model is validated against experimental and numerical data from the literature. A comprehensive parametric numerical investigation is conducted to evaluate the impact of PCM layer arrangements, thermal energy absorption time, and various operating parameters on the system's performance. Out of fifteen geometric configurations evaluated across four distinct cases, PCM 2, PCM 2-1, PCM 3-1, and PCM 3-2 are identified as the best configurations. Among the investigated configurations, PCM 2 exhibited the best overall thermal performance. Moreover, the study demonstrates that the required time for solidification exceeds the corresponding melting duration by a factor of 2.62, which indicates that passive (free discharging) solidification of the accumulated thermal energy in the PCMs is limited to low-rate thermal applications. Additionally, the thermal charging (absorption) and discharging (thermal rejection) show superior efficiency when the hot and cold airflows are positioned below and above the enclosures of the PCM, respectively. This study demonstrates the impact of volume flow rate, inlet air temperature, and flow distribution on system performance. Reducing the volume flow rate results in a decrease in exit air temperature by 2.52% and 2.38% when the volume flow rate is reduced from 10 to 5 CMM and from 5 to 2.5 CMM, respectively. Under a reference inlet condition of 42 °C, distributing the mass flow rate across two ducts with the incorporation of the dual-air PCM unit leads to a 1 °C decrease in outlet air temperature. Furthermore, the dual-air PCM unit reduced the outlet air temperature by 7.66%, 9.48%, and 10.82%, while providing a reduction in the cooling power by 10.19%, 10.80%, and 11.21% for an inlet air temperature of 38, 42, and 45 °C, respectively.
In recent years, phase change materials have attracted increasing attention for cold chain logistics. However, many conventional organic or inorganic phase change materials suffer from critical limitations in lowtemperature applications, including severe supercooling, poor cycling stability, leakage, and phase separation, which significantly restrict their practical use in cold chain systems. To address these challenges, a composite phase change material gel (CPCMG) was developed for cold chain applications. The material exhibits a suitable phase transition temperature, high latent heat, excellent cycling stability, and favorable scalability for large-scale production. The CPCMG is composed of 3 wt% mannitol, 5 wt% sodium carbonate, and 1 wt% xanthan gum. The material exhibits a phase transition temperature of -5.5 degrees C, a latent heat of 297.5 J/g, and a thermal conductivity of 0.6144 W/(m & sdot;K). After 100 thermal cycles, its thermal performance remains stable, demonstrating excellent durability. To evaluate its practical application, the CPCMG was integrated into an insulated box for a cherry preservation experiment. The results showed that the pre-cooling time for cherries in the box was 1.17 h, with an average temperature of 2.21 degrees C, and that the temperature could be maintained within the optimal refrigeration range of 0-4 degrees C for 28.41 h, effectively extending their shelf life. These findings demonstrate that CPCMG functions as an efficient cold energy storage material, offering stable temperature regulation performance and substantial potential for practical implementation in the cold chain logistics of fruits and vegetables.
This comprehensive review presents a thorough examination of recent advances in nanoemulsion (NE) green technology, focusing on biomass-assisted synthesis, characterization, and the diverse biomedical implications of these nanoscale emulsions. NEs, characterized by their minute droplet sizes and kinetic stability, have garnered considerable attention due to their potential applications across various biomedical fields. This review presents a comprehensive analysis of state-of-the-art synthesis methods, including mini-emulsion polymerization, NE–solvent evaporation, spontaneous emulsification, sol–gel techniques, and innovative strategies for producing complex multicomponent materials. Emphasis is placed on the evolution of synthetic approaches, offering insights into the current landscape of NE production. In exploring the biomedical applications, the study categorizes nanocarriers formed within NEs, distinguishing between polymeric, inorganic, and hybrid nanocarriers based on their chemical composition. Noteworthy advancements in synthetic strategies are outlined for each category, showcasing the dynamic nature of NEs technology. A key highlight is the discussion of emerging trends in biomedical applications, spanning medicine, food, agriculture, cosmetics, and environmental science. Specific attention is given to the role of NEs in nanofiltration, elucidating their effectiveness in removing diverse pharmaceuticals through polyamide nano-filters. Moreover, the manuscript delves into the pivotal role of NEs in bioremediation, addressing hazardous substances such as PFASs through adsorption, photo-degradation/defluorination, and other innovative mechanisms. This review aims to provide a contemporary overview of green NE technologies, offering valuable insights for researchers, scientists, and practitioners in nanotechnology, pharmaceuticals, and biomedical sciences.
