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Simple Summary: This study compares 3D printing-guided maxillectomy with conventional maxillectomy in terms of surgical precision and oncological outcomes in head and neck cancer patients. A retrospective analysis of 42 patients (16 in the 3D printing-guided group, 26 in the conventional group) was conducted, comparing demographics, tumor characteristics, and oncologic outcomes. The 3D printing-guided group showed slightly higher rates of negative resection margins (81.3% vs. 76.9%) and trends toward superior 5-year local recurrence-free survival (87.5% vs. 58.7%) and overall survival (84.4% vs. 70.1%), although differences were not statistically significant. Three-dimensional printing-guided maxillectomy demonstrates potential improvements in surgical precision and local control, warranting further validation with larger studies. Background: This study evaluates the impact of three-dimensional (3D) printing-guided maxillectomy compared with conventional maxillectomy on surgical precision and oncological outcomes in patients with head and neck cancer. Materials and Methods: A retrospective analysis was conducted on 42 patients undergoing maxillectomy (16 in a 3D printing-guided group and 26 in a conventional group). Patient demographics, tumor characteristics, and outcomes were compared. Survival outcomes were analyzed using the Kaplan–Meier method. Results: The 3D printing group showed higher rates of negative resection margins (81.3% vs. 76.9%) compared with the conventional group and a trend toward improved 5-year local recurrence-free survival (87.5% vs. 58.7%, respectively) and overall survival (84.4% vs. 70.1%, respectively). However, the differences were not statistically significant. Conclusions: Maxillectomy guided by 3D printing may offer enhanced surgical precision and improved local control in patients undergoing head and neck cancer surgeries. Further research with larger cohorts is necessary to confirm these findings. [ABSTRACT FROM AUTHOR]

Pressure differences in the envelope of a building result in leakage airflow (i.e., the unintended flow of air). This can lead to increased building heating and cooling energy, decreased thermal comfort for occupants, and the spread of moisture. To address this problem, it is necessary to know the leakage airflow in a building. Generally, the leakage airflow in a building is calculated by determining the leakage function through fan pressurization methods, such as the blower door test, and substituting the pressure difference measured by the pressure sensor. However, it is difficult to install continuous pressure sensors in an operating building. Therefore, this study proposes a method to utilize the supply and return airflow of an air conditioning system to predict the variation in the leakage airflow with changing indoor and outdoor airflow, and the efficacy of this approach was verified through experiments. The experiment measured the indoor and outdoor pressure difference of the building with a change in the speed of the supply and return fans and the opening rate of the variable air volume (VAV) damper. As a result of the experiment, the indoor–outdoor pressure difference is proportional to the difference between the indoor supply airflow and the ventilation airflow. In addition, the relationship between the pressure difference and the leakage airflow was derived through the pressurization/decompression method using an air handler, and the leakage airflow from the pressure difference generated by the operation of the air conditioning system was calculated. Lastly, the relationship between the supply and return airflow difference and the leakage airflow was derived based on the experimental results, and the leakage airflow was predicted based on the relationship. [ABSTRACT FROM AUTHOR]

The pressure difference in buildings causes indoor and outdoor airflow, significantly impacting the indoor thermal environment and building energy consumption due to the introduction of outdoor air. The pressure difference in buildings is highly variable, influenced by outdoor wind speed, indoor–outdoor temperature differences, and heating, ventilating and air conditioning (HVAC) system operation, making it difficult to consider this factor during general HVAC system operation, potentially leading to an imbalance in indoor and outdoor pressure differences. Therefore, this study proposes an appropriate operation strategy for HVAC system return fans considering indoor–outdoor pressure differences. The proposed strategy involves adjusting the return fan airflow to maintain a constant indoor airflow balance, thereby controlling the indoor–outdoor pressure difference, satisfying the indoor thermal environment, and reducing HVAC system energy consumption. To evaluate the proposed strategy, dynamic simulations using TRNSYS and TRNFLOW were utilized, targeting one floor of an office building equipped with a variable air volume (VAV) system. The evaluation results showed that the maximum pressure difference decreased from −142 Pa to −18 Pa compared to the existing strategy, and the total energy consumption of the HVAC system was reduced by 29%, highlighting the importance of considering pressure differences during HVAC system operation. [ABSTRACT FROM AUTHOR]

The purpose of this study is to propose a control method that optimizes the set point of the variable air volume (VAV) terminal unit using real-time prediction model of indoor thermal and air environment and energy consumption. Indoor thermal environment and air environment are predicted through indoor load and carbon dioxide (CO2) concentration. A prediction model was developed through operation data of the VAV terminal unit by artificial neural network (ANN) algorithm. The developed prediction model was used for real-time set point control of the VAV terminal unit. The optimal control of VAV terminal unit can be expressed in 3 step. First, it predicts the current indoor load and CO2 concentration. Second, all supply temperatures and supply air flow rate that can be provided in the predicted condition are repeatedly simulated. Finally, the set point of the minimum energy consumption is applied to the control. The evaluation of the proposed control method was compared with the dual maximum control logic. Comparative evaluation was performed using TRNSYS. It was confirmed that the proposed control method reduced the reheat coil energy consumption by about 20% and the air supply fan energy consumption by about 17% compared to the existing control method.

Cinnamomum cassia (cassia) is a tropical aromatic evergreen tree of the Lauraceae family well known for its fragrance and spicy flavor and widely used in Asian traditional medicine. It has recently garnered attention for its diverse potential health benefits, including anti-inflammatory, anti-cancer, and anti-diabetic properties. However, the gastroprotective effect of C. cassia, particularly against ethanol-induced gastric damage, remains unclear. We investigated the potential gastroprotective property of C. cassia and the underlying mechanisms of action in a rat model of ethanol-induced gastric injury. To assess its effectiveness, rats were fed C. cassia for a 14-day period prior to inducing gastric damage by oral administration of ethanol. Our results indicated that pre-treatment with C. cassia mitigated ethanol-induced gastric mucosal lesions and bleeding. Reduced gastric acid secretion and expression of acid secretion-linked receptors were also observed. Additionally, pretreatment with C. cassia led to decreased levels of inflammatory factors, including TNF-α, p-p65, and IκBα. Notably, C. cassia upregulated the expressions of HO1 and HSP90, with particular emphasis on the enhanced expression of PAS and MUC, the crucial gastric mucosa defense molecules. These findings suggest that C. cassia has protective effects on the gastric mucosa and can effectively reduce oxidative stress and inflammation. [ABSTRACT FROM AUTHOR]

Ground heat accumulation caused by imbalanced heating and cooling loads in a building can cause the heat-source temperature to increase as the operating age of a geothermal heat pump (GHP) system increases. An alternative system to improve upon this situation is the hybrid GHP system. This study reviews existing research on GHP systems and hybrid GHP systems, variable water flow (VWF) control, and coefficient of performance (COP) prediction. Generally, constant flow control is applied to the circulating pump to provide a flow rate according to the maximum load. The need for VWF control was identified because the hybrid GHP system is used mainly as a heating and cooling heat source system for partial loads rather than the entire building load. Previous studies on predicting the COPs of GHP systems developed prediction models by selecting input values based on mathematical models, collecting data through multiple measurement points, and utilizing data from production environments. The model can be limited by the field environment, and it is necessary to predict the COP using machine learning based on existing field monitoring data. [ABSTRACT FROM AUTHOR]