To extend the working life of products made of titanium alloy, it is necessary to improve the polishing method to diminish the remaining defects on the workpiece surface. The Halbach array-assisted magnetic abrasive particle polishing method for titanium alloy was employed in this work. The distribution of magnetic field strength was simulated and verified at first to learn the characteristics of the Halbach array used in this work. Then, the polishing performance of the polishing tool was studied by conducting the polishing test, which aimed to display the relationship between shear force and surface roughness with polishing time, and the surface morphology during polishing was also analyzed. Following the establishment of the response surface model, a study on the optimal polishing parameters was conducted to obtain the suitable parameters for maximum shear force and minimum surface roughness. The results show that the maximum shear force 6.11 N and minimum surface roughness Sa 88 nm can be attained, respectively, under the conditions of (1) polishing tool speed of 724.254 r·min-1, working gap of 0.5 mm, and abrasive particle size of 200 μm; and (2) polishing tool speed of 897.87 r·min-1, working gap of 0.52 mm, and abrasive particle size of 160 μm.

β-lactam antibiotics, extensively used worldwide, pose significant risks to human health and ecological safety due to their accumulation in the environment. Recent studies have demonstrated the efficacy of transition metal-activated sulfite systems, like Fe(Ⅲ)/HSO3-, in removing PPCPs from water. However, research on their capability to degrade β-lactam antibiotics remains sparse. This paper evaluates the degradation of 14 types of β-lactam antibiotics in Fe(Ⅲ)/HSO3- system and establishes a QSAR model correlating molecular descriptors with degradation rates using the MLR method. Using cefazolin as a case study, this research predicts degradation pathways through NPA charge and Fukui function analysis, corroborated by UPLC-MS product analysis. The investigation further explores the influence of variables such as HSO3- dosage, substrate concentration, Fe(Ⅲ) dosage, initial pH and the presence of common seen water matrices including humic acid and bicarbonate on the degradation efficiency. Optimal conditions for cefazolin degradation in Fe(Ⅲ)/HSO3- system were determined to be 93.3 μM HSO3-, 8.12 μM Fe(Ⅲ) and an initial pH of 3.61, under which the interaction of Fe(Ⅲ) dosage with initial pH was found to significantly affect the degradation efficiency. This study not only provides a novel degradation approach for β-lactam antibiotics but also expands the theoretical application horizon of the Fe(Ⅲ)/HSO3- system.

Chitosan, a biopolymer obtained from chitin, is known for its remarkable adsorption abilities for dyes, drugs, and fats, and its diverse array of antibacterial characteristics. This study explores the extraction and characterization of chitosan from the mycelium of Amanita phalloides. The moisture content, ash content, water binding capacity, fat binding capacity, and degree of deacetylation of the extracted chitosan were determined. The chitosan exhibited a high yield of 70%, crystallinity of 49.07%, a degree of deacetylation of 86%, and potent antimicrobial properties against both Gram-negative and Gram-positive bacteria. The study also examined the adsorption capabilities of chitosan to remove methylene blue (MB) dye by analysing specific factors like pH, reaction time, and MB concentration using the response surface model. The highest degree of MB dye removal was 91.6% at a pH of 6, a reaction time of around 60 min and an initial dye concentration of 16 ppm. This experimental design can be applied for chitosan adsorption of other organic compounds such as dyes, proteins, drugs, and fats.

Evaluating Behind Armor Blunt Trauma (BABT) is a critical step in preventing non-penetrating injuries in military personnel, which can result from the transfer of kinetic energy from projectiles impacting body armor. While the current NIJ Standard-0101.06 standard focuses on preventing excessive armor backface deformation, this standard does not account for the variability in impact location, thorax organ and tissue material properties, and injury thresholds in order to assess potential injury. To address this gap, Finite Element (FE) human body models (HBMs) have been employed to investigate variability in BABT impact conditions by recreating specific cases from survivor databases and generating injury risk curves. However, these deterministic analyses predominantly use models representing the 50th percentile male and do not investigate the uncertainty and variability inherent within the system, thus limiting the generalizability of investigating injury risk over a diverse military population. The DoD-funded I-PREDICT Future Naval Capability (FNC) introduces a probabilistic HBM, which considers uncertainty and variability in tissue material and failure properties, anthropometry, and external loading conditions. This study utilizes the I-PREDICT HBM for BABT simulations for three thoracic impact locations-liver, heart, and lower abdomen. A probabilistic analysis of tissue-level strains resulting from a BABT event is used to determine the probability of achieving a Military Combat Incapacitation Scale (MCIS) for organ-level injuries and the New Injury Severity Score (NISS) is employed for whole-body injury risk evaluations. Organ-level MCIS metrics show that impact at the heart can cause severe injuries to the heart and spleen, whereas impact to the liver can cause rib fractures and major lacerations in the liver. Impact at the lower abdomen can cause lacerations in the spleen. Simulation results indicate that, under current protection standards, the whole-body risk of injury varies between 6 and 98% based on impact location, with the impact at the heart being the most severe, followed by impact at the liver and the lower abdomen. These results suggest that the current body armor protection standards might result in severe injuries in specific locations, but no injuries in others.

Grape pomace is the main by-product obtained from wine production that is still enriched in bioactive compounds. Within a framework of waste/by-product reuse through a sustainable approach, various green methods were utilized in this work to recover anthocyanins from the pomace resulting from \"Sangiovese\" grape vinification. Ultrasound- and Microwave-Assisted Extractions (UAE and MAE) were coupled with the use of green solvents, such as acidified water, an ethanol/water mixture, and Natural Deep Eutectic Solvents (NaDES), and their efficacy was compared with that of a conventional method based on a methanol/acidified water mixture. The Total Anthocyanin Index ranged from 36.9 to 75.2 mg/g DW for UAE, and from 54.4 to 99.6 mg/g DW for MAE, while resulting in 47.1 mg/g DW for conventional extraction. A Design of Experiments (DoE) approach was applied to MAE, the most efficient technique. Temperature, time, and the solid-to-liquid ratio were set as X variables, while malvidin-3-O-glucoside content and antioxidant activity were used as response variables, measured by High-Performance Liquid Chromatography with Diode Array Detection (HPLC-DAD) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assay, respectively. The correlation between temperature and time and the antioxidant activity of the extract was positive, while it was found to be negative when considering malvidin-3-O-glucoside concentration as a response variable. Thus, the optimal conditions in temperature, time and solid-to-liquid ratio were different depending on the chosen variable. The results underline the importance of selecting an accurate response when using the response surface methodology approach.

The increasing level of O3 pollution in China significantly exacerbates the long-term O3 health damage, and an optimized health-oriented strategy for NOx and VOCs emission abatement is needed. Here, we developed an integrated evaluation and optimization system for the O3 control strategy by merging a response surface model for the O3-related mortality and an optimization module. Applying this system to the Yangtze River Delta (YRD), we evaluated driving factors for mortality changes from 2013 to 2017, quantified spatial and temporal O3-related mortality responses to precursor emission abatement, and optimized a health-oriented control strategy. Results indicate that insufficient NOx emission abatement combined with deficient VOCs control from 2013 to 2017 aggravated O3-related mortality, particularly during spring and autumn. Northern YRD should promote VOCs control due to higher VOC-limited characteristics, whereas fastening NOx emission abatement is more favorable in southern YRD. Moreover, promotion of NOx mitigation in late spring and summer and facilitating VOCs control in spring and autumn could further reduce O3-related mortality by nearly 10% compared to the control strategy without seasonal differences. These findings highlight that a spatially and temporally differentiated NOx and VOCs emission control strategy could gain more O3-related health benefits, offering valuable insights to regions with severe ozone pollution all over the world.

Microbial thermal inactivation in low moisture foods is challenging due to enhanced thermal resistance of microbes and low thermal conductivity of food matrices. In this study, we leveraged the body of previous work on this topic to model key experimental features that determine microbial thermal inactivation in low moisture foods. We identified 27 studies which contained 782 mean D-values and developed linear mixed-effect models to assess the effect of microorganism type, matrix structure and composition, water activity, temperature, and inoculation and recovery methods on cell death kinetics. Intraclass correlation statistics (I2) and conditional R2 values of the linear mixed effects models were: E. coli (R2-0.91, I2-83%), fungi (R2-0.88, I2-85%), L. monocytogenes (R2-0.84, I2-75%), Salmonella (R2-0.69, I2-46%). Finally, global response surface models (RSM) were developed to further study the non-linear effect of aw and temperature on inactivation. The fit of these models varied by organisms from R2 0.88 (E. coli) to 0.35 (fungi). Further dividing the Salmonella data into individual RSM models based on matrix structure improved model fit to R2 0.90 (paste-like products) and 0.48 (powder-like products). This indicates a negative relationship between data diversity and model performance.

Response surface models (RSMs) are a new trend in modern anesthesia. RSMs have demonstrated significant applicability in the field of anesthesia. However, the comparative analysis between RSMs and logistic regression (LR) in different surgeries remains relatively limited in the current literature. We hypothesized that using a total intravenous anesthesia (TIVA) technique with the response surface model (RSM) and logistic regression (LR) would predict the emergence from anesthesia in patients undergoing video-assisted thoracotomy surgery (VATS). This study aimed to prove that LR, like the RSM, can be used to improve patient safety and achieve enhanced recovery after surgery (ERAS). This was a prospective, observational study with data reanalysis. Twenty-nine patients (American Society of Anesthesiologists (ASA) class II and III) who underwent VATS for elective pulmonary or mediastinal surgery under TIVA were enrolled. We monitored the emergence from anesthesia, and the precise time point of regained response (RR) was noted. The influence of varying concentrations was examined and incorporated into both the RSM and LR. The receiver operating characteristic (ROC) curve area for Greco and LR models was 0.979 (confidence interval: 0.987 to 0.990) and 0.989 (confidence interval: 0.989 to 0.990), respectively. The two models had no significant differences in predicting the probability of regaining response. In conclusion, the LR model was effective and can be applied to patients undergoing VATS or other procedures of similar modalities. Furthermore, the RSM is significantly more sophisticated and has an accuracy similar to that of the LR model; however, the LR model is more accessible. Therefore, the LR model is a simpler tool for predicting arousal in patients undergoing VATS under TIVA with Remifentanil and Propofol.

Simultaneous contaminants of emerging concern (CECs) removal and wild microorganisms\' inactivation was evaluated by applying solar photoelectro-Fenton (SPEF) process in actual secondary effluent collected from a real municipal wastewater treatment plant (MWWTP). 20 L of a mixture of four CECs was used as model pollutants (200 μg/L of acetaminophen, caffeine, sulfamethazine, and sulfamethoxazole each one). The SPEF process was carried out on fully sunny days, at circumneutral pH using the complex Fe3+-EDDS, in a solar electrochemical - raceway pond reactor (SEC-RPR). Initially, the optimal conditions for CECs degradation were determined using a response surface model based on current density, iron complex concentration and Fe3+-EDDS addition time (to allow previous accumulation of H2O2) as model inputs. A current density of 24.6 mA/cm2, a Fe3+-EDDS complex concentration of 0.089 mM and 3.8 min of previous H2O2 accumulation were the resulting optimum conditions that were afterwards applied for the simultaneous degradation of the CECs synthetic mixture and wild microorganisms inactivation in actual secondary effluent. About 85% CECs removal and complete E. coli inactivation were achieved in 30 min, approximately, while E. faecalis and total coliforms could be inactivated under detection limit in 60 min and 75 min, respectively.

The synthesis of cationic polyacrylamides (CPAMs) with the desired cationic degree and molecular weight is essential for various industries, including wastewater treatment, mining, paper, cosmetic chemistry, and others. Previous studies have already demonstrated methods to optimize synthesis conditions to obtain high-molecular-weight CPAM emulsions and the effects of cationic degrees on flocculation processes. However, the optimization of input parameters to obtain CPAMs with the desired cationic degrees has not been discussed. Traditional optimization methods are time-consuming and costly when it comes to on-site CPAM production because the input parameters of CPAM synthesis are optimized using single-factor experiments. In this study, we utilized the response surface methodology to optimize the synthesis conditions, specifically the monomer concentration, the content of the cationic monomer, and the content of the initiator, to obtain CPAMs with the desired cationic degrees. This approach overcomes the drawbacks of traditional optimization methods. We successfully synthesized three CPAM emulsions with a wide range of cationic degrees: low (21.85%), medium (40.25%), and high (71.17%) levels of cationic degree. The optimized conditions for these CPAMs were as follows: monomer concentration of 25%, content of monomer cation of 22.5%, 44.41%, and 77.61%, respectively, and initiator content of 0.475%, 0.48%, and 0.59%, respectively. The developed models can be utilized to quickly optimize conditions for synthesizing CPAM emulsions with different cationic degrees to meet the demands of wastewater treatment applications. The synthesized CPAM products performed effectively in wastewater treatment, with the treated wastewater meeting the technical regulation parameters. 1H-NMR, FTIR, SEM, BET, dynamic light scattering, and gel permeation chromatography were employed to confirm the structure and surface of the polymers.