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The cutting temperature in hard turning is extremely high, which reduces tool life, lowers machined-surface quality, and affects dimensional control. However, hard turning differs greatly from conventional turning in that the cutting process mainly happens at the tool-nose radius due to the extremely shallow depth of the cut. This paper provides a comprehensive and systematic analysis of this issue based on an evaluation of tool geometry in hard turning via finite element analysis (FEA) simulations and experiments. The effect of tool angles on cutting temperature in hard turning is analyzed. The impacts of cutting-edge angle, rake angle, inclination angle, and average local rake angle on the cutting temperature are investigated via central composite design (CCD). The simulated results and the empirically measured cutting temperature exhibit comparable patterns, with a minor 2% difference. Increasing the cutting-edge angle, negative rake angle and negative inclination angle enhances the local negative rake angles of the cutting-edge elements at the tool-nose radius involved in the cutting process. Notably, the most important component influencing cutting temperature in hard turning is the inclination angle, as opposed to normal turning, where the rake angle dominates the heat generation. Following this is the cutting-edge angle and the rake angle, which each contribute 40.75%, 32.39%, and 7.03%. These findings could enhance the application of the hard-turning technique by improving tool life and surface quality by focusing on optimizing the inclination angle.

Research on pancreatic cancer has transformed with the advent of organoid technology, providing a better platform that closely mimics cancer biology in vivo. This review highlights the critical advancements facilitated by pancreatic organoid models in understanding disease progression, evaluating therapeutic responses, and identifying biomarkers. These three-dimensional cultures enable the proper recapitulation of the cellular architecture and genetic makeup of the original tumors, providing insights into the complex molecular and cellular dynamics at various stages of pancreatic ductal adenocarcinoma (PDAC). We explore the applications of pancreatic organoids in dissecting the tumor microenvironment (TME); elucidating cancer progression, metastasis, and drug resistance mechanisms; and personalizing therapeutic strategies. By overcoming the limitations of traditional 2D cultures and animal models, the use of pancreatic organoids has significantly accelerated translational research, which is promising for improving diagnostic and therapeutic approaches in clinical settings, ultimately aiming to improve the outcomes of patients with pancreatic cancer. Pancreatic Organoids Transform Cancer Research and Treatment Pancreatic cancer is a challenging disease to study and treat. This article discusses how researchers have developed pancreatic organoids to better study this cancer. Organoids are created by growing cells in a specialized 3D matrix, allowing them to form structures that resemble tissues found in the body. This method is more effective than traditional 2D cultures because it better replicates the natural environment of the cells. Researchers use these organoids to study cancer progression, test new drugs, and understand genetic changes in tumors. They can be made from small tissue samples, making them useful for studying advanced cancer stages where tissue is scarce. The findings from organoid studies help identify potential new treatments and improve our understanding of pancreatic cancer biology. In conclusion, pancreatic organoids offer a promising tool for advancing cancer research and developing personalized treatments. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

Background Organisational culture (OC) has increasingly become a crucial factor in defining healthcare practice and management. However, there has been little research validating and adapting OCAI (organisational culture assessment instrument) to assess OC in healthcare settings in developing countries, including Vietnam. The purpose of this study is to validate the OCAI in a hospital setting using key psychometric tests and confirmatory factor analysis (CFA). Methods This is a cross-sectional study. Self-administered structured questionnaire was completed by 566 health professionals from a Vietnamese national general hospital, the General Hospital of Quang Nam province. The psychometric tests and CFA were utilized to detect internal reliability and construct validity of the instrument. Results The Cronbach’s alpha coefficients (α-reliability statistic) ranged from 0.6 to 0.8. In current culture, the coefficient was 0.80 for clan and 0.60 for adhocracy, hierarchy and market dimension, while in expected culture, the coefficient for clan, adhocracy, hierarchy, and market dimension was 0.70, 0.70, 0.70 and 0.60, respectively. The CFA indicated that most factor loading coefficients were of moderate values ranging from 0.30 to 0.60 in both current and expected culture model. These models are of marginal good fit. Conclusions The study findings suggest that the OCAI be of fairly good reliability and construct validity in measuring four types of organisational culture in healthcare setting in resource-constrained countries such as Vietnam. This result is a first step towards developing a valid Vietnamese version of the OCAI which can also provide a strong case for future research in the field of measuring and managing organisational culture.

The construction industry remains one of the most hazardous work environments, with a fatality rate of 25.6 per 100,000 workers, significantly exceeding the average across all industries. PPE compliance is crucial for worker safety, yet monitoring adherence remains challenging in dynamic construction environments. This paper presents an automated PPE detection system utilizing an ensemble deep learning models to enhance workplace safety monitoring. Our approach combines three advanced architectures with Yolov11, RTDETRv2, and HyperYolo. The individual model predictions are integrated using WBF to improve detection robustness. We evaluate our system on a comprehensive dataset of 4,135 professionally annotated images encompassing critical PPE categories including hard hats, safety vests, protective gloves, and safety boots, along with their corresponding absence classes. The proposed ensemble achieves superior performance with a precision of 0.765, recall of 0.735, mAP@50 of 0.760, and mAP@50:95 of 0.440, outperforming individual models across all evaluation metrics. The results demonstrate the effectiveness of multi-model fusion for automated PPE detection. This research contributes to the advancement of intelligent safety systems that can significantly reduce workplace injuries and fatalities through automated PPE compliance verification.

To analyze hard turning performance characteristics, a new mathematical model was developed for the hard turning process, and cutting force (CF), another important response for cutting machining, was also studied in the present work. The analysis of the mathematical model and experimental results revealed that thrust force (Fy) was the largest, followed by tangential force (Fz) and feed force (Fx). The resultant CF was most influenced by inclination angle (IA) with 25.02%, followed by rake angle (RA) (14.26%) and cutting edge angle (CEA) (10.04%). Increasing CEA changed the position of cutting on the tool-nose radius and increased local negative RA and correspondingly local clearance angle (CA). Meanwhile, increasing negative RA and IA resulted in larger local negative RA and CA. Moreover, local RA and local CA were the main geometric factors affecting surface roughness (SR), tool wear (TW), and CF. Increasing local negative RA resulted in higher SR and CF. In contrast, increasing local CA resulted in lower SR, TW, and CF. Under specific conditions, the positive effects of the local CA overcame the negative effects of the local negative RA, leading to a simultaneous decrease in SR and TW. The proposed novel mathematical model can be further applied to calculate local CF, cutting temperature, and TW for each cutting-edge element, to analyze and optimize the hard turning process.

Electrochemical carbon dioxide reduction reaction (CO2RR) offers a promising route to mitigate climate change while simultaneously enabling renewable energy storage and the sustainable production of value-added chemicals. A wide variety of CO2RR reactor designs have been developed, including both liquid-phase cells and gas-phase configurations. Among these, gas-phase systems, particularly flow-cell and membrane electrode assembly (MEA) designs, have become the primary focus of recent research due to their ability to overcome mass transport limitations and operate at high currents. While catalyst development has received considerable attention in advancing CO2RR performance, the role of membranes in these gas-phase electrolyzers has been less systematically reviewed. This article addresses that gap by critically examining the functions, advantages, and limitations of the major membrane classes used in CO2 electrolysis: anion exchange membranes, cation exchange membranes, bipolar membranes, and non-ion-exchange porous membranes within flow-cell and MEA configurations. We highlight how membrane properties influence local pH regulation, water management, crossover behavior, and overall reactor performance, while emphasizing that product identity is primarily catalyst-determined. By analyzing recent progress and remaining challenges, this review provides design insights for membrane selection and development toward efficient, stable, and scalable CO2 electrolysis systems.

This paper presents an enhanced compensation strategy for distributed generation (DG) systems to simultaneously achieve accurate power sharing and harmonics compensation at the point of common coupling (PCC). In the proposed control strategy, the output impedance is modified at the fundamental and harmonic frequencies to compensate for the line impedance mismatches among DG units, which results in accurate power sharing. In addition, load harmonic currents are effectively adjusted by the DG units to effectively compensate the PCC voltage harmonics. Additionally, the DG equivalent impedance is regulated adaptively to ensure accurate harmonic power sharing even in the presence of sudden load changes. Furthermore, a distributed communication network is adopted instead of a central controller to increase the reliability and stability of the microgrid system. The proposed control strategy is applied to a prototype microgrid system, and its effectiveness and reliability are experimentally validated.

Inaccurate reactive power sharing and voltage distortion at the point of common coupling (PCC) always exist in a parallel inverter system due to feeder impedance mismatches and nonlinear load disturbances. An enhanced inverter control scheme through an output impedance adjustment is proposed to address these issues. Inverter output impedance is regulated considering fundamental and harmonic frequencies, and accurate power sharing and improved PCC voltage quality are realized at the steady state. In addition, the compensation scheme is easily applied in multiple parallel inverters without any prior knowledge of the feeder impedance. Experimental results with three parallel inverters validate the feasibility of the proposed control scheme.

This study investigates the effects of supplemental carotenoid pigments on growth and color performance in bighead catfish (Clarias macrocephalus). Two experiments were undertaken to determine the appropriate types, feed duration, and dose of astaxanthin (As), canthaxanthin (Ca), and xanthophyll (Xa) pigments individually and in combination. In the first experiment, fish were fed with one control diet (basic diet), six experimental diets comprised of three diets of As, Ca, and Xa at a 100 mg/kg rate of supplementation, respectively, and three diets combinations of As + Ca, As + Xa, and Ca + Xa at a supplement rate of 50 mg + 50 mg/kg. The results showed no significant difference in weight gain (WG), specific growth rate (SGR), survival rate (SR), and feed conversion ratio of fish among treatments (p > 0.05) after 6 weeks. The L* (Lightness) and a* (redness) values in the Xa diet were significantly lower than other treatments, while b* (yellowness) was significantly higher than in the control and others treatments (p < 0.05). These values peaked after 4 weeks and remained stable until the end of the experiment. Consistently, the highest muscle carotenoid content (16.89 ± 0.60 mg/100 g) was found in the fish fed with the Xa diet. The Xa diet was selected for the second experiment. This experiment consisted of four Xa supplemented diets at rates of 25, 50, 75, and 100 mg/kg and a basal diet without any Xa supplementation. The results showed that there was no difference in the SGR or SR of fish fed various Xa levels (p > 0.05). Fish fed the Xa diet of 75 mg/kg were the most preferred by consumers for the natural “yellowness” of muscle. Thus, the results suggested that additional carotenoid pigments did not affect the growth performance of fish. Farmers and feed producers could utilize Xa at an optimal dose of 75 mg/kg to enhance color performance in the market size of bighead catfish for at least 4 weeks prior to harvest.

The main purpose of this study is to investigate the influence of tool geometry (cutting edge angle, rake angle, and inclination angle) and to optimize tool wear and surface roughness in hard turning of AISI 1055 (52HRC) hardened steel by using TiN coated mixed ceramic inserts. The results show that the inclination angle is the major factor affecting the tool wear and the surface roughness in hard turning. With the increase in negative rake and inclination angles, the tool wear decreases, and the surface roughness increases. However, the surface roughness will decrease when the inclination angle increases to overpass a certain limit. This is a new and significant point in the research of the hard turning process. From this result, the large negative inclination angle (λ = −10°) should be applied to reduce the surface roughness and the tool wear simultaneously. With the optimal cutting tool angles in the research, the hard machining process is improved remarkably with decreases of surface roughness and tool wear 8.3% and 41.3%, respectively in comparison with the standard tool angles. And the proposed tool-post design approach brings an effective method to change the tool insert angles using standard tool-holders to improve hard or other difficult-to-cut materials turning quality.