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Although chip morphology changes according to the machining method and related cutting parameters, chip formation affects the quality of the machined surface. In this context, it is very important to understand the relationship between chip morphology and surface quality, especially in materials that are difficult to machine. In the presented study, the changes in chip morphology, surface morphology, and surface quality criteria (Ra and Rz) that occurred during the milling of precipitation-hardened steel in different cutting environments were analyzed. Milling experiments were carried out in dry, MQL (minimum quantity lubrication), nano-MQL (graphene), nano-MQL (hBN), Cryo, and Cryo-MQL environments using TiAlN-coated inserts and three different cutting speeds and feed rates. While the highest values in terms of Ra and Rz were measured in dry machining, the minimum values were obtained in a nano-MQL (hBN) cutting environment. Due to the lubrication and low friction provided by the MQL cutting environment, chips were formed in thinner segmented forms. This formation reduced the chip curve radius and thus provided a more stable surface morphology. On the other hand, Cryo-ambient gas could not effectively leak into the cutting zone due to the intermittent cutting process, but it increased the brittleness of the chips with the cooling effect and provided a similar surface morphology. The values of minimum Ra and Rz were obtained as 0.304 mm and 1.825 mm, respectively, at a 60 m/min cutting speed and 0.04 mm/rev feed. Consequently, the use of nano-MQL cutting medium is seriously recommended in terms of surface quality in milling operations of difficult-to-machine materials.

This study examines algorithmic bias in visual outputs generated by contemporary generative artificial intelligence models such as DALL-E 3, Midjourney, and Stable Diffusion. Using a qualitative research design, 450 images were analyzed through content analysis, semiotic interpretation, and critical discourse analysis. Findings reveal that these models systematically reproduce social hierarchies related to gender, race, class, and cultural identity. Leadership and professional roles are predominantly represented by male and Westernlooking figures, while women and non-Western identities are frequently associated with stereotypical or secondary roles. The study also reveals that visual output is shaped by imbalanced training datasets and culturally dominant aesthetic norms, demonstrating that generative Al is not neutral but exists within broader sociotechnical power structures. The research emphasizes the need for more inclusive data practices, transparent model development, and enhanced algorithmic literacy to reduce representational inequalities in Al-generated visuals.

This study aims to optimize and model the resultant cutting force (Fr) and surface roughness (Ra) in the cleaner milling of PH13-8Mo stainless steel, which is extremely difficult to machine due to its high technical properties. The impacts of dry, minimal quantity lubrication (MQL) and cryogenic (Cryo) environments on the Fr and Ra were investigated in the up-milling of PH13-8Mo. The experiments were done using TiAlN-coated inserts at varying cutting speeds and feed rates. Control factors were optimized simultaneously with Taguchi-based grey relational analysis (TGRA) to minimize Fr and Ra. Predictive models of Fr and Ra were developed by the response surface method. An average of 20.98% and 19.86% improvement in Ra was achieved in the MQL and cryo environments, respectively. Increased sticking, chipping and microcracks in the insert due to cryogenic cooling increased Fr and Ra. Optimum factors were found as an MQL environment, a 60 m/min cutting speed and a 0.04 mm/rev feed rate with TGRA. The high correlations of the developed mathematical models showed that the models were reliable. Thus, significant support will be provided to sustainable machining with the industrial use of data obtained for machinability indicators in milling PH13-8Mo steel.

Due to extensive distribution and huge demand of energy efficient processes, the energy-saving of machining processes draws more and more attention, and a significant variety of methods have evolved to prognosis or optimise the energy consumption in machining operations. Similarly, the estimation of power consumption-cutting conditions relationships is of great importance for optimizing processing costs and for cleaner machining. Compared to traditional methods, machine learning (ML) approach is one of the effective analysis options to model machinability indicators such as cutting force, tool wear, power consumption and surface quality. In this study, PH13-8Mo stainless steel was machined with coated carbide inserts using primarily Dry, MQL, nano-Graphene + MQL, nano-hBN + MQL, Cryo, Cryo + MQL cutting environments. Power consumption and its signals during milling were measured and different machine learning models were applied to estimate the Pc. To develop the Pc model based on the ML algorithm, 70% of the power consumption data is reserved for training and 30% for testing. In all cutting environments, power consumption increased by an average of 3.14% as feed speed increased. The reduction in Pc compared to the dry cutting was calculated as an average of 2.2%, 3.17%, 2.57%, 4.88% and 5.45% for MQL, nano-Graphen + MQL, nano-hBN + MQL, Cryo, Cryo + MQL, respectively. It is seen that the developed prediction model can reflect the power consumption-parameter relationships at high accuracy.

Background The ability to predict the presence of lymph node metastasis has gained significant importance in recent years due to changes in treatment strategies. Ensuring the absence of lymph node metastasis is crucial in the management of early gastric cancer. This consideration can help avoid radical treatments and facilitate organ-sparing approaches. This study aimed to retrospectively evaluate early gastric adenocarcinoma (T1a-b) cases treated with radical surgery and identify the factors that affect lymph node metastasis. Methods A retrospective analysis was performed on 360 patients who underwent surgery for gastric adenocarcinoma were reviewed, and 41 patients diagnosed with early gastric cancer were included in the study. The relationship between patient age, gender, tumor stage, tumor size, tumor location, histological subtype, lymphovascular invasion, perineural invasion, ulceration, tumor-infiltrating lymphocytes, and lymph node metastases was analyzed. A cumulative risk score was developed using significant predictors to stratify patients into risk groups. Results The study cohort consisted of 41 patients, with a mean age of 63 years and 66% male. Notably, none of the 14 patients with T1a exhibited lymph node metastasis, whereas 10 of 27 (37%) patients with T1b presented with lymph node metastasis. Univariate analysis revealed that tumor stage ( p  = 0.009), tumor differentiation ( p  = 0.043), and lymphovascular invasion ( p  = 0.006) were significant predictors of lymph node metastasis. Multivariate analysis identified a significant association between lymphovascular invasion ( p  = 0.024) and tumor size ( p  = 0.05) with lymph node metastasis. The proposed risk scoring system effectively stratified patients into low, intermediate, and high-risk groups. Conclusion Examination of radical surgical specimens suggests that organ-preserving methods based on expanded ESD criteria could be a viable option for our population. Tumor stage, histological subtype, tumor size, and lymphovascular invasion were identified as factors influencing the incidence of lymph node metastasis, with tumor stage and lymphovascular invasion emerging as primary determinants. The exploratory scoring model may aid in risk-based clinical decision-making, particularly in selecting candidates for non-surgical treatment.

In the aviation and structural industries, the requirement of smooth holes is an important safety problem. Since holes are a part of the joints made with fasteners, they affect the fatigue strength of the structure. Therefore, it is necessary to be very selective in terms of cutting parameters and cutting tools, especially in drilling metal/composite or composite/metal stacked materials. In this context, cutting conditions in conventional machining methods should be optimized or novel machining methods should be applied. In this context, this study minimized the limitations in machining of carbon fiber-reinforced composite (CFRP)/Ti6Al4V alloy stack material and the delamination problem that occurs especially in composite laminates. For this purpose, cutting conditions have been optimized for each of CFRP/Ti6Al4V alloy material, depending on the thrust force (Fz), surface roughness (Ra), and delamination factor (Fd) obtained by preliminary tests. The drilling tests were performed at the cutting speed of 60 m/min, the feed rate of 0.05 mm/rev for CFRP material, the cutting speed of 15 m/min, and the feed rate 0.05 mm/rev for Ti6Al4V material. The novel method for this study is that the tool was kept in the air for 1 min after each 4 mm drilling of Ti6Al4V alloy to cool the tool during the rebounds to the safe approach distance. Finally, according to the optimized cutting parameters, Fz, Ra, and Fd were assessed to evaluate the performances of cutting tools in the drilling of CFRP/Ti6Al4V stacked material. According to the experimental results and images of the digital camera and SEM device, flank wear and cracking as the wear type in the U-WC tool; flank wear, cracking, and BUE as the wear type in the TiAlN-coated tools; and outer corner wear and coating removal in diamond-coated tools. Moreover, when the tool performance is evaluated according to the cutting tool tip angle, the highest amount of wear was seen in cutting tools with 140° point angle.

The reduction of weight elements is considered as a major objective of several manufacturing companies. This objective will help in growing application sections of the used fiber composites for important structural elements. Modern fiber metal laminate (FML) having lightweight properties is established to be used instead of other substances in different applications including those related to the aerospace industrial sector. Fiber metal laminate is being deemed as an alternative significant substance that is being extensively explored due to its operation, unlike other current materials. There are different profitable FML such as GLARE (glass-reinforced aluminum laminate), established on elevated intensity ARALL glass fibers (aramid-reinforced aluminum laminate), built on fibers of aramid, in addition to CARALL (carbon-reinforced aluminum laminate), centered on fibers of carbon. This paper analyzes important information that contributes to the mechanical characteristics of FMLs under tensile, flexure, impact, etc. conditions.

High chrome white cast iron is particularly preferred in the production of machine parts requiring high wear resistance. Although the amount of chrome in these materials provides high wear and corrosion resistances, it makes their machinability difficult. This study presents an application of the grey relational analysis based on the Taguchi method in order to optimize chrome ratio, cutting speed, feed rate, and cutting depth for the resultant cutting force (FR) and surface roughness (Ra) when hard turning high chrome cast iron with a cubic boron nitride (CBN) insert. The effect levels of machining parameters on FR and Ra were examined by an analysis of variance (ANOVA). A grey relational grade (GRG) was calculated to simultaneously minimize FR and Ra. The ANOVA results based on GRG indicated that the feed rate, followed by the cutting depth, was the main parameter and contributed to responses. Optimal levels of parameters were found when the chrome ratio, cutting speed, feed rate, and cutting depth were 12%, 100 m/min, 0.05 mm/r, and 0.1 mm, respectively, based on the multiresponse optimization results obtained by considering the maximum signal to noise (S/N) ratio of GRG. Confirmation results were verified by calculating the confidence level within the interval width.

Paraoxonase 1 (PON1) is a well recognised member of human endogeneous free radical scavenging systems and its polymorphism and enzyme activity are attributed to various different cancer formations. We aimed to study the Paraoxonase 1 (PON1) polymorphism and enzyme activity in colorectal cancer patients. Peripheral blood samples for DNA extraction were collected from 54 colorectal cancer patients and 85 healthy individuals. Polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) techniques were used for determination of the PON1192 polymorphism. The frequency of AA genotype was greater than BB and AB genotypes in all groups (n:65 with 46.8%; n:15 with 10.8% and n:59 with 42.4%, respectively). In both tumor groups, PON activities were significantly lower than the control group (p < 0.05). The AA genotype was significantly more frequent than the AB and BB genotypes in colorectal cancer patients. Although the rectum cancer patients' number is low in our study, we hypothesise that decreased enzyme activity of PON 1 related to 192 gene polymorphisms might have a role in the formation of an oxidative microenvironment for cancerous DNA damage which may tend to increase distally in the colon. Further studies considering the location and the stage of the colorectal tumors with more patients may put a broadly wider view on this polymorphism and enzyme activity with respect to cancer formation.

Business Process Management and workflow management concepts need to be examined on the basis of practitioners, automation producers and sectors that are not yet aware and also the complexity of these concepts need to be eliminated. Process is the collection of equipment, materials, methods, and environmental elements that interact with each other to produce output. The workflow term encloses the continuation of each type of activities that are performed by any institution or establishment within a certain order.Workflow is used effectively for vital subjects like paperwork and transfer operations. Business process management is largely known as a methodology aimed at increasing productivity and effectiveness through systematic management, guiding efforts to optimize business processes.Businesses have to create a Business Process Management infrastructure and Process Architecture in response to growing demand for quality and global competition. Unfortunately these terms are not conceptually settled in Turkey. In particular we have studied literature and general information for accurate detection of these two concepts in the context of Turkey and demonstrated results. The fact that the subject is newly studied academically reveals the importance of working