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Experimental investigation of process parameters in Wire-EDM of Ti-6Al-4 V
Abstract Wire electric discharge machining (WEDM) is a recent technique that is useful in machining Ti-6Al-4 V alloy, which is a material that is preferred in many industries due to its exceptional hardness. This paper aims to evaluate the effects of WEDM process parameters on the machining characteristics of Ti-6Al-4 V alloy. The 4-axis CNC WEDM machine that was used in this study had brass wire as the electrode and de-ionized water as the dielectric fluid. The parameters under investigation were the peak current (Ip), pulse on time (TON), pulse off time (TOFF), and servo voltage (SV) set at 3 levels each. The experimentation was based on Taguchi’s L9 orthogonal array design. The material removal rate (MRR) and surface roughness of machined ash components were Ra. A total of three Ra results were analyzed using ANOVA. It was shown that response surface methodology, pulse time ton and peak electric current had more significant effects on MRR. Effect-wise results indicated that peak current and time on P ring test allow surface finish to be within MRR levels. It is peak electric current that determines a 72.75% effect on MRR whereas extreme time has an 11.68 balanced effect on peak current. In the case of Ra, peak electric current and extreme pulse time remain dominant factors. The results suggest that higher Ra is favored by less increase in input energy as both peak current and time have been decreased.
Flavonolignans silybin, silychristin and 2,3-dehydrosilybin showed differential cytoprotective, antioxidant and anti-apoptotic effects on splenocytes from Balb/c mice
A versatile and efficient method to isolate nuclei from low-input cryopreserved tissues for single-nuclei transcriptomics
Role of functional genes for seed vigor related traits through genome-wide association mapping in finger millet (Eleusine coracana L. Gaertn.)
Efficient WSI classification with sequence reduction and transformers pretrained on text
Abstract From computer vision to protein fold prediction, Language Models (LMs) have proven successful in transferring their representation of sequential data to a broad spectrum of tasks beyond the domain of natural language processing. Whole Slide Image (WSI) analysis in digital pathology naturally fits to transformer-based architectures. In a pre-processing step analogous to text tokenization, large microscopy images are tessellated into smaller image patches. However, due to the massive size of WSIs comprising thousands of such patches, the problem of WSI classification has not been addressed via deep transformer architectures, let alone via available text-pre-trained deep transformer language models. We introduce SeqShort, a multi-head attention-based sequence shortening layer that summarizes a large WSI into a fixed- and short-sized sequence of feature vectors by removing redundant visual information. Our sequence shortening mechanism not only reduces the computational costs of self-attention on large inputs, it also allows to include standard positional encodings to the previously unordered bag of patches that compose a WSI. We use SeqShort to effectively classify WSIs in different digital pathology tasks using a deep, text pre-trained transformer model while fine-tuning less than 0.1% of its parameters, demonstrating that their knowledge about natural language transfers well to this domain.
Assessing delimiting strategies to identify the infested zones of quarantine plant pests and diseases
Abstract Following the discovery of a quarantine plant pest or disease, delimitation is urgently conducted to define the boundaries of the infested area, typically through surveys that detect the presence or absence of the pest. Swift and accurate delimitation is crucial after a pest or pathogen enters a new region for containment or eradication. Delimiting an area that is too small allows the pest to spread uncontrollably, while delimited areas that are too large can lead to excessive economic costs, making eradication cost-prohibitive. Despite its significance, there is a lack of comprehensive reviews on delimiting strategies and their effectiveness in managing plant pests; many current practices are ad-hoc and not scientifically based. In this study, we used an individual-based model to simulate the spread of Huanglongbing (citrus greening), a priority EU pest, and evaluated three delimiting strategies across various host distribution landscapes. We found that an adaptive strategy was most effective, especially when tailored to the polycyclic nature of the pest. This underscored the need for specific delimiting approaches based on the epidemiological characteristics of the target pest.
Factors influencing partnerships between care workers and families in nursing homes in South Korea
Enhancing food recognition accuracy using hybrid transformer models and image preprocessing techniques
Neuromodulation perception by the general public
Abstract The development of neurotechnologies offers exciting opportunities for novel brain interventions. Public perception plays a crucial role in determining the success and acceptance of these interventions. This study aimed to understand the general non-expert population’s representation of neuromodulation and their preferences for common methods such as pharmaceutical drugs, brain implants, ultrasound, magnetic, and electrical stimulations. We conducted a comprehensive online survey with 784 participants to assess their perception of neuromodulation before and after providing information. We also asked the participants to rank their preferences for different neuromodulation techniques after being provided with information. Statistical analyses included inferential non-linear models and free-text data mining. Our findings revealed that overall, neuromodulation was positively perceived by the participants. Furthermore, providing information resulted in a significant improvement in participants’ perception of neuromodulation. Ultrasound stimulation emerged as the most preferred treatment choice, while pharmaceutical drugs were considered a middle-choice option and brain implants ranked last due to safety concerns. Healthcare providers could benefit from enhancing patient education and awareness to promote informed decision-making and improve treatment adherence. Additionally, stakeholders have to address the existing distrust surrounding pharmaceutical drugs and prioritize the development and promotion of safe, non-invasive neuromodulation treatments.