Processing Line Research Articles

Si/SiO2 silicon-on-insulator based scaffold for interfacing with cerebral organoids

Cerebral organoids are hSPC derived tissue complexes that self-organize over an extended period and begin to recapitulate certain features of in vivo neurogenesis, and there is a need to develop tools that allow for the physical and electrical interrogation of these cell complexes as they mature. Presented here is a method of manufacturing thin, porous, scalable silicon scaffolds as a structure to support multi-electrode arrays using industry standard semiconductor fabrication techniques. Mechanical tests by nanoindentation demonstrate the scaffold as linearly elastic with an approximated effective stiffness of 51.6 MPa. Biological cell studies indicate that mature Cerebral Organoids are capable of cellular expansion through, and partially absorbing, the scaffold, with 0.125 mm3 ± 0.027 of new tissue generation over a 5-day culture period. The structure is designed for compatibility with front end of line and back end of line semiconductor processes for future integration with metal electrodes, which enables deep tissue access in multi-cellular structures.

Process implications on the stability and reliability of 300 mm FAB MoS2 field-effect transistors

Recent advances in fabricating field-effect transistors with MoS2 and other related two-dimensional (2D) semiconductors have inspired the industry to begin with the integration of these emerging technologies into FAB-compatible process flows. Just like in the lab research on 2D devices performed in the last decade, focus during development is typically put on pure technology-related issues, such as low-temperature growth methods of large-area 2D films on target substrates, damage-free transfer from sacrificial substrates and growth of top-gate oxides. With maturing technology, the problem of stability limitations caused by oxide traps is gradually coming into focus now. Thus, here we report an in-depth analysis of hysteresis and bias-temperature instabilities for MoS2 FETs fabricated using a 300 mm FAB-compatible process. By performing a comprehensive statistical analysis on devices with top gate lengths ranging between 18 nm and 10 μm, we demonstrate that aggressive scaling results in additional stability problems, likely caused by defective edges of the scaled top gates, in particular at higher operation temperatures. These are important insights for understanding and addressing the stability limitations in future nanoscale 2D FETs produced using FAB process lines.

ВЛИЯНИЕ РЕЖИМОВ ЛАЗЕРНОЙ НАПЛАВКИ ПОРОШКА КАРБИДА ВОЛЬФРАМА НА ХАРАКТЕРИСТИКИ ПОВЕРХНОСТИ СТАЛИ 12Х18Н10Т

An experimental study of the process of laser surfacing of fine tungsten carbide powder as part of a graphite paste coating on the surface of stainless chromium-nickel steel 12Kh18Ni10Ti was carried out. Surfacing was carried out in continuous conversion mode while ensuring processing speed, changing speed and line configuration.

Evaluation of the impact of olive milling on the mineral oil contamination of extra‐virgin olive oils

AbstractMineral oil saturated (MOSH) and aromatic hydrocarbons (MOAH) are environmental and processing contaminants also found in extra‐virgin olive oil. Knowledge on contamination sources can help minimize them. The main objective of this work was to investigate the impact of milling operations. To this purpose, samples from 25 processing lines (at 5 different processing stages) were analyzed by online high‐performance liquid chromatography—gas chromatography—flame ionization detection. A protocol for eliminating endogenous n‐alkanes was tested and applied when necessary. Generally, transport to the mill had a negligible impact. The washing step had a mitigation impact, more evident on samples with higher contamination. On average, total MOSH decreased of 2.1 mg kg–1. Despite the reduction determined by washing, the entire milling process resulted in an increase in contamination (> 30%) for 20% of the processing lines. Total average MOSH and MOAH contamination increased by 2.3 and 0.6 mg kg–1, respectively.Practical Applications: This work aims to improve the knowledge on the presence and sources of mineral oil hydrocarbons (MOH), contaminants of petrogenic origin, in extra‐virgin olive oil. In particular, this work investigates the impact of processing at the mill, including the transport stage, as well as the potential of the washing step in reducing the contamination. For the first time, a systematic study on this topic has been carried out. The knowledge of the contribution of individual steps in the production process to final product contamination is of paramount importance in identifying critical points on which to take action to mitigate contamination, and this is of great interest for all operators of the sector and for protecting consumer health, especially when considering possible presence of MOAH, which may include genotoxic and carcinogenic compounds.

Scale‐up fabrication and advanced properties of recycled polyethylene terephthalate aerogels from plastic waste

AbstractTraditional fabrication methods of aerogels are time consuming, toxic, and difficult to implement, making the production of aerogels expensive and severely limits widespread adoption. Nonwoven technology is introduced to prepare fibers that can be used to create polymer‐based aerogel. With its introduction, it allows the continuous flow of fine fibers and eliminates the bottlenecking fiber preparation phase of the fabrication process. Using recycled polyethylene terephthalate (rPET) fibers and polyvinyl alcohol, two types of rPET aerogels are successfully fabricated, namely the lab‐scale and the large‐scale aerogels, to investigate the effectiveness of the nonwoven process line for the fiber preparation processing step. Fibers prepared manually (lab‐scale aerogels) and with the aid of a fiber preparation production line (large‐scale aerogels) are characterized and compared. Both lab‐scale and large‐scale aerogels exhibited the required specifications of low densities (12.6–45.9 and 13.2–43.7 mg/cm3, respectively) and high porosity (99.1%–96.7% and 99.0%–96.8%, respectively). Their thermal conductivity (23.4–34.0 and 23.2–31.9 mW/m⋅K, respectively) and compressive modulus (4.74–21.91 and 4.53–22.29 kPa, respectively) were also relatively similar. The advantage of scaled preparation of fibers for aerogel manufacturing includes higher throughputs (the line can produce up to 60 kg/h), improved consistency for defibrillation, homogenous fiber blending, and accurate replication of laboratory‐made aerogel properties. This demonstrates the viability of using nonwoven technology to scale for continuous production to bring down the production cost.Highlights Scale up production of aerogels using nonwoven technology Improving preparation process of aerogels through homogenous fiber blending Preparation rate of up to 60 kg/h Developed high porosity aerogels up to 99% Good thermal insulation of 23.2–31.9 mW/m⋅K

A Deep Neural Network for Predicting Synergistic Drug Combinations on Cancer.

The exploration of drug combinations presents an opportunity to amplify therapeutic effectiveness while alleviating undesirable side effects. Nevertheless, the extensive array of potential combinations poses challenges in terms of cost and time constraints for experimental screening. Thus, it is crucial to narrow down the search space. Deep learning approaches have gained widespread popularity in predicting synergistic drug combinations tailored for specific cell lines in vitro settings. In the present study, we introduce a novel method termed GTextSyn, which utilizes the integration of gene expression data and chemical structure information for the prediction of synergistic effects in drug combinations. GTextSyn employs a sentence classification model within the domain of Natural Language Processing (NLP), wherein drugs and cell lines are regarded as entities possessing biochemical relevance. Meanwhile, combinations of drug pairs and cell lines are construed as sentences with biochemical relational significance. To assess the efficacy of GTextSyn, we conduct a comparative analysis with alternative deep learning approaches using a standard benchmark dataset. The results from a five-fold cross-validation demonstrate a 49.5% reduction in Mean Square Error (MSE) achieved by GTextSyn, surpassing the performance of the next best method in the regression task. Furthermore, we conduct a comprehensive literature survey on the predicted novel drug combinations and find substantial support from prior experimental studies for many of the combinations identified by GTextSyn.

Integrating meta-analysis with a quantitative microbial risk assessment model to investigate Campylobacter contamination of broiler carcasses

This study investigated the prevalence and associated risk factors of Campylobacter in South Korean broilers using a random-effects meta-analysis. Subsequently, to facilitate the design of preventive measures, the prevalence estimate from the meta-analysis was incorporated into a stochastic risk assessment model to quantify the Campylobacter contamination levels on broiler carcasses. The baseline model was developed based on the most common practices along the South Korean broiler processing line, with no interventions. Meta-analysis results revealed Campylobacter prevalence across the chicken supply chain in the following order: farms (60.6 % [57.3–63.4]), retail markets (43.90 % [24.81–64.99]), slaughterhouses (27.71 % [18.56–39.21]), and processing plants (14.50 % [3.96–41.09]). The model estimated a 52 % (36.1–70.8) Campylobacter prevalence at the end of chilling, with an average contamination level of 4.62 (2.50–6.74) log CFU/carcass. Sensitivity analysis indicated that Campylobacter fecal shedding (r = 0.95) and the amount of feces on bird exteriors (r = 0.17) at pre-harvest were the main factors for carcass contamination, while soft scalding (r = -0.22) and air chilling (r = -0.12) can serve as critical control points (CCPs) at harvest. Scenario analysis indicated that a combination of hard scalding, inside-outside bird washing, spray washing, and chlorinated water immersion chilling can offer a 30.9 % reduction in prevalence and a reduction of 2.23 log CFU/carcass in contamination levels compared to the baseline model. Apart from disinfection and sanitation interventions carried out during meat processing, the implementation of robust control measures is indispensable to mitigate Campylobacter prevalence and concentration at broiler farms, thereby enhancing meat safety and public health. Furthermore, given the high Campylobacter prevalence in the retail markets, future studies should explore the potential risk of cross-contamination at post-harvest stage.

Convolutional neural networks for quality and species sorting of roundwood with image and numerical data

Roundwood sorting is still a manual process in many Swiss sawmills, requiring employees to visually inspect and categorize thousands of logs per day. The heavy workload can be both physically and mentally taxing and can lead to increased rates of human error. State-of-the-art automation systems like X-ray log scanners are expensive and difficult to integrate into existing process lines. This paper proposes a novel recommendation system that leverages recent advances in image classification to automate roundwood classification by quality and species. The system integrates a camera to capture cross-sectional images of logs and record numerical data, such as length, taper, and diameter. The analysis of the resulting dataset highlights the challenges of data imbalance and noise, which makes classification difficult and, in some cases, impossible. However, by using selected datasets with reduced noise, state-of-the-art Convolutional Neural Networks (CNNs) can extract quality and species features. Quality models learn from a manually selected and simplified dataset, featuring samples that experts can clearly classify based on the image’s information. Species models are trained on a label-noise-reduced dataset, reflecting real-world complexity. The accuracy on the selected dataset for three quality classes is 80%. The species determination is less challenging and reaches 91% accuracy on a synchronized dataset for the main species spruce and fir. Overall, this paper highlights the potential of Machine Learning in augmenting the roundwood sorting processes and presents a novel system that can improve the efficiency and accuracy of the process.

Data-Tracking in Blockchain Utilizing Hash Chain: A Study of Structured and Adaptive Process

This study presents a series of structured and adaptive processes aimed at tracking and verifying transactions recorded on the blockchain. Permissioned blockchains are employed across diverse enterprises for various purposes, including data recording, management, the utilization of blockchain services, and authentication. However, the processes of data tracking and transactions incur substantial resource and time expenditure. Furthermore, there is potential for information asymmetry within the blockchain ledger due to data breach attacks. Consequently, we propose a contract structured as a hash chain to mitigate resource and time consumption in the tracking and verification processes by organizing transaction hash values and content in a hash chain format based on cryptography. We generate a hash chain for the recorded transactions along the process line and expedite the tracking and verification process by navigating the relevant hash chain. This approach achieves faster and more accurate tracking procedures compared to conventional transaction tracking processes, simultaneously maintaining data symmetry within the blockchain ledger. We conduct a comparative analysis of a contract-based hash-chain-employing structure and two contracts related to tracking in terms of tracking time, CPU usage, and network traffic, among other metrics. The findings suggest that structuring transaction data in the form of a hash chain significantly enhances the efficiency and integrity of the data-tracking and verification processes. Consequently, in this study, we advocate for the adoption of contracts based on the hash chain format when leveraging the blockchain for tracking and verification purposes across various institutions.

ТЕХНОЛОГИЯ ПЕРЕРАБОТКИ НЕОБМОЛОЧЕННЫХ КОЛОСЬЕВ ПШЕНИЦЫ РАННИХ ФАЗ СПЕЛОСТИ В КОРМ ДЛЯ РЫБ: ПРОБЛЕМЫ И РЕШЕНИЯ

The grain crops’ nonthreshed ears of the early stages of ripeness as raw materials for feed preparation can be used. The purpose of this study was: nonthreshed ears of early ripeness phases into food for omnivorous fish processing technology developing and substantiating. This study object - was the technological process of granulated feed from nonthreshed ears of early ripeness phases preparing. A preliminary technological scheme for granular feed preparation from ears had been developed. An experimental test had revealed shortcomings in technological process of feed from nonthreshed ears producing implementation, reducing its energy and economic efficiency and the processing line’s productivity and feed quality’s negative affecting. Possible solutions had been developed. For granular feed production from early ripening phases ears technology effective implementation, it is necessary the raw materials’ drying and grinding as technological operations, as well as its grinding and mixing to combine, for which new technological solutions were proposed. An improved technological scheme for granular fish feed from nonthreshed ears of early ripening producing has been developed, including combined technological operations. New technical means to be developed and already developed into the new scheme are integrated. The results of the study had shown that the technology of granulated feed from nonthreshed ears producing - is an effective means of livestock production’s profitability increasing, since feed produced by this technology using contains more protein than traditional one based on threshed forage grains, as a result fewer expensive protein additives in its composition can be included. The introduction of a new technology for the granular fish feed from nonthreshed ears preparation will make it possible early grain crops harvesting by the ochesmethod using for the feed nutritional value increasing.

ОПРЕДЕЛЕНИЕ ФИЗИКО-МЕХАНИЧЕСКИХ СВОЙСТВ ПРОРОЩЕННОГО ЗЕРНА

One of the most common types of raw feed in farming is grain. It is used as the main component in combined feeds. Sprouted grain is a feed additive natural that vitamins containing. It is known that stronger animals food first eating. In order for the sprouted grain had reached the livestock entire proportion for feed consumption, the first evenly in the feed must be distributed. To do this, the sprouted grain must be dried, crushed, and then mixed with combined feed. The sprouts and sprouted grain’s strength properties differ from ordinary (non sprouted) grain, therefore, at crushing them in conventional hammer crushers, the energy intensity process will increase. To reduce the sprouted grain grinding’s energy consumption, it is necessary that cause destruction’s loads knowing. It is known that the grain by crushing is crushed, and the sprout is cut. To design the grinding machines’ working bodies, it is necessary the grain and sprouted grain’s germ strength properties knowing. At sprouted grain preparing, it is moving along the processing line and pouring itself repeatedly. To avoid sprouted grain’s on the gravity flows’ surface sticking, it is necessary the static friction coefficients taking into account. The stands for loads’ determination causing the grains and germinated grain sprouts’ destruction are presented. On one stand, due to the applied effort, the grain is split by a rod using, and by the rod with a knife replacing the sprout is cut. During the experiments, the force is recorded. On another stand, the static friction coefficients of sprouted and unsprouted grain on galvanized steel, plastic, rubber, plywood surfaces are determined. The experimental studies’ results are presented. It has been established that the Young modul’s of sprouted grain average value is lesser than for unsprouted one. The unsprouted wheat had the lowest the friction coefficient value on plywood, it’s 0.31...0.33, on rubber this coefficient took the highest value - 0.4...0.47.

Classifying scratches on chicken carcasses on processing line using two-dimensional image processing technique

Classifying scratches on chicken carcasses on processing line using two-dimensional image processing technique

Optimization of Rolls-Royce gas turbine components machining using artificial intelligence

Industry 4.0 has changed the ways in which Small to Medium (SME’s) and Large Enterprise (LE’s) manufacturers and businesses operate. Artificial Intelligence (AI), Bigdata, Edge Computing, Cloud Computing, Internet of Everything (IoE), Fifth Generation (5G) and Information Communication Technology (ICT) allow processes to be optimized, controlled, and monitored in close real-time. These enabling technologies allow manufacturing facilities to collect enormous amounts of data from process lines, such as real-time measurement data, machinery state of health, and cycle time, to accurately plan and report the state of both processes, machinery, and final products. In this work, the research programme focuses on the collected data from process input variables that can be monitored to ensure process outputs and final components conform to design specifications. Current methods of analyzing data, especially in aerospace manufacturing environments, require engineers or process operators with a precise and high skill set to be able to map the results into the appropriate chart and interpret these results. Furthermore, the quantity of data analysis required to monitor process inputs in real-time renders conventional analysis techniques unfeasible. Current development using AI has shown the potential and the capability to detect trends in large data sets using machine and deep learning. It also enables a more precise and automated analysis without human intervention. This paper focuses on determining the feasibility of using a deep neural network (i.e., deep neural networks -DNN) to predict process outputs based on process inputs. A simplified example is presented using data collected from firing a ‘statapult’ with varied configurations, training a deep neural network and predicting future results based on process inputs. Initial results are presented, and the results show promising estimating and prediction capabilities.

Design and Efficiency of a String Hulling Machine for Buckwheat

Abstract An important task of food engineering, namely grain processing and the pro-duction of cereals and fodder, is the improvement of hulling equipment and the creation of complex technological lines for the processing of the original crops is gaining particular relevance. The reason for this is the need to carry out several preparatory stages, and, as a result, the use of additional equipment. To solve this problem, a string hulling device had been developed, the use of which allows reducing the number of operations due to the exclusion of preliminary sorting into fractions and wet-heat treatment. These operations are required by other hulling machines included in the technological lines of buckwheat processing. The structural scheme of the string hulling device had been developed and the principle of the shell removal operation had been substantiated. Theoretical studies had been carried out by the methods of analysis and synthesis of the mechanics of destruction and systematic analysis of the process of buckwheat hulling by impact. Experimental studies had been carried out using a laboratory string hulling device. The conducted analytical studies made it possible to determine the regularity between the physical and mechanical characteristics of buckwheat and the critical linear impact speed necessary for the destruction of the shell. This allows deter-mining the frequency of rotation of the string at which the destruction of the shell will occur while preserving the integrity of the core. Experimental studies made it possible to determine the quality of buckwheat hulling by determining the coefficient of integrity of the kernel and the coefficient of hulling. It has been determined that the ranges of the rotation frequency of the strings required to ensure a high degree of the buckwheat hulling technological process efficiency are within 15.8-16.9 s−1.

Spatial changes in Royal Malay Town: The Inheritance of ‘Kota’ for Sustainability of Urban Conservation Practices

The continuous degradation of historical urban fabric in traditional towns has hindered efforts to implement sustainable urban conservation practices. Considering the dynamic and complexities of urban areas, which encompass multiple relationships to geographical settings, functional economic and socio-cultural factors, understanding the contextual formation and growth therefore becomes an important consideration in any development project. However, analysing the evolutionary process requires systematic structuring at each hierarchical scale, temporal dimension and level of morphological elements. Thus, posing a significant challenge in extracting the organic growth development of traditional towns. This study attempts to develop a methodological framework for integrated urban morphological analysis that guides the analytical process of spatial changes in Royal Malay town. A case study at Old Town Centre of Kota Bharu, Kelantan was conducted with an emphasis on structuring the case and plan- unit analysis based on diachronic and synchronic comparisons. The findings unveiled the inherent morphogenetic characteristics of Royal Malay towns central to the spatial structure of Kota, which demarcate the fixation line of the growth process and imperative to the functioning system for spatial resilience. This implies that developing a systematic methodological and mapping analysis process aids in providing a clear and responsive strategy in managing rapid spatial transition. This study brings forward the bridging of multidisciplinary knowledge on urban history, geography, design, planning and management to assist in the formulation of comprehensive development guidelines and policies that emphasize an explicit morphological perspective.

Multicore Fiber Nonuniformly-Spaced Optical Delay Line for Microwave Signal Processing

Multicore Fiber Nonuniformly-Spaced Optical Delay Line for Microwave Signal Processing

Redefining Diagnostic Criteria for Basilar Invagination Using Linear Craniometric Parameters.

To establish the diagnosis of basilar invagination (BI) on the basis of specific bony landmarks Klaus' index (KI), perpendicular distance between the tip of the odontoid process and palato internal occipital protuberance (PI) line. Forty-nine patients were analysed, who underwent surgery for BI, between July 2020 and June 2023. Radiological assessment was done in all the patients using reconstructed midsagittal images on computed tomography scans . Mean age was 34.82 ± 10.52 years with male preponderance (67.35%) in patients with BI. We also analysed randomly selected 120 control subjects (male: female = 59:61) with mean age 43.5 ± 14.08 years. The mean distance of tip of the odontoid process from PI line in patients with BI was 3.39 ± 3.09 mm. The mean value of KI in the patients with BI was 28.57 ± 1.68 mm. Receiver operating characteristic (ROC)curve was used for analysing the distance of the tip of the odontoid process from PI line in the patients with BI which produced area under curve( AUC) of 0.97 (confidence interval [CI] -0.931 to 0.990, p < 0.0001). Cut-off point of 7.5 mm was identified for the distance of tip of odontoid process from PI line with sensitivity of 89.8% and specificity of 97.5% having 95.27% diagnostic accuracy for BI. ROC curve analysis of value of KI for the diagnosis of BI produced AUC of 1( CI: 0.978 to 1.000, p < 0.0001). Cut-off value of 33.2 mm for KI was identified for diagnosing BI with 100% accuracy. The distance of tip of the odontoid process from PI line < 7.5 mm and value of KI < 33.2 mm, both of these parameters can diagnose BI with comparable accuracy to most widely used conventional radiological methods.

Thymoquinone Nanoparticle Induces Apoptosis and Cell Migration Retardation through Modulating of SUMOylation Process Genes in Breast Cancer Cell Line.

Due to the heterogeneity of breast cancer, most advanced-stage patients are resistant to therapy. Disruption of SUMOylation, a post-translational modification, is linked to breast cancer. This study aimed to assess the impact of thymoquinone nanoparticles (Liposomal-TQ), an anti-cancer drug, combined with doxorubicin (DXR), the most effective chemotherapeutic drug used to treat breast cancer, on the expression of SENP2 and SENP6, two major components involved in the SUMOylation process, in normal and cancerous breast cell lines. The MCF7 cell line, a breast cancer cell line, and MCF10, a non-tumor epithelial cell line, were separately treated with Liposomal-TQ and DXR. Cell viability and cell migration were assessed using MTT and scratch tests. Apoptosis analysis was performed using annexin-V/PI staining. Gene expression analysis of SENP2 and SENP6 was conducted using quantitative real-time PCR (RT-qPCR). Additionally, the scratch test evaluated the anti-cell migratory effect of Liposomal-TQ. The findings obtained from RT-qPCR analysis indicated a significant increase in the expression of SENP2 and SENP6 genes in the TQ and DXR treatment groups compared to the control group in MCF7 but not in MCF10 cell lines (p-value < 0.05). Also, after 24 hours of treatment of MCF7 and MCF10 cells with liposomal-TQ, late apoptotic cells were significantly increased compared to the control and liposome groups (p-value < 0.0001) and compared to the control group, both DXR and Liposomal-TQ dramatically reduced the migratory ability of breast cancer cells (p-value = 0.001 and p-value = 0.001, respectively). Our study indicated that Liposomal-TQ promotes apoptosis in breast cancer cells and inhibits cell migration ability. These findings enhance our understanding of the role of Liposomal-TQ in the carcinogenic activities of SENP2 and SENP6 in the SUMOylation pathway of breast cancer.

Ways to solve automation problems in meat poultry farming

Solving the automation problems in the process lines of poultry farms is a complex and multifaceted task. It ensures the smooth operation of the poultry farm without human involvement, replaces manual labor, and prevents potential errors. Additionally, automating of poultry farms solves the problem of labor shortage and makes “non-prestigious work” interesting and attractive for young people. Automation systems of feeding, watering, manure removal, lighting, and ventilation in the poultry house reduces the complexity of processes, enables remote management of the entire production chain via a computer, and allows for real-time response to any changes. From an economic perspective, it has been found that automating poultry production processes decreases feed costs by 15-20%, water and electricity costs by 12-25%, and reduces the return on investment period to 8-12 months. This article reviews solutions to poultry farm automation problems, including ensuring an optimal microclimate by maintaining temperature and humidity conditions, regulating air quality, which provides normative indicators of the concentration of harmful substances; monitoring daily feed consumption, which ensures the regulated feeding of birds and achieving the standard growth of poultry; full monitoring and output to a computer or mobile phone; and printing all parameters.

Shearing Work Analysis and Control Design of Rotary Shears in Material Processing Lines

Abstract Rotary shears are common part of the material processing lines (MPL). During the operation, these shears are loaded with impact cutting torque, which takes only short time but reaches values compared to motor-rated torque. Therefore, it is a technical challenge to ensure the speed stability during the cut. The presented paper deals with the analysis of the rotary shears’ operation and material cutting process from the control point of view and presents a cutting torque compensation possibility. Three types of speed controllers without and with cutting torque compensation are compared.