Labor Time Research Articles

Efficient production system for hydrogel-based transparent soil for plant root observation.

Observation of plant root morphology in soil is of fundamental importance in plant research, but the lack of transparency of the soil hampers direct observation of roots. One of the approaches to overcome this technical limitation is the use of "transparent soil" (TS), hydrogel-based beads produced by spherification of gelling agents. However, the production of TS by natural dripping of gelling solution can be labor intensive, time consuming and difficult to maintain consistent product quality. Here we present a semi-automated system for TS production. A three-channel peristatic pump controls the critical parameters for spherification, such as drop height and ionic strength, allowing larger-scale TS production with less manual operation. This system improves the efficiency of experiments using TS and enables large-scale experiments requiring large amounts of TS.

Design for manufacture and assembly (DfMA) for modular buildings: an analytical framework

ABSTRACT Design for Manufacture and Assembly (DfMA) is a proactive strategy aimed at maximizing the potential of modular buildings to address issues, including labor shortages, time overruns, and low productivity. Despite its growing adoption, research on examining existing design practices remains limited. This study therefore aims to 1) develop an analytical framework and 2) uncover underlying modular building design patterns. Drawing inspiration from space syntax analysis, the framework comprises six components: nomenclature system, space identification, spatial relations, module shape, dimensions, and convex break-up. It was then applied to analyze 39 modular building units in Hong Kong. The established framework helps visualize underlying design patterns, e.g. spatial typologies, module shapes and sizes, and standardized spatial configurations. Several design patterns are also identified, i.e. typical space requirements, common module sizes, dimension-coordinated spaces, and the repetitive use of standardized spaces and modules to form units. This innovative framework, along with a discussion on evolving professional practices, offers valuable insights for advancing DfMA and modular construction. Future research is recommended to refine the framework and enhance DfMA by integrating these patterns with expert knowledge and computational intelligence.

Technical note: A fast and reproducible autosampler for direct vapor equilibration isotope measurements

Abstract. To investigate water movement in environmental systems, stable isotope (2H and 18O) ratios of water are commonly used tracers. Analyzing the isotopic ratios of water in or adsorbed to substances like soil or plant tissue necessitates the extraction or equilibration of water prior to analysis. One such method, direct vapor equilibration, is popular due to its cost-effectiveness and straightforward sample processing. However, sample analysis requires significant manual labor, thereby limiting the number of samples that can be analyzed. This limitation is compounded by the fact that stored samples undergo evaporative isotopic changes over time. Moreover, manual measurements require many laborious procedural steps that can easily compromise reproducibility. The operator has to subjectively decide if the measurements are stable and then record the analyzer readings. To address these challenges, we have developed a system that automates the analysis process. Our autosampler for vapor samples, named VapAuSa, features a modular design that allows for up to 350 ports for direct vapor equilibration samples. These ports sequentially connect the prepared samples to a laser isotope analyzer, enabling continuous automated measurements. Within the accompanying software, measurement criteria can be specified, facilitating reproducible analysis. The developed system was tested by co-measuring 90 soil samples and 21 liquid water samples with known δ values. VapAuSa measurements have a negligible measurement bias (<1×10-13 ‰ for both δ2H and δ18O) and similar measurement repeatability compared to manual analysis of identical samples (δ2H=±4.5 ‰ and δ18O=±0.58 ‰ for VapAuSa measurements vs. δ2H=±5.7 ‰ and δ18O=±0.37 ‰ for manual analysis). However, the increased sample throughput minimizes storage-induced isotopic changes. Moreover, VapAuSa triples sample throughput per week while also reducing the direct labor time to just 10 % of that required for manual processing.

MR-linac: role of artificial intelligence and automation.

The integration of artificial intelligence (AI) into radiotherapy has advanced significantly during the past 5years, especially in terms of automating key processes like organ at risk delineation and treatment planning. These innovations have enhanced consistency, accuracy, and efficiency in clinical practice. Magnetic resonance (MR)-guided linear accelerators (MR-linacs) have greatly improved treatment accuracy and real-time plan adaptation, particularly for tumors near radiosensitive organs. Despite these improvements, MR-guided radiotherapy (MRgRT) remains labor intensive and time consuming, highlighting the need for AI to streamline workflows and support rapid decision-making. Synthetic CTs from MR images and automated contouring and treatment planning will reduce manual processes, thus optimizing treatment times and expanding access to MR-linac technology. AI-driven quality assurance will ensure patient safety by predicting machine errors and validating treatment delivery. Advances in intrafractional motion management will increase the accuracy of treatment, and the integration of imaging biomarkers for outcome prediction and early toxicity assessment will enable more precise and effective treatment strategies.

The role of intrapartum ultrasound combined with free position delivery in the management of abnormal fetal positions during labor

ObjectiveTo investigate the effectiveness of combining intrapartum ultrasound with free maternal positions in managing abnormal labor, specifically focusing on its impact on delivery outcomes.MethodsA retrospective cohort study was conducted on 176 cases of abnormal labor progression in women who attempted vaginal delivery at our hospital from June 2021 to May 2022. Among these, 88 cases were diagnosed with abnormal fetal positions using a combination of intrapartum ultrasound and vaginal examination, and these patients were guided to adopt free maternal positions (experimental group). The control group comprised 88 cases diagnosed with abnormal fetal positions through vaginal examination alone, without any intervention to correct positioning. Maternal and neonatal outcomes, including the duration of the first and second stages of labor, total labor time, cesarean section rates due to failed progression, postpartum hemorrhage, and length of hospital stay, were compared between the two groups.ResultsThe experimental group demonstrated significantly reduced durations of the first and second stages of labor, as well as total labor time, compared to the control group. Furthermore, the rate of cesarean sections due to failed progression was significantly lower in the experimental group. Additionally, the experimental group experienced lower rates of postpartum hemorrhage and shorter hospital stays, with statistically significant differences observed.ConclusionCombining intrapartum ultrasound with free maternal positions shows promise in improving delivery outcomes for women with abnormal fetal positions during labor. These findings highlight the potential benefits of this approach in enhancing the quality of delivery.

Challenges and Future Scope in Onion and Other Root Crop De-Topping Machines and Its Performance: A Review

Onion is one of the important vegetable and spice commodity crop which has yearlong demand but seasonal in production. Onion de-topping (i.e., separation of matured leaves from bulbs) is the important post-harvest operation in onion production which conducted after curing process of onion bulbs. In India onion de-topping done mostly manually in farms using sickle, khurpi and knife. Manually onion de-topping of onion bulbs is time consuming and labour-intensive operation. Availability of labours are difficult in peak harvesting season of onion; therefore, farmers may incur financial and crop loss. Mechanical onion de-topping done using onion harvesters during digging operation of onion bulbs. There are many onion de-topping machines are available for onion bulbs with different mechanism. The different onion de-topping machine were studied in terms of their mechanism, construction, working principles, performance and efficiency. The comparison of performance of the machines with manual onion de-topping was studied over the cutting capacity, efficiency, damage percentage, saving of labour cost and time. This paper reviews such onion de-topping harvesters and de-topping machines. It highlights the mechanism used for de-topping in these machines with their performance in terms of de-topping capacity and de-topping efficiency. It also tries to highlight the necessity of requirement of de-topping machines and current status of adoption of such machines by farmers in India. It was observed that number of onion de-topping machines are available though it is difficult to adopt by the farmers specially medium and low land holding farmers because of cost concern. Therefore, it is necessary to develop the machine which should be low cost, efficient and labour saving for such farmers. Using such an onion de-topping machines will help to save their labour cost, operational time, drudgery of labour and increase efficiency of labour. Also adopting such technologies can encourage the farmers to increase the production of such crop.

NeRF-Accelerated Ecological Monitoring in Mixed-Evergreen Redwood Forest

Forest mapping provides critical observational data needed to understand the dynamics of forest environments. Notably, tree diameter at breast height (DBH) is a metric used to estimate forest biomass and carbon dioxide (CO2) sequestration. Manual methods of forest mapping are labor intensive and time consuming, a bottleneck for large-scale mapping efforts. Automated mapping relies on acquiring dense forest reconstructions, typically in the form of point clouds. Terrestrial laser scanning (TLS) and mobile laser scanning (MLS) generate point clouds using expensive LiDAR sensing and have been used successfully to estimate tree diameter. Neural radiance fields (NeRFs) are an emergent technology enabling photorealistic, vision-based reconstruction by training a neural network on a sparse set of input views. In this paper, we present a comparison of MLS and NeRF forest reconstructions for the purpose of trunk diameter estimation in a mixed-evergreen Redwood forest. In addition, we propose an improved DBH-estimation method using convex-hull modeling. Using this approach, we achieved 1.68 cm RMSE (2.81%), which consistently outperformed standard cylinder modeling approaches.

ВИКОРИСТАННЯ ЦИФРОВИХ ІНСТРУМЕНТІВ ПРИ ПРОВЕДЕННІ ІНВЕНТАРИЗАЦІЇ ОБ’ЄКТІВ ОБЛІКУ

Introduction. The development of the digital economy has left its mark on all areas of activity, including accounting processes. The theoretical and practical foundations of accounting are also undergoing significant changes. Accounting tools must be in line with modern realities. Enterprises automate the collection and registration of primary information using modern measuring instruments, which ensures the documentation of business transactions exclusively in electronic form. The article discusses the need to ensure the reliability of accounting indicators and prevent possible deviations by means of inventory, one of the main methods of accounting and control. The purpose of the article. To study and improve the digital tools used in the inventory of accounting objects at business entities of various types of activities. Methods. The methods of abstraction, analysis, logical, theoretical, generalization and comparison were used in the study. The research is based on the dialectical method. Results. The transformation of accounting in accordance with the new needs of society is a necessary stage in its development. Changes and improvements in the accounting methodology will help not to lose its relevance in the era of universal digitalization. The complexity of the inventory and its labor intensity is explained by the need for a set of preparatory and organizational actions, extensive documentary support, involvement of significant human resources in control procedures, and the multidimensional scope of application. With the ever-increasing range and assortment of inventory items on the market, the number of accounting items is growing, which in turn requires significant time spent on control procedures. Inventory at the vast majority of enterprises is characterized by a statutory procedure and frequency. Conclusions. The use of digital identification technologies in inventory procedures will reduce labor and working time costs, increase the efficiency of such procedures, ensure timeliness and efficiency of inventory, and reduce the likelihood of abuse.

Effectiveness of Birthing Ball Exercises Therapy in Improving Labor Pain and Labor Outcomes: A Systematic Review

Objective: We must treat every woman with respect and compassion during her childbirth, allowing her to choose how she wants to remember the experience. Midwives and nurses use birthing balls to reduce labor pain and enhance maternal comfort without an epidural. The aim of this systematic review was to critically evaluate the available evidences on the effect of birthing balls on labor pain and labour outcomes. Materials and methods: Studies identified through PubMed, Semantic Scholar, and Mendeley electronic databases to gather evidences with selected keywords. This review incorporated randomised controlled trials and quasi-experimental research studies that met specific, predefined inclusion criteria. The search generated 441 titles and abstracts, which were further filtered down to 29 publications that were possibly relevant. Out of those, eight studies met the inclusion criteria. Performed a quality assessment of the articles using the JBI quality assessment tool. Results: All of the included studies show labor pain on a 10-cm Visual Analogue Scale (VAS), and interventional groups reported significantly less labor pain in delivery compared to the control group without birth ball exercise. On labour outcome findings, the intervention group had a higher mean score of cervical dilation in 2 studies, quicker head descent in 3 studies, lower labor time in 4 studies, mother satisfaction throughout labor in 2 studies, and a preference for vaginal delivery in 2 studies. Conclusion: Clinical implementation of a birthing ball exercise during the process of labor is an effective intervention to reduce labor pain and improve labor outcomes.

The Effectiveness of Local Exhaust Ventilation (LEV) System in Welding Training Facilities using Validation Computational Fluid Dynamics (CFD) Simulation

The Local Exhaust Ventilation (LEV) is the most common type of engineering control equipment used to control employees' exposure to chemicals that are hazardous to their health. Before a contaminant disperses into the workroom environment, LEV systems operate on the principle of capturing it at or near its source. The welding guideline stated that the suggested minimum hood velocity is 100 ft/min, the recommended velocity along ducts for vapors, gases, and smoke is 1000 ft/min, and 2000 ft/min. The research objective is to identify the effectiveness of the LEV system using validation computational fluid dynamics (CFD) simulation. The data collected by experimental design during the pre-testing phase of the LEV system is quantitative and obtained through a fieldwork survey and document analysis. Findings found that LEV systems are effective to be used and meet all the minimum requirements set by the guideline. In CFD simulation, upon validation, the average absolute error obtained from the case study is 8.4%. There is good agreement between actual experimental and CFD simulation results, and the acceptable validity of CFD simulation is less than 10%. Therefore, simple CFD modeling is a tool to simulate air velocity in the LEV system, saving labor costs and time consumption during the earliest stage of LEV design development before actual construction. This study's outcome can serve as a benchmark or guideline for training facilities equipped with the LEV system to prioritize safety and health.

Creation of Aerial Arecanut Dataset and Aerial Arecanut Ripeness Level Detection using Deep Neural Networks

Background: Arecanut, a commercially significant crop grown across various regions of the country and contributes significantly to India’s global ranking as the second-largest producer. Harvesting arecanut at precise stages is paramount to achieve optimal yields. Typically, this task requires minimum of two skilled individuals: a professional tree climber proficient in nut plucking and another adept at assessing ripeness. Before proceeding to harvest all the arecanuts, the climber picks one or two nuts and indicates the other person to check it for ripeness assessment. The assessor verifies ripeness by peeling the nut with teeth and uses roti/dhoti (an equipment used to harvest arecanut) to harvest arecanut if it is ripened. Inaccurate predictions can lead to significant crop losses. Manual harvesting, while effective, presents challenges such as labour shortages, time consumption, and potential for life-threatening circumstances. Methods: To address these challenges this paper presents the creation of aerial arecanut dataset and accurate ripeness detection of arecanut using Deep Neural Networks (DNN) such as AlexNet and VGG-16. Images of Arecanut bunch are fed as input to the DNN. The features like colour, shape, texture, etc., will be extracted and given as input features to the classifier. The classifier will categorize the arecanut into three classes: unripened, intermediate and ripened. Result: The accuracy of classification of arecanut ripeness level is 94.58% and 96.87% using AlexNet and VGG-16 respectively. If this model is integrated in roti/dhoti, the life of the human being can be saved. Or if this model is integrated with the climber unit and cutter unit, it will transform the arecanut harvesting system into a fully automated harvesting system and further it reduces the man power required to harvest the arecanut, overcomes the life threats during harvesting and arecanut harvesting process becomes faster compared to the conventional method.

Revisiting the follicle-stimulation hormone receptor expression and function in human myometrium and adipose tissue

BackgroundExtragonadal follicle-stimulating hormone receptor (FSHR) expression at low levels has been shown in several normal and tumor tissues, including myometrium and adipose tissue. FSH-FSHR signaling in the myometrium has been suggested to regulate uterine contractile activity and the timing of labor. In contrast, FSH-FSHR has been linked to the activation of brown/beige fat thermogenesis in adipose tissue. The issue of extragonadal FSHR expression and its functionality remains contentious within the scientific community, as contradictory findings necessitate further independent and critical analyses. Hereby, we re-investigated the FSHR expression and its functionality in normal non-pregnant (M-NP) and pregnant (N-P) human myometrium, as well as in human visceral (VAT) and subcutaneous (SCAT) adipose tissue (AT).MethodsFSHR expression at mRNA (real-time qPCR, RNAscope in situ hybridization) and protein (immunohistochemical staining) levels in adipose tissue, myometrium, and adipocytes were evaluated. Myometrium and adipocytes were treated with recombinant (rh)FSH to study its effects on functional pathways. Myometrium contractile activity was measured using a force transducer with digital output and the DASYLab software unit. Cyclic adenosine monophosphate (cAMP) production by myometrium explants and adipocytes was measured using a cAMP ELISA Kit. The activation of the AKT pathway in myometrium and adipocytes was analyzed by Western blot analysis.ResultsContrary to previous observations, we found no expression of FSHR at either mRNA or protein levels in M-NP, N-P, VAT, and SCAT. Treatment with recombinant human FSH (rhFSH) showed no effect on cAMP production or phosphorylation of AKT in M-NP, N-P, as well as in VAT and SCAT. rhFSH treatment did not influence contractile activity in M-NP, N-P.ConclusionsThese findings suggest that the FSHR signaling pathway does not regulate myometrial contractility during pregnancy. Additionally, the absence of FSHR expression in both VAT and SCAT implied that FSHR does not play a role in the functional signaling pathways in adipose tissues. In conclusion, our findings contradict earlier data on the involvement of FSH-FSHR signaling in regulating myometrial contractility near term, as well as in adipose tissue function.

Aerial LiDAR and Imaging Based Earth Surface Digitization and Data Characteristics Comparison

Abstract The land topography and urban area digitization in the form of point clouds has become an indispensable method for providing many related services. Aerial point cloud measurements are made using active LiDAR or dense matching photogrammetry methods. Aerial LiDAR and dense image matching point clouds are obtained directly in the geodetic coordinate system thanks to navigation data. The geo-referencing based on ground control points require more labour and work time. All kinds of geometric and semantic information about the terrain can be extracted from the point cloud data. Therefore, it should have both location and visualization accuracy. The detection and definition accuracies of image area details depend on the scanning point density and its uniform distribution. In this study, after having been introduced the parameters of the aerial point cloud related to topographic measurement and urban area modelling, a comparison of these two source point clouds was made in areas with different land cover. The registration of a dense matching point cloud into a geospatial reference system was done with flight data and LiDAR measurements. As consequence, The LiDAR point density depends on the min angular step of the instrument scanning light, while the dense matching is relating to ground sampled distance of pixels.

An automatic 3D tomato plant stemwork phenotyping pipeline at internode level based on tree quantitative structural modelling algorithm

Phenotypic traits of stemwork are important indicators of plant growing status, contributing to multiple research domains including yield estimation, breeding engineering, and disease control. Traditional plant phenotyping with human work faces serious bottlenecks on labour intensity and time consumption. In recent years, the application of Quantitative Structural Modeling (QSM) together with three-dimensional (3D) sensor-based data acquisition techniques provides a feasible solution towards the automatic stemwork phenotyping. Nevertheless, existing QSM-based pipelines are sensitive towards the point cloud quality, and mostly focus on the phenotyping at plant or organ level. Information at internode level which are closely related to photosynthesis and light absorption was generally overlooked. To this end, a 3D automatic stemwork phenotyping pipeline is developed for tomato plants at both plant and internode level. Coloured point clouds are taken as the sensor input of the pipeline. A semantic segmentation based on PointNet++ was used to detect and localise the stemwork points. To improve the quality of the segmented stemwork point clouds, a density-based refining pipeline is proposed containing three main processes: non-replacement resampling, interference branch removal, and noise removal. A Tree Quantitative Structural Modeling (TreeQSM) algorithm was then applied to the stemwork point cloud to construct a digital reconstruction. The target phenotypic traits were finally calculated from the digital model by employing an internode association process. The proposed phenotyping pipeline was evaluated with a test dataset containing three tomato plant cultivars: Merlice, Brioso, and Gardener Delight. The related rooted mean squared errors of calculated internode length, internode diameters, leaf branching angle, leaf phyllotactic angle, and stem length range from 4.8 to 64.4%. Considering the time consuming manual phenotyping process, the proposed work provides a feasible solution towards the high throughput plant phenotyping, from which facilitates the related research on plant breeding and crop management.

Paying for green tide management or participating in cleanup activities? Testing and controlling for payment vehicle bias in the valuation of ecological damage caused by green tides

Payment vehicle bias is one of the biases in the contingent valuation method (CVM). This research uses the ecological damage assessment of the Ulva prolifera green tides in Jiaozhou Bay, Qingdao, China, as a case study to examine the factors influencing the payment vehicle bias and control for it. The results indicate that nearly 50% of respondents might refuse to pay because monetary or labor payment vehicles do not meet their payment preferences. This situation leads to nonrandom sample selection and payment vehicle bias. To address these issues, this research proposes a novel valuation framework that combines monetary and labor payment vehicles. And the Heckman two-stage model is used to estimate the economic value of labor time and combines sample data from both monetary and labor payment vehicles to control for bias and obtain a more reliable valuation result. The results show that, compared with sole reliance on monetary payment vehicles, the use of dual payment vehicles increases the observable sample size from 222 to 330. Furthermore, respondents’ average WTP for green tide management increases from 101 CNY/person·year to 116 CNY/person·year. Therefore, employing both payment vehicles simultaneously can reveal more respondents’ true preferences, reduce non-randomness in sample selection and mitigate payment vehicle bias. The findings of this study can demonstrate the value of labor payment vehicles in CVM applications and provide a scientific basis for the Qingdao municipal government to establish more effective strategies for green tide management.

AI-Assisted High-Throughput Tissue Microarray Workflow.

Immunohistochemical (IHC) studies of formalin-fixed paraffin-embedded (FFPE) samples are a gold standard in oncology for tumor characterization, and the identification of prognostic and predictive markers. However, despite the abundance of archived FFPE samples, their research use is limited due to the labor-intensive nature of IHC on large cohorts. This study aimed to create a high-throughput workflow using modern technologies to facilitate IHC biomarker studies on large patient groups. Semiautomatic constructed tissue microarrays (TMAs) were created for two tumor patient cohorts and IHC stained for seven antibodies (ABs). AB expression in the tumor and surrounding stroma was quantified using the AI-supported image analysis software QuPath. The data were correlated with clinicopathological information using an R-script, all results were automatically compiled into formatted reports. By minimizing labor time to 7.7%-compared to whole-slide studies-the established workflow significantly reduced human and material resource consumption. It successfully correlated AB expression with overall patient survival and additional clinicopathological data, providing publication-ready figures and tables. The AI-assisted high-throughput TMA workflow, validated on two patient cohorts, streamlines modern histopathological research by offering cost and time efficiency compared to traditional whole-slide studies. It maintains research quality and preserves patient tissue while significantly reducing material and human resources, making it ideal for high-throughput research centers and collaborations.

Influence of acupuncture and acupressure on labor duration

Objective: in this regard, the main goal of this systematic review is to identify and compare results that can build different perspectives on the efficacy of acupuncture using work time. Methods: the model followed for the construction of this systematic review was the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The keywords chosen were "Acupuncture" and "Labor Time". Studies originally published were analyzed in English and Portuguese between 1987 and 2020. The selected articles were those including acupuncture and acupressure techniques during labor. Results: 17 articles were in eligibility criteria. In six studies, the use of a standard questionnaire was not described. Sixteen were randomized clinical trials. Fourteen articles had the size of the sample equal to or less than one hundred, and only two exceeded three hundred participants. In most studies (n = 12), the early average acupuncture was between 37 ° and 42 ° week of pregnancy. Ten studies used acupuncture as the main technique. All cited the types of points used, including more present: SP6 and LI4. Conclusion: Acupuncture can be considered an effective technique in reducing the duration of work. However, more high-quality articles are needed to consolidate these positive results.

Is Reconstructive Plastic Surgery Appropriately Valued? Comparison of Reimbursement per Unit Time for Reconstructive versus Aesthetic Procedures.

The work relative value units (wRVUs) system was established as a quantifier of physician labor, technical skill, medical decision-making, and training time required to complete a surgical procedure; hence, more challenging operations should theoretically result in higher reimbursement or compensation. Our purpose was to highlight the discrepancies between insurance-based reconstructive and fee-for-service aesthetic procedures based upon dollar/unit time. We analyzed national data from the American College of Surgeons National Surgical Quality Improvement Program, Aesthetic Surgery Databank, and Centers for Medicare and Medicaid Services to compare reimbursement for 8 reconstructive microsurgery and 3 aesthetic procedures and assessed operative times and reimbursement rates, then calculated "relative value unit per unit time" to measure compensation efficiency. This difference in remuneration translates to a 4.7× difference, with an overwhelming gap of $25.26 per minute between microsurgical reconstructive and aesthetic cases. These findings suggest that aesthetic cases are more profitable considering the compensation per unit time. Based on national rates of reimbursement, there is a large discrepancy between reimbursement in microsurgical reconstructive procedures and aesthetic procedures. We demonstrated that complexity and time are not directly related to compensation.

The administration of immune checkpoint inhibitors via an elastomeric pump versus conventional intravenous infusion: an economic perspective

BackgroundRecent studies have underscored the potential of innovative administration methods to mitigate the capacity burden on healthcare systems, without compromising the quality of care. This study assessed and compared the resource utilization and associated costs of two distinct administration modes of immune checkpoint inhibitors: the innovative elastomeric pump and conventional intravenous infusion. This comparison can inform sustainable healthcare practices and healthcare decision-making to optimize treatment efficiency in an era of escalating healthcare demands.MethodsIn this micro-costing study, data on resource use and time allocation for drug preparation and administration were collected using an observational, non-interventional study design. Data were registered at the oncology daycare unit and hospital pharmacy. Cost categories included drug acquisition, disposable materials, healthcare professional time for drug administration, drug preparation, and patient time spent at the oncology day care unit.ResultsDrug administration through the elastomeric pump resulted in substantially lower healthcare costs when compared to conventional infusion, particularly due to reduced labor and chair time. The elastomeric pump reduced the total chair time by 78% and nurse time by 55%. Total average costs (excluding drug costs) were €103,47 and €77.99 for conventional infusion and the elastomeric pump, respectively, showcasing potential savings of €25.48 (P < 0.001) per administration.ConclusionsThis study demonstrated that the elastomeric pump not only offers substantial cost savings but also enhances the treatment capacity of the oncology day care unit. These findings support the adoption of the elastomeric pump in clinical settings as a cost-saving and efficient alternative to conventional infusion.Trial registrationThis study has been registered in the National Trial Register (NTR), with the reference number NTR NL9473. Registration date: 05-05-2021.

Investigation of the Process Parameters in Rotary Friction Welded Dissimilar AA7075/AA5083 Aluminum Alloy Joints on Fatigue Initiation using FEA and ANN

The rotary friction welding (RFW) method is one of the most widespread methods in the world for producing bimetallic components that require high mechanical strength. Simulations play a vital role in improving energy efficiency and reducing environmental impact, aligning with the sustainability goals of modern industry. A neural network (NN)-based incremental learning system was developed to predict crack growth and fatigue for AA5083 and AA7075 aluminum alloys. The results indicate the ability of this method to accommodate the input temperatures and the S-N curve and provide reliable predictions of expected fatigue. This method can reduce labor costs and time spent on crack propagation tests, enhancing the effectiveness of production processes and reducing process costs. This work also reveals the ability of neural . It maynetworks (NN) in monotonic function extrapolation like the S-N curve, which may pave the way for a wide variety of monotonic function-predicting problems. In future studies, a neural network (NN)-based increment learning scheme could be trained with random parts of individual S–N curves and applied to predict the rest. Additionally, the verification utilizing AISI 2205 and AISI 1020 steel has observed that neural networks may obtain S-N curve values for another metal with less than an 8% error rate. Friction pressure increases temperature, deformation, and stress in welding processes. Friction pressure 17 MPa increases temperature to 355 degrees Celsius, while Friction pressure 23 MPa increases deformation to 0.020 mm. A friction pressure of 29 MPa increases equivalent stress to 110 MPa. The indication of the S-N curve shows that increasing welding pressure increases Alternating Stress. Friction pressure also increases life, with minimum life cycles reaching 171040 cycles at 17 MPa, 195560 cycles at 23 MPa, and 283690 cycles at 29 MPa. Comparing research and simulation results, convergence is less than 8%, reducing error.