Initial Setup Research Articles

Analysing a lean manufacturing inventory system with price-sensitive demand and carbon control policies

Production lot-sizing techniques used by lean practitioners to lower waste inventories and increase production efficiency in the manufacturing industry, are the subject of this paper’s speculation. Lean manufacturing aims to incorporate innovative tools into the manufacturing process to improve productivity and reduce processing time. In view of this, the model anticipates a flexible production rate based on labor, energy, and tool/die costs, to meet the demand while minimizing wastage. Moreover, a discrete investment in set-up costs is considered to lower the initial set-up cost since it is a critical component of smooth manufacturing operations. Further, it is found that price plays a significant role in stimulating a product’s demand; consequently, demand is presumed to be price-sensitive. Besides this, to reduce the carbon footprint in the production systems, two methods namely “Carbon tax” and “Cap-and-trade”, have been employed. The purpose of the developed model is to maximize total profit by jointly optimizing the production rate, selling price, and set-up cost. Numerical experiments are performed to validate the model findings. Results suggest that manufacturers’ production time decreases simultaneously with the introduction of advanced labor and technologies. With respect to carbon policies, the cap-and-trade policy performs better with an increase in total profit and a higher production rate as compared to a carbon tax. Also, sensitivity analysis is performed to support the manufacturer in the decision-making process for ancillary benefits of the optimal policy.

Aplanatic freeform-mirror-based optical systems.

The exact partial differential equation to design aplanatic freeform-mirror-based optical systems is presented. The partial differential equation is not limited by the number of freeform surfaces or their orientations. The solutions of this partial differential equation can be useful as initial setups that can be optimized to meet higher criteria. One of these solutions is tested as an example of the initial setup, and the results are as expected by the theory.

Instability-Induced Origami Design by Topology Optimization

Instability-induced wrinkle patterns of thin sheets are ubiquitous in nature, which often result in origami-like patterns that provide inspiration for the engineering of origami designs. Inspired by instability-induced origami patterns, we propose a computational origami design method based on the nonlinear analysis of loaded thin sheets and topology optimization. The bar-and-hinge model is employed for the nonlinear structural analysis, added with a displacement perturbation strategy to initiate out-of-plane buckling. Borrowing ideas from topology optimization, a continuous crease indicator is introduced as the design variable to indicate the state of a crease, which is penalized by power functions to establish the mapping relationships between the crease indicator and hinge properties. Minimizing the structural strain energy with a crease length constraint, we are able to evolve a thin sheet into an origami structure with an optimized crease pattern. Two examples with different initial setups are illustrated, demonstrating the effectiveness and feasibility of the method.

Challenges and opportunities in maintaining research momentum at a primarily undergraduate institution.

Conferences and meetings hosted by scientific societies usually include sessions on how to navigate the academic faculty job search and the initial setup of a laboratory, or how to identify and pursue early-career grant funding opportunities. However, there is not much professional development support available beyond this stage. Faculty may have set up the research lab and have recruited students to their groups but then might find themselves struggling to be successful in accomplishing their goals. In other words, how can we maintain the momentum once research activities are established? This Voices article summarizes a discussion carried out in the context of a round-table session at the American Society for Cell Biology's Cell Bio 2022. We sought to identify and articulate the challenges of carrying out research at primarily undergraduate institutions (PUIs), appreciate the role of undergraduate research in the science enterprise, develop strategies to overcome research challenges and recognize unique opportunities in this setting, with the ultimate goal of launching a community of "late-early" to mid-career PUI faculty.

Finding optimal decision boundaries for human intervention in one-class machine-learning models for industrial inspection

Abstract Anomaly detection with machine learning in industrial inspection systems for manufactured products relies on labelled data. This raises the question of how the labelling by humans should be conducted. Moreover, such a system will most likely always be imperfect and potentially need a human fall-back mechanism for ambiguous cases. We consider the case where we want to optimise the cost of the combined inspection process done by humans together with a pre-trained algorithm. This gives improved combined performance and increases the knowledge of the performance of the pre-trained model. We focus on so-called one-class classification problems which produce a continuous outlier score. After establishing some initial setup mechanisms ranging from using prior knowledge to calibrated models, we then define some cost model for machine inspection with a possible second inspection of the sample done by a human. Further, we discuss in this cost model how to select two optimal boundaries of the outlier score, where in between these two boundaries human inspection takes place. Finally, we frame this established knowledge into an applicable algorithm and conduct some experiments for the validity of the model.

Quantification of six-degree-of-freedom motion during beam delivery in spine stereotactic body radiotherapy using intra-irradiation cone-beam computed tomography imaging technique

PurposeQuantifying intra-fractional six-degree-of-freedom (6DoF) residual errors or motion from approved patient setups is necessary for accurate beam delivery in spine stereotactic body radiotherapy. However, previously reported errors were not acquired during beam delivery. Therefore, we aimed to quantify the 6DoF residual errors and motions during arc beam delivery using a concurrent cone-beam computed tomography (CBCT) imaging technique, intra-irradiation CBCT. MethodsConsecutive 15 patients, 19 plans for various treatment sites, and 199 CBCT images were analyzed. Pre-irradiation CBCT was performed to verify shifts from the initial patient setup using the ExacTrac system. During beam delivery by two or three co-planar full-arc rotations, CBCT imaging was performed concurrently. Subsequently, an intra-irradiation CBCT image was reconstructed. Pre- and intra-irradiation CBCT images were rigidly registered to a planning CT image based on the bone to quantify 6DoF residual errors. Results6DoF residual errors quantified using pre- and intra-irradiation CBCTs were within 2.0 mm/2.0°, except for one measurement. The mean elapsed time (mean ± standard deviation [min:sec]) after pre-irradiation CBCT to the end of the last arc beam delivery was 6:08 ± 1:25 and 7:54 ± 2:14 for the 2- and 3-arc plans, respectively. Root mean squares of residual errors for several directions showed significant differences; however, they were within 1.0 mm/1.0°. Time-dependent analysis revealed that the residual errors tended to increase with elapsed time. ConclusionThe errors represent the optimal intra-fractional error compared with those acquired using the pre-, inter-beam, and post-6DoF image guidance and can be acquired within a standard treatment timeslot.

Topic detection with recursive consensus clustering and semantic enrichment

Extracting meaningful information from short texts like tweets has proved to be a challenging task. Literature on topic detection focuses mostly on methods that try to guess the plausible words that describe topics whose number has been decided in advance. Topics change according to the initial setup of the algorithms and show a consistent instability with words moving from one topic to another one. In this paper we propose an iterative procedure for topic detection that searches for the most stable solutions in terms of words describing a topic. We use an iterative procedure based on clustering on the consensus matrix, and traditional topic detection, to find both a stable set of words and an optimal number of topics. We observe however that in several cases the procedure does not converge to a unique value but oscillates. We further enhance the methodology using semantic enrichment via Word Embedding with the aim of reducing noise and improving topic separation. We foresee the application of this set of techniques in an automatic topic discovery in noisy channels such as Twitter or social media.

Experiences on the Utility and Barriers of Telemedicine in Healthcare Delivery in Kenya.

Telemedicine is the provision of health services over a distance using information communication technology devices. Telemedicine is emerging as a promising component of healthcare care delivery worldwide, accelerated by the COVID-19 pandemic. This study assessed the factors promoting uptake, barriers, and opportunities for telemedicine among doctors in Kenya. Methodology. A semiquantitative, cross-sectional online survey was conducted among doctors in Kenya. During a month, between February and March 2021, 1,200 doctors were approached by email and WhatsApp, of whom 13% responded. Findings. A total of 157 interviewees participated in the study. The general usage of telemedicine was 50%. Seventy-three percent of doctors reported using a mix of in-person care and telemedicine. Fifty percent reported using telemedicine to support physician-to-physician consultations. Telemedicine had limited utility as a standalone clinical service. The inadequate information communication technology infrastructure was the most reported barrier to telemedicine, followed by a cultural resistance to using technology to deliver healthcare services. Other notable barriers were the high cost of initial setup limited skills among patients, limited skills among doctors, inadequate funding to support telemedicine services, weak legislative/policy framework, and lack of dedicated time for telemedicine services. The COVID-19 pandemic increased the uptake of telemedicine in Kenya. The most extensive use of telemedicine in Kenya supports physician-to-physician consultations. There is limited single use of telemedicine in providing direct clinical services to patients. However, telemedicine is regularly used in combination with in-person clinical services, allowing for continuity of clinical services beyond the physical hospital infrastructure. With the widespread adoption of digital technologies in Kenya, especially mobile telephone technologies, the growth opportunities for telemedicine services are immense. Numerous mobile applications will improve access capabilities for both service providers and users and bridge the gaps in care.

Learning asymmetric encryption using adversarial neural networks

We propose a multi-agent adversarial neural networks model where a sender (Alice) and a receiver (Bob) are able to learn to use a pair of public/private keys in order to protect their communication from one or more attackers/eavesdroppers. Existing work in the field required shared symmetric information between Alice and Bob before initiating the training process. To the best of our knowledge, this is the first work in which Alice and Bob with asymmetric information can train themselves to protect their communication. Our initial model setup contains five agents: sender Alice, receiver Bob, eavesdropper Eve and two neural networks (we call them public keys generator and private keys generator) that, based on a (secret) random noise from Bob, will generate a pair of public/private keys that allows Alice to encrypt a message with the public key and Bob to decrypt the message with the private key while preventing Eve from decrypting the secret message using the public key. We show that the neural networks are able to establish a communication and secure it from Eve. Finally, we consider adversaries stronger than Eve to model leakage attacks, chosen plaintext attacks (CPA) and test the distinguishability between ciphertexts. The last three experiments show that neural networks (with asymmetric information) can secure the communication providing stronger security guarantees and resilience to leakage attacks which may include leakage from the private key.

Numerical dependencies of the galactic dynamo in isolated galaxies with SPH

Simulating and evolving magnetic fields within global galaxy simulations provides a large tangled web of numerical complexity due to the vast amount of physical processes involved. Understanding the numerical dependencies that act on the galactic dynamo is a crucial step in determining what resolution and conditions are required to properly capture the magnetic fields observed in galaxies. Here, we present an extensive study on the numerical dependencies of the galactic dynamo in isolated spiral galaxies using smoothed particle magnetohydrodynamics. We performed 53 isolated spiral galaxy simulations with different initial setups, feedback, resolution, Jeans floor, and dissipation parameters. The results show a strong mean-field dynamo occurring in the spiral-arm region of the disk, likely produced by the classical alpha-omega dynamo or the recently described gravitational instability dynamo. The inclusion of feedback is seen to work in both a destructive and positive fashion for the amplification process. Destructive interference for the amplification occurs due to the breakdown of filament structure in the disk, the increase of turbulent diffusion, and the ejection of magnetic flux from the central plane to the circumgalactic medium. The positive effect of feedback is the increase in vertical motions and the turbulent fountain flows that develop, showing a high dependence on the small-scale vertical structure and the numerical dissipation within the galaxy. Galaxies with an effective dynamo saturate their magnetic energy density at levels between 10 and 30% of the thermal energy density. The density-averaged numerical Prandtl number is found to be below unity throughout the galaxy for all our simulations, with an increasing value with radius. Assuming a turbulent injection length of 1 kpc, the numerical magnetic Reynolds number is within the range of Remag = 10 − 400, indicating that some regions are below the levels required for the small-scale dynamo (Remag, crit = 30 − 2700) to be active.

Towards optimization of polymer filament tensile test for material extrusion additive manufacturing process

Material extrusion (MEX) is a popular additive manufacturing (AM) method that can process a wide range of feedstock materials, most commonly in filament form. Currently, there is no standardized testing method for filament tensile properties, and researchers resort to 3D-printed dog-bone specimens, which necessarily include the effects of the printing process. In this study, the impact of the strain measurement device, knife-edge type, gage length, testing speed, and oven treatment on filament tensile properties was explored using an off-the-shelf fixture. It was observed that an extensometer with blunt knife edges, a filament gage length of 165 mm, and a 6.35 mm/min (0.25 in./min) testing speed could accurately evaluate the tensile properties of acrylonitrile butadiene styrene (ABS) filaments. In addition, an optimized raster path, 3D printing design, and process parameters were used to manufacture dog bone tensile specimens according to ASTM D638-22 from the same ABS filament spool. The tensile properties of the filaments were validated using the results of 3D-printed dog-bone specimens. Young's modulus, stress at yield, and stress at break for the optimum filament test set (2.20 GPa, 43.9 MPa, and 39.1 MPa) were very similar to those of the 3D-printed specimens (2.26 GPa, 44.9 MPa, and 37.3 MPa). The optimum filament tensile testing parameters determined in this study for ABS can be used for the initial test setup for other filament materials to provide baseline values that can serve as the foundation for AM process development.

Evaluation of initial patient setup methods for breast cancer between surface-guided radiation therapy and laser alignment based on skin marking in the Halcyon system

BackgroundThis study was conducted to evaluate the efficiency and accuracy of the daily patient setup for breast cancer patients by applying surface-guided radiation therapy (SGRT) using the Halcyon system instead of conventional laser alignment based on the skin marking method.Methods and materialsWe retrospectively investigated 228 treatment fractions using two different initial patient setup methods. The accuracy of the residual rotational error of the SGRT system was evaluated by using an in-house breast phantom. The residual translational error was analyzed using the couch position difference in the vertical, longitudinal, and lateral directions between the reference computed tomography and daily kilo-voltage cone beam computed tomography acquired from the record and verification system. The residual rotational error (pitch, yaw, and roll) was also calculated using an auto rigid registration between the two images based on Velocity. The total setup time, which combined the initial setup time and imaging time, was analyzed to evaluate the efficiency of the daily patient setup for SGRT.ResultsThe average residual rotational errors using the in-house fabricated breast phantom for pitch, roll, and yaw were 0.14°, 0.13°, and 0.29°, respectively. The average differences in the couch positions for laser alignment based on the skin marking method were 2.7 ± 1.6 mm, 2.0 ± 1.2 mm, and 2.1 ± 1.0 mm for the vertical, longitudinal, and lateral directions, respectively. For SGRT, the average differences in the couch positions were 1.9 ± 1.2 mm, 2.9 ± 2.1 mm, and 1.9 ± 0.7 mm for the vertical, longitudinal, and lateral directions, respectively. The rotational errors for pitch, yaw, and roll without the surface-guided radiation therapy approach were 0.32 ± 0.30°, 0.51 ± 0.24°, and 0.29 ± 0.22°, respectively. For SGRT, the rotational errors were 0.30 ± 0.22°, 0.51 ± 0.26°, and 0.19 ± 0.13°, respectively. The average total setup times considering both the initial setup time and imaging time were 314 s and 331 s, respectively, with and without SGRT.ConclusionWe demonstrated that using SGRT improves the accuracy and efficiency of initial patient setups in breast cancer patients using the Halcyon system, which has limitations in correcting the rotational offset.

Prediction and validation of melt pool dimensions and geometric distortions of additively manufactured AlSi10Mg

A finite element–based thermomechanical modeling approach is developed in this study to provide a prediction of the mesoscale melt pool behavior and part-scale properties for AlSi10Mg alloy. On the mesoscale, the widely adopted Goldak heat source model is used to predict melt pool formed by laser during powder bed fusion process. This requires the determination of certain parameters as they control temperature distribution and, hence, melt pool boundaries. A systematic parametric approach is proposed to determine parameters, i.e., absorption coefficient and transient temperature evolution. The simulation results are compared in terms of morphology of melt pool with the literature results. Considering the part-scale domain, there is increasing demand for predicting geometric distortions and analyzing underlying residual stresses, which are highly influenced by the mesh size and initial temperature setup. This study aims to propose a strategy for evaluating the correlation between the mesh size and the initial temperature to provide correct residual stresses when increasing the scale of the model for efficiency. The outcomes revealed that the predicted melt pool error produced by optimal Goldak function parameters is between 5 and 12%. On the part-scale, the finite element model is less sensitive to mesh size for distortion prediction, and layer-lumping can be used to increase the speed of simulation. The effect of large time increments and layer lumping can be compensated by appropriate initial temperature value for AlSi10Mg. The study aids practitioners and researchers to establish and validate design for additive manufacturing within the scope of desired part quality metrics.

The usage of RFID robots in logistics process management

The aim of this post is to point out the use of RFID robots in the management of logistics processes. RFID technology is defined first. RFID technology represents identification using radio frequency waves. The principle is to store the necessary data in radio frequency memory chips and then repeatedly read or write the data using a reader. We divide RFID chips into active and passive. Active RFID chips use energy from a battery, while passive RFID chips are a technology without an internal power source. Passive RFID is the most common form of RFID in warehouses, using which inventory is taken using RFID robots or hand-held RFID readers. Nowadays, many RFID robots from different manufacturers are available on the market. When choosing, I must consider where we want to use the RFID robot and choose the one that suits us based on its specific characteristics. The RFID robot is a mobile and autonomous RFID system that performs an inventory of the given space based on our initial setup. The RFID robot locates each item in 2 dimensions (x and y). Most robots can move in all directions because they can rotate without shifting. The accuracy of the inventory using the RFID robot ranges from 95-99%, while the accuracy of the inventory performed by employees using handheld RFID readers ranges from 85-95%. As for speed, it is on average 10 times faster compared to manual RFID readers.

Автоматизация технологического процесса балансировки кварцевых резонаторов твердотельных волновых гироскопов

The paper discusses the main issues that arise while developing and implementing automatic process control systems (APCS) in relation to the technological operations of balancing quartz hemispherical resonators of solid-state wave gyroscopes. For this, the article gives a general algorithm for performing the technological process of resonator balancing; block diagrams of the automatic process control system of balancing and the general algorithm for balancing the resonators. The latter discloses internal algorithms for determining the physical parameters of the gyroscope resonator, for making a decision on resonator balancing and controlling the etching process of the gyroscope quartz resonator. The necessary application software (SW) for the automatic process control system for balancing gyroscope resonators is considered separately. The paper states that to build the first version of the automatic process control system for balancing resonators, it is recommended, as an intermediate step, to modernise and work out the “advising” automatic process control system, which, in the development of the existing locally automatic process control system, should be supplemented by solving the following important tasks: increasing the accuracy of determining physical parameters, calculating the efficiency of the ongoing balancing operation and estimating the effective control of the ion-plasma source. In the considered automatic process control system for balancing the resonators of the solid state wave gyroscopes (SSWG), it is not supposed to completely exclude the system operator’s role and importance. He performs the primary check of the stand, the installation of the resonator in the stand, as well as the initial setup. Automation at the first stage will consist of closing the operations of determining the physical parameters, calculating the balancing efficiency and ion-plasma etching of the quartz resonator. The closure of these operations is carried out with the help of application software installed on the central control computer of the automated workplace of the balancing system operator.

Direct numerical simulations of liquid–liquid dispersions in a SMX mixer under different inlet conditions

The internal dynamics of static mixers handling liquid–liquid flows have been comprehensively explored over the past decade. Although the effect of the inlet configuration is often overlooked, a few studies have suggested a relationship between the phases’ initial set-up and the performance of the mixer in terms of the droplet size distribution (DSD). Accordingly, different dispersed phase morphologies at the inlet of a SMX static mixer have been tested and their effect on the overall dispersion performance of the mixer has been evaluated based on the DSD and growth of interfacial area. In particular, three representative scenarios are considered: (1) Isolated cases, where one and three individual droplets are injected, mimicking a controlled syringe injection; (2) Numerous variable-sized droplets, simulating a pre-mixed/dispersed inlet; and (3) Jet inlet, emulating a standard phase injection from a gear pump. In addition, this study provides novel insight into the underlying physics dictating droplet deformation and breakage in SMX mixers for industrially-relevant scenarios. This can be achieved thanks to the massively-parallel high-fidelity three-dimensional direct numerical simulations computed with a robust hybrid front-tracking/level-set algorithm, which provides a wealth of information on intricate interfacial dynamics; this information cannot be obtained via experimental or volume-averaged modelling techniques implemented in past studies.

La vida es sueño, de Pedro Calderón de la Barca. Versión de Virtudes Serrano

La vida es sueño, de Pedro Calderón de la Barca. Versión de Virtudes Serrano

The Gibraltar slab dynamics and its influence on past and present-day Alboran domain deformation: Insights from thermo-mechanical numerical modelling

The origin and tectonic evolution of the Gibraltar Arc system is the result of a complex geodynamic evolution involving the convergence of the Eurasian and African plates and the dynamic impact of the Gibraltar slab. Although geologic and geophysical data collected in the last few years have increased our knowledge of the Gibraltar Arc region, it is still unclear which are the mechanical links between the Gibraltar slab and the past deformation of the overriding Alboran lithosphere, as well as to which degree this subduction system is presently active. In this study, we use 2D numerical modelling to investigate the impact of the Gibraltar slab dynamics on the deformation of the overriding Alboran lithosphere. Our model simulates a WE generic vertical section at an approximate latitude of 36°N and considers an initial setup at about Burdigalian times (∼20 Ma), when the subduction front position is relatively well constrained by recent tectonic reconstructions. Our modelling shows a switch in the overriding plate (OP) stress state from extensional stresses during the slab rollback to compressional stresses near the trench when the rollback velocity decreases, caused by the change in slab-induced mantle flow. We also find that much of the crustal and lithospheric deformation occur during fast slab rollback and OP extension in the first 10 Myr of evolution, while after that only moderate deformation associated with subduction is predicted. Finally, we find that despite the subduction rollback ceases, the ongoing motion of the deeper portion of the slab induces a mantle flow that causes some amount of west-directed basal drag of the Alboran lithosphere. This basal drag generates interplate compresional stresses compatible with the distribution of intermediate-depth earthquakes in western Alboran.

Using additive regression models for short-term forecasting of financial macro-indicators and assessing the potential for financing megaprojects

The subject of this article is the issue of using additive regression models to predict financial indicators at the macro level. At the same time, special attention is paid to the impact of the economy monetization on the possibility of attracting funding for global development projects (megaprojects). It is shown that the main drawback of the most common forecasting models today is their situation-dependent nature. This, in turn, creates difficulties with the initial setup of the models and the subsequent interpretation of the results obtained, limiting the scope of the models, making the use of this toolkit difficult for financial professionals who do not have special mathematical training. With the help of modeling, forecast values of the gross domestic product (GDP) and money supply (M2) for the short-term time obtained, on the basis of which the expected value of the level of the economy monetization was calculated. Based on a predictive assessment of the level of monetization, it is shown that at the moment the country has a limited potential for increasing domestic debt, which, in the conditions of closing access to international capital markets and partial blocking of state reserves, can become a factor in disrupting the financing of megaprojects for the economy structural modernization. Directions for improving the monetary policy aimed at correcting this situation and increasing domestic investment activity are proposed.

The modern face of newborn screening.

Newborn screening (NBS) has been developed for years to identify newborns with severe but treatable conditions. Taiwan's NBS system, after the initial setup for a total coverage of newborns in 1990s, was later optimized to ensure the timely return of results in infants with abnormal results. Advancements in techniques such as Tandem mass spectrometry enable the screening into a multiplex format and increase the conditions to be screened. Furthermore, advances in therapies, such as enzyme replacement therapy, stem cell transplantation, and gene therapy, significantly expand the needs for newborn screening. Advances in genomics and biomarkers discovery improve the test accuracy with the assistance of second-tier tests, and have the potential to be the first-tier test in the future. Therefore, challenge of NBS now is the knowledge gap, including the evidence of the long-term clinical benefits in large cohorts especially in conditions with new therapies, phenotypic variations and the corresponding management of some screened diseases, and cost-effectiveness of extended NBS programs. A short-term and a long-term follow-up program should be implemented to gather those outcomes better especially in the genomic era. Ethical and psychosocial issues are also potentially encountered frequently. Essential education and better informed consent should be considered fundamental to parallel those new tests into future NBS.