Low-cost Model Research Articles

Do rising labour costs promote technology upgrading? A novel theoretical hypothesis of an inverted U-shaped relationship

Although many studies have examined the impact of rising labour costs on enterprises’ innovation, there remains a lack of consensus on this issue. Combining the induced innovation hypothesis and the impeded innovation perspective, this study constructs a theoretical model to comprehensively investigate the mechanism of the effect of rising labour costs on technology upgrading. The theoretical model demonstrates that rising labour costs increase technology upgrading ‘impetus’ but reduce ‘capability’. Finally, an inverted U-shaped relationship between rising labour costs and technology upgrading is revealed. Empirical evaluations using data from Chinese listed companies confirm the theoretical hypotheses. This study also investigates the moderating effect of market position, wherein firms with low competitive positions have greater curvature. The results provide new explanations for the theoretical debate and practical evidence, with significant implications for emerging markets regarding the transition from a low-cost labour development model to an innovation-driven growth model.

Design of Ultrawideband RCS Reduction Metasurface Using Space Mapping and Phase Cancellation

An efficient optimizing method of ultra-wideband radar cross-section (RCS) reduction metasurface involve unit amplitude differences and mutual coupling effects is proposed in the letter. Multiple unit phase cancellation was used to broaden RCS-reduction bandwidth. The genetic algorithm was utilized to further design and select the optimal combination from various tiles. To improve the optimization efficiency and accuracy, the space mapping (SM) technique was exploited to refine the design process, which involves the interactions of scattering fields among tiles and subarrays in wideband. Meanwhile, the constraint of wide-angle oblique incidences is also considered in wideband low RCS design. An ultra-wideband RCS reduction checkboard meatsurface can be accomplished by fast optimization of low-cost coarse model and few parameter mapping courses between fine and coarse model. A 10dB RCS reduction for HH and VV polarizations under normal and other oblique incidence angles can be achieved from 5 to 40 GHz. Good agreements between simulation and experiment results are obtained.

The use of near-infrared as process analytical technology (PAT) during 3D printing tablets at the point-of-care

Fused deposition modelling (FDM) is one of the most researched 3D printing technologies that holds great potential for low-cost manufacturing of personalised medicine. To achieve real-time release, timely quality control is a major challenge for applying 3D printing technologies as a point-of-care (PoC) manufacturing approach. This work proposes the use of a low-cost and compact near-infrared (NIR) spectroscopy modality as a process analytical technology (PAT) to monitor a critical quality attribute (drug content) during and after FDM 3D printing process. 3D printed caffeine tablets were used to manifest the feasibility of the NIR model as a quantitative analytical procedure and dose verification method. Caffeine tablets (0–40 % w/w) were fabricated using polyvinyl alcohol and FDM 3D printing. The predictive performance of the NIR model was demonstrated in linearity (correlation coefficient, R2) and accuracy (root mean square error of prediction, RMSEP). The actual drug content values were determined using the reference high-performance liquid chromatography (HPLC) method. The model of full-completion caffeine tablets demonstrated linearity (R2 = 0.985) and accuracy (RMSEP = 1.4 %), indicated to be an alternative dose quantitation method for 3D printed products. The ability of the models to assess caffeine contents during the 3D printing process could not be accurately achieved using the model built with complete tablets. Instead, by building a predictive model for each completion stage of 20 %, 40 %, 60 % and 80 %, the model of different completion caffeine tablets displayed linearity (R2 of 0.991, 0.99, 0.987, and 0.983) and accuracy (RMSEP of 2.22 %, 1.65 %, 1.41 %, 0.83 %), respectively. Overall, this study demonstrated the feasibility of a low-cost NIR model as a non-destructive, compact, and rapid analysis dose verification method enabling the real-time release to facilitate 3D printing medicine production in the clinic.

Molecular Design of Luminescent Complexes of Eu(III): What Can We Learn from the Ligands.

The luminescent metal-organic complexes of rare earth metals are advanced materials with wide application potential in chemistry, biology, and medicine. The luminescence of these materials is due to a rare photophysical phenomenon called antenna effect, in which the excited ligand transmits its energy to the emitting levels of the metal. However, despite the attractive photophysical properties and the intriguing from a fundamental point of view antenna effect, the theoretical molecular design of new luminescent metal-organic complexes of rare earth metals is relatively limited. Our computational study aims to contribute in this direction, and we model the excited state properties of four new phenanthroline-based complexes of Eu(III) using the TD-DFT/TDA approach. The general formula of the complexes is EuL2A3, where L is a phenanthroline with -2-CH3O-C6H4, -2-HO-C6H4, -C6H5 or -O-C6H5 substituent at position 2 and A is Cl- or NO3-. The antenna effect in all newly proposed complexes is estimated as viable and is expected to possess luminescent properties. The relationship between the electronic properties of the isolated ligands and the luminescent properties of the complexes is explored in detail. Qualitative and quantitative models are derived to interpret the ligand-to-complex relation, and the results are benchmarked with respect to available experimental data. Based on the derived model and common molecular design criteria for efficient antenna ligands, we choose phenanthroline with -O-C6H5 substituent to perform complexation with Eu(III) in the presence of NO3¯. Experimental results for the newly synthesized Eu(III) complex are reported with a luminescent quantum yield of about 24% in acetonitrile. The study demonstrates the potential of low-cost computational models for discovering metal-organic luminescent materials.

Low-Cost Object Detection Models for Traffic Control Devices through Domain Adaption of Geographical Regions

Automated inspection systems utilizing computer vision technology are effective in managing traffic control devices (TCDs); however, they face challenges due to the limited availability of training datasets and the difficulty in generating new datasets. To address this, our study establishes a benchmark for cost-effective model training methods that achieve the desired accuracy using data from related domains and YOLOv5, a one-stage object detector known for its high accuracy and speed. In this study, three model cases were developed using distinct training approaches: (1) training with COCO-based pre-trained weights, (2) training with pre-trained weights from the source domain, and (3) training with a synthesized dataset mixed with source and target domains. Upon comparing these model cases, this study found that directly applying source domain data to the target domain is unfeasible, and a small amount of target domain data is necessary for optimal performance. A model trained with fine-tuning-based domain adaptation using pre-trained weights from the source domain and minimal target data, proved to be the most resource-efficient approach. These results contribute valuable guidance for practitioners aiming to develop TCD models with limited data, enabling them to build optimal models while conserving resources.

VILO SLAM: Tightly Coupled Binocular Vision–Inertia SLAM Combined with LiDAR

For the existing visual–inertial SLAM algorithm, when the robot is moving at a constant speed or purely rotating and encounters scenes with insufficient visual features, problems of low accuracy and poor robustness arise. Aiming to solve the problems of low accuracy and robustness of the visual inertial SLAM algorithm, a tightly coupled vision-IMU-2D lidar odometry (VILO) algorithm is proposed. Firstly, low-cost 2D lidar observations and visual–inertial observations are fused in a tightly coupled manner. Secondly, the low-cost 2D lidar odometry model is used to derive the Jacobian matrix of the lidar residual with respect to the state variable to be estimated, and the residual constraint equation of the vision-IMU-2D lidar is constructed. Thirdly, the nonlinear solution method is used to obtain the optimal robot pose, which solves the problem of how to fuse 2D lidar observations with visual–inertial information in a tightly coupled manner. The results show that the algorithm still has reliable pose-estimation accuracy and robustness in many special environments, and the position error and yaw angle error are greatly reduced. Our research improves the accuracy and robustness of the multi-sensor fusion SLAM algorithm.

Simulation-Based Breast Biopsy Training Using a Low-Cost Gelatin-Based Breast Model in Rwanda.

An interdisciplinary team of healthcare providers and simulation specialists adopted and modified a protocol for the creation of a low-cost, gelatin-based breast model for teaching ultrasound-guided breast biopsy and assessed first-time user experience. An interdisciplinary team of healthcare providers and simulation specialists adopted and modified a protocol for the creation of a low-cost, gelatin-based breast model for teaching ultrasound-guided breast biopsy for approximately $4.40 USD. Components include medical-grade gelatin, Jell-O™, water, olives, and surgical gloves. The model was used to train two cohorts comprising 30 students total during their junior surgical clerkship. The learners' experience and perceptions on the first Kirkpatrick level were evaluated using pre- and post-training surveys. Response rate was 93.3% (n = 28). Only three students had previously completed an ultrasound-guided breast biopsy, and none had prior exposure to simulation-based breast biopsy training. Learners that were confident in performing biopsies under minimal supervision rose from 4 to 75% following the session. All students indicated the session increased their knowledge, and 71% agreed that the model was an anatomically accurate and appropriate substitute to a real human breast. The use of a low-cost gelatin-based breast model was able to increase student confidence and knowledge in performing ultrasound-guided breast biopsies. This innovative simulation model provides a cost-effective and more accessible means of simulation-based training especially for low- and middle-income settings.

Chick embryo in experimental embryology and more

Chicken remains an undisputed, powerful, useful, and practical model in developmental research. Chick embryos have been used as model systems for studies in experimental embryology and teratology. As the chicken embryo develops outside the mother, effects of external stresses on cardiovascular development can be studied without interferences of maternal hormonal, metabolic, or hemodynamic alterations. In 2004, the first draft sequence of the complete chicken genome was released, allowing broad genetic analysis and comparison to humans, and enabling expansion of transgenic techniques within the chick model. The chick embryo is relatively simple, quick, and low-cost model. The main advantages of the chick as a model system for experimental embryology are the ease with cells and tissues can be labeled, transplanted, and cultured, along with its similarity to mammalian systems.

Utilizing AEMS (Assess-EOP-Map-Simulate) Algorithm to Assess and Spatially Link Prehospital Emergency Medical Services Resources in Road-Traffic Mass Casualty Incidents in Kumasi, Ghana

Introduction:Due to the high number of road traffic accidents with acute injuries and fatalities–particularly in Mass Casualty Incidents (MCI) in low-resource urban sub-Saharan African cities–research was undertaken to create an evidence-based algorithm that could be used to assess and geospatially link EMS needs in Kumasi, Ghana, to trauma resources. Our examination showed that non-MCI fatalities was approximately 2.5%, however, MCI fatalities were found to be 1.8 times higher–at 4.3%, indicating significant opportunities in the planning, preparedness, care, and transport among MCI patient management.Therefore, several studies (funded through Fulbright-Fogarty and Fulbright Specialist programs), supported the development of the A-E-M-S (Assess-EOP-Map-Simulate) Medical Mass Casualty Algorithm that began networking accident ‘hotspots’ to existing trauma-level capabilities and surge capacity competencies in eight specified Kumasi hospitals. This low-cost response model promises to be an innovative alternative to long-term infrastructure development and high-priced resource distributions. Use of GIS and UAV drones allowed response systems to geospatially locate, classify, shift, and/or augment resources as needed in conjunction with hotspots.Method:Sample sizes were averaged at 295 for all patients' ages, with only a sample size of 292 for adults at 95% confidence intervals, and a standard deviation of 0.5. A total of 300 road-traffic accident victims were collected at KATH A&E in February-May, 2017, utilizing handheld devices by four researchers 24/7 daily.Results:Our examination showed that non-MCI fatalities were approximately 2.5%, however, MCI fatalities were found to be 1.8 times higher–at 4.3%, indicating significant opportunities in the planning, preparedness, care, and transport among MCI patient management.Conclusion:To date–and in partnership with Kwame Nkrumah University of Science and Technology, Komfo Anokye Teaching Hospital, Ghana Medical Council, Health Services, National Disaster Management Organization, and others–over 306 Ghanaian healthcare providers from 80 different facilities have been trained in the AEMS program.

Development of Low-Cost Wave Measurement Model Using Ultrasonic Sensor JSN-SR04T for Supporting Seakeeping Test in the Maneuvering and Engineering Ocean Basin (MOB)

Development of Low-Cost Wave Measurement Model Using Ultrasonic Sensor JSN-SR04T for Supporting Seakeeping Test in the Maneuvering and Engineering Ocean Basin (MOB)

A Paper-Based Simulation Model for Teaching Inguinal Hernia Anatomy

BackgroundInguinal hernias remain a challenging area of learning for medical students due to its relatively complex anatomy. Modern curriculum delivery methods are conventionally limited to didactic lectures and demonstration of anatomy intraoperatively. These strategies have limitations; lectures are inherently descriptive and based on 2-dimensional models, while intraoperative teaching is often unstructured and opportunistic.MethodsA paper-based model was developed comprising three overlapping paper panels simulating the anatomical layers of the inguinal canal which can be modified readily to further simulate various hernia pathologies and their surgical repair. These models were incorporated into a timetabled structured learning session for 3rd- and 4th-year medical students. Learners responded to fully anonymised surveys before and after the learning session.FindingsA total of 45 students participated in these sessions over a period of 6 months. Pre-learning session mean ratings for the learners’ confidence in their understanding of the layers of the inguinal canal, identifying indirect and direct inguinal hernias and in naming the contents of the inguinal canal were 2.5, 3.3 and 2.9, while post-learning session mean ratings were 8.0, 9.4 and 8.2, respectively. Paired samples Student’s t-tests for all three questions were statistically significant (p < 0.001). The mean rating for usefulness of the session was 9.6/10. Free comments from students emphasised the models’ usefulness as a visual learning aid.Discussion and ConclusionOur novel, low-cost paper model was associated with an improvement in learners’ perceived knowledge and understanding of inguinal canal anatomy and pathology.

Hybrid HP-BOA: An Optimized Framework for Reliable Storage of Cloud Data Using Hybrid Meta-Heuristic Algorithm

The prime objective of the cloud data storage process is to make the service, irrespective of being infinitely extensible, a more reliable storage and low-cost model that also encourages different data storage types. Owing to the storage process, it must satisfy the cloud users’ prerequisites. Nevertheless, storing massive amounts of data becomes critical as this affectsthe data quality or integrity. Hence, this poses various challenges for existing methodologies. An efficient, reliable cloud storage model is proposed using a hybrid heuristic approach to overcome the challenges. The prime intention of the proposed system is to store the data effectively in the cloud environment by resolving two constraints, which are general and specific (structural). The cloud data were initially gathered and used to analyze the storage performance. Since the data were extensive, different datasets and storage devices were considered. Every piece of data was specified by its corresponding features, whereas the devices were characterized by the hardware or software components. Subsequently, the objective function was formulated using the network’s structural and general constraints. The structural constraints were determined by the interactions between the devices and data instances in the cloud. Then, the general constraints regarding the data allocation rules and device capacity were defined. To mitigate the constraints, the components were optimized using the Hybrid Pelican–Billiards Optimization Algorithm (HP-BOA) to store the cloud data. Finally, the performance was validated, and the results were analyzed and compared against existing approaches. Thus, the proposed model exhibited the desired results for storing cloud data appropriately.

Development and Validation of a Simulation Model for Collection of Canine Vaginal Samples.

Vaginal cytology is a widely used cytological technique mostly taught by observation, either through direct tutoring or videos. To the best of our knowledge, vaginal cytology simulators have never been assessed in veterinary medicine. Twenty-five undergraduate students with no prior experience in canine vaginal sampling were randomly assigned to two groups that either practiced the procedure in a simulator or a live animal. An inverted classroom design was followed. After observing a video tutorial, students practiced with the simulator/live animal for two classes. Three weeks later, they performed a vaginal cytology on a live animal being recorded. The videos were evaluated through an objective structured clinical examination (OSCE) by an observer blinded to the student's groups. The learning outcome was compared through OSCE pass rates and questionnaires. The simulation model was made by 3D printing and soft silicone for the vulvar labia, having pink and blue colored vaseline in the correct and incorrect locations for sampling. The model was economic and accurately replicated the female reproductive tract. It provided immediate feedback to students, by obtaining pink or blue swabs from the correct and incorrect locations, respectively. Students reported that three to five or more attempts were needed to properly learn the procedure, thus justifying the need for a simulator. No differences in the OSCE pass rates were observed between the groups. The simulation model was effective for learning the vaginal cytology procedure, replacing the use of live animals. This low-cost model should be incorporated in the tool-kit of reproduction classes.

Multi-response optimization for a low-cost multi-dimpling process

PurposeThis study aims to identify the significant factors of the multi-dimpling process, determine the most influential parameters of multi-dimpling to increase the dimple sheet strength and make a low-cost model of the multi-dimpling for sheet metal industries. To create an empirical expression linking process performance to different input factors, the percentage contribution of these elements is also calculated.Design/methodology/approachTaguchi grey relational analysis is used to apply a new effective strategy to experimental data in order to optimize the dimpling process parameters while taking into account several performance factors and low-cost model. In addition, a statistical method called ANOVA is used to ensure that the results are adequate. The optimal process parameters that generate improved mechanical properties are determined via grey relational analysis (GRA). Every level of the process variables, a response table and a grey relational grade (GRG) has been established.FindingsThe factors created for experiment number 2 with 0.5 mm as the sheet thickness, 2 mm dimple diameter, 0.5 mm dimple depth, 8 mm dimples spacing and the material of SS 304 were allotted rank one, which belonged to the optimal parameter values giving the greatest value of GRG.Practical implicationsThe study demonstrates that the process parameters of any dimple sheet manufacturing industry can be optimized, and the effect of process parameters can be identified.Originality/valueThe proposed low-cost model is relatively economical and readily implementable to small- and large-scale industries using newly developed multi-dimpling multi-punch and die.

Results of training with a low-cost simulation model for endoscope-assisted scaphocephaly repair.

Endoscope-assisted repair of sagittal craniosynostosis is an effective technique that requires a learning curve. Surgical simulation models can be applied to acquire the necessary skills for this procedure. Several models with a wide range of costs have been described for training in this technique. The aim of this work was to present the results of training with a low-cost simulation model for endoscope-assisted sagittal craniosynostosis repair. A simulation model for sagittal craniosynostosis was developed using low-cost materials. The model is easily assembled and allows successive uses. Three neurosurgery residents, 3 fellows, and 2 neurosurgeons performed a 4-session training program in sagittal craniosynostosis repair. The Global Rating Scale (GRS) score, number of errors, and the time required to perform the task were reported by 2 independent evaluators using a checklist. Measurements were compared between the first and last training using the Wilcoxon signed-rank test. All participants completed a questionnaire (5-point Likert scale) regarding the realism of the simulation model. A model was developed to recreate the steps required to perform an endoscope-assisted scaphocephaly repair with the patient in a simulated sphinx position. All participants improved their GRS performance between the first and final training. The median time needed to perform the initial training was 47.5 minutes (interquartile range [IQR] 44.5-48 minutes, interrater difference [IRD] p = 0.77), and for the last training was 40.5 minutes (IQR 35.5-43 minutes, IRD p > 0.99). The median number of errors reported in the initial training was 5.5 (IQR 3-7.75 errors, IRD p = 0.8), and in the last training was 1 (IQR 0.75-2.25 errors, IRD p = 0.35). There was a statistically significant difference regarding the time and number of errors between the initial and final training (p < 0.001). More than 85% of the participants found that the surface anatomy, skull and anterior fontanel, fused sagittal suture, and epidural space of the model were realistic and had appropriate detail required to perform the surgery. All respondents agreed or strongly agreed that the endoscope handling was realistic, and that the steps and skills required to complete the task were representative of those required for the real procedure. A low-cost sagittal craniosynostosis simulation model was developed, allowing successive uses. The acquisition of skills within the simulation was demonstrated for all participants regarding the GRS score and the number of errors and time needed to perform the task. In addition, the model was found to be realistic in terms of anatomical references and the procedural steps required for this minimally invasive technique.

368 Development, Outcome and Costs of a Simulation-Based Neurosurgery Bootcamp at the National Level

INTRODUCTION: With a growing interest in simulation-based training to develop clinical proficiency, bootcamps have been utilized for imparting basic skills to medical trainees. Some research on the topic has been published from high income countries, with considerable costs of the course. No such neurosurgical teaching standards have been employed in Low-and Middle-Income Countries METHODS: It was a cross-sectional study. Twenty two participants hailing from 6 institutes attended 12 lectures, and practiced 12 hands-on skills. Burr-holes and craniotomies were done on 3D printed skulls. Lumbar drain insertion was practiced on a lumbar puncture mannequin. For laminectomy, we used an indigenously designed simulator. Knowledge was assessed via a pre and post study design using a validated tool, while the modified Objective Structured Assessment of Technical Skills tool was utilized for skills Assessment. Feedback from faculty and residents was collected via a standard 5-point Likert scale. RESULTS: Only one participant (4.55%) had previously attended a neurosurgical skills workshop. Comparison of knowledge assessment scores of the participants on topics taught showed significant improvement (p value = 0.034). Comparison of outcomes on 1st and 3rd attempts of cranial and spinal skills showed a significant improvement in all 14 domains assessed. Positive feedback was received ranging from 3.9 up to 4.8 on a 5 point Likert scale. Overall cost per participant culminated to $145, significantly lower than previously reported data. CONCLUSIONS: Our findings report the effectiveness of sustainable, low-cost training models which can be easily reproduced elsewhere. This indigenously designed inexpensive simulator can be modified for variable difficulty level and serve as an effective educational strategy in improving learners’ skills, knowledge and confidence.

Evaluation of the Educational Value of Low-Cost Training Model for Emergency Cricothyrotomy.

In this study, we aimed to evaluate the educational value and students' satisfaction with the hand-made low-cost cricothyrotomy simulation model. A low-cost and hand-made model and a high-fidelity model were used to assess the students. The students' knowledge and satisfaction were evaluated using a 10-item checklist and a satisfaction questionnaire, respectively. Medical interns in the present study participated in a two-hour briefing and debriefing session held in the Clinical Skills Training Center by an emergency attending doctor. Based on the results of data analysis, no significant differences were found between the two groups in terms of gender, age, the month of internship, and last semester's grade (P = .628, .356, .847, and .421, respectively). We also found no significant differences between our groups in terms of the median score of each item in the assessment checklist (P = .838, .736, .805, .172, .439, .823, .243, .950, .812, and .756, respectively). The study groups had no significant difference in the median total scores of the checklist as well (P = .504). Regarding the students' satisfaction, our results showed that interns evaluated their experience of the model as positive (median scores of 4 and 5 out of 5). They also gave the hand-made model a median score of 7 in comparison with the high-fidelity model and 8 out of 10 for its usability. The study results showed that a low-cost model could be as effective as an expensive high-fidelity model for teaching the necessary knowledge of cricothyrotomy techniques to medical trainees.

The Gravitational Wave Universe Toolbox

Context. In the current multi-messenger astronomy era, it is important that information about joint gravitational wave (GW) and electromagnetic (EM) observations through short gamma-ray bursts (sGRBs) remains easily accessible to each member of the GW-EM community. The possibility for non-experts to execute quick computations of joint GW-sGRB detections should be facilitated. Aims. For this study, we constructed a model for sGRBs and added this to the framework of the previously built Gravitational Wave Universe Toolbox (GWToolbox or Toolbox). We provide expected joint GW-sGRB detection rates for different combinations of GW detectors and high-energy (HE) instruments. Methods. We employed and adapted a generic GRB model to create a computationally low-cost top-hat jet model suitable for the GWToolbox. With the Toolbox, we simulated a population of binary neutron stars (BNSs) observed by a user-specified GW detector such as LIGO, Virgo, the Einstein Telescope (ET), or the Cosmic Explorer (CE). Based on the characteristics of each binary, our model predicts the properties of a resulting sGRB, as well as its detectability for HE detectors such as Fermi/GBM, Swift/BAT, or GECAM. Results. We report predicted joint detection rates for combinations of GW detectors (LIGO and ET) with HE instruments (Fermi/GBM, Swift/BAT, and GECAM). Our findings stress the significance of the impact that ET will have on multi-messenger astronomy. While the LIGO sensitivity is currently the limiting factor regarding the number of joint detections, ET will observe BNSs at such a rate that the vast majority of detected sGRBs will have a GW counterpart observed by ET. These conclusions hold for CE as well. Additionally, since LIGO can only detect BNSs up to a redshift of ~0.1 where few sGRBs exist, a search for sub-threshold GW signals at higher redshifts using sGRB information from HE detectors has the potential to be very successful and significantly increase the number of joint detections. Equivalently, during the ET era, GW data can assist in finding sub-threshold sGRBs, potentially increasing, for example, the number of joint ET-Fermi/GBM observations by ~270%. Lastly, we find that our top-hat jet model underestimates the number of joint detections that include an off-axis sGRB. We corrected for this by introducing a second, wider and weaker jet component. We predict that the majority of joint detections during the LIGO/Virgo era will include an off-axis sGRB, making GRB170817A not as unlikely as one would think based on the simplest top-hat jet model. In the ET era, most joint detections will contain an on-axis sGRB.

Effects of the individual three-dimensional printed craniofacial bones with a quick response code on the skull spatial knowledge of undergraduate medical students.

Understanding the three-dimensional (3D) structure of the human skull is imperative for medical courses. However, medical students are overwhelmed by the spatial complexity of the skull. Separated polyvinyl chloride (PVC) bone models have advantages as learning tools, but they are fragile and expensive. This study aimed to reconstruct 3D-printed skull bone models (3D-PSBs) using polylactic acid (PLA) with anatomical characteristics for spatial recognition of the skull. Student responses to 3D-PSB application were investigated through a questionnaire and tests to understand the requirement of these models as a learning tool. The students were randomly divided into 3D-PSB (n=63) and skull (n=67) groups to analyze pre- and post-test scores. Their knowledge was improved, with the gain scores of the 3D-PSB group (50.0 ± 3.0) higher than that of the skull group (37.3 ± 5.2). Most students agreed that using 3D-PSBs with quick response codes could improve immediate feedback on teaching (88%; 4.41 ± 0.75), while 85.9% of the students agreed that individual 3D-PSBs clarified the structures hidden within the skull (4.41 ± 0.75). The ball drop test revealed that the mechanical strength of the cement/PLA model was significantly greater than that of the cement or PLA model. The prices of the PVC, cement, and cement/PLA models were 234, 1.9, and 10 times higher than that of the 3D-PSB model, respectively. These findings imply that low-cost 3D-PSB models could revolutionize skull anatomical education by incorporating digital technologies like the QR system into the anatomical teaching repertoire.

Potential predictive value of CT radiomics features for treatment response in patients with COVID-19.

This study aims to explore the predictive value of CT radiomics and clinical characteristics for treatment response in COVID-19 patients. Data were collected from clinical/auxiliary examinations and follow-ups of COVID-19 patients. Whole lung radiomics feature extraction was performed at baseline chest CT. Radiomics, clinical, and combined features (nomogram) were evaluated for predicting treatment response. Among 36 COVID-19 patients, mild, common, severe, and critical disease symptoms were found in 1, 21, 13, and 1 of them, respectively. Twenty-five (1 mild, 18 common, and 6 severe) patients showed a good response to treatment and 11 poor/fair responses. The clinical classification (p = 0.025) and serum creatinine (p = 0.010) on admission and small area emphasis (p = 0.036) from radiomics analysis significantly differed between the two groups. Predictive models were constructed based on the radiomics, clinical features, and nomogram showing an area under the curve of 0.651, 0.836, and 0.869, respectively. The nomogram achieved good calibration. This new, non-invasive, and low-cost prediction model that combines the radiomics and clinical features is useful for identifying COVID-19 patients who may not respond well to treatment.