Low-cost Model Research Articles

The observatory: a model for studies in health, society, and the environment.

The concept of an observatory for examining and monitoring trends for research in the social sciences and health arose from analogy with the facilities of astronomy and the realization that close and consistent observation was essential to understand interactions among determinants of health in a community. Their theoretical foundations are largely grounded in the “population health model,” an intellectual framework developed in 1974 and associated with a movement called “the new public health.” We developed an observatory for an affluent, unexceptional, suburban jurisdiction (“County 20”) in the province of Alberta, in western Canada, and used it to study and monitor both normative and emergent issues in environmental health. The observatory was conceived as a utility, or multi-purpose vehicle, for describing and responding to emerging community issues quickly and gathering data and qualitative findings as required. Case studies on issues of local importance allowed us to observe the dynamics of community response comprehensively, using quantitative and qualitative methods as appropriate. Valuable insights gleaned from the cases studied pertained to risk perception, the NIMBY syndrome, and reorganizing and auditing public health services. It did less well when the object of study was further removed from the community of interest, when there was no clear action item to be recommended, and when sponsors had expectations for certainty that could not be supported by available data sources. The observatory eventually was merged into a community health outreach program. The local observatory model is a practical, low-cost, and sustainable model for capturing generalizable and specifically local case study experience on a small scale but is limited in its effectiveness and by the scope of its coverage. It can be an initial step toward longitudinal and community monitoring studies on a larger scale. The observatory model can be used to elevate the level of case studies, impose rigor on analysis, and compile case studies for comparative and analytical studies.

A Novel Cost-Effective Simulation Model for Continuous Curvilinear Capsulorhexis.

IntroductionWe describe and validate a low-cost simulation model for practicing anterior lens capsule continuous curvilinear capsulorhexis (CCC).MethodsA simulation model for CCC was developed from widely available low-cost materials. Ophthalmologists attending the annual scientific meeting of the Research Institute of Ophthalmology, Giza, Egypt, were asked to perform a five CCC model task and then anonymously answer a questionnaire that assessed the realism and training utility of the model using a five-point Likert scale (1 = unacceptable, 2 = poor, 3 = acceptable, 4 = favorable and 5 = excellent).ResultsTwenty-seven ophthalmologists completed the task and the anonymous questionnaire. Overall, participants felt that the model simulated CCC step in cataract surgery well (mean: 3.5) and was comparable to other kinds of CCC simulation models (mean: 3.3). The model scored highly for its overall educational value (mean: 4.00) and for enlarging a small CCC (mean:3.7), while the feasibility of this model in practicing the management of a runaway leading edge of CCC scored 2.9.ConclusionThis model may provide an alternative method for training for CCC and other anterior lens capsule-related maneuvers. This option may be particularly helpful for residency training programs with limited access to virtual reality simulators or commercially available synthetic eye models.

Low-cost Transport Selection Model on the Polish Airline Services Market

Low-cost Transport Selection Model on the Polish Airline Services Market

ARE RESIDENTS IN URBAN AREAS OF NIGERIA EXPOSED TO HEALTH-IMPACTING LEVELS OF NOISE POLLUTION?

Across the world urban dwellers are facing increasing risks of exposure to noise pollution. The World Health Organization (WHO) described noise pollution as an underestimated threat that can cause various health problems to humans and wildlife. In Nigeria, urban areas are experiencing increasing levels of noise pollution. In this study, a combination of low-cost noise sensors and GIS modelling were used to conduct a preliminary investigation of the spatiotemporal patterns of noise pollution in a prominent urban area in Nigeria. This was to ascertain whether residents are exposed to dangerous noise levels that could affect their health as well as to demonstrate the potentials of deploying network of sensors for real-time monitoring of noise pollution in urban areas of developing countries. We observed noise levels at 5 seconds intervals, over a period of 24 hours, at different strategic locations (e.g. Achara Layout, Abakpa, and Independence Layout) across the city. Using GIS analytics techniques, data obtained from field were used to produce noise maps of the city. We found that night-time noise levels ranged between 32 and 35dBA, which are below recommended limits by the Nigerian government and WHO. Daytime noise levels ranged between 44 and 66dBA, slightly exceeding recommended limits. This contradicts general perceptions that noise levels in the city are dangerously high. This study has given the first insight into the spatiotemporal patterns of noise levels across Enugu Metropolis. It is the first time a spatiotemporal study of noise pollution was conducted in the city, revealing noise footprints of various parts of the city.

A low-cost model for slug tests in a confined aquifer with skin-zone effect

While the effect of small-scale skin has been extensively investigated, numerical models incorporating the effect require expensive computational cost due to fine spatial discretization of the skin and have not been widely available. This study develops a new model for slug tests at a partially-penetrating well in a two-zone confined aquifer of skin and formation zones. A new basic formulation defines transient flow in the skin with an additional skin factor reflecting the skin storage effect. The formulation assumes horizontal flow in the skin with excluding the vertical skin hydraulic conductivity. The analytical solution and finite element solution of the model are developed. The analytical expression relating the skin factor to the skin specific storage is derived. Results suggest the formulation is a useful alternative to conventional flow equation for the skin in achieving coarse spatial discretization and low computational cost. The present solution agrees well with the field head data obtained from Butler (2019). To conclude, this study presents theoretical advance and efficient simulation in modeling of well hydraulics.

A Novel Deep Learning Model for Sea State Classification Using Visual-Range Sea Images

Wind-waves exhibit variations both in shape and steepness, and their asymmetrical nature is a well-known feature. One of the important characteristics of the sea surface is the front-back asymmetry of wind-wave crests. The wind-wave conditions on the surface of the sea constitute a sea state, which is listed as an essential climate variable by the Global Climate Observing System and is considered a critical factor for structural safety and optimal operations of offshore oil and gas platforms. Methods such as statistical representations of sensor-based wave parameters observations and numerical modeling are used to classify sea states. However, for offshore structures such as oil and gas platforms, these methods induce high capital expenditures (CAPEX) and operating expenses (OPEX), along with extensive computational power and time requirements. To address this issue, in this paper, we propose a novel, low-cost deep learning-based sea state classification model using visual-range sea images. Firstly, a novel visual-range sea state image dataset was designed and developed for this purpose. The dataset consists of 100,800 images covering four sea states. The dataset was then benchmarked on state-of-the-art deep learning image classification models. The highest classification accuracy of 81.8% was yielded by NASNet-Mobile. Secondly, a novel sea state classification model was proposed. The model took design inspiration from GoogLeNet, which was identified as the optimal reference model for sea state classification. Systematic changes in GoogLeNet’s inception block were proposed, which resulted in an 8.5% overall classification accuracy improvement in comparison with NASNet-Mobile and a 7% improvement from the reference model (i.e., GoogLeNet). Additionally, the proposed model took 26% less training time, and its per-image classification time remains competitive.

Gonioscopy and Angle-Based Glaucoma Surgical Training on Human Eyes in the Wet Lab.

Human corneoscleral rims provide a low cost model and resource to enhance angle based glaucoma surgical training skills. To understand the feasibility, utility, and efficacy of a low-cost model for performing anterior chamber angle gonioscopy and micro-surgery on human corneoscleral tissues in wet lab on resident skill enhancement. Post-keratoplasty residual corneoscleral rims and/or the expired donor corneoscleral buttons were included for the purpose of this study. Initially, inverted rims were used to demonstrate the basic angle anatomy on a slit lamp bio-microscope. Central hazy cornea was then replaced with an artificial cornea and an artificial anterior chamber to simulate indirect gonioscopy, direct gonioscopy, goniotomy, and other angle-based surgeries. Direct gonioscopy and goniotomy exercises (as a means to simulate intraoperative gonioscopy and other angle-based surgeries respectively) were evaluated quantitatively, and the rest qualitatively. A total of 65 residents were included in the exercise. The mean age was 26.69±1.74 years. Amongst these, 55 ophthalmology residents performed the basic examination, that is, slit lamp mounted angle anatomy examination (n=55) and artificial chamber mounted indirect gonioscopic examination through artificial cornea (n=55). In the second exercise, 10 glaucoma fellows performed the direct gonioscopic and the goniotomy exercises on artificial chamber. The fellows demonstrated a statistically significant improvement in interpretation and surgical skill enhancement concurrent with reduction in time taken with increasing number of attempts ( P <0.05). In the third simulation exercise, micro-stent placement within the Schlemm's canal, subconjunctival space, and the suprachoroidal space was re-produced successfully on multiple occasions. The residual human corneoscleral rims proved to be an important resource for teaching both the basic examination skills and those required for transitioning to advanced intraoperative gonioscopy and goniotomy skills. These low cost, easy to adapt models can be incorporated within the curriculum for improved glaucoma training of both the residents and the glaucoma fellows.

Low-cost numerical lumped modelling of lithium-ion battery pack with phase change material and liquid cooling thermal management system

This study is aimed at developing a low cost lumped model for simulating a Li-ion battery pack with thermal management systems (TMS) under continuous charging/discharging cycles. The considered system is composed of twenty-four commercial Li-ion batteries with phase change material (PCM) and nine aluminium tubes for liquid coolant circulation. A zero-dimensional numerical model is developed based on the transient energy balances and the analogy between heat transfer and electrical transfer using resistances and capacitors. The simulations were carried at 3-C discharging/0.5-C charging rates and obtained results were compared with both three-dimensional computational fluid dynamic (CFD) results and experimental results from the literature. The effect of various system design and operating characteristics such as the cooling method, the coolant temperature and its velocity, the number of coolant pipes and the ambient conditions on the system performance were presented and analysed. Results show that combining both PCM and liquid cooling for battery thermal management leads to reduce the maximal battery temperature by about 38 °C and 4 °C compared to natural convection thermal management mode and to passive PCM thermal management mode, respectively. Increasing the number of cooling pipes improves the performance of the system and its optimal number in this system is up to 9 pipes. The maximal battery cells temperature is reduced from 31 °C to 20 °C as the used liquid coolant inlet temperature is reduced from 25 °C to 10 °C. Finally, the suggested low cost lumped model is a promising tool for simulating, designing and optimising battery pack with thermal management systems under real exploitation conditions.

Improved low-cost 3D reconstruction pipeline by merging data from different color and depth cameras

The performance of traditional 3D capture methods directly influences the quality of digitally reconstructed 3D models. In order to obtain complete and well-detailed low-cost three-dimensional models, this paper proposes a 3D reconstruction pipeline using point clouds from different sensors, combining captures of a low-cost depth sensor post-processed by Super-Resolution techniques with high-resolution RGB images from an external camera using Structure from Motion and Multi-View Stereo output data. The main contribution of this work includes the description of a complete pipeline that improves the stage of information acquisition and merges data from different sensors. Several phases of the 3D reconstruction pipeline were also specialized to improve the model's visual quality. The experimental evaluation demonstrates that the developed method produces good and reliable results for low-cost 3D reconstruction of an object.

Determination gender-based hybrid artificial intelligence of body muscle percentage by photoplethysmography signal

Background and objective: Muscle mass is one of the critical components that ensure muscle function. Loss of muscle mass at every stage of life can cause many adverse effects. Sarcopenia, which can occur in different age groups and is characterized by a decrease in muscle mass, is a critical syndrome that affects the quality of life of individuals. Aging, a universal process, can also cause loss of muscle mass. It is essential to monitor and measure muscle mass, which should be sufficient to maintain optimal health. Having various disadvantages with the ordinary methods used to estimate muscle mass increases the need for the new high technology methods. This study aims to develop a low-cost and trustworthy Body Muscle Percentage calculation model based on artificial intelligence algorithms and biomedical signals.Methods: For the study, 327 photoplethysmography signals of the subject were used. First, the photoplethysmography signals were filtered, and sub-frequency bands were obtained. A quantity of 125 time-domain features, 25 from each signal, have been extracted. Additionally, it has reached 130 features in demographic features added to the model. To enhance the performance, the spearman feature selection algorithm was used. Decision trees, Support Vector Machines, Ensemble Decision Trees, and Hybrid machine learning algorithms (the combination of three methods) were used as machine learning algorithms.Results: The recommended Body Muscle Percentage estimation model have the perfomance values for all individuals R=0.95, for males R=0.90 and for females R=0.90 in this study.Conclusion: Regarding the study results, it is thought that photoplethysmography-based models can be used to predict body muscle percentage.

MORTGAGE AUCTION AT BANK SYARIAH INDONESIA EX-LEGACY BANK BNI SYARIAH IN YOGYAKARTA

This study analyzes the practice of mortgage auctions at Bank Syariah Indonesia, Ex-BNI Syariah Yogyakarta Branch for the period 2016-2019. The study used a normative-empirical approach with data collection carried out through observation, interviews, and documentation. The informants were selected by purposive sampling and consisted of bank employees who had duties related to mortgage auctions. The results showed that the auction of mortgage rights in its implementation was not in accordance with Law Number 21 of 2008 Article 55 which was confirmed by the Decision of the Constitutional Court Number 93/PUUX/2012. In the harmonization of the law on mortgage auctions, it is necessary to have support with an integral, effective, and relatively low-cost dispute resolution model. On the other hand, in realizing the legal harmonization of mortgage auctions, it is necessary to have a Fatwa from the MUI DSN which can be used as a reference for fulfilling sharia principles for Islamic banks.

Paper 78: Integrating PROM Collection for Shoulder Surgical Patients through the Electronic Medical Record: A Low Cost and Effective Strategy for High Fidelity PROM Collection

Objectives:Patient Reported Outcome Measures (PROMs) are critical measures of quality of care and treatment outcomes; however, they are challenging to collect without significant financial and administrative investment. The purpose of this study was to evaluate the efficacy and cost of an automated PROM collection through the electronic medical record for shoulder surgery patients in a large, integrated healthcare system.Methods:An existing, electronic medical record (EMR) based, automated, PROM scheduling system was integrated into the surgical check-in workflow for all elective primary total hip, total knee, and partial knee arthroplasty patients from November 2020 through August 2021 at 3 high volume surgical sites in a large, integrated health system. Rates of completion for Patient Reported Outcomes Measurement Information System Upper Extremity (PROMIS-UE), Patient Reported Outcomes Measurement Information System Pain Interference (PROMIS-PI) and American Shoulder and Elbow Surgeons Shoulder (ASES) surveys were determined. No additional staff were hired to assist in PROM collection. In our institution, if the patient had an ambulatory appointment within 25 days prior to surgery, their PROM scores were marked complete and were not reassigned on the day of surgery (DOS). For all other patients, PROMs were assigned by the automated system on DOS.Results:A total of 325 patients with a mean age of 42 + 28 years were included in this study. The vast majority, 94% (306), were assigned surveys on their day of surgery as a result of the automated system. The other 6% (19) had PROM scores completed in the ambulatory setting as they had a pre-operative visit less than 25 days prior to surgery. For patients completing PROMS on their day of surgery, 87% (266/306) completed at least 1 of PROMIS-UE or ASES, while 82% (251/306) completed both. In total 88% (285/325) of patients completed at least 1 PROM on or within 25 days prior to surgery and 85% (277/325) completed both. This entire system cost $5180 to deploy.Conclusions:A native PROM scheduling and collection system was successfully implemented with a survey completion rate of 82% to 95% of patients. This system serves as an efficient, low-cost model for other surgical departments to leverage existing systems to collect day of surgery PROMs.

Factor analysis of error in oxidation potential calculation: A machine learning study.

The conductor-like polarizable continuum model (C-PCM), which is a low-cost solvation model, cannot treat characteristic interactions between the solvent and substructure(s) of the solute. Moreover, the error in a charged system is significant. Using machine learning, we clarified that the systematic error of the oxidation potential calculated by the G3B3/C-PCM was correlated with the molecular size of a solute. The G3B3/C-PCM overestimated the Gibbs oxidation energy by averaging 6.94 kcal/mol. According to the performance of related methods reported in previous studies, this error is mainly due to the solvation energy of the charged solute. Additionally, we succeeded in reducing the error to 2.27 kcal/mol (32%)-3.2kcal/mol (40%) by correction based on the substructure information of the solute. To modify the C-PCM, effects that correlate with the molecular size of the solute in the charged system should be incorporated.

A data-driven approach for characterising revenues of South-Asian long-haul low-cost carriers per equivalent flight capacity per block hour

This study sets out to investigate the revenue characteristics of long-haul low-cost carriers (LHLCCs) in the Southeast Asian market using a recently established metric that calculates revenue per equivalent flight capacity per block hour (REB). REB allows for the accurate comparison of airlines on different routes with varying cabin configurations, and stage lengths. The majority of the data was sourced from Sabre MIDT and OAG, while supplementary data were from other various sources. In addition to REB, the study investigates: How do LHLCCs yields compare to full-service network carriers (FSNCs)? Are LHLCCs positively impacted by smaller share of connecting passengers? Are LHLCCs positively impacted by ancillary revenues? Do LHLCCs benefit from higher load factors and seat densities?Results show that LHLCCs performed 26.6% less in overall REB compared to their FSNC counterpart despite LHLCCs generating 43.9% less yield. This is a result of less revenue diluting connecting passengers, higher average ancillary revenue per block hour, higher average load factors and higher average seat densities for LHLCCs. On a route-level, some LHLCC operations can equally perform or outperform competition’s revenue performance. Furthermore, the findings are mostly consistent with earlier REB research conducted on the North Atlantic market by Soyk et al. (2018). Revenue and operating characteristic showed the same trends in both markets, although to varying degrees.This study exposes, with high detail, the revenue generating inner-workings of the elusive long-haul low-cost model in its second largest market, and compares it on equal grounds to their full-service network competition. We learn that airlines can drive the airfare down while minimising the loss of revenue per flight capacity of the aircraft by adjusting for the numerous variables that directly impact it, such as seat density, cabin configuration, ancillary revenues, load factors, and percentage of connecting passengers.

Experimental Evaluation and Analysis of LED Illumination Source for Endoscopy Imaging

The minimally invasive surgery uses a small instrument with camera and light to fit the tiny cut in the skin. The selection of the light depends on the power and driving current of the circuit. It can also help in the standardization of the camera and capture the tissues' true-colour image. This paper presents the LED source analysis used in the clinical endoscopes for surgery and thehuman body's medical examination. Initially, a LED source selection mechanism generating intense illuminance in a visibleband is proposed. A low-cost prototype model is developed to analyze the wavelength and illuminance of three different LEDs types. Aneffect on variation in LED illumination is investigated by changing the distance between the Borescope and LED source. True-colour image generation and tissue contrast are more important in medical diagnostics. Therefore, a sigmoid function improving the whole contrast ratio of the captured image in real-time is presented. The results of spectrum and wavelength for a current variation are presented. Type 3 LED produces higher illumination (i.e., 395 Klux) and peak wavelength (i.e., 622.05 nm) than other LEDs, while type-2 LED has better FWHM for the blue colour spectrum. The modification in the sigmoid function enhances the image with 34.25peak PSNR producing a true-colour image.

Tube-based iterative-learning-model predictive control for batch processes using pre-clustered just-in-time learning methodology

Iterative-learning-model predictive control (ILMPC) has been considered a potential control strategy for batch processes. ILMPC can converge to the desired reference trajectory with high precision along cycles and reject real-time disturbances within cycles. However, as a model-based control method, the control performance of the ILMPC algorithm deteriorates when it suffers the problem of model-plant mismatches. Therefore, simultaneously guaranteeing system convergence along the cycle-axis and robust stability on the time-axis is a challenging task in the framework designing of ILMPC control systems. To this end, we present a type of tube-based ILMPC strategy based on an empirical model for nonlinear batch processes. First, to describe the dynamic behavior of nonlinear batch processes as much as possible with the goal of low computational cost and high modeling accuracy, a pre-clustered just-in-time learning (JITL) model focused on operation data is developed. Then, an ancillary MPC controller is combined with the ILMPC algorithm to form a tube scheme to relieve the impact of model error. In addition, we construct an inverse model system (IMS) to systematically determine the first cycle control input trajectory of the proposed tube-based ILMPC algorithm. As a result, they simultaneously ensure the system convergence along the cycle-axis and robust stability on the time-axis. Still, they can improve convergence speed and tracking performance. Finally, comparative simulations demonstrate the superiority of the proposed control algorithm.

A Low-Cost Simulation Model for Endoscopic-Assisted Sagittal Craniosynostosis Repair

The objective is to introduce a low-cost simulation model for endoscopic-assisted sagittal craniosynostosis repair in which bleedings can be simulated and to present the initial experience using the model as a learning tool. A 3-dimensional synthetic skull was printed using polylactic acid. The brain, dura mater, sagittal sinus, and skin were constructed using low-cost materials. The simulation was performed at Garrahan Pediatric Hospital's simulation center employing a rigid endoscope (Pes Pilot HD 0° 4 mm). A low-cost simulation model for sagittal craniosynostosis was built in order to recreate the steps needed to perform a strip craniectomy with lateral extensions. The initial estimated cost is 10 U.S. dollars, and subsequent uses cost approximately 2 U.S. dollars. Four training sessions were performed, and a reduction in surgical time was recorded from 125 to 80 minutes. We introduce a low-cost simulation model for scaphocephaly endoscopic-assisted surgery in which bleeding can be reproduced. The initial experience shows the possibility of using the model as a learning tool.

A Method to Evaluated Gas Content with Coalbed Methane Reservoir Based on Adsorption Theory and Production Analysis

In the process of coalbed methane development, the gas content not only determines the reserves of methane in coal reservoir but also is the most important geological parameter affecting the production of coalbed methane. The gas content directly determines whether coalbed methane can be developed efficiently. However, in the current development evaluation process, it is very difficult to accurately predict the gas content in coal seams. An efficient and accurate method to predict gas content has not been found yet. This is mainly restricted by the development mode and technology of coalbed methane. In the current low-cost development model, gas content test data are relatively scarce. Under such circumstances, it is difficult to accurately evaluate the distribution of CBM gas content in the whole area. At the same time, the gas content of coalbed is the key parameter for efficient development of coalbed methane. Under normal circumstances, gas content heterogeneity will result in a large gap between development effects in different regions. At present, there is no evaluation method for gas content parameters of coal reservoir. Under this background, the key parameters of coalbed methane development in southern Qinshui Basin were evaluated. On the basis of systematically summarizing and understanding the development law of coalbed methane in different types of coal reservoirs, a gas content evaluation method based on adsorption theory and production dynamic analysis is proposed. Combined with the coalbed methane production model and isothermal adsorption model, the critical desorption pressure can be calculated accurately by using the bottom hole pressure when casing pressure occurs in production wells. The critical desorption pressure correction model of coalbed methane was innovatively established. Langmuir equation was used to accurately characterize the adsorption characteristics of coalbed methane. Forming a new method for gas content prediction in the case of fewer coring wells. The gas content evaluation technology coupled with isothermal adsorption theory and production dynamic analysis saves the development cost of coalbed methane and improves the prediction accuracy of coal seam gas content in noncoring wells. At the same time, there is a good relationship between the predicted results and the measured gas content at well points. The coincidence rate reached 97.37%. This technology can effectively improve the prediction accuracy of coal seam gas content. This technique is suitable for the productivity evaluation of coalbed methane reservoir. It can also provide scientific basis for the development and reserve evaluation of coalbed methane reservoirs at home and abroad.

4. Surgical Simulation for Metacarpal Fracture Fixation Improves Satisfaction, Confidence and Skill

Background: Surgical education has long touted the value of high fidelity simulations in the modern training paradigm. The senior authors of this study have therefore created a low-cost model of a human hand using 3D printing and silicone molding to facilitate at-home practice sessions for K-wiring. Methods: Following IRB review and approval, 11 plastic surgery residents (PGY 1-6) were recruited for this study. All residents watched a presentation from the senior author (A.P.), which outlined 10 steps to K-wire fixation; the task at hand was placement of two K wires diagonally across a simulated metacarpal fracture. These trials were timed. Residents were divided into two groups in which Group A performed K-wire fixation and Group B observed. The groups then crossed over. The residents performed four practice sessions at home prior to the next assessment. Confidence and satisfaction data in a 15 question survey were recorded using a Likert scale from 1-5, with 5 corresponding to strong agreement. Aggregate scores are represented in parentheses below. Results: All residents agreed that the model was realistic (4.7), sufficient for fracture identification (4.5) and had appropriate approximation of soft tissue and bony tactile feedback (4.3). Moreover, all residents agreed that they found these sessions stimulating (4.9). All residents would recommend this model to other trainees (4.8) and reported feeling that they had learned valuable skills (4.6). Most residents had scrubbed either 0-5 or 6-10 cases requiring K wiring. All residents felt more confident with K-wiring following the practice sessions when compared to pre-training baselines (2.7 vs. 4.4). Times were stratified by PGY level; PGY 1-4 (n = 8) average times Session 1 was 712 seconds and 433 seconds for Session 2, while PGY 5-6 (n = 3) times were 495 seconds and 247 seconds respectively (p = 0.037). Conclusion: Our analysis demonstrates that residents universally approved of and benefitted from the K wiring instructional session and practice model. The time improvement was statistically significant. We therefore believe that this is a practical and efficacious model to improve a critical skill in hand surgery across training levels.

Chronic lung lesions in COVID-19 survivors: predictive clinical model

ObjectiveThis study aimed to propose a simple, accessible and low-cost predictive clinical model to detect lung lesions due to COVID-19 infection.DesignThis prospective cohort study included COVID-19 survivors hospitalised between 30...