Search results for: recurrent errors

Authors: Hayden R Schott, John M Felder III

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Introduction: Chronic lower extremity wounds in the diabetic and vasculopathic populations are associated with a high degree of morbidity.When wounds require more extensive treatment than can be offered by wound care centers, more aggressive solutions involve local tissue transfer and microsurgical free tissue transfer for achieving definitive soft tissue coverage. These procedures of autologous tissue transfer (ATT) offer resilient, soft tissue coverage of limb-threatening wounds and confer promising limb salvage rates. However, chronic osteomyelitis and recalcitrant soft tissue infections are common in severe diabetic foot wounds and serve to significantly complicate ATT procedures. Stimulan is a resorbable calcium sulfate antibiotic carrier. The use of stimulan antibiotic beads to treat chronic osteomyelitis is well established in the orthopedic and plastic surgery literature. In these procedures, the beads are placed beneath the skin flap to directly deliver antibiotics to the infection site. The purpose of this study was to quantify the success of Stimulan antibiotic beads in treating recalcitrant infections in patients with diabetic foot wounds receiving ATT. Methods: A retrospective review of clinical and demographic information was performed on patients who underwent ATT with the placement of Stimulan antibiotic beads for attempted limb salvage from 2018-21. Patients were analyzed for preoperative wound characteristics, demographics, infection recurrence, and adverse outcomes as a result of product use. The primary endpoint was 90 day infection recurrence, with secondary endpoints including 90 day complications. Outcomes were compared using basic statistics and Fisher’s exact tests. Results: In this time span, 14 patients were identified. At the time of surgery, all patients exhibited clinical signs of active infection, including positive cultures and erythema. 57% of patients (n=8) exhibited chronic osteomyelitis prior to surgery, and 71% (n=10) had exposed bone at the wound base. In 57% of patients (n=8), Stimulan beads were placed beneath a free tissue flap and beneath a pedicle tissue flap in 42% of patients (n=6). In all patients, Stimulan beads were only applied once. Recurrent infections were observed in 28% of patients (n=4) at 90 days post-op, and flap nonadherence was observed in 7% (n=1). These were the only Stimulan related complications observed. Ultimately, lower limb salvage was successful in 85% of patients (n=12). Notably, there was no significant association between the preoperative presence of osteomyelitis and recurrent infections. Conclusions: The use of Stimulanantiobiotic beads to treat recalcitrant infections in patients receiving definitive skin coverage of diabetic foot wounds does not appear to demonstrate unnecessary risk. Furthermore, the lack of significance between the preoperative presence of osteomyelitis and recurrent infections indicates the successful use of Stimulan to dampen infection in patients with osteomyelitis, as is consistent with the literature. Further research is needed to identify Stimulan as the significant contributor to infection treatment using future cohort and case control studies with more patients. Nonetheless, the use of Stimulan antibiotic beads in patients with diabetic foot wounds demonstrates successful infection suppression and maintenance of definitive soft tissue coverage.

Keywords: wound care, stimulan antibiotic beads, free tissue transfer, plastic surgery, wound, infection

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Authors: Paua Ketan, Bhagate Rajkumar, Adiga Ganesh, M. Kiran

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Low gear noise is an important sound quality feature in modern passenger cars. Annoying gear noise from the gearbox is influenced by the gear design, gearbox shaft layout, manufacturing deviations in the components, assembly errors and the mounting arrangement of the complete gearbox. Geometrical deviations in the form of profile and lead errors are often present on the flanks of the inspected gears. Ghost frequencies of a gear are very challenging to identify in standard gear measurement and analysis process due to small wavelengths involved. In this paper, gear whine noise occurring at non-integral multiples of gear mesh frequency of passenger car gearbox is investigated and the root cause is identified using the displacement deviation analysis (DDA) method. DDA method is applied to identify ghost frequency excitations on the flanks of gears arising out of generation grinding. Frequency identified through DDA correlated with the frequency of vibration and noise on the end-of-line machine as well as vehicle level measurements. With the application of DDA method along with standard lead profile measurement, gears with ghost frequency geometry deviations were identified on the production line to eliminate defective parts and thereby eliminate ghost frequency noise from a vehicle. Further, displacement deviation analysis can be used in conjunction with the manufacturing process simulation to arrive at suitable countermeasures for arresting the ghost frequency.

Keywords: displacement deviation analysis, gear whine, ghost frequency, sound quality

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Authors: Andrew N. Saylor, James R. Peters

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Scoliosis is a complex 3D deformity of the thoracic and lumbar spines, clinically diagnosed by measurement of a Cobb angle of 10 degrees or more on a coronal X-ray. The Cobb angle is the angle made by the lines drawn along the proximal and distal endplates of the respective proximal and distal vertebrae comprising the curve. Traditionally, Cobb angles are measured manually using either a marker, straight edge, and protractor or image measurement software. The task of measuring the Cobb angle can also be represented by a function taking the spine geometry rendered using X-ray imaging as input and returning the approximate angle. Although the form of such a function may be unknown, it can be approximated using artificial neural networks (ANNs). The performance of ANNs is affected by many factors, including the choice of activation function and network architecture; however, the effects of these parameters on the accuracy of scoliotic deformity measurements are poorly understood. Therefore, the objective of this study was to systematically investigate the effect of ANN architecture and activation function on Cobb angle measurement from the coronal X-rays of scoliotic subjects. The data set for this study consisted of 609 coronal chest X-rays of scoliotic subjects divided into 481 training images and 128 test images. These data, which included labeled Cobb angle measurements, were obtained from the SpineWeb online database. In order to normalize the input data, each image was resized using bi-linear interpolation to a size of 500 × 187 pixels, and the pixel intensities were scaled to be between 0 and 1. A fully connected (dense) ANN with a fixed cost function (mean squared error), batch size (10), and learning rate (0.01) was developed using Python Version 3.7.3 and TensorFlow 1.13.1. The activation functions (sigmoid, hyperbolic tangent [tanh], or rectified linear units [ReLU]), number of hidden layers (1, 3, 5, or 10), and number of neurons per layer (10, 100, or 1000) were varied systematically to generate a total of 36 network conditions. Stochastic gradient descent with early stopping was used to train each network. Three trials were run per condition, and the final mean squared errors and mean absolute errors were averaged to quantify the network response for each condition. The network that performed the best used ReLU neurons had three hidden layers, and 100 neurons per layer. The average mean squared error of this network was 222.28 ± 30 degrees2, and the average mean absolute error was 11.96 ± 0.64 degrees. It is also notable that while most of the networks performed similarly, the networks using ReLU neurons, 10 hidden layers, and 1000 neurons per layer, and those using Tanh neurons, one hidden layer, and 10 neurons per layer performed markedly worse with average mean squared errors greater than 400 degrees2 and average mean absolute errors greater than 16 degrees. From the results of this study, it can be seen that the choice of ANN architecture and activation function has a clear impact on Cobb angle inference from coronal X-rays of scoliotic subjects.

Keywords: scoliosis, artificial neural networks, cobb angle, medical imaging

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Authors: Hasan Basaran, Emre Unal

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Formation flying of satellites is a mission that involves a relative position keeping of different satellites in the constellation. In this study, different control algorithms are compared with one another in terms of ΔV, velocity increment, and tracking error. Various control methods, covering continuous and impulsive approaches are implemented and tested for satellites flying in low Earth orbit. Feedback linearization, sliding mode control, and model predictive control are designed and compared with an impulsive feedback law, which is based on mean orbital elements. Feedback linearization and sliding mode control approaches have identical mathematical models that include second order Earth oblateness effects. The model predictive control, on the other hand, does not include any perturbations and assumes circular chief orbit. The comparison is done with 4 different initial errors and achieved with velocity increment, root mean square error, maximum steady state error, and settling time. It was observed that impulsive law consumed the least ΔV, while produced the highest maximum error in the steady state. The continuous control laws, however, consumed higher velocity increments and produced lower amounts of tracking errors. Finally, the inversely proportional relationship between tracking error and velocity increment was established.

Keywords: chief-deputy satellites, feedback linearization, follower-leader satellites, formation flight, fuel consumption, model predictive control, rendezvous, sliding mode

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Authors: Kassa Endalamaw Rewnu

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The variability properties of a quasar sample, spectroscopically complete to magnitude J = 22.0, are investigated on a time baseline of 2 years using three different photometric bands (U, J and F). The original sample was obtained using a combination of different selection criteria: colors, slitless spectroscopy and variability, based on a time baseline of 1 yr. The main goals of this work are two-fold: first, to derive the percentage of variable quasars on a relatively short time baseline; secondly, to search for new quasar candidates missed by the other selection criteria; and, thus, to estimate the completeness of the spectroscopic sample. In order to achieve these goals, we have extracted all the candidate variable objects from a sample of about 1800 stellar or quasi-stellar objects with limiting magnitude J = 22.50 over an area of about 0.50 deg2. We find that > 65% of all the objects selected as possible variables are either confirmed quasars or quasar candidates on the basis of their colors. This percentage increases even further if we exclude from our lists of variable candidates a number of objects equal to that expected on the basis of `contamination' induced by our photometric errors. The percentage of variable quasars in the spectroscopic sample is also high, reaching about 50%. On the basis of these results, we can estimate that the incompleteness of the original spectroscopic sample is < 12%. We conclude that variability analysis of data with small photometric errors can be successfully used as an efficient and independent (or at least auxiliary) selection method in quasar surveys, even when the time baseline is relatively short. Finally, when corrected for the different intrinsic time lags corresponding to a fixed observed time baseline, our data do not show a statistically significant correlation between variability and either absolute luminosity or redshift.

Keywords: nuclear activity, galaxies, active quasars, variability

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Authors: Breanna Wright, Peter Bragge

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Diagnostic error rates in healthcare are approximately 10% of cases. Diagnostic errors can cause patient harm due to inappropriate, inadequate or delayed treatment, and such errors contribute heavily to medical liability claims globally. Therefore, addressing diagnostic error is a high priority. In most cases, diagnostic errors are the result of faulty information synthesis rather than lack of knowledge. Specifically, the majority of diagnostic errors involve cognitive factors, and in particular, cognitive biases. Emergency Departments are an environment with heightened risk of diagnostic error due to time and resource pressures, a frequently chaotic environment, and patients arriving undifferentiated and with minimal context. This project aimed to develop a behavioural, evidence-informed intervention to reduce diagnostic error in Emergency Departments through co-design with emergency physicians, insurers, researchers, hospital managers, citizens and consumer representatives. The Forum Process was utilised to address this aim. This involves convening a small (4 – 6 member) expert panel to guide a focused literature and practice review; convening of a 10 – 12 person citizens panel to gather perspectives of laypeople, including those affected by misdiagnoses; and a 18 – 22 person structured stakeholder dialogue bringing together representatives of the aforementioned stakeholder groups. The process not only provides in-depth analysis of the problem and associated behaviours, but brings together expertise and insight to facilitate identification of a behaviour change intervention. Informed by the literature and practice review, the Citizens Panel focused on eliciting the values and concerns of those affected or potentially affected by diagnostic error. Citizens were comfortable with diagnostic uncertainty if doctors were honest with them. They also emphasised the importance of open communication between doctors and patients and their families. Citizens expect more consistent standards across the state and better access for both patients and their doctors to patient health information to avoid time-consuming re-taking of long patient histories and medication regimes when re-presenting at Emergency Departments and to reduce the risk of unintentional omissions. The structured Stakeholder Dialogue focused on identifying a feasible behavioural intervention to review diagnoses in Emergency Departments. This needed to consider the role of cognitive bias in medical decision-making; contextual factors (in Victoria, there is a legislated 4-hour maximum time between ED triage and discharge / hospital admission); resource availability; and the need to ensure the intervention could work in large metropolitan as well as small rural and regional ED settings across Victoria. The identified behavioural intervention will be piloted in approximately ten hospital EDs across Victoria, Australia. This presentation will detail the findings of all review and consultation activities, describe the behavioural intervention developed and present results of the pilot trial.

Keywords: behavioural intervention, cognitive bias, decision-making, diagnostic error

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Authors: M. A. Okezue, K. L. Clase, S. R. Byrn

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The requirement for maintaining data integrity in laboratory operations is critical for regulatory compliance. Automation of procedures reduces incidence of human errors. Quality control laboratories located in low-income economies may face some barriers in attempts to automate their processes. Since data from quality control tests on pharmaceutical products are used in making regulatory decisions, it is important that laboratory reports are accurate and reliable. Zinc Sulphate (ZnSO₄) tablets is used in treatment of diarrhea in pediatric population, and as an adjunct therapy for COVID-19 regimen. Unfortunately, zinc content in these formulations is determined titrimetrically; a manual analytical procedure. The assay for ZnSO4 tablets involves time-consuming steps that contain mathematical formulae prone to calculation errors. To achieve consistency, save costs, and improve data integrity, validated spreadsheets were developed to simplify the two critical steps in the analysis of ZnSO4 tablets: standardization of 0.1M Sodium Edetate (EDTA) solution, and the complexometric titration assay procedure. The assay method in the United States Pharmacopoeia was used to create a process flow for ZnSO₄ tablets. For each step in the process, different formulae were input into two spreadsheets to automate calculations. Further checks were created within the automated system to ensure validity of replicate analysis in titrimetric procedures. Validations were conducted using five data sets of manually computed assay results. The acceptance criteria set for the protocol were met. Significant p-values (p < 0.05, α = 0.05, at 95% Confidence Interval) were obtained from students’ t-test evaluation of the mean values for manual-calculated and spreadsheet results at all levels of the analysis flow. Right-first-time analysis and principles of data integrity were enhanced by use of the validated spreadsheet calculators in titrimetric evaluations of ZnSO₄ tablets. Human errors were minimized in calculations when procedures were automated in quality control laboratories. The assay procedure for the formulation was achieved in a time-efficient manner with greater level of accuracy. This project is expected to promote cost savings for laboratory business models.

Keywords: data integrity, spreadsheets, titrimetry, validation, zinc sulphate tablets

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Authors: Joanna Kochanska, Dagmara Gornicka, Anna Burduk

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The article examines the process of implementing a new assembly line in a manufacturing enterprise of the household appliances industry area. At the initial stages of the project, a decision was made that one of its foundations should be the concept of lean management. Because of that, eliminating as many errors as possible in the first phases of its functioning was emphasized. During the start-up of the line, there were identified and documented all production losses (from serious machine failures, through any unplanned downtime, to micro-stops and quality defects). During 6 weeks (line start-up period), all errors resulting from problems in various areas were analyzed. These areas were, among the others, production, logistics, quality, and organization. The aim of the work was to analyze the occurrence of production failures during the initial phase of starting up the line and to propose a method for determining their critical level during its full functionality. There was examined the repeatability of the production losses in various areas and at different levels at such an early stage of implementation, by using the methods of statistical process control. Based on the Pareto analysis, there were identified the weakest points in order to focus improvement actions on them. The next step was to examine the effectiveness of the actions undertaken to reduce the level of recorded losses. Based on the obtained results, there was proposed a method for determining the critical failures level in the studied areas. The developed coefficient can be used as an alarm in case of imbalance of the production, which is caused by the increased failures level in production and production support processes in the period of the standardized functioning of the line.

Keywords: production failures, level of production losses, new production line implementation, assembly line, statistical process control

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Authors: Hui Luo, Zhenhong Li, Zhen Dong

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The analysis of multi-temporal InSAR (MTInSAR) such as persistent scatterer (PS) and small baseline subset (SBAS) techniques usually relies on temporal/spatial phase unwrapping (PU). Unfortunately, it always fails to unwrap the phase for two reasons: 1) spatial phase jump between adjacent pixels larger than π, such as layover and high discontinuous terrain; 2) temporal phase discontinuities such as time varied atmospheric delay. To overcome these limitations, a least-square based PU method is introduced in this paper, which incorporates baseline-combination interferograms and adjacent phase gradient network. Firstly, permanent scatterers (PS) are selected for study. Starting with the linear baseline-combination method, we obtain equivalent 'small baseline inteferograms' to limit the spatial phase difference. Then, phase different has been conducted between connected PSs (connected by a specific networking rule) to suppress the spatial correlated phase errors such as atmospheric artifact. After that, interval phase difference along arcs can be computed by least square method and followed by an outlier detector to remove the arcs with phase ambiguities. Then, the unwrapped phase can be obtained by spatial integration. The proposed method is tested on real data of TerraSAR-X, and the results are also compared with the ones obtained by StaMPS(a software package with 3D PU capabilities). By comparison, it shows that the proposed method can successfully unwrap the interferograms in urban areas even when high discontinuities exist, while StaMPS fails. At last, precise DEM errors can be got according to the unwrapped interferograms.

Keywords: phase unwrapping, time series, InSAR, urban areas

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Authors: Mausumi Chetia

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One of the main causes of impoverishment of the rural areas of Assam has been the recurrent floods and riverbank erosion. One of the life-changing consequences is displacement. This results not only in a loss of livelihoods but also has wide-reaching socio-economic and cultural effects. Thus, due to such disasters, not only families but communities too are being displaced at large. This compels them to find temporary shelter and begin life from scratch. The role of the state has been highly negligible, with a displacement not being perceived as an ‘issue’ to be addressed. A more holistic approach is thus needed to take socio-economic, cultural, political as well as ecological considerations into account.

Keywords: displacement, policy-framework, human-induced disasters, marginalised communities, India, Assam

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Authors: Luz Estrada

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The currents of evolutionary materialistic thought have argued that knowledge about an object is not obtained through the abstractive method. That is, the object cannot come to be understood if founded upon itself, nor does it take place by the encounter between form and matter. According to this affirmation, the research presented here identified as a problematic situation the absence of comprehension of the formal creation as a generative operation. This has been referred to as a recurrent lack in the production of objects and corresponds to the need to conceive the configurative process from the reality of its genesis. In this case, it is of interest to explore ways of creation that consider the object as if it were a living organism, as well as responding to the object’s experience as embodied in the designer since it unfolds its genesis simultaneously to the ways of existence of those who are involved in the generative experience.

Keywords: architecture, theoretical graphics, evolutionary genetics, formal perception

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Authors: A. Caicedo Padilla, J. Zambrano Nájera

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Cali, the capital of Valle del Cauca and the second city of Colombia, is located in the Cauca River Valley between the Western and Central Cordillera that is South West of the country. The topography of the city is mainly flat, but it is possibly to find mountains in the west. The city has increased urbanization during XX century, especially since 1958 when started a rapid growth due to migration of people from other parts of the region. Much of that population has settled in eastern of Cali, an area originally intended for cane cultivation and a zone of flood from Cauca River and its tributaries. Due to the unplanned migration, settling was inadequate and produced changes in natural dynamics of the basins, which has resulted in increases in runoff volumes, peak flows and flow velocities, that in turn increases flood risk. Sewerage networks capacity were not enough for this higher runoff volume, because in first term they were not adequately designed and built, causing its failure. This in turn generates increasingly recurrent floods generating considerable effects on the economy and development of normal activities in Cali. Thus, it becomes very important to know hydrological behavior of Urban Watersheds. This research aims to determine the impact of urbanization on hydrology of watersheds with very low slopes. The project aims to identify changes in natural drainage patterns caused by the changes made on landscape. From the identification of such modifications it will be defined the most critical areas due to recurring flood events in the city of Cali. Critical areas are defined as areas where the sewerage system does not work properly as surface runoff increases considerable with storm events, and floods are recurrent. The assessment will be done from the analysis of Geographic Information Systems (GIS) theme layers from CVC Environmental Institution of Regional Control in Valle del Cauca, hydrological data and disaster database developed by OSSO Corporation. Rainfall data from a network and historical stream flow data will be used for analysis of historical behavior and change of precipitation and hydrological response according to homogeneous zones characterized by EMCALI S.A. public utility enterprise of Cali in 1999.

Keywords: drainage systems, land cover changes, urban hydrology, urban planning

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Authors: Jia Li, Huacong Li, Xiaobao Han

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Due to the more variable geometry parameters of VCE (variable cycle aircraft engine), presents an adaptive controller method based on the full-state linear model of VCE and has simulated to solve the multivariate controller design problem of the whole flight envelops. First, analyzes the static and dynamic performances of bypass ratio and other state parameters caused by variable geometric components, and develops nonlinear component model of VCE. Then based on the component model, through small deviation linearization of main fuel (Wf), the area of tail nozzle throat (A8) and the angle of rear bypass ejector (A163), setting up multiple linear model which variable geometric parameters can be inputs. Second, designs the adaptive controllers for VCE linear models of different nominal points. Among them, considering of modeling uncertainties and external disturbances, derives the adaptive law by lyapunov function. The simulation results showed that, the adaptive controller method based on full-state linear model used the angle of rear bypass ejector as input and effectively solved the multivariate control problems of VCE. The performance of all nominal points could track the desired closed-loop reference instructions. The adjust time was less than 1.2s, and the system overshoot was less than 1%, at the same time, the errors of steady states were less than 0.5% and the dynamic tracking errors were less than 1%. In addition, the designed controller could effectively suppress interference and reached the desired commands with different external random noise signals.

Keywords: variable cycle engine (VCE), full-state linear model, adaptive control, by-pass ratio

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Authors: Sizar Abed Mohammed, Zahraa Ghazi Sadeeq

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The use of the classic method, least squares (OLS) to estimate the linear regression parameters, when they are available assumptions, and capabilities that have good characteristics, such as impartiality, minimum variance, consistency, and so on. The development of alternative statistical techniques to estimate the parameters, when the data are contaminated with outliers. These are powerful methods (or resistance). In this paper, three of robust methods are studied, which are: Maximum likelihood type estimate M-estimator, Modified Maximum likelihood type estimate MM-estimator and Least Trimmed Squares LTS-estimator, and their results are compared with OLS method. These methods applied to real data taken from Duhok company for manufacturing furniture, the obtained results compared by using the criteria: Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Sum of Absolute Error (MSAE). Important conclusions that this study came up with are: a number of typical values detected by using four methods in the furniture line and very close to the data. This refers to the fact that close to the normal distribution of standard errors, but typical values in the doors line data, using OLS less than that detected by the powerful ways. This means that the standard errors of the distribution are far from normal departure. Another important conclusion is that the estimated values of the parameters by using the lifeline is very far from the estimated values using powerful methods for line doors, gave LTS- destined better results using standard MSE, and gave the M- estimator better results using standard MAPE. Moreover, we noticed that using standard MSAE, and MM- estimator is better. The programs S-plus (version 8.0, professional 2007), Minitab (version 13.2) and SPSS (version 17) are used to analyze the data.

Keywords: Robest, LTS, M estimate, MSE

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Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

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Authors: Alvin Han, Reema Shafi, Alishba Afaq, Jennifer Gommerman, Valeria Ramaglia, Shannon E. Dunn

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Adolescents engaged in contact-sports can suffer from recurrent brain concussions with no loss of consciousness and no need for hospitalization, yet they face the possibility of long-term neurocognitive problems. Recent studies suggest that head concussive injuries during adolescence can also predispose individuals to multiple sclerosis (MS). The underlying mechanisms of how brain concussions predispose to MS is not understood. Here, we hypothesize that: (1) recurrent brain concussions prime microglial cells, the tissue resident myeloid cells of the brain, setting them up for exacerbated responses when exposed to additional challenges later in life; and (2) brain concussions lead to the sensitization of myelin-specific T cells in the peripheral lymphoid organs. Towards addressing these hypotheses, we implemented a mouse model of closed head injury that uses a weight-drop device. First, we calibrated the model in male 12 week-old mice and established that a weight drop from a 3 cm height induced mild neurological symptoms (mean neurological score of 1.6+0.4 at 1 hour post-injury) from which the mice fully recovered by 72 hours post-trauma. Then, we performed immunohistochemistry on the brain of concussed mice at 72 hours post-trauma. Despite mice having recovered from all neurological symptoms, immunostaining for leukocytes (CD45) and IBA-1 revealed no peripheral immune infiltration, but an increase in the intensity of IBA1+ staining compared to uninjured controls, suggesting that resident microglia had acquired a more active phenotype. This microglia activation was most apparent in the white matter tracts in the brain and in the olfactory bulb. Immunostaining for the microglia-specific homeostatic marker TMEM119, showed a reduction in TMEM119+ area in the brain of concussed mice compared to uninjured controls, confirming a loss of this homeostatic signal by microglia after injury. Future studies will test whether single or repetitive concussive injury can worsen or accelerate autoimmunity in male and female mice. Understanding these mechanisms will guide the development of timed and targeted therapies to prevent MS from getting started in people at risk.

Keywords: concussion, microglia, microglial priming, multiple sclerosis

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Devin Doos, Ashley Hughes, Trang Pham, Paul Barach, Rami Ahmed

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Over 115,000 Health Care Workers (HCWs) have died from COVID-19, and millions have been infected while caring for patients. HCWs have filed thousands of safety complaints surrounding safety concerns due to Personal Protective Equipment (PPE) shortages, which included concerns around inadequate and PPE reuse. Protocols for donning and doffing PPE remain ambiguous, lacking an evidence-base, and often result in wide deviations in practice. PPE donning and doffing protocol deviations commonly result in self-contamination but have not been thoroughly addressed. No evidence-driven protocols provide guidance on protecting HCW during periods of PPE reuse. Objective: The aim of this study was to examine safety-related threats and risks to Health Care Workers (HCWs) due to the reuse of PPE among Emergency Department personnel. Method: We conducted a prospective observational study to examine the risks of reusing PPE. First, ED personnel were asked to don and doff PPE in a simulation lab. Each participant was asked to don and doff PPE five times, according to the maximum reuse recommendation set by the Centers for Disease Control and Prevention (CDC). Each participant was videorecorded; video recordings were reviewed and coded independently by at least 2 of the 3trained coders for safety behaviors and riskiness of actions. A third coder was brought in when the agreement between the 2 coders could not be reached. Agreement between coders was high (81.9%), and all disagreements (100%) were resolved via consensus. A bowtie risk assessment chart was constructed analyzing the factors that contribute to increased risks HCW are faced with due to PPE use and reuse. Agreement amongst content experts in the field of Emergency Medicine, Human Factors, and Anesthesiology was used to select aspects of health care that both contribute and mitigate risks associated with PPE reuse. Findings: Twenty-eight clinician participants completed five rounds of donning/doffing PPE, yielding 140 PPE donning/doffing sequences. Two emerging threats were associated with behaviors in donning, doffing, and re-using PPE: (i) direct exposure to contaminant, and (ii) transmission/spread of contaminant. Protective behaviors included: hand hygiene, not touching the patient-facing surface of PPE, and ensuring a proper fit and closure of all PPE materials. 100% of participants (n= 28) deviated from the CDC recommended order, and most participants (92.85%, n=26) self-contaminated at least once during reuse. Other frequent errors included failure to tie all ties on the PPE (92.85%, n=26) and failure to wash hands after a contamination event occurred (39.28%, n=11). Conclusions: There is wide variation and regular errors in how HCW don and doffPPE while including in reusing PPE that led to self-contamination. Some errors were deemed “recoverable”, such as hand washing after touching a patient-facing surface to remove the contaminant. Other errors, such as using a contaminated mask and accidentally spreading to the neck and face, can lead to compound risks that are unique to repeated PPE use. A more comprehensive understanding of the contributing threats to HCW safety and complete approach to mitigating underlying risks, including visualizing with risk management toolsmay, aid future PPE designand workflow and space solutions.

Keywords: bowtie analysis, health care, PPE reuse, risk management

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Authors: Yousef Alwashahi, Ahmed Almoqbali, Mayar Albahrani, Asma Alajmi

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We report a rare case of a 49-year-old Omani woman who is a known case of primary anti-phospholipid syndrome, glucose-6-phosphate dehydrogenase deficiency, and iron deficiency anaemia. During cannulation, she was found to develop bulla that progressed to ulcerations. With chronicity and recurrent abscess formation that usually increase after surgical intervention, a pathergy phenomenon was postulated. High suspicion of pyoderma gangrenosum was considered. Fortunately, the rapid progression of the disease was slowed down with corticosteroids, cyclosporin, and biological agents.

Keywords: anti-phospholipid syndrome, pyoderma gangrenosum, bullous pyoderma gangrenosum, pathergy, pathergy phenomenon

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

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Authors: Didier Auroux, Vladimir Groza

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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

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Authors: Parth Gupta, Ujjawal Singh, Shashank Kumar, Mansi Chandra, Arnab Sarkar

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Microfluidic devices have emerged as indispensable tools across various scientific disciplines, offering precise control and manipulation of fluids at the microscale. Their efficacy in flow-based research, spanning engineering, chemistry, and biology, relies heavily on the geometric design of microfluidic channels. This work introduces a novel approach to optimise these channels through Response Surface Methodology (RSM), departing from the conventional practice of addressing one parameter at a time. Traditionally, optimising microfluidic channels involved isolated adjustments to individual parameters, limiting the comprehensive understanding of their combined effects. In contrast, our approach considers the simultaneous impact of multiple parameters, employing RSM to efficiently explore the complex design space. The outcome is an innovative microfluidic channel that consumes an optimal sample volume and minimises flow time, enhancing overall efficiency. The relevance of geometric parameter optimization in microfluidic channels extends significantly in biomedical engineering. The flow characteristics of porous materials within these channels depend on many factors, including fluid viscosity, environmental conditions (such as temperature and humidity), and specific design parameters like sample volume, channel width, channel length, and substrate porosity. This intricate interplay directly influences the performance and efficacy of microfluidic devices, which, if not optimized, can lead to increased costs and errors in disease testing and analysis. In the context of biomedical applications, the proposed approach addresses the critical need for precision in fluid flow. it mitigate manufacturing costs associated with trial-and-error methodologies by optimising multiple geometric parameters concurrently. The resulting microfluidic channels offer enhanced performance and contribute to a streamlined, cost-effective process for testing and analyzing diseases. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing.

Keywords: microfluidic device, minitab, statistical optimization, response surface methodology

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Authors: Abdul Khalique Baloch, Ali Okatan

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The quality analysis of food and vegetable from image is hot topic now a day, where researchers make them better then pervious findings through different technique and methods. In this research we have review the literature, and find gape from them, and suggest better proposed approach, design the algorithm, developed a software to measure the quality from images, where accuracy of image show better results, and compare the results with Perouse work done so for. The Application we uses an open-source dataset and python language with tensor flow lite framework. In this research we focus to sort food and vegetable from image, in the images, the application can sorts and make them grading after process the images, it could create less errors them human base sorting errors by manual grading. Digital pictures datasets were created. The collected images arranged by classes. The classification accuracy of the system was about 94%. As fruits and vegetables play main role in day-to-day life, the quality of fruits and vegetables is necessary in evaluating agricultural produce, the customer always buy good quality fruits and vegetables. This document is about quality detection of fruit and vegetables using images. Most of customers suffering due to unhealthy foods and vegetables by suppliers, so there is no proper quality measurement level followed by hotel managements. it have developed software to measure the quality of the fruits and vegetables by using images, it will tell you how is your fruits and vegetables are fresh or rotten. Some algorithms reviewed in this thesis including digital images, ResNet, VGG16, CNN and Transfer Learning grading feature extraction. This application used an open source dataset of images and language used python, and designs a framework of system.

Keywords: deep learning, computer vision, image processing, rotten fruit detection, fruits quality criteria, vegetables quality criteria

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Authors: Umporn Wutchana

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An open ended problem and unstructured interview had been used to explore students’ conceptual and procedural understanding of vector components. The open ended problem had been designed based on research instrument used in previous physics education research. Without physical context, we asked students to find out magnitude and draw graphical form of vector components. The open ended problem was given to 211 first year students of faculty of science during the third (summer) semester in 2014 academic year. The students spent approximately 15 minutes of their second time of the General Physics I course to complete the open ended problem after they had failed. Consequently, their responses were classified based on the similarity of errors performed in the responses. Then, an unstructured interview was conducted. 7 students were randomly selected and asked to reason and explain their answers. The study results showed that 53% of 211 students provided correct numerical magnitude of vector components while 10.9% of them confused and punctuated the magnitude of vectors in x- with y-components. Others 20.4% provided just symbols and the last 15.6% gave no answer. When asking to draw graphical form of vector components, only 10% of 211 students made corrections. A majority of them produced errors and revealed alternative conceptions. 46.5% drew longer and/or shorter magnitude of vector components. 43.1% drew vectors in different forms or wrote down other symbols. Results from the unstructured interview indicated that some students just memorized the method to get numerical magnitude of x- and y-components. About graphical form of component vectors, some students though that the length of component vectors should be shorter than those of the given one. So then, it could be combined to be equal length of the given vectors while others though that component vectors should has the same length as the given vectors. It was likely to be that many students did not develop a strong foundation of understanding in vector components but just learn by memorizing its solution or the way to compute its magnitude and attribute little meaning to such concept.

Keywords: graphical vectors, vectors, vector components, misconceptions, alternative conceptions

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Authors: Amare Setegn Enyew, Bikila Teklu Wodajo

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The primary aim of flexible pavement design is to ensure the development of economical and safe road infrastructure. However, failures can still occur due to improper or erroneous structural design. In Ethiopia, the design of flexible pavements relies on doing calculations manually and selecting pavement structure from catalogue. The catalogue offers, in eight different charts, alternative structures for combinations of traffic and subgrade classes, as outlined in the Ethiopian Roads Authority (ERA) Pavement Design Manual 2001. Furthermore, design modification is allowed in accordance with the structural number principles outlined in the AASHTO 1993 Guide for Design of Pavement Structures. Nevertheless, the manual calculation and design process involves the use of nomographs, charts, tables, and formulas, which increases the likelihood of human errors and inaccuracies, and this may lead to unsafe or uneconomical road construction. To address the challenge, a software called AASHERA has been developed for AASHTO 1993 and ERA design methods, using MATLAB language. The software accurately determines the required thicknesses of flexible pavement surface, base, and subbase layers for the two methods. It also digitizes design inputs and references like nomographs, charts, default values, and tables. Moreover, the software allows easier comparison of the two design methods in terms of results and cost of construction. AASHERA's accuracy has been confirmed through comparisons with designs from handbooks and manuals. The software can aid in reducing human errors, inaccuracies, and time consumption as compared to the conventional manual design methods employed in Ethiopia. AASHERA, with its validated accuracy, proves to be an indispensable tool for flexible pavement structure designers.

Keywords: flexible pavement design, AASHTO 1993, ERA, MATLAB, AASHERA

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Authors: Muhammad Yasir Wadood, Fatemeh Babaeian

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By developing ultra-wideband (UWB) systems, there is a high demand for UWB filters with low insertion loss, wide bandwidth, and having a planar structure which is compatible with other components of the UWB system. A microstrip interdigital filter is a great option for designing UWB filters. However, the presence of via holes in this structure creates difficulties in the fabrication procedure of the filter. Especially in the higher frequency band, any misalignment of the drilled via hole with the Microstrip stubs causes large errors in the measurement results compared to the desired results. Moreover, in this case (high-frequency designs), the line width of the stubs are very narrow, so highly precise small via holes are required to be implemented, which increases the cost of fabrication significantly. Also, in this case, there is a risk of having fabrication errors. To combat this issue, in this paper, a via-less UWB microstrip filter is proposed which is designed based on a modification of a conventional inter-digital bandpass filter. The novel approaches in this filter design are 1) replacement of each via hole with a quarter-wavelength open circuit stub to avoid the complexity of manufacturing, 2) using a bend structure to reduce the unwanted coupling effects and 3) minimising the size. Using the proposed structure, a UWB filter operating in the frequency band of 3.9-6.6 GHz (1-dB bandwidth) is designed and fabricated. The promising results of the simulation and measurement are presented in this paper. The selected substrate for these designs was Rogers RO4003 with a thickness of 20 mils. This is a common substrate in most of the industrial projects. The compact size of the proposed filter is highly beneficial for applications which require a very miniature size of hardware.

Keywords: band-pass filters, inter-digital filter, microstrip, via-less

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Authors: Ophir Segal, Daniel Weltsch, Shay Tenenbaum, Ran Thein

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Purpose: Patients with lateral patellar dislocation (LPD) are not always referred to perform an MRI. This might be the case in first time LPD patients without surgical indications or in patients with recurrent LPD who had MRI in previous episodes. Unfortunately, in some cases, there are additional knee pathological findings, which include tearing of the collateral or cruciate ligaments and injury to the tendons or menisci. These findings might be overlooked during the physical examination or masked by nonspecific clinical findings like knee pain, effusion, or hemarthrosis. The prevalence of these findings, which can be revealed by MRI, is misreported in literature and is considered rare. In our practice, all patients with LPD are sent for MRI after LPD. Therefore, we have designed a retrospective comparative study to evaluate the prevalence of additional pathological findings in patients with acute traumatic LPD that had performed MRI, comparing different groups of patients according to age, sex, and Tibial Tuberosity-Trochlear Groove(TT-TG) distance. Methods: MRI of the knee in patients after traumatic LPD were evaluated for the presence of additional pathological findings such as injuries to ligaments: Anterior/Posterior cruciate ligament(ACL, PCL), Medial/Lateral collateral ligament(MCL, LCL), injuries to tendons(QUADICEPS, PATELLAR), menisci(Medial/Lateral meniscus(MM, LM)) and tibial plateau, by a fellowship-trained, senior musculoskeletal radiologist. A comparison between different groups of patients was performed according to age (age group < 25 years, age group > 25 years), sex (Male/Female group), and TT-TG distance (TT-TG<15 groups, TT-TG>15 groups). A descriptive and comparative statistical analysis was performed. Results: 150 patients were included in this study. All suffered from LPD between the years 2012-2017 (mean age 21.3( ± SD 8.9), 86 males). ACL, PCL, MCL, and LCL complete or partial tears were found in 17(11.3%), 3(2%), 22(14.6%), and 4(2.7%) of the patients, respectively. MM and LM tears were found in 10(6.7%) and 3(2%) of the patients, respectively. A higher prevalence of PCL injury, MM tear, and LM tear were found in the older age group compared to the younger group of patients (10.5% vs. 1.8%, 18.4% vs. 2.7%, and 7.9% vs. 0%, respectively, p<0.05). A higher prevalence of non-displaced MM tear and LCL injury was found in the male group compared to the female group (8.1% vs. 0% and 8.1% vs. 0% respectively, p<0.05). A higher prevalence of ACL injury was found in the normal TT-TG group compared to the pathologic TT-TG group (17.5% vs. 2.3%, p= 0.0184). Conclusions: Overall, 43 out of 150 (28.7%) of the patient's MRI’s were positive for additional pathological radiological findings. Interestingly, a higher prevalence of additional pathologies was found in the groups of patients with a lower risk for recurrent LPD, including males, patients older than 25, and patients with TT-TG lower than 15mm, and therefore might not be referred for an MRI scan. Thus, we recommend a strict physical examination, awareness to the high prevalence of additional pathological findings, and to consider performing an MRI in all patients after LPD.

Keywords: additional findings, lateral patellar dislocation (LPD), MRI scan, traumatic patellar dislocation, cruciate ligaments injuries, menisci injuries, collateral ligaments injuries

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Authors: Nashaat A. Deiab, Aida Radwan, Mohamed S. Yahiya, Mohamed Elnagdy, Rasha Moustafa

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This study is to evaluate the dosimetric performance of our institution's 3D treatment planning system for wedged and off-axis 6MV photon beams, guided by the recommended QA tests documented in the AAPM TG53; NCS report 15 test packages, IAEA TRS 430 and ESTRO booklet no.7. The study was performed for Elekta Precise linear accelerator designed for clinical range of 4, 6 and 15 MV photon beams with asymmetric jaws and fully integrated multileaf collimator that enables high conformance to target with sharp field edges. Ten tests were applied on solid water equivalent phantom along with 2D array dose detection system. The calculated doses using 3D treatment planning system PrecisePLAN were compared with measured doses to make sure that the dose calculations are accurate for simple situations such as square and elongated fields, different SSD, beam modifiers e.g. wedges, blocks, MLC-shaped fields and asymmetric collimator settings. The QA results showed dosimetric accuracy of the TPS within the specified tolerance limits. Except for large elongated wedged field, the central axis and outside central axis have errors of 0.2% and 0.5%, respectively, and off- planned and off-axis elongated fields the region outside the central axis of the beam errors are 0.2% and 1.1%, respectively. The dosimetric investigated results yielded differences within the accepted tolerance level as recommended. Differences between dose values predicted by the TPS and measured values at the same point are the result from limitations of the dose calculation, uncertainties in the measurement procedure, or fluctuations in the output of the accelerator.

Keywords: quality assurance, dose calculation, wedged fields, off-axis fields, 3D treatment planning system, photon beam

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Authors: Ehsan Sadie

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Today, the cost of repair and maintenance of structures is very important and by studying the behavior of reinforced concrete structures Will become specified several factors such as : Design and calculation errors, lack of proper implementation of structural changes, the damage caused by the introduction of random loads, concrete corrosion and environmental conditions reduce durability of the structures . Meanwhile building codes alteration also cause changes in the assessment and review of the design and structure rather if necessary will be improved and strengthened in the future.

Keywords: concrete building , expandable cement, honeycombed surface , reinforcement corrosion

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Authors: R. M. Rajapaksa

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Construction industry is one of the key players in driving the economy of a country to achieve its prosperity. However, a dispute is one of the crucial factors which prevent the completion of construction contracts within the budgeted cost, scheduled time, and accepted quality. Disputes are inevitable in the construction contract. Accordingly, a study has been undertaken to identify the factors affecting contractual disputes in construction projects in Sri Lanka. The study was a mixed approach with major qualitative and minor quantitative. Qualitative study was set in the form of in-depth interviews with eighteen participants, and quantitative study was conducted using a questionnaire with twenty-four respondents from previously implemented projects by the National Water Supply & Drainage Board representing the employer, engineer and the Contractor to identify the factors affecting contractual disputes and to verify most critical factors respectively. Data analysis for qualitative and quantitative studies was carried out by means of transcribing, code & categorizeand average score methods, respectively. The study reveals that there are forty factors affecting the contractual disputes in construction contracts in Sri Lanka. The finding further illustrates that conflicting decisions by inexperience personnel in the higher position of the Employer, ambiguities resulting inadequate descriptions of the preliminary/general items in price schedule, unfair valuation and late confirmation of variations, unfair determination due to lack of experience of the Engineer/Consultant, under certification of progress payments, unfair grant of EOT & application of delay damages, unreasonable claims for variation of works, errors/discrepancies/ambiguities in the contract conditions and discrepancies & errors in designs & specifications are the most critical factors affecting contractual disputes. Finally, the study proposed remedial measures to most critical factors affecting contractual disputes.

Keywords: dispute, contractual, factors, employer, engineer, contractor, construction projects

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