Assessment of renal damage in patients with multi-drug resistant strains of pneumonia treated with colistin

Background: Treatment of multi-drug-resistant strains of pneumonia with common antibiotics in renal patients is ine ective and physicians are compelled to use Colistin for such cases. Objectives: This study was conducted to assess the mortality, length of stay, and renal damages in the treatment of multi-drug-resistant pneumonia with Colistin among multiple trauma patients admitted to the emergency department and transferred to the ICU. Methods: This retrospective cohort study was conducted between 2011 and 2016. 102 multiple trauma (MT) patients with multidrug-resistant strains of hospital-acquired pneumonia (HAP) admitted to the emergency department then transferred to the ICU were assessed. All patients received Colistin according to their weight. Renal damage was evaluated according to the RIFLE criteria. The mortality and the length of stay were assessed. In order to statistically analyze the data, SPSS version 23 software was used to conduct t-test and chi-square test. Results: Out of 102 patients, 55 (54) died and 50 (49.1) developed acute renal failure; 64 cases had no hypertension. Patients according to the RIFLE index were assessed: Risk (11.01), Injury (14), Failure (18), Loss (6), and End-stage renal disease. The prevalence and prognosis of acute kidney injury in multiple trauma patients treated with Colistin were significantly correlated with drug dosage, body mass index, and use of corticosteroids (when assessed using relevant scoring systems, P < 0.05). Conclusions: The use of a scoring system in the intensive care unit, determining those patients requiring Colistin, and adjusting the dosage of this drug for treatment of MT patients with multi-drug resistant strains of HAP are vital. Creatinine levels must be carefully monitored. © 2018, Trauma Monthly

Identifying rail asset maintenance processes: a human-centric and sensemaking approach

Efficient asset maintenance is key for delivering services such as transport. Current rail maintenance processes have been mostly reactive with a recent shift towards exploring proactive modes. The introduction of new ubiquitous technologies and advanced data analytics facilitates the embedding of a ‘predict-and-prevent’ approach to managing assets. Successful, user-centred integration of such technology is still, however, a sparsely understood area. This study reports results from a set of interviews, based on Critical Decision Method, with rail asset maintenance and management experts regarding current procedural aspects of asset management and maintenance. We analyse and present the results from a human-centric sensemaking timeline perspective. We found that within a complex sociotechnical environment such as rail transport, asset maintenance processes apply not just at local levels, but also to broader, strategic levels that involve different stakeholders and necessitate different levels of expertise. This is a particularly interesting aspect within maintenance that has not been discussed as of yet within a process-based and timeline-based models of asset maintenance. We argue that it is important to consider asset maintenance activities within both micro (local) and macro (broader) levels to ensure reliability and stability in transport services. We also propose that the traditionally distinct notions of individual, collaborative and artefact-based sensemaking are in fact all in evidence in this sensemaking context, and argue that a more holistic view of sensemaking is therefore appropriate by placing these results within an amended Recogntion Primed Decsion making model

Shrinking projection algorithms for the split common null point problem

DOI: 10.1017/S000497271700017X/a

On the strong convergence theorems by the hybrid method for a family of mappings in uniformly convex Banach spaces

Abstract Some algorithms for finding common fixed point of a family of mappings is constructed. Indeed, let C be a nonempty closed convex subset of a uniformly convex Banach space X whose norm is Gateaux differentiable and let {Tn} be a family of self-mappings on C such that the set of all common fixed points of {Tn} is nonempty. We construct a sequence {xn} generated by the hybrid method and also we give the conditions of {Tn} under which {xn} converges strongly to a common fixed point of {Tn}

A novel approach for swimming analysis in main swimming styles using a single sacrum-worn IMU sensor

Introduction: Today, inertial measurement units (IMU) provide promising solutions for swimmers’ motions analysis [1-3]. However, most studies focused on few parameters, often during strokes of front crawl style [4]. For swimming training session monitoring, there is a need for automatic detection of swimming and lap periods, styles and more details within each lap. This study proposes a general approach starting with macro-level analysis to detect swimming bouts, laps and styles, going to micro-level analysis related to specific phases of swimming. Method: 17 professional swimmers performed four 50-m trials in main swimming styles, i.e. front crawl (FC), backstroke (BaS), breaststroke (BrS) and butterfly (BF), in a 25-m indoor pool. Acceleration and angular velocity were recorded at 500Hz sampling rate with a single sacrum-worn waterproofed inertial sensor (Physilog® IV, Gait Up, CH). Five cameras (GoPro Hero 7 Black, GoPro Inc., US) were used for validation. In macro-analysis, swimming bouts were recognised from rest periods through sharp changes on sacrum inferior-superior acceleration and its derivative. Within each bout, peaks of sacrum anteroposterior (A/P) acceleration were used to mark turns for separating laps. FC and BaS styles were classified from the dominant angular velocity, identified by principal component analysis (PCA) and gravity direction. Frequency analysis of A/P acceleration was used for differentiating between BrS and BF. In micro-level analysis, based on peak detection, zero-crossing, thresholding and PCA different swimming phases were detected as: wall push-off, glide, strokes preparation, strokes and turn. Results: Swimming bouts were detected with 97.5% accuracy, 99.4% sensitivity and 99.8% precision. All turns have been detected correctly. FC and BaS styles were identified with no error, while the accuracy, sensitivity and precision reached respectively 97.2%, 97.2% and 97.9% for BrS, and 97.9%, 97.9% and 97.2% for BF. Finally, errors (in ms) for the onset of each phase were: -20±89 (wall push-off), 5±100 (glide), -31±105 (strokes preparation), 28±205 (strokes), 24±97 (turn), -2±65 (next wall push-off). Discussion: By automatic assessment of swimming and rest bouts, laps number and duration, swimming styles as well as swimming phases within each lap using a single sacrum-worn IMU, this study offers coaches and swimmers an easy to use tool for monitoring swimming training sessions. Compared to other studies [5-6], style identification reached better accuracy. While the performance of the system for phase detection is acceptable, it can be improved by adding IMU sensors to other body locations

Swimming Phase-Based Performance Evaluation Using a Single IMU in Main Swimming Techniques.

Comprehensive monitoring of performance is essential for swimmers and swimming coaches to optimize the training. Regardless of the swimming technique, the swimmer passes various swimming phases from wall to wall, including a dive into the water or wall push-off, then glide and strokes preparation and finally, swimming up to the turn. The coach focuses on improving the performance of the swimmer in each of these phases. The purpose of this study was to assess the potential of using a sacrum-worn inertial measurement unit (IMU) for performance evaluation in each swimming phase (wall push-off, glide, stroke preparation and swimming) of elite swimmers in four main swimming techniques (i.e. front crawl, breaststroke, butterfly and backstroke). Nineteen swimmers were asked to wear a sacrum IMU and swim four one-way 25 m trials in each technique, attached to a tethered speedometer and filmed by cameras in the whole lap as reference systems. Based on the literature, several goal metrics were extracted from the instantaneous velocity (e.g. average velocity per stroke cycle) and displacement (e.g. time to reach 15 m from the wall) data from a tethered speedometer for the swimming phases, each one representing the goodness of swimmer's performance. Following a novel approach, that starts from swimming bout detection and continues until detecting the swimming phases, the IMU kinematic variables in each swimming phase were extracted. The highly associated variables with the corresponding goal metrics were detected by LASSO (least absolute shrinkage and selection operator) variable selection and used for estimating the goal metrics with a linear regression model. The selected kinematic variables were relevant to the motion characteristics of each phase (e.g. selection of propulsion-related variables in wall push-off phase), providing more interpretability to the model. The estimation reached a determination coefficient (R &lt;sup&gt;2&lt;/sup&gt; ) value more than 0.75 and a relative RMSE less than 10% for most goal metrics in all swimming techniques. The results show that a single sacrum IMU can provide a wide range of performance-related swimming kinematic variables, useful for performance evaluation in four main swimming techniques

A Sensor Fusion Approach to the Estimation of Instantaneous Velocity Using Single Wearable Sensor During Sprint.

Power-Force-Velocity profile obtained during a sprint test is crucial for designing personalized training and evaluating injury risks. Estimation of instantaneous velocity is requisite for developing these profiles and the predominant method for this estimation assumes it to have a first order exponential behavior. While this method remains appropriate for maximal sprints, the sprint velocity profile may not always show a first-order exponential behavior. Alternately, velocity profile has been estimated using inertial sensors, with a speed radar, or a smartphone application. Existing methods either relied on the exponential behavior or timing gates for drift removal, or estimated only the mean velocity. Thus, there is a need for a more flexible and appropriate approach, allowing for instantaneous velocity estimation during sprint tests. The proposed method aims to solve this problem using a sensor fusion approach, by combining the signals from wearable Global Navigation Satellite System (GNSS) and inertial measurement unit (IMU) sensors. We collected data from nine elite sprinters, equipped with a wearable GNSS-IMU sensor, who ran two trials each of 60 and 30/40 m sprints. We developed an algorithm using a gradient descent-based orientation filter, which simplified our model to a linear one-dimensional model, thus allowing us to use a simple Kalman filter (KF) for velocity estimation. We used two cascaded KFs, to segment the sprint data precisely, and to estimate the velocity and the sprint duration, respectively. We validated the estimated velocity and duration with speed radar and photocell data as reference. The median RMS error for the estimated velocity ranged from 6 to 8%, while that for the estimated sprint duration lied between 0.1 and -6.0%. The Bland-Altman plot showed close agreement between the estimated and the reference values of maximum velocity. Examination of fitting errors indicated a second order exponential behavior for the sprint velocity profile, unlike the first order behavior previously suggested in literature. The proposed sensor-fusion algorithm is valid to compute an accurate velocity profile with respect to the radar; it can compensate for and improve upon the accuracy of the individual IMU and GNSS velocities. This method thus enables the use of wearable sensors in the analysis of sprint test

Experimental-Numerical Investigation of a Steel Pipe Repaired with a Composite Sleeve

Pressure vessels are subjected to deterioration and damage, which can significantly reduce their strength and loading capabilities. Among several procedures nowadays available to repair damaged steel pipelines, composite-repairing systems have become popular over the past few years to restore the loading capacity of damaged pipelines. This study reports a numerical-experimental investigation performed for a composite-repaired pipeline made of API 5L X60 steel. An experimental burst test was carried out on a 4 m long pipe section, closed by two lateral caps, and tested up to failure by means of high-pressure water. In parallel, the test was numerically replicated through a FEM model of the composite-repaired steel tank, allowing for a cross-comparison of results. It was found that the composite repairing system has almost eliminated both the noteworthy thickness reduction of 80% and the related stress concentrations in the pipe body. These outcomes allow for a better understanding of these repairing procedures in order to drive their subsequent optimization