16 research outputs found

    Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

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    Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

    Effects of Laser Fluence and Pulse Overlap on Machining of Microchannels in Alumina Ceramics Using an Nd:YAG Laser

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    The quality of micro-features in various technologies is mostly affected by the choice of the micro-fabrication technique, which in turn results in several limitations with regard to materials, productivity, and cost. Laser beam micro-machining has a distinct edge over other non-traditional methods in terms of material choices, precision, shape complexity, and surface integrity. This study investigates the effect of laser fluence and pulse overlap while developing microchannels in alumina ceramic using an neodymium-doped yttrium aluminum garnet (Nd:YAG) laser. Microchannels 200 µm wide with different depths were machined using different laser peak fluence and pulse overlap (percentage of overlap between successive laser pulses) values. It was found that high pulse overlaps and fluences should be avoided as they give rise to V-shaped microchannels i.e., 100% bottom width errors. The optimal peak fluence range was found to be around 125–130 J/cm2 corresponding to 3–5 µm depth per scan. In addition, channels fabricated with moderate pulse overlap were found to be of good quality compared to low pulse overlaps

    Prognosis and Multiobjective Optimization of the Sampling Plan for Cylindricity Evaluation

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    The actualization of the befitting sampling strategy and the application of an appropriate evaluation algorithm have been elementary issues in the coordinate metrology. The decisions regarding their choice for a given geometrical feature customarily rely upon the user’s instinct or experience. As a consequence, the measurement results have to be accommodated between the accuracy and the inspection time. Certainly, a reliable and efficient sampling plan is imperative to accomplish a dependable inspection in minimal time, effort, and cost. This paper deals with the determination of an optimal sampling plan that minimizes the inspection cost, while still promising a measurement quality. A cylindrical-shaped component has been utilized in this work to achieve the desired objective. The inspection quality of the cylinder using a coordinate measuring machine (CMM) can be enhanced by controlling the three main parameters, which are used as input variables in the data file, namely, point distribution schemes, total number of points, and form evaluation algorithms. These factors affect the inspection output, in terms of cylindricity and measurement time, which are considered as target variables. The dataset, which comprises input and intended parameters, has been acquired through experimentation on the CMM machine. This work has utilized state-of-the-art machine learning algorithms to establish predictive models, which can predict the inspection output. The different algorithms have been examined and compared to seek for the most relevant machine learning regression method. The best performance has been observed using the support vector regression for cylindricity, with a mean absolute error of 0.000508 mm and a root-mean-squared error of 0.000885 mm. Likewise, the best prediction performance for measuring time has been demonstrated by the decision trees. Finally, the optimal parameters are estimated by employing the grey relational analysis (GRA) and the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS). It has been approved that the values obtained from GRA are comparable with those of the FTOPSIS. Moreover, the quality of the optimal results is bettered by incorporating the measurement uncertainty in the outcome

    A hybrid technique for approximating the solution of fractional order integro differential equations

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    In this article, we present an effective approach for solving nonlinear fractional order integro-differential equations. The fractional order derivative will be in the Caputo sense. For this, we propose an approach combined the least squares method together with the Laplace transform and the shifted Legendre polynomials. Using the proposed approach we will converts the nonlinear fractional order integro-differential equation into a se of (N+1) algebraic equations, where the solution to the resultant equation provides us with the unknown coefficients of the infinite series that have been used to approximate the solution to the considered fractional order integro-differential equations. From the results of the given examples, one can conclude that the recommended approach in this article is simple to implement and accurate

    Efficiency of topical ozone gel as an adjunct to antibiotics and analgesics on sequelae after extraction of impacted mandibular third molar.

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    Introduction: Extraction of the impacted mandibular third molar is a common procedure in dentistry. Many complications may arise after this operation, the most common being pain, trismus, and swelling. Systemic medications have been used in an attempt to manage these problems, but because of their side effects, the need for non-medication treatment arises to treat these complications without side effects, such as cryotherapy, ice packs, low-level laser therapy, and ozone. Ozone is one of the most effective antimicrobials used in the dentistry field, and it also has a positive effect on soft tissue healing, activates cellular metabolism, and can react with blood components; for these reasons ozone is used to manage trismus, swelling, and pain after removal of the mandibular third molar. Aim: The purpose of the study was to assess the effects of topical ozone gel on complications from the extraction of the impacted mandibular third molar. Materials and Methods: Thirty patients were enrolled in the current study and were randomly divided into two equal groups. Preoperatively clinical examination included measurement of facial swelling measurements and maximum mouth opening. The position and configuration of the impacted lower third molar, the surrounding bone, the mandibular canal, and the neighboring tooth were all assessed using a panoramic X-ray. On days 2 and 7, after surgery, the facial swelling dimensions and maximum mouth opening were again assessed. Statistics were used to analyze results. Results: Findings indicate statistical significance for pain, but not for swelling or mouth opening. Conclusions: After lower third molar surgery, topical ozone gel helps reduce postoperative pain

    Path Planning and Setup Orientation for Automated Dimensional Inspection Using Coordinate Measuring Machines

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    Inspection planning is considered an essential practice in the manufacturing industries because it ensures enhanced product quality and productivity. A reasonable inspection plan, which can reduce inspection costs and achieve high customer satisfaction, is therefore very important in the production industry. Considerations such as preparations for part inspection, measuring machines, and their setups as well as the measurement path are described in an inspection plan which is subsequently translated into part inspection machine language. Therefore, the measurement of any component using a coordinate measuring machine (CMM) is the final step preceded by several other procedures, such as the preparation of the part setup and the generation of the probe path. Effective measurement of components using CMM can only be done if the preceding steps are properly optimized to automate the whole inspection process. This paper has proposed a method based on artificial intelligence techniques, namely, artificial neural network (ANN) and genetic algorithm (GA), for fine-tuning output from the different steps to achieve an efficient inspection plan. A case study to check and validate the suggested approach for producing effective inspection plans for CMMs is presented. A decrease of nearly 50% was observed in the travel path of the probe, whereas the CMM measurement time was reduced by almost 25% during the actual component measurement. The proposed method yielded the optimum part setup and the most appropriate measuring sequence for the part considered

    Evolution of Computer-Aided Process Planning for Hybrid Additive/Subtractive Process

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    The hybrid process, which integrates two or more different processes such as additive manufacturing and subtractive manufacturing, has gained appreciable considerations in recent years. This process exploits the benefits of individual processes while overcoming their limitations. Lately, the combination of additive, subtractive, and inspection methods is a valuable conglomeration, considering its potential to produce complicated components precisely. Certainly, computer-aided process plan (CAPP) provides a crucial link among different processes and is essential to avail the benefits of hybridization. However, a valuable process plan can only be achieved through the optimization of its different elements. Therefore, the objective of this work is the accomplishment of an optimized CAPP to fabricate parts in the shortest time employing the hybrid additive, subtractive, and inspection processes. In this work, mathematical models have been developed to optimize part orientation as well as minimize additive and subtractive times. Additionally, the genetic algorithm has been employed to obtain the best path with minimum inspection time. The feasibility and capability of the proposed approach as well as the optimized CAPP for the hybrid process have been demonstrated through a case study

    Investigation of the effect of buffer storage capacity and repair rate on production line efficiency

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    The buffer allocation problem concerning the size and location of storage between the stages of a flow line is a critical research area in the design of production lines. In this study, a production system consisting of two unreliable stages and a buffer between them is considered; the first stage incorporates two identical machines in parallel and the second stage consists of a single machine. A simulation model is designed and used to evaluate the effect of the buffer capacity and the repair rates of machines on production line efficiency. The results revealed the capacity of buffer that yields the maximum production line efficiency with various repair rate values. Keywords: Buffer allocation, Flow line, Simulation model, Production line efficienc

    Optimization of Tree-like Support for Titanium Overhang Structures Produced via Electron Beam Melting

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    Support structures play a significant role in all additive manufacturing (AM) processes. The type of supports, as well as their size, placement, and other characteristics, greatly determine how effectively and efficiently the AM process works. In order to reduce the amount of material and post-processing requirements, tree-like support structures are revolutionary support structures that have so far been employed in polymer AM and have shown good performance. However, they have not yet been investigated for metal AM processes. Therefore, this study aims to propose and optimize the tree-like support structures for additively manufactured metal (Ti6Al4V) overhangs. The overhang specimens are fabricated using Electron Beam Melting (EBM) with a variety of design and process parameters. The effect of design and process structure parameters on the performance of the support is evaluated and optimized experimentally. MOGA-ll is used to perform multi-objective optimization. The results have shown the feasibility of using tree-like support structures in metal AM. The findings of this study demonstrate how important it is to choose the proper minimum distance between rows in order to reduce support volume and support removal time. Furthermore, the most crucial factors in limiting the overhang deviation are the beam current and beam scanning speed. Additionally, the data demonstrate that lowering the beam current and raising the beam scanning speed significantly reduce deformation. Consequently, it is critical to find the right balance between beam current, beam scanning speed, minimum spacing between rows, and branch top diameters that can produce the lowest support volume, lowest support removal time, and least amount of deformation

    A Multi-Part Orientation Planning Schema for Fabrication of Non-Related Components Using Additive Manufacturing

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    Additive manufacturing (AM) is a technique that progressively deposits material in layer-by-layer manner (or in additive fashion) for producing a three-dimensional (3D) object, starting from the computer-aided design (CAD) model. This approach allows for the printing of complicated shaped objects and is quickly gaining traction in the aerospace, medical implant, jewelry, footwear, automotive, and fashion industries. AM, which was formerly used for single part customization, is currently being considered for mass customization of parts because of its positive impacts. However, part quality and build time are two main impediments to the deployment of AM for mass production. The optimal part orientation is fundamental for maximizing the part’s quality as well as being critical for reducing the fabrication time. This research provides a new method for multi-part AM production that improves quality while reducing overall build time. The automatic setup planning or orientation approach described in this paper employs two objective functions: the quality of the build component and the build time. To tackle the given problem, it introduces a three-step genetic algorithm (GA)-based solution. A feature-based technique is utilized to generate a collection of finite alternative orientations for each component within a specific part group to ensure each part’s individual build quality. Then, a GA was utilized to find the best combination of part build orientations at a global optimal level to reduce material consumption and build time. A case study of orienting nine components concurrently inside a given building chamber was provided for illustration. The findings suggest that the developed technique can increase quality, reduce support waste, and shorten overall production time. When components are positioned optimally rather than in random orientations, build time and support volume are reduced by approximately 7% and 16%, respectively
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