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Master'sMASTER OF SCIENC

Experimental Analysis for Factors Affecting the Repeatability of Plastics Injection Molding Tests on the Self-developed Apparatus

To improve the repeatability of the injection molding test result, the affecting factors were investigated by means of experiments. Besides the traditional processing parameter, the factors of test conditions were also considered. In order to focus on the molding process rather than the molded part, the curve measurement of the melt pressure at the entrance to the nozzle was used as the output characteristic. Experiments for polypropylene (PP) showed that the injected volume was the key processing parameter. Within the test conditions, the injection number is the most important factor. According to the analysis the operating procedure was improved effectively. Doi: 10.12777/ijse.5.1.6-11 [How to cite this article: Huang, Y., Li, D., Liu, Y. (2013). Experimental Analysis for Factors Affecting the Repeatability of Plastics Injection Molding Tests on the Self-developed Apparatus. International Journal of Science and Engineering, 5(1),6-11. Doi: 10.12777/ijse.5.1.6-11

Quasi-Closeness: A Toolkit for Social Network Applications Involving Indirect Connections

We come up with a punishment in the form of exponential decay for the number of vertices that a path passes through, which is able to reconcile the contradictory effects of geodesic length and edge weights. This core thought is the key to handling three typical applications; that is, given an information demander, he may be faced with the following problems: choosing optimal route to contact the single supplier, picking out the best supplier between multiple candidates, and calculating his point centrality, which involves indirect connections. Accordingly, three concrete solutions in one logic thread are proposed. Firstly, by adding a constraint to Dijkstra algorithm, we limit our candidates for optimal route to the sample space of geodesics. Secondly, we come up with a unified standard for the comparison between adjacent and nonadjacent vertices. Through punishment in the form of exponential decay, the attenuation effect caused by the number of vertices that a path passes through has been offset. Then the adjacent vertices and punished nonadjacent vertices can be compared directly. At last, an unprecedented centrality index, quasi-closeness, is ready to come out, with direct and indirect connections being summed up

Effectiveness of early rhythm control in improving clinical outcomes in patients with atrial fibrillation:a systematic review and meta-analysis

BackgroundCurrent guidelines recommend rhythm control for improving symptoms and quality of life in symptomatic patients with atrial fibrillation (AF). However, the long-term prognostic outcomes of rhythm control compared with rate control are still inconclusive. In this meta-analysis, we aimed to assess the effects of early rhythm control compared with rate control on clinical outcomes in newly diagnosed AF patients.MethodsWe systematically searched the PubMed and Embase databases up to August 2022 for randomized and observational studies reporting the associations of early rhythm control (defined as within 12 months of AF diagnosis) with effectiveness outcomes. The primary outcome was a composite of death, stroke, admission to hospital for heart failure (HF), or acute coronary syndrome (ACS). Hazard ratios (HRs) and 95% confidence intervals (CIs) from each study were pooled using a random-effects model, complemented with an inverse variance heterogeneity or quality effects model.ResultsA total of 8 studies involving 447,202 AF patients were included, and 23.5% of participants underwent an early rhythm-control therapy. In the pooled analysis using the random-effects model, compared with rate control, the early rhythm-control strategy was significantly associated with reductions in the primary composite outcome (HR = 0.88, 95% CI: 0.86-0.89) and secondary outcomes, including stroke or systemic embolism (HR = 0.78, 95% CI: 0.71-0.85), ischemic stroke (HR = 0.81, 95% CI: 0.69-0.94), cardiovascular death (HR = 0.83, 95% CI: 0.70-0.99), HF hospitalization (HR = 0.90, 95% CI: 0.88-0.92), and ACS (HR = 0.86, 95% CI: 0.76-0.98). Reanalyses using the inverse variance heterogeneity or quality effects model yielded similar results.ConclusionsOur current meta-analysis suggested that early initiation of rhythm control treatment was associated with improved adverse effectiveness outcomes in patients who had been diagnosed with AF within 1 year.RegistrationThe study protocol was registered to PROSPERO (CRD42021295405)

Optimal Models for Plant Disease and Pest Detection Using UAV Image

The use of deep learning methods to detect plant diseases and pests based on UAV images is an important application of remote sensing technology in modern forestry. This paper uses a CenterNet-based object detection method to construct models for plant disease and pest detection. The accuracy of the models is influenced by parameter alpha, which is used to control the affine transformation in the preprocessing of CenterNet. First, different alphas are sampled for training and testing. Next, the least square method is used to fit the curve between alpha and accuracy measured by mAP (mean average precision). Finally, the equation of the curve is fitted as mAP = -0.22 * alpha2 + 0.32 * alpha + 0.42. In comparison, an automated machine learning (AutoML) method is also conducted to automatically search for the best model. The experiments are done with 5,281 images as the training dataset, 1,319 images as the verification dataset, and 3,842 images as the test dataset. The results show that the best alpha value obtained by the least square method is 0.733, and the accuracy of the corresponding model is 0.536 in mAP@[.5, .95]. In contrast, the accuracy of the AutoML method model is higher with the model accuracy of 0.545 in mAP@[.5, .95]. However, the training time and training resource consumption of the AutoML method are about 3 times that of the least square method. Therefore, in practice, a trade-off should be made according to the accuracy requirements, resource consumption, and task urgency

Incision pressing, a simple and effective intervention to reduce colorectal surgical site infection: A propensity score-matched study

BackgroundColorectal surgery is associated with a high risk of surgical site infection (SSI). In March 2017, we developed an intervention, called “PRESS”, with the aim of reducing colorectal superficial SSI. This study assessed the effect of the new intervention in reducing the rates of superficial SSI in colorectal surgery.MethodsThis study was a retrospective review of 312 PRESS+ patients compared to 171 historical control PRESS− patients who were 18 years of age or older and underwent elective colorectal surgery with clean-contaminated wounds from January 2015 to June 2020. In the PRESS+ groups, we pressed the incision downward hard with clean gauze after the interrupted suturing of the skin. Propensity score matching with 15 variables was performed in a 1:1 ratio to reduce selection bias. Univariate analysis and multivariate analysis were performed to identify risk factors associated with SSI.ResultsThe characteristics of the PRESS+ (n = 160) and PRESS− (n = 160) groups were well balanced after propensity score matching. The PRESS+ group had a lower superficial SSI rate (1.9% vs. 6.9%, P = 0.029) and a lower overall SSI rate (2.5% vs. 10.0%, P = 0.006) than the PRESS− group. Furthermore, multivariate analysis showed that the incisional press was an effective protective factor for superficial SSI (adjusted odds ratio = 0.215, 95% confidence interval = 0.057–0.818, P = 0.024). In addition, female sex (P = 0.048) and blood transfusion (P = 0.011) were demonstrated to be independent risk factors for superficial SSI.ConclusionThe incisional press after suturing is a simple, costless, and effective intervention in reducing superficial incisional SSI