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OBJECTIVE: The aim of this study was to determine the effect of a 7-day extended-hours clinical pharmacy service in the ED on medication prescribing errors upon hospital admission and time to medication reconciliation. METHODS: In this retrospective observational study, high-needs patients reviewed by ED pharmacists were compared against those not reviewed, to determine if the service was associated with reduction in admission medication errors. The primary outcome was the rate of medication errors. Errors were independently rated by two senior clinicians using a risk-probability matrix. Secondary outcomes included service's impact on time to best possible medication history (BPMH) and medication reconciliation. RESULTS: There were 242 patients who met the inclusion criteria: 105 intervention vs 137 control. In the intervention arm, 74 patients had at least 1 medication error compared with 113 in the control arm (total errors 206 vs 407). The error rate per 10 medications (interquartile range) was 1.4 (0, 2.9) in the intervention arm compared with 2.7 (1.2, 4.3) in the control arm (risk ratio 0.66 [95% confidence interval: 0.56-0.78]; P < 0.001). There were 33 moderate-risk and no high-risk errors (intervention), compared with 84 moderate-risk and 3 high-risk errors (control). Percent agreement was 98.98% (weighted kappa: 0.62). Time to BPMH and medication reconciliation were reduced from 40.5 and 45.0 h to 7.8 and 40.0 h, respectively. CONCLUSIONS: The 7-day extended-hours ED clinical pharmacy service was associated with a reduction in medication prescribing errors in high-needs patients and improved time to BPMH and medication reconciliation.

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With urbanization and increasing consumption, there is a growing need to prioritize sustainable development across various industries. Particularly, sustainable development is hindered by air pollution, which poses a threat to both living organisms and the environment. The emission of combustion gases containing particulate matter (PM 2.5) during human and social activities is a major cause of air pollution. To mitigate health risks, it is crucial to have accurate and reliable methods for forecasting PM 2.5 levels. In this study, we propose a novel approach that combines support vector machine (SVM) and long short-term memory (LSTM) with complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to forecast PM 2.5 concentrations. The methodology involves extracting Intrinsic mode function (IMF) components through CEEMDAN and subsequently applying different regression models (SVM and LSTM) to forecast each component. The Naive Evolution algorithm is employed to determine the optimal parameters for combining CEEMDAN, SVM, and LSTM. Daily PM 2.5 concentrations in Kaohsiung, Taiwan from 2019 to 2021 were collected to train models and evaluate their performance. The performance of the proposed model is evaluated using metrics such as mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and coefficient of determination (R2) for each district. Overall, our proposed model demonstrates superior performance in terms of MAE (1.858), MSE (7.2449), RMSE (2.6682), and (0.9169) values compared to other methods for 1-day ahead PM 2.5 forecasting. Furthermore, our proposed model also achieves the best performance in forecasting PM 2.5 for 3- and 7-day ahead predictions.

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Falling is one of the most serious health risk problems throughout the world for elderly people. Considerable expenses are allocated for the treatment of after-fall injuries and emergency services after a fall. Fall risks and their effects would be substantially reduced if a fall is predicted or detected accurately on time and prevented by providing timely help. Various methods have been proposed to prevent or predict falls in elderly people. This paper systematically reviews all the publications, projects, and patents around the world in the field of fall prediction, fall detection, and fall prevention. The related works are categorized based on the methodology which they used, their types, and their achievements.

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Following a 240% increase in the number of compounded sterile preparations between 2012 and 2013, three pharmacy technicians at a metropolitan public hospital suffered hand-related, repetitive strain injuries. This study describes the main safety measures implemented to reduce the risk of repetitive strain injuries associated with sterile compounding at the study hospital, and reports pharmacy technicians' perceptions of their effectiveness. The implemented risk reduction strategies were categorized into five domains of 1) equipment and consumables, 2) training and assessment, 3) Lean waste reduction, 4) roster and shift limits, and 5) workload allocation score. Pharmacy technicians' feedback was collected through an anonymous survey in 2020, five years after the implementation of all safety measures. Responders rated their perceived effectiveness of each strategy domain using a five-point Likert Scale, ranging from very ineffective to very effective. All pharmacy technicians who had been undertaking aseptic compounding activities for at least one year between 2015 and 2020 were invited to take the survey. The five domains of 1) equipment and consumables, 2) training and assessment, 3) Lean waste reduction, 4) roster and shift limits, and 5) workload allocation score were rated effective or very effective by 86%, 67%, 86%, 57%, and 71% of pharmacy technicians, respectively (n=7). The overall effectiveness of all interventions combined was rated effective or very effective by 72% of the participants. Pharmacy technicians' feedback indicates the majority perceive the implemented strategies effective in reducing the risk of repetitive strain injuries associated with aseptic compounding.

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The objective of this study was to evaluate the quality of instructional sterile compounding videos posted on a popular video-sharing website (YouTube). YouTube was systematically searched using relevant terms (aseptic compounding, sterile compounding) to identify all videos demonstrating aseptic manipulations of compounded sterile preparations in a cleanroom. Promotional videos, news stories, interviews, and videos with manipulations performed outside a cleanroom, without audio or spoken in a language other than English, were excluded. Three experts independently reviewed each video and assessed the quality of key sterile compounding processes, information delivery, and overall suitability for workforce training using a standardized assessment tool. Kendall's coefficient of concordance (W) was calculated to assess agreement. Included were 66 videos with a median of 839 (IQR 62-3935) views. There was moderate to substantial agreement among assessors when determining the quality of each step of the compounding process (W 0.48 to 0.72; all P<0.002). Only one in five videos demonstrated an acceptable standard of gloving and garbing, while product inspection and waste disposal processes were more likely to be appropriately demonstrated. Most videos had acceptable sound/image quality and English pronunciation, but not all videos had a comprehensive narration. Six videos (9%) were recommended for training compounding personnel by two assessors and a further 17 (26%) videos were recommended by one assessor. No videos were recommended by all three assessors. The conclusions of this study are: 1) there is considerable variation in the quality of instructional sterile compounding videos available on the YouTube website; 2) few videos are suitable for training compounding personnel.

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Proxy Mobile IPv6 is a network-based localized mobility management protocol that supports mobility without mobile nodes' participation in mobility signaling. The details of user authentication procedure are not specified in this standard, hence, many authentication schemes have been proposed for this standard. In 2013, Chuang et al., proposed an authentication method for PMIPv6, called SPAM. However, Chuang et al.'s Scheme protects the network against some security attacks, but it is still vulnerable to impersonation and password guessing attacks. In addition, we discuss other security drawbacks such as lack of revocation procedure in case of loss or stolen device, and anonymity issues of the Chuang et al.'s scheme. We further propose an enhanced authentication method to mitigate the security issues of SPAM method and evaluate our scheme using BAN logic.

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In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters.

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Cloud computing is a new generation of technology which is designed to provide the commercial necessities, solve the IT management issues, and run the appropriate applications. Another entry on the list of cloud functions which has been handled internally is Identity Access Management (IAM). Companies encounter IAM as security challenges while adopting more technologies became apparent. Trust Multi-tenancy and trusted computing based on a Trusted Platform Module (TPM) are great technologies for solving the trust and security concerns in the cloud identity environment. Single sign-on (SSO) and OpenID have been released to solve security and privacy problems for cloud identity. This paper proposes the use of trusted computing, Federated Identity Management, and OpenID Web SSO to solve identity theft in the cloud. Besides, this proposed model has been simulated in .Net environment. Security analyzing, simulation, and BLP confidential model are three ways to evaluate and analyze our proposed model.

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