Slope Instability of the Earthen Levee in Boston, UK: Numerical Simulation and Sensor Data Analysis

The paper presents a slope stability analysis for a heterogeneous earthen levee in Boston, UK, which is prone to occasional slope failures under tidal loads. Dynamic behavior of the levee under tidal fluctuations was simulated using a finite element model of variably saturated linear elastic perfectly plastic soil. Hydraulic conductivities of the soil strata have been calibrated according to piezometers readings, in order to obtain correct range of hydraulic loads in tidal mode. Finite element simulation was complemented with series of limit equilibrium analyses. Stability analyses have shown that slope failure occurs with the development of a circular slip surface located in the soft clay layer. Both models (FEM and LEM) confirm that the least stable hydraulic condition is the combination of the minimum river levels at low tide with the maximal saturation of soil layers. FEM results indicate that in winter time the levee is almost at its limit state, at the margin of safety (strength reduction factor values are 1.03 and 1.04 for the low-tide and high-tide phases, respectively); these results agree with real-life observations. The stability analyses have been implemented as real-time components integrated into the UrbanFlood early warning system for flood protection

A study of production workflows, technology and hybrid printing models in small newspaper companies

During the past five to ten years, the evolution of different media, and especially Internet-related services, has had a direct impact on the printed newspaper. Companies that have remained stable for several years are today exploring and employing new mechanisms to increase efficiency while maintaining their audiences. Although web offset has been for long the basic production process for printing newspapers, the latest developments implemented in equipment and software for newspaper production have achieved a high degree of automation in prepress, press, and post-press. At the same time, the demand of younger audiences for increasingly diverse and personalized products—as well as the emergence of new services, such as the production of commercial printing jobs—has transformed the newspaper production model (Christensen, 2006). Small newspapers, as well as medium and large, are challenged to compete in this new environment. They have to plan for the future in accordance with their opportunities and limitations. The main purpose of this research was to define a descriptive profile and to represent a graphical workflow model for small newspaper production. Information on the degree of automation, equipment employed, and the extent to which production has adopted the hybrid model (semi-commercial production) are also included in this descriptive profile. The study consisted of seven newspapers with an average daily circulation between 12,000 and 50,000 copies. Six of the participants are located in the U.S., and one is located in Latin America. The main source of information was a survey consisting of demographic, circulation, audience, and production workflow questions. Additionally, the researcher conducted personal interviews and field tours at three of these newspapers. The key findings were: • For the majority of the respondents, the newspaper is between 21% and 38% of the total production (measured in total number of copies printed, including TMCs and commercial jobs). • Six of the seven participants have experienced a reduction in circulation during the past few years. In addition to this trend, the age of the core audience has increased, with the average between 50 to 64 years of age for most newspapers. • All of the respondents currently use coldset web offset as the production process. Two companies have plans to expand their facilities by acquiring equipment with heatset dryers and automatic functions. • In general, the respondents do not use a wide variety of finishing processes. The only post-press process used by all newspapers is inserting. In three cases, this is the only post-press process used. • The degree of automation found in the participants’ workflows is relatively low compared to the capabilities offered by printing equipment manufacturers. The stage of production that shows the highest level of automation is prepress. xi • The process that is most frequently a bottleneck is finishing. None of the respondents consider plate production or the press run to be bottlenecks in the workflow. • The majority of the participants responded that they have not implemented a process to ensure quality. It was also found that little information is collected within the respondents’ production processes. • The physical changes considered by the participants are mostly related to contraction of the core product. • All of the surveyed newspapers produce at least one kind of commercial job. The production of other newspapers and inserts are the two most common commercial jobs produced. The majority of the respondents only offer limited types of commercial jobs. • Although the two preferred strategies among the respondents are separating printing from publishing and consolidating printing facilities, there is no clear trend towards any specific strategy. Three of the newspapers stated that they have no specific business strategy for the near future

Implementation of an Innovative Early Warning System: Evidenced-based Strategies for Ensuring System-wide Nursing Adoption

Early deterioration in adult medical-surgical patients is associated with increased intensive care unit and hospital mortality (Goldhill, 2001). Failure to recognize deterioration is a preventable patient safety and quality issue. To address this problem, since 2013, Kaiser Permanente Northern California (KP NCAL) has piloted Advance Alert Monitor (AAM) at two hospitals. This early warning system employs a set of predictive models developed by the KP NCAL Division of Research, which automatically predicts patient deterioration within the next 12 hours based on a complex algorithm of laboratory and clinical data points. Improvements in mortality and length of stay have been realized at the two pilot hospitals. In anticipation of expansion to additional NCAL facilities, major changes to the AAM workflows and processes were developed that increased the sensitivity of the patients identified at risk for clinical deterioration, as well as the timeliness and clarity of clinical response. Expansion to two additional pilot hospitals using these revised processes rely on the evidence-based implementation strategies found in this Doctor of Nursing Practice project. This paper examines the planning, assessment, and implementation of early warning systems at two NCAL facilities using Rogers’ diffusion of innovation theory and Greenhalgh’s extension of Rogers’ theory. Key attributes need to be considered from a cultural and organizational perspective to both start and sustain an implementation. The success of AAM implementation is validated using specific outcome and process measures, including compliance with documentation and timeliness of workflows

A Semantic IoT Early Warning System for Natural Environment Crisis Management

This work was supported in part by the European FP7 Funded Project TRIDEC under Grant 258723, the other project partners in helping to deliver the complete project Syste, in particular, GFZ, and the German Research Centre for Geosciences, Potsdam, Germany. The work of R. Tao was supported by the Queen Mary University of London for a Ph.D. studentship

A Semantic loT Early Warning System for Natural Environment Crisis Management

An early warning system (EWS) is a core type of data driven Internet of Things (IoTs) system used for environment disaster risk and effect management. The potential benefits of using a semantic-type EWS include easier sensor and data source plug-and-play, simpler, richer, and more dynamic metadata-driven data analysis and easier service interoperability and orchestration. The challenges faced during practical deployments of semantic EWSs are the need for scalable time-sensitive data exchange and processing (especially involving heterogeneous data sources) and the need for resilience to changing ICT resource constraints in crisis zones. We present a novel IoT EWS system framework that addresses these challenges, based upon a multisemantic representation model.We use lightweight semantics for metadata to enhance rich sensor data acquisition.We use heavyweight semantics for top level W3CWeb Ontology Language ontology models describing multileveled knowledge-bases and semantically driven decision support and workflow orchestration. This approach is validated through determining both system related metrics and a case study involving an advanced prototype system of the semantic EWS, integrated with a reployed EWS infrastructure

Advance Alert Monitor

Problem: The acute deterioration of patients outside the Intensive Care Unit (ICU) are safety and quality concerns. Studies have shown that these deteriorations are associated with increased morbidity and mortality. This study aims to standardize the Rapid Response Team (RRT) nurse documentation in response to an Advanced Alert Monitor (AAM) alert, as at baseline no such alert nor standardized response and documentation exist. Context: Hospitals are continually challenged to innovate and create systems that can track multiple parameters and identify at-risk patients earlier on. An Early Warning System (EWS) in combination with a RRT significantly reduces patients’ potential for clinical decline. Predictive analytic systems such as an EWS are being introduced in response to this challenge and are anticipated to become the standard of care. The healthcare system/organization examined in this study aims to provide high quality, affordable health care services; and to improve the health of its members and the communities it serves. The Advance Alert Monitor (AAM) program enables this healthcare system/organization to better deliver on that mission by closing the quality gap of failure to recognize clinical decline in patients’ conditions. Interventions: The health system’s EWS is the AAM program. Its goal is to address safety and quality concerns associated with failing to identify a decline in patients’ conditions in a timely manner. The electronic health record and other sources are scanned constantly to generate an AAM score hour. If the score is eight percent or greater risk of deteriorating within 12 hours, E-Hospital staff review the patient’s chart and notify the RRT nurse. The RRT nurse collaborates with the primary nurse to assess the patient and communicate findings to the attending hospitalist. A standardized RRT nursing note is utilized to document the response for all initial AAM alerts. Measures: A family of measures was developed for the project. The outcome measure focused on the percentage of RRT nursing notes present for all initial AAM alerts. This measure recorded both a response and documentation of that response to the alert. Process measures included RRT proactive rounding documentation, and training of 100% RRT nurses on the AAM workflow. Tracking of code blue events outside the ICU was used as a balancing measure. Results: From January 1through June 30, 2018, there were 527 initial AAM alerts. Of those, 504 (95.6%) initial AAM alerts had the RRT nursing note present which indicates an intervention was made. Conclusions: The aim of this project was to integrate AAM predictive analytics with RRT practices that include a newly implemented standardized RRT nursing note; with AAM enabling early intervention to prevent a decline in patients’ conditions, and the RRT nursing note the documentation of such. The project was successfully implemented at the medical center with 95.6% RRT nursing note completion - and thus an intervention made - for all initial AAM alerts

ECHO Information sharing models

As part of the ECHO project, the Early Warning System (EWS) is one of four technologies under development. The E-EWS will provide the capability to share information to provide up to date information to all constituents involved in the E-EWS. The development of the E-EWS will be rooted in a comprehensive review of information sharing and trust models from within the cyber domain as well as models from other domains

The clinical pharmacist improves pharmacotherapy in hospital patients:Medication reviews - Metformin toxicity - Binding interactions

This thesis describes, in three different parts, how the clinical pharmacist can contribute in improving pharmacotherapy of hospital patients. Firstly, the clinical value of pharmacist-led medication reviews was assessed in (pre)dialysis patients and older patients with cancer. We concluded that pharmacist-led medication reviews are a suitable instrument to identify drug related problems and inappropriate prescribing in order to improve medication management in these complex hospital patients. Secondly, the management of metformin associated lactic acidosis (MALA), a rare but serious adverse effect of a frequently used drug for diabetes mellitus type 2, was studied. The incidence of MALA is 5 to16 times higher than reported in literature. When managing lactic acidosis in the emergency department the diagnosis MALA should be considered in patients with a creatinine concentration ≥ 256 umol/l and lactate concentration ≥ 8.4 mmol/l. Severity of lactic acidosis and renal impairment are the main indications for initiating extracorporeal treatment, which may be lifesaving in treating MALA. Finally, several potential new drug binding interactions were studied with sevelamer and polystyrene sulfonate, drugs that are often used by chronic kidney disease patients. Fourteen and 23 potentially new binding interactions with sevelamer and polystyrene sulfonate were established based on an in silico – in vitro approach, which have to be confirmed in vivo. The binding interaction, amitriptyline with polystyrene sulfonate, was studied in healthy volunteers. The exposure of amitriptyline was decreased with 75% when amitriptyline was simultaneously ingested with polystyrene sulfonate compared to intake of amitriptyline alone, necessitating staggered dosing between drugs

Introduction of a Comprehensive Modified Early Warning Scoring System in a Large Rural Hospital

PURPOSE: To develop and test a comprehensive modified early warning scoring (MEWS) system for use on two medical-surgical-telemetry units in a large rural hospital in northeastern Kentucky; to educate and train nursing staff in utilization of a new MEWS system and early identification and management of clinical deterioration; and to determine nursing satisfaction regarding education, training, and use of a new MEWS system. BACKGROUND: Adult medical-surgical patients are at risk for clinical deterioration. Rapid response systems and MEWS systems are strategies that have been employed to assist nursing staff in early identification and management of clinical deterioration. Testing of a newly proposed comprehensive MEWS system and an educational intervention is an essential first step in determining interventional effectiveness. STUDY DESIGN: A retrospective, single center, mixed methods observational study. METHODS: In Phase I, retrospective chart reviews (RCRs) were conducted during a 6-month timeframe for patients meeting one of the following severe adverse event (SAE) criteria: in-hospital cardiac arrest, in-hospital death, unexpected transfer to the intensive care unit, and/or rapid response team utilization specifically pertaining to the medical-surgical-telemetry units of interest. Physiologic parameters (i.e., vital signs and level of consciousness) and nursing responses were recorded in the 24-hours leading up to SAEs; MEWS were retrospectively calculated at 24-hours (MEWS24), 16-hours (MEWS16), and 8-hours (MEWS8) to gauge utility of the MEWS tool. In Phase II, a 3-hour education and training workshop designed for nursing staff was developed, implemented, and evaluated. A focus was placed on use of a new MEWS system and early identification and management of clinical deterioration. RESULTS: In Phase I of RCRs, 81 patients met criteria during a study timeframe of September 2016 through February 2017. Demographic data yielded the following: 51.9% male, 76.5% sixty years of age or older, and 98.8% White. MEWS24 (n = 62) had a mean of 3.0, standard deviation (SD) of 1.6, and range of 1.0 – 7.0; MEWS16 (n = 76) had a mean of 3.3, SD of 1.3, and range of 1.0 – 7.0; and MEWS8 (n = 81) had a mean of 5.0, SD of 2.3, and range of 1.0 – 10.0. In Phase II, nine nursing staff participated in one of eight education and training workshops. Participants reported increased confidence in recognizing deterioration, responding to deterioration, and communicating concerns following an educational intervention. Nursing staff consistently reported respiratory effort, level of consciousness, oxygen saturation, respiratory rate, blood pressure, and heart rate as the most influential parameters in a nursing assessment for determining clinical deterioration. Satisfaction was high regarding the education, training, and use of a new MEWS system. CONCLUSION: RCRs indicated that a MEWS system would be feasible in identifying patients at risk for SAEs in this patient population. Introduction of a new comprehensive MEWS system with an educational intervention had a positive effect on nursing staff’s self-reported confidence, knowledge, and skill in recognizing and managing clinical deterioration. RELEVANCE TO CLINICAL PRACTICE: Before full implementation, a prospective study is recommended to test a comprehensive MEWS system for all admissions through discharge over a defined time period and provide a mandatory educational intervention for interdisciplinary staff on the two medical-surgical-telemetry units of interest. Great insight could be learned regarding tool utility, resource utilization, and staff preparedness