Developing a Prenatal Nutrition Tool: A Process of Evidence, Collaboration, and Consultation

The Prenatal Nutrition Tool was created for care providers that work with pregnant clients and aims to support focused conversations on nutrition topics that influence maternal and infant health outcomes. A systematic 9-step product development process that combined findings from the literature with perspectives of nutrition experts and care providers was used to develop the tool. The results of a literature review and a modified Delphi Process (to obtain expert opinion) laid the foundation for the tool content. The final tool incorporated client feedback. More specifically, client feedback helped to refine tool questions. The tool consists of 2 parts: a questionnaire (written survey) and a conversation guide. The questionnaire covers 4 key themes (pregnancy weight gain, multivitamins, life circumstances, overall food intake) in 13 questions. The conversation guide utilizes public health nutrition guidance documents to lead care providers in focused discussions with clients. The tool is not intended to be a screening tool for medical conditions or replace an in-depth prenatal nutrition assessment. The tool can be accessed by any care provider in Canada on the Alberta Health Services website at Prenatal Nutrition Tool | Alberta Health Services .

Classification of Image and Text Data Using Deep Learning-Based LSTM Model

The advent of social networking and the internet has resulted in a huge shift in how consumers express their loyalty and where firms acquire a reputation. Customers and businesses frequently leave comments, and entrepreneurs do the same. These write-ups may be useful to those with the ability to analyse them. However, analysing textual content without the use of computers and the associated tools is time-consuming and difficult. The goal of Sentiment Analysis (SA) is to discover client feedback, points of view, or complaints that describe the product in a more negative or optimistic light. You can expect this to be a result based on this data if you merely read and assess feedback or examine ratings. There was a time when only the use of standard techniques, such as linear regression and Support Vector Machines (SVM), was effective for the task of automatically discovering knowledge from written explanations, but the older approaches have now been mostly replaced by deep neural networks, and deep learning has gotten the job done. Convolution and compressing RNNs are useful for tasks like machine translation, caption creation, and language modelling, however they suffer from gradient disappearance or explosion issues with large words. This research uses a deep learning RNN for movie review sentiment prediction that is quite comparable to Long Short-Term Memory networks. A LSTM model was well suited for modelling long sequential data. Generally, sentence vectorization approaches are used to overcome the inconsistency of sentence form. We made an attempt to look into the effect of hyper parameters like dropout of layers, activation functions and we also tested the model with different neural network settings and showed results that have been presented in the various ways to take the data into account. IMDB is the official movie database which serves as the basis for all of the experimental studies in the proposed model.

Enhancing Drilling Response and Improving ROP on PDC Bits by Utilizing 1-in. Diameter Cutters

This paper details the improvements to drilling performance and torsional response of fixed cutter bits when changing from a conventional 19-mm cutter diameter configuration to 25-mm cutter diameters for similar blade counts in two different hole sizes. Key performance metrics include rate of penetration (ROP), rerun-ability, torsional response, and ability to maintain tool-face control during directional drilling. A high-performance drilling application was selected with several existing offset wells using a 12¼-in., five-bladed, 19-mm (519) drill bit design, and a concept bit developed using 25-mm diameter cutters while maintaining comparable ancillary features. This was tested in the same field on both vertical and S-shape sections using the same bent-housing motor assembly and drilling performance compared to the existing offsets. A 17½-in. hole size application that experiences high drillstring vibration was also selected, and a 25-mm cutter diameter drill bit was designed with comparable ancillary features to replace a six-bladed, 19-mm (619) drill bit. This was tested in the same field with the drilling performance, and vibration propensity was assessed. Initial testing in the 12¼-in. section showed extremely promising initial results, breaking the field ROP record in a well-established field of more than 3,000 wells. The rerun of the same bit without repair placed fourth in the field in terms of ROP records. Additional testing in the vertical and s-shape sections showed the new 25-mm cutter diameter design consistently exceeding the ROP performance of the 519 drill bit design while achieving directional targets without any reported drilling concerns. Subsequent trials with other operators saw similar performance improvement with multiple instances of breaking field ROP records. The first trial of the new 17½-in. hole size design with 25-mm diameter cutters had 34% average higher ROP than the offset average ROP, achieving the field ROP record. An overall 70% improvement during trials was seen in ROP versus the existing 619 drill bit design. The daily drilling reports and client feedback reported a significantly reduced level of drillstring vibration versus offset wells. This paper demonstrates the potential for a paradigm shift in drilling response and overall ROP by using 25-mm diameter cutters on fixed cutter bits. When correctly modeled, designed, and selected for specific applications, they benefit operators by reducing the time it takes to drill the section, improving repairability, reducing the time that an openhole is left exposed, and reducing drilling costs.

Comparing Traditional and Novel Methods in Determining Reach in Bicycle Fitting

In bicycle fitting, the literature has focus historically on the saddle height and knee flexion angle. There has been little focus in the literature on postural reach; this is the distance between the saddle and handlebars. Currently, this distance is determined by a specialist, a bicycle fitter, and is generally based on a trunk, shoulder, and elbow angle; however, it is primarily based on what "looks right" to the fitter and "feels right" to the client, rather than using anthropometric measurement. This study examined whether there was a relationship between anthropometric measures and postural reach, or if ideal fit should continue to be determined by a trial-and-error process, informed by expert opinion and client feedback. This study found that there was a moderate correlation r(9) = 0.663, p < .05 between the upper extremity measure and postural reach and a fair correlation r(9)= 0.296, p < .05 between the trunk measure and postural reach. A significant regression was found between the upper extremity length and the postural reach F(1, 9) = 7.06. The finding of this study does suggest that there is a relationship between the anthropometric measures and the postural reach. However, due to the low number of data points,the external validity may be somewhat limited, and it is suggested that the study be only used as a guide for future exploration.

‘They already operated like it was a crisis, because it always has been a crisis’: a qualitative exploration of the response of one homeless service in Scotland to the COVID-19 pandemic

Background The COVID-19 pandemic has necessitated unprecedented changes in the way that services are delivered to individuals experiencing homelessness and problem substance use. Protecting those at high risk of infection/transmission, whilst addressing the multiple health and social needs of this group, is of utmost importance. The aim of this novel qualitative study was to document how one service in Scotland, the Wellbeing Centre run by The Salvation Army, adapted in response. Methods Care was taken to identify methods that did not create additional stress at this pressured time. Semi-structured interviews were conducted with Centre clients (n = 10, in-person and telephone) and staff (n = 5, telephone), and external professionals (n = 5, telephone), during April–August 2020. These were audio-recorded, fully transcribed, and analysed using Framework. Service documents were used to enhance contextual understanding. Analysis was informed by theories of psychologically informed environments and enabling environments. Results The start of the pandemic was a time of confusion, disruption, and isolation. Centre staff rapidly adapted methods of engagement to provide a range of comprehensive physical and emotional supports, to both existing and new clients, through telephone and online communication and, eventually, socially distanced in-person support. This involved balancing the risks of COVID-19 infection/transmission with the benefits of continuity of support to those highly vulnerable to a range of harms. Whilst the pandemic created many challenges, it also facilitated removal of barriers, particularly concerning provision of harm reduction services which had previously been severely constrained. Clients described the Centre as a ‘lifeline’, providing stability and safety during a period of profound disruption when other services closed their doors. Strong leadership, intensive team working, support/training for staff, a focus on relationships, and active use of client feedback, enabled responsive adaptation to fast-changing demands and the creation of a ‘culture of care’. Conclusion This study provides a unique insight into the pandemic by analysing the response of one homeless service during the height of the pandemic. We present a range of implications that have international relevance for those designing policies, and adapting front-line services, to proactively respond to COVID-19 and the continued public health crises of homelessness and drug-related deaths.

Abstract P309: Provider Specific Quality Metrics: A Qualitative Approach to Quantitative Data

Introduction: Quality measures and benchmarks are well known constants in the stroke world, but there are no established metrics for provider-specific quality related to the practice of stroke care via telemedicine technologies. We propose quality measures uniquely attributable to the practice of stroke telemedicine, regardless of the site where the telemedicine is provided. Methods: By analyzing client feedback obtained through surveys and reviewing historical opportunities, we identified four common themes essential to an excellent telemedicine provider. We then defined and refined each category into reportable measures. Data for the measures are obtained from data entry fields in our internal electronic medical record and reported using Tableau analytics software. Additional data is obtained from client reports and converted into a numerical score. Results: The four thematic areas we identified are responsiveness, documentation compliance, clinical metrics, and citizenship. Responsiveness is measured by callback time and on-camera time. Documentation compliance is measured by percent compliance with documentation of NIHSS score, IV thrombolytic contraindication, and intra-arterial (IA) intervention contraindication. Clinical metrics are defined as alteplase decision making time and alteplase recommendation rate. Although not a purely objective measure, citizenship is a critical component of telemedicine, and thus included for all providers. We investigate and inventory both compliments and complaints received, which are then converted into a score based on all telemedicine encounters. Conclusion: There is a lack of definition in what constitutes clinical excellence for telemedicine, apart from benchmarks that exist for hospitals. Our approach is a novel perspective on categorizing and quantifying telemedicine performance, which can be used as a constructive feedback tool for providers, as well as a mechanism to evaluate and define clinical excellence. We can track performance over time and recognize providers for excellence. Future study is required to correlate these measures with patient outcomes.