Current Assessment Methods Research Articles

Objective Nontechnical Skills Measurement Using Sensor-based Behavior Metrics in Surgical Teams.

The purpose of this study was to identify objective measures that predict surgeon nontechnical skills (NTS) during surgery. NTS are cognitive and social skills that impact operative performance and patient outcomes. Current methods for NTS assessment in surgery rely on observation-based tools to rate intraoperative behavior. These tools are resource intensive (e.g., time for observation or manual labeling) to perform; therefore, more efficient approaches are needed. Thirty-four robotic-assisted surgeries were observed. Proximity sensors were placed on the surgical team and voice recorders were placed on the surgeon. Surgeon NTS was assessed by trained observers using the NonTechnical Skills for Surgeons (NOTSS) tool. NTS behavior metrics from the sensors included communication, speech, and proximity features. The metrics were used to develop mixed effect models to predict NOTSS score and in machine learning classifiers to distinguish between exemplar NTS scores (highest NOTSS score) and non-exemplar scores. NTS metrics were collected from 16 nurses, 12 assistants, 11 anesthesiologists, and four surgeons. Nineteen behavior features and overall NOTSS score were significantly correlated (12 communication features, two speech features, five proximity features). The random forest classifier achieved the highest accuracy of 70% (80% F1 score) to predict exemplar NTS score. Sensor-based measures of communication, speech, and proximity can potentially predict NOTSS scores of surgeons during robotic-assisted surgery. These sensing-based approaches can be utilized for further reducing resource costs of NTS and team performance assessment in surgical environments. Sensor-based assessment of operative teams' behaviors can lead to objective, real-time NTS measurement.

Gene expression correlation analysis of livers undergoing normothermic machine perfusion identifies interactions between donor demographics and liver function

BackgroundLiver transplantation is currently the only cure for end‐stage liver disease, but the shortage of donor livers severely limits the effectiveness of transplantation. This shortage is made worse by challenges in preserving and assessing livers pre‐transplant that can result in discarding of functional livers. Normothermic machine perfusion (NMP) is a method of liver preservation that aims to provide physiological conditions while allowing real‐time assessment of transplant viability criteria. The aim of this study was to understand the effect of machine perfusion on the transcriptome and to correlate changes in gene expression with functional liver metrics.MethodsTen discarded livers (5 steatotic, 5 non‐steatotic), rejected by local transplant centers, were obtained from donation after circulatory death (DCD). The livers underwent 12 hours of NMP with oxygenated red blood cells. Serial tissue and plasma samples were collected at various times during perfusion. Plasma lactate samples were used to categorize liver as meeting viability criteria (viable) or not (nonviable) following NMP. Transcriptome sequencing was performed on serial biopsies taken at 0, 3, and 6hr during perfusion. Weighted gene co‐expression network analysis (WGCNA) was performed to correlate each module with demographics and functional metrics. Pathway and transcription factor analysis were performed on significant modules of interest.ResultsExpression data at 0, 3 and 6 hr of perfusion was used to construct the weighted co‐expression network. Gene co‐expression modules were then correlated with various clinical demographics and functional data collected during NMP. To evaluate the functional association of genes in the modules that significantly correlated with arterial lactate levels, we performed Gene Ontology enrichment analysis. By using lactate clearance as an indicator of transplant viability we were able to identify co‐expression gene sets enriched for biological processes including drug metabolism, immune response, autophagy, vascular development, nutrient metabolism, and gene expression.ConclusionsCurrent donor liver assessment models are limited by traditionally accessible parameters and can often lead to discarding potentially viable organs. NMP provides a novel data collection platform that could be used to improve traditional assessment models. By performing WGCNA, we were able to capitalize on an extensive set of metrics to identify interactions between the diverse donor demographics, the functional data collected during NMP and changes in gene expression. This may ultimately allow us to identify novel biomarkers to improve our current methods of donor liver assessment and assist the development of targeted therapeutics for more successful preservation and utilization of diverse donor livers.

Early-stage assessment of structural damage caused by braced excavations: Uncertainty quantification and a probabilistic analysis approach

Current early stage assessment methods for deep excavation induced structural damage have large uncertainty due to modeling idealizations (simplification in analyses) and ignorance (incompleteness of information). This paper implements an elastoplastic two-stage solution of soil-structure-interaction to predict building response to adjacent deep excavations with braced supports. This soil-structure-interaction solution is then used to study the uncertainty in two case studies. A global sensitivity analysis is conducted, which indicates that the prediction of ground movement profiles is the major source of uncertainty in early stage building damage assessment. The uncertainty due to ignorance and idealizations related to structural analysis models also contribute significantly when target buildings are modeled as equivalent beams. However, the use of a 2-dimensional elastic frame structural model, in lieu of an equivalent beam, considerably reduces the assessment uncertainty. Considering the existence of uncertainty, a probabilistic analysis approach is proposed to quantify the uncertainty when predicting potential building damage due to excavation-induced subsidence. A computer program called Uncertainty Quantification in Excavation-Structure Interaction (UQESI) is developed to implement this probabilistic analysis approach.

TRAINING AND DEVELOPMENT OF DIGITAL SKILLS IN GENERAL EDUCATION

Based on the analysis of the curricula in computer science subjects in the countries with traditions in the field and the experience of the Republic of Moldova, it is argued the need to further promote the curricular reform in general education. It is proposed to re-conceptualize the current and summative assessment methods in computer science disciplines by basing them on the evaluation of digital products developed by students: documents and electronic presentations, Web documents, computer programs, simulation models. It is recommended that the assessment itself be conducted in a digital environment, giving students the opportunity to demonstrate their knowledge and skills directly on the computer.

An Intelligent Clinical Psychological Assessment Method Based on AHP-LSSVR Model.

Clinical psychology is a branch of applied psychology. Clinical psychology has a clear understanding of individual behavior ability and behavior characteristics through psychological measurement analysis, observation, and other methods and combines the situation learned from individual psychosomatic diagnosis and life history with the observation and analysis of individual living conditions. Psychological quality and its evaluation methods have been widely used in many fields, which has greatly promoted the development of this field. However, the current assessment methods are mainly based on a simple statistical analysis, and the results are not accurate. To this end, this article proposes the analytic hierarchy process (AHP) and least-squares support vector regression algorithm (LSSVR). Specifically, through the construction of the specific object's psychological quality evaluation index system, the design and implementation of the psychological quality evaluation model based on AHP-LSSVR and the proposed method were discussed in the experiment.

Validation of the isothermal Schistosoma haematobium Recombinase Polymerase Amplification (RPA) assay, coupled with simplified sample preparation, for diagnosing female genital schistosomiasis using cervicovaginal lavage and vaginal self-swab samples.

BackgroundFemale genital schistosomiasis (FGS) is a neglected and disabling gynecological disease that can result from infection with the parasitic trematode Schistosoma haematobium. Accurate diagnosis of FGS is crucial for effective case management, surveillance and control. However, current methods for diagnosis and morbidity assessment can be inaccessible to those at need, labour intensive, costly and unreliable. Molecular techniques such as PCR can be used to reliably diagnose FGS via the detection of Schistosoma DNA using cervicovaginal lavage (CVL) samples as well as lesser-invasive vaginal self-swab (VSS) and cervical self-swab samples. PCR is, however, currently unsuited for use in most endemic settings. As such, in this study, we assessed the use of a rapid and portable S. haematobium recombinase polymerase amplification (Sh-RPA) isothermal molecular diagnostic assay, coupled with simplified sample preparation methodologies, to detect S. haematobium DNA using CVL and VSS samples provided by patients in Zambia.Methodology/Principal findingsVSS and CVL samples were screened for FGS using a previously developed Sh-RPA assay. DNA was isolated from VSS and CVL samples using the QIAamp Mini kit (n = 603 and 527, respectively). DNA was also isolated from CVL samples using two rapid and portable DNA extraction methods: 1) the SpeedXtract Nucleic Acid Kit (n = 223) and 2) the Extracta DNA Tissue Prep Kit (n = 136). Diagnostic performance of the Sh-RPA using VSS DNA extacts (QIAamp Mini kit) as well as CVL DNA extracts (QIAamp Mini kit, SpeedXtract Nucleic Acid Kit and Extracta DNA Tissue Prep Kit) was then compared to a real-time PCR reference test.Results suggest that optimal performance may be achieved when the Sh-RPA is used with PuVSS samples (sensitivity 93.3%; specificity 96.6%), however no comparisons between different DNA extraction methods using VSS samples could be carried out within this study. When using CVL samples, sensitivity of the Sh-RPA ranged between 71.4 and 85.7 across all three DNA extraction methods when compared to real-time PCR using CVL samples prepared using the QIAamp Mini kit. Interestingly, of these three DNA extraction methods, the rapid and portable SpeedXtract method had the greatest sensitivity and specificity (85.7% and 98.1%, respectively). Specificity of the Sh-RPA was >91% across all comparisons.Conclusions/SignificanceThese results supplement previous findings, highlighting that the use of genital self-swab sampling for diagnosing FGS should be explored further whilst also demonstrating that rapid and portable DNA isolation methods can be used to detect S. haematobium DNA within clinical samples using RPA. Although further development and assessment is needed, it was concluded that the Sh-RPA, coupled with simplified sample preparation, shows excellent promise as a rapid and sensitive diagnostic tool capable of diagnosing FGS at the point-of-care in resource-poor schistosomiasis-endemic settings.

Implementing Machine Learning Models for Suicide Risk Prediction in Clinical Practice: Focus Group Study With Hospital Providers.

BackgroundInterest in developing machine learning models that use electronic health record data to predict patients’ risk of suicidal behavior has recently proliferated. However, whether and how such models might be implemented and useful in clinical practice remain unknown. To ultimately make automated suicide risk–prediction models useful in practice, and thus better prevent patient suicides, it is critical to partner with key stakeholders, including the frontline providers who will be using such tools, at each stage of the implementation process.ObjectiveThe aim of this focus group study is to inform ongoing and future efforts to deploy suicide risk–prediction models in clinical practice. The specific goals are to better understand hospital providers’ current practices for assessing and managing suicide risk; determine providers’ perspectives on using automated suicide risk–prediction models in practice; and identify barriers, facilitators, recommendations, and factors to consider.MethodsWe conducted 10 two-hour focus groups with a total of 40 providers from psychiatry, internal medicine and primary care, emergency medicine, and obstetrics and gynecology departments within an urban academic medical center. Audio recordings of open-ended group discussions were transcribed and coded for relevant and recurrent themes by 2 independent study staff members. All coded text was reviewed and discrepancies were resolved in consensus meetings with doctoral-level staff.ResultsAlthough most providers reported using standardized suicide risk assessment tools in their clinical practices, existing tools were commonly described as unhelpful and providers indicated dissatisfaction with current suicide risk assessment methods. Overall, providers’ general attitudes toward the practical use of automated suicide risk–prediction models and corresponding clinical decision support tools were positive. Providers were especially interested in the potential to identify high-risk patients who might be missed by traditional screening methods. Some expressed skepticism about the potential usefulness of these models in routine care; specific barriers included concerns about liability, alert fatigue, and increased demand on the health care system. Key facilitators included presenting specific patient-level features contributing to risk scores, emphasizing changes in risk over time, and developing systematic clinical workflows and provider training. Participants also recommended considering risk-prediction windows, timing of alerts, who will have access to model predictions, and variability across treatment settings.ConclusionsProviders were dissatisfied with current suicide risk assessment methods and were open to the use of a machine learning–based risk-prediction system to inform clinical decision-making. They also raised multiple concerns about potential barriers to the usefulness of this approach and suggested several possible facilitators. Future efforts in this area will benefit from incorporating systematic qualitative feedback from providers, patients, administrators, and payers on the use of these new approaches in routine care, especially given the complex, sensitive, and unfortunately still stigmatized nature of suicide risk.

Comparison of Spinal Cord Stimulation Trial Reporting Protocols and Long-Term Pain Relief Outcomes Following Implantation

ObjectivesAppropriate spinal cord stimulation (SCS) candidates are required to undergo an SCS trial before implant, typically with ≥50% pain relief deemed “successful.” However, SCS trialing protocols can vary substantially. The primary aim of this retrospective study is to investigate the associations between SCS trial results and long-term SCS pain outcomes. Materials and MethodsThis study was a retrospective single-center review of successful SCS trials from January 1, 2017, to July 1, 2019. A total of 115 patients were included. Group differences in continuous variables were evaluated using t-tests, and group differences in categorical variables were evaluated using the χ2 test. The percentage improvement in long-term pain intensity was analyzed as a binary variable, where long-term success was defined as ≥50% improvement in numeric rating scale pain scores. The level of significance for all tests was set at p < 0.05. ResultsThe mean age was 64.9 years, and 52% of patients were men. The mean pain score at long-term follow-up was 4.7 ± 2.6, and the median time from implantation to follow-up was 13 months (25th–75th interquartile range; 4–22). In the logistic regression analysis adjusted for age, sex, and follow-up time, greater patient-reported percentage improvement in pain scale during the trial was significantly associated with greater odds of experiencing ≥50% improvement in pain scores (p = 0.048; 95% CI 1.00–1.70). All other assessed trial metrics were not significantly associated with greater odds of experiencing >50% improvement in pain scores at last follow-up. ConclusionsGiven the variability in current assessment techniques, we recommend the patient-reported percentage improvement in pain scale as the posttrial assessment method of choice instead of a calculated percentage improvement. However, our results indicate that current trial assessment methods are generally poor, and improved trial reporting protocols must be sought.

Validating the agreement between the geriatric trauma frailty index and four published frailty scores in the Chinese geriatric trauma population

BackgroundIn the geriatric patient population, frailty significantly affects a patient’s prognostic outcome. This study aimed to compare the consistency of our constructed geriatric trauma frailty index with previously published indexes.MethodsThe geriatric trauma frailty index (GTFI) was compared with four previously published frailty indexes, i.e., the hospital frailty risk score (HFRS), Fried index, trauma-specific frailty index (TSFI), and 11-item modified frailty index (mFI) using the Bland-Altman method, intraclass correlation coefficient (ICC), and kappa consistency test. The indexes were calculated based on data collected from 101 questionnaires and medical records from 101 geriatric trauma patients at a tertiary hospital in Shanghai.ResultsAmong the 101 geriatric trauma patients, 64 (63.4%) were women, with a mean age of 71.18 (SD = 9.89) years and mean length of stay (LOS) of 7.51 (SD = 3.89) days. The mean scores of GTFI score(≥ 1.3045 as frail), Fried index score(≥3 items as frail), TSFI score(≥ 4 as frail), and mFI (≥ 3 as frail),were 0.86 (SD = 1.51), 0.76 (SD = 1.07), 1.76 (SD = 1.96), and 1.29 (SD = 1.17). respectively. The GTFI score had good consistency with the HFRS (ICC: 0.716, 95% confidence interval [CI]: 0.596, 0.799, kappa: 0.608, 95% CI: 0.449, 0.766), fair consistency with the TSFI (ICC: 0.407, 95% CI: 0.227, 0.562, kappa: 0.460, 95% CI: 0.239, 0.672), and poor consistency with the mFI (ICC: 0.286, 95% CI: 0.097, 0.455, kappa: 0.305, 95% CI: 0.069, 0.525) and Fried index score (ICC: 0.256, 95% CI: 0.063, 0.426, kappa: 0.188, 95% CI: − 0.028, 0.408).ConclusionsDifferent frailty indexes are based on different concepts of frailty and cannot be assumed to be interchangeable. There is still no gold standard for the current assessment methods of frailty, but it can be compared based on the understanding in terms of the concepts and measures used in each.

Resilience assessment methods for hospitals subjected to earthquakes: State of the art

AbstractHospitals play essential roles in modern communities in the lives of people. During and after earthquakes, they are supposed to be resilient and provide continued medical and social services. Resilience assessment methods are essential for determining hospitals' resilience levels, and the results will provide a direct basis and foundation for the design of new hospitals and retrofit optimization of existing hospitals. This paper reviews the resilience assessment methods and performance measures for hospitals subjected to earthquakes. Current assessment methods are divided into indicator‐ and functionality‐based categories, and the performance measures for quantifying the functionality of hospitals are classified into availability, productivity, quality, and hybrid. This study will assist stakeholders and managers in understanding available assessment methods.

Pedigree analysis and estimates of effective breeding size characterize sea lamprey reproductive biology.

The sea lamprey (Petromyzon marinus) is an invasive species in the Great Lakes and the focus of a large control and assessment program. Current assessment methods provide information on the census size of spawning adult sea lamprey in a small number of streams, but information characterizing reproductive success of spawning adults is rarely available. We used RAD‐capture sequencing to genotype single nucleotide polymorphism (SNP) loci for ~1600 sea lamprey larvae collected from three streams in northern Michigan (Black Mallard, Pigeon, and Ocqueoc Rivers). Larval genotypes were used to reconstruct family pedigrees, which were combined with Gaussian mixture analyses to identify larval age classes for estimation of spawning population size. Two complementary estimates of effective breeding size (N b), as well as the extrapolated minimum number of spawners (N s), were also generated for each cohort. Reconstructed pedigrees highlighted inaccuracies of cohort assignments from traditionally used mixture analyses. However, combining genotype‐based pedigree information with length‐at‐age assignment of cohort membership greatly improved cohort identification accuracy. Population estimates across all three streams sampled in this study indicate a small number of successfully spawning adults when barriers were in operation, implying that barriers limited adult spawning numbers but were not completely effective at blocking access to spawning habitats. Thus, the large numbers of larvae present in sampled systems were a poor indicator of spawning adult abundance. Overall, pedigree‐based N b and N s estimates provide a promising and rapid assessment tool for sea lamprey and other species.

Border Line Definition Using Hyperspectral Imaging in Colorectal Resections.

Simple SummaryGood oxygenation of both bowel ends is an important prerequisite to promote anastomotic healing after colorectal resections. Bowel oxygenation is usually assessed clinically. Hyperspectral imaging is a contactless and contrast-free tool that allows quantifying tissue oxygen intraoperatively. In this study, the results of 105 colorectal resections with hyperspectral imaging are reported.Background: A perfusion deficit is a well-defined and intraoperatively influenceable cause of anastomotic leak (AL). Current intraoperative perfusion assessment methods do not provide objective and quantitative results. In this study, the ability of hyperspectral imaging (HSI) to quantify tissue oxygenation intraoperatively was assessed. Methods: 115 patients undergoing colorectal resections were included in the final analysis. Before anastomotic formation, the bowel was extracted and the resection line was outlined and imaged using a compact HSI camera, in order to provide instantaneously quantitative perfusion assessment. Results: In 105 patients, a clear demarcation line was visible with HSI one minute after marginal artery transection, reaching a plateau after 3 min. In 58 (55.2%) patients, the clinically determined transection line matched with HSI. In 23 (21.9%) patients, the clinically established resection margin was entirely within the less perfused area. In 24 patients (22.8%), the HSI transection line had an irregular course and crossed the clinically established resection line. In four cases, HSI disclosed a clinically undetected lesion of the marginal artery. Conclusions: Intraoperative HSI is safe, well reproducible, and does not disrupt the surgical workflow. It also quantifies bowel surface perfusion. HSI might become an intraoperative guidance tool, potentially preventing postoperative complications.

Development of a modified standard termite test for mass timber products

U.S. manufacturers are looking to expand the use of cross laminated timber panels (CLT) into the North American market, including states located in the southeast. However, there is no current assessment method for determining CLT vulnerability to the highly destructive native termites found throughout the U.S. The impact of these termites is particularly high in areas with suitable climate to their proliferation, such as the southeastern U.S. This study aimed to evaluate durability of CLT panels and to develop a laboratory assay to test susceptibility of this product to termites. Untreated CLT suffered mass loss of up to 43.8% in testing with an average visual rating of 7.2, indicating a moderate to severe attack with 10 to 30% of the cross-section of the product affected by termite intrusion.&nbsp; Recommendations were developed for inclusion in standardized testing protocols and will be presented to standards organizations as appropriate. The proposed method can also be applied to evaluate termite resistance of other mass lumber products such as parallel strand lumber, laminated veneer lumber, and Glulam.

P03 A qualitative exploration of antimicrobial stewardship and resistance education in undergraduate healthcare professional programmes

BackgroundEducation of undergraduate healthcare professionals (HCPs) on antimicrobial stewardship (AMS) and antimicrobial resistance (AMR) is recommended as an important strategy to prepare future HCPs for their roles in these areas.1 There is limited qualitative research investigating the views of clinical and academic staff involved in the teaching of undergraduate HCP students on current AMS/AMR education practices and curricula.ObjectivesTo explore the views and experiences of clinical and academic staff involved in HCP and public health programmes on AMS and AMR education.MethodsA qualitative study using semi-structured interviews was conducted in October to December 2020. The interview participants were purposively sampled to recruit clinical or academic staff involved in education of students on undergraduate HCP programmes (dentistry, medicine, nursing and midwifery, pharmacy) and public health programmes in an Irish university. Participants were asked to outline their views on current teaching and assessment methods, use of AMS competency frameworks and potential areas for improvement. Interview recordings were conducted online, the recordings were transcribed verbatim, and transcripts analysed by thematic analysis. Ethical approval was obtained, and all participants provided written informed consent.ResultsInterviews were conducted with 15 participants (10 female). A range of disciplines were represented as outlined in the methods. The main interview themes included the challenge of balancing curriculum priorities and capacity in HCP programmes, the importance of ensuring student understanding of AMS/AMR principles, and patient centred application of knowledge. Current teaching and assessment methods were found to vary between the HCP programmes with a mix of didactic lectures and workshops, and assessment ranging from written exams and multiple choice questions to observed structured clinical exams. Very few participants reported educating different HCP students together. Participants were asked to review an antimicrobial education competency framework,2 with most participants believing that this would improve the structure of AMS education, ensuring that key learning outcomes would be addressed in the curriculum. The importance of preparing students for interprofessional practice in AMS in the future was identified as a key theme, with participants highlighting the importance of interprofessional education opportunities to foster communication and teamwork skills in AMS at an early stage.ConclusionsThe importance of AMS and AMR education in HCP programmes was reported in this study, however the main challenge is limited curricular space in busy HCP programmes. Education may be improved by aligning AMS education with an appropriate competency framework. Enhancement of undergraduate interprofessional education opportunities, to prepare students for interprofessional AMS in future practice, is recommended.

Evaluation of Current Quality Assessment Methods and Approaches by Building Contractors in Lagos State, Nigeria

Contractors need to pay close attention to the quality of materials used for construction as well as the level of skills of individuals engaging in the building process. Greedy investors are taking advantage of the fact that there are no strict and standardized procedures to monitor and control the construction of new houses or the renovation of existing ones, the need to check the existing quality assessment methods and Approaches Utilised by Building Contractors comes highly. The aim of this study to evaluate current quality assessment methods and approaches by building contractors in Lagos state, Nigeria,. In order to realize this aim, the study examined the various methods like statistical method, visual method,feedback method, use of record and automated method. The study employed a descriptive case study design where data was collected from senior managers, project managers, engineers, architects, quantity surveyors, and technical managers working with building construction companies in the Lagos Metropolitan Area using the mixed method approach. Quantitative data was collected using questionnaire from 109 randomly selected participants and analysed using descriptive and inferential statistics. Qualitative data was collected through interviews with 9 purposively selected respondents and analysed using the thematic analysis technique. The study identified the earlier mention four(4) current quality Assessment Methods and Approaches Utilised by Building Contractors in Lagos State. The findings identified observation/ physical inspections were the most widely applied method of quality assessment while other method is review of records, Feedback and Sampling. The study concludes that developing a model for guiding the process of assessing quality among Lagos and Nigerian contractors. The model helps to standardize the processes of assessing quality within the Lagos construction industry.

Smart City Dimensions and Associated Risks: Review of literature

Countries have been working on implementing smart city concepts in different regions. The need for the use of information and communication technology in various forms is needed in such cities. There are different dimensions that are to be considered for smart city planning and implementation. This complexity of the dimension, the use of technology, and their integration bring the risk perspectives into the implementation of the smart city concept. If such risks are not adequately understood and addressed, they can create issues in terms of privacy and security and, therefore, the functioning of smart cities. In this review, the identification of dimensions, smart city assessment tools, the available technologies, and the technical and non-technical risk parameters related to smart cities implementation are discussed. The current methods of risk assessment and the possible enhancements are highlighted. The findings of the literature review illustrate that not all smart cities adapt all of the smart city dimensions. The dominant technology used in smart cities’ applications is found to be the Internet of Things, Artificial Intelligence, and blockchain. The paper also provides some research directions for the design, implementation, and operation of smart cities.

Protocol of a pilot-scale, single-arm, observational study to assess the utility and acceptability of a wearable hydration monitor in haemodialysis patients

BackgroundFluid overload has a high prevalence in haemodialysis patients and is an important risk factor for excess mortality and hospitalisations. Despite the risks associated with chronic fluid overload, it is clinically difficult to assess and maintain fluid status adequately. Current methods of fluid status assessment are either imprecise or time intensive. In particular, to date, no method exists to accurately assess fluid status during the interdialytic interval.ObjectivesThis pilot study aimed to evaluate whether a prototype wearable hydration monitor can accurately and reproducibly detect fluid overload in the haemodialysis population when compared to haemodialysis and bioimpedance data.MethodsA prospective, open-label, single-arm observational trial of 20 patients commenced in January 2021 in a single haemodialysis centre in Ireland, with a wearable hydration monitor, the Sixty device. The Sixty device uses diffuse reflectance spectroscopy to measure fluid levels at the level of the subdermis and uses machine learning to develop an algorithm that can determine fluid status. The Sixty device was worn at every dialysis session and nocturnally over a three-week observational period. Haemodialysis parameters including interdialytic weight gain, ultrafiltration volume, blood pressure, and relative blood volume were collected from each session, and bioimpedance measurements using the Fresenius body composition monitor were performed on 4 occasions as a comparator. The primary objective of this trial was to determine the accuracy and reproducibility of the Sixty device compared to bioimpedance measurements.ConclusionIf the accuracy of the wearable hydration monitor is validated, further studies will be conducted to integrate the device output into a multi-parameter machine learning algorithm that can provide patients with actionable insights to manage fluid overload in the interdialytic period.Trial registrationwww.clinicaltrials.govNCT04623281. Registered November 10th, 2020.

Evaluation of noise excitation as a method for detection of hypernasality

Hypernasality is a disorder where excess nasal resonance is perceived during speech, often as a result of abnormal coupling between the oral and nasal tracts known as velopharyngeal insufficiency (VPI). The most common cause of VPI is a cleft palate, which affects around 1 in 1650 babies, around ⅓ of whom have persistent speech problems after surgery. Current equipment-based assessment methods are invasive and require expert knowledge, and perceptual assessment methods are limited by the availability of expert listeners and differing interpretations of assessment scales. Spectral analysis of hypernasality within the academic community has resulted in potentially useful spectral indicators, but these are highly variable, vowel specific, and not commonly used within clinical practice.Previous works by others have developed noise excitation technologies for the measurement of oral tract transfer functions using resonance measurement devices (RMD). These techniques provide an opportunity to investigate the structural system abnormalities which lead to hypernasality, without the need for invasive measurement equipment. Thus, the work presented in this study adapts these techniques for the detection of hypernasality. These adaptations include augmentation of the hardware and development of the software, so as to be suitable for transfer function measurement at the nostrils rather than the mouth (nRMD). The new method was tested with a single participant trained in hypernasal production, producing ‘normal’ and hypernasal vowels, and the recordings validated through a listening test by an expert listener and calculation of nasalance values using a nasality microphone. These validation stages indicated the reliability of the captured data, and analysis of the nRMD measurements indicated the presence of a systematic difference in the frequency range 2 to 2.5 kHz between normal and hypernasal speech. Further investigation is warranted to determine the generalisability of these findings across speakers, and to investigate the origins of differences manifesting in the transfer functions between conditions. This will provide new insights into the effects of nasal tract coupling on voice acoustics, which could in turn lead to the development of useful new tools to support clinicians in their work with hypernasality.

Risk assessment for gas transmission station based on cloud model based multilevel Bayesian network from the perspective of multi-flow intersecting theory

Accidents occurred in the natural gas transmission stations may result in casualties, equipment damage, property loss and even political and ecological impact. It is necessary to propose an approach for the gas transmission stations risk assessment so as to identify risk factors and prevent accidents. However, insufficient attention has been paid to the complex interactions and coupling patterns of these factors with current risk assessment methods. Hence, a novel risk analysis strategy is needed for industrial site risk assessment. Given industrial site risk factors, the multi-flow intersecting theory (MIT) is first defined to consider material, information and behavior risk analysis. Then the multilevel Bayesian network is constructed to represent these factors from different flows. To handle issues of insufficient statistical data and subjectivity associated with expert judgement, cloud model and fuzzy Bayesian are incorporated. For the defuzzification, existing cloud model is improved by introducing the similarity degree of standard cloud and evaluation cloud. Then the prior and conditional probabilities obtained from cloud model are input into Bayesian network for further reasoning and accident probability prediction. To validate the utility of the proposed method, the gas transmission startup process was chosen for risk assessment.

The Digitalization of Learning Assessment

Assessment is recognized as significant in the world of education. The field of assessment is seen as one of the most difficult areas to reform due to the various challenges faced by teachers and students during the process of learning. Changes to digital technology in teaching and learning activities have influenced the assessment process in all educational institutions. Current assessment method that is mainly summative is often described as outdated compared to the development of the current world of education which focuses on outcome-based education (OBE). In general, the development of digital technology has changed the implementation of teaching and learning activities which also involves learning assessment. New technologies and tools have long been seen as a new possibility for assessment due to their features or capabilities that are potentially beneficial as they offer a more holistic, immediate and engaging assessment experience. Nevertheless, past studies have concluded that the use of digital technology is not yet ‘transformative’ due to its limited innovation and because its use is still linked to traditional assessment methods. In general, this paper will address the digital technology in teaching practice and the assessment of learning. Keywords: Digitalization, Learning, Assessment, Formative, Summative