Refinement and Validation of the Minimal Information Data-Modelling (MID) Method for Bridge Management.

Various approaches have been proposed for bridge structural health monitoring. One of the earliest approaches proposed was tracking a bridge's natural frequency over time to look for abnormal shifts in frequency that might indicate a change in stiffness. However, bridge frequencies change naturally as the structure's temperature changes. Data models can be used to overcome this problem by predicting normal changes to a structure's natural frequency and comparing it to the historical normal behaviour of the bridge and, therefore, identifying abnormal behaviour. Most of the proposed data modelling work has been from long-span bridges where you generally have large datasets to work with. A more limited body of research has been conducted where there is a sparse amount of data, but even this has only been demonstrated on single bridges. Therefore, the novelty of this work is that it expands on previous work using sparse instrumentation across a network of bridges. The data collected from four in-operation bridges were used to validate data models and test the capabilities of the data models across a range of bridge types/sizes. The MID approach was found to be able to detect an average frequency shift of 0.021 Hz across all of the data models. The significance of this demonstration across different bridge types is the practical utility of these data models to be used across entire bridge networks, enabling accurate and informed decision making in bridge maintenance and management.

Erector spinae plane blocks for opioid-sparing multimodal pain management after pediatric cardiac surgery.

OBJECTIVE: Peripheral regional anesthesia is proposed to enhance recovery. We sought to evaluate the efficacy of bilateral continuous erector spinae plane blocks (B-ESpB) for postoperative analgesia and the impact on recovery in children undergoing cardiac surgery. METHODS: Patients aged 2 through 17 years undergoing cardiac surgery in the enhanced recovery after cardiac surgery program were prospectively enrolled to receive B-ESpB at the end of the procedure, with continuous infusions via catheters postoperatively. Participants wore an activity monitor until discharge. B-ESpB patients were retrospectively matched with control patients in the enhanced recovery after cardiac surgery program. Outcomes of the matched clusters were compared using exact conditional logistic regression and generalized linear modeling. RESULTS: Forty patients receiving B-ESpB were matched to 78 controls. There were no major complications from the B-ESpB or infusions, and operating room time was longer by a median of 31 minutes. While blocks were infusing, patients with B-ESpB received fewer opioids in oral morphine equivalents than controls at 24 hours (0.60 ± 0.06 vs 0.78 ± 0.04 mg/kg; P = .02) and 48 hours (1.13 ± 0.08 vs 1.35 ± 0.06 mg/kg; P = .04), respectively. Both groups had low median pain scores per 12-hour period. There was no difference in early mobilization, length of stay, or complications. CONCLUSIONS: B-ESpBs are safe in children undergoing cardiac surgery. When performed as part of a multimodal pain strategy in an enhanced recovery after cardiac surgery program, pediatric patients with B-ESpB experience good pain control and require fewer opioids in the first 48 hours.

Clinical classification of memory and cognitive impairment with multimodal digital biomarkers.

INTRODUCTION: Early detection of Alzheimer's disease and cognitive impairment is critical to improving the healthcare trajectories of aging adults, enabling early intervention and potential prevention of decline. METHODS: To evaluate multi-modal feature sets for assessing memory and cognitive impairment, feature selection and subsequent logistic regressions were used to identify the most salient features in classifying Rey Auditory Verbal Learning Test-determined memory impairment. RESULTS: Multimodal models incorporating graphomotor, memory, and speech and voice features provided the stronger classification performance (area under the curve = 0.83; sensitivity = 0.81, specificity = 0.80). Multimodal models were superior to all other single modality and demographics models. DISCUSSION: The current research contributes to the prevailing multimodal profile of those with cognitive impairment, suggesting that it is associated with slower speech with a particular effect on the duration, frequency, and percentage of pauses compared to normal healthy speech.

Minimal Information Data-Modelling (MID) and an Easily Implementable Low-Cost SHM System for Use on a Short-Span Bridge.

Structural Health Monitoring (SHM) is a technique that involves gathering information to ensure that a structure is safe and behaving as expected. Within SHM, vibration-based monitoring is generally seen as one of the more cost-effective types of monitoring. However, vibration-based monitoring has mostly been undertaken on long-span bridges using data collected with a dense network of sensors. Historically, the logistical difficulty of collecting data on short- and medium-span bridges has meant that the usefulness of vibration-based methods on these bridges is largely unknown. Therefore, this study proposes Minimal Information Data-modelling (MID). MID is an approach that utilises low-cost, easily implementable sensors that are potentially feasible for operators to purchase and operate across a network. This approach will be investigated to determine whether MID is a feasible approach for monitoring short- and medium- span bridges. The results from MID were assessed to determine whether they could detect a suitably small shift in frequency, which is indicative of damage. It was determined that the data models could reliably detect frequency shifts as low as 0.01 Hz. This magnitude of frequency shift is similar to the level of frequency shift reported for a range of bridge damage cases found by others and validated with FE models. The accuracy achieved by the data models indicates that MID could potentially be used as a damage detection method. The cost of the equipment used to collect the data was approximately £370, demonstrating that it is feasible to use MID to monitor bridges across an entire network.

Quantifying the Contribution of Habitats and Pathways to a Spatially Structured Population Facing Environmental Change.

The consequences of environmental disturbance and management are difficult to quantify for spatially structured populations because changes in one location carry through to other areas as a result of species movement. We develop a metric, G, for measuring the contribution of a habitat or pathway to network-wide population growth rate in the face of environmental change. This metric is different from other contribution metrics, as it quantifies effects of modifying vital rates for habitats and pathways in perturbation experiments. Perturbation treatments may range from small degradation or enhancement to complete habitat or pathway removal. We demonstrate the metric using a simple metapopulation example and a case study of eastern monarch butterflies. For the monarch case study, the magnitude of environmental change influences the ordering of node contribution. We find that habitats within which all individuals reside during one season are the most important to short-term network growth under complete removal scenarios, whereas the central breeding region contributes most to population growth over all but the strongest disturbances. The metric G provides for more efficient management interventions that proactively mitigate impacts of expected disturbances to spatially structured populations.

Electrocolonography: Non-Invasive Detection of Colonic Cyclic Motor Activity From Multielectrode Body Surface Recordings.

OBJECTIVE: This work validates a novel non-invasive method to identify periods of cyclic motor activity in the colon using multichannel skin-surface electrical recordings on the lower abdominal region, termed electrocolonography (EColG). METHODS: EColG recordings were made from 21 human subjects during a 3 hr meal-response study. A signal processing pipeline based on Continuous Wavelet Transform time-frequency analysis was used to quantify the spectral power in the colonic frequency band ( ≈ 2-6 cycles per minute; cpm) during the fasted and fed states. RESULTS: EColG identified a substantial 7.4 ± 3.5× maximum transient increase in motor activity in the fed state versus the fasted state, as well as a 38.3 ± 16.7% sustained spectral power increase in the colonic frequency band. The dominant frequency was 3.61 ± 0.49 cpm, with activity localized primarily in the infraumbilical region near the (recto-)sigmoid colon segments. CONCLUSION: The colonic meal-responses identified with EColG were closely concordant with rectosigmoid motor activity previously characterized by intracolonic high-resolution manometry. This study is the first to demonstrate that body surface electrical recordings can properly identify rhythmic colonic activity stimulated by food intake. SIGNIFICANCE: The new EColG technique is inexpensive, portable, and presents the opportunity for reliably measuring colonic motility by noninvasive means. We anticipate that EColG could be applied to monitor the progression of post-operative ileus, and more precisely diagnose abnormal colonic motor patterns in patients suffering from common functional disorders, such as irritable bowel syndrome.