Iterative hierarchical clustering algorithm for automated operational modal analysis

Recent developments in sensors and data processing made the structural health monitoring (SHM) sector expanding to big-data field, particularly when continuous long-term strategies are implemented. Nevertheless, main shortcomings are due to the identification and extraction of modal features. In fact, although machine learning methods have been implemented to automate modal identification processes, intense user interaction and time-consuming procedures are still required, limiting the extensive use of these techniques. In order to provide a fully automated procedure capable of identifying and extracting modal properties from covariance driven SSI analyses, an innovative and flexible algorithm for Iterative Hierarchical Clustering Analysis (IHCA) is proposed. To evaluate the stability and robustness of the IHCA method, a Variance-Based Global sensitivity Analysis (VBGA) was performed considering a numerical and experimental case study. The outcomes demonstrated that the IHCA is stable in clustering the physical structural modes and selecting the most representative modal features

On the use of mode shape curvatures for damage localization under varying environmental conditions

A novel damage localization method is introduced in this study, which exploits mode shape curvatures as damage features, while accounting for operational variability. The developed framework operates in an output-only regime,that is, it does not assume availability of records from the influencing environmental/operational quantities but rather from response quantities alone. The introduced tool comprises 3 stages pertaining to training, validation, and diagnostics. During the training stage, a representation of the healthy, or baseline, structural state is acquired over varying operational conditions. A data matrix is formulated, whose individual columns correspond to mode shape curvatures at distinct operational conditions, and principal component analysis (PCA) is applied for extraction of the imprints of separate operational sources on these curvatures. To this end, a residual matrix between the original and the PCA mapped data is formed serving for statistical characterization of each mode. Subsequently, during the validation and diagnostics stages, the mode shape curvature matrices for the currently inspected structural state are assembled and the same PCA mapping is enforced. A typical hypothesis test and a corresponding damage index are then adopted in order to firstly detect damage, and to secondly localize damage, should this exist. The implementation of the proposed method in 2 numerical case studies confirms its effectiveness and the encouraging results suggest further investigation on operating structural systems. ISSN:1545-2255 ISSN:1545-226

Automatic Extraction of Dermatological Parameters from Nevi Using an Inexpensive Smartphone Microscope: A Proof of Concept

The evolution of smartphone technology has made their use more common in dermatological applications. Here we studied the feasibility of using an inexpensive smartphone microscope for the extraction of dermatological parameters and compared the results obtained with a portable dermoscope, commonly used in clinical practice. Forty-two skin lesions were imaged with both devices and visually analyzed by an expert dermatologist. The presence of a reticular pattern was observed in 22 dermoscopic images, but only in 10 smartphone images. The proposed paradigm segments the image and extracts texture features which are used to train and validate a neural network to classify the presence of a reticular pattern. Using 5-fold cross-validation, an accuracy of 100% and 95% was obtained with the dermoscopic and smartphone images, respectively. This approach can be useful for general practitioners and as a triage tool for skin lesion analysis

New insight into the identity of italian grapevine varieties: The case study of calabrian germplasm

Calabria is a region located in Southern Italy and it is characterized by a long tradition of viticulture practices and favorable pedoclimatic conditions for grapevine cultivation. Nevertheless, less than 2% of cultivated land is dedicated to grapevine growing in Calabria. The characterization of local grapevine accessions is crucial to valorize the local and peculiar Italian products and boost the Calabrian winemaking sector. With this purpose, we performed a deep characterization of two widespread Calabrian grapevine varieties—Magliocco Dolce and Brettio Nero, of which very little is known. In particular, a genetic and morphological analysis, a berry physico-chemical and polyphenolic compositions assessment, and oenological evaluation of monovarietal wines were carried out. Our results allowed us to demonstrate that Magliocco Dolce and Brettio Nero are unique and distinct varieties with peculiar morphological and chemical characteristics and show the suitability of these two varieties in high-quality wine production. Moreover, the obtained molecular profiles will be useful for authentication and traceability purposes

Cardiovascular magnetic resonance of the charcoal heart

We report a case of malignant melanoma metastasis to the heart presenting as complete heart block. The highlight of the case is to demonstrate that silent cardiac metastasis is not uncommon and CMR has the potential to characterize these cardiac metastases and should be used routinely as a screening tool for those cancers with a high chance of cardiac involvement

Cognitive performance and normative data between Hispanic and non-Hispanic cohorts: Results from the South Texas Alzheimer’s Disease Research Center (ADRC)

Background: The prevalence of Alzheimer\u27s disease and related dementias (ADRD) in the United States was estimated as 6.5 million people in 2022, with a five-fold increase for the Hispanic/Latinx population expected by 2060. The South Texas Alzheimer\u27s Disease Center (STAC) was designated as a new ADRC in 2021 by the National Institute on Aging (NIA) with a specific aim to serve the growing needs of the local underrepresented Hispanic population. As cultural and linguistic factors can impact performance on cognitive tests, the goal of the study was to compare UDS-3 cognitive test raw scores and normative data in Hispanic and non-Hispanic adults without cognitive impairment residing in South Texas. Method: Participants from the STAC cohort completed the Uniform Data Set (UDS), V.3.0, which includes demographics and neuropsychological battery. All batteries were administered in the participants’ preferred language, English. Normative data was calculated using Weintraub et al. (2018)’s age, sex, and education adjusted regression models for UDSNB 3.0. Mean differences between baseline visit raw scores and normative data were compared using independent sample t-tests among Hispanic and non-Hispanic participants. Result: Thirty-four Hispanic (mean age=70.4, 67.6% female) and thirty-eight non-Hispanic (mean age=71.9, 57.9% female) participants were included. Hispanic participants had fewer years of education relative to non-Hispanic participants [M(SD)] = [14.7(2.5)] to [16.5(2.5)], respectively; (t(70.1)=3.0, p =0.004); although, the groups did not differ in age or sex distribution (p\u3e0.05). Hispanic and non-Hispanic participants generally performed equivalently on the neuropsychological battery. However, Hispanics had lower mean raw scores on the Montreal Cognitive Assessment (MoCA) (t(70.8)= 3.6, p Conclusion: Overall, Hispanic and non-Hispanic participants performed similarly on the UDS-3 neuropsychological battery. However, Hispanics had lower mean raw and normative scores on the MINT, as well as the MoCA which also includes language measures. Our findings highlight the importance of future research validating the sensitivity and specificity of normative data used in underrepresented populations, especially those at higher risk for ADRD

The validity of an updated metabolic power algorithm based upon Di Prampero’s theoretical model in Elite soccer players

The aim of this study was to update the metabolic power (MP) algorithm (P.VO2, W·kg−1) related to the kinematics data (PGPS, W·kg−1) in a soccer-specific performance model. For this aim, seventeen professional (Serie A) male soccer players (.VO2max 55.7 ± 3.4 mL·min−1·kg−1) performed a 6 min run at 10.29 km·h−1 to determine linear-running energy cost (Cr). On a separate day, thirteen also performed an 8 min soccer-specific intermittent exercise protocol. For both procedures, a portable Cosmed K4b2 gas-analyzer and GPS (10 Hz) was used to assess the energy cost above resting (C). From this aim, the MP was estimated through a newly derived C equation (PGPSn) and compared with both the commonly used (PGPSo) equation and direct measurement (P.VO2). Both PGPSn and PGPSo correlated with P.VO2 (r = 0.66, p < 0.05). Estimates of fixed bias were negligible (PGPSn = −0.80 W·kg−1 and PGPSo = −1.59 W·kg−1), and the bounds of the 95% CIs show that they were not statistically significant from 0. Proportional bias estimates were negligible (absolute differences from one being 0.03 W·kg−1 for PGPSn and 0.01 W·kg−1 for PGPSo) and not statistically significant as both 95% CIs span 1. All variables were distributed around the line of unity and resulted in an under-or overestimation of PGPSn, while PGPSo routinely underestimated MP across ranges. Repeated-measures ANOVA showed differences over MP conditions (F1,38 = 16.929 and p < 0.001). Following Bonferroni post hoc test significant differences regarding the MP between PGPSo and P.VO2 /PGPSn (p < 0.001) were established, while no differences were found between P.VO2 and PGPSn (p = 0.853). The new approach showed it can help the coaches and the soccer trainers to better monitor external training load during the training seasons.© 2020 by the authors. Licensee MDPI, Basel, Switzerland

Increased circulating ANG II and TNF-α represents important risk factors in obese Saudi adults with hypertension irrespective of diabetic status and BMI

Central adiposity is a significant determinant of obesity-related hypertension risk, which may arise due to the pathogenic inflammatory nature of the abdominal fat depot. However, the influence of pro-inflammatory adipokines on blood pressure in the obese hypertensive phenotype has not been well established in Saudi subjects. As such, our study investigated whether inflammatory factors may represent useful biomarkers to delineate hypertension risk in a Saudi cohort with and without hypertension and/or diabetes mellitus type 2 (DMT2). Subjects were subdivided into four groups: healthy lean controls (age: 47.9±5.1 yr; BMI: 22.9±2.1 Kg/m2), non-hypertensive obese (age: 46.1±5.0 yr; BMI: 33.7±4.2 Kg/m2), hypertensive obese (age: 48.6±6.1 yr; BMI: 36.5±7.7 Kg/m2) and hypertensive obese with DMT2 (age: 50.8±6.0 yr; BMI: 35.3±6.7 Kg/m2). Anthropometric data were collected from all subjects and fasting blood samples were utilized for biochemical analysis. Serum angiotensin II (ANG II) levels were elevated in hypertensive obese (p<0.05) and hypertensive obese with DMT2 (p<0.001) compared with normotensive controls. Systolic blood pressure was positively associated with BMI (p<0.001), glucose (p<0.001), insulin (p<0.05), HOMA-IR (p<0.001), leptin (p<0.01), TNF-α (p<0.001) and ANG II (p<0.05). Associations between ANG II and TNF-α with systolic blood pressure remained significant after controlling for BMI. Additionally CRP (p<0.05), leptin (p<0.001) and leptin/adiponectin ratio (p<0.001) were also significantly associated with the hypertension phenotype. In conclusion our data suggests that circulating pro-inflammatory adipokines, particularly ANG II and, TNF-α, represent important factors associated with a hypertension phenotype and may directly contribute to predicting and exacerbating hypertension risk

Emergency management in health: key issues and challenges in the UK

Background Emergency planning in the UK has grown considerably in recent years, galvanised by the threat of terrorism. However, deficiencies in NHS emergency planning were identified and the evidence-base that underpins it is questionable. Inconsistencies in terminologies and concepts also exist. Different models of emergency management exist internationally but the optimal system is unknown. This study examines the evidence-base and evidence requirements for emergency planning in the UK health context. Methods The study involved semi-structured interviews with key stakeholders and opinion leaders. Purposive sampling was used to obtain a breadth of views from various agencies involved in emergency planning and response. Interviews were then analysed using a grounded approach using standard framework analysis techniques. Results We conducted 17 key informant interviews. Interviewees identified greater gaps in operational than technical aspects of emergency planning. Social and behavioural knowledge gaps were highlighted with regards to how individuals and organisations deal with risk and behave in emergencies. Evidence-based approaches to public engagement and for developing community resilience to disasters are lacking. Other gaps included how knowledge was developed and used. Conflicting views with regards to the optimal configuration and operation of the emergency management system were voiced. Conclusions Four thematic categories for future research emerged: (i) Knowledge-base for emergency management: Further exploration is needed of how knowledge is acquired, valued, disseminated, adopted and retained. (ii) Social and behavioural issues: Greater understanding of how individuals approach risk and behave in emergencies is required. (iii) Organisational issues in emergencies: Several conflicting organisational issues were identified; value of planning versus plans, flexible versus standardized procedures, top-down versus bottom-up engagement, generic versus specific planning, and reactive versus proactive approaches to emergencies. (iv) Emergency management system: More study is required of system-wide issues relating to system configuration and operation, public engagement, and how emergency planning is assessed