Cumulative Measure Research Articles

Mitigating investment risk using modular technologies

We study logistical investment flexibility provided by modular processing technologies for mitigating risk. Specifically, we propose a multi-stage stochastic programming formulation that determines optimal capacity expansion plans that mitigate demand uncertainty. The formulation accounts for multi-product dependencies between small/large units and for trade-offs between expected profit and risk. The formulation uses a cumulative risk measure to avoid time-consistency issues of traditional, per-stage risk-minimization formulations, and we argue that this approach is more compatible with typical investment metrics such as the net present value. Case studies of different complexity are presented to illustrate the developments. Our studies reveal that the Pareto frontier of a flexible setting (allowing for deployment of small units) dominates the Pareto frontier of an inflexible setting (allowing only for deployment of large units). Notably, this dominance is prevalent despite benefits arising from economies of scale of large processing units.

Genetic risk for bipolar disorder and schizophrenia predicts structure and function of the ventromedial prefrontal cortex.

Background:Bipolar disorder is highly heritable and polygenic. The polygenic risk for bipolar disorder overlaps with that of schizophrenia, and polygenic scores are normally distributed in the population. Bipolar disorder has been associated with structural brain abnormalities, but it is unknown how these are linked to genetic risk factors for psychotic disorders.Methods:We tested whether polygenic risk scores for bipolar disorder and schizophrenia predict structural brain alterations in 98 patients with bipolar disorder and 81 healthy controls. We derived brain cortical thickness, surface area and volume from structural MRI scans. In post-hoc analyses, we correlated polygenic risk with functional hub strength, derived from resting-state functional MRI and brain connectomics.Results:Higher polygenic risk scores for both bipolar disorder and schizophrenia were associated with a thinner ventromedial prefrontal cortex (vmPFC). We found these associations in the combined group, and separately in patients and drug-naive controls. Polygenic risk for bipolar disorder was correlated with the functional hub strength of the vmPFC within the default mode network.Limitations:Polygenic risk is a cumulative measure of genomic burden. Detailed genetic mechanisms underlying brain alterations and their cognitive consequences still need to be determined.Conclusion:Our multimodal neuroimaging study linked genomic burden and brain endophenotype by demonstrating an association between polygenic risk scores for bipolar disorder and schizophrenia and the structure and function of the vmPFC. Our findings suggest that genetic factors might confer risk for psychotic disorders by influencing the integrity of the vmPFC, a brain region involved in self-referential processes and emotional regulation. Our study may also provide an imaging–genetics vulnerability marker that can be used to help identify individuals at risk for developing bipolar disorder.

Integrated assessment of major and trace elements in surface and core sediments from an urban lagoon, China: Potential ecological risks and influencing factors

Marine sediments serve as a sink for contaminants of anthropogenic origin. Here, 25 major and trace elements were determined in surface and core sediments from an urban lagoon (Yundang Lagoon), China. The median concentrations of Pb, Cd, Cu, and Zn in both surface and core sediments exceeded global and crustal averages. Principal component analysis for the elements and ecological impact of the heavy metals indicated spatial heterogeneity in core sediments from different lagoon areas; however, no such pattern was observed in surface sediments. Geodetector analysis indicated spatial locations of lakes, pH, N%, C%, and S% as the major factors influencing the heterogeneity of potential ecological risk index, a cumulative measure of the ecological impact of heavy metal. The interaction detector indicated nonlinear and bivariate enhancement between different physicochemical parameters. Besides, a depth profile of the elements in different samples was also elucidated.

Evaluation of Head Injury Criteria for Injury Prediction Effectiveness: Computational Reconstruction of Real-World Vulnerable Road User Impact Accidents.

This study evaluates the effectiveness of various widely used head injury criteria (HICs) in predicting vulnerable road user (VRU) head injuries due to road traffic accidents. Thirty-one real-world car-to-VRU impact accident cases with detailed head injury records were collected and replicated through the computational biomechanics method; head injuries observed in the analyzed accidents were reconstructed by using a finite element (FE)-multibody (MB) coupled pedestrian model [including the Total Human Model for Safety (THUMS) head–neck FE model and the remaining body segments of TNO MB pedestrian model], which was developed and validated in our previous study. Various typical HICs were used to predict head injuries in all accident cases. Pearson’s correlation coefficient analysis method was adopted to investigate the correlation between head kinematics-based injury criteria and the actual head injury of VRU; the effectiveness of brain deformation-based injury criteria in predicting typical brain injuries [such as diffuse axonal injury diffuse axonal injury (DAI) and contusion] was assessed by using head injury risk curves reported in the literature. Results showed that for head kinematics-based injury criteria, the most widely used HICs and head impact power (HIP) can accurately and effectively predict head injury, whereas for brain deformation-based injury criteria, the maximum principal strain (MPS) behaves better than cumulative strain damage measure (CSDM0.15 and CSDM0.25) in predicting the possibility of DAI. In comparison with the dilatation damage measure (DDM), MPS seems to better predict the risk of brain contusion.

Racial and Economic Adversity Differences in Stress Markers and Immune Function Among Urban Adolescents.

Exposure to racism and associated adversities, such as poverty, is hypothesized to contribute to racial inequities in health via stress and immune pathways. Furthermore, the effects of adversity may be more salient during sensitive developmental periods. Our study examined racial differences in stress and immune biomarkers during adolescence and the effects of exposure to economic adversity at distinct developmental time periods and cumulatively in accounting for potential racial differences. Secondary analysis of the Adolescent Health and Development in Context study was conducted. Data were derived from self-administered surveys; interviews; smartphone-based, geographic-explicit ecological momentary assessment; stress biomarkers (evening salivary cortisol over six nights and hair cortisol); and immune biomarkers (salivary shedding of Epstein-Barr virus [EBV] DNA among EBV-positive adolescents). Current socioeconomic status measures included annual household income and caregiver education. Caregivers also reported experiences of bankruptcy, difficulty paying bills, receipt of food stamps/Supplemental Nutrition Assistance Program/electronic benefit transfer, and job loss when the child was of ages birth-5 years, 6-10 years, and 11 years or older. An affirmative response to any item was defined as exposure to economic adversity for that developmental time period (yes/no). A cumulative economic adversity measure was calculated as the sum of exposures across developmental periods (0 = never exposed to 3 = exposed across all time periods). Descriptive and multivariable regression analyses were conducted, accounting for covariates. Black/African American adolescents had higher salivary cortisol concentration, higher hair cortisol concentration, and an increased odd of salivary shedding of EBV DNA compared to White adolescents. Racial differences were not attenuated by the current socioeconomic status or economic adversity (developmental period or cumulatively). Our study provides evidence that stress and immune biomarkers differ by race as early as adolescence and may be one pathway through which racism and associated adversities contribute to racial health inequities. Further research on the contribution of multiple adversities beyond poverty to racial inequities in physiological stress and health is critical for informing effective prevention and intervention efforts.

The Head AIS 4+ Injury Thresholds for the Elderly Vulnerable Road User Based on Detailed Accident Reconstructions.

Compared with the young, the elderly (age greater than or equal to 60 years old) vulnerable road users (VRUs) face a greater risk of injury or death in a traffic accident. A contributing vulnerability is the aging processes that affect their brain structure. The purpose of this study was to investigate the injury mechanisms and establish head AIS 4+ injury tolerances for the elderly VRUs based on various head injury criteria. A total of 30 elderly VRUs accidents with detailed injury records and video information were selected and the VRUs’ kinematics and head injuries were reconstructed by combining a multi-body system model (PC-Crash and MADYMO) and the THUMS (Ver. 4.0.2) FE models. Four head kinematic-based injury predictors (linear acceleration, angular velocity, angular acceleration, and head injury criteria) and three brain tissue injury criteria (coup pressure, maximum principal strain, and cumulative strain damage measure) were studied. The correlation between injury predictors and injury risk was developed using logistical regression models for each criterion. The results show that the calculated thresholds for head injury for the kinematic criteria were lower than those reported in previous literature studies. For the brain tissue level criteria, the thresholds calculated in this study were generally similar to those of previous studies except for the coup pressure. The models had higher (>0.8) area under curve values for receiver operator characteristics, indicating good predictive power. This study could provide additional support for understanding brain injury thresholds in elderly people.

Change of physical activity parameters of hip and pelvic fracture patients during inpatient rehabilitation and after discharge: analysis of global and in-depth parameters

BackgroundA growing number of older adults suffer hip and pelvic fractures leading to hospital admission. They often result in reduced physical activity (PA) and impaired mobility. PA can be objectively measured with body-worn sensors. Usually, global cumulative PA parameters are analysed, such as walking duration, upright-time and number of steps. These traditional parameters mix different domains of PA, such as physical capacity (PC), behaviour and living environment. We examined the change of global cumulative PA measures during rehabilitation and after discharge in patients with hip or pelvic fracture and whether more ‘in-depth’ PA parameters, such as walking interval length, variability of interval length and sit-to-stand transitions and their changes during rehabilitation and 3 months after discharge might better reflect the above mentioned three clinically relevant domains of PA.MethodsThis study is a secondary data analysis of a randomised controlled trial to improve PA and fall-related self-efficacy in hip or pelvic fracture patients (≥60 years) with concerns about falling. Changes of accelerometer-measured global cumulative and in-depth PA parameters (activPAL3) were analysed in an observational design before and after discharge combining both groups. For comparison, the same analyses were applied to the traditional PC measures gait speed and 5-chair-rise.ResultsSeventy-five percent of the 111 study participants were female (mean age: 82.5 (SD = 6.76) years. Daily walking duration, upright time and number of steps as aspects of global PA increased during inpatient rehabilitation as well as afterwards. The in-depth PA parameters showed differing patterns. While the total number of walking bouts increased similarly, the number of longer walking bouts decreased by 50% after discharge. This pattern was also seen for the average walking interval length, which increased by 2.34 s (95% confidence interval (CI): 0.68; 4.00) during inpatient rehabilitation and decreased afterwards below baseline level (− 4.19 s (95% CI: − 5.56; − 2.82)). The traditional PC measures showed similar patterns to the in-depth PA parameters with improvements during rehabilitation, but not at home.ConclusionOur findings suggest that the in-depth PA parameters add further information to the global cumulative PA parameters. Whereas global cumulative PA parameters improved significantly during inpatient rehabilitation and after discharge, in-depth PA parameters as well as PC did not continuously improve at home. In contrast to global cumulative PA parameters the in-depth parameters seem to reflect contextual factors such as the build environment and aspects of PC, which are traditionally assessed by clinical PC measures. These in combination with digital mobility measures can help clinicians to assess the health status of fragility fracture patients, individually tailor therapy measures and monitor the rehabilitation process.

Measuring Natural Hazard-Related Disasters through Self-Reports

Exposure to multiple natural hazard-related disasters will become more common due to climate change. This article reports on the development and validation of a cumulative measure of exposure to natural hazard-related disasters (2013–2017) at the area level, and an individual-level measure of disaster impact using data from the Longitudinal Cohort Study on the Filipino Child and linked data from the International Disaster Database (EM-DAT). Caregiver reports of cumulative exposure to disasters had statistically significant associations with disasters reported by neighborhood officials and with disasters in EM-DAT. Using ecometric techniques we generated a reliable community average measure of exposure to natural hazard-related disasters. Based on neighbor but not individual self-reports this exogenous measure of disaster exposure in the local area was more strongly related to EM-DAT and official neighborhood reports than individual reports. To capture household variation we developed an individual-level measure of disaster impacts. Disaster impact was associated with measures of exposure (individual and community average), community ratings by officials, and EM-DAT but only moderately associated with the community average exposure. Both the community average and disaster impacts measures were associated with household income and the adequacy of income in households.

Mild blast wave exposure produces intensity-dependent changes in MMP2 expression patches in rat brains – Findings from different blast severities

Matrix metalloproteinase 2 (MMP2) is a gelatinase with multiple functions at the neurovascular interface, including local modification of the glia limitans to facilitate access of immune cells into the brain and amyloid-beta degradation during responses to injury or disease. This study examines regional changes in immunoreactive MMP2 in the rat brain after a single mild (2.7–7.9 psi peak) or moderate (13–17.5 psi peak) blast overpressure (BOP) exposure. Immunopositive MMP2 expression was examined quantitatively in histological sections of decalcified rat heads as a marker at 2, 24, and 72 h after BOP. The MMP2 immunoreactivity was isolated to patchy deposits in brain parenchyma surrounding blood vessels. Separate analyses were conducted for the cerebellum, brain stem caudal to the thalamo-mesencephalic junction, and the cerebrum (including diencephalon). The deposits varied in number, size, staining homogeneity (standard deviation of immunopositive region), and a cumulative measure, the product of size, average intensity and number, as a function of blast intensity and time. The sequences of changes in MMP2 spots from sham control animals suggested that the mild BOP exposure differences normalized within 72 h. However, the responses to moderate exposure revealed a delayed response at 72 h in the subtentorial brain stem and the cerebrum, but not the cerebellum. Hence, local MMP2 responses may be a contextual biomarker for locally regulated responses to widely distributed brain injury foci.

Abstract P069: White Cell Gene Expression Related To Immune Function And Cumulative Blood Pressure During Young Adulthood And Middle Age: Coronary Artery Risk Development In Young Adults (CARDIA)

Introduction: High blood pressure (BP) is a global public health problem that is strongly associated with many aspects of cardiovascular disease. Approximately 90% of hypertension cases have unknown cause. Studies of white blood cell gene expression may help to clarify the pathobiology. Methods: Gene expression (25 genes) was assayed in CARDIA at the Year 25 Exam (N=3,074 black and white men and women in 4 US cities, examined in 2010-2011, age 42-56 years). Whole blood was collected in PAXgene Blood RNA tubes; mRNA was isolated using the PAXgene Blood RNA kit (Qiagen Inc., Germantown, MD). The nCounter analysis system (Nanostring Inc., Seattle, WA) was used to measure expression of 25 genes related to inflammation and oxidative stress. Gene expression levels were logarithmically (base 2) transformed to approximate a normal distribution, so 1 unit higher represents doubling of the expression. Average cumulative sitting rest BP exposure was calculated (N=2,823) as the time weighted average across ≥5 BP measurements among 9 CARDIA exams with ≥1 measurement in each of Set 1 Years 0, 2, 5, 7; Set 2 Years 10, 15; and Set 3 Years 20, 25, 30. We added 10 mmHg to the systolic BP and 5 mmHg to the diastolic BP at visits in which antihypertensive medications were used. Linear regression estimated associations between dependent variables cumulative systolic and diastolic BP and each of the 25 gene expression levels, adjusting for age, race, sex, clinic, and year 25 body mass index. Hypertension at year 25 was defined as BP >140/90 mmHg or taking antihypertensive medications and pre-hypertension at year 25 was defined as BP between 121-139/81-90 mmHg, not taking antihypertensive medications. Unconditional logistic regression models were used to estimate the cross sectional association between hypertension and gene expression after adjusting for the covariates mentioned above. Results: The mean ± standard deviation for cumulative systolic BP was 113±11 mm Hg and for cumulative diastolic BP was 72±8 mmHg. NADH Dehydrogenase [Ubiquinone] 1 Beta Subcomplex Subunit 3 ( NDUFB3) , a mitochondrial gene involved in the electron transport chain was significantly associated with both cumulative systolic (β=1.549; p<0.0001) and diastolic BP measures (β=1.281 mmHg/1 log 2 unit of expression; p<0.0001), even after Bonferroni correction. Other genes had weaker signals. Consistent with these observations, hypertension (n=898) at year 25 (OR: 1.737; p<0.001) and pre-hypertension (n=1,127) at year 25 (OR:1.288; p=0.005) were also associated with increased NDUFB3 expression. Conclusions: Expression of the NDUFB3 gene, an element of oxidative stress, was associated with BP assessed throughout young adult and middle age and with concurrent hypertension.

Abstract P218: The Association Of Mid-life Cumulative Exposure To Systolic Blood Pressure, Myocardial Oxygen Demand, And Hypertension With Later-life Central Arterial Stiffness And Its 5-year Change: The Atherosclerosis Risk In Communities Study - Neurocognitive Study (ARIC-NCS)

Background: Greater central artery stiffness predicts cardiovascular disease and all-cause mortality, thus understanding arterial stiffness determinants has prevention implications. Reports of the temporal association of blood pressure with arterial stiffness are conflicting and the association with myocardial oxygen demand has not been evaluated. Objective: Characterize the association of mid- to later-life cumulative exposure to systolic blood pressure (SBP), myocardial oxygen demand, and hypertension (HTN) with arterial stiffness and its 5-year change in older adults. Methods: We included 1,975 adults (1151 women; 359 Black; visit 5 mean age 74 years) examined in visits 5 (2011-13) and 6 or 7 (2016-19) of the population-based ARIC-NCS with measures of arterial stiffness (carotid-femoral pulse wave velocity (cfPWV)). Higher cfPWV indicates greater arterial stiffness. We calculated cumulative exposures as the sum of averages from four consecutive visits from 1987-89 to 1996-98 divided by total time. Myocardial oxygen demand was calculated as the rate pressure product (RPP): (SBP x heart rate)/1,000. We derived HTN duration as the time since first HTN detection. Associations of cumulative exposures with visit 5 cfPWV and the 5-year cfPWV change were evaluated by multivariable linear regression adjusted for demographics and cardiometabolic factors. Results: Over the mean 5.7 years between visits 5 and 6 or 7, cfPWV increased by 144.9 cm/s (SD: 276.0; range -680.0, 961.5 cm/s). HTN at any visit, duration, and the time-weighted cumulative measures were associated with higher visit 5 cfPWV (Table). Prevalent HTN was inversely associated with cfPWV change. No statistically significant associations were observed for the other exposures and cfPWV change. Conclusion: Cumulative exposure to SBP, RPP, and HTN are modifiable traits associated with higher cfPWV at later-life, but not with rate of cfPWV change in older adulthood. HTN at visit 5 was associated with lower cfPWV change, albeit the change is of small magnitude.

The influence of natural disasters on violence, mental health, food insecurity, and stunting in the Philippines: Findings from a nationally representative cohort

BackgroundClimate change is leading to an increased number of natural disasters. Children from low- and middle-income countries are disproportionately affected. The impacts of exposure to multiple natural disasters on the development of children are not well understood. The Philippines had 6.5 million people affected by natural disasters in 2018 and is therefore an ideal country in which to study the cumulative effects of natural disasters on human development. MethodsWe used wave 1 (2016–17) of the Longitudinal Cohort Study on the Filipino Child, a nationally representative cohort study of 4952 10-year-old children, to examine the impact of natural disasters. For caregivers, we examined mental health, family violence, and food insecurity. For children, we examined exposure to violence and stunting. We used random effects models to estimate the associations between natural disasters and children's development outcomes and caregivers' outcomes, after adjusting for neighbourhood, demographic, and geographic variables. Disaster exposure was measured using caregiver-reported measures of cumulative exposure and cumulative impact of disasters, average neighbourhood reports and data linked from the International Disaster Database (EM-DAT), an independent measure of community exposure to disaster. FindingsWe found that experiencing natural disasters, as measured by neighbourhood reports, was associated with higher levels of family violence in the previous 12 months, parenting stress, children witnessing physical violence, physical abuse of children, stunting in children, and greater food insecurity. Associations with individual self-reported exposure showed was similar. Associations with natural disasters measured using EM-DAT data showed a similar pattern: exposure to greater numbers of natural disasters was associated with higher levels of family violence, physical abuse of children, stunting in children, and food insecurity. Impacts of disasters was associated with higher levels of family violence, depression and food insecurity. InterpretationThis is the first national study to document that cumulative measures of natural disasters had small, but wide-ranging, impacts on children and their caregivers. Further research is needed to identify factors that will protect populations who are at risk of high levels of natural disasters to ensure the optimal development of children. FundingThe Philippines Project, The Australian National University.

A decision making algorithm for rehabilitation after stroke: A guide to choose an appropriate and safe treadmill training.

Walking independently after a stroke can be difficult or impossible, and walking reeducation is vital. But the approach used is often arbitrary, relying on the devices available and subjective evaluations by the doctor/physiotherapist. Objective decision making tools could be useful. To develop a decision making algorithm able to select for post-stroke patients, based on their motor skills, an appropriate mode of treadmill training (TT), including type of physiotherapist support/supervision required and safety conditions necessary. We retrospectively analyzed data from 97 post-stroke inpatients admitted to a NeuroRehabilitation unit. Patients attended TT with body weight support (BWSTT group) or without support (FreeTT group), depending on clinical judgment. Patients' sociodemographic and clinical characteristics, including the Cumulative Illness Rating Scale (CIRS) plus measures of walking ability (Functional Ambulation Classification [FAC], total Functional Independence Measure [FIM] and Tinetti Performance-Oriented Mobility Assessment [Tinetti]) and fall risk profile (Morse and Stratify) were retrieved from institutional database. No significant differences emerged between the two groups regarding sociodemographic and clinical characteristics. Regarding walking ability, FAC, total FIM and its Motor component and the Tinetti scale differed significantly between groups (for all, p < 0.001). FAC and Tinetti scores were used to elaborate a decision making algorithm classifying patients into 4 risk/safety (RS) classes. As expected, a strong association (Pearson chi-squared, p < 0.0001) was found between RS classes and the initial BWSTT/FreeTT classification. This decision making algorithm provides an objective tool to direct post-stroke patients, on admission to the rehabilitation facility, to the most appropriate form of TT.

Do Technical Barriers to Trade Measures Affect Vietnam’s Tea Exports? Evidence from the Gravity Model

This paper explores how technical barriers to trade (TBT) affect Vietnam’s tea exports to 55 importing countries from 2001 to 2019. We use the gravity model with different estimation methods: ordinary least square (OLS), fixed-effect (FE), and random effect (RE) to estimate the impact of TBT on Vietnam’s tea exports. The results show that although GDP, population, distance, tariff, and participation in World Trade Organization (WTO) are crucial factors, the TBT measures imposed by these importing countries have significantly negative impacts on Vietnam’s tea exports. Our findings reveal that while a 1% increase in the cumulative TBT measures imposed by developing countries decreases Vietnam's tea export by 0.341%, the figure for developed countries is 1.308%.

An ordered approach on cumulative extropy measures for information analysis

The present study focus on the ordered approach of random variables in the analysis of uncertainty using cumulative extropy and its dynamic versions. Some important results regarding bounds, aging properties and orderings of cumulative extropy measures based on order statistics have been discussed. The study also presents characterizations of some probability distribution, identical distribution of random variables and symmetry of a probability distribution using cumulative extropy measures based on extreme order statistics. Further, a simple empirical estimator has been proposed to estimate dynamic failure extropy using a real life data set.

Bayesian‐optimized unsupervised learning approach for structural damage detection

AbstractStructural health monitoring (SHM) is developing rapidly to fulfill the world's need for resilient and sustainable communities. Due to the current advancements in machine learning and data science, data‐driven SHM is an attractive solution for real‐time damage detection compared to the traditional nondestructive evaluation techniques. However, most widely available data‐driven SHM methods rely on fully or partially simulated data to train the statistical model, and thus require a number of predefined assumptions and parameters, or are not adapted for post‐extreme events damage diagnosis. In this study, we propose a density‐based unsupervised learning approach for structural damage detection and localization. This approach leverages cumulative intensity measures for damage‐sensitive feature extraction for the first time in an unsupervised learning approach. Furthermore, a statistical model construction process is proposed based on kernel density maximum entropy (KDME) and Bayesian optimization. The framework is evaluated in three case studies. The first two involve a numerical three‐story building and a numerical nine‐story asymmetrical building that are both subjected to 100 ground motion excitations while considering environmental variations. The proposed framework is able to detect and localize damage in those case studies with an average accuracy of 92%. The third case study, which contains 44 shake‐table tests of a three‐story frame structure with masonry infill, is used to experimentally validate the proposed framework in damage detection. The three case studies demonstrate the potential and robustness of the proposed Bayesian‐optimized, multivariate KDME novelty detection framework for detecting and localizing structural damage, especially after extreme events.

Appetite-Regulating Hormone Ghrelin Predicts Decision-Making in Healthy Controls but Not Individuals With Low-Weight Eating Disorders

Background: Ghrelin is an orexigenic hormone known to regulate appetite, glucose homeostasis, and other food-related functions. The potential role of ghrelin beyond energy homeostasis is not well understood. Ghrelin receptors are evident in the mesolimbic reward pathway, and preclinical research has shown that ghrelin administration increases impulsive behavior and choices in rats. However, little is known about whether and how ghrelin is associated with food-independent behavior and decision-making in humans. We investigated the relationship between ghrelin levels and monetary decision-making using a well-established behavioral paradigm in healthy individuals and individuals with a low-weight eating disorder (LWED), as patients with LWEDs have been shown to have high ghrelin levels and resistance to the effects of this hormone. We hypothesized that higher ghrelin levels would predict more impulsive choices of immediate rewards in healthy individuals, while this relationship would be less pronounced in individuals with LWEDs. Methods: Sixty-four female participants with a LWED and 34 healthy controls (HC), aged 10-22 years, presented after a 10-hour fast to undergo a standardized mixed meal followed by a delay discounting task. During this task, participants decided between smaller immediate and larger delayed monetary rewards. Based on their choices, the delay discounting parameter k was calculated as a marker of choice preferences with higher values indicating a stronger preference for the immediate smaller reward. Blood was drawn prior to and 30, 60, and 120 min after the meal for analysis of ghrelin, and area under the curve was calculated as a cumulative measurement of ghrelin levels. Results: As per study design, BMI was lower in the LWED group (17.3±1.5 kg/m2) compared to the HC group (mean±SD: 21.4±2.5 kg/m2; t[96]=11.33, p<0.0001, d=-1.99). Groups did not differ by age (LWED: 18.3±3.2 years, HC: 18.0±3.1 years; t[96]=-0.36, p=0.720, d=-0.10). Ghrelin levels were higher in the LWED compared to HC group (t[96]=-2.67, p=0.009, d=0.57). K was numerically lower in the LWED compared to the HC group, but the difference was not significant (t[96]=1.37, p=0.175, d=-0.30). Importantly, in HC higher ghrelin levels were associated with higher k values (r=0.37, p=0.032). This relationship was not observed in the LWED group (r=-0.13, p=0.304). Conclusions: In HC, higher levels of ghrelin predicted a stronger preference for smaller immediate rewards, which is consistent with increased impulsive choices shown in animal research. We did not observe this relationship in our LWED sample. Our results indicate that beyond energy homeostasis, ghrelin might play a broader role in reward-related behavior and decision-making, such as monetary choices. Future studies are required to further explore the role of ghrelin in human behavior in both clinical and non-clinical populations.

Genesis of Antibiotic Resistance LXVI: Mechanism(s) of a Minimum Antibiotic Footprint (AF) Wane Prospective Infectious Diseases Pandemic, A critical appraisal with a global perspective

Antibiotic Footprint (AF) is a cumulative measure of the amount of antibiotics consumed by the general population inclusive of healthcare, educational activities, and agrochemical – livestock industries reported by each country. The principal objective of AF is to limit intentional and unintentional misuse/overuse curbing the resistance in bacteria (https://amr-review.org/). Defined Daily Dosage (DDD)/1,000 people/day and milligrams per Population Correction Unit (PCU) are utilized for comparison of consumption rate for specific antibiotics in general population and agricultural - livestock industries. The AF is calculated as the total amount (tones) / country in which the antibiotic usage ‘per person's lifetime’ or ‘per consumer product inclusive of antibiotics’ could be derived. According to the Antibiotic Footprint.net Thailand reported that a personal level as Human consumption 2,162.1 tonnes (32%) and Consumption in animal agriculture (ANIM) as 4,688.4 tonnes (68%). Whereas France reported that Human consumption in the community (Including the primary care sector) (COMM)860.7 tonnes (93%), Human consumption in the hospitals (HOSP) 62.7 tonnes (7%). U.S. reported that consumption in animal agriculture (ANIM) as 5,559.2 tonnes. Also, per person consumption was 99.2 grams/person. Though a detailed ESAC-Net Reporting Protocol 2020 and classes of antimicrobials are presented on ESAC-Net home page, it is our contention that the reporting method is flawed as it failed to factor in the number of unused antibiotics/antimicrobials collected each year which should be part of reporting as presented in our earlier work. As an effective means of instilling personal responsibility in each and every human being across the globe to minimize the AF has been presented by the https://www.antibioticfootprint.net/infobox.aspx?pageID=102 to track each individual's AF. In addition to well know measures such as vaccination for infectious diseases with imminent potential for pandemic as identified by CDC, better personal hygiene antibiotic stewardship in healthcare facilities, antibiotic prescription based on the clinical antibiogram of each patient, clean toilet facilities, clean portable water. In addition to that, we have found that the following specific objective measures were compelling as they are pivotal in reducing the AF: i. When was the last time you took antibiotics? ii. Was that possibly overuse? iii. How many times have you had antibiotics since birth? iv. How many times were possibly overuse? v. Do you know how many grams of antibiotics were used to raise the chicken that you are eating? vi. Which meat has a low Antibiotic Footprint? vii. How can you reduce your own and your country's Antibiotic Footprint to a minimum? Taken together, effective implementation of regulatory measures across the globe curbing the misuse and overuse of antibiotics in humans and animals would suffice to minimize the morbidity and mortality rate of a prospective incidence of infectious diseases pandemic inflicted by antibiotic-resistant bacterial pathogens which in turn reduce the consumption of antibiotics.

Infographics Are More Effective at Increasing Social Media Attention in Comparison With Original Research Articles: An Altmetrics-Based Analysis

Purpose To compare social media attention and citation rates between infographics (visual abstracts) and original research articles. Methods All infographics in 2019 from electronic versions of Arthroscopy were matched by topic to articles in the “Original Research” section of the journal in a 4:1 ratio within the same year. The primary outcome was the Altmetric Attention Score (AAS), a cumulative measure of social media attention from various platforms such as Twitter and Facebook. Secondary outcomes included citation rates, article characteristics, and number of shares on social media platforms. Independent t tests and χ2 analyses were used to compare primary and secondary outcomes between infographics and control articles. Multivariate linear regression analysis was performed to determine the association between article type and social media attention while controlling for bibliometric characteristics. Results A total of 60 matched research articles (n = 48, 80.0%) and infographics (n = 12, 20.0%) published in 2019 in Arthroscopy were included. The mean AAS among all infographics was 29.75 ± 32.84 (range, 3-118), whereas the mean AAS among all control research articles was 5.75 ± 8.90 (range, 0-41), representing a statistically significant difference (P < .001). Infographics had significantly more Twitter mentions (100% vs 70.8%, P < .001) and Facebook mentions (75% vs. 6.2%, P < .001) compared with original articles. Multivariate linear regression analysis demonstrated a statistically significant and positive association between AAS and article type, with an additional mean increase in the AAS of 33.7 (95% confidence interval 11.6-50.6; P = .003) for every infographic article compared with an original research article. The mean citation rate among all infographics was 2.4 ± 2.4 (range, 0-7), whereas the mean citation rate among all control research articles was 2.2 ± 4.0 (range, 0-27), which was not a significant difference (P = .69). Conclusions Infographics resulted in significantly greater AAS and social media attention in comparison with original research articles of similar topics. We recommend the routine creation of infographics by journals to increase the social media attention that their research and chosen topics of interest receive. However, viewers of infographics should read them out of interest but turn their attention toward the original article or a source of more detailed information before making changes in clinical decision-making or practice, as they can be oversimplified. Clinical Relevance Infographics are an increasingly used by journals as a form of depicting research findings from select studies. By producing infographics, journals may increase the amount of social media attention received for a particular study or topic of interest. To compare social media attention and citation rates between infographics (visual abstracts) and original research articles. All infographics in 2019 from electronic versions of Arthroscopy were matched by topic to articles in the “Original Research” section of the journal in a 4:1 ratio within the same year. The primary outcome was the Altmetric Attention Score (AAS), a cumulative measure of social media attention from various platforms such as Twitter and Facebook. Secondary outcomes included citation rates, article characteristics, and number of shares on social media platforms. Independent t tests and χ2 analyses were used to compare primary and secondary outcomes between infographics and control articles. Multivariate linear regression analysis was performed to determine the association between article type and social media attention while controlling for bibliometric characteristics. A total of 60 matched research articles (n = 48, 80.0%) and infographics (n = 12, 20.0%) published in 2019 in Arthroscopy were included. The mean AAS among all infographics was 29.75 ± 32.84 (range, 3-118), whereas the mean AAS among all control research articles was 5.75 ± 8.90 (range, 0-41), representing a statistically significant difference (P < .001). Infographics had significantly more Twitter mentions (100% vs 70.8%, P < .001) and Facebook mentions (75% vs. 6.2%, P < .001) compared with original articles. Multivariate linear regression analysis demonstrated a statistically significant and positive association between AAS and article type, with an additional mean increase in the AAS of 33.7 (95% confidence interval 11.6-50.6; P = .003) for every infographic article compared with an original research article. The mean citation rate among all infographics was 2.4 ± 2.4 (range, 0-7), whereas the mean citation rate among all control research articles was 2.2 ± 4.0 (range, 0-27), which was not a significant difference (P = .69). Infographics resulted in significantly greater AAS and social media attention in comparison with original research articles of similar topics. We recommend the routine creation of infographics by journals to increase the social media attention that their research and chosen topics of interest receive. However, viewers of infographics should read them out of interest but turn their attention toward the original article or a source of more detailed information before making changes in clinical decision-making or practice, as they can be oversimplified.

An unsupervised clustering-based sectionalized displacement reconstruction method for smart geogrids integrated with fiber Bragg grating sensors

It has been found that cumulative measurement errors adversely affect the accurate reconstructions of the displacements of smart geogrids integrated with fiber Bragg grating sensors. The correction coefficients tend to vary with the deformation forms of the geogrids, which hinder the accurate self-corrections of the smart geogrids. Therefore, in order to address these issues and increase the displacement measurement accuracys, a sectionalized displacement reconstruction method for the smart geogrids was proposed. Two novel feature descriptors, which were termed as the displacement variation direction and logarithm of the strain absolute value, were designed. This was followed by an unsupervised clustering algorithm, which was designed to process the two designed features and categorize the smart geogrids into different sections. Each of the sections were corrected using the corresponding correction coefficients, which were optimized using a differential evolution algorithm. Then, simulations of smart geogrids with different lengths and different deformation patterns were performed for the purpose of validating the performance of the proposed method. It was determined that the mean of mean absolute errors (MAEs) of the simulation cases had been decreased from 18.6 mm to 2.2 mm. In addition, the proposed method was validated using laboratory experiments and model testing. The experimental results indicated that for the three different performed experiments, the proposed method had successfully reduced the mean MAEs from 12 mm to 5 mm. Therefore, smart geogrids using sectionalized displacement reconstruction methods were confirmed to be promising new developments in the field of practical civil engineering applications.