Analysis of a continuous-time model of structural balance

It is not uncommon for certain social networks to divide into two opposing camps in response to stress. This happens, for example, in networks of political parties during winner-takes-all elections, in networks of companies competing to establish technical standards, and in networks of nations faced with mounting threats of war. A simple model for these two-sided separations is the dynamical system dX/dt = X^2 where X is a matrix of the friendliness or unfriendliness between pairs of nodes in the network. Previous simulations suggested that only two types of behavior were possible for this system: either all relationships become friendly, or two hostile factions emerge. Here we prove that for generic initial conditions, these are indeed the only possible outcomes. Our analysis yields a closed-form expression for faction membership as a function of the initial conditions, and implies that the initial amount of friendliness in large social networks (started from random initial conditions) determines whether they will end up in intractable conflict or global harmony.Comment: 12 pages, 2 figure

The energy landscape of social balance

We model a close-knit community of friends and enemies as a fully connected network with positive and negative signs on its edges. Theories from social psychology suggest that certain sign patterns are more stable than others. This notion of social "balance" allows us to define an energy landscape for such networks. Its structure is complex: numerical experiments reveal a landscape dimpled with local minima of widely varying energy levels. We derive rigorous bounds on the energies of these local minima and prove that they have a modular structure that can be used to classify them.Comment: 4 pages, 3 figure

Invariant submanifold for series arrays of Josephson junctions

We study the nonlinear dynamics of series arrays of Josephson junctions in the large-N limit, where N is the number of junctions in the array. The junctions are assumed to be identical, overdamped, driven by a constant bias current and globally coupled through a common load. Previous simulations of such arrays revealed that their dynamics are remarkably simple, hinting at the presence of some hidden symmetry or other structure. These observations were later explained by the discovery of (N - 3) constants of motion, each choice of which confines the resulting flow in phase space to a low-dimensional invariant manifold. Here we show that the dimensionality can be reduced further by restricting attention to a special family of states recently identified by Ott and Antonsen. In geometric terms, the Ott-Antonsen ansatz corresponds to an invariant submanifold of dimension one less than that found earlier. We derive and analyze the flow on this submanifold for two special cases: an array with purely resistive loading and another with resistive-inductive-capacitive loading. Our results recover (and in some instances improve) earlier findings based on linearization arguments.Comment: 10 pages, 6 figure

Neutrophils in cancer: neutral no more

Neutrophils are indispensable antagonists of microbial infection and facilitators of wound healing. In the cancer setting, a newfound appreciation for neutrophils has come into view. The traditionally held belief that neutrophils are inert bystanders is being challenged by the recent literature. Emerging evidence indicates that tumours manipulate neutrophils, sometimes early in their differentiation process, to create diverse phenotypic and functional polarization states able to alter tumour behaviour. In this Review, we discuss the involvement of neutrophils in cancer initiation and progression, and their potential as clinical biomarkers and therapeutic targets

AN ELECTRONIC MEDICAL RECORD BASED ALGORITHM TO TAILOR CARDIOVASCULAR DISEASE PREVENTION USING LIPOPROTEIN(A), APOLIPOPROTEIN B, CHOLESTEROL AND MYOCARDIAL INFARCTION DIAGNOSIS: ABCDS PREVENTION PROGRAM

Therapeutic Area: CVD Prevention – Primary and Secondary; ASCVD/CVD Risk Assessment; Preventive Cardiology Best Practices Background: According to the 2022 American Heart Association Heart Disease and Stroke Statistics, coronary heart disease remains the leading cause of death attributable to cardiovascular disease (CVD). Opportunity exists to utilize electronic medical records (EMRs) and biomarkers to facilitate early identification of patients at high risk for CVD. Additionally, automatic or opt-out orders are EMR-based tools that have the potential to improve referral rates to prevention programs. The role of cardiovascular biomarkers and electronic medical records (EMRs) in optimizing identification and referral of patients at risk for CVD are explored in the ABCDs PREVENTION program. Methods: A multidisciplinary team of cardiologists, internists, engineers, and clinical informaticists defined the logic for the guideline based ABCDs PREVENTION tool. The EMR algorithm used the cardiovascular risk biomarker thresholds of lipoprotein(a) > 70 nmol/L, apolipoprotein B > 90 mg/dL, low-density lipoprotein cholesterol  > 150 mg/dL, and triglycerides > 200 mg/dL, and/or a diagnosis of ST-elevation myocardial infarction (STEMI) or non-ST-elevation MI (NSTEMI) based on ICD-10 codes to generate automatic referrals to (1) cardiac rehabilitation (CR), (2) the advanced lipid disorders clinic, and/or (3) Corrie Cardiovascular Health Program (Figure 1). Results: In a test environment, the algorithm was applied to 27 patients identified by the clinical team with STEMI or NSTEMI. The algorithm was 90% successful in triggering automatic referrals to CR and Corrie. Fail rates can be attributed to our current algorithm not detecting some ICD codes related to NSTEMI. The automatic referral to lipid disorders clinic based on abnormal lipid biomarkers is now live and undergoing automation optimization to validate accuracy. Conclusion: Building an EMR-based algorithm to individualize CVD prevention using cardiovascular risk biomarkers and diagnoses may enable early identification and intervention on high-risk patients. Future directions include applying the algorithm to clinical decision support tools as well as an automated order set to increase referral rates to evidenced-based programs focused on primary and secondary CVD prevention. Ultimately, use analysis will determine if the algorithm improves referral rates to CR, lipid clinic, and the Corrie Cardiovascular Health Program to improve access to these evidence-based services