Integration Point Research Articles

Improving the estimation of countermovement jump height from force plate recordings by considering the interaction between multiple procedural steps: An optimisation approach

ABSTRACT Force plates are used as standalone measurement systems in research and practice to evaluate metrics such as jump height. Calculating jump height involves multiple procedural steps, but previous investigations aiming to improve calculation procedures have only considered the influence of a single procedural step in isolation. The purpose of this study was to investigate if considering the interacting influence of multiple procedural steps in conjunction would impact the accuracy of jump height calculated from force plate recordings. An optimisation procedure was used to determine the combination of filter type, filter order, filter cut-off, integration start point and instant of take-off, that would minimize the root mean squared difference between force plate calculated jump height and a kinematic criterion. The best filter approach was a fifth order Butterworth filter with a 6 Hz cut-off frequency or a third order Chebyshev filter with a 5 Hz cut-off frequency. The best starting point for integration was approximately 0.25 s prior to the onset of the jump and the instant of take-off was best identified by finding the first instant that the force-time signal decreased by the magnitude of system weight. The presented optimisation technique provides an improved quantitative approach to develop standard procedures.

Crystal plasticity framework related to size effect: From single crystal parameters to polycrystalline mechanical properties

Size effect has a significant influence on the accuracy of two key factors of parameters and models in crystal plasticity simulation. This study introduces a parameter identification method that considers the indentation size effect, determining the initial slip resistance of IN625 alloy. Based on the identified parameters and utilizing the integral point traversal method, a grain boundary affected zone (GBAZ), whose strength field related to the distance to the grain boundary (GB) is introduced into the polycrystalline microstructure to represent the hindering effect of GBs on dislocations. This method effectively predicts the Hall-Petch effect and strain hardening behavior of IN625 alloy. The research reveals that dislocation pile-ups primarily concentrate in small grain clusters within the material. In fine-grained microstructures, a large volume fraction of GBs promotes dislocation pile-ups, reducing the mean free path of dislocations, leading to an increase in dislocation multiplication rate, and consequently, enhancing the strain hardening rate. An increase in GBAZ thickness results in a large stress level within the material, accompanied by a decrease in the homogeneity of stress distribution. However, the sensitivity of strain to GBAZ thickness is found to be low. The method proposed in this work holds significant applicative relevance in parameter calibration and prediction the mechanical properties of polycrystalline materials.

Physics‐constrained symbolic model discovery for polyconvex incompressible hyperelastic materials

AbstractWe present a machine learning framework capable of consistently inferring mathematical expressions of hyperelastic energy functionals for incompressible materials from sparse experimental data and physical laws. To achieve this goal, we propose a polyconvex neural additive model (PNAM) that enables us to express the hyperelastic model in a learnable feature space while enforcing polyconvexity. An upshot of this feature space obtained via the PNAM is that (1) it is spanned by a set of univariate basis functions that can be re‐parametrized with a more complex mathematical form, and (2) the resultant elasticity model is guaranteed to fulfill the polyconvexity, which ensures that the acoustic tensor remains elliptic for any deformation. To further improve the interpretability, we use genetic programming to convert each univariate basis into a compact mathematical expression. The resultant multi‐variable mathematical models obtained from this proposed framework are not only more interpretable but are also proven to fulfill physical laws. By controlling the compactness of the learned symbolic form, the machine learning‐generated mathematical model also requires fewer arithmetic operations than its deep neural network counterparts during deployment. This latter attribute is crucial for scaling large‐scale simulations where the constitutive responses of every integration point must be updated within each incremental time step. We compare our proposed model discovery framework against other state‐of‐the‐art alternatives to assess the robustness and efficiency of the training algorithms and examine the trade‐off between interpretability, accuracy, and precision of the learned symbolic hyperelastic models obtained from different approaches. Our numerical results suggest that our approach extrapolates well outside the training data regime due to the precise incorporation of physics‐based knowledge.

A robust finite strain isogeometric solid-beam element

In this work, an efficient and robust isogeometric three-dimensional solid-beam finite element is developed for large deformations and finite rotations with merely displacements as degrees of freedom. The finite strain theory and hyperelastic constitutive models are considered and B-Spline and NURBS are employed for the finite element discretization. Similar to finite elements based on Lagrange polynomials, also NURBS-based formulations are affected by the non-physical phenomena of locking, which constrains the field variables and negatively impacts the solution accuracy and deteriorates convergence behavior. To avoid this problem within the context of a solid-beam formulation, the Assumed Natural Strain (ANS) method is applied to alleviate membrane and transversal shear locking and the Enhanced Assumed Strain (EAS) method against Poisson thickness locking. Furthermore, the Mixed Integration Point (MIP) method is used to make the formulation more efficient and robust. The proposed novel isogeometric solid-beam element is tested on several single-patch and multi-patch benchmark problems, and it is validated against classical solid finite elements and first-order Lagrange solid-beam element. The results show that the proposed formulation can alleviate the locking effects and significantly improve the performance of the isogeometric solid-beam element. With the developed element, efficient and accurate predictions of mechanical properties of lattice-based structured materials can be achieved. The proposed solid-beam element inherits both the merits of solid elements e.g. flexible boundary conditions and of the beam elements i.e. higher computational efficiency.

A microstructure-based graph neural network for accelerating multiscale simulations

Simulating the mechanical response of advanced materials can be done more accurately using concurrent multiscale models than with single-scale simulations. However, the computational costs stand in the way of the practical application of this approach. The costs originate from microscale Finite Element (FE) models that must be solved at every macroscopic integration point. A plethora of surrogate modeling strategies attempt to alleviate this cost by learning to predict macroscopic stresses from macroscopic strains, completely replacing the microscale models. In this work, we introduce an alternative surrogate modeling strategy that allows for keeping the multiscale nature of the problem, allowing it to be used interchangeably with an FE solver for any time step. Our surrogate provides all microscopic quantities, which are then homogenized to obtain macroscopic quantities of interest. We achieve this for an elasto-plastic material by predicting full-field microscopic strains using a graph neural network (GNN) while retaining the microscopic constitutive material model to obtain the stresses. This hybrid data-physics graph-based approach avoids the high dimensionality originating from predicting full-field responses while allowing non-locality to arise. In addition, this approach introduces beneficial inductive bias to the model by encoding microscopic geometrical features. By training the GNN on a variety of meshes, it learns to generalize to unseen meshes, allowing a single model to be used for a range of microstructures. The embedded microscopic constitutive model in the GNN implicitly tracks history-dependent variables and leads to improved accuracy. While the microscopic stresses are fully dependent on the microscopic strains, we found it crucial to include both microscopic strains and stresses in the loss function. We demonstrate for several challenging scenarios that the surrogate can predict complex macroscopic stress–strain paths. As the computation time of our method scales favorably with the number of elements in the microstructure compared to the FE method, our method can significantly accelerate FE2 simulations.

Newton–Okounkov bodies and minimal models for cluster varieties

Let Y be a (partial) minimal model of a scheme V with a cluster structure (of type A, X or of a quotient of A or a fibre of X). Under natural assumptions, for every choice of seed we associate a Newton–Okounkov body to every divisor on Y supported on Y∖V and show that these Newton–Okounkov bodies are positive sets in the sense of Gross, Hacking, Keel and Kontsevich [31]. This construction essentially reverses the procedure in [31] that generalizes the polytope construction of a toric variety to the framework of cluster varieties.In a closely related setting, we consider cases where Y is a projective variety whose universal torsor UTY is a partial minimal model of a scheme with a cluster structure of type A. If the theta functions parametrized by the integral points of the associated superpotential cone form a basis of the ring of algebraic functions on UTY and the action of the torus TPic(Y)⁎ on UTY is compatible with the cluster structure, then for every choice of seed we associate a Newton–Okounkov body to every line bundle on Y. We prove that any such Newton–Okounkov body is a positive set and that Y is a minimal model of a quotient of a cluster A-variety by the action of a torus.Our constructions lead to the notion of the intrinsic Newton–Okounkov body associated to a boundary divisor in a partial minimal model of a scheme with a cluster structure. This notion is intrinsic as it relies only on the geometric input, making no reference to the auxiliary data of a valuation or a choice of seed. The intrinsic Newton–Okounkov body lives in a real tropical space rather than a real vector space. A choice of seed gives an identification of this tropical space with a vector space, and in turn of the intrinsic Newton–Okounkov body with a usual Newton–Okounkov body associated to the choice of seed. In particular, the Newton–Okounkov bodies associated to seeds are related to each other by tropicalized cluster transformations providing a wide class of examples of Newton-Okounkov bodies exhibiting a wall-crossing phenomenon in the sense of Escobar–Harada [18].This approach includes the partial flag varieties that arise as minimal models of cluster varieties (for example full flag varieties and Grassmannians). For the case of Grassmannians, our approach recovers, up to interesting unimodular equivalences, the Newton–Okounkov bodies constructed by Rietsch–Williams in [56].

On the Efficient and Accurate Non-linear Computational Modeling of Multilayered Bending Plates. State of the Art and a Novel Proposal: The 2D+\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2\ ext {D}+$$\\end{document} Multiscale Approach

After conducting a comprehensive historical review of presently established methods for computational modeling of multilayered bending plates, the present work introduces a novel 2D multiscale strategy, termed the 2D+ approach. The proposed approach is based on the computational homogenization formalism and is envisaged to serve as an appealing alternative to current methodologies for modeling multilayered plates in bending-dominated situations. Such structural elements involve modern and relevant materials, such as laminated composites characterized by the heterogeneous distribution of low-aspect-ratio layers showing substantial non-linear mechanical behavior across their thickness.Within this proposed approach, the 2D plate mid-plane constitutes the macroscopic scale, while a 1D filament-like Representative Volume Element (RVE), orthogonal to the plate mid-plane and spanning the plate thickness, represents the mesoscopic scale. Such RVE, in turn, is capturing the non-linear mechanical behavior throughout the plate thickness at each integration point of the 2D plate-midplane finite element mesh. The chosen kinematics and discretization at the considered scales are particularly selected to (1) effectively capture relevant aspects of non-linear mechanical behavior in multilayered plates under bending-dominated scenarios, (2) achieve affordable computational times (computational efficiency), and (3) provide accurate stress distributions compared to the corresponding high-fidelity 3D simulations (computational accuracy).The proposed strategy aligns with the standard, first-order, hierarchical multiscale setting, involving the linearization of the macro-scale displacement field along the thickness. It employs an additional fluctuating displacement field in the RVE to capture higher-order behavior, which is computed through a local 1D finite element solution of a Boundary Value Problem (BVP) at the RVE. A notable feature of the presented 2D+ approach is the application of the Hill–Mandel principle, grounded in the well-established physical assumption imposing mechanical energy equivalence in the macro and meso scales. This links the 2D macroscopic plate and the set of 1D mesoscopic filaments, in a weakly-coupled manner, and yields remarkable computational savings in comparison with standard 3D modeling. Additionally, solving the resulting RVE problem in terms of the fluctuating displacement field allows the enforcement of an additional condition: fulfillment of linear momentum balance (equilibrium equations). This results in a physically meaningful 2D-like computational setting, in the considered structural object (multilayered plates in bending-dominated situations), which provides accurate stress distributions, typical of full 3D models, at the computational cost of 2D models.

Integration of figital sports from the student community point of view

Fijital sport is a new word in the development of physical culture, fijital is on the border between cybersports and traditional sports. This type of sport has been developing lightning fast in the last few years, large nationwide events have already been held, where hundreds of thousands of people watch athletes in the new field. The development of fijtal-sports in the country's universities, its timely integration helps motivate students to engage in physical education, especially cyber athletes, whose activities are closely associated with hypodynamia. In order to address the issue of integrating fijital sport into the framework of the educational program, it is necessary to have feedback from the representatives of the student community, for this purpose in this paper it was decided to conduct a survey among students to determine the student point of view on fijital sport. The key points of integration of this sport into practice students consider: 1) sufficient modern equipment, which unmistakably provides an opportunity for athletes to train to perform at any events - 96% of students, consider this a primary issue, 2) 84% of students supported the idea of a systematic unified approach to integration, 3) 78% were in favor of the need for regular classes, trainings, 4) in achieving the goal the most important point, according to 72% of students, is the active position of the student community. Thus, the program of integration of fijital-sport will be built on a number of key aspects highlighted by students - future sportsmen.

Optimizing integration point density for exponential finite element shape functions for phase-field modeling of fracture in functionally graded materials

In the realm of fracture mechanics and phase-field modeling, the utilization of exponential finite element (EFE) shape functions has shown promise in accurately predicting fracture responses, particularly in scenarios with intricate crack propagation paths. However, the computational complexity associated with EFE shape functions, including higher integration schemes and orientation requirements, prompts the need for optimization. This study delves into the critical aspect of integration point density and aims to determine the ideal balance between accuracy and computational efficiency in the context of EFE shape functions. The research focuses on functionally graded materials, which inherently exhibit spatial variations in solution quantities due to their graded material system. Through a systematic investigation, the study aims to identify the optimal number of integration points required to maximize the computational advantages offered by EFE shape functions while minimizing the associated computational resources. By conducting a comprehensive analysis across various loading scenarios, such as tension and shear, this study intends to establish a quantitative relationship between integration point density and prediction accuracy for fracture responses.

Coupling μ-computed tomography and multi-scale modelling to assess the mechanical performance of material extrusion metal components

The porosity defects arising in objects produced by metal Material Extrusion (MEX) additive manufacturing affect the macroscopic mechanical behaviour. This paper presents a new approach integrating μ-computed tomography (μXCT) and multi-scale finite element analysis to evaluate the mechanical performance of components fabricated by metal MEX. The porosity information from μXCT is mapped into the finite element model, allowing to define the volume fraction of porosity to each finite mesh element. Then, the Mori-Tanaka homogenization technique is used to estimate the effective mechanical properties in each integration point, assuming a representative volume element composed by a metal matrix with a void. The reliability of the proposed approach was assessed using tensile specimens of stainless steel 316L produced by metal MEX. The numerical predictions were compared with experimental measurements, namely the strain field evolution measured by digital image correlation (DIC). The results highlight the detrimental influence of the porosity distribution, evaluated in the specimen using μXCT, on the strain distribution during the loading stage. The numerical predictions are in agreement with the experimental measurements, i.e. the difference is lower than 11%. Therefore, the proposed approach offers valuable insights for evaluating the mechanical performance of components produced by metal MEX, focusing on the detrimental effects of porosity defects.

Gender effect of glucose, insulin/glucagon ratio, lipids, and nitrogen-metabolites on serum HGF and EGF levels in patients with diabetes type 2.

Hepatocyte growth factor (HGF) exhibits potent growth-inducing properties across various tissues, while epidermal growth factor (EGF) acts as a molecular integration point for diverse stimuli. HGF plays a crucial role in hepatic metabolism, tissue repair, and offers protective effects on epithelial and non-epithelial organs, in addition to its involvement in reducing apoptosis and inflammation, underscoring its anti-inflammatory capabilities. The HGF-Met system is instrumental in hepatic metabolism and enhancing insulin sensitivity in animal diabetes models. Similarly, the EGF and its receptor tyrosine kinase family (EGFR) are critical in regulating cell growth, proliferation, migration, and differentiation in both healthy and diseased states, with EGF also contributing to insulin sensitivity. In this observational study, we aimed to identify correlations between serum levels of HGF and EGF, insulin, glucagon, glucose, and primary serum lipids in patients with type 2 diabetes mellitus (DM), taking into account the impact of gender. We noted differences in the management of glucose, insulin, and glucagon between healthy men and women, potentially due to the distinct influences of sexual hormones on the development of type 2 DM. Additionally, metabolites such as glucose, albumin, direct bilirubin, nitrites, and ammonia might influence serum levels of growth factors and hormones. In summary, our results highlight the regulatory role of insulin and glucagon in serum glucose and lipids, along with variations in HGF and EGF levels, which are affected by gender. This link is especially significant in DM, where impaired cell proliferation or repair mechanisms lead to metabolic changes. The gender-based differences in growth factors point to their involvement in the pathophysiology of the disease.

Dimensional reduction technique-based maximum entropy principle method for safety degree analysis under twofold random uncertainty

A modified failure chance measure (FCM) was proposed to assess the safety degree of structures under the influence of twofold random uncertainty. This uncertainty arises from random inputs with random distribution parameters. The aim of this paper is to effectively evaluate the safety degree of structures in such conditions. This paper introduces a method named dimensional reduction technique-based maximum entropy principle to address the issue at hand. The proposed method utilizes maximum entropy principle method to efficiently approach optimal probability density characteristics while adhering to the constraints imposed by fractional moments. Additionally, the dimensional reduction strategy is employed to estimate fractional moments, resulting in a linear increase in computational cost with respect to the dimensionality. The primary contribution of this work involves the detailed decoupling of the double-uncertainty analysis used to estimate FCM into a single-uncertainty analysis. This approach allows for the innovative re-use of the same group integral grid points to estimate different fractional moments required for solving FCM. The results of applying the proposed method to solve FCM under acceptable accuracy demonstrate that the number of evaluations required for the performance function can be reduced to less than 100 when the uncertainty dimensionality is limited to 20. This finding confirms the high efficiency of the proposed method for solving FCM.

IJCM_36A: Community-based Explanatory Mixed method approach to Understand Perceptions regarding Complementary food items in Urban slums of Mumbai

Background: There is a paucity of research to explore the common age of initiation of each food group item and its perceptions. Objective: To assess the age of initiation of complementary food items, understand its perceptions and determine IYCF indicators. Methodology: An explanatory mixed-method study was conducted in the urban slums of Mumbai. A total of 93 Health care workers (HCWs) working in different areas and 24 mothers were interviewed with the pretested questionnaire. Later 5 and 6 FGDs with mothers and AWs respectively were done. The data was analyzed with the point of integration for the mixed- method approach Results: In 68.9% and 52.7% of the HCWs areas, commonly started cereals at 6 to 8 months are rice and ragi. Vitamin A-rich vegetables, green leafy vegetables, and other vegetables are usually started at 9 to 11 months (32.2%), after 12 months (32.9%), and after 19 months (35.4%) respectively. Banana is a common fruit initiated at 6 months onwards. Intake of chicken and egg are started at 9 months onwards in 31% and 42% of areas respectively. Pulses and beans consumption is initiated at 6 to 8 months and after 12 months in 42% and 33% of areas respectively. Cow’s milk is started in 78.9% of the areas. Milk products intake starts at 12 to 19 months onwards. Biscuits are started at 6 months (39.1%). The Minimum Meal Frequency, Minimum dietary diversity and Zero vegetable consumption are 56%, 28% and 22% respectively Mothers self-efficacy, Family members’ and neighbour’s influences, Child’s responses to feeding, and Family food habits are factors that decide food items at a particular age. Conclusion: Dietary diversity at 6 to 8 months is very poor. Mothers’ self-efficacy plays a key role in improving dietary diversity at an early age.

A criterion for nondensity of integral points

AbstractWe give a general criterion for Zariski degeneration of integral points in the complement of a divisor with components in a variety of dimension defined over or over a quadratic imaginary field. The key condition is that the intersection of the components of is not well approximated by rational points, and we discuss several cases where this assumption is satisfied. We also prove a greatest common divisor (GCD) bound for algebraic points in varieties, which can be of independent interest.

Abstract 6206: Molecular stratification of AML: Integrative genomic and immune profiling points to high risk subgroup and targetable molecular drivers

Abstract Background: Acute Myeloid Leukemia (AML) is a complex hematological malignancy characterized by clinical diversity. The ability to accurately subtype patients can inform prognosis and guide therapeutic approaches. With the integration of multi-omics data, it is possible to elucidate the molecular mechanisms underpinning unique AML subtypes, with intent to identify potential drug targeting pathways in a precision medicine strategy. Method: RNAseq datasets from Beat-AML (discovery, N=462), TCGA-AML (validation, N=173), and Leucegene (validation, N=452) were analyzed through non-negative matrix factorization to delineate distinct transcriptomic-driven molecular subtypes within AML. A curated set of the top 1,000 most variable genes was utilized to minimize analytical noise. GSVA was used for pathway analyses across Hallmark, KEGG, Reactome, and the immune microenvironment was characterized via xCell. Recurring DNA variants were examined in each subtype. Clinical outcomes of each subtype were analyzed using the Kaplan-Meier method and assessed by a log-rank test. These insights were subsequently validated in two independent cohorts - TCGA AML and Leucegene. The most influential components of immunological effector mechanisms, which characterize poor prognostic subpopulation, were assessed using bootstrap forest partitioning as a feature selection technique. Results: Our Beat-AML analysis identified 5 distinct clusters. Cluster 3 consisted of 20% of AML cases (n=86), and displayed a worse overall survival with a HR (95% CI) of 1.41 (1.03, 1.92, P=0.03). This cluster was characterized by three co-mutations: FLT3, NPM1, and DNMT3A. Pathway analysis highlighted biological processes key to antibody therapy intervention, specifically complement pathways, NK cell cytotoxicity, and FCGR-mediated phagocytosis as enriched within this subpopulation. Concurrently, oncogenic (PI3K/AKT/MTOR, TGFB, NOTCH) and metabolic pathways (fatty acid and oxidative phosphorylation) were activated. Immune profiling indicated increased levels of M2 macrophages. Using bootstrap forest partitioning, C2 and ITGAM were identified as key genes defining cluster 3. These observations were confirmed in TCGA AML and Leucegene cohorts. Conclusion: Our comprehensive analysis identified a distinct high-risk AML subgroup characterized by unique genomic, transcriptomic, and immunological patterns. The combined presence of NPM1/FLT3-ITD and DNMT3A mutations in cluster 3—each previously attributed with varied prognostic outcomes—warrants in-depth biological investigation. With these consistent AML subgroup results identified across three independent cohorts (total of 1,087 patients), we highlight the complexities within the molecular landscape of AML and emphasize the need for tailored therapeutic approaches - a transformative shift in AML treatment. Citation Format: Kubra Karagoz, Lauren Brady, Brandon Higgs, Han Si. Molecular stratification of AML: Integrative genomic and immune profiling points to high risk subgroup and targetable molecular drivers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6206.

Integrability, multifractality, and two-photon dynamics in disordered Tavis-Cummings models

The Tavis-Cummings model is a paradigmatic central-mode model in which a set of two-level quantum emitters (spins) are coupled to a collective cavity mode. Here we study the eigenstate spectrum, its localization properties, and the effect on dynamics, focusing on the two-excitation sector relevant for nonlinear photonics. These models admit two sources of disorder: in the coupling between the spins and the cavity, and in the energy shifts of the individual spins. While this model was known to be exactly solvable in the limit of a homogeneous coupling and inhomogeneous energy shifts, we establish here the solvability in the opposite limit of a homogeneous energy shift and inhomogeneous coupling, presenting the exact solution and corresponding conserved quantities. We identify three different classes of eigenstates, exhibiting different degrees of multifractality and semilocalization closely tied to the integrable points, and we study their stability to perturbations away from these solvable points. The dynamics of the cavity occupation number away from equilibrium, exhibiting boson bunching and a two-photon blockade, is explicitly related to the localization properties of the eigenstates, and it illustrates how these models support a collective spin description despite the presence of disorder. Published by the American Physical Society 2024

GERMANY’S SECURITY MANAGEMENT IN THE LIGHT OF THE INTEGRATED SECURITY – CURRENT STATE AND PROSPECTS

In June 2023, the Federal Government of Germany presented the first national security strategy (NSS). The NSS promotes Integrated Security as a new foreign and security policy. However, research has shown that the idea of Integrated Security is not new and that the integration of all resources of national power has been a goal for Germany for 30 years. Research has purpose to give an answer to following questions: Can the current organization of the German national security system support the idea of Integrated Security as a new security policy and what are the key requirements related to the organization, functioning and management of the German national security system that should be fulfilled so that Integrated Security can be implemented? The basic hypothesis of this research is that the national security system of Germany is not organized and governed in a way that can enable the implementation of Integrated Security, primarily because, on the strategic level, Germany does not have a national security council which could serve as a focal point and impetus for integration, coordination and government of a security system. In order to provide answers to the above stated questions in the first part of paper we explained Integrated Security and the national security objectives of the NSS, then we described organization of the three ministries and security services as the most important actors in the implementation of the NSS objectives at the operational level and at the end we did the capability analysis of the strategic level of management to implement Integrated Security. The research showed that the organizational solutions have not been aligned with the determinations stated in the NSS. The result of this research are proposed solutions for organization and position of the Federal Security Council which should be provided with competencies that will enable the integration of elements from all levels into a single structure which aims to achieve the national security objectives.

Outpatient parenteral antimicrobial therapy (OPAT) in Germany: insights and clinical outcomes from the K-APAT cohort study

PurposeOutpatient parenteral antimicrobial therapy (OPAT) offers several key advantages, including enhanced patient quality of life, reduced healthcare costs, and a potential reduction of nosocomial infections. It is acknowledged for its safety and effectiveness. This study provides the first systematic clinical data for Germany, where OPAT has not yet been widely adopted. The aim is to establish a foundational reference point for further research and integration of OPAT into the German healthcare system.MethodsThis prospective observational study descriptively analyses data obtained from a cohort of patients receiving OPAT. Both in- and outpatients from all medical specialties could be recruited. Patients administered the anti-infective medications themselves at home using elastomeric pumps.Results77 patients received OPAT, with a median duration of 15 days and saving 1782 inpatient days. The most frequently treated entities were orthopaedic infections (n = 20, 26%), S. aureus bloodstream infection (n = 16, 21%) and infectious endocarditis (n = 11, 14%). The most frequently applied drugs were flucloxacillin (n = 18, 23%), penicillin G (n = 13, 17%) and ceftriaxone (n = 10; 13%). Only 5% of patients (n = 4) reported to have missed more than one outpatient dose (max. 3 per patient). Only one catheter-related adverse event required medical intervention, and there were no catheter-related infections.ConclusionThe study demonstrates that OPAT can be safely conducted in Germany. In preparation for its broader implementation, crucial next steps include creating medical guidelines, fostering interdisciplinary and inter-sectoral communication, as well as creating financial and structural regulations that facilitate and encourage the adoption of OPAT.Trial registration numberNCT04002453.

Tight Sum-of-squares Lower Bounds for Binary Polynomial Optimization Problems

For binary polynomial optimization problems of degree 2d with n variables Sakaue, Takeda, Kim, and Ito [ 33 ] proved that the \(\lceil \frac{n+2d-1}{2}\rceil\) th semidefinite (SDP) relaxation in the SoS/Lasserre hierarchy of SDP relaxations provides the exact optimal value. When n is an odd number, we show that their analysis is tight, i.e., we prove that \(\frac{n+2d-1}{2}\) levels of the SoS/Lasserre hierarchy are also necessary. Laurent [ 24 ] showed that the Sherali-Adams hierarchy requires n levels to detect the empty integer hull of a linear representation of a set with no integral points. She conjectured that the SoS/Lasserre rank for the same problem is n -1. In this article, we disprove this conjecture and derive lower and upper bounds for the rank.

A novel sequentially linear approach based on exponential saw-tooth softening in fracture analysis of quasi-brittle material

The Newton-Raphson iterative scheme is a widely used technique for modeling the non-linear problems, but it is well known that the scheme is unstable and the convergence may be difficult to obtain in case of snap-back or bifurcation. The sequentially linear approach, which sets a critical integration point and uses a saw-tooth softening approximation, is an alternative approach to address these issues. However, the sequentially linear approach cannot fully solve some drawbacks such as mesh dependency of crack patterns, which is main shortcomings of smeared crack approach. In this paper, the saw-tooth curve based on exponential softening is newly developed and an approach combined it with local crack tracking algorithm is proposed. The crack tip point is chosen by crack tracking algorithm and the fracture behavior is analyzed by sequentially reducing the stiffness and strength in elements within crack path. Several benchmark examples are numerically solved to check the accuracy of crack path, ultimate load and capture of snap-back predicted by the proposed approach and the results are compared with those by traditional sequentially linear approach and experiments.