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The cure progression of one-part room temperature vulcanizing (1-RTV) sealants and adhesives is a vital intrinsic material property for their typical end-use applications. Under-standing the key factors controlling the cure mechanism becomes more and more important given an ever-increasing demand to improve productivity by allowing assemblies using these materials to move faster through the manufacturing process. For 1-RTV systems, ultimate mechanical and adhesive strengths attain an equilibrium value as their cure proceeds in the presence of atmospheric moisture. A diffusion-controlled, moisture-cure mechanism was established for this family of materials about 10 years ago, most definitively by Comyn et al. The depth z of unidirectional cure with time t was derived to be a function of the vapor pressure p of water in the atmosphere in the proximity of the material surface, and two material properties: the permeability P of moisture through the cured layer and the equivalent material volume V reacting with 1 mol of water, and cure time, t, i.e. z=(2VPp t)1/2. Hence, the thickness of the cured layer should increase as t1/2. That is, a plot of z vs. t1/2 should yield a straight line where, for a particular RTV material, the mag-nitude of its slope is a function of the temperature and relative humidity (RH) during cure. This was shown for organic hot-melt adhesives and silicone sealants; validation of the moisture-cure model was demonstrated using gravimetrically based measurements to deter-mine V and P separately. However, a deviation from the moisture-cure model was reported from a study using an alkoxy silicone sealant in geometries requiring deep-section cure and, therefore, longer cure times. An increase in the slope of the z vs. t1/2 plot was observed after a certain time x interval that was a function of cure conditions. The change in cure rate was attributed to the migration of low molar mass crosslinkers and adhesion promoters towards the cure front and the eventual depletion of these species, which com-pete with the silicone polymer for reacting with the diffusing water. It was possible to determine the diffusion coefficient, D, of additives that act as adhesion promoters and crosslinkers in uncured alkoxy silicone sealant. From these studies, the utility of the moisture-cure diffusion model was demonstrated. The variables impacting cure performance are reviewed; and, a generalized form of the model is presented to account for variability in cure rates observed over extended time intervals in assembly geometries requiring deep-section cure. By plotting z as a function of (tp)1/2, data-sets for each material collected at different conditions of temperature and RH merged into a single straight line with a very high coefficient of determination. For end-users of 1-RTV silicone sealants and adhesives, this latter approach provides a material-specific reference line that demonstrates the corre-spondence between cure time and vapor pressure; i.e. a certain cured depth can be reached at short cure times with a high RH or at long times with a low RH. [ABSTRACT FROM AUTHOR]

The object of research is the technological process of cutting rectangular materials into haberdashery parts. The mathematical statement of the problem to find cutting diagrams of rectangular materials for haberdashery parts is given. The structural components of this problem and its mathematical model were described. A method for implementing the task set is proposed, which includes the following stages: – generation of layouts; – generation of a set of permissible sections of one part, from a combination of two parts, and from a combination of three product parts; – generation of cutting diagrams of rectangular materials for haberdashery parts from a combination of designed sections. Implementation algorithms have been proposed for each of the stages of the task. The proposed algorithms were used in the development of information technology support for finding cutting diagrams of rectangular materials for haberdashery parts. The information and technological support that was offered makes it possible to create graphic visualizations of rational cutting schemes and save them in a file. This feature allows automated cutting systems to use information about such schemes. The developed information technology support was tested on the parts of haberdashery and showed its effectiveness. This information and technological support can be successfully used at haberdashery enterprises in preparatory and cutting production to increase the utilization of material during cutting by 1.5–2.5 %. Thus, the proposed information and technological support makes it possible to improve the technological process of designing rational schemes of cutting for haberdashery articles. [ABSTRACT FROM AUTHOR]

In magnetic resonance imaging (MRI), high-power gradient power amplifiers (GPAs) are required to drive the gradient coils to generate strong and high-fidelity gradient fields. High precision is an essential requirement for the GPAs since precision directly impacts MRI imaging quality. Various aspects of the GPA have been the subject of research in the past years; however, high-precision GPA control that meets the stringent requirements of MRI applications is still a challenge. This article proposes a novel multi-rational-delay variables state space control method and an efficient out-of-band signal injection method to achieve GPA control accuracy at the level of one part per million at MVA output power levels. First, a systematic modeling and design method of the state space controller for high-power GPA is introduced utilizing state vectors with multi-rational-delay variables. This method improves the GPA dynamic performance significantly. Second, an efficient out-of-band signal injection method is presented to further improve the control precision at low output current, enabling the fulfillment of the challenging high-precision MRI requirements over the full GPA output range. Finally, the high-precision control method is validated in a GPA demonstrator with 500 A/1000 V output. Key results are a 30% improvement in current pulse reproducibility with respect to the conventional control method and a factor of 2.5 less noise at low currents. These experimental results validate the proposed novel method for the high-precision control of GPAs in MRI applications and prove its capability to contribute to significantly improved MRI image quality. [ABSTRACT FROM AUTHOR]

We establish that two-part models of pointing performance (Welford's model) describe pointing on a computer display significantly better than traditional one-part models (Fitts's Law). We explore the space of pointing models and describe how independent contributions of movement amplitude and target width to pointing time can be captured in a parameter k. Through a reanalysis of data from related work we demonstrate that one-part formulations are fragile in describing pointing performance, and that this fragility is present for various devices and techniques. We show that this same data can be significantly better described using two-part models. Finally, we demonstrate through further analysis of previous work and new experimental data that k increases linearly with gain. Our primary contribution is the demonstration that Fitts's Law is more limited in applicability than previously appreciated, and that more robust models, such as Welford's formulation, should be adopted in many cases of practical interest. [ABSTRACT FROM AUTHOR]

The article proposes a new nonlinear mathematical model that describes the process of possibility (instability of the state) or impossibility (stability of the state) of separating the region from the state. The model is described by the Cauchy problem for a nonlinear two-dimensional dynamic system. The model assumes that only two categories of citizens live in a particular region of a state: the first category, which is a supporter of the center (unionists) and opposes the secession of the region; the second - supporters of the separation of the region (separatists), i.e. its separation from the center, in order to form a new independent state. The general mathematical model implies the presence of both federal and external sides, which influence the separatists and unionists, respectively, by various factors, in order to change their opinion (will). Natural conditions are proposed under which secession of the region is considered possible (for example, the presence of a majority or qualified majority of citizens of the region who support separatism). In the case of variable coefficients of the model, under some restrictions, in quadratures, an exact solution to the Cauchy problem was found for a two-dimensional dynamic system, and in the case of constant coefficients, conditions were found under which secession of the region is impossible. In the particular case, the absence of external stakeholders for the region, in the case of constant coefficients and opposite values of demographic factors of the sides, the problem is actually reduced to a predator-victim model and is described by a nonlinear two-dimensional dynamic system of the Lotka-Volterra type. At the same time, conditions were found for the coefficients of attracting opponents to allies, demographic factors and baseline conditions under which it is impossible to separate the region. The article also proposes a new nonlinear mathematical model that describes in a certain politically conflicting region of the state the presence of three groups of the population with different political priorities. One part of the population (unionists) is politically oriented towards preserving the region as part of the state, the second part of the region supports the idea of separatism, separation of the region from the state in order to form a new independent state (separatists), and the third part of the region supports the idea of irredentism of the region, that is, separation in order to join another, possibly bordering state (irredentists). Weak (a simple majority of the region's population) and strong (a qualified majority of the region's population) conditions are offered, which in a legal sense may not have direct consequences, but may determine the aspirations of the majority of the region's population. The model is described by a nonlinear three-dimensional dynamic system with variable coefficients. With some constraints on model parameters, accurate analytical solutions are found. Additional conditions were also found under which: the region remains within the state; possible secession of the region; the irredentism of the region is possible, that is, its accession to another state. [ABSTRACT FROM AUTHOR]

This paper considers a production problem for a transfer line subject to random failures and repairs, and differs from other studies on transfer lines. It considers a manufacturing system consisting of three machines (two machines with passive redundancy, and one in series with the previous ones) producing one part type. The control problem is subject to non-negative constraints on work-in-process (WIP). The decision variables are the production rates of two main machines and a standby machine, and influence the WIP levels, the inventory levels and the system's capacity, which is assumed to be described by a finite-state Markov chain. The objective of this paper is to minimise WIP and finished goods inventory costs; it also aims to respect the essential space–time during intervention on machine down, in order to minimise the possibility of the circumvention of protection devices or of the retraction of lockout/tagout procedures through a passive redundancy system. This paper therefore verifies the effect of passive redundancy on optimal stock levels. Given that an analytical or even a numerical solution of the problem is very difficult to find, and that we want to have a more realistic model for industries, we present a combined approach, which is presented based on a combination of analytical formalism, simulation modelling, design of experiments, and response surface methodology to optimise a transfer line with passive redundancy, producing one part type. The usefulness of the proposed approach is illustrated through a numerical example and a sensitivity analysis. [ABSTRACT FROM PUBLISHER]

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We present an analytical model to predict the magnetoelectric (ME) effect in multiferroic laminated plates consisting of piezoelectric material and giant magnetostrictive material (GMM). The nonlinear behavior of GMM is taken into account by employing a simple quadratic constitutive relation. Both static and dynamic cases are considered. It is found that: (1) the dependence of ME effect on the applied magnetic field is quite different from that reported in the previous analysis; and (2) one part of the induced electric field has a frequency that is double the driving frequency of the applied magnetic field. The results indicate that multiferroic laminated plates with GMM layers have potential applications in multipliers and energy harvesters. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to develop a new coupled mathematical model of angiogenesis (new blood vessel growth) and tumor growth to study cancer development and anti-angiogenesis therapy. The angiogenesis part assumes the capillary to be a viscoelastic continuum whose stress depends on cell proliferation or death, and the tumor part is a Darcy’s law model regarding the tumor mass as an incompressible fluid where the nutrient-dependent growth elicits volume change. For the coupled model, we provide both an inviscid analysis and a parameter sensitivity analysis of the angiogenesis model in response to a stationary hypoxic tumor, and a steady state analysis of the tumor growth in response to a fixed and long blood capillary. The analysis shows that the stable steady state tumor with an invading blood capillary exists if and only if the nutrient release rate divided by the decay rate is less than the tumor viable limit, and the full tumor encloses one part of the capillary in this steady state. Afterwards, we use the coupled model to simulate vascularized tumor growth and anti-angiogenesis therapy. The simulations show that the tumor tends to maximize the nutrient transfer by blood vessel co-option and the anti-angiogenesis treatment by using growth factor neutralizing antibodies would regress the neovasculature and shrink the tumor size. However, the shrunken tumor mass could survive by feeding on mature blood vessels that resist the treatment. This implies the limited efficacy of the anti-angiogenesis monotherapy and its effect on vessel normalization. [ABSTRACT FROM AUTHOR]

This paper presents a new study based on a machine learning technique, specifically an artificial neural network, for predicting systolic blood pressure through the correlation of variables (age, BMI, exercise level, alcohol consumption level, smoking status, stress level, and salt intake level). The study was carried out using a database containing a variety of variables/factors. Each database of raw data was split into two parts: one part for training the neural network and the remaining part for testing the performance of the network. Two neural network algorithms, back-propagation and radial basis function, were used to construct and validate the prediction system. According to the experiment, the accuracy of our predictions of systolic blood pressure values exceeded 90%. Our experimental results show that artificial neural networks are suitable for modeling and predicting systolic blood pressure. This new method of predicting systolic blood pressure helps to give an early warning to adults, who may not get regular blood pressure measurements that their blood pressure might be at an unhealthy level. Also, because an isolated measurement of blood pressure is not always very accurate due to daily fluctuations, our predictor can provide the predicted value as another figure for medical staff to refer to. [ABSTRACT FROM AUTHOR]

Andrews, Lewis, and Lovejoy studied arithmetic properties of partitions with designated summands that are defined on ordinary partitions by tagging exactly one part among parts with equal size. A bipartition of n is an ordered pair of partitions (π1; π2) with the sum of all of the parts being n. In this paper, we investigate arithmetic properties of bipartitions with designated summands. Let PD-2(n) denote the number of bipartitions of n with designated summands. We establish several Ramanujan-like congruences and an infinite family of congruences modulo 9 satisfied by PD-2(n). [ABSTRACT FROM AUTHOR]

Objective: A major issue facing all health systems is improving population health while at the same time responding to both growing patient numbers and needs and developing and retaining the health care workforce. One policy response to workforce shortages has been the development of advanced clinical practice roles. In the context of an English national policy promoting such roles in the health service, we explored senior managers' and senior clinicians' perceptions of factors at the organization level that support or inhibit the introduction of advanced clinical practice roles. The investigation was framed by theories of the diffusion of innovation and the system of professions. Methods: We conducted a qualitative interview study of 39 senior manager and clinicians in 19 National Health Service acute, community, mental health and ambulance organizations across a metropolitan area in 2019. Results: Small numbers of advanced clinical practice roles were reported, often in single services. Four main influences were identified in the development of advanced clinical practice roles: staff shortages (particularly of doctors in training grades) combined with rising patient demand, the desire to retain individual experienced staff, external commissioners or purchasers of services looking to shape services in line with national policy, and commissioner-funded new roles in new ambulatory care services and primary care. Three factors were reported as enabling the roles: finance for substantive posts, evidence of value of the posts, and structural support within the organization. Three factors were perceived as inhibiting developing the roles: confusion and lack of knowledge amongst clinicians and managers, the availability of finance for the roles, and a nervousness (sometimes resistance) to introducing the new roles. Conclusions: While the national policy was to promote advanced clinical practice roles, the evidence suggested there was and would continue to be limited implementation at the operational level. Development scenarios that introduced new monies for such roles reduced some of the inhibiting factors. However, where the introduction of roles required funding to move from one part of a service to another, and potentially from one staff group to another, the growth of these roles was and is likely to be contested. In such scenarios, research and business evidence of relative advantage will be important, as too will be supporters in powerful positions. The paucity of publicly available evidence on the effectiveness of advanced clinical practice roles across the specialties and professions in different contexts requires urgent attention. [ABSTRACT FROM AUTHOR]

The manufacturing industry has been pursuing an efficient and economical assembly system. By considering assembly line balancing (ALB) and part feeding (PF) as an integrated problem and programming them simultaneously opens additional opportunities to improve the performance of the entire assembly system. However, the integrated ALB and PF problem is a non-deterministic polynomial (NP) hard problem. This implies that exact solutions cannot be obtained in a reasonable computation time and its near-optimal solutions can only be realised by meta-heuristics. In this study, we propose a novel bi-level multi-objective genetic algorithm (NBMGA) to solve the integrated ALB and PF problem. First, a bi-level mathematical model is established to simultaneously minimise the number of stations and workload smoothness of ALB in the upper level as well as the number of supermarkets of PF in the lower level. Second, the NBMGA with two modified strategies, including extending fitness evaluation and adaptive termination condition, is designed for problem solving. Finally, a series of computational experiments are conducted to demonstrate the efficacy of the proposed algorithm. The computational results indicate that the proposed algorithm outperforms the bi-level nondominated sorting genetic algorithm (NSGA) II in terms of the approximation to the true frontier without sacrificing computational efficiency. [ABSTRACT FROM AUTHOR]

As one part of our life, there are many different types of security threats in social network, and the virtual assets of social networking users has become the attack target. It is of great importance to use security patches in social network to offset the security threats. However, the dissemination of security patches will bring challenges to energy consumptions and network resources which are limited in social networks. In this paper, we will construct a novel optimal dissemination strategy based on differential game to get the desired equilibrium between security risks and resource consumption. The optimal dissemination rate is obtained from the Nash equilibrium solution. Simulation analysis will be given to illustrate that resource consumption and virtual assets loss can be reduced based on the proposed scheme. [ABSTRACT FROM AUTHOR]

In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia. [ABSTRACT FROM AUTHOR]

Cliodynamics is a still a relatively new research area with the purpose of investigating and modelling historical processes. One of its first important mathematical models was proposed by Turchin and called "Demographic-Fiscal Model" (DFM). This DFM was one of the first and is one of a few models that link population with state dynamics. In this work, we propose a possible alternative to the classical Turchin DFM, which contributes to further model development and comparison essential for the field of cliodynamics. Our "Demographic-Wealth Model" (DWM) aims to also model link between population and state dynamics but makes different modelling assumptions, particularly about the type of possible taxation. As an important contribution, we employ tools from nonlinear dynamics, e.g., existence theory for periodic orbits as well as analytical and numerical bifurcation analysis, to analyze the DWM. We believe that these tools can also be helpful for many other current and future models in cliodynamics. One particular focus of our analysis is the occurrence of Hopf bifurcations. Therefore, a detailed analysis is developed regarding equilibria and their possible bifurcations. Especially noticeable is the behavior of the so-called coexistence point. While changing different parameters, a variety of Hopf bifurcations occur. In addition, it is indicated, what role Hopf bifurcations may play in the interplay between population and state dynamics. There are critical values of different parameters that yield periodic behavior and limit cycles when exceeded, similar to the "paradox of enrichment" known in ecology. This means that the DWM provides one possible avenue setup to explain in a simple format the existence of secular cycles, which have been observed in historical data. In summary, our model aims to balance simplicity, linking to the underlying processes and the goal to represent secular cycles. [ABSTRACT FROM AUTHOR]

Many studies have addressed supply chain that shows the importance of the subject and the competition in the supply chain consisting of several companies. The previous studies address the issue of reducing the Bullwhip Effect in the supply chain, which is possible by predicting the correct amount of customer demand. This paper improves the accuracy of the model prediction and reduces the existing error in the previous models to attain an accurate and very close-to-reality forecast and also to reduce the Bullwhip Effect in the supply chain. Literature shows the absence of research on the presentation of a metaheuristic algorithm consisting of a neural network and bat algorithm to forecast supply chain demand in manufacturing companies; therefore, this article is innovative. On the other hand, no researchers have addressed Bullwhip Effect reduction using mixed metaheuristic algorithms. Therefore, this article improves the previous models, reduces the number of errors in demand forecasting, and reduces the Bullwhip Effect. For this purpose, the scalable gradient algorithm method is used for better network training. The results indicate the optimal performance of neural network training with a comparable gradient and bat algorithm on reducing the Bullwhip Effect. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to discuss the mathematical modelling of a compliance-assisted flapping mechanism and morphable structures for an UAV. Design/methodology/approach: A compliance-assisted flapping wing was designed and modelled mathematically, and signals for the corresponding curves were calculated. The actual wing tip trace of a hummingbird was taken, and variables a, b, h and k were calculated from the image. This data was given to the mathematical model for plotting the graph, and the curve was compared with the input curve. The wing frame and mechanism for control surfaces using morphing is modelled along with single pivoted spine for centre of gravity augmentation and flight orientation control. Findings: The model efficiently approximates the 2D path of the wing using line segments using the muscle and compliance mechanism. Practical implications: Using a compliance-assisted flapping mechanism offers practical advantages. It allows us to synchronize the flapping frequency with the input signal frequency, ensuring efficient operation. Additionally, the authors can enhance the torque output by using multiple muscle strands, resulting in a substantial increase in the system's torque-to-weight ratio. This approach proves to be more favourable when compared to conventional methods involving motors or servos, ultimately offering a more efficient and robust solution for practical application. Social implications: This model focuses on creating a flexible and tunable mechanism that can at least trace four types of wing traces from the same design, for shifting from one mode of flight to another. Originality/value: Conventional ornithopter flapping mechanisms are gear or servo driven and cannot trace a wing tip, but some can trace complicated curves, but only one at a time. This model can trace multiple curves using the same hardware, allowing the user to program the curve based on their needs or bird. The authors may vary the shape of the wing tip trace to switch between forward flight, hovering, backward flying, etc., which is not conceivable with any traditional flapping mechanism. [ABSTRACT FROM AUTHOR]

The graph AG(R) of a commutative ring R with identity has an edge linking two unique vertices when the product of the vertices equals the zero ideal and its vertices are the nonzero annihilating ideals of R. The annihilatingideal graph with respect to an ideal (I), which is denoted by AGI (R), has distinct vertices K and J that are adjacent if and only if KJ ⊆ I. Its vertices are {K | KJ ⊆ I for some ideal J and K, J * I, K is a ideal of R}. The study of the two graphs AGI (R) and AG(R/I) and extending certain prior findings are two main objectives of this research. This studys among other things, the findings of this study reveal that AGI (R) is bipartite if and only if AGI (R) is triangle-free. [ABSTRACT FROM AUTHOR]

Assembly sequence planning (ASP) is an indispensable and important step in the intelligent assembly process, and aims to solve the optimal assembly sequence with the shortest assembly time as its optimization goal. This paper focuses on modular cabin construction for large cruise ships, tackling the complexities and challenges of part assembly during the process, based on real engineering problems. It introduces the multiple optimal solutions genetic algorithm (MOSGA). The MOSGA analyzes product constraints and establishes a mathematical model. Firstly, the traditional genetic algorithm (GA) is improved in the case of falling into the local optimum when facing complex problems, so that it can jump out of the local optimum under the condition of satisfying the processing constraints and achieve the global search effect. Secondly, the problem whereby the traditional search algorithm converges to the unique optimal solution is solved, and multiple unique optimal solutions that are more suitable for the actual assembly problem are solved. Thirdly, for a variety of restrictions and emergencies that may occur during the assembly process, the assembly sequence flexible planning (ASFP) method is introduced so that each assembly can be flexibly adjusted. Finally, an example is used to verify the feasibility and effectiveness of the method. This method improves the assembly efficiency and the diversity of assembly sequence selection, and can flexibly adjust the assembly sequence, which has important guiding significance for the ASP problem. [ABSTRACT FROM AUTHOR]

The widely observed positive bias on self-evaluation is mainly explained by the self-enhancement motivation which minimizes negative feedbacks and emphasizes positive ones. Recent agent based simulations suggest that a positive bias also emerges if the sensitivity to feedbacks decreases when the self-evaluation increases. This paper proposes a simple mathematical model in which these different biases are integrated. Moreover, it describes an experiment (N = 1509) confirming that the sensitivity to feedbacks tends to decrease when self-evaluation increases and that a directly related positive bias is detected. [ABSTRACT FROM AUTHOR]

We study a trilinear singular integral form acting on twodimensional functions and possessing invariances under arbitrary matrix dilations and linear modulations. One part of the motivation for introducing it lies in its large symmetry groups acting on the Fourier side. Another part of the motivation is that this form stands between the bilinear Hilbert transforms and the first Calderón commutator, in the sense that it can be reduced to a superposition of the former, while it also successfully encodes the latter. As the main result we determine the exact range of exponents in which the Lp estimates hold for the considered form. [ABSTRACT FROM AUTHOR]

Iterative ensemble smoothers have been widely used for calibrating simulators of various physical systems due to the relatively low computational cost and the parallel nature of the algorithm. However, iterative ensemble smoothers have been designed for perfect models under the main assumption that the specified physical models and subsequent discretized mathematical models have the capability to model the reality accurately. While significant efforts are usually made to ensure the accuracy of the mathematical model, it is widely known that the physical models are only an approximation of reality. These approximations commonly introduce some type of model error which is generally unknown and when the models are calibrated, the effects of the model errors could be smeared by adjusting the model parameters to match historical observations. This results in a bias estimated parameters and as a consequence might result in predictions with questionable quality. In this paper, we formulate a flexible iterative ensemble smoother, which can be used to calibrate imperfect models where model errors cannot be neglected. We base our method on the ensemble smoother with multiple data assimilation (ES-MDA) as it is one of the most widely used iterative ensemble smoothing techniques. In the proposed algorithm, the residual (data mismatch) is split into two parts. One part is used to derive the parameter update and the second part is used to represent the model error. The proposed method is quite general and relaxes many of the assumptions commonly introduced in the literature. We observe that the proposed algorithm has the capability to reduce the effect of model bias by capturing the unknown model errors, thus improving the quality of the estimated parameters and prediction capacity of imperfect physical models. [ABSTRACT FROM AUTHOR]

A virtual synchronous generator (VSG) strategy can introduce the rotational inertia and damping characteristics of the synchronous generator to the static inverter, e.g., PV, wind generation, and ESS, which are used to enhance the system frequency support characteristics of the micro-grid. However, under various operations of the VSG, the inertia and damping support capabilities are different, and the conventional VSG strategy with a fixed control coefficient sacrifices a certain degree of dynamic regulation performance with less robustness. This research proposes an improved VSG strategy with adaptive inertia and damping coefficients to increase the flexibility of VSG. To this end, a mathematical model is first established to analyze the impact of various parameters on the characteristics of VSG, and then the root trajectory is used to explore the impacts of various rotational inertia and damping coefficients on the stability ofthe VSG system. Second, an improved control strategy with adaptive inertia and damping coefficients is proposed based on the characteristics of the second- order system and the system frequency deviations. Finally, a simulation system with the VSG is constructed based on MATLAB/Simulink. The effectiveness of the proposed control strategy is verified by comparing the simulation results to the conventional control strategy with the fixed control coefficients under over- frequency and under-frequency disturbances. [ABSTRACT FROM AUTHOR]

This paper presents a novel mathematical model to determine the minimum cost for the design of reinforced-concrete strap combined footings under biaxial bending, with each column using a genetic algorithm. The pressure is assumed to be linearly distributed along the contact area. This study comprises two steps: firstly, identifying the smallest ground contact area, and secondly, minimizing the cost. The methodology integrates moment, bending shear, and punching shear calculations according to the ACI standard. Some authors present a smaller area (but limited to one or two property lines) and the design considers that the thickness of the footings and beam are equal, and do not show the lower cost of a strap combined footing; generally, the beam has a greater thickness than the footings and therefore the footings would have an unnecessary thickness that would generate a higher cost. A numerical example is shown to find the lowest cost for the design of strap combined footings considering four different conditions such as square footings and other limitation at the ends of the footings. The minimum area does not guarantee that it is the lowest cost. The proposed model is versatile, applicable to T-shaped and rectangular combined footings, and is not restricted to specific property lines. The contributions include eliminating trial and error practices, accommodating various design conditions, and emphasizing equilibrium in the derived equations. The model is adaptable to different building codes, offering a comprehensive approach to achieving optimal design and cost considerations for strap combined footings. [ABSTRACT FROM AUTHOR]

In recent years, path dependence has gained increasing scientific attention in many disciplines, leading to various new concepts and notations, such as path creation or path plasticity. However, if mathematical arguments are used, they are based on the early works by Brian W. Arthur and Paul A. David, usually referring to the mathematical concept of ergodicity. We extend their mathematical framework and develop a graphical representation of systems that allows for a metaphorical discussion of system behaviors beyond the original cases, especially in evolving systems, and the inclusion of the recently developed concepts within path dependence. Visualizations are used to explain the definition and characteristics of seven types of path dependence: lock-in, path-breaking, path-furrowing, path plasticity, path formation, path creation, and path selection. Although these visualizations are explained verbally and can be understood without a mathematical expertise, a mathematical model is used to generate them. The deduction of the metaphorical concept from a mathematical model guarantees the completeness of the identified processes and the rigor in their categorization as well as the identification of respective characteristics for their distinction. However, the aim of the paper is to provide an illustrative concept that allows researchers to classify and structure the various path-dependent processes they observe in their application. While five of the identified processes are in line with concepts from the literature and are defined accordingly, we also detect a sixth process that is new to the literature so far: path-furrowing. Moreover, slightly deviating from the literature, we define path selection as the possibility to choose a path intentionally, thereby focusing on the mindful choice of options. [ABSTRACT FROM AUTHOR]

COVID-19 has substantially impacted health systems and the global economy. Moreover, it is more likely to have a detrimental influence on unstable nations than on more stable ones. All these consequences encouraged investigators to develop mathematical models to predict new cases, fatalities, and recoveries. These models allow a better understanding of the reasons and mechanisms of infection spread and preventive methods. In addition, these models help us understand the infection's origin, mode of transmission, and the impact of national responses on these variables. On the other hand, the efficacy and accuracy of these models during the COVID-19 pandemic are questionable. This review highlights several types of predictive models for forecasting the transmission of infectious diseases. Despite the crucial role of mathematical models in understanding outbreaks, most models fail because of the misunderstanding of their assumptions or the misuse of the best model for the targeted scenario. [ABSTRACT FROM AUTHOR]

We aimed to explore managerial and project staff perceptions of the pilot implementation of an algorithm-supported care navigation model, targeting people at risk of hospital readmission. The pilot was implemented from May to November 2017 at a Victorian health service (Australia) and provided to sixty-five patients discharged from the hospital to the community. All managers and the single clinician involved participated in a semi-structured interview. Participants (n = 6) were asked about their perceptions of the service design and the enablers and barriers to implementation. Interviews were transcribed verbatim and analysed according to a framework approach, using inductive and deductive techniques. Constructed themes included the following: an algorithm alone is not enough, the health service culture, leadership, resources and the perceived patient experience. Participants felt that having an algorithm to target those considered most likely to benefit was helpful but not enough on its own without addressing other contextual factors, such as the health service's capacity to support a large-scale implementation. Deductively mapping themes to the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework highlighted that a formal facilitation would be essential for future sustainable implementations. The systematic identification of barriers and enablers elicited critical information for broader implementations of algorithm-supported models of care. [ABSTRACT FROM AUTHOR]

This study introduces a mathematical model for electrolytic chemical reactions, employing an energy variation approach grounded in classical thermodynamics. Our model combines electrostatics and chemical reactions within well-defined energetic and dissipative functionals. Extending the energy variation method to open systems consisting of charge, mass, and energy inputs, this model explores energy transformation from one form to another. Electronic devices and biological channels and transporters are open systems. By applying this generalized approach, we investigate the conversion of an electrical current to a proton flow by cytochrome c oxidase, a vital mitochondrial enzyme contributing to ATP production, the 'energetic currency of life'. This model shows how the enzyme's structure directs currents and mass flows governed by energetic and dissipative functionals. The interplay between electron and proton flows, guided by Kirchhoff's current law within the mitochondrial membrane and the mitochondria itself, determines the function of the systems, where electron flows are converted into proton flows and gradients. This important biological system serves as a practical example of the use of energy variation methods to deal with electrochemical reactions in open systems. We combine chemical reactions and Kirchhoff's law in a model that is much simpler to implement than a full accounting of all the charges in a chemical system. [ABSTRACT FROM AUTHOR]

This article proposes an interconnected framework, Ways of thinking in STEM-based Problem Solving, which addresses cognitive processes that facilitate learning, problem solving, and interdisciplinary concept development. The framework comprises critical thinking, incorporating critical mathematical modelling and philosophical inquiry, systems thinking, and design-based thinking, which collectively contribute to adaptive and innovative thinking. It is argued that the pinnacle of this framework is learning innovation, involving the generation of powerful disciplinary knowledge and thinking processes that can be applied to subsequent problem challenges. Consideration is first given to STEM-based problem solving with a focus on mathematics. Mathematical and STEM-based problems are viewed here as goal-directed, multifaceted experiences that (1) demand core, facilitative ways of thinking, (2) require the development of productive and adaptive ways to navigate complexity, (3) enable multiple approaches and practices, (4) recruit interdisciplinary solution processes, and (5) facilitate the growth of learning innovation. The nature, role, and contributions of each way of thinking in STEM-based problem solving and learning are then explored, with their interactions highlighted. Examples from classroom-based research are presented, together with teaching implications. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to assess whether a music therapy (MT) intervention could improve memory decline in older adults with and without cognitive impairment. A dual-retrieval model of episodic memory was employed to estimate memory processes. Methods: Forty-three older adults with a mean age of 76.49 years (n = 25 with Alzheimer's disease (AD) and mixed dementia, and n = 18 healthy older adults) were randomly selected for the experimental and control groups. The study design was a double-blind randomized controlled clinical trial and a certified music therapist delivered the MT. The primary outcomes were measures of working memory, episodic memory, and autobiographical memory. Results: In the primary outcome measures, MT effects were restricted to episodic memory measures like the Figure Memory Test of the BCSB and the Speech and Sing Memory Test. In both tests, the experimental group improved from pre-test to post-test in delayed recall, but in the Speech and Sing Memory Test, the improvement was restricted to the AD and mixed dementia group. MT had no effects on the secondary outcome measures. Conclusions: These findings suggest that a structured MT intervention can be promising for rehabilitating episodic memory in older adults with dementia. [ABSTRACT FROM AUTHOR]

The aim of this paper is to provide a robust framework to assist researchers in deciding which methods to use, depending on the problem at hand, in order to estimate the probability of failure of marine structural parts that are subjected to variable loads (both hull-girder and local pressure loads) that exhibit uncertainties in their material properties and that involve fabrication-related uncertainties. The limitations of analytical approaches both in deterministic mathematical modeling (strength formulas) and probabilistic estimation will be provided, and respective computational tools will be demonstrated (FEA and Monte Carlo simulation). The approach is showcased in flat and bow-defected rectangular plates through analytical and numerical approaches. [ABSTRACT FROM AUTHOR]

In the current research papers on multi-agent (multi-person) scheduling, a person's objective function is always considered as a cost function on scheduling, whereas a cooperative profit function is defined to serve as his objective one in this paper. In the two-person scheduling problem addressed in this paper, the two persons jointly order a common operational time interval of a single machine. Each person needs to process a set of his own jobs in that time window. The same objective function of each person still relies on the sequence of all the jobs of both persons since each part of the function is determined by some given parameters except one part assumed to be a given multiple of the total completion time of his own jobs. The two persons have to negotiate a job sequence and determine the (related) final solution on cooperative profit allocation. Such a two-person scheduling problem is essentially a cooperative game. An algorithm is designed to yield the cooperative-profit-based Pareto efficient solution set acting as the first game-based solution concept in this paper. The parallelized version of the algorithm is also developed. The second game-based solution concept is the Shapley value appropriate for the above cooperative-game situation on two-person scheduling. Several instances are presented and analyzed to reveal the necessity to employ the two solution concepts together. [ABSTRACT FROM AUTHOR]

Scheduling problem for the hybrid flow shop scheduling problem (HFSP) followed by an assembly stage considering aging effects and additional preventive and maintenance activities is studied in this paper. In this production system, a number of products of different kinds are produced. Each product is assembled with a set of several parts. The first stage is a hybrid flow shop to produce parts. All machines can process all kinds of parts in this stage but each machine can process only one part at a time). The second stage is a single assembly machine or a single assembly team of workers. The aim is to schedule the parts on the machines and assembly sequence and also determine when the preventive maintenance activities get done in order to minimize the completion time of all products (makespan). A mathematical modeling is presented and its validation is shown by solving a small scale example. This problem has been proved to be strongly NP-hard, then in order to solve the problem in medium and large scales, four heuristic algorithms is proposed based on the Johnson’s algorithm. The numerical experiments are used to run the mathematical model and evaluate the performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

The authors propose a mathematical model for a multi-channel queueing system with feedback in which one part of calls instantaneously enters the system for repeated service and the other part either retries in some random time or finally leaves the system. The behavior of the serviced calls is randomized. Both exact and asymptotic methods are developed to calculate the characteristics of the proposed model. The results of numerical experiments are presented. [ABSTRACT FROM AUTHOR]

Rapid urbanization, intensified industrialization, rise of income, and a more sophisticated form of consumerism are leading to an increase in the amount and toxicity of waste all over the world. Whether reused, recycled, incinerated or put into landfill sites, the management of household and industrial waste yield financial and environmental costs. This paper presents a modeling approach that can be used for designing one part of recycling logistics network through defining optimal locations of collection points, and possible optimal scheduling of vehicles for collecting recyclables. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to discuss the characteristics of several stochastic simulation methods applied in computation issue of structure health monitoring (SHM). Design/methodology/approach – On the basis of the previous studies, this research focusses on four promising methods: transitional Markov chain Monte Carlo (TMCMC), slice sampling, slice-Metropolis-Hasting (M-H), and TMCMC-slice algorithm. The slice-M-H is the improved slice sampling algorithm, and the TMCMC-slice is the improved TMCMC algorithm. The performances of the parameters samples generated by these four algorithms are evaluated using two examples: one is the numerical example of a cantilever plate; another is the plate experiment simulating one part of the mechanical structure. Findings – Both the numerical example and experiment show that, identification accuracy of slice-M-H is higher than that of slice sampling; and the identification accuracy of TMCMC-slice is higher than that of TMCMC. In general, the identification accuracy of the methods based on slice (slice sampling and slice-M-H) is higher than that of the methods based on TMCMC (TMCMC and TMCMC-slice). Originality/value – The stochastic simulation methods evaluated in this paper are mainly two categories of representative methods: one introduces the intermediate probability density functions, and another one is the auxiliary variable approach. This paper provides important references about the stochastic simulation methods to solve the ill-conditioned computation issue, which is commonly encountered in SHM. [ABSTRACT FROM AUTHOR]

Flowshop scheduling methods that appear in the literature assume that products are processed in either batch mode or cyclic mode. In batch mode, a product starts after another product is completely processed. On the other hand, in cyclic mode, products are run in mixed mode with unit transfer. In this paper, a new scheduling method, the batch-cyclic scheduling method, is proposed to schedule the products. In the proposed method, multiple sets of products (Cyclic Sets) are selected first and then products in each cyclic set are run in mixed mode. Overall, the general solution approach consists of three phases: (1) family formation based on processing similarity; (2) subfamily formulation based on a processing time dissimilarity (proposed mathematical model); (3) product scheduling using the batch-cyclic method (proposed mathematical model). As in the cyclic method, batch-cyclic scheduling is feasible when setup times are negligible. Due to the lack of work in this newly proposed batch-cyclic method, it is compared with the batch method. Additionally, the performance of the three-phase approach is compared with the two-phase approach using 27 scenarios. The results show that the proposed three-phase approach minimises the number of machines and lowers makespan when the bottleneck machine shifts. [ABSTRACT FROM AUTHOR]

Despite being a relatively new concept, psychiatric comorbidity, i.e. the co-occurrence of two or more mental disorders, has become widespread in clinical practice and psychiatric research. In this article, we trace the origin of the concept of psychiatric comorbidity, discuss the conceptual literature and point to basic problems concerning inadequate definition of the concept, differential diagnostic issues, and reification of mental disorders. We illustrate how these problems may have consequences for diagnostic assessment in current clinical practice and psychiatric research. To address some of the problems related to psychiatric comorbidity, we discuss potential principles for assessing psychiatric comorbidity. Inspired by Feinstein's original concept of comorbidity in general medicine and his differential diagnostic principles, we emphasize the importance of independence of mental disorders when assessing psychiatric comorbidity. We suggest that knowledge of trait v. state conditions and of the multitudinous clinical manifestations beyond what is captured in the diagnostic manuals may be helpful for assessing the independence of mental disorders and thus psychiatric comorbidity. We further argue that a more hierarchical diagnostic system and explicit exclusionary rules could improve clinical practice and research by reducing informational complexity and combating unwarranted psychiatric comorbidity. [ABSTRACT FROM AUTHOR]

Aim: To describe a small multidisciplinary team's experience of the process of embedding nurse‐led supportive care into an existing Chronic Obstructive Pulmonary Disease outpatient service. Design: Case study methodology Methods: Data were collected from multiple sources including key documents and semi‐structured interviews with healthcare professionals (n = 6) conducted between June and July 2021. A purposive sampling strategy was used. Content analysis was applied to key documents. Interviews were transcribed verbatim and analysed using an inductive approach. Results: Subcategories under the four‐stage process were identified from the data. Assessment: evidence of needs of patients with Chronic Obstructive Pulmonary Disease; gaps in care and evidence of other models of supportive care. Planning: setting the supportive care service structure and intention; resources and funding; leadership, specialization and respiratory/palliative care roles. Implementation: relationships and trust; embedding supportive care and communication. Evaluation: benefits and positive outcomes for staff and patients, and, improvements and future considerations for supportive care in the COPD service. Conclusion: A collaboration between respiratory and palliative care services resulted in successfully embedding nurse‐led supportive care in a small outpatient service for patients with Chronic Obstructive Pulmonary Disease. Nurses are well placed to lead new models of care that aim to address unmet biopsychosocial‐spiritual needs of patients. More research is needed to evaluate nurse‐led supportive care in Chronic Obstructive Pulmonary Disease and other chronic illness settings; the effectiveness of nurse‐led supportive care from the perspective of patients and caregivers and the impact of nurse‐led supportive care on health service usage. Patient or Public Contribution: The development of the model of care is informed by ongoing discussions with patients with COPD and their caregivers. Data availability statement: Research data are not shared (due to ethical restrictions). Impact Embedding nurse‐led supportive care in an existing Chronic Obstructive Pulmonary Disease outpatient service is achievable.Nurses with clinical expertise can lead innovative models of care that address the unmet biopsychosocial‐spiritual needs of patients with conditions such as Chronic Obstructive Pulmonary Disease.Nurse‐led supportive care may have utility and relevance in other chronic disease contexts. [ABSTRACT FROM AUTHOR]

The Multi-state EHR-based Network for Disease Surveillance (MENDS) developed a pilot electronic health record (EHR) surveillance system capable of providing national chronic disease estimates. To strategically engage partner sites, MENDS conducted a latent class analysis (LCA) and grouped states by similarities in socioeconomics, demographics, chronic disease and behavioral risk factor prevalence, health outcomes, and health insurance coverage. Three latent classes of states were identified, which inform the recruitment of additional partner sites in conjunction with additional factors (e.g. partner site capacity and data availability, information technology infrastructure). This methodology can be used to inform other public health surveillance modernization efforts that leverage timely EHR data to address gaps, use existing technology, and advance surveillance. [ABSTRACT FROM AUTHOR]

This paper assesses the different models, in conjunction with the different theories surrounding the distinction and interdependencies between space- and capital markets. First, the theory of space- and capital markets is discussed with reference to two models, the FDW and the REEFM models. The FDW model provides a diagrammatic explanation of the behaviour of the property market, while the REEFM is an econometric model based on statistical principles that are able to forecast property-market behaviour by interpreting specific given variables. The REEFM model as the perceived more sophisticated model, untested in South Africa, was then analysed to test its applicability in the South African context. The findings confirmed the applicability of the model, although one part is not confirmed and is suggested for further research. [ABSTRACT FROM AUTHOR]

In this paper we consider a model shape optimization problem. The state variable solves an elliptic equation on a domain with one part of the boundary described as the graph of a control function. We prove higher regularity of the control and develop a priori error analysis for the finite element discretization of the shape optimization problem under consideration. The derived a priori error estimates are illustrated on two numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, a scheduling problem for a two-stage production system including machining operations and assembly operations is studied. In this system, a number of products of different kinds are produced. Each product is assembled with a set of several parts. The first stage is a hybrid flow shop to produce parts. All machines can process all kinds of parts in this stage, but each machine can process only one part at a time. The second stage is a single assembly machine or a single assembly team of workers. The considered objective is to minimize the completion time of all products (makespan). A mathematical modeling is presented, and since this problem has been proved strongly nondeterministic polynomial-time hard, a series of heuristic algorithms based on the basic idea of Johnson algorithm is proposed. Also, two lower bounds is introduced and improved to evaluate the final solution obtained from heuristic algorithms. The numerical experiments are used to evaluate the performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Abstract: This paper develops a model for determining ordering/trade-credit policy of a supply chain, where one supplier sells a product to a retailer, who faces a deterministic demand, and may offer the retailer two types of trade credit contracts: a “one-part” or a “two-part” contract. We discuss the existence of the optimal solution to the model, and provide a simple algorithm for finding the optimal ordering and trade credit policy of two members. We specify the conditions under which it is beneficial in reducing operational cost for the supplier to offer the two trade credit contracts. Through numerical experiments, we reveal that it is more superior in reducing operational cost for the supplier to offer a two-part credit than to offer a one-part credit, which can be extended to a multi-part credit. The sensitivity analysis is presented at the end of the paper. [Copyright &y& Elsevier]

This study examined the relationships among adolescents’ emotion regulation strategies (suppression and cognitive reappraisal), self-concept, and internalizing problems using structural equation modeling. The sample consisted of 438 early adolescents (13 to 15 years old) in Taiwan, including 215 boys and 223 girls. For both boys and girls, suppression was negatively associated, and cognitive reappraisal was positively associated with self-concept. Self-concept negatively predicted adolescents’ internalizing problems. The findings support the hypothesis that self-concept mediates the relationship between emotion regulation and internalizing problems. These findings support generalization of one part of Cicchetti’s and Toth’s model of the development of internalizing problems to an Asian culture. [ABSTRACT FROM AUTHOR]

The present study investigated factors that explain patient trust in health technology and the relationship between patient trust in technology and trust in their care provider. Sociotechnical systems theory states that changes in one part of the system are likely related to other parts of the system. Therefore, attitudes about technologies, like trust, are likely related to other aspects of the system. Contributing to appropriate trust at the technological, interpersonal, and system levels can potentially lead to positive health outcomes. The study described in this manuscript used data collected from 101 patients with a Trust in Medical Technology instrument. The instrument measured patients’ trust in (1) their providers, (2) the technology, and (3) how their providers used the technology. Measure 3 was positively associated with measures 1 and 2, while measures 1 and 2 were not positively or negatively associated with one another. These results may indicate that patient assessments of the trustworthiness of care providers and technologies are based on their observations of how providers use technologies. Practitioner Summary: Though patients are not active users of technologies in health care, the results of this study show that their perceptions of how providers use technology are related to their trust in both technology and the care provider. Study findings have implications for how trust is conceptualised and measured in interpersonal relationships and in technologies. [ABSTRACT FROM AUTHOR]

Ronald Ross and George Macdonald are credited with developing a mathematical model of mosquito-borne pathogen transmission. A systematic historical review suggests that several mathematicians and scientists contributed to development of the Ross-Macdonald model over a period of 70 years. Ross developed two different mathematical models, Macdonald a third, and various "Ross-Macdonald" mathematical models exist. Ross-Macdonald models are best defined by a consensus set of assumptions. The mathematical model is just one part of a theory for the dynamics and control of mosquito-transmitted pathogens that also includes epidemiological and entomological concepts and metrics for measuring transmission. All the basic elements of the theory had fallen into place by the end of the Global Malaria Eradication Programme (GMEP, 1955-1969) with the concept of vectorial capacity, methods for measuring key components of transmission by mosquitoes, and a quantitative theory of vector control. The Ross-Macdonald theory has since played a central role in development of research on mosquito-borne pathogen transmission and the development of strategies for mosquito-borne disease prevention. [ABSTRACT FROM AUTHOR]