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This article justifies a historically grounded method for reading Romantic aesthetics in mathematical terms, and argues that the application of this method: 1) helps us to reread Romantic texts that both do and do not address infinity explicitly, beginning with theories of the sublime; 2) helps to clarify certain aspects of the Romantic inheritance in later modern poetry; and 3) allows us to ground critical treatments of poetry and mathematics in an early nineteenth-century moment at which aesthetics and poetics participate in mathematical debates. The article identifies a century-long "crisis of infinity" during which the concept of infinity lacked a stable mathematical definition and, for that reason among others, generated heated discussion within the discourses of religion, philosophy, mathematics, and aesthetics. In this context, the article excavates models of infinity animating key intellectual resources for Romantic and Victorian poetry and then uses these models to illuminate famously enigmatic moments in the canonical poetries of both periods, taking William Wordsworth and Robert Browning as key examples.

A user-centric location privacy trading framework, called ULPT, is constructed to facilitate location privacy trading between workers and the platform. Each worker can decide how much location privacy to disclose to the platform in an MCS task based on its own location privacy leakage budget $\xi$ . The higher $\xi$ is, the more privacy its reported location discloses. Accordingly, it receives higher payment from the platform as compensation. Besides, ULPT enables the platform to select a suitable set of winning workers to achieve desirable MCS service accuracy while taking into account its budget limit and worker privacy requirements. For this purpose, a heuristic algorithm is devised with a bounded optimality gap. As formally proved in this manuscript, ULPT guarantees a series of nice properties, including $\xi$ -privacy, $(\alpha, \beta)$ -accuracy, budget feasibility. Moreover, both rigorous theoretical analysis and extensive simulations are conducted to evaluate tradeoffs among these three.

We study bargaining models in discrete time with a finite number of players, stochastic selection of the proposing player, endogenously determined sets and orders of responders, and a finite set of feasible alternatives. The standard optimality conditions and system of recursive equations may not be sufficient for the existence of a subgame perfect equilibrium in stationary strategies (SSPE) in case of costless delay. We present a characterization of SSPE that is valid for both costly and costless delay. We address the relationship between an SSPE under costless delay and the limit of SSPEs under vanishing costly delay. An SSPE always exists when delay is costly, but not necessarily so under costless delay, even when mixed strategies are allowed for. This is surprising as a quasi SSPE, a solution to the optimality conditions and the system of recursive equations, always exists. The problem is caused by the potential singularity of the system of recursive equations, which is intimately related to the possibility of perpetual disagreement in the bargaining process.

In this paper, we highlight three issues that limit performance of machine learning on biomedical images, and tackle them through 3 case studies: 1) Interactive Machine Learning (IML): we show how IML can drastically improve exploration time and quality of direct volume rendering. 2) transfer learning: we show how transfer learning along with intelligent pre-processing can result in better Alzheimer's diagnosis using a much smaller training set 3) data imbalance: we show how our novel focal Tversky loss function can provide better segmentation results taking into account the imbalanced nature of segmentation datasets. The case studies are accompanied by in-depth analytical discussion of results with possible future directions.

Suppose that in a given planar circular region, there are some smart mobile evaders and we would like to find them using sweeping agents. We assume that each agent has a line sensor of length 2r. We propose procedures for designing cooperative sweeping processes that ensure the successful completion of the task, thereby deriving conditions on the sweeping velocity of the agents and their paths. Successful completion of the task means that evaders with a given limit on their velocity cannot escape the sweeping agents. A simpler task for the sweeping swarm is the confinement of the evaders to their initial domain. The feasibility of completing these tasks depends on geometric and dynamic constraints that impose a lower bound on the velocity that the sweeper swarm must have. This critical velocity is derived to ensure the satisfaction of the confinement task. Increasing the velocity above the lower bound enables the agents to complete the search task as well. We present results on the total search time as a function of the sweeping velocity of the swarm's agents given the initial conditions on the size of the search region and the maximal velocity of the evaders., arXiv admin note: text overlap with arXiv:1905.04006

There is sustained and widespread interest in understanding the limit, if any, to the human lifespan. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social security systems. A central question is whether the endpoint of the underlying lifetime distribution is finite. Recent analyses of data on the oldest human lifetimes have led to competing claims about survival and to some controversy, due in part to incorrect statistical analysis. This paper discusses the particularities of such data, outlines correct ways of handling them and presents suitable models and methods for their analysis. We provide a critical assessment of some earlier work and illustrate the ideas through reanalysis of semi-supercentenarian lifetime data. Our analysis suggests that remaining life-length after age 109 is exponentially distributed, and that any upper limit lies well beyond the highest lifetime yet reliably recorded. Lower limits to 95% confidence intervals for the human lifespan are around 130 years, and point estimates typically indicate no upper limit at all., Comment: 30 pages, including Appendix

We present a search for transient radio sources on timescales of 2 to 9 yr at 150 MHz. This search is conducted by comparing the first Alternative Data Release of the TIFR GMRT Sky Survey (TGSS ADR1) and the second data release of the LOFAR Two-metre Sky Survey (LoTSS DR2). The overlapping survey area covers 5570 $\rm{deg}^2$ on the sky, or 14 per cent of the total sky. We introduce a method to compare the source catalogues that involves a pair match of sources, a flux density cutoff to meet the survey completeness limit and a newly developed compactness criterion. This method is used to identify both transient candidates in the TGSS source catalogue that have no counterpart in the LoTSS catalogue and transient candidates in LoTSS without a counterpart in TGSS. We find that imaging artefacts and uncertainties and variations in the flux density scales complicate the transient search. Our method to search for transients by comparing two different surveys, while taking into account imaging artefacts around bright sources and misaligned flux scales between surveys, is universally applicable to future radio transient searches. No transient sources were identified, but we are able to place an upper limit on the transient surface density of $, 14 pages, 11 figures

A robust computer vision-based approach is developed to estimate the load asymmetry angle defined in the revised NIOSH lifting equation. The angle of asymmetry enables the computation of a recommended weight limit for repetitive lifting operations in a workplace to prevent lower back injuries. An open-source package OpenPose is applied to estimate the two-dimensional (2-D) locations of skeletal joints of the worker from two synchronous videos. Combining these joint location estimates, a computer vision correspondence and depth estimation method is developed to estimate the 3-D coordinates of skeletal joints during lifting. The angle of asymmetry is then deduced from a subset of these 3-D positions. Error analysis reveals unreliable angle estimates due to occlusions of upper limbs. A robust angle estimation method that mitigates this challenge is developed. We propose a method to flag unreliable angle estimates based on the average confidence level of 2-D joint estimates provided by OpenPose. An optimal threshold is derived that balances the percentage variance reduction of the estimation error and the percentage of angle estimates flagged. Tested with 360 lifting instances in a NIOSH-provided dataset, the standard deviation of angle estimation error is reduced from 10.13° to 4.99°. To realize this error variance reduction, 34% of estimated angles are flagged and require further validation.

We study the higher integrability of weights satisfying a reverse Hölder inequality ( ⨏ I u β ) 1 β ≤ B ⁢ ( ⨏ I u α ) 1 α {\biggl{(}\fint_{I}u^{\beta}\biggr{)}^{\frac{1}{\beta}}}\leq B{\biggl{(}\fint_{I}u^{\alpha}\biggr{)}^{\frac{1}{\alpha}}} for some B > 1 B>1 and given α < β \alpha , in the limit cases when α ∈ { - ∞ , 0 } \alpha\in\{-\infty,0\} and/or β ∈ { 0 , + ∞ } \beta\in\{0,+\infty\} . The results apply to the Gehring and Muckenhoupt weights and their corresponding limit classes.

The Qian–Sheng model is a system describing the hydrodynamics of nematic liquid crystals in the Q-tensor framework. When the inertial effect is included, it is a hyperbolic-type system involving a second-order material derivative coupling with forced incompressible Navier–Stokes equations. If formally letting the inertial constant [Formula: see text] go to zero, the resulting system is the corresponding parabolic model. We provide the result on the rigorous justification of this limit in [Formula: see text] with small initial data, which validates mathematically the parabolic Qian–Sheng model. To achieve this, an initial layer is introduced to not only overcome the disparity of the initial conditions between the hyperbolic and parabolic models, but also make the convergence rate optimal. Moreover, a novel [Formula: see text]-dependent energy norm is carefully designed, which is non-negative only when [Formula: see text] is small enough, and handles the difficulty brought by the second-order material derivative.

Teaching a multicultural classroom has always been challenging for educators. With the rush toward global standardization, there is a concern that uniformity in education will sacrifice students’ freedom in expressing their skills and knowledge. This problem can be seen in the way students are being assessed. The rapid growth of standardized tests and the demand to meet yearly progress thresholds are tangible examples of how assessments may limit the way students demonstrate their learning attainment. This article aims at presenting several alternatives teachers could take to implement Universal Design for Learning (UDL) and inclusive assessment principles in assessing multicultural classrooms. This analytic autoethnography study yielded three themes: providing options of assessment forms, providing accommodation in conducting assessments, and using the strength-based language in assessment feedback.

Negative handprints or hand-stencils, which occur in many prehistoric sites around the world, occupy a particular place in accounts of rock art. Although they frequently occur alongside paintings, their indexical status as imprints leads them to be treated separately from other types of representations that are more easily accepted as such. This article argues that the negative handprint operates as a kind of limit-case for definitions of art. I examine how it has given rise to imagined scenarios of making — what we might call primal scenes of art — by writers including Georges Bataille, Maurice Blanchot and Marguerite Duras. While its logic of presence invites us to think about it as a point of origin, a trace that connects us to our earliest human ancestors, I show how it can be read against that logic of presence through the lens of one particular ‘primal scene’, that imagined by Jean-Luc Nancy. In this reading, it is precisely the question of absence or distance that gives the handprint its status as a point of origin that undoes the very idea of origins.

Accurate estimation of remaining useful life (RUL) of industrial equipment can enable advanced maintenance schedules, increase equipment availability and reduce operational costs. However, existing deep learning methods for RUL prediction are not completely successful due to the following two reasons. First, relying on a single objective function to estimate the RUL will limit the learned representations and thus affect the prediction accuracy. Second, while longer sequences are more informative for modelling the sensor dynamics of equipment, existing methods are less effective to deal with very long sequences, as they mainly focus on the latest information. To address these two problems, we develop a novel attention-based sequence to sequence with auxiliary task (ATS2S) model. In particular, our model jointly optimizes both reconstruction loss to empower our model with predictive capabilities (by predicting next input sequence given current input sequence) and RUL prediction loss to minimize the difference between the predicted RUL and actual RUL. Furthermore, to better handle longer sequences, we employ the attention mechanism to focus on all the important input information during the training process. Finally, we propose a new dual-latent feature representation to integrate the encoder features and decoder hidden states, to capture rich semantic information in data. We conduct extensive experiments on four real datasets to evaluate the efficacy of the proposed method. Experimental results show that our proposed method can achieve superior performance over 13 state-of-the-art methods consistently.

In a decision which once again legitimates discriminatory welfare cuts, the UK Supreme Court has unanimously upheld the so-called ‘two-child limit’ for eligibility for child tax credit. The case co...

In this paper, first we prove some new refinements of discrete weighted inequalities with negative powers on finite intervals. Next, by employing these inequalities, we prove that the self-improving property (backward propagation property) of the weighted discrete Muckenhoupt classes holds. The main results give exact values of the limit exponents as well as the new constants of the new classes. As an application, we establish the self-improving property (forward propagation property) of the discrete Gehring class.

Although adaptation finance is increasing, the latest UNEP Adaptation Gap Report shows that it does not outweigh mounting adaptation costs. More funding is required, preferably for anticipatory adaptation. Closing the adaptation finance gap simultaneously requires a maximization of efforts to limit adaptation costs through ambitious mitigation and sustainable finance policies.

Support vector machines (SVMs) are powerful classifiers that have high computational complexity in the training phase, which can limit their applicability to large datasets. An effective approach to address this limitation is to select a small subset of the most representative training samples such that desirable results can be obtained. In this study, a novel instance selection method called border point extraction based on locality-sensitive hashing (BPLSH) is designed. BPLSH preserves instances that are near the decision boundaries and eliminates nonessential ones. The performance of BPLSH is benchmarked against four approaches on different classification problems. The experimental results indicate that BPLSH outperforms the other methods in terms of classification accuracy, preservation rate, and execution time. The source code of BPLSH can be found in https://github.com/mohaslani/BPLSH .

In this article we review a model of stochastic evolution under general noisy best-response protocols, allowing the probabilities of suboptimal choices to depend on their payoff consequences. We survey the methods developed by the authors which allow for a quantitative analysis of these stochastic evolutionary game dynamics. We start with a compact survey of techniques designed to study the long run behavior in the small noise double limit (SNDL). In this regime we let the noise level in agents' decision rules to approach zero, and then the population size is formally taken to infinity. This iterated limit strategy yields a family of deterministic optimal control problems which admit an explicit analysis in many instances. We then move in by describing the main steps to analyze stochastic evolutionary game dynamics in the large population double limit (LPDL). This regime refers to the iterated limit in which first the population size is taken to infinity and then the noise level in agents' decisions vanishes. The mathematical analysis of LPDL relies on a sample-path large deviations principle for a family of Markov chains on compact polyhedra. In this setting we formulate a set of conjectures and open problems which give a clear direction for future research activities.

The indoor scenes usually exhibit strong structural regularity; on the other hand, the local geometric features are scarce and difficult to be distinguished. The properties make the solutions of the existing global registration algorithms ambiguous. In addition, finding global optimal solution is usually computationally expensive. These problems make the global registration of indoor point clouds a challenging task. Based on the Manhattan-world assumption and color information, we propose a fast and effective algorithm for the global registration of indoor colored point clouds in this paper. We introduce the Manhattan-world assumption into the global registration of indoor point cloud to limit the number of all possible rotation solutions. As a result, our algorithm solves the problem very fast. Furthermore, we utilize the color information hierarchically to eliminate the ambiguity induced by the structural models. The limited rotation set is filtered by the global color histograms, and the final solution is evaluated by the local features. The experiments demonstrate that our algorithm can complete the global registration for the point clouds with hundreds of thousands of points in 0.1 second with comparable accuracy with others.

A vote-buying mechanism is such that each agent buys a quantity of votes x to cast for an alternative of her choosing, at a cost c(x), and the outcome is determined by the total number of votes cast for each alternative. In the context of binary decisions, we prove that the choice rules that can be implemented by vote-buying mechanisms in large societies are parameterized by a positive parameter rho, which measures the importance of individual preference intensities on the social choice: The limit with rho= 0 is majority rule, rho = 1 is utilitarianism, and rho?8 is the Rawlsian maximin rule. We show that any vote-buying mechanism with limit cost elasticity (1 rho)/rho as x?0 implements the choice rule defined by rho. The utilitarian efficiency of quadratic voting (Lalley and Weyl, 2016) follows as a special case.

A reaction-diffusion-ODE model for the Neolithic spread of farmers in Europe has been recently proposed in [7] . In this model, farmers are assumed to be divided into two subpopulations according to a mobility rule, namely, into sedentary and migrating farming populations. The conversion between the farming subpopulations depends on the total density of farmers and it is superimposed on the classical Lotka-Volterra competition model, so that it is described by a three-component reaction-diffusion-ODE system. In this article we consider a singular limit problem when the conversion rate tends to infinity and prove under appropriate conditions that solutions of the three component system converge to solutions of a two-component system with a linear diffusion and nonlinear degenerate diffusion.

Many states in recent decades enacted laws that limit the collection of property taxes. This study examines the impacts of New York State’s 2011 tax cap on education revenues and student achievemen...

Objective The objective was to identify sonographer perceptions of distractions and policies for improving obstetric sonography examinations (OBUS). Materials and Methods A survey, with closed- and open-ended questions, was sent to OBUS practicing members of the Society of Diagnostic Medical Sonography (SDMS). Descriptive analyses, including frequency distributions overall and by various groups, were performed. Chi-square analyses were used to examine the relationships between categorical variables, including level of perceived distraction, and concordance with policies. Results Of the 3525 accessed e-mails, 807 responses were eligible for analysis. Over half (62%) of the respondents reported no observer policy. Sonographers reported strong agreement with observer policies and desired limits on observers. Policy disagreement themes included number of observers, children observers, patient satisfaction, and patient truthfulness. Most sonographers reported existence of (85%) and strong agreement (97%) with recording policies. Disagreements centered around the strictness of policies, policy enforcement and notification, distraction of recording, medico-legal issues, and finding anomalies while being recorded. Conclusion Discrepancies existed between policies regarding observers and recording in OBUS. Sonographers both desired and agreed with protocols to limit distractions. However, there were concerns regarding stringency, notification, and enforcement of policies. Further research is needed to determine if policies help limit distractions during OBUS.

The methodology, formulating a reasonable task assignment to find the most suitable workers for a task and achieving the desired objectives, is the most fundamental challenge in spatial crowdsourcing. Many task assignment approaches have been proposed to improve the quality of crowdsourcing results and the number of task assignment and to limit the budget and the travel cost. However, these approaches have two shortcomings: (1) these approaches are commonly based on the attributes influencing the result of task assignment. However, different tasks may have different preferences for individual attributes; (2) the performance and efficiency of these approaches are expected to be improved further. To address the above issues, we proposed a task assignment approach in spatial crowdsourcing based on multiattribute decision-making (TASC-MADM), with the dual objectives of improving the performance as well as the efficiency. Specifically, the proposed approach jointly considers the attributes on the quality of the worker and the distance between the worker and the task, as well as the influence differences caused by the task’s attribute preference. Furthermore, it can be extended flexibly to scenarios with more attributes. We tested the proposed approach in a real-world dataset and a synthetic dataset. The proposed TASC-MADM approach was compared with the RB-TPSC and the Budget-TASC algorithm using the real dataset and the synthetic dataset; the TASC-MADM approach yields better performance than the other two algorithms in the task assignment rate and the CPU cost.

North Korea is well-known for the intense social control it imposes upon its citizens and foreign visitors. This social control serves to circumscribe interactions between the two groups, limit the...

Conflict analysis has become a hot issue in management science. In the context of conflict analysis, there are three attitudes for agents to describe the opinion, including supportive, opposite, and neutral. Then, the conflict situation is discussed and analyzed. In this paper, we propose an extended Pawlak conflict model concerning the trust mechanism to solve the problem of the reaching consensus process. Firstly, the degree of conflict is defined by the weights of agents considering the penalty factors, and an extended Pawlak conflict model is presented. Then, the trust recommendation mechanism is proposed to modify the opinions of agents and reach conflict consensus. Four kinds of feedback mechanism are discussed by using four perspectives: 1) without the penalty factors and no limit to the range of adjustments; 2) without the penalty factors and the attitude of agents vary from pessimistic to neutral; 3) with the penalty factors and no limit to the range of adjustments; 4) with the penalty factors and the attitude of agents vary from pessimistic to neutral. Furthermore, this paper presents a process of reaching consensus based on the trust recommendation mechanism for the conflict analysis problem. Finally, a case study is used to validate the effectiveness and superiority of the proposed method. A comparative analysis is completed for the parameters and the maximum alliances could be obtained with the original Pawlak conflict model.

The Markov chain hypothesis is the hypothesis discussed in stochastic interactions, and has several applications. This strategy is always coordinated with future situations whose whereabouts cannot be known with certainty, so the community tries to carry out exercises with future directions full of vulnerabilities. Hypotheses are numerical ways of dealing with competitive planning situations and the struggles between different interests. This hypothesis is designed to examine the dynamic cycle of various serious states and includes at least two interests. In this situation, the information obtained from the voting results is then assessed for its legitimacy and quality by using the SPSS program. The consequence of counting with Markov chain's S Noodle items reduces the share of the entire industry by 5.8%, while the fun noodle items expands a portion of the entire industry by 41%, the side effect of the game hypothesis being specific. namely X1 with probability 0.5, X2 with probability 0.5 and X3 with probability 3.16. Meanwhile, to limit misfortune, Indomie consolidates three systems, namely Y1 with likelihood - 0.1, Y2 with likelihood 0.5 and Y3 with likelihood 1.

It is impossible to obtain the forming limit curve (FLC) by full zone hydraulic forming test under quasi-static (QS) condition since the liquid will leak from the notches of the specimen once the pressure increases. In this study, a novel method is proposed to investigate the frictionless full zone hydraulic FLC of AA5A06 under high strain rate (HSR) condition based on the impact hydroforming technology (IHF). It is found that the FLC is increased significantly by IHF compared with the quasi-static rigid punch (QS-R) forming and the quasi-static hydraulic (QS-H) forming. Differentiating with the QS-H, the increase amounts of FLC at the biaxial tension zone and the tension-compression zone are notably different for IHF. Additionally, the theoretical calculations of FLC is conducted by using M-K model combining with Hill48 anisotropic yield criterion under QS and HSR conditions. The results calculated by the M-K model reasonably agree with the ones obtained from experimentation under QS and HSR condition, and a higher initial thickness ratio is assigned for HSR considering the neck postponing effect of inertia.

Mandatory minimums limit judicial discretion in many jurisdictions in the United States, often compelling judges to impose harsh incarcerative terms. Using qualitative interviews with 41 criminal term judges presiding in a state in the United States, we explore how mandatory minimums influence the judicial sentencing function. We find that judges vary in their approaches to sentencing and that their approaches correspond with their perceptions of mandatory minimum statutes. While our respondents consider case-level, systemic, and pragmatic factors, the majority of judges are focused on the case level and perceive that mandatory minimums often strip away the flexibility they need to craft appropriate sentences in individual cases, leading to punishments that are unduly harsh, and sometimes preventing the imposition of promising alternatives to incarceration. Some judges experience moral dilemmas and guilt feelings during this process. In contrast, judges who highlight pragmatic factors (e.g., public perceptions) are more receptive to statutory restrictions.

The preventive motive for war arises because states cannot commit to limit the use of their growing power. This commitment problem can lead to war when there are not enough resources available to compensate the declining state for their expected losses. In this article, we show how capital markets affect preventive war incentives by introducing a profit-maximizing bond market to the canonical bargaining model of war. We find that the nature of the power shift and fundamentals of the market for debt interact to determine when a preventive motive is more likely to lead to war. Two main results show that (1) less probable but more extreme power shifts are most dangerous and (2) unlike the direct effect of interest rates on the cost of war, higher interest on sovereign debt makes war more likely. We present evidence for the latter effect by extending Lemke’s (2003) study of preventive war for major-power dyads between 1816 and 1992.

This article explores the intersection of politics and popular entertainment in contemporary Chinese leitmotiv cinema (zhuxuanlü dianying), a genre that conflates political didacticism with Hollywood-style entertainment. Through my reading of three movies by Feng Xiaoning – the hero-epos Qingzang xian/A Railway in the Clouds (2006) about the building of a rail link to Tibet, the disaster movie Chaoqiang taifeng/Super Typhoon (2008) about a Chinese metropolis hit by a storm, and the war-action movie Jiawu dahaizhan/Naval Battle (2012) about the Sino-Japanese naval conflict of 1895 – I will illustrate how leitmotiv cinema negotiates demands for doctrinal orthodoxy with expectations for box-office success. Feng’s cinematic aesthetics are thus symptomatic of the discursive complexity of post-socialist Chinese Cinema where multiple temporalities and modes of production coexist in a climate of state-enforced ideological hegemony and revenue-driven market economics.

In this work, we discuss m-th exponential spacings △k:m:n obtained from order statistics. We study limit results for such spacings when the sample size n tends to infinity and the indices k and m are either fixed or also tend to infinity. We also investigate asymptotic properties of largest exponential m-th spacing.

This paper proposes a novel method of image enhancement via energy curve equalization (ECE). Histogram equalization (HE) appears to be the most straightforward method for image contrast enhancement. Many modifications are already recommended to overcome the confines of HE. The computation of the histogram does not consider the spatial correlations among the surrounding pixels. The current method utilizes the energy curve as a substitute for the histogram of an image. In contrast to the histogram, this approach covers the spatial context information of neighboring pixels. The modified Hopfield neural network (HNN) architecture is employed to compute an image's energy curve. It has peaks and valleys and appears smoother than the image histogram. The average value of the mean and median of the energy curve is used as the plateau limit to control the enhancement rate. The clipped energy curve is partitioned into three individual regions based on the standard deviation value. The final transformation function is utilized to remap the pixel intensity values and is formulated by integrating the individual portions of equalized energy curves. The simulation results confirm the projected technique's effectiveness compared to conventional HE-based methods with and without plateau limit.

Does the partisanship of officeholders affect environmental outcomes? The popular perception is that Republicans are bad for the environment, but complicating factors like federalism may limit this outcome. Using a dataset that tracks toxic releases over 20 years, we examine how partisan control of executive and legislative branches at both state and federal levels affect environmental policy. Moving beyond the passage of policies or environmental program spending allows us to fully understand the impact of Republicans on the environment. In addition, we take into account structural complications that may shape the relationship between Republican control and environmental outcomes. We find that the conventional wisdom that Republicans are bad for the environment has some validity, but it is dependent on what offices Republican elected officials occupy. More specifically, Republicans significantly affect toxic chemical releases when occupying governorships and controlling Congress. Our conclusions provide further insight into understanding how partisanship affects environmental outcomes, including how partisanship composition across the federal system matters.

What is the role of legislative term limits in the structure of legislative institutions? Using Mooney’s collective action problem theoretical framework on legislative leadership power, I claim that legislative term limits should be a key determinant in a state Speaker’s power via the delegation of institutional tools that control the lawmaking process. Speakers can use these tools to influence policy outcomes and their colleagues. I test this expectation in an analysis of lower chamber rules in nearly all states between 1981 and 2015. The results indicate that states with implemented term limits are associated with a more powerful Speaker. These findings suggest that a more nuanced relationship between legislative term limits and leadership power exist than previously thought.

This paper proposes a sticky inflation model in which inflation persistence is endogenously generated from the optimizing behavior of forward-looking firms. Although firms change prices periodically, their ability to fully adjust them in response to changes in economic conditions is assumed to be constrained due to the presence of managerial and customer costs of price adjustment. In essence, the model assumes that price stickiness arises from a combination of staggered contracts as in Calvo (1983) as well as quadratic adjustment cost as in Rotemberg (1982). We estimate the model using Bayesian techniques. Our findings strongly support both sources of price stickiness in the U.S. data. The model performs well in matching microeconomic evidence on price setting, particularly regarding the size and frequency of price changes. The paper also shows how incomplete price adjustments in a staggered price contracts model limit the contribution of expectations to inflation dynamics: it generates the delayed response of inflation to demand and monetary shocks, and the observed correlation between inflation and economic activity.

Since the rigid constructions of the traditional exoskeletons are liable to increase inertia of the joint and limit wearer flexibility, the soft-type exoskeletons have been developed in recent years, which can reduce system inertia, increase interaction compliance, and ensure operation safety. In this article, we present the detailed design and preliminary control of a soft body-worn and tendon-sheath-driven exoskeleton that can apply appropriate torques to the biological knee joints during rehabilitation training. This article focuses on the design of compliance tendon-sheath actuation system based on Hill muscle model, which utilizes multi-wrap pulleys and Hill-based series elastic actuator to transmit effective forces. Besides, the overall control system and strategy architectures of knee soft exoskeleton are also proposed. A fuzzy proportional–integral–derivative controller is developed for the passive rehabilitation training. On this basis, a back-propagation-neural-network-based adaptive impedance control scheme is presented to provide adaptive force based on the disease condition of the patient. Finally, preliminary experiments are conducted to demonstrate the effectiveness of proposed exoskeleton and control strategies.

New expressions are derived for the Green function (GF) for diffraction and radiation of waves by a two-dimensional (2D) body in finite water depth. The finite depth GF is expressed as a sum of singularities, the infinite depth GF and smoothly-varying integrals that are convergent for all parameter values. The infinite depth component is given explicitly, making it very fast to compute. Explicit expressions are derived for the limiting cases of zero and infinite frequency, for both finite and infinite water depth. The low frequency limit of the 2D GF is inconsistent with the zero-frequency 2D GF, with the real part tending to infinity when the water depth is infinite and the imaginary part tending to infinity in finite water depth. The inconsistencies with the zero frequency GF differ between the 2D and 3D cases. These inconsistencies lead to differences between the low-frequency behaviour of the added mass and damping of an oscillating body and the values at zero frequency. It is shown that these differences can be inferred directly from the behaviour of the GF at low frequencies.

Economics research is increasingly performed in teams, and team-authored work has a large and increasing impact advantage. This article considers the benefits and costs of this “rise of teams.” Among its benefits, teamwork allows individuals to aggregate knowledge in productive and novel ways. For example, as knowledge accumulates over time, individuals become narrower in their expertise, and teamwork is a natural organizational approach to aggregating expertise and maintaining one’s reach. But teamwork also brings costs. For example, teamwork divides and obscures credit, which is central to the reward system of science. By clouding credit assignment, teamwork can undermine individual career progression and exacerbate issues of bias. In addressing the rise of teamwork, this paper further considers institutional innovations, especially those inspired by the hard sciences, that can help limit the costs teamwork imposes while realizing the benefits.

Acceptance sampling plans are one of the oldest methods of quality control. Acceptance sampling is used in conjunction with statistical process control methods when it is assumed that the process is under statistical control. The primary goal of acceptance sampling plans is to make sure units or raw materials to be used in the manufacturing process are of good quality. Acceptance sampling plans are typically classified into three broad categories: sampling plans for attributes, sampling plans for variables, and special sampling plans. The chapter discusses single sampling plans for attributes, other sampling plans for attributes, and sampling standard ANSI/ASQ Z1.4‐2003. Dodge‐Romig tables were designed as sampling plans to minimize average total inspection. The concept of an acceptance quality limit applies only when an acceptance sampling scheme with rules for switching between normal, tightened, reduced, and discontinuance of sampling inspection is used.

We investigate the performance of a voting procedure in which voters cast multiple votes, with some votes positive and some negative. The procedure is a variant of the “D21” method proposed by Janecek (2016). The setting is the 2018 Czech Republic presidential election. Evidence is provided through a survey of secondary school students asked to cast ballots in both single- and multi-vote election experiments. Using the survey data, we estimate a spatial voting model to uncover ideological positions of candidates and respondents. Results suggest that the multi-vote procedure may limit the success of extreme candidates in elections.

This work addresses the mathematical analysis – by means of asymptotic analysis – of a penalisation strategy for the full discretisation of elastic wave propagation problems in quasi-incompressible media that has been recently developed by the authors. We provide a convergence analysis of the solution to the continuous version of the penalised problem towards its formal limit when the penalisation parameter tends to infinity. Moreover, as a fundamental intermediate step we provide an asymptotic analysis of the convergence of solutions to quasi-incompressible problems towards solutions to purely incompressible problems when the incompressibility parameter tends to infinity. Finally, we further detail the regularity assumptions required to guarantee that the mentioned convergence holds.

We write down the most general membrane equations dual to black holes for a general class of gravity theories, up to sub-leading order in $1/D$ in large $D$ limit. We derive a "minimal" entropy current which satisfies a local form of second law from these membrane equations. We find that consistency with second law requires the membrane equations to satisfy certain constraints. We find additional constraints on the membrane equations from the existence of membrane solutions dual to stationary black holes. Finally we observe a tension between second law and matching with Wald entropy for dual stationary black hole configurations, for the minimal entropy current. We propose a simple modification of the membrane entropy current so that it satisfies second law and also the stationary membrane entropy matches the Wald entropy., Comment: 36+10 pages, Section on matching membrane entropy to Wald entropy changed to include discussions on modified entropy current. Corresponding changes included in abstract and other relevant places in the paper

This paper studies the joint optimization of price and two-dimensional (2-D) warranty policy with limits of both warranty length and usage. For this purpose, in this paper, we first propose a new sales function to characterize the joint influence of price, warranty length, and usage limit on the sales rate while considering the influence of the heterogeneous customer usage rate. Then, we model the joint dynamic optimization of price and 2-D warranty policy as a nonlinear optimal control problem, and solve it via a numerical approach based on Pontryagin's maximum principle. We show that the proposed dynamic 2-D warranty policy can help achieve higher profits than the existing one-dimensional policies and static 2-D policy.

We study the tails of closing auction return distributions for a sample of liquid European stocks. We use the stochastic call auction model of Derksen et al. (2020a), to derive a relation between tail exponents of limit order placement distributions and tail exponents of the resulting closing auction return distribution and we verify this relation empirically. Counter-intuitively, large closing price fluctuations are typically not caused by large market orders, instead tails become heavier when market orders are removed. The model explains this by the observation that limit orders are submitted so as to counter existing market order imbalance.