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Let G be an intersection graph of n geometric objects in the plane. We show that a maximum matching in G can be found in O (ρ 3 ω / 2 n ω / 2) time with high probability, where ρ is the density of the geometric objects and ω > 2 is a constant such that n × n matrices can be multiplied in O (n ω) time. The same result holds for any subgraph of G, as long as a geometric representation is at hand. For this, we combine algebraic methods, namely computing the rank of a matrix via Gaussian elimination, with the fact that geometric intersection graphs have small separators. We also show that in many interesting cases, the maximum matching problem in a general geometric intersection graph can be reduced to the case of bounded density. In particular, a maximum matching in the intersection graph of any family of translates of a convex object in the plane can be found in O (n ω / 2) time with high probability, and a maximum matching in the intersection graph of a family of planar disks with radii in [ 1 , Ψ ] can be found in O (Ψ 6 log 11 n + Ψ 12 ω n ω / 2) time with high probability. [ABSTRACT FROM AUTHOR]

We propose a model that reconciles two aspects of social capital: social capital as reciprocal sharing of favors within a selected group vs. social capital as trust that lubricates transactions in societies. The core assumption is that individuals have productive potentials, e.g., innovations, that can not be put at use autonomously. However, individuals can associate in a club to match productive innovator-implementor dyads among the members. For a given club, allowing one new member has the effect of a) an increased pool of innovations and b) an increased pool of potential implementers. Whether a particular member supports the expansion of the club depends on whether she expects to be an implementor or an innovator. When expansion of membership is decided by vote, both small exclusive clubs and open clubs encompassing the whole society can emerge. The outcome depends both on the voting protocol, on the distribution of innovator and implementer skills, and on the maximal potential club size. Moreover, identical environments may generate multiple equilibrium club sizes. In which of these the society ends up depends on the initial conditions and on the voting protocol. [ABSTRACT FROM AUTHOR]

University-enterprise cooperation has experienced nearly 30 years of development in China, there are still a large number of failure cases in practice, and academic research often presents a unilateral situation of 'enterprise-university'. This study starts with the bilateral matching between enterprises and universities, using data on invention patents jointly applied for by Chinese enterprises and universities from 2010 to 2020, discusses the influence of university-enterprise knowledge potential matching on the innovation performance of university-enterprise cooperation and the influence of university level and enterprise R&D investment intensity on the innovation performance of university-enterprise cooperation when the knowledge potential difference is similar. The results show that: (1) knowledge potential matching has a significant effect on the innovation performance of university-enterprise cooperation: the smaller the knowledge potential difference, the higher the innovation performance; (2) with similar knowledge potential difference, the level of the university has no significant impact on the innovation performance, and the R&D investment intensity of enterprises is positively correlated with the innovation performance of university-enterprise cooperation; (3) geographical proximity has a significant inverted U-shaped moderating effect on the relationship between knowledge potential matching and the innovation performance of university-enterprise cooperation. [ABSTRACT FROM AUTHOR]

Blocking flows were introduced by Dinic (Soviet Math Doklady 11: 1277–1280, 1970) to speed up the computation of maximum network flows. They have been used in algorithms for problems such as maximum cardinality matching of bipartite graphs Hopcroft and Karp (SIAM J Comput 2(4), 225–231, 1973) and general graphs Micali and Vazirani (in: Proceedings of the 21st Annual Symposium on Foundations of Computer Science, 17–27, 1980), maximum weight matching of general graphs Gabow and Tarjan (J ACM 38(4), 815–853, 1991), and many others. The blocking algorithm of Gabow and Tarjan (1991) for matching is based on depth-first search. We extend the depth-first search approach to find f-factors of general multigraphs. Here f is an arbitrary integral-valued function on vertices, an f-matching is a subgraph where every vertex x has degree ≤ f (x) , an f-factor has equality in every degree bound. A set of blocking trails for an f-matching M is a maximal collection A of edge-disjoint augmenting trails such that M ⨁ A ∈ A A is a valid f-matching. Blocking trails are needed in efficient algorithms for maximum cardinality f-matching Huang and Pettie (Algorithmica 84(7): 1952–1992, 2022), maximum weight f-factors/matchings by scaling Duan et al. (In: Proceedings of the 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020), Vol. 168 of LIPIcs, 41:1-41:17, 2020; Gabow (A weight-scaling algorithm for f-factors of multigraphs.arXiv:2010.01102, 2020), and approximate maximum weight f-factors and f-edge covers Huang and Pettie (2022). Since these algorithms find many sets of blocking trails, the time to find blocking trails is a dominant factor in the running time. Our blocking trail algorithm runs in linear time O(m). In independent work and using a different approach, Huang and Pettie (2022) present a blocking trails algorithm using time O (m α (m , n)) . As examples of the time bounds for the above applications, an approximate maximum weight f-factor is found in time O (m α (m , n)) using Huang and Pettie (2022), and our algorithm eliminates the factor α (m , n) . Similarly a maximum weight f-factor is found in time O (Φ log Φ m α (m , n) log (Φ W)) using Huang and Pettie (2022) , ( Φ = ∑ v ∈ V f (v) , W the maximum edge weight) and our algorithm eliminates the α (m , n) factor, making the time within a factor log Φ of the bound for bipartite multigraphs. The technical difficulty for this work stems from the fact that a fixed vertex can occur many times in a given search. This does not occur in ordinary matching or in algorithms for maximum cardinality or maximum weight f-matching. These multiple occurrences can create a new variant of blossom, the "skew blossom". Also they can make blossoms become "incomplete", i.e., partially processed yet still relevant in future searches. [ABSTRACT FROM AUTHOR]

The challenge for graph matching algorithms is to extend known time bounds for bipartite graphs to general graphs. We discuss combinatorial algorithms for finding a maximum weight f-factor on an arbitrary multigraph, for given integral weights of magnitude at most W. (An f-factor is a subgraph whose degree function is the given function f : V → N .) For simple bipartite graphs the best-known time bound for combinatorial algorithms is O (n 2 / 3 m log n W) [Gabow and Tarjan, SIAM J Comput 18(5):1013–1036, 1989; n and m are respectively the number of vertices and edges.] A recent algorithm of Duan et al. [in: Proc. of the 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020), 2020] for f-factors of simple general graphs comes within logarithmic factors of this bound, O ~ (n 2 / 3 m log W) . The best-known bound for bipartite multigraphs is O (Φ m log Φ W) ( Φ ≤ m is the size of the f-factor, Φ = ∑ v ∈ V f (v) / 2 ). This bound is more general than the restriction to simple graphs, and is even superior on "small" simple graphs, i.e., Φ = o (n 4 / 3) . We present an algorithm that comes within a log Φ factor of this bound, i.e., O (Φ log Φ m log Φ W) . The algorithm is a direct generalization of the algorithm of Gabow and Tarjan [J ACM 38(4):815–853, 1991] for the special case of ordinary matching ( f ≡ 1 ). We present that algorithm first. Our analysis is a simplified and more concrete version of Gabow and Tarjan [J ACM 38(4):815–853, 1991] and has independent interest. Furthermore the algorithm and analysis are both incorporated, without modification, into the f-factor algorithm. To extend these ideas to f-factors, the first step is "expanding" edges (i.e., replacing an edge by a length 3 alternating path). Duan et al. [in: Proc. of the 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020), 2020] uses a one-time expansion of the entire graph. In contrast, our algorithm keeps the graph small by only expanding selected edges (edges incident to blossoms, in "I(B) sets"). Expanded edges get "compressed" back to their source when no longer needed. Expansion necessitates using an alternate graph model for blossoms (we call them "e-blossoms"). Compression requires coordinating e-blossoms with standard blossoms. [ABSTRACT FROM AUTHOR]

Standard approaches to comparing health providers' performance rely on hierarchical logistic regression models that adjust for patient characteristics at admission. Estimates from these models may be misleading when providers treat different patient populations and the models are misspecified. To address this limitation, we propose a novel profiling approach that identifies groups of providers treating similar populations of patients and then evaluates providers' performance within each group. The groups of providers are identified using a Bayesian multilevel finite mixture of general location models. To compare the performance of our proposed profiling approach to standard methods, we use patient-level data from 119 skilled nursing facilities in Massachusetts. We use simulated and observed outcome data to explore the performance of these profiling methods in different settings. In simulations, our proposed method classifies providers to groups with similar patients' admission characteristics. In addition, in the presence of limited overlap in patient characteristics across providers and misspecifications of the outcome model, the provider-level estimates obtained using our approach identified providers that under- and overperformed compared to the standard regression-based approaches more accurately. [ABSTRACT FROM AUTHOR]

A graph is called k -extendable if each k -matching can be extended to a perfect matching. We give spectral conditions for the k -extendability of graphs and bipartite graphs using Tutte-type and Hall-type structural characterizations. Concretely, we give a sufficient condition in terms of the spectral radius of the distance matrix for the k -extendability of a graph and completely characterize the corresponding extremal graphs. A similar result is obtained for bipartite graphs. [ABSTRACT FROM AUTHOR]

Improvement in the built environment is an essential component of transit-oriented development; however, the economic effects of such investments have not yet been fully understood because their investigation requires a suitable empirical case. Using the decentralized development of station plazas, this study identified the conditions under which plaza development raises the economic value of the surrounding areas. We empirically analyzed the impact of station plaza development on the land prices of 3870 properties in the surrounding areas at 181 of the 1556 stations in the Tokyo Metropolitan Area from 2000 to 2010, where station plazas were developed for the revitalization of station areas in a mature urban economy. Mahalanobis distance matching was applied to obtain the treatment effect, and the heterogeneity in the effects on the land price of properties by land-use pattern and geographical location was analyzed. The results showed that the properties benefited from station plaza development depending on the accessibility to and from the nearest station and the Tokyo Station (the central station) and their land-use patterns. The study found that there could be a redistributive effect in that the plaza development had positive effects on land price changes around the stations and negative effects in places far from the stations. • Impacts of railway station plaza development on land prices are analyzed. • Empirical data in the Tokyo Metropolitan Area in 2000 and 2010 are used. • The effect of plaza development is estimated with Mahalanobis distance matching. • Station plaza development has heterogeneous effects on land price. [ABSTRACT FROM AUTHOR]

The inspection of condition of underwater pipelines (UPs) based on autonomous underwater vehicles (AUVs) requires high accuracy of positioning while the AUV is moving along to the object being examined. Currently, acoustic, magnetometric, and visual means are used to detect and track UPs with AUVs. Compared to other methods, visual navigation can provide higher accuracy for local maneuvering at short distances to the object. According to the authors of the present article, the potential of video information for these purposes is not yet fully utilized, and, therefore, the study focused on the more efficient use of stereo images taken with an AUV's video camera. For this, a new method has been developed to address inspection challenges, which consists in the highlighting of visible boundaries and the calculation of the UP centerline using algorithms for combined processing of 2D and 3D video data. Three techniques for initial recognition of the direction of UP upon its detection were analyzed: on the basis of a stereo-pair of images using point features of the surface; using tangent planes to the UP in one of the stereo-pair; and using the UP median planes in both images of the stereo-pair. Approaches for determining the parameters of the relative positions of the AUV and the UP during the subsequent tracking are also considered. The technology proposed can be of practical use in the development of navigation systems to be applied for UP inspection without deploying additional expensive equipment, either separately or in combination with measurements from other sensors. [ABSTRACT FROM AUTHOR]

The article aims to investigate whether social segregation in urban areas can be reduced by transferring jurisdiction over urban planning from municipalities to the inter-municipal level. Specifically, we analyse the evolution of social segregation between 1968 and 2010 in French inter-municipal cooperation structures exercising jurisdiction over urban planning since at least 1995 and compare it with that of groupings of municipalities that do not have this competence. In order to minimise the risk of selection bias we use difference-in-difference matching methods. The effects revealed by the analysis are mixed and show that the success of this transfer of competence depends on the communities' intentions as well as on the extent of responsibilities that have been transferred. [ABSTRACT FROM AUTHOR]

We consider marriage markets with externalities. We focus on weak externalities, that is, markets in which each agent is primarily concerned about her partner. We formalize and prove the claim that weak externalities are not so significant in the marriage market: in this case, the ω‐core and the α‐core coincide and are both nonempty. In addition, we show that, if we allow agents to block matchings without changing their mate, the results do not longer hold. [ABSTRACT FROM AUTHOR]

Let G$$ G $$ be a finite tree. For any matching M$$ M $$ of G$$ G $$, let U(M)$$ U(M) $$ be the set of vertices uncovered by M$$ M $$. Let ℳG$$ {\mathcal{M}}_G $$ be a uniform random maximum size matching of G$$ G $$. In this paper, we analyze the structure of U(ℳG)$$ U\left({\mathcal{M}}_G\right) $$. We first show that U(ℳG)$$ U\left({\mathcal{M}}_G\right) $$ is a determinantal process. We also show that for most vertices of G$$ G $$, the process U(ℳG)$$ U\left({\mathcal{M}}_G\right) $$ in a small neighborhood of that vertex can be well approximated based on a somewhat larger neighborhood of the same vertex. Then we show that the normalized Shannon entropy of U(ℳG)$$ U\left({\mathcal{M}}_G\right) $$ can be also well approximated using the local structure of G$$ G $$. In other words, in the realm of trees, the normalized Shannon entropy of U(ℳG)$$ U\left({\mathcal{M}}_G\right) $$—that is, the normalized logarithm of the number of maximum size matchings of G$$ G $$—is a Benjamini‐Schramm continuous parameter. [ABSTRACT FROM AUTHOR]

Prior studies on the link between country‐level cultural aspects and firms' arbitrary accounting practices are scant, and they show mixed results. To gain more insight about the impact of national culture on earnings characteristics, we exploit the matching concept between revenues and expenses, which well reflects managerial estimation and discretion in earnings quality. Using a large sample of 57 countries over the period 1989–2012, we find that (1) the economic association between revenues and expenses becomes stronger in firms from collectivistic and high uncertainty‐avoidant countries, (2) the impact of these dimensions of national culture on the matching is more salient for firms from countries characterized by a higher level of accrual accounting, a greater proportion of special‐items, and limited openness, and (3) the cultural impact on matching is mainly driven by the correlation between revenue and discretionary expense (i.e., selling, general, and administrative expense). These findings are consistent with the view that national culture plays an informal governance role to influence firms' discretionary accounting choices. [ABSTRACT FROM AUTHOR]

In the one-sided assignment game, any two agents can form a trade; they can decide to form a partnership and agree on how to share the surplus created. Contrary to the two-sided assignment game, stable outcomes often fail to exist in the one-sided assignment game. Hence the core, which coincides with the set of stable payoffs, may be empty. We introduce the idea of tradewise-stable (t-stable) outcomes: they are individually rational outcomes where all trades are stable; that is, no matched agent can form a blocking pair with any other agent, neither matched nor unmatched. We propose the set of constrained-optimal (optimal) t-stable outcomes, the set of the maximal elements of the set of t-stable outcomes, as a natural solution concept for this game. We prove that this set is non-empty, it coincides with the set of stable outcomes when the core is non-empty, and it satisfies similar properties to the set of stable outcomes even when the core is empty. We propose a partnership formation process that starts with the outcome where every player stands alone, goes through steps where the set of active players expands, always forming t-stable outcomes, and ends in an (in any) optimal t-stable outcome. Finally, we also use the new concept to establish conditions under which the core is non-empty. [ABSTRACT FROM AUTHOR]

Afacan (Games and Economic Behavior 110: 71-89, 2018) introduces an object allocation with random priorities problem. He proposes the constrained probabilistic serial (CPS) mechanism. This study, for the first time in the literature, provides axiomatic characterizations of CPS. The first result characterizes it via non-wastefulness, claimwise stability, constrained ordinal fairness, and surplus invariance to truncations. The other axiomatizes CPS via constrained stochastic efficiency, claimwise stability, and constrained ordinal fairness. The independence of the axioms is provided. [ABSTRACT FROM AUTHOR]

Understanding when people are likely to feel ambivalent is important, as ambivalence is associated with key attitude outcomes, such as attitude-behavior consistency. Interestingly, the presence of conflicting positive and negative reactions (objective ambivalence) is weakly related to feeling conflicted (subjective ambivalence). We tested a novel situation that can influence the correspondence between objective and subjective ambivalence: whether a message and a recipient's topic match in affective versus cognitive orientation. When a person encounters a message with an affective or cognitive match to the topic, conflicting reactions may be more accessible, increasing feelings of ambivalence. Across five studies, greater objective–subjective ambivalence correspondence occurred with an affective–cognitive match between message and topic orientation. Studies 4 and 5 also demonstrated that this primarily occurred when the message was counterattitudinal. This work contributes to the literature explaining the gap between measures of objective and subjective ambivalence as well as how messages can influence attitude strength properties. [ABSTRACT FROM AUTHOR]

Matching by a confounder in a case–control study nearly always produces a control-selection bias that mixes with the confounding to produce a net bias. Previous theoretical work has assumed that control for a single confounder, the matching factor, is sufficient to remove all the confounding and that the confounder-exposure, confounder-outcome and exposure-outcome associations are monotonic. Under these conditions: (a) The net bias is toward the null if the exposure affects the outcome and nil if it does not. (b) If the confounding is away from the null, the selection bias is toward the null. (c) If the confounding is toward the null, the selection bias can be in any direction or even nil. If more than one confounder needs to be controlled to remove all the confounding, the net bias from matching by one of them can be away from the null, whether the exposure affects the outcome or not. An influential heuristic, that matching controls to cases by a variable associated with exposure always brings the marginal exposure distributions of the case and control groups closer together, turns out to be faulty. The implications of matching by confounders in case–control studies are less straightforward than previously thought. Suggestions are offered for advancing the methodologic literature on this topic. [ABSTRACT FROM AUTHOR]

We study the joint implementation of reservation and de-reservation policies in India that has been enforcing comprehensive affirmative action since 1950. The landmark judgment of the Supreme Court of India in 2008 mandated that whenever the OBC category (with 27% reservation) has unfilled positions, they must be reverted to general category applicants in admissions to public schools without specifying how to implement it. We disclose the drawbacks of the recently reformed allocation procedure in admissions to technical colleges and offer a solution through "de-reservation via choice rules." We propose a novel priority design—Backward Transfers (BT) choice rule—for institutions and the deferred acceptance mechanism under these choice rules (DA-BT) for centralized clearinghouses. We show that DA-BT corrects the shortcomings of existing mechanisms. By formulating India's legal requirements and policy goals as formal axioms, we show that the DA-BT mechanism is unique for the concurrent implementation of reservation and de-reservation policies. This paper was accepted by Yan Chen, behavioral economics and decision analysis. [ABSTRACT FROM AUTHOR]

Covariate‐adjusted randomization (CAR) can reduce the risk of covariate imbalance and, when accounted for in analysis, increase the power of a trial. Despite CAR advances, stratified randomization remains the most common CAR method. Matched randomization (MR) randomizes treatment assignment within optimally identified matched pairs based on covariates and a distance matrix. When participants enroll sequentially, sequentially matched randomization (SMR) randomizes within matches found "on‐the‐fly" to meet a pre‐specified matching threshold. However, pre‐specifying the ideal threshold can be challenging and SMR yields less‐optimal matches than MR. We extend SMR to allow multiple participants to be randomized simultaneously, to use a dynamic threshold, and to allow matches to break and rematch if a better match later enrolls (sequential rematched randomization; SRR). In simplified settings and a real‐world application, we assess whether these extensions improve covariate balance, estimator/study efficiency, and optimality of matches. We investigate whether adjusting for more covariates can be detrimental upon covariate balance and efficiency as is the case of traditional stratified randomization. As secondary objectives, we use the case study to assess how SMR schemes compare side‐by‐side with common and related CAR schemes and whether adjusting for covariates in the design can be as powerful as adjusting for covariates in a parametric model. We find each SMR extension, individually and collectively, to improve covariate balance, estimator efficiency, study power, and quality of matches. We provide a case‐study where CAR schemes with randomization‐based inference can be as and more powerful than non‐CAR schemes with parametric adjustment for covariates. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) developments enable human capability to deliver the same outcome at a lower cost. This research performs a high-level matching between AI solutions and challenges within the port area by developing a novel academic approach. This way, the matching is carried out more structured than when one (manager, developer, challenge owner, etc.) fulfils it based on their opinion without following any structured approach. Therefore, the study defines first a comprehensive typology of port stakeholders' challenges, which can be solved via AI solutions. This typology presents challenges, including their main issues, widespread impact, and potential solutions. A state-of-the-art review of AI solutions that can address these challenges is carried out in parallel. Secondly, this review clearly distinguishes between AI solutions based on their technology and functionality. Thirdly, this research selects an appropriate AI solution for addressing each identified challenge in the port operation by upgrading the Gale–Shapley algorithm. Finally, it shows that the most critical presented AI solutions in this study use various machine learning (ML) techniques. Besides, concerning the AI solution's reusability feature and the result of high-level matching, this research shows that the implementation phase effort can be drastically reduced by using the recently developed matching algorithm. [ABSTRACT FROM AUTHOR]

In modern society, digital images can be far-reaching, and the images are manipulated by various software and hardware technologies. The image forgery activities are undertaken by the attackers mainly for damaging the reputation of people or receiving fiscal gain, etc. Taking this into consideration, many techniques are developed to detect the forged images. In this paper, a new deep learning-based approach is introduced for copy-move forgery detection. The input images are segmented into non-overlapping patches using superpixel-based modified dense peak clustering and the features are extracted from the segmented patches by applying deep learning structure of attention-based DenseNet 121 model. Besides, to compare every block, the depth of each pixel is reconstructed, and eventually matching process is carried out using the adaptive chimp patch matching approach, which detects the suspicious forged regions in an image. Finally, the matched keypoints are merged with the segmented patches using the merged keypoint matching algorithm. As a result, the new deep learning approach has detected the forged regions efficiently from the tampered image with less time even the image is compressed, rotated, or scaled. The performance is evaluated in terms of recall, precision, accuracy, F1-score, computational time, and False Positive Rate (FPR). Moreover, the performance is compared with the other existing approaches, and the outcomes showed that the proposed method has achieved higher accuracy of 97%, recall of 99%, precision of 97.84%, F1-score of 98.81%, FPR of 0.022 and less computational time of 2.5 s. [ABSTRACT FROM AUTHOR]

Fine balance is a matching technique to improve covariate balance in observational studies. It constrains a match to have identical distributions for some covariates without restricting who is matched to whom. However, despite its wide application and excellent performance in practice, there is very little theory indicating when the method is likely to succeed or fail and to what extent it can remove covariate imbalance. In order to answer these questions, this paper studies the limits of what is possible for covariate balancing using fine balance and near‐fine balance. The investigations suggest that given the distributions of the treated and control groups, in large samples, the maximum achievable balance by using fine balance only depends on the matching ratio (ie, the ratio of the sample size of the control group to that of the treated group). In addition, the results indicate how to estimate this matching ratio threshold without knowledge of the true distributions in finite samples. The findings are also illustrated by numerical studies in this paper. [ABSTRACT FROM AUTHOR]

Governments involved in civil wars often seek to shape foreign perceptions of the conflict and of the government's role in the conflict. To this end, for example, many such governments have engaged in public diplomacy campaigns (PDCs) in the United States since the end of the Cold War. Specifically, these governments have hired US public relations (PR) and lobbying firms to present favorable narratives of themselves and their role in the conflict. Through PDCs, governments seek to shape US public pronouncements about the governments and the conflict itself. Are PDCs effective tools to reach this goal? We argue that the effect of PDCs is divergent. PDCs help mobilize both supporters and opponents of the sponsoring governments. In so doing, PDCs increase both positive and negative public statements from US officials toward the civil war government. We compile data on PDCs in the United States since the end of the Cold War. Our results have implications for research on foreign influence in foreign policy, combatants' moral hazard, and international norms about combatant behavior. Moreover, in order to gauge the influence of foreign actors on domestic narratives of civil wars, it is crucial to consider how such foreign actors can indirectly shape the discourse around conflict by mobilizing domestic factions. [ABSTRACT FROM AUTHOR]

In observational causal inference, exact covariate matching plays two statistical roles: (i) it effectively controls for bias due to measured confounding; (ii) it justifies assumption-free inference based on randomization tests. In this paper we show that inexact covariate matching does not always play these same roles. We find that inexact matching often leaves behind statistically meaningful bias, and that this bias renders standard randomization tests asymptotically invalid. We therefore recommend additional model-based covariate adjustment after inexact matching. In the framework of local misspecification, we prove that matching makes subsequent parametric analyses less sensitive to model selection or misspecification. We argue that gaining such robustness is the primary statistical role of inexact matching. [ABSTRACT FROM AUTHOR]

We propose a simple model in which agents are matched in pairs in order to complete a task of unit size. The preferences of agents are single-peaked and continuous on the amount of time they devote to it. Our model combines features of two models: assignment games (Shapley and Shubik (1971)) and the division problem (Sprumont (1991)). We provide an algorithm (Select-Allocate-Match) that generates a stable and Pareto efficient allocation. We show that stable allocations may fail to exist if either the single-peakedness or the continuity assumption fail. [ABSTRACT FROM AUTHOR]

We propose a new classified mixed model prediction (CMMP) procedure, called pseudo-Bayesian CMMP, that uses network information in matching the group index between the training data and new data, whose characteristics of interest one wishes to predict. The current CMMP procedures do not incorporate such information; as a result, the methods are not consistent in terms of matching the group index. Although, as the number of training data groups increases, the current CMMP method can predict the mixed effects of interest consistently, its accuracy is not guaranteed when the number of groups is moderate, as is the case in many potential applications. The proposed pseudo-Bayesian CMMP procedure assumes a flexible working probability model for the group index of the new observation to match the index of a training data group, which may be viewed as a pseudo prior. We show that, given any working model satisfying mild conditions, the pseudo-Bayesian CMMP procedure is consistent and asymptotically optimal both in terms of matching the group index and in terms of predicting the mixed effect of interest associated with the new observations. The theoretical results are fully supported by results of empirical studies, including Monte-Carlo simulations and real-data validation. [ABSTRACT FROM AUTHOR]

This article studies human connections by examining the helping game—a hybrid between the classic two-player and multi-player prisoner's dilemma. In the helping game, players are presented with a pool of heterogeneous players and have to decide whom to help, if any. Helping others is associated with a cost unique to each potential partner, and receiving help is associated with a fixed benefit. An economic experiment was conducted with 100 students to analyse under which circumstances partnerships (defined as both helping each other) develop in the game. The findings indicate that partnerships form in the game, although mainly when providing help is relatively cheap for both parties. Therefore, most partnerships are between lower helping-cost players, while higher helping-cost players struggle to form partnerships. In addition, establishing partnerships is easier when players meet potential partners consecutively rather than simultaneously, as long as helping others is not too costly. Moreover, less risk-tolerant subjects provide more help to reduce the risk of not forming partnerships, yet establish fewer partnerships, as less risk-tolerant players avoid helping others when it is costly. [ABSTRACT FROM AUTHOR]

In an observational study there are two disjointed groups of samples, one of treatment samples and the other of control samples. Each of the samples is characterized by several observed covariates. Covariate balancing problems arise when estimating causal effects using observational data. It is desirable to replicate a randomized experiment by obtaining treatment and control groups with similar covariate distributions. Even though covariate balancing problems have been studied extensively, the complexity status of many variants has not been established. Some of our results demonstrate that 2-covariate balancing problems are polynomial time solvable, whereas almost all problems are hard for three or more covariates. These results have practical implications, such as justifying the use of implicit enumeration techniques or heuristics for the hard cases. A new approach suggested by our results is to use the 2-covariate polynomial cases and relax the problem by aggregating covariates into two sets to be solved efficiently. (accepted paper title: Algorithms and complexities of matching variants in covariate balancing) Here, we study several variants of matching problems that arise in covariate balancing. Covariate balancing problems can be viewed as variants of matching, or b-matching, with global side constraints. We present here a comprehensive complexity study of the covariate balancing problems providing polynomial time algorithms, or a proof of NP-hardness. The polynomial time algorithms described are mostly combinatorial and rely on network flow techniques. In addition, we present several fixed-parameter tractable results for problems where the number of covariates and the number of levels of each covariate are seen as a parameter. Funding: This work was supported by National Science Foundation [Grants CMMI-1760102 and NSF 2112533]; Israel Science Foundation (308/18). Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2022.2286. [ABSTRACT FROM AUTHOR]

Problem definition: Motivated by ride-hailing platforms such as Uber, Lyft and Didi, we study the problem of matching riders with self-interested drivers over a spatial network. We focus on the performance impact of two operational platform controls—demand-side admission control and supply-side repositioning control—considering the interplay with two practically important challenges: (i) spatial demand imbalances prevail for extended periods of time; and (ii) self-interested drivers strategically decide whether to join the network, and, if so, whether to reposition when not serving riders. Methodology/results: We develop and analyze the steady-state behavior of a novel game-theoretic fluid model of a two-location, four-route loss network. First, we fully characterize and compare the steady-state system equilibria under three control regimes, from minimal control to centralized control. Second, we provide insights on how and why platform control impacts equilibrium performance, notably with new findings on the role of admission control: the platform may find it optimal to strategically reject demand at the low-demand location even if drivers are in excess supply, to induce repositioning to the high-demand location. We provide necessary and sufficient conditions for this policy. Third, we derive upper bounds on the platform's and drivers' benefits caused by increased platform control; these are more significant under moderate capacity and significant cross-location demand imbalance. Managerial implications: Our results contribute important guidelines on the optimal operations of ride-hailing networks. Our model can also inform the design of driver compensation structures that support more centralized network control. Supplemental Material: The e-companion and Supplemental Material are available at https://doi.org/10.1287/msom.2023.1221. [ABSTRACT FROM AUTHOR]

A large number of carbon emissions are generated in the life cycle of metal forming equipment. The movable components are the critical part of the mechanical system in the equipment, which accounts for the carbon emissions in both of manufacturing and use stages. Reducing carbon emissions of the components in the manufacturing stage by lightweight design may result in a significant increment of emissions in the use stage. To overcome the obstacle, a method of matching the mechanical system of metal forming equipment to reduce life cycle carbon emissions is proposed. The effect of the weight of the components that determine the manufacturing’s emission on the configuration of the drive units that determine the emission in the usage stage, was analyzed and quantified. Then, the drive units were reconfigured and optimized to meet the required output force and velocity with the different weights of the components to find the optimal scheme with the lowest emissions in the life cycle. The method was applied to a 2000-ton hydraulic forming equipment, and results indicate that 14.87% of the weight of the movable components can be reduced with a total carbon emissions reduction of 22.48%. The total carbon emissions were reduced by 35.94% compared to that of the movable components through the topology optimization method. The proposed matching method can assist in the low-carbon design of the mechanical system in metal forming equipment. [ABSTRACT FROM AUTHOR]

The purpose of this article is to illustrate the growing limitations of the current methods of calculating earnings, particularly when earnings is a negative number. Earnings, presumably the most important output of a financial reporting system, is not a singular metric. It is obtained by subtracting numerous expense line items from revenues, both of which are calculated after applying a diverse, and often inconsistent, set of accounting conventions. Despite this apparent deficiency, earnings could be informative of recurring profits, if revenues are measured correctly and expenses are traced to revenues. However, both principles are increasingly violated for the cohorts of firms listed in the last 30 years, which now constitute over 80% of the set of listed firms. Revenues of recent cohorts do not capture many events that create recurring cash flows. Their operating expenses are dominated by intangible outlays that are unmatched to current revenues. As a result, newer cohorts' profits and profit margins, especially when negative, offer little to inform future profits. Given that revenue and expense recognition rules are unlikely to change anytime soon, the current developments raise a question: Should the reporting of the summary measure of earnings be voluntary instead of mandatory? [ABSTRACT FROM AUTHOR]

In group or cluster-randomized trials (GRTs), matching is a technique that can be used to improve covariate balance. When baseline data are available, we suggest a strategy that can be used to achieve the desired balance between treatment and control groups across numerous potential confounding variables. This strategy minimizes the overall within-pair Mahalanobis distance; and involves iteratively: 1) making pairs that minimize the distance between pairs of clusters with respect to potentially confounding variables; 2) visually assessing the potential effects of these pairs and resulting possible randomizations; and 3) reweighting variables of selecting weights to make pairs of clusters. In step 2, we plot the between-arm differences with a parallel-coordinates plot. Investigators can compare plots of different weighting schemes to determine the one that best suits their needs prior to the actual, final, randomization. We demonstrate application of the approach with the Mupirocin-Iodophor Swap Out trial. A webapp is provided.

Abstract Introduction Propensity score (PS) matching is widely used in medical record studies to create balanced treatment groups, but relies on prior knowledge of confounding factors. High-dimensional PS (hdPS) is a semi-automated algorithm that selects variables with the highest potential for confounding from medical databases. The objective of this study was to evaluate performance of hdPS and PS when used to compare antihypertensive therapies in the UK clinical practice research datalink (CPRD) GOLD database. Methods Patients initiating antihypertensive treatment with either monotherapy or bitherapy were extracted from the CPRD GOLD database. Simulated datasets were generated using plasmode simulations with a marginal hazard ratio (HRm) of 1.29 for bitherapy versus monotherapy for reaching blood pressure control at 3 months. Either 16 or 36 known covariates were forced into the PS and hdPS models, and 200 additional variables were automatically selected for hdPS. Sensitivity analyses were conducted to assess the impact of removing known confounders from the database on hdPS performance. Results With 36 known covariates, the estimated HRm (RMSE) was 1.31 (0.05) for hdPS and 1.30 (0.04) for PS matching; the crude HR was 0.68 (0.61). Using 16 known covariates, the estimated HRm (RMSE) was 1.23 (0.10) and 1.09 (0.20) for hdPS and PS, respectively. Performance of hdPS was not compromised when known confounders were removed from the database. Results on Real Data With 49 investigator-selected covariates, the HR was 1.18 (95% CI 1.10; 1.26) for PS and 1.33 (95% CI 1.22; 1.46) for hdPS. Both methods yielded the same conclusion, suggesting superiority of bitherapy over monotherapy for time to blood pressure control. Conclusion HdPS can identify proxies for missing confounders, thereby having an advantage over PS in case of unobserved covariates. Both PS and hdPS showed superiority of bitherapy over monotherapy for reaching blood pressure control.

This paper presents a novel computational process used for determining matching coefficients for optical spectra either in real time or from a database. This simple algorithmic method is capable of outputting a set of coefficients relating to comparative matching datapoints and to a weighted similarity ratio between spectra whilst still maintaining high computational efficiency due to the minimization of floating-point calculations. The process works as effectively on signal data during real time processing or on images of spectra which may be stored in a database. A subset of the algorithm has already been used very effectively in an embedded mobile field device to determine the presence or absence of special security fluorescent emission peaks present in printing inks used in anti-counterfeiting labels. The process involves the division of test spectrum(s) signal/image into a grid of user definable blocks while applying the same grid to the test image or images. Each block is then checked to see if the signal/image passes through the block, if the signal/image passes through a block then the value of this grid block is set to 1 in a grid array. The same check is then applied to the reference signal/image(s).While it is possible to process a signal comparison without the need for data storage, useful for some embedded processes, it may be preferable to store the resultant data in simple data arrays. These arrays can then undergo simple arithmetical processing to quickly calculate a set of values representing the number of matching data points, the variation in non-matching data points and a divergence value. This check can be carried out between the test image or images and a larger number of reference images simultaneously by use of additional counters. In addition, when used with large databases of spectra this novel technique may be used to rapidly reduce a large test set to a more relevant subset which can be further analyzed using more conventional methods or by visual inspection. This grid square analysis method works as efficiently on images as it can for signal data and it is believed by the authors that the method will have applications in other image processing applications where fast and efficient comparative analysis between images is required.

Abstract Background Understanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs’ (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population. Methods In a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts within each month utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes. Results From an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 37 covariates used in matching after excluding patients for: no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%). Conclusion This successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2.

Food standards are the important basis and criterion to guide the scientific， standardized and orderly implementation of food safety supervision.But there are problems such as poor compliance with regulatory needs. At present， China’s food standard system is still in the stage of gradual construction stage. According to the role and application of food standards in the food safety supervision， the compliance and matching are analyzed and studied between food standard system and actual supervision. The paper mainly analyzes China’s food standard system according with the application during food safety supervision. It is suggested to improve the follow-up evaluation of the standards tracking and evaluation gradually， simplifying and optimizing the revision process of the standard system， and integrating food classification standards to provide strong support and basis for food safety supervision.

OBJECTIVE: Presenting geographic matching trends over 5 match cycles (2016-2020) to serve as a context for changes in residency match outcomes due to the coronavirus disease 2019 (COVID-19) pandemic. STUDY DESIGN: Retrospective review. SETTING: Single academic institution-affiliated otolaryngology-head and neck surgery residency program. METHODS: Residency match outcomes for all applicants to our institution (2015-2019) were collected from the National Residency Matching Program, including medical school and matched program. Matches were categorized as home program, home region, or out of region and sorted by US geographic region. Statistical analysis included frequencies, totals, χ2 testing, and binary logistic regression. RESULTS: From 2016 to 2020, the US MD senior match rate was 84.9%: 18.9% to home programs, 35.7% to home region, and 45.3% to out of region. Rates were similar across regions and decreased over time. Westerners matched to home programs more than Southerners or Midwesterners (27.5% vs 16.0% and 16.0%, P < .01). Southerners and Westerners were more likely to match within their regions (South: 63.1%, P = .011, odds ratio [OR] = 1.296, 95% CI, 1.060-1.584; West: 42.0%, P = .018, OR = 1.462, 95% CI, 1.066-2.004). Matching from out of region was more likely in the West and less likely in the South (West: 58.0%, P = .017, OR = 1.379, 95% CI, 1.059-1.796; South: 36.9%, P < .001, OR = 0.584, 95% CI, 0.47-0.727). CONCLUSION: From 2016 to 2020 in otolaryngology-head and neck surgery, about 1 in 5 matches were to home institutions, a trend that appeared to be more common in the West. Over 4 out of 5 trainees match to nonhome programs, and nearly half relocate to a new region for training. Changes to travel, rotations, and interviews due to COVID-19 may influence these trends.

Electronic cigarettes (e-cigarettes) are the preferred smoking-cessation aid in the United States; however, there is little evidence regarding long-term effectiveness among those who use them. We used the Population Assessment of Tobacco and Health Study to compare long-term abstinence between matched US smokers who tried to quit with and without use of e-cigarettes as a cessation aid. We identified a nationally representative cohort of 2,535 adult US smokers in 2014-2015 (baseline assessment), who, in 2015-2016 (exposure assessment), reported a past-year attempt to quit and the cessation aids used, and reported smoking status in 2016-2017 (outcome assessment; self-reported ≥12 months continuous abstinence). We used propensity-score methods to match each e-cigarette user with similar nonusers. Among US smokers who used e-cigarettes to help quit, 12.9% (95% confidence interval (CI): 9.1%, 16.7%) successfully attained long-term abstinence. However, there was no difference compared with matched non-e-cigarette users (cigarette abstinence difference: 2%; 95% CI: -3%, 7%). Furthermore, fewer e-cigarette users were abstinent from nicotine products in the long term (nicotine abstinence difference: -4%; 95% CI: -7%, -1%); approximately two-thirds of e-cigarette users who successfully quit smoking continued to use e-cigarettes. These results suggest e-cigarettes may not be an effective cessation aid for adult smokers and, instead, may contribute to continuing nicotine dependence.

The authors propose a new conceptual basis for predicting when and why consumers match others' consumption choices. Specifically, they distinguish between ordinal ("ranked") versus nominal ("unranked") attributes and propose that consumers are more likely to match others on ordinal than on nominal attributes. Eleven studies involving a range of different ways of operationalizing ordinal versus nominal attributes collectively support this hypothesis. The authors' conceptualization helps resolve divergent findings in prior literature and provides guidance to managers on how to leverage information about prior customers' choices and employees' recommendations to shape and predict future customers' choices. Furthermore, the authors find process evidence that this effect is driven in part by consumers' beliefs that a failure to match on ordinal (but not nominal) attributes will lead to social discomfort for one or both parties. Although the primary focus is on food choices, the effects are also demonstrated in other domains, extending the generalizability of the findings and implications for managerial practice and theory. Finally, the conceptual framework offers additional paths for future research. [ABSTRACT FROM AUTHOR]

The relationship between international remittances and political participation remains unsettled. Studies based on the resource model of participation suggest that remittances are associated with an increase in political participation. In contrast, the insulation model of participation posits that remittances are associated with the likelihood of a decreased political engagement. While most studies have explored this topic using conventional measures of political participation, such as voting, protests, and contacting government officials, we expand the concept of political participation to include media contact. This form of participation has recently gained relevance in both the developed and developing world. Utilizing the 6th and 7th rounds of the Afrobarometer survey and employing matching methods, we explore whether the treatment of receiving remittances stimulates political engagements through contacting the media in Ghana. We find that remittance recipients are more likely to participate in governance by contacting the media, through actions such as calling a radio program or writing a letter to a newspaper to request action from the government. This finding suggests that an adverse exogenous shock to remittances may decrease the likelihood of political activism in households. With recent calls for accountability of governments in developing countries, media engagement of citizens could be an important channel through which citizens hold their governments accountable. As such, our finding has strong policy implications because if remittance engenders media engagement, then it also encourages good governance.

In critical care medicine, where there is a demanding career with a problematic work-life balance, mentoring is an important support tool to grow professionally, creating a network of support throughout the career. The mentoring process consists of evidence-based steps to guide critical care mentors and mentees and pair them with each other according to the correct selection and matching of participants. In order to focus on the active role of a young intensivist selected as a mentee at any level and to support their success in a mentoring relationship, the NEXT Committee of the European Society of Intensive Care Medicine (ESICM) developed 2012 a mentoring program. The critical steps of the mentoring program start from establishing a policy and program objectives, passing through the selection of participants, and matching with mentors up to the definition of the personal development plan supported by checklists, worksheets, and evaluation forms. The present manuscript provides key steps and tips for a good, essential based on our experience in the ESICM NEXT-Mentoring Program so that they guide for future mentoring programs conducted by other scientific societies. In addition, we discuss common challenges and how to avoid them. [ABSTRACT FROM AUTHOR]

Background: Understanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs' (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population. Methods: In a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts within each month utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes. Results: From an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 37 covariates used in matching after excluding patients for: no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%). Conclusion: This successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Decompositions make it possible to investigate whether gaps between groups in certain outcomes would remain if groups had comparable characteristics. In practice, however, such a counterfactual comparability is difficult to establish in the presence of lacking common support, functional-form misspecification, and insufficient sample size. In this article, the authors show how decompositions can be undermined by these three interrelated issues by comparing the results of a regression-based Kitagawa-Blinder-Oaxaca decomposition and matching decompositions applied to simulated and real-world data. The results show that matching decompositions are robust to issues of common support and functional-form misspecification but demand a large number of observations. Kitagawa-Blinder-Oaxaca decompositions provide consistent estimates also for smaller samples but require assumptions for model specification and, when common support is lacking, for model-based extrapolation. The authors recommend that any decomposition benefits from using a matching approach first to assess potential problems of common support and misspecification. [ABSTRACT FROM AUTHOR]

The Grover walk is one of the most well-studied quantum walks on graphs. In this paper, we investigate its periodicity to reveal the relationship between the quantum walk and the underlying graph, focusing particularly on the characterization of graphs exhibiting a periodic Grover walk. Graphs having a periodic Grover walk with periods of 2, 3, 4, and 5 have previously been characterized. It is expected that graphs exhibiting a periodic Grover walk with odd period correspond to cycles with odd length. We address that problem and are able to perfectly characterize the class of graphs exhibiting an odd-periodic Grover walk by using a combinatorial method. [ABSTRACT FROM AUTHOR]

Introduction: The excess suicide mortality on Monday was reported in numerous studies. However, it is uncertain that the uneven weekly distribution of deaths is observed among suicide, or common among various causes of death. Methods: Weekly distributions of suicide and other causes of death from 2012 to 2017 in South Korea were compared. Logistic regression models were fitted to investigate the association between causes of death and day‐of‐the‐week effects. We also fitted conditional logistic regression models after age and gender matching. Results: A total of 1,622,213 deaths, including 80,492 suicide decedents, were analyzed. A total of 16.0% of suicide deaths occurred on Monday, whereas 12.4% on Saturday and 13.0% on Sunday. Suicide decedents were more likely to die on Monday than other causes of deaths after controlling sociodemographic factors in unmatched data. However, there was no evidence of excess suicide deaths on Mondays than other days in contrast to matched death controls. Conclusion: While the increase in mortality on Mondays was not unique to suicide, our findings have suicide prevention implications. Mental health practitioners should consider providing additional mental health resources on earlier working days. Workplace mental health programs to reduce psychological burdens of employees could help to prevent suicide during working days. [ABSTRACT FROM AUTHOR]