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Building upon the concept of edge computing (EC), a distributed EC market requires decentralized and verified transaction management to trade computing resources. Towards this goal, we study a blockchain-aided EC market wherein each data service operator (DSO) rents a group of edge computing nodes (ECNs) and leases the ECNs to the user terminals (UTs) to provide computation offloading services. First, we propose a smart contract based matching mechanism to establish the renting association between the DSOs and ECNs with the aim of maximizing the social welfare. Second, we propose a social welfare improved double auction (SWIDA) mechanism to build up the leasing association between the DSOs and UTs, and show that the proposed mechanism can achieve individual rationality, balanced budget, truthfulness in expectation, and an improved social welfare than the benchmark mechanisms. Moreover, we put forth a trustworthiness-driven Proof-of-Stake (PoS) consensus mechanism to enable verified transaction and fair reward allocation. We formulate the block generation as a coalitional game, wherein each stakeholder votes according to its trustworthiness and coinage, and shares the reward among the coalition according to the Shapley values. The simulation results show that the proposed PoS consensus mechanism can reduce the wealth inequality among the network entities.

International audience; Background and Objectives: Some medications require specific medical procedures in the weeks before their start. Such procedures may meet the definition of instrumental variables (IVs). We examined how they may influence treatment effect estimation in propensity score (PS)-adjusted comparative studies, and how to remedy. Study Design and Setting: Different covariate assessment periods (CAPs) did and did not include the month preceding treatment start were used to compute PS in the French claims database (Syt eme National des Donn ees de Sant e-SNDS), and 1:1 match patients with metastatic castration resistant prostate cancer initiating abiraterone acetate or docetaxel. The 36-month survival was assessed. Results: Among 1, 213 docetaxel and 2, 442 abiraterone initiators, the PS distribution resulting from the CAP [-12; 0 months] distinctly separated populations (c 5 0.93; 273 matched pairs). The CAPs [-12;-1 months] identified 765 pairs (c 5 0.81). Strong docetaxel treatment predictors during the month before treatment start were implantable delivery systems (1% vs. 59%), which fulfilled IV conditions. The 36-month survival was not meaningfully different under the [-12; 0 months] CAP but differed by 10% points (38% vs. 28%) after excluding month À1. Conclusion: In the setting of highly predictive pretreatment procedures, excluding the immediate pre-exposure time from the CAP will reduce the risk of including potential IVs in PS models and may reduce bias.

本論文の目的は，日本基準における現金割引の非対称的な会計処理の問題を明らかにし，その問題を解消するための組替調整の方法を提案することにある．日本基準では，売上割引には実際に適用された現金割引を売上から控除する総額- 評価勘定法が適用され，仕入割引には実際に適用された現金割引を金融収益とする総額- 金融収益費用法が採用されている．このような非対称的な会計処理は，売上を実際取引価格で測定し，売上原価を信用取引価格で測定するため，売上と売上原価の対応関係に歪みを生じさせる原因となっている．本論文では，比較可能性を確保しつつ，この歪みを解消する2 つの手段を提案している．第1 の方法は，売上割引を売上高に加算する方法であり，この組替調整により，売上と売上原価の測定基礎は信用取引価格で統一される．第2 の方法は，仕入割引を売上原価から控除する方法であり，この組替調整により，売上と売上原価の測定基礎は実際取引価格で統一される．

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.

Sustainable Intensification (SI) practices offer adopters exploiting improvement potentials in environmental performance of farming, i.e. enhance ecosystem functionality, while maintaining productivity. This paper proposes a directional meta-frontier approach for measuring farms’ eco-efficiency and respective improvement potentials in the direction of farms’ ecological output for SI evaluation. We account for farms’ selection processes into SI using a behavioural model and rely on a matched sample for adopters and non-adopters of agronomic SI practices from the northern German Plain. We conclude that the SI adopters determined the sample’s system frontier and showed higher mean eco-efficiency, but that most farms in our sample did not fully exploit the improvement potentials in biodiversity as ecological outcome.

International audience; We investigate the maximum bottleneck matching problem in bipartite graphs. Given a bipartite graph with nonnegative edge weights, the problem is to determine a maximum cardinality matching in which the minimum weight of an edge is the maximum. To the best of our knowledge, there are two widely used solvers for this problem based on two different approaches. There exists a third known approach in the literature, which seems inferior to those two which is presumably why there is no implementation of it. We take this third approach, make theoretical observations to improve its behavior, and implement the improved method. Experiments with the existing two solvers show that their run time can be too high to be useful in many interesting cases. Furthermore, their performance is not predictable, and slight perturbations of the input graph lead to considerable changes in the run time. On the other hand, the proposed solver's performance is much more stable; it is almost always faster than or comparable to the two existing solvers, and its run time always remains low.

National audience; The matching setting, a particular case of recommendation problem, focuses on applications where a so-called item can be attributed to at most one user, with the job market and the matrimonial market as chief examples. In such cases, recommending the items preferred by each user might contribute to a congestion issue as users aiming at the same item cannot be all satisfied. While some state of art approaches proceed by repairing the recommendationpolicy to account for the congestion issue, other approaches take inspiration from the optimal transport (OT) framework, and aim to map the user population onto the item population in order to minimize some global transportation cost. In OT-based recommendation state-of-art approaches,the collaborative matrix (reporting the user-item matches) is interpreted as if it were the result of an OT plan ; the underlying transport cost is inferred and used e.g. to propose new congestion-avoiding recommendation policies. In this paper, another OT-based recommendation strategy is defined, noting that the collaborative matrix reflecting the individual decisions can hardly be considered as the result of a (centralized) OT plan. Accordingly, the proposed algorithm first learns a recommendation score from the data and then defines a cost matrix, with the transportation cost decreasing depending on the matching relevance. The optimal transport plan is thereafter used for the recommendation. The experimental validation of the approach presents com-parative results on benchmark data on the matrimonial market, and proprietary real-world data on the job market, illustrating the trade-off between the recall and the congestion indicators. The discussion focuses on the integration of individual and collective criteria.; La recommandation de biens rivaux (sur le marché du travail ou des rencontres) fait face au danger majeur de la congestion. Pour concevoir un système de recommandation évitant la congestion, une approche possible repose sur le transport optimal, cherchant un appariement global entre l'ensemble des utilisateurs et l'ensemble des items selon un coût de transport à définir. L'originalité de l'approche RECTO (REcommandation diminuant la Congestion parTransport Optimal) est de construire le coût de transport en fonction du score de recommandation, et de définir la politique de recommandation en fonction du plan de transport entre utilisateurs et items. Une validation expérimentale comparative, menée sur une base de données publiquerelative au marché matrimonial et une base de données propriétaire relative au marché du travail, illustre le compromis entre précision et congestion. La discussion porte sur l’intégration de critères individuels et collectifs.

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Funding Information: I thank Seppo Laakso, Tuukka Saarimaa, Heidi Falkenbach, the Editor and two anonymous reviewers for their useful comments and suggestions. This study is partially funded by the ROBUST project, as part of the Horizon 2020 Framework Programme of the European Union under Grant Agreement no. 727988. The information and views set out in this article are those of the author and do not necessarily reflect the official opinion of the European Union. Research funding from the Jenny and Antti Wihuri Foundation and the City of Helsinki is also gratefully acknowledged. Publisher Copyright: © 2022 The Authors. Journal of Regional Science published by Wiley Periodicals LLC. This study examines the relationship between agglomeration and labor market matching by investigating the small-scale sociospatial determinants of a network created by the within-region mobility of employees across organizations. The local labor flow network is constructed on the basis of an establishment-level matched employer–employee database covering selected knowledge-intensive industries in the Helsinki–Uusimaa Region in Finland during the period 2001–2015. The results from the analysis of various tie formation processes reveal that the formation of a link by interorganizational employee mobility within an integrated labor market area is more likely between organizations geographically closer to each other, all else being equal. The findings highlight the importance of local density for the job search process.

International audience; The introduction of the Internet in the 2000s was believed to be an effective solution for helping rural economies but previous studies found mixed results. Following the prevailing COVID-19 pandemic, the idea has surfaced that broadband accessibility would result in an increasing number of people and firms relocating to smaller towns and rural areas. In this study, we provide new evidence on the impact of ultrafast broadband on rural economies by considering industrial and spatial heterogeneity. To achieve this, we evaluated the impact of the French Very High-Speed Broadband Plan on business startups in rural municipalities between 2013 and 2018 using difference-in-differences with prematching. The evidence reveals that positive broadband effects are limited to municipalities with good initial conditions in terms of local economic climate, natural amenities, and demographics. From a policy perspective, our results suggest that broadband is not a panacea, and focusing on broadband access only is likely to have little impact in structurally weak rural areas.

Many recent works on Entity Resolution (ER) leverage Deep Learning techniques involving language models to improve effectiveness. This is applied to both main steps of ER, i.e., blocking and matching. Several pre-trained embeddings have been tested, with the most popular ones being fastText and variants of the BERT model. However, there is no detailed analysis of their pros and cons. To cover this gap, we perform a thorough experimental analysis of 12 popular language models over 17 established benchmark datasets. First, we assess their vectorization overhead for converting all input entities into dense embeddings vectors. Second, we investigate their blocking performance, performing a detailed scalability analysis, and comparing them with the state-of-the-art deep learning-based blocking method. Third, we conclude with their relative performance for both supervised and unsupervised matching. Our experimental results provide novel insights into the strengths and weaknesses of the main language models, facilitating researchers and practitioners to select the most suitable ones in practice.

Background: Mixing vaccines was proposed as a solution to tackle supply chain interruptions during the crisis of the COVID-19 pandemic. This study aimed to investigate the safety of mixing COVID-19 vaccines for a booster dose in Hanoi, Vietnam. Method: A cross-sectional study was conducted via a telephone-based interview to identify the adverse events following COVID-19 vaccination among 719 participants in Hanoi, Vietnam. Results: In total, 45.76% of participants experienced at least one adverse event following two doses of the COVID-19 vaccine. Most of the adverse events were local effects with mild symptoms such as fever, headache, muscle pain, and/or pain at the site. In general, matching two doses in the same vaccines was not associated with the adverse events as compared to mixing vaccines (OR = 1.43, 96%CI: 0.93–2.2), except matching two doses of Pfizer (OR = 2.25, 95%CI: 1.33–3.82). Conclusion: The findings of this study suggest the overall safety of mixed vaccination. In light of the vaccine shortage, mixing vaccinations for COVID-19 prevention is a good solution. Further studies with larger cohorts and investigating immunity following mixing vaccines are needed to elucidate the mechanism.

We present an Õ(log2 n) round deterministic distributed algorithm for the maximal independent set problem. By known reductions, this round complexity extends also to maximal matching, Δ+1 vertex coloring, and 2Δ−1 edge coloring. These four problems are among the most central problems in distributed graph algorithms and have been studied extensively for the past four decades. This improved round complexity comes closer to the Ω(logn) lower bound of maximal independent set and maximal matching [Balliu et al. FOCS ’19]. The previous best known deterministic complexity for all of these problems was Θ(log3 n). Via the shattering technique, the improvement permeates also to the corresponding randomized complexities, e.g., the new randomized complexity of Δ+1 vertex coloring is now Õ(log2logn) rounds. Our approach is a novel combination of the previously known (and seemingly orthogonal) two methods for developing fast deterministic algorithms for these problems, namely global derandomization via network decomposition (see e.g., [Rozhon, Ghaffari STOC’20; Ghaffari, Grunau, Rozhon SODA’21; Ghaffari et al. SODA’23]) and local rounding of fractional solutions (see e.g., [Fischer DISC’17; Harris FOCS’19; Fischer, Ghaffari, Kuhn FOCS’17; Ghaffari, Kuhn FOCS’21; Faour et al. SODA’23]). We consider a relaxation of the classic network decomposition concept, where instead of requiring the clusters in the same block to be non-adjacent, we allow each node to have a small number of neighboring clusters. We also show a deterministic algorithm that computes this relaxed decomposition faster than standard decompositions. We then use this relaxed decomposition to significantly improve the integrality of certain fractional solutions, before handing them to the local rounding procedure that now has to do fewer rounding steps., STOC 2023: Proceedings of the 55th Annual ACM Symposium on Theory of Computing, ISBN:978-1-4503-9913-5

Ancient numismatics, the study of ancient coins, has in recent years become an attractive domain for the application of computer vision and machine learning. Though rich in research problems, the predominant focus in this area to date has been on the task of attributing a coin from an image, that is of identifying its issue. This may be considered the cardinal problem in the field and it continues to challenge automatic methods. In the present paper, we address a number of limitations of previous work. Firstly, the existing methods approach the problem as a classification task. As such, they are unable to deal with classes with no or few exemplars (which would be most, given over 50,000 issues of Roman Imperial coins alone), and require retraining when exemplars of a new class become available. Hence, rather than seeking to learn a representation that distinguishes a particular class from all the others, herein we seek a representation that is overall best at distinguishing classes from one another, thus relinquishing the demand for exemplars of any specific class. This leads to our adoption of the paradigm of pairwise coin matching by issue, rather than the usual classification paradigm, and the specific solution we propose in the form of a Siamese neural network. Furthermore, while adopting deep learning, motivated by its successes in the field and its unchallenged superiority over classical computer vision approaches, we also seek to leverage the advantages that transformers have over the previously employed convolutional neural networks, and in particular their non-local attention mechanisms, which ought to be particularly useful in ancient coin analysis by associating semantically but not visually related distal elements of a coin’s design. Evaluated on a large data corpus of 14,820 images and 7605 issues, using transfer learning and only a small training set of 542 images of 24 issues, our Double Siamese ViT model is shown to surpass the state of the art by a large margin, achieving an overall accuracy of 81%. Moreover, our further investigation of the results shows that the majority of the method’s errors are unrelated to the intrinsic aspects of the algorithm itself, but are rather a consequence of unclean data, which is a problem that can be easily addressed in practice by simple pre-processing and quality checking. Publisher PDF

With the constant changes in modern industry, companies in the manufacturing field must always keep close attention to their performance. There is an increasing emphasis on the benefits of monitoring business performance for the goal of increasing company success. In this competitive environment for manufacturing companies, it is important to keep business running as smoothly as possible. Lean production and digital manufacturing in the wave of the fourth industrial revolution allow manufacturing companies to improve their processes and work methods., Vykstant nuolatiniams pokyčiams šiuolaikinėje pramonėje, gamybos srityje veikiančios įmonės visada turi atidžiai stebėti savo rezultatus. Vis dažniau pabrėžiama verslo veiklos našumo stebėsenos nauda siekiant didinti įmonės sėkmę. Šioje konkurencinėje aplinkoje gamybos įmonėms svarbu, kad verslas vystytųsi kuo sklandžiau. “Lean” ir skaitmeninė gamyba ketvirtosios pramonės revoliucijos bangoje sudaro sąlygas gamybos įmonėms tobulinti procesus ir darbo metodus.

Massive surges of enrollments in courses have led to a crisis in several computer science departments - not only is the demand for certain courses extremely high from majors, but the demand from non-majors is also very high. Much of the time, this leads to significant frustration on the part of the students, and getting seats in desired courses is a rather ad-hoc process. One approach is to first collect information from students about which courses they want to take and to develop optimization models for assigning students to available seats in a fair manner. What makes this problem complex is that the courses themselves have time conflicts, and the students have credit caps (an upper bound on the number of courses they would like to enroll in). We model this problem as follows. We have n agents (students), and there are "resources" (these correspond to courses). Each agent is only interested in a subset of the resources (courses of interest), and each resource can only be assigned to a bounded number of agents (available seats). In addition, each resource corresponds to an interval of time, and the objective is to assign non-overlapping resources to agents so as to produce "fair and high utility" schedules. In this model, we provide a number of results under various settings and objective functions. Specifically, in this paper, we consider the following objective functions: total utility, max-min (Santa Claus objective), and envy-freeness. The total utility objective function maximizes the sum of the utilities of all courses assigned to students. The max-min objective maximizes the minimum utility obtained by any student. Finally, envy-freeness ensures that no student envies another student’s allocation. Under these settings and objective functions, we show a number of theoretical results. Specifically, we show that the course allocation under the time conflicts problem is NP-complete but becomes polynomial-time solvable when given only a constant number of students or all credits, course lengths, and utilities are uniform. Furthermore, we give a near-linear time algorithm for obtaining a constant 1/2-factor approximation for the general maximizing total utility problem when utility functions are binary. In addition, we show that there exists a near-linear time algorithm that obtains a 1/2-factor approximation on total utility and a 1/4-factor approximation on max-min utility when given uniform credit caps and uniform utilities. For the setting of binary valuations, we show three polynomial time algorithms for 1/2-factor approximation of total utility, envy-freeness up to one item, and a constant factor approximation of the max-min utility value when course lengths are within a constant factor of each other. Finally, we conclude with experimental results that demonstrate that our algorithms yield high-quality results in real-world settings., LIPIcs, Vol. 256, 4th Symposium on Foundations of Responsible Computing (FORC 2023), pages 8:1-8:23

Purpose Although service research typically asserts that institutions coordinate actors’ value creation processes, institutions and resources are not necessarily transparent, aligned, or pre-existing. This paper aims to develop a more granular perspective on how actors coordinate for value. Design/methodology/approach Drawing on the established concepts of signaling and screening theory, this paper adopts a service marketing perspective to explore how independent heterogeneous actors coordinate for value creation at the individual level. Illustrative cases of corporate startup collaborations are presented in support of the proposed conceptual framework. Findings Actors share and acquire information through signaling and screening activities in a coordinative dialogue with other actors. These resource integration activities (for resource creation and matching) affect actors’ valuations and future actions. Originality/value The one-sided explanations of coordination in the existing literature reflect the dominance of the institutional theory. By contrast, the proposed agency-oriented perspective based on the integration of signaling and screening functions offers a more granular conceptualization of the resource integration process. As well as capturing how actors use coordinating dialogue to match resources and institutions, this account also shows that matching is a core element of resource integration rather than an antecedent. The findings indicate paths for future research that focus on the actor.

In this paper, We study how an on the job training program targeting low-income jewellery artisans (SOKO) impact on their vulnerability to poverty in Kenya. We use propensity score matching to assess SOKO's impact on the poverty likelihood of artisans. We find that SOKO artisans have a lower vulnerability to poverty as compared to artisans with similar socio-demographic characteristics but no SOKO affiliation. We also find that female artisans affiliated with SOKO are more vulnerable to poverty as compared to male artisans. Our findings are robust to various propensity score matching specifications and to alternative measures of vulnerability to poverty.

The Finger-vein recognition (FVR) method has received increasing attention in recent years. It is a new method of personal identification and biometric technology that identifies individuals using unique finger-vein patterns, which is the first reliable and suitable area to be recognized. It was discovered for the first time with a home imaging system; it is characterized by high accuracy and high processing speed. Also, the presence of patterns of veins inside one's body makes it almost difficult to repeat and difficult to steal. Based on the increased focus on protecting privacy, that also produces vein biometrics safer alternatives without forgery, damage, or alteration over time. Fingerprint recognition is beneficial because it includes the use of low-cost, small devices which are difficult to counterfeit. This paper discusses preceding finger-vein recognition approaches systems with the methodologies taken from other researchers' work about image acquisition, pretreatment, vein extraction, and matching. It is reviewing the latest algorithms; continues to critically review the strengths and weaknesses of these methods, and it states the modern results following a key comparative analysis of methods.

Motivated by adjacency in perfect matching polytopes, we study the shortest reconfiguration problem of perfect matchings via alternating cycles. Namely, we want to find a shortest sequence of perfect matchings which transforms one given perfect matching to another given perfect matching such that the symmetric difference of each pair of consecutive perfect matchings is a single cycle. The problem is equivalent to the combinatorial shortest path problem in perfect matching polytopes. We prove that the problem is NP-hard even when a given graph is planar or bipartite, but it can be solved in polynomial time when the graph is outerplanar.

We prove that in a market where agents rank objects independently and uniformly at random, there exists an assignment of objects to agents with a constant average rank (i.e., an average rank independent of the market size). The proof builds on techniques from random graph theory and the FKG inequality (Fortuin et al. (1971)). When the agents' rankings are their private information, no Dominant Strategy Incentive Compatible mechanism can implement the assignment with the smallest average rank; however, we show that there exists a Bayesian Incentive Compatible mechanism that does so. Together with the fact that the average rank under the Random Serial Dictatorship (RSD) mechanism grows infinitely large with the market size, our findings indicate that the average rank under RSD can take a heavy toll compared to the first‐best, and highlight the possibility of using other assignment methods in scenarios where average rank is a relevant objective.

PurposeThis study examines the impact of access to credit on the technical efficiency (TE) of maize-producing smallholder farmers in Ethiopia and explores factors determining credit utilization.Design/methodology/approachThe study relies on nationally representative data collected in 2015/2016. The data are analyzed by combining the Propensity Score Matching technique with a stochastic frontier model that corrects selectivity bias arising from unobserved variables.FindingsThe result shows that credit service improves TE and helps smallholder farmers to achieve the maximum possible output level from a given set of inputs used.Originality/valueTo the best of author’s knowledge, no study has yet measured the impact of access to credit on TE by controlling for both observed and unobserved heterogeneities. Existing research relied on a single production frontier model, assuming that credit users and non-users have similar production characteristics or ignored selection bias due to observable and unobservable characteristics.

Placing micro-textures on a tool surface can play an anti-wear and friction-reducing role and capture impurities and improve the tool-chip friction state, thus improving the cutting performance of the tool and the quality of the workpiece. To ensure the processing quality in the micro-texture-coated tool-cutting process, the process parameters and micro-texture parameters are limited to smaller parameters, which reduces the processing efficiency and increases the cost. Aiming at this problem, this paper designs orthogonal experiments of the cutting process and micro-texture parameters, builds an experimental platform for milling titanium alloy with a micro-texture-coated ball-end milling cutter, analyzes the influence of cutting parameters on tool milling performance and workpiece quality, establishes a high fitting prediction model, and optimizes parameters. The results show that the cutting parameters significantly affect the milling force, tool wear, and workpiece surface roughness, which are in the first response level, and the micro-texture parameters, which are in the second response level. It is proven that micro-texture has anti-wear and anti-friction effects, and it is found that micro-texture parameters affect the evaluation index by changing the distribution state of the micro-texture. It is found that the multiple linear regression model fits better. Parameter optimization results are: v = 159.4232 (m/min), ap = 0.211 (mm), f = 0.06 (mm/r), micro-pit diameter D = 62.3429 (μm), distance from blade L = 121.5184 (μm), and micro-pit spacing L1 = 235.6443 (μm). It provides some guidance for the selection of micro-texture parameters and cutting parameters on a micro-texture-coated tool.

International audience; A set of segments in the plane may form a Euclidean TSP tour or a matching, among others. Optimal TSP tours as well as minimum weight perfect matchings have no crossing segments, but several heuristics and approximation algorithms may produce solutions with crossings. To improve such solutions, we can successively apply a flip operation that replaces a pair of crossing segments by non-crossing ones. This paper considers the maximum number D(n) of flips performed on n segments. First, we present reductions relating D(n) for different sets of segments (TSP tours, monochromatic matchings, red-blue matchings, and multigraphs). Second, we show that if all except t points are in convex position, then D(n) = O(tn^2), providing a smooth transition between the convex O(n^2) bound and the general O(n^3) bound. Last, we show that if instead of counting the total number of flips, we only count the number of distinct flips, then the cubic upper bound improves to O(n^8/3).

When solving optimization problems that arise from real-world decision-making processes, uncertainty is a ubiquitous phenomenon that poses a significant obstacle. More often than not, lack of (full) knowledge about certain input parameters requires us to make decisions without knowing what their full effects will be. This thesis investigates how to algorithmically deal with such uncertainties when solving matching and packing problems. Both matching and packing problems are well-studied and among the most fundamental problems in combinatorial optimization. In matching problems, the task is to find a set of disjoint pairs of items, a matching, while in packing problems, items need to be assigned to containers with limited capacities. Additionally, there is an optimization objective, such as minimizing the cost of the matching or maximizing the value of packed items. Both problems have numerous practical applications in which uncertainty plays an important role. It may manifest itself, for instance, in the form of unknown items that are revealed only over time. It should come as no surprise that missing information about crucial problem parameters generally prevents us from reaching the same quality as an optimal offline solution. We consider several matching and packing problems and design algorithms that compute provably good solutions despite uncertainty in the input. Specifically, we consider the following models of uncertainty: online, recourse, and dynamic.

The 1989 Convention on the Rights of the Child is the main legal instrument on the protection of children. It embodies four general principles, including The best interests of the child. Although there is no standard definition of "best interests of the child," the term generally refers to the deliberation that courts undertake when deciding what type of services, actions, and orders will best serve a child as well as who is best suited to take care of a child. "Best interests" determinations are generally made by considering a number of factors related to the child's circumstances and the parent or caregiver's circumstances and capacity to parent, with the child's ultimate safety and well-being the paramount concern. CRC neither offers a precise definition, nor explicitly outlines common factors of the best interests of the child, but stipulates that: the best interests must be the determining factor for specific actions, notably adoption and separation of a child from parents against their will; the best interests must be a primary consideration for all other actions affecting children, whether undertaken by public or private social welfare institutions, courts of law, administrative authorities or legislative bodies. The best interests of the child stands as a main principle in the Moldovan legislation regarding child protection including the Law on adoptions but, unfortunately, it is not always taken into consideration by authorities., {"references":["1.\tConvenția privind Drepturile Copilului, New York, 20.11.1989.","2.\tLegea Nr.140 din 14.06.2013 privind protecţia specială a copiilor aflaţi în situaţie de risc şi copiilor separaţi de părinţi. În: Monitorul Oficial al Republicii Moldova, 2013, nr.167-172, art.534.","3. Legea nr.99 din 28.05.2010 privind regimul juridic al adopției. În: Monitorul Oficial al Republicii Moldova, 2010, nr.131-134 art.441."]}

This paper proposes a model of the firm as a “team assembly technology,” with the aim of explaining why differences between firms represent a large and growing dimension of wage inequality. In the model, firms assign tasks to workers who vary in overall quality and task specific skills. Hiring takes place in a frictional labor market. Worker-task specialization not only reinforces the potential gains from team production, but also endogenously generates coworker complementarity: the quality of the least capable team member disproportionately influences joint output. In equilibrium, therefore, employers hire workers of similar quality and those with superstar teams pull away in terms of productivity and pay. The key model mechanisms are validated using rich administrative micro data. A theory-informed measure of coworker complementarity doubles from the mid-1980s to the 2010s, mirroring a shift towards greater task complexity. According to a structural estimation exercise, this rise explains close to 40% of the empirically observed increase in the between-firm share of wage inequality in Germany. Additionally, the model sheds light on how the interaction between specialization and labor market frictions influences total factor productivity.

Given an undirected graph G and a real edge-weight vector, the connected subgraph problem consists of finding a maximum-weight subset of edges which induces a connected subgraph of G. In this paper, we establish a link between the complexity of the connected subgraph problem and the matching number. We study the separation problem associated with the Matching-partition inequalities wich are introduced by Didi Biha et al. [4] for the connected subgraph polytope.

In strategy-proof mechanisms truth-telling is a dominant strategy yielding optimal results for all participants, yet according to experimental evidence truthful revelation rates are worryingly low. This thesis is based on the growing realm of literature finding that participants tend not to play their dominant strategy, i.e. tell the truth, within matching markets even when given strategy-proof mechanisms. I design an experiment using the well-known Gale-Shapley Deferred Acceptance (DA) algorithm that aims to test whether using tutorials helps participants better understand that truth-telling is their optimal strategy within strategy-proof mechanisms. These tutorials allow participants to practice their approach and observe the outcome of their choices before having to commit to a final strategy. I hypothesise that participant engagement in tutorials will increase truth-telling rates in matching mechanisms and predict that given advice alone reduces rates of truthful preference revelation, participant engagement in tutorials can effectively mitigate the misleading power of advice. This thesis finds that the proportion of participants that told the truth was 3% lower if they received the tutorials compared to when no additional information was presented. However, tutorials improve on truth-telling rates compared to advice as 31% more people told the truth when given tutorials and no advice compared to if they were presented with advice alone. Additionally, participants engaging with both advice and tutorials together had truth-telling rates 11% higher than those given solely advice, which further supports the effectiveness of tutorials in overcoming the misleading effect of advice.

Fully pairing all elements of a set while attempting to maximize the total benefit is a combinatorically difficult problem. Such pairing problems naturally appear in various situations in science, technology, economics, and other fields. In our previous study, we proposed an efficient method to infer the underlying compatibilities among the entities, under the constraint that only the total compatibility is observable. Furthermore, by transforming the pairing problem into a traveling salesman problem with a multi-layer architecture, a pairing optimization algorithm was successfully demonstrated to derive a high-total-compatibility pairing. However, there is substantial room for further performance enhancement by further exploiting the underlying mathematical properties. In this study, we prove the existence of algebraic structures in the pairing problem. We transform the initially estimated compatibility information into an equivalent form where the variance of the individual compatibilities is minimized. We then demonstrate that the total compatibility obtained when using the heuristic pairing algorithm on the transformed problem is significantly higher compared to the previous method. With this improved perspective on the pairing problem using fundamental mathematical properties, we can contribute to practical applications such as wireless communications beyond 5G, where efficient pairing is of critical importance. As the pairing problem is a special case of the maximum weighted matching problem, our findings may also have implications for other algorithms on fully connected graphs.

Altres ajuts: acords transformatius de la UAB ; ICREA Academia programme 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 withthe 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.

This paper provides micro-econometric evidence on the effectiveness of Active Labor Market Policies (ALMP) in Poland. We sketch the theoretical framework of matching estimators as a substitute for randomization in labor market programs. Using retrospective data from the 18th wave of the Polish Labor Force Survey we implement a conditional difference-in-differences matching estimator of treatment effects. Treatment and control groups are matched over individual observable characteristics and pre-treatment labor market histories to minimize bias from unobserved heterogeneity. We also require that observations on controls are from the same regional labor market and from an identical phase of the transition cycle. Considering as the outcome a multinomial variable of labor market status, our first important finding suggests that training of men and women has a positive effect on the employment probability. For men public works and intervention works have negative treatment effects, while participation in intervention works does not affect women's employment probabilities. We attribute the negative treatment effects for men to benefit churning rather than to stigmatization of intervention and public works participants

Bisher mangelt es an kontrollierten Untersuchungen zum Effekt des offenen Vollzugs auf die Legalbewährung, da vorherige Studien unterschiedliche Gruppen von Inhaftierten miteinander verglichen. Um diesem Selektionseffekt entgegenzuwirken, wurden in der vorliegenden Studie mittels Matching-Verfahren vergleichbare Gruppen von Gefangenen gebildet. Mit Hilfe von Bundeszentralregisterdaten konnten die Rückfallquote, -geschwindigkeit und -schwere untersucht sowie individuelle Risiko- und Schutzfaktoren der Gefangenen kontrolliert werden. Die Ergebnisse zeigen, dass die Unterbringung im offenen Vollzug über die Positivauswahl von Gefangenen hinaus einen eigenständigen Effekt hat und das Risiko einer erneuten Inhaftierung signifikant reduziert. Until now, there has been a lack of research on the effect of being incarcerated in an open prison on legal probation. Previous studies have mostly compared quite different groups of prisoners. In order to counteract this selection bias, this study forms comparable groups of prisoners from the open and closed prison systems using matching procedures. Data from the Federal Central Criminal Register were used to examine the rates, speed and severity of recidivism, while individual risk and protection factors were statistically checked. The results show that incarceration in an open prison has an independent effect on legal probation - beyond the effect of positive selection of prisoners - and significantly reduces reincarceration.

The theoretical part of this paper provides the foundations of three statistical discriminations that are specific to the older workers: employers can think that a senior is characterized by (i) a shorter distance to the retirement age, (ii) a larger distance to the technological frontier, and/or (iii) a smaller ability to move from old toward new occupations than a younger worker. In the empirical part of the paper, a controlled experiments is designed in order to test each of these statistical discriminations. We also present a "pure" discrimination equilibrium and a controlled experiments specific to this assumption. Our empirical results, based on data collected in France, support the view that the older worker are discriminated in the hiring process via these 4 channels. This suggests that the French gap in the employment rate of the older workers is partially explained by significant discriminations., La partie théorique de cet article pose les bases de trois discriminations statistiques propres aux seniors : les employeurs peuvent penser qu'un senior se caractérise par (i) une courte distance à l'âge de la retraite, (ii) une distance plus grande à la frontière technologique, et/ou (iii) une plus faible capacité qu'un jeune travailleur à passer d'un ancien vers un nouveaux métiers. Dans la partie empirique de l'article, une expérience contrôlée est conçue afin de tester chacune de ces discriminations statistiques. Nous présentons également un équilibre du marché du travail où il existe de la discrimination "pure". Une expérimentation contrôlée spécifique à cette hypothèse est alors menée. Nos résultats empiriques, basés sur des données collectées en France, confirment l'hypothèse que les seniors sont discriminés à l'embauche via ces 4 canaux. Ceci suggère que l'écart français du taux d'emploi des seniors s'explique en partie par des discriminations importantes.

Drawing from the extremely novel impact investing landscape and the limited existing literature on the topic, it appears that investing in social enterprises should come at the cost of partially sacrificing financial returns to invested capital. This paper investigates the existence of this tradeoff by assessing how the performance of impact investing funds compares to that of traditional private equity and venture capital operators. Focusing on portfolio firm operating performance, we construct a dataset of 85 impact-investing observations and 5310 traditional observations over the period ranging from 2009 to 2020, in order to compare the performance of the traditional investor-backed firms with those of sustainable companies participated by social impact investors. Advanced matching methods such as Radius and Kernel matching suggest that the composition of the shareholding structure significantly affects the profitability of the company, with traditional firms outperforming their socially-concerned counterparts. Looking instead within the subsample of impact investor portfolio companies, and focusing only on the post-investment observations, we analyze how the percentage owned by the impact investors impacts the performance of the owned companies. The results show that, similarly to traditional ownership, a greater share controlled by impact investors leads to higher returns.

Local negative externalities of an establishment of wind turbines have been documented in research; often with the help of the hedonic methodology and property values. We use mixed methods including hedonic methodology, propensity score matching, and the difference-in-difference approach to estimate causal effects, using almost 600,000 real estate transactions in Sweden from 2005 to 2018. The results indicate that we can reject the hypothesis that proximity to wind turbines does not impact property values, and this impact is relatively strong and varies over time and geographic region. Difference-in-difference with matching confirms estimates in the hedonic price equation studies. Furthermore, there is no indication of pre-event differences in house price outcomes based on distance from new wind turbines. Depending on the region, the total negative capitalisation amounts to between 10 and 25 percent within 0–2 kilometres from the wind power plant. We apply these estimates to the total housing stock in three different potential future development areas. Although effects per property are relatively marginal, the total effects of a wind farm establishment will be significant if they are located in densely populated areas.

We revisit the issue of the energy efficiency (EE) gap by explicitly acknowledging the two-sided nature of the rental housing market and two-sided asymmetries of information between tenants and landlords. Employing a theoretical matching model, we show that Energy Performance Certificates (EPCs) that signal a dwelling’s energy performance induce optimal EE investments by landlords only if tenants pay their energy expenditures in full. When landlords pay part of the energy expenditures, they seek tenants who will conserve energy. Our model shows that asymmetry of information over tenant characteristics results in suboptimally low investments in EE. This may even render EPCs counterproductive. As a remedy, we show that tenant-side signaling needs to be rolled out jointly with EPCs and may even be sufficient when contracts include energy expenditures. Data from an original survey provides support for these insights and suggests that information on the tenants’ side contributes to more EE investment.

Anyone who has attended a statistics class has heard the old adage “correlation does not imply causation,” usually followed by a series of hilarious graphs showing spurious correlations. Even if we strongly agree with it, this reminder has been taken a little too far: it is repeated like a mantra to criticize every observational study as being unable to detect causation behind statistical association. This chapter helps the reader go beyond the mantra, firstly, by explaining that “correlation does not imply causation” in observational studies because of selection bias (i.e. the composition of treatment and control groups follows a non-random selection) and parametric model dependence. Then, it introduces readers to weighting and matching techniques, smart statistical tools for reducing imbalance in the empirical distribution of pretreatment covariates between the treatment and control groups. Lastly, it provides an empirical illustration by focusing on two powerful algorithms: the entropy balancing (EB) and the coarsened exact matching (CEM). The chapter ends with caveats.

Mit der positiven Entwicklung des Arbeitsmarkts ist die Zahl der Beschäftigten in Deutschland zwischen 2010 und 2022 um rund sechs Millionen gestiegen. Während die Zahl der offenen Stellen im Jahr 2022 einen neuen Höchststand erreicht hat, ist die Zahl der arbeitsuchenden Personen erheblich gesunken. Damit fällt es Betrieben zunehmend schwer, geeignete Arbeitskräfte zu rekrutieren. Mit Daten der IAB-Stellenerhebung und der Statistik der Bundesagentur für Arbeit dokumentieren wir die zunehmende Anspannung der Arbeitsmärkte und untersuchen die Konsequenzen für betriebliche Rekrutierungsprozesse und Beschäftigung., IAB-Kurzbericht

This paper aims to investigate whether there is empirical evidence supporting the learning-to-export hypothesis, which has received little attention in the literature. By taking full advantage of plant-product level data from Korea during 1990-1998, we find some evidence for the learning-to-export effect, especially for the innovated product varieties with delayed exporters: their productivity, together with research and development and investment activity, was superior to their matched sample. On the other hand, this learning-to-export effect was not significantly pronounced for industries protected by import tariffs. Thus, our empirical findings suggest that it would be desirable to implement certain policy tools to promote the learning-to-export effect, whereas tariff protection is not justifiable for that purpose.

Purpose Coronavirus increases mortality rate in people with underlying disease. The purpose of the present research was to compare the clinical outcomes in Covid-19 patients with and without underlying diabetes disease using propensity score matching. Methods A matched case–control study was conducted on 459 diabetic patients with Covid-19 (case group) and 459 non-diabetic patients with Covid-19 (control group). Matching in two groups was performed using propensity score matching method. The effect of covariates on the clinical outcome of the patients (recovery-death) was assessed using logistic regression and the associations of factors with the patients' survival were determined using Cox proportional hazards regression model. Data were analyzed using R software. Results The mean (standard deviation) age of patients in the case and control groups were 65.77 (12.2) and 65.8 (12.24), respectively. 196 patients (43%) in the case group, and 249 patients (54%) in the control group were male (with P-value

In this era of the digital world, data play a central role and are continuously challenging spectrum efficiency. With the introduction of enriched multimedia user-generated content, the challenges are even more aggravated. In this vein, uplink caching is considered as one of the promising solutions to effectively cater the user’s demands. One of the main challenges for uplink caching is duplication elimination. In this paper, a cache enabled uplink transmission with a duplication elimination scheme is proposed. The proposed scheme matches the mobile’s data to be uploaded with the cached contents both at mobile station (MS) and small base station (SBS). In contrast to existing techniques, the proposed scheme broadcasts the cached contents at an SBS to all the MSs under its footprint. This provides MS an opportunity to exploit the list of cached contents before uploading its data. A MS only uploads its data if it is not already cached at an SBS. This significantly reduces duplication before the real transmission takes place. Furthermore, the proposed technique reduces energy consumption in addition to improving spectral efficiency and network throughput. Besides, a higher caching hit ratio and lower caching miss ratio are also observed as compared to other schemes. The simulation results reveal that the proposed scheme saves 97% energy for SBS, whereas 96–100% energy is saved for MS on average.

Field data is often limited regarding causal inference. This is partly because randomization techniques are often impractical or unethical within certain fields (e.g., randomly assigning individuals to different types of classroom instruction in educational settings). Matching procedures, like propensity score matching (PSM; Rosenbaum & Rubin, 1983), are regularly used to strengthen interpretations of group membership-effects in field research. By matching individuals from different subgroups of a field sample (e.g., participations vs. nonparticipation in a special education program), relevant confounds to group membership-effects (e.g., socio-economic status) can be balanced out and thereby eliminated retrospectively. That way, matching turns field data into quasi-experimental data. Currently, the most prominent approach to matching individuals is nearest neighbor matching (NNM) (see Austin, 2014; Austin & Stuart, 2015; Heinz et al., 2022; Jacovidis, 2017). Available statistical software (e.g., R-packages like MatchIt, Ho et al., 2011), however, does not fully realize the potential of NNM to reduce sample-related bias in field data due to unsystematic procedures for the identification of apt pairs to match. Furthermore, existing matching applications are limited to two-group designs (that being said, weighting applications for more than two groups do exists, e.g., MMW-S, Hong, 2012). In addition, balance estimation, as a matching quality check, is often conducted rudimentarily (e.g., by solely reporting between-group post-matching differences). So far, conventions on balance estimation for more than two groups are absent. To address these shortcomings, we developed a systematic algorithm, designed for matching individuals from two or more groups alongside a set of adequate balance estimates. We call it “MAGMA” (for MAny-Group MAtching). In this work, we demonstrate and evaluate the MAGMA-algorithm, using two empirical examples from extensive field data.

The vegetation covering regions is confined due to deforestation, mining industries, and environmental factors. The intensified deforestation and industrial development processes impact the vegetation coverage and fail to meet the food demands. Therefore, accurate monitoring of such regions aids in preventing adversary processes and their plant extinction. The monitoring process requires accurate data collection and analysis to identify the root cause that can be due to human/climatic/environmental changes. This article introduces a concentrated stream data processing method (CSDPM) assisted by an extreme learning paradigm. The different causes are analyzed using the extracted features in different learning perceptron layers. In this learning, the accumulated data is analyzed for similar features and trained for the consecutive or lagging input data streams. The monitoring process concluded with the learning output by classifying the plant extinction reason. Therefore, the identified reason is addressed through official policies with new recommendations or alternate vegetation improvements. More specifically, the data concentrated towards deforestation are the fundamental data required for feature matching. The features are initially trained from the existing datasets and previously acquired data from the converted landscapes. This proposed method is analyzed using the metrics analysis rate, analysis time, recommendation rate, and complexity.

Motivation Seeking probabilistic motifs in a sequence is a common task to annotate putative transcription factor binding sites (TFBS). Useful motif representations include Position Weight Matrices (PWMs), dinucleotidic PWMs (di-PWMs), and Hidden Markov Models (HMMs). Dinucleotidic PWMs combine the simplicity of PWMs-a matrix form and a cumulative scoring function-, but also incoporate dependency between adjacent positions in the motif (unlike PWMs which disregard any dependency). For instance, to represent binding sites, the HOCOMOCO database provides di-PWM motifs derived from experimental data. Currently, two programs, SPRy-SARUS and MOODS, can search for di-PWMs in sequences. Results We propose a Python package, dipwmsearch, which provides an original and efficient algorithm for this task (it first enumerates matching words for the di-PWM, and then search them at once in the sequence even if it contains IUPAC codes). The user benefits from an easy installation via Pypi or conda, a documented Python interface, and reusable example scripts that smooth the use of di-PWMs.; La recherche de motifs probabilistes dans une séquence est une tâche courante pour annoter les sites putatifs de liaison des facteurs de transcription (TFBS). Les représentations utilisées des motifs incluent les matrices de poids de position (PWM), les PWM dinucléotidiques (di-PWM) et les modèles de Markov cachés (HMM). Les PWM dinucléotidiques combinent la simplicité des PWM -- une forme de matrice et une fonction de score cumulative --, mais intègrent également la dépendance entre les positions adjacentes du motif (contrairement aux PWM qui ne tiennent pas compte de cette dépendance). Par exemple, pour représenter les sites de liaison, la base de données HOCOMOCO fournit des motifs di-PWM dérivés de données expérimentales. Actuellement, deux programmes, SPRy-SARUS et MOODS, peuvent rechercher des di-PWM dans des séquences.Nous proposons un package Python, /dipwmsearch/, qui fournit un algorithme original et efficace pour cette tâche: il énumère d'abord les mots correspondants à une di-PWM, puis les recherche en une seule fois dans la séquence (même si elle contient des codes IUPAC). L'utilisateur bénéficie d'une installation facile via /Pypi/ ou /conda/, d'une interface Python documentée, et de scripts d'exemple réutilisables qui facilitent l'utilisation des di-PWMs.Accès:1. Python package: https://pypi.org/project/dipwmsearch/2. Documentation: https://rivals.lirmm.net/dipwmsearch/3. Conda package: https://anaconda.org/atgc-montpellier/dipwmsearch4. Source code: https://gite.lirmm.fr/rivals/dipwmsearch

This work proposes a tool to compare a high-precision surface scan with its original CAD model. The project is divided into three steps: how to process the CAD files, compute and optimize the registration, and develop tools for visualization. Because CAD files can contain multiple representations, we can't work directly with them. Normally this is approached by triangulating the described components and simplifying the mesh for a fast rendering, but this doesn't work for our high-density scans. Instead, we need to process the CAD to obtain a point cloud with a parameterized distance between points ---this will give a good starting point for the registration---. Next, the registration can be divided into two parts, coarse and fine. For the coarse register, we adapt the Initial Alignment Sample Consensus algorithm (IA RanSac) to automate the configuration settings and optimize the time for our input size. While in the fine register we will use the classic Iterative Closest Point (ICP). Due to the approach being a random consensus and the input being two big points cloud, reducing the number of points to a feasible number (statistically and computationally) will be essential to find a solution. For this, we developed a local optimizer that combines a set of LOD to find a global solution. Finally, to analyze the result, we have developed a color visualization interface with a set of modifier tools (colormaps, transparencies, range modifiers, etc.). This allows us to detect discrepancies between the two models that can be caused by wear or manufacturing imperfections.

The objective of this project is to make data and code available from research involving propensity scores methods led by Dr. Walter Leite, his colleagues and students at the Research and Evaluation Methodology program at University of Florida. It includes updated code and data for the examples in the book "Practical Propensity Score Methods Using R" (by Walter Leite, published by Sage Publications in 2017). The resources in this project cover estimation of propensity scores, propensity score weighting, matching and stratification, propensity score methods for multiple treatments, continuous treatments, and propensity score methods for multilevel data and with structural equation modeling.