Academic literature on the topic 'Aggregate entity'
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Journal articles on the topic "Aggregate entity"
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Hirose, Shoichi, and Junji Shikata. "Aggregate Entity Authentication Identifying Invalid Entities with Group Testing." Electronics 12, no. 11 (May 31, 2023): 2479. http://dx.doi.org/10.3390/electronics12112479.
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It is common to implement challenge-response entity authentication with a MAC function. In such an entity authentication scheme, aggregate MAC is effective when a server needs to authenticate many entities. Aggregate MAC aggregates multiple tags (responses to a challenge) generated by entities into one short aggregate tag so that the entities can be authenticated simultaneously regarding only the aggregate tag. Then, all associated entities are valid if the pair of a challenge and the aggregate tag is valid. However, a drawback of this approach is that invalid entities cannot be identified when they exist. To resolve the drawback, we propose group-testing aggregate entity authentication by incorporating group testing into entity authentication using aggregate MAC. We first formalize the security requirements and present a generic construction. Then, we reduce the security of the generic construction to that of aggregate MAC and group testing. We also enhance the generic construction to instantiate a secure scheme from a simple and practical but weaker aggregate MAC scheme. Finally, we show some results on performance evaluation.
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Guangyu, Lei, and Han Jichang. "Based on the CT Image Rebuilding the Micromechanics Hierarchical Model of Concrete." Advances in Civil Engineering 2022 (October 12, 2022): 1–12. http://dx.doi.org/10.1155/2022/2445901.
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Establishing a mesoscopic numerical model to investigate the mechanical properties of concrete has very important significance. This paper considers the random distribution of aggregate in concrete. The aggregate is assumed to be spherical, respectively, to simulate the interface layer as the entity unit or the contact elements. The random aggregate model and the interface model of random aggregate were established. Based on the CT image and the application of MATLAB and MIMICS software, the different characteristics of the concrete model for 3D reconstruction were set up. Through comparative analysis of the advantages and disadvantages of different models, considering the CT number included in the CT images, this paper establishes the reconstruction model, which includes the shape of concrete aggregates, gradation, holes, etc. The analysis results have shown that the model can infer realistic concrete behavior, providing a new approach for studying concrete properties at the mesoscale.
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Korkontzelos, Ioannis, Dimitrios Piliouras, Andrew W. Dowsey, and Sophia Ananiadou. "Boosting drug named entity recognition using an aggregate classifier." Artificial Intelligence in Medicine 65, no. 2 (October 2015): 145–53. http://dx.doi.org/10.1016/j.artmed.2015.05.007.
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Cui, Xiaohui, Xiaolong Qu, Dongmei Li, Yu Yang, Yuxun Li, and Xiaoping Zhang. "MKGCN: Multi-Modal Knowledge Graph Convolutional Network for Music Recommender Systems." Electronics 12, no. 12 (June 15, 2023): 2688. http://dx.doi.org/10.3390/electronics12122688.
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With the emergence of online music platforms, music recommender systems are becoming increasingly crucial in music information retrieval. Knowledge graphs (KGs) are a rich source of semantic information for entities and relations, allowing for improved modeling and analysis of entity relations to enhance recommendations. Existing research has primarily focused on the modeling and analysis of structural triples, while largely ignoring the representation and information processing capabilities of multi-modal data such as music videos and lyrics, which has hindered the improvement and user experience of music recommender systems. To address these issues, we propose a Multi-modal Knowledge Graph Convolutional Network (MKGCN) to enhance music recommendation by leveraging the multi-modal knowledge of music items and their high-order structural and semantic information. Specifically, there are three aggregators in MKGCN: the multi-modal aggregator aggregates the text, image, audio, and sentiment features of each music item in a multi-modal knowledge graph (MMKG); the user aggregator and item aggregator use graph convolutional networks to aggregate multi-hop neighboring nodes on MMKGs to model high-order representations of user preferences and music items, respectively. Finally, we utilize the aggregated embedding representations for recommendation. In training MKGCN, we adopt the ratio negative sampling strategy to generate high-quality negative samples. We construct four different-sized music MMKGs using the public dataset Last-FM and conduct extensive experiments on them. The experimental results demonstrate that MKGCN achieves significant improvements and outperforms several state-of-the-art baselines.
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Aberbach, Adin, Mayank Kejriwal, and Ke Shen. "Multipartite Entity Resolution: Motivating a K-Tuple Perspective (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 21 (March 24, 2024): 23434–35. http://dx.doi.org/10.1609/aaai.v38i21.30417.
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Entity Resolution (ER) is the problem of algorithmically matching records, mentions, or entries that refer to the same underlying real-world entity. Traditionally, the problem assumes (at most) two datasets, between which records need to be matched. There is considerably less research in ER when k > 2 datasets are involved. The evaluation of such multipartite ER (M-ER) is especially complex, since the usual ER metrics assume (whether implicitly or explicitly) k < 3. This paper takes the first step towards motivating a k-tuple approach for evaluating M-ER. Using standard algorithms and k-tuple versions of metrics like precision and recall, our preliminary results suggest a significant difference compared to aggregated pairwise evaluation, which would first decompose the M-ER problem into independent bipartite problems and then aggregate their metrics. Hence, M-ER may be more challenging and warrant more novel approaches than current decomposition-based pairwise approaches would suggest.
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Tsukui, Kazuo, and Kenji Tadokoro. "Affinity Association between Polynucleotide, Glycoprotein, or Sulfated Polysaccharides and Disease-Associated Prion Protein." Microbiology Insights 2 (January 2009): MBI.S3103. http://dx.doi.org/10.4137/mbi.s3103.
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Proteinase-K resistant prion protein (PrPres) has the property to aggregate in TSE-injured animal tissues. We have developed a test method to discriminate scrapie-infected and mock-infected hamsters by detecting the PrPres in plasma. It seemed that aggregation of the PrPres with some heterogeneous molecule(s) enabled successful detection by this method. In order to investigate which molecule became the partner in the PrPres aggregates; we examined some molecules that could presumably have this ability. As a result, we found synthetic Poly-A RNA, especially in its denatured form, to be the most effective entity although glycoprotein, sulfated polysaccharide showed less effectiveness. DNA in the denatured form also has a high affinity, although in the presence of protein the effectiveness unsuccessful. On the basis of this result, it is possible that the PrPres aggregate in scrapie-infected hamster plasma is composed of PrPres and RNA.
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SEID, DAWIT, and SHARAD MEHROTRA. "AGGREGATE QUERY PROCESSING FOR SEMANTIC WEB DATABASES: AN ALGEBRAIC APPROACH." International Journal of Semantic Computing 01, no. 04 (December 2007): 479–95. http://dx.doi.org/10.1142/s1793351x07000226.
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As a growing number of applications represent data as semantic graphs like RDF (Resource Description Format) and the many entity-attribute-value formats, query languages for such data are being required to support operations beyond graph pattern matching and inference queries. Specifically the ability to express aggregate queries is an important feature which is either lacking or is implemented with little attention to the peculiarities of the data model. In this paper, we study the meaning and implementation of grouping and aggregate queries over RDF graphs. We first define grouping and aggregate operators algebraically and then show how the SPARQL query language can be extended to express grouping and aggregate queries.
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Yi, Liu, Diao Xing-chun, Cao Jian-jun, Zhou Xing, and Shang Yu-ling. "A Method for Entity Resolution in High Dimensional Data Using Ensemble Classifiers." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/4953280.
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In order to improve utilization rate of high dimensional data features, an ensemble learning method based on feature selection for entity resolution is developed. Entity resolution is regarded as a binary classification problem, an optimization model is designed to maximize each classifier’s classification accuracy and dissimilarity between classifiers and minimize cardinality of features. A modified multiobjective ant colony optimization algorithm is employed to solve the model for each base classifier, two pheromone matrices are set up, weighted product method is applied to aggregate values of two pheromone matrices, and feature’s Fisher discriminant rate of records’ similarity vector is calculated as heuristic information. A solution which is called complementary subset is selected from Pareto archive according to the descending order of three objectives to train the given base classifier. After training all base classifiers, their classification outputs are aggregated by max-wins voting method to obtain the ensemble classifiers’ final result. A simulation experiment is carried out on three classical datasets. The results show the effectiveness of our method, as well as a better performance compared with the other two methods.
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Yuan, Xu, Qihang Lei, Shuo Yu, Chengchuan Xu, and Zhikui Chen. "Fine-grained relational learning for few-shot knowledge graph completion." ACM SIGAPP Applied Computing Review 22, no. 3 (September 2022): 25–38. http://dx.doi.org/10.1145/3570733.3570735.
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Few-shot knowledge graph completion (FKGC) task aims to infer missing entities or relations by using few-shot support instances in the knowledge graph. Existing FKGC methods focus on the learning of few-shot relation representations, which are obtained by aggregating the neighbor information of each entity. However, most of these models take the entity's neighbor relations and entities as the same hierarchy and do not make fine-grained distinctions, resulting in entity embeddings with low expressiveness, which may further decrease the quality of learned few-shot relation embeddings. Moreover, many of those models directly use the concatenation of the entity embeddings as the relation representations, and neglect the valuable interaction between relations. In this paper, we propose a fine-grained relational learning framework IDEAL for few-shot knowledge graph completion task. Specifically, we first propose a unique hierarchical attention encoder to aggregate the neighbor information of each entity from two levels, i.e., the entity-relation level and the relation-entity level. Then a relation recoding validator is proposed to formulate the interaction between different relations. Instead of obtaining the few-shot relation representations by using the entity embeddings, the relation recoding validator module aggregates the neighbor relations of each entity to encode the few-shot relation, which can reduce the over-dependence on specific entities in the few-shot relation encoding phase. The relation recoding module is also extended with respect to the excellent performance of the transformer in modeling sequence information. We then introduce a transformer encoder to extract underlying and valuable sequence information between relations. Extensive experiments are conducted on two datasets, i.e., NELL and Wiki. The experimental results demonstrate that our model outperforms state-of-the-art FKGC methods. Besides, we devise the ablation study to demonstrate the effectiveness of each key component. The case study also shows the interpretability of our model intuitively.
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Hager, Liesl. "The Insolvency Act’s deviation from the common law: Juristic ghost or aggregate approach?" South African Law Journal 138, no. 1 (2021): 152–70. http://dx.doi.org/10.47348/salj/v138/i1a7.
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In this article I engage with the provisions of the Insolvency Act 24 of 1936 regulating the dissolution of the universal partnership upon insolvency. Our common law prefers an aggregate approach to partnerships, meaning that a partnership enjoys no separate legal personality distinct from its composing partners. The lack of separate legal personality of a partnership is described by some academics as a ‘remarkable defect’. The Insolvency Act however creates an exception to this general rule by deeming a partnership to be a separate legal entity. The Insolvency Act’s deviation from the common-law rule and creation of a ‘juristic ghost’ is explored in this article. The ‘dual priorities’ rule, the aggregate theory and the entity theory are explained in this article. Furthermore, the judicial debates about the Act’s deviation are discussed. In conclusion, it is suggested that the presumption that legislation does not intend to change existing law should not apply when dealing with the Insolvency Act, as the legislature has expressly deviated from the common-law aggregate approach.
Dissertations / Theses on the topic "Aggregate entity"
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Cordero, Sanchez Celia. "Characterization of a mouse model for Tubular Aggregate Myopathy and development of small molecules." Doctoral thesis, Università del Piemonte Orientale, 2022. https://hdl.handle.net/11579/148545.
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Tubular aggregate myopathy (TAM) is one of a cluster of rare genetic diseases, together with Stormorken syndrome and York platelet syndrome (YPS). The aetiology of these diseases is the mutation in one of two key proteins, ORAIi and STIMÍ. Both proteins are the principai protagonists in Store-Operated Calcium Entry (SOC Entry), a mechanism of calcium homeostasis. Up to now, no mouse model has been designed bearing a luminal STIM1 mutation associated with the clinical diagnosis of any of the diseases. A mouse model bearing 11 15F mutation, which is associated with TAM and YPS, is extremely needed, to guarantee the effectiveness of putative treatment in patients bearing luminal STIM1 mutations. This thesis project demonstrates that the KI-STIM" mouse model is valid for both TAM and YPS, confirming at the same time the hypothesis of some authors, who defend that TAM, Stormorken, and YPS are indeed the spectra of the same disease whose symptoms differences are base in the position and effect of the point mutation.
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Jarige, Benoit. "La fiscalité internationale des sociétés de personnes : étude critique des images fiscales à la lumière des droits britannique et américain." Electronic Thesis or Diss., Bordeaux, 2022. http://www.theses.fr/2022BORD0099.
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La transparence, la semi-transparence, la translucidité ou encore la personnalité fiscale sont autant d’images fiscales formant le paradigme français de la fiscalité internationale des sociétés de personnes, en ce sens que ces images sont mobilisées pour poser et répondre aux problématiques relatives à l’imposition française du revenu réalisé sous la forme d’une société de personnes en situation d’extranéité. Par ce recours aux images fiscales, la conception française de la fiscalité internationale des sociétés de personnes distingue les sociétés de personnes de droit français de celles de droit étranger. D’une part, les sociétés de personnes de droit français, réputées semi-transparentes et disposant d’une personnalité fiscale distincte de leurs associés, sont considérées comme les sujets d’une imposition pourtant assumée par leurs associés. Sur ce fondement, ces sociétés sont qualifiées de résident au sens des conventions visant à éliminer les doubles impositions. Les règles conventionnelles de territorialité sont alors appliquées au niveau de la société et non à celui de leurs associés. D’autre part, le droit fiscal français accepte de recevoir la transparence fiscale des sociétés de personnes étrangère pour appliquer les conventions fiscales à leurs associés. Il en résulte une conception française de la fiscalité internationale des sociétés de personnes difficilement compréhensible, non seulement au regard de celle pratiquée par les droits étrangers, mais également au regard du droit interne. En se détachant du recours constant aux images fiscales pour se concentrer sur une étude des textes français, britannique et américain, la conception française de la fiscalité internationale des sociétés de personnes peut être écartée. Par cette étude critique des images fiscales, l’altérité véhiculée par les images fiscales entre les sociétés de personnes de droit français et les partnerships de droits anglais, écossais et américain peut être dépassée au profit d’une unité (Partie 1). Celle-ci renverse les fondements de la conception française de la fiscalité internationale des sociétés de personnes et offre alors la perspective de son renouvellement (Partie 2)Transparency, semi-transparency, translucency or fiscal personality are tax images used as a paradigm in the French conception of partnerships in international tax law, in that those images are used to think and resolve the issues raised by the taxation, in France, of international partnerships. Based on those images, the French conception of international taxation of partnership distinguishes between local partnerships and foreign partnerships. On the one hand, local partnerships are said to be semi-transparent or translucent and to have a fiscal personality distinct from their partners. Thusly, local partnerships are construed as the subject of a tax that is yet paid by the partners. Consequently, local partnerships are qualified as resident for the purpose of the bilateral conventions and the foreign partners cannot claim the application of the treaty. On the other hand, the recognition of the transparency of foreign partnerships is accepted in French tax law so the partners may claim the stipulations of the bilateral convention. This conception of international taxation of partnerships, founded on a dual approach of partnerships, is isolated from the taxation known in others countries and lacks coherence in the view of the French tax law. With a critical study of tax images in the light of the British law and the American law, this conception may be challenged. The comparison between French partnerships and British and American partnerships permits to overcome the otherness suggested by the resort of tax images, and to demonstrate instead the unity among those entities (Part 1). Once it has been ascertained, this unity challenges the foundation of the French conception of international taxation of partnership and allows the prospect of its renewal (Part 2)
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Endo, Yukari. "Dominant mutations in ORAI1 cause tubular aggregate myopathy with hypocalcemia via constitutive activation of store-operated Ca2+ channels." Kyoto University, 2015. http://hdl.handle.net/2433/198937.
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MEMBRETTI, MARCO. "Firm size and the Macroeconomy." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2023. https://hdl.handle.net/10281/403956.
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La tesi è formata da due capitoli su dinamica della distribuzione delle imprese e shock aggregati. Usando un modello ad imprese eterogenee, la tesi studia le fluttuazioni di ciclo economico dovute a shock alla tecnologia ed ai costi in entrata.This dissertation collects two essays on firm size dynamics and aggregate shocks. By employing a model with heterogeneous firms, search frictions and endogenous entry/exit we investigate the business cycle dynamics of the firm size distribution by looking at entry cost and technology shocks. The thesis is divided into two chapters.\\ The first chapter explores how an increase in entry costs affects the size of new entrants and the concentration of employment according to firm size, along with its effects on macro-variables such as unemployment and the exit rate. To this aim we use a BVAR model to estimate the response of such variables to an entry cost shock, then we develop a heterogeneous-firm model with search frictions and endogenous entry/exit dynamics calibrated on data from Business Dynamics Statistics (BDS) database to address our empirical results.\\ We find that positive entry cost shocks increase the average size of entrants and move employment shares toward the largest firms. These results reveal the role of entry costs' fluctuations in explaining the dynamics at business cycle horizons of both firm and employment share distributions according to size.\\ The second chapter perturbed the model with a technology shock to replicate the long-run differential of job destruction due to exit between small and large firms and its empirical response to technology shocks (estimated by a BVAR). Contrary to frameworks with \textit{exogenous} exit, the model is able to account for the volatility of exit and the differential of job destruction due to exit between small and large firms conditional to the technology shock. Moreover we find that not only entry but also exit is a viable amplification channel for the response of unemployment to the shock.\\
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Talfi, Mohamed. "Organisation des systèmes de retraite et modélisation des fonds de pension." Phd thesis, Université Claude Bernard - Lyon I, 2007. http://tel.archives-ouvertes.fr/tel-00325943.
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Des nombreux aspects des fonds de pension, nous nous intéressons ici à leur modélisation et à l'organisation des systèmes de retraites dans le monde. Dans une première partie, nous présentons les différentes organisations de systèmes de retraites et la modélisation des fonds de pension en général suivie de la modélisation dynamique discrète avec la modélisation statique comme cas particulier de la discrète. Ainsi, nous constatons que les différents systèmes de retraites sont caractérisés par une grande diversité, mais restent néanmoins regroupés sous trois grands groupes qui se croisent souvent. Ce sont : les retraites par répartition, les retraites par capitalisation et les retraites par subvention. Nous introduisons la modélisation des systèmes de retraites par capitalisation en commençant par donner une vision générale incorporant une typologie des risques de fonds de pension. Nous présentons ensuite les méthodes pratiques et courantes de la modélisation en temps discret. La deuxième partie de la thèse accueille les développements de la modélisation en temps continu. Dans une économie dynamique et un marché non nécessairement complet, avec une expression stochastique des évolutions de l'inflation et des prix, nous usons du zéro-coupon nominal et du zéro-coupon indexé sur les prix de la consommation. Grâce aux outils et principes des assurances, des valeurs actuarielles des flux continus de cotisations et pensions sont fournies. Tout en faisant le lien avec les résultats issus de la littérature, nous appuyons, aussi bien en première partie qu'en deuxième, les portefeuilles optimaux de fonds de pension avec leurs probabilités de ruine, par des illustrations à travers des exemples concrets et des simulations numériques.
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Solow, Benjamin Lewis. "Aggregate uncertainty, framing effects, and candidate entry." Thesis, 2016. https://hdl.handle.net/2144/19570.
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This dissertation studies how different voter characteristics and electoral rules affect the incentives and decisions to seek political office. The focus is on generalizing standard approaches to observed differences in the runoff rule and incorporating more accurate descriptions of voter behavior which may not be fully rational. In each chapter, I consider a model of strategic entry by candidates for office in democratic elections.
In the first chapter, I incorporate the observed differences in thresholds for first-round victory in a model of runoff elections. The set of equilibria varies substantially with the threshold, indicating that the 50 percent threshold used in most models is not innocuous. The set of equilibria immediately contains equilibria that were thought to exist only under plurality rule, whereas for thresholds above 50 percent, there is no change in the set of equilibria. Additionally, for any threshold under one half, there exist equilibria in which a candidate who loses with certainty still chooses to run. The set of two candidate equilibria is invariant to all thresholds under one third, and the set of multicandidate equilibria is invariant to all thresholds above one half.
In the second chapter, I introduce aggregate uncertainty by making candidates unsure of the distribution of voter preferences in the electorate. The set of three candidate equilibria expands and equilibrium platforms become more diverse. This provides a theoretical basis for Duverger’s Hypothesis. Equilibria also feature two common empirical phenomena. For instance, some candidates choose to enter despite losing with certainty in equilibrium. Also, in some equilibria, a Condorcet winning candidate (a candidate who would win every pairwise election) fails to win the election.
In the third chapter, I generalize the citizen-candidate model to a multidimensional setting and characterize the set of equilibria. I later incorporate two well-documented violations of the Weak Axiom of Revealed Preference in a model of plurality elections: the compromise and attraction effects. Entry by an extreme candidate may shift the frame of reference for some voters in ways which favor particular moderate candidates. Incorporating these preferences generate equilibria in which extremist candidates enter plurality elections in order to attractively frame their preferred moderate, even if the extremist has probability zero of obtaining office themselves.
Books on the topic "Aggregate entity"
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Bagnoli, Luca, and Massimo Cini, eds. La cooperazione sociale nell'area metropolitana fiorentina. Florence: Firenze University Press, 2009. http://dx.doi.org/10.36253/978-88-8453-415-6.
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This study proposes a reading of the financial statements of co-operatives operating within the Florentine metropolitan area, with a view to underscoring business aspects of a quantitative and monetary nature. The entrepreneurial nature of the co-operatives is taken as read, focusing as with any other corporate entity on assets and economic results as indicators of success. The financial statements were collected from co-operatives with their registered offices in the provinces of Florence, Prato and Pistoia for the financial years 2004-2007, and the accounts were then aggregated, reclassified and analysed. The observations on the resulting data are then broken down by province and by type of co-operative (A or B).
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DeSombre, Elizabeth R. Understanding Environmental Behavior. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190636272.003.0001.
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This chapter introduces the entire book, which is about what social science can tell us about the causes of environmental behavior and about how to change this behavior. In addition to an overview of the topics of each chapter, this introduction argues that individual behavior is worth examining: even though each act is in itself an unimaginably small contribution to any given environmental problem, individual behavior aggregates, and collectively these individual behaviors have enormous global effect. Nevertheless the argument of the book is not that we should persuade people individually to change their behavior: doing so is inefficient and ineffective, for reasons elaborated throughout the book. Instead, the focus should be on institutions and on incentives that affect in a larger way the behavior of individuals.
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Lay, Jann, and Tevin Tafese. Formalization and productivity: firm-level evidence from Viet Nam. UNU-WIDER, 2020. http://dx.doi.org/10.35188/unu-wider/2020/921-1.
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Using a firm-level panel dataset on private small- and medium-sized enterprises (SMEs) in Viet Nam’s manufacturing sector, this paper examines productivity dynamics of formal and informal firms. We decompose productivity changes into changes within and between formal and informal firms. We assess the contributions of firm entry and exit as well as informal–formal transitions. Our results show that productivity is considerably lower and misallocation more prevalent in the informal than in the formal sector. Yet, formalizing firms in Viet Nam make an important contribution to aggregate productivity growth among manufacturing SMEs, growing faster than other firms and increasing efficiency. We identify two ‘regimes’ of formalization. Until early 2010, more productive (previously) informal firms formalize. Policy changes and accelerated formalization then alter the characteristics of formalizers, as less productive firms become formal. While this formalization wave depresses average formal total factor productivity growth, the overall productivity effect is positive.
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Jockers, Matthew L. Macroanalysis. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252037528.003.0004.
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This chapter discusses the potentials of a computer-based macroanalytic approach to the study of literature. It first compares macroanalysis to macroeconomics as opposed to microeconomics, which can be seen as analogous to the study of individual texts via “close readings” whereas macroeconomics is about the study of the entire economy. It then proposes a blended approach that combines the macro and micro scales and promises a new, enhanced, and better understanding of the literary record. It also explains how macroanalysis yields specific insights into some important literary historical questions and considers the distinct advantages of a macroanalytic approach over the more traditional practice of studying literary periods and genres. The chapter concludes with an overview of the book's exploration of macroanalysis and its argument that literary studies should be approached not simply as an examination of seminal works but as an examination of an aggregated ecosystem or “economy” of texts.
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Gulati, Namrata, and Tridip Ray. Inequality and Neighbourhood Effects. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198812555.003.0011.
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The key insight in our research is to recognize inequality–neighbourhood interaction: neighbourhood effects interacting with income inequality may affect poor people’s ability to access basic facilities like health-care services, schooling, and so on. While Gulati and Ray (2016) model this interaction on a monopolist service provider in a neighbourhood structured as a linear city where rich and poor consumers live side by side, in this chapter we extend the analysis to a competitive framework with free entry and exit where the natural neighbourhood structure is a circular city. We find inverted-U shape relationships between income inequality and market access and welfare of the poor: if we compare a cross-section of societies, the poor community as a whole is initially better off living in relatively richer societies, but, beyond a point, the aggregate market access and consumer surplus of the poor starts declining as society becomes richer. We identify the possibility of complete exclusion of the poor from the market: a scenario where the service providers cater only to the rich and the poor have absolutely no market access, and find that it is the higher income gap between rich and poor that exposes the poor to this unfortunate outcome.
Book chapters on the topic "Aggregate entity"
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Privatto, Pedro Ivo Monteiro, and Ivan Rizzo Guilherme. "When External Knowledge Does Not Aggregate in Named Entity Recognition." In Intelligent Systems, 616–27. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91699-2_42.
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Östlund, Johan, and Tobias Wrigstad. "Multiple Aggregate Entry Points for Ownership Types." In ECOOP 2012 – Object-Oriented Programming, 156–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31057-7_8.
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Hoschka, Tobias C. "The Scale of Cross-Border Entry in EC Financial Services: an Aggregate Analysis." In Cross-Border Entry in European Retail Financial Services, 176–96. London: Palgrave Macmillan UK, 1993. http://dx.doi.org/10.1007/978-1-349-22979-6_7.
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Alfani, Guido. "Economic inequality in preindustrial Europe, 1300-1800: methods and results from the EINITE project." In Disuguaglianza economica nelle società preindustriali: cause ed effetti / Economic inequality in pre-industrial societies: causes and effect, 21–36. Florence: Firenze University Press, 2020. http://dx.doi.org/10.36253/978-88-5518-053-5.07.
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This article provides an overview of the research done in recent years by the ERC-funded projects EINITE-Economic Inequality across Italy and Europe 1300-1800, and SMITE-Social Mobility and Inequality across Italy and Europe 1300-1800. It begins by discussing the sources available for reconstructing preindustrial economic inequality, especially in Italy, then it provides an overview of the methods which have been developed to produce reliable and homogenous information about inequality levels and trends. The method developed by EINITE to produce measures or distributions representative of broader aggregates (regions or entire states) is also discussed, as well as the techniques that can be employed to explore in a meaningful way such distributions to answer relevant historical questions.
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Malewitz, Raymond. "Viruses." In Microbium, 129–41. Earth, Milky Way: punctum books, 2023. http://dx.doi.org/10.53288/0396.1.10.
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Of the many kinds of living micro-matter, viruses might seem to be the least neglected—particularly now, given the recent SARS-CoV-2 pandemic. However, many aspects of COVID-19 history illustrate not only how viruses are neglected but also how their very existence depends upon their ability to evade detection. To explain this dynamic, the entry begins with a short reading of Mona Awad’s short story “A Blue Sky Like This,” published at the end of the first wave of COVID-19. The story’s strange protagonist and her interactions with New York City residents under lockdown illustrate both the motivations for and consequences of willfully neglect of viral dangers. This reading is juxtaposed with a discussion of scientific efforts to identify and understand viruses during the twentieth century, which illustrate the analogous challenges of understanding miniscule lifeforms, whose effects, in aggregate, can stretch to enormous geographical scales. The entry concludes with a reading of Charles Yu’s short story “Systems,” which attempts to represent these scales and overcome viral neglect by radically restructuring the form, content, and characters of conventional Western narrative.
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Geng, Christoph, Natalia Moriz, Andreas Bunte, and Henning Trsek. "Concept for Rule-Based Information Aggregation in Modular Production Plants." In Technologien für die intelligente Automation, 77–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-662-64283-2_6.
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AbstractIn the context of Industrie 4.0, (Self-)adapting Cyber-Physical Production Systems (CPPS) offer a solution for production facilities to adapt to changing market requirements. The operation of a CPPS requires information of the entire plant at any time, which can usually be derived by aggregating the individual information of the production modules of a CPPS (information models). Even if the information models are designed following standardized guidelines, the aggregation of these individual information models often needs to be done manually, which requires a lot of effort and is error prone. To achieve an automated information aggregation, this paper presents a novel concept for modular production plants. The main aspect of the concept is the use of a Rule Engine for the processing of information models in order to create aggregated plant information. This Rule Engine uses a classification method for plant components in order to enable standardization. The challenge of this work is to design a Rule Engine that is suitable for different aspects of CPPS.
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Pettigrew, Richard. "The Aggregate Utility Solution I: Which Attitudes to Aggregate?" In Choosing for Changing Selves, 49–72. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198814962.003.0006.
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The chapter starts to describe a new solution to the problem of choosing for changing selves. It proposes that we should consider it as a judgement aggregation problem. In a judgement aggregation problem, a collective entity is required to aggregate the beliefs and values of the various entities that make it up before making a decision on the basis of those collective attitudes. In the Aggregate Utility Solution, the individual agent is the collective and the selves are the entities that make it up. The chapter asks, in particular: at what level should we aggregate the utilities of the selves to give the utilities of the individual agent? At the level of the preference orderings, or the valuation functions, or the credence and utility functions?
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Augusto, Alexandre B., and Manuel E. Correia. "A Mobile-Based Attribute Aggregation Architecture for User-Centric Identity Management." In Architectures and Protocols for Secure Information Technology Infrastructures, 266–87. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4514-1.ch010.
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The massive growth of the Internet and its services is currently being sustained by the mercantilization of users’ identities and private data. Traditional services on the Web require the user to disclose many unnecessary sensitive identity attributes like bankcards, geographic position, or even personal health records in order to provide a service. In essence, the services are presented as free and constitute a means by which the user is mercantilized, often without realizing the real value of its data to the market. In this chapter the auhors describe OFELIA (Open Federated Environment for Leveraging of Identity and Authorization), a digital identity architecture designed from the ground up to be user centric. OFELIA is an identity/authorization versatile infrastructure that does not depend upon the massive aggregation of users’ identity attributes to offer a highly versatile set of identity services but relies instead on having those attributes distributed among and protected by several otherwise unrelated Attribute Authorities. Only the end user, with his smartphone, knows how to aggregate these scattered Attribute Authorities’ identity attributes back into some useful identifiable and authenticated entity identity that can then be used by Internet services in a secure and interoperable way.
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Sergiy, Kostrikov, and Seryogin Denis. "Urbogeosystemic Approach to Agglomeration Study within the Urban Remote Sensing Frameworks." In Urban Agglomeration [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.102482.
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The spatial arrangement of human activity within urban areas is normally provided by areal management, and its effective provision is a complicated problem. The current urban development causes a number of problems and urgent challenges, which can be met and resolved exclusively on the basis of innovative scientific and technological advances. The main research objective of this chapter is to represent the authors’ theoretic concept of the urban geographical system combined with the original Urban Remote Sensing approach based on the advanced technique of airborne LiDAR (Light Detection And Ranging) data processing. The authors attempted to prove that the presented concept could contribute to an understanding of the urban agglomeration as an urbanized spatial entity. The chapter explains in what way the urbanistic environment is a quasi-rasterized 3D model of actual city space, and the urbogeosystem (UGS) is a quasi-vector 3D model of the hierarchical formalized aggregate of UGS elementary functional units–buildings, both can efficiently simulate and visualize an urbanized area. Web-based geoinformation software for LiDAR data processing with the objectives of urban studies has been introduced together with its key functionalities. The population estimation use case has been examined in detail within the presented approach frameworks.
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Fehr, Hans, and Fabian Kindermann. "Dynamic macro II: The stochastic OLG model." In Introduction to Computational Economics Using Fortran. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198804390.003.0016.
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In Chapters 6 and 7 we discussed how to compute overlapping generations models and how to use them for policy analysis. The models developed there are completely deterministic in that they exclude both income and investment risk. While this ensured analytical tractability of the household problem and greatly facilitated computation, it certainly limit the scope of policy analysis. Consequently these chapters centred around clarifying the impact of public policy on the labour-supply and savings decisions of households and around evaluating its consequences for intergenerational redistribution. In practice, however, households face all kinds of risks that cannot be insured perfectly by the market. This opens up an additional channel through which the government could increase households’ welfare, namely by providing public insurance. In Chapter 10, we studied individual behaviour in an uncertain world, where individuals face idiosyncratic labour income and mortality risk as well as aggregate capital-market risk. The models therein are partial equilibrium models, meaning that prices are fixed and there is no need for the government to operate a balanced budget. In this chapter, we embed a household’s decision model with idiosyncratic labour-productivity risk and endogenous labour-supply decisions into a general equilibrium framework, which leads us to the stochastic OLG model. In this setup, factor prices respond to changes in individual behaviour and the government will be an explicit entity that collects revenue from taxes to finance its expenditure. Such a setup allows us to analyse both the distortionary and the risk-sharing effects of public policies. This chapter is organized in three main sections. The first two closely follow the setup of Chapter 6. We first explain the general structure of the stochastic OLG model with all its actors and conduct some steady-state policy analysis. We then discuss how to extend the model to include a transition path between steady states and to compute aggregate efficiency effects. In the last section, Section 11.3, we provide some policy applications where we analyse optimal tax schedules and the optimal size of the social-security system in more detail. In the following, we extend the life-cycle model with variable labour supply from Section 10.1.2 to a full general equilibrium setup with overlapping generations.
Conference papers on the topic "Aggregate entity"
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Hirose, Shoichi, and Junji Shikata. "Group-Testing Aggregate Entity Authentication." In 2023 IEEE Information Theory Workshop (ITW). IEEE, 2023. http://dx.doi.org/10.1109/itw55543.2023.10160240.
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Li, Yan, Tingjian Ge, and Cindy Chen. "Online Indices for Predictive Top-k Entity and Aggregate Queries on Knowledge Graphs." In 2020 IEEE 36th International Conference on Data Engineering (ICDE). IEEE, 2020. http://dx.doi.org/10.1109/icde48307.2020.00096.
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Lu, Jiamin, and Shitao Wang. "Heterogeneous Entity Matching with Complex Attribute Associations using BERT and Neural Networks." In 4th International Conference on Machine Learning Techniques and NLP. Academy & Industry Research Collaboration, 2023. http://dx.doi.org/10.5121/csit.2023.131605.
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Across various domains, data from different sources such as Baidu Baike and Wikipedia often manifest in distinct forms. Current entity matching methodologies predominantly focus on homogeneous data, characterized by attributes that share the same structure and concise attribute values. However, this orientation poses challenges in handling data with diverse formats. Moreover, prevailing approaches aggregate the similarity of attribute values between corresponding attributes to ascertain entity similar- ity. Yet, they often overlook the intricate interrelationships between attributes, where one attribute may have multiple associations. The simplistic approach of pairwise attribute comparison fails to harness the wealth of information encapsulated within entities.To address these challenges, we introduce a novel en- tity matching model, dubbed ”Entity Matching Model for Capturing Complex Attribute Relationships (EMMCCAR),” built upon pre-trained models. Specifically, this model transforms the matching task into a sequence matching problem to mitigate the impact of varying data formats. Moreover, by introducing attention mechanisms, it identifies complex relationships between attributes, emphasizing the degree of matching among multiple attributes rather than one-to-one correspondences. Through the integration of the EMM-CCAR model, we adeptly surmount the challenges posed by data heterogeneity and intricate attribute interdependencies. In comparison with the prevalent DER-SSM and Ditto approaches, our model achieves improvements of approximately 4% and 1% in F1 scores, respectively. This furnishes a robust solution for addressing the intricacies of attribute complexity in entity matching.
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Long, Xinwei, Shuzi Niu, and Yucheng Li. "Consistent Inference for Dialogue Relation Extraction." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/535.
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Relation Extraction is key to many downstream tasks. Dialogue relation extraction aims at discovering entity relations from multi-turn dialogue scenario. There exist utterance, topic and relation discrepancy mainly due to multi-speakers, utterances, and relations. In this paper, we propose a consistent learning and inference method to minimize possible contradictions from those distinctions. First, we design mask mechanisms to refine utterance-aware and speaker-aware representations respectively from the global dialogue representation for the utterance distinction. Then a gate mechanism is proposed to aggregate such bi-grained representations. Next, mutual attention mechanism is introduced to obtain the entity representation for various relation specific topic structures. Finally, the relational inference is performed through first order logic constraints over the labeled data to decrease logically contradictory predicted relations. Experimental results on two benchmark datasets show that the F1 performance improvement of the proposed method is at least 3.3% compared with SOTA.
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Nie, Feng, Shuyan Zhou, Jing Liu, Jinpeng Wang, Chin-Yew Lin, and Rong Pan. "Aggregated Semantic Matching for Short Text Entity Linking." In Proceedings of the 22nd Conference on Computational Natural Language Learning. Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/k18-1046.
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Rangelov, Milena, Heather Dylla, and Nadarajah Sivaneswaran. "Using environmental product declarations for green public procurement and life cycle assessment of concrete pavements." In 12th International Conference on Concrete Pavements. International Society for Concrete Pavements, 2021. http://dx.doi.org/10.33593/8ziapl8i.
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Environmental impacts of concrete production have been evaluated for more than a decade. As a result, a national program for environmental product declarations (EPDs) of concrete has been initiated. The main objective of this paper is to analyze concrete EPDs produced to date and evaluate their applicability for green public procurement (GPP) and life-cycle assessment (LCA) of concrete pavements. EPDs provide transparent and verified quantification of environmental impacts, calculated per predetermined guidelines, known as Product Category Rules (PCRs). PCRs for concrete were developed through involvement of stakeholders from the building industry; therefore, these PCRs may not be fully applicable to paving concrete. The analysis included over 70 published EPDs and revealed that there are marked variations in underlying data sources and data quality, which hinders comparability of EPDs and use of EPDs for benchmarking. Concrete EPDs were created primarily using proprietary data sources suitable for the private sector. However, in the public sector, the use of proprietary data may be cost-prohibitive for agencies, disable transparency, and present the impediment to wider GPP and LCA adoption. To that end, reliable public datasets offer more promise for the development of paving concrete EPD. This study also compares concrete PCR to that of other paving materials (cement, aggregate, asphalt), all of which were created with no overarching entity. Accordingly, the potential options for harmonization and synergetic use of these EPDs in GPP and pavement LCA are also investigated.
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Hui, Tianrui, Zihan Ding, Junshi Huang, Xiaoming Wei, Xiaolin Wei, Jiao Dai, Jizhong Han, and Si Liu. "Enriching Phrases with Coupled Pixel and Object Contexts for Panoptic Narrative Grounding." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/99.
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Panoptic narrative grounding (PNG) aims to segment things and stuff objects in an image described by noun phrases of a narrative caption. As a multimodal task, an essential aspect of PNG is the visual-linguistic interaction between image and caption. The previous two-stage method aggregates visual contexts from offline-generated mask proposals to phrase features, which tend to be noisy and fragmentary. The recent one-stage method aggregates only pixel contexts from image features to phrase features, which may incur semantic misalignment due to lacking object priors. To realize more comprehensive visual-linguistic interaction, we propose to enrich phrases with coupled pixel and object contexts by designing a Phrase-Pixel-Object Transformer Decoder (PPO-TD), where both fine-grained part details and coarse-grained entity clues are aggregated to phrase features. In addition, we also propose a Phrase-Object Contrastive Loss (POCL) to pull closer the matched phrase-object pairs and push away unmatched ones for aggregating more precise object contexts from more phrase-relevant object tokens. Extensive experiments on the PNG benchmark show our method achieves new state-of-the-art performance with large margins.
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Roberts, N., P. Van Buskirk, D. Murphy, and D. Byrd. "Characterization and Learnings of Far Field Fracture Propagation in the Marcellus Shale Using Aggregated LF-DAS Datasets." In SPE Eastern Regional Meeting. SPE, 2023. http://dx.doi.org/10.2118/215913-ms.
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Abstract Economic optimal recovery of hydrocarbons from unconventional reservoirs requires consistent and sufficient stimulation energy across an entire drill spacing unit (DSU), both along laterals and between them. This necessitates an understanding of how and why fractures propagate away from the treatment well. While legacy methods such as Distributed Acoustic and Temperature Surveys (DAS/DTS), pressure responses, logging/imaging has allowed us to investigate the point of stimulation origination, analyzing Low Frequency Distributed Acoustic Sensing (LF-DAS) gives us unique insights into far field fracture behavior. This paper aggregates several existing LF-DAS datasets in the Marcellus as well as the most representative log data available to draw conclusions on the impacts of geology, completion test parameters, stage and well frac order, frac design and materials, lateral placement, and many other influence factors on far field fracture behavior. Both statistical analysis and data visualization of these datasets independently and in aggregate was used to identify numeric as well as engineer-based observations and conclusions. By using these two methods, correlations between influence factors and far field fracture behavior are identified and quantified, and a level of variability is demonstrated for the Marcellus as well as some specific sub-plays. The analysis presented identifies controllable parameters to adjust as well as uncontrollable parameters that must be designed around to achieve stimulation goals. Also included is a description of where additional data collection is required to improve certainty and robustness of the analysis. Aggregated analysis on cross well far field fracture behavior has not previously been performed for Marcellus. This paper displays multi-project trends that were previously unidentified allowing the opportunity to design future tests around and confirm or challenge existing theories and conclusions. Previously non discussed fracture behaviors in the dataset are also described and addressed.
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Fu, Cheng, Xianpei Han, Jiaming He, and Le Sun. "Hierarchical Matching Network for Heterogeneous Entity Resolution." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/507.
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Entity resolution (ER) aims to identify data records referring to the same real-world entity. Most existing ER approaches rely on the assumption that the entity records to be resolved are homogeneous, i.e., their attributes are aligned. Unfortunately, entities in real-world datasets are often heterogeneous, usually coming from different sources and being represented using different attributes. Furthermore, the entities’ attribute values may be redundant, noisy, missing, misplaced, or misspelled—we refer to it as the dirty data problem. To resolve the above problems, this paper proposes an end-to-end hierarchical matching network (HierMatcher) for entity resolution, which can jointly match entities in three levels—token, attribute, and entity. At the token level, a cross-attribute token alignment and comparison layer is designed to adaptively compare heterogeneous entities. At the attribute level, an attribute-aware attention mechanism is proposed to denoise dirty attribute values. Finally, the entity level matching layer effectively aggregates all matching evidence for the final ER decisions. Experimental results show that our method significantly outperforms previous ER methods on homogeneous, heterogeneous and dirty datasets.
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Simpson, Greer, Ashley Mercer, Matt Mantell, Charles Bourgeois, Anthony Battistel, Trent Pehlke, and Tom Littleford. "Virtually Unplugging Perforations: High-Resolution Acoustic Imaging Enabling Statistical Analysis of Calibration and Post-Frac Perforation Entry and Exit-Hole Datasets." In SPE/ICoTA Well Intervention Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/212908-ms.
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Abstract High-resolution acoustic imaging technology provides operators the ability to extract submillimetric measurements of perforations at any depth into the casing wall. Due to its three-dimensional nature, submillimetric acoustic data permits the extraction of highly accurate area-based measurements at any radial distance into the perforation, with key distances at the inner and outer casing boundary. This novel technology is fluid agnostic and is unaffected by fluid opacity or clarity. The platforms robust 3D measurement capabilities have made it into an ideal means to evaluate casing and perforations in challenging environments such as hydraulically fractured wells. The integration of high-resolution acoustic imaging into numerous operators’ hydraulic fracture and completions evaluation workflows has resulted in a highly insightful aggregate submillimetric perforation dataset. This large dataset has led to the development of a method to virtually unplug perforations by using a well-specific "perforation entry and exit-hole area correlation". The correlation established can only be extracted using acoustic based imaging as it requires submillimetric resolution of both the ID and OD profile of each perforation Using this correlation, the resulting set of post-frac perforation exit-hole measurements improves an operators’ ability to complete a holistic well completion evaluation, even when well conditions cause perforations to be plugged. The outcome is improved operational insight through the ability to directly compare stages with plugged perforations to those without. This approach can be applied at any point in the well's life cycle, which allows operators to revisit assessments and virtually unplug obscured and proppant-filled perforations. The methodology requires a sound baseline knowledge of the performance of the downhole perforating charges. The baseline is commonly obtained through a calibration stage, which is a stage of charges that are shot but left unstimulated to provide the control measurements for the specific charge in the given well conditions. Current industry performance of downhole perforating charges is investigating through the aggregated dataset of calibration charges. To validate this solid-state acoustic technology and demonstrates its high degree of accuracy for entry and exit-hole perforation measurements, machined samples were scanned with this technology, and with a metrology-grade laser scanner for comparison. This paper presents a novel virtual unplugging methodology, enabled by highly accurate and validated entry-hole measurements, as well as other insights garnered from the aggregate analysis of the world's largest calibration perforation datasets.
Reports on the topic "Aggregate entity"
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Asturias, Jose, Sewon Hur, Timothy Kehoe, and Kim Ruhl. Firm Entry and Exit and Aggregate Growth. Cambridge, MA: National Bureau of Economic Research, February 2017. http://dx.doi.org/10.3386/w23202.
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Clementi, Gian Luca, and Berardino Palazzo. Entry, Exit, Firm Dynamics, and Aggregate Fluctuations. Cambridge, MA: National Bureau of Economic Research, July 2013. http://dx.doi.org/10.3386/w19217.
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Jia, Ruixue, Xiao Ma, and Victoria Wenxin Xie. Expecting Floods: Firm Entry, Employment, and Aggregate Implications. Cambridge, MA: National Bureau of Economic Research, July 2022. http://dx.doi.org/10.3386/w30250.
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Snyder, Victor A., Dani Or, Amos Hadas, and S. Assouline. Characterization of Post-Tillage Soil Fragmentation and Rejoining Affecting Soil Pore Space Evolution and Transport Properties. United States Department of Agriculture, April 2002. http://dx.doi.org/10.32747/2002.7580670.bard.
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Tillage modifies soil structure, altering conditions for plant growth and transport processes through the soil. However, the resulting loose structure is unstable and susceptible to collapse due to aggregate fragmentation during wetting and drying cycles, and coalescense of moist aggregates by internal capillary forces and external compactive stresses. Presently, limited understanding of these complex processes often leads to consideration of the soil plow layer as a static porous medium. With the purpose of filling some of this knowledge gap, the objectives of this Project were to: 1) Identify and quantify the major factors causing breakdown of primary soil fragments produced by tillage into smaller secondary fragments; 2) Identify and quantify the. physical processes involved in the coalescence of primary and secondary fragments and surfaces of weakness; 3) Measure temporal changes in pore-size distributions and hydraulic properties of reconstructed aggregate beds as a function of specified initial conditions and wetting/drying events; and 4) Construct a process-based model of post-tillage changes in soil structural and hydraulic properties of the plow layer and validate it against field experiments. A dynamic theory of capillary-driven plastic deformation of adjoining aggregates was developed, where instantaneous rate of change in geometry of aggregates and inter-aggregate pores was related to current geometry of the solid-gas-liquid system and measured soil rheological functions. The theory and supporting data showed that consolidation of aggregate beds is largely an event-driven process, restricted to a fairly narrow range of soil water contents where capillary suction is great enough to generate coalescence but where soil mechanical strength is still low enough to allow plastic deforn1ation of aggregates. The theory was also used to explain effects of transient external loading on compaction of aggregate beds. A stochastic forInalism was developed for modeling soil pore space evolution, based on the Fokker Planck equation (FPE). Analytical solutions for the FPE were developed, with parameters which can be measured empirically or related to the mechanistic aggregate deformation model. Pre-existing results from field experiments were used to illustrate how the FPE formalism can be applied to field data. Fragmentation of soil clods after tillage was observed to be an event-driven (as opposed to continuous) process that occurred only during wetting, and only as clods approached the saturation point. The major mechanism of fragmentation of large aggregates seemed to be differential soil swelling behind the wetting front. Aggregate "explosion" due to air entrapment seemed limited to small aggregates wetted simultaneously over their entire surface. Breakdown of large aggregates from 11 clay soils during successive wetting and drying cycles produced fragment size distributions which differed primarily by a scale factor l (essentially equivalent to the Van Bavel mean weight diameter), so that evolution of fragment size distributions could be modeled in terms of changes in l. For a given number of wetting and drying cycles, l decreased systematically with increasing plasticity index. When air-dry soil clods were slightly weakened by a single wetting event, and then allowed to "age" for six weeks at constant high water content, drop-shatter resistance in aged relative to non-aged clods was found to increase in proportion to plasticity index. This seemed consistent with the rheological model, which predicts faster plastic coalescence around small voids and sharp cracks (with resulting soil strengthening) in soils with low resistance to plastic yield and flow. A new theory of crack growth in "idealized" elastoplastic materials was formulated, with potential application to soil fracture phenomena. The theory was preliminarily (and successfully) tested using carbon steel, a ductile material which closely approximates ideal elastoplastic behavior, and for which the necessary fracture data existed in the literature.
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Bilbiie, Florin, and Marc Melitz. Aggregate-Demand Amplification of Supply Disruptions: The Entry-Exit Multiplier. Cambridge, MA: National Bureau of Economic Research, December 2020. http://dx.doi.org/10.3386/w28258.
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Finkelstein-Shapiro, Alan, Federico S. Mandelman, and Victoria Nuguer. Fintech Entry, Firm Financial Inclusion, and Macroeconomic Dynamics in Emerging Economies. Inter-American Development Bank, January 2022. http://dx.doi.org/10.18235/0003918.
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Financial inclusion is strikingly low in emerging economies. In only a few years, financial technologies (fintech) have led to a dramatic expansion in the number of non-traditional credit intermediaries, but the macroeconomic and credit-market implications of this rapid growth of fintech are not known. We build a model with a traditional banking system and endogenous fintech intermediary creation and find that greater fintech entry delivers positive long-term effects on aggregate output and consumption. However, greater entry bolsters aggregate firm financial inclusion only if it stems from lower barriers to accessing fintech credit by smaller, unbanked firms. Decreasing entry costs for fintech intermediaries alone has only marginal effects in the aggregate. While firms that adopt fintech credit are less sensitive to domestic financial shocks and contribute to a reduction in output volatility, greater fintech entry also leads to greater volatility in bank credit, thereby introducing a tradeoff between output volatility and credit-market volatility.
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Graziano, Alejandro, Georg Schaur, Christian Volpe Martincus, and Jerónimo Carballo. Endogenous Border Times. Inter-American Development Bank, June 2016. http://dx.doi.org/10.18235/0011740.
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We examine transaction-level Peruvian import data to show that firms are subject to significant costs of port-of-entry delays. At the transaction level, we observe the time it takes a shipment to clear each step in the entry process. Our theory shows conditions under which observed entry times are endogenous. As a result, total entry delays potentially lead to biased policy conclusions and non-informative efficiency rankings of countries' entry procedures. We make three empirical contributions that help unbundle sources for time costs in trade and border effects. First, we provide evidence that at least part of the total port-entry-time is endogenous. Second, we identify the effect of entry delays on imports based on exogenous necessary entry processing. Third, we provide evidence that trade costs due to entry delays are heterogeneous across firm types. New and large importersare more elastic with respect to entry delays. This information allows researchers and policymakers to interpret aggregate port of entry delay data and their costs across different types of firms.
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Ahlgren, Per, Tobias Jeppsson, Esa Stenberg, and Erik Berg. A bibliometric analysis of battery research with the BATTERY 2030+ roadmap as point of departure. Uppsala universitet, 2022. http://dx.doi.org/10.33063/diva-473454.
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In this bibliometric study, we analyze the six battery research subfields identified in the BATTERY 2030+ roadmap: Battery Interface Genome, Materials Acceleration Platform, Recyclability, Smart functionalities: Self-healing, Smart functionalities: Sensing, and Manufacturability. In addition, we analyze the entire research field related to BATTERY 2030+ as a whole, using two operationalizations. We (a) evaluate the European standing in the subfields/the BATTERY 2030+ field in comparison to the rest of the world, and (b) identify strongholds of the subfields/the BATTERY 2030+ field across Europe. For each subfield and the field as a whole, we used seed articles, i.e. articles listed in the BATTERY 2030+ roadmap or cited by such articles, in order to generate additional, similar articles located in an algorithmically obtained classification system. The output of the analysis is publication volumes, field normalized citation impact values with comparisons between country/country aggregates and between organizations, co-publishing networks between countries and organizations, and keyword co-occurrence networks. For the results related to (a), the performance of EU & associated (countries) is similar to China and the aggregate Japan-South Korea-Singapore and well below North America regarding citation impact and with respect to the field as a whole. Exceptions are, however, the subfields Battery Interface Genome and Recyclability. For the results related to (b), there is a large variability in the EU & associated organizations regarding volume in the different subfields. For citation impact, examples of high-performing EU & associated organizations are ETH Zurich and Max Planck Society for the Advancement of Science.
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Finkelstein-Shapiro, Alan, and Andrés González Gómez. Macroprudential Policy and Labor Market Dynamics in Latin America. Inter-American Development Bank, March 2015. http://dx.doi.org/10.18235/0011688.
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This paper builds a small open economy business cycle model with labor and financial market frictions that incorporates frictional, endogenous self-employment entry and a link between formal credit markets, informal credit, and the labor market. The paper then shows that the model is consistent with the cyclical behavior of both labor and credit markets in Latin American economies and analyzes the aggregate consequences of cyclical macroprudential policy for labor market and aggregate dynamics. It is found that a policy that reduces credit fluctuations successfully reduces consumption, investment, and output volatility, but generates substantially higher unemployment fluctuations in response to productivity shocks. Moreover, the policy increases the volatility of all these variables in response to net worth shocks. The link between formal credit markets, input credit between firms, and self-employment plays a key role in explaining the adverse impact of macroprudential policy on unemployment dynamics. The findings point to potential gains from policy complementarities between macroprudential regulation and active labor market interventions over the business cycle.
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Schiffbauer, Marc, Philip Keefer, and Ishac Diwan. Pyramid Capitalism: Cronyism, Regulation, and Firm Productivity in Egypt. Inter-American Development Bank, October 2016. http://dx.doi.org/10.18235/0011766.
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Using a large, original database of 385 politically connected firms under the Mubarak regime in Egypt, we document for the first time the negative impact of cronyism on economic growth. In the early 2000s, a policy shift in Egypt led to the expansion of crony activities into new, previously unconnected sectors. 4-digit sectors that experienced crony entry between 1996 and 2006 experienced lower aggregate employment growth during the period than those that did not. A wide array of supporting evidence indicates that this effect was causal, reflecting the mechanisms described in Aghion et al. (2001), and not due to selection. Crony entry skewed the distribution of employment toward smaller, less productive firms; crony firms did not enter into sectors that would have also grown more slowly even in the absence of crony entry; and they enjoyed multiple regulatory and fiscal privileges that reduced competition and investments by non-crony firms, including trade protection, energy subsidies, access to land, and favorable regulatory enforcement. Moreover, energy subsidies and trade protection account for the higher profits of politically connected firms.