Supply networks are essential for modern production, yet their critical properties remain understudied. We present a stochastic model with random production capacities to analyze material flow to a root node, focusing on topology and buffer stocks. The critical demand, where unsatisfied demand diverges, is examined mostly through numerical simulations. Without stocks, minimal production dictates behavior, making topology irrelevant. With stocks, memory effects arise, making topology crucial. Increased local connectivity is beneficial: firms should favor broad, short supply chains over long, narrow ones.
Les autrices examinent la manière dont les inégalités présentes sur le marché du travail traditionnel influent sur la situation des travailleurs de plateformes. Elles utilisent le cadre des régimes d’inégalités élaboré par Acker, en s’intéressant plus particulièrement au genre, et l’appliquent à une étude de cas qualitative portant sur une plateforme de travail indépendant qui fournit des services juridiques. L’analyse, qui comporte une dimension longitudinale, montre que les obstacles structurels à l’oeuvre dans la profession juridique classique se retrouvent sous une forme amplifiée dans l’univers des plateformes, ce qui invalide l’idée que le travail de plateformes peut être un levier.
The Internet of Vehicles (IoV) has great potential to transform transportation systems by enhancing road safety, reducing traffic congestion, and improving user experience through onboard infotainment applications. Decentralized data sharing can improve security, privacy, reliability, and facilitate infotainment data sharing in IoVs. However, decentralized data sharing may not achieve the expected efficiency if there are IoV users who only want to consume the shared data but are not willing to contribute their own data to the community, resulting in incomplete information observed by other vehicles and infrastructure, which can introduce additional transmission latency. Therefore, in this article, by modeling the data sharing ecosystem as a data trading market, we propose a decentralized data-sharing incentive mechanism based on multi-intelligent reinforcement learning to learn the supply-demand balance in markets and minimize transmission latency. Our proposed mechanism takes into account the dynamic nature of IoV markets, which can experience frequent fluctuations in supply and demand. We propose a time-sensitive Key-Policy Attribute-Based Encryption (KP-ABE) mechanism coupled with Named Data Networking (NDN) to protect data in IoVs, which adds a layer of security to our proposed solution. Additionally, we design a decentralized market for efficient data sharing in IoVs, where continuous double auctions are adopted. The proposed mechanism based on multi-agent deep reinforcement learning can learn the supply-demand equilibrium in markets, thus improving the efficiency and sustainability of markets. Theoretical analysis and experimental results show that our proposed learning-based incentive mechanism outperforms baselines by 10% in determining the equilibrium of supply and demand while reducing transmission latency by 20%.
Desheng Hu, Muhammad Abu Bakar Aziz, Jeffrey Gleason
et al.
Is Google Search a monopoly with gatekeeping power? Regulators from the US, UK, and Europe have argued that it is based on the assumption that Google Search dominates the market for horizontal (a.k.a. "general") web search. Google disputes this, claiming that competition extends to all vertical (a.k.a. "specialized") search engines, and that under this market definition it does not have monopoly power. In this study we present the first analysis of Google Search's market share under both horizontal and vertical segmentation of online search. We leverage observational trace data collected from a panel of US residents that includes their web browsing history and copies of the Google Search Engine Result Pages they were shown. We observe that Google Search receives 71.8% of participants' queries when compared to other horizontal search engines, and that participants' search sessions begin at Google greater than 50% of the time in 24 out of 30 vertical market segments (which comprise almost all of our participants' searches). Our results inform the consequential and ongoing debates about the market power of Google Search and the conceptualization of online markets in general.
Segment anything model (SAM), a foundation model with superior versatility and generalization across diverse segmentation tasks, has attracted widespread attention in medical imaging. However, it has been proved that SAM would encounter severe performance degradation due to the lack of medical knowledge in training and local feature encoding. Though several SAM-based models have been proposed for tuning SAM in medical imaging, they still suffer from insufficient feature extraction and highly rely on high-quality prompts. In this paper, we construct a large CT dataset consisting of 1.1M CT images and 5M masks from public datasets and propose a powerful foundation model SAMCT allowing labor-free prompts. Specifically, based on SAM, SAMCT is further equipped with a U-shaped CNN image encoder, a cross-branch interaction module, and a task-indicator prompt encoder. The U-shaped CNN image encoder works in parallel with the ViT image encoder in SAM to supplement local features. Cross-branch interaction enhances the feature expression capability of the CNN image encoder and the ViT image encoder by exchanging global perception and local features from one to the other. The task-indicator prompt encoder is a plug-and-play component to effortlessly encode task-related indicators into prompt embeddings. In this way, SAMCT can work in an automatic manner in addition to the semi-automatic interactive strategy in SAM. Extensive experiments demonstrate the superiority of SAMCT against the state-of-the-art task-specific and SAM-based medical foundation models on various tasks. The code, data, and models are released at https://github.com/xianlin7/SAMCT.
Refletimos sobre a contribuição de Marx no século XIX, com o intuito de entender as demandas socioeducacionais do século atual. Comparamos concepções categóricas de Hegel, Gramsci e Lukács para analisar a educação pública de tempo integral em favor das classes subalternas e gêneros diversos. Para tal, tomamos como exemplo os Centros Integrados de Educação Pública (CIEPs/CIEPs-RJ), idealizados e materializados por Darcy Ribeiro, entre os anos 1983-1987. Indicamos a importância da educação popular de acesso gratuito às crianças e aos adolescentes, para além dos turnos escolares tradicionalmente fragmentados.
Palavras-chave: Marx; Marxismo; Darcy Ribeiro; CIEPs; Cultura.
Special aspects of education, Labor market. Labor supply. Labor demand
Homenageamos Carlos Walter Porto-Gonçalves, apresentando um quadro das contribuições de sua obra para a geografia e para ciências sociais. Apontamos chaves de leitura que indicam as linhas de força que constituem seu pensamento e apontam para um renovado horizonte teórico-metodológico, ético e político de leitura da geograficidade social: i) a Geografia como verbo: as geo-grafias desde os de baixo e das r-existências; ii) o conflito como chave de leitura da geograficidade do social: a tensão de territorialidades; iii) a ecologia política da questão ambiental e as lutas por reapropriação social da natureza; iv) a reinvenção dos territórios na América Latina/Abya Yala/Quilombola.
Palavras-chaves: Carlos Walter Porto-Gonçalves; Geo-grafias desde os debaixo; R-existências; ecologia política; a reinvenção dos territórios.
Palavras-chaves: Carlos Walter Porto-Gonçalves- Geo-grafias desde os debaixo- r-existências - ecologia política – a reinvenção dos territórios.
Special aspects of education, Labor market. Labor supply. Labor demand
Mustafa Can Camur, Chin-Yuan Tseng, Aristotelis E. Thanos
et al.
COVID-19 resulted in some of the largest supply chain disruptions in recent history. To mitigate the impact of future disruptions, we propose an integrated hybrid simulation framework to couple nonstationary demand signals from an event like COVID-19 with a model of an end-to-end supply chain. We first create a system dynamics susceptible-infected-recovered (SIR) model, augmenting a classic epidemiological model to create a realistic portrayal of demand patterns for oxygen concentrators (OC). Informed by this granular demand signal, we then create a supply chain discrete event simulation model of OC sourcing, manufacturing, and distribution to test production augmentation policies to satisfy this increased demand. This model utilizes publicly available data, engineering teardowns of OCs, and a supply chain illumination to identify suppliers. Our findings indicate that this coupled approach can use realistic demand during a disruptive event to enable rapid recommendations of policies for increased supply chain resilience with controlled cost.
Across the legal profession, statistics related to the numbers of women and other underrepresented groups in leadership roles continue to paint a bleak picture of diversity and inclusion. Some approaches to closing this gap have focused on the cause; some have devised and applied solutions. Questions about the efficacy of many of these solutions remain essentially unanswered. This empirical study represents one of the first of its kind. Studies of the legal profession have not focused on the dynamics of supply and demand in the context of leadership positions (counsel and partner (equity and non-equity)). Neither have they examined the interrelationships of these dynamics to race and gender demographic factors (white female and minorities (male and female)). This research seeks to determine the supply-demand position of leadership in the legal profession and establish market equilibrium for these counsel and partner roles.
In this paper, we introduce the R package mcmsupply which implements Bayesian hierarchical models for estimating and projecting modern contraceptive market supply shares over time. The package implements four model types. These models vary by the administration level of their outcome estimates (national or subnational estimates) and dataset type utilised in the estimation (multi-country or single-country contraceptive market supply datasets). mcmsupply contains a compilation of national and subnational level contraceptive source datasets, generated by IPUMS and Demographic and Health Survey microdata. We describe the functions that implement the models through practical examples. The annual estimates and projections with uncertainty of the contraceptive market supply, produced by mcmcsupply at a national and subnational level, are the first of their kind. These estimates and projections have diverse applications, including acting as an indicator of family planning market stability over time and being utilised in the calculation of estimates of modern contraceptive use.
Unlike developed market, some emerging markets are dominated by retail and unprofessional trading. China A share market is a good and fitting example in last 20 years. Meanwhile, lots of research show professional investor in China A share market continuously generate excess return compare with total market index. Specifically, this excess return mostly come from stock selectivity ability instead of market timing. However for some reason such as fund capacity limit, fund manager change or market regional switch, it is very hard to find a fund could continuously beat market. Therefore, in order to get excess return from mutual fund industry, we use quantitative way to build the sparse portfolio that take advantage of favorite stocks by mutual fund in China A market. Firstly we do the analysis about favourite stocks by mutual fund and compare the different method to construct our portfolio. Then we build a sparse stock portfolio with constraint on both individual stock and industry exposure using portfolio optimizer to closely track the partial equity funds index 930950.CSI with median 0.985 correlation. This problem is much more difficult than tracking full information index or traditional ETF as higher turnover of mutual fund, just first 10 holding of mutual fund available and fund report updated quarterly with 15 days delay. Finally we build another low risk and balanced sparse portfolio that consistently outperform benchmark 930950.CSI.
Maria Clara Bueno Fischer, Doriedson do Socorro Rodrigues
O presente texto traz, a partir do materialismo histórico-dialético, uma contribuição à análise do intercâmbio seres humanos-natureza mediados pelo trabalho como crítica do modo de produção capitalista, que impõe uma ruptura dessa relação nesse intercâmbio. Contudo, contrapondo-se a essa perspectiva, é possível identificar outros modos de vida que resistem a isso no interior das contradições capital-trabalho. As reflexões propostas almejam colaborar com o aprofundamento de análises sobre as relações entre trabalho e educação, em particular o trabalho como princípio educativo, a partir do enfoque do tema relações entre seres humanos e natureza.
Palavras-chave: Relações entre seres humanos-natureza; Trabalho como princípio educativo; Modos de vida. Povos e comunidades tradicionais.
Special aspects of education, Labor market. Labor supply. Labor demand
MEMÓRIA E DOCUMENTOS me trazem à mente duas questões. Uma delas é a memória e sua existência na vida humana. A outra questão são os documentos. Mia Couto, o escritor moçambicano, nos diz que que existimos enquanto alguém se lembrar de nós, enquanto estivermos na memória. Esta ideia serve para os indivíduos, mas, principalmente, para as instituições com seus coletivos, ideias, interesses diversos e divergências.
Special aspects of education, Labor market. Labor supply. Labor demand
Cándida Lorenzo, Golnaz Shadmani, Hajar Valouzi
et al.
Saffron is a spice that is obtained by dehydrating the stigmas of the <i>Crocus sativus</i> flower. Iran is the country that produces the largest amount of saffron, exceeding 90% of world production. Currently, there is a growing medicinal use which implies that there is more demand than supply worldwide, in turn, a large amount of labor is required to obtain it; for these two reasons, it reaches a high price in the international market. This demand is due to the high concentration of apocarotenoid metabolites that it biosynthesizes. In this work, the content of these metabolites of saffron from six production areas of Iran and neighbouring countries infected with saffron latent virus (SaLV) and dehydrated at two temperatures is compared. The corms of the six provenances were planted in a homogeneous plot and the stigmas analyzed were those of the second year after planting. The analysis showed that corms do not completely retain the memory of their original origin. In general, the ratio of the sum of mmol/kg of HTCC derivatives to the sum of the mmol of crocins is greater than two. This implies that the biosynthesis of saffron apocarotenoids due to the degradation of β-carotene towards HTCC is more important than that of zeaxanthin formation, which later gives HTCC and crocetin dialdehyde.
Felipe Addor, Layssa Ramos Maia de Almeida, Bianca de Carvalho P. Campos
Partindo de uma visão crítica do atual modelo democrático hegemônico na América Latina, destaca-se a necessidade de se experimentar novas práticas democráticas que estejam vinculadas com a dinâmica territorial do cotidiano e que busquem contribuir para sistemas econômicos menos desiguais. Nesse sentido, fazemos uma análise da experiência venezuelana da “democracia participativa y protagónica”, dos seus limites e potencialidades, no sentido de inspirar outras experiências de aprofundamento da democracia na região.
Palavra-chave: Venezuela; Democracia Participativa; Conselhos Comunais; Território; Economia Comunal.
Special aspects of education, Labor market. Labor supply. Labor demand
We propose a theory of the market impact of metaorders based on a coarse-grained approach where the microscopic details of supply and demand is replaced by a single parameter $ρ\in [0,+\infty]$ shaping the supply-demand equilibrium and the market impact process during the execution of the metaorder. Our model provides an unified explanation of most of the empirical observations that have been reported and establishes a strong connection between the excess volatility puzzle and the order-driven view of the markets through the square-root law.
I study the role of industries' position in supply chains in shaping the transmission of final demand shocks. First, I use a novel shift-share design leveraging destination-specific final demand shocks and a new measure of destination exposure accounting for direct and indirect linkages. I find that demand shocks amplify significantly as they propagate upstream, with upstream industries experiencing output elasticities up to three times larger than final good producers, consistent with the bullwhip effect. To rationalize these empirical results, I develop a tractable production network model with inventories and study how the properties of the network and the cyclicality of inventories interact to determine whether final demand shocks amplify or dissipate upstream. I test the mechanism by directly estimating the model-implied relationship between output growth and demand shocks, mediated by network position and inventories. I find that the presence of inventories increases output elasticities by 18% on average, highlighting the macroeconomic significance of this channel. Finally, I use the model to quantitatively study the effects of long-run trends of lengthening supply chains and rising inventories on the volatility of the economy.
Dmitriy Rodionov, Anastasia Ivanova, Olga Konnikova
et al.
The aim of the article is to investigate the impact of the new coronavirus infection on the Russian labor market and to suppose the actions to be taken to minimize negative economic consequences. The distinctiveness of this study is the differentiation of the impact of the physical and informational spread of COVID-19. The informational spread of coronavirus is measured through the dynamics of news messages related to the topic of “coronavirus” in the largest Russian media. The analysis of the average level of wages by type of economic activity, as well as the demand of employers and the number of vacancies, allow testing the hypothesis that the physical and informational spread of coronavirus caused an increase in the number of unemployed, a decrease in average wages in the studied range of economic activities, an increase in supply on the labor market, and a decrease in demand for employees. Another task of the study is to assess the dynamics of related search queries in Yandex (Russian biggest search engine), which can help to reveal the logic in the behavior of the Russian people during the pandemic as well as to understand if the Russian economy, the labor market, and society were prepared for the changes caused by the pandemic. Using a regression modeling methodology, it was found that the influence of the information environment, namely the informational spread of coronavirus, had an even greater impact on studied parameters than the physical spread. A “delay effect of physical consequences” was discovered. The conclusions obtained showed that in the conditions of wide informatization of society, it is necessary to systematically influence the physical and informational spread of coronavirus to minimize the negative consequences of the pandemic on the labor market.
The importance of vocational training and capacity assessment has grown since the 1980s. Vocational education is an important foundation for societal and economic development. Therefore, it is crucial to develop vocational training and education that meet the demands of the labor market. Modern industrial structure is different from that of the past, creating an imbalance in the supply and demand of the labor force. The purpose of the Skills Competition (the collective term for the regional competition under the Taiwan National Skills Competition in this research) is to encourage the young generation to participate in vocational education and training, thereby further improving the effect and efficiency of learning and training. In order to develop suitable indicators for the joinery trade of the regional competition, Taiwan National Skills Competition (hereinafter referred to as the Regional Competition), we first identify the level of importance of each indicator. Firstly, this study formed a hierarchical structure via the fuzzy Delphi method (FDM) with six training indicators (drawings, internal and external joints, assembly, measurements, finishing and appearance, and application of materials), and 27 sub-indicators were developed on the basis of these six major indicators. Secondly, in order to develop suitable training indicators for the joinery trade of the Regional Competition, the fuzzy analytic hierarchy process (fuzzy AHP) was adopted to seek the relative weight value of each indicator by assessing subjects through a paired-comparison. The results show that, among the six indicators, the relative weight value of measurements was the highest, followed by finishing and appearance and drawings. The indicators with higher relative weight value, such as measurement and finishing and appearance, should be paid more attention during the training processes. It is hoped that these results be presented to the trainers or instructors of training institutions or vocational schools as a reference to improve their training models, strategies, and quality.