Miracle-dz/UniFAR-FTUs huggingface dataset:
Intertemporal Consumption with Directly Measured Welfare Functions and Subjective Expectations

Euler equation estimation of intertemporal consumption models imposes heavy demands on data and identifiability conditions. For example, one typically needs panel data on consumption, assumptions on expectations, and a parameterization of preferences. We aim at reducing some of these requirements, by using additional information on respondents’ preferences and expectations. The results suggest that individually measured welfare functions and expectations have predictive power for the variation in consumption across households. Furthermore, estimates of the intertemporal elasticity of substitution based on the estimated welfare functions are plausible and of a similar order of magnitude as other estimates found in the literature. JEL Codes: D91, D84, D12
Graph learning methods to analyze and support industrial resilience

Graphs are increasingly used to describe interactions between entities. They are based on simple formalism that nevertheless allows modelling of complex systems such as industrial ecosystems. Thus, a knowledge graph can be built from traditional economic variables, but also from new alternatives variables from open-source’s data and big data. In this article, we review some graph learning methods and discusses latest advances in this field. Machine and deep graph learning method learn embeddings for nodes/edges in a graph to perform many tasks, such as link prediction, clustering, and nodes classification. Originality of this talk is the application on graph learning’s methods to analyze and support industrial resilience. Indeed, by learning knowledge graphs which represents an industrial ecosystem, we could help for a more resilient and ecological production. In this survey, we discuss on many advantages of graph learning models and their limits. This review shows latest advances and leads to a discussion of prospects for future research.
Cirrus Cloud Microphysical Properties and Aerosol Indirect Effects using Airborne Observations and a Global Climate Model

CIRRUS CLOUD MICROPHYSICAL PROPERTIES AND AEROSOL INDIRECT EFFECTS USING AIRBORNE OBSERVATIONS AND A GLOBAL CLIMATE MODEL by Ryan Patnaude Cirrus clouds are strong controllers of the global radiation budget, but significant uncertainties remain regarding the thermodynamic, dynamic, and aerosol indirect effects on their microphysical properties. The lack of observational analysis on cirrus cloud controlling factors, i.e., temperature, relative humidity, vertical velocity, and aerosol number concentrations (Na), limits our understanding of their impact on cirrus microphysical properties, making quantification and parameterization of cirrus clouds in climate models difficult. Using seven flight campaigns funded by the National Science Foundation (NSF), impacts of cirrus controlling factors and their regional distributions are individually quantified, and used to evaluate the National Center for Atmospheric Research (NCAR) Community Atmosphere Model 6 (CAM6). Na is found to produce positive correlations with respect to cirrus microphysical properties (i.e., ice water content, ice crystal number concentrations, and mean diameter) when Na is 3 – 10 times higher than average values. The magnitudes of the correlations depend on the size of the aerosols (i.e., > 500 nm or > 100 nm) and environmental conditions, indicating different roles of heterogeneous and homogeneous nucleation, respectively. Compared with observations, CAM6 simulations show large biases in terms of aerosol indirect effects and regional variations of cirrus microphysical properties, underscoring the importance of evaluating and improving cirrus cloud parameterizations in climate models.
International Perspectives on Sexual and Reproductive Health

A critical element in preventing unwanted and mistimed births, and in reducing the need for induced abortions, is the proportion of couples adopting a contraceptive method who continue to use it or another method. 1,2 Analyses of survey data have demonstrated that contraceptive discontinuation is common. 2–4 In a comparative analysis of contraceptive histories collected in Demographic and Health Surveys (DHS) from 15 developing countries, for example, the percentage of users who discontinued using any method within 12 months for quality related reasons (method failure, side effects, partner disapproval , health concerns and cost) varied from 9% in Zimbabwe to 34% in the Dominican Republic. 5 In each of these countries, discontinuation for quality-related reasons was more common than that for reduced need (desire to get pregnant, marital dissolution, menopause). BACKGROUND The decision to continue or discontinue use of a contraceptive involves a number of factors—the acceptability of contraceptive options, current and future circumstances, and fertility desires. 2 Despite the expected significance of fertility desires in deciding whether to continue contraceptive use, the majority of cases of contraceptive discon
Minimisation du Temps de Réponse moyen d'une Cascade de Détection

La detection visuelle d'objets est importante dans de nombreux domaines d'application. L'objectif est de determiner la presence et la position de certains types d'objets dans une image. Les approches existantes realisent classiquement un echantillonnage de l'image en fenetres, chacune etant analysee pour determiner si elle contient l'objet recherche (echantillon positif) ou non (echantillon negatif). Cette approche induit un temps de traitement important parce qu'une image genere une grande quantite d'echantillons, surtout negatifs. Pour pallier ce probleme, des architectures de classification en cascade ont ete proposees dans lesquelles des classificateurs faibles sont utilises a chaque etage. Un echantillon classifie negatif a un niveau de la cascade est definitivement rejete (et ne traverse par les niveaux suivants). Les cascades construites avec la methode AdaBoost comptent parmi les plus performantes. AdaBoost est base sur un apprentissage supervise d'un modele de classification qui utilise une somme ponderee des resultats des classificateurs faibles. A chaque niveau de la cascade est associe un seuil de classification : si le score obtenu par un echantillon a un etage est superieur ou egale au seuil, ce dernier est classe positif, sinon il est negatif et rejete. Ces seuils sont choisis afin de respecter un taux de vrais positifs souhaite (TPR). La variante la plus recente de cascade est le modele soft-cascade sue lequel est base notre travail. La qualite d'une soft-cascade etant principalement mesuree en termes de TPR et de taux de faux positifs (FPR), les methodes d'apprentissage classiques ne prennent pas en compte explicitement leur temps de reponse, pourtant central dans des applications ou l'environnement est fortement dynamique. Dans ce travail, nous envisageons une technique de minimisation du temps de reponse qui consiste a optimiser les seuils de classification utilises a chaque etage de la cascade. Nous produisons trois contributions : (1) nous prouvons tout d'abord que determiner des seuils de classification qui minimise le temps de reponse d'une soft-cascade est NP-Difficile; (2) nous proposons ensuite des proprietes de dominance permettant de reduire de facon importante l'espace de recherche de solution; (3) exploitant ces proprietes, nous introduisons une formulation de programmation lineaire 0-1 originale pour resoudre ce probleme; (4) nous validons enfin la methode proposee de facon experimentale sur un basee de donnees de la litterature.
Minimum-Income Benefits in OECD Countries: Policy Design, Effectiveness and Challenges

Almost all OECD countries operate comprehensive minimum-income programmes for working-age individuals, either as last-resort safety nets alongside primary income replacement benefits, or as the principal instrument for delivering social protection. Such safety-net benefits aim primarily at providing an acceptable standard of living for families unable to earn sufficient incomes from other sources. This paper provides an overview of social assistance and other minimum-income programmes in OECD countries, summarises their main features, and highlights a number of current policy challenges.
Intellectual capital and firm performance in India after the companies act, 2013: A study of selected BSE-listed firms

This study explores the effect of Intellectual Capital (IC) on the performance of Fast-Moving Consumer Goods (FMCG) and Information Technology (IT) sector firms in India after the Companies Act, 2013. This study used Return on Assets (ROA) as a performance variable. The IC efficiency and its constituents are used as predictor variables and measured by Value Added Intellectual Coefficient (VAICTM) model, which was applied to the longitudinal dataset during Financial Year (FY) 2015-16 to FY 2019-20. The study finds that IC had a momentous affirmative impact on accounting performance during the study period. This study also finds that the components of IC, human capital, and structural capital positively impact firm performance. Nevertheless, this study fails to extract any significant stimulus from the efficiency of physical capital on firm performance. Further, firm experience and size positively influence the performance measured by ROA. This paper highlights new determinants of firm performance, i.e., IC and its components, which market regulators, policymakers, researchers, and investors can take into consideration for different market-related decisions.
Complement downregulation promotes an inflammatory signature that renders colorectal cancer susceptible to immunotherapy

Background and aims The role of inflammatory immune responses in colorectal cancer (CRC) development and response to therapy is a matter of intense debate. While inflammation is a known driver of CRC, inflammatory immune infiltrates are a positive prognostic factor in CRC and predispose to response to immune checkpoint blockade (ICB) therapy. Unfortunately, over 85% of CRC cases are primarily unresponsive to ICB due to the absence of an immune infiltrate, and even the cases that show an initial immune infiltration can become refractory to ICB. The identification of therapy supportive immune responses in the field has been partially hindered by the sparsity of suitable mouse models to recapitulate the human disease. In this study, we aimed to understand how the dysregulation of the complement anaphylatoxin C3a receptor (C3aR), observed in subsets of patients with CRC, affects the immune responses, the development of CRC, and response to ICB therapy. Methods We use a comprehensive approach encompassing analysis of publicly available human CRC datasets, inflammation-driven and newly generated spontaneous mouse models of CRC, and multiplatform high-dimensional analysis of immune responses using microbiota sequencing, RNA sequencing, and mass cytometry. Results We found that patients’ regulation of the complement C3aR is associated with epigenetic modifications. Specifically, downregulation of C3ar1 in human CRC promotes a tumor microenvironment characterized by the accumulation of innate and adaptive immune cells that support antitumor immunity. In addition, in vivo studies in our newly generated mouse model revealed that the lack of C3a in the colon activates a microbiota-mediated proinflammatory program which promotes the development of tumors with an immune signature that renders them responsive to the ICB therapy. Conclusions Our findings reveal that C3aR may act as a previously unrecognized checkpoint to enhance antitumor immunity in CRC. C3aR can thus be exploited to overcome ICB resistance in a larger group of patients with CRC.
Comparative dosimetric analysis and NTCP modelling of 4D-CT planning scans within the UK NeoSCOPE trial

: Neoadjuvant chemoradiotherapy for resectable oesophageal cancer improves overall survival compared to surgery alone but is associated with increased toxicity. NeoSCOPE is a trial of two different nCRT regimens for resectable oesophageal and was the first multi-centre trial in the UK to incorporate 4D-CT into the radiotherapy planning. Using NeoSCOPE 4D-CT cases, we undertook a dosimetric comparison study of 3D-CT versus 4D-CT plans comparing target volume coverage and dose to organs at risk. We used established
Land Tenure and the Management of Land and Trees in Asia and Africa

This paper summarizes and extends the results of seven-country projects conducted in Ghana, Uganda, Malawi, Sumatra (Indonesia), Vietnam, Nepal, and Japan on the land tenure institutions and the management of forest, agroforest, and cropland. It is found that traditional or customary land tenure institutions possess no built-in mechanisms to prevent deforestation. They have evolved, however, from communal ownership to individualized ownership so as to provide proper incentives to induce commercial tree planting and the management of tree fields (or agroforestry). It is also found that common property system is efficient for the management of forests producing minor products such as firewood, whereas more individualized system is more efficient for the management of timber forests.
Indigenous People and Economic Development : An International Perspective

Indigenous peoples are an intrinsic part of countries like Australia, New Zealand, Canada, Finland, USA, India, Russia and almost all parts of South America and Africa. A considerable amount of research has been done during the twentieth century mainly by anthropologists, sociologists and linguists in order to describe, and document their traditional life style for the protection and safeguarding of their established knowledge, skills, languages and beliefs. These communities are engaging and adapting rapidly to the changing circumstances partly caused by post modernisation and the process of globalization. These have led them to aspire to better living standards, as well as preserving their uniqueness, approaches to environment, close proximity to social structures and communities. For at least the last two decades, patterns of increased economic activity by indigenous peoples in many countries have been viewed to be significantly on the rise. Indigenous People and Economic Development reveals some of the characteristics of this economic activity, 'coloured' by the unique regard and philosophy of life that indigenous people around the world have. The successes, difficulties and obstacles to economic development, their solutions and innovative practices in business - all of these elements, based on research findings, are discussed in this book and offer an inside view of the dynamics of the indigenous societies which are evolving in a globalised and highly interconnected contemporary world.
Neural Radiance Fields for 6D Pose Estimation

This project looks into Neural Radiance Fields (NeRF) for 6D pose estimation. Since its introduction in 2020, Neural Radiance Fields (NeRF)[9] learned image priors from large-scale image sets. NeRFs have found uses in robotics applications for visuomotor control and vision-only robot navigation (with a pre-mapped NERF environment). The end application analyzed here concerns how NeRFs can be employed for 6D pose estimation. 6D pose estimation is the task of detecting the location and orientation of an object given a 2D image of the object.
Territorial mapping to reduce the mismatch between soil organic carbon stocks and potential storage capacity

The ‘4 per 1000’ initiative aims to increase soil organic carbon stocks to offset carbon dioxide emissions. For a French case study, this graphic offers evidence of the links between carbon stocks and agricultural productions at the territorial level: stocks are positively associated to animal loads, whereas soils with arable crops have much lower stocks despite a higher storage potential. Territorial mapping of both storage capacities and organic resources is needed to optimize soil carbon storage.
ery high resolution Earth observation features for monitoring plant nd animal community structure across multiple spatial scales in rotected areas

Monitoring the status and future trends in biodiversity can be prohibitively expensive using groundbased surveys. Consequently, significant effort is being invested in the use of satellite remote sensing to represent aspects of the proximate mechanisms (e.g., resource availability) that can be related to biodiversity surrogates (BS) such as species community descriptors. We explored the potential of very high resolution (VHR) satellite Earth observation (EO) features as proxies for habitat structural attributes that influence spatial variation in habitat quality and biodiversity change. In a semi-natural grassland mosaic of conservation concern in southern Italy, we employed a hierarchical nested sampling strategy to collect field and VHR-EO data across three spatial extent levels (landscape, patch and plot). Species incidence and abundance data were collected at the plot level for plant, insect and bird functional groups. Spectral and textural VHR-EO image features were derived from a Worldview-2 image. Three window sizes (grains) were tested for analysis and computation of textural features, guided by the perception limits of different organisms. The modelled relationships between VHR-EO features and BS responses differed across scales, suggesting that landscape, patch and plot levels are respectively most appropriate when dealing with birds, plants and insects. This research demonstrates the potential of VHR-EO for biodiversity mapping and habitat modelling, and highlights the importance of identifying the appropriate scale of analysis for specific taxonomic groups of interest. Further, textural features are important in the modelling of functional group-specific indices which represent BS in high conservation value habitat types, and provide a more direct link to species interaction networks and ecosystem functioning, than provided by traditional taxonomic diversity indices.
Rfid Handbook: Fundamentals and Applications in Contactless Smart Cards and Identification

RFID (Radio Frequency Identification) is used in all areas of automatic data capture allowing contactless identification of objects using RF. With applications ranging from secure internet payment systems to industrial automation and access control, RFID technology solutions are receiving much attention in the research and development departments of large corporations. RFID is a major growth are in auto ID, allowing emergency vehicles to safely trip traffic signals, and providing the technology behind contactless smart cards, "autopiloting" cars, and production automation. Fully revised and updated to include all the latest information on industry standards and applications, this new edition provides a standard reference for people working with RFID technology.Expanded sections explain exactly how RFID systems work, and provide up-to-date information on the development of new tags such as the smart label. This book provides updated coverage of RFID technologies, including electron data carrier architecture and common algorithms for anticollision. It details the latest RFID applications, such as the smartlabel, e-commerce and the electronic purse, document tracking and e-ticketing. It includes a detailed appendix providing up-to-date information on relevant ISO standards and regulations, including descriptions of ISO 14443 for contactless ticketing and ISO 15693 covering the smartlabel.A leading-edge reference for this rapidly evolving technology, this text is of interest to practitioners in auto ID and IT designing RFID products and end-users of RFID technology, computer and electronics engineers in security system development and microchip designers, automation, industrial and transport engineers and materials handling specialists. It is also a valuable resource for graduate level students in electronics and industrial engineering design.
The Scientific Revolution

This work contains Steven Shapin's historical exploration into the origins of the modern scientific worldview. What historians have traditionally called the Scientific Revolution was, in Shapin's view, a diversity of practices and ideas that developed over the course of nearly two centuries. Rejecting the idea that there is anything like an "essence" of early modern science, the author shows that the Scientific Revolution in reality lacked the jarring abruptness and cataclysmic nature implied by its "revolutionary" name.
Analytical Placement with 3D Poisson’s Equation and ADMM-based Optimization for Large-scale 2.5D Heterogeneous FPGAs

As design complexity keeps increasing, the 2.5D field-programmable gate array (FPGA) with large logic capacity has become popular in modern circuit applications. A 2.5D FPGA consists of multiple dies connected through super long lines (SLLs) on an interposer. Each die contains heterogeneous logic blocks and ASIC-like clocking architectures to achieve better skew and timing. Existing works consider these problems separately and thus may lead to serious timing issues or routing failure. This article presents an analytical placement algorithm for the 2.5D FPGA to simultaneously minimize the number of inter-die SLL signals and intra-die clocking violations. Using a lifting dimension technique, we first formulate the 2.5D global placement problem as a three-dimensional continuous and differential minimization problem, where the SLL-aware block distribution is modeled by 3D Poisson’s equation and directly solved to obtain an analytical solution. Then, we further reformulate the minimization problem as a separable optimization problem with linear constraints. Based on the proximal alternating direction method of multipliers optimization method, we efficiently optimize the separable subproblems one by one in an alternating fashion. Finally, clock-aware legalization and detailed placement are applied to legalize and improve our placement results. Compared with the state-of-the-art works, experimental results show that our algorithm can resolve all clocking constraints and reduce the number of SLL crossing signals by 36.9% with similar wirelength in a comparable running time.
HEAVY VEHICLE DRIVER WORKLOAD ASSESSMENT. TASK 4: REVIEW OF WORKLOAD AND RELATED RESEARCH

This report reviews literature on workload measures and related research. It depicts the preliminary development of a theoretical basis for relating driving workload to highway safety and a selective review of driver performance evaluation, workload evaluation in driving contexts, and risk-taking and risk adaptation behavior. An actuarial approach to establish the safety relevance of workload measures is discussed in conjunction with a driver resources allocation model of in-cab device workload. The report concludes with the presentation of a driver resources-based taxonomy of in-cab tasks and candidate workload measures and their potential sensitivity to tasks described in the taxonomy.