Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Disability Insurance Receipt Discourage Work? Using Examiner Assignment to Estimate Causal Effects of Ssdi Receipt Does Disability Insurance Receipt Discourage Work? Using Examiner Assignment to Estimate Causal Effects of Ssdi Receipt

This product is part of the RAND Labor and Population working paper series. RAND working papers are intended to share researchers' latest findings and to solicit informal peer review. They have been approved for circulation by RAND Labor and Population but have not been formally edited or peer reviewed. Unless otherwise indicated, working papers can be quoted and cited without permission of the author, provided the source is clearly referred to as a working paper. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors. is a registered trademark. Abstract We present the first estimates of the causal effects of Social Security Disability Insurance receipt on labor supply estimated using the entire population of program applicants. We exploit administrative data to match applications to disability examiners, and use natural variation in examiners' allowance rates as an instrument for the allowance decision in a labor supply equation contrasting denied vs. allowed applicants. Importantly, we find that the disincentive effect is heterogeneous, ranging from a 10 percentage point reduction in labor force participation for those with more severe impairments to a 60 percentage point reduction for entrants with relatively less severe impairments. Security Administration (SSA) through the Michigan Retirement Research Center (MRRC). The opinions and conclusions expressed are solely those of the authors and do not represent the opinions or policy of SSA or any agency of the Federal Government.
Odour intensity learning in fruit ﬂies

Animals’ behaviour towards odours depends on both odour quality and odour intensity. While neuronal coding of odour quality is fairly well studied, how odour intensity is treated by olfactory systems is less clear. Here we study odour intensity processing at the behavioural level, using the fruit ﬂy Drosophila melanogaster . We trained ﬂies by pairing a MEDIUM intensity of an odour with electric shock, and then, at a following test phase, measured ﬂies’ conditioned avoidance of either this previously trained MEDIUM intensity or a LOWer or a HIGHer intensity. With respect to 3-octanol, n -amylacetate and 4-methylcyclohexanol, we found that conditioned avoidance is strongest when training and test intensities match, speaking for intensity-speciﬁc memories. With respect to a fourth odour, benzaldehyde, on the other hand, we found no such intensity speciﬁcity. These results form the basis for further studies of odour intensity processing at the behavioural, neuronal and molecular level.
Mosaic: An Architecture for Scalable & Interoperable Data Views

Mosaic is an architecture for greater scalability, extensibility, and interoperability of interactive data views. Mosaic decouples data processing from specification logic: clients publish their data needs as declarative queries that are then managed and automatically optimized by a coordinator that proxies access to a scalable data store. Mosaic generalizes Vegalite's selection abstraction to enable rich integration and linking across visualizations and components such as menus, text search, and tables. We demonstrate Mosaic's expressiveness, extensibility, and interoperability through examples that compose diverse visualization, interaction, and optimization techniques—many constructed using vgplot, a grammar of interactive graphics in which graphical marks act as Mosaic clients. To evaluate scalability, we present benchmark studies with order-of-magnitude performance improvements over existing web-based visualization systems—enabling flexible, real-time visual exploration of billion+ record datasets. We conclude by discussing Mosaic's potential as an open platform that bridges visualization languages, scalable visualization, and interactive data systems more broadly.
Investments in Agricultural Innovation and Food Security in Sub-Saharan Africa

Empirical evidence proves that agricultural R&D expenditure and researchers attract high returns though the investments have long-gestation periods. Nonetheless, sub-Saharan Africa (SSA) invests meanly in agricultural R&D and researchers. This study explores the impacts of agricultural R&D expenditures and researchers on food security in the region and across the sub-regions. The study applies Bootstrapped LSDV and two-step system GMM techniques to analyze the data on 23–24 SSA countries over the period 2000–2016. Our �ndings show that investments in agricultural innovation substantially increase food accessibility, availability, and utilization through food productivity growth. Indeed, the investments are more effective in enhancing food utilization than in boosting food availability and accessibility. The �ndings also reveal that the investments are effective in enhancing food security at least in Southern and Western African sub-regions while they instead exacerbate the problem of food insecurity in Central Africa. The policy implications are adequate resources should be channeled into proper agricultural research and development to introduce new crop varieties or signi�cantly improved crops, etc. There should also be coordination between large and small countries in investments so that the countries can bene�t from economies of scale.
A SECURITY SYSTEM FOR E-EXAMS USING AN IoT AND FOG COMPUTING ENVIRONMENT

A recently significant confirmation has adopted to e-learning systems are in great demand. Students, instructors, and examiners share large amounts of data, which should be transmitted securely. One of the most support infrastructures to merging intelligent devices, data analysis, and cybersecurity is the Internet of Things(IoT). Specifically, when combined with Fog and cloud potentials to strengthen the performance of various latency-sensitive and computing-intensive. This paper presents the IoT-Fog-Cloud framework to provide security factors in sharing E-exam which poses several security challenges, such as fine-grained access control and security preservation of E-exam. Further, the proposed framework supports bringing closer the services to the students. Besides, this paper improves the efficiency of E-exam data analysis, reduces the encryption burden in terms of computation cost on user’s devices by offloading part of encryption cost to fog servers, and provides fine-grained access control to E-exam content by encrypting with different cryptographic techniques. IoT–fog–cloud framework works in consideration of two main elements: the layer components and the layer processes. Layer components to be integrated include the FGNs, cloud data centers, and GFNs. In layer processes, a series of benefits can be realized, since distribution processes help students to reduce latency and enhance response times and the preservation of privacy and security . Finally, this paper shows that the proposed IoT-Fog-Cloud framework can achieve data confidentiality, fine-grained access control, collusion resistance, and unforgeability to ensure secure procedures to apply the proposed framework.
Structural characteristics of a subducting oceanic plate off Western Canada

The plate tectonic regime off the southwest coast of British Columbia is convergent; the oceanic Juan de Fuca and Explorer plates are obliquely subducting beneath the continental America plate. To investigate the structural complexity of this region, the Vancouver Island Seismic Project was conducted in August 1980. The principal component of this project was a reversed refraction profile perpendicular to the continental margin, extending 350 km from the America plate to the deep ocean of the Juan de Fuca plate. This work deals with the marine section of the profile. Data from large explosive sources and an airgun were recorded on three ocean bottom seismographs (in the deep ocean, on the continental rise and on the shelf). Continuous seismic reflection profiles complemented the refraction information. To adequately model the seismic structure of this complex region required the application of ray-tracing procedures and a synthetic seismogram technique, based on asymptotic ray theory, for laterally varying media. Consistency between the seismic interpretation and previously published gravity anomaly variations across the margin was verified with the aid of empirical velocity-density relations. Additional seismic constraints were provided by multichannel reflection sections and sonic log data from a nearby well. The aim of a l l procedures for data modelling was to obtain velocity and density models which had the least structure consistent with a l l available geophysical information. The interpreted structural section indicates that the sediments thicken from 1 km in the deep ocean to 2 km at the base of the continental rise, where the eastward dip of the oceanic basement increases from 1.4° to about 3° and sediment velocities increase landwards. A str a t i f i e d upper crustal velocity sequence has been derived below the deep ocean which is similar to that deduced from other studies on the Juan de Fuca plate. This stratification is discordant with the descending oceanic plate further east; i t is replaced by a block of relatively low velocity material beneath the continental rise. This unit is interpreted to be a highly sheared and compressed melange. Lower crustal structure remains constant over the entire marine profile, suggesting that the melange material may have been formed as upper crustal layers were scraped off the descending oceanic plate. The lower crust has been modelled as a constant velocity gradient region, extending down to approximately 9 km below sea floor in the deep ocean. At this depth there is a strong decrease in velocity gradient, interpreted to be the Mohorovicic discontinuity. Resolution of Moho structure is poor, but no velocity discontinuity at the boundary is required by the data. There is an increase in the dip of the Moho under the continental rise from about 1° to 6 ° . The refraction data are thus explicable in terms of a relatively simple, two-dimensional velocity model, which is consistent with multichannel, well-log, and gravity information.
Discussion Papers in Economics Dynamics of Output Growth, Consumption and Physical Capital in Two-Sector Models of Endogenous Growth Learning About Monetary Policy Rules

We study macroeconomic systems with forward-looking private sector agents and a monetary authority that is trying to control the economy through the use of a linear policy feedback rule. A typical (cid:222) nding in the burgeoning literature in this area is that policymakers should be relatively aggressive in responding to available information about the macroeconomy. A natural question to ask about this result is whether policy responses which are too aggressive might actually destabilize the economy. We use stability under recursive learning a la Evans and Honkapohja (2000) as a criterion for evaluating monetary policy rules in this context. We (cid:222) nd that considering learning can alter the evaluation of alternative policy rules. JEL Classi (cid:222) cation E4, E5. and su ﬃ cient conditions for local explosiveness- for this we need all the eigenvalues of B to be inside the unit circle. The conditions are somewhat messy but a casual observation shows that an aggressive response of the interest rate to lagged in (cid:223) ation and output will necessarily cause explosiveness.
University of Birmingham Mechanical modelling quantifies the functional importance of outer tissue layers during root elongation and bending

model to describe elongation and bending. To accurately parameterise the model, we take detailed measurements of cell turgor, cell geometries and wall thicknesses. (cid:1) The model demonstrates how cell properties and shapes contribute to tissue-level extensibility and yield. Exploiting the highly organised structure of the elongation zone (EZ) of the Arabidopsis root, we quantify the contributions of different cell layers, using the measured parameters. We show how distributions of material and geometric properties across the root cross-section contribute to the generation of curvature, and relate the angle of a gravitropic bend to the magnitude and duration of asymmetric wall softening. (cid:1) We quantify the geometric factors which lead to the predominant contribution of the outer cell ﬁles in driving root elongation and bending.
A NOVEL APPROACH FOR AUTOMATIC SPEAKER IDENTIFICATION OF ASSAMESE LANGUAGE USING COSINE SIMILARITY AND ABSOLUTE MFCC FEATURE MATRIX

Automatic speaker Identification (ASI) is always challenging work for researchers. ASI is a process where a speaker is recognized automatically from his/her voice sample by comparing it with their previously recorded voices. The machine learning approach has been gaining popularity in recent years for ASI. Different machine learning approaches used in ASI in recent years are Convolutional Neural Network (CNN) [14,15,16], Deep Neural Network (DNN) [10,11,12,13], Artificial Neural Network (ANN) [17,18]. This research aims to build an automatic speaker identification system for the Assamese language, which is spoken in the North-Eastern part of India and is one of the low-resource languages. So far, cosine similarity and parallel processing methods have not been used for speaker identification in the Assamese Language, which is the novelty of the current work. The model developed in this work uses Mel-frequency cepstral coefficient (MFCC) to extract important features of speakers' voices to create a training sample set in the first phase. In the present approach, we have used the Speaker's absolute feature vectors (MFCC) directly, without any averaging, in order to retain and exploit the Speaker's unique characteristics. In the second phase, the features in the training sample set of the first phase are compared with the real-time test voice samples using the cosine similarity method to identify the Speaker automatically. Parallel processing is used to compare all the coefficients in the test voice sample with the training voice sample to make the system faster. The effectiveness of the proposed method has been established in terms of precision, recall, f1 score, and accuracy value. The model demonstrated an accuracy of 91% for speaker identification in the Assamese language.
Phase-coherent Oscillatory Modes in Solar and Geomagnetic Activity and Climate Variability

Oscillatory modes with the period of approximately 7–8 years were detected in monthly time series of sunspot numbers, geomagnetic activity aa index, NAO index and near-surface air temperature from several mid-latitude European locations. Instantaneous phases of the modes underwent synchronization analysis and their statistically significant phase coherence, beginning from 1950's, has been observed. Thus the statistical evidence for a coupling between solar/geomagnetic activity and climate variability has been obtained from continuous monthly data, independent of the season, however, confined to the temporal scale related to oscillatory periods about 7–8 years.
Making World Heritage Truly Global: the Culture Certificate Scheme World Heritage and Conservation Needs Outline of the Proposal Making World Heritage Truly Global

Culture has attributes of a global public good that needs to be preserved for mankind as a whole. World Culture Certificates are proposed to efficiently preserve World Heritage. The community of nations has to agree on the Global Heritage List and how much each nation is to contribute to that purpose. Each World Heritage site conserved is acknowledged through the issuance of a tradable Certificate. Countries and private firms are induced to seek sites where financial resources can be spent most productively. This leads to an efficient allocation of resources to preserve World Heritage. The UNESCO Convention on World Heritage of 1972 " seeks to encourage the identification, protection and preservation of cultural and natural heritage around the world considered to be of outstanding value to humanity ". 3 It aims to preserve monuments, natural and cultural landscapes as a legacy of the past, in order to pass this heritage on to future generations. From its very beginning the convention's intention has been directed towards the entire world. World Heritage is a clear example of a global common good: " The World Heritage List reflects the wealth and diversity of the Earth's cultural and natural heritage " (UNESCO, 2005). The convention goes far beyond established national conservation efforts because it acknowledges that due to the free-rider problem associated with managing preservation on a purely national level the aggregate quantity of preservation is inefficiently low. A host country will pay only to preserve up to the point where the marginal national benefit equal marginal cost. The World Heritage movement started in 1959 with the international campaign launched by UNESCO to save the Abu Simbel temples in the Nile valley. 4 At the beginning, World Heritage was directed to cultural sites but since 1968 is also includes natural sites, and since 1992 also stresses significant interactions between people and the natural environment, entitled " cultural landscapes " (UNESCO, 2005). This noble ideal has only been attained to a limited extent. In particular, the distribution of 1 We are grateful to Isabel Ellenberger for checking the text and an anonymous referee for excellent suggestions for improvement. We thank It must be emphasized that UNESCO does not provide any (or at best only minor) financial help; UNESCO provides expertise and scientific support. 4 It might be argued that the great attention paid to the seven " Classical World Wonders " (Great Pyramid of Giza, …
Cryptocurrencies-tax evasion nexus: Does economic performance matter? The case of G-7 countries

The global challenge of tax evasion presents a profound impact, leading to diminished tax revenues that are the lifeblood of a nation's seamless operations. This issue is exacerbated by the ingenious strategies employed by tax evaders, which distort economic performance benchmarks and create financial imbalances. Amidst these concerns, cryptocurrencies have emerged as a contentious subject, accused of abetting tax evasion. The covert nature of cryptocurrency transactions poses a significant hurdle for regulatory oversight and transaction recording. In response to this burgeoning concern, our comprehensive study delves into the intricate interplay between cryptocurrencies and tax evasion, utilizing annual data spanning from 2013 to 2020. With an extensive scope testing thirty two hypotheses and twelve interaction terms, our research unfurls the multifaceted dynamics at play. This study embarks by constructing a latest tax evasion index for the esteemed G-7 nations. Employing asymmetric/symmetric panel techniques, our investigation unveils a compelling revelation: cryptocurrencies exert a counteractive influence on instances of tax evasion. Furthermore, the nexus between economic performance and cryptocurrencies bears considerable sway over their correlation with tax evasion. Innovatively, our research charts the intricate relationship between tax evasion and cryptocurrencies across varying levels of economic performance. Notably, our findings underscore that Economic Freedom, Government Integrity, Government Spending, Business Freedom, Labor Freedom, Monetary Freedom, Investment Freedom, and Bureaucracy function as moderators, influencing the association between tax evasion and cryptocurrencies. These insights transcend academia, delivering significant implications to policymakers with informed guidance to devise nuanced strategies and policies.
Derived completion for comodules

Theobjectiveofthispaperistointroduceandstudycompletionsandlocalhomol-ogy of comodules over Hopf algebroids, extending previous work of Greenlees and May in thediscretecase.Inparticular,werelatemodule-theoretictocomodule-theoreticcompletion, constructvariouslocalhomologyspectralsequences,andderiveatilting-theoreticinterpre-tationoflocaldualityformodules.Ourresultstranslatetoquasi-coherentsheavesoverglobal quotientstacksandfeedintoanovelapproachtothechromaticsplittingconjecture.
Helping COPD patients change health behavior in order to improve their quality of life

: Chronic obstructive pulmonary disease (COPD) is one of the most prevalent and debilitating diseases in adults worldwide and is associated with a deleterious effect on the quality of life of affected patients. Although it remains one of the leading causes of global mortality, the prognosis seems to have improved in recent years. Even so, the number of patients with COPD and multiple comorbidities has risen, hindering their management and highlighting the need for futures changes in the model of care. Together with standard medical treatment and therapy adherence – essential to optimizing disease control – several nonpharmacological therapies have proven useful in the management of these patients, improving their health-related quality of life (HRQoL) regardless of lung function parameters. Among these are improved diagnosis and treatment of comorbidities, prevention of COPD exacerbations, and greater attention to physical disability related to hospitalization. Pulmonary rehabilitation reduces symptoms, optimizes functional status, improves activity and daily function, and restores the highest level of independent physical function in these patients, thereby improving HRQoL even more than pharmacological treatment. Greater physical activity is significantly correlated with improvement of dyspnea, HRQoL, and mobility, along with a decrease in the loss of lung function. Nutritional support in malnourished COPD patients improves exercise capacity, while smoking cessation slows disease progression and increases HRQoL. Other treatments such as psychological and behavioral therapies have proven useful in the treatment of depression and anxiety, both of which are frequent in these patients. More recently, telehealthcare has been associated with improved quality of life and a reduction in exacerbations in some patients. A more multidisciplinary approach and individualization of interventions will be essential in the near future.
Data-driven subtypes of major depressive disorder

Background: It is difficult to predict recurrence of depressive episodes in patients with major depression (MD): evidence for many risk factors is inconsistent and general prediction algorithms are lacking. The aim of this study was to develop a prediction model for recurrence of depressive episodes in women using improved methodology. Methods: We used prospective data from a general population sample of female twins with a last-year MD episode (n=194). A rich set of baseline predictors was analyzed with Cox proportional hazards regression subject to elastic net regularization to find a model predicting recurrence of depressive episodes. Prediction accuracy of the model was assessed in an independent test sample (n=133), which was limited by the unavailability of a number of key predictors. Results: A wide variety of risk factors predicted recurrence of depressive episodes in women: depressive and anxiety symptoms during the index episode, the level of symptoms at the moment of interview, psychiatric and family history, early and recent adverse life events, being unmarried, and problems with friends and finances. Kaplan Meier estimated survival curves showed that the model differentiated between patients at higher and lower risk for recurrence; estimated areas under the curve were in the range of 0.61-0.79. Conclusions: Recurrence of episodes of MD in women is highly multifactorial. Future studies should take this into account for the development of clinically useful prediction algorithms.