Miracle-dz/UniFAR-FTUs huggingface dataset:
of Forecast Performance

Does a central bank influence inflation expectations through its publicized forecast? Does such influence depend on how accurate the central bank’s forecasts have been? Given the importance of anchoring inflation expectations to inflationtargeting monetary frameworks, and given the central role of forecast in such frameworks, understanding the answers to these questions is important. We show, using an incentivized individual-choice experiment, that forecast performance matters a lot. We observe that the relationship between forecast performance and perceived forecast credibility is not as sharp as theory predicts due to an overprecision bias. Second, we find that the weight agents attach to central bank forecasts is strongly related to the forecast performance in the last 4 quarters. This is true whether subjects are forming short-term inflation forecasts or forecasting average inflation over a much longer time horizon. Low-frequency communication can significantly mitigate, though perhaps not fully, the effect of poor recent forecast performance. Using a high-frequency identification strategy, we show that this recency bias extends to real-world markets. We incorporate our experimental findings into an otherwise standard three-equation New Keynesian model to demonstrate how endogenous forecast credibility can lead to highly persistent inflation dynamics.
Evaluating the long-term impact of anti-poverty interventions in Bangladesh: an overview

This paper provides an overview of a research project that assessed the long-term impact of three antipoverty interventions in Bangladesh – the introduction of new agricultural technologies, educational transfers, and microfinance – on monetary and non-monetary measures of well-being. It begins by setting out the conceptual framework, methodology, and empirical methods used for the evaluation of long-term impacts. It discusses the context of the evaluations and the longitudinal data used. Key findings from the papers are then presented, followed by an indicative analysis of the cost-effectiveness of these interventions. The overview concludes with implications for programmes and policy.
Diversity for Contingency: Learning Diverse Behaviors for Efficient Adaptation and Transfer

Discovering all useful solutions for a given task is crucial for transferable RL agents, to account for changes in the task or transition dynamics. This is not considered by classical RL algorithms that are only concerned with finding the optimal policy, given the current task and dynamics. We propose a simple method for discovering all possible solutions of a given task, to obtain an agent that performs well in the transfer setting and adapts quickly to changes in the task or transition dynamics. Our method iteratively learns a set of policies, while each subsequent policy is constrained to yield a solution that is unlikely under all previous policies. Unlike prior methods, our approach does not require learning additional models for novelty detection and avoids balancing task and novelty reward signals, by directly incorporating the constraint into the action selection and optimization steps.
Method for ocean surface currents measurement by SAR

A new method for mapping shallow water topography surface currents from SAR image is introduced based on the shallow water topography SAR imaging mechanism. M4S (presented by Romeiser R.) was used to forward simulate radar signatures of the oceanic features over the ocean surface. The first guessed surface currents can be estimated from the normalized radar cross section (NRCS) of the shallow water topography profile in the SAR image according to the Apers-Hennings linear theory, the NRCS induced by the varying shallow water topography surface currents could be simulated by the forward simulating model. The wind speed and shallow water topography surface currents gradients are modified using the iterative method until the simulated radar signals close to the NRCS calculated from SAR image. By this method, the wind speed and the surface currents can be retrieved finally. This method is tested on an ERS-2 SAR image in the Taiwan Shoal. Results show that the simulated shallow water topography radar signal is consistent with the NRCS extracted from SAR image, and their correlation coefficient is up to 90%, which means that this method is convergent and applicable.
Antibacterial Activity of Thyme, Laurel, Rosemary and Parsley Essential Oils Against Some Bacterial Fish Pathogen

In this study, the antibacterial activities of the essential oils of thyme ( Thymus vulgaris L.) (TEO), laurel ( Laurus nobilis L.) (LEO), rosemary ( Rosmarinus officinalis L.) (REO) and parsley ( Petroselinum crispum L.) (PEO) against different fish pathogens such as Yersinia ruckeri two strains (a & b), Lactococcus garvieae, Pseudomonas fluorescens, Aeromonas sobria, Aeromonas salmonicida and Aeromonas veronii were investigated. The essential oils had been extracted by hydro-distillation using a Clevenger apparatus
Multicomponent reactive transport modeling in variably saturated porous media using a generalized formulation for kinetically controlled reactions

A generalized formulation for kinetically controlled reactions has been developed and incorporated into a multicomponent reactive transport model to facilitate the investigation of a large variety of problems involving inorganic and organic chemicals in variably saturated media. The general kinetic formulation includes intra‐aqueous and dissolution‐precipitation reactions in addition to geochemical equilibrium expressions for hydrolysis, aqueous complexation, oxidation‐reduction, ion exchange, surface complexation, and gas dissolution‐exsolution reactions. The generalized approach allows consideration of fractional order terms with respect to any dissolved species in terms of species activities or in terms of total concentrations, which facilitates the incorporation of a variety of experimentally derived rate expressions. Monod and inhibition terms can be used to describe microbially mediated reactions or to limit the reaction progress of inorganic reactions. Dissolution‐precipitation reactions can be described as surface‐controlled or transport‐controlled reactions. The formulation also facilitates the consideration of any number of parallel reaction pathways, and reactions can be treated as irreversible or reversible processes. Two groundwater contamination scenarios, both set in variably saturated media but with significantly different geochemical reaction networks, are investigated and demonstrate the advantage of the generalized approach. The first problem focuses on a hypothetical case study of the natural attenuation of organic contaminants undergoing dissolution, volatilization, and biodegradation in an unconfined aquifer overlaid by unsaturated sediments. The second problem addresses the generation of acid mine drainage in the unsaturated zone of a tailings impoundment at the Nickel Rim Mine Site near Sudbury, Ontario, and subsequent reactive transport in the saturated portion of the tailings.
Biodiversity conservation and the Brazilian Forest Code : small-scale farmers and law compliance in Southern Brazil

Various strategies may be used to promote biodiversity conservation on private land and support conservation at the landscape level. Brazil has had a law that addresses this issue to some extent since 1934. It is called Forest Code (FC), and has been revised twice, in 1965 and 2012. One of the reasons that led to its most recent revision was insufficient compliance among landowners. Another argument was that it was difficult to conciliate agricultural practices and conservation needs as established by the FC in small rural properties. A case study was carried out in the municipality of Arroio do Tigre, state of Rio Grande do Sul, to investigate factors that influenced small-scale farmers’ motivations to comply with the FC. Semi-structured interviews with small-scale farmers were carried out, and data was examined through thematic analysis. Findings demonstrate that diverse factors affected their compliance decisions by influencing their instrumental, normative, and legitimacy motivations for compliance. These factors are enforcement of the law, socioeconomic conditions, perceptions about forests, group behavior, distribution of costs and benefits, and contradictory governmental policies. Awareness about regulations also played a role. Strategies that could support increased conformity with the FC, as well as the possibility of the 2012 FC achieving greater compliance, and considerations on implications of the latest version of the law for biodiversity conservation are discussed.
IRISA participation to BioNLP-ST13: lazy-learning and information retrieval for information extraction tasks

This paper describes the information extraction techniques developed in the framework of the participation of IRISA-TexMex to the following BioNLP-ST13 tasks: Bacterial Biotope subtasks 1 and 2, and Graph Regulation Network. The approaches developed are general-purpose ones and do not rely on specialized preprocessing, nor specialized external data, and they are expected to work independently of the domain of the texts processed. They are classically based on machine learning techniques, but we put the emphasis on the use of similarity measures inherited from the information retrieval domain (Okapi-BM25 (Robertson et al., 1998), language modeling (Hiemstra, 1998)). Through the good results obtained for these tasks, we show that these simple settings are competitive provided that the representation and similarity chosen are well suited for the task.
The Influence of Organizational Structure on Software Quality: an Empirical Case Study

Often software systems are developed by organizations consisting of many teams of individuals working together. Brooks states in the Mythical Man Month book that product quality is strongly affected by organization structure. Unfortunately there has been little empirical evidence to date to substantiate this assertion. In this paper we present a metric scheme to quantify organizational complexity, in relation to the product development process to identify if the metrics impact failure-proneness. In our case study, the organizational metrics when applied to data from Windows Vista were statistically significant predictors of failure-proneness. The precision and recall measures for identifying failure-prone binaries, using the organizational metrics, was significantly higher than using traditional metrics like churn, complexity, coverage, dependencies, and pre-release bug measures that have been used to date to predict failure-proneness. Our results provide empirical evidence that the organizational metrics are related to, and are effective predictors of failure-proneness.
Seasonal march of Asian summer monsoon

This paper investigates the seasonal march of the summer monsoon through several different sub-divisions of the Asian monsoon region. Five data sets, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP), the upper-tropospheric water vapour band Brightness Temperature (BT), the Outgoing Longwave Radiation (OLR), the lower tropospheric wind and Korean daily rainfall for 1980–1995, are used. Analysis shows that the largest area of deep convection in the global atmosphere is located over the tropical Indian Ocean–equatorial western Pacific; its centre being positioned 110°E along the equator in boreal winter and then moves northwestward to 80°E at 5°N in late July. In late April, the area of deep convection first extends northward into the Indo-China Peninsula (ICP). In mid-May it abruptly covers over the central South China Sea (SCS) region. After the onset of SCS monsoon, deep convection starts to develop northward along the eastern coast of China, East Tibet Plateau (ETP) and Indian sub-continent, simultaneously. Based on the analysis of BT and lower-tropospheric circulation, Asian summer monsoon can be divided into six inter-linked sub-regional monsoons. They are Indo-China Peninsula monsoon, SCS monsoon, South Asian (Indian) monsoon, ETP monsoon, East Asian (south China, lower Yangtze River and Japan) monsoon and Northeast Asian (north China and Korea) monsoon. In seasonal course, their onset periods take place in late April–mid-May, mid-May, mid-May–late July, mid-May–early June, mid-May–late June and late June–mid-July, respectively. Copyright © 2000 Royal Meteorological Society
Relations between seismic signals and reservoir properties of deep gas reservoirs in Northwest-Germany -Wustrow member, Rotliegend

This study tries to find the petrophysical basis for correlations between reservoir properties and seismic signals calibrated with geological information for Wustrow-sediments of the Rotliegend in NW-Germany. A secondary objective consists in explaining the large scatter of permeability for Wustrow reservoir rocks of comparable properties. The correlations were ascertained in the DGMK-project 593-8, for instance to authigenic clay mineral types and permeability. The investigations demonstrate that the differences in seismic signals (amplitude, shape and lateral coherency of seismic traces) are a product of distinct compressional field velocities (from wireline logs) and attenuation processes as in-situ bulk densities are barely varying within the investigated horizon. The regions of different clay mineral authigenesis (illite and chlorite) diverge by their average compressional in-situ speeds. The differences suffice to provoke relevant variations in seismic signals.
A Comprehensive study on Federated Learning frameworks: Assessing

Federated Learning now a days has emerged as a promising standard for machine learning model training, which can be executed collaboratively on decentralized data sources. As the adoption of Federated Learning grows, the selection of the apt frame work for our use case has become more important. This study mainly concentrates on a comprehensive overview of three prominent Federated Learning frameworks Flower, FedN, and FedML. The performance, scalability, and utilization these frame works is assessed on the basis of an NLP use case. The study commences with an overview of Federated Learning and its significance in distributed learning scenarios. Later on, we explore into the examination of the Flower framework in-depth covering its structure, communication methods and interaction with deep learning libraries. The performance of Flower is evaluated by conducting experiments on a standard benchmark dataset. Metrics provide measurements for accuracy, speed and scalability. Tests are also conducted to assess Flower's ability to handle large-scale Federated Learning setups. The same is carried out with the other two frameworks FedN and FedML also. To gain better insight into the strengths, limitations, and suitability of Flower, FedN, and FedML for different Federated Learning scenarios, the study utilizes the above stated comparative analysis on a real time use case. The possibilities for integrating these frameworks with current machine learning workflows are discussed. Furthermore, the final results and conclusions may help researchers and practitioners to make conversant decisions regarding framework selection for their Federated Learning applications.
Precision estimate for Odin‐OSIRIS limb scatter retrievals

[1] The limb scatter measurements made by the Optical Spectrograph and Infrared Imaging System (OSIRIS) instrument on the Odin spacecraft are used to routinely produce vertically resolved trace gas and aerosol extinction profiles. Version 5 of the ozone and stratospheric aerosol extinction retrievals, which are available for download, are performed using a multiplicative algebraic reconstruction technique (MART). The MART inversion is a type of relaxation method, and as such the covariance of the retrieved state is estimated numerically, which, if done directly, is a computationally heavy task. Here we provide a methodology for the derivation of a numerical estimate of the covariance matrix for the retrieved state using the MART inversion that is sufficiently efficient to perform for each OSIRIS measurement. The resulting precision is compared with the variability in a large set of pairs of OSIRIS measurements that are close in time and space in the tropical stratosphere where the natural atmospheric variability is weak. These results are found to be highly consistent and thus provide confidence in the numerical estimate of the precision in the retrieved profiles.
The human histaminergic system in health and neuropsychiatric disorders

Ling Shan onderzocht het effect van een nieuw medicijn dat al in de kliniek wordt gebruikt als mogelijke behandeling voor de ziektes van Alzheimer en Parkinson, zonder dat er fundamentele kennis is opgedaan over het effect van het middel die kan worden verkregen na autopsie. Het onderzoek van Shan onthult cruciale informatie uit deze post-mortem-studies. Zenuwcellen in de hersenen die histamine afgeven, bevinden zich in de hypothalamus (een onderdeel van de hersenen) en hebben hun weerslag overal in het centrale zenuwstelsel. Histamine is betrokken bij een aantal functies, zoals het waakslaapritme, gedrag en leren en geheugen. Bij psychiatrische stoornissen zijn al deze functies ernstig aangetast.
Reputation Spillover from Agencies in Online Platforms: Evidence from the Entertainment Industry

Digital markets proliferated in recent years, overcoming many market inefficiencies by facilitating direct interactions between consumers and creators. Thanks to this disintermediation, consumers now have access to a vast number of alternatives, while creators can efficiently reach huge markets. However, the success of digital markets created a concomitant challenge for creators: differentiation. In crowded markets, agencies (e.g., publishing companies in books, freelance agencies in online labor markets, independent labels in music) can differentiate creators by signaling product quality. But how do agencies’ reputations affect product success for creators? Can some agencies do more harm than good? To investigate these research questions, we theorize how variation in creator and agency reputation leads to asymmetric and heterogeneous effects, including that (1) more-reputable agencies have stronger positive effects on less reputable creators than they have on more-reputable creators, while (2) less reputable agencies hurt more-reputable creators more than they hurt less reputable ones. Analyses of more than one million observations from two digital markets provide empirical support to these theory-driven arguments. The findings have design implications for markets, and contribute to our understanding of how agencies, depending on creator reputation, can either benefit or hurt product success.
Giotto's second encounter : the mission to comet P/Grigg-Skjellerup

July 10, 1992, saw the second highlight in the life of the Giotto spacecraft which was originally designed for a short 8-month lifetime, the main mission of which was to explore andphotograph comet Halley. Not only did Giotto survive the harsh environment around Halley but it was also able, after more than 7 years in orbit around the Sun, to pass within about 200 km of a second comet, P/Grigg-Skjellerup, to provide exciting scientificmeasurements about the environment close to the comet.
Variational Autoencoder with Copula for Collaborative Filtering

Variational autoencoder (VAE) has been successfully utilized for collaborative filtering (CF) models. Although effective, it still has some limitations that can be improved. For instance, there exist correlations between different features of the observation data. Accurately capturing these correlations is challenging and can significantly impact VAE-based CF models’ performance. Moreover, earlier VAE-based CF models model the families of distributions based on the mean-field theory, which greatly limits their generalizability. This paper addresses this research gap by using Gaussian copula to help the variational model preserve dependency among latent variables. Besides, to make Gaussian Copula perform well in our VAE-CF model, we design a novel reparameterization technique in the sampling process. Consequently, our approach is able to construct more complex distributions, and the resulting variational family can better approximate the posterior distributions. Finally, we empirically demonstrate the superiority of our proposed method over several state-of-the-art baselines on three real-world datasets.
A Comparison of in Situ, Reanalysis, and Satellite Water Budgets over the Upper Colorado River Basin

AbstractUsing in situ, reanalysis, and satellite-derived datasets, surface and atmospheric water budgets of the Upper Colorado River basin are analyzed. All datasets capture the seasonal cycle for each water budget component. For precipitation, all products capture the interannual variability, though reanalyses tend to overestimate in situ while satellite-derived precipitation underestimates. Most products capture the interannual variability of evapotranspiration (ET), though magnitudes differ among the products. Variability and magnitude among storage volume change products widely vary. With regards to the surface water budget, the strongest connections exist among precipitation, ET, and soil moisture, while snow water equivalent (SWE) is best correlated with runoff. Using in situ precipitation estimates, the Max Planck Institute (MPI) ET estimates, and accumulated runoff, changes in storage are calculated and compare well with estimated changes in storage calculated using SWE, reservoir, and the Climate.
Seasonal variation of gravity wave activity at 5–20 km observed with VHF radar at White Sands Missile Range, New Mexico

Wind observations at altitudes from 5 to 20 km obtained from the VHF wind profiler radar at the White Sands Missile Range (WS), New Mexico, are used to construct a climatology of gravity wave intensities over WS during the nearly 6-year period from January 1991 through September 1996. The kinetic energy densities for both high-frequency gravity waves (ground-based period of 6 min to 2 hours) and low-frequency gravity waves (period from 2 to 21 hours) are considered. These results are compared to earlier results from the middle and upper atmosphere (MU) radar in Japan. Comparisons of gravity wave variability at high and low frequency reveal both similarities and differences between the two sites. The primary differences occur at high frequency. The seasonal cycle in the high-frequency gravity waves is less pronounced and less regular at WS compared to MU. The magnitude of the high-frequency kinetic energy density is generally larger at WS compared to MU, and the relationship between the upper tropospheric jet stream winds and the high-frequency gravity wave activity is not nearly so strong at WS as at MU. The primary high-frequency gravity wave excitation mechanism at WS appears to change with season. There is evidence of a connection in winter and spring between the wind speeds in the middle troposphere and the high-frequency gravity wave activity, suggesting a topographic source for these waves. Strong summertime high-frequency variability at WS in the upper troposphere is most likely linked to waves launched by deep convection during the monsoon season in New Mexico. The results for low-frequency gravity waves are more consistent between WS and MU. Similarities appear in the kinetic energy density, the nature of the seasonal cycle, and the correlation between the kinetic energy density and the mean winds.
Performance of laser penetration through forest vegetation

One of the major advantages with laser sensors compared to passive optronic sensors, is the capability to penetrate sparse vegetation. Therefore, the most limiting performance issue is the portion of laser "shots" being absorbed by the foliage. This issue is the main focus in this paper and an analysis of the effect of forest vegetation of Nordic type is presented. The conclusions are based on laser scanner measurement as well as photos. While the analysis covers several elevation angles, the evaluation focuses on ground-to-ground measurements.