Miracle-dz/UniFAR-FTUs huggingface dataset:
How well do global ocean biogeochemistry models simulate dissolved iron distributions?

Numerical models of ocean biogeochemistry are relied upon to make projections about the impact of climate change on marine resources and test hypotheses regarding the drivers of past changes in climate and ecosystems. In large areas of the ocean, iron availability regulates the functioning of marine ecosystems and hence the ocean carbon cycle. Accordingly, our ability to quantify the drivers and impacts of fluctuations in ocean ecosystems and carbon cycling in space and time relies on first achieving an appropriate representation of the modern marine iron cycle in models. When the iron distributions from 13 global ocean biogeochemistry models are compared against the latest oceanic sections from the GEOTRACES program, we find that all models struggle to reproduce many aspects of the observed spatial patterns. Models that reflect the emerging evidence for multiple iron sources or subtleties of its internal cycling perform much better in capturing observed features than their simpler contemporaries, particularly in the ocean interior. We show that the substantial uncertainty in the input fluxes of iron results in a very wide range of residence times across models, which has implications for the response of ecosystems and global carbon cycling to perturbations. Given this large uncertainty, iron fertilization experiments based on any single current generation model should be interpreted with caution. Improvements to how such models represent iron scavenging and also biological cycling are needed to raise confidence in their projections of global biogeochemical change in the ocean.
Revisiting the Question of Atmospheric Predictability

This study seeks to demystify the claim that the ‘atmospheric chaos’ imposes a two-week limit on reliable weather forecasts. ‘Deterministic chaos’ indeed occurs due to the use of nonlinear numerical models for these forecasts. This ‘deterministic chaos’ does impose time limits on valid predictions, but it also facilitates, through the ensemble forecasting technique, the use of interesting statistical indicators that define regions and the duration these predictions are more or less reliable. Recently published articles show that the ‘uncertainties’ in the initial conditions are an inherent difficulty in meteorological observations and have nothing to do with the atmospheric behavior. These studies demonstrate two important aspects regarding ‘uncertainties’ in data used to initialize models. First, to achieve improvements in numerical weather forecasts, these ‘uncertainties’ must be skillfully introduced in the large scale and not in the small scale. Secondly, the numerical models must include equations or parameterizations that reproduce nature’s ways that let different scales ‘interact’, that is, the models should reproduce how the energy of different atmospheric modes ‘travels’.
The Role Of Infrastructure In Promoting Economic Growth In Iran

ack of infrastructure continues to be a key obstacle to growth and development in most of low-income countries. In recent years, however, the role of infrastructure has received increased attention. The goal of this paper is to provide an empirical evaluation of the role of infrastructure on economic growth of Iran over the period of 1985 to 2008. To do this, we have employed the autoregressive distributed lag (ARDL) framework and introduced Infrastructure capital as an input into aggregate production, because it comes at the cost of reduced investment in other types of capital. Our findings indicate that transportation facilities distinctively length of railway and roadway, also telecommunication infrastructure (fixed phone line) have positive and significant impact on economic growth of Iran but electricity production capacity doesn’t have significant impact on per capita output growth.
Information distance estimation between mixtures of multivariate Gaussians.

There are efficient software programs for extracting from image sequences certain mixtures of distributions, such as multivariate Gaussians, to represent the important features needed for accurate document retrieval from databases. This note describes a method to use information geometric methods to measure distances between distributions in mixtures of multivariate Gaussians. There is no general analytic solution for the information geodesic distance between two k-variate Gaussians, but for many purposes the absolute information distance is not essential and comparative values suffice for proximity testing. For two mixtures of multivariate Gaussians we must resort to approximations to incorporate the weightings. In practice, the relation between a reasonable approximation and a true geodesic distance is likely to be monotonic, which is adequate for many applications. Here we compare several choices for the incorporation of weightings in distance estimation and provide illustrative results from simulations of differently weighted mixtures of multivariate Gaussians.
Enhancing product architecture application in education and industrial practice

Creating good product architectures is one of the keys to designing configurable and successful products. As defined by Ulrich [1], product architecture is a scheme by which the function of a product is allocated to its physical components. Since product architecture is determined in an early phase of research and development, it is crucial to provide a solid framework that leads to both comparable and innovative results. Comparable results would require a strict set of rules, which at the same time impacts creativity and innovation, thus leading to a conflict. Our long-term goal is to improve understanding and application of product architecture in education and practice by creating a standardized framework that allows both. This paper intends to show the current stages of research towards this objective at RWTH Aachen University, and should be understood as an indicator concerning the direction of future research. It summarizes the experience we gathered by teaching product architecture and captures the problems we identified with present theory. Three lab studies with a total of 216 graduate engineering students have been carried out that clearly show the need for a standardized set of rules, since the same definition of both product architecture and tasks leads to a wide range of different results.
An Effective Carrier-Based Modulation Strategy to Reduce the Switching Losses for Indirect Matrix Converters

In this paper, an effective carrier-based modulation (CBM) strategy to reduce the switching losses for indirect matrix converters (IMCs) is presented. The discontinuous pulse width modulation method is applied to decrease the switching numbers in one carrier cycle, and an optimum offset voltage is selected to avoid commutations of the high output phase currents. By decreasing the switching numbers along with avoiding commutation of the high currents, the proposed CBM strategy significantly reduces the switching losses in IMCs. In addition, the proposed CBM strategy is independent of load conditions, such as load power and power factor, and it has good performance in terms of the input/output waveforms. Simulation and experimental results are provided to verify the effectiveness of the proposed CBM strategy.
4-Channel Single Shot and Turn-by-Turn Spectral Measurements of Bursting CSR

The test facility and synchrotron radiation source ANKA at the Karlsruhe Institute of Technology (KIT) in Karlsruhe, Germany, can be operated in a short-pulse mode. Above a threshold current, the high charge density leads to microwave instabilities and the formation of sub-structures. These timevarying sub-structures on bunches of picosecond duration lead to the observation of bursting coherent synchrotron radiation (CSR) in the terahertz (THz) frequency range. The spectral information in this range contains valuable information about the bunch length, shape and sub-structures. We present recent measurements of a spectrometer setup that consists of 4 ultra-fast THz detectors, sensitive in different frequency bands, combined with the KAPTURE readout system developed at KIT for studies requiring high data throughput. This setup allows to record continuously the spectral information on a bunch-by-bunch and turn-by-turn basis. This contribution describes the potential of timeresolved spectral measurements of the short-bunch beam dynamics.
THE ASSESSMENT OF QUALITY IN DESIGN STAGES

The importance of Quality has become more and more important as much in the industrial world as in social life. Quality is nowadays understood both as "Total Quality" and as complex property of a product, and represents an imperative to be more competitive and to guarantee an orderly development of production, and to ensure a total compliance of the expectations and of the needs of users and customers. The aim of the research is an attempt to find the right trend to follow to integrate Design Methodologies and the developed Quality Indicators within a proper "Assessment Procedure" that allow us to define the way to cover in order to improve products Quality and assure an optimal compliance with the Quality Standards in Industry.
Financial Integration in Emerging Market Economies

This paper analyzes de-facto integration in some Emerging Market Economies based on behavior of deviations from Covered Interest Parity in the last decade. An Asymmetric Self Exciting Threshold Autoregressive model is used to estimate bands of speculative inaction. The estimated bands follow the pattern expected, and reveal a rational market in the sense that deviations from parity are self correcting. The paper uses information from the estimated models to construct a new index of de-facto integration. Such a price-based measure of integration is crucial to studies of effectiveness of controls and of impact of capital openness on macroeconomic variables.
Interactive Effects of Elevated Atmospheric CO2 and Waterlogging on Vegetative Growth of Soybean (Glycine max (L.) Merr.)

Abstract Waterlogging is a major predicted agricultural problem for crop production in some areas under current climate change, but no studies are available on the interactive effects of waterlogging and elevated atmospheric CO2 concentration ([CO2]). We hypothesized that elevated [CO2] could alleviate the damage caused by waterlogging, and tested the hypothesis using vegetative growth of soybean (Glycine max) in 10 experiments (different sowing time and different soil type) conducted at Morioka and Tsukuba for three years. The 2-week-old plants grown under elevated and ambient [CO2] were exposed to waterlogging for 2 weeks. Total dry weight at the end of the treatment was higher under elevated [CO2] than under ambient [CO2], and it was significantly reduced by waterlogging under both levels of [CO2], without significant [CO2]×waterlogging interactions, at both locations. The negative effects of the waterlogging were greater in root dry weight than in top dry weight, and the root exudation per unit root dry weight was also reduced by waterlogging, without a [CO2] ×waterlogging interaction. Therefore, the hypothesis of a [CO2]×waterlogging interaction can be rejected, and provide an important basis for predicting future damage caused by waterlogging under elevated [CO2] conditions.
Visual Servoing for UAVs

Vision is in fact the richest source of information for ourself and also for outdoors Robotics, and can be considered the most complex and challenging problem in signal processing for pattern recognition. The first results using Vision in the control loop have been obtained in indoors and structured environments, in which a line or known patterns are detected and followed by a robot (Feddema & Mitchell (1989), Masutani et al. (1994)). Successful works have demonstrated that visual information can be used in tasks such as servoing and guiding, in robot manipulators and mobile robots (Conticelli et al. (1999), Mariottini et al. (2007), Kragic & Christensen (2002). ) Visual Servoing is an open issue with a long way for researching and for obtaining increasingly better and more relevant results in Robotics. It combines image processing and control techniques, in such a way that the visual information is used within the control loop. The bottleneck of Visual Servoing can be considered the fact of obtaining robust and on-line visual interpretation of the environment, which can be usefully treated by control structures and algorithms. The solutions provided in Visual Servoing are typically divided into Image Based Control Techniques and Pose Based Control Techniques, depending on the kind of information provided by the vision system that determine the kind of references that have to be sent to the control structure (Hutchinson et al. (1996), Chaumette & Hutchinson (2006) and Siciliano & Khatib (2008)). Another classical division of the Visual Servoing algorithms considers the physical disposition of the visual system, yielding to eye-in-hand systems and eye-to-hand systems, that in the case of Unmanned Aerial Vehicles (UAV) can be translated as on-board visual systems (Mejias (2006)) and ground visual systems (Martinez et al. (2009)). The challenge of Visual Servoing is to be useful in outdoors and non-structured environments. For this purpose the image processing algorithms have to provide visual information that has to be robust and works in real time. UAV can therefore be considered as a challenging testbed for visual servoing, that combines the difficulties of abrupt changes in the image sequence (i.e. vibrations), outdoors operation (non-structured environments) and 3D information changes (Mejias et al. (2006)). In this chapter we give special relevance to the fact of obtaining robust visual information for the visual servoing task. In section (2). we overview the main algorithms used for visual tracking and we discuss their robustness when they are applied to image sequences taken from the UAV. In sections (3). and (4). we analyze how vision systems can perform 3D pose estimation that can be used for
Combination of Lighthill Acoustic Analogy and Stochastic Turbulence Modelling for Far-Field Acoustic Prediction

There are many approaches in determining the sound propagated from turbulent flows. Hybrid approaches, in which the turbulent noise source field is computed or modeled separately from the far-field calculation, are frequently used. To have a more feasible approach for basic estimation of sound propagation, cheaper methods can be developed using stochastic modeling of the turbulent fluctuations (turbulent noise source field). In this paper, a simple and easy to use stochastic model for the generation of turbulent velocity fluctuations called continuous filter white noise (CFWN) model is used. This method is based on the use of classical Langevian-equation to model the details of fluctuating field superimposed on averaged computed quantities. The sound propagation due to the generated unsteady field is evaluated using Lighthill's acoustic analogy. Our results are validated by comparing the directivity and the overall sound pressure level (OSPL) magnitudes with the available experimental results. Numerical results show reasonable agreement with the experiments, both in maximum directivity and magnitude of the OSPL.
Environmental Sustainability of Alpine Livestock Farms

The 2006 FAO report concerning the environmental impact of the livestock sector has generated scientific debate, especially considering the context of global warming and the need to provide animal products to a growing world population. However, this sector differs widely in terms of environmental context, production targets, degree of intensification and cultural role. The traditional breeding systems in the Alps were largely based on the use of meadows and pastures and produced not only milk and meat but also other fundamental positive externalities and ecosystem services, such as conservation of genetic resources, water flow regulation, pollination, climate regulation, landscape maintenance, recreation and ecotourism and cultural heritage. In recent decades, the mountain livestock, mainly represented by dairy cattle, has been affected by a dramatic reduction of farms, a strong increase of animals per farm, an increase in indoor production systems, more extensive use of specialised non-indigenous cattle breeds and the increasing use of extra-farm concentrates instead of meadows and pastures for fodder. This paper firstly describes the livestock sector in the Italian Alps and analyses the most important factors affecting their sustainability. Secondly, it discusses the need to assess the ecosystem services offered by forage-based livestock systems in mountains with particular attention to greenhouse gas emission and its mitigation by carbon sequestration. In conclusion, comparison between the different elements of the environmental sustainability of mountain livestock systems must be based on a comprehensive overview of the relationships among animal husbandry, environment and socio-economic context.
An Empirical Investigation of the Relationship between Corporate Ownership Structures and their Performances (Evidence from Tehran Stock Exchange)

This study investigates the effects of ownership structure on the performance of the listed companies in the Tehran Stock Exchange (TSE). Consequently, a main hypothesis is presented, which states that there is a significant relationship between companies" ownership structures and their performances and then five sub- hypotheses are provided. For testing the hypotheses, the statistical "panel data" technique is employed. For testing each hypotheses, 4 accounting and economics performance evaluation variables models based on different ownership structures are established. The statistical population includes 66 companies in the period between 2003- 2008. Based on the research results, all hypotheses except the fourth one, were confirmed. The findings revealed a significant negative relationship between the "institutional ownership" and companies" performances; and the relationship between "corporate ownership" and companies" performance generally was significantly positive. "Management ownership", however, would affect the performance significantly and negatively. For "foreign ownership", there was no information that would indicate ownership of the foreign investors in our samples companies. With respect to the "company ownership", just in the models based on the accounting variables (i.e., ROA and ROE) coefficients are significant and negative. But in the models based on the "market variables" (i.e., Q- Tobin and MBVR) coefficients are not significant. In general, there was a significant relationship between companies" ownership structures and their performances.
Secondary school pupils’ perceptions of physics

This paper describes the analysis of data collected by Durham University’s YELLIS project, over the period of 1999 to 2004. Included in this data was the degree to which pupils in England at the end of their secondary education ‘liked’ or ‘disliked’ different subjects, and their expected examination grades in these subjects. The authors’ study focused on the perceptions of pupils in the science subjects of biology, chemistry and physics. Using the available data, they were able to analyse the perceptions of a large number of pupils (e.g. 9827 pupils in 2004) who took examinations in the separate sciences. The study found that physics was perceived as the least popular science, particularly by female pupils. We also found that the expected grade in a particular science subject correlated quite strongly (Spearman’s rho of around 0.5) with the liking of that subject. These expected grades were found to be the lowest in physics, again particularly for female pupils. The authors therefore concluded that in order to redress the gender imbalance in physics, they need to tackle this problem that physics is perceived as difficult by female pupils.
Solar radio emission as a disturbance of aeronautical radionavigation

On November 4th, 2015 secondary air traffic control radar was strongly disturbed in Sweden and some other European countries. The disturbances occurred when the radar antennas were pointing at the Sun. In this paper, we show that the disturbances coincided with the time of peaks of an exceptionally strong (∼10 5 Solar Flux Units) solar radio burst in a relatively narrow frequency range around 1 GHz. This indicates that this radio burst is the most probable space weather candidate for explaining the radar disturbances. The dynamic radio spectrum shows that the high flux densities are not due to synchrotron emission of energetic electrons, but to coherent emission processes, which produce a large variety of rapidly varying short bursts (such as pulsations, fiber bursts, and zebra patterns). The radio burst occurs outside the impulsive phase of the associated flare, about 30 min after the soft X-ray peak, and it is temporarily associated with fast evolving activity occurring in strong solar magnetic fields. While the relationship with strong magnetic fields and the coherent spectral nature of the radio burst provide hints towards the physical processes which generate such disturbances, we have so far no means to forecast them. Well-calibrated monitoring instruments of whole Sun radio fluxes covering the UHF band could at least provide a real-time identification of the origin of such disturbances, which reports in the literature show to also affect GPS signal reception.
The Evolution Conditions of Strategic Emerging Industry System

The strategic emerging industry system is a dynamic system, has openness, non-equilibrium, non stability and fluctuation. On the basis of the Prigogine, the Theory of Dissipative Structure, the paper studies the evolution conditions and operation mechanism of the strategic emerging industry system. The evolution development of system depends on the change of total entropy, ( which includes two parts, the internal entropy production dis and the external entropy flow des, namely ds=dis+des). In addition, the Brussels model of strategic emerging industry system is established on the basis of Brusselator model. Which explores the relationships of disand des each other in the system. The quantified research on the conditions of dissipative structure of strategic emerging industry system is done a study.
The dangerous path towards your own cryptography method

Would you like to have your own cryptography method? Experts say you should not do it. If you think you can develop a better cryptography method anyway. We present a brief discussion about some well known cryptography methods and how our model fails against the traditional attacks. We do not want to discourage anybody, we just want to show that, despite of the importance of developing better cryptography models, it is a very hard task.
LED Based Spectrophotometer can compete with conventional one

Spectrophotometers are the common devise used for blood analysis. These analyses are simply optioned from the transmittance of monochromatic light through a blood sample. It disperses their light sources by different techniques; the simplest one is the use of interference filters in front of broad-band light source. As Interference bandpass filters are relatively inexpensive wavelength selectors. Interference filters that allow transmission of a predetermined wavelength while rejecting or blocking other wavelengths are widely used in instrumentation for clinical chemistry. On the other hand, the lights emitting diodes (LEDs) emits a specified band and have a wide selection options. An economic device based on LEDs (LED based spectrometer) is explained in this work. Instead of the wide spectrum light source and filters (commercial spectrophotometer), The LED based spectrophotometer is calibrated with standard solutions, and its measurement results is compared with the Mindray BS-200 Chemistry Analyzer (commercial spectrophotometer). The comparison shows acceptable results between both spectrophotometers with maximum error 2.33%. The errors can be reduced by applying more fining alignment. Another benefit of the new designee is to minimize testing costs.