Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of total ozone and erythemal UV data from OMI with ground-based measurements at Rome station

Ground-based total ozone and surface UV irradiance measurements have been collected since 1992 using Brewer spectrophotometer at Rome station. Erythemal Dose Rates (EDRs) have been also determined by a broad-band radiometer (model YES UVB-1) operational since 2000. The methodology to retrieve the EDR and the Erythemal Daily Dose (EDD) from the radiometer observations is described. Ground-based measurements were compared with satellite-derived total ozone and UV data from the Ozone Monitoring Instrument (OMI). OMI, onboard the NASA EOS Aura spacecraft, is a nadir viewing spectrometer that provides total ozone and surface UV retrievals. The results of the validation exercise showed satisfactory agreement between OMI and Brewer total ozone data, for both OMI-TOMS and OMI-DOAS ozone algorithms (biases of −1.8% and −0.7%, respectively). Regarding UV data, OMI data overestimate ground based erythemally weighted UV irradiances retrieved from both Brewer and YES Radiometer (biases about 20%). The effect of aerosols on UV comparisons was investigated in terms of Aerosol Optical Depth (AOD), showing medium-large correlation at SZA larger than 55°. Further sources of uncertainty, such as the difference in the atmospheric conditions between local noon and OMI overpass time and the OMI spatial resolution, were also discussed.
OpenFortran : Extending Fortran with Metaprogramming

Meta-programming has shown much promise for improving the quality of software by offering programming language techniques to address issues of modularity, reusability, maintainability, and extensibility. A system that supports metaprogramming is able to generate or manipulate other programs to extend their behavior. This paper describes OpenFortran, a Meta-Object Protocol (MOP) that is able to bring the power of meta-programming to Fortran, one of the most widely used languages in the area of High Performance Computing (HPC). OpenFortran provides a framework that allows library developers to build arbitrary source-to-source program transformation libraries for Fortran programs. To relieve the burden of learning the details about how the underlying transformations are performed, a domain-specific language named SPOT has been created that allows developers to specify direct manipulation of programs. The paper provides a general motivation for using a MOP in HPC and offers details about the implementation of OpenFortran and SPOT. As an example, the paper demonstrates how to use the framework to build a simple profiling library. Keywords—Meta-programming; program transformation; Meta-Object Protocol; Domain-Specific Language;
Giga-Pixel Lensfree Holographic Microscopy and Tomography Using Color Image Sensors

We report Giga-pixel lensfree holographic microscopy and tomography using color sensor-arrays such as CMOS imagers that exhibit Bayer color filter patterns. Without physically removing these color filters coated on the sensor chip, we synthesize pixel super-resolved lensfree holograms, which are then reconstructed to achieve ∼350 nm lateral resolution, corresponding to a numerical aperture of ∼0.8, across a field-of-view of ∼20.5 mm2. This constitutes a digital image with ∼0.7 Billion effective pixels in both amplitude and phase channels (i.e., ∼1.4 Giga-pixels total). Furthermore, by changing the illumination angle (e.g., ±50°) and scanning a partially-coherent light source across two orthogonal axes, super-resolved images of the same specimen from different viewing angles are created, which are then digitally combined to synthesize tomographic images of the object. Using this dual-axis lensfree tomographic imager running on a color sensor-chip, we achieve a 3D spatial resolution of ∼0.35 µm×0.35 µm×∼2 µm, in x, y and z, respectively, creating an effective voxel size of ∼0.03 µm3 across a sample volume of ∼5 mm3, which is equivalent to >150 Billion voxels. We demonstrate the proof-of-concept of this lensfree optical tomographic microscopy platform on a color CMOS image sensor by creating tomograms of micro-particles as well as a wild-type C. elegans nematode.
Robustness to Mutations Depends on whether RNA Virus Replication Occurs Geometrically or Via a Stamping Machine

SFI Working Papers contain accounts of scientific work of the author(s) and do not necessarily represent the views of the Santa Fe Institute. We accept papers intended for publication in peer-reviewed journals or proceedings volumes, but not papers that have already appeared in print. Except for papers by our external faculty, papers must be based on work done at SFI, inspired by an invited visit to or collaboration at SFI, or funded by an SFI grant. ©NOTICE: This working paper is included by permission of the contributing author(s) as a means to ensure timely distribution of the scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the author(s). It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may be reposted only with the explicit permission of the copyright holder. www.santafe. edu
Advanced Planning for Multi-product Across a Supply Chain

This paper presents a linear integer programming model to plan the production for multiple products. The production is planned using information shared across a supply chain. The advantage of information sharing has been proved from research that it can make the whole supply chain globally visualized and yet decreasing in variability on the supply chain. The objective function of the proposed model is to minimize the total costs involved including the production costs, the distribution costs, the setup costs of manufacturing, and the fixed costs of distributing. From previous research, one more restriction which is limitation of distribution centers has been added to make the model more realistic. Numerical results verify that this model can be used to generate feasible and optimal plans for multiple products across the supply chain.
Implication of Neuromodulation Therapy by Electroacupuncture in Treatment of Diabetes

Diabetes affects approximately 366 million individuals worldwide. Current pharmacological therapy is not perfect, and often is associated with adverse side effects. Acupuncture is used as an adjunctive treatment for a number of cardiovascular diseases. Chronic activation of the sympathetic nervous system has emerged as a key player in both the pathogenesis and progression of diabetes and metabolic syndrome. Recent evidence indicates that the down regulation of central nitric oxide system leads to an increased renal sympathetic neural activity in diabetic rats. Our experimental studies have shown that electroacupuncture stimulation exerts sympathoinhibitory effects through activation of neurons in the arcuate nucleus, ventrolateral gray, and nucleus raphe to inhibit the neural activity in the rostral ventrolateral medulla. This brief review will discuss current knowledge of the effects of acupuncture on central nervous system and provide a perspective on the future of treatment of diabetes with this alternative medicine technique.
LOCAL SELF-OPTIMIZING CONTROL WITH AVERAGE LOSS MINIMIZATION

Self-optimizing control provides nearly optimal operation of process systems in the face of varying disturbances, where the inputs are adjusted to hold selected controlled variables (c) at constant setpoints. It is possible to have better self-optimizing properties by controlling linear combinations of measurements (c = Hy) than by controlling individual measurements. Previous work focused on selecting combination matrix H to minimize worst-case loss, that arises due to the use of suboptimal self-optimizing control policy. In this paper, we present a method for finding combination matrix H that minimizes average loss for local self-optimizing control. It is further shown that the combination matrix that minimizes average loss is superoptimal in the sense that it also minimizes worst-case loss simultaneously. The usefulness of the results is demonstrated using an evaporator case study.
Business process optimization using bio-inspired methods — Ants or bees intelligence?

This paper presents two bio-inspired methods addressing the problem of business process optimization. We provide a comparative approach for optimal business process flow selection and resource allocation using two of the most important bio-inspired meta-heuristics: Ant Colony Optimization and Bee Colony Optimization. Our approach does not use predefined rules for making the decisions when selecting the flow in the business process model. Given a business process, our approach starts from the business goal and reconstructs the optimal process flow by going backwards in the process in an iterative manner and solving everything that needs to be done for that goal to be completed. This reconstruction is realized by combining the bio-inspired algorithms with resource allocation strategies. The bio-inspired optimizations have been comparatively evaluated on a set of manufacturing scenarios.
Foreign activity effects and capital structure: Brazilian evidence

Este trabajo analiza si las empresas brasilenas con actividades en el extranjero (MNC) tienen una estructura de capital diferente de las que desarrollan sus actividades principalmente a nivel nacional (DC). Si es asi, ? la prediccion de la hipotesis de upstream-downstream es valida, esto es, que las empresas internacionalizadas utilizan mas deuda que las que realizan actividades locales? La muestra se compone de 131 firmas en el periodo 2004-2008. Encontramos que las empresas multinacionales brasilenas utilizan mas deuda debido a las actividades internacionales, con un aumento de 9,6%, de los cuales 5,8% proviene de fuentes a largo plazo. Nuestros resultados tambien muestran que la actividad internacional se relaciona positivamente con el uso de la deuda en moneda extranjera, y en promedio las empresas multinacionales llevan mas de 12,7% de deuda en moneda extranjera en su estructura de capital. Aunque con frecuencia se sugiere que el acceso a los mercados internacionales de capital es una motivacion para que las empresas se internacionalicen, este es el primer estudio que pone a prueba empiricamente si la actividad internacional y la financiacion de la deuda estan relacionadas
A Power Law Relay Routing Overlay

Application relays can be used to reduce end-to-end latency to provide shorter paths than IP default paths. To fit the large-scale and distributed features of Internet, the nodes can cooperate to form a latency-reducing routing overlay by acting as relays for each other in peer-to-peer paradigms. In this paper, we utilize the triangle inequality violations (TIV) in delay space to model the relays and analyze their properties to help relay selections. We find that the utility of relays approximate the power law distribution, which inspires us to propose a distributed power law relay selection algorithm, which tries to locate super candidates which has large relay utility to act as good relays. It is simulated to show its performance and efficiency.
TDOA Self-Localization based on Ambient Sound Signals

We present a localization system for mobile devices relying only on ambient sound signals from unknown positions. By evaluation of the time differences of arrival (TDOA) we can calculate both the positions of smartphones with microphones and of ambient sound signals. The localization system requires no infrastructure, except for a wireless network which is used for synchronization and the exchange of recorded time marks. In our software application we synchronize the devices and timestamp the audio stream up to an order of 0.1 ms. This results in a positioning precision in
FDR's Body Politics: The Rhetoric of Disability

Franklin Roosevelt instinctively understood that a politician of his era who was unable to control his own body would be perceived as unable to control the body politic. He therefore took great care to hide his polio-induced lameness both visually and verbally. In FDR's Body Politics. Davis W. Houck and Amos Kiewe draw on never-before-used primary sources to analyze the silences surrounding Roosevelt's disability, the words he chose to portray himself and his policies as powerful and health-giving, and the methods he used to maximize the appearance of physical strength. They examine his broad strategies, as well as the speeches Roosevelt delivered during his political comeback after polio struck, to understand how he overcame the whispering campaign against him in 1928 and 1932. Ultimately, this is a story of triumph and courage that reveals a master politician's understanding of the body politic in the most fundamental of ways.
An Approach to Match Semantic Web Services Based on Multidimension

Due to the availability of huge number of Web Sevices(WSs), calculating similarity between services is still a challenge. Usually, the similarity is measured in different dimensions, i.e. input/output parameters, QoS, correlations between preconditions and effects, etc. In this paper, we present an approach to measuring the degree of similarity between semantic web services considering multiple dimensions as a whole. It can integrate the results obtained from different matching algorithms in a generic and customizable manner. So that, the user may determine the relative importance of each dimension and obtain a single rank for candidates services matching a given service.
Design and Implementation of Expert Recommending System with Extended Object-Based Thesauri on Social Network Services

SNS (Social Network Service) characterized by Facebook and Twitter has become the next generation paradigm of obtaining data, information and knowledge on the web. The aim of this paper is to recommend relevant expert communities to users on the social network by exploiting the extended object-based thesaurus. It is basically an object- based thesaurus taking the urls of domain experts as its instances. Based on the thesaurus, the recommendation is made by inferring relationships between concepts such as "is super/sub of," "is synonym of," "association of" and "user defined. " During the inference, the concepts are matched with set of terms extracted from messages of the SNS users and directed by operators added during the semantic analysis of the messages. For example, given a message "those who have experiences about RIA web application using Eclipse," our system infers the relevant concept "Rich Ajax platform" which uses "Eclipse" among RIA web application platforms. Since the concept includes the urls of the corresponding experts resident in a social network, the experts could be recommended to the users through the social network. The inference for the recommendation is implemented as a query evaluation against the thesauri constructed with OTM (Object -based Ontology/Thesaurus Manager). To be shared and to be easily reused on SNS, the thesauri are transformed into XTM (Xml Topic Maps) by OTM after the assignment of proper expert urls to each concept in the thesaurus. For the assignment, we exploit a conventional ranking algorithm applied to each concept, which analyzes papers, reports and related news of the experts to estimate the grade of their expertise. Once the ranked name list of them is obtained together with the associated email list, they are invited to generate their urls in the experimental SNS. Our inference engine adopts its inference mechanism from object inference proposed in OSEM[1], though in a quite different context. It works on the top of Tomcat 6.0, using XTM 1.0 and jQuery 1.4. 2. Ten thousands of concepts including synonyms are constructed in the thesaurus for the inference.
Linked Data as facilitator for TEL recommender systems in research and practice

Personalisation, adaptation and recommendation are central features of TEL environments. In this context, information retrieval techniques are applied as part of TEL recommender systems to filter and deliver learning resources according to user preferences and requirements. However, the suitability and scope of possible recommendations is fundamentally dependent on the quality and quantity of available data, for instance, metadata about TEL resources as well as users. On the other hand, throughout the last years, the Linked Data (LD) movement has succeeded to provide a vast body of wellinterlinked and publicly accessible Web data. This in particular includes Linked Data of explicit or implicit educational nature. The potential of LD to facilitate TEL recommender systems research and practice is discussed in this paper. In particular, an overview of most relevant LD sources and techniques is provided, together with a discussion of their potential for the TEL domain in general and TEL recommender systems in particular based on insights from highly related European projects, mEducator and LinkedUp.
Labile evolution of display traits in bowerbirds indicates reduced effects of phylogenetic constraint

Bowerbirds (Ptilonorhynchidae) have among the most exaggerated sets of display traits known, including bowers, decorated display courts and bright plumage, that differ greatly in form and degree of elaboration among species. Mapping bower and plumage traits on an independently derived phylogeny constructed from mitochondrial cytochrome b sequences revealed large differences in display traits between closely related species and convergences in both morphological and behavioural traits. Plumage characters showed no effect of phylogenetic inertia, although bowers exhibited some constraint at the more fundamental level of design, but above which they appeared free of constraint. Bowers and plumage characters, therefore, are poor indicators of phylogenetic relationship in this group. Testing Gilliard's (1969) transferral hypothesis indicated some support for the idea that the focus of display has shifted from bird to bower in avenue–building species, but not in maypole–builders or in bowerbirds as a whole.
An Anatomical Basis for Opponent Process Mechanisms of Opiate Withdrawal

Opponent process theory predicts that the first step in the induction of drug withdrawal is the activation of reward-related circuitry. Using the acoustic startle reflex as a model of anxiety-like behavior in rats, we show the emergence of a negative affective state during withdrawal after direct infusion of morphine into the ventral tegmental area (VTA), the origin of the mesolimbic dopamine system. Potentiation of startle during withdrawal from systemic morphine exposure requires a decrease in opiate receptor stimulation in the VTA and can be relieved by administration of the dopamine receptor agonist apomorphine. Together, our results suggest that the emergence of anxiety during withdrawal from acute opiate exposure begins with activation of VTA mesolimbic dopamine circuitry, providing a mechanism for the opponent process view of withdrawal.
An Active Impulsive Noise Control Algorithm With Logarithmic Transformation

To overcome the limitations of the existing algorithms for active impulsive noise control, an algorithm based on minimizing the squared logarithmic transformation of the error signal is proposed in this correspondence. The proposed algorithm is more robust for impulsive noise control and does not need the parameter selection and thresholds estimation according to the noise characteristics. These are verified by theoretical analysis and numerical simulations.
Boosting joint models for longitudinal and time‐to‐event data

Joint models for longitudinal and time‐to‐event data have gained a lot of attention in the last few years as they are a helpful technique clinical studies where longitudinal outcomes are recorded alongside event times. Those two processes are often linked and the two outcomes should thus be modeled jointly in order to prevent the potential bias introduced by independent modeling. Commonly, joint models are estimated in likelihood‐based expectation maximization or Bayesian approaches using frameworks where variable selection is problematic and that do not immediately work for high‐dimensional data. In this paper, we propose a boosting algorithm tackling these challenges by being able to simultaneously estimate predictors for joint models and automatically select the most influential variables even in high‐dimensional data situations. We analyze the performance of the new algorithm in a simulation study and apply it to the Danish cystic fibrosis registry that collects longitudinal lung function data on patients with cystic fibrosis together with data regarding the onset of pulmonary infections. This is the first approach to combine state‐of‐the art algorithms from the field of machine‐learning with the model class of joint models, providing a fully data‐driven mechanism to select variables and predictor effects in a unified framework of boosting joint models.
Can a Flight Data Recorder be Placed in a Cloud ?

Flight Data Recorders (Black Boxes) generate data that is collected on an embedded memory device. A well-known difficulty with these devices is that the embedded memory device runs out of space. The worry of getting into this problematical situation compels the software of the flight data recorder to operate in a watchful mode it constantly makes efforts to minimize the use of memory space; otherwise a larger flight data recorder will be needed; however a larger flight data recorder can be very problematic because flight data recorders have very rigorous requirements; therefore an enlargement is very expensive and costly. In this paper it is suggested to send the data to a remote cloud, so the flight data recorder memory device will be in actual fact unbounded. Keywords— IaaS, Flight Data Recorder, Data Compression.
WaaS: Workflow-as-a-Service for the Cloud with Scheduling of Continuous and Data-Intensive Workflows

Data-intensive and long-lasting applications running in the form of workflows are being increasingly dispatched to cloud computing systems. Current scheduling approaches for graphs of dependencies fail to deliver high resource efficiency while keeping computation costs low, especially for continuous data processing workflows, where the scheduler does not perform any reasoning about the impact new input data may have in the workflow final output. To face such a challenge, we introduce a new scheduling criterion, Quality-of-Data (QoD), which describes the requirements about the data that are worthy of the triggering of tasks in workflows. Based on the QoD notion, we propose a novel service-oriented scheduler planner, for continuous data processing workflows, that is capable of enforcing QoD constraints and guide the scheduling to attain resource efficiency, overall controlled performance and task prioritization. To contrast the advantages of our scheduling model against others, we developed WaaS (Workflow-as-a-Service), a workflow coordinator system for the Cloud where data is shared among tasks via cloud columnar database.
RECEIVERS IN THE PRESENCE OF SYMBOL TIMING ERRORS

In I/Q processing receivers, matching the ampli tudes and phases of the Iand Q-branches is of major concern. In practise, matching can never be perfect in the analog front-end which results in insuff icient rejection of the image frequency band. As a consequence, the desired channel signal is interfered by up to 50-100 dB stronger image signal and some kind of imbalance compensation is needed. In this paper, the interference due to imbalancing is modelled by instantaneous linear mixing model and the compensation is carried out by a blind source separation (BSS) method. The effects of symbol timing errors on EASI algorithm based compensation structure are analyzed both analytically and through computer simulations. The obtained results indicate that timing errors degrade the performance of the proposed method. The effects of timing errors can, however, be reduced with proper selection of non-linearity in the EASI algorithm.