Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental factors structuring Arctic megabenthos—a case study from a shelf and two fjords

From photographic samples, we describe the benthic megafaunal communities in two north Svalbard fjords and on the adjacent continental shelf. We analyze the fauna in relation to abiotic factors of depth, bottom water temperature, percent cover of hard substratum, heterogeneity of stone size, and bottom-water turbidity to explore how these factors might affect the fauna and how they are related to the functional traits (size, morphology, mobility, colonial/solitary, and feeding type) of the megabenthos. Depth and bottom water temperature were consistently the strongest correlates with faunal composition and functional traits of the constituent species. A greater proportion of the variability in the functional traits of the megabenthos could be explained by abiotic factors rather than faunal composition, indicating that the abiotic factors of depth and temperature were strongly related to the functional traits of the megabenthos. On a local scale, stone size heterogeneity explained most variation in the functional traits of the megabenthos in one fjord. The results of this case study show a significant relationship between bottom water temperature and the functioning of north Svalbard megabenthic communities. Warming temperatures in the Arctic will likely decrease the variety of functional traits represented in Svalbard megabentos, resulting in scavenger-dominated communities. A reduction in megabenthic biomass may also result, reducing energy availability to higher trophic levels.
Human tracking in thermal catadioptric omnidirectional vision

We propose to explore a novel tracking system for human tracking in thermal catadioptric omnidirectional (TCO) vision, which is able to realize the surveillance in all-weather and wide field of view conditions. In contrast, previous human tracking system mainly focuses on tracking in conventional imaging system. In this paper, the proposed tracking method adopts the classification posterior probability of Support Vector Machine (SVM) to relate the observation likelihood of particle filter for efficient tracking. However, previous works only employ the final output label of SVM for classification. Due to no existing TCO vision dataset available in public, we establish a dataset including TCO videos and extracted human samples to train the classifier and test the proposed tracking method. Moreover, we adjust tracking window distribution of particle filter to fit the characteristic of catadioptric omnidirectional vision which is the size of target in omni-image depends on the distance between target image and the center of catadioptric omnidirectional image. Finally, the experimental results show that our proposed tracking method has a stable and good performance in TCO vision tracking system.
Effects of the U.S. quantitative easing on the Peruvian economy

Emerging economies were largely affected because of FED's quantitative easing (QE) policies. This paper assesses the impact of these measures in terms of key macroeconomic variables for a small open economy (SOE) such as Peru. We identify QE policy shocks in a SVAR with Block Exogeneity (Zha, 1999) and we impose a mixture of zero and sign restrictions (Arias et al., 2014). In addition, following Pesaran and Smith (2014), we implement a counterfactual exercise in order to gauge the differences between two scenarios: with and without QE policies. Overall, we find that QE policies had significant effects over financial variables such as aggregate credit and the exchange rate. On the other hand, we find small but significant effects over inflation and output in the medium run.
VERTICAL ARRANGEMENTS AND THE RULE OF REASON

This is not a radical proposal. Most of these practices, which I lump under the term "restricted dealing," are in common use. All of them except the prescription of prices and tying are dealt with under a highly deferential standard of review and are lawful except in the rarest of cases. The treatment of prices and tying is an anomaly that should be brought in line with the treatment of vertical integration and other restrictions on distribution.
Cognitively Inspired and Perceptually Salient Graphic Displays for Efficient Spatial Inference Making

Developing a visual hierarchy in map displays that is congruent with thematic levels of relevance is a fundamental cartographic design task. Cartographers employ a set of visual variables (e.g., size, color hue, color value, orientation, etc.) for 2-D, static maps to systematically match levels of thematically relevant information to a perceptual hierarchy based on figure–ground relationships. In this article, we empirically investigate the relationship of thematic relevance and perceptual salience in static weather map displays. We are particularly interested in how novices' viewing patterns are modified when thematically relevant items are made perceptually more salient through design. In essence, we are asking whether perceptually salient elements draw novice viewers' attention to thematically relevant information, whether or not users have domain knowledge. In a factorial experiment, we ask novice participants to evaluate the wind direction in weather maps before and after training all participants on meteorological principles. Our empirical results suggest that display design (i.e., saliency) does not influence the accuracy of response, whether participants have prior knowledge or not (i.e., training). Analysis of the eye-movement patterns, however, suggests that display design does affect viewing behavior and response time. These findings provide rare empirical evidence for generally accepted design practices within the cartographic community (e.g., the effects of visual variables). We chose weather map displays as one typical example of commonly used maps for our study, but the methods employed are generic enough to be applicable to any spatial display (static or interactive) that might be produced by GIScientists, cartographers, geographic information system (GIS) practitioners, and others.
The relevance of aerosol optical depth to cumulus fraction changes: a five-year climatology at the ACRF SGP site

The objective of this study is to investigate, by observational means, the magnitude and sign of the actively discussed relationship between cloud fraction N and aerosol optical depth ? a. Collocated and coincident ground-based measurements and Terra/Aqua satellite observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site form the basis of this study. The N? a relationship occurred in a specific 5-year dataset of fair-weather cumulus (FWC) clouds and mostly non-absorbing aerosols. To reduce possible contamination of the aerosols on the cloud properties estimation (and vice versa), we use independent datasets of ? a and N obtained from the Multi-filter Rotating Shadowband Radiometer (MFRSR) measurements and from the ARM Active Remotely Sensed Clouds Locations (ARSCL) value-added product, respectively. Optical depth of the FWC clouds ? cld and effective radius of cloud droplets re are obtained from the MODerate resolution Imaging Spectroradiometer (MODIS) data. We found that relationships between cloud properties (N,? cld, re) and aerosol optical depth are time-dependent (morning versus afternoon). Observed time-dependent changes of cloud properties, associated with aerosol loading, control the variability of surface radiative fluxes. In comparison with pristine clouds, the polluted clouds are more transparent in the afternoon due to smaller cloud fraction, smaller optical depth and larger droplets. As a result, the corresponding correlation between the surface radiative flux and ? a is positive (warming effect of aerosol). Also we found that relationship between cloud fraction and aerosol optical depth is cloud size dependent. The cloud fraction of large clouds (larger than 1 km) is relatively insensitive to the aerosol amount. In contrast, cloud fraction of small clouds (smaller than 1 km) is strongly positively correlated with ? a. This suggests that an ensemble of polluted clouds tends to be composed of smaller clouds than a similar one in a pristine environment. One should be aware of these time- and size-dependent features when qualitatively comparing N? a relationships obtained from the satellite observations, surface measurements, and model simulations.
Testing an Adoption Model for E-Government Services Using Structure Equation Modeling

The prevalent issue in the adoption of e-Government services may be in the social behavior of the user themselves, particularly in a developing country. The problem is finding the factors impacting on the users adoption to new technologies. The purpose of this research is to investigate citizen perceptions of e-government adoption in Iran by utilizing the Technology Acceptance Model (TAM) theory and other related models focusing on Intention to Use. The proposed model considered Trustworthiness as an exogenous variable. A causal adoption model was derived from direct and indirect antecedents of e-government intention to use. Questionnaires were then designed and distributed to fifteen public organizations in Esfahan, Iran. The proposed model relationships were tested using the Structured Equation Modeling (SEM) approach. The SEM results indicated that e-Government services is perceived as acceptable and is more likely to contribute towards e-government adoption. Besides, trustworthiness, perceived usefulness, perceived ease of use along with compatibility and social influence intention provide evidence that e-Government services are more likely to motivate the citizens to use the services. The overall goodness-of-fit indicates that the developed SEM model has respectable outcomes. In addition, from implementers' point of view, the results of this research prove imperative as an indicator for the government of Iran to successfully implement and manage its e-Government services.
Reconfigurable Solar Converter for PV battery application

A photovoltaic system is an arrangement of components designed to supply usable electric power using the sun as the power source. PV systems have many advantages like it provide clean energy, it can be made available almost anywhere there is sunlight, the operating and maintenance costs for PV panels are considered to be low. The conventionally used converters in solar systems have many disadvantages such as multiple conversion stages, complex control, less efficient, high cost, bulky, etc. A new converter, for photovoltaic battery applications, called Reconfigurable Solar Converter (RSC), uses only single-stage three phase grid-tie solar PV converter to perform dc/ac and dc/dc operations, overcomes the drawback of conventional converters. The RSC concept is based on energy storage integration for utility-scale solar PV systems and it provides a minimal overlap between the PV energy storage and energy release time. In this paper a RSC which uses minimum number of conversion stages which in turn improves the efficiency and reduces the cost, weight and volume has been realized.
An in Tegr a Ted F R a Mew or K F or Ra Pid S Ystem Prototypin G an D Au Toma Tic C Ode Distribu Tion

Rapid prototyping of parallel systems is of interest to quickly produce a parallel prototype. The emergence of distributed systems technology has enabled to develop software system distributed over large networks. Rapid prototyping must deal with real parallelism over a set of processors, either closely or loosely coupled We describe in this paper an extension of the CPN/TAGADA project to manage distributed code generation over a set of CPU. To achieve a mapping of components over the target architecture, both hardware and software have to be described. We expose our technique and apply it to a multi producer and consumer example that is studied for several communication strategies. Key-words : Rapid prototyping, Parallel systems, Distribution, Hardware description.
Site-specific labeling of RNA by combining genetic alphabet expansion transcription and copper-free click chemistry

Site-specific labeling of long-chain RNAs with desired molecular probes is an imperative technique to facilitate studies of functional RNA molecules. By genetic alphabet expansion using an artificial third base pair, called an unnatural base pair, we present a post-transcriptional modification method for RNA transcripts containing an incorporated azide-linked unnatural base at specific positions, using a copper-free click reaction. The unnatural base pair between 7-(2-thienyl)imidazo[4,5-b]pyridine (Ds) and pyrrole-2-carbaldehyde (Pa) functions in transcription. Thus, we chemically synthesized a triphosphate substrate of 4-(4-azidopentyl)-pyrrole-2-carbaldehyde (N3-PaTP), which can be site-specifically introduced into RNA, opposite Ds in templates by T7 transcription. The N3-Pa incorporated in the transcripts was modified with dibenzocyclooctyne (DIBO) derivatives. We demonstrated the transcription of 17-, 76- and 260-mer RNA molecules and their site-specific labeling with Alexa 488, Alexa 594 and biotin. This method will be useful for preparing RNA molecules labeled with any functional groups of interest, toward in vivo experiments.
Purification of requirement engineering model for rapid application development

Due to shortage of time, most of the software organizations are shifting their projects to rapid application development's life cycle. But main problem is that rate of projects failure is increasing day by day. According to Standish group report, success rate of projects is only 16.2%. The main reason of project's failure is poor requirement engineering. The main objective of carried research is to purpose a model for requirement engineering process of rapid application development. The proposed model has 7 steps. Our proposed model specifies techniques for each step of requirement engineering process. Our proposed model also introduces new stages of conflict management by win-win approach and requirement prioritization by card sorting in requirement engineering model for rapid application development's life cycle. Validation of purposed model has been done by survey from 50 experienced software professionals of 20 different organizations. Survey proved that our purposed model has more customer's favor then traditional requirement engineering model for rapid application development. Our proposed model is fully customer's oriented. It is more time effective, cost effective, well managed and efficient than traditional model.
Rotation invariants of two dimensional curves based on iterated integrals

We introduce a novel class of rotation invariants of two dimensional curves based on iterated integrals. The invariants we present are in some sense complete and we describe an algorithm to calculate them, giving explicit computations up to order six. We present an application to online (stroke-trajectory based) character recognition. This seems to be the first time in the literature that the use of iterated integrals of a curve is proposed for (invariant) feature extraction in machine learning applications.
MASOOD SHAIKH : A COMPARATIVE STUDY OF COLOR EDGE DETECTION TECHNIQUES

Edge detection has attracted the attention of many researchers and is one of the most important areas in low level computer vision. In recent years, the focus of edge detection has shifted from grayscale single component images to multicomponent color images that utilize the inter-spectral correlation of the neighboring color samples to eliminate color artifacts and increase the accuracy of edge detection process. This project presents the study of color edge detection based on vector order statistics operators. Variations are introduced in the vector order statistics color edge operator to improve noise performance and we demonstrate their ability to attenuate noise with added algorithm complexity. We present a performance evaluation framework to assess the quality of color edge detectors and compare it with the Canny edge detector which is the optimal edge detector used for grayscale images. The edge detectors are evaluated with subjective and objective tests using statistical indices by comparing it with human ground truth images extracted from the BSDS300 dataset.
Numerical resolution of the C-root model using Discontinuous Galerkin methods on unstructured meshes: Application to the simulation of root system growth

Modeling and simulating root growth is still a challenging topic to understand plant growth. Among the various modeling approaches, C-Root is a density based model that follows the evolution in time and space of the root density in a given soil volume, in accordance with the ecophysiological phases of the root system development. The unknown variable, which is solution of an advection-reaction-diffusion equation, is the root density. This model is generic enough to adapt to different root system types by calibration. In this work we solved the model on unstructured meshes using the Discontinuous Galerkin (DG) method. The DG method applied to root growth is briefly presented and the code is validated in the case of a plagiotropic root of Eucalyptus.
An Adaptive Rule Based on Unknown Pattern for Improving K-Nearest Neighbor Classifier

One of popular and simple pattern classification algorithms is the k-nearest neighbor rule. However, it often fails to work well when patterns of different classes overlap in some regions in the feature space. To overcome this problem, many researches strive for developing various adaptive or discriminatory metrics to improve its performance for classification, recently. In this paper, we proposed a simple adaptive nearest neighbor rule on distance measure for two objects. First one is to separate the overlapping data, and the second one is to avoid the influence of outliers. From the experimental results, our method is robust for the choice of the number of k and outperforms than k-nearest neighbor classifier.
Designing a strategy Map in order to Facilitate strategy implementation

The strategy map is a visual presentation of a company’s critical success factors and the cause-and-effect relations between them. Strategy maps can be used, e.g., to illustrate the strategy of a company. Especially, the duty-related strategy maps can illustrate how the duties of an employee relate to the objectives of an organisation. The objective of this paper is to model the designing of a strategy map. Also, the question whether strategy maps can be used in decreasing the gap between strategy formulation and strategy implementation is discussed in the paper. The research can be characterised as a qualitative and normative action research. The empirical part of the research consists of one case in which the strategy maps were designed for supporting the implementation of the new goal setting. The contribution this paper makes is as follows. First, the paper presents a step-by-step model of designing a strategy map. Second, this paper presents how to design a duty-related strategy map. Third, the process of designing strategy maps is described in practice.
Computing with activities III: chunking and aspect integration of complex situations by a new kind of kohonen map with whu-structures

In this paper we present a new theory and give first examples of a new kind of network structure, which shows oscillatory behaviour and codes the aspects of complex situations more exactly than it can be expected by a common neural net. It will be shown, that by introducing lateral `wide hook up¿-structure (resp. whu-structures) on SOMs, an aspect integration can be done which generates very filigree classification and/or action strategies and makes it possible to supervise time trajectories. In addition these structures enable to integrate several aspects of a scene into a mega-concept corresponding to the Chunking process of the brain. The categorization of concepts will hereby be done by active whu-structures which become dominant since they sum up the activities of the involved neurons instead of considering one and only one high-active winner neuron.
Harnessing the immune system's arsenal: producing human monoclonal antibodies for therapeutics and investigating immune responses

Monoclonal antibody technology has undergone rapid and innovative reinvention over the last 30 years. Application of these technologies to human samples revealed valuable therapeutic and experimental insights. These technologies, each with their own benefits and flaws, have proven indispensable for immunological research and in our fight to provide new treatments and improved vaccines for infectious disease.
Performance of Multiplex Cytokine Assays in Serum and Saliva among Community-Dwelling Postmenopausal Women

Multiplexing arrays increase the throughput and decrease sample requirements for studies employing multiple biomarkers. The goal of this project was to examine the performance of Multiplex arrays for measuring multiple protein biomarkers in saliva and serum. Specimens from the OsteoPerio ancillary study of the Women’s Health Initiative Observational Study were used. Participants required the presence of at least 6 teeth and were excluded based on active cancer and certain bone issues but were not selected on any specific condition. Quality control (QC) samples were created from pooled serum and saliva. Twenty protein markers were measured on five multiplexing array panels. Sample pretreatment conditions were optimized for each panel. Recovery, lower limit of quantification (LLOQ) and imprecision were determined for each analyte. Statistical adjustment at the plate level was used to reduce imprecision estimates and increase the number of usable observations. Sample pre-treatment improved recovery estimates for many analytes. The LLOQ for each analyte agreed with manufacturer specifications except for MMP-1 and MMP-2 which were significantly higher than reported. Following batch adjustment, 17 of 20 biomarkers in serum and 9 of 20 biomarkers in saliva demonstrated acceptable precision, defined as <20% coefficient of variation (<25% at LLOQ). The percentage of cohort samples having levels within the reportable range for each analyte varied from 10% to 100%. The ratio of levels in saliva to serum varied from 1∶100 to 28∶1. Correlations between saliva and serum were of moderate positive magnitude and significant for CRP, MMP-2, insulin, adiponectin, GM-CSF and IL-5. Multiplex arrays exhibit high levels of analytical imprecision, particularly at the batch level. Careful sample pre-treatment can enhance recovery and reduce imprecision. Following statistical adjustments to reduce batch effects, we identified biomarkers that are of acceptable quality in serum and to a lesser degree in saliva using Multiplex arrays.