Miracle-dz/UniFAR-FTUs huggingface dataset:
Coordinated cell-shape changes control epithelial movement in zebrafish and Drosophila

Epithelial morphogenesis depends on coordinated changes in cell shape, a process that is still poorly understood. During zebrafish epiboly and Drosophila dorsal closure, cell-shape changes at the epithelial margin are of critical importance. Here evidence is provided for a conserved mechanism of local actin and myosin 2 recruitment during theses events. It was found that during epiboly of the zebrafish embryo, the movement of the outer epithelium (enveloping layer) over the yolk cell surface involves the constriction of marginal cells. This process depends on the recruitment of actin and myosin 2 within the yolk cytoplasm along the margin of the enveloping layer. Actin and myosin 2 recruitment within the yolk cytoplasm requires the Ste20-like kinase Msn1, an orthologue of Drosophila Misshapen. Similarly, in Drosophila, actin and myosin 2 localization and cell constriction at the margin of the epidermis mediate dorsal closure and are controlled by Misshapen. Thus, this study has characterized a conserved mechanism underlying coordinated cell-shape changes during epithelial morphogenesis.
Tax holidays and tax noncompliance : an empirical study of corporate tax audits in China's developing economy

Many developing economies use tax holidays to attract foreign investment by providing a limited period of tax exemptions and reductions for qualified investors. This paper investigates the effect of tax holidays on foreign investors' tax noncompliance behavior in China's developing economy. We measure noncompliance in terms of tax audit adjustments the Chinese tax authorities require in response to avoidance and evasion. The results indicate that a company's tax‐holiday position affects noncompliance. Companies are least compliant before entering a tax holiday, and most compliant while in a tax‐exemption period. In addition, domestic market‐oriented companies, service‐oriented companies, and joint ventures are less compliant than export‐oriented companies, manufacturing‐oriented companies, and wholly foreign‐owned enterprises, respectively. Our evidence is relevant to policymakers designing tax incentives to attract foreign investors. Our evidence on noncompliance should also help tax authorities and fiel.
Non-isolated Bidirectional Soft-Switching Current-Fed LCL Resonant DC/DC Converter to Interface Energy Storage in DC Microgrid

This paper proposes a current-fed non-isolated soft-switching bidirectional dc/dc converter for interfacing energy storage to dc microgrid. The proposed converter employs a current-fed half-bridge boost converter at front-end followed by an LCL resonant circuit to aid in soft-switching of semiconductor devices. A voltage doubler at output is selected to enhance the gain by 2×. The LCL resonant circuit also adds a suitable voltage gain. Therefore, the topology offers overall high voltage gain without transformer or large number of multiplier circuits. For buck operation, high side voltage is first divided by half with capacitor divider to gain higher stepdown ratio. Converter operates at high switching frequency to realize merits of reduced magnetics and filters. Zero voltage turn-on is achieved for all switches and zero current turn-on and turn-off is achieved for all diodes for both buck/boost operation. Voltage across switches and diode is clamped naturally without any external snubber circuit. Detailed analysis and design have been proposed. A proof-of-concept experimental prototype rated at 350 W has been designed, developed, and tested in the laboratory to demonstrate the performance and validate the claims of the converter for wide load variation.
Value name conflict while integrating data indatabase integration

Integration of data is performed to provide user a unified view of heterogeneous data sources residing on different places. Major challenge in data integration process is; first identify and then resolve the data level conflicts. Ignoring identification and resolution of these conflicts produces inconsistent and erroneous data. In this paper we identify and resolve a new data level conflict. Data in different data sources may have similar semantics with different values. This difference in data may create inconsistent results when queried. Value of one concept may be present with different name in two different databases. These types of conflict need to be resolved for consistent and error free data. We named this conflict as Value Name Conflict. We provide the formal definition of this conflict using Z-Notation. Formal resolution function of this conflict is also presented.
Discovering Influential Nodes in Social Networks through Community Finding

Finding influential nodes in a social network has many practical applications in such areas as marketing, politics and even disease control. Proposed methods often take greedy approaches to find the best k nodes to activate so that the diffusion of activation will spread to the largest number of nodes. In this paper, we study the effects of using a community finding approach to not only maximize the number of activated nodes but to also spread the activation to more segments of the network. After describing our approach we present experiments that explain the effects of this approach.
Tasseled Tap Transformation and Neural Networks for the Design of an Optimum Image Classification Algorithm using Multispectral Data

The paper aims at improving image automatic classification from remote sensing data using neural network algorithms (NN). NN have been found to have good generalization properties and their use is becoming increasingly prevalent in the field of remote sensing and in particular for image classification. However, the type of input to be considered for the algorithm in order to maximize the information available from the measurement is still an open issue. Using the mere spectral signature with no pre-processing is not an effective choice. Another point regards the use of textural features to improve the classification which involves taking decisions on how many and what specific features should be considered. More in general, minimizing the number of inputs of a neural network algorithm, avoiding significant loss of information, affects positively the NN mapping ability and computational efficiency. In this paper we propose a new methodology facing with the aforementioned problems and providing a solution to them.
DESIGN OF THE MERCURY HANDLING SYSTEM FOR A MUON COLLIDER/NEUTRINO FACTORY TARGET ∗

The baseline target concept for a Muon Collider or Neutrino Factory is a free mercury jet within a 20-T magnetic field being impacted by an 8-GeV proton beam. A pool of mercury serves as a receiving reservoir for the mercury and a dump for the unexpended proton beam. Modifications to this baseline are discussed in which the field at the target is reduced from 20 to 15 T, and in which the magnetic field drops from its peak value down to 1.5 T over 7 rather than 15 m.
GDF - A general dataformat for BIOSIGNALS

Biomedical signals are stored in many different data formats. Most formats have been developed for a specific purpose of a specialized community for ECG research, EEG analysis, sleep research, etc. So far none of the existing formats can be considered a general purpose data format for biomedical signals. In order to solve this problem and to unify the various needs of the various biomedical signal processing fields, the so-called "General Data Format for biomedical signals" (GDF) is developed. This GDF format is fully described and specified. Software for reading and writing GDF data is implemented in Octave/Matlab and C/C++ and provided through BioSig - an free and open source software library for biomedical signal processing. BioSig privides also converters from various data formats to GDF, and a viewing and scoring software.
Applications of Binary Classification and Adaptive Boosting to the Query-By-Humming Problem

In the query-by-humming problem, we attempt to retrieve a speci c song from a target set based on a sung query. Recent evaluations of query-by-humming systems show that the state-of-the-art algorithm is a simple dynamic programming-based interval matching technique. Other techniques based on hidden Markov models are far more expensive computationally and do not appear to offer signi cant increases in performance. Here, we borrow techniques from arti cial intelligence to create an algorithm able to outperform the current state-of-the-art with only a negligible increase in running time.
Gaze-based selection of standard-size menu items

With recent advances in eye tracking technology, eye gaze gradually gains acceptance as a pointing modality. Its relatively low accuracy, however, determines the need to use enlarged controls in eye-based interfaces rendering their design rather peculiar. Another factor impairing pointing performance is deficient robustness of an eye tracker's calibration. To facilitate pointing at standard-size menus, we developed a technique that uses dynamic target expansion for on-line correction of the eye tracker's calibration. Correction is based on the relative change in the gaze point location upon the expansion. A user study suggests that the technique affords a dramatic six-fold improvement in selection accuracy. This is traded off against a much smaller reduction in performance speed (39%). The technique is thus believed to contribute to development of universal-access solutions supporting navigation through standard menus by eye gaze alone.
The Future Orientation of Past Memory: The Role of BA 10 in Prospective and Retrospective Retrieval Modes

Klein made the provocative suggestion that the purpose of human episodic memory is to enable individuals to plan and prepare for the future. In other words, although episodic (retrospective) memory is about the past, it is not actually for the past; it is for the future. Within this focus, a natural subject for investigation is prospective memory, or memory to do things in the future. An important theoretical construct in the fields of both retrospective memory and prospective memory is that of a retrieval mode, or a neurocognitive set or readiness to treat environmental stimuli as potential retrieval cues. This construct was originally introduced in a theory of episodic (retrospective) memory and has more recently been invoked in a theory of how some prospective memory tasks are accomplished. To our knowledge, this construct has not been explicitly compared between the two literatures, and thus this is the purpose of the present article. Although we address the behavioral evidence for each construct, our primary goal is to assess the extent to which each retrieval mode appears to rely on a common neural region. Our review highlights the fact that a particular area of prefrontal cortex (BA 10) appears to play an important role in both retrospective and prospective retrieval modes. We suggest, based on this evidence and these ideas, that prospective memory research could profit from more active exploration of the relevance of theoretical constructs from the retrospective memory literature.
Motion control of thruster-driven underwater vehicle based on Model Predictive Control

Underwater vehicles have been developed over the last six decades for potential uses in scientific, commercial, environmental, and military purposes, and always utilized to perform difficult tasks in cluttered environments such as deep-sea mining, underwater sampling and oceanic investigations. Since underwater vehicles have nonlinear and highly coupled dynamics, motion control can be difficult when completing complex tasks. This paper describes the implementation of a model predictive controller novel in a class of thruster-driven underwater vehicle. In this paper, a constrained discrete-time model predictive control method is employed for the motion control of thruster-driven underwater vehicles. A nonlinear model in six degree of freedom is established based on the dynamics of human occupied vehicle Jiao-long, and converted into a state space model after practical simplification. To ensure the performance of model predictive controller, a full feedback state observer is established to observe the state. In addition, Hildreth's quadratic programming algorithm is incorporated for solving the optimal control sequence, which greatly reduced the computation of the model predictive control algorithm. In order to show the effectiveness of the motion control method, simulations based on dynamics of human occupied vehicle Jiao-long are conducted. Performance on depth control, heading control and hovering control are evaluated. All the results demonstrate the effectiveness of the method.
A case study in geometric algebra : Fitting roommodels to 3 D point clouds

Many geometrical problems exist which have been researched thoroughly, but always using classical methods such as linear algebra as a framework for the problem. As linear algebra is an algebra based on coordinates and numbers as basic elements of computation, this leads to longwinded and non-universal code. Geometric algebra is an alternative formalism in which geometric objects are the basic elements of computation. Using this formalism to represent geometrical problems can often yield more readable and more compact code. In this paper we present a case study of such a problem – specifically fitting room models to 3D point clouds – and the advantages geometric algebra has over classical methods in solving this problem.
A real-time MHE and NMPC scheme for wind turbine control

Model Predictive Control (MPC) is a strong candidate for the control of large Multi-Mega Watt Wind Turbine Generators (WTG). Several MPC and some Nonlinear MPC schemes have been proposed in the literature, formulating the problem of balancing the power generation against the structural and actuator fatigue through a reference-tracking scheme. While the resulting schemes offer very promising results in term of load reduction, especially when reliable LIDAR systems are available, no NMPC scheme fast enough to achieve a real-time implementation has yet been proposed. This paper presents such a real-time NMPC scheme. Moreover, the proposed scheme uses directly the power generation as a cost function, as opposed to tracking the optimal wind-dependent WTG steady-state.
A Fast Image Copy-Move Forgery Detection Method Using Phase Correlation

Copy-move is a common used forgeries in digital image tampering. In this paper, a non block-matching based fast method to detect image copy-move forgery is proposed exploiting phase correlation. Results of experiments indicate that the proposed method is valid in detecting the image region duplication and quite robust to additive noise and blurring.
Do Party Manifestos Matter in Policy-Making? Capacities, Incentives and Outcomes of Electoral Programmes in France

A key factor in modern democracies’ legitimisation is the extent to which policies submitted for public approval before an election translate into material outcomes once a political party has won power. Current research finds no clear empirical evidence for partisanship in policy-making nor has any unified theory been offered or tested systematically. This article addresses that gap by offering a conditional approach to policy-making undertaken by parties in government. It suggests that partisan influence on policy depends on both office-holders’ capacity for implementing policies evoked during their electoral campaigns and on governing parties’ incentives to implement electoral promises. Data from French Agendas Project datasets is used to compare the contents of governing parties’ pre-election manifestos with legislation passed in France between 1981 and 2012. Panel negative binomial regressions on electoral and legislative agendas support the expected outcome, namely that issues featuring in governing parties’ electoral manifesto have had an impact on their subsequent legislative agendas, with the effect depending on both partisan capacities and incentives. Party programmes do matter in policy-making, albeit only under certain conditions.
Relationship and Network Approach to Innovation and Capabilities Building in Small and Medium-Sized UK Organic Food and Drink Suppliers: A Literature Review

Both business and consumer markets of food and drink are increasingly changing, concomitant with changing consumer habits and lifestyles. Particularly in industrialised countries, there has been a tremendous growth in consumer interest for organic food in the last fifteen years, largely driven by the need for healthy food. These market changes have implications for the way firms in the food and drink industry conduct their business. Nevertheless, unlike large firms, small suppliers tend to be constrained in terms of innovations and capabilities, for instance to enable them keep pace with market changes. Based on the literature review, this paper develops a framework that suggests that market-driven innovations may be developed and implemented through augmentation of small and medium-sized suppliers’ (SMEs) own capabilities with those of their larger customers. This consequently would enable SMEs to keep pace with market changes and hence sustain their survival.
Phloem sap and leaf δ13C, carbohydrates, and amino acid concentrations in Eucalyptus globulus change systematically according to flooding and water deficit treatment

Phloem is a central conduit for the distribution of photoassimilate, nutrients, and signals among plant organs. A revised technique was used to collect phloem sap from small woody plants in order to assess changes in composition induced by water deficit and flooding. Bled phloem sap δ13C and sugar concentrations were compared to δ13C of bulk material, soluble carbon extracts, and the neutral sugar fraction from leaves. Amino acid composition and inorganic ions of the phloem sap was also analysed. Quantitative, systematic changes were detected in phloem sap composition and δ13C in response to altered water availability. Phloem sap δ13C was more sensitive to changes of water availability than the δ13C of bulk leaf, the soluble carbon fraction, and the neutral soluble fraction of leaves. Changes in water availability also resulted in significant changes in phloem sugar (sucrose and raffinose), inorganic nutrient (potassium), and amino acid (phenylalanine) concentrations with important implications for the maintenance of phloem function and biomass partitioning. The differences in carbohydrate and amino acid composition as well as the δ13C in the phloem, along with a new model system for phloem research, offer an improved understanding of the phloem-mediated signal, nutrient, and photoassimilate transduction in relation to water availability.
A valency dictionary architecture for Machine Translation

This research is aimed at developing a valency dictionary architecture to comprehensively list the full range of alternations associated with a given predicate sense, both eﬃciently and robustly. The architecture is designed to incorporate all information available in current on-line resources, as well as additional features such as argument status, grammatical relations, and an augmented case-role representation. Words are divided into senses, which are distinguished on semantic grounds, depending on the core lexical meaning of the verb. Each sense may have one or more alternations, thus keeping the number of senses manageable, while allowing for systematic variation in the lexical realization. Individual syntactic case frames are indexed back to the basic semantic argument component of the given predicate sense.
Echo State Networks in Audio Processing

In this article echo state networks, a special form of recurrent neural networks, are discussed in the area of nonlinear audio signal processing. Echo state networks are a novel approach in recurrent neural networks with a very easy (linear) training algorithm. Signal processing examples in nonlinear system identification (valve distortion, clipping), inverse modeling (quality enhancement) and audio prediction are briefly presented and discussed.
Patterns of introduction and adaptation during the invasion of Aegilops triuncialis (Poaceae) into Californian serpentine soils

Multiple introductions can play a prominent role in explaining the success of biological invasions. One often cited mechanism is that multiple introductions of invasive species prevent genetic bottlenecks by parallel introductions of several distinct genotypes that, in turn, provide heritable variation necessary for local adaptation. Here, we show that the invasion of Aegilops triuncialis into California, USA, involved multiple introductions that may have facilitated invasion into serpentine habitats. Using microsatellite markers, we compared the polymorphism and genetic structure of populations of Ae. triuncialis invading serpentine soils in California to that of accessions from its native range. In a glasshouse study, we also compared phenotypic variation in phenological and fitness traits between invasive and native populations grown on loam soil and under serpentine edaphic conditions. Molecular analysis of invasive populations revealed that Californian populations cluster into three independent introductions (i.e. invasive lineages). Our glasshouse common garden experiment found that all Californian populations exhibited higher fitness under serpentine conditions. However, the three invasive lineages appear to represent independent pathways of adaptation to serpentine soil. Our results suggest that the rapid invasion of serpentine habitats in California may have been facilitated by the existence of colonizing Eurasian genotypes pre‐adapted to serpentine soils.
Uniprocessor scheduling under precedence constraints for embedded systems design

In this paper, we present a novel approach to the constrained scheduling problem, while addressing a more general class of constraints that arise from the timing requirements on real-time embedded controllers. We provide general necessary and sufficient conditions for scheduling under precedence constraints and derive sufficient conditions for two well-known scheduling policies. We define mathematical problems that provide optimum priority and deadline assignments, while ensuring both precedence constraints and system's schedulability. We show how these problems can be relaxed to corresponding integer linear programming (ILP) formulations leveraging on available solvers. The results are demonstrated on a real design case.
Towards a Robust Top-Down Model for Valuation of Mining Assets

Our goal is to create a simple, yet robust, statistical model which can be used to quantify the risk present in a portfolio of mining assets. In pursuit of this goal we aim at explaining a systematic approach which takes as input a model which is constructed based on fundamental economic principles and simple statistical technniques (e.g. a mixed-effect linear model with explanatory variables chosen from economic reasoning). Additional enrichment is then imposed, based on input coming from a more detailed model (built, for instance, from bottom up). And finally, the robustification step is obtained by computing worst-case performance analysis among all models that are within some distance of our simple model. This step quantifies the error induced by using a simple-yet-tractable model, which might be incorrect.