Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving the Practice of Conservation: a Conceptual Framework and Research Agenda for Conservation Science

Abstract: Effective conservation requires addressing three fundamental questions whose answers can only be sought in conservation practice: (1) What should our goals be and how do we measure progress in reaching them? (2) How can we most effectively take action to achieve conservation? and (3) How can we learn to do conservation better? This essay provides a conceptual framework and research agenda for a conservation science that uses the principles of adaptive management to answer these questions. The framework is based on a general model of a conservation project. The conservation target involves defining the specific area or population the project is trying to influence. This target is affected by direct and indirect threats and opportunities; we provide a table of potential direct threats. Conservation actions that are taken to counter these threats can be divided into approaches, strategies, and specific tools; we present a comprehensive table of potential approaches. Finally, the practicioners that take these actions include individuals, organizations, project alliances, and networks; we define the specific functional roles necessary to achieve effective adaptive management. We then use this framework to outline a research agenda for conservation science that involves defining clear and practical measures of conservation success, determining sound guiding principles for using conservation strategies and tools, and developing the knowledge and skills in individuals and organizations for good adaptive management and thus for making conservation more effective.
" Step by step " evolution of cognitive function : the Composite Learning System

While biological evolution and learning are stepwise processes, classical Artiicial Neural Networks (ANNs) are designed and trained "in one go". The authors suggests that artiicial organisms whose neural architecture emerges via Darwinian evolution and which are trained "step by step" may be able to achieve richer functionality than is possible for conventional ANNs. The paper presents the Composite Learning System Model (CLSM): a model of cognitive evolution designed to validate this hypothesis. In the CLSM a Genetic Algorithm (GA) operates on a population of artii-cial organisms represented as ANNs. The GA produces "organisms" with the ability to learn sets of functions, representing the ecological niches in which individual organisms operate. The deenition of these functions allows simple functions to act as building blocks-or pre-adaptations for the computation of more complex ones. The paper presents a series of implementations of the model along with simulation results. Initial simulations showed that CLSM networks were able to acquire simple function sets but incapable of acquiring more complex functions pre-deened by the experimenter. This led to the introduction of "Variable Characteristic Functions": the functions to be acquired were themselves subjected to variation and selection. In this modiied version of the model the population was rapidly invaded by a single lineage of organisms computing a set of very simple functions. In order to force the learning of more complex functions the model was revised, to take account of nite food resources in individual niches. This allowed the evolution of a higher degree of functional complexity. The paper discusses the signiicance of these results. It is conjectured that that learning time for CLSM organisms may be less than linearly proportional to problem complexity and that they may thus avoid the scaling problems of classical ANNs; the use of variable Characteristic Functions is shown to have advantages in the avoidance of local optima; a mechanism is suggested for the accumulation of cerebral complexity in the absence of corresponding tness gains; the model is used to show the advantages of a highly modular brain architecture as well as a possible mechanism for xed learning sequences as observed in human and animal developmental psychology. At the end of the paper brief indications are given concerning directions for future research.
Tonic Inhibition in Principal Cells of the Amygdala: A Central Role for α3 Subunit-Containing GABAA Receptors

GABAergic inhibition in the amygdala is essential in regulating fear and anxiety. Although fast “phasic” inhibition arising through the activation of postsynaptic GABAA receptors (GABAARs) has been well described in the amygdala, much less is known about extrasynaptic GABAARs mediating persistent or tonic inhibition and regulating neuronal excitability. Here, we recorded tonic currents in the basolateral (BLA) nucleus and the lateral (LA) nucleus of the amygdala. While all BLA principal cells expressed a robust GABAergic tonic current, only 70% of LA principal cells showed a tonic current. Immunohistochemical stainings revealed that the α3 GABAAR subunit is expressed moderately in the LA and strongly throughout the BLA nucleus, where it is located mostly at extrasynaptic sites. In α3 subunit KO mice, tonic currents are significantly reduced in BLA principal cells yet not in LA principal cells. Moreover, the α3 GABAAR-selective benzodiazepine site agonist and anxiolytic compound TP003 increases tonic currents and dampens excitability markedly in wild-type BLA principal cells but fails to do so in α3KO BLA cells. Interneurons of the LA and BLA nuclei also express a tonic current, but TP003-induced potentiation is seen in only a small fraction of these cells, suggesting that primarily other GABAAR variants underlie tonic inhibition in this cell type. Together, these studies demonstrate that α3 GABAAR-mediated tonic inhibition is a central component of the inhibitory force in the amygdala and that tonically activated α3 GABAARs present an important target for anxiolytic or fear-reducing compounds.
Intermetallic compounds in heterogeneous catalysis—a quickly developing field

Abstract The application of intermetallic compounds for understanding in heterogeneous catalysis developed in an excellent way during the last decade. This review provides an overview of concepts and developments revealing the potential of intermetallic compounds in fundamental as well as applied catalysis research. Intermetallic compounds may be considered as platform materials to address current and future catalytic challenges, e.g. in respect to the energy transition.
Organizing Continuous Product Development and Commercialization: The Collaborative Community of Firms Model

The increased importance of knowledge creation and use to firms’ global competitiveness has spawned considerable experimentation with organizational designs for product development and commercialization over the last three decades. This paper discusses innovation-related organizational design developments during this period, showing how firms have moved from stand-alone organizations to multifirm network organizations to community-based organizational designs. The collaborative community of firms model, the most recent organizational design in this evolutionary process, is described in detail. Blade.org, a purposefully designed collaborative community of firms dedicated to the continuous development and commercialization of blade servers, a computer technology with large but unforeseeable market potential, is used as an illustrative case. Blade.org’s organizational design combines a community ‘‘commons’’ for the collective development and sharing of knowledge among member firms with explicit institutional mechanisms for the support of direct intermember collaboration. These design elements are used to overcome the challenges associated with (1) concurrent technological and market experimentation and (2) the dynamic coordination of a complex emergent system of hardware, software, and services provided by otherwise independent firms. To date, Blade.org has developed more than 60 new products, providing strong evidence of the innovation prowess of the collaborative community of firms organizational model. Based on an analysis of the evolution of organizational designs and the case of Blade.org, implications for innovation management theory and practice are derived.
Swarm Intelligence Approaches for Distributed Load Balancing on the Grid

With the rapid growth of data and computational needs, distributed systems and computational Grids are gaining more and more attention. The huge amount of computations a Grid can fulfill in a specific amount of time cannot be performed by the best supercomputers. However, Grid performance can still be improved by making sure all the resources available in the Grid are utilized optimally using a good load balancing algorithm. This research proposes two new distributed swarm intelligence inspired load balancing algorithms. One algorithm is based on ant colony optimization and the other algorithm is based on particle swarm optimization. A simulation of the proposed approaches using a Grid simulation toolkit (GridSim) is conducted. The performance of the algorithms are evaluated using several performance criteria (e.g. makespan and load balancing level). A comparison of our proposed approaches with a classical approach called State Broadcast Algorithm and two random approaches is provided. Experimental results show the proposed algorithms can perform very well in a Grid environment. Especially the use of particle swarm optimization, can yield better performance results in many scenarios than the ant colony approach.
The OmpA-Like Protein Loa22 Is Essential for Leptospiral Virulence

Pathogenic mechanisms of Leptospira interrogans, the causal agent of leptospirosis, remain largely unknown. This is mainly due to the lack of tools for genetic manipulations of pathogenic species. In this study, we characterized a mutant obtained by insertion of the transposon Himar1 into a gene encoding a putative lipoprotein, Loa22, which has a predicted OmpA domain based on sequence identity. The resulting mutant did not express Loa22 and was attenuated in virulence in the guinea pig and hamster models of leptospirosis, whereas the genetically complemented strain was restored in Loa22 expression and virulence. Our results show that Loa22 was expressed during host infection and exposed on the cell surface. Loa22 is therefore necessary for virulence of L. interrogans in the animal model and represents, to our knowledge, the first genetically defined virulence factor in Leptospira species.
Atmospheric chemistry of a 33–34 hour old volcanic cloud from Hekla Volcano (Iceland): Insights from direct sampling and the application of chemical box modeling

[1] On 28 February 2000, a volcanic cloud from Hekla volcano, Iceland, was serendipitously sampled by a DC-8 research aircraft during the SAGE III Ozone Loss and Validation Experiment (SOLVE I). It was encountered at night at 10.4 km above sea level (in the lower stratosphere) and 33–34 hours after emission. The cloud is readily identified by abundant SO2 (≤1 ppmv), HCl (≤70 ppbv), HF (≤60 ppbv), and particles (which may have included fine silicate ash). We compare observed and modeled cloud compositions to understand its chemical evolution. Abundances of sulfur and halogen species indicate some oxidation of sulfur gases but limited scavenging and removal of halides. Chemical modeling suggests that cloud concentrations of water vapor and nitric acid promoted polar stratospheric cloud (PSC) formation at 201–203 K, yielding ice, nitric acid trihydrate (NAT), sulfuric acid tetrahydrate (SAT), and liquid ternary solution H2SO4/H2O/HNO3 (STS) particles. We show that these volcanically induced PSCs, especially the ice and NAT particles, activated volcanogenic halogens in the cloud producing >2 ppbv ClOx. This would have destroyed ozone during an earlier period of daylight, consistent with the very low levels of ozone observed. This combination of volcanogenic PSCs and chlorine destroyed ozone at much faster rates than other PSCs that Arctic winter. Elevated levels of HNO3 and NOy in the cloud can be explained by atmospheric nitrogen fixation in the eruption column due to high temperatures and/or volcanic lightning. However, observed elevated levels of HOx remain unexplained given that the cloud was sampled at night.
Impact of PSCA Variation on Gastric Ulcer Susceptibility

Peptic ulcer is one of the most common gastrointestinal disorders with complex etiology. Recently we conducted the genome wide association study for duodenal ulcer and identified disease susceptibility variations at two genetic loci corresponding to the Prostate stem cell antigen (PSCA) gene and the ABO blood group (ABO) gene. Here we investigated the association of these variations with gastric ulcer in two Japanese case-control sample sets, a total of 4,291 gastric ulcer cases and 22,665 controls. As a result, a C-allele of rs2294008 at PSCA increased the risk of gastric ulcer with odds ratio (OR) of 1.13 (P value of 5.85×10−7) in an additive model. On the other hand, SNP rs505922 on ABO exhibited inconsistent result between two cohorts. Our finding implies presence of the common genetic variant in the pathogenesis of gastric and duodenal ulcers.
The Whole Greater than the Sum of Its Parts: An Investigation into the Existence of European Identity, Its Unity and Its Divisions

The article offers an alternative stance to established research emphasising the absence of a European public sphere and the presence of Euroscepticism both in the media and public opinion at large. Whereas these are recognised and proven phenomena, the article argues that a perpetual, albeit evolving, cosmopolitan European identity is being reproduced as part of the natural process of globalisation. Europeanness finds some of its fresh strength in phenomena such as work migration. Although migration for work is by no means a new occurrence, Eastern European work diasporas participate in the construction of a renewed idea of Europe through new networks of communication supported by new media technologies which, although not mainstream, appear to gather strength and will become indispensable to the way new spaces of European identity are articulated.
Biocompatibility and Surface Properties of TiO2 Thin Films Deposited by DC Magnetron Sputtering

We present the study of the biocompatibility and surface properties of titanium dioxide (TiO2) thin films deposited by direct current magnetron sputtering. These films are deposited on a quartz substrate at room temperature and annealed with different temperatures (100, 300, 500, 800 and 1100 °C). The biocompatibility of the TiO2 thin films is analyzed using primary cultures of dorsal root ganglion (DRG) of Wistar rats, whose neurons are incubated on the TiO2 thin films and on a control substrate during 18 to 24 h. These neurons are activated by electrical stimuli and its ionic currents and action potential activity recorded. Through X-ray diffraction (XRD), the surface of TiO2 thin films showed a good quality, homogeneity and roughness. The XRD results showed the anatase to rutile phase transition in TiO2 thin films at temperatures between 500 and 1100 °C. This phase had a grain size from 15 to 38 nm, which allowed a suitable structural and crystal phase stability of the TiO2 thin films for low and high temperature. The biocompatibility experiments of these films indicated that they were appropriated for culture of living neurons which displayed normal electrical behavior.
The Post-Merger Segmentation of Euronext: A Solution to the Inadequacy of National Securities Regulators?

We investigate the effects on financial reporting quality and liquidity of the merger of four European national exchanges into Euronext, and the subsequent creation of two named Euronext segments, which allowed firms to bond to improved financial reporting and disclosure. We find a larger post-merger improvement in accounting quality and value relevance of earnings for segment firms relative to nonsegment firms, as well as a significant increase in liquidity for segment but not for non-segment firms. Our results have implications for recent cross-border stock exchange mergers, suggesting that the mergers may have positive effects on firms’ financial reporting by exposing them to a broader investor clientele, but only in the presence of a mechanism to commit to enhanced reporting quality and disclosure. We appreciate generous funding from the Goizueta Business School at Emory University, research assistance from Ronald Harris, ByungHun Chung, Sonia Shadadpuri, and Jochen Pochun Chang, and comments from two anonymous FARS/IAS reviewers, Marco Trombetta (the FARS/IAS discussant), Jivas Chakravarthy, Willie Choi, Jenna McAuley, Shiva Rajgopal, Maria Wieczynska, and workshop participants at Southern Methodist and Emory Universities, the 2010 Nick Dopuch Conference, the 2011 FARS/IAS Midyear Meeting, and the 2011 European Accounting Association Annual Congress. An earlier version of this paper was circulated under the title “The Effects of the Integration of the Euronext Stock Market on Financial Reporting Quality and Liquidity of Listed Companies. ”
Web classification using support vector machine

In web classification, web pages from one or more web sites are assigned to pre-defined categories according to their content. Since web pages are more than just plain text documents, web classification methods have to consider using other context features of web pages, such as hyperlinks and HTML tags. In this paper, we propose the use of Support Vector Machine (SVM) classifiers to classify web pages using both their text and context feature sets. We have experimented our web classification method on the WebKB data set. Compared with earlier Foil-Pilfs method on the same data set, our method has been shown to perform very well. We have also shown that the use of context features especially hyperlinks can improve the classification performance significantly.
Trends That Affect Temporal Analysis Using SourceForge Data

SourceForge is a valuable source of software artifact data for researchers who study project evolution and developer behavior. However, the data exhibit patterns that may bias temporal analyses. Most notable are cliff walls in project source code repository timelines, which indicate large commits that are out of character for the given project. These cliff walls often hide significant periods of development and developer collaboration—a threat to studies that rely on SourceForge repository data. We demonstrate how to identify these cliff walls, discuss reasons for their appearance, and propose preliminary measures for mitigating their effects in evolution-oriented studies.
Passive Operating System Identification From TCP / IP Packet Headers *

Accurate operating system (OS) identification by passive network traffic analysis can continuously update less-frequent active network scans and help interpret alerts from intrusion detection systems. The most recent open-source passive OS identification tool (ettercap) rejects 70% of all packets and has a high 75-class error rate of 30% for non-rejected packets on unseen test data. New classifiers were developed using machine-learning approaches including cross-validation testing, grouping OS names into fewer classes, and evaluating alternate classifier types. Nearest neighbor and binary tree classifiers provide a low 9-class OS identification error rate of roughly 10% on unseen data without rejecting packets. This error rate drops to nearly zero when 10% of the packets are rejected.
An Evaluation of Output Quality of Machine Translation Program

This article reports an exploratory evaluation of the output quality of two prevalent English-Persian Machine Translation programs. The purpose of the research is to find out which program produces relatively better output, and what major linguistic bottlenecks MT programs will encounter in their processing of texts. Criteria were established in light of structural theories to solve the MT output from the perspective of Accuracy and Intelligibility. For each program, the mean score it obtained for its output and the rate of correctness of its translation of the testing points were calculated. An analysis of the mean score and the rate of correctness of each program generated the following findings about the output quality of these two programs: 1) Padideh Translator produces the best output. 2) The major linguistic bottlenecks in English-Persian MT programs occur in the areas of morphology, complex sentences, syntactic ambiguity and semantic analysis, generation of Persian, and long sentences.
Cross-Domain Face Verification: Matching ID Document and Self-Portrait Photographs

Cross-domain biometrics has been emerging as a new necessity, which poses several additional challenges, including harsh illumination changes, noise, pose variation, among others. In this paper, we explore approaches to cross-domain face verification, comparing self-portrait photographs ("selfies") to ID documents. We approach the problem with proper image photometric adjustment and data standardization techniques, along with deep learning methods to extract the most prominent features from the data, reducing the effects of domain shift in this problem. We validate the methods using a novel dataset comprising 50 individuals. The obtained results are promising and indicate that the adopted path is worth further investigation.
Effects of Surfactant on Bubble Size Distribution and Gas Hold-up in a Bubble Column

This study investigates the influence of two surfactants –a non-ionic (Tween20) and a zwitterionic (Cocoamidopropyl Betaine) – upon the gas-liquid hydrodynamics in a bubble column. These kinds of substances can have an important influence upon the gas-liquid hydrodynamics, specifically on the bubble size and gas hold-up. Bubble diameters were measured photographically in a bubble column, which was operating in the homogeneous regime with air and aqueous surfactant solutions. The bubble size and gas hold-up data were determined for several values of the superficial gas velocity (0.13, 0.26 and 0.5 cm/s). On the other hand, bubble diameter was determined for different values of surfactant concentration (0.02, 0.05 and 0.1 %vol). At superficial gas velocity below 0.26 cm/s, addition of surfactant in air-water has low influence on bubble size, whereas higher gas velocity addition of surfactant increases the number of bubble. In surfactant solutions (in comparison with pour water), resulted in an increase in number of bubble and a rough decrease in Sauter mean bubble diameter. Bubbles tend to become smaller with decreasing surface tension of water. Therefore, surfactant existence increases the gas hold-up. Further, gas holdup increased when gas bubbles movement increased.