Miracle-dz/UniFAR-FTUs huggingface dataset:
Science in Environmental Policy: The Politics of Objective Advice

Scientists often bring issues to the policy agenda, translating scientific questions into everyday language and political terms. When Roger Revelle characterized Earth as a spaceship in testimony to Congress in 1957, his evocative language framed the issue of our planet's climate vulnerability in a way that technical discourse could not. In this book, Ann Campbell Keller examines the influence of scientists on environmental policymaking and makes the novel argument that scientists' adherence to the role of neutral advisor varies over the course of the policymaking process. Keller divides the policy process into three stages -- agenda setting, legislation, and implementation -- and compares scientists' influence on acid rain and climate change policy at these different stages over the course of several decades. She finds that scientists face more pressure to uphold the ideal of objectivity as policy-making processes advance and become more formalized, and thus are more likely to engage in advocacy and persuasion in the earlier, less formal, agenda-setting stage of the process. In the later, more structured legislative and implementation phases, scientists -- working hard to give the appearance of neutral expertise -- cede the role of persuader to others. Keller draws on theoretical work in political science and science studies and on empirical evidence from scientific reports, news coverage, congressional hearings, and interviews. Focusing on comparable cases and considering scientists' participation in them over time, she offers unique insights into how the context of decision making affects scientists' policy influence and emphasizes the multiple pathways by which scientific meaning is constructed in public settings.
Finger Print Analysis Using Termination and Bifurcation Minutiae

— A fingerprint is believed to be unique to each person and each finger. Even the fingerprints of identical twins are different. Fingerprints are one of the most full-grown biometric technologies and are used as proofs of evidence in courts of law all over the world. A fingerprint consists of various types of minutiae and it is one of the most popular categories used in the fingerprint verification system. In this paper, a simple technique is proposed for fingerprint analysis using minutiae extraction process with the combination of several techniques for image pre-processing and post-processing steps to improve the input image until it is suitable for minutiae extraction. In addition, two major categories of minutiae, termination and bifurcation are used here.
Private Provision of Public Goods and Information Diffusion in Social Groups

I describe a dynamic model of costly information sharing where private information affecting collective‐value actions is transmitted by social proximity. Individuals make voluntary contributions toward the provision of a pure public good, and information transmission about quality of provision is a necessary condition for collective provision to take place in a stationary equilibrium. I show that unlike in the case of private goods, better informed individuals face positive incentives to incur a cost to share information with their neighbors and that these incentives are stronger and provision of the pure public good greater the smaller are individuals' social neighborhoods.
On Cup Anemometer Rotor Aerodynamics

The influence of anemometer rotor shape parameters, such as the cups' front area or their center rotation radius on the anemometer's performance was analyzed. This analysis was based on calibrations performed on two different anemometers (one based on magnet system output signal, and the other one based on an opto-electronic system output signal), tested with 21 different rotors. The results were compared to the ones resulting from classical analytical models. The results clearly showed a linear dependency of both calibration constants, the slope and the offset, on the cups' center rotation radius, the influence of the front area of the cups also being observed. The analytical model of Kondo et al. was proved to be accurate if it is based on precise data related to the aerodynamic behavior of a rotor's cup.
Characterizing the energy consumption of data transfers and arithmetic operations on x86−64 processors

The energy efficiency of computer systems is influenced by many interdependent aspects. To asses the efficiency, typical benchmarks characterized the total power consumption of a computer system under certain domain specific workloads. For example, in case of the SPECPower benchmark the workload is a typical web server specific Java application. The contribution of individual components is usually not considered in this class of benchmarks. The CPU makes the most significant contribution due to both its high peak power consumption and the high variability depending on the workload. Correlations of workload and energy consumption of parts of the processors are usually done with simulations rather than actual measurements. This is mainly a consequence of the limited time resolution of power meters that is usually orders of magnitude too low to observe variations in the time scale of microarchitectural events. Furthermore, it is usually not possible to solely measure power consumption of processors as they are supplied by multiple power lines that are not easily accessible and are often shared with other components. In this paper we present benchmarks and a measurement methodology that compensate for the time resolution of our power meter by applying a constant and well-defined workload to the system. Using this experimental setup we analyze x86−64 microarchitectures from AMD and Intel. We furthermore characterize the contribution of individual operations and data transfers to the total power consumption of the Intel system.
Compressed Beamforming in Ultrasound Imaging

Emerging sonography techniques often require increasing the number of transducer elements involved in the imaging process. Consequently, larger amounts of data must be acquired and processed. The significant growth in the amounts of data affects both machinery size and power consumption. Within the classical sampling framework, state of the art systems reduce processing rates by exploiting the bandpass bandwidth of the detected signals. It has been recently shown, that a much more significant sample-rate reduction may be obtained, by treating ultrasound signals within the Finite Rate of Innovation framework. These ideas follow the spirit of Xampling, which combines classic methods from sampling theory with recent developments in Compressed Sensing. Applying such low-rate sampling schemes to individual transducer elements, which detect energy reflected from biological tissues, is limited by the noisy nature of the signals. This often results in erroneous parameter extraction, bringing forward the need to enhance the SNR of the low-rate samples. In our work, we achieve SNR enhancement, by beamforming the sub-Nyquist samples obtained from multiple elements. We refer to this process as “compressed beamforming”. Applying it to cardiac ultrasound data, we successfully image macroscopic perturbations, while achieving a nearly eightfold reduction in sample-rate, compared to standard techniques.
normoxia more than living and training in 2 ? maximproveV ? o Living and training in moderate hypoxia does not

[PDF] [Full Text] [Abstract] , January 1, 2006; 100 (1): 20-25. J Appl Physiol Fabrice Favret, Kyle K. Henderson, Julie Allen, Jean-Paul Richalet and Norberto C. Gonzalez hypertension but does not prevent pulmonary hypertension of prolonged hypoxia Exercise training improves lung gas exchange and attenuates acute hypoxic pulmonary [PDF] [Full Text] [Abstract] , September 1, 2006; 71 (4): 652-660. Cardiovasc Res Obert O. Cazorla, Y. Aït Mou, L. Goret, G. Vassort, M. Dauzat, A. Lacampagne, S. Tanguy and P. cardiomyocyte Effects of high-altitude exercise training on contractile function of rat skinned [PDF] [Full Text] [Abstract] , January 1, 2007; 102 (1): 412-416. J Appl Physiol Poole S. A. Hahn, L. F. Ferreira, J. B. Williams, K. P. Jansson, B. J. Behnke, T. I. Musch and D. C. Downhill treadmill running trains the rat spinotrapezius muscle [PDF] [Full Text] [Abstract] , June 1, 2007; 102 (6): 2179-2185. J Appl Physiol Cuneyt Yilmaz, D. Merrill Dane and Connie C. W. Hsia Alveolar diffusion-perfusion interactions during high-altitude residence in guinea pigs [PDF] [Full Text] [Abstract] 2009; 106 (6): 1810-1818. J Appl Physiol Britton, Lauren G. Koch, Harrieth E. Wagner and Peter D. Wagner Scott D. Kirkton, Richard A. Howlett, Norberto C. Gonzalez, Patrick G. Giuliano, Steven L. lung function Continued artificial selection for running endurance in rats is associated with improved
New Norcantharidin Analogs: Synthesis and Anticancer Activity

The reaction of direct condensation between S‐ethyl‐N‐(7‐oxabicyclo‐[2.2.1]heptane‐2,3‐dicarbonyl)isothiosemicarbazide (1) and primary amines was used for synthesizing new N‐substituted amides of 3‐(3‐ethylthio‐1,2,4‐triazol‐5‐yl)‐7‐oxabicyclo‐[2.2. 1]heptane‐2‐carboxylic acid (2–12) as norcantharadin analogs. Moreover, the anticancer activity of the obtained compounds was studied. Among all compounds, the N‐3‐methylbutyl amide of 3‐(3‐ethylthio‐1,2,4‐triazol‐5‐yl)‐7‐oxabicyclo‐[2.2. 1]heptane‐2‐carboxylic acid (4) presented selective in vitro toxic and antiproliferative effects against the human hepatoma cell line Hep3B, without affecting normal human liver stellate cells (LX‐2 cell line).
Kolmogorov complexities Kmax, Kmin on computable partially ordered sets

We introduce a machine free mathematical framework to get a natural formalization of some general notions of infinite computation in the context of Kolmogorov complexity. Namely, the classes Max^{X\to D}_{PR} and Max^{X\to D}_{Rec} of functions X \to D which are pointwise maximum of partial or total computable sequences of functions where D = (D,<) is some computable partially ordered set. The enumeration theorem and the invariance theorem always hold for Max^{X\to D}_{PR}, leading to a variant KD;max of Kolmogorov complexity. We characterize the orders D such that the enumeration theorem (resp. the invariance theorem) also holds for Max^{X\to D}_{Rec} . It turns out that Max^{X\to D}_{Rec} may satisfy the invariance theorem but not the enumeration theorem. Also, when Max^{X\to D}_{Rec} satisfies the invariance theorem then the Kolmogorov complexities associated to Max^{X\to D}_{Rec} and Max^{X\to D}_{PR} are equal (up to a constant). Letting K^D_{min} = K^{D^{rev}}_{max}, where D^{rev} is the reverse order, we prove that either K^D_{min} =_{ct} K^D_{max} =_{ct} K^D (=_{ct} is equality up to a constant) or K^D_{min}, K^D_{max} are _{ct} K^{0',D}. We characterize the orders leading to each case. We also show that K^D_{min}, K^D_{max} cannot be both much smaller than K^D at any point. These results are proved in a more general setting with two orders on D, one extending the other.
Measurement as legitimacy versus legitimacy of measures: Performance evaluation of social enterprise

Purpose - – The purpose of this paper is to review the growing emphasis on quantifiable performance measures such as social return on investment (SROI) in third sector organisations – specifically, social enterprise – through a legitimacy theory lens. It then examines what social enterprises value (i.e. consider important) in terms of performance evaluation, using a case study approach. Design/methodology/approach - – Case studies involving interviews, documentary analysis, and observation, of three social enterprises at different life-cycle stages with different funding structures, were constructed to consider “what measures matter” from a practitioner's perspective. Findings - – Findings highlight a priority on quality outcomes and impacts in primarily qualitative terms to evaluate performance. Further, there is a noticeable lack of emphasis on financial measures other than basic access to financial resources to continue pursuing social goals. Social implications - – The practical challenges faced by social enterprises – many of which are small to medium sized – in evaluating performance and by implication organisational legitimacy are contrasted with measures such as SROI which are resource intensive and have inherent methodological limitations. Hence, findings suggest the limited and valuable resources of social enterprises would be better allocated towards documenting the actual outcomes and impacts as a first step, in order to evaluate social and financial performance in terms appropriate to each objective, in order to demonstrate organisational legitimacy. Originality/value - – Findings distinguish between processes which may hold symbolic legitimacy for select stakeholder groups, and processes which hold substantive, cognitive legitimacy for stakeholders more broadly, in the under-researched context of social enterprise.
A Game-Theoretic Approach to Replanning-Aware Interactive Scene Prediction and Planning

This paper presents a novel cooperative-driving prediction and planning framework for dynamic environments based on the methods of game theory. The proposed algorithm can be used for highly automated driving on highways or as a sophisticated prediction module for advanced driver-assistance systems with no need for intervehicle communication. The main contribution of this paper is a model-based interaction-aware motion prediction of all vehicles in a scene. In contrast to other state-of-the-art approaches, the system also models the replanning capabilities of all drivers. With that, the driving strategy is able to capture complex interactions between vehicles, thus planning maneuver sequences over longer time horizons. It also enables an accurate prediction of traffic for the next immediate time step. The prediction model is supported by an interpretation of what other drivers intend to do, how they interact with traffic, and the ongoing observation. As part of the prediction loop, the proposed planning strategy incorporates the expected reactions of all traffic participants, offering cooperative and robust driving decisions. By means of experimental results under simulated highway scenarios, the validity of the proposed concept and its real-time capability is demonstrated.
Iterative MMSE receivers for multiuser MIMO cooperative systems

In this work we study a two-user multiple antenna system under quasi-static fading employing a novel scheme that combines cooperation and iterative multiuser detection based on minimum mean square error estimation. We investigate three different receivers: a joint detector for the two users, a separate (per-user) detector, and a distributed matrix-Alamouti detector. We show that the separate detector and the distributed matrix-Alamouti have close performance but different detection complexity depending on the antenna configuration. Frame error rate performance under Monte Carlo simulations is finally shown.
Branch and bound algorithm for computing the minimum stability degree of parameter-dependent linear systems

We consider linear systems with unspecified parameters that lie between given upper and lower bounds. Except for a few special cases, the computation of many quantities of interest for such systems can be performed only through an exhaustive search in parameter space. We present a general branch and bound algorithm that implements this search in a systematic manner and apply it to computing the minimum stability degree.
Distributed dynamics analysis of spiking neural network simulations

In order increase the chance of the adoption of new parallelization strategies and algorithms in the computational neuroscience community, one needs first to quantify qualitatively and quantitatively their impact on the almost chaotic dynamic behavior of neural microcircuit simulations. The analysis of this dynamics behavior is computationally expensive, as a large number of simulation scenarios need to be considered and high-dimensional data sets have to be analyzed. In this work, we proposed an improvement of the dimensionality reduction approach considered in the dynamics analysis methodology. Furthermore, by adding support for distributed processing with MPI to the existing OpenMP-based spiking neural network simulator, we enable the processing of such scenarios on high-performance computing resources. The preliminary results are presented in the paper. They have been obtained at the simulation of small-world neural microcircuits with hybrid parallelization on a Linux cluster with 64 cores. As such, the approach undertaken here provides partial solutions to both challenges outlined above.
Recognizing Textual Entailment by Generality Using Informative Asymmetric Measures and Multiword Unit Identification to Summarize Ephemeral Clusters

In the context of Ephemeral Clustering of web Pages, it can be interesting to label each cluster with a small summary instead of just a label. Within this scope, we introduce the paradigm of Textual Entailment by Generality, which can be defined as the entailment from a specific web snippet towards a more general web snippet. The subjacent idea is to find the best web snippet, which summarizes and subsumes all the other web snippets within an ephemeral cluster. To reach this objective, we first propose a new informative asymmetric similarity measure called the Simplified Asymmetric InfoSimba(AISs), which can be combined with different asymmetric association measures. In particular, the AISs proposes an unsupervised language-independent solution to infer Textual Entailment by Generality and as such can help to encounter the web snippet with maximum semantic coverage. This new methodology is tested against the first Recognizing Textual Entailment data set (RTE-1)1 for an exhaustive number of asymmetric association measures with and without the identification of Multiword Units. The comparative experiments with existing state-of-the-art methodologies show promising results.
Linear matrix inequalities, Riccati equations, and indefinite stochastic linear quadratic controls

This paper deals with an optimal stochastic linear-quadratic (LQ) control problem in infinite time horizon, where the diffusion term in dynamics depends on both the state and the control variables. In contrast to the deterministic case, we allow the control and state weighting matrices in the cost functional to be indefinite. This leads to an indefinite LQ problem, which may still be well posed due to the deep nature of uncertainty involved. The problem gives rise to a stochastic algebraic Riccati equation (SARE), which is, however, fundamentally different from the classical algebraic Riccati equation as a result of the indefinite nature of the LQ problem. To analyze the SARE, we introduce linear matrix inequalities (LMIs) whose feasibility is shown to be equivalent to the solvability of the SARE. Moreover, we develop a computational approach to the SARE via a semi-definite programming associated with the LMIs. Finally, numerical experiments are reported to illustrate the proposed approach.
Subjective cognitive dysfunction in first-episode and chronic schizophrenic patients.

Previous studies indicate that first-episode and chronic schizophrenic patients do not differ regarding neuropsychological performance as assessed with standard cognitive tasks. For the present study, it was investigated whether first-episode and chronic schizophrenics report similar subjective cognitive deficits. The Frankfurt Complaint Questionnaire (FCQ), a scale devised for assessing subjective cognitive disturbances in schizophrenia, was administered to 20 first-episode and 36 chronic schizophrenic patients, as well as 20 healthy controls. The schizophrenic subsamples did not differ on any of the FCQ subscales or on a "lie scale," measuring illness denial. Psychopathological ratings were comparable for both groups. As expected, healthy subjects reported significantly less cognitive and perceptual problems than schizophrenic patients. In marked contrast to a Kraepelinian view of schizophrenia, the present data confirm previous studies conducted with objective neuropsychological tests that schizophrenia is a neurodevelopmental rather than a neurodegenerative disorder.
Catch me in the dark: Effective privacy-preserving outsourcing of feature extractions over image data

Advances in cloud computing have greatly motivated data owners to outsource their huge amount of personal multimedia data and/or computationally expensive tasks onto the semi-trusted cloud by leveraging its abundant resources for cost saving and flexibility. From the privacy perspective, however, the outsourced multimedia data and its originated applications may reveal the data owner's private information, such as the personal identity, locations or even financial profiles. This observation has recently aroused new research interest on privacy-preserving computations over outsourced multimedia data. In this paper, we propose an effective privacy-preserving computation outsourcing protocol for the prevailing scale-invariant feature transform (SIFT) over massive encrypted image data. We first show that previous solutions to this problem have either efficiency/security or practicality issues, and none can well preserve the important characteristics of the original SIFT in terms of distinctiveness and robustness. We for the first time present a new privacy-preserving outsourcing protocol for SIFT with the preservation of its key characteristics, by randomly splitting the original image data, carefully distributing the feature extraction computations to two independent cloud servers and further leveraging the garbled circuit for secure keypoints comparisons. We both carefully analyze and extensively evaluate the security and effectiveness of our design. The results show that our solution is practically secure, outperforms the state-of-the-art and performs comparably to the original SIFT in terms of various characteristics, including rotation invariance, image scale invariance, robust matching across affine distortion and change in 3D viewpoint.
Towards Extremely Sensitive Ultraviolet-Light Sensors Employing Photochromic Optical Microfiber

We propose an extremely responsive ultraviolet-light sensor (−1.39 × 106 dB/(W/cm2)) based on photochromic optical microfiber. A densely packed planar coil of ZBLAN optical microfiber is doped with photochromic dyes. Under ultraviolet radiation, the photochromic microfiber experiences temporary photodarkening, and the change in the transmission of the probe light provides a measure of the incident ultraviolet light. This novel design grants an enhancement in sensitivity (3.13 nW/cm2) by at least one order of magnitude compared to traditional electrical counterparts.