Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic resonance in the high-Q and near-monochromatic regime

This communication investigates the sensitive behavior of dynamic resonant scattering when an extended system is weakly coupled to a resonator (high-Q) and the source field is nearly monochromatic but of finite energy. We analyze a specific model that incorporates certain universal features of resonance. It is a resonant modification of the Lamb model for the interaction between an oscillator and a continuum. This resonant Lamb model incorporates a two-part scatterer attached to an infinite string with continuous spectrum. The non-resonant part of the scatterer is associated with direct scattering; and the resonant part-an oscillator coupled weakly to the string- is associated with field amplification and delayed scattering. A sharp anomaly in the transmission coefficient occurs when the source frequency is within γ2 of the resonant frequency (where γ is the coupling constant and the Q-factor is of order γ-2); this anomaly is mollified as the source spreads spectrally. Resonant amplification occurs when the source frequency is within γ of the resonant frequency. The amount of amplification depends on the relationships between the spectral width γ2 of the transmission resonance, the spectral width σ of the source field, and the difference between the source frequency and the resonant frequency.
Modem for High Order Modulation Schemes (MHOMS)

R. De Gaudenzi and A. Ginesi ESA/ESTEC, Keplerlaan 1, PO Box 299, 2200 AG Noordwijk The Netherlands D. Giancristofaro Alcatel Alenia Space Italia, Via Pile 60, 67100 L'Aquila Italy S. Benedetto and G. Montorsi Politecnico of Torino, Dipartimento di Elettronica, C. Duca degli Abruzzi 24, 10129 Torino Italy Marco Luise University of Pisa, Dipartimento di Ingegneria dell’Informazione, Via G. Caruso, 56122 Pisa Italy L. Giugno Wiser S.r. l, Via Fiume 23, 57123 Livorno Italy C. Berrou and C. Douillard ENST Bretagne Technopole de Brest Iroise, CS 83 818 29238 Brest Cedex 3 France G. Gallinaro Space Engineering S.p.A. , via dei Berio 91, 00155 Roma Italy
Generating Schedules to Maximize Quality

In knowledge generating production processes such as intelligence gathering and news reporting, the quality of the result produced by a given activity depends on its duration, and, due to resource limitations and process deadlines, tradeoffs must invariably be made regarding how much time to devote to various activities to achieve maximum overall effect. In essense, some activities must be executed in faster time cycles than would be desirable under non-constraining circumstances, with consequent degradation of process quality. In this paper, we consider this type of scheduling problem, which we refer to generally as quality maximization. Starting with normal resource-constrained project scheduling problem (RCPSP) assumptions, we define a new type of scheduling problem by additionally associating a quality profile with each activity in the project. Quality profiles have an “anytime” property, implying that activities can be terminated at any point, with the quality of the output being proportional to duration. Instead of finishing all activities as fast as possible, the goal of scheduling in this context is to maximize the overall quality given a hard project due date. We formulate this quality maximization problem as a constraint-based optimization problem, and present a new constraint posting algorithm for solving this problem that incorporates a linear optimization program. Different constraint posting heuristics are defined and evaluated on a set of quality maximization RCPSP problems constructed from standard reference RCPSP problems. The experimental results show the overall effectiveness of our approach for generating schedules to maximize quality. And ratio-based heuristics provide a promising starting point for stochastic sampling or other schedule refining techniques by solving 100% problems without backtracking.
Bounded distortion harmonic shape interpolation

Planar shape interpolation is a classic problem in computer graphics. We present a novel shape interpolation method that blends C∞ planar harmonic mappings represented in closed-form. The intermediate mappings in the blending are guaranteed to be locally injective C∞ harmonic mappings, with conformal and isometric distortion bounded by that of the input mappings. The key to the success of our method is the fact that the blended differentials of our interpolated mapping have a simple closed-form expression, so they can be evaluated with unprecedented efficiency and accuracy. Moreover, in contrast to previous approaches, these differentials are integrable, and result in an actual mapping without further modification. Our algorithm is embarrassingly parallel and is orders of magnitude faster than state-of-the-art methods due to its simplicity, yet it still produces mappings that are superior to those of existing techniques due to its guaranteed bounds on geometric distortion.
Determinants of Public Participation in Kenya County Governments

The Constitution of Kenya 2010 introduced a framework for devolving public resources in Kenya’s forty-seven Counties. The Counties were given the responsibilities of maintaining health, roads and agriculture, among others. Using the Afrobarometer (2015) survey, we employ probit regression to examine the determinants of successful public participation in the Counties. We find that approval of the Governor’s performance has a positive and significant influence on public participation. However, difficulty among the citizenry in influencing County decision-making; lack of responsive County Assembly Members; difficulty in accessing information on County budgets, legislation and projects; and corruption in the Governor’s office have a negative significance.
Jason Microwave Radiometer Performance and On-Orbit Calibration

Results are presented from the on-orbit calibration of the Jason Microwave Radiometer (JMR). The JMR brightness temperatures (TBs) are calibrated at the hottest and coldest ends of the instrument's dynamic range, using Amazon rain forest and vicarious cold on-Earth theoretical brightness temperature references. The retrieved path delay values are validated using collocated TOPEX Microwave Radiometer and Radiosonde Observation path delay (PD) values. Offsets of 1–4 K in the JMR TBs and 8–12 mm in the JMR PDs, relative to TMR measurements, were initially observed. There were also initial TB offsets of 2 K between the satellite's yaw state. The calibration was adjusted by tuning coefficients in the antenna temperature calibration algorithm and the antenna pattern correction algorithm. The calibrated path delay values are demonstrated to have no significant bias or scale errors with consistent performance in all nonprecipitating weather conditions. The uncertainty of the individual path delay measurements is estimated to be 0.74 cm ± 0.15, which exceeds the mission goal of 1.2 cm RMS.
TA-MAC : A Traffic-Adaptive MAC Protocol for Asynchronous Wireless Sensor Networks

Wireless Sensor Network MAC protocols usually employ periodic sleep and wakeup, achieving low dutycycle to save energy and to increase the lifetime of batterypowered sensor devices. Previously proposed PW-MAC (Predictive Wakeup MAC) protocol is based on asynchronous duty cycling. PW-MAC minimizes sensor node energy consumption by enabling senders to predict receiver′s wakeup times. However, PW-MAC protocol performs poorly in the drastically changed traffic wireless sensor networks. In such environment, the duty cycles of sensor nodes should be adjusted appropriately to ensure energy efficiency while meeting traffic demands and keeping low latency. In this paper, we propose a TA-MAC (Traffic-Adaptive MAC) protocol that dynamically adjusts node′s duty cycle based on the traffic to reduce packet transmission delay and save the sensor node′s energy.
Fundamentals of Parallel Logic Simulation

Parallel processing is being recognized as a practical way to achieve very high performance in logic simulation of large designs. This tutorial summarizes many of the basic methods employed, and estimates attainable throughput. Next, data structuring and processing factors are explored as they impact parallel simulation. Experience indicates that support processing necessary before and after simulation kernel execution can be accelerated using parallel methods. We conclude by suggesting pitfalls to avoid, and discuss future development directions for parallel logic simulation.
Protein Hypernetworks: a Logic Framework for Interaction Dependencies and Perturbation Effects in Protein Networks

Motivation: Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of such systems emerge not from the protein interactions themselves but from the dependencies between these interactions. Therefore, a comprehensive approach for integrating and using information about such dependencies is required. Results: We present an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining protein hypernetworks. First we demonstrate how this framework straightforwardly improves the prediction of protein complexes. Next we show that modeling protein perturbations in hypernetworks, rather than in networks, allows to better infer the functional necessity of proteins for yeast. Furthermore, hypernetworks improve the prediction of synthetic lethal interactions in yeast, indicating their capability to capture high-order functional relations between proteins. Conclusion: Protein hypernetworks are a consistent formal framework for modeling dependencies between protein interactions within protein networks. First applications of protein hypernetworks on the yeast interactome indicate their value for inferring functional features of complex biochemical systems.
Memory Systems for Cognitive Agents

The several different memory systems in human beings play crucial roles in facilitating human cognition. To build artificial agents that have cognitive capabilities similar to those of human beings, we have to develop these agents based on architectures modelling what we know of human cognition from neuroscience, psychology and cognitive science. In this paper we describe the various memory systems in the LIDA Architecture, which implements Global Workspace Theory. We discuss the interaction between these memory systems, feelings and emotions, and consciousness in the context of cognitive cycles. Finally, we look at our current work on spatial memory in the LIDA model.
Assessment of the Proliferative Marker Ki-67 and p53 Protein Expression in HBV- and HCV-related Hepatocellular Carcinoma Cases in Egypt.

BACKGROUND Chronic HBV and HCV infections are the major risk factors for the development of HCC through a multistep pathway that involves viral and non-viral dependent pathophysiological steps. Hepatic expression of the nuclear proliferative marker ki-67 and the p53 oncoprotein were found to be associated with poor outcome. So, the present study was done to evaluate the changes in expression of Ki-67 and p53 oncoprotein, and to determine p53 gene mutation in HBV/HCV-related HCC Egyptian patients. METHODS Eight HBV-and 22 HCV-positive HCC cases have been examined for the presence of p53 mutation by immunohistochemistry (IHC) and single-strand conformation polymorphism (SSCP), followed by direct DNA sequencing. HCV were genotyped by LiPA-II. RESULTS Our results have shown that the proliferative marker ki-67 LI and p53 were highly expressed and significantly related to tumor grade in the Egyptian HCC cases (p<0.05). Also, p53 mutation was found in 16 HCC cases by IHC and in 14 HCC cases by SSCP, only 11 patients showed p53 mutation by sequencing. The highest mutation rate was scored for exon 7 (7 mutations) at codon 249; 4 out of 8 (50%) of HBV-related HCC cases and 3 out of 22 (13.6%) of HCV-related HCC cases, followed by exon 5 (3 mutations) at codons 133, 146, 176 in HCV-related HCC cases, then exon 8 at codon 275 in HCV-related HCC cases. The concordance between the IHC and sequencing analysis was 69%. CONCLUSION The present study demonstrates the association between the proliferative marker ki-67 and p53 expression with the tumor grade of Egyptian HBV/HCV-related HCC cases. Our results also support the hypothesis that p53 mutations are rather a late event in the carcinogenesis. Also, they suggest that the final steps of hepatocarcinogenesis are common and independent of the aetiology of the viral infection.
Overview of Datalog Extensions with Tuples and Sets

Datalog (with negation) is the most powerful query language for relational database with a well-deened declarative semantics based on the work in logic programming. However , Datalog only allows inexpressive at structures and cannot directly support complex values such as nested tuples and sets common in novel database applications. For these reasons, Datalog has been extended in the past several years to incorporate tuple and set constructors. In this paper, we examine four diierent Datalog extensions: LDL, COL, Hilog and Relationlog.
A Coupled Heat and Flow Solver for Extrusion Simulation

In this paper we investigate the simulation of aluminum extrusion processes by means of a newly developed coupled heat-and ow solver. The extrusion problem is here formulated as two sub-problems which are solved separately in a staggered solution strategy: 1) A non-Newtonian Navier-Stokes ow problem where the viscosity depends both on the eeective strain rate and the temperature, and 2) a linear heat conduction problem. The latter problem is again divided into several sub-problems for the various material regions that make up the extrusion package. The constitutive properties of the aluminum are represented by the Zener-Hollomon material model. A mixed interpolation of the unknown variables is employed in the nite element discretization of the mathematical model, using second order polynomials for the velocity and temperature elds and linear polynomials for the pressure. The extrusion solver is implemented in C++ based on the Diipack software package (see http://www.nobjects.com/Diffpack). The results of the numerical simulations are veriied against physical experiments conducted by the extrusion laboratory at SINTEF in Trondheim.
Ensemble Monte Carlo/molecular dynamics simulation of electron mobility in silicon with ordered dopant arrays

Electron transport in bulk silicon with ordered dopant arrays is studied using an ensemble Monte Carlo (EMC) technique coupled with molecular dynamics (MD) method. This work is motivated by a recently developed single-ion implantation (SII) technique, which enables us to fabricate a semiconductor device with an ordered dopant array. We numerically estimate the carrier mobility in silicon with such an ordered dopant array comparing to that with conventional random dopant distribution. The calculation results show that electron mobility can be enhanced in the ordered dopant array if the fluctuation of dopant position is less than 5 nm.
Automated construction of a software-specific word similarity database

Many automated software engineering approaches, including code search, bug report categorization, and duplicate bug report detection, measure similarities between two documents by analyzing natural language contents. Often different words are used to express the same meaning and thus measuring similarities using exact matching of words is insufficient. To solve this problem, past studies have shown the need to measure the similarities between pairs of words. To meet this need, the natural language processing community has built WordNet which is a manually constructed lexical database that records semantic relations among words and can be used to measure how similar two words are. However, WordNet is a general purpose resource, and often does not contain software-specific words. Also, the meanings of words in WordNet are often different than when they are used in software engineering context. Thus, there is a need for a software-specific WordNet-like resource that can measure similarities of words. In this work, we propose an automated approach that builds a software-specific WordNet like resource, named WordSimSEDB, by leveraging the textual contents of posts in StackOverflow. Our approach measures the similarity of words by computing the similarities of the weighted co-occurrences of these words with three types of words in the textual corpus. We have evaluated our approach on a set of software-specific words and compared our approach with an existing WordNet-based technique (WordNetres) to return top-k most similar words. Human judges are used to evaluate the effectiveness of the two techniques. We find that WordNetres returns no result for 55 % of the queries. For the remaining queries, WordNetres returns significantly poorer results.
An evil face? Verbal evaluative multi-CS conditioning enhances face-evoked mid-latency magnetoencephalographic responses

Abstract Humans have a remarkable capacity for rapid affective learning. For instance, using first-order US such as odors or electric shocks, magnetoencephalography (MEG) studies of multi-CS conditioning demonstrate enhanced early (<150 ms) and mid-latency (150–300 ms) visual evoked responses to affectively conditioned faces, together with changes in stimulus evaluation. However, particularly in social contexts, human affective learning is often mediated by language, a class of complex higher-order US. To elucidate mechanisms of this type of learning, we investigate how face processing changes following verbal evaluative multi-CS conditioning. Sixty neutral expression male faces were paired with phrases about aversive crimes (30) or neutral occupations (30). Post conditioning, aversively associated faces evoked stronger magnetic fields in a mid-latency interval between 220 and 320 ms, localized primarily in left visual cortex. Aversively paired faces were also rated as more arousing and more unpleasant, evaluative changes occurring both with and without contingency awareness. However, no early MEG effects were found, implying that verbal evaluative conditioning may require conceptual processing and does not engage rapid, possibly sub-cortical, pathways. Results demonstrate the efficacy of verbal evaluative multi-CS conditioning and indicate both common and distinct neural mechanisms of first- and higher-order multi-CS conditioning, thereby informing theories of associative learning.
Making Memories. On the fly.

Abstract Stimulus directed behavior is regulated by communication between neurons within neural circuits throughout an animal’s brain. Experience can change the dynamics of neural circuits by modifying specific synaptic connections. However, pinpointing the sites of behavioral-relevant plasticity has proven challenging. Technical advances in controlling and monitoring neural activity in behaving animals have allowed for marked progress in understanding the logic underlying learning and memory in the model system Drosophila melanogaster. The fruit fly has a numerically simple brain and probing identified network components has become feasible. Here, we discuss cellular and circuit mechanisms underlying associative learning. We also provide insights into the computational operations encoding associative memories in the fly. Beyond their roles in learning and memory retrieval, these circuit components are recruited for the reevaluation of memories during memory extinction and reconsolidation.
Race, Racism and Identification in the Era of Technosecurity

ABSTRACT In the era of technosecurity the State’s concerns with migration, terrorism, and crime are increasingly entangled. This is reflected in the development of identification systems that depend on the collection and analysis of both data and bodily traces. Race is a persistent if sometimes elusive element in this. Examination of three domains of innovation in technosecurity – the management of dispersed borders, the expanding use of DNA in criminal justice, and the sourcing, sharing and analysis of digitized facial images – reveals the complexities of the resulting politics. Across these different domains, there is a varied and ambiguous relationship between explicit race talk and patterns of disadvantage. This can obscure a common underlying pattern: emerging socio-technical arrangements, directly or indirectly, highlight and discriminate against minorities. The inter-dependences of security and technology reconfigure the race object as an unstable assemblage of corporeal, digital, and discursive elements. The implementation and management of new identification systems often accommodate to contemporary sensitivities around cultural difference and expression of identity but in ways that do little to address the structured inequalities they reinforce.
Exploring Spatial Patterns of Guardianship Through Civic Technology Platforms

Civic technologies levy advances in digital tools to promote civic engagement, giving people a voice to participate in public decision-making. While democratizing participation, the use of such civic tech also leaves behind a digital trace of the behavior of its users. This article uses such a digital trace to explore spatial patterns in active guardianship of public space. Through mapping people’s participation in a platform for reporting neighborhood concerns (a form of digitally enabled guardianship), the spatial range of guardianship is unpacked using exploratory spatial data analysis. Typologies for guardianship behavior are then created using k-means clustering. Results provide an insight into the heterogeneity of spatial behavior of different groups of guardians outside the home environment. Guardians appear to not be limited to activity within a neighborhood, and instead cover a larger awareness space with nodes and paths, and also show distinct patterns, indicating heterogeneity in guardianship patterns. Recommendations are made to consider operationalizing guardians as heterogeneous, and active in their entire activity space, rather than homogeneous groups assigned as crime prevention forces to a residential area.
Super-Sample Signal

When extracting cosmological information from power spectrum measurements, we must consider the impact of super-sample density fluctuations whose wavelengths are larger than the survey scale. These modes contribute to the mean density fluctuation $\delta_b$ in the survey and change the power spectrum in the same way as a change in the cosmological background. They can be simply included in cosmological parameter estimation and forecasts by treating $\delta_b$ as an additional cosmological parameter enabling efficient exploration of its impact. To test this approach, we consider here an idealized measurement of the matter power spectrum itself in the $\Lambda$CDM cosmology though our techniques can readily be extended to more observationally relevant statistics or other parameter spaces. Using sub-volumes of large-volume $N$-body simulations for power spectra measured with respect to either the global or local mean density, we verify that the minimum variance estimator of $\delta_b$ is both unbiased and has the predicted variance. Parameter degeneracies arise since the response of the matter power spectrum to $\delta_b$ and cosmological parameters share similar properties in changing the growth of structure and dilating the scale of features especially in the local case. For matter power spectrum measurements, these degeneracies can lead in certain cases to substantial error degradation and motivates future studies of specific cosmological observables such as galaxy clustering and weak lensing statistics with these techniques.