Miracle-dz/UniFAR-FTUs huggingface dataset:
The Projection of Development: Cinematic Representation as A(nother) Source of Authoritative Knowledge?

Abstract Popular representations of development need to be taken seriously (though not uncritically) as sources of authoritative knowledge, not least because this is how most people in the global North (and elsewhere) ‘encounter’ development issues. To this end, and building on the broader agenda presented in a previous article exploring the usefulness of literary representations of development, we consider three different types of cinematic representations of development: films providing uniquely instructive insights, those unhelpfully eliding and simplifying complex processes, and those that, with the benefit of historical hindsight, usefully convey a sense of the prevailing assumptions that guided and interpreted the efficacy of development-related interventions at a particular time and place. We argue that the commercial and technical imperatives governing the production of contemporary films, and ‘popular’ films in particular, generate a highly variable capacity to ‘accurately’ render key issues in development, and thereby heighten their potential to both illuminate and obscure those issues.
The Value Relevance of Earnings and Income Smoothing: Greek Evidence on Causality Effects

The present paper examines the existence of causality between income smoothing and value relevance of earnings for a sample of firms listed in the Athens Stock Exchange. Using a switching regression model we find evidence suggesting that the low information content of earnings may be a motive for managers to engage in actions that signal the existence of income smoothing. A potential explanation for our results is that management uses income smoothing in order to maximize its utility rather than to affect investors expectations about the future prospects of the firm in the market.
Hydrology and Earth System Sciences Uncertainties on Mean Areal Precipitation: Assessment and Impact on Streamflow Simulations

This paper investigates the influence of mean areal rainfall estimation errors on a specific case study: the use of lumped conceptual rainfall-runoff models to simulate the flood hydrographs of three small to medium-sized catchments of the upper Loire river. This area (3200 km 2) is densely covered by an operational network of stream and rain gauges. It is frequently exposed to flash floods and the improvement of flood forecasting models is then a crucial concern. Particular attention has been drawn to the development of an error model for rainfall estimation consistent with data in order to produce realistic streamflow simulation uncertainty ranges. The proposed error model combines geo-statistical tools based on kriging and an autoregressive model to account for temporal dependence of errors. It has been calibrated and partly validated for hourly mean areal precipitation rates. Simulated error scenarios were propagated into two calibrated rainfall-runoff models using Monte Carlo simulations. Three catchments with areas ranging from 60 to 3200 km 2 were tested to reveal any possible links between the sensitivity of the model outputs to rainfall estimation errors and the size of the catchment. The results show that a large part of the rainfall-runoff (RR) modelling errors can be explained by the uncertainties on rainfall estimates, especially in the case of smaller catchments. These errors are a major factor limiting accuracy and sharpness of rainfall-runoff simulations, and thus their operational use for flood forecasting.
A Two-Component Language for Adaptation: Design, Semantics and Program Analysis

Adaptive systems are designed to modify their behaviour in response to changes of their operational environment. We propose a two-component language for adaptive programming, within the Context-Oriented Programming paradigm. It has a declarative constituent for programming the context and a functional one for computing. We equip our language with a dynamic formal semantics. Since wrong adaptation could severely compromise the correct behaviour of applications and violate their properties, we also introduce a two-phase verification mechanism. It is based on a type and effect system that type-checks programs and computes, as an effect, a sound approximation of their behaviour. The effect is exploited at load time to mechanically verify that programs correctly adapt themselves to all possible running environments.
Antibody Engineering as Opportunity for Selection and Optimization of Anti- HIV Therapeutic Agents

Since among patients who receive care for HIV-1 infection, the prevalence of antiretroviral drug resistance is 50%, clearly, new approaches to control viral replication are needed. A hundred years later the first proposal of a magic bullet by Paul Ehrlich antibody -based therapeutics currently enjoys unprecedented success. The methodologies devel- oped in these years such as antibody library, phage display, single domain antibody and the possibility to modify the al- ready well-studied antibodies in a way to render them more suitable for the specific purpose, make antibody a different and valid alternative therapy. Four human\humanized antibodies for anti HIV treatment are currently in clinical trial with some promising results. They target different antigens: the gp120 of the viral coat and the receptor or co-receptor of the virus. The development of therapeutic antibody in HIV field is progressing slowly but today, the improvement in the knowledge of antibody structure and function together with advances in protein engineering can be used to reshape anti- body molecules and devise strategies to obtain more suitable antibody for therapy.
Residential segregation and black-white intermarriage

I use 1980, 1990, and 2000 Census data to show that greater residential segregation is associated with a lower probability that black men, black women, white men, and white women are in black-white marriages. This negative relationship grows stronger among whites and remains constant among blacks when I control for local marriage market characteristics. Plausible explanations for the results are discussed and investigated.
Sentencing Guidelines: Lessons from Pennsylvania

Understanding Sentencing. Constructing Pennsylvania's Sentencing Guidelines. Pennsylvania's Commission Meets New Challenges. Sentencing Serious Violent Offenders. Racial, Ethnic, and Gender Disparity. Location Matters: Variation Among Counties. Guilty Pleas vs. Trial Convictions: Unwarranted Disparity? Guidelines and Mandatory Minimums. Can Guidelines Change Sentencing Practices? Lessons from Pennsylvania's Struggle for Justice.
Pose recovery for a mobile manipulator using a particle filter

A multirobot system composed by a five DoF manipulator (SCORTEC-ER 1) and a mobile base (ATRV-Jr by iRobot) is considered. The system is equipped with uniform software architecture able to control the motion of both components. Some exteroceptive sensors like sonars and laser rangefinders are available on the mobile platform, some others are mounted on the end-effector of the manipulator: a colour camera, able to locate objects to operate with; an ultrasound range finder, near the camera, that will be used to get distance measures. In this paper we consider the problem of relocalising the mobile manipulator in a known environment supposing that no base movement is allowed to avoid hazard operations. As only the arm can be safely panned to explore the surroundings, the proposed procedure is based exclusively on the ultrasound rangefinder. Using such measures, and making the hypothesis that the arm configuration in known, a Monte Carlo filter is designed to estimate the base pose. Such multiple hypotheses filter is appropriate in this kind of problems where, in the best case, it is possible to retrieve a finite number of possible poses compatible with available measures
A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications

In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively.
Bidirectional Regulation of Innate and Learned Behaviors That Rely on Frequency Discrimination by Cortical Inhibitory Neurons

The ability to discriminate tones of different frequencies is fundamentally important for everyday hearing. While neurons in the primary auditory cortex (AC) respond differentially to tones of different frequencies, whether and how AC regulates auditory behaviors that rely on frequency discrimination remains poorly understood. Here, we find that the level of activity of inhibitory neurons in AC controls frequency specificity in innate and learned auditory behaviors that rely on frequency discrimination. Photoactivation of parvalbumin-positive interneurons (PVs) improved the ability of the mouse to detect a shift in tone frequency, whereas photosuppression of PVs impaired the performance. Furthermore, photosuppression of PVs during discriminative auditory fear conditioning increased generalization of conditioned response across tone frequencies, whereas PV photoactivation preserved normal specificity of learning. The observed changes in behavioral performance were correlated with bidirectional changes in the magnitude of tone-evoked responses, consistent with predictions of a model of a coupled excitatory-inhibitory cortical network. Direct photoactivation of excitatory neurons, which did not change tone-evoked response magnitude, did not affect behavioral performance in either task. Our results identify a new function for inhibition in the auditory cortex, demonstrating that it can improve or impair acuity of innate and learned auditory behaviors that rely on frequency discrimination.
Differences in Visual Field Bias in Emotional Attribution Tasks Between Children with Autism Spectrum Disorders and Typical Development

Autism spectrum disorders (ASD) are characterized by social deficits in emotional comprehension. Since typical emotional attribution improves when using the left visual field, effects of lateralization on facial affect assessment were compared between children with ASD, pervasive developmental disorder not otherwise specified (PDD-NOS) and typical development (TD). The ASD group showed significantly lower percent accuracy, longer response time and slower pulse rate than the TD group. Within the ASD group, there was a significant right visual field bias in emotional attribution tasks, which contrasted with the left visual field bias seen within the TD group. The PDD-NOS group demonstrated no visual field advantage. Emotional attribution tasks could be an assessment tool to differentially diagnose disorders within the autism spectrum.
Formant tracking using context-dependent phonemic information

A new formant-tracking algorithm using phoneme information is proposed. Conventional formant-tracking algorithms obtain formant tracks by analyzing the acoustic speech signal using continuity constraints without any additional information. The formant-tracking error rate of the conventional methods is reportedly in the range of 10%-20%. In this paper, we show that if text or phoneme transcription of speech utterances is available, the error rate can be significantly reduced. The basic idea behind this approach is that given the phoneme identity, formant-tracking algorithms can have a better clue of where to look for formants. The algorithm consists of three phases: 1) analysis, 2) segmentation and alignment, and 3) formant tracking by the Viterbi searching algorithm. In the analysis phase, formant candidates are obtained for each analysis frame by solving the linear prediction polynomial. In the segmentation and alignment phase, the text corresponding to the input speech utterance is converted into a sequence of phoneme symbols. Then, the phoneme sequence is time aligned with the speech utterance. A hidden Markov model (HMM) based automatic segmentation algorithm is used for forced-time alignment. For each phoneme segment, nominal formant frequencies are assigned at the center of each phoneme segment. Then nominal formant tracks for the entire utterance are obtained by interpolating the nominal formant frequencies. In order to compensate for the coarticulation effect, different interpolation methods are used depending on the phonemic context. The interpolation process makes the formant-tracking algorithm robust to possible segmentation errors made by the HMM-based segmentation algorithm. As a result, the proposed formant-tracking algorithm does not require highly accurate alignment/segmentation. Finally, a set of formants is chosen from the formant candidates in such a way that the resulting formant tracks come close to the nominal formant tracks while satisfying the continuity constraints. The algorithm is tested using natural speech utterances and the performance is compared against formant tracks obtained by the conventional method using continuity constraints only. The new algorithm significantly reduces the formant-tracking error rate (5.03% for male and 3.73% for female) over the conventional formant-tracking algorithm (13.00% for male and 15.82% for female).
How to Kill Two Birds With One Transgenic Pig

Islet transplantation promises to provide safe, long-lasting insulin independence to individuals with diabetes. Yet the need for lifelong immunosuppression coupled with a vastly insufficient supply of donor tissue continues to prevent the widespread application of this approach to treating diabetes. A study (1) in this issue of Diabetes describes significant progress in addressing both of these issues. Porcine islets have long been touted as a potentially unlimited source of transplantable islet tissue. Porcine and human insulin are highly homologous, and until the late 1970s, with the advent of recombinant protein technology, porcine insulin was routinely injected into humans with diabetes. However, the transplantation of porcine tissue has not proven to be so straightforward. Over the past decade, nonhuman primate studies demonstrated that a strong immunosuppression protocol was required to avoid rejection of porcine islet xenografts (2,3). Consequently, although the use of porcine islets would overcome the issue of tissue supply, their use would be tantamount to patients trading insulin injections for strong immunosuppression—not an attractive clinical solution for many. In the current study, Klymiuk et al. (1) developed transgenic pigs that express an immunomodulatory fusion protein under the control of the insulin promoter. These animals produce the immunosuppressant protein locally upon activation of the insulin promoter within β-cells, but do not appear systemically immunosuppressed, …
Service Mosaic: A Model-Driven Framework for Web Services Life-Cycle Management

Although Web services provide abstractions for simplifying integration at lower levels of the interaction stacks, they don't yet help simplify integration at higher abstraction levels such as business-level interaction protocols. Using a model-driven framework for Web services life-cycle management, the authors help facilitate the scalable development and maintenance of service-oriented applications by analyzing and managing Web service business protocols. Instead of using simple black and white measures, they identify different classes of protocol compatibility and replaceability. They implemented this framework in a prototype platform called Service Mosaic
Local Document Relevance Clustering in IR Using Collocation Information

A series of different automatic query expansion techniques has been suggested in Information Retrieval. To estimate how suitable a document term is as an expansion term, the most popular of them use a measure of the frequency of the co-occurrence of this term with one or several query terms. The benefit of the use of the linguistic relations that hold between query terms is often questioned. If a linguistic phenomenon is taken into account, it is the phrase structure or lexical compound. We propose a technique that is based on the restricted lexical cooccurrence (collocation) of query terms. We use the knowledge on collocations formed by query terms for two tasks: (i) document relevance clustering done in the first stage of local query expansion and (ii) choice of suitable expansion terms from the relevant document cluster. In this paper, we describe the first task, providing evidence from first preliminary experiments on Spanish material that local relevance clustering benefits largely from knowledge on collocations.
Drop*STAR: support system of musical arrangement and performance for small groups

The purpose of this study is to make users enjoy musical performance like a band regardless of skill level on musical instruments. Other studies have focused on only beginners or only experts [1] [5] [4]. Very few attempts have been made at our purpose. Our system consists of miniature stage and dolls as players. When users move dolls on the stage, sound changes with corresponding dolls' motion and position. If users play in concert, users enjoy not only instruments or music but also talking about the course of performance and practice process. Band members often practice with making conditioning in order to make their songs better. If users use this system, they discuss the mood and flow of their music, practice their timing to play under their policy, keep a good balance between instruments and contrive ways to move their dolls. And they will show off their playing prowess. In the process, users are able to experience performance like a band. We call this system Drop*STAR (<u>D</u>olls <u>R</u>hythmic Po<u>p</u> <u>Stars</u>).
Atmospheric Chemistry and Physics Cloud Optical Thickness and Liquid Water Path – Does the K Coefficient Vary with Droplet Concentration?

Cloud radiative transfer calculations in general circulation models involve a link between cloud microphys-ical and optical properties. Indeed, the liquid water content expresses as a function of the mean volume droplet radius, while the light extinction is a function of their mean surface radius. There is a small difference between these two parameters because of the droplet spectrum width. This issue has been addressed by introducing an empirical multiplying correction factor to the droplet concentration. Analysis of in situ sampled data, however, revealed that the correction factor decreases when the concentration increases, hence partially mitigating the aerosol indirect effect. Five field experiments are reanalyzed here, in which standard and upgraded versions of the droplet spectrometer were used to document shallow cumulus and stratocumulus topped boundary layers. They suggest that the standard probe noticeably underestimates the correction factor compared to the upgraded versions. The analysis is further refined to demonstrate that the value of the correction factor derived by averaging values calculated locally along the flight path overestimates the value derived from liquid water path and optical thickness of a cloudy column, and that there is no detectable relationship between the correction factor and the droplet concentration. It is also shown that the droplet concentration dilution by entrainment-mixing after CCN activation is significantly stronger in shallow cumuli than in stra-tocumulus layers. These various effects are finally combined to produce the today best estimate of the correction factor to use in general circulation models.
Finding Relevant Web Pages Through Equivalent Hyperlinks

Finding pages on the web that are relevant to some user-defined criteria is a longestablished area of research. Early work on search engines concentrated on the textual content of web pages to find relevant pages, but in recent years, the analysis of information encoded in hyperlinks has been used to vastly improve search engine performance. This paper presents a variation on the use of link analysis for automatically categorizing web pages, by defining a similarity measure and search technique based on hyperlinks. This measure is used to categorize hyperlinks themselves, rather than web pages. This allows us to, given a particular hyperlink, to find others like it in terms of its context and referred-to web pages. We have implemented a prototype version of the technique as a browser application. Initial tests appear to show that the method, as implemented in our browser, returns precise, well-focussed results.
Determining the Optimal Redistribution for a Given Data Partition

The classical redistribution problem aims at optimally scheduling communications when moving from an initial data distribution to a target distribution where each processor will host a subset of data items. However, modern computing platforms are equipped with a powerful interconnection switch, and the cost of a given communication is (almost) independent of the location of its sender and receiver. This leads to generalizing the redistribution problem as follows: find the optimal one-toone mapping of the subsets of data items onto the processors for which the cost of the redistribution is minimal. This paper studies the complexity of this generalized problem. We provide optimal algorithms and evaluate their gain over classical redistribution through simulations. We also show the NP-hardness of the problem to find the optimal data partition and processor permutation (defined by new subsets) that minimize the cost of redistribution followed by a simple computation kernel.
The star formation region NGC 6530: Distance, ages and initial mass function

We present astrometry and BV I photometry, down to V � 22, of the very young open cluster NGC 6530, obtained from observations taken with the Wide Field Imager camera at the MPG/ESO 2.2 m Telescope. Both the V vs. B − V and the V vs. V − I color−magnitude diagrams (CMD) show that the upper main sequence is dominated by very bright cluster stars, while, because of the high obscuration of the giant molecular cloud surrounding the cluster, the blue envelopes of the diagrams at V 14 are limited to the main sequence stars at the distance of NGC 6530. This particular structure of the NGC 6530 CMD allows us to conclude that its distance is about d � 1250 pc, significantly lower than the previous determination of d = 1800 pc. We have positionally matched our optical catalog with the list of X-ray sources found in a Chandra-ACIS observation, finding a total of 828 common stars, 90% of which are pre-main sequence stars in NGC 6530. Using evolutionary tracks of Siess et al. (2000), mass and age values are inferred for these stars. The median age of the cluster is about 2.3 Myr; in the mass range (0.6−4.0) M� , the Initial Mass Function (IMF) shows a power law index x = 1.22 ± 0.17, consistent with both the Salpeter index (1.35), and with the index derived for other young clusters; towards smaller masses the IMF shows a peak and then it starts to decrease.