Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Look at Care in Pregnancy: Simple, Effective Interventions for Neglected Populations

Background Although this is beginning to change, the content of antenatal care has been relatively neglected in safe-motherhood program efforts. This appears in part to be due to an unwarranted belief that interventions over this period have far less impact than those provided around the time of birth. In this par, we review available evidence for 21 interventions potentially deliverable during pregnancy at high coverage to neglected populations in low income countries, with regard to effectiveness in reducing risk of: maternal mortality, newborn mortality, stillbirth, prematurity and intrauterine growth restriction. Selection was restricted to interventions that can be provided by non-professional health auxiliaries and not requiring laboratory support. Methods In this narrative review, we included relevant Cochrane and other systematic reviews and did comprehensive bibliographic searches. Inclusion criteria varied by intervention; where available randomized controlled trial evidence was insufficient, observational study evidence was considered. For each intervention we focused on overall contribution to our outcomes of interest, across varying epidemiologies. Results In the aggregate, achieving high effective coverage for this set of interventions would very substantially reduce risk for our outcomes of interest and reduce outcome inequities. Certain specific interventions, if pushed to high coverage have significant potential impact across many settings. For example, reliable detection of pre-eclampsia followed by timely delivery could prevent up to ¼ of newborn and stillbirth deaths and over 90% of maternal eclampsia/pre-eclampsia deaths. Other interventions have potent effects in specific settings: in areas of high P falciparum burden, systematic use of insecticide-treated nets and/or intermittent presumptive therapy in pregnancy could reduce maternal mortality by up to 10%, newborn mortality by up to 20%, and stillbirths by up to 25–30%. Behavioral interventions targeting practices at birth and in the hours that follow can have substantial impact in settings where many births happen at home: in such circumstances early initiation of breastfeeding can reduce risk of newborn death by up to 20%; good thermal care practices can reduce mortality risk by a similar order of magnitude. Conclusions Simple interventions delivered during pregnancy have considerable potential impact on important mortality outcomes. More programmatic effort is warranted to ensure high effective coverage.
Workshop on job and worker flows 15-16 November 2012 , Kyoto W ORKER FLOWS AND ESTABLISHMENT WAGE DIFFERENTIALS : A BREAK DOWN OF THE RELATIONSHIP

We address the relation between establishment wage differentials and worker flows, i.e., the churning rate and the quit rate. Our analysis is based on a linked employeremployee dataset covering the French private sector from 2002 to 2005. Our estimations support the hypothesis that wage premium is an effi ci nt human resource management tool to stabilize workers: churning rates are lower in high -paying firms due to lower quit rates. We further show that the relation is not linear, and i t iffers among skill groups and according to establishment size: it is strongest for low-wage le vels, for low-skilled workers and in large establishments.
Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models

The steady growth of graph data from social networks has resulted in wide-spread research in finding solutions to the influence maximization problem. In this paper, we propose a holistic solution to the influence maximization (IM) problem. (1) We introduce an opinion-cum-interaction (OI) model that closely mirrors the real-world scenarios. Under the OI model, we introduce a novel problem of Maximizing the Effective Opinion (MEO) of influenced users. We prove that the MEO problem is NP-hard and cannot be approximated within a constant ratio unless P=NP. (2) We propose a heuristic algorithm OSIM to efficiently solve the MEO problem. To better explain the OSIM heuristic, we first introduce EaSyIM - the opinion-oblivious version of OSIM, a scalable algorithm capable of running within practical compute times on commodity hardware. In addition to serving as a fundamental building block for OSIM, EaSyIM is capable of addressing the scalability aspect - memory consumption and running time, of the IM problem as well. Empirically, our algorithms are capable of maintaining the deviation in the spread always within 5% of the best known methods in the literature. In addition, our experiments show that both OSIM and EaSyIM are effective, efficient, scalable and significantly enhance the ability to analyze real datasets.
Latency-avoiding Dynamic Optical Circuit Prefetching Using Application-specific Predictors

Optical circuits are capable of providing large bandwidth improvements relative to electrical-switched networks in high-performance computing (HPC) systems. However, due to the circuit switching nature of optical systems, setup delays may prevent HPC systems from fully utilizing the available bandwidth. This paper proposes an applicationguided circuit management technique that can achieve latency-avoiding dynamic reconfiguration, better leveraging the high-bandwidth photonics and accelerating system performance. By learning the temporal locality and communication patterns from upper-layer applications, the technique not only caches a set of circuits to maximize reuse, but also prefetches predicted circuits to actively hide the setup latency. We apply the technique to communication patterns from a spectrum of science and engineering applications. The results show that setup delays via circuit misses are significantly reduced, showing how the proposed technique can improve circuit switching in HPC optical interconnects.
H2 optimal semistable control for linear dynamical systems: An LMI approach

In this paper, we develop H2 semistability theory for linear dynamical systems. Using this theory, we design H2 optimal semistable controllers for linear dynamical systems. Unlike the standard H2 optimal control problem, a complicating feature of the H2 optimal semistable stabilization problem is that the closed-loop Lyapunov equation guaranteeing semistability can admit multiple solutions. An interesting feature of the proposed approach, however, is that a least squares solution over all possible semistabilizing solutions corresponds to the H2 optimal solution. It is shown that this least squares solution can be characterized by a linear matrix inequality minimization problem.
Relaxations for Combinatorial Relaxation

Last week, we talked about submodular functions and showed a way to relax them to convex functions via the Lovasz Theorem. The idea was that, if we could optimize the Lovasz Extension, which is a continuous convex optimization problem, then we could optimize submodular functions. Today, we’re going to be doing something very similar to that with one exception: the problems we’ll try to approximate aren’t easy to solve. In general, we’ll focus on NP-hard combinatorial optimization problems, which we’ll approximate using similar relaxations.
New Vision, Broader Scope, and Same Commitment to Transformation among Higher Educators and Practitioners

In this inaugural introduction, new editors for the Journal of Transformative Learning offer the vision, scope, and continued commitment to the journal’s presence as a resource for research and dialogue on transformative learning. The co-editors share the journal’s structure and upcoming special issue opportunities along with brief summaries of articles in the current volume.
Workplace Violence and Job Performance among Community Healthcare Workers in China: The Mediator Role of Quality of Life

Objective: To explore the impact of workplace violence on job performance and quality of life of community healthcare workers in China, especially the relationship of these three variables. Methods: From December 2013 to April 2014, a total of 1404 healthcare workers were recruited by using the random cluster sampling method from Community Health Centers in Guangzhou and Shenzhen. The workplace violence scale, the job performance scale and the quality of life scale (SF-36) were self-administered. The structural equation model constructed by Amos 17.0 was employed to assess the relationship among these variables. Results: Our study found that 51.64% of the respondents had an experience of workplace violence. It was found that both job performance and quality of life had a negative correlation with workplace violence. A positive association was identified between job performance and quality of life. The path analysis showed the total effect (β = −0.243) of workplace violence on job performance consisted of a direct effect (β = −0.113) and an indirect effect (β = −0.130), which was mediated by quality of life. Conclusions: Workplace violence among community healthcare workers is prevalent in China. The workplace violence had negative effects on the job performance and quality of life of CHCs’ workers. The study suggests that improvement in the quality of life may lead to an effective reduction of the damages in job performance caused by workplace violence.
Automatic Raaga Identification System for Carnatic Music Using Hidden Markov Model

As for as the Human Computer Interactions (HCI) is concerned, there is broad range of applications in the area of research in respective of Automatic Melakarta Raaga Identification in music. The pattern of identification is the main object for which, the basic mathematical tool is utilized. On verification, it is observed that no model is proved consistently and effectively to be predicted in its classification. This paper is, therefore, introduces a procedure for Raaga Identification with the help of Hidden Markov Models (HMM) which is rather an appropriate approach in identifying Melakarta Raagas. This proposed approach is based on the standard speech recognition technology by using Hidden continuous Markov Model. Data is collected from the existing data base for training and testing of the method with due design process relating to Melakarta Raagas. Similarly, to solve the problem of automatic identification of raagas, a suitable approach from the existing database is presented. The system, particularly, this model is based on a Hidden Markov Model enhanced with Pakad string matching algorithm. The entire system is built on top of an automatic note transcriptor. At the end, detailed elucidations of the experiments are given. It clearly indicates the effectiveness and applicability of this method with its intrinsic value and significance.
Etude de l'ordonnancement conjoint de tâches et de messages : application à l'exécutif OSEK/VDX et au réseau CAN

Dans les systemes temps reel, les tâches et les messages sont en principe ordonnances grâce a leur priorite. Une fois ces priorites affectees et connaissant les caracteristiques des tâches, du reseau et des messages, on sait calculer analytiquement le pire temps de reponse de ces tâches et celui des messages. Cependant, contrairement au cas uniprocesseur, il n'existe pas d'algorithme optimal pour affecter ces proprietes dans le cas distribue. En effet, les calculs du pire temps de reponse des tâches et des messages sont interdependants. On parle alors de transactions, lorsque des messages et des tâches sont lies : d'une part les messages sont toujours crees par les tâches et d'autre part certaines tâches sont activees par des messages. Le calcul des temps de reponse dans le pire cas de ces transactions necessite alors la connaissance globale du systeme. l'utilisation d'algorithmes genetiques couplee a celles d'heuristiques permet pour des systemes complexes de trouver une ou plusieurs solutions verifiant les contraintes temporelles du systeme.
Decomposing CAD models of objects of daily use and reasoning about their functional parts

Today's robots are still lacking comprehensive knowledge bases about objects and their properties. Yet, a lot of knowledge is required when performing manipulation tasks to identify abstract concepts like a “handle” or the “blade of a spatula” and to ground them into concrete coordinate frames that can be used to parametrize the robot's actions. In this paper, we present a system that enables robots to use CAD models of objects as a knowledge source and to perform logical inference about object components that have automatically been identified in these models. The system includes several algorithms for mesh segmentation and geometric primitive fitting which are integrated into the robot's knowledge base as procedural attachments to the semantic representation. Bottom-up segmentation methods are complemented by top-down, knowledge-based analysis of the identified components. The evaluation on a diverse set of object models, downloaded from the Internet, shows that the algorithms are able to reliably detect several kinds of object parts.
Comparing the Difficulty of Tasks Using Eye Tracking Combined with Subjective and Behavioural Criteria

In this article, we attempted to examine the issue of the existence of differences in eye move-ment of school-age students as they solve tasks of different difficulty levels in the sciences and natural sciences (computer science, mathematics, physics, biology). Categories of the task’s difficulty level were established on the basis of two types of criteria: subjective (an evaluation made by the subjects) and behavioural (connected to the correctness of their solution). The relationships of these criteria with the visual activity parameters, which were considered to be indicators of mental effort, were identified. An analysis of the data obtained enabled the observation of discrepancies in categorizing difficulties of the tasks on the basis of subjective and behavioural criteria. A significant and strong correlation was noticed between task difficulty level, determined by the percentage of correct answers, and the fixation parameters, although such a relationship with the blink parameters was not found. There was no correlation of the activity of the eye movement parameters, considered to be mental effort indicators, with a student’s opinion about the task’s difficulty level. On the basis of the investigations made, it can be stated that the fixation duration average can be taken as an index of the difficulty level of the task being solved.
Stochastic modelling of animal movement

Modern animal movement modelling derives from two traditions. Lagrangian models, based on random walk behaviour, are useful for multi-step trajectories of single animals. Continuous Eulerian models describe expected behaviour, averaged over stochastic realizations, and are usefully applied to ensembles of individuals. We illustrate three modern research arenas. (i) Models of home-range formation describe the process of an animal ‘settling down’, accomplished by including one or more focal points that attract the animal's movements. (ii) Memory-based models are used to predict how accumulated experience translates into biased movement choices, employing reinforced random walk behaviour, with previous visitation increasing or decreasing the probability of repetition. (iii) Lévy movement involves a step-length distribution that is over-dispersed, relative to standard probability distributions, and adaptive in exploring new environments or searching for rare targets. Each of these modelling arenas implies more detail in the movement pattern than general models of movement can accommodate, but realistic empiric evaluation of their predictions requires dense locational data, both in time and space, only available with modern GPS telemetry.
An Approximated Principal Component Prediction Model for Continuous-time Stochastic Processes

SUMMARY In this paper, a linear model for forecasting a continuous-time stochastic process in a future interval in terms of its evolution in a past interval is developed. This model is based on linear regression of the principal components in the future against the principal components in the past. In order to approximate the principal factors from discrete observations of a set of regular sample paths, cubic spline interpolation is used. An application for forecasting tourism evolution in Granada is also included.
Referent control of action and perception: Challenging conventional theories in behavioral neuroscience

This book provides a long-awaited description of a classic motor control theory of action and perception referent control. Strictly based on experimental material, this theory places action and perception in the context of physical laws to offer solutions of several classical problems in behavioral neuroscience and neurological pathologies. The author re-visits and refines many basic concepts in behavioral neuroscience, including central pattern generators, reflexes, and motor learning. Further, he provides many examples of how task-specific referent control of action and perception can be accomplished by the nervous system. This information may help researchers design theory-driven experiments that address the question of how actions are controlled and how changes in biomechanical characteristics emerge without pre-programming. This book may be interesting to researchers, students in behavioral neurosciences as well as to a broader audience who want to know how action and perception are accomplished by the nervous system
Robustness, Stability and Efficiency of Phage lambda Gene Regulatory Network: Dynamical Structure Analysis

Based on our physical and biological studies we have recently developed a mathematical framework for the analysis of nonlnear dynamics. We call this framework the dynamical structure analysis. It has four dynamical elements: potential landscape, transverse matrix, descendant matrix, and stochastic drive. In particular, the importance and the existence of the potential landscape is emphasized. The dynamical structure analysis is illustrated in detail by the study of stability, robustness, and efficiency of the simplest gene regulatory network of phage lambda.
The Limiting Effects of Dust in Brown Dwarf Model Atmospheres

We present opacity sampling model atmospheres, synthetic spectra, and colors for brown dwarfs and very low mass stars in the following two limiting cases of dust grain formation: (1) Inefficient gravitational settling (i.e., the dust is distributed according to the chemical equilibrium predictions) and (2) efficient gravitational settling (i.e., the dust forms and depletes refractory elements from the gas, but their opacity does not affect the thermal structure). The models include the formation of over 600 gas-phase species and 1000 liquids and crystals and the opacities of 30 different types of grains including corundum (Al2O3), the magnesium aluminum spinel MgAl2O4, iron, enstatite (MgSiO3), forsterite (Mg2SiO4), amorphous carbon, SiC, and a number of calcium silicates. The models extend from the beginning of the grain formation regime well into the condensation regime of water ice (Teff = 3000-100 K) and encompass the range of log g = 2.5-6.0 at solar metallicity. We find that silicate dust grains can form abundantly in the outer atmospheric layers of red and brown dwarfs with a spectral type later than M8. The greenhouse effects of dust opacities provide a natural explanation for the peculiarly red spectroscopic distribution of the latest M dwarfs and young brown dwarfs. The grainless (cond) models, on the other hand, correspond closely to methane brown dwarfs such as Gliese 229B. We also discover that the λλ5891, 5897 Na I D and λλ7687, 7701 K I resonance doublets play a critical role in T dwarfs, in which their red wings define the pseudocontinuum from the I to the Z bandpass.
Design of a Certifying Compiler Supporting Proof of Program Safety

Safety is an important property of high-assurance software, and one of the hot research topics on it is the verification method for software to meet its safety policies. In our previous work, we designed a pointer logic system and proposed a framework for developing and verifying safety critical programs. And in this paper, we present the design and implementation of a certifying compiler based on that framework. Here we will mainly explain verification condition generation, generation of code and assertions, and proof generation for basic blocks. Our certifying compiler has the following novelties: 1) it supports a programming language equipped with both a type system and a logic system; 2) and it can produce safety proofs for programs with pointers.
LONG RANGE INSPECTION OF RAIL USING GUIDED WAVES - FIELD EXPERIENCE

Ultrasonic techniques have been used for many years for the inspection of rail. These measurements can detect the presence of a wide variety of defects but there are practical difficulties with the technology. While large transverse cracks of the type likely to cause catastrophic failure can be detected, the large, critical defects can be masked by large numbers of small, surface defects along the length of the rail. It would be very useful to be able to determine reliably the largest defect size in a length of rail. Also alumino-thermic welds are difficult to inspect due to the typical defect orientation and the attenuation of the weld material. Guided waves provide a very attractive solution to these problems; they travel along the rail, for tens or hundreds of metres, and are partially reflected by any defects which are present. They are particularly sensitive to vertical defects and they are used at relatively low frequency so they are not significantly attenuated by weld material. With financial support from Network Rail, the authors have developed a practical inspection tool based on guided wave measurements. This paper describes the design of a pre-production prototype guided wave instrument suitable for site trials. Results obtained at a level crossing are presented that demonstrate the use of the system as a practical screening tool. For the covering abstract see ITRD E123761.
An algorithm for petro-graphic colour image segmentation used for oil exploration

We propose a new heuristic algorithm for porosity segmentation for the coloured petro-graphic images. The proposed algorithm automatically detects the porosities that represent the presence of oil, gas or even water in the analyzed thin section rock segment based on the colour of the porosity area filled with dies in the analyzed sample. For the purpose of the oil exploration the thin section fragments are died in order to emphasize the porosities that are analyzed under the microscope. The percentage of the porosity is directly proportional to the probability of the oil, gas or even water presence in the area where the drilling is performed, i.e. the increased porosity indicates the higher probability of oil existence in the region. The proposed automatic algorithm shows better results to the existing K-means segmentation method.
Critical Discourse Analysis of Student Responses to Teacher Feedback on Student Writing

This study explores the genre of ‘student response to teacher feedback’ and analyzes students’ responses through the framework of critical discourse analysis (CDA). Drawing on CDA as a theoretical framework, we examined the structural, interactional, and interdiscursive features of the students’ comments and investigated relations between the text, interaction, and context. The structural analysis indicates that the students’ comments demonstrate their emerging academic literacy skills. Our interactional analysis shows that most students took on an active role as a good student and a hard-working writer, but some students exerted their agency by taking an opportunity to resist the authority of the teacher while others rejected it altogether. Our interdiscursive analysis illustrates that students used not only language from the teacher’s comments, but also metalanguage of the composition classroom to formulate their responses. Based on our findings, we discuss implications for teaching practices and future research on students’ responses to teacher feedback.