Miracle-dz/UniFAR-FTUs huggingface dataset:
Women leadership barriers in healthcare, academia and business

Purpose The purpose of this paper is to map the barriers to women leadership across healthcare, academia and business, and identify barriers prevalence across sectors. A barriers thematic map, with quantitative logic, and a prevalence chart have been developed, with the aim to uncover inequalities and provide orientation to develop inclusion and equal opportunity strategies within different work environments. Design/methodology/approach A systematic literature review method was adopted across five electronic databases. Rigorous inclusion/exclusion criteria were applied to select relevant publications, followed by critical appraisal of the eligible articles. The geographical target was Europe, with a publication time range spanning the period from 2000 to 2015. Certain specialized international studies were also examined. The key themes were identified using summative content analysis and the findings were analyzed using qualitative meta-summary method to formulate hypotheses for subsequent research. Findings In total, 26 barriers were identified across the aforementioned sectors. A high degree of barriers commonalities was identified, with some striking differences between the prevalence of barriers across sectors. Research limitations/implications The results of this study may need further validation using statistical methodology given the knowledge base gaps regarding the range of barriers and the differences in their prevalence. Bias and interpretation in reporting anchored in different theoretical frameworks ought to be further examined. Additional variables such as ambiguously stated barriers, sector overlap, women’s own choices, cultural and educational background and analysis in the context of the economic crisis, ensuing austerity and migratory pressure, are also worth exploring. Practical implications Women’s notable and persisting underrepresentation in top leading positions across sectors reflects a critical drawback in terms of organizational and societal progress particularly regarding inclusion and balanced decision making. Practice-related blind spots may need to be further examined and addressed through specific policies. Originality/value The comparative nature of barriers to women leadership across three sectors allows the reader to contrast the differences in gender inequalities and to comprehend inclusion challenges in healthcare, academia and business. The authors draw attention to varying degrees of barriers prevalence that have been understudied and deserve to be further explored. This gap in knowledge extends to policy, thus, highlighting the need to address the gender equality and inclusion challenges in a context-specific manner across work environments.
Antiprotozoal Activities of Millettia richardiana (Fabaceae) from Madagascar

With at least 60% of the Millettia species (Fabaceae) being in medicinal use, we found it relevant to assess the potential antiprotozoal and antifungal activities of Millettia richardiana. Water and methanol crude extracts of the stem barks from M. richardiana and the six fractions resulting from the fractionation of the methanol extract were tested. The dichloromethane extracted fraction showed the best in vitro antiprotozoal activities (IC50 = 5.8 μg/mL against Plasmodium falciparum, 11.8 μg/mL against Leishmania donovani and 12.8 μg/mL against Trypanosoma brucei brucei) as well as low cytotoxicity on several cell lines. The phytochemical analysis showed this selected fraction to be rich in terpenoids and alkaloids, which could explain its antiparasitic activity. A phytochemical study revealed the presence of lonchocarpenin, betulinic acid, β-amyrin, lupeol, palmitic acid, linoleic acid and stearic acid, among which betulinic acid and lupeol could be the compounds responsible of these antiprotozoal activities. By contrast, neither the crude extracts nor the fractions showed antifungal activity against Candida. These results confirm the importance of the genus Millettia in Malagasy ethnomedicine, its potential use in antiparasitic therapy, and the interest of developing a sustainable exploitation of this plant. Moreover, both molecules betulinic acid and lupeol appeared as very relevant molecules for their antiprotozoal properties.
Efficient node reconfiguration in mobile ad hoc networks (MANETs) for wireless internet access point connection

In this paper, we consider a multi-hop network where a mobile node can operate as a host as well as a router, helping other mobile nodes to connect to the access point. We propose a network reconfiguration algorithm to re-establish connections between mobile nodes, to achieve load-balancing for wireless access network. The current network topology is ignored, and by taking into consideration the mobility of nodes and the traffic load at access points, the destination node selects the best route to reach the access point. The proposed algorithm also aims to allow every node in the network to find a route to at least one of the access point. In this paper, we present a grid-representation that illustrates the distribution of nodes in the network based on the number of hops each node is away from the access points. This representation better illustrates the relationship between nodes in different regions in the network. We also define a new metric known as 'Index' for measuring the quality of each possible parent node, to which a node can connect to reach the access point. After reconfiguration is done using the proposed algorithm, NS2 network simulator is used to perform the simulations of the ad hoc network of 22 wireless mobile nodes. The performance of the algorithm will be evaluated based on the average throughput and average end-to-end delay.
Integration of Information Filtering and Data Mining Process for Web Information Retrieval

This paper examines a new approach to Web information retrieval, and proposes a new two stage scheme. The aim of the first stage is to quickly filter irrelevant information based on the user profiles. The proposed user profiles learning algorithm are very efficient and effective within a relevance feedback framework. The aim of the second stage is to apply data mining techniques to rationalize the data relevance on the reduced data set. Our experiments on RCV1 (Reuters Corpus Volume 1) data collection which is used by TREC in 2002 for filtering track show that more effective and efficient access Web information has been achieved by combining the strength of information filtering and data mining method.
Boosting in the Presence of Outliers: Adaptive Classification With Nonconvex Loss Functions

ABSTRACT This article examines the role and the efficiency of nonconvex loss functions for binary classification problems. In particular, we investigate how to design adaptive and effective boosting algorithms that are robust to the presence of outliers in the data or to the presence of errors in the observed data labels. We demonstrate that nonconvex losses play an important role for prediction accuracy because of the diminishing gradient properties—the ability of the losses to efficiently adapt to the outlying data. We propose a new boosting framework called ArchBoost that uses diminishing gradient property directly and leads to boosting algorithms that are provably robust. Along with the ArchBoost framework, a family of nonconvex losses is proposed, which leads to the new robust boosting algorithms, named adaptive robust boosting (ARB). Furthermore, we develop a new breakdown point analysis and a new influence function analysis that demonstrate gains in robustness. Moreover, based only on local curvatures, we establish statistical and optimization properties of the proposed ArchBoost algorithms with highly nonconvex losses. Extensive numerical and real data examples illustrate theoretical properties and reveal advantages over the existing boosting methods when data are perturbed by an adversary or otherwise. Supplementary materials for this article are available online.
A Semantic-Based Approach to Grid Service Matching

Grid service matching is one of the key technologies to improve the reuse of resources and achieve high efficiency in service grid. This paper introduces more semantic features into the Grid service matching and then proposes a four-stage service matching model with semantics (FSMMS) which computes the similarity with the features of the service category, the precondition and outEffect, the inputs and outputs, and the text description of service. The experimental results show that our approach can achieve higher recall and precision than that of other approaches.
I am near my navel: learning mappings between location and skin

We describe a hypothetical device which observes and clusters location patterns, performs Principle Component Analysis, and maps the resulting eigenvectors to haptic sensations along the limbs. In doing so, we suggest machine learning methods to generate artiﬁcial sensory motor contingencies in a predictable and meaningful way. Instead of performing simple sensor-to-stimulus mappings, we believe transformations of sensed information can be more purposeful.
Global Stack Allocation – Register Allocation for Stack Machines

Register allocation is a critical part of any compiler, yet register allocation for stack machines has received relatively little attention in the past. We present a framework for the analysis of register allocation methods for stack machines which has allowed us to analyse current methods. We have used this framework to design the ﬁrst truly procedure-wide register allocation methods for stack machines. We have designed two such meth-ods, both of which outperform current techniques. This work was funded by the AMADEUS project, part of the DTI’s Next Wave Technologies and Markets Program, in collaboration with MPE Ltd.
Regulation of Muscle Satellite Cell Activation and Chemotaxis by Angiotensin II

The role of angiotensin II (Ang II) in skeletal muscle is poorly understood. We report that pharmacological inhibition of Ang II signaling or ablation of the AT1a receptor significantly impaired skeletal muscle growth following myotrauma, in vivo, likely due to impaired satellite cell activation and chemotaxis. In vitro experiments demonstrated that Ang II treatment activated quiescent myoblasts as evidenced by the upregulation of myogenic regulatory factors, increased number of β-gal+, Myf5-LacZ myoblasts and the acquisition of cellular motility. Furthermore, exogenous treatment with Ang II significantly increased the chemotactic capacity of C2C12 and primary cells while AT1a−/− myoblasts demonstrated a severe impairment in basal migration and were not responsive to Ang II treatment. Additionally, Ang II interacted with myoblasts in a paracrine-mediated fashion as 4 h of cyclic mechanical stimulation resulted in Ang II-induced migration of cocultured myoblasts. Ang II-induced chemotaxis appeared to be regulated by multiple mechanisms including reorganization of the actin cytoskeleton and augmentation of MMP2 activity. Collectively, these results highlight a novel role for Ang II and ACE inhibitors in the regulation of skeletal muscle growth and satellite cell function.
Data miming: inferring spatial object descriptions from human gesture

Speakers often use hand gestures when talking about or describing physical objects. Such gesture is particularly useful when the speaker is conveying distinctions of shape that are difficult to describe verbally. We present data miming---an approach to making sense of gestures as they are used to describe concrete physical objects. We first observe participants as they use gestures to describe real-world objects to another person. From these observations, we derive the data miming approach, which is based on a voxel representation of the space traced by the speaker's hands over the duration of the gesture. In a final proof-of-concept study, we demonstrate a prototype implementation of matching the input voxel representation to select among a database of known physical objects.
Are breakfast consumption patterns associated with weight status and nutrient adequacy in African-American children?

Abstract Objective The objective of the present study was to assess whether weight status, nutrient intake and dietary adequacy were associated with breakfast consumption patterns. Design A representative sample of the US population was used in a secondary analysis of nutrient intake/diet quality and weight status by breakfast consumption patterns. Setting The 1999–2002 National Health and Nutrition Examination Survey (NHANES). Subjects The study sample included African-American (AA) children aged 1–12 years (n 1389). Results Forty-five per cent of children aged 1–5 years and 38 % of those aged 6–12 years consumed ready-to-eat cereal (RTEC) at breakfast; while 7·4 % and 16·9 % in those age groups skipped breakfast, respectively. The lowest mean BMI (P ≤ 0·05) and mean waist circumference (P ≤ 0·05) was found in children 1–12 years of age who consumed RTEC at breakfast compared with other consumption groups. RTEC breakfast consumers had the highest mean intakes of vitamins A, B6 and B12, thiamine, riboflavin, niacin, folate, Ca, Fe and Zn (P ≤ 0·05) and the highest Mean Adequacy Ratio (P ≤ 0·05). RTEC breakfast consumers also had the highest intake of carbohydrates and total sugars, and the lowest intakes of total fat (P ≤ 0·05). Conclusions Consuming RTEC at breakfast was associated with improved weight and nutrient adequacy in AA children. AA children in all breakfast categories still had mean intakes of most nutrients below recommended levels. The implications are that consuming a breakfast meal should be encouraged in these children, and that RTEC at breakfast provides important nutrients and may help promote a healthy weight.
Informatics challenges of high-throughput microscopy

In this article, we discussed the emerging informatics issues of high-throughput screening (HTS) using automated fluorescence microscopy technology, otherwise known as high-content screening (HCS) in the pharmaceutical industry. Optimal methods of scoring biomarkers and identifying candidate hits have been actively studied in academia and industry, with the exception of data modeling topics. To find candidate hits, we need to score the images associated with different compound interventions. In the application example of RNAi genome-wide screening, we aim to find the candidate effectors or genes which correspond to the images acquired using the three channels. Scoring the effectors is equivalent to scoring the images based on the number of phenotypes existing in those images. Our ultimate objective of studying HTS is to model the relationship between gene networks and cellular phenotypes, investigate cellular communication via protein interaction, and study the disease mechanism beyond the prediction based on the molecular structure of the compound. Finally, computational image analysis has become a powerful tool in cellular and molecular biology studies. Signal processing and modeling for high-throughput image screening is an emerging filed that requires novel algorithms for dynamical system analysis, image processing, and statistical modeling. We hope that this article will motivate the signal processing communities to address challenging data modeling and other informatics issues of HTS
Analysis of the Error Surface of the XOR Network with TwoHidden

Appears in Proc. Seventh Australian Conf. Artificial Neural Networks, pages 179-183, 1996. Analysis of the Error Surface of the XOR Network with Two Hidden Nodes Leonard G. C. Hamey len@mpce.mq. edu.au School of MPCE Macquarie University NSW 2109 Australia ABSTRACT The exclusive-or learning task in a feed-forward neural network with two hidden nodes is investigated. Constraint equations have been derived which fully describe the nite stationary points of the error surface. It is shown that the stationary points occur in a single connected union of eighteen manifolds. A Taylor series expansion is applied to the network error surface and it is shown that all points within the enumerated manifolds are arbitrarily close to points of lower error. It follows that the nite stationary points of the exclusive-or task are saddle points, not relative minima. This result is surprising in view of the commonly held belief that the exclusive-or task exhibits local minima. The present result complements a recent result which proves the absence of regional local minima in the exclusive-or task.
Autoconfocal microscopy with nonlinear transmitted light detection

We describe a simple and robust technique for transmission confocal laser scanning microscopy wherein the detection pinhole is replaced by a thin second-harmonic generation crystal. The advantage of this technique is that self-aligned confocality is achieved without the need for signal descanning. We derive the point-spread function of our instrument and quantify both signal degradation and background rejection when imaging deep within a turbid slab. As an example, we consider a slab whose index of refraction fluctuations exhibit Gaussian statistics. Our model is corroborated by experiment.
Location Contexts of User Check-Ins to Model Urban Geo Life-Style Patterns

Geo-location data from social media offers us information, in new ways, to understand people's attitudes and interests through their activity choices. In this paper, we explore the idea of inferring individual life-style patterns from activity-location choices revealed in social media. We present a model to understand life-style patterns using the contextual information (e. g. location categories) of user check-ins. Probabilistic topic models are developed to infer individual geo life-style patterns from two perspectives: i) to characterize the patterns of user interests to different types of places and ii) to characterize the patterns of user visits to different neighborhoods. The method is applied to a dataset of Foursquare check-ins of the users from New York City. The co-existence of several location contexts and the corresponding probabilities in a given pattern provide useful information about user interests and choices. It is found that geo life-style patterns have similar items—either nearby neighborhoods or similar location categories. The semantic and geographic proximity of the items in a pattern reflects the hidden regularity in user preferences and location choice behavior.
A Moving Object Segmentation Method for Low Illumination Night Videos Soumya

object segmentation is one of the important tasks in autonomous system such as security and surveillance system. This paper presents a moving object segmentation method of low illumination video for night surveillance. A unique characteristic of the algorithm is its ability to extract the meaningful information like moving objects with low contrast or low illumination. When the camera system is stationary, background subtraction is a commonly used technique for segmenting out moving objects in a scene. A new approach is specified here to segment the moving object from the poor illuminated area. Also a dilation approach is specified to track the correct pixels. The experimental results on real images show the effectiveness of the approach. Performance analysis is carried out with the help of PSNR and ground-truth measure.
Improving F0 prediction using bidirectional associative memories and syllable-level F0 features for HMM-based Mandarin speech synthesis

The speech generated by hidden Markov model (HMM) based speech synthesis method always sounds monotonous compared with natural recordings. An important reason is that the predicted F0 trajectories are over-smoothed. This arises from the adoption of frame-level F0 features and the averaging effect of acoustic modeling using Gaussians in the conventional F0 modeling approach. In this paper, we propose a method to improve the F0 prediction of HMM-based Mandarin speech synthesis in a post-filtering way. Syllable-level F0 features, e.g., length-normalized logF0 vectors or quantitative target approximation (qTA) parameters, are extracted from the F0 trajectories predicted by the conventional approach. These features are mapped towards natural ones by Gaussian bidirectional associative memory (GBAM) based transformation. Our subjective experiments indicate that the GBAM-based F0 post-filtering method using either logF0 vectors or qTA parameters can significantly improve the naturalness of synthetic speech. Using raw logF0 vectors for post-filtering can achieve better performance than using derived qTA parameters.
The Highly Relativistic Kiloparsec-Scale Jet of the Gamma-Ray Quasar 0827+243

We present Chandra X-ray (0.2-8 keV) and Very Large Array radio (15 and 5 GHz) images of the γ-ray-bright, superluminal quasar 0827+243. The X-ray jet bends sharply—by ~90°, presumably amplified by projection effects—5'' from the core. Only extremely weak radio emission is detected between the nuclear region and the bend. The X-ray continuum spectrum of the combined emission of the knots is rather flat, with a slope of -0.4 ± 0.2, while the 5-15 GHz spectra are steeper for knots detected in the radio. These characteristics, as well as nondetection of the jet in the optical band by the Hubble Space Telescope, pose challenges to models for the spectral energy distributions (SEDs) of the jet features. The SEDs could arise from pure synchrotron emission from either a single or dual population of relativistic electrons only if the minimum electron energy per unit mass γmin ≳ 1000. In the case of a single population, the radiative energy losses of the X-ray-emitting electrons must be suppressed owing to inverse Compton scattering in the Klein-Nishina regime, as proposed by Dermer & Atoyan. Alternatively, the X-ray emission could result from inverse Compton scattering of the cosmic microwave background photons by electrons with Lorentz factors as low as γ ~ 15. In all models, the bulk Lorentz factor of the jet flow Γ ≳ 20 found on parsec scales must continue without substantial deceleration out to 800 kpc (deprojected) from the nucleus, and the magnetic field is very low, ≲2 μG, until the bend. Deceleration does appear to occur at and beyond the sharp bend, such that the flow could be only mildly relativistic at the end of the jet. Significant intensification of the magnetic field occurs downstream of the bend, where there is an offset between the projected positions of the X-ray and radio features.
Completely dark galaxies: their existence, properties and strategies for finding them

There are a number of theoretical and observational hints that large numbers of low-mass galaxies composed entirely of dark matter exist in the field. The theoretical considerations follow from the prediction of cold dark matter theory that there exist many low-mass galaxies for every massive one. The observational considerations follow from the observed paucity of these low-mass galaxies in the field but not in dense clusters of galaxies; this suggests that the lack of small galaxies in the field is due to the inhibition of star formation in the galaxies as opposed to the fact that their small dark matter haloes do not exist. In this work we outline the likely properties of low-mass dark galaxies, and describe observational strategies for finding them, and where in the sky to search. The results are presented as a function of the global properties of dark matter, in particular the presence or absence of a substantial baryonic dark matter component. If the dark matter is purely cold and has a Navarro, Frenk & White density profile, directly detecting dark galaxies will only be feasible with present technology if the galaxy has a maximum velocity dispersion in excess of 70 km s−1, in which case the dark galaxies could strongly lens background objects. This is much higher than the maximum velocity dispersions in most dwarf galaxies. If the dark matter in galaxy haloes has a baryonic component close to the cosmic ratio, the possibility of directly detecting dark galaxies is much more realistic; the optimal method of detection will depend on the nature of the dark matter. A number of more indirect methods are also discussed.