Mode-Coupling Model of Mott Gap Collapse in the Cuprates: Natural Phase Boundary for Quantum Critical Points

A simple antiferromagnetic approach to the Mott transition was recently shown to provide a satisfactory explanation for the Mott gap collapse with doping observed in photoemission experiments on electron-doped cuprates. Here this approach is extended in a number of ways. RPA, mode coupling (via self-consistent renormalization), and (to a limited extent) self-consistent Born approximation calculations are compared to assess the roles of hot-spot fluctuations and interaction with spin waves. When fluctuations are included, the calculation satisfies the Mermin-Wagner theorem, and the mean-field gap and transition temperature are replaced by pseudogap and onset temperature. The model is in excellent agreement with experiments on the doping dependence of both photoemission dispersion and magnetic properties. The magnetic phase terminates in a quantum critical point (QCP), with a natural phase boundary for this QCP arising from hot-spot physics. Since the resulting T=0 antiferromagnetic transition is controlled by a generalized Stoner factor, an ansatz is made of dividing the Stoner factor up into a material-dependent part, the bare susceptibility and a correlation-dependent part, the Hubbard U, which depends only weakly on doping. From the material dependent part of the interaction, it is possible to explain the striking differences between electron- and hole-doping, despite an approximate symmetry in the doping of the QCP. The slower divergence of the magnetic correlation length in hole doped cuprates may be an indication of more Mott-like physics.Comment: This replaces cond-mat/0308469. 50 eps figures, revtex [Version 1 had included old file

Assessing Learning Behaviors Using Gaussian Hybrid Fuzzy Clustering (GHFC) in Special Education Classrooms

The article suggests an unsupervised model for featuring student’s learning patterns in an open-ended learning scenario. The article proceeds by generating powerful metrics to characterize the learner’s behavior and efficacy through Coherence investigation. Then, the selected features are combined through a Gaussian Hybrid Fuzzy Clustering (GHFC) that categorizes students based on their learning patterns. The proposed system features the essential behaviors of every group and associate the behaviors with ability to develop right models to gauge the learning gains between pre- and post-test scores. Also, this article explains the deployment of behavior characterization to be developed as a adaptive framework of learning behaviors

Voice cues are used in a similar way by blind and sighted adults when assessing women’s body size

Humans’ ability to gauge another person’s body size from their voice alone may serve multiple functions ranging from threat assessment to speaker normalization. However, how this ability is acquired remains unknown. In two experiments we tested whether sighted, congenitally blind and late blind adults could accurately judge the relative heights of women from paired voice stimuli, and importantly, whether errors in size estimation varied with task difficulty across groups. Both blind (n = 56) and sighted (n = 61) listeners correctly judged women’s relative heights on approximately 70% of low difficulty trials, corroborating previous findings for judging men’s heights. However, accuracy dropped to chance levels for intermediate difficulty trials and to 25% for high difficulty trials, regardless of the listener’s sightedness, duration of vision loss, sex, or age. Thus, blind adults estimated women’s height with the same degree of accuracy, but also the same pattern of errors, as did sighted controls. Our findings provide further evidence that visual experience is not necessary for accurate body size estimation. Rather, both blind and sighted listeners appear to follow a general rule, mapping low auditory frequencies to largeness across a range of contexts. This sound-size mapping emerges without visual experience, and is likely very important for humans

Real-time Migration Risk Analysis Model for Improved Immigrant Development Using Psychological Factors

The problem of immigrant migration risk analysis is deeply studied and there are number of issues identified in the selection of country. There exists number of approaches available in the selection of countries towards migration. However, the methods do not produce effective results in the selection of migrant country. To handle this issue, an efficient real-time migrant risk analysis model (RMAM) is presented in this article. The method uses the traces of previos migration histories and data set maintained by the model. Using the migration data set, the method preprocesses the data set for noise removal and normalization. With the normalized data set, the method applies Nation Centric Religious Support Analysis and Psychological Support Analysis. The nation centric religious support analysis algorithm measure the risk factors on religious features by computing National Religious Support (NRS) and the Psychological Support Analysis algorithm computes the value of Psychological Support (PS) for different countries. Based on the result of different analysis, the method computes Migration Support (MS) for various countries towards the selection of migration countries. The proposed model improves the performance of risk analysis and migration control

Impact des proprietes physicochimiques des sols de culture du manioc sur l’abondance et la diversite des communautes de champignons mycorhiziens à arbuscules dans la zone agroecologique d’azaguie, Sud-Est de la Côte D’Ivoire

En Côte d’ Ivoire, la baissede la fertilité des terres de culture du manioc,  est à l’origine des rendements faibles. L’utilisation de l’effet bénéfique des  champignons mycorhiziens arbusculaires (CMA) pourrait améliorer  durablement ces rendements. Ce travail a pour but de mettre en évidence l’écologie, la diversité et la structuration des communautés de CMA  endogènes associés à la culture du manioc dans les sols de la zone  agroécologique d’Azaguié. Les études ont été menées à partir des sols de champs de manioc (Ahoua 1, Ahoua 2, Mbromé 1, Mbromé 2). Ces sols étaient très acides (pH inférieurs à 5,17), pauvres en bases échangeables (CEC inférieures à 17,1 cmol/kg), en phosphore assimilable (P.  assimilable inférieur à 30,71 ppm) et en matière organique. Il a été  dénombré 44 espèces de CMA reparties en treize genres. Les genres  Glomus (55,17 %) et Acaulospora (30,14 %) sont les plus abondants. Les densités des spores de CMA, sont inférieures à 14,68 spores.g-1. La proportion moyenne de spores non-viables (55 %) est élevée. Il a été noté des corrélations positives entre les communautés de CMA et le  magnésium (R = 0,65), la CEC (R = 0,69), l'argile (R = 0,74) et le limon grossier (R = 0,79). Par contre des corrélations négatives ont été obtenues avec le sable fin (R = -0,60) et le sable grossier (R = -0,59).Mots clés : Manioc, Azaguié, Côte d’Ivoire, champignons mycorhiziens à arbuscules.INFLUENCE OF CASSAVA SOILS PHYSICOCHEMICAL PROPERTIES ONTHE ABUNDANCE AND DIVERSITYOF ARBUSCULAR MYCORRIZAL FUNGI  COMMUNITIES’ IN AZAGUIÉ AGROECOLOGICAL AREA, SOUTH-EAST CÔTE D’IVOIREIn Côte d’Ivoire, the decline in cassava soil fertility is causing low yields. The use of the beneficial effect of arbuscular mycorrhizal fungi (AMF) can sustainably improve the yields. The aim of this study was to highlight the ecology, diversity and community structure of endogenous CMA associated with cassava. The studies were conducted using cassava field soils (Ahoua 1 Ahoua 2 Mbromé 1 Mbromé 2). These soils were very acidic (pH less than 5.17), with low exchangeable bases capacities values (CEC less than 17.1 cmol / kg), low available phosphorus levels (available P less than 30.71 ppm) and poor organic matter proportions. Thirteen AMF genera comprising 44 species were identified. The genera Glomus (55.17 %) and Acaulospora (30.14 %) were the most abundant. AMF spores densities were (8.42 and 14.68 spores.g-1). The proportion of non-healthy spores was 55 %. There were positive correlations between AMF communities and magnesium (R = 0.65 and 0.59), CEC (R = 0.69), clay (R = 0.74) and coarse silt (R = 0.79) and negative correlations were obtained with fine sand (R = -0.60) and coarse sand (R = -0.59).Key words : Cassava, Azaguié Côte d’Ivoire, abuscular mycorrhiral fungi

It’s all about the money? A qualitative study of healthcare worker motivation in urban China

Background China’s healthcare reform programme continues to receive much attention. Central to these discussions has been how the various financial incentives underpinning reform efforts are negatively impacting on the healthcare workforce. Research continues to document these trends, however, qualitative analysis of how these incentives impact on the motivation of healthcare workers remains underdeveloped. Furthermore, the application of motivational theories to make sense of healthcare worker experiences has yet to be undertaken. Methods The purpose of our paper is to present a comparative case study account of healthcare worker motivation across urban China. It draws on semi structured interviews (n = 89) with a range of staff and organisations across three provinces. In doing so, the paper analyses how healthcare worker motivation is influenced by a variety of financial incentives; how motivation is influenced by the opportunities for career development; and how motivation is influenced by the day to day pressures of meeting patient expectations. Results The experience of healthcare workers in China highlights how a reliance on financial incentives has challenged their ability to maintain the values and ethos of public service. Our findings suggest greater attention needs to be paid to the motivating factors of improved income and career development. Further work is also needed to nurture and develop the motivation of healthcare workers through the building of trust between fellow workers, patients, and the public. Conclusions Through the analysis of healthcare worker motivation, our paper presents a number of ways China can improve its current healthcare reform efforts. It draws on the experience of other countries in calling for policy makers to support alternative approaches to healthcare reform that build on multiple channels of motivation to support healthcare workers

Intervention, recruitment and evaluation challenges in the Bangladeshi community: Experience from a peer lead educational course

<p>Abstract</p> <p>Background</p> <p>The incidence of Type 2 diabetes is increasing worldwide and diabetes is four times more common among ethnic minority groups than among the general Caucasian population. This study reflects on the specific issues of engaging people and evaluating interventions through written questionnaires within older ethnic minority groups.</p> <p>Methods</p> <p>The original protocol set out to evaluate an adapted version of the X-PERT^®patient program <url>http://www.xpert-diabetes.org.uk/</url> using questionnaires and interviews.</p> <p>Results</p> <p>Questionnaires, even verbally completed, were unsuccessful and difficult to administer as participants found the questionnaire structure and design difficult to follow and did not perceive any benefit to completing the questionnaires. The benefits of attending the course were also poorly understood by participants and in many cases people participated in coming to the course as a favour to the researcher. Engaging participants required word of mouth and the involvement of active members of the community.</p> <p>Conclusion</p> <p>Peer led courses and their evaluation in older ethnic minority communities needs a very different approach for that in younger Caucasian patients. A structured approached to evaluation (favoured by western educational system) is inappropriate. Engaging participants is difficult and the employment of local well known people is essential.</p

Volitional exaggeration of body size through fundamental and formant frequency modulation in humans

Several mammalian species scale their voice fundamental frequency (F0) and formant frequencies in competitive and mating contexts, reducing vocal tract and laryngeal allometry thereby exaggerating apparent body size. Although humans’ rare capacity to volitionally modulate these same frequencies is thought to subserve articulated speech, the potential function of voice frequency modulation in human nonverbal communication remains largely unexplored. Here, the voices of 167 men and women from Canada, Cuba, and Poland were recorded in a baseline condition and while volitionally imitating a physically small and large body size. Modulation of F0, formant spacing (∆F), and apparent vocal tract length (VTL) were measured using Praat. Our results indicate that men and women spontaneously and systemically increased VTL and decreased F0 to imitate a large body size, and reduced VTL and increased F0 to imitate small size. These voice modulations did not differ substantially across cultures, indicating potentially universal sound-size correspondences or anatomical and biomechanical constraints on voice modulation. In each culture, men generally modulated their voices (particularly formants) more than did women. This latter finding could help to explain sexual dimorphism in F0 and formants that is currently unaccounted for by sexual dimorphism in human vocal anatomy and body size

Smart Crop Advisor using Machine Learning

Now-a-days selection of crop is a significant challenge for farmers it becomes more difficult, if they are having no experience or do not have knowledge to select the best possible viable crop. Introducing the Smart Crop Advisor (SCA) which aids in such recommendations to local conditions. Smart Crop Advisor is an online decision support system that adopts Gradient Boosting algorithm to improve the accuracy of agricultural decisions, and gives low-level farmers a personal crop selection advice. Smart Crop Advisor is Designed using Python, HTML and CSS. Python is used for backend development and machine learning model implementation. The user interface is designed using HTML and CSS, allowing for anyone to just add their conditions easily. This application provides insights based on data by utilizing a large agricultural database. The farmers have to enter the specifications based on their soil test report like PH value, climatic conditions such as humidity, temperature. The system proposes best crops suited for particular region and situations. SCA improves crop yields and minimizes chemical inputs, reduces resource loss by selecting the right crops for a specific region and climate, farmers can improve crop yields and reduce waste. It promotes sustainable farming S which the system promotes sustainable farming practices by recommending crops that are well-suited to the local condition