The Weekly Adjustment Indicators Checklist: An Application in the Child Welfare Field

Research on the effectiveness of various home-based interventions implemented in the 1980s and 1990s indicates that results have been equivocal. Because of the unique and complex behavioral challenges presented by each family and the need for individualized treatments and long-term interventions for these families, group research and evaluation designs are often insufficient in assessing effectiveness of home-based interventions. Alternative evaluation strategies are needed. The purpose of this exploratory study was two-fold: (a) to investigate the applicability and acceptability of the Weekly Adjustment Indicators Checklist (WAIC) in monitoring adult and child behaviors and (b) to monitor, on an on-going basis, the progress of a family referred to an urban family preservation and reunification program. The target family on whom data were collected consisted of a 13-year old girl and her foster parent who was her maternal aunt. The findings of this study indicate that the WAIC is applicable in monitoring the progress of children and adults in care and that it has the endorsement of its user, namely, the direct care provider. Other results of the study, limitations of the study, and future research needs are discussed

ENSO’s far reaching connection to Indian cold waves

During boreal winters, cold waves over India are primarily due to transport of cold air from higher latitudes. However, the processes associated with these cold waves are not yet clearly understood. Here by diagnosing a suite of datasets, we explore the mechanisms leading to the development and maintenance of these cold waves. Two types of cold waves are identified based on observed minimum surface temperature and statistical analysis. The first type (TYPE1), also the dominant one, depicts colder than normal temperatures covering most parts of the country while the second type (TYPE2) is more regional, with significant cold temperatures only noticeable over northwest India. Quite interestingly the first (second) type is associated with La Niña (El Niño) like conditions, suggesting that both phases of ENSO provide a favorable background for the occurrence of cold waves over India. During TYPE1 cold wave events, a low-level cyclonic anomaly generated over the Indian region as an atmospheric response to the equatorial convective anomalies is seen advecting cold temperatures into India and maintaining the cold waves. In TYPE2 cold waves, a cyclonic anomaly generated over west India anomalously brings cold winds to northwest India causing cold waves only in those parts

Tetraspanin (TSP-17) Protects Dopaminergic Neurons against 6-OHDA-Induced Neurodegeneration in <i>C. elegans</i>

Parkinson's disease (PD), the second most prevalent neurodegenerative disease after Alzheimer's disease, is linked to the gradual loss of dopaminergic neurons in the substantia nigra. Disease loci causing hereditary forms of PD are known, but most cases are attributable to a combination of genetic and environmental risk factors. Increased incidence of PD is associated with rural living and pesticide exposure, and dopaminergic neurodegeneration can be triggered by neurotoxins such as 6-hydroxydopamine (6-OHDA). In C. elegans, this drug is taken up by the presynaptic dopamine reuptake transporter (DAT-1) and causes selective death of the eight dopaminergic neurons of the adult hermaphrodite. Using a forward genetic approach to find genes that protect against 6-OHDA-mediated neurodegeneration, we identified tsp-17, which encodes a member of the tetraspanin family of membrane proteins. We show that TSP-17 is expressed in dopaminergic neurons and provide genetic, pharmacological and biochemical evidence that it inhibits DAT-1, thus leading to increased 6-OHDA uptake in tsp-17 loss-of-function mutants. TSP-17 also protects against toxicity conferred by excessive intracellular dopamine. We provide genetic and biochemical evidence that TSP-17 acts partly via the DOP-2 dopamine receptor to negatively regulate DAT-1. tsp-17 mutants also have subtle behavioral phenotypes, some of which are conferred by aberrant dopamine signaling. Incubating mutant worms in liquid medium leads to swimming-induced paralysis. In the L1 larval stage, this phenotype is linked to lethality and cannot be rescued by a dop-3 null mutant. In contrast, mild paralysis occurring in the L4 larval stage is suppressed by dop-3, suggesting defects in dopaminergic signaling. In summary, we show that TSP-17 protects against neurodegeneration and has a role in modulating behaviors linked to dopamine signaling

Comparison of self-medication practice for dysmenorrhoea in medical, nursing and dental students

Background: Dysmenorrhea is common in adolescent and young adult females and is responsible for impaired daily activities and significant absenteeism from college among female students. The self-treatment strategy varies among the students. Hence, the present study was done to analyse and compare the self-medication practice for dysmenorrhoea among medical, nursing and dental students.Methods: This was a cross-sectional study conducted among 188 female students with dysmenorrhoea in M. S. Ramaiah College Campus, Bangalore which included 62 medical, 63 nursing and 63 dental students. Data was collected with prevalidated questionnaire related to various aspects like demographic data, severity and duration of dysmenorrhoea and pattern of management in the three groups. Data collected was analysed using SPSS version 20.Results: The mean age of female students with dysmenorrhoea was 19.12±0.87 years. 28% students perceived hormonal changes as causative factor for dysmenorrhoea. About 92 (48.9%) were on self-medication and 46 (24.5%) of students used home remedies for dysmenorrhoea. Among 92 students drugscommonly used for self-medication were mefenemic acid+dicyclomine  (67.4%) followed by paracetamol (20.7%), ibuprofen (5.4%), dicyclomine (4.3%), and diclofenac (2.2%). NSAIDS such as mefenamic acid, paracetamol, ibuprofen, diclofenac were used commonly by students in the three groups.Conclusions: Dysmenorrhoea is a common cause for self-medication among young females. Self-medication practice for dysmenorrhoea was seen more in medical students where as non-pharmacological remedies in nursing and dental female students. NSAIDS like mefenamic acid and paracetamol are the mainstay of self-medication for dysmenorrhoea

Strain Relaxation Mechanisms and Local Structural Changes in Si_{1-x}$Ge_{x} Alloys

In this work, we address issues pertinent to the understanding of the structural and electronic properties of Si_{1-x} Ge_{x}alloys, namely, (i) how does the lattice constant mismatch between bulk Si and bulk Ge manifests itself in the alloy system? and (ii) what are the relevant strain release mechanisms? To provide answers to these questions, we have carried out an in-depth study of the changes in the local geometric and electronic structures arising from the strain relaxation in Si_{1-x} Ge_{x} alloys using an ab initio molecular dynamics scheme. The optimized lattice constant, while exhibiting a general trend of linear dependence on the composition (Vegard's law), shows a negative deviation from Vegard's law in the vicinity of x=0.5. We delineate the mechanisms responsible for each one of the above features. We show that the radial-strain relaxation through bond stretching is responsible for the overall trend of linear dependence of the lattice constant on the composition. On the other hand, the negative deviation from Vegard's law is shown to arise from the angular-strain relaxation.Comment: 21 pages, 7 figure

Limited Data Speaker Verification: Fusion of Features

The present work demonstrates experimental evaluation of speaker verification for different speech feature extraction techniques with the constraints of limited data (less than 15 seconds). The state-of-the-art speaker verification techniques provide good performance for sufficient data (greater than 1 minutes). It is a challenging task to develop techniques which perform well for speaker verification under limited data condition. In this work different features like Mel Frequency Cepstral Coefficients (MFCC), Linear Prediction Cepstral Coefficients (LPCC), Delta (4), Delta-Delta (44), Linear Prediction Residual (LPR) and Linear Prediction Residual Phase (LPRP) are considered. The performance of individual features is studied and for better verification performance, combination of these features is attempted. A comparative study is made between Gaussian mixture model (GMM) and GMM-universal background model (GMM-UBM) through experimental evaluation. The experiments are conducted using NIST-2003 database. The experimental results show that, the combination of features provides better performance compared to the individual features. Further GMM-UBM modeling gives reduced equal error rate (EER) as compared to GMM

Dirac electrons in graphene-based quantum wires and quantum dots

In this paper we analyse the electronic properties of Dirac electrons in finite-size ribbons and in circular and hexagonal quantum dots made of graphene.Comment: Contribution for J. Phys.: Cond. Mat. special issue on graphene physic

Immune-mediated competition in rodent malaria is most likely caused by induced changes in innate immune clearance of merozoites

Malarial infections are often genetically diverse, leading to competitive interactions between parasites. A quantitative understanding of the competition between strains is essential to understand a wide range of issues, including the evolution of virulence and drug resistance. In this study, we use dynamical-model based Bayesian inference to investigate the cause of competitive suppression of an avirulent clone of Plasmodium chabaudi (AS) by a virulent clone (AJ) in immuno-deficient and competent mice. We test whether competitive suppression is caused by clone-specific differences in one or more of the following processes: adaptive immune clearance of merozoites and parasitised red blood cells (RBCs), background loss of merozoites and parasitised RBCs, RBC age preference, RBC infection rate, burst size, and within-RBC interference. These processes were parameterised in dynamical mathematical models and fitted to experimental data. We found that just one parameter μ, the ratio of background loss rate of merozoites to invasion rate of mature RBCs, needed to be clone-specific to predict the data. Interestingly, μ was found to be the same for both clones in single-clone infections, but different between the clones in mixed infections. The size of this difference was largest in immuno-competent mice and smallest in immuno-deficient mice. This explains why competitive suppression was alleviated in immuno-deficient mice. We found that competitive suppression acts early in infection, even before the day of peak parasitaemia. These results lead us to argue that the innate immune response clearing merozoites is the most likely, but not necessarily the only, mediator of competitive interactions between virulent and avirulent clones. Moreover, in mixed infections we predict there to be an interaction between the clones and the innate immune response which induces changes in the strength of its clearance of merozoites. What this interaction is unknown, but future refinement of the model, challenged with other datasets, may lead to its discovery

Modular Composition of Gene Transcription Networks

Predicting the dynamic behavior of a large network from that of the composing modules is a central problem in systems and synthetic biology. Yet, this predictive ability is still largely missing because modules display context-dependent behavior. One cause of context-dependence is retroactivity, a phenomenon similar to loading that influences in non-trivial ways the dynamic performance of a module upon connection to other modules. Here, we establish an analysis framework for gene transcription networks that explicitly accounts for retroactivity. Specifically, a module's key properties are encoded by three retroactivity matrices: internal, scaling, and mixing retroactivity. All of them have a physical interpretation and can be computed from macroscopic parameters (dissociation constants and promoter concentrations) and from the modules' topology. The internal retroactivity quantifies the effect of intramodular connections on an isolated module's dynamics. The scaling and mixing retroactivity establish how intermodular connections change the dynamics of connected modules. Based on these matrices and on the dynamics of modules in isolation, we can accurately predict how loading will affect the behavior of an arbitrary interconnection of modules. We illustrate implications of internal, scaling, and mixing retroactivity on the performance of recurrent network motifs, including negative autoregulation, combinatorial regulation, two-gene clocks, the toggle switch, and the single-input motif. We further provide a quantitative metric that determines how robust the dynamic behavior of a module is to interconnection with other modules. This metric can be employed both to evaluate the extent of modularity of natural networks and to establish concrete design guidelines to minimize retroactivity between modules in synthetic systems.United States. Air Force Office of Scientific Research (FA9550-12-1-0129