Miracle-dz/UniFAR-FTUs huggingface dataset:
Front-end Channel Compensation using Mixture-dependent Feature Transformations for i-Vector Speaker Recognition

State-of-the-art session variability compensation for speaker recognition are generally based on various linear statistical models of the Gaussian Mixture Model (GMM) mean super-vectors, while frontend features are only processed by standard normalization techniques. In this study, we propose a front-end channel compensation frame-work using mixture-localized linear transforms that operate before super-vector domain modeling begins. In this approach, local linear transforms are trained for each Gaussian component of a Universal Background Model (UBM), and are applied to acoustic features according to their mixture-wise probabilistic alignment, yielding an operation that is globally non-linear. We examine Principal Component Analysis (PCA), whitening, Linear Discriminant Analysis (LDA) and Nuisance Attribute Projection (NAP) as frontend feature transformations. We also propose a method, Nuisance Attribute Elimination (NAE), which is similar to NAP but performs dimensionality reduction in addition to channel compensation. We show that the proposed frame-work can be readily integrated with a standard i-Vector system by simply applying the transformations on the first order Baum-Welch statistics and transforming the UBM. Experiments performed on the telephone trials of the NIST SRE 2010 demonstrate significant performance gain from the proposed frame-work, especially using LDA as the front-end transformation.
Drop-out from a psychodynamic group psychotherapy outpatient unit

Abstract Background. Drop-out from psychotherapy is common and represents a considerable problem in clinical practice and research. Aim. To explore pre-treatment predictors of early and late drop-out from psychodynamic group therapy in a public outpatient unit for non-psychotic disorders in Denmark. Methods. Naturalistic design including 329 patients, the majority with mood, neurotic and personality disorders referred to 39-session group therapy. Predictors were socio-demographic and clinical variables, self-reported symptoms (Symptom Check List-90-Revised) and personality style (Millon Clinical Multiaxial Inventory-II). Drop-out was classified into early and late premature termination excluding patients who dropped out for external reasons. Results. Drop-out comprised 20.6% (68 patients) of the sample. Logistic regression revealed social functioning, vocational training, alcohol problems and antisocial behavior to be related to drop-out. However, early drop-outs had prominent agoraphobic symptoms, lower interpersonal sensitivity and compulsive personality features, and late drop-outs cognitive and somatic anxiety symptoms and antisocial personality features. Clinical and psychological variables accounted for the major part of variance in predictions of drop-out, which ranged from 15.6% to 19.5% (Nagelkerke Pseudo R-Square). Conclusion. Social functioning was consistently associated with drop-out, but personality characteristics and anxiety symptoms differentiated between early and late drop-out. Failure to discriminate between stages of premature termination may explain some of the inconsistencies in the drop-out literature. Clinical implications. Before selection of patients to time-limited psychodynamic groups, self-reported symptoms should be thoroughly considered. Patients with agoraphobic symptoms should be offered alternative treatment. Awareness of and motivation to work with interpersonal issues may be essential for compliance with group therapy.
Bootstrapping Fine-Grained Classifiers : Active Learning with a Crowd in the Loop

We propose an iterative crowd-enabled active learning algorithm for building high-precision visual classifiers from unlabeled images. Our method employs domain experts to identify a small number of examples of a specific visual event. These expert-labeled examples seed a classifier, which is then iteratively trained by active querying of a non-expert crowd. These non-experts actively refine the classifiers at every iteration by answering simple binary questions about the classifiers’ detections. The advantage of this approach is that experts efficiently shepherd an unsophisticated crowd into training a classifier capable of fine-grained distinctions. This obviates the need to label an entire dataset to obtain high-precision classifiers. We find these classifiers are advantageous for creating a large vocabulary of visual attributes for specialized taxonomies. We demonstrate our crowd active learning pipeline by creating classifiers for attributes related to North American birds and fashion.
A multiscale texture analysis procedure for improved forest stand classification

Image texture is a complex visual perception. With the ever-increasing spatial resolution of remotely sensed data, the role of image texture in image classification has increased. Current approaches to image texture analysis rely on a single band of spatial information to characterize texture. This paper presents a multiscale approach to image texture where first and second-order statistical measures were derived from different sizes of processing windows and were used as additional information in a supervised classification. By using several bands of textural information processed with different window sizes (from 5×5 to 15×15) the main forest stands in the image were improved up to a maximum of 40%. A geostatistical analysis indicated that there was no single window size that would adequately characterize the range of textural conditions present in this image. A number of different statistical texture measures were compared for this image. While all of the different texture measures provided a degree of improvement (from 4 to 13% overall), the multiscale approach achieved a higher degree of classification accuracy regardless of which statistical procedure was used. When compared with single band texture measures, the level of overall improvement varied between 4 and 8%. The results indicate that this multiscale approach is an improvement over the current single band approach to analysing image texture.
Applications of ground-penetrating radar (GPR) to sedimentological, geomorphological and geoarchaeological studies in coastal environments

Abstract Acquisition of high resolution data regarding the stratigraphy and internal structure of coastal sedimentary sequences is becoming increasingly important in many sedimentological, geomorphological and geoarchaeological studies. Such information is usually obtained from the logging of field exposures, shallow trenches and cores. However, ground-penetrating radar (GPR), a relatively new and rapidly developing non-invasive geophysical technique, may also aid such investigations in certain coastal settings, providing additional, complimentary and often unique data sets. The technique is based on the transmission, reflection and reception of high frequency electromagnetic (radar) waves, with reflections occurring in the subsurface due to the varying electrical properties of the sediments. Such reflections can occur due the presence of primary sedimentary structures, lithological/material changes or water content changes. Examples presented from the UK indicate that the technique can accurately delineate the stratigraphy and internal sedimentary structure of coastal barriers, spits and strandplains, both above and below a fresh groundwater table. Sand and/or gravel-dominated beach-dune systems on moderate to high wave energy, macrotidal coasts appear to provide optimum settings for GPR deployment. In addition, the technique also has the potential to locate, map and provide stratigraphic context for a wide range of archaeological features that are commonly found in such coastal environments.
Hydraulic Transients in Viscoelastic Branched Pipelines

AbstractPlastic pipes are widely used in pressurized water systems. Their viscoelastic behavior has to be taken into account in the design phase as well as in the interpretation of water-hammer signals for diagnostic purposes. The aim of the present paper is to experimentally investigate the transient waves’ transmission and reflection in branched networks of high density polyethylene (HDPE) pipes and to test the efficacy of a viscoelastic model for the interpretation of the results. Two laboratory Y-shaped systems were built in the Water Engineering Lab of the University of Cassino and Southern Lazio (Italy) and a set of water-hammer tests was conducted on them. A significant variation of transmission and reflection coefficients at the pipe junction is observed in comparison with the values suggested in classical textbooks. The strong agreement between the experimental pressure values and those obtained using the viscoelastic model suggests that the differences from the classical theory are due to the vi.
Modeling of Channel Potential and Subthreshold Slope of Symmetric Double-Gate Transistor

A new physically based classical continuous potential distribution model, particularly considering the channel center, is proposed for a short-channel undoped body symmetrical double-gate transistor. It involves a novel technique for solving the 2-D nonlinear Poisson's equation in a rectangular coordinate system, which makes the model valid from weak to strong inversion regimes and from the channel center to the surface. We demonstrated, using the proposed model, that the channel potential versus gate voltage characteristics for the devices having equal channel lengths but different thicknesses pass through a single common point (termed ldquocrossover pointrdquo). Based on the potential model, a new compact model for the subthreshold swing is formulated. It is shown that for the devices having very high short-channel effects (SCE), the effective subthreshold slope factor is mainly dictated by the potential close to the channel center rather than the surface. SCEs and drain-induced barrier lowering are also assessed using the proposed model and validated against a professional numerical device simulator.
Pattern of congenital anomalies in newborn: a hospital-based study

Birth defects, encountered frequently by pediatricians, are important causes of childhood morbidity and mortality. Birth defects can be classified according to their severity, pathogenic mechanism, or whether they are involving a single system or multiple systems. This hospital-based prospective descriptive study highlights the prevalence of Congenital Anomalies (CAs) in one year among live born neonates delivered in Zagazig University Hospital (Egypt). All women giving birth to viable babies were included. Demographic details, associated risk factors and the type of CAs in all babies were recorded. Diagnosis of CAs was based on clinical evaluation, radiographic examination, ultrasonography, echocardiography and chromosomal analysis of the newborn whenever recommended. The overall incidence of CAs among live born neonates was 2.5%, as most of the cases were referred to Zagazig University Hospital (Egypt) for delivery. The musculoskeletal system (23%) was the most commonly involved followed by the central nervous system (20.3%). Involvement of more than one system was observed in (28.6%) cases. Among maternal and fetal risk factors; parental consanguinity, maternal under nutrition and obesity, positive history of an anomaly in the family, low birth weight, and prematurity were significantly associated with higher frequency of CAs (P<0.05), with non-significant differences for maternal age and the sex of the neonates. The current study highlights the prevalence of congenital anomalies in one year in Zagazig University Hospital. It revealed a high prevalence of congenital anomalies in our locality and stressed the importance of carrying out a thorough clinical examination of all neonates at birth.
Web-Based Versus In-Class: An Exploration of How Instructional Methods Influence Postsecondary Students' Environmental Literacy

An investigation of Web-based versus in-class learning environments indicated that student's environmental knowledge, beliefs, opinions, and self-perceptions were equivalent prior to participating in an introductory environmental science course. However, by the end of the 16-week course, students from the in-class group had significantly improved their environmental knowledge and expressed more environmentally friendly opinions compared with students from the Web-based group. The author offers suggestions, based on these results, for improving Web-based environmental education through future research.
Trajectories of Childhood Weight Gain: The Relative Importance of Local Environment versus Individual Social and Early Life Factors

Objective To determine the association between local environmental factors with child weight status in a longitudinal study, using a semi-parametric, group-based method, while also considering social and early life factors. Methods Standardized, directly measured BMI from 4–10 y of age, and group-based trajectory modeling (PROC TRAJ) were used to estimate developmental trajectories of weight change in a Québec birth cohort (n = 1,566). Associations between the weight trajectories and living location, social cohesion, disorder, and material and social deprivation were estimated after controlling for social and early life factors. Results Four weight trajectory groups were estimated: low-increasing (9.7%); low-medium, accelerating (36.2%); medium-high, increasing (43.0%); and high-stable (11.1%). In the low-increasing and medium-high trajectory groups, living in a semi-urban area was inversely related to weight, while living in a rural area was positively related to weight in the high-stable group. Disorder was inversely related to weight in the low-increasing group only. Other important risk factors for high-stable weight included obesity status of the mother, smoking during pregnancy, and overeating behaviors. Conclusions In this study, associations between local environment factors and weight differed by trajectory group. Early life factors appear to play a more consistent role in weight status. Further work is needed to determine the influence of place on child weight.
Role-based Label Propagation Algorithm for Community Detection

Community structure of networks provides comprehensive insight into their organizational structure and functional behavior. LPA is one of the most commonly adopted community detection algorithms with nearly linear time complexity. But it suffers from poor stability and occurrence of monster community due to the introduced randomize. We note that different community-oriented node roles impact the label propagation in different ways. In this paper, we propose a role-based label propagation algorithm (roLPA), in which the heuristics with regard to community-oriented node role were used. We have evaluated the proposed algorithm on both real and artificial networks. The result shows that roLPA is comparable to the state-of-the-art community detection algorithms.
Social and Institutional issues in the Adoption of School-based Technology-aided Sexual Health Education Program

Objective: School-based sexual health education interventions can reach young people of diverse backgrounds and equip them with knowledge and skills for protecting themselves against HIV/AIDS, unwanted pregnancies, and live healthy and responsible lives. However, given that school-based sexual health education intervention are health projects implemented in educational settings, variety of social and institutional issues can present challenges. This study aimed to obtain rich insights into the facilitating or inhibiting mediators for the implementation of a school-based sexual health education intervention in Uganda. Method: This study conducted 16 qualitative interviews to investigate the mediators for the implementation of the school-based sexual health education intervention based on experiences of two Ugandan schools: the school which successfully completed the implementation of the intervention, and the school which abandoned the intervention half-way the implementation. Results: Rather than the technological aspects, results indicate that the implementation was strongly influenced by interplay of social and institutional mediators, which were more favourable in the “successful” school than in the “failure school”. These mediators were: perceived students’ vulnerability to HIV and unwanted pregnancies; teachers’ skills and willingness to deliver the intervention, management support; match with routine workflow, social-cultural and religious compatibility, and stakeholder involvement. Conclusion: Rather than focusing exclusively on technological aspects, experiences from this evaluation suggest the urgent need to also create social, institutional, and religious climate which are supportive of school-based computer-assisted sexual health education. Evidence-based recommendations are provided, which can guide potential replications, improvements, and policy formulation in subsequent school-based sexual health education interventions.
Efficient Multiplier Architectures for Galois Fields GF(2 4n)

This contribution introduces a new class of multipliers for finite fields GF((2/sup n/)/sup 4/). The architecture is based on a modified version of the Karatsuba-Ofman algorithm (KOA). By determining optimized field polynomials of degree four, the last stage of the KOA and the module reduction can be combined. This saves computation and area in VLSI implementations. The new algorithm leads to architectures which show a considerably improved gate complexity compared to traditional approaches and reduced delay if compared with KOA-based architectures with separate module reduction. The new multipliers lead to highly modular architectures and are, thus, well suited for VLSI implementations. Three types of field polynomials are introduced and conditions for their existence are established. For the small fields, where n=2,3,. ,8, which are of primary technical interest, optimized field polynomials were determined by an exhaustive search. For each field order, exact space and time complexities are provided.
Time series analysis of long‐term river dissolved organic carbon records

Two long records of dissolved organic carbon (DOC) concentrations in river water were examined by a detailed time series analysis in order to shed light on the mechanisms generating observed increases in DOC concentrations across the UK. The records date back as far as 1962 and come from catchments 589 and 818 km2 in area. The DOC records were compared with others taken simultaneously for flow, pH, alkalinity, air temperature and rainfall, and in one of the catchments also for turbidity and conductivity. All records were examined by the seasonal Kendall test; frequency distributions of daily DOC measurements were examined; annual cycles were calculated, Autoregressive and impulse functions were derived for DOC against flow records. The time series analysis shows that: (i) DOC trends cannot be readily explained by trends in flow, pH, alkalinity, turbidity or conductivity; (ii) there is a significant increase in carbon flux from these catchments; (iii) maximum and minimum components of the annual distribution of daily readings both show increases in DOC, implying that DOC flux is increasing for differing hydrological pathways; (iv) increases in DOC concentrations coincide with increases in temperature, though the biggest increases in temperature are in the winter months when such increases might be expected to have less effect on DOC production; (v) change in trend, and therefore flux, was observed to occur after a severe drought in 1976. The study suggests that there are real, significant increases in carbon loss from upland peat catchments and that climate is a major driver, especially a severe drought. Severe drought triggering changes in the DOC flux might be attributed to enzymic latch mechanisms. Copyright © 2004 John Wiley & Sons, Ltd.
General Versus Specific Victim Blaming

Abstract The authors investigated (a) whether victim blaming is a general variable in a person's make-up or (b) whether the extent of blaming depends on the kind of victim considered. The authors evaluated scales for blaming (a) victims in general, (b) society in general, (c) a specific kind of victim (i.e., AIDS), and (d) the society in which AIDS victims live. The general and specific scales had favorable psychometric properties, including reliability. General and specific victim blaming were significantly and positively correlated, whereas victim blaming and society blaming were not significantly correlated. Multiple regression analyses provided evidence of construct validity for the scales. All blaming variables were significantly related in the hypothesized directions to social distance, social responsibility, and discrimination (regarding persons with AIDS). The general and specific scales made significant and unique contributions. Implications for attribution theory and research are specified.
Prevention of diabetes-promoted colorectal cancer by (n-3) polyunsaturated fatty acids and (n-3) PUFA mimetic

The global obesity / diabetes epidemic has resulted in robust increase in the incidence of colorectal cancer (CRC). Epidemiological, animal and human studies have indicated efficacy of (n-3) PUFA in chemoprevention of sporadic and genetic-driven CRC. However, diabetes-promoted CRC presents a treatment challenge that surpasses that of sporadic CRC. This report analyzes the efficacy of (n-3) PUFA generated by the fat-1 transgene that encodes an (n-6) to (n-3) PUFA desaturase, and of synthetic (n-3) PUFA mimetic (MEDICA analog), to suppress CRC development in carcinogen-induced diabetes-promoted animal model. Carcinogen-induced CRC is shown here to be promoted by the diabetes context, in terms of increased aberrant crypt foci (ACF) load, cell proliferation and epithelial dedifferentiation, being accompanied by increase in the expression of HNF4α, β-catenin, and β-catenin-responsive genes. Incorporating the fat-1 transgene in the diabetes context, or oral MEDICA treatment, resulted in ameliorating the diabetic phenotype and in abrogating CRC, with decrease in ACF load, cell proliferation and the expression of HNF-4α, β-catenin, and β-catenin-responsive genes. The specificity of (n-3) PUFA in abrogating CRC development, as contrasted with enhancing CRC by (n-6) PUFA, was similarly verified in CRC cell lines. These findings may indicate prospective therapeutic potential of (n-3) PUFA or MEDICA in the management of CRC, in particular diabetes-promoted CRC.
Multineuronal spike sequences repeat with millisecond precision

Cortical microcircuits are nonrandomly wired by neurons. As a natural consequence, spikes emitted by microcircuits are also nonrandomly patterned in time and space. One of the prominent spike organizations is a repetition of fixed patterns of spike series across multiple neurons. However, several questions remain unsolved, including how precisely spike sequences repeat, how the sequences are spatially organized, how many neurons participate in sequences, and how different sequences are functionally linked. To address these questions, we monitored spontaneous spikes of hippocampal CA3 neurons ex vivo using a high-speed functional multineuron calcium imaging (fMCI) technique that allowed us to monitor spikes with millisecond resolution and to record the location of spiking and non-spiking neurons. Multineuronal spike sequences (MSSs) were overrepresented in spontaneous activity compared to the statistical chance level. Approximately 75% of neurons participated in at least one sequence during our observation period. The participants were sparsely dispersed and did not show specific spatial organization. The number of sequences relative to the chance level decreased when larger time frames were used to detect sequences. Thus, sequences were precise at the millisecond level. Sequences often shared common spikes with other sequences; parts of sequences were subsequently relayed by following sequences, generating complex chains of multiple sequences.