Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring Wage and Occupational Discrimination: A Comprehensive Approach. Institute for Research on Poverty Discussion Papers.

Differences in t occupat! onal distributtons of men and women represen. an important source of male-female wage differentials. Although some studies of 3ex discrimination the labor market deal explicit1)7 with occupational segregation and some deal directly with the problem of unequal pay for equal work, few have concerned themselves with both issues simultaneously. This study develops an approach that decomposes the aggregate male-female differenzial such that the effects of occupational barriers are distinguishable from the effects of wage discrimination. Our model allows for variation both in occupational distribution and in wages resulting from differences in job qualifications and productivity Indicators. The usual approach to explaining wage differentials is shown to be a special case. Our approach uses multinomial logit analysis to predict occupational attainment from a set of personal characteristics. This estimation is performed on the National Longitudinal Survey (NLS) sample of mature men and the resulting parameters are used to simulate the occupational distribution of the NLS mature women that would exist if these women faced the same structure of occupational determination as the men. Wages are then estimated as a function of productivity measures for both men and women within each occupation so that the components of the wage differential can be calculated. We find that almost the entire differential would be eliminated by ending both forms of discrimination, with occupational discrimination accounting for one-third to one-half of the differential and pure wage discrimiltation the remainder.
Unity in Diversity: A Unified Parsing Strategy for Major Indian Languages

This paper presents our work to apply non linear neural network for parsing ﬁve resource poor Indian Languages belonging to two major language families - Indo-Aryan and Dravidian. Bengali and Marathi are Indo-Aryan languages whereas Kannada, Telugu and Malayalam belong to the Dravidian family. While little work has been done previously on Bengali and Telugu linear transition-based parsing, we present one of the ﬁrst parsers for Marathi, Kannada and Malayalam. All the Indian languages are free word order and range from being moderate to very rich in morphology. Therefore in this work we propose the usage of linguistically motivated morphological features ( sufﬁx and postposition ) in the non linear framework, to capture the intricacies of both the language families. We also capture chunk and gender, number, person information elegantly in this model. We put forward ways to represent these features cost effectively using monolingual distributed embeddings. Instead of relying on expensive morphological analyzers to extract the information, these embeddings are used effectively to increase parsing accuracies for resource poor languages. Our experiments provide a comparison between the two language families on the importance of varying morphological features. Part of speech taggers and chunkers for all languages are also built in the process.
Characteristics of Biosolids in Dimethyl Ether Dewatering Method

In this study, a method for removing water from biosolids that uses dimethyl ether (DME) as an extractant was considered. This study evaluates the applicability of the DME dewatering method to biosolid cakes by using a DME flow‐type experimental apparatus. It was found that a high dewatering ratio is clearly achieved by increasing the liquefied DME/biosolid ratio and lowering the liquefied DME linear velocity. As the liquefied DME/biosolid ratio was increased, the carbon content in dewatered biosolid showed a slight decrease and the TOC concentration in separated liquid increased significantly. Finally, the input energy Es to remove 1 kg of water from the biosolid cake, using both the DME dewatering method and the conventional drying method was estimated. The calculation shows that Es for the DME dewatering process is approximately a third of Es for the conventional thermal drying process.
A Quality-Centric Data Model for Distributed Stream Management Systems

It is challenging for large-scale stream management systems to return always perfect results when processing data streams originating from distributed sources. Data sources and intermediate processing nodes may fail during the lifetime of a stream query. In addition, individual nodes may become overloaded due to processing demands. In practice, users have to accept incomplete or inaccurate query results because of failure or overload. In this case, stream processing systems would benefit from knowing the impact of imperfect processing on data quality when making decisions about query optimisation and fault recovery. In addition, users would want to know how much the result quality was degraded. In this paper, we propose a quality-centric relational stream data model that can be used together with existing query processing methods over distributed data streams. Besides giving useful feedback about the quality of tuples to users, the model provides the distributed stream management system with information on how to optimise query processing and enhance fault tolerance. We demonstrate how our data model can be applied to an existing distributed stream management system. Our evaluation shows that it enables quality-aware load-shedding, while introducing only a small pertuple overhead.
Drinking in the year after treatment as a predictor of three-year drinking outcomes.

OBJECTIVE Previous research suggests that abstinence from alcohol during the first year posttreatment for alcohol-use disorders (AUDs) is an important, independent predictor of longer-term alcohol consumption and related functioning. The purpose of this study was to test the hypothesis that abstinence during the first year posttreatment initiation predicts alcohol use at Months 37-39. A second aim of this study was to explore the relationship between "moderate" drinking in the first year and drinking at Months 37-39. METHOD Secondary data analyses were conducted on the outpatient Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity) sample (N = 952 at baseline and 802 at Months 37-39). For these analyses, participants were classified first as abstainers, moderate drinkers, or heavy drinkers based on their alcohol use in the first year posttreatment initiation. RESULTS Analyses of covariance showed that the first-year drinker classification predicted both percentage of days abstinent and drinks per drinking day at Months 37-39. Subsequent analyses showed that the abstainers functioned significantly better than (1) both of the other drinker groups combined and (2) either of the other two groups, which did not differ from each other on either measure of alcohol use. A third set of exploratory analyses evaluated first-year abstinence and heavy drinking as continuous variables and showed an essentially linear relationship between them and drinking at 3 years. CONCLUSIONS This study confirmed the strong relationship between first-year abstinence and later drinking but did not show that participants who engaged in moderate drinking during the first year had positive alcohol-use outcomes at 3 years. The clinical implications of the findings, their generalizability to different populations of individuals presenting for specialty alcohol treatment, and future research directions are discussed.
Quadratic Sinusoidal Analysis of Neurons in Voltage Clamp

Nonlinear biophysical properties of individual neurons are known to play a major role in the nervous system. Earlier electrophysiological studies have made use of piecewise linear characterization of voltage clamped neurons, which consists of a sequence of linear admittances computed at different voltage levels. In this paper, the linear approach is extended to a piecewise quadratic characterization in two different ways. First, an analytical model is derived with power series following the work pionneered by Fitzhugh. Second, matrix calculus is developed to provide a novel quantitative analysis not dependent on differential equations. This method provides an assessment of quadratic responses for both data recorded from individual neurons and their corresponding models.
PSD93 Regulates Synaptic Stability at Neuronal Cholinergic Synapses

Neuronal cholinergic synapses play important roles in both the PNS and CNS. However, the mechanisms that regulate the formation, maturation, and stability of neuronal cholinergic synapses are poorly understood. In this study, we use the readily accessible mouse superior cervical ganglion (SCG) and submandibular ganglion (SMG) to examine the assembly of the postsynaptic complex of neuronal cholinergic synapses. We find that novel splicing forms of PSD93 (postsynaptic density 93) are expressed in SCG. By immunostaining, we show that PSD93 proteins precisely colocalize with neuronal nicotinic acetylcholine receptors (nAChRs) at synapses of the SCG and SMG. Subcellular fractionation demonstrates that PSD93 is enriched in the PSD fraction of SCG, and coimmunoprecipitation shows that PSD93 and neuronal nAChRs form a complex in vivo. Furthermore, two additional components of the well characterized glutamatergic postsynaptic complex, GKAP/SAPAP (guanylate kinase domain-associated protein/synapse-associated protein-associated protein) and Shank/ProSAP family proteins, are also present at neuronal cholinergic synapses. To assess the function of this protein complex at neuronal cholinergic synapses in vivo, we examined ganglia in mice that lack PSD93. We find that neuronal cholinergic synapses form properly in PSD93 null mice. After denervation, however, synaptic clusters of nAChRs disassemble much faster in mice lacking PSD93 than those in wild-type mice. These results demonstrate that PSD93 is a key component of the postsynaptic scaffold at neuronal cholinergic synapses and plays an important role in synaptic stability. In addition, these results suggest that the mechanism of postsynaptic scaffolding is conserved between neuronal cholinergic and glutamatergic synapses.
Human - Robot Swarm Interaction for Entertainment : From animation display to gesture based control

This work shows experimental results with three systems that take real-time user input to direct a robot swarm formed by tens of small robots. These are: real-time drawing, gesture based interaction with an RGB-D sensor and control via a hand-held tablet computer. Categories and Subject Descriptors I.2 [Artificial Intelligence]: Robotics
Time is myocardium and time is outcomes.

As an interventional cardiologist and a clinical trialist, I am often asked, “what do we need to do to improve mortality by another 1% in the setting of acute myocardial infarction? ” Indeed, nearly a decade and a half of effort and many hundreds of millions of dollars have been spent in pursuit of this elusive “1% reduction” in mortality by both the pharmaceutical and the device industry. As the report by the Assessment of the Safety and Efficacy of a New Thrombolytic (ASSENT 2) investigators in the present issue of Circulation highlights, 1 this kind of advance may not be achieved exclusively with new drugs or devices, but in also reducing time to treatment and in modifying patient behavior to seek these potentially life-saving treatments earlier. See p 2653 In a time of dizzying advances in diagnostic modalities, it is refreshing to see what a useful, simple, noninvasive, broadly accessible, easily repeatable/applied, and affordable tool the ECG is. 1 Time to treatment and ST-segment resolution were roughly similar in their ability to risk-stratify patients in the study by Fu et al.1 For both time to treatment and ST-segment resolution, there was an ≈2-fold gradient between the lowest risk category and the highest risk category ( 4 hours for time to treatment and >70% resolution versus <30% resolution for ST-segment resolution). Although time to treatment may reflect the extent of necrosis before therapy (with greater myocardial salvage observed with shorter times to treatment), ST-segment resolution may instead reflect the response to therapy. It is notable is that these 2 variables allow further risk stratification within each category of the other. As a result, limitations of ST-segment resolution as a sole end point become apparent: patients with electrocardiographic success (ie, complete ST resolution) but with symptoms who were treated …
The human Kv1.1 channel is palmitoylated, modulating voltage sensing: Identification of a palmitoylation consensus sequence

Voltage-dependent K+ channels rely on precise dynamic protein interactions with surrounding plasma membrane lipids to facilitate complex processes such as voltage sensing and channel gating. Many transmembrane-spanning proteins use palmitoylation to facilitate dynamic membrane interactions. Herein, we demonstrate that the human Kv1.1 ion channel is palmitoylated in the cytosolic portion of the S2-S3 linker domain at residue C243. Through heterologous expression of the human Kv1.1 protein in Sf9 cells, covalent radiolabeling with [3H]palmitate, chemical stability studies of the [3H]-palmitoylated protein, and site-directed mutagenesis, C243 was identified as the predominant site of palmitoylation. The functional sequelae of palmitoylation were examined by analysis of whole cell currents from WT and mutant channels, which identified a 20-mV leftward shift in the current-voltage relationship when palmitoylation at C243 (but not with other cysteine deletions) is prevented by site-directed mutagenesis, implicating a role for palmitoylated C243 in modulating voltage sensing through protein-membrane interactions. Database searches identified an amino acid palmitoylation consensus motif (ACP/RSKT) that is present in multiple other members of the Shaker subfamily of K+ channels and in several other unrelated regulatory proteins (e.g., CD36, nitric oxide synthase type 2, and the mannose-6 phosphate receptor) that are known to be palmitoylated by thioester linkages at the predicted consensus site cysteine residue. Collectively, these results (i) identify palmitoylation as a mechanism for K+ channel interactions with plasma membrane lipids contributing to electric field-induced conformational alterations, and ii) define an amino acid consensus sequence for protein palmitoylation.
The student voice in models of language learning motivation: listening to secondary school students’ experiences of foreign language learning

Post-14 foreign language learning in England has seen a decline in recent years. This follows changes to languages education policies which made the subject optional rather than part of the statutory National Curriculum. Such changes were predicated in part on the belief that optional study would increase students’ motivation to continue with language learning. However, the number of students choosing to study for a General Certificate in Secondary Education (GCSE) in another language decreased significantly once the changes were implemented in 2004.
Analysis of the relationship between self esteem, trait anger and anger expression in athletes making team sports.

The purpose of the study is to investigate the relationship between self esteem, trait anger and anger expression styles. The study group consists of basketball (n=53), football (n=76) and handball (n=73) players making a total of 202 athletes who played in different clubs in İzmir during 2010-2011 season. In the research “Self Esteem Scale” developed by Arıcak (1999), “Trait anger-anger expression styles scale” which was developed by Spielberger (1988) and adapted to Turkish language by Özer (1994) and a “personal information form” developed by authors was utilized. In data analysis frequency distributions, t-test, one-way analysis of variance (ANOVA) and Pearson correlation coefficient were used. As a result; no significant results were obtained in self esteem, trait anger-anger expression styles according to gender, sport branch, sport age, being a national athlete. However, significant correlations were obtained between self esteem, trait anger and anger expression styles scales.
Cognition-based Segmentation for Music Information Retrieval Systems

Abstract This paper investigates the generic problem of model selection in the specific context of Music Information Retrieval (MIR). In MIR research, similarity measures are developed for ranking musical items with respect to their relevance to a user's musical query. The application of such similarity measures in MIR systems typically requires musical works to be divided into more manageable units. This involves two tasks: melody segmentation and voice separation. For both of these tasks, several computational models have been proposed in the symbolic domain. It seems reasonable to assume that those solutions that are most in accordance with human performance will result in the best ranking of retrieval output. We conducted two experiments, each with twenty experts and twenty novices. In the melody segmentation experiment, we found a high agreement between the participants. Evaluating algorithm output against participant data, we conclude that human output cannot be distinguished from three of the segmentation algorithms (Grouper, IDyOM and LBDM). For voice separation—which we evaluated by means of a melody identification task—the situation is different, as the combined results of two algorithms (Skyline and SSA) were shown to agree best with experimental results, and differences were found between novice and expert performance. Several other model selection criteria besides performance are discussed in conclusion.
Estimating uncertain spatial relationships in robotics

In this paper, we describe a representation for spatial information, called the stochastic map, and associated procedures for building it, reading information from it, and revising it incrementally as new information is obtained. The map contains the estimates of relationships among objects in the map, and their uncertainties, given all the available information. The procedures provide a general solution to the problem of estimating uncertain relative spatial relationships. The estimates are probabilistic in nature, an advance over the previous, very conservative, worst-case approaches to the problem. Finally, the procedures are developed in the context of state-estimation and filtering theory, which provides a solid basis for numerous extensions.
Excitatory and inhibitory intermediate zone interneurons in pathways from feline group I and II afferents: differences in axonal projections and input

The aim of the present study was to compare properties of excitatory and inhibitory spinal intermediate zone interneurons in pathways from group I and II muscle afferents in the cat. Interneurons were labelled intracellularly and their transmitter phenotypes were defined by using immunocytochemistry. In total 14 glutamatergic, 22 glycinergic and 2 GABAergic/glycinergic interneurons were retrieved. All interneurons were located in laminae V–VII of the L3–L7 segments. No consistent differences were found in the location, the soma sizes or the extent of the dendritic trees of excitatory and inhibitory interneurons. However, major differences were found in their axonal projections; excitatory interneurons projected either ipsilaterally, bilaterally or contralaterally, while inhibitory interneurons projected exclusively ipsilaterally. Terminal projections of glycinergic and glutamatergic cells were found within motor nuclei as well as other regions of the grey matter which include the intermediate region, laminae VII and VIII. Cells containing GABA/glycine had more restricted projections, principally within the intermediate zone where they formed appositions with glutamatergic axon terminals and unidentified cells and therefore are likely to be involved in presynaptic as well as postsynaptic inhibition. The majority of excitatory and inhibitory interneurons were found to be coexcited by group I and II afferents (monosynaptically) and by reticulospinal neurons (mono‐ or disynaptically) and to integrate information from several muscles. Taken together the morphological and electrophysiological data show that individual excitatory and inhibitory intermediate zone interneurons may operate in a highly differentiated way and thereby contribute to a variety of motor synergies.
Toward an Optimal SVM Classification System for Hyperspectral Remote Sensing Images

Recent remote sensing literature has shown that support vector machine (SVM) methods generally outperform traditional statistical and neural methods in classification problems involving hyperspectral images. However, there are still open issues that, if suitably addressed, could allow further improvement of their performances in terms of classification accuracy. Two especially critical issues are: 1) the determination of the most appropriate feature subspace where to carry out the classification task and 2) model selection. In this paper, these two issues are addressed through a classification system that optimizes the SVM classifier accuracy for this kind of imagery. This system is based on a genetic optimization framework formulated in such a way as to detect the best discriminative features without requiring the a priori setting of their number by the user and to estimate the best SVM parameters (i.e., regularization and kernel parameters) in a completely automatic way. For these purposes, it exploits fitness criteria intrinsically related to the generalization capabilities of SVM classifiers. In particular, two criteria are explored, namely: 1) the simple support vector count and 2) the radius margin bound. The effectiveness of the proposed classification system in general and of these two criteria in particular is assessed both by simulated and real experiments. In addition, a comparison with classification approaches based on three different feature selection methods is reported, i.e., the steepest ascent (SA) algorithm and two other methods explicitly developed for SVM classifiers, namely: 1) the recursive feature elimination technique and 2) the radius margin bound minimization method
The association of asthma with BMI and menarche in the 1958 British Birth Cohort

Abstract Background: Obesity and early menarche have been associated with asthma. In this report, we assess the association of asthma with BMI and with changes in BMI from childhood to early adulthood. In addition, we determine if, in girls, any observed association of asthma with menarche can be explained by BMI. Methods: In a large national birth cohort, the associations of asthma at age 7, 11, 16 and 33 years with BMI, and of, asthma at age 33 years with changes in BMI from age 7 to age 33 years was assessed using logistic and mixed effects models as appropriate. Associations of asthma with age of menarche in girls were similarly assessed with and without adjustment for BMI. Results: Information on asthma, BMI, onset of menarche and confounders at all assessments was available for 1968 girls and 2223 boys. Obesity was relatively uncommon (<2%) in childhood. Overweight (BMI 25+) girls had more asthma. Girls with early menarche were more likely to be overweight. At age 11 years, asthma was associated with early menarche (OR = 1.70, 95% CI 1.17–2.47, after adjustment for BMI OR = 1.60, 95% CI 1.10–2.34). Across all ages, asthma was significantly associated with BMI (OR = 1.50, 95% CI 1.18–1.90) but not with early menarche (OR = 1.24, 95% CI 0.95–1.63). Conclusion: Asthma is more common in overweight girls. Early menarche is more common in overweight girls but this does not explain its association with asthma at age 11 years. Early menarche is not a risk factor for asthma at age 33 years in this cohort.