Miracle-dz/UniFAR-FTUs huggingface dataset:
HORMONAL CONTROL OF LYSOSOMAL ENZYME RELEASE FROM HUMAN NEUTROPHILS

The purpose of this investigation was to examine the effects of autonomic neurohormones, cyclic nucleotides, and related agents on the immunologic discharge of lysosomal enzymes from, and phagocytosis by, purified human neutrophils. In order to discern the possible intracellular mechanisms by which certain neurohormones influence neutrophil function, the concentrations of cyclic AMP and cyclic GMP in neutrophils were assessed during cell contact with phagocytizable particles and autonomic agents. The model system employed for study was the interaction of purified human neutrophils with rheumatoid arthritic (RA) serum-treated zymosan particles at 37°C in a neutral, balanced salt solution containing glucose. Neutrophils ingested the particles and discharged β-glucuronidase but not lactate dehydrogenase activity during 30 min of incubation. Treatment of zymosan particles with RA serum was more effective than treatment with normal serum with regard to the extent of both particle uptake and lysosomal enzyme release. During contact of neutrophils with RA serum-treated zymosan particles epinephrine, isoproterenol, and cyclic AMP inhibited both particle ingestion and β-glucuronidase discharge. These actions of epinephrine were associated with a concomitant elevation of cyclic AMP levels. In contrast to the actions of catecholamines and cyclic AMP, acetylcholine and cyclic GMP accelerated lysosomal enzyme release without affecting particle uptake. The actions of acetylcholine were associated with a concomitant elevation of cyclic GMP levels. Increases in neutrophil levels of cyclic GMP but not of cyclic AMP were associated also with the discharge of β-glucuronidase provoked by particles in the absence of added cholinergic agents. The data suggest that the immunologic release of lysosomal enzymes from human neutrophils can be regulated by autonomic neurohormones, perhaps via the selective formation of appropriate nucleotides.
Early Interventions for Children With Reading Problems: Study Designs and Preliminary Findings

Preliminary results are described for a multi-year grant, entitled Early Interventionsfor Children with Reading Problems and funded by the National Institute ofChild Health and Human Development. Results from a kindergarten prevention study of 181 children in a culturally diverse school district show that 15 minutes ofdaily phonological awareness activities accelerated growth in phonological analysis skill relative to a comparison group. In a study with 113 second and third graders identified with reading disabilities, children who received an Orton-Gillingham, synthetic phonics approach outperformed children receiving a combined synthetic/analytic phonics approach or a sight-word approach in the development of literacy-related skills. However, when verbal IQ and ethnicity were included in the model of skill development, children tended to make comparable gains in all three programs. Finally, a study of375 first and second graders eligible for Title 1 tutorials highlights the importance ofexplicit instruction in the alphabetic code during classroom instruction if reading failure is to be avoided.
Effects of Age and Polytherapy, Risk Factors of Valproic Acid (VPA) Hepatotoxicity, on the Excretion of Thiol Conjugates of (E)‐2,4‐diene VPA in People with Epilepsy Taking VPA

Summary: Purpose: Valproic acid (VPA) is an antiepileptic drug (AED) used for generalized and absence seizures. It has a rare but potentially fatal hepatotoxicity side effect, and many researchers believe that reactive metabolites of VPA could be involved. We demonstrated here that the thiol conjugates of (E)‐2,4‐diene VPA were significantly elevated in a high‐risk group of patients.
Discovering Relational Items Sets Efficiently

Frequent item set mining is a major data mining research area. Generalising from the standard single table case to a multirelational setting is simple in principle, but hard in practice. That is, it is simple to define frequent item sets in the multirelational setting, as well as extending the A-Priori algorithm. It is hard, because the well-known frequent pattern explosion at low min-sup settings is far worse than it is in the standard case. In this paper we introduce an effective algorithm for the discovery of frequent, multi-relational item sets. These relational patterns show which item sets occur together. Answering questions like: ‘What type of Books are bought together with what Record types? ’. Hence, they provide a symmetric insight in the relation and reveal patterns that are relevant with respect to the relation. It extends our earlier work on using MDL to discover a small set of characteristic item sets. The algorithm, R-KRIMP, first discovers the small set of characteristic patterns in the single tables and then combines these to find a small set of characteristic multi-relational item sets. This reduces the original search space dramatically and, hence, brings down the computational complexity by orders of magnitude. In the experiments we show that this approach yields a very good approximation of the naive approach, joining all tables into one huge table, while being far more efficient.
Diffuse Intrinsic Brainstem Tumor in an Infant: A Case of Therapeutic Efficacy With Vinorelbine

Brainstem gliomas constitute 10% to 20% of all pediatric tumors of the central nervous system, and diffusely infiltrative brainstem gliomas are the most common brainstem tumors associated with a poor prognosis. A small subset of these tumors is benign, showing low-grade features on histology. The role of chemotherapy in the management of these tumors is ill defined, especially in the neonates. There are anecdotal reports of spontaneous remission, but the natural history of these tumors does not support a wait-and-see approach. Thus, we report a successful experience of chemotherapy in a 4-month-old girl with a diffuse brainstem fibrillary astrocytoma, treated with vinorelbine (30 mg/m2/d on days 0, 8, and 22), a vinca alkaloid that has shown activity against glioma. Our experience suggests that vinorelbine may be effective in pediatric low-grade gliomas as this patient showed significant clinical improvement over a short period of time.
First Step into Visceral Interaction with Autonomous Vehicles

Autonomous vehicles (AVs) seem to be the next big step into the future of mobility solutions. Various research institutions in the automobile industry and academic sectors are striving to come out with the most futuristic concept. This paper focuses on the interaction between AVs and pedestrians. Furthermore, the paper aims to explore if complex communication needs can be signaled to pedestrians through motion behavior of the vehicle. In order to learn how other road users feel surrounded by self-driving cars, participants were confronted with different drivability of a self-programmed vehicle during our evaluation. As the results show, the vehicle's motion behavior is able to evoke certain emotions, which in turn lead to rational decisions within the participants. This can be seen as a form of mutual communication.
The impact of exposure categorisation for grouped analyses of cohort data

Background: Poisson regression is routinely used in occupational and environmental epidemiology. For typical Poisson regression analyses, person-time and events are tabulated by categorising predictor variables that were originally measured on a continuous scale. In order to estimate a dose-response trend, a researcher must decide how to categorise exposures and how to assign scores to exposure groups. Aims: To investigate the impact on regression results of decisions about exposure categorisation and score assignment. Methods: Cohort data were generated by Monte Carlo simulation methods. Exposure categories were defined by quintiles or deciles of the exposure distribution. Scores were assigned to exposure groups based on category midpoint and mean exposure levels. Estimated exposure-disease trends derived via Poisson regression were compared to the “true” association specified for the simulation. Results: Under the assumption that exposures conform to a lognormal or exponential distribution, trend estimates tend to be negatively biased when scores are assigned based on category midpoints and positively biased when scores are assigned based on cell specific mean values. The degree of bias was greater when exposure categories were defined by quintiles of the exposure distribution than when categories were defined by deciles of the exposure distribution. Conclusions: The routine practice of exposure categorisation and score assignment introduces exposure misclassification that may be differential with respect to disease status and, consequently, lead to biased exposure-disease trend estimates. When using the Poisson regression method to evaluate exposure-disease trends, such problems can be minimised (but not necessarily eliminated) by forming relatively refined exposure categories based on percentiles of the exposure distribution among cases, and by assigning scores to exposure categories that reflect person-time weighted mean exposure levels.
Randomized and multipointer paging with locality of reference

What is the best paging algorithm if one has partial information about the possible sequences of page requests? Borodin, Irani, Raghavan and Schieber [2] proposed a framework in which such questions can be addressed, by studying the competitive analysis of paging algorithms in the access graph model. This model restricts page requests so that they conform to a notion of locality of reference, given by an arbitrary access graph. It can also be viewed as an example of a diffuse adversary model, as defined by Koutoupias and Papadimitriou [11]. We present two results in this model. The first is a randomized algorithm which is strongly competitive against oblivious adversaries for undirected access graphs. We also present strongly competitive algorithms against adversaries that can use multiple pointers into the access graph in order to construct the reference sequence. This models more closely a multiprogramming environment, or a situation in which there are multiple threads of control.
Understanding the impact of commercialization on public support for scientific research: Is it about the funding source or the organization conducting the research?

This research examines the influence of commercialization on support for scientific research. It compares the effects of the funding source with the type of organization on public support for stem cell research. Using a national Australian telephone survey (n = 1000), the results reveal that support drops significantly when scientific research is funded by private rather than public interests, and even more so when it is conducted in a private company rather than a public university. Respondents’ preference for university research was enhanced if they trusted universities, distrusted major companies and believed that the research would be beneficial. A preference for public funding was also associated with lower trust in companies and a belief that the research would benefit people. Implications of these results are discussed in relation to the challenge of maintaining public support in an increasingly commercialized research environment.
Segmentation of continuous speech using acoustic-phonetic parameters and statistical learning

In this paper, we present a methodology for combining acoustic-phonetic knowledge with statistical learning for automatic segmentation and classification of continuous speech. At present we focus on the recognition of broad classes-vowel, stop, fricative, sonorant consonant and silence. Judicious use is made of 13 knowledge-based acoustic parameters (APs) and support vector machines (SVMs). It has been shown earlier that SVMs perform comparable to hidden Markov models (HMMs) for detection of stop consonants. We achieve performance on segmentation of continuous speech better than the BMM based approach that uses 39 cepstrum-based speech parameters.
Sex Differences in Computer Attitudes and Beliefs Among Rural Middle School Children After a Teacher Training Intervention

AbstractSeventeen rural teachers of Grades 4-8 completed training in computer education and gender equity. Their students and students of nonparticipating teachers answered questions about attitudes toward and beliefs about gender appropriateness of five subjects. The training program improved teacher skills and increased student access to computing. There was no significant difference between participating and nonparticipating groups in beliefs about their gender appropriateness of various subjects, but the nonparticipating group reported liking computers, science, and mathematics more than did the participating group. Sex differences were reported for liking writing, computers, and video games, and for beliefs about gender appropriateness of these three subjects. An interaction effect occurred between group and sex in liking science. More boys than girls had home computers (5:4), and more males than females used them (5:3).
T-Wave Alternans Found in Preventricular Tachyarrhythmias in CCU Patients Using a Wavelet Transform-Based Methodology

Ventricular tachyarrhythmias are potentially lethal cardiac pathologies and the commonest cause of sudden cardiac death. Efforts to predict the onset of such events are based on feature extraction from the surface ECG. T-wave alternans (TWAs) are considered a marker of abnormal ventricular function that may be associated with ventricular tachycardia (VT) and ventricular fibrillation. A novel TWA detection algorithm utilizing the continuous wavelet transform is described in this paper. Simulated ECGs containing artificial TWA were used to test the algorithm that achieved a sensitivity of 91.40% and a specificity of 94.00%. The algorithm was subsequently used to analyze the ECGs of eight patients prior to the onset of VT. Of these, the algorithm indicated that five patients exhibited TWA prior to the onset of the tachyarrhythmic events, while the remaining three patients did not exhibit identifiable TWA. Healthy individuals were also studied in which one short TWA episode was detected by the algorithm. However, closer visual inspection of the data revealed this to be a likely false positive result.
Characteristics and mechanism of tunable work function gate electrodes using a bilayer metal structure on SiO/sub 2/ and HfO/sub 2/

In this letter, we investigate a method to adjust the gate work function of an MOS structure by stacking two metals with different work functions. This method can provide work function tunability of approximately 1 eV as the bottom metal layer thickness is increased from 0 to about 10 nm. This behavior is demonstrated with different metal combinations on both SiO/sub 2/ and HfO/sub 2/ gate dielectrics. We use capacitance-voltage (C-V) characteristics to investigate the effect of different annealing conditions and different metal/metal bilayer couples on the work function. By comparing the as-deposited and annealed films, and by comparing with metals that are relatively inert with each other, we deduce that the work function tuning behavior likely involves metal/metal interdiffusion.
The Positive and Negative Syndrome Scale (PANSS): A Three-Factor Model of Psychopathology in Marginally Housed Persons with Substance Dependence and Psychiatric Illness

Rates of psychopathology are elevated in marginalized and unstably housed persons, underscoring the need for applicable clinical measures for these populations. The Positive and Negative Syndrome Scale (PANSS) is a clinical instrument principally developed for use in schizophrenia to identify the presence and severity of psychopathology symptoms. The current study investigates whether a reliable and valid PANSS factor structure emerges in a marginally housed, heterogeneous sample recruited from the Downtown Eastside of Vancouver where substance use disorders and psychiatric illness are pervasive. Participants (n = 270) underwent structured clinical assessments including the PANSS and then were randomly assigned to either exploratory (EFA) or confirmatory factor analytic (CFA) subsamples. EFA pointed to a novel three factor PANSS. This solution was supported by CFA. All retained items (28 out of 30) load significantly upon hypothesized factors and model goodness of fit analyses are in the acceptable to good range. Each of the three first-order factor constructs, labeled Psychosis/Disorganized, Negative Symptoms/Hostility, and Insight/Awareness, contributed significantly to measurement of a higher-order psychopathology construct. Further, the latent structure of this 3-factor solution appears temporally consistent over one-year. This PANSS factor structure appears valid and reliable for use in persons with multimorbidity, including substance use disorders. The structure is somewhat distinct from existing solutions likely due to the unique characteristics of this marginally housed sample.
Changes in Carbon Cycling during Development of Successional Agroforestry

Successional agroforestry systems (SAFS) mimic the structure of natural forests while providing economical outputs. This study clarifies how carbon cycling and carbon sequestration change during successional development of SAFS. In Brazil, three successional stages of SAFS, 6, 12, and 34 years old, were compared in terms of carbon balance. Aboveground biomass, fruit harvest, litterfall, soil respiration, and soil organic carbon were measured for two years and analyzed. Carbon sequestration expressed by net primary productivity increased with age of SAFS from 9.8 Mg·C·ha −1 ·year −1 in 6-year-old system to 13.5 Mg·C·ha −1 ·year −1 in 34-year-old system. Accumulation of plant biomass and increased internal carbon cycling in SAFS led to an intensive sequestration of carbon. SAFS can be a sustainable way of agricultural production on vulnerable tropical soils.
Picture Imperfect: Photography and Eugenics, 1870-1940

Introduction Racial-type Photographs in the Colonial Period The Degenerate Face: Nineteenth-Century Prison Photographs The Eugenics Movement Begins: Galton and the Races of Britain Building a Healthy Nation: Eugenic Images in the United States, 1890-1935 Creating the Master Race: Photography and Racial Selection in Germany Sub-Human Versus the Master Race: Racial-Type Photographs and Nazi Party Propaganda Eugenics Under Fire: the Racial-type Imagery of Boas, Du Bois, Huxley and Hadden Conclusion Index.
Social influence in social advertising: evidence from field experiments

Social advertising uses information about consumers' peers, including peer affiliations with a brand, product, organization, etc., to target ads and contextualize their display. This approach can increase ad efficacy for two main reasons: peers' affiliations reflect unobserved consumer characteristics, which are correlated along the social network; and the inclusion of social cues (i.e., peers' association with a brand) alongside ads affect responses via social influence processes. For these reasons, responses may be increased when multiple social signals are presented with ads, and when ads are affiliated with peers who are strong, rather than weak, ties. We conduct two very large field experiments that identify the effect of social cues on consumer responses to ads, measured in terms of ad clicks and the formation of connections with the advertised entity. In the first experiment, we randomize the number of social cues present in word-of-mouth advertising, and measure how responses increase as a function of the number of cues. The second experiment examines the effect of augmenting traditional ad units with a minimal social cue (i.e., displaying a peer's affiliation below an ad in light grey text). On average, this cue causes significant increases in ad performance. Using a measurement of tie strength based on the total amount of communication between subjects and their peers, we show that these influence effects are greatest for strong ties. Our work has implications for ad optimization, user interface design, and central questions in social science research.
End-to-End Prediction of Buffer Overruns from Raw Source Code via Neural Memory Networks

Detecting buffer overruns from a source code is one of the most common and yet challenging tasks in program analysis. Current approaches based on rigid rules and handcrafted features are limited in terms of flexible applicability and robustness due to diverse bug patterns and characteristics existing in sophisticated real-world software programs. In this paper, we propose a novel, data-driven approach that is completely end-to-end without requiring any hand-crafted features, thus free from any program language-specific structural limitations. In particular, our approach leverages a recently proposed neural network model called memory networks that have shown the state-of-the-art performances mainly in question-answering tasks. Our experimental results using source code samples demonstrate that our proposed model is capable of accurately detecting different types of buffer overruns. We also present in-depth analyses on how a memory network can learn to understand the semantics in programming languages solely from raw source codes, such as tracing variables of interest, identifying numerical values, and performing their quantitative comparisons.
John Henryism, Gender, and Arterial Blood Pressure in an African American Community

Objective To examine the interaction between gender and John Henryism in relationship to arterial blood pressure in an African American community in the Southern United States. It was hypothesized that, within this specific social and cultural context, John Henryism would be associated with blood pressure differently for men and women. Methods A cross-sectional survey of 600 persons, aged 25 to 65, was conducted in the African American community of a small Southern city. John Henryism was assessed using the 12-item John Henryism Scale for Active Coping. Blood pressure was assessed by conventional methods. Results The interaction effect between gender and John Henryism was assessed as a cross-product term in ordinary least squares regression analysis using arterial blood pressure as the dependent variable, and with logistic regression using hypertension as the dependent variable. This interaction effect was significant (p < .05) in relation to systolic blood pressure and hypertension, with the effect evident (p < .07) in relation to diastolic blood pressure. For men, as John Henryism increases, blood pressure and the risk of hypertension increases. For women, as John Henryism increases, blood pressure and the risk of hypertension decreases. Conclusions The association of the behavioral disposition of John Henryism with blood pressure is dependent on the gender of the individual. Men and women face differing cultural expectations and social structural constraints in this community. The sociocultural context modifies the meaning of the behavioral disposition, and hence its effects.
Layoff Survivors’ Perceptions Of Fairness As Determinant Of Affective Commitment Following Downsizing

This study examines the effects of fairness perceptions on the organizational commitment of downsizing survivors during the February 2001 economic crisis. Samples were drawn from bluecollar employees in the service industry. In the statistical analysis, distributive justice was found to be significantly related to the affective commitment of survivors, while procedural justice was not found to be positively associated with the affective commitment of survivors in the service industry. The analysis also yields that interactional justice is strongly and positively associated with the affective commitment of survivors. The managerial and theoretical implications of study are also discussed.