LLukas22/scidocs huggingface dataset:
Moving Beyond Neighborhood: Activity Spaces and Ecological Networks As Contexts for Youth Development.

Many scholars, policy analysts, and practitioners agree that neighborhoods are important contexts for urban youth. Yet, despite decades of research, our knowledge of why and how neighborhoods influence the day-to-day lives of youth is still emerging. Theories about neighborhood effects largely assume that neighborhoods operate to influence youth through exposure-based mechanisms. Extant theoretical approaches, however, have neglected the processes by which neighborhood socioeconomic contexts influence the routine spatial exposures-or activity spaces-of urban residents. In this article, we argue that exposure to organizations, institutions, and other settings that characterize individual activity spaces is a key mechanism through which neighborhoods influence youth outcomes. Moreover, we hypothesize that aggregate patterns of shared local exposure-captured by the concept of ecological networks-are influenced by neighborhood socioeconomic characteristics and are independently consequential for neighborhood youth. Neighborhoods in which residents intersect in space more extensively as a result of routine conventional activities will exhibit higher levels of social capital relevant to youth well-being, including (1) familiarity, (2) beneficial (weak) social ties, (3) trust, (4) shared expectations for pro-social youth behavior (collective efficacy), and (5) the capacity for consistent monitoring of public space. We then consider the implications of ecological networks for understanding the complexities of contextual exposure. We specifically discuss the role of embeddedness in ecological communities-that is, clusters of actors and locations that intersect at higher rates-for understanding contextual influences that are inadequately captured by geographically defined neighborhoods. We conclude with an overview of new approaches to data collection that incorporate insights from an activity-space and ecological-network perspective on neighborhood and contextual influences on youth. Our approach offers (1) a new theoretical approach to understanding the links between neighborhood socioeconomic characteristics and youth-relevant dimensions of neighborhood social capital; (2) a basis for conceptualizing contextual influences that vary within, or extend beyond, traditionally understood geographic neighborhoods; and (3) a suite of methodological tools and resources to address the mechanisms of contextual influence more precisely. Research into the causes and consequences of urban neighborhood routine activity structures will illuminate the social processes accounting for compromised youth outcomes in disadvantaged neighborhoods and enhance the capacity for effective youth-oriented interventions.
Semantic Role Labeling Via Integer Linear Programming Inference

We present a system for the semantic role labeling task. The system combines a machine learning technique with an inference procedure based on integer linear programming that supports the incorporation of linguistic and structural constraints into the decision process. The system is tested on the data provided in CoNLL2004 shared task on semantic role labeling and achieves very competitive results.
Derivation and validation of REASON: a risk score identifying candidates to screen for peripheral arterial disease using ankle brachial index.

BACKGROUND
The recommendation of screening with ankle brachial index (ABI) in asymptomatic individuals is controversial. The aims of the present study were to develop and validate a pre-screening test to select candidates for ABI measurement in the Spanish population 50-79 years old, and to compare its predictive capacity to current Inter-Society Consensus (ISC) screening criteria.


METHODS AND RESULTS
Two population-based cross-sectional studies were used to develop (n = 4046) and validate (n = 3285) a regression model to predict ABI < 0.9. The validation dataset was also used to compare the model's predictive capacity to that of ISC screening criteria. The best model to predict ABI < 0.9 included age, sex, smoking, pulse pressure and diabetes. Assessment of discrimination and calibration in the validation dataset demonstrated a good fit (AUC: 0.76 [95% CI 0.73-0.79] and Hosmer-Lemeshow test: χ(2): 10.73 (df = 6), p-value = 0.097). Predictions (probability cut-off value of 4.1) presented better specificity and positive likelihood ratio than the ABI screening criteria of the ISC guidelines, and similar sensitivity. This resulted in fewer patients screened per diagnosis of ABI < 0.9 (10.6 vs. 8.75) and a lower proportion of the population aged 50-79 years candidate to ABI screening (63.3% vs. 55.0%).


CONCLUSION
This model provides accurate ABI < 0.9 risk estimates for ages 50-79, with a better predictive capacity than that of ISC criteria. Its use could reduce possible harms and unnecessary work-ups of ABI screening as a risk stratification strategy in primary prevention of peripheral vascular disease.
Delay in presentation of symptomatic referrals to a breast clinic: patient and system factors

We attempted to identify factors associated with delay in presentation and assessment of women with breast symptoms who attended a London breast clinic. A total of 692 consecutive symptomatic referrals, aged 40–75 years, were studied. Patient delay, assessed prior to diagnosis, was defined as time elapsing between symptom discovery and first presentation to a medical provider. This was studied in relation to: reasons for delaying, beliefs and attitudes, socio-demographic and clinical variables, psychiatric morbidity and subsequent diagnosis. Thirty-five per cent of the cohort delayed presentation 4 weeks or more (median 13 days). The most common reason given was that they thought their symptom was not serious (odds ratio (OR) =3.6–8.0). Others thought their symptom would go away (OR = 3.73, 95% CI 2.2–6.4) or delayed because they were scared (OR = 4.61, 95% CI 2.1–10.0). Delay was associated with psychiatric morbidity but not age. Patients who turned out to have cancer tended to delay less (median 7 days) but not significantly. Median system delay – time between first medical consultation and first clinic visit – was 18 days. Patients who thought they had cancer and those so diagnosed were seen more promptly (median 14 days). Most factors, including socio-economic status and ethnicity were non-contributory. Beliefs about breast symptoms and their attribution are the most important factors determining when women present. Health education messages should aim to convince symptomatic women that their condition requires urgent evaluation, without engendering fear in them. © 2000 Cancer Research Campaign
Early detection: The case for early detection

Early detection represents one of the most promising approaches to reducing the growing cancer burden. It already has a key role in the management of cervical and breast cancer, and is likely to become more important in the control of colorectal, prostate and lung cancer. Early-detection research has recently been revitalized by the advent of novel molecular technologies that can identify cellular changes at the level of the genome or proteome, but how can we harness these new technologies to develop effective and practical screening tests?
A climbing autonomous robot for inspection applications in 3D complex environments

Often inspection and maintenance work involve a large number of highly dangerous manual operations, especially within industrial fields such as shipbuilding and construction. This paper deals with the autonomous climbing robot which uses the "caterpillar" concept to climb in a complex 3D metallic-based structures. During its motion the robot generates in real-time the path and grasp planning in order to ensure stable self-support, avoid the environment obstacles, and optimise the robot consumption during the inspection. The control and monitoring of the robot is achieved through an advanced Graphical User Interface to allow an effective and user friendly operation of the robot. The experiments confirm its advantages in executing the inspection operations.
Altmetric: enriching scholarly content with article-level discussion and metrics

Scholarly content is increasingly being discussed, shared and bookmarked online by researchers. Altmetric is a start-­up that focuses on tracking, collecting and measuring this activity on behalf of publishers and here we describe our approach and general philosophy. Over the past year we've seen sharing and discussion activity around approximately 750k articles. The average number of articles shared each day grows by 5-­ 10% a month. We look at examples of how people are interacting with papers online and at how publishers can collect and present the resulting data to deliver real value to their authors and readers. Introduction Scholars are increasingly visible on the web and social media 1. While the majority of their online activities may not be directly related to their research they are nevertheless discussing, sharing and bookmarking scholarly articles online in large numbers. We know this because our job at Altmetric is to track the attention paid to papers online. Founded in January 2011 and with investment from Digital Science we're a London based start-­‐up that identifies, tracks and collects article level metrics on behalf of publishers. Article level metrics are quantitative or qualitative indicators of the impact that a single article has had. Examples of the former would be a count of the number of times the article has been downloaded, or shared on Twitter. Examples of the latter would be media coverage or a blog post from somebody well respected in the field. Tracking the conversations around papers Encouraging audiences to engage with articles online isn't anything new for many publishers. The Public Library of Science (PLoS), BioMed Central, Cell Press and Nature Publishing Group have all tried encouraging users to leave comments on papers with varying degrees of success but the response from users has generally been poor, with only a small fraction of papers ever receiving notable attention 2. A larger proportion of papers are discussed in some depth on academic blogs and a larger still proportion shared on social networks like Twitter, Facebook and Google+. Scholars seem to feel more comfortable sharing or discussing content in more informal environments tied to their personal identity and where
Prevention and treatment of oral mucositis 
in patients receiving chemotherapy

Oral mucositis is one of the most common side effects of cancer treatment (chemotherapy and/or radiotherapy). It is an inflammatory process that affects the mucosa of the oral cavity, giving rise to erythematous areas in combination with ulcers that can reach a large size. The true importance of oral mucositis is the complications it causes - fundamentally intense pain associated to the oral ulcers, and the risk of overinfection. This in turn may require reduction or even suspension of the antineoplastic treatment, with the risk of seriously worsening the patient prognosis. This points to the importance of establishing therapeutic tools of use in the prevention and/or treatment of mucositis. The present study offers a literature review of all the articles published over the last 10 years referred to the prevention and/or treatment of oral mucositis associated to chemotherapy. Key words:Oral mucositis, management, prevention, treatment, chemotherapy.
Control of DFIG-based wind farms for power network frequency support

This paper investigates the frequency control scheme of a doubly fed induction generator (DFIG)-based wind farms to provide frequency support for the power system steady operation. Due to the decoupling of the rotor speed and the grid frequency by the connected converters, the DFIG-based wind farm rarely contributes to the network effective inertia. This is particularly true in the small isolated power system with lower system inertia. A novel method of controlling the DFIG active power and rotor speed is proposed to enable the DFIG-based wind farms participate in the network frequency support. A typical network that combines synchronous generator-based power plants and DFIG-based wind farms is modeled by MATLAB/Simulink to assess the system dynamic performance. The control strategy of the DFIG-based wind farm for the power network frequency regulation is validated by the simulation studies. With the proposed strategy, the DFIG-based wind farm system can provide useful network support as a conventional power plant. Thereby the power network operation and reliability can be improved.
JET-SHAPE OBSERVABLES

Studies of jet-shape observables in hard processes are summarized together with future developments
Rules for Synthesizing Quantum Boolean Circuits Using Minimized Nearest-Neighbour Templates

Quantum Boolean circuit (QBC) synthesis issues are becoming a key area of research in the domain of quantum computing. While Minterm gate based synthesis and Reed-Muller based canonical decomposition techniques are adopted commonly, nearest neighbor synthesis technique for QBC utilizes the quantum logic gates involving only the adjacent target and control qbits for a given quantum network. Instead of Quantum Boolean circuit synthesis using (SNOT gate, we have chosen the template-based technique for synthesis of QBC. This work defines new minimization rules using nearest neighbor templates, which results in reduced number of quantum gates and circuit levels. The need of proper relative placements of the quantum gates in order to achieve the minimum gate configuration has also been discussed.
The Disengaged Immigrant: Mapping the Francophone Caribbean Metropolis

As an exemplary locus of crosscultural contact, the city offers fertile ground for theories of hybridity, transnationalism, and globalization. Today's metropolis signals the transformative and transforming identifications, the new axes of belonging and exclusion, and the reconfiguring of national and regional borders occurring across the globe, while at the same time occupying a privileged role as the quintessential space of transnationalism. Recent work on postcolonial urban spaces has foregrounded the incidence of the immigrant in these transformations: emblem of the era's mass migrations, this cultural outsider is paradoxically of the new global city, fundamentally changing the fabric of the metropolis through the crosscultural exchange his or her inscription in urban daily life embodies.1 The productive encounters generated by these intersections thus reveal a dependence on the figure of the immigrant, a need for both the presence and the dialogical engagement of the exogenous city dweller in the construction of a transnational metropolitanism. This essay seeks to examine the particular terms of this engagement through a consideration of two recent novels of Francophone Caribbean migration: Marie-Celie Agnant's La Dot de Sara (1995) and Gisele Pineau's L'Exil selon Julia (1996). As contributions to the growing canon on Francophone Caribbean exile in Western metropolitan settings, these novels recall inaugural voices such as Cesaire's and Fanon's as well as later works by Michele Lacrosil, Andre and Simone Schwarz-Bart, Myriam Warner- Vieyra, and Joseph Zobel.2 While Pineau's L'Exil selon Julia reflects a recurrent preoccupation with the autobiographically inflected subject of French metropolitan exile, La Dot de Sara is Agnant's first novel and effects a Haitian-Canadian displacement of this Parisian setting in the tradition of Dany Laferriere and Emile Ollivier.3 Amongst these myr
Jensen Type Inequalities Involving Homogeneous Polynomials

By means of algebraic, analytical and majorization theories, and under the proper hypotheses, we establish several Jensen type inequalities involving th homogeneous polynomials as follows: , , and , and display their applications.
Systematic Characterizations of Text Similarity in Full Text Biomedical Publications

BACKGROUND
Computational methods have been used to find duplicate biomedical publications in MEDLINE. Full text articles are becoming increasingly available, yet the similarities among them have not been systematically studied. Here, we quantitatively investigated the full text similarity of biomedical publications in PubMed Central.


METHODOLOGY/PRINCIPAL FINDINGS
72,011 full text articles from PubMed Central (PMC) were parsed to generate three different datasets: full texts, sections, and paragraphs. Text similarity comparisons were performed on these datasets using the text similarity algorithm eTBLAST. We measured the frequency of similar text pairs and compared it among different datasets. We found that high abstract similarity can be used to predict high full text similarity with a specificity of 20.1% (95% CI [17.3%, 23.1%]) and sensitivity of 99.999%. Abstract similarity and full text similarity have a moderate correlation (Pearson correlation coefficient: -0.423) when the similarity ratio is above 0.4. Among pairs of articles in PMC, method sections are found to be the most repetitive (frequency of similar pairs, methods: 0.029, introduction: 0.0076, results: 0.0043). In contrast, among a set of manually verified duplicate articles, results are the most repetitive sections (frequency of similar pairs, results: 0.94, methods: 0.89, introduction: 0.82). Repetition of introduction and methods sections is more likely to be committed by the same authors (odds of a highly similar pair having at least one shared author, introduction: 2.31, methods: 1.83, results: 1.03). There is also significantly more similarity in pairs of review articles than in pairs containing one review and one nonreview paper (frequency of similar pairs: 0.0167 and 0.0023, respectively).


CONCLUSION/SIGNIFICANCE
While quantifying abstract similarity is an effective approach for finding duplicate citations, a comprehensive full text analysis is necessary to uncover all potential duplicate citations in the scientific literature and is helpful when establishing ethical guidelines for scientific publications.
A Compromise Principle in Deep Monocular Depth Estimation

Monocular depth estimation, which plays a key role in understanding 3D scene geometry, is fundamentally an illposed problem. Existing methods based on deep convolutional neural networks (DCNNs) have examined this problem by learning convolutional networks to estimate continuous depth maps from monocular images. However, we find that training a network to predict a high spatial resolution continuous depth map often suffers from poor local solutions. In this paper, we hypothesize that achieving a compromise between spatial and depth resolutions can improve network training. Based on this “compromise principle”, we propose a regression-classification cascaded network (RCCN), which consists of a regression branch predicting a low spatial resolution continuous depth map and a classification branch predicting a high spatial resolution discrete depth map. The two branches form a cascaded structure allowing the main classification branch to benefit from the auxiliary regression branch. By leveraging large-scale raw training datasets and some data augmentation strategies, our network achieves competitive or state-of-the-art results on three challenging benchmarks, including NYU Depth V2 [1], KITTI [2], and Make3D [3].
The Role of Customer Gratitude in Relationship Marketing

Most theories of relationship marketing emphasize the role of trust and commitment in affecting performance outcomes; however, a recent meta-analysis indicates that other mediating mechanisms are at work. Data from two studies—a laboratory experiment and a dyadic longitudinal field survey—demonstrate that gratitude also mediates the influence of a seller’s relationship marketing investments on performance outcomes. Specifically, relationship marketing investments generate short-term feelings of gratitude that drive long-lasting performance benefits based on gratitude-related reciprocal behaviors. The authors identify a set of managerially relevant factors and test their power to alter customer perceptions of relationship marketing investments to increase customer gratitude, which can make relationship marketing programs more effective. Overall, the research empirically demonstrates that gratitude plays an important role in understanding how relationship marketing investments increase purchase intentions, sales growth, and share of wallet.
Detecting perinatal common mental disorders in Ethiopia: validation of the self-reporting questionnaire and Edinburgh Postnatal Depression Scale.

BACKGROUND
The cultural validity of instruments to detect perinatal common mental disorders (CMD) in rural, community settings has been little-investigated in developing countries.


METHODS
Semantic, content, technical, criterion and construct validity of the Edinburgh Postnatal Depression Scale (EPDS) and Self-Reporting Questionnaire (SRQ) were evaluated in perinatal women in rural Ethiopia. Gold-standard measure of CMD was psychiatric assessment using the Comprehensive Psychopathological Rating Scale (CPRS). Community-based, convenience sampling was used. An initial validation study (n=101) evaluated both EPDS and SRQ. Subsequent validation was of SRQ alone (n=119).


RESULTS
EPDS exhibited poor validity; area under the receiver operating characteristic (AUROC) curve of 0.62 (95%CI 0.49 to 0.76). SRQ-20 showed better validity as a dimensional scale, with AUROC of 0.82 (95%CI 0.68 to 0.96) and 0.70 (95%CI 0.57 to 0.83) in the two studies. The utility of SRQ in detecting 'cases' of CMD was not established, with differing estimates of optimal cut-off score: three and above in Study 1 (sensitivity 85.7%, specificity 75.6%); seven and above in Study 2 (sensitivity 68.4%, specificity 62%). High convergent validity of SRQ as a dimensional measure was demonstrated in a community survey of 1065 pregnant women.


LIMITATIONS
Estimation of optimal cut-off scores and validity coefficients for detecting CMD was limited by sample size.


CONCLUSIONS
EPDS demonstrated limited clinical utility as a screen for perinatal CMD in this rural, low-income setting. The SRQ-20 was superior to EPDS across all domains for evaluating cultural equivalence and showed validity as a dimensional measure of perinatal CMD.
Comparison of Modulation Techniques Used In WCDMA

Wideband Code Division Multiple Access (WCDMA) was introduced to provide higher data rates in mobile communication. This technology provides the users with many multimedia rich applications such as video streams and high resolution pictures. Thus in order to enhance the performance of this technology it is necessary to determine a suitable modulation technique. Also suitable error correcting mechanisms need to be implemented to enhance these services. Analysis of these techniques is crucial to improve the performance of a system. We have considered two modulation techniques of Quadrature Amplitude Modulation (QAM) and Quadrature Phase Shift Keying (QPSK) used in WCDMA systems. We have studied the performance of these two modulation techniques and compared them using the parameters of eye pattern. This analysis will help us determine a suitable modulation technique for WCDMA. We have used MATLAB for the simulation of WCDMA transmitter section. Keywords— WCDMA, UMTS, TDMA, FDMA, CDMA, BER, SNR, Orthogonality, LOS, DSSS.