Knowledge-Based Techniques for Scholarly Data Access: Towards Automatic Curation

Accessing up-to-date and quality scientific literature is a critical preliminary step in any research activity. Identifying relevant scholarly literature for the extents of a given task or application is, however a complex and time consuming activity. Despite the large number of tools developed over the years to support scholars in their literature surveying activity, such as Google Scholar, Microsoft Academic search, and others, the best way to access quality papers remains asking a domain expert who is actively involved in the field and knows research trends and directions. State of the art systems, in fact, either do not allow exploratory search activity, such as identifying the active research directions within a given topic, or do not offer proactive features, such as content recommendation, which are both critical to researchers. To overcome these limitations, we strongly advocate a paradigm shift in the development of scholarly data access tools: moving from traditional information retrieval and filtering tools towards automated agents able to make sense of the textual content of published papers and therefore monitor the state of the art. Building such a system is however a complex task that implies tackling non trivial problems in the fields of Natural Language Processing, Big Data Analysis, User Modelling, and Information Filtering. In this work, we introduce the concept of Automatic Curator System and present its fundamental components.openDottorato di ricerca in InformaticaopenDe Nart, Dari

The Relationship Between Demographic Characteristics, Types of Contact with Police, and Perceptions of Police

Police officers play a very important role in their communities, considering they need to interact with the public in order to carry out their duties. For that reason, the relationship between the public and police officers has been the focus of many studies. The current study analyzed data from the 2011 Police-Public Contact Survey (n= 49,246). The study was conducted in three separate parts - the relationship between individual demographic characteristics and type of contact with the police, individual demographic characteristics and perceptions of police, and type of contact with the police and perceptions of the police. The results from this study were consistent with previous findings from studies that used smaller populations, as it was found that women were more likely to have voluntary contact with police than men, non-Hispanics had more voluntary contact with police than those of Hispanic Origin, women reported more positive perceptions of police, there was a positive relationship between age and perception of the police, and those who had voluntary contact had a more positive perception of police officers than those who had involuntary contact

Subphenotyping of Mexican Patients With COVID-19 at Preadmission To Anticipate Severity Stratification: Age-Sex Unbiased Meta-Clustering Technique

[EN] Background: The COVID-19 pandemic has led to an unprecedented global health care challenge for both medical institutions and researchers. Recognizing different COVID-19 subphenotypes-the division of populations of patients into more meaningful subgroups driven by clinical features-and their severity characterization may assist clinicians during the clinical course, the vaccination process, research efforts, the surveillance system, and the allocation of limited resources. Objective: We aimed to discover age-sex unbiased COVID-19 patient subphenotypes based on easily available phenotypical data before admission, such as pre-existing comorbidities, lifestyle habits, and demographic features, to study the potential early severity stratification capabilities of the discovered subgroups through characterizing their severity patterns, including prognostic, intensive care unit (ICU), and morbimortality outcomes. Methods: We used the Mexican Government COVID-19 open data, including 778,692 SARS-CoV-2 population-based patient-level data as of September 2020. We applied a meta-clustering technique that consists of a 2-stage clustering approach combining dimensionality reduction (ie, principal components analysis and multiple correspondence analysis) and hierarchical clustering using the Ward minimum variance method with Euclidean squared distance. Results: In the independent age-sex clustering analyses, 56 clusters supported 11 clinically distinguishable meta-clusters (MCs). MCs 1-3 showed high recovery rates (90.27%-95.22%), including healthy patients of all ages, children with comorbidities and priority in receiving medical resources (ie, higher rates of hospitalization, intubation, and ICU admission) compared with other adult subgroups that have similar conditions, and young obese smokers. MCs 4-5 showed moderate recovery rates (81.30%-82.81%), including patients with hypertension or diabetes of all ages and obese patients with pneumonia, hypertension, and diabetes. MCs 6-11 showed low recovery rates (53.96%-66.94%), including immunosuppressed patients with high comorbidity rates, patients with chronic kidney disease with a poor survival length and probability of recovery, older smokers with chronic obstructive pulmonary disease, older adults with severe diabetes and hypertension, and the oldest obese smokers with chronic obstructive pulmonary disease and mild cardiovascular disease. Group outcomes conformed to the recent literature on dedicated age-sex groups. Mexican states and several types of clinical institutions showed relevant heterogeneity regarding severity, potentially linked to socioeconomic or health inequalities. Conclusions: The proposed 2-stage cluster analysis methodology produced a discriminative characterization of the sample and explainability over age and sex. These results can potentially help in understanding the clinical patient and their stratification for automated early triage before further tests and laboratory results are available and even in locations where additional tests are not available or to help decide resource allocation among vulnerable subgroups such as to prioritize vaccination or treatments.We sincerely thank the different types of clinical institutions and the Mexican government, which made a huge effort to make these data publicly available. We also thank the clinicians and epidemiologists from the Servicios de Salud de Nayarit for the useful discussions on specific aspects of the medical attention to hospitalized patients and the reporting of epidemiological data processes related to COVID-19. Furthermore, we would also like to thank Francisco Tomas Garcia Ruiz for his valuable help in data visualization design. This work was supported by Universitat Politecnica de Valencia contract no. UPV-SUB.2-1302 and FONDO SUPERA COVID-19 by CRUE-Santander Bank grant: "Severity Subgroup Discovery and Classification on COVID-19 Real World Data through Machine Learning and Data Quality assessment (SUBCOVERWD-19) ." The authors thank the Institute for Information and Communication Technologies (ITACA) at the Universitat Politecnica de Valencia for its support in the publication of this manuscript.Zhou, L.; Romero-Garcia, N.; Martínez-Miranda, J.; Conejero, JA.; Garcia-Gomez, JM.; Sáez Silvestre, C. (2022). Subphenotyping of Mexican Patients With COVID-19 at Preadmission To Anticipate Severity Stratification: Age-Sex Unbiased Meta-Clustering Technique. JMIR Public Health and Surveillance. 8(3):1-21. https://doi.org/10.2196/300321218

What did the public think of health services reform in Bangladesh? Three national community-based surveys 1999–2003

BACKGROUND: Supported by development partners, the Government of Bangladesh carried out a comprehensive reform of health services in Bangladesh between 1998 and 2003, intended to make services more responsive to public needs: the Health and Population Sector Programme (HPSP). They commissioned a series of surveys of the public, as part of evaluation of the HPSP. This article uses the survey findings to examine the changes in public opinions, use and experience of health services in the period of the HPSP. METHODS: We carried out three household surveys (1999, 2000 and 2003) of a stratified random sample of 217 rural sites and 30 urban sites. Each site comprised 100–120 contiguous households. Each survey included interviews with 25,000 household respondents and managers of health facilities serving the sites, and gender-stratified focus groups in each site. We measured: household ratings of government health services; reported use of services in the preceding month; unmet need for health care; user reports of waiting times, payments, explanations of condition, availability of prescribed medicines, and satisfaction with service providers. RESULTS: Public rating of government health services as "good" fell from 37% to 10% and the proportion using government treatment services fell from 13% to 10%. Unmet need increased from 3% to 9% of households. The proportion of visits to government facilities fell from 17% to 13%, while the proportion to unqualified practitioners rose from 52% to 60%. Satisfaction with service providers' behaviour dropped from 66% to 56%. Users were more satisfied when waiting time was shorter, prescribed medicines were available, and they received explanations of their condition. CONCLUSION: Services have retracted despite increased investment and the public now prefer unqualified practitioners over government services. Public opinion of government health services has deteriorated and the reforms have not specifically helped the poorest people. User satisfaction could be increased if government doctors improved their interaction with patients and if waiting times were reduced by better management of facilities

New Insights into the Seasonal Variation of DOM Quality of a Humic-Rich Drinking-Water Reservoir—Coupling 2D-Fluorescence and FTICR MS Measurements

Long-term changes in dissolved organic matter (DOM) quality, especially in humic-rich raw waters, may lead to intensive adaptions in drinking-water processing. However, seasonal DOM quality changes in standing waters are poorly understood. To fill this gap, the DOM quality of a German drinking water reservoir was investigated on a monthly basis by Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS) measurements and 2D fluorescence for 18 months. FTICR MS results showed seasonal changes of molecular formula (MF) intensities, indicating photochemical transformation of DOM as a significant process for DOM quality variation. For an assessment of the two humic-like components, identified by parallel factor analysis (PARAFAC) of excitation–emission matrices (EEM), their loadings were Spearman’s rank-correlated with the intensities of the FTICR MS-derived MF. One of the two PARAFAC components correlated to oxygenrich and relatively unsaturated MF identified as easily photo-degradable, also known as coagulants in flocculation processes. The other PARAFAC component showed opposite seasonal fluctuations and correlated with more saturated MF identified as photo-products with some of them being potential precursors of disinfection byproducts. Our study indicated the importance of elucidating both the chemical background and seasonal behavior of DOM if raw water-quality control is implemented by bulk optical parameters

Inflammatory Adipokines, High Molecular Weight Adiponectin, and Insulin Resistance: A Population-Based Survey in Prepubertal Schoolchildren

BackgroundThe aim of this study was to investigate sex differences and associations of high molecular weight (HMW) adiponectin, leptin and proinflammatory adipokines, individually or in combinations, with adiposity and insulin resistance (IR) measures in prepubertal childhood.MethodologyWe studied 305 prepubertal children (boys/girls: 144/161; Tanner stage 1; age: 5-13 yr), included in a cohort of 44,231 adolescents who participated in an extensive Italian school-based survey. According to Cole's criteria, 105 individuals were lean (L; boys/girls: 59/46), 60 overweight (OW; boys/girls: 32/28) and 140 obese (OB; boys/girls: 70/70). Measurements comprised total and HMW adiponectin, leptin, as well as a panel of proinflammatory adipokines/chemokines associated with diabetes risk.Principal findingsLeptin-, and the leptin-to-HMW adiponectin ratio (L/HMW)-, increased progressively (pConclusionsIn prepubertal children, leptin emerges as a sex-independent discrimination marker of adiposity degree and as a useful, sex-associated predictor of the systemic insulin resistance

Temperature, light and nitrate sensing coordinate Arabidopsis seed dormancy cycling resulting in winter and summer annual phenotypes

Seeds use environmental cues to sense the seasons and their surroundings to initiate the plants life cycle. Dormancy cycling underlying this process is extensively described, but the molecular mechanism is largely unknown. To address this we selected a range of representative genes from published array experiments in the laboratory and investigated their expression patterns in seeds of Arabidopsis ecotypes, having contrasting life cycles, over an annual dormancy cycle in the field. We show how mechanisms identified in the laboratory are coordinated in response to the soil environment to determine dormancy cycles that result in winter and summer annual phenotypes. Our results are consistent with a seed specific response to seasonal temperature patterns (temporal sensing) involving the gene DELAY OF GERMINATION1 (DOG1) that indicates the correct season; and concurrent temporally driven co-opted mechanisms that sense spatial signals i.e. nitrate via CBL-INTERACTING PROTEIN KINASE 23 (CIPK23) phosphorylation of the NITRATE TRANSPORTER 1 (NRT1.1) and light via PHYTOCHROME A (PHYA). In both ecotypes studied, when all three genes have low expression there is enhanced GIBBERELLIN 3 BETA-HYDROXYLASE 1 (GA3ox1) expression, exhumed seeds have the potential to germinate in the laboratory, and the initiation of seedling emergence occurs following soil disturbance (exposure to light) in the field. Unlike DOG1, expression of MOTHER of FLOWERING TIME (MFT) has an opposite thermal response in seeds of the two ecotypes indicating a role in determining their different dormancy cycling phenotypes

Exploring the Tail of Patented Invention Value Distributions

We explore the tail of patented invention value distributions by using value estimates obtained directly from patent holders. The paper focuses on those full-term German patents of the application year 1977 which were held by West German and U.S. residents. The most valuable patents in our data account for a large fraction of the cumulative value over all observations. Several tests are conducted to pin down more precisely the nature of the high-value tail distribution. Among the Pareto, Singh-Maddala and log normal distributions, the log normal appears to provide the best fit to our patented invention value data. --Patents,Skew Distributions

Intrinsic bias in breast cancer gene expression data sets

<p>Abstract</p> <p>Background</p> <p>While global breast cancer gene expression data sets have considerable commonality in terms of their data content, the populations that they represent and the data collection methods utilized can be quite disparate. We sought to assess the extent and consequence of these systematic differences with respect to identifying clinically significant prognostic groups.</p> <p>Methods</p> <p>We ascertained how effectively unsupervised clustering employing randomly generated sets of genes could segregate tumors into prognostic groups using four well-characterized breast cancer data sets.</p> <p>Results</p> <p>Using a common set of 5,000 randomly generated lists (70 genes/list), the percentages of clusters with significant differences in metastasis latencies (HR p-value < 0.01) was 62%, 15%, 21% and 0% in the NKI2 (Netherlands Cancer Institute), Wang, TRANSBIG and KJX64/KJ125 data sets, respectively. Among ER positive tumors, the percentages were 38%, 11%, 4% and 0%, respectively. Few random lists were predictive among ER negative tumors in any data set. Clustering was associated with ER status and, after globally adjusting for the effects of ER-α gene expression, the percentages were 25%, 33%, 1% and 0%, respectively. The impact of adjusting for ER status depended on the extent of confounding between ER-α gene expression and markers of proliferation.</p> <p>Conclusion</p> <p>It is highly probable to identify a statistically significant association between a given gene list and prognosis in the NKI2 dataset due to its large sample size and the interrelationship between ER-α expression and markers of proliferation. In most respects, the TRANSBIG data set generated similar outcomes as the NKI2 data set, although its smaller sample size led to fewer statistically significant results.</p