Several Sources Of Information Research Articles

Sound event detection of passing trains using convolutional recurrent neural network (CRNN)

Acoustic measurements near railway infrastructure typically involve precise identification and labelling of train passages in time series of noise measurements. The labelling of events is done manually by an acoustician, by cross-referencing several sources of information, such as train timetable data, audio data, images and/or videos. In this paper, we present a method which automatically detects and labels the passage of trains in front of a microphone using a convolutional recurrent neural network (CRNN). The advantage of this type of model is that it can be trained using existing data (time series of LAeq,1s and 1/3 octave band with a good labelling of passing trains); which has been widely available for a number of years. The results are promising if limited to binary classification but would require further development if the aim included the recognition and categorisation of various train types.

The LEADING Guideline: Reporting Standards for Expert Panel, Best-Estimate Diagnosis, and Longitudinal Expert All Data (LEAD) Studies.

Accurate assessments of symptoms and illnesses are essential for health research and clinical practice but face many challenges. The absence of a single error-free measure is currently addressed by assessment methods involving experts reviewing several sources of information to achieve a more accurate or best-estimate assessment. Three bodies of work spanning medicine, psychiatry, and psychology propose similar assessment methods: The Expert Panel, the Best-Estimate Diagnosis, and the Longitudinal Expert All Data (LEAD) method. However, the quality of such best-estimate assessments is typically very difficult to evaluate due to poor reporting of the assessment methods and when they are reported, the reporting quality varies substantially. Here, we tackle this gap by developing reporting guidelines for such best-estimate assessment studies. The development of the reporting guidelines followed a four-stage approach: 1) drafting reporting standards accompanied by rationales and empirical evidence, which were further developed with a patient organization for depression, 2) incorporating expert feedback through a two-round Delphi procedure, 3) refining the guideline based on an expert consensus meeting, and 4) testing the guideline by i) having two researchers test it and ii) using it to examine the extent previously published studies report the standards. The last step also provides evidence for the need for the guideline: 10 to 63% (Mean = 33%) of the standards were not reported across thirty randomly selected studies. The LEADING guideline comprises 20 reporting standards related to four groups: The Longitudinal design (four standards); the Appropriate data (four standards); the Evaluation - experts, materials, and procedures (ten standards); and the Validity group (two standards). We hope that the LEADING guideline will be useful in assisting researchers in planning, conducting, reporting, and evaluating research aiming to achieve best-estimate assessments.

Early clinical drug product shelf-life setting using accelerated predictive stability and metabolite data for impurity qualification: A case study

This case study demonstrates how knowledge of degradation products together with predictions can establish a lean stability strategy using the accelerated predictive stability (APS) principles. Applying all available data for AZD4831, (R)-1-(2-(1-aminoethyl)-4-chlorobenzyl)-2-thioxo-2,3-dihydro-1H-pyrrolo[3,2-d]pyrimidin-4(5H)-one, a reliable predictive model was developed despite minor differences in technical batch tablet compositions. Early forced degradation studies were performed to map potential degradation pathways. The insights from these studies guided the design of an APS study, which in turn inform on a suitable clinical stability program, initial specification and shelf-life. The use of APS predictions of degradants as well as total impurities highlighted at an early stage, when designing the clinical stability program, the opportunity to identify which degradation product that would be shelf-life limiting. Hence, it was possible to guide the development stability activities and set an initial shelf-life of a tablet formulation. The presented study displays the importance of combining several sources of information in drug development, e.g., potential degradation pathways, accelerated stability, stability program design, metabolite data, and specification limits.

Combining genetic markers, on-farm information and infrared data for the in-line prediction of blood biomarkers of metabolic disorders in Holstein cattle

BackgroundVarious blood metabolites are known to be useful indicators of health status in dairy cattle, but their routine assessment is time-consuming, expensive, and stressful for the cows at the herd level. Thus, we evaluated the effectiveness of combining in-line near infrared (NIR) milk spectra with on-farm (days in milk [DIM] and parity) and genetic markers for predicting blood metabolites in Holstein cattle. Data were obtained from 388 Holstein cows from a farm with an AfiLab system. NIR spectra, on-farm information, and single nucleotide polymorphisms (SNP) markers were blended to develop calibration equations for blood metabolites using the elastic net (ENet) approach, considering 3 models: (1) Model 1 (M1) including only NIR information, (2) Model 2 (M2) with both NIR and on-farm information, and (3) Model 3 (M3) combining NIR, on-farm and genomic information. Dimension reduction was considered for M3 by preselecting SNP markers from genome-wide association study (GWAS) results.ResultsResults indicate that M2 improved the predictive ability by an average of 19% for energy-related metabolites (glucose, cholesterol, NEFA, BHB, urea, and creatinine), 20% for liver function/hepatic damage, 7% for inflammation/innate immunity, 24% for oxidative stress metabolites, and 23% for minerals compared to M1. Meanwhile, M3 further enhanced the predictive ability by 34% for energy-related metabolites, 32% for liver function/hepatic damage, 22% for inflammation/innate immunity, 42.1% for oxidative stress metabolites, and 41% for minerals, compared to M1. We found improved predictive ability of M3 using selected SNP markers from GWAS results using a threshold of > 2.0 by 5% for energy-related metabolites, 9% for liver function/hepatic damage, 8% for inflammation/innate immunity, 22% for oxidative stress metabolites, and 9% for minerals. Slight reductions were observed for phosphorus (2%), ferric-reducing antioxidant power (1%), and glucose (3%). Furthermore, it was found that prediction accuracies are influenced by using more restrictive thresholds (−log10(P-value) > 2.5 and 3.0), with a lower increase in the predictive ability.ConclusionOur results highlighted the potential of combining several sources of information, such as genetic markers, on-farm information, and in-line NIR infrared data improves the predictive ability of blood metabolites in dairy cattle, representing an effective strategy for large-scale in-line health monitoring in commercial herds.

Posttraumatische Belastungsstörung bei Kindern und Jugendlichen: Ergebnisse einer Querschnittsstudie zu Auswirkungen der neu formulierten Diagnosen PTBS und kPTBS in der ICD-11

ZusammenfassungHintergrundDie in der ICD-11 enger gefassten Kriterien der posttraumatischen Belastungsstörung (PTBS) und die Einführung der komplexen PTBS (kPTBS) mit zusätzlichen Schwierigkeiten in der Selbstorganisation und -regulation (SSO) können deutliche Auswirkungen auf die Diagnosehäufigkeit haben. In der vorliegenden Studie wurde untersucht, aufgrund welcher ICD-11-Cluster Kinder und Jugendliche die Diagnose verfehlen und ob Bezugspersonen Veränderungen im SSO-Bereich eher auf den Entwicklungsstand oder das traumatische Ereignis attribuieren und wie diese Attributionen wiederum mit der Symptomschwere zusammenhängen.MethodenN = 88 deutschsprachige Kinder und Jugendliche (Alter: 7–17) mit traumatischen Ereignissen sowie N = 79 Bezugspersonen wurden zwischen September 2019 und November 2020 zur (k)PTBS-Symptomschwere (CATS-2) und der Attribution der SSO-Symptome (Fragebogen für Bezugspersonen) befragt.ErgebnisseDie ICD-11-Kriterien (CATS‑2 und eine entwicklungsangepasste Version) ergaben geringere Häufigkeitsraten der PTBS als DSM‑5 und ICD-10. Am seltensten wurden die ICD-11-Cluster „Wiedererleben“ und „Übererregung“ erfüllt. Veränderungen der SSO-Symptome wurden vorwiegend als ereignisbedingt eingeschätzt. Diese Attribution hing mit höherer PTBS- und SSO-Symptomschwere im Fremdbericht zusammen. Die entwicklungsbedingte Attribution hing mit einer höheren SSO-, jedoch nicht PTBS-Symptomschwere im Fremdbericht zusammen.DiskussionIm Rahmen der Diagnostik und bei der Überarbeitung von Diagnoseinstrumenten für ICD-11-(k)PTBS sollten auch entwicklungsspezifische Symptomausprägungen berücksichtigt werden. Eine Herausforderung stellt die Abgrenzung von Veränderungen im SSO-Bereich als „traumabezogen“ gegenüber „entwicklungsbedingt“ dar und erfordert mehrere Informationsquellen.

Utilization of GIS Model Mapping to Detect Fault Segments in Mesopotamian Foredeep Basin

The Mesopotamia Basin is widely recognized as a significant aggradation geomorphological entity, characterized by the dominance of fluvial, lacustrine, and aeolian landforms. The geographical scope of this study spans a specific region within the Mesopotamian Basin, specifically including Nasiriyah and Basrah located in the southern region of Iraq. It comprises a collection of Joint and fault systems that serve as indicators of various tectonic occurrences that have influenced the Arabian plate from the pre-Cambrian era up till the present day. The major goal of this model is to mapping and detects fault segments to get information about the large faults existing which is not recognized by prior work. A Geographic Information System (GIS) model was employed to create three digital layers, namely Lineament, drainage patterns, and lithological contact. These layers were established using several sources of information. The initial step of the GIS demonstration includes the input information, and the subsequent includes the selection of the equation for this model to specify the vulnerability of faulting segments in the research sector. Moderate to large lineaments (fault lines) were identified the results suggest an additional (26,15) new fault segment line numbers for the areas Nasiriyah and Basrah respectively which were not known by the fault map over the research sector, these fault lines reflect crustal structures (large length lineaments), as well as analysis lineaments from satellite images, enables obtaining a miscellany of terrain applications, such as the selection of landfill sites, determining terrain stability, dam sites, and many other applications

Drug information-seeking behaviour among Jordanian physicians: a cross-sectional study.

Background: Due to the huge number of drugs available and the rapid growth and change in drug information, healthcare professionals, especially physicians, frequently require reliable, easily accessible, rapid, and accurate reference sources to obtain the necessary drug information. Several sources of information are available for physicians to use and select from; however, the information-seeking behaviour of healthcare providers is varied, and this process can be challenging. Objectives: In this study, Jordanian physicians were approached to evaluate the drug information they require, the sources of information they use, the perceived credibility of the sources, and the challenges they face when searching for the most accurate and current information about drugs. Methods: This is an observational, cross-sectional study. A self-administered questionnaire was distributed to practising physicians in Jordan using a convenience sampling method (purposive sampling followed by snowball sampling) regardless of their speciality, age, gender, seniority, or place of employment. Results: Three hundred and eighty physicians participated in the study. Most participants responded that they performed drug information searches on a weekly (155, 40.8%) or a daily basis (150, 39.5%). The drug-related information that physicians most frequently searched for concerned dosage regimens and adverse drug events. The majority of surveyed doctors (97.9%) reported using online websites to acquire drug information; UpToDate®, Medscape and Drugs.com were the most frequently used online databases, although many participants did not consider online sources to be the most reliable source. The most prevalent and recurrent challenges encountered concerned an inability to access subscription-only journals and websites (56.6%), difficulty identifying trusted and credible sources (41.8%) and the enormous number of available sources (35.3%). However, these challenges were less of a problem for physicians who currently work or have previously worked in academia (p < 0.001). Conclusion: This study demonstrated that Jordanian physicians frequently use online websites to look for drug information and all doctors face challenges throughout this process particularly those with no experience in academia. This suggests that being in academia makes the process of information-seeking easier which highlights the need for academics to transfer their knowledge and experience to their non-academic colleagues and the upcoming generations of physicians.

Generative Adversarial Networks to incorporate the Training Image uncertainty in multiple-point statistics simulation

Multiple-point geostatistics (MPS) algorithms have been extensively used for geostatistical reservoir modeling. These techniques are known for building geostatistical simulations with curvilinear features, which are crucial for applications in flow simulation. One challenge in using MPS algorithms is obtaining a representative Training Image (TI). The result is that often one TI is used to condition the entire set of geostatistical simulations, and the TI uncertainty is disregarded. If the TI is uncertain, this uncertainty should be considered in the geostatistical simulations. Otherwise, the spatial uncertainty represented by the geostatistical simulations is underestimated. Incorporating the TI uncertainty requires building a data set or catalog of plausible TIs. In this context, we propose to use Generative Adversarial Networks (GANs) to build this catalog of TIs prior to the MPS simulation. Each TI generated by GAN is used to condition one realization built by the chosen MPS algorithm. The proposed workflow combines the strength of GAN to generate TIs with the strength of MPS algorithms to consider several sources of information to condition the simulations. A case study is shown, where the methodology is compared against the traditional MPS workflow, which uses a single TI. The results show that the proposed method successfully incorporated the TI uncertainty into the geostatistical workflow. The proposed method built numerical models with higher uncertainty and variability and, thus, provides a more realistic quantification of the space of uncertainty.

Drug-induced Sudden Death: A Scoping Review.

The risk of sudden cardiac death (SCD) can be increased with the use of drugs. However, it has been described heterogeneously in the literature. This study aims to systematically review epidemiological studies dealing with druginduced sudden death, describe their methodologies, and summarize the results found. A scoping review has been carried out using Medline electronic database. The search was limited up to 2020. Epidemiological studies were included, and case reports or case series were excluded. Out of 3,114 potential articles, 74 were included. Most studies originated from North America (40.5%) or Europe (39.2%). Case-control (47.3%) or cohort (40.5%) studies were the most common designs. The data for outcomes and exposure were retrieved mainly from administrative databases (37.8%) or medical charts/hospital discharge reports (32.4%), but most studies used several sources of information. A composite variable of sudden death or SCD, mainly with ventricular arrhythmia, was the most frequently used endpoint. Only 18.9% of the studies included autopsy results to confirm the death. Psychotropic drugs were the most frequently studied. An increased risk of different outcomes for typical antipsychotics, tricyclic antidepressants, domperidone, and antiepileptics is suggested. The methodologies used were highly heterogeneous, and the results were, in general, not conclusive. An improvement of the methodologies is needed to achieve a conclusion regarding the risk of SCD associated with drug use.

Lessons from Reality on Automated Container Terminals: What Can Be Expected from Future Technological Developments?

Automating container terminals is a consolidated trend in the port sector that is expected to grow. The main drivers for this growth are improving efficiency, reducing operating costs, remedying labor shortages, and increasing productivity. However, in practice there is no clear evidence confirming that automated terminals outperform conventional ones in handling productivity rates, cycle times, or vessel berthing times. Both the academic corpus and industry data show mixed results. Based on that, the goal of this article is to research productivity rates and factors affecting productivity, and understand to what extent future technological developments can enhance automated terminals. To do so, several sources of information are used and analyzed to shed light on the real productivity performance. The main conclusion gives no strong evidence linking automation with greater productivity, even though it might reduce terminal operators’ costs. In fact, in many instances, productivity is worse. Moreover, currently, semi-automated terminals are still preferred to fully automated terminals because of better handling times. However, it is expected that future technological developments will likely overcome the current issues faced by automated terminals, when a technological paradigm shift takes places.

A further step for efficient corrections of inconsistent probabilistic data sets

Partial conditional probability assessments are having renewed attention and the merging of several sources of information is one of the more compelling needs associated with them. We focus here on the consequent task of correcting inconsistent probabilistic databases.We propose an efficient method for correcting incoherent (i.e. inconsistent) conditional probability assessments, that has a polynomial space complexity, differently from methods based on probabilistic satisfiability problems (PSAT) which require an exponential amount of memory space.This method uses Mixed Integer Programming (MIP) procedure to minimize the L1 distance between probability assessments and exploits the presence of the so-called “zero layers”. Through a simple prototypical example, we illustrate the feasibility and the peculiarities of the proposed procedure.Finally, we show some experimental results obtained through randomly generated incoherent assessments.

Educator Perspectives on Accessing Disability-Related Information and Resources

Familiarity with local disability information and resources can impact the ways educators support students with disabilities and their families. We surveyed 462 educators regarding their awareness of and access to disability-related information and resources. Specifically, we examined (a) their familiarity with resources and services across multiple areas, (b) the sources of information they consider to be helpful in their work, and (c) the likelihood they would draw upon new resources designed to connect them to local information and resources. Overall, educators reported mixed familiarity with resources related to supporting important student experiences (e.g., having friends, being physically healthy, participating in recreational activities) and addressing key service needs (e.g., speech therapy, behavior supports, mental health care). Familiarity tended to be higher for resources related to student experiences than for service needs. Educators considered several sources of information to be most helpful in their work, including internet searches, fellow teachers or other school staff, and conferences or workshops. We address implications for teacher training programs, state-level educational leaders, and school districts.

Mammals of the Tandilia Mountain system, current species inhabiting Pampean highland grasslands

Neotropical temperate grasslands comprise the Pampas ecoregion in Argentina. This region is also the center of agricultural development in Argentina, which has led to a significant simplification and homogenization of the landscape. The Tandilia Mountains, located in the Southeast of the ecoregion, house one of the last remnants of the highland grassland that acts as a refuge for several native species, including both endemic and threatened species. This work aims to present an updated inventory of mammal species that inhabit the highland grassland remnants of the Tandilia Mountains. We used several sources of information to compile the list, including museum collections, citizen science projects (i.e., iNaturalist, EcoRegistros, and Argentinian Network for Monitoring Run Over Fauna), literature, and personal observations. We recorded 40 species of mammals, which include 32 native species and eight exotic species. The richest orders were Rodentia (42.5%), Chiroptera (17.5%), and Carnivora (12.2%). The native mammals found in the Tandilia Mountains represent 44% of the mammal diversity of the Pampas ecoregion, among which there are endemic species of the ecoregion, species whose populations are declining globally, and threatened species. Unfortunately, the presence of protected areas in the system is limited to a few small ones, which highlights the urgency of increasing the number and variety of protected areas. The information presented in this work contributes to the knowledge of biodiversity and the planning of conservation actions for the last remnants of highland grasslands.

Maternal morbidity and mortality in Brazil and the urgency of a national surveillance system for maternal near miss

The World Health Organization (WHO) recommends the analysis of severe maternal morbidity/maternal near miss cases as complementary to the analysis of maternal deaths since the incidence is higher and the predictive factors of the two outcomes are similar. Considering that the reasons for maternal mortality in Brazil have remained constant despite the commitment made during the General Assembly of the United Nations in 2015, this article aims to propose a nationwide maternal near miss surveillance system. We propose the inclusion of maternal near miss events in the National List of Compulsory Notification of Diseases, Injuries, and Public Health Events, via the compatibility of the diagnostic criteria of maternal near miss, informed by the WHO, with the codes of the International Classification of Diseases for the identification of cases. Considering that health surveillance is based on several sources of information, notification could be made by health service professionals as soon as a confirmed or suspected case is identified. With the study of the factors associated with the outcomes, we expect a qualified evaluation of the services focused on obstetric care and consequent implementation of more efficient policies to prevent not only maternal death but also events that can both cause irreversible sequelae to women's health and increase the risk of fetal and neonatal death.

Repressão e violência do Estado no romance O corpo interminável, de Cláudia Lage

This article examines Cláudia Lage's novel O corpo interminável in light of the events of repression and violence during the military dictatorship in Brazil (1964-1985). The narrator-protagonist's revisiting of this past and the events that led to his mother's disappearance is a painful process, difficult to apprehend, a fact that requires an investigation that uses several sources of information. It is, therefore, an archaeological novel, which recomposes the events of the past through research, witnesses, vestiges and interpretation, in order to get closer to the truth.

Seguimiento de la biodiversidad en la era del Big Data

The monitoring and evaluation of the distribution, structure and functioning of biodiversity, as well as the effects exerted by different pressures and threats on its conservation and dynamics in a context of Global Change, constitute one of the greatest challenges of current science and a critical axis in the agendas of numerous government agencies. Given the importance of having reliable, representative and temporally dynamic data to respond to these challenges, Ecology, like other branches of Biology and Earth Sciences, has recently echoed the phenomenon known as "Big Data" or "Data Science". In Ecology, this massive dataset relates to several sources of information: a) time series of remote observation data; b) aggregation of local and regional field or experimental data; c) long-term monitoring networks with national and international field data; d) automated sensor networks, and, e) Citizen Science initiatives, among others. Together, Big Data amplifies the spatio-temporal scale of issues related to biodiversity monitoring and management, making it possible to cover aspects and scales that were unthinkable only a few years ago. However, its application in Ecology still presents great challenges and there is currently an intense debate about its applicability at scales related to the management of spaces and species. Through its pages, this review tries to present the current state of the science on monitoring biodiversity of terrestrial ecosystems and its sources of information, as well as its synergies, applications, analysis methodologies, challenges and opportunities in the era of Big Data.

Many Faces of Mediation

Many Faces of Mediation

Validating a German Version of the Conspiracy Mentality Scale (CMS)

Increased scientific interest in conspiracy beliefs raises the need for validated individual difference measures in the general tendency to believe in conspiracy theories, otherwise referred to as conspiracy mentality. In this article, we present a German language version of the Conspiracy Mentality Scale (CMS). A representative sample of German-speaking Swiss residents (N = 468) filled in the scale, along with measures of trust in several sources of information, need for social validation, compliance with Covid-19 preventive measures, perceived severity of the pandemic, loneliness, functional literacy and interpersonal conflict. Confirmatory factor analysis supported the two-dimensional structure of the original scale. Positive correlations between conspiracy theory ideation and trust in friends and the need for social validation on the one hand, and negative correlations with trust in scientific publications and scientific experts, perceived severity of the pandemic and functional literacy on the other hand supported construct validity. We conclude that our German language version of the scale is a valid measure of conspiracy theory ideation and skepticism.

Implementasi Manajemen Mutu Terpadu Dalam Meningkatkan Mutu Lulusan Di SMP IT Wahdatul Ummah Kota Metro

This study will examine the obstacles to implementing integrated quality management at SMP IT Wahdatul Ummah Metro City to improve the quality of graduates. This project aims to develop an effective quality management system starting from planning, implementation, and evaluation in order to improve the quality of graduates of SMP IT Wahdatul Ummah Metro City. This qualitative study involves interviewing a representative sample of individuals. This methodology aims to gain a deeper understanding of the experience of the academic community in implementing integrated quality management to address the challenges of education services. Principals, vice principals of curriculum, vice principals for student affairs, teachers, students, and their parents were surveyed for this study. Observation, interviews, and documentation are data collection methods used in this study. Test the validity of the data using triangulation in conjunction with data analysis that utilizes multiple data sources to build a more precise representation. This can be achieved by comparing several sources of information to determine whether they agree. If it is determined that the data is invalid, it is corrected or rewritten. This study found that the implementation of integrated quality management can improve the achievement of school goals, starting from the crucial planning, implementation, and evaluation stages. To improve student achievement and the quality of graduates, it is necessary to define the school's vision, mission, and goals. Programs and activities should be directed to improve student achievement and customer satisfaction. In order for schools to continue to emphasize their goals, all parts of the school service must experience continuous development

Development of the method of complexing the results of radio monitoring and remote earth sensing

The objects of the research are the objects of monitoring of groups of troops (forces). The relevance of the research lies in the need for a comprehensive analysis of monitoring objects from several sources of information. The results of the analysis show that the most reliable and accurate information comes from aerial monitoring, orbital remote sensing of the Earth and radio monitoring. At the same time, instrumental errors of radio monitoring devices do not allow determining the location of sources of radio radiation with the accuracy necessary for localization (neutralization) of threats. A method of integrating the results of radio monitoring and remote sensing of the Earth has been developed. The essence of the proposed research is the complex processing of monitoring results from various sources of information extraction. The difference between the proposed method and the known ones is that the specified method contains the following improved procedures: ‒ taking into account the type of uncertainty about the state of the monitoring object (complete uncertainty, partial uncertainty, full awareness); ‒ carry out a multi-level analysis of the state of the monitoring object according to 4 levels and 3 significant events; ‒ detection of a monitoring object as part of a group monitoring object. The use of the proposed approach to radio monitoring information processing and monitoring using unmanned aerial vehicles/devices of remote sensing of the Earth allows to reduce the time required for deciphering aerospace images by at least 1.3 times. At the same time, the accuracy of determining the coordinates will be limited by the resolution of the equipment of unmanned aerial vehicles/ devices of remote sensing of the Earth and is of the order of 0.5 m.