scholarly journals Comparison of Different Analytical Methods for the On-Site Analysis of Traces at Clandestine Drug Laboratories

2021 ◽  
Vol 11 (9) ◽  
pp. 3754
Author(s):  
René Reiss ◽  
Frank Hauser ◽  
Sven Ehlert ◽  
Michael Pütz ◽  
Ralf Zimmermann
Keyword(s):  
Large Scale ◽  
Ambient Pressure ◽  
Relevant Information ◽  
Information Value ◽  
Site Analysis ◽  
Complex Information ◽  
Skilled Operator ◽  
Validation Parameters ◽  
Clandestine Laboratories ◽  
To Receive

While fast and reliable analytical results are crucial for first responders to make adequate decisions, these can be difficult to establish, especially at large-scale clandestine laboratories. To overcome this issue, multiple techniques at different levels of complexity are available. In addition to the level of complexity their information value differs as well. Within this publication, a comparison between three techniques that can be applied for on-site analysis is performed. These techniques range from ones with a simple yes or no response to sophisticated ones that allows to receive complex information about a sample. The three evaluated techniques are immunoassay drug tests representing easy to handle and fast to explain systems, ion mobility spectrometry as state-of-the-art equipment that needs training and experience prior to use and ambient pressure laser desorption with the need for a highly skilled operator as possible future technique that is currently under development. In addition to the measurement of validation parameters, real case samples are investigated to obtain practically relevant information about the capabilities and limitations of these techniques for on-site operations. Results demonstrate that in general all techniques deliver valid results, but the bandwidth of information widely varies between the investigated techniques.

INFORMATION ASPECT OF THE FORMATION OF THE ANTI-TERRORIST EURASIAN SPACE

2020 ◽  
Author(s):  
L.L. KHOPERSKAYA
Keyword(s):  
Central Asia ◽  
Relevant Information ◽  
Kyrgyz Republic ◽  
Sources Of Information ◽  
Labor Migrants ◽  
Legal Documents ◽  
Complex Information ◽  
Special Services ◽  
State Commission ◽  
The Republic

The article deals with the problem of completeness of information on measures to counter terrorism and extremism taken by the labor-surplus states of Central Asia. With the help of some former labor migrants, a new model of terrorism (IS 2.0) is being developed based on the use of pendulum migration of radical Islamists to the countries of Central Asia and Russia, such Islamists serve as the core of various extremist organizations. A serious problem for the Russian experts is that none of the countries (Tajikistan, Kyrgyzstan or Uzbekistan) sending labor migrants to Russia publishes complex information each country publishes mainly statistical or regulatory information or news. For example, not all official documents are available in Tajikistan or Uzbekistan and it is difficult to obtain official statistics in Uzbekistan or Kyrgyzstan. Nevertheless, the analysis of the disparate experience of the three countries, among which we can highlight the purposeful work with labor migrants carried out by the representative offices of the Republic of Tajikistan abroad the courses for imams of mosques and clerics on the prevention of radicalization of the population organized by the State Commission for religious affairs of the Kyrgyz Republic and the system of social rehabilitation of repentant extremists in Uzbekistan prove the need for relevant information in a certain standardized form. The main sources of information used in the article are documents of the UN, the CIS Anti-Terrorist Center, speeches of the President of the Republic of Tajikistan containing statistical information, news information from the websites of the special services of the Kyrgyz Republic and legal documents of Uzbekistan. The article substantiates the conclusion about the need to highlight the information aspect in the formation of the anti-terrorist Eurasian space, the relevance of which was discussed at the Council of the CSTO Parliamentary Assembly in May 2019.

The Effect of the Familiarity of a Survey Sender on Response Outcomes in a Large-Scale Survey of Emergency Medical Services Agencies

2021 ◽  
Vol 44 (3) ◽  
pp. 260-267
Author(s):  
Morgan M. Millar ◽  
Hilary A. Hewes ◽  
Andrea L. Genovesi ◽  
Michael Ely ◽  
Braden Green ◽  
...  
Keyword(s):  
Emergency Medical Services ◽  
Large Scale ◽  
Nationwide Survey ◽  
Survey Response ◽  
Medical Services ◽  
Healthcare Organizations ◽  
Emergency Medical ◽  
Established Relationship ◽  
To Receive

Survey response is higher when the request comes from a familiar entity compared to an unknown sender. Little is known about how sender influences response to surveys of organizations. We assessed whether familiarity of the sender influences response outcomes in a survey of emergency medical services agencies. Emergency medical services agencies in one U.S. state were randomly assigned to receive survey emails from either a familiar or unfamiliar sender. Both deployment approaches were subsequently used nationwide, with each state selecting one of the two contact methods. Experimental results showed that requests from the familiar sender achieved higher survey response (54.3%) compared to requests from the unfamiliar sender (36.9%; OR: 2.03; 95% CI: 1.23, 3.33). Similar results were observed in the subsequent nationwide survey; in states where the familiar sender deployed the survey, 62.0% of agencies responded, compared to 51.0% when the survey was sent by the unfamiliar sender (OR: 1.57; 95% CI: 1.47, 1.67). The response difference resulted in nearly 60 additional hours of staff time needed to perform telephone follow-up to nonrespondents. When surveying healthcare organizations, surveyors should recognize that it is more challenging to obtain responses without a pre-established relationship with the organizations.

scholarly journals Assessing the impact of hydrodynamics on large-scale flood wave propagation – a case study for the Amazon Basin

2017 ◽  
Vol 21 (1) ◽  
pp. 117-132 ◽  
Author(s):  
Jannis M. Hoch ◽  
Arjen V. Haag ◽  
Arthur van Dam ◽  
Hessel C. Winsemius ◽  
Ludovicus P. H. van Beek ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Hydrodynamic Model ◽  
Large Scale ◽  
Hydrologic Model ◽  
Flood Events ◽  
Coupled Models ◽  
Validation Parameters ◽  
Directional Coupling ◽  
Inundation Extent ◽  
The Impact

Abstract. Large-scale flood events often show spatial correlation in neighbouring basins, and thus can affect adjacent basins simultaneously, as well as result in superposition of different flood peaks. Such flood events therefore need to be addressed with large-scale modelling approaches to capture these processes. Many approaches currently in place are based on either a hydrologic or a hydrodynamic model. However, the resulting lack of interaction between hydrology and hydrodynamics, for instance, by implementing groundwater infiltration on inundated floodplains, can hamper modelled inundation and discharge results where such interactions are important. In this study, the global hydrologic model PCR-GLOBWB at 30 arcmin spatial resolution was one-directionally and spatially coupled with the hydrodynamic model Delft 3D Flexible Mesh (FM) for the Amazon River basin at a grid-by-grid basis and at a daily time step. The use of a flexible unstructured mesh allows for fine-scale representation of channels and floodplains, while preserving a coarser spatial resolution for less flood-prone areas, thus not unnecessarily increasing computational costs. In addition, we assessed the difference between a 1-D channel/2-D floodplain and a 2-D schematization in Delft 3D FM. Validating modelled discharge results shows that coupling PCR-GLOBWB to a hydrodynamic routing scheme generally increases model performance compared to using a hydrodynamic or hydrologic model only for all validation parameters applied. Closer examination shows that the 1-D/2-D schematization outperforms 2-D for r2 and root mean square error (RMSE) whilst having a lower Kling–Gupta efficiency (KGE). We also found that spatial coupling has the significant advantage of a better representation of inundation at smaller streams throughout the model domain. A validation of simulated inundation extent revealed that only those set-ups incorporating 1-D channels are capable of representing inundations for reaches below the spatial resolution of the 2-D mesh. Implementing 1-D channels is therefore particularly of advantage for large-scale inundation models, as they are often built upon remotely sensed surface elevation data which often enclose a strong vertical bias, hampering downstream connectivity. Since only a one-directional coupling approach was tested, and therefore important feedback processes are not incorporated, simulated discharge and inundation extent for both coupled set-ups is generally overpredicted. Hence, it will be the subsequent step to extend it to a two-directional coupling scheme to obtain a closed feedback loop between hydrologic and hydrodynamic processes. The current findings demonstrating the potential of one-directionally and spatially coupled models to obtain improved discharge estimates form an important step towards a large-scale inundation model with a full dynamic coupling between hydrology and hydrodynamics.

Lipid-lowering treatment in hypercholesterolaemic patients: the CEPHEUS Pan-Asian survey

2011 ◽  
Vol 19 (4) ◽  
pp. 781-794 ◽  
Author(s):  
Jeong Euy Park ◽  
Chern-En Chiang ◽  
Muhammad Munawar ◽  
Gia Khai Pham ◽  
Apichard Sukonthasarn ◽  
...  
Keyword(s):  
Cardiovascular Risk ◽  
High Risk ◽  
Large Scale ◽  
Goal Attainment ◽  
Density Lipoprotein ◽  
Final Analysis ◽  
Relevant Information ◽  
Lipid Lowering ◽  
Lipid Lowering Therapy ◽  
Lipid Lowering Drugs

Background: Treatment of hypercholesterolaemia in Asia is rarely evaluated on a large scale, and data on treatment outcome are scarce. The Pan-Asian CEPHEUS study aimed to assess low-density lipoprotein cholesterol (LDL-C) goal attainment among patients on lipid-lowering therapy. Methods: This survey was conducted in eight Asian countries. Hypercholesterolaemic patients aged ≥18 years who had been on lipid-lowering treatment for ≥3 months (stable medication for ≥6 weeks) were recruited, and lipid concentrations were measured. Demographic and other clinically relevant information were collected, and the cardiovascular risk of each patient was determined. Definitions and criteria set by the updated 2004 National Cholesterol Education Program guidelines were applied. Results: In this survey, 501 physicians enrolled 8064 patients, of whom 7281 were included in the final analysis. The mean age was 61.0 years, 44.4% were female, and 85.1% were on statin monotherapy. LDL-C goal attainment was reported in 49.1% of patients overall, including 51.2% of primary and 48.7% of secondary prevention patients, and 36.6% of patients with familial hypercholesterolaemia. The LDL-C goal was attained in 75.4% of moderate risk, 55.4% of high risk, and only 34.9% of very high-risk patients. Goal attainment was directly related to age and inversely related to cardiovascular risk and baseline LDL-C. Conclusion: A large proportion of Asian hypercholesterolaemic patients on lipid-lowering drugs are not at recommended LDL-C levels and remain at risk for cardiovascular disease. Given the proven efficacy of lipid-lowering drugs in the reduction of LDL-C, there is room for further optimization of treatments to maximize benefits and improve outcomes.

scholarly journals A Survey of Arabic Named Entity Recognition and Classification

2014 ◽  
Vol 40 (2) ◽  
pp. 469-510 ◽  
Author(s):  
Khaled Shaalan
Keyword(s):  
Language Processing ◽  
Named Entity Recognition ◽  
Relevant Information ◽  
Arabic Language ◽  
Entity Recognition ◽  
Named Entities ◽  
Linguistic Resources ◽  
Named Entity ◽  
To Receive ◽  
Made In

As more and more Arabic textual information becomes available through the Web in homes and businesses, via Internet and Intranet services, there is an urgent need for technologies and tools to process the relevant information. Named Entity Recognition (NER) is an Information Extraction task that has become an integral part of many other Natural Language Processing (NLP) tasks, such as Machine Translation and Information Retrieval. Arabic NER has begun to receive attention in recent years. The characteristics and peculiarities of Arabic, a member of the Semitic languages family, make dealing with NER a challenge. The performance of an Arabic NER component affects the overall performance of the NLP system in a positive manner. This article attempts to describe and detail the recent increase in interest and progress made in Arabic NER research. The importance of the NER task is demonstrated, the main characteristics of the Arabic language are highlighted, and the aspects of standardization in annotating named entities are illustrated. Moreover, the different Arabic linguistic resources are presented and the approaches used in Arabic NER field are explained. The features of common tools used in Arabic NER are described, and standard evaluation metrics are illustrated. In addition, a review of the state of the art of Arabic NER research is discussed. Finally, we present our conclusions. Throughout the presentation, illustrative examples are used for clarification.

“Red” and “green” flags of risk disclosures – identifying associations between positive and negative key phrases and consecutive cumulative abnormal stock returns

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Deborah Yvonne Nagel ◽  
Stephan Fuhrmann ◽  
Thomas W. Guenther
Keyword(s):  
Stock Returns ◽  
Relevant Information ◽  
Risk Information ◽  
Information Value ◽  
Research Approach ◽  
Content Type ◽  
Abnormal Stock Returns ◽  
Key Phrases ◽  
Risk Disclosures ◽  
Selection Of

Purpose The usefulness of risk disclosures (RDs) to support equity investors’ investment decisions is highly discussed. As prior research criticizes the extensive aggregation of risk information in existing empirical research, this paper aims to provide an attempt to identify disaggregated risk information associated with cumulative abnormal stock returns (CARs). Design/methodology/approach The sample consists of 2,558 RDs of companies listed in the S&P 500 index. The RDs were filed within 10 K filings between 2011 and 2017. First, this study automatically extracted 35,685 key phrases that occurred in a maximum of 1.5% of the RDs. Second, this study performed stepwise regressions of these key phrases and identified 67 (78) key phrases that show positive (negative) associations with CARs. Findings The paper finds that investors seem to value most the more common key phrases just below the 1.5% rarest key phrase threshold and business-related key phrases from RDs. Furthermore, investors seem to perceive key phrases that contain words indicating uncertainty (impacts) as a negative (positive) rather than a positive (negative) signal. Research limitations/implications The research approach faces limitations mainly due to the selection of the included key phrases, the focus on CARs and the methodological choice of the stepwise regression analysis. Originality/value The study reveals the potential for companies to increase the information value of their RDs for equity investors by providing tailored information within RDs instead of universal phrases. In addition, the research indicates that the tailored RDs encouraged by the SEC contain relevant information for investors. Furthermore, the results may guide the attention of equity investors to relevant text passages whose deeper analysis might be useful with regard to investors’ capital market decisions.

scholarly journals Retrospectives: Lange and von Mises, Large-Scale Enterprises, and the Economic Case for Socialism

1991 ◽  
Vol 5 (4) ◽  
pp. 229-236 ◽  
Author(s):  
Joseph Persky
Keyword(s):  
Large Scale ◽  
Allocative Efficiency ◽  
Relevant Information ◽  
Great Difficulty ◽  
Socialist Economy ◽  
Private Ownership ◽  
Economic Calculation ◽  
Market Socialism ◽  
Von Mises ◽  
Static Conditions

In the debates over “economic calculation” launched by Ludwig von Mises in 1920 and extending well into the 1940s, the central issue concerned the ability of a socialist economy to achieve allocative efficiency. Von Mises emphasized that a collectivist state would have great difficulty in gathering and acting on relevant information; therefore, under socialism, even well-intentioned bureaucrats would lack a meaningful system of values on which to calculate. Defenders of socialism, such as Oskar Lange, countered that a market socialism could match demand to supply just as well as capitalism and meet the range of static conditions required for Pareto optimality. That debate is a rich and interesting story that has been told many times before. But in all that has been written, an important aspect of the original debate has been lost. Somewhat oddly, both the socialists like Oskar Lange and the advocates of private ownership like von Mises and Friedrich Hayek maintained that they were defending the progressive tendencies of competitive capitalism against the deadening hand of monopoly power. This historic paradox deserves consideration, if only because it serves to focus attention on our still incomplete theories of large-scale enterprises under socialism and capitalism.

Attentional Fluctuations Influence the Neural Fidelity and Connectivity of Stimulus Representations

2018 ◽  
Vol 30 (9) ◽  
pp. 1209-1228 ◽  
Author(s):  
David Rothlein ◽  
Joseph DeGutis ◽  
Michael Esterman
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Brain Networks ◽  
Relevant Information ◽  
Mental States ◽  
Attention Task ◽  
Default Mode ◽  
Neural Representations ◽  
Similarity Structure ◽  
Similarity Matrices

Attention is thought to facilitate both the representation of task-relevant features and the communication of these representations across large-scale brain networks. However, attention is not “all or none,” but rather it fluctuates between stable/accurate (in-the-zone) and variable/error-prone (out-of-the-zone) states. Here we ask how different attentional states relate to the neural processing and transmission of task-relevant information. Specifically, during in-the-zone periods: (1) Do neural representations of task stimuli have greater fidelity? (2) Is there increased communication of this stimulus information across large-scale brain networks? Finally, (3) can the influence of performance-contingent reward be differentiated from zone-based fluctuations? To address these questions, we used fMRI and representational similarity analysis during a visual sustained attention task (the gradCPT). Participants ( n = 16) viewed a series of city or mountain scenes, responding to cities (90% of trials) and withholding to mountains (10%). Representational similarity matrices, reflecting the similarity structure of the city exemplars ( n = 10), were computed from visual, attentional, and default mode networks. Representational fidelity (RF) and representational connectivity (RC) were quantified as the interparticipant reliability of representational similarity matrices within (RF) and across (RC) brain networks. We found that being in the zone was characterized by increased RF in visual networks and increasing RC between visual and attentional networks. Conversely, reward only increased the RC between the attentional and default mode networks. These results diverge with analogous analyses using functional connectivity, suggesting that RC and functional connectivity in tandem better characterize how different mental states modulate the flow of information throughout the brain.

Using Network Analysis and Visualization to Analyze Problematic Enterprise Information Systems

2013 ◽  
pp. 291-310
Author(s):  
David Greenwood ◽  
Ian Sommerville
Keyword(s):  
Information Systems ◽  
Network Analysis ◽  
Large Scale ◽  
Research Question ◽  
Analytical Techniques ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Complex Information ◽  
Or Groups ◽  
Technical Issues

Society is demanding larger and more complex information systems to support increasingly complex and critical organisational work. Whilst troubleshooting socio-technical issues in small-to-medium scale situations may be achievable using approaches such as ethnography, troubleshooting enterprise scale situations is an open research question because of the overwhelming number of socio-technical elements and interactions involved. This paper demonstrates proof-of-concept tools for network analysis and visualisation that may provide a promising avenue for identifying problematic elements and interactions among an overwhelming number of socio-technical elements. The findings indicate that computers may be used to aid the analysis of problematic large-scale complex socio-technical situations by using analytical techniques to highlighting elements, or groups of interacting elements, that are important to the overall outcome of a problematic situation.

Querying Web Accessibility Knowledge from Web Graphs

2011 ◽  
pp. 1437-1461 ◽  
Author(s):  
Rui Lopes ◽  
Luís Carriço
Keyword(s):  
Social Inclusion ◽  
Large Scale ◽  
Web Accessibility ◽  
Relevant Information ◽  
Point Of View ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Framework ◽  
Web Graphs ◽  
The Web

Web Accessibility is a hot topic today. Striving for social inclusion has resulted in the requirement of providing accessible content to all users. However, since each user is unique, and the Web evolves in a decentralized way, little or none is known about the shape of the Web’s accessibility on its own at a large scale, as well as from the point-of-view of each user. In this chapter the authors present the Web Accessibility Knowledge Framework as the foundation for specifying the relevant information about the accessibility of a Web page. This framework leverages Semantic Web technologies, side by side with audience modeling and accessibility metrics, as a way to study the Web as an entity with unique accessibility properties dependent from each user’s point of view. Through this framework, the authors envision a set of queries that can help harnessing and inferring this kind of knowledge from Web graphs.

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