bluuebunny/crossref_metadata_2025_split huggingface dataset:
Management of proximal deep vein thrombosis
Authors: Nyamekye I , Merker L 
Published: March 2012

Iliofemoral DVT constitutes approximately 20–25% of lower limb DVT and represents a specific subgroup of patients at highest risk for post-thrombotic syndrome (PTS). Anticoagulation alone has no significant thrombolytic activity and has not impact on PTS prevention. Early thrombus removal has reduced PTS in uncontrolled reports and reviews but major trials are awaited. The optimal timing for treatment appear to be thrombus <2 weeks old and, methods for thrombus removal include direct open or suction thrombectomy, catheter directed thrombolysis (CDT), with or without percutaneous mechanical thrombectomy (PMT) devices. Three principle types of PMT device are in use (rotational, rheolytic and ultrasound enhanced devices) and are combined with CDT in pharmocomechanical thrombolysis (PhMT) to enhance early thrombus removal. These devices have individual device specific attributes and side effects that are additional to the bleeding complications of thrombolysis. A number of additional interventions may be utilised to the improve results of CDT and PhMT. IVC filter deployment to reduce periprocedural PE, is supported by little evidence unless an indication for its use already exists. However, balloon venoplasty and vein stents undoubtedly vein patency after treatment. Early thrombus removal comes with additional upfront costs derived from devices, imaging and critical care bed usage. However, significant potential savings from reduction in PTS and rethrombosis rates may reduce overall societal costs. This review focuses on iliofemoral thrombosis, however, the less commonly encountered but clinically important subclavian vein thrombosis is also discussed.
Discerning Trends in Multiplex Immunoassay Technology with Potential for Resource-Limited Settings
Authors: Gordon Julian , Michel Gerd 
Published: March 2012

Abstract

BACKGROUND
In the search for more powerful tools for diagnoses of endemic diseases in resource-limited settings, we have been analyzing technologies with potential applicability. Increasingly, the process focuses on readily accessible bodily fluids combined with increasingly powerful multiplex capabilities to unambiguously diagnose a condition without resorting to reliance on a sophisticated reference laboratory. Although these technological advances may well have important implications for the sensitive and specific detection of disease, to date their clinical utility has not been demonstrated, especially in resource-limited settings. Furthermore, many emerging technological developments are in fields of physics or engineering, which are not readily available to or intelligible to clinicians or clinical laboratory scientists.

CONTENT
This review provides a look at technology trends that could have applicability to high-sensitivity multiplexed immunoassays in resource-limited settings. Various technologies are explained and assessed according to potential for reaching relevant limits of cost, sensitivity, and multiplex capability. Frequently, such work is reported in technical journals not normally read by clinical scientists, and the authors make enthusiastic claims for the potential of their technology while ignoring potential pitfalls. Thus it is important to draw attention to technical hurdles that authors may not be publicizing.

SUMMARY
Immunochromatographic assays, optical methods including those involving waveguides, electrochemical methods, magnetorestrictive methods, and field-effect transistor methods based on nanotubes, nanowires, and nanoribbons reveal possibilities as next-generation technologies.
Risk Factor Changes for Sudden Infant Death Syndrome After Initiation of Back-to-Sleep Campaign
Authors: Trachtenberg Felicia L. , Haas Elisabeth A. , Kinney Hannah C. , Stanley Christina , Krous Henry F. 
Published: March 2012

OBJECTIVE:To test the hypothesis that the profile of sudden infant death syndrome (SIDS) changed after the Back-to-Sleep (BTS) campaign initiation, document prevalence and patterns of multiple risks, and determine the age profile of risk factors.METHODS:The San Diego SIDS/Sudden Unexplained Death in Childhood Research Project recorded risk factors for 568 SIDS deaths from 1991 to 2008 based upon standardized death scene investigations and autopsies. Risks were divided into intrinsic (eg, male gender) and extrinsic (eg, prone sleep).RESULTS:Between 1991–1993 and 1996–2008, the percentage of SIDS infants found prone decreased from 84.0% to 48.5% (P &lt; .001), bed-sharing increased from 19.2% to 37.9% (P &lt; .001), especially among infants &lt;2 months (29.0% vs 63.8%), prematurity rate increased from 20.0% to 29.0% (P = .05), whereas symptoms of upper respiratory tract infection decreased from 46.6% to 24.8% (P &lt; .001). Ninety-nine percent of SIDS infants had at least 1 risk factor, 57% had at least 2 extrinsic and 1 intrinsic risk factor, and only 5% had no extrinsic risk. The average number of risks per SIDS infant did not change after initiation of the BTS campaign.CONCLUSIONS:SIDS infants in the BTS era show more variation in risk factors. There was a consistently high prevalence of both intrinsic and especially extrinsic risks both before and during the Back-to-Sleep era. Risk reduction campaigns emphasizing the importance of avoiding multiple and simultaneous SIDS risks are essential to prevent SIDS, including among infants who may already be vulnerable.
Strategies for Prevention of Health Care–Associated Infections in the NICU
Authors: Polin Richard A. , Denson Susan , Brady Michael T. ,   THE COMMITTEE ON FETUS AND NEWBORN and COMMITTEE ON INFECTIOUS DISEASES, Papile Lu-Ann , Baley Jill E. , Carlo Waldemar A. , Cummings James J. , Kumar Praveen , Tan Rosemarie C. , Watterberg Kristi L. , Byington Carrie L. , Davies H. Dele , Edwards Kathryn M. , Glode Mary P. , Jackson Mary Anne , Keyserling Harry L. , Maldonado Yvonne A. , Murray Dennis L. , Orenstein Walter A. , Schutze Gordon E. , Willoughby Rodney E. , Zaoutis Theoklis E. 
Published: March 2012

This Clinical Report was reaffirmed March 2023.
Health care–associated infections in the NICU result in increased morbidity and mortality, prolonged lengths of stay, and increased medical costs. Neonates are at high risk of acquiring health care–associated infections because of impaired host-defense mechanisms, limited amounts of protective endogenous flora on skin and mucosal surfaces at time of birth, reduced barrier function of their skin, use of invasive procedures and devices, and frequent exposure to broad-spectrum antibiotic agents. This clinical report reviews management and prevention of health care–associated infections in newborn infants.
Decision Support in Long Term Planning of Petroleum Production Fields
Authors: Erlingsen Espen , Strat Torgeir , Gunnerud Vidar , Nygreen Bjørn , Dueñas Díes Marta 
Published: March 2012

Abstract
In this paper, the goal is to optimize a petroleum production area consisting of several fields. This domain has great potential for using decision support tools to improve economical performance. In many of the mature petroleum areas, the potential for new development mainly includes smaller fields. Hence, strategic planning of the new development projects becomes increasingly important since smaller fields require more extensive planning to ensure profitability. The planning process for strategic investment decisions and production levels is today based on manual scenario analysis, a process that is both complex and time consuming. The intention of the decision support tool presented is to improve the efficiency of the concept study and give the planners a better basis for making their long term decisions.
Improved Performance in Real-Time Operational Support Processes through Application Process Work Flow Optimization in Russia
Authors: Rawlins Sheldon , Giasson Todd , Okafor Zim , Bokarev Anton , Moroz Pavel 
Published: March 2012

Abstract
The emergence of real-time enabled support centers has significantly improved the level of service delivery that is received by the operator companies that are drilling across the numerous oil fields in Russia. These support centers are multidisciplinary in approach and are focused on supporting measurement-while-drilling, logging-while-drilling, and directional drilling services and executing work flows without incurrence of nonproductive time. Many challenges, ranging from ensuring connectivity in remote areas to client acceptance of the role of support centers in their internal decision-making processes, have been successfully overcome. Key to this success was the implementation of work flows that optimize drilling processes in the holistic well construction cycle with incorporation of geomechanics and that support the optimal geological well placement based upon petrophysical analysis and interpretation.
These process work flows were synthesized to capitalize on the strong petrotechnical expertise and synergies existing within the collaborative environment of the support center. To further improve on the performance of such support centers, an engineering study was conducted in 2010 to assess further possibilities for improving service quality. Several areas of opportunity were identified, one of which included the incorporation of Lean and Six Sigma techniques to quantify the effect of modifications on these work processes. It was critical in this assessment to ensure that these process work flows seamlessly integrated into the work flows of the internal and external stakeholders that are beneficiaries of the support centers.
This paper discusses the results from the initial generations of these process work flows and the way forward for the continued process work flow integration, using a support center that was developed in Russia as an example. The application of these work flows has brought demonstrable financial and service-quality benefits to both operators and service companies, and the broader applications in its consistent execution have presented a critical step change in Russian environment drilling performance.
Production Monitoring Using Artificial Intelligence, APLT Asset
Authors: Olivares G. , Escalona C. , Gimenez E. 
Published: March 2012

Abstract
The Litoral de Tabasco asset, in PEMEX's southwest marine region, was initially implemented to monitor and estimate the flow rate of naturally flowing wells, using daily operational conditions and well tests with the so-called Gilbert and Ashford and Pierce correlations.
The effectiveness of these correlations has now been reduced as a result of irregularities in operational conditions; lack of consistency in conducting the production well tests; limited availability of measurement and operational issues with mass, conventional, and multiphase flow meters; and ongoing problems with electronics communication, nonavailability of vessels, and high operational costs. If the operational conditions measured during the well tests were wrong, all the properties are suspect and may have affected the correlations developed in determining the estimated volume per well and associated monitoring workflow.
To address this problem, a new workflow using a set of predictive proxy models has been developed that combines artificial intelligence techniques such as neural networks with nodal analysis, and sporadic and high-frequency data to allow engineers to process and understand production behavior from the large amounts of information available, which are gathered according to the system being studied or evaluated.
This workflow enables validation of field well test data, which reduces the uncertainties in well production allocation, increases the accuracy of hydrocarbon accounting from the pumping process to the marine terminal, and implements an early detection system for anomalies that is published on the Internet for sharing with the entire asset management.
Now, when it is not possible to measure well production, the outputs of a proxy model and a nodal analysis are combined with sporadic and real-time data to reconstruct the historical and actual volume on a daily basis.
Integrating Mathematical Optimization and Decision Making in Intelligent Fields
Authors: Ciaurri David Echeverría , Conn Andrew R. , Mello Ulisses T. , Onwunalu Jerome E. , Onwunalu Jerome E. 
Published: March 2012

Abstract
In this paper a decision-making approach that can be applied to problems that are relevant to the oil and gas industry is presented. This methodology is supported by state-of-the-art mathematical optimization algorithms, and is based on the formal integration of the decisions in question with well-studied optimization procedures. The integration of the methodology with the application adds to its robustness. Two different types of problems are formulated and solved. The first kind is based on deciding which wells have to be shut in during a given production interval whilst simultaneously optimizing the controls for each selected well. The second category involves deciding for a group of wells which ones have to be injectors or producers, and at the same time searching for optimal well locations. In all the results obtained we can systematically see that the set of decisions proposed by the integrated approach mean substantial improvement in field production. For example, in the first class of problems studied, the production oil target is satisfied, and up to 50 percent of produced water is saved with respect to the reference case. The huge amount of information available, for example, in Intelligent/Smart Fields or Closed-Loop Reservoir Management can be utilized for rigorously making solid decisions. In this work we put an emphasis on integration of real-life decisions with a realistic simulation-based mathematical optimization framework. This framework can be also useful for establishing a common language for decision makers and researchers within a given organization, and as a consequence endowing the decision-making process with agility and robustness. It should be stressed that ultimately it is human interpretation and intuition that drives the making of crucial decisions. Automated tools should be understood as an additional (and hopefully valuable) source of information for making these important decisions.
Integrating WITSML, PRODML, and RESQML Standards for Cross-Domain Workflows
Authors: McKenzie William , Morandini Francis , Verney Philippe , Deny Laurent , Rainaud Jean-Francois , Eastick Rob , Masters Gary , Endres David Mack 
Published: March 2012

Abstract
The WITSML™, PRODML™, and RESQML™ standards for data and Web services have achieved early success in providing the "information plumbing" to enable the digital oil field in their domains (drilling and completions, production operations, and reservoir management, respectively). As the adoption of these standards accelerates, it has become clear that a simple way is needed to combine information objects from these standards for cross-functional workflows. This paper examines a proposal for an EnergyML Package file format that can be transported over standard protocols such as HTTP and FTP with emphasis on the following features. The file format can be consumed without special parsing by all major programming languages. It provides relationship files that can identify and link individual data objects according to the role they play in a workflow. All objects can reference common metadata, such as geographic coordinate systems, a common property dictionary, and Dublin Core® attributes.
Transformation and Change in Oil and Gas Production
Authors: Rubio Sergio Sama , Lochmann Mark J. , Denver Larry , Rees Dave 
Published: March 2012

Abstract
Intelligent Energy ("IE") describes a new way of monitoring and performing production operations, with IE initiatives driven by multiple business imperatives such as increasing production, reducing cost, managing risk, etc. Disciplines within exploration and production ("E&P") and other industries have undergone similar changes, but E&P companies have been typically slow to embrace new operating practices. Published case studies, Cambridge Energy Research Associates and other sources (Dutra et al. 2010, Moisés et al. 2008, Sankaran et al. 2011 and García et al. 2010) have provided a continuous stream of justifications for adopting these new methods. Given the substantial gains possible, the pace of innovation associated with these initiatives seems inconsistent however. Some of the reasons for hesitancy in adopting new solutions include:
Culture. Culture is a major factor in transformation and in an organization's ability to embrace change. Production is driven by process efficiency, reliability, tight control and predictability among others. Change threatens to upset these accepted norms; therefore, it is largely unwelcome.
Entrenched business models. Production groups have for years repeated the same tasks and experiences where habit, personal judgment and good management have delivered acceptable returns.
Fragmentation. Disparate applications, data, and procedures have become "stacked" haphazardly without a stabilizing, unifying framework. People have adapted to a highly fragmented environment by not changing anything unless required but if everyone does the same things as before, there can be no meaningful gains.
People, process, and technology. Each must be aligned to reach a business goal. If one component is missing or misaligned, the goal is less likely to be achieved. Engineers are comfortable with technology and accept ownership of processes, but almost universally believe that someone else is responsible for "people." These components may never align without strong leadership.
Manpower. If an organization is "getting by" with limited resources, new processes often mean core activities are threatened. Such threats tend to make companies avoid disruptions and maintain the status quo. Manpower shortages can impact nearly all aspects of business success. At this time, staffing issues may be more critical than any other single factor when the consequences and ramifications of insufficient staffing are examined. It is likely that E&P performance will be most heavily impacted in today's environment by our industry's ability or inability to address this critical issue. This paper examines the key contributing factor of manpower availability, its impact on the industry, and assesses the readiness for transformation within E&P.
Successful Real-Time Optimization of a Highly Complex, Integrated Gas System: Intelligent Energy in the Real World
Authors: Göbel Derek , Briers Jan , De Boer Frank , Cramer Ron , Lai Kok-Lam , Hooimeijer Martijn 
Published: March 2012

Abstract
This paper describes the successful application of Real-Time Optimization by Shell Malaysia E&P on the Integrated Gas Production System in Sarawak, implementing models for real-time monitoring and optimization of wells and facilities on a gas production network spanning more than 100 wells on more than 40 platforms across a number of different Production Sharing Contracts. We highlight how Digital Oil Field practices enable field-based data to be turned into information, support decision making, and lead to actions that ensure production is optimized continuously.
The technology described in this paper is applied to achieve consistent gas supply to meet demand, maximize revenue, and enable improved and timely operational decisions - striking a balance between short- and long-term value, and taking into account the reality of commercial and contractual constraints, finance, and economics. The optimization is data-driven and covers more than 1,000 variables and features multiple, mutually dependent objectives and constraints.
The solution has proven significantly better than prior physical model-based solutions, which deliver optimized field settings, but with inherently unstable results, and not fast enough for application in a real-time decision making environment. Field trials have proven a result of: increased condensate production at current or improved expected Ultimate Recovery, whilst maintaining a stable gas supply, fulfilling quality constraints and contractual LNG nominations.
This is one of the first successful attempts to implement truly-real-time optimization in a production environment of this size and complexity, including a complicated set of commercial and contractual constraints, and striking a transparent balance between short-term and long-term value. Having proven that a multi-departmental reality can be successfully captured and modeled, might mark the start of a transformation towards embedding intelligent energy to its true potential.
Maximizing the Value of the Intelligent Field: Experience and Prospective
Authors: Alhuthali Ahmed H. , Al-Ajmi Fahad A. , Shamrani Sultan S. , Abitrabi Ballan Abdel N. 
Published: March 2012

Abstract
Our industry has embarked largely on implementing the intelligent field initiative in recent years, which is a clear indication of the surge to adapt to new methods, processes and workflows to manage existing and new fields. The capacity at which this technology was implemented worldwide is a sign of a strong buy-in from the industry that this technology will deliver on its promises in terms of maximizing hydrocarbon production, recovery, profits, or health, safety and environmental compliance.
Saudi Aramco is considered to be a leader in deploying and utilizing the intelligent field technology to maximize the value of hydrocarbon reservoirs. This paper discusses the implementation of intelligent field initiative in Saudi Arabian fields and particularly in the world's largest intelligent field, the Khurais complex. It highlights the huge infrastructure to measure and transmit data and to manage and control production in this field. As a result of the lessons learned from this experience, the classical reservoir management concepts are going through a major transformation to adapt to a fundamental change in data acquisition and production controls. Moreover, the engineers were faced with a new challenge in the reservoir monitoring process and overall field optimization, which requires a paradigm shift in analysis, interpretation, and decision making to maximize the value of the intelligent field. So far, the industry's efforts to utilize intelligent field technology are mainly focused at well level to optimize production rate and ensure target rate compliance. Saudi Aramco's efforts are going beyond the well level to optimize reservoir performance and enhance oil recovery. This paper illustrates some of those efforts, which resulted in a better understanding of well deliverability and reservoir connectivity.
In addition, this paper highlights the major challenges facing operating companies, to manage those fields. It provides methods and workflows to mitigate these challenges and maximize the value of intelligent fields and fully utilize the existing infrastructure and capabilities.