Accelerating Hydrocarbon Maturation and Project Delivery by 30% with Digitalization - Standardizing on the Fly Analysis to Enable Informed Decision Making Using Petabytes of Petro Technical Data

In recent years, with the steep drop and increased volatility in oil price, there is an urgency for making our field (re-development) plans more dynamic and efficient with faster payback and with particular emphasis on robustness against uncertainties. This paper describes a root cause analysis and a methodology to achieve up to ~30% improvement in field development planning project cycle and developing a better-integrated reservoir understanding. A comprehensive integrated analysis of available data is a key success criterion for robust decision-making. A detailed value stream mapping and a timeline analysis for data analysis in the hydrocarbon maturation process revealed that our process cycle efficiency is only 16% with a significant room for improvement. Any improvement can be directly translated to man-hour cost saving and acceleration of oil delivery. Effective use of technology and digitalization for knowledge management, standardized ways of working and easy access to historical data, analysis and diagnostics were identified as key focus areas to improve delivery. An innovative process and web based digital platform, iResDAT, is developed for accelerating data analysis. It mines from volumes of petro-technical databases and translates data into standardized diagnostics using latest data analytics and visualization technologies. It has already reduced dramatically the time to mine critical subsurface data and prepare required integrated diagnostics that are auditable and can be re-created in a few seconds. Based on the early pilot studies the cycle time reduction in the data analysis phase is close to 30% with improved quality and standardization of the integrated analysis. It has already transformed the ways of working where the subsurface discussion can happen across disciplines using a single platform that enforces early integration for reservoir understanding and associated uncertainty characterization. It is a web-based platform where the diagnostic dashboards are crowd sourced; sustained and enhanced by the business to ensure the relevance and sustainability with the Corporate Data Management and IT functions. It is a building block towards quality controlled and auditable data analysis and interpreted dataset, which may form the backbone for any advanced analytics in future to enable digitally enabled hydrocarbon maturation.

Insights into financial technology (FinTech): a bibliometric and visual study

This paper conducted a comprehensive analysis based on bibliometrics and science mapping analysis. First, 848 publications were obtained from Web of Science. Their fundamental characteristics were analyzed, including the types, annual publications, hot research directions, and foci (by theme analysis, co-occurrence analysis, and timeline analysis of author keywords). Next, the prolific objects (at the level of countries/regions, institutions, journals, and authors) and corresponding pivotal cooperative relationship networks were used to highlight who pays attention to FinTech. Furthermore, the citation structures of authors and journals were investigated, including citation and co-citation. Additionally, this paper presents the burst detection analysis of cited authors, journals, and references. Finally, combining the analysis results with the current financial environment, the challenges and future development opportunities are discussed further. Accordingly, a comprehensive study of the FinTech documents not only reviews the current research characteristics and trajectories but also helps scholars find the appropriate research entry point and conduct in-depth research.

A Cognitive Personal Assistant System to Enhance the Individual-Centric Research Capabilities

The intelligent personal assistant system is designed to support the individual researchers to enhance their quality of the research through the natural language interface. Specifically, this system automatically provides intrinsic details about the importance of the topic of discussion using the timeline analysis. The results generated by the system help the researchers to understand the preference of the global researchers in the specific research field. This system primarily identifies the core topic of the discussion from the user's presentation. Further, the importance of the topic is calculated based on the research articles published over three decades in the related field. The experimental results confirm that the proposed method accurately identifies whether the research topic the user presented is HOT.

Rise and fall of total mesorectal excision with lateral pelvic lymphadenectomy for rectal cancer: an updated systematic review and meta-analysis of 11,366 patients

The role of lateral lymph node dissection (LLND) during total mesorectal excision (TME) for rectal cancer is still controversial. Many reviews were published on prophylactic LLND in rectal cancer surgery, some biased by heterogeneity of overall associated treatments. The aim of this systematic review and meta-analysis is to perform a timeline analysis of different treatments associated to prophylactic LLND vs no-LLND during TME for rectal cancer. Methods A literature search was performed in PubMed, SCOPUS and WOS for publications up to 1 September 2020. We considered RCTs and CCTs comparing oncologic and functional outcomes of TME with or without LLND in patients with rectal cancer. Results Thirty-four included articles and 29 studies enrolled 11,606 patients. No difference in 5-year local recurrence (in every subgroup analysis including preoperative neoadjuvant chemoradiotherapy), 5-year distant and overall recurrence, 5-year overall survival and 5-year disease-free survival was found between LLND group and non LLND group. The analysis of post-operative functional outcomes reported hindered quality of life (urinary, evacuatory and sexual dysfunction) in LLND patients when compared to non LLND. Conclusion Our publication does not demonstrate that TME with LLND has any oncological advantage when compared to TME alone, showing that with the advent of neoadjuvant therapy, the advantage of LLND is lost. In this review, the most important bias is the heterogeneous characteristics of patients, cancer staging, different neoadjuvant therapy, different radiotherapy techniques and fractionation used in different studies. Higher rate of functional post-operative complications does not support routinely use of LLND.

A cost-effective way to design a two-layered cell trapping microfluidic device

When studying cells population, sometimes is necessary to isolate a specific subset to perform a timeline analysis or determinate the evolution on cell progeny. Microfluidic devices are being used for fulfill this function in multiple designs. However, the design and fabrication of this type of devices involve multiple challenges and high cost. Miniaturization tends to be the primarily challenge where those devices below 10um tends to be so expensive that needs special facilities for fabrication, but using techniques as multilayer fabrication those problems can be overcome. In this work are stated techniques (photolithography, soft-lithography) that helps solving that limitations, from using inexpensive materials, to alignment techniques that does not requires high-tech equipment, and a practical design for microfluidic cell trapping array. Where multiple cell types could be seeded and trapped in small cluster (varying on cell size) to be retrieved later on in an easy and practical way.

Who Has Benefited? A Socio-Ecological Chronology of Urban Resilience in the Early Reconstruction of Talca after the 27-F Earthquake, Chile 2010–2012

This article engages in the understanding of resilience from the perspective of socio-ecological systems (SES) and the reconstitution of events of recovery and reconstruction in the city of Talca after the 27-F earthquake in Chile, between 2010 and 2012. For such purposes, we have developed a chronological or timeline-analysis model. This methodology, which uses mostly ethnographic and participant-observation techniques to recapitulate these events, observes the interaction of social agents, elements of the built environment, government institutions, and other institutional functions of the urban domain within the socio-ecological panarchy. The results suggest that key events, such as local government institutional actions, the observation of probable property speculation events, and community agency efforts dismissal, among other factors, could alter both human and natural resilience processes. In turn, this could affect the capacity of this city, its inhabitants, and its social institutions to endure future crises, as a product of deteriorated and maladaptive resilience mechanisms, aside from the natural and geographical conditions of Chile, exposed to future earthquake events. Likewise, the partial loss of the civic environment in this historic city and weakened neighborhood networks, contrasting with the redevelopment of real estate in central areas, altogether portray considerable risks with regard to the (un)generated social mechanisms of resilience, affecting future developments. The final section focuses on discussing these findings and their relevance in integrating a coherent understanding of SES resilience in urban planning and governance practice, especially in cities or urban areas that are prone to natural risks or catastrophes.

The Y chromosome ancestry marker R1b1b2: a surrogate of the SARS-CoV-2 population affinity

Individual and population susceptibilities to disease remain a murky area of investigation, clouded by past bias based on ideological differences and wars. The current SARS-CoV-2 pandemic, the largest in living memory, brought this matter to forefront as the disparity in disease burden became apparent. A timeline analysis of the pandemic revealed the presence of country clusters that display a marked preponderance of disease among populations carrying the ancestry marker R1b1b2, notably associated with both infection and mortality. This marker is a relic of past human expansions from western Asia and subsequently Europe and the rest of the world, which may have been accompanied by peculiar biological events rendering these populations vulnerable to SARS-CoV-2.

Low-fat, lactose-free and leucine-enriched chocolate cow milk prototype: A preliminary study on sensorial acceptability and gastrointestinal complaints following exhaustive exercise

Background Chocolate milk has gained recent scientific support as a recovery drink. However, it is known that high exercise-demand triggers gastrointestinal discomfort which continues post-exercise, thereby hindering this nutritional strategy. In addition, those who are lactose intolerant cannot benefit from a milk-based beverage. Thus, the aim of this preliminary study was to develop a low-fat, lactose-free, and leucine-enriched chocolate cow milk prototype (CML) representing nutrition-related recommendations for football players, as well as assess athletes’ individual subjective outcomes for gastrointestinal complaints and sensorial acceptability in a field-based setting following strenuous team-sport physical demands. Methods This study followed a single group and repeated-measured design with 10 football players (23 ± 2 yrs., 74 ± 14 kg, 174 ± 5 cm) who consumed CML following a 90-min football match simulation protocol (FMP). The total CML intake to achieve 0.150 g leucine·kg [BW]·h− 1 occurred in aliquots of 50, 30 and 20% at 0-, 45- and 75-min post-FMP, respectively. Athletes were evaluated by the prevalence, the type and severity (bloating, nausea, flatulence, and gastric reflux) of gastrointestinal complaints and sensorial acceptability (overall perception, appearance, consistency, and flavour) after drinking each aliquot in a 4-h recovery period. Results The CML showed higher scores for “Product Acceptability Index” (88%) and sensorial acceptability (~ 8 in 9-point hedonic scale). Kendall’s W with bootstrapped resample (95%CI) revealed agreement among respondents as “moderate” (overall perception, flavour) to “strong” (appearance, consistency) and with no significant agreement differences between rater response in the timeline analysis (0.57 up to 0.87; p > 0.05). Agresti-Caffo add-4 analysis (95% confidence interval, [95%CI]) revealed no differences in each time-point analysis versus baseline for athletes classified as having severe gastrointestinal symptoms, but confirmed concern with bloating (three athletes showed a transient response at 2-h and only one continued until 3-h; p = 0.051). Conclusions These preliminary findings suggest that CML presents good taste and high acceptability by the sampled athletes. Thus, CML may be an alternative sport drink for immediate post-workout supplementation to overcome the energy deficit, offer co-ingested leucine, maintain palatability and adherence including lactose intolerance following a team sport-specific fatigue. Trial registration RBR-2vmpz9, 10/12/2019, retrospectively registered.

Discovering Spatio-Temporal Pattern of City Crime – Visual Analysis on Felony Crime in New York

Pattern recognition has long been regarded as key role for crime prevention and reduction. Crime analysts and policy makers can formulate effective strategies and allocate resources with reference to spatial and temporal pattern of crime. In order the combat and prevent severe crime in New York City (NYC), this study analyzed Felony Crime data of NYC in previous 5 years (2015 2020) and discovered criminal hotspots pattern and temporal patterns with open criminal complaint data provided by New York Police Department (NYPD). This study adapt a human computer interactive appraoch to draw patterns from crime data, whereas computations and visualization are performed by Python libraries, and human to inform the decision of visualization methods, computational parameters and direction of this exploratary analysis. Density based clustering algorithms, Grid Thematic Mapping and Density Heatmap are displayed to identify hotspots and demonstrates their associations with spatial features. Timeline analysis on moments of crime occurance demonstrates seasonality where crimes are mostly commited, while aoristic analysis showed hours of day when crime is mostly committed considering their timespan. Lastly, 3D visualization improved recognition of the displacement of hotspot over time, and suggested long term hotspots in NYC in 3 D visualization. This inform strategic plans for police deployment.

The Enhanced Forensic Examination and Analysis for Mobile Cloud Platform by Applying Data Mining Methods

Investigating the mobile cloud environment is a challenging task due to the characteristics of voluminous data, dispersion of data, virtualization, and diverse data. Recent research works focus on applying the latest forensic methodologies to the mobile cloud investigation. This paper proposes an enhanced forensic examination and analysis model for the mobile cloud environment that incorporates timeline analysis, hash filtering, data carving, and data transformation sub-phases to improve the performance of the cloud evidence identification and overall forensic decision-making. It analyzes the timeline of events and filters the case-specific files based on the hash values and metadata using the data mining methods. The proposed forensic model performs the in-place carving on the filtered data to guide the investigation and integrates the heterogeneous file types and distributed pieces of evidence with the assistance of the data mining. Finally, the proposed approach employs LSTM based model that significantly improves the forensic decision making.