Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive observer for kick detection and switched control for bottomhole pressure regulation and kick attenuation during managed pressure drilling

Control of the annulus pressure during drilling of oil and gas wells can be a challenging task, due to the complex dynamics of the multiphase flow. Since well kicks and fluid losses are potentially dangerous, it is important to improve the performance and the capabilities of estimation and control and to initiate an automatic well control system. Novel adaptive observers for estimation the flow rates through the well are developed for kick and loss detection, and asymptotic convergence properties are established. A switched control algorithm for feedback control of the choke and the back-pressure pump is proposed for pressure control and kick attenuation and asymptotic convergence is achieved. A new observer is developed to estimate the reservoir pore pressure for improved kick management. Simulation results obtained with a high fidelity drilling simulator are presented to demonstrate the effectiveness of the proposed observer and control scheme. The results show that the proposed observers effectively detect kicks in the early phase and that the automatic control scheme improves the kick handling.
Ovarian development and ovipositional preference of the western corn rootworm (Coleoptera: Chrysomelidae) variant in east central Illinois.

The rotation of maize, Zea mays L. , and soybean, Glycine max (L.) Merr. , has been the traditional cultural tactic to manage the western corn rootworm, Diabrotica virgifera virgifera LeConte, in the Corn Belt. The reduced effectiveness of this rotation as a pest management tool in east central Illinois, northern Indiana, and southern Michigan can be explained by the shift in the ovipositional behavior of the new variant of western corn rootworm. The objective of this study was to evaluate the influence of maize, soybean, oat, Avena sativa L. , stubble, and alfalfa, Medicago sativa L. , on the ovarian development and ovipositional preferences of the variant western corn rootworm. Field research was conducted near Urbana, IL, during 1998-2000. Gravid females were present throughout the season in all crops, and due to the prolonged period in which western corn rootworm females can lay eggs, none of the crops were immune from oviposition. Results indicated that the western corn rootworm variant oviposits in maize, soybean, oat stubble, and alfalfa In 1998 and 1999, maize was the preferred oviposition site among crops; however, in 2000, maize, soybean, and oat stubble treatments had similar densities of western corn rootworm eggs. Lack of oviposition preference of the western corn rootworm variant demonstrated in this experiment represents a reasonable explanation of why the effectiveness of the rotation strategy to control western corn rootworm has diminished.
A New Method for Designing Constrained Causal Stable IIR Variable Digital Filters

This paper studies the design of causal stable Farrow-based IIR variable digital filters (VDFs), whose subfilters have a common denominator. This structure has the advantages of reduced implementation complexity and avoiding undesirable transient response when tuning the spectral parameter in the Farrow structure. The design of such IIR VDFs is based on a new model reduction technique which is able to incorporate prescribed flatness and peak error constraints to the IIR VDF under the second order cone programming framework. Design examples are given to demonstrate the effectiveness of the proposed approach
Tobacco smoking- and alcohol drinking-attributable cancer mortality in Germany

The aim was to estimate the cancer mortality explained by tobacco smoking and alcohol risk drinking. The methods included (1) smoking rates from the largest population survey and alcohol drinking data from the German National Health Survey, and (2) vital statistics from Germany. The tobacco- and alcohol-related data were analysed using formulas for the estimation of attributable fractions. The results show that 19.7% of all malignant neoplasm deaths are explained by tobacco smoking alone, a further 0.2% by alcohol consumption alone and a further 5.6% by tobacco smoking and alcohol drinking. It is concluded that this overlap in the two substance use behaviours has to be taken into account when considering attributable mortality data.
Modeling and Design for a Novel Adaptive Voltage Positioning (AVP) Scheme for Multiphase VRMs

Adaptive voltage positioning (AVP) has been used in multiphase voltage regulator module (VRM) applications. A novel scheme, called AVP+, is analyzed in this paper. Small signal model is used to look into the control performance issues such as output impedance and stability. The model has been verified in the experiments and simulations. Compared to a conventional AVP schemes, the present scheme provides better stability margin and output- impedance performance. This is especially true for the prevailing trend of using ceramic output capacitors and high switching frequency. The focus of the present paper is the small-signal modeling for control loop design using the AVP+ scheme which was never analyzed before. And the comparisons were made between AVP+ and AVP- on the stability and output impedance performance.
Hybridizable discontinuous Galerkin and mixed finite element methods for elliptic problems on surfaces

We define and analyze hybridizable discontinuous Galerkin methods for the Laplace-Beltrami problem on implicitly defined surfaces. We show that the methods can retain the same convergence and superconvergence properties they enjoy in the case of flat surfaces. Special attention is paid to the relative effect of approximation of the surface and that introduced by discretizing the equations. In particular, we show that when the geometry is approximated by polynomials of the same degree of those used to approximate the solution, although the optimality of the approximations is preserved, the superconvergence is lost. To recover it, the surface has to be approximated by polynomials of one additional degree. We also consider mixed surface finite element methods as a natural part of our presentation. Numerical experiments verifying and complementing our theoretical results are shown.
Hydrophobic Cellulose-based Materials Obtained by Uniaxial High Pressure Compression: In-situ Esterification with Fatty Acids and Fatty Anhydrides

High-pressure molding at an elevated temperature was investigated as a potential technique for performing the esterification of octanoic acid and octanoic anhydride on cellulose and miscanthus. Emulsion, solvent exchange, and high-pressure homogenizer pretreatments were performed on the reactants in order to improve liquid-solid contacts. After pretreatment, cellulose or miscanthus and octanoic acid or octanoic anhydride were molded at 220 MPa and an elevated temperature. The mechanical properties of the resulting compressed materials were measured, and the material was then ground and washed; the water drop angle was measured, and IR analysis was performed, as well as an accurate measure of the degree of substitution. The esterification reaction was confirmed, the water properties of the grafted cellulose were modified, and the mechanical properties of the modified materials were altered. From this pioneering work, a better understanding of the effect of the molding process on the reaction and production of water-resistant compressed cellulose materials was developed.
A modular approach to disease registry design: Successful adoption of an internet‐based rare disease registry

There is a need to develop Internet‐based rare disease registries to support health care stakeholders to deliver improved quality patient outcomes. Such systems should be architected to enable multiple‐level access by a range of user groups within a region or across regional/country borders in a secure and private way. However, this functionality is currently not available in many existing systems. A new approach to the design of an Internet‐based architecture for disease registries has been developed for patients with clinical and genetic data in geographical disparate locations. The system addresses issues of multiple‐level access by key stakeholders, security and privacy. The system has been successfully adopted for specific rare diseases in Australia and is open source. The results of this work demonstrate that it is feasible to design an open source Internet‐based disease registry system in a scalable and customizable fashion and designed to facilitate interoperability with other systems. © 2012 Wiley Periodicals, Inc.
Supporting Software Developers with a Holistic Recommender System

The promise of recommender systems is to provide intelligent support to developers during their programming tasks. Such support ranges from suggesting program entities to taking into account pertinent Q&A pages. However, current recommender systems limit the context analysis to change history and developers' activities in the IDE, without considering what a developer has already consulted or perused, e.g., by performing searches from the Web browser. Given the faceted nature of many programming tasks, and the incompleteness of the information provided by a single artifact, several heterogeneous resources are required to obtain the broader picture needed by a developer to accomplish a task. We present Libra, a holistic recommender system. It supports the process of searching and navigating the information needed by constructing a holistic meta-information model of the resources perused by a developer, analyzing their semantic relationships, and augmenting the web browser with a dedicated interactive navigation chart. The quantitative and qualitative evaluation of Libra provides evidence that a holistic analysis of a developer's information context can indeed offer comprehensive and contextualized support to information navigation and retrieval during software development.
Age-related changes of nasal cavity and conchae volumes and volume fractions in children: a stereological study.

BACKGROUND The anatomy of the human nasal cavity (NC) is complex and its structures are closely related to the functions of the NC. Studies which assessing the mean volumes of NC and conchae are very infrequent. The purpose of current study is to investigate development of NC and conchae according to age and sex by using stereological method. MATERIALS AND METHODS This retrospective volumetric study was carried out on 342 individuals (166 females and 176 males) between 0 and 18 years old with no pathological conditions or medical procedures that affected the skeletal morphology of the NC. Volumetric estimations were determined on computed tomography (CT) images using point-counting approach of stereological methods. RESULTS NC, inferior nasal conchae (INC) and middle nasal conchae (MNC) volume measurements that obtained using point-counting method were increased with age in both sexes until 15 years old. Regardless of gender; no significant difference was determined between the left and right values for NC, conchae volumes and choanae measurements. Generally, significant differences were determined in NC and INC volumes according to gender after they reached maximum growth period. According to age the volume ratios of INC to NC and MNC to NC were ranged from 18% to 32% and 9% to15%, respectively. CONCLUSIONS The current study demonstrated that the point-counting method is effective in determining volume estimation of NC and is well suited for CT studies. Our results could provide volumetric indexes for the NC and conchae, which could help the physician for both patient selections for surgery, and for the assessment of any surgical technique used to treatment of nasal obstruction. (.
Anomaly diagnosis based on regression and classification analysis of statistical traffic features

Traffic anomalies caused by Distributed Denial-of-Service DDoS attacks are major threats to both network service providers and legitimate customers. The DDoS attacks regularly consume and exhaust the resources of victims and hence result in abnormal bursty traffic through end-user systems. Additionally, malicious traffic aggregated into normal traffic often show dramatic changes in the traffic nature and statistical features. This study focuses on early detection of traffic anomalies caused by DDoS attacks in light of analyzing the network traffic behavior. Key statistical features including variance, autocorrelation, and self-similarity are employed to characterize the network traffic. Further, artificial neural network and support vector machine subject to the performance metrics are employed to predict and classify the abnormal traffic. The proposed diagnosis mechanism is validated through experiments where the datasets consist of two groups. The first group is the Massachusetts Institute of Technology Lincoln Laboratory dataset containing labeled DoS attack. The second group collected from DDoS attack simulation experiments covers three representative traffic shapes resulting from the dynamic attack rate configuration, namely, constant intensity, ramp-up behavior, and pulsing behavior. The experimental results demonstrate that the developed mechanism can effectively and precisely alert the abnormal traffic within short response period. Copyright © 2013 John Wiley & Sons, Ltd.
Spatial analysis of Influenza A H1N1 and evaluation of risk factors in Changsha City based on GIS

Most traditional epidemiological studies are based on the statistical analysis rather than spatial information. Therefore, the study combining spatial analysis with epidemiology is a promising and perspective field. This paper, based on the technology of GIS, the method of disease mapping and traditional statistics, is focus on the spatial data of influenza A virus subtype H1N1. A spatial database of H1N1 flu in Changsha and the map of incidence rate are established to analyze the cause formation of accumulation areas combining with the spread characteristics. After spatial risk factors are explored, results show that these risk factors are correlated to incidence rate of H1N1 flu in Changsha. It has a huge significance to check out specific situation about Changsha region so as to provide more effective and protective measures though the scientific research method.
Dietary sodium intake and incidence of congestive heart failure in overweight US men and women: first National Health and Nutrition Examination Survey Epidemiologic Follow-up Study.

BACKGROUND Cross-sectional epidemiologic studies suggest that a higher intake of dietary sodium is associated with an increased risk of left ventricular hypertrophy. We studied the relationship between dietary sodium intake and incidence of congestive heart failure (CHF) in the first National Health and Nutrition Examination Survey Epidemiologic Follow-up Study participants. PARTICIPANTS AND METHODS The study sample consisted of 5233 nonoverweight and 5129 overweight men and women without a history of CHF at their baseline examination. Dietary sodium and other nutrient intake estimates were obtained by a 24-hour dietary recall method at the baseline examination, conducted from 1971 to 1975. The incidence of CHF was assessed using medical records and death certificates obtained in 1982 to 1984, 1986, 1987, and 1992. RESULTS During an average of 19 years of follow-up, we documented 413 cases of CHF in nonoverweight and 679 cases of CHF in overweight participants. After adjustment for known CHF risk factors, the relative risk of CHF among overweight participants was 1.43 (95% confidence interval, 1.07-1.91) for those whose sodium intake was greater than 113.6 mmol/d compared with those whose intake was less than 50.2 mmol/d. The relative risks of CHF for a 100-mmol/d higher intake of sodium or per 1743 kcal (average energy intake in the study population) were 1.26 (95% confidence interval, 1.03-1.53) and 1.21 (95% confidence interval, 1.04-1.40), respectively. CONCLUSIONS A higher intake of dietary sodium is a strong independent risk factor for CHF in overweight persons. A reduction in sodium intake may play an important role in the prevention of CHF in overweight individuals and populations.
A Combined Signal Subspace Projection and Partial Filtering Approach to Target Detection for Hyperspectral images

In the study, a novel signal subspace projection (SSP) approach is first proposed to detect and extract target signatures in unknown background. The weights of SSP are equivalent to optimal weights given by Wiener-Hopf equations. To further reduce the computation complexity in SSP, we implement the SSP-based classifier by an adaptive filter combined with some partial filters, called CSSPPF. In CSSPPF, we partition the image into several groups according to their associated band correlation. By the way, we transfer the design of a large fully filter into several small partial filter designing. Simulation results performed on AVIRIS images have demonstrated the efficiency of the proposed approaches.
Adaptive Piecewise Linear Controller for Servo Mechanical Control Systems

In this paper, an adaptive piecewise linear control scheme is proposed for improving the performance and response time of servo mechanical control systems. It is a gain stabilized control technique. No large phase lead compensations or pole zero cancellations are needed for performance improvement. Large gain is used for large tracking error to get fast response. Small gain is used between large and small tracking error for good performance. Large gain is used again for small tracking error to cope with disturbance. It gives an almost command independent response. It can speed up the rise time while keeping robustness unchanged. The proposed control scheme is applied to a servo system with large time lag and a complicated electro-hydraulic velocity/position servo system. Time responses show that the proposed method gives significant improvements for response time and performance.
Progress with peptide scanning to study structure-activity relationships: the implications for drug discovery

ABSTRACT Introduction: Peptides have gained renewed interest as candidate therapeutics. However, to bring them to a broader clinical use, challenges such as the rational optimization of their pharmacological properties remain. Peptide scanning techniques offer a systematic framework to gain information on the functional role of individual amino acids of a peptide. Due to progress in mastering new chemical synthesis routes targeting amino acid backbone, they are currently diversified. Structure-activity relationship (SAR) analyses such as alanine- or enantioneric- scanning can now be supplemented by N-substitution, lactam cyclisation- or aza-amino scanning procedures addressing not only SAR considerations but also the peptide pharmacological properties. Areas covered: This review highlights the different scanning techniques currently available and illustrates how they can impact drug discovery. Expert opinion: Progress in peptide scanning techniques opens new perspectives for peptide drug development. It comes with the promise of a paradigm change in peptide drug design in which peptide drugs will be closer to the parent peptides. However, scanning still remains assimilable to a trial and error strategy that could benefit from being combined with specific in silico approaches that start reaching maturity.
[Poster] Motion detection based ghosted views for occlusion handling in augmented reality

This work presents an improvement to the scene analysis pipeline of a visualization technique called Ghosting. Computer vision and image processing techniques are used to extract natural features, from each video frame. These features will guide the assignment of transparency to pixels, in order to give the ghosting effect, while blending the virtual object into the real scene. Video sequences were obtained from traditional RGB cameras. The main contribution of this work is the inclusion of a motion detection technique to the scene feature analysis step. This procedure leads to a better perception of the augmented scene because the proper ghosting effect is achieved when a moving natural salient object, that catches users attention, passes in front of an augmented one.
Daily mapping of Landsat-like LAI and correlation to grape yield

Wine grape quality and quantity are affected by vine growing conditions during some critical growing stages. In this paper, MODIS and Landsat were used to map daily LAI in two Grape Remote sensing Atmospheric Profiling and Evapotranspiration eXperiment (GRAPEX) experimental fields near Lodi, California in 2013. A data fusion approach was applied to map daily LAI at 30 m spatial resolution. The LAI data from two fields were validated using insitu measurements. Cumulative LAI from two fields were compared to the 2013 grape yields. High correlations were found between yield and cumulative LAI. The within-season yield predictability was examined using daily LAI maps. Results show that the grape yields were highly correlated with the cumulative LAI after the month of June. This suggests that grape yields are predictable using remotely sensed data 2-3 months prior to harvest under normal conditions.
Image-Based 3D Human Pose Recovery with Locality Sensitive Sparse Retrieval

Image-based 3D human pose recovery is usually conducted by retrieving relevant poses with image features. However, it suffers from high dimensionality of image features and low efficiency of retrieving process. In this paper, we propose a novel approach to recover 3D human poses from silhouettes. This approach improves traditional methods by adopting locality sensitive sparse coding in the retrieving process. It incorporates a local similarity preserving term into the objective of sparse coding, which groups similar silhouettes to alleviate the instability of sparse codes. The experimental results demonstrate the effectiveness of the proposed method.
Understanding the Behavior of Workshop Facilitators in Systems Analysis and Design Projects: Developing Theory from Process Modeling Projects

Organizational and technological systems analysis and design practices such as process modeling have received much attention in recent years. However, while knowledge about related artifacts such as models, tools, or grammars has substantially matured, little is known about the actual tasks and interaction activities that are conducted as part of analysis and design acts. In particular, key role of the facilitator has not been researched extensively to date. In this paper, we propose a new conceptual framework that can be used to examine facilitation behaviors in process modeling projects. The framework distinguishes four behavioral styles in facilitation (the driving engineer, the driving artist, the catalyzing engineer, and the catalyzing artist) that a facilitator can adopt. To distinguish between the four styles, we provide a set of ten behavioral anchors that underpin facilitation behaviors. We also report on a preliminary empirical exploration of our framework through interviews with experienced analysts in six modeling cases. Our research provides a conceptual foundation for an emerging theory for describing and explaining different behaviors associated with process modeling facilitation, provides first preliminary empirical results about facilitation in modeling projects, and provides a fertile basis for examining facilitation in other conceptual modeling activities.
Species-specific oligodeoxynucleotide probes for the identification of periodontal bacteria

Oligodeoxynucleotide probes were developed for identification of the periodontal bacteria Actinobacillus actinomycetemcomitans, Bacteroides gingivalis, B. intermedius types I and II, B. forsythus, Eikenella corrodens, Fusobacterium nucleatum, Haemophilus aphrophilus, Streptococcus intermedius, and Wolinella recta. Probes were designed by sequencing the 16S rRNA for each bacterium, identifying hypervariable regions, and chemically synthesizing species-specific probes. These probes were specific when tested against a panel of nucleic acids from closely related bacteria.