Miracle-dz/UniFAR-FTUs huggingface dataset:
Tandem mass spectrometry of very large molecules: serum albumin sequence information from multiply charged ions formed by electrospray ionization.

Serum albumin proteins, Mr approximately 66 kDa, from 10 different species (bovine, human, rat, horse, sheep, goat, rabbit, dog, porcine, and guinea pig) have been studied by electrospray ionization mass spectrometry (ESI-MS) and tandem MS using a triple-quadrupole instrument. The effectiveness of collisional activation for the multiply charged albumin ions greatly exceeds that for singly charged ions, allowing an extension by a factor of at least 20 to the molecular mass range for obtaining sequence-specific product ions by tandem MS. Efficient dissociation is largely attributed to "preheating" in the interface Coulombic instability and the large number of collisions. Increasing the electric field in the intermediate pressure region, between the nozzle-skimmer elements of the atmospheric pressure/vacuum interface, allows fragmentation of the multiply protonated (to 96+) molecules produced by ESI. The most abundant dissociation product ions assigned have a low charge state (2+ to 5+) and are attributed to "bn" mode species from cleavage of the -CO-N- peptide backbone bonds. Particularly abundant dissociation products originate from regions near residues n = 20-25 from the NH2 terminus for parent ions of moderate charge (approximately 50+). Collisionally activated dissociation (CAD) mass spectra from porcine serum albumin, in contrast to the other albumins, also gave prominent singly charged "yn" fragments formed from cleavages near the COOH terminus. Tandem mass spectrometry (MS/MS) of the multiply charged molecular ions, and of fragment species produced by dissociation in the interface (i.e., effective MS/MS/MS), produced similar "bn" species and served to confirm spectral assignments. We also show that ESI mass spectra allow a qualitative assessment of protein microheterogeneity and, in some cases, resolution of major contributions. The physical and analytical implications of the results are discussed, including the identification of possible errors in previously published sequences.
Primary duct closure versus T-tube drainage following exploration of the common bile duct.

T-tube drainage of the common bile duct (CBD) following duct exploration has become standard surgical practice. This randomized prospective study has compared primary closure versus T-tube drainage of the CBD following exploration for calculous disease. Thirty-seven patients underwent primary closure and 26 underwent closure over T-tube. Both groups were comparable in terms of age, indications for surgery, associated illnesses, pre-operative bilirubin, amylase and white cell count. Forty-three per cent of operations were performed by a consultant in the primary closure group and 65% in the T-tube group. There was no significant difference in the duration of operation, incidence of wound infection, surgical or other complications following operation between the two groups. However, the postoperative stay was significantly prolonged in the T-tube group, to a median of 11 days, compared to 8 days in the primary closure group (P = 0.0001). This prolongation in stay was unrelated to whether admission was as an emergency or elective. T-tube drainage of the bile continued for a median of 7 days postoperative, whereas the bile drained via a wound drain in only 13 (35%) of the primary closure group, for a median of 5 days in these 13 patients. Long-term follow up was achieved in 48 patients, by a questionnaire sent at a median of 2.8 years following operation. Abdominal pains following recovery from the operation were experienced by 18% of the primary closure group and 20% of the T-tube group. No patient developed jaundice or pancreatitis, nor needed further biliary surgery following operation. (ABSTRACT TRUNCATED AT 250 WORDS)
Full envelope dynamics modeling and simulation for tail-sitter hybrid UAVs

This paper presents a comprehensive modeling approach for tail-sitter hybrid UAVs featured by vertical take-off and landing (VTOL) and cruise flight capabilities. The modeling approach includes all essential components, such as full angle of attack envelope wing and fuselage aerodynamics, sideslip wind effect and actuator dynamics. A unified formulation comprising all model components is derived to constitute the core of our simulation environment. Simulation results show that our approach is effective to predict flight dynamics and can serve as the testbed for real implementations.
Cascade of convolutional neural networks for lung texture classification: overcoming ontological overlapping

The infiltrative lung diseases are a class of irreversible, non-neoplastic lung pathologies requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. Traditionally, such classification relies on a two-dimensional analysis of axial CT images. This paper proposes a cascade of the existing CNN based CAD system, specifically tuned-up. The advantage of using a deep learning approach is a better regularization of the classification output. In a preliminary evaluation, the combined approach was tested on a 13 patient database of various lung pathologies, showing an increase of 10% in True Positive Rate (TPR) with respect to the best suited state of the art CNN for this task.
Key Performance Indicator for Security Measurement at Airports

Airport Management nowadays is based on scattered information. The flow of such important information as an unattended piece of luggage from security officers to airline personnel is tenacious. A collaborative airport management culture can speed up the flow provided that appropriate data are available. We introduce the notion of a Level of Security comprising of a number, which sums all security facts to make the overall security situation easily accessible, and a management structure. With the help of this notion, decisions handling security situations are not only based on intuition and experience, but also on an indicator, which mines all internal and external sources. Determining the Level of Security involves opinions and is subjective. With the help of Fuzzy Logic, such subjective arguments can be addressed in a systematic fashion.
Putting Entrepreneurship into Marketing: The Processes of Entrepreneurial Marketing

This paper considers how marketing can be made more appropriate in entrepreneurial contexts by proposing a conceptual model of the processes of marketing as undertaken by entrepreneurs. Although marketing is a key factor in the survival and development of business ventures, a number of entrepreneurial characteristics seem to be at variance with marketing according to the textbook. These include over‐reliance on a restricted customer base, limited marketing expertise, and variable, unplanned effort. However, entrepreneurs and small business owners interpret marketing in ways that do not conform to standard textbook theory and practise. An examination of four key marketing concepts indicates ways in which entrepreneurial marketing differs from traditional marketing theory. Entrepreneurs tend to be “innovation‐oriented”, driven by new ideas and intuitive market feel, rather than customer oriented, or driven by rigorous assessment of market needs. They target markets through “bottom‐up” self‐selection and recommendations of customers and other influence groups, rather than relying on “top‐down” segmentation, targeting and positioning processes. They prefer interactive marketing methods to the traditional mix of the four or seven “P’s”. They gather information through informal networking rather than formalised intelligence systems. These processes play to entrepreneurial strengths and represent marketing that is more appropriate in entrepreneurial contexts, rather than marketing which is second best due to resource limitations.
Scaffolding Health Information Infrastructure's Generativity by Scaffolded Gateways: The Case of Vietnam

Standards and gateways are important components that play critical roles in information infrastructure (e‐infrastructure) evolution. Surprisingly, little research has been conducted into this area. To fill that gap, we undertook a longitudinal action research study in the health care sector in Vietnam in the period between 2012 and 2015. The empirical work involved designing or cultivating, reconfiguring, (re)assembling multiple socio‐technical components and transforming them into a larger health information infrastructure. To understand how gateways performed in our cases, we employed a concept namely “scaffolded gateways”, which was basically a hybrid between scaffoldings and gateways. We defined it as having three properties: interconnecting, supportive, and evanescent.
DNNs for Unsupervised Extraction of Pseudo FMLLR Features Without Explicit Adaptation Data

In this paper, we propose the use of deep neural networks (DNN) as a regression model to estimate feature-space maximum likelihood linear regression (FMLLR) features from unnormalized features. During training, the pair of unnormalized features as input and corresponding FMLLR features as target are provided and the network is optimized to reduce the mean-square error between output and target FMLLR features. During test, the unnormalized features are passed through this DNN feature extractor to obtain FMLLR-like features without any supervision or first pass decode. Further, the FMLLR-like features are generated frame-by-frame, requiring no explicit adaptation data to extract the features unlike in FMLLR or ivector. Our proposed approach is therefore suitable for scenarios where there is little adaptation data. The proposed approach provides sizable improvements over basis-FMLLR and conventional FMLLR when normalization is done at utterance level on TIMIT and Switchboard-33hour data sets.
Modeling and scenario simulation for decision support in management of requirements activities in software projects

There are many tools and techniques readily available to support the work in requirements activities of software development processes. As a consequence, the high frequency of errors still occurring in requirements activities suggests that the misunderstanding of the relationships among key decisions is the probable reason for this. The present work presents a system dynamics model constructed to make it possible for users to better understand the relations among key decision variables in requirements activities. The model was parameterized with data taken from previous studies and from a software development company so as to run two sets of simulations with three scenarios each. Optimistic, baseline and pessimistic scenarios are created on the basis of different assumptions regarding risk factors related to requirements volatility and people turnover. We used our simulation results to foresee the effects of these risk factors on the quality and cost of work in requirements activities. Up-to-date results from the software engineering literature strongly support the simulation outcomes obtained in our research. Copyright © 2010 John Wiley & Sons, Ltd.
NELS - Never-Ending Learner of Sounds

Sounds are essential to how humans perceive and interact with the world and are captured in recordings and shared on the Internet on a minute-by-minute basis. These recordings, which are predominantly videos, constitute the largest archive of sounds we know. However, most of these recordings have undescribed content making necessary methods for automatic sound analysis, indexing and retrieval. These methods have to address multiple challenges, such as the relation between sounds and language, numerous and diverse sound classes, and large-scale evaluation. We propose a system that continuously learns from the web relations between sounds and language, improves sound recognition models over time and evaluates its learning competency in the large-scale without references. We introduce the Never-Ending Learner of Sounds (NELS), a project for continuously learning of sounds and their associated knowledge, available on line in nels.cs. cmu.edu
Lifetime multiple response optimization of metal extrusion die

The aim of this paper is to optimize the lifetime of dies for the multiple response in metal extrusion process. The main objective of the multiple response optimization is to improve the quality of a product or process by minimizing the effects of variation without eliminating the causes. Numerical simulations with ABAQUS software obtain the results of the tests.
Interactive Video Annotation by Multi-Concept Multi-Modality Active Learning

Active learning has been demonstrated to be an effective approach to reducing human labeling effort in multimedia annotation tasks. However, most of the existing active learning methods for video annotation are studied in a relatively simple context where concepts are sequentially annotated with fixed effort and only a single modality is applied. However, we usually have to deal with multiple modalities, and sequentially annotating concepts without preference cannot suitably assign annotation effort. To address these two issues, in this paper we propose a multi-concept multi-modality active learning method for video annotation in which multiple concepts and multiple modalities can be simultaneously taken into consideration. In each round of active learning, this method selects the concept that is expected to get the highest performance gain and a batch of suitable samples to be annotated for this concept. Then, a graph-based semi-supervised learning is conducted on each modality for the selected concept. The proposed method is able to sufficiently explore the human effort by considering both the learnabilities of different concepts and the potentials of different modalities. Experimental results on TRECVID 2005 benchmark have demonstrated its effectiveness and efficiency.
Performance comparison of real-time single-channel speech dereverberation algorithms

This paper investigates four single-channel speech dereverberation algorithms, i.e., two unsupervised approaches based on (i) spectral enhancement and (ii) linear prediction, as well as two supervised approaches relying on machine learning which incorporate deep neural networks to predict either (iii) the magnitude spectrogram or (iv) the ideal ratio mask. The relative merits of the four algorithms in terms of several objective measures, automatic speech recognition performance, robustness against noise, variations between simulated and recorded reverberant speech, computation time and latency are discussed. Experimental results show that all four algorithms are capable of providing benefits in reverberant environments even with moderate background noises. In addition, low complexity and latency indicate their potential for real-time applications.
A Comparative Study of Clinical and Radiologic Outcomes of Unstable Colles Type Distal Radius Fractures in Patients Older Than 70 Years: Nonoperative Treatment Versus Volar Locking Plating

Objectives: To compare final functional and radiographic outcomes of closed reduction and casting (CAST) with open reduction and internal fixation (ORIF) with palmar locking plate for unstable Colles type distal radius fractures (DRFs) in low-demand patients older than 70 years. Design: Retrospective, clinical study. Setting: Level 1 university trauma center. Patients: Over a mean period of 4 years and 7 months, 130 consecutive patients older than 70 years were treated for an unstable dorsally displaced DRF of which 114 or 87% were followed for 1 year or longer. Intervention: ORIF (n = 53) using volar locking plate or closed reduction and casting (n = 61). Main Outcome Measurements: Objective and subjective functional results (active range of motion; grip strength; disabilities of the arm, shoulder and hand (DASH) score; patient-rated wrist evaluation (PRWE) score; visual analog scale; and Green and O'Brien score) and radiographic assessment (dorsal tilt, radial inclination, radial shortening, fracture union, and posttraumatic arthritis) were assessed. Results: At final follow-up, there was no significant difference between the 2 groups for mean ranges of motion, grip strength, DASH score, PRWE score, and Green and O'Brien score. Pain level was significantly less for the patients in the CAST group. An obvious clinical deformity was present in 77% of cast group and none in the ORIF group. At final follow-up, in the ORIF group, there was a mean loss of dorsal tilt of 1.3 degrees, radial inclination of 0.3 degrees, and radial length of 0.5 mm compared with the postoperative measurements. No primary acceptable reduction was achieved in 44% of the CAST group. At final follow-up, in the CAST group, dorsal tilt, radial inclination, and radial shortening averaged −24.4 ± 12 degrees, 19.2 ± 6.5 degrees, and +3.9 ± 2.7 mm, respectively. Malunion occurred in 89% primarily reduced fractures. Dorsal tilt, radial inclination, and radial shortening were significantly better in the ORIF group. Conclusions: Radiographic results (dorsal tilt, radial inclination, and radial shortening) after unstable dorsally displaced DRFs are significantly better in patients treated by ORIF using a volar fixed-angle plate rather than those treated by cast immobilization (P < 0.05). At a mean follow-up time of 4 years and 7 months, the clinical outcomes of active range of motion, the PRWE, DASH, and Green and O'Brien scores do not differ between the 2 methods of treatment. The pain level was significantly less in the CAST group (P < 0.05), and this group experienced no complications. There was no difference between the subjective and functional outcomes for the surgical and the nonsurgical treatments in a cohort of patients older than 70 years. Unsatisfactory radiographic outcome in older patients does not necessarily translate into unsatisfactory functional outcome. Nonoperative treatment may be the preferred method of treatment in this age group.
An Exploratory Study of Data Quality and Participation in a Games-for-Science Game Community

In this paper we explore what predicts data quality and participation by human subjects in an online, games-for-science community. The advent of games for science, citizen science, and online laboratories represent a new world of possibilities for conducting scientific research with human subjects. However, many questions remain about the quality of participation across individual games. In this paper, we use data on user behavior from a unique dataset of 40,000 game sessions across 14 studies to explore what factors predict game completion, consent, and data quality among volunteer participants on a single platform called Volunteer Science.
Worldline approach to helicity flip in plane waves

We apply worldline methods to the study of vacuum polarization effects in plane wave backgrounds, in both scalar and spinor QED. We calculate helicity-flip probabilities to one loop order and treated exactly in the background field, and provide a toolkit of methods for use in investigations of higher-order processes. We also discuss the connections between the worldline, S-matrix, and lightfront approaches to vacuum polarization effects.
Public assistance receipt among immigrants and natives: How the unit of analysis affects research findings

Differences between immigrant and native households in rates of welfare receipt depend on nativity differences in individual-level rates of receipt, in household size, in mean number of recipients in receiving households, and in household nativity composition. We present algebraic derivations of these relationships and use data from the 1990 and 1991 panels of the Survey of Income and Program Participation to examine empirically the extent to which levels of welfare receipt for immigrants and natives are sensitive to the use of household-, family-, or individual-level units of analysis or presentation. The findings show that nativity differences are statistically significant only at the level of larger units. The results also indicate that if immigrants and natives had identical living arrangements, immigrants’ household-level receipt of Supplemental Security Income would significantly exceed natives’ receipt even more than it actually does, but the nativity difference in receipt of Aid to Families with Dependent Children (AFDC) would reverse directions. Moreover, the level of AFDC receipt of immigrant households falls significantly below that of native households when native-born children living in households headed by immigrants are treated as if they were foreign born.
Preface: Special section on the 2nd International Conference on Nonlinear Programming with Applications

The Second International Conference on Nonlinear Programming with Applications was held during 7–9 April 2009 in Beijing, China. The conference was chaired by Shouyang Wang, Yifan Xu, Xinmin Yang, and Xiaoqi Yang, and was supported by the Chinese Academy of Mathematics and Systems Science, Chongqing Normal University, Fudan University, the Hong Kong Polytechnic University, and the National Natural Science Foundation of China. It consisted of 3 plenary lectures, 21 invited lectures, and 80 contributed talks. This special issue contains five papers resulting from the conference. All have been through rigorous refereeing procedures, as set by Optimization Methods and Software. We wish to take this opportunity to express our gratitude to the Editor-in-Chief, Professor Oleg Burdakov, for his kind help in editing this special issue. We are also grateful to all the speakers and participants of the conference and the supporting staff of the Chinese Academy of Mathematics and Systems Science for their contribution to its success. Finally, we are in debt to the referees of all submissions to this issue for their careful and insightful reviews and suggestions.
Cell cycle deregulation and mosaic loss of Ext1 drive peripheral chondrosarcomagenesis in the mouse and reveal an intrinsic cilia deficiency

Peripheral chondrosarcoma (PCS) develops as malignant transformation of an osteochondroma, a benign cartilaginous outgrowth at the bone surface. Its invasive, lobular growth despite low‐grade histology suggests a loss of chondrocyte polarity. The known genetics of osteochondromagenesis include mosaic loss of EXT1 or EXT2 in both hereditary and non‐hereditary cases. The most frequent genetic aberrations in human PCS also include disruptions of CDKN2A or TP53. In order to test the sufficiency of either of these to drive progression of an osteochondroma to PCS, we added conditional loss of Trp53 or Ink4a/Arf in an Ext1‐driven mouse model of osteochondromagenesis. Each additional tumour suppressor silencing efficiently drove the development of growths that mimic human PCS. As in humans, lobules developed from both Ext1‐null and Ext1‐functional clones within osteochondromas. Assessment of their orientation revealed an absence of primary cilia in the majority of mouse PCS chondrocytes, which was corroborated in human PCSs. Loss of primary cilia may be responsible for the lost polarity phenotype ascribed to PCS. Cilia deficiency blocks proliferation in physeal chondrocytes, but cell cycle deregulation is sufficient to rescue chondrocyte proliferation following deciliation. This provides a basis of selective pressure for the frequent cell‐cycle regulator silencing observed in peripheral chondrosarcomagenesis. Mosaic loss of Ext1 combined with loss of cell cycle regulators promotes peripheral chondrosarcomagenesis in the mouse and reveals deficient ciliogenesis in both the model and the human disease, explaining biological behaviour including lobular and invasive growth. Copyright © 2015 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.