Miracle-dz/UniFAR-FTUs huggingface dataset:
Localization of anticoagulantly active heparan sulfate proteoglycans in vascular endothelium: antithrombin binding on cultured endothelial cells and perfused rat aorta

We have studied the interaction of 125I-antithrombin (125I-AT) with microvascular endothelial cells (RFPEC) to localize the cellular site of anticoagulantly active heparan sulfate proteoglycans (HSPG). The radiolabeled protease inhibitor bound specifically to the above HSPG with a Kd of approximately 50 nM. Confluent monolayer RFPEC cultures exhibited a linear increase in the amount of AT bound per cell for up to 16 d, whereas suspension RFPEC cultures possessed a constant number of protease inhibitor binding sites per cell for up to 5 d. These results suggest that monolayer RFPEC cultures secrete anticoagulantly active HSPG, which then accumulate in the extracellular matrix. This hypothesis was confirmed by quantitative light and EM level autoradiography which demonstrated that the AT binding sites are predominantly located in the extracellular matrix with only small quantities of protease inhibitor complexed to the cell surface. We have also pinpointed the in vivo position of anticoagulantly active HSPG within the blood vessel wall. Rat aortas were perfused, in situ, with 125I-AT, and bound labeled protease inhibitor was localized by light and EM autoradiography. The anticoagulantly active HSPG were concentrated immediately beneath the aortic and vasa vasorum endothelium with only a very small extent of labeling noted on the luminal surface of the endothelial cells. Based upon the above data, we propose a model whereby luminal and abluminal anticoagulantly active HSPG regulate coagulation mechanism activity.
A Framework for Inferring Causality from Multi-Relational Observational Data using Conditional Independence

The study of causality or causal inference - how much a given treatment causally affects a given outcome in a population - goes way beyond correlation or association analysis of variables, and is critical in making sound data driven decisions and policies in a multitude of applications. The gold standard in causal inference is performing "controlled experiments", which often is not possible due to logistical or ethical reasons. As an alternative, inferring causality on "observational data" based on the "Neyman-Rubin potential outcome model" has been extensively used in statistics, economics, and social sciences over several decades. In this paper, we present a formal framework for sound causal analysis on observational datasets that are given as multiple relations and where the population under study is obtained by joining these base relations. We study a crucial condition for inferring causality from observational data, called the "strong ignorability assumption" (the treatment and outcome variables should be independent in the joined relation given the observed covariates), using known conditional independences that hold in the base relations. We also discuss how the structure of the conditional independences in base relations given as graphical models help infer new conditional independences in the joined relation. The proposed framework combines concepts from databases, statistics, and graphical models, and aims to initiate new research directions spanning these fields to facilitate powerful data-driven decisions in today's big data world.
Chronic immune sensory polyradiculopathy

Background: Chronic inflammatory neuropathies can present with a sensory ataxia due to involvement of dorsal root ganglia (DRG) or sensory nerves. Selective inflammatory involvement of sensory nerve roots proximal to the DRG has been postulated. Methods: The authors identified 15 patients with a sensory syndrome and normal nerve conduction studies. Sensory nerve root involvement was suggested by either somatosensory evoked potential (SSEP) or imaging abnormalities. CNS disease was excluded. Results: All patients had gait ataxia, large fiber sensory loss, and paresthesias, and nine had frequent falls. The disease course was chronic and progressive (median duration 5 years, range 3 months to 18 years). Sural sensory nerve action potential amplitudes were preserved and SSEP abnormalities were consistent with sensory nerve root involvement. Five patients had enlargement of lumbar nerve roots on MRI with enhancement in three. The CSF protein was elevated in 13 of 14 patients tested. Three patients had lumbar sensory rootlet biopsies that showed thickened rootlets, decreased density of large myelinated fibers, segmental demyelination, onion-bulb formation, and endoneurial inflammation. Six patients who required aids to walk were treated with immune modulating therapy and all had marked improvement with four returning to normal ambulation. Conclusion: Based on the described clinical features, normal nerve conduction studies, characteristic somatosensory evoked potential (SSEP) abnormality, enlarged nerve roots, elevated CSF protein, and inflammatory hypertrophic changes of sensory nerve rootlet tissue, we suggest the term chronic immune sensory polyradiculopathy (CISP) for this syndrome. This condition preferentially affects large myelinated fibers of the posterior roots, may respond favorably to treatment, and may be a restricted form of chronic inflammatory demyelinating polyradiculoneuropathy.
Consensus report: faecal microbiota transfer – clinical applications and procedures

Faecal microbiota transplantation or transfer (FMT) aims at replacing or reinforcing the gut microbiota of a patient with the microbiota from a healthy donor. Not many controlled or randomised studies have been published evaluating the use of FMT for other diseases than Clostridium difficile infection, making it difficult for clinicians to decide on a suitable indication.
The Prevalence of Metabolic Syndrome Using Three Different Diagnostic Criteria among Low Earning Nomadic Kazakhs in the Far Northwest of China: New Cut-Off Points of Waist Circumference to Diagnose MetS and Its Implications

Background Although the epidemic of metabolic syndrome (MetS) has aroused wide public concern, most studies on MetS tend to examine urban and high income settings, and few studies cover nomadic areas and low earning populations. This research aims to investigate the prevalence of MetS and explore the cut-off point of waist circumference in a nomadic minority typical of low income populations in the remote northwest region of China. Methods A cross-sectional study was performed in a representative sample of 3900 Kazakh adults aged 18–84 years from 2009–2010. Three widely used criteria (ATP III\IDF\JIS) were employed to estimate the prevalence of MetS in Kazakhs to compare them with other populations. Receiver operator characteristic (ROC) curve analysis was used to explore the optimal cut-off values of waist circumference. Results The age-adjusted prevalence of MetS was 13.8%, 20.9%, and 24.8% based on the ATP III, IDF, and JIS criteria, respectively. The prevalence of MetS was higher in women and increased with age. Except for reduced HDL-cholesterol, the risk of other components of MetS increased with waist circumference enlargement. The cut-off point of waist circumference in screening at least two other components of MetS was 88 cm in men (Sensitivity = 61.1%, Specificity = 62.1%, ROC Curve Distance = 0.54) and 83 cm in women (Sensitivity = 60.0%, Specificity = 59.6%, ROC Curve Distance = 0.57). Conclusion The prevalence of MetS in Kazakhs is higher than the national level of China and falls in between the Euro-American and Asia levels, as their cut-off points of waist circumference differ from that recommended for Chinese. We suggest a cost-effective strategy to screen for MetS and prevent cardiovascular disease using new cut-off points of waist circumference in low earning nomadic Kazakhs.
An experiment of a 3D real-time robust visual odometry for intelligent vehicles

Vision systems are nowadays very promising for many on-board vehicles perception functionalities, like obstacles detection/recognition and ego-localization. In this paper, we present a 3D visual odometric method that uses a stereo-vision system to estimate the 3D ego-motion of a vehicle in outdoor road conditions. In order to run in real-time, the studied technique is sparse meaning that it makes use of feature points that are tracked during several frames. A robust scheme is also employed to reject outliers that are detected on moving objects of the environment. Moreover, efforts have been spent on the realtime implementation of the method. In this article, we describe the key stages of the method: features extraction and tracking, quadrifocal constraints, optimization solver and robustification. Real experiments are reported to compare the performance of this approach with GPS data and 2D-wheel-based odometry.
Coagulase‐negative Staphylococcus culture in chronic rhinosinusitis

Coagulase‐negative Staphylococcus (CoNS) is commonly isolated from patients with chronic rhinosinusitis (CRS). However, the role of CoNS in CRS remains controversial. We aimed to determine the association between positive CoNS culture at functional endoscopic sinus surgery (FESS) and CRS severity.
Interaction of sleep quality and sleep duration on impaired fasting glucose: a population-based cross-sectional survey in China

Objectives To explore the interactions of sleep quality and sleep duration and their effects on impaired fasting glucose (IFG) in Chinese adults. Design Cross-sectional survey. Setting Community-based investigation in Xuzhou, China. Participants 15 145 Chinese men and women aged 18–75 years old who fulfilled the inclusion criteria. Primary and secondary outcome measures The Pittsburgh Sleep Quality Index was used to produce sleep quality categories of good, common and poor. Fasting blood glucose levels were assessed for IFG. Sleep duration was measured by average hours of sleep per night, with categories of <6, 6–8 and >8 h. The products of sleep and family history of diabetes, obesity and age were added to the logistic regression model to evaluate the addictive interaction and relative excess risk of interaction (RERI) on IFG. The attributable proportion (AP) of the interaction and the synergy index (S) were applied to evaluate the additive interaction of two factors. Bootstrap measures were used to calculate 95% CI of RERI, AP and S. Results The prevalence of IFG was greatest in those with poor sleep quality and short sleep duration (OR 6.37, 95% CI 4.66 to 8.67; p<0.001) compared with those who had good sleep quality and 6–8 h sleep duration, after adjusting for confounders. After adjusting for potential confounders RERI, AP and S values (and their 95% CI) were 1.69 (0.31 to 3.76), 0.42 (0.15 to 0.61) and 2.85 (2.14 to 3.92), respectively, for the interaction between poor sleep quality and short sleep duration, and 0.78 (0.12 to 1.43), 0.61 (0.26 to 0.87) and −65 (−0.94 to −0.27) for the interaction between good sleep quality and long sleep duration. Conclusions The results suggest that there are additive interactions between poor sleep quality and short sleep duration.
The consequences of different printing chamber temperatures in extrusion-based additive manufacturing

Materials that are processed by means of extrusion-based additive manufacturing are exposed to complex temperature conditions during manufacturing, resulting from quick temperature alterations due to the moving nozzle. Consequently, a rather inhomogeneous temperature distribution is present in the printing chamber, which can intensify issues such as high internal stresses, unintentional crystal growth and undesired part deformations. This study aims at tackling these problems by investigating the consequences of increased printing chamber temperatures on 3D-printed polypropylene (PP). In-situ thermography measurements during printing revealed a drastic decrease in the temperature fluctuations as soon as parts are printed at a controlled increased chamber temperature, leading to a more homogeneous temperature distribution. As a result, internal stresses declined and the warpage of printed parts considerably decreased compared to the conventionally used surrounding room temperature. Since the maxima of the strand temperatures easily surpass 100 °C for a chamber temperature of 55 °C, the crystal modification partly changed from α-PP to β-PP, which was confirmed by thermograms and X-ray diffraction. As the mean strand temperatures during printing are in the close proximity of the temperature of the maximum crystal growth rate of PP, fewer and bigger, but more homogeneous spherulites were formed. Additionally, shish-kebab structures tended to form at high chamber temperatures due to strong process orientations. The found crystallographic changes introduced by changes in the printing chamber temperature can be employed to tailor the material properties of 3D-printed PP. The proposed strategy can act as the foundation for similar studies on other printable semi-crystalline polymers.
COLLISION IN THE COLON: CONCURRENT ADENOCARCINOMA AND DIFFUSE LARGE B-CELL LYMPHOMA IN THE SAME TUMOUR

Abstract Double malignancies in the gastrointestinal tract are unusual. Concurrent lymphoma and adenocarcinoma is a rare clinical condition. We herein report a collision tumour which first presented with a diffuse large B-cell lymphoma in the skull base and ileocecal junction area. After rituximab and chemotherapy the skull base tumour disappeared, but the ileocecal lesion remained. A biopsy revealed the presence of adenocarcinoma in the same lesion. The tumour was surgically removed. Further microscopic examination of the tumour showed it was an adenocarcinoma but residual lymphoma cell infiltration could still be observed. Serum Epstein-Barr virus (EBV) was detected at diagnosis of lymphoma and the concentration further elevated at diagnosis of adenocarcinoma. Therefore, both lymphoma and carcinoma may be EBV related. Our experience illustrated that such collision tumours are rare and difficult in diagnosis. Clinicians and pathologists should be aware of such an association in order to make a correct diagnosis and initiate proper treatment.
Empirical Distributions of Beliefs Under Imperfect Observation

Let (xn)n be a process with values in a finite set X and law P, and let yn f(xn) be a function of the process. At stage n, the conditional distribution pn P(xnx1,,xn1), element of (X), is the belief that a perfect observer, who observes the process online, holds on its realization at stage n. A statistician observing the signals y1,,yn holds a belief enP(pnx1,,xn) () on the possible predictions of the perfect observer. Given X and f, we characterize the set of limits of expected empirical distributions of the process (en) when P ranges over all possible laws of (xn)n.
Behavioral Assessment of the Type A Behavior Pattern

&NA; The present study attempted to assess systematically a set of behavioral subcomponents associated with the Type A behavior pattern. Sixty middle‐aged men underwent the structured interview (SI) and a repeated version of the SI after a four‐month interval. A high degree of interrater reliability was established for a number of behavioral components including speed and volume of speech, motoric activity, expiratory sighs, response latency, interruptions, unevenness of speech, plosive words, and potential for hostility. In general, these behaviors were stable over the four‐month interval, although they did not all distinguish Type As from Type Bs. Only four behaviors successfully discriminated Type As and Bs at both interview sessions: speed of speech, volume of speech, number of interruptions, and potential for hostility. The results are discussed in terms of how these behavioral subcomponents may contribute to increased risk of premature coronary disease.
QoS‐aware ant‐based route, wavelength and timeslot assignment algorithm for optical burst switched networks

All‐optical networks are the aspiration of bandwidth‐greedy applications providers and users such as telecom operators and scientific research centres. Because of the limitations of current network infrastructures, some optical switching paradigms have been proposed. Among these paradigms, optical burst switching (OBS) is seen as the most appropriate solution. However, OBS suffers from high burst loss ratio as a result of contention at the buffer‐less core node. According to current optical technology reviews, cost effective optical memories are yet to be cost effective. In this paper, an ant‐based route, wavelength and timeslot allocation algorithm is proposed to address high burst loss in OBS and improve the overall network performance. The solution was implemented in hierarchical time‐sliced OBS and was evaluated through computer simulation where it was compared with shortest path (SP) algorithm. Simulation results show that the proposed algorithm outperforms SP in terms of burst loss ratio and delay. Copyright © 2015 John Wiley & Sons, Ltd.
Computer‐Assisted Keyword and Document Set Discovery from Unstructured Text

The (unheralded) first step in many applications of automated text analysis involves selecting keywords to choose documents from a large text corpus for further study. Although all substantive results depend on this choice, researchers usually pick keywords in ad hoc ways that are far from optimal and usually biased. Most seem to think that keyword selection is easy, since they do Google searches every day, but we demonstrate that humans perform exceedingly poorly at this basic task. We offer a better approach, one that also can help with following conversations where participants rapidly innovate language to evade authorities, seek political advantage, or express creativity; generic web searching; eDiscovery; look-alike modeling; industry and intelligence analysis; and sentiment and topic analysis. We develop a computer-assisted (as opposed to fully automated or human-only) statistical approach that suggests keywords from available text without needing structured data as inputs. This framing poses the statistical problem in a new way, which leads to a widely applicable algorithm. Our specific approach is based on training classifiers, extracting information from (rather than correcting) their mistakes, and summarizing results with easy-to-understand Boolean search strings. We illustrate how the technique works with analyses of English texts about the Boston Marathon bombings, Chinese social media posts designed to evade censorship, and others.
The Economics of Conservation Subdivisions

The environmental benefits of less land consumption and a growing interest in addressing the negative economic and social impacts of sprawl have resulted in calls for more sensitive subdivision designs. One such design is conservation subdivisions. However, not much is known about these subdivisions, in particular about their economics. This article addresses the issue by examining price premiums, investment costs, and absorption rates for lots in conservation versus those in conventional subdivisions. The results show that lots in conservation subdivisions carry a premium, are less expensive to build, and sell more quickly than lots in conventional subdivisions. The results suggest that designs that take a holistic view of ecology, aesthetics, and sense of community can assuage concerns about higher density. However, the potential negative consequences of conservation subdivisions require further study.
The Skyline operator

We propose to extend database systems by a Skyline operation. This operation filters out a set of interesting points from a potentially large set of data points. A point is interesting if it is not dominated by any other point. For example, a hotel might be interesting for somebody traveling to Nassau if no other hotel is both cheaper and closer to the beach. We show how SSL can be extended to pose Skyline queries, present and evaluate alternative algorithms to implement the Skyline operation, and show how this operation can be combined with other database operations, e.g., join.
Modeling of Wet Stiction in Microelectromechanical Systems (MEMS)

Stiction, which is a term commonly used in micro-electromechanical systems (MEMS) to refer to adhesion, is a major failure mode in MEMS. Undesirable stiction, which results from the contact between surfaces, can severely compromise the reliability of MEMS. In this paper, a model is developed for predicting stiction between uncharged micro parts interacting in a humid environment. In this condition, for hydrophilic surfaces, the capillary and asperity deformation forces are dominant. Here, using a newly developed multiple asperity contact model, a model is developed for the capillary force between rough micro surfaces, and the new model is combined with a newly developed elastic/plastic deformation model for rough surfaces to solve for the equilibrium of the forces. This in turn yields the equilibrium distance between micro surfaces using which the apparent work of adhesion can be found. The theoretical results are compared with the available experimental data from literature. The developed model can be easily used for design purposes. If the topographic data and material constants are known, the desirable adhesion parameters can be quickly found from the model.
Industrial process identification and control design: step-test and relay-experiment-based methods [book review]

The main goal of this monograph is to deal with both problems in an integral way: given a process to be controlled, how should a simple model be identified and used to design a controller to fulfill some requirements? This book is neither a comprehensive handbook of process control design [1] nor a treatise on system identification and parameter estimation [2] but rather provides the tools to reach the final objective of designing a control system for an industrial process. The book has two parts: Part I: Process Identification (Chapters 1¿6) and Part II: Control System Design (Chapters 7¿12). One of the main difficulties in handling experimental data is the presence of measurement noise. Generally, experimental data are filtered and integrated to get a smoother set of data. Different identification algorithms are used according to the selected model structure, and uidelines to choose the involved parameters are suggested and discussed. A number of examples illustrate the practical use of these algorithms. In the second part of the book, these reduced-order models are used to design a variety of control structures, including single loop control, two-degree-of-freedom (2DOF) controllers, cascade control, multiloop control, decoupling control, and batch control. The main issues considered in the design are disturbances, noise rejection, robustness, and setpoint tracking, with special attention paid to the control of multivariable time-delayed plants. The content of the book is well structured, and each chapter deals with a specific topic. The scope and objective of process identification, the excitation signals commonly used for open-loop and closed-loop identification tests, and the model fitting criteria are summarized in Chapter 1.