Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk aversion and optimal satellite systems

Long-term, multiple-payload satellites in Earth orbit can be designed either as consolidated or distributed satellite systems. A consolidated satellite architecture aggregates multiple payload capabilities onto individual large satellites. A distributed (or `disaggregated') satellite architecture allocates payloads across multiple smaller, heterogeneous satellites. Each system type has certain advantages and disadvantages. A consolidated system often has highly-reliable individual satellites and may offer a lower initial deployment cost. The advantages of a distributed system include the ability to replace a failed unit, or to insert a new technology, more quickly and at a lower cost. Such a system may also be less vulnerable to adversarial threats. We model the value of a satellite program as that of the data that it provides, and use this approach to find optimal sequential decisions to choose and operate the satellite system. The model includes a failure risk analysis to assess and compare the benefits of different system configurations. In sum, we provide a model that enables value-based comparison of entire satellite architectures, where each technical and operational characteristic is optimally exploited. The results of this research indicate that risk-averse decision makers are likely to prefer a distributed satellite system. This work has implications for research on resilience, value, and mission analysis for future space systems.
Clusters of week‐specific maternal gestational weight gain pattern and their association with birthweight: an observational cohort study

Gestational weight gain varies widely among different populations, and an inappropriate gestational weight gain is associated with adverse pregnancy outcomes. We aimed to investigate week‐specific serial changes in gestational weight gain in an urban Chinese population to derive clusters of gestational weight gain patterns and explore the impact of gestational weight gain patterns on birthweight.
SPECT imaging of dopamine and serotonin transporters with [123I]β‐CIT: Pharmacological characterization of brain uptake in nonhuman primates

Single photon emission computed tomography (SPECT) studies of regional kinetic uptake and pharmacological specificity of [123I] methyl 3β‐ (4‐iodophenyl) tropane‐2β‐carboxylate ([123I]β‐CIT) were performed in nonhuman primates (n = 41). In control experiments, activity was concentrated in striatum and in hypothalamic/midbrain regions. Striatal uptake increased for 140–180 min and displayed stable levels thereafter. Striatal to cerebellar activity rations were 7.3 ± 0.9 (mean ± SEM) at 300 min. About 75% of striatal uptake was displaceable by injection of nonradioactive β‐CIT. Hypothalamic/midbrain activity reached maximal levels at approximately 45 min. A slow washout phase followed this peak activity. Activities in frontal, occipital, and cerebellar regions were characterized by an early peak (20–30 min), followed by rapid washout. Displacement studies demonstrated that striatal uptake was associated with dopamine (DA) transporters, as it was displaced by GBR 12909, a selective DA uptake inhibitor, but not by citalopram, a selective serotonin (5‐HT) uptake inhibitor. The inverse was true in the hypothalamic/midbrain area, suggesting that the uptake in this area was associated primarily with 5‐HT transporters. Maprotiline, a selective norepinephrine uptake inhibitor, did not affect [123I]β‐CIT uptake. In vivo site occupancy ED50 values of cocaine, 2β‐carbomethoxy‐3β‐(4‐fluorophenyl) tropane (CFT), and β‐CIT were measured in the striatum with a stepwise displacement paradigm. In vivo ED50 values correlated strongly with in vitro IC50 values for binding to DA transporters. Infusion of high dose of L‐DOPA (250 μMol/kg) failed to displace striatal [123I]β‐CIT binding, suggesting that the binding would not be affected by L‐DOPA administration in Parkinsonian patients. However, studies performed with injection of d‐amphetamine indirectly suggested that high synaptic levels of DA may compete with [123I]β‐CIT binding, These studies suggest that [123I]β‐CIT will be a useful SPECT tracer of DA and 5‐HT transporters in living human brain. © 1993 Wiley‐Liss, Inc.
Reliability of Basophil Activation Test Using CD203c Expression in Diagnosis of Pollen Allergy

Background CD203c is a basophil surface marker and its expression is rapidly up-regulated after cross-linking of high-affinity immunoglobulin E (IgE) receptor (FcepsilonR1) by an allergen. CD203c basophil activation tests have been studied for the in vitro diagnosis of several allergic conditions. However, there is limited data about its diagnostic usefulness. The optimum allergen concentrations for stimulation and allergen specific cutoff values remain unknown for a number of allergens. This study was designed to investigate the efficacy of basophil activation test via CD203c in the diagnosis of pollen allergy. Methods The CD203c basophil activation was determined in 31 allergic rhinitis patients with pollen allergy and 9 healthy nonatopic controls during the off-season. CD203c expression was evaluated using three-color staining protocol by flow cytometry. Results After an in vitro stimulation with grass pollen extract, the CD203c assay clearly discriminated pollen-allergic patients from controls (p < 0.001). A dose-dependent increase in the percentages of CD203c-activated basophils was shown in rhinitis patients with pollen allergy (p < 0.001). The sensitivity and specificity was 100% and optimal cutoff values were 14.05 and 10.05% with 45.1 and 4.5 μg/mL Phl p 5 stimulation, respectively. Although the specificity was also 100%, the sensitivity was 93 and 87% and the cutoff values were 5.40 and 5.35% with 4.5 x 10–4 and 4.5 x 10–5 micrograms/mL Phl p 5 stimulation, respectively. Conclusion The CD203c basophil activation test seems to be a reliable tool in the diagnosis of grass pollen allergy. It could be used when conventional diagnostic tests fail or can not be performed.
A qualitative study of rural primary care clinician views on remote monitoring technologies.

PURPOSE Remote monitoring technologies (RMTs) may improve the quality of care, reduce access barriers, and help control medical costs. Despite the role of primary care clinicians as potential key users of RMTs, few studies explore their views. This study explores rural primary care clinician interest and the resources necessary to incorporate RMTs into routine practice. METHODS We conducted 15 in-depth interviews with rural primary care clinician members of the Oregon Rural Practice-based Research Network (ORPRN) from November 2011 to April 2012. Our multidisciplinary team used thematic analysis to identify emergent themes and a cross-case comparative analysis to explore variation by participant and practice characteristics. RESULTS Clinicians expressed interest in RMTs most relevant to their clinical practice, such as supporting chronic disease management, noting benefits to patients of all ages. They expressed concern about the quantity of data, patient motivation to utilize equipment, and potential changes to the patient-clinician encounter. Direct data transfer into the clinic's electronic health record (EHR), availability in multiple formats, and review by ancillary staff could facilitate implementation. Although participants acknowledged the potential system-level benefits of using RMTs, adoption would be difficult without payment reform. CONCLUSIONS Adoption of RMTs by rural primary care clinicians may be influenced by equipment purpose and functionality, implementation resources, and payment. Clinician and staff engagement will be critical to actualize RMT use in routine primary care.
Research on LBS privacy protection technology in mobile social networks

With the rapid development of mobile Internet and locating technology, location-based services (LBS) are widely used in mobile social networks, while the user obtained the LBS services, their location information is also provided to the service provider, this information may be obtained by the attacker and the user's other personal privacy may be inferred, threatening to the user's personal information security. Based on the location privacy protection of LBS services, this paper analyzes the method and model of user's location privacy protection, and introduces some location privacy protection technologies and trajectory privacy protection technologies in LBS.
Miniaturized wireless ECG-monitor for real-time detection of epileptic seizures

Recent advances in miniaturization of ultra-low power components allow for more intelligent wearable health monitors. Such systems may be used in a wide range of application areas. Here, the development and evaluation of a wireless wearable electrocardiogram (ECG) monitor to detect epileptic seizures from changes in the cardiac rhythm is described. The ECG is measured using an ultra-low-power circuit for bio-potential acquisition. The ECG data is continuously analyzed by embedded algorithms: a robust beat-detection algorithm combined with a real-time heart beat-based epileptic seizure detector. Each detected seizure candidate triggers its transmission to a receiving radio-station. At the same time, the detected events and the raw ECG data are stored on an embedded memory card from which they can be wirelessly downloaded for off-line analysis. The performance of the system in terms of power-consumption, robustness of the radio-link and comfort of use is reported. In its current implementation, the proposed ECG-monitor prototype has a size of 52x36x15mm3, and an autonomy of one day. Wireless, miniaturized and comfortable, this prototype opens new perspectives for continuous and ambulatory health monitoring.
Image Segmentation using Discontinuity-Based Approach

Image segmentation is the process by which we segment a given image into several parts so that we can further analyzed each of these parts present in the image. We can extract some information by analyzing them and this information is useful for high-level machine vision application. There are numerous techniques of image segmentation available in literature. In this paper, we will analyze the discontinuity-based approach for image segmentation. The discontinuity-based segmentation can be classified into three approaches: point detection, line detection, and edge detection. In this paper, we will implement and analyses the result of these various approaches in MATLAB using Image Processing Toolbox (IPT). We will also implement the different edge operators such as Prewitt, Roberts, LoG, Canny and the results of these operators will be shown on various images.
Statistical power when testing for genetic differentiation

A variety of statistical procedures are commonly employed when testing for genetic differentiation. In a typical situation two or more samples of individuals have been genotyped at several gene loci by molecular or biochemical means, and in a first step a statistical test for allele frequency homogeneity is performed at each locus separately, using, e.g. the contingency chi‐square test, Fisher’s exact test, or some modification thereof. In a second step the results from the separate tests are combined for evaluation of the joint null hypothesis that there is no allele frequency difference at any locus, corresponding to the important case where the samples would be regarded as drawn from the same statistical and, hence, biological population. Presently, there are two conceptually different strategies in use for testing the joint null hypothesis of no difference at any locus. One approach is based on the summation of chi‐square statistics over loci. Another method is employed by investigators applying the Bonferroni technique (adjusting the P‐value required for rejection to account for the elevated alpha errors when performing multiple tests simultaneously) to test if the heterogeneity observed at any particular locus can be regarded significant when considered separately. Under this approach the joint null hypothesis is rejected if one or more of the component single locus tests is considered significant under the Bonferroni criterion. We used computer simulations to evaluate the statistical power and realized alpha errors of these strategies when evaluating the joint hypothesis after scoring multiple loci. We find that the ‘extended’ Bonferroni approach generally is associated with low statistical power and should not be applied in the current setting. Further, and contrary to what might be expected, we find that ‘exact’ tests typically behave poorly when combined in existing procedures for joint hypothesis testing. Thus, while exact tests are generally to be preferred over approximate ones when testing each particular locus, approximate tests such as the traditional chi‐square seem preferable when addressing the joint hypothesis.
Myosin heavy chain kinase B participates in the regulation of myosin assembly into the cytoskeleton

Myosin II plays critical roles in events such as cytokinesis, chemotactic migration, and morphological changes during multicellular development. The amoeba Dictyostelium discoideum provides a simple system for the study of this contractile protein. In this system, myosin II filament assembly is regulated by myosin heavy chain (MHC) phosphorylation in the tail region of the molecule. Earlier studies identified an alpha‐kinase, MHC kinase A (MHCK A), which phosphorylates three mapped threonine residues in the myosin tail, driving myosin disassembly. Using molecular and genomic approaches, we have identified a series of related kinases in Dictyostelium. The enzyme MHCK B shares with MHCK A a domain organization that includes a highly novel catalytic domain coupled to a carboxyl‐terminal WD repeat domain. We have engineered, expressed, and purified a FLAG‐tagged version of the novel kinase. In the present study, we report detailed biochemical and cellular studies documenting that MHCK B plays a physiological role in the control of Dictyostelium myosin II assembly and disassembly during the vegetative life of Dictyostelium amoebae. The presented data supports a model of multiple related MHCKs in this system, with different regulatory mechanisms and pathways controlling each enzyme. © 2002 Wiley‐Liss, Inc.
Natural language processing and early-modern dirty data: applying IBM Languageware to the 1641 depositions

This article provides an account of the steps involved in adapting IBM's Languageware natural language processing software to a large corpus of highly non-standard 17th century documents. It examines the challenges encountered as part of this process, and outlines the approach adopted to provide a robust and reusable tool for the linguistic analysis of early modern source texts.
Familiar route retrieval for multicasting in MANETs

In the recent days, Mobile ad hoc networks (MANETs) are used extensively for applications that require mobility while routing, more importantly for emergency and military operations. Routing information to nodes without a fixed infrastructure and with dynamically changing infrastructure is one of the greatest challenges. Multicasting is a more frequent requirement for such defense operations, which adds on to the level of difficulty while routing. In order to overcome this challenge, a couple of protocols exist in the literature providing various solutions to delivering data to multiple destinations at mobility. However, these strategies are either of greater complexity or the cost is high. In this paper, we propose Familiar Route Retrieval for Multicasting (FRRM) in MANETs to use the route familiarity of nodes efficiently to construct routes to destinations. The performance of this algorithm is analyzed using the simulations in the network simulator.
Adenovirus vector-mediated gene transfer to regional lymph nodes.

Regional lymph nodes (RLNs) possess important immune functions and represent a major pathway of metastasis for solid tumors. Given these facts, the ability to transfer exogenous genes to the RLNs with the goal of manipulating the local immunological milieu would be desirable. On the basis of the hypothesis that a significant proportion of adenovirus (Ad) gene transfer vectors traffic through the lymphatics, E1-E3- Ad vectors were injected into the hind footpad of C3H/He mice and the RLNs assessed for vector trafficking and transgene expression. A low dose (10(9) particles) of an Ad vector encoding the firefly luciferase gene (Ad-CMV.Luc) resulted in luciferase expression only in the injection site and RLNs, with no detectable systemic (liver, spleen, lung) expression. At a higher dose (10(11) particles), some expression could be detected systemically in addition to the RLNs, but at levels in liver 14-fold less than in the RLNs. Transgene expression in the RLNs was transient, peaking at 1 day, decreasing markedly by 7 days. At high doses (10(11) particles), interruption of draining lymphatics decreased the amount of systemic dissemination 22-fold, suggesting that a large proportion of the vector trafficks through the lymphatics before reaching the systemic circulation. Administration of a vector encoding the jellyfish green fluorescent protein gene (AdCMV.GFP, 10(11) particles) showed that transgene expression in the RLNs was primarily in the cortical area. After footpad injection of a fluorescent-labeled Ad vector (Cy3-AdCMV.Null), fluorescent virions were visualized in the draining lymph. Regional lymph collected from animals injected in the footpad with AdCMV.Luc (10(11) particles) contained functional vector. Augmentation of local immune function in the RLNs was achieved by footpad administration of an Ad vector encoding murine IL-12, resulting in high mIL-12 and IFN-gamma levels in the regional, but not distant, nodes. These data demonstrate that expression of exogenous genes in RLNs is easily accomplished with Ad vectors, Ad vector dissemination occurs primarily via the lymphatics after footpad administration in mice, and basic immune functions in the RLNs can be manipulated by Ad-mediated gene transfer in vivo.
AMBIENTES DE APRENDIZAJE: UNA APROXIMACION CONCEPTUAL

En este articulo se aborda el problema de los ambientes de aprendizaje desde una revision bibliografica con miras a contribuir a la delimitacion conceptual del problema, sin pretender convertirse en una revision exhaustiva. No obstante que las transformaciones de la cultura contemporanea han puesto en cuestion el monopolio que ha ejercido la escuela sobre lo educativo, ella sigue siendo uno de los ambientes de aprendizaje mas importantes en las sociedades actuales, de alli que sea necesario repensar ambientes como el aula desde perspectivas diversas y complejas que no reduzcan el problema a una sola de sus dimensiones. Entre estas perspectivas se tratan los ambientes de aprendizaje desde lo ludico, lo estetico y el problema de las nuevas mediaciones tecnologicas, para senalar ejes sobre los cuales debe girar una reflexion mas profunda sobre la educacion contemporanea, si se quieren superar posturas instrumentalistas, transmisionistas y disciplinarias en las aulas escolares.
AC-TR-17-014 December 2017 Backdoor Treewidth for SAT

A strong backdoor in a CNF formula is a set of variables such that each possible instantiation of these variables moves the formula into a tractable class. The algorithmic problem of finding a strong backdoor has been the subject of intensive study, mostly within the parameterized complexity framework. Results to date focused primarily on backdoors of small size. In this paper we propose a new approach for algorithmically exploiting strong backdoors for SAT: instead of focusing on small backdoors, we focus on backdoors with certain structural properties. In particular, we consider backdoors that have a certain tree-like structure, formally captured by the notion of backdoor treewidth. First, we provide a fixed-parameter algorithm for SAT parameterized by the backdoor treewidth w.r. t. the fundamental tractable classes Horn, Anti-Horn, and 2CNF. Second, we consider the more general setting where the backdoor decomposes the instance into components belonging to different tractable classes, albeit focusing on backdoors of treewidth 1 (i.e., acyclic backdoors). We give polynomial-time algorithms for SAT and #SAT for instances that admit such an acyclic backdoor.
Running head : SCREENING FOR SLEEP APNEA 1 Screening for Sleep Apnea in the Heart Failure Population

Background: Sleep disordered breathing (SDB) occurs in over half of the estimated 5.1 million people in the U.S. diagnosed with heart failure (HF). Evidence shows that treatment of SDB in this population decreases not only morbidity and mortality rates, but the overall cost burden of the disease as well. The routine use of a sleep apnea screening protocol in the HF population can help identify patients in need of treatment. Methods: A project was conducted at an urban community heart failure clinic to evaluate provider preference of three evidence-based screening tools to be included in the implementation of a comprehensive SDB screening protocol. This project’s long-term goal was to design and implement a SDB protocol for heart failure patients treated at an urban heart failure clinic using the Health Belief Model. Results: Providers chose the Epworth Sleepiness Scale (ESS) as the screening questionnaire to be used in the final screening protocol. Conclusion: Ease of use, sensitivity within patient population, and patientfriendly format were cited as the deciding factors for provider choice of the ESS as the preferred screening tool.
Combining Lightly-Supervised Text Classification Models for Accurate Contextual Advertising

In this paper we propose a lightly-supervised framework to rapidly build text classifiers for contextual advertising. Traditionally text classification techniques require labeled training documents for each predefined class. In the scenario of contextual advertising, advertisers often want to target to a specific class of webpages most relevant to their product or service, which may not be covered by a pre-trained classifier. Moreover, the advertisers are interested in whether a webpage is “relevant” or “irrelevant”. It is time-consuming to solicit the advertisers for reliable training signals for the negative class. Therefore, it is more suitable to model the problem as a one-class classification problem, in contrast to traditional classification problems where disjoint classes are defined a priori. We first apply two state-of-the-art lightly-supervised classification models, generalized expectation (GE) criteria (Druck et al., 2008) and multinomial naive Bayes (MNB) with priors (Settles, 2011) to one-class classification where the user only needs to provide a small list of labeled words for the target class. To combine the strengths of the two models, we fuse them together by using MNB to automatically enrich the constraints for GE training. We also explore ensemble method to combine classifiers. On a corpus of webpages from real-time bidding requests, the proposed model achieves the highest average F1 of 0.69 and closes more than half of the gap between previous state-of-the-art lightly-supervised models to a fully-supervised MaxEnt model.