Miracle-dz/UniFAR-FTUs huggingface dataset:
Competitive adsorption of fibronectin and albumin on hydroxyapatite nanocrystals

Abstract Competitive adsorption of two-component solutions containing fibronectin (Fn) and albumin (Ab) on hydroxyapatite (HAp) nanocrystals was analyzed in situ using the quartz crystal microbalance with dissipation (QCM-D) technique. Adsorption of the one-component protein (Fn or Ab) and the two-component proteins adjusted to different molar ratios of Fn to Ab at a fixed Fn concentration was investigated. The frequency shift (Δf; Hz) and the dissipation energy shift (ΔD) were measured with the QCM-D technique, and the viscoelastic changes of adlayers were evaluated by the saturated ΔD/Δf value and the Voigt-based viscoelastic model. For the adsorption of the one-component protein, the Fn adlayer showed a larger mass and higher viscoelasticity than the Ab adlayer, indicating the higher affinity of Fn on HAp. For the adsorption of the two-component proteins, the viscoelastic properties of the adlayers became elastic with increase in Ab concentration, whereas the adsorption mass was similar to that of Fn in the one-component solution regardless of the Ab concentration. The specific binding mass of the Ab antibody to the adlayers increased with increase in Ab concentration, whereas that of the Fn antibody decreased. Therefore, Fn preferentially adsorbs on HAp and Ab subsequently interacts with the adlayers, indicating that the interfacial viscoelasticity of the adlayers was dominated by the interaction between Fn and Ab.
The Effect of Osmolytes on Protein Fibrillation

Osmolytes are small molecules that are exploited by cells as a protective system against stress conditions. They favour compact protein states which makes them stabilize globular proteins in vitro and promote folding. Conversely, this preference for compact states promotes aggregation of unstructured proteins. Here we combine a brief review of the effect of osmolytes on protein fibrillation with a report of the effect of osmolytes on the unstructured peptide hormone glucagon. Our results show that osmolytes either accelerate the fibrillation kinetics or leave them unaffected, with the exception of the osmolyte taurine. Furthermore, the osmolytes that affected the shape of the fibrillation time profile led to fibrils with different structure as revealed by CD. The structural changes induced by Pro, Ser and choline-O-sulfate could be due to specific osmolytes binding to the peptides, stabilizing an otherwise labile fibrillation intermediate.
An investigation into the corrosion behaviour and effect of inhibitor additions on commercial Zn-Mg-Al alloys

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Graves' Ophthalmopathy: A Review of Immunogenetics

Graves’ disease (GD) is the most common cause of thyrotoxicosis and often involves the orbits. Graves’ ophthalmopathy (GO), also known as Thyroid Eye Disease (TED), can be clinically significant and advance to sight-threatening stages. Our knowledge of the immunogenetic pathophysiology of GO is rapidly expanding. The present review is an attempt to summarize the current state of knowledge on the immunogenetics of GO. First we briefly review the epidemiology and clinical importance of GO, and then we describe in detail the macromolecular pathogenesis and finally immunogenetics of GO. Discrepancies between the results from various reports and the limitations of the available data are discussed. In particular, there is a scarcity of data from non-Asian populations. While several studies have demonstrated significant associations between polymorphisms in certain genes (especially CTLA-4, HLA-DRB-1, and TNF-α), there is a need for studies that investigate the relationship between polymorphisms and both serum and local concentrations of the resulting proteins. A complete understanding of GO susceptibility and pathogenesis has not been yet possible due to a number of important knowledge gaps that need to be filled by future research.
Analysis of optimal cluster number in heterogenous wireless sensor networks

Recently, researchers have shown an increased interest in the area of energy efficient operation of the sensors inside the wireless sensor networks (WSNs). The energy efficiency could be achieved by designing an effective routing protocol. Cluster based routing protocol is a well known technique to increase the energy efficiency of the sensor nodes as well as extending the lifetime of the network. Cluster based routing protocol was formed a number of clusters which gather the data sensed from all sensor nodes in the network. Then, the data were sent to the sink node. In addition, the number of clusters needs to be selected properly to avoid faster network degradation. This paper shows the derivation of an analytical formula to optimize the number of clusters (k) in three level heterogeneous wireless sensor networks in order to increase the network lifetime. It was formulated by considering the energy consumption per iteration. Simulation results verify both the correctness of our mathematical models and the effectiveness of computing the k value to increase the network lifetime.
Resilience evaluation via symbolic fault injection on intermediate code

There is a growing need for error-resilient software that can tolerate hardware faults as well as for new resilience evaluation techniques. For the latter, a promising direction is to apply formal techniques in fault injection-based evaluations to improve the coverage of evaluation results. Building on the recent development of Software-implemented Fault Injection (SWiFI) techniques on compiler's intermediate code, this paper proposes a novel resilience evaluation framework combining LLVM-based SWiFI and SMT-based symbolic execution. This novel combination offers significant advantages over state-of-the-art approaches with respect to accuracy and coverage.
Maternal pregravid weight is the primary determinant of serum leptin and its metabolic associations in pregnancy, irrespective of gestational glucose tolerance status.

CONTEXT Several previous studies have investigated circulating levels of the adipokine leptin in relation to gestational diabetes mellitus (GDM). However, these studies have yielded markedly conflicting results, including increased, decreased, and unchanged leptin levels in women with GDM as compared with their peers. OBJECTIVE We sought to evaluate the metabolic determinants of serum leptin in a well-characterized cohort reflecting the full spectrum of glucose intolerance in pregnancy. DESIGN, SETTING, AND PARTICIPANTS Metabolic characterization, including oral glucose tolerance test (OGTT) and measurement of serum leptin, insulin, lipids, adiponectin, and C-reactive protein, was performed in 817 pregnant women. The OGTT identified 198 women with GDM, 142 with gestational impaired glucose tolerance, and 477 with normal glucose tolerance. RESULTS Median leptin (ng/ml) did not differ between the normal glucose tolerance (33.7), gestational impaired glucose tolerance (36.3), and GDM (36.4) groups (P = 0.085). On univariate correlation analysis, leptin was most strongly associated with prepregnancy body mass index (BMI) (r = 0.54, P < 0.0001), fasting insulin (r = 0.60, P < 0.0001), and C-reactive protein (r = 0.38, P < 0.0001) but only weakly associated with area under the glucose curve (AUC(glucose)) on the OGTT (r = 0.10, P = 0.0066). On multiple linear regression analysis, the strongest independent determinant of leptin was prepregnancy BMI (t = 11.55, P < 0.0001), whereas AUC(glucose) was not a significant predictor (t = -0.95, P = 0.34). Furthermore, although its respective associations with fasting insulin, triglycerides, and adiponectin varied across tertiles of prepregnancy BMI, leptin was not significantly associated with AUC(glucose) in any BMI tertile. CONCLUSIONS Pregravid BMI, rather than gestational glucose tolerance, is the primary determinant of serum leptin concentration in pregnancy.
Consensus statement on concussion in sport--the 4th International Conference on Concussion in Sport held in Zurich, November 2012.

the 4th International Conference on Concussion in Sport held in Zurich, November 2012 Paul McCrory, Willem H Meeuwisse, Mark Aubry, Bob Cantu, Jiří Dvořák, Ruben J Echemendia, Lars Engebretsen, Karen Johnston, Jeffrey S Kutcher, Martin Raftery, Allen Sills, Brian W Benson, Gavin A Davis, Richard G Ellenbogen, Kevin Guskiewicz, Stanley A Herring, Grant L Iverson, Barry D Jordan, James Kissick, Michael McCrea, Andrew S McIntosh, David Maddocks, Michael Makdissi, Laura Purcell, Margot Putukian, Kathryn Schneider, Charles H Tator, Michael Turner
Yukta: Multilayer Resource Controllers to Maximize Efficiency

Since computers increasingly execute in constrained environments, they are being equipped with controllers for resource management. However, the operation of modern computer systems is structured in multiple layers, such as the hardware, OS, and networking layers—each with its own resources. Managing such a system scalably and portably requires that we have a controller in each layer, and that the different controllers coordinate their operation. In addition, such controllers should not rely on heuristics, but be based on formal control theory. This paper presents a new approach to build coordinated multilayer formal controllers for computers. The approach uses Structured Singular Value (SSV) controllers from Robust Control Theory. Such controllers are especially suited for multilayer computer system control. Indeed, SSV controllers can read signals from other controllers to coordinate multilayer operation. In addition, they allow designers to specify the discrete values allowed in each input, and the desired bounds on output value deviations. Finally, they accept uncertainty guardbands, which incorporate the effects of interference between the controllers. We call this approach Yukta. To assess its effectiveness, we prototype it in an 8-core big. LITTLE board. We build a two-layer SSV controller, and show that it is very effective. Yukta reduces the ExD and the execution time of a set of applications by an average of 50% and 38%, respectively, over advanced heuristic-based coordinated controllers.
Plants Integrate Information About Nutrients and Neighbors

Plant root growth is modified in the presence of within-species competition and uneven local resource distributions. Animals regularly integrate information about the location of resources and the presence of competitors, altering their foraging behavior accordingly. We studied the annual plant Abutilon theophrasti to determine whether a plant can demonstrate a similarly complex response to two conditions: presence of a competitor and heterogeneous resource distributions. Individually grown plants fully explored the pot by using a broad and uniform rooting distribution regardless of soil resource distributions. Plants with competitors and uniform soil nutrient distributions exhibited pronounced reductions in rooting breadth and spatial soil segregation among the competing individuals. In contrast, plants with competitors and heterogeneous soil nutrient distributions reduced their root growth only modestly, indicating that plants integrate information about both neighbor and resource distributions in determining their root behavior.
Impact of Presentation Format and Self-Reported Risk Aversion on Revealed Skewness Preferences

This paper reports the results of an experiment on the revealed preference for skewness in a comparison of continuous return distributions. We find that revealed preferences are highly sensitive to the way asset risks are communicated. Whereas probability density functions lead to a pronounced preference for left-skewed distributions, the opposite is true for cumulative distribution functions. Systematic misperceptions of the variance cannot explain the sensitivity of preferences to the presentation format. Part of the preference for positive skewness when risks are communicated through probability density functions is due to a systematic misestimation of the expected return. We also find that self-reported risk aversion, a measure of risk attitude commonly used in practice, is a valuable predictor of skewness preferences. Individuals that judge themselves as more risk averse show a stronger preference for right skewness.
Effect of field of view and iris pupil diameter on the quality of retinal image with allyl carbonate (CR-39) polymer contact lenses

Contact lenses are manufactured from high-grade plastic polymers and prescribed by specialists to treat myopia, hyperopia, astigmatism and presbyopia. Some people opt to wear contact lenses directly on the cornea for aesthetic reasons. The formed image is mainly focused on the retina. Manufacturers are constantly searching for and developing optimal materials for contact lenses to satisfy patients and practitioners in terms of the standard optical characteristics (i.e. Refractive index, abbe number, light reflectance and light transmittance). In this study, allyl carbonate, which is commonly known as CR-39, was tested as the polymer material for contact lenses. The CR-39 polymer material data (refractive index, 1.49; density, 1.32; Abbe number, (58–59) were used in establishing the Liou & Brennan model. The effect of iris, pupil size and the field of view (F.O.V.) on the retinal image was evaluated and analyzed using Zemax-EE software (2005), The modulation transfer function (MTF), point spread function (PSF), blur spot size (RMS), encircled energy (EE) and the type and amount of aberrations, are used as a criteria to analysis the retinal image degradation. The results show that the CR-39 polymer material has good optical properties, which render it a recommended material for ophthalmic contact lenses.
Fractal antenna for wireless applications

In this paper, a compact single-element fractal antenna system measuring 20×15 mm2 is proposed. The ring resonator increased the number of resonances which make antenna multiband. The reflection coefficient of antenna is found to be below −10dB in the range of 5.1–6.3 GHz and 7.5–8.8 GHz. The performance of the antenna is studied in terms of mutual coupling, pattern of radiation, realized peak gain, directivity and VSWR. The maximum gain of antenna found to be 2.14dB.
Herbivore perception decreases photosynthetic carbon assimilation and reduces stomatal conductance by engaging 12-oxo-phytodienoic acid, mitogen-activated protein kinase 4 and cytokinin perception.

Herbivory-induced changes in photosynthesis have been documented in many plant species; however, the complexity of photosynthetic regulation and analysis has thwarted progress in understanding the mechanism involved, particularly those elicited by herbivore-specific elicitors. Here, we analysed the early photosynthetic gas exchange responses in Nicotiana attenuata plants after wounding and elicitation with Manduca sexta oral secretions and the pathways regulating these responses. Elicitation with M. sexta oral secretions rapidly decreased photosynthetic carbon assimilation (AC ) in treated and systemic (untreated, vascularly connected) leaves, which were associated with changes in stomatal conductance, rather than with changes in Rubisco activity and 1-5 ribulose-1,5-bisphosphate turnover. Phytohormone profiling and gas exchange analysis of oral secretion-elicited transgenic plants altered in phytohormone regulation, biosynthesis and perception, combined with micrografting techniques, revealed that the local photosynthetic responses were mediated by 12-oxo-phytodienoic acid, while the systemic responses involved interactions among jasmonates, cytokinins and abscisic acid signalling mediated by mitogen-activated protein kinase 4. The analysis also revealed a role for cytokinins interacting with mitogen-activated protein kinase 4 in CO2 -mediated stomatal regulation. Hence, oral secretions, while eliciting jasmonic acid-mediated defence responses, also elicit 12-oxo-phytodienoic acid-mediated changes in stomatal conductance and AC , an observation illustrating the complexity and economy of the signalling that regulates defence and carbon assimilation pathways in response to herbivore attack.
Diabetes and periodontitis: multidisciplinary management

Diabetes has reached epidemic levels in North America and continues to rise in prevalence, generating a significant financial burden on society. The strong link between type 2 diabetes and periodontitis provides a sound basis for dental professionals to screen for and help manage diabetic patients. Literature from journals of both medicine and dentistry was included to provide a comprehensive examination of the bi-directional relationship between diabetes and periodontitis. This review highlights the necessity for multidisciplinary management of patients suffering from both disease processes, and the benefits of how treatment of one can positively impact the other. Additional analysis of the precise effect of hyperglycemia on the severity and progression of periodontal disease should be conducted to gain further insight into the relationship between the two diseases. It is incumbent on oral health care providers to become a partner in managing patients with periodontitis and type-2 diabetes. Abbreviations: AGE: advanced glycated end product; BOP: bleeding on probing; CDC: center for disease control; DM: diabetes mellitus; HbA1c: hemoglobin A1c; LPS: lipopolysaccharide; MMP: matrix metalloproteinases; NET: neutrophil extracellular trap; PISA: periodontal inflamed surface area; PD: probing depths; PMN: polymorphonuclear lymphocyte; RAGE: receptor of advanced glycation end product; RANKL: receptor activator of nuclear factor kappa-b ligand; ROS: reactive oxygen species; T2DM: type 2 diabetes mellitus; TNFalpha: tumor necrosis factor-alpha
Surprise Me If You Can: Serendipity in Health Information

Our natural tendency to be curious is increasingly important now that we are exposed to vast amounts of information. We often cope with this overload by focusing on the familiar: information that matches our expectations. In this paper we present a framework for interactive serendipitous information discovery based on a computational model of surprise. This framework delivers information that users were not actively looking for, but which will be valuable to their unexpressed needs. We hypothesize that users will be surprised when presented with information that violates the expectations predicted by our model of them. This surprise model is balanced by a value component which ensures that the information is relevant to the user. Within this framework we have implemented two surprise models, one based on association mining and the other on topic modeling approaches. We evaluate these two models with thirty users in the context of online health news recommendation. Positive user feedback was obtained for both of the computational models of surprise compared to a baseline random method. This research contributes to the understanding of serendipity and how to "engineer" serendipity that is favored by users.
Discriminating Among Word Meanings by Identifying Similar Contexts

Word sense discrimination is an unsupervised clustering problem, which seeks to discover which instances of a word/s are used in the same meaning. This is done strictly based on information found in raw corpora, without using any sense tagged text or other existing knowledge sources. Our particular focus is to systematically compare the efficacy of a range of lexical features, context representations, and clustering algorithms when applied to this problem.
Declarative Processing of Semistructured Web Data

In order to give application programs access to data stored in the web in semistructured formats, in particular, in XML format, we propose a domain-specific language (DSL) for declarative processing such data. Our language is embedded in the functional logic programming language Curry and offers powerful matching constructs that enable a declarative description of accessing and transforming XML data. We exploit advanced features of functional logic programming to provide a high-level and maintainable implementation of our language. Actually, this paper contains the complete code of our implementation so that the source text of this paper is an executable implementation of our embedded DSL.
On the minimum hybrid rank of a graph relative to a partition of its edges and its application to electrical network analysis

We consider the following problem in this paper: given a partition of the set of edges of a graph such that the subgraphs on the blocks of the partition are connected, what is the minimum number of node fission (splitting a node into two) and node fusion (coalescing two nodes) operations that will destroy all circuits containing edges from more than one block of the partition? This problem can be seen to be a generalization of the problem of determining the minimum hybrid rank of a graph. We may therefore regard this minimum number as the minimum hybrid rank of the graph relative to a specified partition of the edge set of the graph. We give an efficient algorithm for the construction of a minimum length sequence of such operations. Our solution can be applied to the problem of analysing networks after first decomposing them into subnetworks-the equations of the network can be displayed in a bordered block diagonal form where the blocks along the diagonal correspond to the subnetworks and the thickness of the border corresponds to the minimum hybrid rank relative to the partition of the sets of edges of the network into the sets of edges of the subnetworks.