Miracle-dz/UniFAR-FTUs huggingface dataset:
Recombinant spider silk-based bioinks

Bioinks, 3D cell culture systems which can be printed, are still in the early development stages. Currently, extensive research is going into designing printers to be more accommodating to bioinks, designing scaffolds with stiff materials as support structures for the often soft bioinks, and modifying the bioinks themselves. Recombinant spider silk proteins, a potential biomaterial component for bioinks, have high biocompatibility, can be processed into several morphologies and can be modified with cell adhesion motifs to enhance their bioactivity. In this work, thermally gelled hydrogels made from recombinant spider silk protein encapsulating mouse fibroblast cell line BALB/3T3 were prepared and characterized. The bioinks were evaluated for performance in vitro both before and after printing, and it was observed that unprinted bioinks provided a good platform for cell spreading and proliferation, while proliferation in printed scaffolds was prohibited. To improve the properties of the printed hydrogels, gelatin was given as an additive and thereby served indirectly as a plasticizer, improving the resolution of printed strands. Taken together, recombinant spider silk proteins and hydrogels made thereof show good potential as a bioink, warranting further development.
Semi-supervised learning with explicit misclassification modeling

This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This algorithm optimizes the classification maximum likelihood of a set of labeled-unlabeled data, using a variant form of the Classification Expectation Maximization (CEM) algorithm. Its originality is that it makes use of both unlabeled data and of a probabilistic misclassification model for these data. The parameters of the label-error model are learned together with the classifier parameters. We demonstrate the effectiveness of the approach on four data-sets and show the advantages of this method over a previously developed semi-supervised algorithm which does not consider imperfections in the labeling process.
Mining User Comment Activity for Detecting Forum Spammers in YouTube

Research shows that comment spamming (comments which are unsolicited, unrelated, abusive, hateful, commercial advertisements etc) in online discussion forums has become a common phenomenon in Web 2.0 applications and there is a strong need to counter or combat comment spamming. We present a method to automatically detect comment spammer in YouTube (largest and a popular video sharing website) forums. The proposed technique is based on mining comment activity log of a user and extracting patterns (such as time interval between subsequent comments, presence of exactly same comment across multiple unrelated videos) indicating spam behavior. We perform empirical analysis on data crawled from YouTube and demonstrate that the proposed method is effective for the task of comment spammer detection.
Young adult born neurons enhance hippocampal dependent performance via influences on bilateral networks

Adult neurogenesis supports performance in many hippocampal dependent tasks. Considering the small number of adult-born neurons generated at any given time, it is surprising that this sparse population of cells can substantially influence behavior. Recent studies have demonstrated that heightened excitability and plasticity may be critical for the contribution of young adult-born cells for certain tasks. What is not well understood is how these unique biophysical and synaptic properties may translate to networks that support behavioral function. Here we employed a location discrimination task in mice while using optogenetics to transiently silence adult-born neurons at different ages. We discovered that adult-born neurons promote location discrimination during early stages of development but only if they undergo maturation during task acquisition. Silencing of young adult-born neurons also produced changes extending to the contralateral hippocampus, detectable by both electrophysiology and fMRI measurements, suggesting young neurons may modulate location discrimination through influences on bilateral hippocampal networks. DOI: http://dx.doi. org/10.7554/eLife.22429. 001
Characteristics of files in NFS environments

As local area networks of workstations and file servers grow, the management of user and system files becomes increasingly more challenging for system administrators. In order to develop effective management tools for these administrators, the nature of files in workstation environments must be understood. This paper presents a static analysis of file usage patterns of a typical workstation environment using a standard client-server paradigm (NFS). The data reveals some differences in characteristics for files in networked environments compared with files in timesharing systems. The study also suggests what data and techniques might be appropriate as a basis for a management tool for network administrators. The paper concludes with a recommendation for the construction of a real-time management and data gathering tool that may give early-warnings of server overload or may be useful in exploring trade-offs among file allocation strategies.
A Language For Describing Predictors And Its Application To Automatic Synthesis

As processor architectures have increased their reliance on speculative execution to improve performance, the importance of accurate prediction of what to execute speculatively has increased. Furthermore, the types of values predicted have expanded from the ubiquitous branch and call/return targets to the prediction of indirect jump targets, cache ways and data values. In general, the prediction process is one of identifying the current state of the system, and making a prediction for some as yet uncomputed value based on that state. Prediction accuracy is improved by learning what is a good prediction for that state using a feedback process at the time the predicted value is actually computed. While there have been a number of efforts to formally characterize this process, we have taken the approach of providing a simple algebraic-style notation that allows one to express this state identification and feedback process. This notation allows one to describe a wide variety of predictors in a uniform way. It also facilitates the use of an efficient search technique called genetic programming, which is loosely modeled on the natural evolutionary process, to explore the design space. In this paper we describe our notation and the results of the application of genetic programming to the design of branch and indirect jump predictors.
DOCUMENTING MANTLE AND CRUSTAL CONTRIBUTIONS TO FLOOD BASALT MAGMATISM VIA COMPUTATIONAL MODELING OF THE STEENS BASALT, SOUTHEAST OREGON

DOCUMENTING MANTLE AND CRUSTAL CONTRIBUTIONS TO FLOOD BASALT MAGMATISM VIA COMPUTATIONAL MODELING OF THE STEENS BASALT, SOUTHEAST OREGON by Sylvana Juliette Bendaña July 2016 Flood basalts are enormous volcanic events with volumes of volcanic cover and intrusive equivalents that are affected by and significantly affect the crust. Steens Basalt represents 31,800 km of flood basalt lavas that erupted in eastern Oregon ~16.8 Ma in less than 300,000 years. Analytical data of flows from a 1 km vertical exposure at Steens Mtn. documents time-transgressive changes in composition of two geochemically distinct units: (1) lower Steens, MgO-rich lavas with lower incompatible trace element concentrations and Sr/Sr, and (2) upper Steens, MgO-poor, with higher incompatible trace element concentrations and Sr/Sr. Results from the Energy-Constrained Recharge Assimilation Fractional Crystallization (EC-RAFC) computational modeling tool make predictions about the relative roles that magmatic processes (recharge, assimilation, and fraction crystallization) have in time (upsection), thus yielding estimates of the mantle vs. crustal mass contribution to the magmatic system. While all three processes are shown to be critical at Steens, results suggest sub-equal mantle-derived
Intrathecal Clonidine as Spinal Anaesthesia Adjuvant — Is there a Magical Dose?

Clonidine was synthesized in 1962 as nasal decongestant, and marketed as antihypertensive in 1972. Bloor and Flacke in 1982 [1] demonstrated in mongrel dogs that intravenous clonidine 5 and 20 μg/kg decreased halothane MAC by 42% and 48% respectively. Since then, clonidine has been used by anaesthesiologists as an anaesthetic adjunct to provide increased perioper‐ ative cardiovascular and sympathoadrenal stability, to enhance general and regional anaes‐ thesia, as well as sedation and analgesia. [2, 3] In 1999, dexmedetomidine, a novel selective and specific alpha2 agonist, was approved for postoperative sedation in intensive care patients, and has also been investigated in general anaesthesia, regional anaesthesia and pain treatment. Basic research in animals and clinical studies in humans performed with epidural clonidine have shown its analgesic effects, with less side effects than any other neuroaxial anaesthesia adjuvant. Similar results were also obtained with intrathecal injection of clonidine. Due to the short duration of analgesic action by the latter route, the extradural administration is the most studied. Epidural administration of clonidine has been widely utilized; indeed, the FDA has only approved peridural use of clonidine infusion in chronic pain patients. There are many publications with epidural clonidine for intraoperative surgical pain as an adjunct to general anaesthesia and epidural anaesthesia, postoperative pain, pediatrics, and labour analgesia. It has been used alone, or in combination with local anaesthetics, opioids, in bolus, or by continuous infusion.
Demodulation of DPSK signals up to 40 gb/s using a highly birefringent photonic bandgap fiber

Phase-to-intensity modulation conversion of differential phase-shift keying signals is successfully demonstrated at 10 and 40 Gb/s using a polarization Mach-Zehnder delay interferometer implemented with only 2.4 m of a highly birefringent air-guiding photonic bandgap (PBG) fiber. Such a PBG fiber exhibits a birefringence one order of magnitude larger than that of conventional polarization-maintaining fibers, thus enabling the realization of compact interferometers. Furthermore, its single material nature is expected to result in reduced temperature sensitivity
Multi-view video segmentation and tracking for video surveillance

Tracking moving objects is a critical step for smart video surveillance systems. Despite the complexity increase, multiple camera systems exhibit the undoubted advantages of covering wide areas and handling the occurrence of occlusions by exploiting the different viewpoints. The technical problems in multiple camera systems are several: installation, calibration, objects matching, switching, data fusion, and occlusion handling. In this paper, we address the issue of tracking moving objects in an environment covered by multiple un-calibrated cameras with overlapping fields of view, typical of most surveillance setups. Our main objective is to create a framework that can be used to integrate objecttracking information from multiple video sources. Basically, the proposed technique consists of the following steps. We first perform a single-view tracking algorithm on each camera view, and then apply a consistent object labeling algorithm on all views. In the next step, we verify objects in each view separately for inconsistencies. Correspondent objects are extracted through a Homography transform from one view to the other and vice versa. Having found the correspondent objects of different views, we partition each object into homogeneous regions. In the last step, we apply the Homography transform to find the region map of first view in the second view and vice versa. For each region (in the main frame and mapped frame) a set of descriptors are extracted to find the best match between two views based on region descriptors similarity. This method is able to deal with multiple objects. Track management issues such as occlusion, appearance and disappearance of objects are resolved using information from all views. This method is capable of tracking rigid and deformable objects and this versatility lets it to be suitable for different application scenarios.
Dynamic behavior of lung surfactant.

We have previously developed an adsorption-limited model to describe the exchange of lung surfactant and its fractions to and from an air-liquid interface in oscillatory surfactometers. Here we extend this model to allow for diffusion in the liquid phase. Use of the model in conjunction with experimental data in the literature shows that diffusion-limited transport i.s important for characterizing the transient period from the start of oscillations to the achievement of steady-state conditions. Matching previous data shows that upon high levels of film compression, large changes occur in adsorption rate, desorption rate, and diffusion constant, consistent with what one might expect if the subsurface region was greatly enriched in DPPC. Collapse of the surfactant film that occurs during compression leads to a . significant elevation of surfactant concentration immediately heneath the interface, consistent with the subsurface depot of surfactant that has heen postulated by other investigators. Modeling studies also uncovered a phenomenon of surfactant behavior in which the interfacial tension remains constant at its minimum equilibrium value while the film is compressed, hut without collapse of the film. The phenomenon was due to desorption of surfactant from the interface and termed "pseudo-film collapse. '' The new model also gave improved agreement with steady-state oscillatory cycling in a pulsating bubble surfactometer.
Human Smart Cities: A Human-centric model aiming at the wellbeing and quality of life of citizens

MyNeighbourhood is a European project, part of the CIP ICT PSP Program in Smart Cities, aiming at recreating and strengthening the social ties within neighbourhoods, envisioning a new approach to the City. The project is based on an innovative vision, methodologies and tools which intend to create a Human Smart City starting from the neighbourhood and scaling up to the city. The project is a test bed of the Human Smart City concept that proposes to develop a citizen-driven, smart, all-inclusive and sustainable environment, with a new governance framework in which citizens and government engage in listening and talking to each other. This public governance model favours the emergence of a participatory innovation ecosystem that creates jobs, wealth and ultimately generates happiness for citizens.
Geometric characterization of series-parallel variable resistor networks

The authors describe an efficient method for computing exact bounds on the operating conditions of series-parallel networks. The range of operating conditions for a series-parallel network of variable linear resistors, voltage sources, and current sources can be represented as a convex polygon in a Thevenin or Norton half plane. For a network with k variable elements, these polygons have at most 2k vertices. By introducing a class of infinite points, circuits with potentially infinite Thevenin resistance or Norton conductance can also be represented. <<ETX>>
Self-Calibrating Imaging Polarimetry

To map the polarization state (Stokes vector) of objects in a scene, images are typically acquired using a polarization filter (analyzer), set at different orientations. Usually these orientations are assumed to be all known. Often, however, the angles are unknown: most photographers manually rotate the filter in coarse undocumented angles. Deviations in motorized stages or remote-sensing equipment are caused by device drift and environmental changes. This work keeps the simplicity of uncontrolled uncalibrated photography, and still extracts from the photographs accurate polarimetry. This is achieved despite unknown analyzer angles and the objects' Stokes vectors. The paper derives modest conditions on the data size, to make this task well-posed and even over-constrained. The paper then proposes an estimation algorithm, and tests it in real experiments. The algorithm demonstrates high accuracy, speed, simplicity and robustness to strong noise and other signal disruptions.
Localization of Group V Phospholipase A2 in Caveolin-enriched Granules in Activated P388D1 Macrophage-like Cells*

In murine P388D1 macrophages, the generation of prostaglandin E2 in response to long term stimulation by lipopolysaccharide involves the action of Group V secreted phospholipase A2 (PLA2), Group IV cytosolic PLA2 (cPLA2), and cyclooxygenase-2 (COX-2). There is an initial activation of cPLA2 that induces expression of Group V PLA2, which in turn induces both the expression of COX-2 and most of the arachidonic acid substrate for COX-2-dependent prostaglandin E2 generation. Because Group V PLA2 is a secreted enzyme, it has been assumed that after cellular stimulation, it must be released to the extracellular medium and re-associates with the outer membrane to release arachidonic acid from phospholipids. In the present study, confocal laser scanning microscopy experiments utilizing both immunofluorescence and green fluorescent protein-labeled Group V PLA2 shows that chronic exposure of the macrophages to lipopolysaccharide results in Group V PLA2 being associated with caveolin-2-containing granules close to the perinuclear region. Heparin, a cell-impermeable complex carbohydrate with high affinity for Group V PLA2, blocks that association, suggesting that the granules are formed by internalization of the Group V sPLA2 previously associated with the outer cellular surface. Localization of Group V PLA2 in perinuclear granules is not observed if the cells are treated with the Group IV PLA2 inhibitor methyl arachidonyl fluorophosphonate, confirming the important role for Group IV PLA2 in the activation process. Cellular staining with antibodies against COX-2 reveals the presence of COX-2-rich granules in close proximity to those containing Group V PLA2. Collectively, these results suggest that encapsulation of Group V PLA2 into granules brings the enzyme to the perinuclear envelope during cell activation where it may be closer to Group IV PLA2 and COX-2 for efficient prostaglandin synthesis.
Bimodal T-Ratios: The Impact of Thick Tails on Inference

This paper studies the distribution of the classical t-ratio with data generated from distributions with no finite moments and shows how classical testing is affected by bimodality. A key condition in generating bimodality is independence of the observations in the underlying data-generating process (DGP). The paper highlights the strikingly different implications of lack of correlation versus statistical independence in DGPs with infinite moments and shows how standard inference can be invalidated in such cases, thereby pointing to the need for adapting estimation and inference procedures to the special problems induced by thick-tailed (TT) distributions. The paper presents theoretical results for the Cauchy case and develops a new distribution termed the "double-Pareto", which allows the thickness of the tails and the existence of moments to be determined parametrically. It also investigates the relative importance of tail thickness in case of finite moments by using TT distributions truncated on a compact support, showing that bimodality can persist even in such cases. Simulation results highlight the dangers of relying on naive testing in the face of TT distributions. Novel density estimation kernel methods are employed, given that our theoretical results yield cases that exhibit density discontinuities. Copyright The Author(s). Journal compilation Royal Economic Society 2010.
Evaluating the Semiempirical $H$– $Q$ Model Used to Calculate the L-Band Emissivity of a Rough Bare Soil

In this paper, a numerical modeling approach was used to evaluate the semiempirical H-Q model used in the Soil Moisture and Ocean Salinity (SMOS) retrieval algorithm to account for roughness effects over bare soil. The H-Q model uses four parameters, H<sub>R</sub>, Q<sub>R</sub>, N<sub>RH</sub> , and N<sub>RV</sub>, which are usually calibrated at the ground scale for different surface types. The aim of this paper is to investigate whether these empirical parameters could be linked to the physical roughness parameters of standard deviation of surface heights σ and autocorrelation length L<sub>c</sub>. First, a numerical modeling approach was used to calculate rough soil emissivities for different roughness and soil moisture conditions. Second, H -Q model parameters were retrieved by minimizing a cost function between these emissivities and those calculated by the H -Q model. It was found that the retrieved H<sub>R</sub> could be related directly to Zs = σ<sup>2</sup>/L<sub>c</sub> and that Q<sub>R</sub>, N<sub>RV</sub>, and N<sub>RH</sub> were dependent on H<sub>R</sub>. H<sub>R</sub> was found to have a negligible dependence on soil moisture. Based on these results, a new model was proposed where the four H-Q model parameters were calibrated to Zs. This model was tested on the PORTOS 1993 data set and found to yield a root-mean-square difference between the retrieved and measured soil moisture values of ~ 0.03 m<sup>3</sup>/m<sup>3</sup>, which was within the desired 0.04-m<sup>3</sup>/m<sup>3</sup> error margin for the SMOS mission.
Ranking Users Based on Influence in a Directional Social Network

This paper describes the preliminary work on a study that ranks users in a directional social network by their influence during a particular time period. Our method considers a user with high influence to be one who has a high ratio of forwarded messages to the number of messages she posts. After implementing our influence ranking program, we plan to compare our method with others in the literature. This comparison will evaluate the similarity of the lists of influential users that are generated by these different methods. We will also evaluate the ease of use and time required by each of the influence calculation methods.
MuRanker: a mutant ranking tool

Mutation testing is a fault‐based software testing technique in which a large number of mutants are generated in order to assess the adequacy of test cases devised. One of the daunting problems in this area consists in determining whether a mutant can be killed by a test case or it cannot be killed easily because the mutant is semantically equivalent to the original programme. A possible solution, as proposed in this paper, is to measure the complexity of each mutant and prioritize them according to how easy or hard they are to be exposed. As a result, using a proper metric based on the mutants' complexity, the tester may decide whether to focus on killing easy or hard mutants first.
Task-Set Inertia, Attitude Accessibility, and Compatibility-Order Effects: New Evidence for a Task-Set Switching Account of the Implicit Association Test Effect

Based on a task-set switching account of the Implicit Association Test (IAT), the authors predict a specific pattern of aftereffects as a consequence of working through IAT blocks. In Study 1, performance in an evaluative decision task, but not in a color-naming task, was decreased after working through the incompatible rather than compatible block of a flower-insect IAT. In Study 2, response latencies in an evaluative rating task, but not in a color-rating task, were analogously affected, whereas the ratings themselves were not a function of the compatibility of prior IAT blocks. The aftereffects demonstrate reactivity of the IAT; they bear on the mechanisms underlying the IAT and on compatibility-order effects.