Miracle-dz/UniFAR-FTUs huggingface dataset:
Colloidal Consolidation of Ceramic Nanoparticles by Pressure Filtration

The applied pressure and suspension height during consolidation of an aqueous suspension of nanometer-sized particles (24 nm hydroxyapatite, 30 nm SiC, 68 nm 8 mol% yttria-stabilized zirconia, 150 nm Al2O3, and 800 nm SiC) were continuously recorded using a pressure filtration apparatus. The packing density decreased when the particle size was less than 70 nm. The final packing density of 150−800 nm particles at 19 MPa was strongly influenced by the surface charge. However, surface charge does not affect the packing density of particles less than 70 nm. The ratio of the energy applied to two particles during consolidation to the interaction energy between two particles in a suspension was correlated to the packing density. The low packing density of 20−30 nm particles was improved by steric stabilization. The estimated thickness of the dispersant layer adsorbed on the particle surfaces was less than 1 nm and nearly independent of the molecular weight of the dispersants. When the applied pressure was released, the height of the consolidated cake increased because of the release of the elastic strain stored in the dispersant layer.
Open-Loop Link Adaptation for Next-Generation IEEE 802.11n Wireless Networks

In this paper, we propose a novel open-loop autorate fallback algorithm (i.e., the autorate fallback for high-throughput (ARFHT) algorithm) for the emerging high-throughput (HT) IEEE 802.11n wireless networks. ARFHT extends the legacy link adaptation algorithms for single-input-single-output (SISO) wireless networks to be applicable in the context of multiple-input-multiple-output (MIMO)-based 802.11n wireless networks. It adapts the MIMO mode in terms of spatial multiplexing and spatial diversity, which are the two fundamental characteristics of MIMO technology. It also modifies the link estimation and probing behavior of legacy SISO algorithms. The combined adaptation to the appropriate MIMO mode and the modulation coding scheme together achieves more efficient channel utilization. We will present in detail the design guidelines and key ideas for the ARFHT algorithm. A comprehensive simulation study using ns-2 demonstrates that ARFHT achieves excellent throughput and packet error-rate performance in diverse environments and is highly responsive to time-varying link conditions with minimum computational complexity and protocol overhead.
Affective Spatial Compatibility Task (AffSCt): Theory and Applications

Emotional stimuli are processed very ef ﬁ ciently, in ﬂ uencing physiological and behavioral responses as well as attention, perceptual processes and sensory-motor integration. In a previous work, we introduced a new paradigm, the Affective Spatial Compatibility task (AffSCt), to study whether the affective valence of the stimulus in ﬂ uences spatial compatibility effects. By using ﬁ gures of soccer players of Favorite and Rival Teams as positive and negative valence stimuli, we found a normal Spatial Compatibility effect for the Favorite team and a reversed one for the Rival team. Here, we analyzed the time course of inhibitory and facilitatory effects of emotional valence by the Vincentization method. We found that for Favorite team, the facilitatory effect for
Distinctive Image Features from Scale-Invariant Keypoints

This paper presents a method for extracting distinctive inv ar ant features from images that can be used to perform reliable matching between diff rent views of an object or scene. The features are invariant to image scale and rotation, and are shown to provide robust matching across a a substantial r ange of affine distortion, change in 3D viewpoint, addition of noise, and chan ge in illumination. The features are highly distinctive, in the sense that a sing le feature can be correctly matched with high probability against a large databa se of features from many images. This paper also describes an approach to using t hese features for object recognition. The recognition proceeds by matchi ng individual features to a database of features from known objects using a fas t ne rest-neighbor algorithm, followed by a Hough transform to identify cluste r belonging to a single object, and finally performing verification through leas t-squares solution for consistent pose parameters. This approach to recognition c an robustly identify objects among clutter and occlusion while achieving near re al-time performance. Accepted for publication in the International Journal of Computer Vision, 2004.
A pattern-based approach to parametric specification mining

This paper presents a technique for using execution traces to mine parametric temporal specifications in the form of quantified event automata (QEA) - previously introduced as an expressive and efficient formalism for runtime verification. We consider a pattern-based mining approach that uses a pattern library to generate and check potential properties over given traces, and then combines successful patterns. By using predefined models to measure the tool's precision and recall we demonstrate that our approach can effectively and efficiently extract specifications in realistic scenarios.
An intrusion and defense testbed in a cyber-power system environment

The proposed testbed of the cyber‐power system consists of power system simulation, substation automation, and the SCADA system. Scenarios for substation cyber security intrusions and anomaly detection concepts have been proposed. An attack tree method can be used to identify vulnerable substations and intrusions through remote access points. Specific substation vulnerability scenarios have been tested. Temporal anomaly is determined by data and information acquired at different time points. This is a metric to determine the anomaly between two snapshots. In a distributed intrusion detection algorithm, distributed agents are trained with a large number of scenarios and intended for real‐time applications. In a distributed environment, if an anomaly is detected by one agent, it is able to distribute critical information to other agents in the network.
Part-Based Tracking via Salient Collaborating Features

We present a novel part-based method for model-free tracking. In our model, key points are considered as elementary predictors, collaborating to localize the target. In order to differentiate reliable features from outliers and bad predictors, we define the notion of feature saliency including three factors: the persistence, the spatial consistency, and the predictive power of local features. Saliency information is learned during tracking to be used in several algorithmic steps: local predictions, global localization, feature removal, etc. By exploiting saliency information and key point structural properties, the proposed algorithm is able to track accurately generic objects, facing several difficulties such as occlusions, presence of distractors, and abrupt motion. The proposed tracker demonstrated a high robustness on challenging public datasets, outperforming significantly five recent state-of-the-art trackers.
Tetrandrine, a Compound Common in Chinese Traditional Medicine, Preferentially Kills Breast Cancer Tumor Initiating Cells (TICs) In Vitro

Tetrandrine is a bisbenzylisoquinoline alkaloid found in Stephania tetrandra, a Chinese medicine commonly used as an anti-inflammatory. It has extensive pharmacological activity, including positive ion channel blockade and inhibition of multiple drug resistance proteins. These activities are very similar to that of salinomycin, a known drug targeting breast cancer initiation cells (TICs). Herein, we tested tetrandrine targeting of breast cancer TICs. SUM-149, an inflammatory breast cancer cell line and SUM-159, a non-inflammatory metaplastic breast cancer cell line were used in these studies. In proliferation assays using 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS), we found that the IC50 for inhibition of proliferation is 15.3 ± 4.1 μM for SUM-149 and 24.3 ± 2.1 μM for SUM-159 cells. Tetrandrine also inhibited mammosphere formation, a surrogate for breast cancer TICs growth in vitro with IC50 around 1 μM for SUM-149 and around 2 μM for SUM-159 cells. Tetrandrine has similar effects on the mammosphere formation from cells isolated from fresh patient sample. Moreover, tetrandrine decreases the aldehyde dehydrogenase (ALDH) positive population in SUM-159 by 45% ± 5.45% P = 0.005. In summary, tetrandrine demonstrates significant efficacy against in vitro surrogates for inflammatory and aggressive breast cancer TICs.
Crowdsourcing Contests with Private Types and Evaluation Uncertainty

We introduce a general model of crowdsourcing contests in which the performance of an agent is driven by his privately known ability type (adverse selection), his costly effort choice and it is further affected by evaluation uncertainty or luck (moral hazard). We show that when the marginal cost of effort is sufficiently large and the solvers' types, as well as, the evaluation uncertainty are independent and identically distributed respectively, there exists a unique Bayes Nash equilibrium effort. This equilibrium effort is in symmetric and pure strategies and involves inactive types. Our model includes as special cases the Tullock contest (Tullock, 1980), the all-pay auction model with private information of Moldovanu et al. (2001), and the symmetric effort with evaluation uncertainty model of Lazear et al. (1981) that have been studied separately thus far. Our results suggest that several comparative statics results of the all-pay auctions with private information are robust in the presence of noisy feedback.
P‐64: Using Electroless Plating Technology for Copper Metallization in AMLCD Application

The feasibility of using electro‐less plating (ELP) technology to manufacture copper (Cu) gate electrodes in TFTs is investigated. The poor adhesion between Cu and glass substrates is overcome by introducing ELP nickel‐phosphorus layers. Self‐aligning characteristics also omits the Cu‐etching process. The similar electrical performance verifies the compatibility of this technology.
Using the COSMIC method to estimate Agile user stories

Agile Project Management (APM) is widely used in different software projects from different application domains. APM includes a series of commonly used project management approaches with the intent to handle better uncertainty and unpredictability, which is not always successful. For instance, in a large portion of software projects, accurate planning (and estimating) of whole project lifetime with Agile is difficult. Since a continuously change in (product) requirements occurs as well their incompleteness at the project initialization phase, project plan must be under control and continuously be revised according to its needs and resources. In Agile projects, planning is mainly based on guess estimate of the effort trying to balance the product and the resources not showing the part of each one. In order to improve the guess estimate, this paper proposes an approach moving from the COCOMO (Constructive Cost Model) worked, using the COSMIC measurement method at the micro-level (User Stories) jointly with the quality of the documentation for deploying the functional analysis. The proposed procedure shows that this approach can help the planner to know better why the global effort changes by the time.
A working memory model based on fast Hebbian learning

Recent models of the oculomotor delayed response task have been based on the assumption that working memory is stored as a persistent activity state (a ‘bump’ state). The delay activity is maintained by a finely tuned synaptic weight matrix producing a line attractor. Here we present an alternative hypothesis, that fast Hebbian synaptic plasticity is the mechanism underlying working memory. A computational model demonstrates a working memory function that is more resistant to distractors and network inhomogeneity compared to previous models, and that is also capable of storing multiple memories.
Silhouette measurements for Bayesian object tracking in noisy point clouds

In this paper, we consider the problem of jointly tracking the pose and shape of objects based on noisy data from cameras and depth sensors. Our proposed approach formalizes object silhouettes from image data as measurements within a Bayesian estimation framework. Projecting object silhouettes from images back into space yields a visual hull that constrains the object. In this work, we focus on the 2D case. We derive a general equation for the silhouette measurement update that explicitly considers segmentation uncertainty of each pixel. By assuming a bounded error for the silhouettes, we can reduce the complexity of the general solution to only consider uncertain edges and derive an approximate measurement update. In simulations, we show that the proposed approach dramatically improves point-cloud-based estimators, especially in the presence of high noise.
Method for continuous casting of metal wire and tube containing optical fibre

AbstractThe Ohno continuous casting technique has been applied for the first time to the fabrication of wires and tubes containing optical fibres. By selection of the appropriate casting parameters, conditions were established by which it was possible to embed optical fibre within tin wires 2 mm in diameter and within the walls of tubes of outer diameter 8·8 mm and inner diameter 5 mm. Optical fibres were confined within the wire or the tube wall even though there is a large density difference between the fibre and the molten metal. Successful confinement of the fibre was obtained by locating an appropriately designed fibre feed guide at the entrance of the mould cavity.MST/3152
Network analyses identify liver‐specific targets for treating liver diseases

We performed integrative network analyses to identify targets that can be used for effectively treating liver diseases with minimal side effects. We first generated co‐expression networks (CNs) for 46 human tissues and liver cancer to explore the functional relationships between genes and examined the overlap between functional and physical interactions. Since increased de novo lipogenesis is a characteristic of nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC), we investigated the liver‐specific genes co‐expressed with fatty acid synthase (FASN). CN analyses predicted that inhibition of these liver‐specific genes decreases FASN expression. Experiments in human cancer cell lines, mouse liver samples, and primary human hepatocytes validated our predictions by demonstrating functional relationships between these liver genes, and showing that their inhibition decreases cell growth and liver fat content. In conclusion, we identified liver‐specific genes linked to NAFLD pathogenesis, such as pyruvate kinase liver and red blood cell (PKLR), or to HCC pathogenesis, such as PKLR, patatin‐like phospholipase domain containing 3 (PNPLA3), and proprotein convertase subtilisin/kexin type 9 (PCSK9), all of which are potential targets for drug development.
Molecular Analysis of Laminin N-terminal Domains Mediating Self-interactions*

The ability of laminins to self-polymerize is crucial for the formation of basement membranes. Development of this polymerized network has profound effects upon tissue architecture as well as on the intracellular organization and differentiation of neighboring cells. The laminin N-terminal (LN) domains have been shown to mediate this interaction and studies using proteolytic fragments derived from laminin-1 led to the theory that network assembly depends on the formation of a heterotrimeric complex between LN domains derived from α, β, and γ chains in different laminin molecules with homologous interactions being insignificant. The laminin family consists of 15 known isoforms formed from five α, three β, and three γ chains, of which some are truncated and lack the N-terminal LN domain. To address whether the model of heterotrimeric complex formation is applicable to laminin isoforms other than laminin-1, eight LN domains found in the laminin protein family were recombinantly expressed and tested in three different assays for homologous and heterologous interactions. The results showed that the lack of homologous interactions is an exception, with such interactions being seen for LN domains derived from all α chains and from the β and2 β3 subunits. The γ chain-derived LN domains showed a far more limited binding repertoire, particularly in the case of the γ3 chain, which is found present in a range of non-basement membrane locations. Further, whereas the interactions depended upon Ca2+ ions, with EDTA reversibly abrogating binding, EDTA-induced conformational changes were not reversible. Together these results demonstrate that the assembly model proposed on the basis of laminin-1 may be a simplification, with the assembly of naturally occurring laminin networks being far more complex and highly dependent upon which laminin isoforms are present.
Monomeric Monocyte Chemoattractant Protein-1 (MCP-1) Binds and Activates the MCP-1 Receptor CCR2B*

To address the role of dimerization in the function of the monocyte chemoattractant protein-1, MCP-1, we mutated residues that comprise the core of the dimerization interface and characterized the ability of these mutants to dimerize and to bind and activate the MCP-1 receptor, CCR2b. One mutant, P8A*, does not dimerize. However, it has wild type binding affinity, stimulates chemotaxis, inhibits adenylate cyclase, and stimulates calcium influx with wild type potency and efficacy. These data suggest that MCP-1 binds and activates its receptor as a monomer. In contrast, Y13A*, another monomeric mutant, has a 100-fold weaker binding affinity, is a much less potent inhibitor of adenylate cyclase and stimulator of calcium influx, and is unable to stimulate chemotaxis. Thus Tyr13 may make important contacts with the receptor that are required for high affinity binding and signal transduction. We also explored whether a mutant, [1+9–76]MCP-1 (MCP-1 lacking residues 2–8), antagonizes wild type MCP-1 by competitive inhibition, or by a dominant negative mechanism wherein heterodimers of MCP-1 and [1+9–76]MCP-1 bind to the receptor but are signaling incompetent. Consistent with the finding that MCP-1 can bind and activate the receptor as a monomer, we demonstrate that binding of MCP-1 in the presence of [1+9–76]MCP-1 over a range of concentrations of both ligands fits well to a simple model in which monomeric [1+9–76]MCP-1 functions as a competitive inhibitor of monomeric MCP-1. These results are crucial for elucidating the molecular details of receptor binding and activation, for interpreting mutagenesis data, for understanding how antagonistic chemokine variants function, and for the design of receptor antagonists.
Modeling of caterpillar crawl using novel tensegrity structures

Caterpillars are soft-bodied animals. They have a relatively simple nervous system, and yet are capable of exhibiting complex movement. This paper presents a 2D caterpillar simulation which mimics caterpillar locomotion using Assur tensegrity structures. Tensegrity structures are structures composed of a set of elements always under compression and a set of elements always under tension. Assur tensegrities are a novel sub-group of tensegrity structures. In the model, each caterpillar segment is represented by a 2D Assur tensegrity structure called a triad. The mechanical structure and the control scheme of the model are inspired by the biological caterpillar. The unique engineering properties of Assur tensegrity structures, together with the suggested control scheme, provide the model with a controllable degree of softness—each segment can be either soft or rigid. The model exhibits several characteristics which are analogous to those of the biological caterpillar. One such characteristic is that the internal pressure of the caterpillar is not a function of its size. During growth, body mass is increased 10 000-fold, while internal pressure remains constant. In the same way, the model is able to maintain near constant internal forces regardless of size. The research also suggests that caterpillars do not invest considerably more energy while crawling than while resting.
Inductive learning of feature-tracking rules for scientific visualization

Numerical simulation and scientiﬁc visualization are often used by scientists to help them understand physical phenomena. One approach taken by some visualization systems is to identify and quantify coherent features in a simulation and track their trajectories as they evolve over time. Such feature-tracking systems operate either by relying on manual (human) efforts, or by utilizing ad hoc programs embodying heuristics that are computationally expensive to use. Our research demonstrates the use of inductive learning to construct feature-tracking programs for ﬂuid ﬂows. Our approach uses manually generated feature trajectories as training data, and applies inductive learning to construct feature-tracking rules that can then be incorporated into a feature-tracking program. This results in a more efﬁcient system that can match up objects across large time steps without inspecting intermediate steps. We demonstrate our approach on the problem of tracking vortices in turbulent viscous ﬂuids.
Catalytic efficiency of iron(III) oxides in decomposition of hydrogen peroxide: competition between the surface area and crystallinity of nanoparticles.

Various iron(III) oxide catalysts were prepared by controlled decomposition of a narrow layer (ca. 1 mm) of iron(II) oxalate dihydrate, FeC(2)O(4). 2H(2)O, in air at the minimum conversion temperature of 175 degrees C. This thermally induced solid-state process allows for simple synthesis of amorphous Fe(2)O(3) nanoparticles and their controlled one-step crystallization to hematite (alpha-Fe(2)O(3)). Thus, nanopowders differing in surface area and particle crystallinity can be produced depending on the reaction time. The phase composition of iron(III) oxides was monitored by XRD and (57)Fe Mössbauer spectroscopy including in-field measurements, providing information on the relative contents of amorphous and crystalline phases. The gradual changes in particle size and surface area accompanying crystallization were evaluated by HRTEM and BET analysis, respectively. The catalytic efficiency of the synthesized nanoparticles was tested by tracking the decomposition of hydrogen peroxide. The obtained kinetic data gave an unconventional nonmonotone dependence of the rate constant on the surface area of the samples. The amorphous nanopowder with the largest surface area of 401 m(2) g(-1) revealed the lowest catalytic efficiency, while the highest efficiency was achieved with the sample having a significantly lower surface area, 337 m(2) g(-1), exhibiting a prevailing content of crystalline alpha-Fe(2)O(3) phase. The obtained rate constant, 26.4 x 10(-3) min(-1) (g/L)(-1), is currently the highest value published. The observed rare catalytic phenomenon, where the particle crystallinity prevails over the surface area effects, is discussed with respect to other processes of heterogeneous catalysis.