Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Ligand-Based Method for Purifying Active Human Plasma-Derived Ficolin-3 Complexes Supports the Phenomenon of Crosstalk between Pattern-Recognition Molecules and Immunoglobulins

Despite recombinant protein technology development, proteins isolated from natural sources remain important for structure and activity determination. Ficolins represent a class of proteins that are difficult to isolate. To date, three methods for purifying ficolin-3 from plasma/serum have been proposed, defined by most critical step: (i) hydroxyapatite absorption chromatography (ii) N-acetylated human serum albumin affinity chromatography and (iii) anti-ficolin-3 monoclonal antibody-based affinity chromatography. We present a new protocol for purifying ficolin-3 complexes from human plasma that is based on an exclusive ligand: the O-specific polysaccharide of Hafnia alvei PCM 1200 LPS (O-PS 1200). The protocol includes (i) poly(ethylene glycol) precipitation; (ii) yeast and l-fucose incubation, for depletion of mannose-binding lectin; (iii) affinity chromatography using O-PS 1200-Sepharose; (iv) size-exclusion chromatography. Application of this protocol yielded average 2.2 mg of ficolin-3 preparation free of mannose-binding lectin (MBL), ficolin-1 and -2 from 500 ml of plasma. The protein was complexed with MBL-associated serine proteases (MASPs) and was able to activate the complement in vitro. In-process monitoring of MBL, ficolins, and total protein content revealed the presence of difficult-to-remove immunoglobulin G, M and A, in some extent in agreement with recent findings suggesting crosstalk between IgG and ficolin-3. We demonstrated that recombinant ficolin-3 interacts with IgG and IgM in a concentration-dependent manner. Although this association does not appear to influence ficolin-3-ligand interactions in vitro, it may have numerous consequences in vivo. Thus our purification procedure provides Ig-ficolin-3/MASP complexes that might be useful for gaining further insight into the crosstalk and biological activity of ficolin-3.
Implementation of the IEEE 802.11p/1609.4 DSRC/WAVE in NS-2

Due to the high costs of deploying and testing VANETs, simulations are required for development and evaluation of new protocols at any layer of WAVE protocol stack. Although there are powerful tools to simulate VANETs and especially the IEEE 802.11p/1609.4 DSRC/WAVE protocols, however, they are not free or not publically available. NS-2 Network Simulator is a free and widely accepted simulator used by researchers to simulate DSRC/WAVE. To the best of our knowledge, current version of NS-2 and developed simulation tools based on NS-2 do not appropriately support for the multichannel operation of the IEEE 802.11p/1609.4. In this paper, a new developed simulation tool based on NS-2 is introduced that provides a more realistic implementation of DSRC multiple channels and IEEE 1609.4 multichannel operation. The developed simulation tool has been tested through some simulation experiments.
The Power Analysis of Sparse Representation based on Laplace-Beltrami eigenfunctions

In localizing a group difference or a covariate of a factor of interest on structure model in invivo human brains using magnetic resonance imaging (MRI), various approaches have been used. For approaches that analyze the local differences voxel-wisely, voxel-based morphometry (VBM), deformation-based morphometry (DBM) and tensor-based morphometry (TBM) have been proposed [1, 7, 2]. In these methods, the local measure of brain tissue for a voxel is quantified. In VMB, the probability of certain tissue such as gray matter is used as a gray matter density that quantifies local integrity of gray matter of a corresponding voxel. In TBM, the local volume is quantified as Jacobian determinant of deformation vector field that deforms the template volume to an individual volume. Then the difference of local measures at each voxel usually is tested by a general linear model (GLM) while the family-wise error rate is controlled by statistical techniques such as false discovery rate (FDR) or random field theory (RFT).
Search-based detection of high-level model changes

Software models are iteratively refined, restructured and evolved. The detection and analysis of changes applied between two versions of a model are one of the most important tasks during evolution and maintenance activities. In this paper, we propose an approach to detect high-level model changes in terms of refactorings. Our approach takes as input an exhaustive list of possible refactorings, the initial model and revised model, and generates as output a list of detected changes representing a sequence of refactorings. A solution is defined as a combination of refactorings that should maximize as much as possible the similarity between the expected revised model and the generated model after applying the refactoring sequence on the initial model. Due to the huge number of possible refactoring combinations, a heuristic method is used to explore the space of possible solutions. To this end, we used and adapted genetic algorithm as global heuristic search. The validation results on various versions of real-world models taken from an open source project confirm the effectiveness of our approach.
Real -Time Facial Motion Tracking System Using Matlab

It is a well-known fact that the world has gone digital as the saying goes, as well, the universal shift from analog to digital electronics, which has been employed in our daily activities such asface detection and tracking has been an important and active research field. Face tracking has offers many applications especially in video surveillance, biometric identification, filming devices and so many other fields. This paper focuses on the implementation of a real-time facial motion tracking system using hardware-in-the-loop method of MATLAB application. The techniques employed in the actualization of this system involves: Computational techniques involving MATLAB, Code programming and implementation involving the microcontroller board and its respective environment (In this case, Arduino Uno microcontroller and theArduino IDE), Pulse-Width Modulation involving the interaction of the microcontroller board (Arduino Uno) and the servo motor. Power source analysis for the servo motor was done. The system was tested and deemed capable of achieving the aforementioned task of facial motion tracking in real-time.
The role of emotional dependence in the relationship between attachment and impulsive behavior

The emotional dependence has been related with the problems in the impulse control and with the preoccupied attachment style. The objectives of this study are to analyze the relation between the emotional dependence, attachment and the impulsive behavior, as well as, to analyze if these final two can predict the emotional dependence. Furthermore, it analyze if the emotional dependence mediate in the relation between attachment and impulsivity and, finally, it studies the differences of gender in the three mentioned variables. The sample is formed by 1533 teenagers (707 women and 826 men), with ages between 14-18 years old (M = 15.76; DT = 1.25). The results showed of positives relations between the emotional dependence and the parental permission, childhood trauma and impulsive behavior. Moreover, the impulsivity is positively related with the fact to avoid to be alone, asymmetric relation, the need to please others, parental permission and childhood trauma. In the same way, it proves how the parental permission, self-sufficiency and resentment against parents and childhood trauma can predict the emotional dependence. Finally, it observes how the relation between the attachment and the impulsive behavior is mediated with the emotional dependency and it appreciates differences between the three variables in gender basis.
Universal parallel numerical computing for 3D convection-diffusion equation with variable coefficients

A universal parallelized numerical approach for solving the three-dimensional (3D) convection diffusion equation with variable coefficients is proposed by combining the implicit difference method of Crank-Nicolson with alternating bar parallelization, which can be used to solve numerically any variation of the 3D convection diffusion equation. By virtue of bar parallelization and a multistep iteration technique, this approach trades off parallelism and accuracy. Its main merits are generality, absolute stability, acceptable space requirements and second-order accuracy. Its parallel implementation, named Codie4D, on a network of workstations using the MPI library uses the benefits of portability and applicability. Experimental results show that Codie4D has good runtime performance.
The Relationship between Morphological Awareness and Vocabulary Knowledge of Thai EFL Students

This study focuses on the relationship between morphological awareness and vocabulary knowledge of English among Thai EFL university students. All participants are taking English language as their major field in the universities situated at the lower northern region of Thailand. The morphological awareness identification test was employed to identify the linkage between morphological awareness and vocabulary gain Thai EFL learners. The test was divided into 2 parts: self-checking and morpheme identification. Fifty English vocabularies in intermediate and upper-intermediate level were used in the test in which the participants were requested to check whether they have seen the vocabularies in the test and also asked to break those vocabularies into morphemic units. The results showed that the participants possessed an adequate level of morphological awareness to break words into morphemes correctly even though they were unknown words of the participants. Additionally, the findings also revealed that there is no significant difference between male and female in acquiring morphological awareness of English and gaining English vocabularies.
Energy and connectivity performance of routing groups in multi-radio multi-hop networks

This paper explores the logical device aggregation of termi nals in future generation networks, where the availability of se veral different radio access techniques is integrated by mea ns of common radio resource management algorithms. In particula r, we investigate the creation of routing groups among adjacen t nodes, which might be beneficial in order to improve connectivity, decrease signaling overhead and increase transmis sion efficiency. A simple analytical approach is proposed, which allows the performance evaluation of device aggregation al gorithms. We measure the performance of establishing routing groups with special focus on two metrics of interest: the con nectivity of the nodes and the energy consumption. Within this framework, many detailed insights are obtained and pre sented throughout the paper. In particular, we focus on the e ffectiveness of these aggregation techniques in improving n etwork connectivity and on the cost incurred in getting the ext ra information needed to build and maintain group structures. In the final part of the paper, we provide simulation results whi ch further validate our discussion and highlight additional a spects that are to be considered in real scenarios. Our work is a first step in the investigation of the effectiveness of in-networ k aggregation of terminals equipped with multiple radio techno logies. The results derived in the paper are encouraging and motivate further research on the topic. keywords: routing groups, multiple radio technologies, radio technology diversity, radio access techniques, mobili ty exploitation, radio resource management, connectivity perf ormance, analytical evaluation.
Descriptive Statistics of the Genome: Phylogenetic Classification of Viruses

The typical process for classifying and submitting a newly sequenced virus to the NCBI database involves two steps. First, a BLAST search is performed to determine likely family candidates. That is followed by checking the candidate families with the pairwise sequence alignment tool for similar species. The submitter's judgment is then used to determine the most likely species classification. The aim of this article is to show that this process can be automated into a fast, accurate, one-step process using the proposed alignment-free method and properly implemented machine learning techniques. We present a new family of alignment-free vectorizations of the genome, the generalized vector, that maintains the speed of existing alignment-free methods while outperforming all available methods. This new alignment-free vectorization uses the frequency of genomic words (k-mers), as is done in the composition vector, and incorporates descriptive statistics of those k-mers' positional information, as inspired by the natural vector. We analyze five different characterizations of genome similarity using k-nearest neighbor classification and evaluate these on two collections of viruses totaling over 10,000 viruses. We show that our proposed method performs better than, or as well as, other methods at every level of the phylogenetic hierarchy. The data and R code is available upon request.
Technique of Coronary Transfer for TGA with Single Coronary Artery

An eight-day-old neonate was diagnosed with dextro-transposition of the great arteries, atrial septal defect, patent ductus arteriosus, and a single sinus origin of the coronary arteries. The single coronary artery originated from the left sinus (sinus 2), had a proximal left circumflex arterial branch, and passed anteriorly to the right side of the aorta, further branching into the right coronary and left anterior descending arteries. We successfully performed an arterial switch operation and coronary transfer by tube graft reconstruction with autologous aortic tissue to treat the dextro-transposition of the great arteries and atrial septal defect with a single-sinus origin of the coronary arteries.
Toward a fully autonomous hovercraft visually guided thanks to its own bio-inspired motion sensors

Based on a biorobotic approach developed in our laboratory over the past 25 years, we have designed and built several terrestrial and aerial vehicles controlling their position and speed on the basis of optic flow cues. In particular, in our project on the autonomous guidance of Micro-Air Vehicles (MAVs) in confined indoor and outdoor environments, we have developed a vision-based autopilot, which is called LORA III (Lateral Optic flow Regulation Autopilot, Mark III). This autopilot, based on the dual optic flow regulation, allows an air vehicle to travel along a corridor by automatically controlling both its speed and its clearance from the walls. The optic flow regulation is a feedback control based on an optic flow sensor, which strives to maintain a perceived optic flow at a constant set-point by adjusting a thrust. The LORA III autopilot consists of a dual optic flow regulator in which each regulator has its own optic flow set-point and controls the robot's translation in one degree of freedom: a bilateral optic flow regulator controls the robot's forward speed, while a unilateral optic flow regulator controls the side thrust, making the robot avoid the walls of the corridor. This autopilot draws on former studies which aimed to understand how a honeybee might be able to center along a corridor, to follow a single wall, and to adjust its speed according to the corridor width. Computer-simulated experiments have shown that a miniature hovercraft equipped with the LORA III autopilot can navigate along a straight or tapered corridor at a relatively high speed (up to 1m/s). The minimalistic visual system (comprised of only four pixels) may suffice for the hovercraft to be able to control both its clearance from the walls and its forward speed jointly, without ever measuring speed or distance, in a similar manner to what honeybees are thought to be capable of. The LORA robot is equipped with two rear thrusters and two lateral thrusters, in addition to the lift fan used to inflate the skirt. The hovercraft can move freely without any umbilicus, which makes its system identification and its own locomotion easier. However, the dynamics of all five motors turned out to be highly sensitive to the drop in supply voltage of the onboard Lithium Polymer (Li-Po) batteries. This is a critical issue for the identification of the robot's dynamical parameters. To perform an efficient system identification of the hovercraft's dynamics, we decided to confer upon each motor a dedicated controller that would make the four thrusters and the lift fan robust to any variations in the battery supply voltage.
3D Printing with Nucleic Acid Adhesives

By relying on specific DNA:DNA interactions as a “smart glue”, we have assembled microparticles into a colloidal gel that can hold its shape. This gel can be extruded with a 3D printer to generate centimeter size objects. We show four aspects of this material: (1) The colloidal gel material holds its shape after extrusion. (2) The connectivity among the particles is controlled by the binding behavior between the surface DNA and this mediates some control over the microscale structure. (3) The use of DNA-coated microparticles dramatically reduces the cost of DNA-mediated assembly relative to conventional DNA nanotechnologies and makes this material accessible for macroscale applications. (4) This material can be assembled under biofriendly conditions and can host growing cells within its matrix. The DNA-based control over organization should provide a new means of engineering bioprinted tissues.
Reformulating Branch Coverage as a Many-Objective Optimization Problem

Test data generation has been extensively investigated as a search problem, where the search goal is to maximize the number of covered program elements (e.g., branches). Recently, the whole suite approach, which combines the fitness functions of single branches into an aggregate, test suite-level fitness, has been demonstrated to be superior to the traditional single-branch at a time approach. In this paper, we propose to consider branch coverage directly as a many-objective optimization problem, instead of aggregating multiple objectives into a single value, as in the whole suite approach. Since programs may have hundreds of branches (objectives), traditional many-objective algorithms that are designed for numerical optimization problems with less than 15 objectives are not applicable. Hence, we introduce a novel highly scalable many-objective genetic algorithm, called MOSA (Many-Objective Sorting Algorithm), suitably defined for the many- objective branch coverage problem. Results achieved on 64 Java classes indicate that the proposed many-objective algorithm is significantly more effective and more efficient than the whole suite approach. In particular, effectiveness (coverage) was significantly improved in 66% of the subjects and efficiency (search budget consumed) was improved in 62% of the subjects on which effectiveness remains the same.
Fine-Scale Geographical Origin of an Insect Pest Invading North America

Invasive species may rapidly spread throughout new areas once introduced, which may potentially lead to serious damage to local fauna and flora. Information on geographical origins, introduction routes, and biology in native regions of such invasive species is of critical importance in identifying means of transport, preventing reintroduction, and establishing control/eradication methods. The plataspid stinkbug Megacopta cribraria, known as kudzu bug, recently invaded North America and now has become not only an agricultural pest of soybean but also a nuisance pest. Here we investigate the geographical origin of the invasive M. cribraria populations. Phylogeographical analyses based on 8.7 kb mitochondrial DNA sequences of the introduced and East Asian native Megacopta populations identified a well-supported clade consisting of the introduced populations and M. punctatissima populations in the Kyushu region of Japan, which strongly suggests that the invading M. cribraria populations are derived from a M. punctatissima population in the Kyushu region. Therefore, the region is proposed as a promising source of natural enemies for biological control of the invasive pest. Based on the phylogenetic information, relationship and treatment of the two Megacopta species are discussed.
First-order theory change systems and their dynamic semantics

Systems of rst-order theory change are motivated, developed, and shown to be strongly connected to revisable systems of dynamic semantics. Such systems are applicable in the analysis of dialogue contributions in a full account of information exchange. They remedy the following problem; \our approach to information change is eliminative rather than constructive. And we don't know yet how to do better than that. " A full theory of communication must incorporate the pragmatics of belief integration (or information change) in dialogue. Systems of theory change (TC) or \belief revision" ((Fuhrmann, 1994, GG ardenfors, 1986]) invoke transformations over sets of sentences (syntactic structures) expressed in propositional logic (the \AGM" approach). In contrast, systems of dynamic semantics (DS) typically employ transformations over sets of possibilities (semantical structures) of rst-order complexity. Cognitively relevant information processing is often argued to have at least the complexity of rst-order logic. Accordingly, predicates and variables are distinguished in the processing of information in natural language interpretation. In order to meet the demands of a model of communication , systems of theory change and their associated dynamic semantics must operate over structures expressed in rst-order logic. ) has been connned to the dynamics of propositional systems. The paper is organized as follows. Intuitions are given about a set of rst-order rationality postulates for contraction, covering quantiiers, names, variables, and identity. Some of the intuitions are formalized. Following this, a family of systems for rst-order theory change (FOTC) are sketched, along with their
Naming every individual in news video monologues

Naming every individual person appearing in broadcast news videos with names detected from the video transcript leads to better access of the news video content. In this paper, we approach this challenging problem with a statistical learning method. Two categories of information extracted from multiple video modalities have been explored, namely <i>features</i>, which help distinguish the true name of every person, as well as <i>constraints</i>, which reveal the relationships among the names of different persons. The person-naming problem is formulated into a learning framework which predicts the most likely name for each person based on the features, and refines the predictions using the constraints. Experiments conducted on ABC World New Tonight and CNN Headline News videos demonstrate that this approach outperforms a non-learning alternative by a large amount.
Real-time outdoor trail detection on a mobile robot

In this paper we present a reliable approach for real-time outdoor trail following and obstacle avoidance. The trail classification is done using an off-the-shelf webcam and a pitched 2D laser scanner on a KURT2 robot equipped with an Intel Centrino laptop. This simple setup enables us to follow given pathways of different kinds using a GPS receiver for rough orientation.