Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular basis of antibody binding to mucin glycopeptides in lung cancer

Glycopeptides bearing Tn epitopes are emerging targets for cancer diagnosis and immunotherapy. In this study, we analyzed membrane proteins containing O-glycosylated tandem repeat (TR) sequences in lung cancer patients of different types and stages, using gene microarray data in public domain. The expression of Tn and glycopeptide epitopes on the surface of lung cancer cell lines were studied by monoclonal IgG antibodies 14A, 16A, and B72.3. The binding of mAbs to synthetic glycopeptides were studied by surface plasmon resonance. Nine mucin mRNAs were found to be expressed in lung cancer patients but at similar level to healthy individuals. At protein level, a glycopeptide epitope on cancer cell surface is preferably recognized by mAb 16A, as compared to peptide-alone (14A) or sugar-alone epitopes (B72.3). 14A and 16A favor clustered TR containing more than three TR sequences, with 10-fold lower Kd than two consecutive TR. B72.3 preferrably recognized clustered sialyl-Tn displayed on MUC1 but not other O-glycoproteins, with 100-fold stronger binding when MUC1 is transfected as a sugar carrier, while the total sugar epitopes remain unchanged. These findings indicate that clusters of both TR backbones and sugars are essential for mAb binding to mucin glycopeptides. Three rules of antibody binding to mucin glycopeptides at molecular level are presented here: first, the peptide backbone of a glycopeptide is preferentially recognized by B cells through mutations in complementarity determining regions (CDRs) of B cell receptor, and the sugar-binding specificity is acquired through mutations in frame work of heavy chain; secondly, consecutive tandem repeats (TR) of peptides and glycopeptides are preferentially recognized by B cells, which favor clustered TR containing more than three TR sequences; thirdly, certain sugar-specific B cells recognize and accommodate clustered Tn and sialyl-Tn displayed on the surface of a mucin but not other membrane proteins.
Extending the punctuation module for european portuguese

This paper describes our recent work on extending the punctuation module of automatic subtitles for Portuguese Broadcast News. The main improvement was achieved by the use of prosodic information. This enabled the extension of the previous module which covered only full stops and commas, to cover question marks as well. The approach uses lexical, acoustic and prosodic information. Our results show that the latter is relevant for all types of punctuation. An analysis of the results also shows what type of interrogative is better dealt with by our method, taking into account the specificities of Portuguese. This may lead to different results for different types of corpora, depending on the types of interrogatives that are more frequent.
A Randomizing Butterfly Transformation Useful in Block Matrix Computations

19 The RBT approach also suggests other interesting avenues for work. Randomization appears to ooer new strategies for linear systems solution that are well-suited to high-performance computers. High-performance machines tend to favor algorithmic simplicity. The RBT trades naive time complexity (the number of`steps' performed by a sequential algorithm) for algorithmic simplicity, and this may give better performance.
The period sensitivity and modal sensitivity of optical fiber force sensor based on mechanical induced ultra-long period fiber grating

In this study, a mechanical induced ultra-long period fiber grating (MULPFG) with periods of several millimeter is demonstrated. The periodic grooved plate used to create the grating in the single-mode fiber (SM600) is the rectangular grooved plate which is fabricated by the 3D printer. The experimental results clearly show that the MULPFGs with the longer grating period are more sensitive to the perturbation force than the shorter grating period. The force sensitivity to the resonance wavelengths of the MULPFG with higher modes are more sensitive than the lower modes. The fabricated force sensor based on MULPFG by using the 3D printer is robust and stable in operation and exhibits a high-sensitivity of ∼ 0.470 nm/N. It offers the advantages of being inexpensive, erasable, and reconfigurable as well.
Multi-objective evolutionary fuzzy cognitive maps for decision support

This paper proposes an extension of genetically evolved fuzzy cognitive maps (GEFCMs) used for decision-making, aiming at increasing their reliability and overcoming its main weakness which lies with the recalculation of weights corresponding to more than one concept every time a new multiple scenario is introduced. A new evolutionary approach is proposed to support multi-objective decision-making based on the introduction of a dedicated genetic algorithm (GA), which is responsible for finding an optimal weight matrix that satisfies two or more activation levels among the participating concept nodes. This evolutionary methodology is very appealing since it offers the optimal solution without a problem-solving strategy once the requirements are defined
Estimation of PM 10 concentrations over Seoul using multiple empirical models with AERONET and MODIS data collected during the DRAGON-Asia campaign

Abstract. The performance of various empirical linear models to estimate the concentrations of surface-level particulate matter with a diameter less than 10 μm (PM10) was evaluated using Aerosol Robotic Network (AERONET) sun photometer and Moderate-Resolution Imaging Spectroradiometer (MODIS) data collected in Seoul during the Distributed Regional Aerosol Gridded Observation Network (DRAGON)-Asia campaign from March to May 2012. An observed relationship between the PM10 concentration and the aerosol optical depth (AOD) was accounted for by several parameters in the empirical models, including boundary layer height (BLH), relative humidity (RH), and effective radius of the aerosol size distribution (Reff), which was used here for the first time in empirical modeling. Among various empirical models, the model which incorporates both BLH and Reff showed the highest correlation, which indicates the strong influence of BLH and Reff on the PM10 estimations. Meanwhile, the effect of RH on the relationship between AOD and PM10 appeared to be negligible during the campaign period (spring), when RH is generally low in northeast Asia. A large spatial dependency of the empirical model performance was found by categorizing the locations of the collected data into three different site types, which varied in terms of the distances between instruments and source locations. When both AERONET and MODIS data sets were used in the PM10 estimation, the highest correlations between measured and estimated values (R = 0.76 and 0.76 using AERONET and MODIS data, respectively) were found for the residential area (RA) site type, while the poorest correlations (R = 0.61 and 0.68 using AERONET and MODIS data, respectively) were found for the near-source (NS) site type. Significant seasonal variations of empirical model performances for PM10 estimation were found using the data collected at Yonsei University (one of the DRAGON campaign sites) over a period of 17 months including the DRAGON campaign period. The best correlation between measured and estimated PM10 concentrations (R = 0.81) was found in winter, due to the presence of a stagnant air mass and low BLH conditions, which may have resulted in relatively homogeneous aerosol properties within the BLH. On the other hand, the poorest correlation between measured and estimated PM10 concentrations (R = 0.54) was found in spring, due to the influence of the long-range transport of dust to both within and above the BLH.
Large-Scale Plantlet Conversion and Ex Vitro Transplantation Efficiency of Siberian Ginseng by Bioreactor Culture

To achieve large-scale low-cost ex vitro acclimatization of Siberian ginseng plants, heart- and torpedo-shaped secondary somatic embryos (SEs) induced from germinated SEs on agar medium were collected and then inoculated to 10-l bubble column bioreactor, respectively. For plantlet conversion, inoculation of torpedo-shaped secondary SEs was more effective than heart-shaped SEs. TS2 (culture of torpedo-shaped SEs in a bioreactor with a 2-week subculture interval) plantlets had a higher root number and leaf number and larger leaf area than did HS3 (culture of heart-shaped SEs in a bioreactor with a 3-week subculture interval) and HS2 (culture of heart-shaped SEs in a bioreactor with a 2-week subculture interval) plantlets. Of these converted plants, TS2 plantlets had higher survival rate (83.7%) and growth characteristics after transplantation in a simple shed covered with a 50% sunshade net only for 6 months. TS2 plantlets also showed significantly lower H2O2 content and significantly increased superoxide dismutase (SOD), glutathione peroxidase (GPX), and glutathione transferase (GST) expression levels as compared to HS2 plants when exposure to ex vitro conditions.
Phase transitions and random quantum satisfiability

Princeton Center for Theoretical Science, Princeton University, Princeton, NJ 08544(Dated: March 11, 2009)Alongside the e ort underway to build quantum computers, it is important to better understandwhich classes of problems they will nd easy and which others even they will nd intractable. Westudy random ensembles of the QMA
Galactic Spiral Shocks with Thermal Instability

Using one-dimensional hydrodynamic simulations including interstellar heating, cooling, and thermal conduction, we investigate nonlinear evolution of gas flow across galactic spiral arms. We model the gas as a non-self-gravitating, unmagnetized fluid and follow its interaction with a stellar spiral potential in a local frame comoving with the stellar pattern. Initially uniform gas with density n0 in the range 0.5 cm −3 ⩽ n0 ⩽ 10 cm −3 rapidly separates into warm and cold phases as a result of thermal instability (TI) and also forms a quasi-steady shock that prompts phase transitions. After saturation, the flow follows a recurring cycle: warm and cold phases in the interarm region are shocked and immediately cool to become a denser cold medium in the arm; postshock expansion reduces the mean density to the unstable regime in the transition zone and TI subsequently mediates evolution back into warm and cold interarm phases. For our standard model with n0 = 2 cm −3, the gas resides in the dense arm, thermally unstable transition zone, and interarm region for 14%, 22%, and 64% of the arm-to-arm crossing time, respectively. These regions occupy 1%, 16%, and 83% of the arm-to-arm distance, respectively. Gas at intermediate temperatures (i.e., neither warm stable nor cold states) represents ~25%-30% of the total mass, similar to the fractions estimated from H I observations (larger interarm distances could reduce this mass fraction, whereas other physical processes associated with star formation could increase it). Despite transient features and multiphase structure, the time-averaged shock profiles can be matched to that of a diffusive isothermal medium with temperature 1000 K (which is < Twarm) and a “particle” mean free path of l0 = 100 pc . Finally, we quantify numerical conductivity associated with translational motion of phase-separated gas on the grid and show that convergence of numerical results requires the numerical conductivity to be comparable to or smaller than the physical conductivity.
The nested blocks and guidelines model

We propose the nested blocks and guidelines model for the design and validation of visualization systems. The nested blocks and guidelines model extends the previously proposed four-level nested model by adding finer grained structure within each level, providing explicit mechanisms to capture and discuss design decision rationale. Blocks are the outcomes of the design process at a specific level, and guidelines discuss relationships between these blocks. Blocks at the algorithm and technique levels describe design choices, as do data blocks at the abstraction level, whereas task abstraction blocks and domain situation blocks are identified as the outcome of the designer’s understanding of the requirements. In the nested blocks and guidelines model, there are two types of guidelines: within-level guidelines provide comparisons for blocks within the same level, while between-level guidelines provide mappings between adjacent levels of design. We analyze several recent articles using the nested blocks and guidelines model to provide concrete examples of how a researcher can use blocks and guidelines to describe and evaluate visualization research. We also discuss the nested blocks and guidelines model with respect to other design models to clarify its role in visualization design. Using the nested blocks and guidelines model, we pinpoint two implications for visualization evaluation. First, comparison of blocks at the domain level must occur implicitly downstream at the abstraction level; second, comparison between blocks must take into account both upstream assumptions and downstream requirements. Finally, we use the model to analyze two open problems: the need for mid-level task taxonomies to fill in the task blocks at the abstraction level and the need for more guidelines mapping between the algorithm and technique levels.
Risky Module Estimation in Safety-Critical Software

Software used in safety-critical system must have high dependability. Software testing and V&V (Verification and Validation) activities are very important for assuring high software quality. If we can predict the risky modules in safety-critical software, testing activities and regulation activities can be applied to them more intensively. In this paper, we classify the estimated risk classes which can be used for deep testing and V&V. We predict the risk class for each module using support vector machines. We can consider that the modules classified to risk class 5 or 4 are more risky than others relatively. For all classification error rates, we expect that the results can be useful and practical for software testing, V&V, and activities for regulatory reviews. In the future works, to improve the practicality, we will have to investigate other machine learning algorithms and datasets.
Caveolin limits membrane microdomain mobility and integrin-mediated uptake of fibronectin-binding pathogens

Staphylococcus aureus, which is a leading cause of hospital-acquired infections, binds via fibronectin to integrin α5β1, a process that can promote host colonization in vivo. Integrin engagement induces actin cytoskeleton rearrangements that result in the uptake of S. aureus by non-professional phagocytic cells. Interestingly, we found that fibronectin-binding S. aureus trigger the redistribution of membrane microdomain components. In particular, ganglioside GM1 and GPI-linked proteins were recruited upon integrin β1 engagement, and disruption of membrane microdomains blocked bacterial internalization. Several membrane-microdomain-associated proteins, such as flotillin-1 and flotillin-2, as well as caveolin, were recruited to sites of bacterial attachment. Whereas dominant-negative versions of flotillin-2 did not affect bacterial attachment or internalization, cells deficient for caveolin-1 (Cav1−/−) showed increased uptake of S. aureus and other Fn-binding pathogens. Recruitment of membrane microdomains to cell-associated bacteria was unaltered in Cav1−/− cells. However, fluorescence recovery after photobleaching (FRAP) revealed an enhanced mobility of membrane-microdomain-associated proteins in the absence of caveolin-1. Enhanced membrane microdomain mobility and increased uptake of S. aureus was repressed by expression of wild-type caveolin-1, but not caveolin-1 G83S, which harbors a point mutation in the caveolin scaffolding domain. Similarly, chemical or physical stimulation of membrane fluidity led to increased uptake of S. aureus. These results highlight a crucial role for caveolin-1 in negative regulation of membrane microdomain mobility, thereby affecting endocytosis of bacteria-engaged integrins. This process might not only limit host cell invasion by integrin-binding bacterial pathogens, but might also be physiologically relevant for integrin-mediated cell adhesion.
Sequence classification: A regression based generalization of two-stage clustering

Two-stage clustering based approaches has been used for sequence classification. However, certain parameters of these process are either hand picked or found through exhaustive searches. In this paper we propose a simple regression based approach, derived from parameter values found in a previous study, which generalizes the method to find values of three different parameters through proposed equations. We tested the applicability of our method on eight UCR sequence datasets and found our method to be comparable with hand picked approaches and better than single clustering based approaches.
Mutations in the K+/Cl− Cotransporter Gene kazachoc (kcc) Increase Seizure Susceptibility in Drosophila

During a critical period in the developing mammalian brain, there is a major switch in the nature of GABAergic transmission from depolarizing and excitatory, the pattern of the neonatal brain, to hyperpolarizing and inhibitory, the pattern of the mature brain. This switch is believed to play a major role in determining neuronal connectivity via activity-dependent mechanisms. The GABAergic developmental switch may also be particularly vulnerable to dysfunction leading to seizure disorders. The developmental GABA switch is mediated primarily by KCC2, a neuronal K+/Cl− cotransporter that determines the intracellular concentration of Cl− and, hence, the reversal potential for GABA. Here, we report that kazachoc (kcc) mutations that reduce the level of the sole K+/Cl− cotransporter in the fruitfly Drosophila melanogaster render flies susceptible to epileptic-like seizures. Drosophila kcc protein is widely expressed in brain neuropil, and its level rises with developmental age. Young kcc mutant flies with low kcc levels display behavioral seizures and demonstrate a reduced threshold for seizures induced by electroconvulsive shock. The kcc mutation enhances a series of other Drosophila epilepsy mutations indicating functional interactions leading to seizure disorder. Both genetic and pharmacological experiments suggest that the increased seizure susceptibility of kcc flies occurs via excitatory GABAergic signaling. The kcc mutants provide an excellent model system in which to investigate how modulation of GABAergic signaling influences neuronal excitability and epileptogenesis.
Automatic Signature Recognition and Verification Using Principal Components Analysis

The fact that the signature is widely used as a means of personal verification emphasizes the need for an automatic recognition system. Recognition can be performed either offline or online based on the application. Online systems use dynamic information of a signature captured at the time the signature is made. Offline systems work on the scanned image of a signature. In this paper we present a method for Offline recognition and verification signatures using Principal components analysis. The proposed method consists of image prepossessing , feature extraction, evaluate the Principal components analysis for the extracted feature and the identification step. The identification step contain tow process recognition and verification. In the recognition process we use the K nearest-neighbours classifier and in the verification process we use the neural network classifier.
MOBILITY MODELING AND MANAGEMENT IN WIRELESS NETWORKS

MOBILITY MODELING AND MANAGEMENT IN WIRELESS NETWORKS Zainab R. Zaidi, Ph.D. George Mason University, 2002 Dissertation Director: Dr. Brian L. Mark We propose to investigate robust estimation algorithms for tracking the location and dynamic motion of mobile units in wireless cellular and ad hoc networks. The underlying mobility model that we have assumed, for both types of wireless network, is based on a dynamic linear system driven by a discrete command process that determines the mobile unit’s acceleration. The command process is modeled as a semi-Markov process over a finite set of acceleration levels. Our proposed tracking algorithm for cellular network is based on an arrangement of averaging filter and modified Kalman filters in combination with an efficient hidden semi-Markov model (HSMM) estimation algorithm to estimate the parameters of the command process. Numerical results show that the proposed tracking algorithm performs accurately over a wide range of mobility parameter values. Moreover, future movements of the mobile nodes can be predicted using the prediction model. In an ad hoc wireless network, connectivity is determined by the physical locations and transmission ranges of the mobile units. In effect, user mobility causes the topology of an ad hoc network to change dynamically over time, which complicates the important tasks of routing and flow control. In our proposed mobility estimation scheme for ad hoc networks, the mobile nodes track their positions using pilot signal strength measurements from neighboring nodes. Mobility tracking is performed using an extended Kalman filter preceded by an efficient averaging filter. We have also developed a local coordinate system for ad hoc networks using relative distances between the mobile nodes. Different local systems can be easily related to each other to form a network coordinate system. Our numerical results show that the mobility tracking scheme performs effectively and can enhance routing performance in ad hoc networks. The mobility tracking and prediction model can be used to develop mobilitybased algorithms for adaptive resource allocation in both types of networks. We propose to develop dynamic channel reservation and call admission control algorithms for cellular networks that exploit the information provided by our estimation algorithm. We shall also develop cluster-based routing algorithms in ad hoc networks that can achieve superior performance by utilizing our mobility estimation and prediction model. Finally, we shall validate our mobility estimation model using real data from a CDMA cellular system and investigate issues relevant to real-time practical mobility tracking problem. CHAPTER
Evaluation of RT-PCR for detection of Sudanese serotypes of epizootic hemorrhagic disease virus serogroup

Epizootic hemorrhagic disease (EHD) is an infectious non-contagious disease of deer and cattle. At least 2 serotypes of EHD virus, designated EHDV-4 and EHDV-318, are enzootic in the Sudan. To facilitate clinical disease investigation and control of the disease a rapid diagnostic assay is urgently needed. A reverse transcriptase (RT) polymerase chain reaction (RT-PCR) protocol, previously reported for detection of the United States EHDV serotypes 1 and 2 ribonucleic acid (RNA) in cell culture and clinical specimens, was evaluated for detection of the Sudanese EHDV serotypes. RNA from Sudanese isolates of EHDV-4 and EHDV-318, propagated in cell cultures, were detected by the described RT-PCR-based assay. The specific 387 bp PCR products were visualized on ethidium bromide-stained agarose gel. Amplification product was not detected when the EHDV RT-PCR-based assay was applied to RNA from Sudanese bluetongue virus (BTV) serotype 4 (BTV-4) or total nucleic acid extracts from uninfected BHK-21 cells. The scientific observations reported in this paper indicated that the previously described EHDV RT-PCR assay could be applied for detection of EHDV infection among the Sudanese susceptible animal populations.