Miracle-dz/UniFAR-FTUs huggingface dataset:
High-throughput quantitative profiling of serum N-glycome by MALDI-TOF mass spectrometry and N-glycomic fingerprint of liver fibrosis.

BACKGROUND The use of MALDI-TOF mass spectrometry (MS) in quantitative glycan profiling has not been reported. In this study, we attempted to establish a high-throughput quantitative assay for profiling serum N-glycome, and we applied the new assay to identifying serum N-glycans for diagnosis of liver fibrosis and cirrhosis. METHODS N-glycans from whole serum proteins in 2 microL serum were released by enzymatic digestion, cleaned up by hydrophilic chromatography, and subsequently quantitatively profiled with a linear MALDI-TOF MS system, which was originally designed for quantitative proteomic profiling. Serum N-glycome profiles from 46 patients with chronic hepatitis B infection and with different degrees of liver fibrosis were examined. RESULTS The intra- and interassay CVs of peak intensities of the standard N-glycans were <8% and <17%, respectively. When the assay was applied to the analysis of serum N-glycome profiles, 17 peaks were found to be potential biomarkers for detection of liver fibrosis/cirrhosis. Linear regression analysis revealed that 4 peaks of 1341.5, 1829.7, 1933.3, and 2130.3 m/z (all P <0.005) had complementary value in detecting liver fibrosis and included them, but not any serological markers, in the diagnostic model. Leave-one-out cross-validation showed the diagnostic model could identify significant fibrosis (Ishak score > or = 3) and cirrhosis (Ishak score > or = 5), both at 85% accuracy. CONCLUSION This is the first study to illustrate the quantitative aspect of MALDI-TOF MS in N-glycome profiling and the first study to reveal the potential value of the serum N-glycan profile for identifying liver fibrosis.
Learning Phase Competition for Traffic Signal Control

Increasingly available city data and advanced learning techniques have empowered people to improve the efficiency of our city functions. Among them, improving urban transportation efficiency is one of the most prominent topics. Recent studies have proposed to use reinforcement learning (RL) for traffic signal control. Different from traditional transportation approaches which rely heavily on prior knowledge, RL can learn directly from the feedback. However, without a careful model design, existing RL methods typically take a long time to converge and the learned models may fail to adapt to new scenarios. For example, a model trained well for morning traffic may not work for the afternoon traffic because the traffic flow could be reversed, resulting in very different state representation. In this paper, we propose a novel design called FRAP, which is based on the intuitive principle of phase competition in traffic signal control: when two traffic signals conflict, priority should be given to one with larger traffic movement (i.e., higher demand). Through the phase competition modeling, our model achieves invariance to symmetrical cases such as flipping and rotation in traffic flow. By conducting comprehensive experiments, we demonstrate that our model finds better solutions than existing RL methods in the complicated all-phase selection problem, converges much faster during training, and achieves superior generalizability for different road structures and traffic conditions.
On Flow Profile Image for Video Representation

Video representation is a key challenge in many computer vision applications such as video classification, video captioning, and video surveillance. In this paper, we propose a novel approach for video representation that captures meaningful information including motion and appearance from a sequence of video frames and compacts it into a single image. To this end, we compute the optical flow and use it in a least squares optimization to find a new image, the so-called Flow Profile Image (FPI). This image encodes motions as well as foreground appearance information while background information is removed. The quality of this image is validated in activity recognition experiments and the results are compared with other video representation techniques such as dynamic images [1] and eigen images [2]. The experimental results as well as visual quality confirm that FPIs can be successfully used in video processing applications.
Enhancement Priming and Their Modulation by Cholinergic Effects of Attention and Emotion on Repetition

[PDF] [Full Text] [Abstract] , June 29, 2004; 101 (26): 9827-9832. PNAS A. Ishai, L. Pessoa, P. C. Bikle and L. G. Ungerleider Repetition suppression of faces is modulated by emotion [PDF] [Full Text] [Abstract] , August 1, 2004; 92 (2): 1241-1247. J Neurophysiol E. Eger, R.N. A. Henson, J. Driver and R. J. Dolan Attention BOLD Repetition Decreases in Object-Responsive Ventral Visual Areas Depend on Spatial [PDF] [Full Text] [Abstract] , August 1, 2005; 17 (8): 1245-1260. J. Cogn. Neurosci. P. Vuilleumier, S. Schwartz, S. Duhoux, R. J. Dolan and J. Driver Visual Memory: Suppressions and Enhancements Revealed by fMRI Selective Attention Modulates Neural Substrates of Repetition Priming and "Implicit"
Robust Learning from Noisy Side-information by Semidefinite Programming

Robustness recently becomes one of the major concerns among machine learning community, since learning algorithms are usually vulnerable to outliers or corruptions. Motivated by such a trend and needs, we pursue robustness in semi-definite programming (SDP) in this paper. Specifically, this is done by replacing the commonly used squared loss with the more robust L1-loss in the low-rank SDP. However, the resulting objective becomes neither convex nor smooth. As no existing algorithms can be applied, we design an efficient algorithm, based on majorization-minimization, to optimize the objective. The proposed algorithm not only has cheap iterations and low space complexity but also theoretically converges to some critical points. Finally, empirical study shows that the new objective armed with proposed algorithm outperforms state-of-the-art in terms of both speed and accuracy.
Variational Principles of Micromagnetics Revisited

We revisit the basic variational formulation of the minimization problem associated with the micromagnetic energy, with an emphasis on the treatment of the stray field contribution to the energy, which is intrinsically non-local. Under minimal assumptions, we establish three distinct variational principles for the stray field energy: a minimax principle involving magnetic scalar potential and two minimization principles involving magnetic vector potential. We then apply our formulations to the dimension reduction problem for thin ferromagnetic shells of arbitrary shapes.
A reversible allelic partition process and Pitman sampling formula

We introduce a continuous-time Markov chain describing dynamic allelic partitions which extends the branching process construction of the Pitman sampling formula in Pitman (2006) and the birth-and-death process with immigration of Karlin and McGregor (1967), in turn related to the celebrated Ewens sampling formula. A biological basis for the scheme is provided in terms of a population of individuals grouped into families, that evolves according to a sequence of births, deaths and immigrations. We investigate the asymptotic behaviour of the chain and show that, as opposed to the birth-and-death process with immigration, this construction maintains in the temporal limit the mutual dependence among the multiplicities. When the death rate exceeds the birth rate, the system is shown to have reversible distribution identified as a mixture of Pitman sampling formulae, with negative binomial mixing distribution on the population size. The population therefore converges to a stationary random configuration, characterised by a finite number of families and individuals.
Generalized Sampling on Graphs With Subspace and Smoothness Priors

We propose a framework for generalized sampling of graph signals that parallels sampling in shift invariant (SI) subspaces. This framework allows for arbitrary input signals which are not constrained to be bandlimited. Furthermore, the sampling and reconstruction filters may be different. We present design methods of the correction filter that compensate for these differences and lead to closed form expressions in the graph frequency domain. In this study, we consider two priors on graph signals: The first is a subspace prior, where the signal is assumed to lie in a periodic graph spectrum (PGS) subspace. The PGS subspace is proposed as a counterpart of the SI subspace used in standard sampling theory. The second is a smoothness prior that imposes a smoothness requirement on the graph signal. We suggest the use of recovery techniques when the recovery filter can be optimized and under a setting in which a predefined filter must be used. Sampling is performed in the graph frequency domain, which is a counterpart of “sampling by modulation” used in SI subspaces. We compare our approach with existing sampling techniques on graph signal processing. The effectiveness of the proposed generalized sampling approach is validated numerically through several experiments.
Temperature study of the dielectric polarization effects of capacitive RF MEMS switches

This paper investigates both theoretically and experimentally the dielectric charging effects of capacitive RF microelectromechanical system switches with silicon nitride as dielectric layer. Dielectric charging caused by charge injection under voltage stress was observed. The amphoteric nature of traps and its effect on the switch operation were confirmed under both positive and negative control voltages. It has been confirmed that charging is a complicated process, which can be better described through the stretched exponential relaxation. This mechanism is thermally activated with an activation energy being calculated from the temperature dependence of the capacitance transient response. The charging mechanism, which is responsible for the pull-out voltage and the device failure, is also responsible for the temperature-induced shift of the capacitance minimum bias.
Multisource Single-Tree Inventory in the Prediction of Tree Quality Variables and Logging Recoveries

Abstract: The stem diameter distribution, stem form and quality information must be measured as accurately as possible to optimize cutting. For a detailed measurement of the stands, we developed and demonstrated the use of a multisource single-tree inventory (MS-STI). The two major bottlenecks in the current airborne laser scanning (ALS)-based single-tree-level inventory, tree detection and tree species recognition, are avoided in MS-STI. In addition to airborne 3D data, such as ALS, MS-STI requires an existing tree map with tree species information as the input information. In operational forest management, tree mapping would be carried out after or during the first thinning. It should be highlighted that the tree map is a challenging prerequisite, but that the recent development in mobile 2D and 3D laser scanning indicates that the solution is within reach. In our study, the tested input tree map was produced by terrestrial laser scanning (TLS) and by using a Global Navigation Satellite System. Predictors for tree quality
CCR2 Positive Exosome Released by Mesenchymal Stem Cells Suppresses Macrophage Functions and Alleviates Ischemia/Reperfusion-Induced Renal Injury

Mesenchymal stem cells (MSCs) derived exosomes have been shown to have protective effects on the kidney in ischemia/reperfusion-induced renal injury. However, the key components in the exosomes and their potential mechanisms for the kidney protective effects are not well understood. In our current study, we focused on the abundant proteins in exosomes derived from MSCs (MSC-exo) and found that the C-C motif chemokine receptor-2 (CCR2) was expressed on MSC-exo with a high ability to bind to its ligand CCL2. We also proved that CCR2 high-expressed MSC-exo could reduce the concentration of free CCL2 and suppress its functions to recruit or activate macrophage. Further, knockdown of CCR2 expression on the MSC-exo greatly abolished these effects. Finally, we also found that CCR2 knockdown impaired the protective effects of MSC-exo for the renal ischemia/reperfusion injury in mouse. The results indicate that CCR2 expressed on MSC-exo may play a key role in inflammation regulation and renal injury repair by acting as a decoy to suppress CCL2 activity. Our study may cast new light on understanding the functions of the MSC-exo and these receptor proteins expressed on exosomes.
Distributing Data Rate Using Cooperative Channel Assignment for Multi-Rate Wireless Mesh Networks

Wireless Mesh Networks (WMNs) have emerged to provide cost-effective broadband Internet accesses. Today's IEEE 802.11 PHY and MAC specifications support multi-channel and multi-rate capabilities. Designing an efficient channel assignment protocol utilizing available channels and data rates is a hot issue to leverage the network capacity. In multi-rate networks, low-rate links severely decrease the capacity of high-rate links, known as performance anomaly. In this paper, we design a Cooperative Channel Assignment (CoCA) protocol to address the performance anomaly in WMNs. For the channel assignment of family architecture, CoCA utilizes the Estimated Delivery Time (EDT) metric and the balancing algorithm. With the EDT metric, CoCA separates different rate links via multiple channels. By using the balancing algorithm, CoCA also increases throughput fairness. Our simulation results show that CoCA outperforms the existing well-known channel assignment protocols for WMNs.
Demonstrating the importance of multi-wave assessment of peer victimization

" " " ii" " " " iii" ABSTRACT Christopher S. Sheppard: Demonstrating the Importance of Multi-wave Assessment of Peer Victimization (Under the direction of Mitchell J. Prinstein) The current study assessed the extent to which chronic victimization is a unique type of peer victimization. This was examined using stability analyses, trajectory analyses, and comparisons of victimization and adjustment outcomes both concurrently and longitudinally over a 3-year period. A community sample of 652 adolescent (50% females) in Grades 6-8 participated in the study. Participants completed measures of peer-reported victimization and associated adjustment correlates (both self and peer-report) at three time points. Peer victimization was not stable for all victims, and four trajectories of victimization were identified: chronic, high decreasing, low increasing, and low stable. The chronic victimization trajectory was associated with worse overall outcomes than the other trajectories. Results provided additional support for the idea that the chronicity of peer victimization influences the impact of victimization on youth, and that a single time point assessment of victimization is insufficient to capture the nuances of this construct.
Interactive image-based model building for handheld devices

Models of objects in 3D and their creation process are central elements for a variety of applications in Augmented Reality. In this paper we extend our previous work in the area of interactive in-situ model building for handhelds and in particular we study two handheld devices in the context of 3D feature selection. In a controlled experiment we compare two interactive methods to specify 3D vertices and discuss the findings of our results and identify design recommendations. We further extend the system by incorporating an object detection process which starts and/or re-initializes the tracker when lost creating a more fluid interaction process.
Real-time sound signal acquisition based on robot auditory system

Signal acquisition based on multiple sensors is widely used in many applications, especially in robot with binaural auditory system. This paper provides one recording procedure with dual-caching and multi-thread technologies for unlimited time and synchronized sound signal collecting. Besides, in order to solve time delay in multiple recording, timer must be taken in system procedure. Furthermore, use normalized method to handle raw PCM (Pulse Code Modulation) before transmitted to MATLAB; at last, amount of signal data fragment without sound signal will be cut with dual-threshold endpoint detection method. Through experiments, signal segment containing valid sound data can be well extracted, in a large extent which can optimize the redundant data.
Fork Bomb Attack Mitigation by Process Resource Quarantine

A fork bomb attack is a denial of service attack. An attacker generates many processes rapidly, exhausting the resources of the target computer systems. There are several previous work to detect and remove the processes that cause fork bomb attacks. However, the operating system with the previous methods have the risks to terminate inappropriate processes that do not fork bomb processes. In this paper, we propose a new method that named process resource quarantine. With the proposed method, the operating systems don't terminate the detected fork bomb processes. Instead of the termination, the operating systems make resource limitations for the detected processes and inspect them periodically. We implemented the proposed method on Linux kernel and executed several evaluation experiments. The results show that the proposed method is effective for fork bomb attacks mitigation.
A Fast Algorithm for Balanced Graph Clustering

Scalability problem is a long-lasting challenge for both information visualization and graph drawing communities. Available graph visualization techniques could perform well for small or medium size graphs but they are rarely able to handle very large and complex graphs. One of effective approach to solve this problem is to employ graph abstraction; that is to hierarchically partitioning the complete graph into a clustered graph. A graph visualization technique is then applied to display the abstract view of this clustered graph with partially displayed detail of one or a few sub-graphs where the user is currently focusing on. This reduces the complexity of display and makes it easier for users to interpret, perceive and navigate the large scale information. In this paper, we propose a graph clustering method which can quickly discover the community structure embedded in large graphs and partition the graph into densely connected sub-graphs. The proposed algorithm can not only run fast, but also achieve a consistent partitioning result in which a graph is divided into a set of clusters of the similar size in terms of their visual complexity and the number of nodes and edges. In addition, we also provide a mechanism to partition very dense graphs in which the number of edges is much larger than the number of nodes.
Fuzzy logic controller based distribution static compensator

This paper presents distribution static compensator (DSTATCOM) using a Takagi-Sugeno (TS) fuzzy logic controller (FLC) for harmonic elimination, power factor correction, load balancing and voltage regulation. The TS fuzzy logic controller is based on linguistic variables which eliminates the need of a mathematical model of the DSTATCOM. A three phase insulated gate bipolar transistors (IGBTs) based current controlled voltage source converter (CC-VSC) is employed as a DSTATCOM. Two FLCs are used in proposed control algorithm. The DC link voltage of a DSTATCOM and amplitude of phase voltages are used as an input signals for the FLC. The PWM current controller is used to generate switching signals for CC-VSC. Results have been obtained in MATLAB simulink environment to demonstrate the efficacy of proposed control algorithm as a harmonic eliminator, a power factor corrector, a load balancer and as a voltage regulator.
Cloning of a chromosomal gene required for phage infection of Lactococcus lactis subsp. lactis C2

A phage-resistant mutant with a defect in a membrane component required for phage infections in Lactococcus lactis subsp. lactis C2 was transformed with a chromosomal library of the wild-type, phage-sensitive strain. Of the 4,200 transformants screened for phage sensitivity, three were positively identified as phage sensitive. A cause-and-effect relationship between the cloned chromosomal fragments and the phage-sensitive phenotype was established on the basis of the following two criteria: (i) the frequency of loss of the cloned fragments in the absence of antibiotic selection pressure correlated with the frequency of loss of phage sensitivity; and (ii) phage sensitivity was transferred to 100% of recipient, phage-resistant cells transformed with the cloned fragment. The cloned chromosomal DNA from the three independent isolates was physically mapped with restriction endonucleases. The sizes of the cloned fragments were 9.6, 11.8, and 9.5 kb. Each fragment contained an identical stretch of DNA common to all three, which was 9.4 kb. The gene that conferred phage sensitivity was localized by subcloning to a 4.5-kb region. Further subcloning indicated that a single EcoRI site within the 4.5-kb region must lie within the gene or its promoter. The required 4.5-kb region was sequenced and found to code for one partial and two complete open reading frames. The gene required for complementation was functionally mapped by Tn5 mutagenesis and localized to one of the two complete open reading frames, which was designated pip (an acronym for phage infection protein). pip is 2,703 bases in length. Potential promoters start 206 and 212 bases upstream of the open reading frame. A ribosome binding site and a seven-base spacer precede the GTG (Val) translation initiation codon. The amino acid sequence deduced from the gene has 901 residues and an M(r) of 99,426. Hydropathy analysis revealed four to six potential membrane-spanning regions, one near the amino terminus and the others at the extreme carboxyl terminus. The amino terminus has characteristics of a signal sequence. The putative protein would have a 650-residue, central polar domain.
Building a learner corpus for Russian

In this paper we describe an open learner corpus of Russian. The Russian Learner Corpus (RLC) is the ﬁrst corpus with clear distinction between foreign language learners and heritage speakers. We discuss the structure of the corpus, its development and the annotation principles. This paper describes the platform of the RLC which combines online tools for text uploading, processing, error annotation and corpus search.
An enhanced authentication scheme in GLOMONETs

The anonymity, mutual authentication and low computation cost are the three important requirements for authentication of global mobility networks (GLOMONETs). Based on these three requirements, many authentication schemes have been proposed. In [9], an enhanced authentication scheme called Enhanced Authentication with Anonymity for Roaming Service (EAARS) has been proposed and it is claimed that the scheme can guarantee anonymity of mobile users and establish a secure session key for mobile users. In this paper, we discover that the scheme cannot provide user anonymity against malicious mobile users as claimed. We analyze the vulnerabilities of the EAARS scheme and propose an improved authentication scheme. The proposed scheme can not only keep the merits of the EAARS scheme, but also provide user anonymity and avoids session key compromise. Our numerical results by Colored Petri Nets (CPN) modeling show that our proposed scheme is more secure with ability to avoid these threats.
The Role of Formalisms

P. Alencar University of Waterloo, Canada A.M. Dearden University of York, UK J.S. Dong DIT, CSIRO, Australia D.J. Duke University of York, UK G.P. Faconti CNUCE-CNR, Pisa, Italy P. Girard LISI/ENSMA, Futuroscope, France M.D. Harrison University of York, UK J.K. Hyde Middlesex University, UK P. Markopoulos QMW College, London, UK N. Merriam University of York, UK F. Paterno’ CNUCE-CNR, Pisa, Italy S. Reeves University of Waikato, New Zealand J.C. Torres University of Granada, Spain J. Wesson University of Port Elizabeth, South Africa