Miracle-dz/UniFAR-FTUs huggingface dataset:
Inhibition of hybrid- and complex-type glycosylation reveals the presence of the GlcNAc transferase I-independent fucosylation pathway.

A mammalian N-acetylglucosamine (GlcNAc) transferase I (GnT I)-independent fucosylation pathway is revealed by the use of matrix-assisted laser desorption/ionization (MALDI) and negative-ion nano-electrospray ionization (ESI) mass spectrometry of N-linked glycans from natively folded recombinant glycoproteins, expressed in both human embryonic kidney (HEK) 293S and Chinese hamster ovary (CHO) Lec3.2. 8.1 cells deficient in GnT I activity. The biosynthesis of core fucosylated Man5GlcNAc2 glycans was enhanced in CHO Lec3.2. 8.1 cells by the alpha-glucosidase inhibitor, N-butyldeoxynojirimycin (NB-DNJ), leading to the increase in core fucosylated Man5GlcNAc2 glycans and the biosynthesis of a novel core fucosylated monoglucosylated oligomannose glycan, Glc1Man7GlcNAc2Fuc. Furthermore, no fucosylated Man9GlcNAc2 glycans were detected following inhibition of alpha-mannosidase I with kifunensine. Thus, core fucosylation is prevented by the presence of terminal alpha1-2 mannoses on the 6-antennae but not the 3-antennae of the trimannosyl core. Fucosylated Man5GlcNAc2 glycans were also detected on recombinant glycoprotein from HEK 293T cells following inhibition of Golgi alpha-mannosidase II with swainsonine. The paucity of fucosylated oligomannose glycans in wild-type mammalian cells is suggested to be due to kinetic properties of the pathway rather than the absence of the appropriate catalytic activity. The presence of the GnT I-independent fucosylation pathway is an important consideration when engineering mammalian glycosylation.
Do Physiological Responses and Personality Traits Relate to Auditory Perceptual Learning in Musicians and Non-Musicians?

Peripheral nervous system can influence learning and memory functions by increasing the activity level (‘arousal’) of the system with increasing task difficulty. Several studies show that musicians discriminate auditory stimuli more effectively both neurally and behaviourally. Yet, the effects of individual peripheral nervous responses or personality during auditory learning have not studied in musicians. In this paper, we show preliminary evidence on physiological differences between musicians and non-musicians during auditory perceptual learning. Results suggest that musicians have a higher change in skin temperature and heart rate between resting state and active auditory discrimination than non-musicians. Musicians had also higher levels of approach (vs withdrawal) related personality trait that correlated with their skin conductance level changes. Approach tendency correlated with respiration in non-musicians. Both groups showed a significant relationship between physiological responses and learning scores in active auditory discrimination task. Taken together, the present results indicate that there are differences in basic physiological processes as well as in personality profiles between musicians and non-musicians.
Toward the Discovery and Extraction of Money Laundering Evidence from Arbitrary Data Formats using Descriptive Data Languages and Hyperstructured Combinatory Reductions

—The evidence of money laundering schemes exist undetected in the electronic ﬁles of banks and insurance ﬁrms scattered around the world. Intelligence and law enforcement analysts, impelled by the duty to discover connections to drug cartels and other participants in these criminal activities, require the information to be searchable and extractable from all types of data formats. In this overview paper, we articulate an approach — a capability that uses a data description language called Data Format Description Language (DFDL) extended with higher-order functions as a host language to XML Linking (XLink) and XML Pointer (XPointer) languages in order to link, discover and extract ﬁnancial data fragments from raw-data stores not co-located with each other —see ﬁgure 1. The strength of the approach is grounded in the speciﬁcation of a declarative compiler for our concrete language using a higher-order rewriting system with binders called Combinatory Reduction Systems Extended (CRSX). By leveraging CRSX, we anticipate formal operational semantics of our language and signiﬁcant optimization of the compiler.
Improving game-tree search by incorporating error propagation and social orientations

Game-tree search algorithms, such as the two-player Minimax algorithm and its multi-player counterpart, Max-n, are a fundamental component in the development of computer programs for playing extensive-form games. The success of these algorithms is limited by the underlying assumptions on which they are built. For example, it is traditionally assumed that deeper search always produces better decisions and also that search procedures can assume all players are selfish and ignore social orientations. Deviations from these assumptions can occur in real games and can affect the success of a traditional search algorithms. The goal of my thesis is to determine when such deviations occur and modify the search procedure to correct the errors that are introduced.
Energy Efficient Routing Protocol for Ad hoc Networks

In Ad hoc networks, routing protocols just like AODV didn't take the energy of nodes into account during routing discovery process, so energy drain of some of nodes may cause network partition. This paper proposed an energy saving routing protocol named EEAODV based on AODV. During routing discovering, the source node takes the residual energy of the intermediate nodes and considers the influence of motivation of those nodes imposed on the topology of network which may cause route path change. Simulation results show that the proposed protocol achieves better network service performance compared to current protocols.
Do Bivariate SVAR Models with Long-Run Identifying Restrictions Yield Reliable Results? An Investigation into the Case of Germany

Bivariate SVAR models employing long-run identifying restrictions are popular tools to investigate the source of business cycle fluctuations. Their advantage is the simplicity in use and interpretation. However, their low dimension may also lead to a failure of the identification procedure, with the result that the identified shocks are a mixture of the 'true' shocks. To investigate this issue, the consistency of results from different bivariate SVAR models estimated for German data is evaluated using the FAUST and LEEPER (1997) test procedure. The principal result is that these models do not allow reliable inference on the sources of output fluctuations.
A proper model for the partitioning of electrical circuits

Partitioning algorithms for electrical circuits are often based on the heuristic manipulation of a simple element-to-element interconnection matrix. However, the element-to-element interconnection matrix does not properly represent an electrical interconnection, or “net”, among more than two elements. This paper expands on several aspects of the discrepancy: 1) its source, 2) the circumstances under which it is likely to be significant, and its magnitude for typical circuits, and 3) the comparative difficulty and expense of using a more appropriate representation. A physically correct “net-cut” model is presented. This model is computationally straightforward and is easily adapted to the typical heuristic solution strategies. The “net-cut” model is coupled with the Kernighan-Lin partitioning algorithm [3]; using the same algorithm, comparisons with the “edge-cut” model demonstrate that the correct model reduces net-cuts by 19 to 50% for four digital logic circuits.
Optimal Dual Martingales, Their Analysis, and Application to New Algorithms for Bermudan Products

In this paper we introduce and study the concept of optimal and surely optimal dual martingales in the context of dual valuation of Bermudan options and outline the development of new algorithms in this context. We provide a characterization theorem, a theorem which gives conditions for a martingale to be surely optimal, and a stability theorem concerning martingales which are nearly surely optimal in a sense. Guided by these results we develop a framework of backward algorithms for constructing such a martingale which can be utilized for computing an upper bound of the Bermudan product. The methodology is purely dual in the sense that it does not require certain input approximations to the Snell envelope. In an Ito--Levy environment we outline a particular regression-based backward algorithm which allows for computing dual upper bounds without nested Monte Carlo simulation. Moreover, as a by-product this algorithm also provides approximations to the continuation values of the product, which in turn deter.
Mouse models of liver cancer: Progress and recommendations

To clarify the pathogenesis of hepatocellular carcinoma (HCC) and investigate the effects of potential therapies, a number of mouse models have been developed. Subcutaneous xenograft models are widely used in the past decades. Yet, with the advent of in vivo imaging technology, investigators are more and more concerned with the orthotopic models nowadays. Genetically engineered mouse models (GEM) have greatly facilitated studies of gene function in HCC development. Recently, GEM of miR-122 and miR-221 provided new approaches for better understanding of the in vivo functions of microRNA in hepatocarcinogenesis. Chemically induced liver tumors in animals share many of the morphological, histogenic, and biochemical features of human HCC. Yet, the complicated and obscure genomic alternation restricts their applications. In this review, we highlight both the frequently used mouse models and some emerging ones with emphasis on their merits or defects, and give advises for investigators to chose a “best-fit” animal model in HCC research.
SMART High Precision: TREC 7

The Smart information retrieval project emphasizes completely automatic approaches to the understanding and retrieval of large quantities of text. We continue our work in TREC 7, concentrating on high precision retrieval. In particular, we present an in-depth analysis of our High-Precision Track results, including o ering evaluation approaches and measures for time dependent evaluation. We participated in the Query Track, making initial e orts at analyzing query variability, one of the major obstacles for improving retrieval e ectiveness. Basic Indexing and Retrieval In the Smart system, the vector-processing model of retrieval is used to transform both the available information requests as well as the stored documents into vectors of the form: Di = (wi1; wi2; : : : ; wit) where Di represents a document (or query) text and wik is the weight of term Tk in document Di. A weight of zero is used for terms that are absent from a particular document, and positive weights characterize terms actually assigned. The assumption is that t terms in all are available for the representation of the information. The basic \tf*idf" weighting schemes used within SMART have been discussed many times. For TREC 7 we use the same basic weights and document length normalization as were developed at Cornell by Amit Singhal for TREC 4([3, 5]. Tests on various collections show that this indexing is reasonably collection independent and thus should be valid across a wide range of new collections. No human expertise in the subject matter is required for either the initial collection creation, or the actual query formulation. The same phrase strategy (and phrases) used in all previous TRECs (for example [2, 3, 4, 1]) are used for TREC 7. Any pair of adjacent non-stopwords is regarded as a potential phrase. The nal list of phrases is composed of those pairs of words occurring in 25 or more documents of the initial TREC 1 document set. Phrases are weighted with the same scheme as single terms. When the text of document Di is represented by a vector of the form (di1; di2; : : : ; dit) and query Qj by the vector (qj1; qj2; : : : ; qjt), a similarity (S) computation between the two items can conveniently be obtained as the inner product between corresponding weighted term vectors as follows:
On Ioms(q): Incomplete Orthogonalization Methods for Large Unsymmetric Linear Systems

The truncated version, Incomplete Orthogonalization Methods (IOMs(q)), of Full Orthogonalization Methods (FOM), proposed by Saad has been used a long time for solving large unsymmetric linear systems. However, no convergence analysis has been made. In this paper, we analyze in detail IOMs(q) from a theoretical point of view, and establish a convergence theory of the methods. We derive a number of important results of how the unsymmetry of the matrix A to aaect the basis vectors generated by IOMs(q), and establish the relationships between the residuals for IOMs(q) and the full orthogonalization method (FOM). The results show that IOMs(q) behave much like FOM once the basis vectors generated by IOMs(q) are well conditioned. However, it is shown that IOMs(q) may generate an ill-conditioned basis for any unsymmetric matrix and the parameter q such that IOMs(q) may fail to converge or at least cannot behave like FOM. Due to the mathematical equivalence between IOMs(q) and the truncated ORTHORES(q) developed by Young and Jea, essentially we give insights into the convergence of ORTHORES(q). As for practical considerations, we suggest one strategy of choosing the parameter q. Numerical experiments are reported to show convergence behaviors of IOMs(q).
Content Collection and Analysis in the Domain of Epidemiology

We describe a system that tracks the spread of epidemics by automatically extracting content from the Web. The system continuously monitors a large set of news sources, extracts information from new articles, and accumulates the extracted facts in a database in real time. The system provides functionality for visualizing results, as well as alerting capability. We present the current state of the system and discuss challenges and further enhancements.
Optic Neuritis and Multiple Sclerosis

T HE INVESTMENT of the National Eye Institute in the Optic Neuritis Treatment Trial continues to pay dividends. In this issue of the ARCHIVES, the Optic Neuritis Study Group reports on the risk of developing multiple sclerosis (MS) after an attack of isolated optic neuritis. This issue is of great importance to patients and physicians and, as the authors acknowledge, has been addressed in prior studies, some of which yielded similar results. However, with its impressive number of subjects, high retention rate, prospective design, standardized procedures, and well-defined criteria, the Optic Neuritis Treatment Trial has produced results that will likely be influential. The Optic Neuritis Study Group provides 10to 13year follow-up on a cohort of patients who had experienced an attack of acute optic neuritis unaccompanied by other clinical evidence of MS. Follow-up was available on 87% of the original 388 patients, a remarkable achievement in itself. The risk of developing MS by clinical criteria was 38% at 10 years and 40% at 12 years. Magnetic resonance imaging (MRI) findings at the time of the acute optic neuritis episode correlated with the risk. Patients with at least 1 brain lesion had a 10-year risk of 56%, whereas 22% of those with normal brain MRI results developed clinical MS during that interval.
Targeting with Consumer Search : an Economic Analysis of Keyword Advertising

This article investigates the role of a search engine as an intermediary between firms and consumers. Search engines enable firms to target consumers who have revealed some specific needs through their query. In a framework with horizontal product differentiation, imperfect product information and in which consumers incur search costs, I show that introducing a mechanism which enables firms to target consumers reduces social inefficiencies but has ambiguous effects on the equilibrium price. A profit maximizing search engine has incentives to design the mechanism so as to soften price competition between firms, in order to extract profit from them, and this may not be socially efficient. Sufficient conditions for efficiency of the outcome are provided.
An Approach for Alleviating the Starvation Problem in Road Side Units (RSUs)-based Vehicular Ad Hoc Networks(VANETs)

Scheduling for data exchange in Vehicular Ad Hoc Networks (VANETs) is being considered as a vital issue by the researchers. Road Side Units (RSUs) being the standalone buffer point is to compensate the less connectivity problem due to mobility of vehicles. Here we formulate an RSU-based VANETs model. Due to vehicle mobility and RSU range constraint scheduling is an important issue to meet a vehicle’s issued demand in hard real-time. We investigate existing scheduling algorithm serve a data item only based on vehicles’ submitted requests’ characteristics and avoiding the relationship between a vehicle and its submitted requests which leads a vehicle level starvation problem. In this paper, we address this starvation problem and propose a solution to minimize the problem. Simulation result also supports our proposed approach and offers expected result.
Statistics in Nuclear Cardiology: So, What’s the Difference? The t-Test: Pitfalls and Options in Hypothesis Testing for Comparing Differences in Means

Decisions related to differences of the measures of central tendency of population parameters are an important part of clinical research. Choice of the appropriate statistical test is critical to avoiding errors when making those decisions. All statistical tests require that one or more assumptions be met. The t-test is one of the most widely used tools but is not appropriate when assumptions such as normality are not met, especially when small samples, < 40, are used. Non-parametric tests, such as the Wilcoxon rank sum and others, offer effective alternatives when there are questions about meeting assumptions. When normality is in question, the Wilcoxon non-parametric tests offer substantially higher levels of power and an reliable alternative to the t-test.
Turbulent viscosity in clumpy accretion disks - II. Supernova driven turbulence in the Galaxy

An analytical model for a turbulent clumpy gas disk is presented where turbulence is maintained by the energy input due to supernovae. Expressions for the disk parameters, global filling factors, molecular fractions, and star formation rates are given as functions of the Toomre parameter Q , the ratio between the cloud size and the turbulent driving length scale δ , the mass accretion rate within the disk $\dot{M}$, the constant of molecule formation α , the disk radius, the angular velocity, and its radial derivative. Two different cases are investigated: a dominating stellar disk and a self-gravitating gas disk in z direction. The turbulent driving wavelength is determined in a first approach by energy flux conservation, i.e. the supernovae energy input is transported by turbulence to smaller scales where it is dissipated. The results are compared to those of a fully gravitational model. For $Q=1$ and $\delta=1$ both models are consistent with each other. In a second approach the driving length scale is directly determined by the size of supernovae remnants. Both models are applied to the Galaxy and can reproduce its integrated and local gas properties. The influence of thermal and magnetic pressure on the disk structure is investigated. We infer $Q \sim 1$ and $\dot{M} \sim 0.05$–0.1 $M_{\odot}$ yr -1 for the Galaxy.
Modeling of Modern Router Architectures Supporting Network Virtualization

For the emerging concept of network virtualization where a multitude of virtual networks (VNs) coexist, the main challenge is to isolate and control the resources allocated for individual virtual networks. Realizing such resource allocation requires deliberate design of the router enhanced specifically for handling a large number of virtual network flows. This paper discusses fundamental challenges on modeling the architecture of modern routers for the support of the virtual networks. Our intention is to discuss strategies for scheduling the traffic on each isolated VN and to provide an elementary framework for evaluating the performance of the router extended to classify incoming VN traffic. Furthermore, we also present simulation results and discuss challenges and future directions encountered in the implementation and deployment of VNs.
Well-being, Smartphone Sensors, and Data from Open-access Databases: A Mobile Experience Sampling Study

We investigated fluctuations of well-being by using a smartphone-based mobile experience sampling method (real-time and multiple time point measurements in the field using smartphones). Moreover, temperature, longitude, latitude, altitude, wind speed, rainfall, and further environment-based indicators were included as predictors either from smartphone sensors or from open-access Internet databases. Overall, a total of 213 participants reported on their well-being (over 14 days; three measurements per day; 8,000+ well-being judgments). We were able to replicate and refine past research about the dynamics of well-being fluctuations during the day (low in the morning, high in the evening) and over the course of a week (low just before the beginning of the week, highest near the end of the week). We also show what kind of benefits empirical researchers can gain for their research using smartphones and their built-in sensors by combining these measures with data from open-access databases.
2 Astrocytes and Functional Hyperemia : Origins and Revisions

Astrocytes have recently been shown to be essential participants in the control of cerebral blood flow (CBF) through their prominent control of cerebral vessel diameter. Although the unique close relationship of astrocytes with cerebral blood vessels has long been recognized it is only within the last few years that evidence has shown how astrocytes might translate information to the vasculature on the activity level and energy demands of neurons. These findings suggest that astrocytes are key players in the system for the delivery and clearance of molecules important to brain function.
Don't Take This Personally: Sentiment Analysis for Identification of "Subtweeting" on Twitter

The purpose of this project is to identify subtweets. The Oxford English Dictionary deﬁnes “subtweet” as a “[Twitter post] that refers to a particular user without directly mentioning them, typically as a form of furtive mockery or criticism. ” This paper details a process for gathering a labeled ground truth dataset, training a classiﬁer, and creating a Twitter bot which interacts with subtweets in real time. The Naive Bayes classiﬁer trained in this project classiﬁes tweets as subtweets and non-subtweets with an average F 1 score of 72%.
Birefringence imaging for optical sensing of tissue damage

We present an automated technique to detect and quantify damage to biological tissue by sensing changes in the tissue's optical birefringence. Birefringence is a property of many types of tissue, which decreases with damage. Using a polarisation-sensitive optical coherence tomography scanner, the method first acquires a 3D scan of the area of tissue under analysis. By calculating the birefringence at each location on the surface of the tissue, we build a 2D image indicative of the biological microstructure, with areas of abnormally low birefringence indicating tissue damage. The technique is demonstrated using a model of localised thermal damage on porcine tendon. The resulting birefringence images are validated against a histological gold standard, showing strong correspondence between areas of low and high birefringence, and areas of damaged and undamaged tissue respectively.