Miracle-dz/UniFAR-FTUs huggingface dataset:
Bystin as a novel marker for reactive astrocytes in the adult rat brain following injury

Bystin has been identified as a protein which mediates cellular interactions between trophoblastic and endometrial epithelial cells by forming complexes with two partners, trophinin and tastin, during embryo implantation. However, the presence of bystin in the central nervous system has not been demonstrated. Here, we report the cloning of the full‐length cDNA of the rat bystin gene from adult brain. Immunohistochemical and RT‐PCR analysis showed that the levels of bystin expression were markedly up‐regulated in the both 6‐hydrodopamine‐lesioned rat nigrostriatum and stab‐lesioned cerebral cortex in adult rats. Double immunofluorescence staining revealed that most bystin‐expressing glial cells were astrocytes (immature or mature). To determine the mechanisms for the up‐regulation of bystin expression in glial cells, primary cultures of postnatal cortical astrocytes were employed. Western blot analysis showed that the expression of bystin was elevated by treatment with pro‐inflammatory mediators lipopolysaccharide and interleukin‐1β. Nerve growth factor known to be released after brain injury also induced bystin expression in the cultures. Exposure of astrocyte cultures to the differentiating agent forskolin resulted in up‐regulation of bystin followed by a pronounced astrocytic stellation. The results suggest that the injury in the adult brain induces spatiotemporal up‐regulation of bystin and it could be influenced, at least in part, by elevation of intracellular cAMP level. Bystin expressed by reactive astrocytes may be involved in their differentiation during the inflammatory processes following brain injury. The reappearance of bystin may also indicate that some reactive astrocytes have the capacity to recapitulate early developmental stages.
Alterations in intracellular Ca2+-homeostasis of skeletal muscle fibers during sepsis*

Objective:To investigate changes in intracellular Ca2+-regulation and Ca2+-sensitivity of the contractile apparatus in murine skeletal muscle fibers during sepsis. Design and Setting:Animal study in a university-based research laboratory. Subjects:Isolated muscle fibers (M. extensor digitorum longus) of septic mice. Interventions:In one group, sepsis was induced in “black six” mice using cecal ligation and puncture (CLP). In a second group, laparotomy (SHAM), and in a third group, general anesthesia (GA) was performed. Saponin-skinned skeletal muscle fibers were examined 2, 3, 5, and 7 days after treatment, and caffeine-induced Ca2+-release from the sarcoplasmic reticulum (SR) as well as Ca2+-sensitivity of the contractile apparatus were assessed. Measurements and Results:In the CLP group, Ca2+-release significantly decreased over 5 days and increased again after 7 days. In the SHAM group, Ca2+-release decreased at days 2 and 3, whereas no changes were observed in the GA group. Ca2+-sensitivity significantly increased over 5 days in the CLP group and decreased again at day 7. In the SHAM group, Ca2+-sensitivity increased at days 2 and 3, and no changes were seen in the GA group. Conclusions:In murine skeletal muscle fibers, Ca2+-release from the SR decreases during sepsis, with effects being most pronounced 2–3 days after CLP. In parallel, Ca2+-sensitivity of the contractile apparatus is increased, and all changes are reversible. Thus, these effects might be involved in skeletal muscle dysfunction during sepsis as corresponding changes are less pronounced or absent in control groups.
Circular sectoral waveguides

Hollow cylindrical waveguides that have pie-shaped cross sections are described. The explicit equations for the field components of the TE (transverse electric) and TM (transverse magnetic) waves are given, and the modal patterns for a number of modes are plotted. The relation between the field distributions inside the circular and sectoral waveguides is discussed. It is shown that the electric and magnetic fields of the modes TE/sub 1n/ and TM/sub 1n/ display edge singularity when the sectoral angle is greater than pi . Formulas convenient for the evaluation of Bessel functions of fractional order on a personal computer are given. <<ETX>>
Automatic identification and multi-translatable translation of vocabulary terms with a combined approach

Automatic translation of out of vocabulary (OOV) terms has been extensively studied in the past, but multi-translatable OOV terms have received little attention. Multi-translatable OOV terms are OOV terms with some possible OOV synonyms, thus they have more than one correct translations. Traditional methods usually ignore such problem and neither identify/extract multi-translatable OOV terms nor translate them. This paper proposes a web-based OOV term translation method by utilizing a novel automatic multi-translatable OOV term identification and extraction approach. This approach integrates synonymous features and pattern matching to solve multi-translatable OOV term problems. A combined translation method is proposed for extracting translation candidates. To achieve high translation selection quality, we conducted statistical feature extraction, an artificial neural network combined with backward feature selection, and evolutionary parameter optimization is trained for selecting correct translations. Our method outperforms existing method with an accuracy of 82.61%.
Improving Source Code Quality through the Definition of Linguistic Antipatterns

Previous studies showed that linguistic information contained in source code is a valuable source of information and can help to improve program comprehension. The proposed research focuses on improving the quality of source code by studying common negative practices with respect to linguistic information. The definition of the so called linguistic antipatterns are expected to increase the awareness of the existence of such bad practices and to discourage their use. We also propose to study the relation between negative practices in linguistic information (i.e., linguistic antipatterns) and negative practices in structural information (i.e., design antipatterns). We discuss the proposed methodology and some preliminary results.
A Class of Single-Class Minimax Probability Machines for Novelty Detection

Single-class minimax probability machines (MPMs) offer robust novelty detection with distribution-free worst case bounds on the probability that a pattern will fall inside the normal region. However, in practice, they are too cautious in labeling patterns as outlying and so have a high false negative rate (FNR). In this paper, we propose a more aggressive version of the single-class MPM that bounds the best case probability that a pattern will fall inside the normal region. These two MPMs can then be used together to delimit the solution space. By using the hyperplane lying in the middle of this pair of MPMs, a better compromise between false positives (FPs) and false negatives (FNs), and between recall and precision can be obtained. Experiments on the real-world data sets show encouraging results
Second-Order SMO Improves SVM Online and Active Learning

Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow online and active learning. Second, for large data sets, computing the exact SVM solution may be too time-consuming, and an efficient approximation can be preferable. The powerful LASVM iteratively approaches the exact SVM solution using sequential minimal optimization (SMO). It allows efficient online and active learning. Here, this algorithm is considerably improved in speed and accuracy by replacing the working set selection in the SMO steps. A second-order working set selection strategy, which greedily aims at maximizing the progress in each single step, is incorporated.
Merging Query Results From Local Search Engines for Georeferenced Objects

The emergence of numerous online sources about local services presents a need for more automatic yet accurate data integration techniques. Local services are georeferenced objects and can be queried by their locations on a map, for instance, neighborhoods. Typical local service queries (e.g., “French Restaurant in The Loop”) include not only information about “what” (“French Restaurant”) a user is searching for (such as cuisine) but also “where” information, such as neighborhood (“The Loop”). In this article, we address three key problems: query translation, result merging and ranking. Most local search engines provide a (hierarchical) organization of (large) cities into neighborhoods. A neighborhood in one local search engine may correspond to sets of neighborhoods in other local search engines. These make the query translation challenging. To provide an integrated access to the query results returned by the local search engines, we need to combine the results into a single list of results. Our contributions include: (1) An integration algorithm for neighborhoods. (2) A very effective business listing resolution algorithm. (3) A ranking algorithm that takes into consideration the user criteria, user ratings and rankings. We have created a prototype system, Yumi, over local search engines in the restaurant domain. The restaurant domain is a representative case study for the local services. We conducted a comprehensive experimental study to evaluate Yumi. A prototype version of Yumi is available online.
Real Time Location based Tracking using WIFI Signals

Now-a-days the difficult to tracking the mobile devices has become an issue. Various needs are arising for finding out ways of tracking mobile devices. In this research paper included different algorithm for location tracking. The activity of tracking includes learning and inference, sensing. Different algorithms have different mechanisms based on which the tracking is made possible. For tracking a device in nearby place efforts required are less than from far-away places. Algorithms include their own mechanisms for tracking the devices easily. Some of the algorithms are simple in nature while others are complex. The cost incurred for tracking devices differs when used via wireless against wired networks. Wireless technology is beneficial for tracking the devices in close areas easily. Wire-less technology such as WI-FI becomes very helpful in such cases. For tracking devices in indoor places the system named WITS (Wireless Indoor Tracking System) is used. WLAN based location tracking algorithms is categorized into two types: deterministic and probabilistic. In this paper algorithm such as Bayesian algorithm, nearest neighbor algorithm, Historybased tracking algorithm, H.M. M. (Hidden Markov model), RADAR etc. is explained. The use of wireless 802.11 frameworks is done to locate the devices. Moreover the WI-FI technology can also be used in forest area for tracking animals. WI-FI signals are much useful in places where the wired connections are not possible to set up. Despite of the use of WI-FI signals in location tracking, they are also used in tracking Bar Code stickers. Some of the WI-FI based techniques are only software based so it decreases the cost of hardware maintenance. Radio-frequency based tracking in WLAN signals has gained more and more popularity in recent years. In early days the WLAN was used to track only static devices but later on by making advances in the technology it was possible to track the moving devices as well.
Hybrid power control for multi-carrier systems

Uplink conventional power control techniques in systems with frequency reuse one have some limitations, typically regarding the tradeoff between the average throughput of users at cell center and cell edge. Moreover, one of the main drawbacks is the excess use of power. From our point of view, one of the reasons for this waste of power is the practice of giving all the users in the cell the same target SINR in the power control process. Since there exists a rate limit for users in the cell, depending on their positions, a Hybrid Power Control (HPC) technique is introduced here in order to overcome these limitations and provide a more flexible solution. The HPC uses power control with at least two different types of setup and the rate limit of the cell users is respected. Moreover, this HPC method shows a significant reduction in the average cell transmission power, satisfactory cell edge users performance and an improvement in the overall cell rate, around 25%. Moreover, the average transmitted power is reduced by more than 20 dB.
An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers

The Bayesian classifier is a simple approach to classification that produces results that are easy for people to interpret. In many cases, the Bayesian classifier is at least as accurate as much more sophisticated learning algorithms that produce results that are more difficult for people to interpret. To use numeric attributes with Bayesian classifier often requires the attribute values to be discretized into a number of intervals. We show that the discretization of numeric attributes is critical to successful application of the Bayesian classifier and propose a new method based on iterative improvement search. We compare this method to previous approaches and show that it results in significant reductions in misclassification error and costs on an industrial problem of troubleshooting the local loop in a telephone network. The approach can take prior knowledge into account by improving upon a user-provided set of boundary points, or can operate autonomously.
Development of an ultrahigh resolution Si-PM based PET system for small animals

Since a high resolution PET system is needed for small animal imaging, especially for mouse studies, we developed a new small animal PET system that decreased the size of the scintillators to less than 1 mm. Our developed PET system used 0.5 × 0.7 × 5 mm3 LYSO pixels arranged in an 11 × 13 matrix to form a block with a 0.1 mm BaSO4 reflector between the pixels. Two LYSO blocks were optically coupled to two optical fiber based angled image guides. These LYSO blocks and image guides were coupled to a Si-PM array (Hamamatsu MPPC S11064–050P) to form a block detector. Eight block detectors (16 LYSO blocks) were arranged in a 34 mm inner diameter ring to form a small animal PET system. The block detector showed good separation for the 22 × 13 LYSO pixels in the two-dimensional position histogram. The energy resolution was 20% full-with at half-maximum (FWHM) for 511 keV gamma photons. The transaxial resolution reconstructed by filtered backprojection was 0.71 to 0.75 mm FWHM and the axial resolution was 0.70 mm. The point source sensitivity was 0.24% at the central axial field-of-view. High resolution mouse images were obtained using our PET system. The developed ultrahigh resolution PET system showed attractive images for small animal studies and has a potential to provide new findings in molecular imaging researches.
Obliviousness, Modular Reasoning, and the Behavioral Subtyping Analogy

The obliviousness property of AspectJ conflicts with the ability to reason about an AspectJ program in a modular fashion. This makes debugging and maintenance dicult. In object-oriented programming, the discipline of behavioral subtyping allows one to reason about programs modularly, despite the somewhat oblivious nature of dynamic binding; however, it is not clear what discipline would help AspectJ programmers obtain modular reasoning. We describe this problem in detail, and sketch a solution that allows programmers to tell both “superimposition” and “evolution” stories in their AspectJ programs.
User Access Pattern Enhanced Small Web Search

Current search engines generally employ link analysis techniques to web-page re-ranking. However, the same techniques are problematic in small webs, such as websites or intranet webs, because the link structure is different from the global Web. We propose a re-ranking mechanism based on implicit links generated from user access patterns. Experimental results indicate that our method outperforms keyword-based method, explicit link-based PageRank and DirectHit.
HOWERD: A Hidden Markov Model for Automatic OWL-ERD Alignment

The HOWERD model for estimating the most likely alignment between an OWL ontology and an Entity Relation Diagram (ERD) is presented. Automatic alignment between relational schema and ontology represents a big challenge in Semantic Web research due to the different expressiveness of these representations. A relational schema is less expressive than the ontology, this is a non trivial problem when accessing data via an ontology and for ontology storing by means of a relational schema. Existent alignment methodologies fail in loosing some contents of the involved representations because the ontology captures more semantic information, and several elements are left unaligned. HOWERD relies on a Hidden Markov Model (HMM) to estimate the most likely sequence of ERD symbols in a relational schema that correspond to the constructs of an OWL axiom in the ontology to be aligned. Such constructs are the observable states in the HMM, while hidden states are modeled as the symbols of a context free grammar defined purposely for describing the input ERD lexically.
Dynamic fractional frequency reuse (D-FFR) for multicell OFDMA networks using a graph framework

A graph-based framework is proposed in this paper to implement dynamic fractional frequency reuse (D-FFR) in a multicell Orthogonal Frequency Division Multiple Access (OFDMA) network. FFR is a promising resource-allocation technique that can effectively mitigate intercell interference (ICI) in OFDMA networks. The proposed D-FFR scheme enhances the conventional FFR by enabling adaptive spectral sharing as per cell-load conditions. Such adaptation has significant benefits in practical systems where traffic loads in different cells are usually unequal and time-varying. The dynamic adaptation is accomplished via a graph framework in which the resource-allocation problem is solved in two phases: (1) constructing an interference graph that matches the specific realization of FFR and the network topology and (2) coloring the graph by use of a heuristic algorithm. Various realizations of FFR can easily be incorporated in the framework by manipulating the first phase. The performance improvement enabled by the proposed D-FFR scheme is demonstrated by computer simulation for a 19-cell network with equal and unequal cell loads. In the unequal-load scenario, the proposed D-FFR scheme offers significant performance improvement in terms of cell throughput and service rate as compared to conventional FFR and previous interference management schemes. Copyright © 2011 John Wiley & Sons, Ltd.
Performance of filled polymer systems under novel dynamic extrusion processing conditions

Abstract Dynamic extrusion processing experiments have been carried out on PP-CaCO3 and LDPE-CaCO3 blends using an electromagnetic dynamic plasticating extruder and the effects of vibration forcefield on the extrusion processing of lled polymer systems were studied. It is shown that a proper vibration force eld can reduce the extrusion pressure and the extrusion power with the result that the degree of mixing of lled polymer systems is effectively improved compared with a traditional extruder.
Geometric Routing Precluding Loops and Dead Ends in 3-D Wireless Sensor Networks

Numerous algorithms on geometric networks has been studied, and most of them were based on 2-dimensional networks. But 2-dimensional geometric routing algorithms cannot be directly adapted to the 3-dimensional networks. In this paper, we propose routing algorithms based on the iteration of specific angles on the networks of Delaunay Triangulation in 3D space, and prove the certainty of data transmission of our routing algorithms. In the algorithms, the messages only need to carry information of O(1) nodes and each node just keeps 1-hop neighbors' information.
Bulky disease has an impact on outcomes in primary diffuse large B‐cell lymphoma of the breast: a retrospective analysis at a single institution

Objectives: Primary breast lymphoma (PBL) is rare, and its clinical behavior and standard initial treatment are not yet established. Methods: We retrospectively analyzed the clinicopathological features and treatment outcomes of 14 patients with primary breast diffuse large B‐cell lymphoma. Results: There were nine patients with stage IE and five with stage IIE disease. The median largest tumor diameter was 4.5 cm, and five patients had bulky disease >5 cm. The complete response rate was 94%. However, the 5‐year progression‐free survival rate was 52% with a median follow‐up of 5.2 years. Patients with bulky disease had an unfavorable prognosis. All five patients with bulky disease progressed or relapsed. Of the four patients that recurred in the central nervous system (CNS), three had bulky disease although some received rituximab. There were no CNS recurrences in the three patients who received CNS prophylaxis. All eight patients who responded to radiotherapy (RT) did not have recurrences in the ipsilateral breast, although one patient with bulky disease relapsed in the adjacent regional lymph nodes within the RT field despite immunochemotherapy. Conclusions: Patients with bulky disease had a poorer prognosis and recurred frequently in the CNS. CNS prophylaxis might yield better outcomes, but a larger, prospective trial is needed to elucidate the optimal initial treatment of PBL in the rituximab era.
Dependency-Based Automatic Evaluation for Machine Translation

We present a novel method for evaluating the output of Machine Translation (MT), based on comparing the dependency structures of the translation and reference rather than their surface string forms. Our method uses a treebank-based, widecoverage, probabilistic Lexical-Functional Grammar (LFG) parser to produce a set of structural dependencies for each translation-reference sentence pair, and then calculates the precision and recall for these dependencies. Our dependency-based evaluation, in contrast to most popular string-based evaluation metrics, will not unfairly penalize perfectly valid syntactic variations in the translation. In addition to allowing for legitimate syntactic differences, we use paraphrases in the evaluation process to account for lexical variation. In comparison with other metrics on 16,800 sentences of Chinese-English newswire text, our method reaches high correlation with human scores. An experiment with two translations of 4,000 sentences from Spanish-English Europarl shows that, in contrast to most other metrics, our method does not display a high bias towards statistical models of translation.