Miracle-dz/UniFAR-FTUs huggingface dataset:
hypoDD -- A Program to Compute Double-Difference Hypocenter Locations

HypoDD is a Fortran computer program package for relocating earthquakes with the double-difference algorithm of Waldhauser and Ellsworth (2000). This document provides a brief introduction into how to run and use the programs ph2dt and hypoDD to compute double-difference (DD) hypocenter locations. It gives a short overview of the DD technique, discusses the data preprocessing using ph2dt, and leads through the earthquake relocation process using hypoDD. The appendices include the reference manuals for the two programs and a short description of auxiliary programs and example data. Some minor subroutines are presently in the c language, and future releases will be in c. Earthquake location algorithms are usually based on some form of Geiger's method, the linearization of the travel time equation in a first order Taylor series that relates the difference between the observed and predicted travel time to unknown adjustments in the hypocentral coordinates through the partial derivatives of travel time with respect to the unknowns. Earthquakes can be located individually with this algorithm, or jointly when other unknowns link together the solutions to indivdual earthquakes, such as station corrections in the joint hypocenter determination (JHD) method, or the earth model in seismic tomography. The DD technique (described in detail in Waldhauser and Ellsworth, 2000) takes advantage of the fact that if the hypocentral separation between two earthquakes is small compared to the event-station distance and the scale length of velocity heterogeneity, then the ray paths between the source region and a common station are similar along almost the entire ray path (Fréchet, 1985; Got et al., 1994). In this case, the difference in travel times for two events observed at one station can be attributed to the spatial offset between the events with high accuracy. DD equations are built by differencing Geiger's equation for earthquake location. In this way, the residual between observed and calculated travel-time difference (or double-difference) between two events at a common station are a related to adjustments in the relative position of the hypocenters and origin times through the partial derivatives of the travel times for each event with respect to the unknown. HypoDD calculates travel times in a layered velocity model (where velocity depends only on depth) for the current hypocenters at the station where the phase was recorded. The double-difference residuals for pairs of earthquakes at each station are minimized by weighted least squares using the method of singular value decomposition (SVD) …
Imaging in cancer—the significance of the results*

The effective management of patients with cancer requires a multidisciplinary team approach with the diagnostic radiologist playing an extremely important role in that team. Increasingly it is realized that it is often the responsibility of the radiologist to understand and elucidate the significance of the findings of a test. Its significance lies not only in the clinical context but also in appreciating the impact that the test will have on the patient’s outcome. The latter requires a knowledge of the cost-effectiveness of the use of any imaging technique.
Einfluss regionaler sozialer Ungleichheits- und Arbeitsmarktmerkmale auf die Gesundheit

Zusammenfassung: Der Einfl uss von Kontextfaktoren auf den individuellen Gesundheitsstatus hat sich in zahlreichen Studien selbst dann gezeigt, wenn auf die individuelle sozioökonomische Situation (und sonstige relevante Einfl ussgrößen) kontrolliert wurde. Der Beitrag untersucht, ob und inwiefern sich Merkmale des Wohnortes auf den individuellen Gesundheitsstatus auswirken. Dabei wird nicht nur auf Einkommensniveau und -ungleichheit Bezug genommen, sondern ebenfalls auf Effekte von Bildungsniveau und -ungleichheit und der regionalen Arbeitslosenquote. Als Datengrundlage für die individuellen Merkmale wird die Welle des Sozio-oekonomischen Panels (SOEP) aus 2006 herangezogen, während regionale Informationen auf der Basis der Raumordnungsregionen des Mikrozensus von 2005 zugespielt und mittels Mehrebenenanalyse ausgewertet werden. Die Ergebnisse zeigen zum einen, dass regionale Bildungsungleichheit den individuellen Bildungseffekt verstärkt. Demnach weisen Angehörige bildungsferner Schichten in bildungsungleichen Regionen besonders geringe Gesundheitschancen auf. Zum anderen verstärkt eine hohe regionale Arbeitslosenquote den negativen Effekt der individuellen Arbeitslosigkeit der Männer auf ihre Gesundheit.
Evaluation of hydrometeor classification algorithms from multi-frequency dual-polarimetric radar observations collected during HyMeX

1 INTRODUCTION One of the major outcome of dual-polarization radar is the ability to determine the type of hydrometeors within cloud systems. Météo-France, which owns and operate 15 polarimetric operational radars throughout mainland France, has developed a fuzzy logic hydrometeor identification (HID) algorithm, which allows to discriminate between five microphysical types regardless of the radar wavelength: Rain, Wet Snow, Dry Snow, Ice, and Hail (Al-Sakka et al, 2013). This hydrometeor classification algorithms is based upon combination sets of dual-polarimetric observables (horizontal reflectivity Zh, differential reflectivity Zdr, cross-coefficient correlation ρHV, specific differential phase KDP) along with temperature data inferred from a NWP model outputs.
Optimal polynomial blow up range for critical wave maps

We prove that the critical Wave Maps equation with target S2 and origin R2+1 admits energy class blow up solutions of the form u(t ,r ) =Q(λ(t )r )+ε(t ,r ) where Q : R2 → S2 is the ground state harmonic map and λ(t) = t−1−ν for any ν > 0. This extends the work [17], where such solutions were constructed under the assumption ν> 2 . Also in the later chapter, we give the necessary remarks and key changes one needs to notice while the same problem is considered in a more general case while N is a surface of revolution. We are also able to extends the blow-up range in Carstea’s work [3] to ν> 0. In light of a result of Struwe [29], our results are optimal for polynomial blow up rates.
Refining Information Extraction Rules using Data Provenance

Developing high-quality information extraction (IE) rules, or extractors, is an iterative and primarily manual process, extremely time consuming, and error prone. In each iteration, the outputs of the extractor are examined, and the erroneous ones are used to drive the refinement of the extractor in the next iteration. Data provenance explains the origins of an output data, and how it has been transformed through a query. As such, one can expect data provenance to be valuable in understanding and debugging complex IE rules. In this paper we discuss how data provenance can be used beyond understanding and debugging, to automatically refine IE rules. In particular, we overview the main ideas behind a recent provenance-based solution for suggesting a ranked list of refinements to an extractor aimed at increasing its precision, and outline several related directions for future research.
CELEX: Building a Multifunctional, Polytheoretical Lexical Database

Recent developments in Computational Linguistics have brought about an increasing interest in large scale lexical modules, at a time when current trends in hardware and software engineering bring this goal within reach. This paper describes one such system, the C E L E X database. For expository purposes only, this system is contrasted with another big project that starts from different premisses and is meant to serve different goals .
Design and Fabrication of a Micro Electrostatic Vibration-to-Electricity Energy Converter

This paper presents a micro electrostatic vibration-toelectricity energy converter. For the 3.3 V supply voltage and 1cm2 chip area constraints, optimal design parameters were found from theoretical calculation and Simulink simulation. In the current design, the output power is 200 $\mu$W/cm2 for the optimal load of 8 M\Omega. The device was fabricated in a silicon-on-insulator (SOI) wafer. Mechanical and electrical measurements were conducted. Residual particles caused shortage of the variable capacitor and the output power could not be measured. Device design and fabrication processes are being refined.
An Engineering Solution for Using Coarse Meshes in the Simulation of Delamination with Cohesive Zone Models

This paper presents a methodology to determine the parameters used in the simulation of delamination in composite materials using decohesion finite elements. A closed-form expression is developed to define the stiffness of the cohesive layer. A novel procedure that allows the use of coarser meshes of decohesion elements in large-scale computations is proposed. The procedure ensures that the energy dissipated by the fracture process is correctly computed. It is shown that coarse-meshed models defined using the approach proposed here yield the same results as the models with finer meshes normally used in the simulation of fracture processes.
A Feature Selection-based Ensemble Method for Arrhythmia Classification

In this paper, a novel method is proposed to build an ensemble of classifiers by using a feature selection schema. The feature selection schema identifies the best feature sets that affect the arrhythmia classification. Firstly, a number of feature subsets are extracted by applying the feature selection schema to the original dataset. Then classification models are built by using the each feature subset. Finally, we combine the classification models by adopting a voting approach to form a classification ensemble. The voting approach in our method involves both classification error rate and feature selection rate to calculate the score of the each classifier in the ensemble. In our method, the feature selection rate depends on the extracting order of the feature subsets. In the experiment, we applied our method to arrhythmia dataset and generated three top disjointed feature sets. We then built three classifiers based on the top-three feature subsets and formed the classifier ensemble by using the voting approach. Our method can improve the classification accuracy in high dimensional dataset. The performance of each classifier and the performance of their ensemble were higher than the performance of the classifier that was based on whole feature space of the dataset. The classification performance was improved and a more stable classification model could be constructed with the proposed approach.
Next generation PON evolution

Passive optical network (PON) features a point-to-multi-point (P2MP) architecture to provide broadband access. The P2MP architecture has become the most popular solution for FTTx deployment among operators. PON-based FTTx has been widely deployed ever since 2004 when ITU-T Study Group 15Q2 completed recommendations that defined GPON system [ITU-T seriesG.984]. As full services are provisioned by the massive deployment of PON networks worldwide, operators expect more from PONs. These include improved bandwidths and service support capabilities as well as enhanced performance of access nodes and supportive equipment over their existing PON networks. The direction of PON evolution is a key issue for the telecom industry. Full Service Access Network (FSAN) and ITU-T are the PON interest group and standard organization, respectively. In their view, the next-generation PONs are divided into two phases: NG-PON1 and NG-PON2. Mid-term upgrades in PON networks are defined as NG-PON1, while NG-PON2 is a long-term solution in PON evolution. Major requirements of NG-PON1 are the coexistence with the deployed GPON systems and the reuse of outside plant. Optical Distribution Networks (ODNs) account for 70% of the total investments in deploying PONs. Therefore, it is crucial for the NGPON evolution to be compatible with the deployed networks. With the specification of system coexistence and ODN reuse, the only hold-up of the migration from GPON to NG-PON1 is the maturity of the industry chain. Unlike NG-PON1 that has clear goals and emerging developments, there are many candidate technologies for NG-PON2. The selection of NG-PON2 is under discussion. However, one thing is clear, NG-PON2 technology must outperform NG-PON1 technologies in terms of ODN compatibility, bandwidth, capacity, and cost-efficiency.
Efficient neuro-fuzzy system and its Memristor Crossbar-based Hardware Implementation

In this paper a novel neuro-fuzzy system is proposed where its learning is based on the creation of fuzzy relations by using new implication method without utilizing any exact mathematical techniques. Then, a simple memristor crossbar-based analog circuit is designed to implement this neuro-fuzzy system which offers very interesting properties. In addition to high connectivity between neurons and being fault-tolerant, all synaptic weights in our proposed method are always non-negative and there is no need to precisely adjust them. Finally, this structure is hierarchically expandable and can compute operations in real time since it is implemented through analog circuits. Simulation results show the efficiency and applicability of our neuro-fuzzy computing system. They also indicate that this system can be a good candidate to be used for creating artificial brain.
Tonal development and voice quality in the stops of Seoul Korean

Korean stops are currently undergoing a tonogenetic sound change, as found in the Seoul dialect in which a merged VOT of aspirated and lax stops induces F0 to be the primary cue for distinguishing the two stops and the lax stops have lower F0 than the aspirated stops. In tonal languages, low tone is produced with a breathy voice. This study investigated whether there are changes in voice quality with respect to the tonogenetic sound change of Korean stops. Two age groups speaking the Seoul dialect participated in this study: five females and six males born in the 1940s and 1950s and nine females and eight males born in the 1980s and 1990s. This study replicated previous findings of VOT and F0 and further examined H1-H2, H1-A1, and H1-A2 to see how they correlate with the sound change. In the older and younger generations, H1-H2, H1-A1, and H1-A2 were significantly lower after the tense stops than after the aspirated and lax stops, but they were not significantly different after the aspirated and lax stops. However, the younger females exhibited some different results for H1-H2 and H1-A2 than the older generation. In the younger females, the H1-H2 mean was higher after the aspirated stops than it was after the lax stops at the vowel onset, and the H1-H2 difference increased at the vowel midpoint. Although there was an inter-speaker variation in the results of H1-H2 and H1-A1, analyses of individual speakers showed that the H1-H2 and H1-A1 were higher after the lax stops than after the aspirated stops in the younger female speakers. These results indicate that lax stops tend to be breathier than aspirated stops in the younger female speakers. They also indicate that changes in voice quality are on Korean stops with tonal sound change, but are still developing. stops in the YG group. However, an inter-speaker variation was found in the H1-H2 and H1-A2 in the female of the YG group.
Variable-phase-shift-based RF-baseband codesign for MIMO antenna selection

We introduce a novel soft antenna selection approach for multiple antenna systems through a joint design of both RF (radio frequency) and baseband signal processing. When only a limited number of frequency converters are available, conventional antenna selection schemes show severe performance degradation in most fading channels. To alleviate those degradations, we propose to adopt a transformation of the signals in the RF domain that requires only simple, variable phase shifters and combiners to reduce the number of RF chains. The constrained optimum design of these shifters, adapting to the channel state, is given in analytical form, which requires no search or iterations. The resulting system shows a significant performance advantage for both correlated and uncorrelated channels. The technique works for both transmitter and receiver design, which leads to the joint transceiver antenna selection. When only a single information stream is transmitted through the channel, the new design can achieve the same SNR gain as the full-complexity system while requiring, at most, two RF chains. With multiple information streams transmitted, it is demonstrated by computer experiments that the capacity performance is close to optimum.
Approximate Multiple String Searching by Clustering

We are given a nite set S of text strings and a pattern P over some xed alphabet . The topic of this paper is the design of a data structure D(S) which supports approximate multiple string searching queries e ciently. Thereby, for a given upper bound k 2 Z on the allowable distance, P = p1 pm is said to appear approximately in a text T = t1 tn, m; n 2 Z, if there exist positions u; v in T such that the edit distance between P and tu tv is at most k. Let N denote the sum of the lengths of all strings in S. We present an algorithm that constructs the data structure D(S) in O(N) time and space. Afterwards, an approximate multiple string search query can be answered in O(N) expected-time if the allowable distance k is bounded above by O( m logm). The method can be used to search large nucleotide and amino acid sequence databases for similar sequences.
Parametric Modeling in Mitigating the I/Q Mismatch: Estimation, Equalization, and Performance Analysis

In this work, we, using a mapping, transform the mismatch compensation problem into an estimation and equalization problem. By doing so, the in-phase and quadrature (I/Q) system mismatch parameters, i.e., the amplitude gains of I/Q channels and the phase imbalance, can be first estimated reliably and then mitigated by equalization. We also derive the Cramer-Rao lower bounds (CRLBs) of the parameters and study the performances of different phase imbalance estimates. Simulation results show that the mean square errors of the estimated parameters follow the trends of their corresponding CRLBs. Hence the I/Q mismatch can be mitigated by equalization successfully.
Methylated DNA is over-represented in whole-genome bisulfite sequencing data

The development of whole-genome bisulfite sequencing (WGBS) has resulted in a number of exciting discoveries about the role of DNA methylation leading to a plethora of novel testable hypotheses. Methods for constructing sodium bisulfite-converted and amplified libraries have recently advanced to the point that the bottleneck for experiments that use WGBS has shifted to data analysis and interpretation. Here we present empirical evidence for an over-representation of reads from methylated DNA in WGBS. This enrichment for methylated DNA is exacerbated by higher cycles of PCR and is influenced by the type of uracil-insensitive DNA polymerase used for amplifying the sequencing library. Future efforts to computationally correct for this enrichment bias will be essential to increasing the accuracy of determining methylation levels for individual cytosines. It is especially critical for studies that seek to accurately quantify DNA methylation levels in populations that may segregate for allelic DNA methylation states.
Benchmarking domain-specific expert search using workshop program committees

Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets.
Evaluation of Novel Human Immunodeficiency Virus Type 1 Gag DNA Vaccines for Protein Expression in Mammalian Cells and Induction of Immune Responses

ABSTRACT Human immunodeficiency virus (HIV)-specific cytotoxic T lymphocytes (CTL) are an important parameter of host defenses that limit viral replication after infection. Induction of effective CTL against conserved viral proteins such as Gag may be essential to the development of a safe and effective HIV type 1 (HIV-1) vaccine. DNA vaccination represents a novel strategy for inducing potent CD8+ CTL responses in vivo. However, expression of HIV-1 structural proteins by DNA vectors has been hampered by a stringent requirement for coexpression with other viral components, such as Rev and RRE. Furthermore, even with Rev and RRE present, the level of expression of HIV-1 Gag, Pol, or Env is very low in murine cells. These problems have limited our ability to address the key issue of how to generate effective CTL responses to Gag in a mouse model. To overcome this problem, we compared several novel DNA expression vectors for HIV-1 Gag protein expression in primate and mouse cells and for generating immune responses in mice after DNA vaccination. A DNA vector containing wild type HIV-1 gag coding sequences did not induce detectable Gag expression in any of the cells tested. Attempts to increase nuclear export of Gag expression RNA by adding the constitutive transport element yielded only a moderate increase in Gag expression in monkey-derived COS cells and an even lower increase in Gag expression in HeLa cells or several mouse cell lines. In contrast, silent-site mutations in the HIV-1 gag coding sequences significantly increased Gag expression levels in all cells tested. Furthermore, this construct induced both Gag-specific antibody and CTL responses in mice after DNA vaccination. Using this construct, we achieved stable expression of HIV-1 Gag in the mouse cell line p815, which can now be used as a target cell for measuring HIV-1 Gag-specific CTL responses in immunized mice. The DNA vectors described in this study should make it possible to systematically evaluate the approaches for maximizing the induction of CTL responses against HIV-1 Gag in mouse and other animal systems.
Multi-modal information retrieval with a semantic view mechanism

The explosive growth of multimedia information on the Web in recent years calls for an elegant means to model and manage multimedia content to facilitate semantic-level access and sharing across diversified applications. From the perspective of retrieval, the semantics of multimedia data features context-dependency and media-independency; both are inadequately supported by the state-of-the-art data modeling technology. In this paper, we address this problem by advocating MediaView as an extended object-oriented view mechanism to bridge the "semantic gap" between conventional databases and semantics-intensive multimedia applications. This mechanism captures the dynamic semantics of multimedia using a modeling construct named media view (MV), which formulates a customized context where heterogeneous media objects with similar/related semantics are characterized by additional properties and user-defined semantic relationships. View operators are proposed for the manipulation and derivation of individual MVs, which can be fit into the desired real-life scenarios automatically. The usefulness and elegancy of MediaView are demonstrated by its applications in various (subjective) activities supporting multi-modal retrieval.