Miracle-dz/UniFAR-FTUs huggingface dataset:
Gender Disparity in STEM Across Cultures

Miner et al. (2018) claim that focusing on individual factors to understand gender inequity in the fields of science, technology, engineering, and mathematics (STEM) provides an incomplete explanation of the phenomenon. They challenge the appropriateness of individual-level explanations that hold women responsible for the injustices they experience, suggesting that this perspective fails to consider larger social-contextual influences. Instead, to explain gender disparity in the STEM fields, Miner et al. offer a social-structural lens through which to view the situation that relies on commonly held beliefs about women in society. The inequality that characterizes these fields, however, is a worldwide phenomenon that spans societal boundaries. Therefore, understanding the social-contextual factors that contribute to gender inequality in the STEM fields requires a cross-cultural examination of norms and values. In this commentary, I first outline a program of research aimed at developing an empirically supported theoretical framework that explains gender inequity in the STEM fields from a cross-cultural perspective. Then, I review the ways in which cultural beliefs influence education and careers in the STEM fields. Finally, I provide some practical suggestions of ways to promote gender equality in STEM fields. As such, this commentary serves as a call to integrate concepts from vocational, educational, and cross-cultural psychology to address an issue of upmost importance: equal representation.
Evaluation of video quality degradation due to packet loss

In this paper video quality degradation due to packet loss is evaluated. The quality degradation of contaminated frames is first investigated, where acute quality degradation followed by a steady quality period has been observed, as well as a rise of frame quality along with error propagation. Based on the observations, the quality of the contaminated video section is assessed, and its relationship with frame quality is evaluated. Extensive experimental results reveal that the quality of a contaminated video section would be higher than the average frame quality of the section, and it has a strong correlation with the frame quality in the steady quality period.
Discovery of Multi Dimensional Quantitative Closed Association Rules by Attributes Range Method

In this paper we propose a novel algorithm for discovering multi dimensional association rules with right hand side containing closed frequent itemsets of varying length, by finding the boundaries of attributes domains dynamically. It first builds an abstraction, called Multi-Variate Tree, in a single scan of the database. During this construction the boundaries of domains of quantitative attributes are identified dynamically. These identified attributes boundary values associated with frequent itemsets are then used for finding closed association rules. When a transaction database is very dense and the minimum support is very low, i.e., when the database contains a significant number of large frequent itemsets, mining all frequent itemsets might not be a good idea. The concept of closed frequent itemsets solves this problem.
Semantic Augmentation of the Storage Resource Broker

— Information discovery is looming as a major challenge with the growth of tera-byte size datagrids. In order to manage their distributed data collections, many scientific organizations are adopting the San Diego SuperComputer's Storage Resource Broker (SRB). The SRB's Metadata Catalogue (MCAT) focuses primarily on system or administrative metadata and supports domain-specific metadata through user-defined extensions. Although providing maximum flexibility, this approach will lead to interoperability problems when searching across distributed collections described using a variety of different user-defined metadata schemes. The aim of the work described in this poster is to semantically augment the SRB through an ontology and Resource Description Framework (RDF) descriptions in order to support arbitrary metadata schemata and to enhance the system's search capabilities. In particular we describe a semantic search engine and interface built on top of an OWL ontology, RDF instance data and a Jena reasoning engine that enables easier, more sophisticated searching, browsing, inferencing and retrieval of heterogeneous data stored using the SRB.
Getting There from Here: Research on the Effects of Work–Family Initiatives on Work–Family Conflict and Business Outcomes

Many employing organizations have adopted work–family policies, programs, and benefits. Yet managers in employing organizations simply do not know what organizational initiatives actually reduce work–family conflict and how these changes are likely to impact employees and the organization. We examine scholarship that addresses two broad questions: first, do work–family initiatives reduce employees’ work–family conflict and/or improve work–family enrichment? Second, does reduced work–family conflict improve employees’ work outcomes and, especially, business outcomes at the organizational level? We review over 150 peer-reviewed studies from a number of disciplines in order to summarize this rich literature and identify promising avenues for research and conceptualization. We propose a research agenda based on four primary conclusions: the need for more multi-level research, the necessity of an interdisciplinary approach, the benefits of longitudinal studies that employ quasi-experimental or experimental designs and the challenges of translating research into practice in effective ways.
Radionuclide Sentinel Lymph Node Scan and Biopsy in Breast Cancer: The Experience in a Cancer Center

Backgrounds: In the past, axillary lymph node dissection (ALND) was a routine procedure used in the surgery of invasive breast cancer. But procedure related morbidity was not uncommon. Sentinel lymph node (SLN) biopsy is a newly developed method to avoid unnecessary ALND. The purpose of this study was to evaluate the detection rate of radionuclide SLN scan and the negative predictive value of SLN biopsy in early stage breast cancer. Methods: This study included 49 patients of early stage breast cancer. All patients underwent radionuclide SLN scan on the day or the day before surgery. The radionuclide SLN scan was performed with subdermal injection of 0.3. -1.0 mCi of filtered (superscript 99m)Tc-sulfur colloid in the pen-tumor area or area around the scar of excision biopsy. Gamma camera mapping and intraoperative gamma probe were used for SLN biopsy. All SLNs were dissected followed by ALND. All lymph nodes were examined with hematoxylin and eosin (H&E) stain. Immunohistochemistry staining of cytokeratin were done in the SLNs negative on H&E examination to exclude micrometastasis. Results: SLNs were successfully detected by SLN scan in all of patients with detection rate of 100%. Positive SLN metastasis was found in 15 of 49 patients (30.6%), and thirty four patients were negative for SLN metastasis. There was one false negative SLN biopsy and the negative predictive value was 97.1%. Conclusion: Radionuclide SLN scan can provide information about the location and number of SLN(s) before SLN biopsy with high successful rate. The SLN biopsy was predictive for axillary lymph node status and should be used to avoid unnecessary ALND in early stage breast cancer.
A Perceptually Constrained GSVD-Based Approach for Enhancing Speech Corrupted by Colored Noise

The singular value decomposition (SVD)-based method for single-channel speech enhancement has been shown to be very useful when the additive noise is white. For colored noise, with this approach, one needs to whiten the noise spectrum prior to SVD-based approach and perform the inverse whitening processing afterwards. A truncated quotient SVD (QSVD)-based approach has been proposed to handle this problem and found very useful. In this paper, a generalized SVD (GSVD)-based subspace approach for speech enhancement is first extended from the concept of the truncated QSVD-based approach, in which the dimension of the signal subspace can be precisely and automatically determined for each frame of the noisy signal. But with this new approach some residual noise is still perceivable under lower signal-to-noise ratio conditions. Therefore a perceptually constrained GSVD (PCGSVD)-based approach is further proposed to incorporate the masking properties of human auditory system to make sure the undesired residual noise to be nearly un-perceivable. Closed-form solutions are obtained for both the GSVD- and PCGSVD-based enhancement approaches. Very carefully performed objective evaluations and subjective listening tests show that the PCGSVD-based approach proposed here can offer improved speech quality, intelligibility and recognition accuracy, whether the noise is stationary or nonstationary, especially when the additive noise is nonwhite
Integration of Dynamic Automated Metadata Exchange into the SAML 2.0 Web Browser SSO Profile

This document specifies the integration of Dynamic Automated Metadata Exchange (DAME) through an intermediate trusted third party into the Security Assertion Markup Language (SAML) 2.0 Web Browser SSO Profile. The user-triggered, on-demand, and fully automated metadata exchange between identity provider (IDP) and service provider (SP) is intended for scenarios in which the a-priori, e.g., federation-based exchange of SAML metadata is neither practical, scalable nor mandatory for non- technical aspects, such as contract-based trust building between IDP and SP. The main benefit of DAME is the removal of waiting times for users and manual setup tasks for IDP and SP administrators before users can access the service. Implementations of DAME can leverage existing metadata repositories, such as REEP, and metadata transfer protocols, such as MD Query.
Accurate transient calorimetric measurement of soft-switching losses of 10kV SiC MOSFETs

The characterization of soft-switching losses of modern high-voltage SiC MOSFETs is a difficult but necessary task in order to accurately model converter systems such as medium-voltage-connected Solid-State Transformers (SSTs), where soft-switching techniques are employed for an increased efficiency. Usually, switching losses in general are measured with the well-known double pulse method. However, in case of soft-switching loss measurements, this method is very sensitive to several effects such as probe skew and limited measurement accuracy, among others, and thus unsuitable for the characterization of fast switching high-voltage MOSFETs. This paper presents an accurate and reliable calorimetric method for the measurement of soft-switching losses using the example of 10 kV SiC MOSFETs. Finally, measured soft-switching loss curves of these 10 kV SiC MOSFETs are presented for different DC-link voltages, currents and gate resistors.
RNAi induced in mammalian and Drosophila cells via transfection of dimers and trimers of small interfering RNA

Twenty one base pair long small interfering RNAs (siRNAs) are widely in use in mammalian RNAi experiments. The present study assesses the capability of 43 and 63bp dsRNAs with two 2nt long 3′-overhangs to induce RNAi in mammalian and Drosophila cells. Human Dicer was found to cleave these dsRNAs from their ends to generate two or three monomeric siRNA units, each 21-22bp in length. When, in 43bp dsRNA, there was present a highly-effective siRNA sequence in frame with respect to the Dicer digestion, considerably high RNAi activity was noted to be induced in mouse embryonic stem E14TG2a, human HeLa, Chinese hamster CHO-K1 or Drosophila S2 cells. In contrast, RNAi depending on 63bp dsRNA, containing a highly effective siRNA sequence in frame with respect to Dicer digestion, varied considerably depending on cell lines used. While there was no appreciable RNAi in HeLa cells associated with relatively strong interferon response, a significant level of RNAi was noted in E14TG2a, CHO-K1 and S2 cells, in all of which interferon response induction was but slight, if at all. It would thus follow that siRNA oligomers with sequence of a highly functional siRNA monomer unit in frame with respect to dicer digestion should serve as a good RNAi agent in Drosophila and certain mammalian cells.
Winter storm risk of residential structures ? model development and application to the German state of Baden-Württemberg

Abstract. The derivation of probabilities of high wind speeds and the establishment of risk curves for storm damage is of prime importance in natural hazard risk analysis. Risk curves allow the assessment of damage being exceeded at a given level of probability. In this paper, a method for the assessment of winter storm damage risk is described in detail and applied to the German state of Baden-Wurttemberg. Based on meteorological observations of the years 1971–2000 and on damage information of 4 severe storm events, storm hazard and damage risk of residential buildings is calculated on the level of communities. For this purpose, highly resolved simulations of storm wind fields with the Karlsruher Atmospheric Mesoscale Model (KAMM) are performed and a storm damage model is developed. Risk curves including the quantification of the uncertainties are calculated for every community. Local differences of hazard and risk are presented in state-wide maps. An average annual winter storm damage to residential buildings of minimum 15 million Euro (reference year 2000) for Baden-Wurttemberg is expected.
PAPER Special Section on Processing Natural Speech Variability for Improved Verbal Human-Computer Interaction Speaker Recognition by Combining MFCC and Phase Information in Noisy Conditions

SUMMARY In this paper, we investigate the effectiveness of phase for speaker recognition in noisy conditions and combine the phase information with mel-frequency cepstral coefficients (MFCCs). To date, almost speaker recognition methods are based on MFCCs even in noisy conditions. For MFCCs which dominantly capture vocal tract information, only the magnitude of the Fourier Transform of time-domain speech frames is used and phase information has been ignored. High complement of the phase information and MFCCs is expected because the phase information includes rich voice source information. Furthermore, some researches have reported that phase based feature was robust to noise. In our previous study, a phase information extraction method that normalizes the change variation in the phase depending on the clipping position of the input speech was proposed, and the performance of the combination of the phase information and MFCCs was remarkably better than that of MFCCs. In this paper, we evaluate the robustness of the proposed phase information for speaker identification in noisy conditions. Spectral subtraction, a method skipping frames with low energy/Signal-to-Noise (SN) and noisy speech training models are used to analyze the effect of the phase information and MFCCs in noisy conditions. The NTT database and the JNAS (Japanese Newspaper Article Sentences) database added with stationary/non-stationary noise were used to evaluate our proposed method. MFCCs outperformed the phase information for clean speech. On the other hand, the degradation of the phase information was significantly smaller than that of MFCCs for noisy speech. The individual result of the phase information was even better than that of MFCCs in many cases by clean speech training models. By deleting unreliable frames (frames having low energy/SN), the speaker identification performance was improved significantly. By integrating the phase information with MFCCs, the speaker identification error reduction rate was about 30%–60% compared with the standard MFCC
An Approach of XML Schema Matching Using Top-K Mapping

Schema Matching aims at finding the semantic correspondence of concepts between different data sources. Solving such match problems is a key task in numerous application fields, particularly to support data exchange, and all kinds of data integration. Researchers have proposed a number of matching methods in order to identify and discover such semantic correspondence across the XML data. In this paper, we propose the XML schema matching approach based on top-k mapping. We first calculate similarity of XML node elements and structure, then get the similarity matrix, respectively. Such similarity matrix could not distinguish the correct and incorrect mapping effectively. So we present the k best schema mapping, in an iterative process, to identify useful matching. Our experiment demonstrate the approach of the schema matching using top-k mapping have a better performance.
SPEAKER SIMILARITIES IN HUMAN PERCEPTION AND THEIR SPECTRAL PROPERTIES

The acoustic properties of voiced sonorants are said to be speaker-dependent, and it is also reported that these sounds are effective for identifying the speakers. In our previous experiments, we found that the nasal sounds are highly effective for speaker identification by listening, and that the inter-speaker distances in the spectra were also greater in nasals than in oral sounds. This present study further analyses the spectral properties of nasals and orals in terms of perceptual and acoustical voice similarity and shows that nasal sounds may have longer interval that listeners can exploit for speaker identification.
Extreme Personalities at Work and in Life

Contemporary personality taxonomies cast personality traits as ranging from the maladaptive (e.g., low conscientiousness) to adaptive (e.g., high conscientiousness) levels. Despite philosophical and conventional wisdom dating back to the ancients, researchers have only recently begun to uncover evidence that extreme standing on “normal” or “desirable” personality traits might be maladaptive. Here, we present an emerging perspective on why and how extreme standing on “desirable” trait continua translates into maladaptive behavior and undesirable outcomes at work and in life. An overview of the literature on the topic is presented for each trait within the five-factor model. We suggest two reasons for the lack of clarity in the empirical literature: (a) problems with statistical tests resulting from measurement error and (b) lack of breadth in the conceptualization and measurement of personality traits. We suggest that a solution to this problem is to extend trait continua to reflect maladaptive levels at both ends. We close by pointing out that a major implication of this emerging perspective indicates that many more people possess optimal personality-trait levels than previously thought and that future research needs to examine whether the question is consistent with evolutionary and neurophysiological accounts of personality science.
Programmable Quantum Gate Arrays

We present a probabilistic quantum processor for qubits. The processor itself is represented by a fixed array of gates. The input of the processor is constituted by two registers. In the program register the set of instructions (program) is encoded. This program is applied to the data register. The processor we present can perform any operation on a single qubit with a certain probability. If the operation is unitary, the probability is in general 1/4, but for more restricted sets of operators the probability can be higher.
Template-Based Adaptation of Semantic Web Services with Model-Driven Engineering

Service-oriented enterprise systems, which tend to be heterogeneous, loosely coupled, long-lived, and continuously running, have to cope with frequent changes to their requirements and the environment. In order to address such changes, applications need to be inherently flexible and adaptive, supported by appropriate infrastructures. In this paper, we propose a model-driven approach for the dynamic adaptation of Web services based on ontology-aware service templates. Model-driven engineering raises the level of abstraction from concrete Web service implementations to high-level service models, which leads to more flexible and automated adaptations through template designs and transformations. The ontological semantics enhances the service matching capabilities required by the dynamic adaptation process. Service templates are based on OWL-S descriptions and provide the necessary means to capture and parameterize specific behavior patterns of service models. In this paper, we apply our approach in the context of the EU-funded ALIVE project and illustrate, as an example, how the proposed framework supports the adaptation of the authentication mechanism used by an interactive tourist recommendation system.
Analytic integration of real-virtual counterterms in NNLO jet cross sections i

We present analytic evaluations of some integrals needed to give explicitly the integrated real-virtual counterterms, based on a recently proposed subtraction scheme for next-to-next-to-leading order (NNLO) jet cross sections. After an algebraic reduction of the integrals, integration-by-parts identities are used for the reduction to master integrals and for the computation of the master integrals themselves by means of differential equations. The results are written in terms of one- and two-dimensional harmonic polylogarithms, once an extension of the standard basis is made. We expect that the techniques described here will be useful in computing other integrals emerging in calculations in perturbative quantum field theories.
Combining description and similarity logics

Categorisation of objects into classes is currently supported by (at least) two ‘orthogonal’ methods. In logic-based approaches, classifications are defined through ontologies or knowledge bases which describe the existing relationships among terms. Description logic (DL) has become one of the most successful formalisms for representing such knowledge bases, in particular because theoretically well-founded and efficient reasoning tools have been readily available. In numerical approaches, classifications are obtained by first computing similarity (or proximity) measures between objects and then categorising them into classes by means of Voronoi tessellations, clustering algorithms or nearest neighbour computations, etc. In many areas such as bioinformatics, computational linguistics or medical informatics, these two methods have been used independently of each other: although both of them are often applied to the same domain (and even by the same researcher), up to now no formal interaction mechanism has been developed. In this paper, we propose a DL-based integration of the two classification methods. Our formalism, called SL + ALCQIO, extends the expressive DL ALCQIO by means of constructors which allow definitions of concepts in terms of both comparative and absolute similarity. In the combined knowledge base the user should declare similarity spaces where the new operators are interpreted. Of course, SL + ALCQIO can only be useful if classifications with this logic are supported by automated reasoning tools. We lay theoretical foundations for the development of such tools by showing that reasoning problems for SL+ALCQIO can be decomposed into the corresponding problems for its DL-part ALCQIO and similarity part SL. Using our new theorem stating that reasoning in SL is ExpTime-complete and a recent complexity result of Pratt-Hartmann for ALCQIO, we prove that reasoning in SL+ALCQIO is NExpTime-complete.